Trends in risk factors for non-communicable diseases in South … Publications... · 2017. 6....

Trends in risk factors for non-communicable

diseases in South Africa

Muchiri Wandai and Candy Day

May 2015

Report prepared for: Report prepared by:

INTERNAL REVIEW ONLY

Health Systems Trust

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Westville 3630

Contact details:

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Trends in risk factors for non-communicable diseases in South Africa 2

© Health Systems Trust (2015). All rights reserved.

The information contained in this publication may be freely distributed and reproduced,

provided the source is acknowledged and the information is used for non-commercial

purposes.


Table of contents

1. Introduction ..................................................................................................................... 4

2. Objectives of this review report ....................................................................................... 4

3. Methods .......................................................................................................................... 5

3.1 Sampling in GHS and NiDS ..................................................................................... 5

3.2 Questions for diagnosis with chronic condition (GHS and NiDS) .............................. 6

3.3 NCD study variables ................................................................................................ 6

3.4 Height and weight measurements for BMI ............................................................... 7

3.5 Non-response rates by race based on height, weight and systolic BP...................... 8

3.6 Disaggregating variables.......................................................................................... 9

3.7 Data Analysis ........................................................................................................... 9

4. Results .......................................................................................................................... 10

4.1 Self-reported hypertension ..................................................................................... 10

4.2 Prevalence of hypertension (raised BP or on medication for hypertension) ............ 18

4.3 Prevalence of prehypertension and raised BP ....................................................... 25

4.4 Distribution of mean systolic and diastolic BP ........................................................ 33

4.5 Body Mass Index (BMI (kg/m2)) ............................................................................. 44

4.6 Prevalence of BMI by categories ............................................................................ 48

4.7 Risk factor of physical inactivity .............................................................................. 55

4.8 Risk factor of alcohol use ....................................................................................... 61

4.9 Smoking status ...................................................................................................... 73

4.10 Comparing hypertension prevalence by districts using multilevel analysis ............. 81

4.11 Other Non-communicable diseases ....................................................................... 86

5. Concluding remarks ...................................................................................................... 99

6. References ................................................................................................................. 101


1. Introduction

In June 2014, the World Health Organization (WHO) South Africa Country Office reported

that about two out of five deaths are related to non-communicable disease (NCD), which can

be attributed to high prevalence of major risk factors: tobacco use, harmful use of alcohol,

unhealthy diet and high salt intake, obesity and physical inactivity.1 In an effort to combat this

trend, the South African National Department of Health has developed a Strategic Plan for

the Prevention and Control of Non-Communicable Diseases (NCD) 2013-172 that has

prioritised the goal of reducing NCD morbidity, mortality and related risk factors by

implementing the following three major components:

1) prevention of NCDs and promotion of health and wellness at individual, community

and population levels

2) improved control of NCDs through health systems strengthening and reform

3) monitoring NCDs and their main risk factors and conducting innovative research.

The non-communicable diseases of importance in this strategic plan have been identified as

cardiovascular diseases, diabetes, chronic respiratory conditions and cancer. The plan has

also outlined four risk factors, namely physical inactivity, tobacco use, unhealthy diets, and

harmful use of alcohol, that are modifiable for prevention and control of the identified non-

communicable diseases.

Various steps have been taken to improve lifestyle changes in South Africa. These include

legislation by the government in controlling a better food environment, for example legislation

and regulations on food labelling and advertising3 as well as on substance content.4 Studies

on workable methods for implementing lifestyle interventions have also been documented5,

and certain metropolitan municipalities such as the City of Johannesburg have provided an

open-door gym in Petrus Molefe Eco-Park in Soweto which opened in mid-2012.

In order to efficiently and effectively implement the components of the NCD strategy,

stakeholders‟ understanding of the epidemiological questions of who is/are at high risk,

where the risk is highest, and how trends have evolved over years becomes of utmost

importance.

Building on previous similar work,6 this report undertakes a profiling of the major risk factors

for NCDs, namely the intermediary risk factors of elevated blood pressure, tobacco and

alcohol use, physical inactivity and body mass index (BMI). The intention is to gain a better

understanding of those in the population, based on age, gender and race, who are most

affected; where they are located based on geographical dwellings (for example, whether the

burden is highest in urban or rural settings), and whether there are differences in the

prevalence of the risk factors over time.

2. Objectives of this review report

1. To investigate any changes in the prevalence of

Self-reported hypertension

Hypertension based on measured systolic and diastolic blood pressure

Treatment coverage (% of hypertensive patients on treatment)

Effective coverage (% of hypertensive patients controlled on treatment)


2. To investigate self-reported prevalence of the following risk factors for non-

communicable diseases:

Overweight and obesity based on BMI categorisation

Physical inactivity

Alcohol use

Smoking

3. To investigate self-reported prevalence of other non-communicable diseases, namely

diabetes, asthma, heart problems, stroke and cancer

3. Methods

Monitoring of the aforementioned NCD risk factors and the non-communicable conditions is

based on data from the three waves7-9 of the National Income Dynamics Study (NiDS) panel

survey, carried out by the Southern Africa Labour and Development Research Unit

(SALDRU) in the School of Economics at the University of Cape Town. Various documents

detailing the survey methodology10, weighting11, 12 and users‟ manuals13, 14 can be found on

the NiDS website (www.nids.co.za) and on the data distributor‟s website

(http://www.datafirst.uct.ac.za/).

In addition to the data from the NiDS, data from the General Household Survey (GHS), which

has been carried out by Statistics South Africa since 2002, were also used to describe

prevalence of certain self-reported non-communicable health conditions for the years 2009 to

2013. Unlike in the NiDS, measurements of systolic and diastolic blood pressure, heart pulse

rate, and weight and height measurements for calculating Body Mass Index (BMI) and waist

circumference are not taken in the GHS. Stroke data in the GHS were first collected in the

year 2013.

The GHS data were extracted from Statistics South Africa‟s Nesstar data repository.15-19 The

survey collects data on a wide range of health and social development areas such as

housing, education, household access to services and facilities, food security and agriculture.

Health variables collected through these surveys include medical aid coverage, injuries,

health worker consultation, access to health facilities, utilisation of health facilities and

satisfaction with health services utilised; communicable diseases suffered in the month

before the survey; and non-communicable diseases diagnosed by a health worker.

3.1 Sampling in GHS and NiDS

The General Household Survey has always used multi-stage stratified sampling with primary

sampling units (PSUs) selected from the strata with probability proportional to size (PPS),

and systematic sampling of dwelling units from the PSUs. The strata have, however, differed

in a number of years. From 2002 to 2005, the first stage was stratification by province, then

by type of area within each province (urban/non-urban).20-22 The stratum variable indicating

rural and urban areas for each province was however dropped in the 2005 survey. In the

2006 and 2007 surveys, the strata were presented first by province then by the 53 district

councils.23, 24 The primary sampling units (PSUs) were allocated to these strata by the power

allocation method, and sampling of the PSUs was done using the probability proportional to

size (PPS) principle. Finally, for the surveys between 2008 and 2013, the first stage

stratification was the metro/non-metro within provinces and the second stratification stage

was by household size, education, occupancy status, gender, and industry and income.25 In

each year‟s survey, at least 3 000 PSUs were selected.

http://www.nids.co.za/

http://www.datafirst.uct.ac.za/


In the NiDS, 400 PSUs were sampled from the selected 3 000 PSUs sampled from the

master sample used by Statistics South Africa (Stats SA) for its Labour Force Surveys and

General Household Surveys between 2004 and 2007, and used the 53 [sic] district councils

as the explicit strata.26 Prior to the release of the Census 2011 data in 2013, the NiDS

calculated the geographic variables based on the 2001 Census boundaries. There were

relatively significant changes to district and provincial boundaries over this period, as well as

changes in the geographic type variables and population estimates. As a result, SALDRU

released new geographic variables and weights for all waves of the datasets after applying

the necessary adjustments.27

3.2 Questions for diagnosis with chronic condition (GHS and NiDS)

Prior to 2009, the GHS question related to health asked only: “What sort of illnesses or

injuries did … suffer from?” Starting from the 2009 survey, a new question was added for

chronic illnesses and phrased as: “Has … been informed by a medical practitioner or nurse

that he/she suffers from any of the following chronic illnesses or conditions?” The response

options are „Yes‟, „No‟ or „Unspecified‟. This new question elicited much larger reporting on

chronic conditions, and is similar to what is asked in the NiDS. For example, in the NiDS, the

question on high blood pressure is asked as: “Have you ever been told by a doctor, nurse or

health care professional that you have high blood pressure?” with possible responses being

„Yes‟, „No‟, „Refused‟ or „Don‟t know‟. Unspecified responses in the GHS as well as the

„refused‟ and „don‟t know‟ responses in the NiDS were treated as missing when estimating

the prevalences.

3.3 NCD study variables

The NCD risk factors under study include self-reported hypertension, systolic and diastolic

blood pressure (BP), smoking and alcohol use, body mass index (BMI) and physical

inactivity. In the NiDS study, systolic and diastolic BP readings were measured twice.

Following the method used by Ardington and Case28, seemingly unrealistic measurements for

the two sets of systolic and diastolic readings were eliminated from the analysis according to

the following rules:

1. If systolic BP <40 mmHg or >240 mmHg and diastolic <30 mmHg or ≥140 mmHg

2. A set of readings for systolic and diastolic blood pressure were retained if systolic BP

≥80 mmHg and also at least 15 mmHg larger than the diastolic BP.

3. If the second systolic or diastolic BP differed by more than 5 mmHg, the first BP

reading was excluded.

A final measurement for each type of BP was calculated from the average of the two

measurements, or the single measurement if only one reading met the criteria. Table 1

shows the number of records before and after the cleaning of the blood pressure

measurements.


Table 1: Number of records before and after blood pressure measurement cleaning

BP type 2008 2010 2012

Before After Before After Before After

Systolic_1 14 016 5 400 15 164 7 063 18 347 8 072

Systolic_2 13 978 13 705 15 072 14 655 18 337 18 299

Mean systolic 13 838 14 922 18 331

Diastolic_1 14 013 5 389 15 128 7 038 183 47 8 072

Diastolic_2 13 982 13 655 15 064 14 649 18 336 18 298

Mean diastolic 13 804 14 889 18 330

Measured systolic and diastolic blood pressure readings were used to define blood pressure

levels as „normal‟, „prehypertension‟ or „raised blood pressure‟ using criteria similar to those

used in the 2012 South African National Health and Nutrition Examination Survey

(SANHANES)29 as shown in Table 2. The terminology „raised BP‟ as used here is similar to

that referred to as hypertension in the 2012 SANHANES.

Table 2: Blood pressure classification

Normal Prehypertension Raised BP Hypertension

SBP <120 mmHg and

DBP <80 mmHg

SBP 120–139 mmHg or

DBP 80–89 mmHg

SBP ≥140 mmHg or DBP

≥90 mmHg

Raised BP or self-reported

medication use for

hypertension

In this report, the NiDS survey respondents were defined as having hypertension if they had

raised BP or were on medication for hypertension. The self-reported hypertension, systolic

and diastolic blood pressure, raised BP and hypertension as defined in Table 2 were

analysed in relation to the population‟s demographics, and geographic and time variants.

Data on smoking, alcohol consumption, physical exercise and medication for chronic

conditions were all self-reported.

3.4 Height and weight measurements for BMI

Height and weight measurements that were used for calculation of BMI for each respondent

were recorded for survey respondents in duplicate and a third reading was taken only if the

first and second reading differed by more than five units. The readings for the three sets of

heights ranged between 3 cm and 207.4 cm as recorded in the raw data, while those of

weight ranged between 12.3 and 150 kg. In the analysis for this report, height, weight and

BMI cleaning was done as shown in Table 3.

Table 3: Minimum and maximum height, weight and BMI measurements

Variable Lower limit Upper limit Unit

Height 60 250 cm

Weight 30 250 kg

BMI 10 60 kg/m2

The respective averages of the available weight and height measurements were used to

calculate body mass index (BMI) in kg/m2, which was subsequently used to classify


respondents as Underweight, Normal weight, Overweight or Obese, after eliminating BMI

values below 10 kg/m2 or above 60 kg/m2. Finally, the BMI categorisation was done as

indicated in Table 4. Expectant mothers (n=247, 249 and 320 for waves 1, 2 and 3

respectively) were eliminated from the analysis of BMI.

Table 4: BMI categorisation

BMI values (kg/m2) Category

<18 Underweight

≥18 and <25 Normal weight

≥25 and <30 Overweight

≥30 Obese

3.5 Non-response rates by race based on height, weight and systolic BP

The percentage of missing measurements based on height, weight and systolic blood

pressure by race show that in 2008 and 2010, more than 25% of Whites and about 20% of

Indians did not have measurements taken. There was a dramatic drop in the percentage of

missing measurements in 2012, although Whites still had the highest percentage missing.

Table 5: Non-response rates by race

Year Race Height Weight Systolic

n % missing n % missing n % missing

2008

African 12 249 8.0 12 249 9.0 12 249 7.8

Coloured 2 213 13.4 2 213 15.8 2 213 13.5

Indian 223 19.7 223 20.6 223 21.1

White 908 26.3 908 27.8 908 27.7

Total 15 593 10.0 15 593 11.2 15 593 10.0

2010

African 14 634 10.0 14 634 11.3 14 634 11.3

Coloured 2 247 19.1 2 247 21.7 2 247 23.7

Indian 193 20.7 193 20.2 193 23.8

White 549 34.6 549 37.3 549 40.6

Total 17 623 12.0 17 623 13.6 17 623 13.9

2012

African 15 408 1.6 15 408 1.7 15 408 1.6

Coloured 2 576 3.0 2 576 3.1 2 576 3.3

Indian 194 3.1 194 3.1 194 3.1

White 531 3.0 531 3.8 531 4.3

Total 18 709 1.8 18 709 2.0 18 709 1.9


3.6 Disaggregating variables

The prevalence of the risk factors for the non-communicable health conditions was analysed

by the following characteristics:

1. Demographic and social characteristics: age, gender, population group (African/Black,

Coloured, Indian/Asian, White), education (None, Primary, Secondary,

Certificate/Diploma and Bachelor‟s degree and above). Age was categorised into six

categories of 10 years beginning at 15 years, except for the last (65 +) category.

2. Geographical characteristics of interest were the geographical type of dwelling

categorised as Traditional/Urban/Farms setting and the 52 health districts.

3.7 Data Analysis

In terms of individuals in the study who were 15 years and older, there were 16 871 in wave

1, 21 880 in wave 2 and 22 481 in wave 3, while there were 13 691 records with a balanced

response for all the waves. These records include missing entries for all the self-reported

items for the presence of a chronic condition (1254, 4244 and 3771 for Wave 1, Wave 2 and

Wave 3 respectively).

The estimated quantities are all weighted (unless otherwise indicated in the results) using the

recommended weight variable, as per the data producer‟s recommendations.12 Variations in

the aforementioned NCD risk factors were studied in relation to each specific demographic

and geographic characteristic (geographic type). It has been indicated in the documentation

for wave 1 that the sample is not representative at the provincial level26 and so analysis at

this level is not recommended. Consequently it is assumed that the sample may not be

representative for analysis at the district level as well. However, in order to investigate

variation at the district level, multilevel regression30 was used to analyse any random effects

(unmeasured/unknown/unaccounted risk factors) on hypertension at the district level, after

adjusting for joint confounding of known risk factors (age, gender, race, smoking, alcohol use,

BMI and physical activity) associated with it (systolic/diastolic blood pressure, or hypertension

as defined in this report). The objective is to increase the sample‟s effect size by utilising

available information as much as possible with the expectation that any differences in the

outcome (hypertension) can be attributed to differences between the districts.

In producing the analysis for this report, no effort was made to impute the missing entries,

and therefore those respondents who had missing values or refused to answer were

removed from the analysis and this could slightly affect the estimated prevalence for the NCD

risk factors under study.

All the analyses were done on Stata version 13.


4. Results

4.1 Self-reported hypertension

The population prevalence for those self-reporting having been informed by a health

professional that they have high blood pressure increased slightly between 2008 and 2012.

This could imply that either high BP has indeed increased in the population, or that more

people in the populace have been consulting healthcare practitioners to ascertain their BP

status.

Table 6: Prevalence (%) and 95% CI of self-reported hypertension: NiDS

Self-reported hypertension

2008 2010 2012

n Prevalence n Prevalence n Prevalence

Yes 2 489 13.6 (12.5–14.5) 2 133 11.3 (10.4–12.4) 3 224 16.1 (15.0–17.2)

No 13 015 86.4 (85.2–87.5) 15 305 88.7 (87.6–89.6) 15 442 83.9 (82.8–85.0)

4.1.1 Prevalence of self-reported hypertension by gender and age groups

For both genders, the percentage of those who self-reported (those who had an encounter

with health practitioner to ascertain their BP status) having hypertension increased slightly

from 2008 to 2012. However, for the three study periods, females are at least one-and-a-half

times more likely to self-report having hypertension compared with males.

Table 7: Prevalence (%) and 95% CI of self-reported hypertension by gender and age group: NiDS

Gender Age

group

2008 2010 2012


Females

15-24 66 2.4 (1.7–3.3) 38 1.2 (0.7–1.8) 59 1.4 (1.0–2.0)

25-34 115 5.7 (4.0–7.9) 84 6.1 (4.2–9.0) 172 8.0 (6.1–10.4)

35-44 289 20.2 (17.1–23.6) 197 11.2 (8.9–13.9) 319 18.5 (15.7–21.7)

45-54 465 32.2 (28.5–36.0) 410 25.9 (22.4–29.6) 569 33.4 (29.8–37.2)

55-64 440 42.4 (37.5–47.5) 407 38.8 (33.0–44.9) 646 51.8 (46.9–56.7)

65+ 498 45.8 (40.7–51.0) 465 46.3 (39.9–52.9) 668 59.1 (53.2–64.8)

≥15 1 873 17.8 (16.4–19.4) 1 601 15.0 (13.6–16.6) 2 433 20.7 (19.4–22.0)

≥25 1 808 23.3 (21.4–25.4) 1 563 19.8 (17.9–21.8) 2 375 27.0 (25.3–28.8)

Males

15-24 14 0.6 (0.3–1.1) 15 0.7 (0.3–1.5) 16 0.5 (0.2–1.2)

25-34 41 3.0 (1.9–4.9) 29 1.8 (1.0–3.2) 44 2.9 (1.7–4.9)

35-44 79 5.8 (3.9–8.5) 64 6.1 (3.9–9.4) 91 8.4 (4.7–14.7)

45-54 149 16.9 (12.6–22.2) 123 13.7 (10.5–17.6) 192 21.4 (16.3–27.5)

55-64 175 28.6 (23.2–34.6) 144 21.4 (16.5–27.2) 225 36.6 (29.4–44.5)

65+ 156 32.7 (26.1–40.0) 157 34.1 (28.0–40.8) 222 43.3 (36.8–50.0)

≥15 614 8.2 (7.0–9.5) 532 7.0 (6.0–8.1) 790 10.7 (9.2–12.4)

≥25 601 11.5 (9.8–13.4) 517 9.6 (8.3–11.2) 774 14.6 (12.7–16.8)


The effect of age on self-reported hypertension is evident (Figure 1), as the prevalence for

both genders increases with age and is highest in those aged 45 years and older in the 2012

wave of the study.

Figure 1: Prevalence of self-reported hypertension by gender and age group: NiDS

The prevalences of self-reported hypertension among females (20.7%) and among males

(10.7%) for the year 2012 are similar to those estimated in the 2012 SANHANES, which were

20.6% and 12.0% respectively. The estimated prevalences by age groups in the 2012 NiDS

are also comparable to those reported in the 2012 SANHANES for some age groups within

each gender.

59.146.345.8

51.838.8

42.4

33.425.9

32.2

18.511.2

20.2

8.06.15.7

1.41.22.4

43.334.1

32.7

36.621.4

28.6

21.413.7

16.9

8.46.15.8

2.91.83.0

0.50.70.6

0 20 40 60 0 20 40 60

65+

54-64

45-54

35-44

25-34

15-24

65+

54-64

45-54

35-44

25-34

15-24

Female Male

2008 2010 2012

Prevalence (%)

Prevalence of self-reported hypertension by gender and age group


4.1.2 Number with self-reported hypertension by gender and age group: NiDS

Table 8: Number self-reporting hypertension by gender and age group: NiDS

Gender Age group

2008 2010 2012

n Number (95% CI) n Number (95% CI) n Number (95% CI)

Females

15-24 2 585 98 871

(63 691–134 050) 2 983

50 774 (27 830–73 719)

3 117 58 749

(36 881–80 617)

25-34 1 700 211 328

(137 956–284 700) 1 992

247 221 (144 724–349 719)

2 276 318 227

(216 763–419 691)

35-44 1 605 597 615

(481 138–714 093) 1 666

359 934 (267 767–452 102)

1 780 618 203

(494 890–741 516)

45-54 1 381 697 404

(600 605–794 204) 1 455

605 226 (490 825–719 627)

1 600 814 863

(672 512–957 214)

55-64 963 600 232

(509 016–691 447) 1 056

596 055 (462 659–729 451)

1 193 832 743

(684 161–981 325)

65+ 1 035 594 517

(502 358–686 676) 1 056

682 519 (517 457–847 582)

1 151 909 084

(742 663–1 075 506)

≥15 9 269 2 799 968

(2 491 943–3 107 993) 10 208

2 541 730 (2 155 481–2 927 979)

11 117 3 551 869

(3 073 451–4 030 287)

≥25 6 694 2 704 668

( 2 407 122, 3 002 215) 7 626

2 490 956 (2 116 439, 2 865 473)

8 001 3 493 504

(3 026 735, 3 960 272)

Males

15-24 2 107 22 359

(8 000–36 718) 2 717

30 818 (7 037–54 598)

2 811 21 916

(4 228–39 604)

25-34 1 234 96 185

(50 693–141 678) 1 469

65 964 (26 745–105 183)

1 589 107 196

(39 993–174 398)

35-44 988 131 792

(80 226–183 357) 1 022

168 688 (89 333–248 042)

1 060 240 100

(89 526–390 674)

45-54 801 267 012

(181 563–352 462) 880

255 449 (173 633–337 264)

911 392 043

(261 412–522 674)

55-64 579 276 039

(214 133–337 946) 627

245 223 (170 287–320 158)

643 435 919

(324 129–547 710)

65+ 506 222 682

(154 862–290 503) 514

254 584 (183 154–326 014)

533 346 903

(260 610–433 195)

≥15 6 215 1 016 070

(859 236–1 172 905) 7 229

1 020 725 (831 303–1 210 146)

7 547 1 544 077

(1 230 190–1 857 964)

≥25 4 117 994 048

(836 981, 1 151 114) 4 212

989 907 (806 471, 1 173 344)

4 737 1 522 161

(1 210 971, 1 833 351)

Total

≥15 15 485 3 816 038

(3 426 204–4 205 871) 17 437

3 562 455 (3 065 499–4 059 411)

18 664 5 095 946

(4 380 470, 5 811 422)

≥25 10 793 3 694 808

[3 314 267–4 075 349] 11 737

3 480 863 (3 002 934–3 958 792)

12 736 5 015 281

(4 313 920–5 716 642)


4.1.3 Prevalence of self-reported hypertension by gender: GHS

Figure 2: Self-reported prevalence of hypertension by gender: GHS

The self-reported prevalence of hypertension is higher among females than among males,

which may indicate that there is indeed a higher prevalence of hypertension in females or

that their health-seeking behaviour is higher than that of males. For both genders, the

patterns are almost similar from year to year.

4.1.4 Self-reported hypertension by gender (2010 and 2012): NiDS and GHS

Table 9: Prevalence and 95% CI of self-reported hypertension by gender: NiDS and GHS

Year Gender NiDS GHS

n Prevalence n Prevalence

2008

Female 1 874 17.8 (16.4–19.4)

Male 615 8.2 (7.0–9.5)

Total 2 489 13.6 (12.5–14.8)

2010

Female 1 601 15.0 (13.6–16.6) 2 035 12.6 (12.2–13.0)

Male 532 7.0 (6.0–8.1) 5 260 6.0 (5.7–6.3)

Total 2 133 11.3 (10.4–12.4) 7 295 9.4 (9.1–9.7)

2012

Female 2 434 20.7 (19.4–22.0) 5 649 14.1 (13.6–14.6)

Male 790 10.7 (9.2–12.4) 2 365 7.1 (6.7–7.6)

Total 3 224 16.1 (15.0–17.2) 8 014 10.7 (10.4–11.17)

The estimated prevalences of self-reported hypertension in the 2012 SANHANES were

20.6% and 12.0% for females and males respectively. Self-reported prevalence is thus

substantially lower according to the GHS than in the NiDS or SANHANES. The respective

sample sizes for each age group in the 2010 and 2012 years are larger in the GHS compared

with the NiDS.

6

8

10

12

14

2009 2010 2011 2012 2013

Year

Female Male All

Self-reported prevalence of hypertension by gender


4.1.5 Prevalence of self-reported hypertension by age group: GHS

Figure 3: Self-reported prevalence of hypertension by age group: GHS

Estimates for those in the first two age groups are almost the same, while those for the upper

three age groups have wide gaps between them. The prevalence among the first three age

groups is lower than the overall prevalence (shown by dashed line), while that among the

older three age groups is higher than the overall prevalence.

0

10

20

30

40

50

2009 2010 2011 2012 2013

Year

15-24 25-34 35-44 45-54 55-64 65+ All

Self-reported prevalence of hypertension by age group


4.1.6 Prevalence of self-reported hypertension by gender and age group

Table 10: Comparison of self-reported prevalence of hypertension from four surveys

Gender Age group

1998 SADHS

2010 NiDS 2010 GHS 2012 NiDS 2012 GHS 2012

SANHANES

Females

15–24 3.8 1.2 (0.7–1.8) 0.4 (0.3–0.5) 1.4 (1.0–2.0) 0.9 (0.6–1.5) 5.1 (4.0–6.5)

25–34 8.0 6.1 (4.2–9.0) 2.4 (2.0–2.8) 8.0 (6.1–10.4) 3.1 (2.5–3.8) 9.8 (8.2–11.8)

35–44 15.1 11.2 (8.9–13.9) 9.2 (8.3–10.2) 18.5 (15.7–21.7) 10.0 (9.1–11.0) 17.0 (14.7–19.5)

45–54 30.5 25.9 (22.4–29.6) 22.8 (21.4–24.2) 33.4 (29.8–37.2) 23.7 (22.4–25.2) 35.7 (31.7–39.9)

55–64 40.9 38.8 (33.0–44.9) 36.2 (34.3–38.2) 51.8 (46.9–56.7) 40.8 (38.9–42.8) 46.5 (41.0–52.0)

65+ 42.2 46.3 (39.9–52.9) 45.1 (43.0–47.2) 59.1 (53.2–64.8) 48.4 (46.3–50.6) 52.9 (47.3–58.5)

Total 18.6 15.0 (13.6–16.6) 12.6 (12.2–13.0) 20.7 (19.4–22.0) 14.1 (13.6–14.6) 20.6 (19.2–22.1)

Males

15–24 0.2 0.7 (0.3–1.5) 0.2 (0.1–0.4) 0.5 (0.2–1.2) 0.6 (0.3–0.9) 2.0 (1.3–3.0)

25–34 2.7 1.8 (1.0–3.2) 0.9 (0.7–1.2) 2.9 (1.7–4.9) 1.4 (0.9–2.2) 5.0 (3.5–7.0)

35–44 7.5 6.1 (3.9–9.4) 3.9 (3.3–4.6) 8.4 (4.7–14.7) 4.4 (3.7–5.2) 11.5 (8.9–14.7)

45–54 18.0 13.7 (10.5–17.6) 10.7 (9.6–12.0) 21.4 (16.3–27.5) 14.0 (12.7–15.4) 21.7 (17.6–26.4)

55–64 16.9 21.4 (16.5–27.2) 22.4 (20.4–24.4) 36.6 (29.4–44.5) 26.0 (23.9–28.2) 30.9 (25.9–36.5)

65+ 25.0 34.1 (28.0–40.8) 35.2 (32.5–38.0) 43.3 (36.8–50.0) 35.2 (32.7–37.9) 46.9 (39.2–54.8)

Total 7.9 7.0 (6.0–8.1) 6.0 (5.7–6.3) 10.7 (9.2–12.4) 7.1 (6.7–7.6) 12.0 (10.7–13.4)

The estimated prevalences from the NiDS and SANHANES are comparable for all age

groups, while the GHS shows much lower prevalences compared with either of the other two.

However, the trends are similar for the three surveys, whereby the self-reporting increases as

age increases. As indicated by the results from both the NiDS and SANHANES in 2012, the

self-reported prevalences have increased especially among those aged 35 years and older

compared with the 1998 South African Demographic and Health Survey (SADHS) results.

This increase may reflect both an increase in the actual prevalence of hypertension as well

as an increase in awareness and diagnosis.

4.1.7 Age distribution by race

Before comparing prevalence of the risk factors and related health conditions by race, it is

helpful to examine how age (an important demographic risk factor) is distributed across the

races. Figure 4 shows the percentage of adults in each age group according to race. The

majority of Africans and Coloureds are in the younger age groups with only about 6% being

65 years and older. In contrast, Whites are slightly more evenly distributed by age, although

the representation in younger age groups is lower than in the older age groups. This

differentiation is important when making comparisons, especially between Whites and either

Africans or Coloureds.


Figure 4: Age distribution by race: 2012 NiDS

4.1.8 Prevalence of self-reported hypertension by race and gender

The estimated prevalence among Indians for the three study periods is unreliable due to the

small sample sizes compared with that of the other races. Self-reported hypertension is

lowest in Africans and highest in Whites, followed by Coloureds for both the 2008 and 2012

study waves.

Table 11: Prevalence and 95% CI for self-reported hypertension by gender and race: NiDS

Gender Race 2008 2010 2012


Female

Africans 7 315 16.5 (14.9–18.2) 8 522 13.7 (12.4–15.3) 9 174 19.7 (18.3–21.1)

Coloured 1 331 25.3 (20.6–30.6) 1 323 21.6 (16.0–28.6) 1 531 25.1 (21.2–29.4)

Indians 133 16.5 (12.7–21.3) 109 13.2 (8.7–19.4) 111 19.6 (13.1–28.2)

Whites 500 22.4 (17.0–28.9) 300 19.3 (12.4–28.7) 302 24.5 (18.1–32.4)

Total 9 279 17.8 (16.4–19.4) 10 254 15.0 (13.6–16.6) 11 118 20.7 (19.4–22.0)

Male

Africans 4 853 6.3 (5.3–7.5) 6 007 5.3 (4.5–6.3) 6 192 8.5 (7.1–10.0)

Coloured 875 11.6 ([8.4–15.8) 919 11.8 (9.0–15.4) 1 045 16.6 (11.3–23.7)

Indians 90 16.4 (9.2–27.5) 84 26.9 (16.0–41.7) 83 16.7 (9.3–28.5)

Whites 406 18.1 (11.8–26.8) 244 11.4 (6.8–18.5) 228 23.0 (16.1–31.8)

Total 6 224 8.2 (7.0–9.5) 7 254 7.0 (6.0–8.1) 7 548 10.7 (9.2–12.4)

15-24 25-34 35-44 45-54 55-64 65+

African 28.4 25.9 19.6 12.5 7.4 6.2

Coloured 23.2 22.0 22.7 16.0 9.8 6.3

Indian 19.3 24.3 20.7 12.5 13.5 9.7

White 12.8 15.2 18.2 19.4 17.4 17.0

0.0

5.0

10.0

15.0

20.0

25.0

30.0

Pe

rce

nta

ge

Age distribution by race


Figure 5: Prevalence of self-reported hypertension by race and gender: NiDS

The 2012 self-reported hypertension prevalence by gender and race is highest among White

(24.5%) and Coloured females (25.1%), followed by the White males (23.0%). The

prevalence is lowest in African males (8.5%). These estimates from the 2012 wave of the

NiDS are similar to those reported in the 2012 SANHANES survey. It is worth noting,

however, that with the exception of Africans, the sample sizes by race in the NiDS are

smaller, more so for Indians, than those used in the 1998 SADHS and also in the 2012

SANHANES. Compared with the results of the 1998 SADHS, these results show that self-

reported hypertension has increased among all races and in both genders. As found in the

1998 SADHS, Africans of both genders and White males still have the lowest and highest

prevalence respectively.

0

10

20

30

40

2008 2010 2012 2008 2010 2012

Female Male

African Coloured Indian White

Pre

va

lence

(%

)

Year of NiDS survey

Prevalence of self-reported hypertension by race and gender

Pre

vale

nce (

%)


Table 12: Prevalences (%) of self-reported hypertension for 1998 SADHS, 2012 SANHANES and 2012 NiDS by gender and race

Gender Race 1998 SADHS 2012 SANHANES 2012 NiDS


Female

Africans 6 269 5.8 6 112 19.7 (18.4– 21.6) 9 174 19.7 (18.3–21.1)

Coloured 806 9.0 1 803 27.2 (24.7– 29.9) 1 531 25.1 (21.2–29.4)

Indians 300 11.9 734 20.8 (16.6– 25.9) 111 19.6 (13.1–28.2)

Whites 767 21.1 391 19.5 (13.7– 27.0) 302 24.5 (18.1–32.4)

Total 8 142 7.9 9 040 20.6 (19.2– 22.1) 11 118 20.7 (19.4– 22.0)

Male

Africans 4 257 17.4 4 174 10.4 (9.1– 12.0) 6 192 8.5 (7.1–10.0)

Coloured 637 22.3 1 279 15.9 (12.9– 19.4) 1 045 16.6 (11.3–23.7)

Indians 195 23.8 597 16.9 (12.8– 22.0) 83 16.7 (9.3–28.5)

Whites 564 21.4 330 18.9 (13.4– 26.0) 228 23.0 (16.1–31.8)

Total 5 653 18.6 6 380 12.0 (10.7–13.4) 7 548 10.7 (9.2–12.4)

4.2 Prevalence of hypertension (raised BP or on medication for hypertension)

The prevalence of hypertension (measured BP above the threshold or on medication for

hypertension) has remained almost the same (≈31%) between 2008 and 2012 in the NiDS

surveys.

Table 13: Prevalence (%) and 95% CI of hypertension

Also shown is that, for the three study periods, the prevalence of actual hypertension in the

population is more than double that of self-reported hypertension (cf. Table 6)

4.2.1 Distribution of hypertension by gender and age groups

For the three study periods, the prevalence of hypertension among females in the younger

age groups (15-24 and 25-34) is lower (though not significantly) than that of males in the

same age categories. In the rest of the age groups, the prevalence of hypertension in women

is higher (again not significantly) than that of males for all three study periods.

Hypertension Status

2008 2010 2012


Hypertension 4 909 31.0 (29.5– 32.4) 4 745 30.6 (29.2–32.0) 6 007 31.8 ( 30.3–33.4)

No Hypertension 9 153 69.0 (67.6–70.5) 10 296 69.4 (68.0–70.8) 12 405 68.2 (66.6–69.7)


Table 14: Prevalence (%) and 95% CI of hypertension by gender and age group

Gender Age group

1998 SADHS 2008 NiDS 2010 NiDS 2012 NiDS

n Prev. n Prevalence n Prevalence n Prevalence

Females

15-24 2 084 4.1 2 387 7.9 (6.0–10.3) 2 579 8.6 (7.1–10.5) 3 084 7.9 (6.4–9.7)

25-34 1 720 10.2 1 545 17.2 (14.6–20.1) 1 722 18.2 (15.1–21.7) 2 246 18.9 (16.1–22.1)

35-44 1 460 21.8 1 447 38.0 (33.8–42.3) 1 451 31.4 (27.4–35.6) 1 755 33.2 (29.8–36.8)

45-54 1 116 38.7 1 264 57.3 (52.3–62.2) 1 288 53.6 (48.6–58.5) 1 573 52.4 (48.1–56.7)

55-64 914 51.8 901 65.8 (60.1–71.1) 942 67.1 (61.6–72.1) 1 185 66.6 (60.8–71.9)

65+ 861 60.4 944 77.3 (72.6–81.3) 939 76.9 (71.2–81.7) 1 129 78.7 (74.5–82.3)

≥15 8 155 24.6 8 488 33.5 (31.6–35.6) 8 921 33.0 (31.2–34.8) 10 972 33.5 (32.0–35.1)

≥25 - - 6 110 42.8 (40.4–45.2) 6 342 41.3 (39.0–43.6) 7 889 42.0 (40.2–43.9)

Males

15-24 1 816 7.4 1 924 9.8 (7.8–12.3) 2 315 10.2 (8.2–12.6) 2 779 11.8 (9.8–14.2)

25-34 1 123 14.6 1 078 19.8 (16.2–24.1) 1 249 22.8 (18.7–27.5) 1 564 21.1 (17.3–25.5)

35-44 1 005 24 873 29.8 (25.6–34.4) 837 29.8 (24.5–35.6) 1 044 32.6 (26.4–39.4)

45-54 701 38.2 707 43.9 (38.0–50.0) 736 41.6 (35.7–47.8) 889 46.5 (40.8–52.3)

55-64 518 44 512 61.8 (55.1–68.0) 543 57.3 (50.9–63.5) 635 59.4 (49.7–68.5)

65+ 507 52 465 70.0 (62.5–76.5) 440 68.8 (60.4–76.1) 527 70.6 (63.1–77.1)

≥15 5 670 22.9 5 559 27.6 (25.6–29.6) 6 120 27.8 (25.5–30.2) 7 438 29.8 (27.5–32.3)

≥25 - - 3 641 35.6 (32.9–38.4) 3 805 35.3 (32.4–38.2) 4 660 36.9 (33.9–40.0)

Figure 6: Prevalence of hypertension by gender and age group: NiDS

As seen in Figure 6, the prevalence of those in the age group 45-54 years and older is much

higher than the overall highest prevalence of 31.8% (shown by the red line) for the year 2012,

while the prevalence for those in the younger age groups (15-24 and 25-34 years) is

0

20

40

60

80

0

20

40

60

80

2008 2010 2012 2008 2010 2012 2008 2010 2012

15-24 25-34 35-44

45-54 55-64 65+

Female Male

Pre

va

lence

(%

)

Year of NiDS survey

Prevalence of hypertension by gender and age group

Pre

vale

nce (

%)


significantly lower than the overall prevalence for the same year for both genders. The

prevalence among those aged 35-44 years is about average.

4.2.2 Estimated number with hypertension by gender and age group

Table 15: Estimated number with hypertension by gender and age group

Gender Age group

2008 2010 2012

n Number (95% CI) n Number (95% CI) n Number (95% CI)

Females

15-24 2 387 295 329

(203 927–386 731) 2 579

317 055 (233 381–400 728)

3 084 332 554

(250 554–414 554)

25-34 1 545 575 131

(468 569–681 693) 1 722

599 445 (456 321–742 569)

2 246 739 705

(574 248–905 163)

35-44 1 447 1 001 812

(842 760–1 160 865) 1 451

866 686 (708 895–1 024 477)

1 755 1 093 149

(921 130–1 265 168)

45-54 1 264 1 129 175

(990 609–1 267 740) 1 288

1 090 205 (907 433–1 272 977)

1 573 1 249 730

(1 044 670–1 454 790)

55-64 901 849 872

(749 251–950 494) 942

905 339 (736 520–1 074 159)

1 185 1 060 728

(890 890–1 230 566)

65+ 944 893 901

(776 711–1 011 091) 939

951 477 (769 917–1 133 037)

1 129 1 192 195

(994 408–1 389 982)

≥15 8 488 4 745 220

(4 313 809–5 176 631) 8 921

4 730 207 (4 128 550–5 331 865)

10 972 5 668 061

(4 966 497–6 369 625)

≥25 6 101 4 457 325

(4 074 351–4 840 299) 6 342

4 413 153 (3 850 273–4 976 032)

7 888 5 335 891

(4 671 293–6 000 488)

Males

15-24 1 924 337 167

(255 348–418 985) 2 315

370 095 (278 905–461 285)

2 779 473 652

(364 783–582 520)

25-34 1 078 555 990

(430 524–681 455) 1 249

712 268 (501 657–922 878)

1 564 777 926

(614 010–941 842)

35-44 873 593 809

(489 336–698 282) 837

673 097 (512 816–833 378)

1 044 907 121

(651 092–1 163 150)

45-54 707 599 892

(498 781–701 003) 736

631 603 (484 127–779 080)

889 830 759

(666 609–994 910)

55-64 512 523 694

(444 207–603 182) 543

557 184 (441 088–673 279)

635 700 911

(556 830–844 992)

65+ 465 444 719

(348 339–541 100) 440

423 173 (332 655–513 692)

527 560 458

(441 505–679 411)

≥15 5 559 3 055 271

(2 796 715–3 313 827) 6 120

3 367 420 (2 864 493–3 870 348)

7 438 4 250 826

(3 634 642–4 867 010)

≥25 3 635 2 723 431

(2 487 338–2 959 523) 3 805

2 997 325 (2 535 060–3 459 591)

4 659 3 778 252

(3 216 868–4 339 636)

Total

≥15 14 047 7 800 491 (7 250 704–8 350 278)

15 041 8 097 627 (7 117 293–9 077 962)

18 410 9 918 887 (8 694 846–11 142 929)

≥25 9 736 7 167 995 (6 677 376–7 658 615)

10 147 7 410 478 (6 530 198–8 290 757)

12 547 9 112 681 (8 003 063–10 222 300)


4.2.2.1 Discussion

The results for estimated prevalence of hypertension for the years 2008 and 2010 are similar

although not identical to those found by Day et al6 who used earlier versions of the same

datasets. The minor discrepancies are probably due to the way in which data were validated

for systolic and diastolic BP. For example, in Day et al,6 diastolic BP ranged from 35-140

mmHg, while in this analysis it ranged from 30-140 mmHg. Demographic information from

Census 2011 was used to adjust the survey weights in the recent releases of the NiDS

datasets, and this may also contribute to small differences between the current and previous

analyses. Similarly, the estimated number of those with hypertension by gender and age

group (Table 15) is different from the result shown in Day et al.6 The results from the three

waves of NiDS show an increase in the prevalence of hypertension among all age groups,

when compared with the 1998 SADHS (Table 14).

Table 16: Self-reported and actual hypertension (%) by gender for four surveys

Survey Self-reported hypertension

Actual hypertension (BP ≥ 140/90 mmHg) or on medication for hypertension

Females Males Females Males

1998 SADHS 18.6 7.9 24.6 22.9

2003 SADHS 18.9 8.8 17.9** 12.5**

2012 GHS 10.0 5.0 - -

2012 NiDS 20.7 10.7 34.0 30.0

2012 SANHANES

20.6 12.0 26.9* 26.4*

*Reporting only BP ≥ 140/90 mmHg without patients controlled on medication **Authors have indicated use of result with caution

The self-reported prevalences for both genders have been consistently low when compared

with actual hypertension for all the surveys, indicating a substantial gap in diagnosis and

treatment.


4.2.3 Prevalence of hypertension in those self-reporting no diagnosis

Table 17: Prevalence (%) and 95% CI of hypertension for those self-reporting no diagnosis per age group by gender

Gender Age group

2008 2010 2012


Females

15-24 2 325 7.2 (5.3–9.7) 2 536 8.4 (6.8–10.3) 3 023 7.3 (5.8–9.1)

25-34 1 433 13.8 (11.4–16.6) 1 645 14.3 (11.9–17.1) 2 073 15.5 (12.6–18.9)

35-44 1 163 24.9 (21.0–29.3) 1 262 22.8 (18.9–27.2) 1 437 21.4 (18.4–24.7)

45-54 805 38.2 (32.6–44.0) 898 37.1 (31.6–42.9) 1 002 32.2 (27.2–37.7)

55-64 464 41.4 (34.5–48.7) 556 43.2 (37.2–49.3) 539 36.3 (29.3–44.0)

65+ 450 57.0 (49.1–64.6) 491 55.0 (46.9–62.9) 462 52.5 (43.8–60.9)

Total 6 640 20.3 (18.3–22.5) 7 388 20.9 (19.4–22.5) 8 536 18.9 (17.4–20.6)

Males

15-24 1 908 9.4 (7.4–11.9) 2 290 9.7 (7.8–12.1) 2 757 11.7 (9.7–14.1)

25-34 1 043 18.7 (15.0–22.9) 1 220 21.8 (17.7–26.5) 1 513 19.6 (15.9–24.0)

35-44 791 26.6 (22.8–30.7) 781 26.3 (21.1–32.2) 952 29.6 (23.1–37.1)

45-54 562 35.5 (29.7–41.7) 623 33.3 (27.2–40.0) 697 38.1 (32.4–44.2)

55-64 342 46.6 (38.8–54.6) 402 44.2 (36.6–52.1) 410 37.5 (27.8–48.3)

65+ 310 58.2 (49.1–66.8) 293 51.8 (42.1–61.4) 305 53.2 (43.5–62.7)

Total 4 956 22.1 (20.2–24.2) 5 609 22.6 (20.4–25.0) 6 634 23.4 (21.1–25.9)


Table 18: Ratio of number with hypertension to no hypertension for those self-reporting no diagnosis

Year Gender Age group

Hypertension n Ratio

Yes No

2008

Females

15-24 262 052 3 384 130 2 325 0.08

25-34 434 012 2 707 401 1 433 0.16

35-44 511 869 1 541 163 1 163 0.33

45-54 489 399 793 394 805 0.62

55-64 292 152 413 184 464 0.71

65+ 323 878 244 076 450 1.33

Total 2 313 361 9 083 349 6 640 0.25

Males

15-24 320 520 3 083 228 1 908 0.10

25-34 506 267 2 207 671 1 043 0.23

35-44 490 269 1 355 216 791 0.36

45-54 395 943 720 668 562 0.55

55-64 270 794 309 812 342 0.87

65+ 241 870 173 587 310 1.39

Total 2 225 663 7 850 183 4 956 0.28

2010

Females

15-24 302 748 3 309 266 2 536 0.09

25-34 441 514 2 641 040 1 645 0.17

35-44 550 963 1 870 152 1 262 0.29

45-54 531 576 902 594 898 0.59

55-64 331 110 435 998 556 0.76

65+ 330 828 270 513 491 1.22

Total 2 488 739 9 429 563 7 388 0.26

Males

15-24 347 230 3 228 516 2 290 0.11

25-34 667 687 2 399 541 1 220 0.28

35-44 559 664 1 570 811 781 0.36

45-54 431 151 864 642 623 0.50

55-64 318 932 402 074 402 0.79

65+ 201 274 187 408 293 1.07

Total 2 525 938 8 652 991 5 609 0.29

2012

Females

15-24 303 832 3 855 795 3 023 0.08

25-34 557 429 3 042 121 2 073 0.18

35-44 572 821 2 107 180 1 437 0.27

45-54 504 543 1 061 419 1 002 0.48

55-64 276 415 484 547 539 0.57

65+ 316 104 286 544 462 1.10

Total 2 531 144 10 837 606 8 536 0.23

Males

15-24 462 598 3 499 182 2 757 0.13

25-34 697 429 2 859 754 1 513 0.24

35-44 753 754 1 790 871 952 0.42

45-54 531 594 863 870 697 0.62

55-64 278 259 463 972 410 0.60

65+ 238 726 209 590 305 1.14

Total 2 962 360 9 687 239 6 634 0.31


4.2.3.1 Discussion

These results show that the percentage of females aged 35-44 years and older who had

hypertension but had not self-reported a previous diagnosis decreased marginally between

2008 and 2012, while a decrease among males aged 55-64 years and older is noticed (Table

17). This phenomenon almost corresponds with the slight increases observed in the self-

reported diagnosis with hypertension between 2008 and 2012 for both genders and in the

age group 45-54 years and older (Table 7). Comparing these results with those of self-

reported diagnosis with high blood pressure, it is clear that a large proportion of the

population has high blood pressure but is unaware of it. The gap in diagnosis is somewhat

higher in males and increases steadily with age for both genders. Therefore, although self-

reporting with hypertension was highest in older age groups, it is also clear that the highest

gap in diagnosis is still in the older age groups. These groups should be the target of

interventions as per the NDoH 2013-2017 Strategic Plan2 for reducing raised blood pressure.

4.2.4 Distribution of hypertension by gender and race

The estimates for Indians, as was the case for self-reported prevalence, are affected by the

small sample size. Prevalence of hypertension for African females remained almost constant

between 2008 and 2012, while that of African males increased slightly but progressively

during the same period. The estimated prevalences for Coloureds and Whites, which are

highest and second-highest respectively for both genders in each study year, show a slight

decrease between 2008 and 2012. Irrespective of age, females of each race, except for

Indians in 2010 and 2012, have a higher prevalence of hypertension compared with males.

Table 19: Prevalence (%) of hypertension with 95% CI by gender and race

Gender Race 2008 2010 2012


Female

African 6 812 31.6 (29.5–33.7) 7 591 31.0 (29.4–32.6) 9 079 31.7 (30.1–33.3)

Coloured 1 201 43.3 (39.9–46.7) 1 061 43.0 (38.1–48.1) 1 494 40.3 (36.5–44.3)

Indian 113 35.0 (24.2–47.5) 83 32.0 (21.5–44.7) 108 41.2 (30.4–52.9)

White 371 42.1 (33.0–51.7) 186 42.4 (30.0–55.7) 292 40.0 (32.5–48.0)

Total 8 497 33.5 (31.6–35.6) 8 921 33.0 (31.2–34.8) 10 973 33.5 (32.0–35.1)

Male

African 4 417 25.3 (23.2–27.5) 5 223 26.2 (23.9–28.6) 6 125 28.0 (25.3–30.8)

Coloured 756 39.4 (32.1–47.2) 684 36.8 (28.0–46.7) 1 009 37.3 (31.0–44.1)

Indian 71 31.0 (19.6–45.4) 64 33.8 (20.8–49.9) 81 42.6 (29.0–57.6)

White 321 37.4 (29.8–45.7) 149 34.8 (23.6–48.1) 224 36.2 (27.7–45.6)

Total 5 565 27.6 (25.7–29.7) 6 120 27.8 (25.5–30.2) 7 439 29.8 (27.5–32.3)


Figure 7: Prevalence of hypertension by gender and race

4.3 Prevalence of prehypertension and raised BP

In this section, estimated prevalence of blood pressure status is based purely on systolic and

diastolic blood pressures without considering medication status, as is the case in section 4.2.

This is important in describing the size of the burden of uncontrolled hypertension, which

includes those never diagnosed with hypertension, people diagnosed but not treated with

medication, and those diagnosed and treated but who nonetheless remain above the desired

thresholds.

4.3.1 Prevalence of prehypertension and raised BP by age group and gender

The prevalence of raised BP for both genders increases with age, and it is higher among

females than among males aged 45-54 years and older. Prevalence of prehypertension is

higher among males than among females in the three years of the NiDS survey.

20

30

40

50

60

2008 2010 2012 2008 2010 2012

Female Male


Pre

va

lence

(%

)

Year of NiDS survey

Prevalence of hypertension by gender and race

Pre

vale

nce (

%)


Table 20: Prevalence (%) and 95% CI of prehypertension and raised BP by gender and age group

Year Gender Age group n Prehypertension Raised BP

2008

Female

15-24 2 386 21.6 (19.0–24.4) 7.3 (5.4–9.8)

25-34 1 535 36.3 (33.0–39.9) 15.0 (12.6–17.8)

35-44 1 429 31.5 (28.0–35.2) 31.8 (27.6–36.4)

45-54 1 225 31.4 (27.2–35.9) 43.0 (38.2–47.9)

55-64 861 34.9 (29.7–40.6) 51.2 (46.0–56.3)

65+ 889 28.2 (23.6–33.4) 61.5 (56.0–66.8)

Total 8 325 30.0 (28.3–31.8) 26.7 (24.9–28.7)

Male

15-24 1 924 33.9 (30.8–37.1) 9.8 (7.8–12.3)

25-34 1 076 40.6 (35.6–45.9) 19.4 (15.7–23.7)

35-44 863 41.4 (36.8–46.1) 27.2 (23.5–31.1)

45-54 687 42.6 (35.8–49.7) 38.7 (33.2–44.5)

55-64 493 33.3 (27.3–39.9) 50.9 (44.2–57.5)

65+ 447 24.8 (19.2–31.5) 55.7 (48.3–62.9)

Total 5 490 37.5 (35.2–39.8) 24.5 (22.6–26.4)

2010

Female

15-24 2 579 25.4 (22.9–28.0) 8.5 (7.0–10.4)

25-34 1 717 35.2 (31.4–39.1) 17.3 (14.2–20.8)

35-44 1 438 38.3 (34.4–42.4) 26.1 (22.2–30.4)

45-54 1 263 34.2 (30.3–38.4) 42.8 (38.1–47.7)

55-64 907 31.0 (26.1–36.4) 49.7 (43.9–55.5)

65+ 885 27.7 (22.2–34.1) 60.6 (53.8–66.9)

Total 8 789 32.1 (30.3–34.0) 26.9 (25.2–28.7)

Male

15-24 2 313 38.0 (35.2–40.9) 10.1 (8.1–12.6)

25-34 1 249 40.8 (36.1–45.7) 22.1 (18.0–26.7)

35-44 834 47.4 (40.4–54.4) 27.2 (22.1–32.9)

45-54 724 42.8 (36.2–49.6) 36.5 (30.7–42.8)

55-64 527 34.8 (28.1–42.2) 48.0 (41.1–55.0)

65+ 413 27.6 (21.6–34.7) 58.1 (49.8–66.0)

Total 6 060 40.3 (37.9–42.8) 25.0 (22.7–27.4)

2012

Females

15-24 3 084 22.9 (19.8–26.2) 7.6 (6.1–9.5)

25-34 2 245 29.5 (26.4–32.8) 18.1 (15.3–21.3)

35-44 1 748 38.9 (34.4–43.7) 26.5 (23.4–30.0)

45-54 1 558 33.2 (29.5–37.2) 40.7 (36.2–45.4)

55-64 1 174 33.7 (29.4–38.3) 46.1 (40.4–51.8)

65+ 1 096 29.2 (24.7–34.2) 55.3 (49.9–60.6)

Total 10 905 30.6 (28.9–32.3) 26.1 (24.6–27.8)

Males

15-24 2 779 34.4 (31.4–37.5) 11.8 (9.8–14.1)

25-34 1 564 46.9 (40.4–53.4) 20.6 (16.7–25.1)

35-44 1 041 44.7 (38.6–51.0) 31.5 (25.3–38.4)

45-54 887 40.8 (35.1–46.8) 39.0 (33.8–44.3)

55-64 630 40.0 (30.7–50.1) 42.9 (34.9–51.3)

65+ 523 28.5 (21.4–36.8) 58.0 (50.5–65.1)

Total 7 424 40.6 (38.0–43.2) 26.5 (24.1–29.0)


4.3.1.1 Discussion

Comparing the results in Table 20 with those in Table 14, it can be seen that the difference

between the prevalence of hypertension (raised BP or on hypertension medication) and

raised BP alone progressively increases as age increases. This is because more of those in

the older age groups have been diagnosed with hypertension and have subsequently been

put on medication.

Table 21: Prevalence of raised BP for 2012 NiDS and SANHANES

Age group 2012 NiDS 2012 SANHANES

n Prevalence (%) n Prevalence (%)

15-24 531 9.7 1 886 6.4

25-34 721 19.3 1 166 12.9

35-44 818 28.8 1 069 25.7

45-54 1 033 40.0 1 126 42.4

55-64 936 44.7 946 51.3

65+ 935 56.2 829 64.4

Total 4 974 26.3 7 022 26.6

The overall prevalence of raised BP in the year 2012 is nearly equal to that of the 2012

SANHANES (Table 21). However, estimates for the younger three age groups are higher in

the NiDS than in the SANHANES surveys, while those in the older three age groups are

lower in the NiDS compared with those in the SANHANES. Sample sizes in the younger

three age groups are much lower in the NiDS compared with those in SANHANES, but those

of the older three age groups are comparable in the two surveys. It is therefore suspected

that if the sample sizes of the three younger age groups in the NiDS were the same as those

in the SANHANES, it is likely that the estimated prevalence by age group would all be slightly

lower in the NiDS than in SANHANES. Of major concern is that both surveys indicate that

more than a quarter of all adults and well over half of the elderly (age 65 and older) have

raised blood pressure.


Figure 8: Prevalence of prehypertension and raised BP by gender and age group: NiDS

Prevalence of prehypertension and raised BP by race and gender

Table 22: Prevalence (%) and 95% CI of prehypertension and raised BP by race and gender

Year Race Females Males

n Prehypertension Raised BP n Prehypertension Raised BP

2008

African 6 721 28.7 (26.9–30.5) 25.6 (23.6–27.6) 4 387 35.9 (33.8–38.1) 23.2 (21.2–25.3)

Coloured 1 164 31.1 (27.3–35.3) 34.1 (29.8–38.6) 740 37.1 (31.5–43.2) 36 (28.2–44.5)

Indian 108 42.2 (29.3–56.3) 27.7 (15.3–44.9) 68 40.1 (29.1–52.3) 23 (13.0–37.4)

White 341 38.4 (31.2–46.1) 30.2 (22.3–39.5) 301 50.9 (41.7–60.1) 27.4 (20.8–35.1)

Total 8 334 30.0 (28.3–31.7) 26.7 (24.9–28.7) 5 496 37.5 (35.2–39.8) 24.5 (22.6–26.4)

2010

African 7 507 31.1 (29.3–33.0) 25.9 (24.4–27.5) 5 189 40.0 (37.7–42.4) 24.4 (22.2–26.9)

Coloured 1 018 34.6 (27.8–41.9) 34.2 (30.0–38.7) 668 40.0 (31.1–49.5) 32.6 (23.0–44.0)

Indian 83 29.6 (21.8–38.8) 23.7 (15.8–34.1) 63 43.3 (26.8–61.4) 16.8 (11.1–24.6)

White 181 40.1 (29.5–51.7) 30.3 (20.2–42.8) 140 43.6 (29.2–59.1) 25.9 (17.0–37.4)

Total 8 789 32.1 (30.3–34.0) 26.9 (25.2–28.7) 6 060 40.3 (37.9–42.8) 25.0 (22.7–27.4)

2012

African 9 031 30.3 (28.6–32.1) 24.8 (23.2–26.4) 6 117 39.5 (36.7–42.4) 25.6 (23.0–28.5)

Coloured 1 482 29.2 (26.3–32.3) 33.6 (28.7–38.8) 1 004 39.0 (33.0–45.4) 32.6 (26.3–39.7)

Indian 108 25.1 (17.0–35.2) 38.5 (27.0–51.3) 81 40.9 (25.0–58.9) 31.8 (19.1–47.9)

White 285 35.4 (27.2–44.6) 27.3 (20.8–35.0) 223 51.8 (40.3–63.1) 26.5 (18.9–35.8)

Total 10 906 30.6 (28.9–32.3) 26.2 (24.6–27.8) 7 425 40.6 (38.0–43.2) 26.5 (24.1–29.0)

Between the years 2008 and 2012, raised BP for African females, Coloured females and

White males remained almost unchanged, while that of African males increased slightly and

that of Coloured males and White females decreased slightly.

28.126.226.4

33.429.932.6

32.933.8

30.3

38.737.9

31.1

29.435.036.2

22.925.4

21.5

53.357.257.5

45.647.947.7

40.442.341.5

26.425.8

31.4

18.017.214.9

7.68.57.3

28.225.323.4

39.834.031.9

40.742.440.8

44.747.1

41.1

46.940.840.5

34.437.9

33.9

57.453.352.6

42.747.048.8

38.936.237.1

31.427.027.0

20.622.0

19.3

11.810.19.8

0 20 40 60 0 20 40 60 0 20 40 60 0 20 40 60

65+

55-64

45-54

35-44

25-34

15-24

65+

55-64

45-54

35-44

25-34

15-24

65+

55-64

45-54

35-44

25-34

15-24

65+

55-64

45-54

35-44

25-34

15-24

Female: Prehypertension. Female: Raised BP Male: Prehypertension. Male: Raised BP

2008 2010 2012

Prevalence (%)

Prevalence of prehypertension and raised BP by gender and age group


4.3.2.1 Discussion

The overall respective prevalences for Africans, Coloureds, Indians and Whites for the 2012

wave were 25.2%, 33.2%, 35.2% and 27.0%, and are similar to those of the 2012

SANHANES which were respectively 25.6%, 33.2%, 25.9% and 29.3%. The estimates for

Indians in the 2012 NiDS are based on a relatively small sample size (81) as is the case for

Whites (134) in the 2012 SANHANES.

4.3.3 Prevalence of prehypertension and raised BP by geographic type

Table 23: Prevalence (%) and 95% CI of prehypertension and raised BP by geographic type

Year Geographic type n Prehypertension Raised BP

2008

Traditional 5 911 31.0 (29.3–32.7) 23.5 (21.6–25.5)

Urban 6 314 34.2 (31.9–36.6) 26.9 (24.9–28.9)

Farms 1 605 36.3 (30.8–42.1) 27.3 (21.7–33.6)

Total 13 830 33.3 (31.7–34.9) 25.8 (24.4–27.2)

2010

Traditional 6 748 36.0 (33.7–38.4) 23.1 (21.4–24.9)

Urban 6 498 35.5 (33.3–37.8) 28.2 (26.2–30.3)

Farms 1 502 38.5 (32.7–44.7) 23.6 (20.0–27.5)

Total 14 748 35.9 (34.3–37.5) 26.1 (24.7–27.6)

2012

Traditional 8 020 33.5 (31.6–35.4) 25.1 (23.1–27.2)

Urban 8 760 35.7 (33.7–37.8) 27.0 (24.8–29.2)

Farms 1 551 38.3 (33.2–43.8) 25.9 (20.7–31.8)

Total 18 331 35.2 (33.7–36.6) 26.3 (24.8–27.9)

Raised BP is lowest in the traditional dwellers for all the three study periods. However, there

seems not to be any significant difference in the prevalence of raised BP by geographic type

for the three study periods.

4.3.3.1 Discussion

The 2012 SANHANES found that 28.8%, 18.3%, 28.4% and 25.2% of urban formal, urban

informal, rural formal and rural informal adults had elevated blood pressure respectively. The

NiDS geographic categorisation used in this review is based on the 2011 Census, while that

used in SANHANES was based on the 2001 Census. Notwithstanding the different

categorisation, the results obtained from the three waves of the NiDS shows that the

prevalences by the three geographic types are similar to those in the 2012 SANHANES,

except, probably, for urban informal dwellers. It is suspected that those who live in urban

informal settlements are relatively younger than those in the other three geographic types in

the 2012 SANHANES.


4.3.4 Prevalence of prehypertension and raised BP by education level

Table 24: Prevalence (%) and 95% CI of prehypertension and raised BP by education level

Year Education level

n Prehypertension Raised BP

2008

None 1 968 30.4 (27.0–34.0) 46.0 (42.0–50.0)

Primary 3 526 32.7 (30.4–35.2) 32.2 (29.6–34.9)

Secondary 7 454 31.2 (29.4–33.1) 20.1 (18.4–22.0)

Cert/Dip 918 41.4 (36.7–46.2) 23.5 (19.9–27.5)

Bachelor+ 243 40.6 (31.6–50.2) 19.9 (13.7–28.0)

Total 14 109 32.7 (31.2–34.3) 25.3 (23.9–26.7)

2010

None 1 887 30.7 (27.6–34.0) 47.4 (43.9–50.9)

Primary 3 523 34.5 (31.5–37.6) 32.9 (30.2–35.8)

Secondary 8 461 35.8 (34.0–37.7) 20.7 (19.1–22.5)

Cert/Dip 1 005 37.5 (32.9–42.4) 25.0 (20.5–30.1)

Bachelor+ 186 40.0 (26.0–55.9) 27.4 (17.7–39.9)

Total 15 062 35.5 (33.9–37.1) 25.7 (24.4–27.2)

2012

None 1 917 32.9 (29.9–36.1) 45.0 (41.1–49.0)

Primary 4 002 33.7 (31.2–36.3) 37.1 (34.2–40.1)

Secondary 10 372 34.6 (32.8–36.6) 21.3 (19.5–23.2)

Cert/Dip 1 798 37.5 (33.5–41.8) 26.5 (23.1–30.3)

Bachelor+ 341 40.3 (28.5–53.3) 19.2 (11.6–30.2)

Total 18 430 35.0 (33.6–36.5) 26.2 (24.6–27.8)

The prevalence of raised BP is highest in those without any formal schooling followed by

those with primary-level schooling for all the three study periods.


4.3.5 Prevalence of raised BP: systolic and diastolic blood pressures separately

Table 25: Prevalence of raised BP: Systolic or diastolic BP only

Year Age group

Females Males

Systolic Diastolic Systolic Diastolic

n Prevalence n Prevalence n Prevalence n Prevalence

2008

15-24 2 387 1.9 (1.2–2.9) 2 385 6.4 (4.6–8.9) 1 927 5.7 (4.3–7.3) 1 924 6.6 (4.8–8.8)

25-34 1 535 5.7 (4.3–7.7) 1 532 13.7 (11.4–16.3) 1 076 12.3 (9.1–16.2) 1 075 15.0 (11.9–18.7)

35-44 1 430 18.0 (15.0–21.6) 1 426 29.9 (25.8–34.3) 863 16.8 (14.0–20.1) 861 23.1 (19.8–26.8)

45-54 1 227 28.1 (24.6–32.0) 1 221 39.1 (34.5–43.9) 687 29.1 (24.3–34.5) 684 31.5 (26.5–37.0)

55-64 861 44.8 (40.0–49.7) 858 42.5 (37.8–47.4) 493 44.5 (37.8–51.4) 492 41.5 (35.1–48.2)

65+ 890 54.1 (49.3–58.8) 887 44.0 (37.7–50.4) 447 48.3 (41.2–55.5) 444 36.8 (30.3–43.8)

≥ 15 8 330 17.3 (16.2–18.5) 8 309 23.1 (21.3–25.0) 5 493 17.5 (15.9–19.1) 5 480 19.0 (17.3–20.8)

≥ 25 5 952 23.0 (21.4–24.6) 5 933 29.3 (27.2–31.4) 3 572 22.9 (20.7–25.3) 3 562 24.7 (22.5–27)

2010

15-24 2 583 2.4 (1.7–3.5) 2 579 7.7 (6.2–9.7) 2 315 4.9 (3.7–6.4) 2 315 8.0 (6.2–10.4)

25-34 1 717 6.0 (3.8–9.3) 1 716 15.6 (12.8–18.9) 1 252 13.3 (10.3–17.1) 1 245 16.7 (13.0–21.2)

35-44 1 438 11.8 (9.5–14.4) 1 436 24.7 (20.9–29.0) 834 17.2 (12.4–23.2) 833 23.1 (18.5–28.4)

45-54 1 264 30.0 (25.5–35.0) 1 260 37.3 (32.8–42.0) 723 24 (19.7–28.9) 720 31.1 (25.6–37.2)

55-64 906 41.1 (35.6–46.9) 902 38.9 (33.1–45.0) 527 39.4 (33.3–45.9) 523 35.7 (29.1–42.8)

65+ 884 52.7 (45.9–59.4) 882 43.8 (37.6–50.2) 413 49.0 (40.8–57.4) 412 43.1 (35.2–51.3)

≥ 15 8 792 16.7 (15.4–18.1) 8 775 22.8 (21.2–24.6) 6 064 16.6 (14.8–18.6) 6 048 19.8 (17.8–22.0)

≥ 25 6 209 21.7 (19.9–23.6) 6 196 28.1 (26.0–30.4) 3 749 21.6 (19.2–24.2) 3 733 24.9 (22.4–27.6)

2012

15-24 3 084 1.2 (0.8–1.9) 3 084 7.4 (5.9–9.3) 2 779 5.3 (4.0–6.9) 2 779 9.5 (7.7–11.6)

25-34 2 245 5.0 (3.7–6.9) 2 245 17.4 (14.7–20.6) 1 564 9.2 (7.0–12.1) 1 563 18.1 (14.5–22.4)

35-44 1 748 12.5 (10.3–15.2) 1 748 24.9 (21.8–28.3) 1 041 20.4 (16.1–25.6) 1 041 25.4 (19.3–32.7)

45-54 1 558 26.4 (22.3–31.0) 1 558 36.8 (32.7–41.1) 887 28.2 (24.0–32.9) 887 31.9 (27.5–36.8)

55-64 1 174 39.6 (34.4–45.0) 1 174 35.8 (31.0–40.9) 630 33.7 (27.0–41.2) 630 35.4 (28.3–43.3)

65+ 1 096 49.8 (44.8–54.8) 1 096 37.4 (32.3–42.8) 523 52.3 (45.0–59.6) 523 39.6 (33.5–46.1)

≥ 15 10 905 15.7 (14.5–16.9) 10 905 22.6 (21.1–24.1) 7 424 17.1 (15.3–19.0) 7 423 21.5 (19.2–23.9)

≥ 25 7 822 20.5 (19.1–22.0) 7 822 27.6 (25.9–29.5) 4 646 21.7 (19.4–24.3) 4 645 26.2 (23.3–29.3)

4.3.5.1 Discussion

As for the combined systolic/diastolic (raised BP) prevalence, the prevalence of raised

systolic BP only and diastolic BP only increases with advancing age among both females and

males. For the younger four age groups in both genders and for the three study periods, the

prevalence of raised systolic BP only is lower than that of diastolic BP only, while for the two

oldest age groups (55-64 and 65+ years), the prevalence of raised diastolic BP only is lower

than that of raised systolic BP alone, except for the 55-64 age group in 2012.

The prevalences of raised systolic BP among females (15.7%) and among males (17.1%) for

2012 are lower than those of the 2012 SANHANES which are 24.0% and 25.4% respectively.

Conversely, the 2012 NiDS results for raised diastolic BP (22.6% and 21.5% for females and

males respectively) are higher than those reported by SANHANES for females (12.6%) and

males (11.7%).


4.3.6 Estimated number with raised systolic BP

Table 26: Number with raised BP: Systolic BP only

Gender Age group

2008 2010 2012

n Number n Number n Number

Female

15-24 2 387 70 221

(39 065–101 377) 2 583

89 093 (53 805–124 382)

3 084 52 370

(30 142–74 598)

25-34 1 535 191 668

(132 907–250 429) 1 717

197 755 (105 336–290 174)

2 245 197 037

(125 779–268 294)

35-44 1 430 473 608

(374 050–573 166) 1 438

321 971 (248 883–395 060)

1 748 41 1173

(323 309–499 036)

45-54 1 227 539 266

(462 819–615 714) 1 264

604 058 (476 840–731 276)

1 558 624 655

(489 216–760 093)

55-64 861 544 864

(465 411–624 317) 906

536 521 (427 795–6452 48)

1 174 623 990

(511 629–736 350)

65+ 890 588 641

(505 677–671 604) 884

622 501 (494 952–750 049)

1 096 727 383

(600 393–854 372)

≥15 8 330 2 408 268

(2 184 378–2 632 158) 8 792

2 371 900 (2 038 750–2 705 050)

10 905 2 636 607

(2 290 301–2 982 912)

≥25 5 952 2 341 909

(2 124 889–2 558 930) 6 209

2 282 806 (1 968 195– 2 597 418)

7 822 2 584 621

(2 246 577– 2 922 664)

Male

15-24 1 927 193 900

(139 942–247 857) 2 315

176 742 (122 847–230 638)

2 779 211 226

(145 529–276 923)

25-34 1 076 342 853

(239 158–446 549) 1 252

418 228 (283 470–552 985)

1 564 340 587

(244 266–436 908)

35-44 863 333 411

(271 853–394 970) 834

388 052 (257 541–518 564)

1 041 569 146

(393 753–744 538)

45-54 687 386 638

(306 327–466 950) 723

361 485 (267 463–455 507)

887 504 018

(393 802–614 234)

55-64 493 365 764

(301 077–430 451) 527

374 789 (288 947–460 631)

630 396 151

(304 460–487 843)

65+ 447 291 950

(231760–352 141) 413

277 460 (210 810–344 110)

523 411 241

(321 846–500 636)

Total ≥15

5 493 1 914 517

(1 725 767–2 103 268) 6 064

1 996 756 (1 663 882–2 329 630)

7 424 2 432 369

(2 057 699–2 807 038)

Total ≥25

3 572 1 725 944

(1 547 061–1 904 827) 3 749

1 820 014 (1 515 711– 2 124 317)

4 646 2 222 221

(1 868 711– 2 575 730)


4.3.7 Estimated number with raised diastolic BP

Table 27: Number with raised BP: Diastolic BP only

Gender Age group

2008 2010 2012

n Number n Number n Number

Females

15-24 2 385 239 250

(153 582–324 918) 2 579

284 583 (203 819–365 347)

3 084 314 086

(233 063–395 109)

25-34 1 532 456 266

(366 782–545 750) 1 716

510 430 (384279–636 582)

2 245 683 198

(524 691–841 705)

35-44 1 426 781 935

(638 472–925 397) 1 436

676 439 (536 758–816 119)

1 748 817 835

(675 627–960 043)

45-54 1 221 743 355

(640 811–845 899) 1 260

749 615 (605 365–893 865)

1 558 870 242

(708 580–1 031 903)

55-64 858 515 479

(440 081–590 877) 902

504 699 (395 215–614 183)

1 174 564 525

(469 003–660 047)

65+ 887 476 173

(386 024–566 321) 882

504 380 (398 207–610 552)

1 096 545 990

(436 529–655 452)

≥15 8 309 3 212 458

(2 879 604–3 545 311) 8 775

3 230 146 (2 783 954–3 676 338)

10 905 3 795 876

(3 293 304–4 298 447)

≥25 5 933 2 976 177

(2 693 976– 3 258 377) 6 196

2 945 563 (2 546 595– 3 344 530)

7 822 3482173

(3021237– 3943110)

Males

15-24 1 924 224 648

(155 638–293 659) 2 315

291502 (206267–376737)

2 779 380 294

(286 426–474 161)

25-34 1 075 418 997

(314 667–523 327) 1 245

521 050 (338 642–703 457)

1 563 666 783

(513 474–820 092)

35-44 861 457 647

(378 149–537 144) 833

519 930 (384 621–655 239)

1 041 707 858

(473 785–941 931)

45-54 684 416 548

(339 634–493 461) 720

465 862 (352 694–579 030)

887 570 836 (450 275–691

398)

55-64 492 340 173

(275 918–404 428) 523

337 324 (253 320–421 329)

630 415 770

(313 243–518 297)

65+ 444 221 677

(163 489–279 865) 412

244 887 (181 744–308 031)

523 311 104

(238 910–383 298)

≥15 5 480 2 079 689

(1 864 841–2 294 537) 6 048

2 380 556 (1 986 403–2 774 709)

7 423 3 052 645

(2 561 079–3 544 212)

≥25 3 562 1 860 367

(1 671 468– 2 049 267) 3 733

2 089 054 (1 738 821– 2 439 287)

4 645 2 673 430

(2 231 315– 3 115 545)

4.4 Distribution of mean systolic and diastolic BP

The mean systolic BP is slightly above the cut-off point (120 mmHg) for a normal systolic BP,

while that of the diastolic BP is about the cut-off point of 80 mmHg for all the three study

periods. There has also been a very slight decrease in mean systolic and an increase in the

mean diastolic BP between 2008 and 2012.

Table 28: Mean systolic and diastolic BP over the study waves

Type of BP 2008 2010 2012

Systolic BP 123.2 (122.5–124.0) 122.8 (122.1–123.5) 122.5 (121.8–123.1)

Diastolic BP 79.4 (78.8–80.0) 79.9 (79.4–80.4) 80.7 (80.3–81.2)

4.4.1 Mean systolic and diastolic BP by gender and age group

The mean systolic BP among males has remained above the cut-off point of 120 mmHg,

while that of females has decreased from above the cut-off point in 2008 to about the cut-off

point in 2012. In the 2008 and 2010 study periods, the diastolic BP among males was about


the cut-off point of 80 mmHg, but in 2012 increased slightly to above this value, while that of

females has remained steady, averaging about the cut-off point for a normal diastolic BP.

Table 29: Mean systolic and diastolic BP and 95% CI by gender

Type of BP Gender 2008 2010 2012

Systolic

Female 122.0 (121.1–122.9) 121.5 (120.8–122.3) 120.7 (120.0–121.5)

Male 124.8 (123.8–125.7) 124.3 (123.2–125.4) 124.5 (123.6–125.4)

Total 123.2 (122.5–124.0) 122.8 (122.1–123.5) 122.5 (121.8–123.1)

Diastolic

Female 80.1 (79.5–80.8) 80.2 (79.7–80.8) 80.6 (80.0–81.1)

Male 78.5 (77.8–79.3) 79.5 (78.7–80.2) 80.9 (80.3–81.6)

Total 79.4 (78.8–80.0) 79.9 (79.4–80.4) 80.7 (80.3–81.2)

Table 30: Mean systolic and diastolic BP and 95% CI by age group

Type of BP

Age group 2008 2010 2012

Systolic

15-24 112.6 (111.8–113.5) 112.7 (112.0–113.4) 112.0 (111.3–112.7)

25-34 118.7 (117.5–119.9) 118.5 (117.3–119.6) 117.3 (116.4–118.2)

35-44 124.1 (122.9–125.4) 123.4 (122.1–124.7) 123.5 (122.2–124.8)

45-54 131.8 (130.2–133.4) 130.7 (129.0–132.4) 129.7 (128.3–131.2)

55-64 140.6 (138.4–142.7) 138.0 (135.6–140.4) 136.7 (134.5–139.0)

65+ 144.9 (142.7–147.1) 144.0 (141.3–146.6) 144.2 (141.6–146.9)

Diastolic

15-24 72.2 (71.3–73.0) 73.2 (72.5–73.8) 74.0 (73.4–74.6)

25-34 77.7 (77.0–78.5) 78.3 (77.5–79.2) 79.4 (78.7–80.2)

35-44 81.8 (80.9–82.7) 82.0 (81.2–82.8) 83.1 (82.2–84.0)

45-54 85.5 (84.4–86.6) 85.8 (84.9–86.7) 86.0 (85.0–86.9)

55-64 88.2 (87.1–89.2) 86.3 (84.7–88.0) 86.6 (85.1–88.1)

65+ 87.5 (86.1–88.9) 87.4 (86.0–88.8) 86.3 (85.0–87.6)

The mean systolic BP among males is higher than that of females especially in the younger

three age groups (15-24 to 35-44 years). It can also be seen that only among the youngest

age group (15-24 years) is the mean systolic BP way below the cut-off point (120 mmHg

shown by red dashed line) for a normal systolic BP.


Figure 9: Mean systolic BP by gender and age group

The mean diastolic BP for those aged 35-44 years and older is much higher than the normal

diastolic BP, shown by the red dashed line in Figure 10.

Figure 10: Mean diastolic BP by gender and age group

110

120

130

140

150

110

120

130

140

150

2008 2010 2012 2008 2010 2012 2008 2010 2012

15-24 25-34 35-44

45-54 55-64 65+

Female Male

Mea

n S

ysto

lic B

P (

mm

Hg

)

Year of NiDS survey

Mean systolic BP over gender by age group

70

75

80

85

90

70

75

80

85

90

2008 2010 2012 2008 2010 2012 2008 2010 2012

15-24 25-34 35-44

45-54 55-64 65+

Female Male

Mea

n D

iasto

lic B

P (

mm

Hg)

Year of NiDS survey

Mean Diastolic BP by gender and age group

Mean

Systo

lic B

P (

mm

Hg)

Mean

Dia

sto

lic B

P (

mm

Hg)


4.4.1.1 Discussion

The mean systolic BP among males is higher than that of females, while the diastolic BP is

higher among females than among males except in the 2012 survey period. This pattern is

similar to the SANHANES results, although the mean systolic BP is lower and the mean

diastolic BP is higher than the corresponding values in the 2012 SANHANES. For the age

groups, the mean systolic and diastolic BP follow a similar pattern to that found in the

SANHANES, but again, the respective mean systolic BP is lower and the mean diastolic BP

is higher than that found in SANHANES.

4.4.2 Systolic and diastolic BP by self-reported BP status: 2012 wave

Among males in the younger three age groups and among females in the two younger age

groups, the mean systolic BP is higher among those who self-reported diagnosis with

hypertension compared with those who had not been diagnosed with hypertension. In the

older three age groups, the mean systolic BP for both genders was higher among those self-

reporting no hypertension compared with those self-reporting diagnosis with hypertension.

Figure 11: Mean systolic BP by self-reported hypertension, gender and age group: 2012 NiDS

Except among females aged 25-34 years and among males in the youngest two age groups,

the mean diastolic BP for those self-reporting diagnosis with hypertension is lower than that

of those who self-report no diagnosis with hypertension.

120

140

160

180

15-2

4

25-3

4

35-4

4

45-5

4

55-6

465

+

15-2

4

25-3

4

35-4

4

45-5

4

55-6

465

+

Female Male

No self-report hypertension Self-report hypertension

Mea

n B

P (

mm

Hg)

Age group

Mean systolic BP by self reported hypertension, gender and age group

Mean

BP

(m

mH

g)


Figure 12: Mean diastolic BP by self-reported hypertension, gender and age group: 2012 NiDS

4.4.3 Mean systolic and diastolic BP by race

For the 2008 and 2010 study periods, the mean systolic and diastolic BP is highest in

Coloureds followed by Whites.

Table 31: Mean systolic and diastolic BP and 95% CI by race

BP type Race 2008 2010 2012

Systolic

African 122.3 (121.5– 123.2) 122.3 (121.6– 123.0) 121.5 (120.9– 122.1)

Coloured 128.0 (125.8– 130.2) 128.0 (125.0– 130.9) 126.3 (123.0– 129.5)

Indians 124.0 (119.9– 128.0) 117.6 (114.9– 120.2) 123.9 (119.0– 128.7)

White 127.0 (124.3– 129.6) 124.5 (121.8– 127.2) 126.6 (124.0– 129.2)

Diastolic

African 78.8 (78.2– 79.4) 79.5 (79.0– 80.0) 80.4 (79.9– 80.9)

Coloured 82.9 (81.3– 84.4) 83.0 (80.9– 85.1) 83.1 (80.9– 85.3)

Indians 80.2 (76.9– 83.6) 78.4 (76.9– 80.0) 81.8 (79.1– 84.5)

White 81.8 (80.2– 83.4) 81.4 (79.7– 83.1) 80.8 (79.5– 82.0)

Figure 13 illustrates that most of the race, gender and study period combinations have a

mean systolic BP that is above the cut-off point for normal BP (120 mmHg). The estimate for

Indians, however, is unreliable given the wide confidence interval resulting from a relatively

low sample size.

80

90

10

011

0

15-24 25-34 35-44 45-54 55-64 65+ 15-24 25-34 35-44 45-54 55-64 65+

Female Male

No self-report hypertension Self-report hypertension

Mea

n D

iasto

lic B

P (

mm

Hg)

Age group

Mean diastolic BP by self reported hypertension, gender and age group

Mean

Dia

sto

lic B

P (

mm

Hg)


Figure 13: Mean systolic BP by gender and race

The African community appears to have the lowest mean absolute diastolic BP, while

Coloureds have the highest absolute mean diastolic BP compared with other races.

Specifically, Coloured females seem to have a mean diastolic BP that is considerably higher

than the threshold point of 80 mmHg.

Figure 14: Mean diastolic BP by gender and race

110

120

130

140

2008 2010 2012 2008 2010 2012

Female Male


Mea

n S

ysto

lic B

P (

mm

Hg

)

Year of NiDS survey

Mean systolic BP by gender and race

75

80

85

90

2008 2010 2012 2008 2010 2012

Female Male


Mea

n D

iasto

lic B

P (

mm

Hg)

Year of NiDS survey

Mean diastolic BP by gender and race

Me

an

Systo

lic B

P (

mm

Hg

) M

ean

Dia

sto

lic B

P (

mm

Hg)


4.4.3.1 Discussion

The estimated mean values by race for systolic BP are lower, while those for diastolic BP are

higher compared with results obtained in the 2012 SANHANES. However, the results follow

the same pattern showing that Coloureds and Whites had the highest mean systolic BP. The

mean diastolic BP is also highest in Coloureds and lowest in Africans.

4.4.4 Mean systolic and diastolic BP by geographic type

The mean systolic BP for traditional dwellers is significantly lower than that of urban dwellers

in the year 2012. Mean systolic BP is also above the cut-off point for normal BP for all three

categories of geographical type. Mean diastolic BP is lower than the cut-off point of 80mmHg

in the years 2008 and 2010 for traditional dwellers.

Table 32: Mean systolic and diastolic BP and 95% CI by geographic type

BP type Geographic type 2008 2010 2012

Mean (95% CI)

Systolic

Traditional 122.0 (120.8–123.1) 122.2 (121.4–123.1) 120.9 (120.1–121.8)

Urban 123.8 (122.7–124.9) 123.3 (122.2–124.4) 123.1 (122.2–124.0)

Farms 124.5 (122.6–126.4) 121.8 (120.1–123.5) 123.8 (121.1–126.5)

Diastolic

Traditional 78.2 (77.5–79.0) 78.3 (77.7–78.9) 79.9 (79.1–80.6)

Urban 79.9 (79.0–80.8) 80.9 (80.2–81.7) 81.2 (80.6–81.8)

Farms 80.9 (79.4–82.4) 79.2 (78.1–80.3) 80.8 (78.7–82.9)

4.4.5 Mean systolic and diastolic BP by education level

Mean systolic BP is highest among those with no or primary-level education and lowest

among those with secondary-level education. For those with tertiary-level education, the

mean systolic BP is about the cut-off point for a normal BP.


Figure 15: Mean systolic BP by education level

Similarly, the diastolic BP is lowest among those with secondary-level education and highest

again among those with no education or primary-level education.

Figure 16: Mean diastolic BP by education level

120

125

130

135

140

Mea

n (

mm

Hg

)

2008 2010 2012

Year of NiDS survey

None Primary Secondary Cert/Dip Bachelors+

Mean systolic BP by education level

75

80

85

90

Mea

n D

iasto

lic B

P (

mm

Hg)

2008 2010 2012

Year of NiDS survey

None Primary Secondary Cert/Dip Bachelors+

Mean diastolic BP by education level

Me

an

Dia

sto

lic B

P (

mm

Hg)

Me

an

(m

mH

g)


4.4.6 Treatment coverage based on self-reported BP status

Table 33 shows results of those who self-reported diagnosis with hypertension and who self-

reported being on medication for hypertension.

Table 33: Prevalence of self-reported hypertension medication

2008 2010 2012

n Coverage n Coverage n Coverage

2 489 73.4 (70.2–76.3) 2 133 77.5 (73.9–80.7) 3 224 74.7 (71.4–77.8)

Treatment coverage for self-reported BP medication has not changed between the study

waves.

Table 34: Prevalence (%) and 95% CI of self-reported medication for hypertension by gender and age group

Gender Age group

2008 2010 2012


Females

15-24 66 32.5 (17.3–52.6) 38 20.6 (8.4–42.2) 59 36.2 (19.8–56.7)

25-34 115 55.7 (39.0–71.2) 84 42.9 (23.6–64.6) 172 30.6 (22.3–40.4)

35-44 289 61.6 (51.2–71.1) 197 76.6 (65.8–84.7) 319 67.6 (59.1–75.0)

45-54 465 80.8 (74.1–86.1) 410 85.6 (80.0–89.8) 568 81.6 (74.8–86.9)

55-64 440 84.0 (75.9–89.8) 407 90.3 (85.8–93.5) 644 85.6 (79.1–90.3)

65+ 498 86.2 (81.7–89.8) 464 85.9 (78.9–90.9) 667 89.5 (85.2–92.7)

Total 1 873 75.0 (70.8–78.7) 1 600 80.1 (76.4–83.2) 2 429 76.8 (73.7–79.7)

Males

15-24 14 27.2 (9.7–56.6) 15 25.1 (8.0–56.4) 16 25.5 (5.6–66.4)

25-34 41 22.4 (10.3–42.1) 29 41.7 (16.6–72.0) 44 22.1 (10.6–40.4)

35-44 79 66.8 (48.1–81.4) 64 56.7 (33.3–77.5) 91 54.9 (39.7–69.2)

45-54 149 68.3 (48.3–83.3) 123 66.5 (50.8–79.2) 192 65.1 (45.5–80.7)

55-64 175 80.8 (70.8–87.9) 144 87.6 (79.7–92.8) 225 87.9 (81.7–92.1)

65+ 156 80.7 (66.2–90.0) 157 82.8 (68.0–91.6) 221 82.0 (72.6–88.6)

Total 614 69.0 (62.9–74.5) 532 71.2 (63.5–77.7) 789 70.2 (63.5–76.1)

Self-reported prevalence of hypertension medication is higher among females than among

males and progressively increases with age.


4.4.7 Treatment coverage based on measured BP status

Table 35 shows the high blood pressure treatment status by gender, age group and study

years for those classified as having hypertension (raised BP or on medication). The category

„Not applicable‟ describes those who were diagnosed as hypertensive at the time of the study

based on systolic and diastolic BP measurement, but their blood pressure status was not

known (that is, no prior self-reporting of diagnosis with high blood pressure) and so

medication does not apply. As in Day et al,6 the treatment coverage is calculated by including

this category in the denominator of those on treatment. An advantage of calculating treatment

coverage in this way is that the treatment gap is identified and hopefully will be made known

to the health providers. The disadvantage of this method is that the expected treatment

coverage is underestimated since the majority of those with hypertension have not been

given an opportunity to take medication.

Table 35: Medication status for respondents with hypertension (raised BP or on medication) by gender and age group

Year Age group

Gender and hypertension medication status

Male Female

Yes No Not

applicable Total Yes No

Not applicable

Total

2008

15-24 5 4 180 189 26 3 165 194

25-34 12 9 212 233 57 12 218 287

35-44 55 9 248 312 191 44 311 546

45-54 110 13 225 348 390 40 335 765

55-64 143 9 173 325 387 21 232 640

65+ 133 9 178 320 426 38 277 741

Total 458 53 1 216 1 727 1 477 158 1 538 3 173

2010

15-24 7 4 223 234 9 4 196 209

25-34 13 7 254 274 41 13 247 301

35-44 40 8 226 274 147 20 322 489

45-54 87 15 222 324 337 30 366 733

55-64 119 12 175 306 354 21 251 626

65+ 130 9 155 294 411 24 267 702

Total 396 55 1 255 1 706 1 299 112 1 649 3 060

2012

15-24 4 4 282 290 17 8 227 252

25-34 15 14 314 343 67 40 312 419

35-44 54 17 260 331 225 41 349 615

45-54 144 28 267 439 479 44 330 853

55-64 181 34 178 393 576 46 226 848

65+ 179 28 152 359 587 45 231 863

Total 577 125 1 453 2 155 1 951 224 1 675 3 850


Table 36: Treatment coverage (%) for respondents with hypertension (raised BP or on medication) by gender and age group

Gender Age group 2008 2010 2012


Female

15-24 194 10.9 (5.6–20.1) 208 3.3 (1.4–7.8) 252 6.4 (3.2–12.4)

25-34 287 20.5 (12.5–31.6) 296 17.7 (8.9–32.2) 419 13.2 (8.3–20.4)

35-44 546 36.8 (29.7–44.5) 488 31.8 (24.6–40.0) 615 38.2 (31.8–45.0)

45-54 765 50.1 (44.9–55.4) 728 47.5 (41.7–53.4) 853 53.1 (47.3–58.9)

55-64 640 59.3 (53.3–65.1) 625 59.5 (52.6–66.0) 846 67.2 (61.2–72.7)

65+ 741 57.4 (51.1–63.4) 702 61.6 (53.6–69.0) 862 68.2 (61.4–74.4)

≥15 3 173 44.3 (40.1–48.6) 3 047 43.0 (39.3–46.8) 3 847 48.1 (44.9–51.3)

≥25 2 984 46.5 (42.5– 50.6) 2 839 45.9 (42.0– 49.8) 3 599 50.7 (47.3– 54.1)

Male

15-24 189 1.8 (0.7–4.7) 233 2.1 (0.8–5.3) 290 1.2 (0.3–5.0)

25-34 233 3.9 (1.9–7.8) 272 3.9 (1.2–11.3) 343 3.0 (1.3–6.7)

35-44 312 14.8 (9.1–23.2) 272 14.2 (7.3–25.8) 331 14.5 (7.9–25.3)

45-54 348 30.4 (22.9–39.2) 323 26.9 (19.4–35.9) 439 30.7 (24.1–38.3)

55-64 325 42.6 (34.6–51.0) 305 38.6 (29.7–48.3) 393 54.7 (46.6–62.4)

65+ 320 40.4 (32.3–49.1) 293 49.8 (41.8–57.8) 359 50.6 (43.2–58.0)

≥15 1 727 22.9 (19.7–26.6) 1 698 21.6 (17.9–25.7) 2 155 25.5 (22.2–29.1)

≥25 1 538 25.5 (22.0– 29.3) 1 465 24.0 (20.0– 28.5) 1 866 28.5 (24.8– 32.6)

Total 4 900 35.9 (32.6–39.4) 4 745 34.1 (31.1–37.2) 6 002 38.4 (35.7–41.2)

4.4.7.1 Discussion

As in Day et al,6 the estimates for 2008 for the age groups up to 45-54 years are higher than

those of 2010, while those of the other two older age groups are higher for 2010 than for

2008. However, the point estimates in the current analysis are slightly higher, although the

confidence interval includes the estimates obtained in Day et al.6 The results confirm that

females with hypertension are nearly twice as likely to be treated than are males. In fact, 74%

of males with hypertension are untreated and the treatment gap is largest in the younger age

groups. Although there does appear to be some increase in treatment coverage between

2008 and 2012, this is not significant.


4.4.8 Controlled on treatment based on medication and BP biomarkers

The respondent‟s medication status is based on self-reporting, while the effectiveness of the

treatment is based on hypertension status (Hypertensive/Pre-hypertensive/Normal) as shown

by the BP biomarkers. Among those on medication, some did not have systolic and diastolic

BP measurements and so their status is unknown at the times of the study.

Table 37: Percentage of respondents reporting medication for hypertension by BP status

BP status 2008 2010 2012


Normal 212 13.4 (10.9–16.5) 185 11.7 (8.6–15.7) 281 15.0 (12.1–18.5)

Prehypertension 422 24.1 (21.1–27.4) 365 25.4 (21.1–30.1) 669 28.1 (25.0–31.4)

Raised BP 1 070 50.0 (45.7–54.4) 948 54.0 (49.1–58.7) 1 498 53.8 (50.1–57.6)

Unknown 232 12.4 (9.9–15.4) 192 9 .0 (7.0–11.4) 81 3.1 (2.0–4.7)

Although there was a slight increase in the prevalence of those with normal BP or in

prehypertension state between 2008 and 2012, this increase was not significant. The

percentage without valid BP readings decreased over this period, possibly due to improved

survey implementation and data management. Nevertheless, it should be noted that the

sample size of those on medication when categorised by the BP status is somewhat low.

Table 38: Number on hypertension treatment by BP status

Hypertension level

2008 2010 2012

Normal 377 045 (267 662; 486 428) 322 195 (212 009, 432 381) 571 577 (410 467, 732 687)

Prehypertension 676 762 (562 393; 791 132) 700 723 (527 388, 874 058) 1 068 733 (880 612, 1 256 853)

Raised BP 1 403 905 (1 232 601, 1 575 209) 1 489 758 (1223506, 1756011) 2 049 843 (1 747 382, 2 352 304)

Unknown 348 090 (260 730, 435 451) 248 023 (187 756, 308 290) 117 857 (66 889, 168 826)

These results suggest that management of hypertension among those who have been

diagnosed and placed on treatment is woefully inadequate. Over two million adults (53.8% of

patients treated for hypertension) had measured BP above the threshold in NiDS 2012. A

further million (28.1%) were classified as prehypertensive.

4.5 Body Mass Index (BMI (kg/m2))

The mean BMI as well as the prevalence of being overweight or obese is reported by various

demographics.

4.5.1 Mean BMI by gender and age

The mean BMI remained almost the same (≈26 kg/m2) between 2008 and 2012.

Nevertheless, there appears to be a slight increase in the mean BMI for both genders

between 2008 and 2010, which again slightly decreased in 2012. In the three study periods,

females had a mean BMI that was significantly higher (on average more than 4.0 kg/m2) than

that of males.


Table 39: Mean Body Mass Index (BMI) by gender

Year Female Male Total

n Mean n Mean n Mean

2008 8 293 27.90 (27.63–28.18*) 5 520 23.64 (23.31–23.96) 13 813 26.02 (25.82–26.23)

2010 8 950 28.50 (28.18*–28.81) 6 189 24.33 (23.98–24.69) 15 139 26.58 (26.32–26.83)

2012 10 904 28.35 (28.05–28.64) 7 416 24.19 (23.88–24.50) 18 320 26.45 (26.22–26.67)

*The exact values are 28.17998 and 28.18093 in 2008 and 2010 respectively

4.5.2 Mean BMI by age group

Table 40: Mean Body Mass Index (BMI) by gender and age group

Age group

Gender 2008 2010 2012

n Mean (95% CI) n Mean (95% CI) n Mean (95% CI)

15-24

Female 2 389 24.5 (24.1–24.9) 2 664 24.8 (24.3–25.3) 3 094 24.4 (24.1–24.7)

Male 1 944 21.5 (21.2–21.8) 2 387 22.5 (22.1–22.9) 2 789 22.1 (21.8–22.4)

Subtotal 4 333 23.0 (22.8–23.3) 5 051 23.7 (23.4–24.0) 5 883 23.3 (23.1–23.5)

25-34

Female 1 534 27.4 (26.9–27.8) 1 748 28.2 (27.7–28.8) 2 254 28.2 (27.7–28.7)

Male 1 089 23.7 (23.2–24.2) 1 274 23.8 (23.2–24.5) 1 562 23.7 (23.2–24.1)

Subtotal 2 623 25.7 (25.3–26.0) 3 022 26.1 (25.6–26.5) 3 816 26.0 (25.6–26.4)

35-44

Female 1 429 29.8 (29.2–30.4) 1 466 30.4 (29.7–31.0) 1 759 30.2 (29.7–30.8)

Male 867 24.5 (24.0–25.0) 857 25.6 (24.5–26.7) 1 039 25.2 (24.7–25.8)

Subtotal 2 296 27.5 (27.1–27.9) 2 323 28.2 (27.6–28.8) 2 798 27.9 (27.5–28.3)

45-54

Female 1 229 30.7 (29.9–31.5) 1 278 31.0 (30.3–31.7) 1 562 30.9 (30.2–31.7)

Male 684 25.5 (24.8–26.2) 733 25.9 (25.0–26.8) 883 25.8 (25.1–26.6)

Subtotal 1 913 28.6 (28.1–29.1) 2 011 28.8 (28.2–29.3) 2 445 28.7 (28.2–29.3)

55-64

Female 849 29.9 (29.2–30.6) 908 30.9 (30.1–31.8) 1 170 30.7 (30.1–31.3)

Male 490 26.3 (25.4–27.3) 534 26.5 (25.8–27.2) 629 26.8 (26.1–27.4)

Subtotal 1 339 28.5 (27.9–29.0) 1 442 29.1 (28.4–29.7) 1 799 29.0 (28.6–29.5)

65+

Female 854 29.9 (29.2–30.6) 886 29.6 (28.9–30.4) 1 064 29.2 (28.5–30.0)

Male 439 25.3 (24.4–26.1) 404 26.0 (25.2–26.7) 513 26.1 (25.1–27.1)

Subtotal 1 293 28.2 (27.6–28.8) 1 290 28.4 (27.8–29.1) 1 577 28.1 (27.5–28.7)

Total 13 797*

26.0 (25.8 –26.2) 15 139 26.6 (26.3–26.8) 18 318 26.4 (26.2–26.7)

* 16 individuals did not have age recorded in 2008

For all age groups, females have much higher mean BMIs than males for all the three waves

of the study. The mean BMI for males in the age groups 35-44 years and older has increased

between 2008 and 2012, as can be seen by the distance from the cut-off point (25 kg/m2) for

being overweight. Between 2008 and 2012, the mean BMI among those aged 15-24 years of

both genders has remained below the cut-off point (25 kg/m2) for being overweight, and the

difference between the genders among this age group has remained almost the same.

Gauging from the 2008 and 2012 waves of the NiDS, it appears that mean BMI is at its peak

in the age groups 45-54 for females and 55-64 for males.


Figure 17: Mean BMI and 95% CI by gender and age group

4.5.3 Mean BMI by gender and race

Figure 18: Mean BMI and 95% CI by gender and race

The difference in mean BMI between the genders is highest among Africans, followed by

Coloureds. For Indians and Whites, there appears to be no significant difference in the mean

BMI, although on average, females in each of the two races have higher mean BMIs than

males.

15-24

25-34

35-44

45-54

55-64

65+

20 25 30 35 20 25 30 35 20 25 30 35

2008 2010 2012

Female Male

Age

gro

up

Mean (kg/m2)

Mean BMI and 95% CI by gender and age group

Black

Coloured

Indian

White

20 25 30 20 25 30 20 25 30

2008 2010 2012

Female Male

Ra

ce

Mean (kg/m2)

Mean BMI and 95% CI by gender and race

Race

Ag

e g

rou

p


Figure 19: Mean BMI by age group and race

In Figure 19, the range between the red and the purple dashed lines indicates the range for

overweight. It can be seen that between 2008 and 2012, the mean BMI for Whites in the age

groups 35-44 years and older has progressively moved from overweight status towards

obese status.

4.5.4 Mean BMI and education level

Figure 20: Mean BMI by education level

15-24

25-34

35-44

45-54

55-64

65+

20 25 30 35 20 25 30 35 20 25 30 35

2008 2010 2012


Age

gro

up

Mean (kg/m2)

Mean BMI by age group and race

25

26

27

28

29

Mea

n B

MI (k

g/m

2)

2008 2010 2012

Year of NiDS survey

None Pri Sec Cert/Dip Bachelors+

Mean BMI by education level

Me

an B

MI

(kg

/m2)

Ag

e g

rou

p


Those with secondary-level education have a mean BMI that is way below that of those with

none, certificate/diploma or degree education in the 2008 and 2012 study waves. However,

the estimated mean for those with a certificate/diploma or at least a Bachelor‟s degree level

of education may be biased due to relatively low sample sizes.

4.5.5 Mean BMI by geographical type of dwelling

Table 41: Mean BMI by geographical type

Geographical type 2008 2010 2012

Mean (95% CI)

Traditional 25.4 (25.1–25.8) 26.1 (25.8–26.4) 25.7 (25.4–25.9)

Urban 26.5 (26.2–26.8) 27.0 (26.6–27.4) 26.9 (26.5–27.2)

Farms 25.2 (24.5–26.0) 25.5 (24.9–26.1) 26.1 (25.7–26.6)

Urbanites have a higher mean BMI score compared with dwellers in traditional/farm settings

for all the three study periods. There is no clear trend in mean BMI within each geographical

setting, although there is a slight increase in mean BMI in 2012 and in 2010 compared with

2008.

4.6 Prevalence of BMI by categories

There was a slight increase in prevalence of overweight and a corresponding decrease in

prevalence of underweight individuals from 2008 to 2012.

Table 42: Distribution of BMI by categories

BMI Category 2008 2010 2012


Underweight 675 4.1 (3.5–4.7) 602 3.5 (2.9–4.3) 717 3.4 (2.9–3.9)

Normal weight 6 359 45.9 (44.2–47.6) 6 453 42.6 (41.0–44.3) 8 437 45.0 (43.1–46.9)

Overweight 3 257 24.9 (23.6–26.2) 3 843 25.4 (24.0–26.7) 4 631 26.5 (24.9–28.2)

Obese 3 522 25.2 (23.9–26.6) 4 176 28.5 (27.0–30.0) 4 538 25.1 (23.8–26.5)

4.6.1 Prevalence of BMI categories by age group and gender

The prevalence of obesity consistently increased in the younger four age groups for both

genders. The prevalence of obesity in females is at least twice that of males among all age

groups, but in the overweight category, only in the youngest two age groups is the

prevalence in females higher than that of males. Among females, the youngest three age

groups have prevalences of obesity that are significantly different from each other, while the

four oldest age groups have obesity prevalences that do not differ significantly from each

other.


Table 43: Prevalence of BMI categories by gender and age group

Year Age group

Females Males

n Overweight Obese n Overweight Obese

2008

15-24 2 389 26.3 (23.9–28.9) 14.1 (11.8–16.6) 1 944 10.9 (9.0–13.1) 4.1 (3.0–5.6)

25-34 1 534 31.0 (27.3–34.9) 29.9 (26.6–33.4) 1 089 22.1 (17.7–27.3) 11.4 (8.5–15.1)

35-44 1 429 27.0 (23.2–31.1) 46.4 (42.2–50.7) 867 30.2 (25.5–35.3) 15.8 (12.2–20.3)

45-54 1 229 22.4 (18.0–27.4) 54.1 (48.4–59.6) 684 29.9 (24.3–36.3) 22.5 (17.8–28.0)

55-64 849 26.9 (22.2–32.2) 48.6 (43.1–54.1) 490 32.3 (25.6–39.9) 24.9 (19.5–31.3)

65+ 854 27.0 (22.4–32.1) 47.1 (41.8–52.5) 439 28.1 (21.4–35.9) 20.8 (14.1–29.6)

Total 8 284 27.1 (25.7–28.6) 35.0 (33.2–36.9) 5 513 22.1 (20.0–24.3) 12.7 (11.0–14.7)

2010

15-24 2 651 26.3 (23.7–29.2) 16.7 (14.5–19.1) 2 382 15.4 (12.9–18.4) 7.9 (5.9–10.5)

25-34 1 733 31.9 (28.6–35.5) 36.9 (32.9–41.1) 1 264 19.4 (15.4–24.1) 13.6 (10.5–17.5)

35-44 1 461 26.3 (22.6–30.3) 48.5 (44.2–52.9) 853 28.8 (24.2–34.0) 20.5 (15.6–26.4)

45-54 1 273 25.8 (21.5–30.7) 55.4 (51.0–59.8) 731 26.6 (21.3–32.7) 27.1 (20.3–35.2)

55-64 905 24.4 (19.2–30.6) 55.1 (48.7–61.4) 533 39.2 (32.0–46.9) 26.5 (20.7–33.2)

65+ 885 27.5 (22.5–33.1) 47.7 (41.4–54.1) 403 30.4 (22.7–39.4) 21.5 (16.1–28.2)

Total 8 908 27.4 (25.9–29.0) 38.9 (36.9–41.1) 6 166 22.9 (20.7–25.4) 16.2 (14.3–18.4)

2012

15-24 3 095 24.1 (21.2–27.2) 12.3 (10.6–14.2) 2 789 13.0 (10.6–15.8) 4.5 (3.2–6.3)

25-34 2 254 28.1 (25.0–31.5) 35.6 (32.2–39.1) 1 562 24.0 (19.9–28.7) 8.6 (6.4–11.3)

35-44 1 759 31.3 (27.2–35.7) 45.8 (41.5–50.2) 1 039 35.6 (29.7–42.0) 14.3 (10.9–18.4)

45-54 1 563 26.6 (23.0–30.6) 51.9 (47.3–56.4) 884 25.5 (20.6–31.0) 23.5 (17.9–30.2)

55-64 1 170 23.8 (20.4–27.6) 53.0 (48.2–57.7) 629 41.6 (32.6–51.2) 21.7 (16.2–28.3)

65+ 1 064 33.6 (28.3–39.3) 39.6 (34.4–45.1) 513 32.1 (24.9–40.2) 22.2 (14.7–32.0)

Total 10 905 27.6 (25.9–29.3) 36.0 (34.1–38.0) 7 416 25.2 (22.8–27.8) 12.2 (10.7–14.0)


Figure 21: Prevalence of overweight by gender and age group

Figure 22: Prevalence of obesity by gender and age group

4.6.2 Prevalence of BMI categories by race and gender

In the three study periods, female Indians and male Whites have the highest prevalence of

being overweight, while the prevalence of being obese is highest in Whites for both genders.

There is, however, no significant difference in the prevalence of overweight and obesity in

females by race, but for males, the prevalence of obesity for Africans and Coloureds is

significantly lower than in Whites, except in 2008.

33.627.5

27.0

23.824.4

26.9

26.625.8

22.4

31.326.327.0

28.131.9

31.0

24.126.326.3

32.130.4

28.1

41.639.2

32.3

25.526.6

29.9

35.628.8

30.2

24.019.4

22.1

13.015.4

10.9

0 10 20 30 40 0 10 20 30 40

65+

55-64

45-54

35-44

25-34

15-24

65+

55-64

45-54

35-44

25-34

15-24

Female Male

2008 2010 2012

Prevalence (%)

Prevalence of overweight by gender and age group

39.647.747.1

53.055.1

48.6

51.955.4

54.1

45.848.5

46.4

35.636.9

29.9

12.316.7

14.1

22.221.520.8

21.726.5

24.9

23.527.1

22.5

14.320.5

15.8

8.613.6

11.4

4.57.9

4.1

0 20 40 60 0 20 40 60

65+

55-64

45-54

35-44

25-34

15-24

65+

55-64

45-54

35-44

25-34

15-24

Female Male

2008 2010 2012

Prevalence (%)

Prevalence of obesity by gender and age group


Table 44: Prevalence of BMI categories by gender and race

Year Gender Race n Underweight Normal weight Overweight Obese

2008

Females

African 6 702 2.6 (2.0–3.4) 36.2 (34.3–38.2) 26.9 (25.5–28.4) 34.3 (32.1–36.4)

Coloured 1 130 3.9 (2.5–6.1) 31.2 (25.1–38.1) 25.8 (21.4–30.8) 39.0 (35.3–42.9)

Indian 107 2.2 (0.4–11.3) 30.8 (20.6–43.3) 39.7 (21.2–61.8) 27.3 (13.8–46.9)

White 354 0.5 (0.1–2.5) 32.1 (25.0–40.2) 26.9 (21.2–33.4) 40.4 (31.9–49.6)

Total 8 293 2.5 (2.0–3.2) 35.4 (33.7–37.0) 27.1 (25.7–28.5) 35.0 (33.2–36.9)

Male

African 4 406 5.9 (5.0–7.0) 64.1 (61.3–66.8) 19.6 (17.7–21.7) 10.3 (8.8–12.1)

Coloured 740 11.4 (7.0–17.8) 44.5 (36.6–52.8) 25.2 (18.5–33.3) 18.9 (13.3–26.3)

Indian 72 8.6 (6.2–11.8) 39.1 (26.1–53.9) 33.4 (16.9–55.4) 18.9 (7.2–41.2)

White 302 1.4 (0.6–3.7) 33.5 (26.4–41.5) 38.0 (31.0–45.5) 27.1 (19.8–35.9)

Total 5 520 6.0 (5.1–7.1) 59.2 (56.2–62.2) 22.1 (20.0–24.3) 12.7 (11.0–14.6)

2010

Females

African 7 596 2.4 (1.9–3.0) 31.3 (29.5–33.0) 27.6 (26.1–29.1) 38.8 (36.7–41.0)

Coloured 1 043 3.5 (2.2–5.7) 33.2 (26.8–40.4) 25.4 (20.0–31.6) 37.9 (33.0–43.0)

Indian 86 4.7 (1.2–17.1) 38.6 (31.2–46.5) 29.7 (18.3–44.4) 27.0 (17.2–39.7)

White 183 1.1 (0.3–4.4) 26.2 (17.8–36.8) 27.7 (18.7–38.9) 45.1 (32.8–58.0)

Total 8 908 2.4 (1.9–3.0) 31.2 (29.5–33.0) 27.4 (25.9–29.0) 38.9 (36.9–41.1)

Males

African 5 254 4.5 (3.6–5.6) 59.9 (57.2–62.7) 22.0 (19.5–24.6) 13.6 (12.0–15.4)

Coloured 692 11.3 (7.0–17.6) 45.8 (41.6–50.0) 25.3 (18.0–34.4) 17.6 (11.5–26.0)

Indian 67 8.2 (3.5–18.0) 49.4 (34.4–64.6) 27.6 (15.9–43.6) 14.8 (4.1–41.4)

White 153 0.9 (0.1–5.1) 28.7 (20.4–38.9) 29.1 (21.1–38.5) 41.3 (29.8–53.8)

Total 6 166 4.8 (3.9–6.0) 56.0 (53.2–58.7) 22.9 (20.7–25.4) 16.2 (14.3–18.4)

2012

Females

African 9 031 2.0 (1.6–2.5) 34.9 (33.0–36.8) 27.7 (26.0–29.4) 35.4 (33.4–37.6)

Coloured 1 481 1.9 (1.1–3.0) 41.3 (36.0–46.7) 22.7 (19.3–26.7) 34.1 (29.9–38.6)

Indian 108 3.9 (0.8–17.1) 32.4 (20.4–47.3) 28.8 (18.3–42.3) 34.8 (22.8–49.2)

White 286 1.8 (0.5–6.0) 24.4 (18.3–31.8) 31.2 (22.9–40.9) 42.6 (33.7–52.1)

Total 10 906 2 (1.6–2.5) 34.4 (32.6–36.2) 27.6 (25.9–29.3) 36.0 (34.1–38.0)

Males

African 6 102 4.9 (4.1–5.9) 62.2 (59.4–64.9) 23.4 (21.1–25.8) 9.5 (8.4–10.9)

Coloured 1 009 9.7 (6.1–15.3) 55.1 (45.5–64.3) 21.2 (14.3–30.1) 14.0 (10.3–18.8)

Indian 81 6.5 (2.3–17.2) 42.8 (31.5–55.0) 36.6 (26.8–47.5) 14.2 (8.0–23.8)

White 225 0.5 (0.1–3.9) 23.1 (15.5–32.9) 42.3 (33.9–51.2) 34.1 (25.2–44.2)

Total 7 417 5.0 (4.1–6.0) 57.6 (54.5–60.6) 25.2 (22.8–27.8) 12.2 (10.7–14.0)


Figure 23: Prevalence of overweight by gender and race

Figure 24: Prevalence of obesity by gender and race

31.2

27.7

26.9

28.8

29.7

39.7

22.7

25.4

25.8

27.7

27.6

26.9

42.3

29.1

38.0

36.6

27.6

33.4

21.2

25.3

25.2

23.4

22.0

19.6

0 10 20 30 40 0 10 20 30 40

White

Indian

Coloured

African

White

Indian

Coloured

African

Female Male

2008 2010 2012

Prevalence (%)

Prevalence of overweight by gender and race

42.6

45.1

40.4

34.8

27.0

27.3

34.1

37.9

39.0

35.4

38.8

34.3

34.1

41.3

27.1

14.2

14.8

18.9

14.0

17.6

18.9

9.5

13.6

10.3

0 10 20 30 40 50 0 10 20 30 40 50

White

Indian

Coloured

African

White

Indian

Coloured

African

Female Male

2008 2010 2012

Prevalence (%)

Prevalence of obesity by gender and race


4.6.3 Prevalence of BMI category by geographical type

Table 45: Prevalence of BMI category by geographical type

Year Geographical type n Underweight Normal Overweight Obese

2008

Traditional 5 919 4.7 (3.9–5.7) 50.1 (47.9–52.2) 23.3 (21.9–24.8) 21.9 (20.0–23.8)

Urban 6 292 3.7 (3.0–4.6) 42.5 (40.0–45.1) 25.9 (23.8–28.0) 27.9 (26.0–29.9)

Farms 1 602 3.8 (2.6–5.7) 51.8 (45.7–57.9) 24.2 (20.5–28.2) 20.2 (16.3–24.7)

Total 13 813 4.1 (3.5–4.7) 45.9 (44.2–47.6) 24.9 (23.6–26.2) 25.2 (23.9–26.6)

2010

Traditional 6 855 3.3 (2.6–4.3) 44.9 (42.8–47.0) 26.1 (24.1–28.2) 25.7 (24.0–27.5)

Urban 6 555 3.5 (2.6–4.6) 40.5 (37.9–43.2) 25.1 (23.2–27.1) 30.9 (28.7–33.3)

Farms 1 561 5.2 (3.9–6.9) 48.7 (44.6–52.7) 24.6 (21.2–28.4) 21.6 (18.5–25.0)

Total 14 971 3.6 (2.9–4.3) 42.6 (40.9–44.3) 25.4 (24.0–26.8) 28.5 (27.0–30.0)

2012

Traditional 8 004 3.6 (2.9–4.3) 50.0 (47.6–52.4) 26.0 (24.0–28.1) 20.5 (18.8–22.2)

Urban 8 761 3.2 (2.6–3.9) 42.4 (39.7–45.2) 26.7 (24.4–29.2) 27.6 (25.7–29.6)

Farms 1 558 4.1 (2.7–6.1) 44.5 (39.4–49.7) 27.1 (24.3–30.1) 24.3 (21.2–27.6)

Total 18 323 3.4 (2.9–3.9) 45.0 (43.1–46.9) 26.5 (24.9–28.2) 25.1 (23.8–26.5)

The prevalence of obesity is significantly higher in urban dwellers than in traditional and farm

dwellers for all three study periods. There is no clear pattern for prevalence of overweight, as

it is highest in urban, traditional and farm dwellers in 2008, 2010 and 2012 respectively (not

significant).

4.6.4 Prevalence of BMI category by education level

The prevalence of obesity is lowest among those with secondary-level education, and is

significantly lower than that of those with a certificate/diploma and at least a Bachelor‟s

degree in the year 2012 study wave. The prevalence of overweight is highest in those with at

least a Bachelor‟s degree, followed by those with either a certificate or a diploma.

Table 46: Prevalence of BMI category by education level


n Underweight Normal Overweight Obese

2008

None 1 855 5.9 (4.3–8.0) 42.2 (38.2–46.2) 22.5 (19.5–25.8) 29.4 (25.8–33.4)

Primary 3 455 4.9 (4.1–6.0) 44.9 (42.4–47.5) 22.4 (20.4–24.6) 27.7 (25.5–30.1)

Secondary 7 377 4.1 (3.4–4.9) 49.2 (47.0–51.4) 24.1 (22.5–25.9) 22.6 (21.0–24.2)

Cert/Dip 885 1.4 (0.8–2.6) 36.1 (31.2–41.2) 32.2 (27.5–37.2) 30.3 (26.0–35.0)

Bachelor 241 0 30.2 (21.0–41.2) 38.9 (27.2–52.0) 30.9 (22.6–40.7)

Total 13 813 4.1 (3.5–4.7) 45.9 (44.2–47.6) 24.9 (23.6–26.2) 25.2 (23.9–26.6)

2010

None 1 823 3.7 (2.4–5.7) 38.7 (34.8–42.9) 24.4 (21.4–27.7) 33.2 (28.9–37.7)

Primary 3 491 4.9 (3.6–6.6) 42.4 (39.3–45.6) 24.2 (21.3–27.3) 28.5 (26.2–31.0)

Secondary 8 549 3.6 (2.8–4.4) 45.0 (42.8–47.2) 25.5 (23.7–27.3) 26.0 (24.0–28.0)

Cert/Dip 1 014 1.9 (1.1–3.4) 34.4 (29.7–39.5) 26.8 (22.7–31.2) 36.9 (32.0–42.1)

Bachelor 195 0 35.3 (25.0–47.2) 28.3 (19.6–39.0) 36.4 (25.9–48.3)

Total 15 072 3.5 (2.9–4.3) 42.6 (41.0–44.3) 25.4 (24.0–26.7) 28.5 (27.0–30.0)

2012

None 1 868 3.2 (2.1–4.8) 41.3 (37.9–44.9) 29.4 (26.2–32.8) 26.1 (22.7–29.9)

Primary 3 955 4.4 (3.4–5.6) 47.3 (44.8–49.9) 24.0 (21.3–27.0) 24.3 (22.0–26.7)

Secondary 10 359 3.8 (3.2–4.5) 48.4 (45.8–51.0) 25.2 (23.3–27.3) 22.6 (20.8–24.5)

Cert/Dip 1 800 1.4 (0.7–2.7) 33.4 (30.0–37.1) 31.7 (27.7–36.1) 33.5 (30.2–36.9)

Bachelor 339 0.1 (0.0–0.5) 30.7 (22.6–40.3) 33.4 (25.2–42.7) 35.8 (29.9–42.2)

Total 18 321 3.4 (2.9–3.9) 45 (43.1–46.9) 26.5 (24.9–28.2) 25.1 (23.8–26.5)


4.6.5 Mean systolic and diastolic BP by BMI levels

Both systolic and diastolic BP increase with increased BMI. There is a significant difference in

the two types of blood pressures for those classified as normal, overweight and obese in all

three study years.

Figure 25: Mean systolic and diastolic BP by BMI category

4.6.6 Prevalence of hypertension and raised BP by BMI category

Table 47: Prevalence (%) and 95% CI of hypertension and raised blood pressure by BMI category

Year BMI category Hypertension Raised BP


2008

Underweight 166 21.7 (17.3–26.8) 148 19.8 (15.9–24.5)

Normal weight 1 478 20.2 (18.6–21.9) 1 329 18.1 (16.5–19.8)

Overweight 1 132 31.0 (28.7–33.5) 989 27.3 (24.9–29.9)

Obese 1 782 48.1 (44.8–51.4) 1 447 38.2 (35.2–41.3)

Total 4 558 30.0 (28.5–31.4) 3 913 25.5 (24.1–27.0)

2010

Underweight 120 20.5 (13.5–29.9) 108 19.1 (12.0–28.9)

Normal weight 1 291 20.7 (18.9–22.8) 1 187 19.0 (17.1–21.0)

Overweight 1 174 30.0 (27.3–32.8) 1 007 25.2 (22.6–28.0)

Obese 1 869 45.6 (42.7–48.4) 1 576 38.4 (36.0–40.8)

Total 4 454 30.1 (28.7–31.6) 3 878 26.0 (24.6–27.5)

2012

Underweight 128 16.3 (12.3–21.2) 113 14.5 (10.9–19.1)

Normal weight 1 860 21.4 (19.6–23.4) 1 660 19.2 (17.3–21.4)

Overweight 1 579 32.7 (29.9–35.7) 1 307 26.1 (23.4–28.9)

Obese 2 300 50.5 (47.9–53.1) 1 827 40.2 (37.5–42.9)

Total 5 867 31.5 (30.0–33.0) 4 907 26.1 (24.6–27.7)

Prevalence of hypertension and raised BP both increased as BMI increased.

80

100

120

140

2008 2010 2012 2008 2010 2012

Systolic Diastolic

Underweight Normal weight Overweight Obese

Mea

n (

mm

Hg

)

Year of NiDS survey

Mean systolic and diastolic BP by BMI category

Me

an (

mm

Hg)


4.6.7 Discussion: Body Mass Index (BMI)

The mean BMIs for females (≈28 kg/m2) and males (≈24kg/m2) in the three study years are

similar to the results of the 2012 SANHANES (29.0 and 23.2 kg/m2 respectively). The

prevalence of being overweight for the three study periods ranged between 27.1-27.9% and

22.1-25.2%, while that of obesity ranged between 35-38.9% and 12.0-16.2% among females

and males respectively. These results are slightly higher than those in the SANHANES

(overweight and obesity were 25.0% and 40.1% for females and 19.6% and 11.6% for males

respectively) except for the prevalence of obesity in females. As in the SANHANES, there is

a trend indicating that prevalence of obesity increased with age in both genders, especially

for the younger four age groups before slightly decreasing in either of the two oldest age

groups.

Table 48: Comparing BMI in 1998 SADHS and 2012 NiDS

Va

ria

ble

Mean BMI Overweight Obese

Females Males Females Males Females Males

1998 SADHS

2012 NiDS

1998 SADHS

2012 NiDS

1998 SADHS

2012 NiDS

1998 SADHS

2012 NiDS

1998 SADHS

2012 NiDS

1998 SADHS

2012 NiDS

Age group

15-24 23.7 24.4 21.1 22.1 20.0 24.1 8.4 13.0 9.6 12.3 2.7 4.5

25-34 27.2 28.2 23.4 23.7 29.2 28.1 20.7 24.0 27.0 35.6 7.8 8.6

35-44 29.2 30.2 25.0 25.2 30.7 31.3 24.9 35.6 39.3 45.8 12.8 14.3

45-54 29.9 30.9 25.3 25.8 26.5 26.6 28.1 25.5 45.5 51.9 17.3 23.5

55-64 29.8 30.7 25.2 26.8 25.6 23.8 28.3 41.6 46.1 53.0 14.4 21.7

65+ 27.7 29.2 24.4 26.1 26.5 33.6 28.5 32.1 33.3 39.6 13.9 22.2

Race

African 27.6 28.3 23.0 23.7 25.9 27.7 17.1 23.4 31.2 35.4 7.8 9.5

Coloured 27.0 27.7 24.1 24.0 25.3 22.7 22.1 21.2 28.5 34.1 9.2 14.0

Indian 25.1 27.4 23.1 25.4 27.3 28.8 23.7 36.6 21.3 34.8 9.0 14.2

White 26.5 29.7 26.2 28.5 27.4 31.2 36.1 42.3 25.5 42.6 20.8 34.1

Total 27.3 28.3 23.4 24.2 26.1 27.6 19.8 25.2 30.1 36.0 9.3 12.2

There is a trend indicating that mean BMI and the prevalence of overweight and obesity for

both genders disaggregated by age and race have increased when comparing the 1998

SADHS and 2012 NiDS results.

4.7 Risk factor of physical inactivity

Information on physical exercise was collected based on the number of times per week

(never; less than once; once; twice; three or more) that the respondent engaged in physical

activity, but with no indication of intensity or duration. In this report, the first four categories

are combined to describe physical inactivity, while the last category (three or more times)

describes the acceptable number of physical exercise sessions per week.


4.7.1 Physical inactivity by gender

Table 49: Prevalence (%) and 95% CI of physical inactivity by gender

Year Physical activity

Gender

Male Female Total


2008 3+ times 1 279 21.6 (19.7–23.7) 639 8.7 (7.6–10.0) 1 918 14.4 (13.2–15.7)

<3 times 4 919 78.4 (76.3–80.3) 8 618 91.3 (90.0–92.4) 13 537 85.6 (84.3–86.8)

2010 3+ times 1 032 15.0 (12.9–17.4) 375 4.9 (4.0–6.1) 1 407 9.6 (8.3–11.0)

<3 times 5 877 85.0 (82.6–87.1) 9 405 95.1 (93.9–96.0) 15 282 90.4 (89.0–91.7)

2012 3+ times 1 556 19.5 (17.7–21.5) 706 7.5 (6.3–8.9) 2 262 13.0 (11.8–14.2)

<3 times 6 009 80.5 (78.5–82.3) 10 426 92.5 (91.1–93.7) 16 435 87.0 (85.8–88.2)

The prevalence of physical inactivity is exceedingly high (more than 85%) for all the study

years and females are more physically inactive compared with males.

4.7.2 Physical inactivity by age groups

Table 50: Distribution of physical inactivity by age groups

Year Age group Physical exercise per week

3+ times <3 times n Prevalence (95% CI) n Prevalence (95% CI)

2008

15-24 932 21.8 (20.0–23.8) 3 740 78.2 (76.2–80.0)

25-34 334 12.2 (10.2–14.4) 2 589 87.8 (85.6–89.8)

35-44 284 14.1 (11.7–17.0) 2 304 85.9 (83.0–88.3)

45-54 180 10.4 (7.9–13.5) 1 998 89.6 (86.5–92.1)

55-64 103 9.2 (6.8–12.3) 1 436 90.8 (87.7–93.2)

65+ 85 7.7 (5.2–11.3) 1 452 92.3 (88.7–94.8)

Total 1 918 14.4 (13.2–15.7) 13 519 85.6 (84.3–86.8)

2010

15-24 758 14.8 (12.9–16.9) 4 725 85.2 (83.1–87.1)

25-34 271 10.2 (7.5–13.6) 3 030 89.8 (86.4–92.5)

35-44 171 7.1 (5.3–9.5) 2 381 92.9 (90.5–94.7)

45-54 108 7.3 (5.1–10.4) 2 112 92.7 (89.6–94.9)

55-64 62 5.2 (3.1–8.4) 1 551 94.8 (91.6–96.9)

65+ 37 3.5 (2.0–6.2) 1 482 96.5 (93.8–98.0)

Total 1 407 9.6 (8.3–11.0) 15 281 90.4 (89.0–91.7)

2012

15-24 1 104 18.7 (16.5–21.0) 4 833 81.3 (79.0–83.5)

25-34 466 14.6 (12.2–17.3) 3 408 85.4 (82.7–87.8)

35-44 285 11 (8.9–13.6) 2 557 89.0 (86.4–91.1)

45-54 200 8.4 (6.6–10.5) 2 316 91.6 (89.5–93.4)

55-64 121 7.6 (5.4–10.5) 1 716 92.4 (89.5–94.6)

65+ 85 7.7 (5.1–11.6) 1 603 92.3 (88.4–94.9)

Total 2 261 13.0 (11.8–14.2) 16 433 87.0 (85.8–88.2)

The percentage of physical inactivity increases as age increases for the three study periods.


4.7.3 Physical inactivity by race

Table 51: Distribution of physical inactivity by race

Year Race

Physical exercise per week

3+ times <3 times

n Prevalence (95% CI) n Prevalence (95% CI)

2008

African 1 252 12.5 (11.3–13.7) 10 877 87.5 (86.3–88.7)

Coloured 340 14.1 (10.9–18.1) 1 862 85.9 (81.9–89.1)

Indian 40 24.1 (16.0–34.5) 184 75.9 (65.5–84.0)

White 286 27.0 (22.3–32.3) 615 73.0 (67.7–77.7)

Total 1 918 14.4 (13.2–15.7) 13 538 85.6 (84.3–86.8)

2010

African 1 098 8.8 (7.5–10.2) 12 842 91.2 (89.8–92.5)

Coloured 199 9.5 (5.6–15.7) 1 910 90.5 (84.3–94.4)

Indian 37 26.6 (16.6–39.7)*

138 73.4 (60.3–83.4)

White 73 12.1 (8.5–16.8) 392 87.9 (83.2–91.5)

Total 1 407 9.6 (8.3–11.0) 15 282 90.4 (89.0–91.7)

2012

African 1 527 11.1 (9.9–12.3) 13 871 88.9 (87.7–90.1)

Coloured 555 19.3 (16.0–23.2) 2 019 80.7 (76.8–84.0)

Indian 31 15.6 (10.7–22.2) 164 84.4 (77.8–89.3)

White 149 22.5 (17.6–28.2) 381 77.5 (71.8–82.4)

Total 2 262 13 (11.8–14.2) 16 435 87.0 (85.8–88.2)

*sample size too small

Physical inactivity is highest among Africans, followed by Coloureds and is lowest in Whites

for all the three study periods. Estimates for Indians are based on a small sample.

4.7.4 Physical inactivity by geographical type

Table 52: Distribution of physical inactivity by geographical type

Year Geographical type


3+ times <3 times


2008

Traditional 559 10.4 (8.8–12.1) 5 735 89.6 (87.9–91.2)

Urban 1 145 16.6 (14.8–18.6) 6 296 83.4 (81.4–85.2)

Farms 214 13.7 (10.6–17.4) 1 507 86.3 (82.6–89.4)

Total 1 918 14.4 (13.2–15.7) 13 538 85.6 (84.3–86.8)

2010

Traditional 461 6.2 (5.1–7.6) 6 943 93.8 (92.4–94.9)

Urban 779 11.2 (9.4–13.2) 6 719 88.8 (86.8–90.6)

Farms 158 11.6 (6.7–19.4) 1 515 88.4 (80.6–93.3)

Total 1 398 9.5 (8.3–11.0) 15 177 90.5 (89.0–91.7)

2012

Traditional 788 10.5 (9.2–12.0) 7 324 89.5 (88.0–90.8)

Urban 1 223 14.3 (12.7–16.1) 7 773 85.7 (83.9–87.3)

Farms 251 12.7 (9.9–16.1) 1 338 87.3 (83.9–90.1)

Total 2 262 13.0 (11.8–14.2) 16 435 87.0 (85.8–88.2)

Those living in traditional settings are more physically inactive compared with those in farms

and urban settings.


4.7.5 Physical inactivity by education level

Table 53: Distribution of physical inactivity by education level



3+ times <3 times


2008

None 38 2.3 (1.5–3.6) 2 083 97.7 (96.4–98.5)

Primary 256 7.6 (6.1–9.5) 3 532 92.4 (90.5–93.9)

Secondary 1 303 16.5 (15.1–18.1) 6 887 83.5 (81.9–84.9)

Cert/Dip 240 24.8 (20.0–30.3) 797 75.2 (69.7–80.0)

Bachelor+ 81 19.8 (13.5–28.1) 239 80.2 (71.9–86.5)

Total 1 918 14.4 (13.2–15.7) 13 538 85.6 (84.3–86.8)

2010

None 21 1.1 (0.6–2.0) 2 031 98.9 (98.0–99.4)

Primary 213 5.6 (4.3–7.4) 3 653 94.4 (92.6–95.7)

Secondary 1 005 11.3 (9.8–12.9) 8 388 88.7 (87.1–90.2)

Cert/Dip 135 12.3 (9.1–16.4) 998 87.7 (83.6–90.9)

Bachelor+ 32 10.9 (6.6–17.5) 211 89.1 (82.5–93.4)

Total 1 406 9.6 (8.3–11.0) 15 281 90.4 (89.0–91.7)

2012

None 55 2.9 (1.7–4.9) 1 892 97.1 (95.1–98.3)

Primary 337 6.8 (5.6–8.3) 3 716 93.2 (91.7–94.4)

Secondary 1 466 14.2 (12.7–15.8) 9 035 85.8 (84.2–87.3)

Cert/Dip 335 18.9 (15.3–23.1) 1 508 81.1 (76.9–84.7)

Bachelor+ 69 18.2 (13.5–24.1) 282 81.8 (75.9–86.5)

Total 2 262 13.0 (11.8–14.2) 16 433 87.0 (85.8–88.2)

Physical inactivity is more prevalent among those with no education while it is lowest among

those with at least tertiary-level education (certificate and above).

4.7.6 Factors associated with physical exercise

A logistic model is fitted here to test which of the five factors (gender, age, race, geographic

type and education level) was significantly associated with physical exercise. The odds of

males engaging in at least three days of physical exercise per week is more than three times

that of females. Whites were also about three times more likely than Africans to engage in at

least three days of physical exercise, and the odds of achieving the desired level of physical

exercise decreased as age increased. The probability of engaging in physical exercise at

least three times a week appears to increase with higher levels of education.


Table 54: Demographic and social factors associated with physical exercise (3+ times per week)

Characteristic 2008 2010 2012

Odds Ratio (OR) Prob. Odds Ratio (OR) Prob.*

Odds Ratio (OR) Prob.

Gender cf.: Female

Male 3.49 0.000 4.14 0.000 3.69 0.000

Age group cf.: 15-24

25-34 0.45 0.000 0.54 0.000 0.56 0.000

35-44 0.47 0.000 0.46 0.000 0.45 0.000

45-54 0.37 0.000 0.36 0.000 0.38 0.000

55-64 0.32 0.000 0.34 0.000 0.33 0.000

65+ 0.31 0.000 0.27 0.000 0.29 0.000

Race cf.: African

Coloured 1.66 0.000 1.10 0.269 2.96 0.000

Indian 1.60 0.014 2.80 0.000 1.69 0.013

White 3.45 0.000 1.92 0.000 4.18 0.000

Geographic type cf.: Traditional

Urban 1.27 0.000 1.56 0.000 0.92 0.174

Farms 1.27 0.014 1.54 0.000 1.22 0.028

Education level cf.: None

Primary 2.56 0.000 3.29 0.000 1.75 0.000

Secondary 4.83 0.000 5.03 0.000 2.49 0.000

Cert/Dip 8.21 0.000 6.58 0.000 3.94 0.000

Bachelor+ 7.33 0.000 7.85 0.000 4.44 0.000

*Prob. = probability

4.7.7 Mean systolic and diastolic BP by physical activity

Table 55: Mean systolic and diastolic BP by physical activity

Year Type of BP

Physical activity

Mean (95% CI)

2008

Systolic 3+ times 120.8 (119.2– 122.4)

<3 times 123.6 (122.9– 124.4)

Diastolic 3+ times 77.4 (76.0– 78.7)

<3 times 79.8 (79.2– 80.3)

2010

Systolic 3+ times 121.6 (119.1– 124.0)

<3 times 122.9 (122.2– 123.7)

Diastolic 3+ times 77.9 (76.2– 79.6)

<3 times 80.1 (79.6– 80.6)

2012

Systolic 3+ times 121.8 (120.1– 123.5)

<3 times 122.6 (121.9– 123.2)

Diastolic 3+ times 78.7 (77.5– 79.8)

<3 times 81.0 (80.6– 81.5)

The mean systolic BP is only significantly different between the two states of physical activity

in the year 2008, while the mean diastolic BP is significantly higher in those who are

physically inactive compared with that of the physically active.


4.7.8 Distribution of raised BP by physical activity

Table 56: Prevalence of blood pressure status by physical activity

Year BP Status


3+ times <3 times


2008

Normal 737 43.1 (38.8–47.4) 4 633 40.6 (38.6–42.7)

Prehypertension 597 36.3 (32.9–39.7) 3 776 32.8 (31.1–34.5)

Raised BP 346 20.6 (17.4–24.4) 3 682 26.6 (25.1–28.1)

2010

Normal 532 42.9 (35.8–50.4) 5 103 37.5 (35.7–39.4)


Raised BP 234 20.0 (15.7–25.0) 3 752 26.8 (25.3–28.3)

2012

Normal 919 40.9 (36.9–44.9) 6 384 38.2 (36.6–39.9)


Raised BP 507 21.9 (18.5–25.8) 4 464 26.9 (25.4–28.5)

The prevalence of raised BP among the physically inactive is significantly higher than that

among those who are physically active for the three study periods. Consequently, for the

physically inactive, the prevalence of normal blood pressure is lower (not significant) than

that of the physically active.

4.7.8.1 Discussion: Physical inactivity

A review of studies that have identified physical inactivity as a modifiable risk factor

associated with a number of non-communicable diseases including cardiovascular diseases,

diabetes, stroke, cancer, arthritis and depression have been documented31, and have shown

that among both men and women who reported increased levels of physical activity and

fitness, the risk of death was reduced by about 20-35%. Studies on prevalence of physical

inactivity have shown wide variability depending on the setting. For example, a World Health

Survey 2002-200332 comparing worldwide variability in physical inactivity among 51 countries

ranked South Africa third and fourth for males and females with a prevalence of 44.7% and

47.6% of physical inactivity respectively. The results found in the NiDS data for this review

show prevalence of more than 78% for both males and females for the three study periods,

although similarly, females have a higher prevalence than males. However, there may be

differences in the way the questionnaires in the two surveys were phrased. The World Health

Survey32 defined a person as physically inactive if they did not meet either of the following

criteria:

three or more days of vigorous activity during the last week, consisting of at least 20

minutes per day; or

five or more days of moderate-intensity activity or walking during the last week,

consisting of at least 30 minutes per day; or five or more days of any combination of

walking, moderate-, or vigorous-intensity activities during the last week, achieving a

minimum of at least 600 MET-minutes per week, where one MET is defined as the

energy spent sitting quietly (equivalent to [4.184 kJ] · kg -1 · h-1).

This definition of physical activity was also used in the 2003 SADHS, in which prevalence of

physical inactivity in males was 31.6% and that of females 46.8%, as well as in a 2000


study33 that estimated burden of disease attributable to physical inactivity, which found

prevalence of physical inactivity in males and females was 43.4% and 45.8% respectively.

The second criterion in the definition of physical activity may be very important in

distinguishing physical exercise from physical activity. Physical exercise is a subcategory of

physical activity that is planned, structured, repetitive and purposeful in the sense that the

improvement or maintenance of one or more components of physical fitness is the objective,

whereas physical activity includes exercise as well as other activities which involve bodily

movement and are done as part of playing, working, active transportation, house chores and

recreational activities.34 It is suspected that the NiDS survey collects data on physical

exercise rather than physical activity and therefore might have excluded many respondents

from meeting the criteria for being physically active. Therefore, these results cannot be

compared to those of the 2003 SADHS or the 2002-2003 World Health Survey. The results

are also not comparable to the 2012 SANHANES survey, in which where physical fitness was

evaluated by a medical doctor by taking a cardiovascular fitness test.

4.8 Risk factor of alcohol use

Data on alcohol use were collected in terms of the amount of standard alcohol (small glass of

wine; a 330 ml can of regular beer; a tot of spirits; or a mixed drink) consumed in a particular

day (seven categories), and also on the number of days per week (eight categories) during

which the respondent consumed alcohol. For the two alcohol use variables, the majority of

the categories had few responses and in this analysis, some of these categories were

combined in order to make reasonably reliable estimates of alcohol use based on

disaggregation by demographic variables. The amount of standard drinks consumed was

reconstructed with three categories (none, <5, and 5+ standard drinks), while the number of

days per week during which the respondent consumed alcohol was reduced to four

categories (never drunk; no longer drink; rarely drink; and drinks at least one day per week).

In the 1998 SADHS, risky drinking was defined as drinking five or more standard drinks per

day for men and three or more drinks per day for women. In the 2003 SADHS, responsible

drinking is defined as less than four standard drinks per day, hazardous levels as four to five

drinks per day, and harmful drinking as six or more drinks per day for men, while for women

the comparable amounts are less than two, two to three, and four or more. It is not clear why

there are different cut-off points in the number of standard alcoholic drinks for the categories

of alcohol use by gender and whether there is evidence to show that these are the

comparable numbers of standard drinks for the same health effects by gender.

The American National Institute of Alcohol Abuse and Alcoholism (NIAAA)35 has summarised

the following definition for alcohol use:

1. According to the Dietary Guidelines for Americans, moderate alcohol drinking is up to

one drink per day for women and up to two drinks per day for men.

2. The NIAAA has defined binge drinking as a pattern of drinking that brings blood

alcohol concentration (BAC) levels to 0.08 g/dL. This typically occurs after four drinks

for women and five drinks for men – in about two hours.

3. The Substance Abuse and Mental Health Services Administration (SAMHSA), which

conducts the annual National Survey on Drug Use and Health (NSDUH), defines

binge drinking as drinking five or more alcoholic drinks on the same occasion on at

least one day in the past 30 days.


4. Heavy drinking is defined as consumption of five or more drinks on the same

occasion on each of five or more days in the past 30 days.

In other literature,36 heavy episodic drinking (HED) is defined as consumption of 60 or more

grams of pure alcohol (more than six standard drinks in most countries) on at least one single

occasion at least monthly.

Based on the data structure (sparseness especially after disaggregation) and this brief

literature analysis, alcohol use based on the amount of standard drinks consumed is

categorised into three levels: none, <5, and 5+, with the last two categories representing

„moderate/non-risky‟ drinking and „risky‟ drinking respectively. No differentiation is made in

the categorisation of the amount of alcohol consumed between the genders.

4.8.1 Prevalence of alcohol use (amount of standard drinks)

Table 57: Distribution of amount of standard alcohol drinks consumed

Standard drinks

2008 2010 2012


None 11 735 72.9 (70.7–74.9) 13 307 74.7 (72.5–76.8) 14 300 72.4 (70.3–74.5)

<5 2 159 15.8 (13.8–18.1) 1 777 14.8 (12.9–16.9) 2 462 16.6 (14.8–18.6)

5+ 1 595 11.3 (10.3–12.4) 1 443 10.5 (9.4–11.7) 1 820 10.9 (9.8–12.2)

4.8.2 Distribution of alcohol use (amount of alcohol drinks) by gender

Table 58: Distribution of amount of alcohol use by gender

Year Gender

Amount of standard alcohol drinks

None <5 5+


2008

Female 8 010 84.3 (81.7–86.5) 886 11.9 (9.7–14.4) 376 3.9 (3.2–4.7)

Male 3 725 58.5 (56.0–60.8) 1 273 20.9 (18.6–23.4) 1 218 20.7 (18.8–22.7)

Total 11 735 72.9 (70.8–74.9) 2 159 15.8 (13.8–18.1) 1 594 11.3 (10.3–12.4)

2010

Female 8 789 86.2 (83.9–88.2) 639 10.4 (8.6–12.6) 321 3.3 (2.7–4.1)

Male 4 518 61.0 (58.3–63.6) 1 138 20.0 (17.7–22.6) 1 122 19.0 (17.1–21.1)

Total 13 307 74.7 (72.5–76.8) 1 777 14.8 (12.9–16.9) 1 443 10.5 (9.4–11.7)

2012

Female 9 670 83.9 (81.7–85.9) 969 11.9 (10.1–13.9) 460 4.2 (3.4–5.1)

Male 4 630 58.7 (55.9–61.4) 1 493 22.3 (20.1–24.7) 1 360 19.0 (17.0–21.2)

Total 14 300 72.4 (70.3–74.5) 2 462 16.6 (14.8–18.6) 1 820 10.9 (9.8–12.2)

For the three study periods, males are at least five times more likely to consume five or more

standard alcohol drinks in comparison to females. Also, the percentage of males consuming

at least five standard alcohol drinks is markedly above the overall percentage, while that of

females is significantly below this percentage.


4.8.3 Distribution of alcohol use (amount of standard drinks) by age group

Table 59: Amount of alcohol use by age group

Year Age group

Amount of standard alcohol drinks

None <5 5+


2008

15-24 3 907 80.3 (78.2–82.3) 423 11.0 (9.5–12.8) 355 8.6 (7.5–9.9)

25-34 2 075 70.1 (66.9–73.1) 411 14.2 (12.2–16.6) 441 15.7 (13.2–18.5)

35-44 1 843 68.5 (64.9–71.8) 429 18.2 (15.4–21.3) 321 13.4 (11.2–15.8)

45-54 1 558 70.9 (65.8–75.4) 371 18.7 (14.4–23.9) 253 10.5 (8.5–12.9)

55-64 1 139 68.6 (63.6–73.2) 258 21.3 (16.7–26.7) 148 10.1 (7.9–12.8)

65+ 1 203 73.7 (67.2–79.3) 263 22.2 (16.7–28.8) 72 4.1 (3.0–5.6)

Total 11 725 72.9 (70.8–74.9) 2 155 15.8 (13.8–18.1) 1 590 11.3 (10.3–12.4)

2010

15-24 4 700 82.5 (80.3–84.5) 403 9.8 (8.1–11.7) 352 7.7 (6.5–9.1)

25-34 2 451 70.5 (67.4–73.5) 411 14.3 (12.0–16.9) 405 15.2 (13.0–17.8)

35-44 1 907 67.2 (62.6–71.4) 332 20.0 (16.1–24.5) 273 12.9 (10.4–15.8)

45-54 1 671 72.1 (66.8–76.8) 289 17.6 (13.1–23.3) 231 10.3 (8.4–12.5)

55-64 1 281 74.5 (69.0–79.3) 199 18.5 (14.3–23.6) 118 7.0 (5.0–9.5)

65+ 1 296 83.5 (77.5–88.1) 143 12.9 (8.7–18.7) 64 3.6 (2.5–5.2)

Total 13 306 74.7 (72.5–76.8) 1 777 14.8 (12.9–16.9) 1 443 10.5 (9.4–11.7)

2012

15-24 4 896 81.1 (78.6–83.3) 528 10.3 (8.7–12.3) 489 8.6 (7.2–10.3)

25-34 2 657 64.2 (60.9–67.4) 602 19.3 (16.7–22.3) 585 16.4 (14.1–19.0)

35-44 2 076 67.9 (63.8–71.8) 450 18.9 (15.8–22.5) 306 13.1 (10.7–16.0)

45-54 1 874 71.4 (67.6–74.9) 384 20.7 (17.4–24.4) 242 8.0 (6.2–10.1)

55-64 1 407 74.0 (68.2–79.1) 277 17.5 (14.1–21.7) 136 8.4 (4.7–14.7)

65+ 1 389 80.8 (76.1–84.7) 221 15.7 (11.9–20.6) 61 3.5 (2.5–4.9)

Total 14 299 72.4 (70.3–74.5) 2 462 16.6 (14.8–18.6) 1 819 10.9 (9.8–12.2)

The percentage consuming five or more standard drinks of alcohol is highest between the

ages of 25-44 years and lowest in the younger and oldest age groups.

4.8.4 Distribution of alcohol use (amount of standard drinks) by race

The estimate for the amount of alcohol consumed is somewhat unreliable for Indians due to

the relatively small sample size. The percentage of those drinking no alcohol is highest

among Africans for the three study periods. Moderate drinking (less than five standard drinks)

is highest among Whites and lowest among Africans, while heavy drinking (five or more

standard drinks) is highest among Coloureds followed by Africans. The percentages of heavy

and moderate drinking among Whites decreased slightly between 2008 and 2012, while

those of heavy drinking among Coloureds and Africans has remained unchanged.


Table 60: Prevalence of amount of alcohol consumed by race

Year Race

Amount of standard drinks consumed

None < 5 5+


2008

African 9 830 78.2 (76.7–79.6) 1 153 10.7 (9.8–11.7) 1 173 11.1 (10.1–12.2)

Coloured 1 406 63.6 (59.4–67.5) 462 19.7 (15.1–25.3) 335 16.7 (13.2–20.9)

Indian* 167 66.6 (56.5–75.3) 47 24.8 (17.3–34.4) 10 8.6 (4.4–16.0)

White 332 41.4 (33.0–50.4) 497 49.6 (39.9–59.3) 77 9.0 (5.8–13.7)

Total 11 735 72.9 (70.7–74.9) 2 159 15.8 (13.8–18.1) 1 595 11.3 (10.3–12.4)

2010

African 11 486 79.5 (77.7–81.1) 1 200 9.7 (8.6–11.0) 1 145 10.8 (9.6–12.0)

Coloured 1 460 66.4 (61.5–70.9) 366 19.9 (16.3–24.0) 252 13.8 (9.6–19.5)

Indian* 126 72.1 (59.2–82.2) 37 25.0 (15.1–38.3) 10 2.9 (1.2–6.9)

White 235 43.5 (35.6–51.7) 174 49.4 (41.5–57.4) 36 7.1 (4.8–10.3)

Total 13 307 74.7 (72.5–76.8) 1 777 14.8 (12.9–16.9) 1 443 10.5 (9.4–11.7)

2012

African 12 268 76.8 (75.0–78.5) 1 687 12.3 (11.2–13.4) 1 343 10.9 (9.7–12.3)

Coloured 1647 61.5 (57.9–64.9) 479 21.7 (17.5–26.6) 438 16.9 (12.8–22.0)

Indian* 148 72.5 (62.3–80.7) 35 20.4 (13.6–29.4) 12 7.2 (3.8–13.1)

White 237 46.4 (36.5–56.5) 261 47.7 (38.2–57.4) 27 5.9 (2.8–12.1)

Total 14 300 72.4 (70.3–74.5) 2 462 16.6 (14.8–18.6) 1 820 10.9 (9.8–12.2)

* sample size relatively small

The results, showing that Whites have the highest prevalence of moderate drinkers, are

similar to those found in the 2003 SADHS.

4.8.5 Distribution of alcohol (amount of standard drinks) use by geographic type

The percentage of the amount of alcohol consumed (less than five or at least five standard

drinks) is not significantly different between urban and farm dwellers for the three study

periods. The highest percentage of non-drinkers is found among traditional dwellers. The

results show that for two of the three study periods, prevalence of moderate drinking (<5

drinks) was highest among urbanites. These results, although lower than those of the 2003

SADHS, follow a similar pattern where urban dwellers were found to have high prevalence of

moderate drinking (<4 drinks) compared with non-urban dwellers.

Table 61: Distribution of amount of standard alcohol drinks consumed by geographic type



None <5 5+


2008

Traditional 5 480 85.3 (83.8–86.7) 442 7.8 (6.7–9.1) 383 6.9 (6.1–7.8)

Urban 5 084 66.8 (63.4–70.1) 1 394 20.1 (16.9–23.8) 987 13.1 (11.5–14.7)

Farms 1 171 68.9 (63.6–73.8) 323 15.7 (11.8–20.6) 225 15.4 (11.4–20.3)

Total 11 735 72.9 (70.7–74.9) 2 159 15.8 (13.8–18.1) 1 595 11.3 (10.3–12.4)

2010

Traditional 6 486 86.5 (83.9–88.7) 456 6.2 (5.2–7.4) 433 7.3 (5.5–9.7)

Urban 5 454 68.4 (65.4–71.3) 1 096 19.4 (16.6–22.6) 845 12.2 (10.8–13.7)

Farms 1 277 73.0 (67.1–78.2) 213 15.3 (11.6–19.9) 157 11.7 (8.2–16.4)

Total 1 3217 74.7 (72.6–76.8) 1 765 14.7 (12.9–16.8) 1 435 10.5 (9.4–11.7)




None <5 5+


2012

Traditional 6 853 82.5 (80.1–84.6) 663 8.8 (7.8–10.0) 547 8.7 (7.1–10.5)

Urban 6 315 67.6 (64.5–70.5) 1 549 20.4 (17.7–23.4) 1 068 12 (10.4–13.8)

Farms 1 132 68.7 (63.7–73.3) 250 19.7 (15.7–24.6) 205 11.6 (8.5–15.6)

Total 14 300 72.4 (70.3–74.5) 2 462 16.6 (14.8–18.6) 1 820 10.9 (9.8–12.2)

4.8.6 Distribution of alcohol (amount of standard drinks) use by education level

Table 62: Distribution of amount of standard alcoholic drinks consumed by education level

Year Education Level


None <5 5+


2008

None 1 679 79.6 (76.4–82.5) 230 9.7 (7.9–11.8) 211 10.7 (8.4–13.4)

Primary 2 924 76.0 (73.5–78.3) 451 12.4 (10.6–14.4) 420 11.6 (9.9–13.7)

Secondary 6 323 74.8 (72.9–76.6) 1 080 14.0 (12.4–15.8) 809 11.2 (9.9–12.6)

Cert/Dip 652 61.5 (55.6–67.1) 263 25.1 (19.4–31.7) 125 13.4 (10.3–17.2)

Bachelor+ 157 37.0 (25.4–50.4) 135 55.6 (40.7–69.6) 30 7.3 (3.9–13.3)*

Total 11 735 72.9 (70.7–74.9) 2 159 15.8 (13.8–18.1) 1 595 11.3 (10.3–12.4)

2010

None 1 699 83.1 (79.6–86.1) 205 9.1 (7.4–11.2) 133 7.8 (5.4–11.1)

Primary 3 107 80.4 (77.9–82.7) 365 9.7 (7.9–11.7) 353 10.0 (8.4–11.7)

Secondary 7 516 75.6 (73.3–77.8) 983 14.2 (12.3–16.3) 816 10.2 (9.0–11.7)

Cert/Dip 823 63.1 (57.9–68.1) 167 20.6 (16.2–25.8) 124 16.3 (12.6–20.8)

Bachelor+ 160 45.9 (31.4–61.1) 57 48.1 (34.6–62.0) 17 6.0 (3.2–10.8)*

Total 13 305 74.7 (72.5–76.8) 1 777 14.8 (12.9–16.9) 1 443 10.5 (9.4–11.7)

2012

None 1 569 81.5 (78.0–84.6) 225 11.7 (9.2–14.7) 134 6.8 (5.1–9.0)

Primary 3 141 75.3 (72.5–77.8) 481 13.7 (11.8–15.9) 411 11.0 (9.1–13.2)

Secondary 8 104 73.9 (71.8–75.8) 1 302 15.4 (13.7–17.2) 1 036 10.8 (9.5–12.2)

Cert/Dip 1 250 64.1 (59.1–68.9) 367 22.3 (18.0–27.2) 213 13.6 (10.8–17.0)

Bachelor+ 235 53.5 (37.7–68.7) 86 36.3 (24.9–49.4) 26 10.2 (4.1–23.2)*

Total 14 299 72.4 (70.3–74.5) 2 461 16.6 (14.8–18.6) 1 820 10.9 (9.8–12.2) * Estimates unreliable due to small sample size

The percentage of moderate drinking (less than five standard drinks of alcohol) is highest

among those with at least a Bachelor‟s degree for all three study periods. Given the relatively

small sample sizes for this educational level in the 2010 and 2012 study periods, it cannot be

established that the observed decrease in prevalence between the study periods is accurate.

There is no clear relationship between education level and risk drinking (5+ standard drinks).

This is contrary to the 2003 SADHS findings, in which those with no education reported the

highest hazardous alcohol drinking (4-5 standard drinks).


4.8.7 Systolic and diastolic BP by alcohol use (standard drinks consumed)

Table 63: Mean systolic and diastolic BP by amount of standard alcohol drinks consumed

BP type Number of standard drinks

2008 2010 2012

Systolic

None 122.6 (121.8– 123.4) 122.2 (121.5– 122.9) 121.6 (120.8– 122.3)

< 5 124.9 (123.5– 126.4) 123.6 (122.0– 125.1) 125.5 (124.2– 126.7)

5+ 125.4 (123.6– 127.3) 125.5 (123.5– 127.6) 123.6 (122.0– 125.2)

Diastolic

None 79.0 (78.4– 79.6) 79.5 (79.0– 80.0) 80.2 (79.7– 80.8)

< 5 80.7 (79.8– 81.7) 81.3 (80.0– 82.6) 82.2 (81.3– 83.0)

5+ 80.3 (79.1– 81.5) 80.6 (79.3– 82.0) 81.5 (80.4– 82.6)

There is a significant difference in mean systolic BP between those who do not consume

alcohol and those who consume alcohol (whether less than five or at least five standard

alcohol drinks) between 2008 and 2012. The mean diastolic BP for those who do not use

alcohol is slightly lower than that of those who consume less than five standard drinks of

alcohol. There is no statistical difference between those who consume more than five

standard alcohol drinks and those who do not consume alcohol. However, it should be noted

that the estimate for those who take at least five standard drinks could be affected by the

relatively small sample size compared with that of the other categories of the amount of

alcohol consumed.

4.8.8 Prevalence (%) and 95% CI of raised BP by amount of alcohol consumed

Table 64: Prevalence of raised BP by amount of standard alcoholic drinks consumed

Amount of alcohol consumed

2008 2010 2012


None 2 955 24.9 (23.3–26.5) 3 092 25.0 (23.6–26.5) 3 624 25.3 (23.7–26.8)

<5 603 25.6 (22.7–28.7) 485 28.0 (24.1–32.3) 766 28.6 (25.4–32.0)

5+ 479 28.0 (24.4–32.0) 362 27.7 (23.5–32.3) 531 27.8 (23.7–32.4)

Total 4 037 25.3 (23.9–26.8) 3 939 25.7 (24.3–27.2) 4 921 26.1 (24.6–27.7)

For the three study periods, there appears to be no statistical difference in the prevalence of

raised BP in the three categories of amount of alcohol consumed. Nevertheless, the

prevalence of raised BP is higher for those who consume alcohol (whether less than five or at

least five standard alcohol drinks) compared with those who do not. The pattern shown here,

where there is an increase in prevalence of raised BP from those who do not drink to those

who drink less than five drinks, followed by a slight decrease in those who drink five or more

drinks, is in line with findings from a previous study.37


4.8.9 Frequency (days per week) of alcohol use

Table 65: Distribution of alcohol consumption by number of days per week

Alcohol consumption per week

2008 2010 2012


Never drunk 10 144 63.0 ( 60.965.1) 11 996 65.7 (63.3–68.1) 12 801 64.1 (61.9–66.3)

No longer drink 1 592 9.8 (8.8–10.9) 1 311 7.9 (7.1–8.8) 1 499 7.9 (7.1–8.9)

Rarely 1 912 13.6 (12.5–14.9) 1 878 15.1 (13.6–16.8) 2 065 13.9 (12.5–15.5)

1+ days 1 855 13.6 (12.0–15.3) 1 554 11.2 (10.1–12.6) 2 323 14.0 (12.8–15.4)

The percentage of those who consume alcohol at least one day per week is similar for the

2008 and 2012 study periods, and is slightly higher than that of the 2010 study period.

4.8.10 Prevalence of alcohol use (frequency of days per week) by gender

Table 66: Frequency (days/week) of alcohol use by gender

Year Gender

Alcohol use by days per week

Never drunk No longer drink Rarely 1+ days


2008

Female 7 238 76.6 (74.0–79.0) 772 7.6 (6.6–8.7) 743 9.6 (8.3–11.1) 527 6.2 (4.7–8.1)

Male 2 906 45.8 (43.5–48.0) 820 12.7 (11.2–14.3) 1 168 18.7 (17.1–20.4) 1 328 22.9 (20.8–25.2)

Total 10 144 63.0 (60.9–65.1) 1 592 9.8 (8.8–11.0) 1 911 13.6 (12.4–14.9) 1 855 13.6 (12.0–15.3)

2010

Female 8 157 79.0 (76.4–81.4) 632 6.6 (5.8–7.6) 656 10.2 (8.6–12.1) 370 4.1 (3.4–5.1)

Male 3 839 50.1 (47.4–52.9) 679 9.4 (8.2–10.9) 1 222 20.9 (18.7–23.2) 1 184 19.6 (17.5–21.9)

Total 11 996 65.7 (63.3–68.1) 1 311 7.9 (7.1–8.8) 1 878 15.1 (13.6–16.8) 1 554 11.2 (10.1–12.6)

2012

Female 8 930 77.4 (74.9–79.7) 740 6.3 (5.4–7.3) 821 9.7 (8.3–11.3) 641 6.6 (5.5–7.9)

Male 3 871 48.4 (45.8–50.9) 759 9.9 (8.6–11.3) 1 244 18.9 (17.0–20.9) 1 682 22.9 (20.9–25.0)

Total 12 801 64.1 (61.9–66.3) 1 499 7.9 (7.1–8.9) 2 065 13.9 (12.5–15.5) 2 323 14.0 (12.8–15.4)

For the three study periods, males are at least three times more likely to consume alcohol at

least one day per week compared with females.


4.8.11 Frequency (days per week) of alcohol use by age group

Table 67: Frequency (days/week) of alcohol use by age group

Year Age group

Alcohol use by days per week



2008

15-24 3 604 73.9 (71.5–76.2) 303 6.2 (5.2–7.5) 496 12.6 (10.9–14.4) 288 7.3 (6.0–8.8)

25-34 1 741 57.8 (54.3–61.1) 334 12.3 (10.2–14.9) 424 14.6 (12.5–16.8) 430 15.3 (12.6–18.6)

35-44 1 537 58.3 (54.8–61.7) 307 10.2 (8.4–12.2) 342 13.9 (11.9–16.2) 410 17.6 (15.0–20.6)

45-54 1 315 61.1 (56.4–65.6) 243 9.8 (7.8–12.2) 292 14.6 (11.5–18.4) 332 14.5 (11.4–18.4)

55-64 938 57.0 (52.6–61.3) 201 11.6 (8.8–15.1) 173 12.9 (9.9–16.6) 233 18.5 (15.4–22.0)

65+ 999 61.3 (55.2–67.0) 204 12.4 (9.8–15.6) 181 12.7 (10.0–15.9) 157 13.7 (8.7–20.7)

Total 10 134 63.0 (60.8–65.1) 1 592 9.8 (8.8–11.0) 1 908 13.6 (12.5–14.9) 1 850 13.6 (12.0–15.3)

2010

15-24 4 472 77.0 (74.4–79.3) 228 4.6 (3.5–5.9) 523 12 (10.3–13.8) 283 6.5 (5.4–7.9)

25-34 2 180 61.5 (58.2–64.8) 271 8.1 (6.7–9.7) 486 17.5 (15.0–20.2) 371 12.9 (11.0–15.1)

35-44 1 693 59.6 (55.2–63.8) 214 6.4 (5.2–7.8) 340 17.8 (14.6–21.6) 306 16.2 (13.4–19.4)

45-54 1 423 57.9 (52.6–63.0) 248 13 (10.5–16.0) 260 16.1 (11.7–21.8) 295 13 (10.8–15.5)

55-64 1 097 61.8 (56.2–67.2) 184 11.5 (9.4–14.1) 169 15.3 (11.1–20.8) 175 11.3 (8.8–14.5)

65+ 1 131 71.7 (66.5–76.3) 165 10.5 (7.9–13.8) 100 10.4 (7.1–14.9) 124 7.5 (5.3–10.5)

Total 11 996 65.7 (63.3–68.1) 1 310 7.9 (7.1–8.8) 1 878 15.1 (13.6–16.8) 1 554 11.2 (10.1–12.6)

2012

15-24 4 581 75.3 (72.4–78.1) 315 5.4 (4.3–6.7) 587 11.0 (9.3–13.0) 451 8.3 (7.0–9.7)

25-34 2 338 56.0 (52.7–59.1) 319 7.7 (6.4–9.3) 609 19.8 (17.1–22.8) 609 16.5 (14.3–19.0)

35-44 1 816 60.1 (56.2–63.9) 260 7.7 (6.2–9.5) 320 13.8 (11.1–17.1) 445 18.3 (15.5–21.5)

45-54 1 630 60.0 (56.2–63.7) 244 10.8 (8.9–13.0) 253 14.4 (11.4–18.0) 388 14.8 (12.3–17.6)

55-64 1 216 63.4 (58.2–68.3) 191 10.7 (8.3–13.7) 162 9.2 (7.5–11.2) 266 16.7 (12.4–22.2)

65+ 1 219 70.3 (65.6–74.6) 170 10.0 (7.6–13.0) 134 9.5 (6.9–13.0) 163 10.2 (8.0–12.8)

Total 12 800 64.1 (61.9–66.3) 1 499 7.9 (7.1–8.9) 2 065 13.9 (12.5–15.5) 2 322 14.0 (12.8–15.4)

For the three study periods, only the youngest age group had a prevalence that was

significantly lower than the respective overall prevalence of consuming alcohol at least one

day per week.


4.8.12 Frequency of alcohol consumption per week by race

Table 68: Distribution of number of days per week of alcohol consumption by race

Year Race




2008

African 8 849 69.2 (67.4–71.0) 982 8.9 (7.9–9.9) 1 249 11.6 (10.5–12.8) 1 086 10.3 (9.1–11.5)

Coloured 916 46.0 (41.8–50.2) 490 17.5 (15.2–20.1) 363 15.3 (12.2–19.0) 438 21.3 (18.2–24.7)

Indian* 151 59.9 (49.0–70.0) 16 6.7 (3.6–12.1) 36 15.4 (9.3–24.5) 21 18.0 (11.6–26.9)

White 228 29.7 (24.5–35.6) 104 11.7 (7.1–18.6) 264 27.0 (21.8–32.9) 310 31.6 (23.5–40.9)

Total 10 144 63.0 (60.9–65.1) 1 592 9.8 (8.8–10.9) 1 912 13.6 (12.5–14.9) 1 855 13.6 (12.0–15.3)

2010

African 10 556 71.3 (69.4–73.2) 930 7.0 (6.4–7.7) 1 348 11.3 (10.2–12.5) 1 155 10.3 (9.1–11.8)

Coloured 1 140 49.1 (43.2–55.0) 320 16.3 (12.2–21.4) 351 20.4 (17.0–24.3) 299 14.2 (11.3–17.6)

Indian* 117 69.0 (56.5–79.2) 9 2.6 (1.1–6.3) 28 14.4 (9.1–21.9) 21 14.0 (8.9–21.4)

White 183 33.6 (25.7–42.5) 52 9.2 (6.6–12.7) 151 41.9 (34.8–49.3) 79 15.4 (11.3–20.5)

Total 11 996 65.7 (63.3–68.1) 1 311 7.9 (7.1–8.8) 1 878 15.1 (13.6–16.8) 1 554 11.2 (10.1–12.6)

2012

African 11 105 68.3 (66.3–70.2) 1 163 8.1 (7.1–9.2) 1 535 11.7 (10.6–12.8) 1 587 11.9 (10.8–13.1)

Coloured 1 358 51.1 (47.2–54.9) 289 10.1 (7.9–12.8) 359 16.6 (13.2–20.6) 567 22.2 (19.2–25.7)

Indian* 143 69.4 (59.4–77.8) 5 3.1 (1.0–8.8) 28 18.3 (10.6–29.6) 19 9.3 (4.7–17.4)

White 195 40.4 (31.4–50.1) 42 5.7 (3.3–9.6) 143 28.8 (21.0–38.0) 150 25.1 (18.9–32.6)

Total 12 801 64.1 (61.9–66.3) 1 499 7.9 (7.1–8.9) 2 065 13.9 (12.5–15.5) 2 323 14.0 (12.8–15.4)


For the three study periods, the percentage of those who drink at least one day per week is

highest among Whites followed by Coloureds. The highest percentage of those who have

never drunk is highest among Indians, followed by Africans. Some estimates for Indians may

be unreliable due to small sample sizes in certain categories.


4.8.13 Frequency (days per week) of alcohol use geographic type

Table 69: Frequency (days/week) of alcohol use by geographic type

The prevalence of alcohol consumption per week is similar for the urban and farm dwellers,

but quite different compared with that of people living in traditional dwellings.

Year Geographic type




2008

Traditional 5 101 78.2 (75.2–80.9) 379 7.0 (5.6–8.7) 449 8.2 (7.1–9.4) 382 6.7 (5.8–7.7)

Urban 4 089 55.6 (52.2–59.1) 996 11.2 (9.7–12.9) 1 185 16.1 (14.3–18.1) 1 201 17.0 (14.5–19.9)

Farms 954 58.1 (52.6–63.4) 217 10.8 (8.5–13.7) 278 16.3 (13.5–19.5) 272 14.8 (11.1–19.5)

Total 10 144 63 (60.9–65.1) 1 592 9.8 (8.8–10.9) 1 912 13.6 (12.5–14.9) 1 855 13.6 (12.0–15.3)

2010

Traditional 6 052 79.3 (76.5–81.8) 434 6.2 (5.4–7.1) 501 7.5 (6.4–8.9) 457 7.0 (5.6–8.6)

Urban 4 768 58.7 (55.4–62.0) 686 8.6 (7.4–10.0) 1 142 19.1 (16.9–21.6) 912 13.5 (11.8–15.4)

Farms 1 098 62.5 (56.0–68.5) 179 8.8 (6.2–12.2) 221 15.9 (11.4–21.6) 176 12.9 (9.9–16.6)

Total 11 918 65.8 (63.4–68.2) 1 299 7.8 (7.0–8.7) 1 864 15 (13.5–16.7) 1 545 11.3 (10.1–12.6)

2012

Traditional 6 282 74.5 (71.5–77.2) 571 7.5 (6.2–9.0) 618 9.3 (7.9–10.9) 639 8.8 (7.6–10.1)

Urban 5 527 59 (56.0–62.0) 788 8.2 (7.1–9.6) 1 248 16.2 (14.2–18.5) 1 425 16.5 (14.7–18.4)

Farms 992 61.5 (56.1–66.6) 140 7.2 (5.0–10.3) 199 14.3 (9.8–20.4) 259 17.1 (12.1–23.4)

Total 12 801 64.1 (61.9–66.3) 1 499 7.9 (7.1–8.9) 2 065 13.9 (12.5–15.5) 2 323 14.0 (12.8–15.4)


4.8.14 Frequency of alcohol use by education level

Table 70: Alcohol use (number of days per week) by education level





2008

None 1 441 69.0 (65.8–72.1) 238 10.6 (8.9–12.5) 200 8.1 (6.7–9.8) 243 12.2 (9.8–15.2)

Primary 2 475 65.0 (62.4–67.5) 449 11.0 (9.4–12.9) 417 11.9 (10.4–13.7) 457 12.1 (10.3–14.0)

Secondary 5 552 65.6 (63.5–67.6) 772 9.2 (8.0–10.5) 1 023 13.5 (12.1–15.1) 873 11.7 (10.4–13.2)

Cert/Dip 545 49.9 (44.5–55.4) 107 11.5 (8.4–15.5) 200 17.4 (14.6–20.6) 189 21.1 (15.7–27.8)

Bachelor+ 131 30.1 (20.7–41.6) 26 6.9 (3.2–14.4)* 72 28.5 (19.4–39.9)* 93 34.4 (23.9–46.8)

Total 10 144 63.0 (60.9–65.1) 1 592 9.8 (8.8–10.9) 1 912 13.6 (12.5–14.9) 1 855 13.6 (12.0–15.3)

2010

None 1 491 70.4 (66.3–74.2) 208 11.5 (9.3–14.0) 176 7.5 (5.9–9.5) 189 10.7 (8.1–14.0)

Primary 2 745 70.0 (66.9–72.8) 362 9.0 (7.8–10.5) 350 9.8 (8.2–11.7) 419 11.2 (9.5–13.2)

Secondary 6 880 67.5 (64.9–70.0) 636 7.1 (6.1–8.2) 1 113 14.9 (13.2–16.7) 790 10.5 (9.2–12.0)

Cert/Dip 734 53.3 (47.7–58.7) 89 9.0 (6.5–12.3) 186 22.7 (18.6–27.5) 127 15.0 (11.7–19.1)

Bachelor+ 144 39.5 (26.0–54.8) 16 5.3 (2.3–11.6)* 53 41.6 (28.5–55.9)* 29 13.6 (8.5–20.9)*

Total 11 994 65.7 (63.3–68.1) 1 311 7.9 (7.1–8.8) 1 878 15.1 (13.6–16.8) 1 554 11.2 (10.1–12.6)

2012

None 1 379 72.2 (68.2–75.8) 190 8.7 (7.0–10.7) 159 8.4 (6.3–11.0) 218 10.8 (8.7–13.3)

Primary 2 769 64.4 (61.4–67.3) 372 10.6 (8.8–12.8) 331 9.7 (8.0–11.7) 577 15.2 (13.1–17.7)

Secondary 7 314 66.1 (63.8–68.3) 790 7.4 (6.5–8.5) 1 200 13.8 (12.4–15.4) 1 194 12.6 (11.4–14.0)

Cert/Dip 1 125 56.1 (51.4–60.8) 125 7.5 (5.6–10.0) 315 18.6 (15.2–22.5) 278 17.8 (14.6–21.6)

Bachelor+ 213 48.8 (34.6–63.1) 22 4.4 (2.1–9.0)* 59 25.3 (15.9–37.8)* 56 21.4 (15.4–29.1)*

Total 12 800 64.1 (61.9–66.3) 1 499 7.9 (7.1–8.9) 2 064 13.9 (12.5–15.5) 2 323 14.0 (12.8–15.4)


There is a high prevalence of alcohol consumption at least one day per week among those

with a certificate or diploma compared with those with lower education or no education.


4.8.15 Systolic and diastolic BP by frequency (number of days per week) of alcohol

use

Table 71: Systolic and diastolic BP by frequency of alcohol use

BP type Frequency of alcohol use

2008 2010 2012

Systolic BP

Never drunk 122.3 (121.5; 123.1) 121.9 (121.2; 122.6) 121.5 (120.7; 122.2)

No longer drink 124.2 (122.3; 126.1) 124.9 (122.4; 127.4) 122.4 (120.5; 124.2)

Rarely drink 123.7 (121.9; 125.4) 123.1 (121.2; 125.1) 123.2 (122.0; 124.4)

1+ days 126.6 (124.9; 128.3) 126.2 (124.8; 127.5) 126.3 (124.8; 127.7)

Diastolic BP

Never drunk 78.9 (78.2; 79.5) 79.3 (78.7; 79.8) 80.2 (79.6; 80.7)

No longer drink 80.1 (78.8; 81.5) 81.4 (79.9; 82.9) 81.0 (79.8; 82.1)

Rarely drink 79.4 (78.2; 80.7) 80.6 (79.2; 82.0) 81.2 (80.3; 82.1)

1+ days 81.6 (80.7; 82.6) 81.7 (80.5; 82.9) 82.8 (81.8; 83.9)

For the three study periods, the mean systolic and diastolic BPs for those who drink at least

one day per week is significantly higher than the readings for those who have never used

alcohol. In 2012, those who no longer drank had a mean systolic BP that was significantly

lower than that of those who drank at least one day per week.

4.8.16 Prevalence of raised BP by frequency (days per week) of alcohol use

Table 72: Prevalence (%) and 95% CI of raised BP by number of days alcohol is consumed per week

Days/week alcohol is consumed

2008 2010 2012


Never drunk 2 486 24.6 (22.9–26.4) 2 735 24.7 (23.1–26.2) 3 177 24.8 (23.2–26.4)

No longer drink 470 26.7 (23.0–30.8) 357 28.3 (24.0–33.2) 447 29.2 (25.2–33.6)

Rarely drink 498 22.9 (19.6–26.6) 473 26.4 (22.3–31.0) 579 25.4 (21.9–29.2)

1+ days/week 586 30.2 ([27.0–33.7) 429 29.8 (25.8–34.1) 763 31.6 (28.1–35.3)

The prevalence of raised blood pressure is highest in those who consume alcohol at least

one day per week, followed by former users of alcohol. The prevalence of raised BP among

those who have „never drunk‟ alcohol and those who „rarely drink‟ is more or less the same,

as shown by results from the three waves of the study. It also appears that for the 2008 and

2012 study periods, the prevalence of raised BP is significantly higher among those who

consume alcohol at least once a week compared with those who do not consume alcohol at

all.

4.8.17 Demographic and social factors associated with alcohol use

A simple logistic model was used to find out which of the five demographic and social factors

(gender, age, race, geographic type and education) were associated with use of alcohol

(„ever taken alcohol‟ compared with „never used alcohol‟). Data from the three waves show

that race and gender had the strongest association with use of alcohol, where the odds of

ever using alcohol are at least 3.7 times higher for Whites compared with Africans. The odds

of males ever having used alcohol are almost five times that of females. Urban and farm

dwellers were also found to be more likely to use alcohol compared with traditional dwellers.

There is strong indication that those with secondary-level education are less likely to be users


of alcohol compared with those who have no education or those who have at least a

certificate/diploma level of education. The highest use of alcohol also seems to be in the age

group 25-34 years. These results showing gender and race differences in the use of alcohol

are similar to those reported in van Heerden et al.38

Table 73: Demographic and social factors associated with alcohol use

Characteristic

2008 2010 2012

Odds Ratio (OR)

Prob.*

Odds Ratio (OR)

Prob.*

Odds Ratio (OR)

Prob.*

Gender cf.: Female

Male 4.88 0.000 5.16 0.000 4.66 0.000

Age group cf.: 15-24

25-34 2.03 0.000 2.30 0.000 2.41 0.000

35-44 1.87 0.000 2.12 0.000 1.84 0.000

45-54 1.79 0.000 2.03 0.000 1.65 0.000

55-64 1.52 0.000 1.56 0.000 1.43 0.000

65+ 1.29 0.006 1.01 0.931 0.96 0.665

Race cf.: African

Coloured 1.85 0.000 1.61 0.000 1.89 0.000

Indian 1.03 0.864 1.43 0.057 0.96 0.832

White 5.72 0.000 3.66 0.000 4.75 0.000


Urban 2.12 0.000 2.11 0.000 1.79 0.000

Farms 2.03 0.000 1.53 0.000 1.57 0.000


Primary 0.89 0.121 0.85 0.046 0.86 0.057

Secondary 0.81 0.007 0.81 0.010 0.80 0.004

Cert/Dip 1.04 0.722 0.86 0.172 0.93 0.461

Bachelors+ 1.35 0.048 0.88 0.492 0.75 0.058


4.9 Smoking status

In the NiDS study, data on smoking status were collected based on whether the respondent

smokes (current), ever smoked regularly, and average number of cigarettes smoked per day

(both to current and past smokers). In the 1998 SADHS, tobacco use data were collected by

asking the respondents if they „ever used tobacco products‟. Similarly, in the 2012

SANHANES, no data on the number of cigarettes smoked were collected, but respondents

were asked if they ever smoked tobacco („never‟, „past smoker‟, „fewer than daily smoker‟

and „daily smoker‟). The last three categories were combined into a single category „ever

smoked‟. In the NiDS, respondents are classified as, „past smokers‟, „present smokers‟, or

„never smoked‟ by combining data from the variables of current smoking and the number of

cigarettes smoked, in order to compare results with other studies, especially the 1998

SADHS and 2012 SANHANES.

Heavy smoking has been defined differently in the literature. In Rusanen et al,39 heavy

smoking was defined as smoking more than two packs (40 cigarettes) per day, and this

appears to be the highest figure reported in the literature for defining heavy smoking. In

another study to investigate smoking patterns in Vietnam veterans,40 heavy smoking was


defined as consumption of 25 or more cigarettes per day and in Clair et al41 as smoking 20

cigarettes per day. A counter-definition of heavy smoking can also be inferred from Husten et

al,42 who have reviewed several definitions that have been used to define light and

intermittent smoking, which have ranged from a low of „1-4‟ to a high of „1-39‟ cigarettes per

day. Much of the grey literature seems to define heavy smoking as smoking of 20 or more

cigarettes per day.

Since there are no standard cut-off values for levels of smoking based on the number of

cigarettes smoked per day, the analysis in this report (for NiDS data) categorises the average

number of cigarettes smoked as „None‟, „<20‟ and „≥20‟, with the latter category representing

heavy smoking. In each study wave, some respondents indicated that they were current

smokers but did not provide data on the number of cigarettes smoked.

Table 74: Number of cigarettes smoked by smoking status

Year Cigarettes smoked per day Respondent smokes cigarettes

Yes No Total

2008

None 0 11 569 11 569

<20 2 652 527 3 179

>20 328 123 451

Unknown 299 0 299

Total 3 279 12 219 15 498

2010

None 0 13 836 13 836

<20 2 249 274 2 523

>20 235 62 297

Unknown 168 0 168

Total 2 652 14 172 16 824

2012

None 0 15 030 15 030

<20 2 862 337 3 199

>20 279 86 365

Unknown 100 0 100

Total 3 241 15 453 18 694

It can be seen from Table 74 that the number of those who report that they are smokers and

fail to provide the number of cigarettes smoked per day has decreased from 2008 to 2012.

4.9.1 Prevalence of smoking by gender

Table 75: Prevalence of smoking by gender

Year Ever smoked

Gender Total

Male Female

n Prevalence (%) n Prevalence (%) n Prevalence (%)

2008

Past smoker 419 6.1 (5.2–7.2) 268 3.0 (2.3–4.0) 687 4.4 (3.8–5.1)

Current smoker 2 282 36.5 (34.3–38.7) 997 9.1 (7.7–10.8) 3 279 21.2 (19.8–22.7)

Never smoked 3 526 57.4 (55.2–59.6) 8 009 87.8 (85.8–89.5) 11 535 74.4 (72.8–75.9)

2010

Past smoker 232 4.0 (3.0–5.3) 137 1.9 (1.4–2.8) 369 2.9 (2.2–3.8)

Current smoker 1 979 30.6 (28.0–33.3) 665 7.3 (5.7–9.4) 2 644 18.0 (16.3–19.9)

Never smoked 4 722 65.4 (62.7–68.1) 9 020 90.7 (88.4–92.6) 13 742 79.1 (77.0–81.0)


Year Ever smoked

Gender Total

Male Female


2012

Past smoker 299 4.0 (3.3–5.0) 165 2.0 (1.4–2.9) 464 2.9 (2.4–3.6)

Current smoker 2 414 33.6 (31.3–36.0) 827 7.8 (6.3–9.7) 3 241 19.6 (18.0–21.3)

Never smoked 4 850 62.4 (60.0–64.7) 10 139 90.2 (88.0–92.0) 14 989 77.5 (75.7–79.2)

It appears that the overall estimated prevalence of past smokers dropped between 2008 and

2010 and then stagnated between 2010 and 2012. Between 2008 and 2010, there was also a

3% decrease in the prevalence of current smokers, which increased slightly between 2010

and 2012. Prevalences of current smokers in the three study waves are more than four times

higher in males compared with females. The prevalences of past smokers are also higher in

males than in females for the three study periods.

Table 76: Comparison of prevalence of average number of cigarettes smoked by smoking status

Year Ever smoked

Average number of cigarettes smoked per day

<20 ≥20

n Prevalence (%) n Prevalence (%)

2008

Past smoker 525 83.3 (78.5–87.2) 120 16.7 (12.8–21.5)

Current smoker 2 652 86.8 (83.7–89.5) 328 13.2 (10.5–16.3)

Total 3 177 86.2 (83.4–88.6) 448 13.8 (11.4–16.6)

2010

Past smoker 273 82.0 (75.7–87.0) 62 18.0 (13.0–24.3)

Current smoker 2 241 86.8 (82.6–90.1) 235 13.2 (9.9–17.4)

Total 2 514 86.1 (82.5–89.1) 297 13.9 (10.9–17.5)

2012

Past smoker 337 72.7 (63.7–80.1) 86 27.3 (19.9–36.3)

Current smoker 2 862 86.6 (82.7–89.6) 279 13.4 (10.4–17.3)

Total 3 199 84.8 (81.3–87.8) 365 15.2 (12.2–18.7)

For the three study periods, the prevalence of heavy smoking is slightly higher in those who

are past smokers compared with those who are current smokers. Consequently, the

prevalence of light smokers is higher in current smokers compared with that of past smokers.


4.9.2 Distribution of smoking status by age group

Table 77: Prevalence of smoking by age group

Year Age group

Ever smoked

Past smoker Current smoker Never smoked


2008

15-24 113 2.5 (1.9–3.3) 602 13.5 (11.8–15.4) 3 974 84.0 (82.0–85.8)

25-34 105 3.9 (2.9–5.1) 749 23.7 (21.2–26.4) 2 077 72.4 (69.5–75.2)

35-44 124 4.8 (3.6–6.3) 706 27.8 (24.8–30.9) 1 766 67.5 (64.3–70.5)

45-54 125 5.3 (3.8–7.4) 600 25.8 (22.3–29.6) 1 459 68.9 (64.5–73.0)

55-64 114 8.0 (5.9–10.9) 381 22.8 (19.7–26.2) 1 048 69.2 (65.6–72.5)

65+ 103 6.4 (4.4–9.0) 234 15.4 (12.5–18.8) 1 203 78.3 (74.6–81.6)

2010

15-24 58 1.5 (1.0–2.1) 512 10.4 (8.8–12.3) 4 940 88.1 (86.1–89.8)

25-34 56 2.1 (1.2–3.5) 613 21.5 (17.9–25.7) 2 646 76.4 (72.2–80.2)

35-44 60 3.1 (1.5–6.1) 520 24.2 (21.2–27.6) 1 979 72.7 (68.7–76.3)

45-54 59 3.8 (2.3–6.1) 518 24.0 (19.9–28.5) 1 646 72.2 (67.1–76.8)

55-64 78 6.2 (4.0–9.4) 314 18.2 (14.9–22.1) 1 233 75.6 (71.2–79.6)

65+ 58 5.0 (3.4–7.4) 166 8.2 (6.1–11.0) 1 298 86.8 (83.4–89.5)

2012

15-24 71 1.6 (1.1–2.3) 580 10.9 (9.2–12.9) 5 286 87.5 (85.3–89.4)

25-34 71 1.9 (1.2–2.9) 841 23.8 (20.8–27.1) 2 957 74.3 (71.1–77.4)

35-44 80 3.2 (2.1–4.8) 614 24.1 (21.0–27.5) 2 151 72.7 (69.2–76.0)

45-54 82 3.1 (2.2–4.3) 586 25.5 (21.2–30.3) 1 847 71.4 (66.6–75.7)

55-64 75 5.9 (3.7–9.3) 392 19.2 (16.0–22.9) 1 370 74.9 (71.5–78.0)

65+ 85 6.6 (4.0–10.7) 226 14.3 (11.0–18.4) 1 377 79.0 (74.4–83.1)

The prevalence of past smokers increases with age and is consistently so in the year 2012.

The prevalence of current smoking increases with age up to the age groups of 35-44/45-54

years and decreases thereafter.


4.9.3 Smoking by race

Table 78: Smoking status by race

Year Race

Ever smoked



2008

African 311 3.1 (2.6–3.6) 1 882 17.0 (15.7–18.4) 9 974 79.9 (78.5–81.3)

Coloured 237 10.4 (7.5–14.2) 1 040 41.6 (37.6–45.7) 929 48.0 (44.4–51.6)

Indian*

9 4.0 (2.1–7.3) 50 22.2 (15.4–30.9) 164 73.8 (66.0–80.3)

White 130 9.9 (7.4–13.2) 307 37.0 (30.9–43.7) 469 53.0 (47.8–58.1)

2010

African 204 1.6 (1.3–2.1) 1 628 14.4 (12.9–16.1) 12 175 83.9 (82.2–85.5)

Coloured 122 7.3 (4.3–12.2) 859 42.1 (36.2–48.2) 1 129 50.6 (45.5–55.7)

Indian*

12 8.6 (4.4–16.3) 33 17.4 (11.0–26.3) 129 74.0 (61.0–83.8)

White 31 7.8 (4.2–14.1) 124 26.7 (21.1–33.2) 309 65.5 (57.6–72.6)

2012

African 285 2.1 (1.7–2.6) 1 948 16.0 (14.7–17.5) 13 161 81.9 (80.4–83.3)

Coloured 123 4.8 (2.8–8.0) 1 110 43.3 (38.0–48.6) 1 342 51.9 (47.3–56.5)

Indian*

5 3.7 (0.9–14.7) 39 17.6 (11.3–26.4) 150 78.7 (71.1–84.6)

White 51 7.9 (5.1–12.1) 144 27.5 (21.6–34.4) 336 64.5 (57.5–71.0)

*relatively small sample size for past smokers

Coloureds, followed by Whites, had the highest percentage of current smokers for the three

study periods. Also judging from the 2008 wave, which has a reasonable sample for both

Whites and Coloureds in the „past smoker‟ category compared with the other two study

waves, the prevalence of past smokers is higher than that of Africans. There were too few

respondents among Indians in both the „past smoker‟ and „current smoker‟ categories to

make credible conclusions.

4.9.4 Smoking by geographical type

The prevalence of past smokers is highest in urban dwellers, followed by farm dwellers in the

year 2008 and 2012, while prevalence of current smoking is highest in farm dwellers followed

by urban dwellers for all three years. The prevalence in those who live in traditional settings

is significantly lower than that of those who live in urban and farm settings. The sample size

of farm dwellers, however, is relatively smaller, especially in the 2010 and 2012 study years.

Table 79: Prevalence of smoking status by geographic type

Year Geographic type

Ever smoked



2008

Traditional 99 2.0 (1.4–2.8) 753 13.6 (12.2–15.2) 5 461 84.4 (82.6–86.0)

Urban 490 5.6 (4.7–6.7) 1 985 24.1 (22.0–26.4) 4 990 70.2 (67.8–72.6)

Farms 98 4.6 (3.2–6.5) 541 29.5 (25.1–34.3) 1 085 65.9 (60.1–71.4)

2010

Traditional 100 1.6 (1.1–2.2) 662 9.6 (8.3–11.2) 6 681 88.8 (87.0–90.4)

Urban 210 3.3 (2.3–4.7) 1 566 22.2 (19.7–24.9) 5 749 74.5 (71.6–77.2)

Farms 55 4.1 (2.0–8.1) 403 23.7 (19.6–28.4) 1 215 72.2 (66.9–76.9)

2012

Traditional 117 1.6 (1.2–2.3) 809 12.3 (10.8–13.8) 7 184 86.1 (84.4–87.6)

Urban 286 3.7 (2.8–4.7) 2 020 23.0 (20.7–25.4) 6 688 73.4 (70.9–75.7)

Farms 61 2.2 (1.3–3.9) 412 24.3 (19.8–29.4) 1 117 73.5 (67.9–78.5)


4.9.5 Smoking by educational level

Table 80: Smoking status by educational level


Ever smoked



2008

None 59 3.1 (2.1–4.5) 316 17.7 (14.8–20.9) 1 572 79.3 (76.0–82.2)

Primary 120 2.5 (1.9–3.3) 968 26.4 (23.7–29.3) 2 965 71.1 (68.2–73.8)

Secondary 200 2.3 (1.8–3.0) 1 621 19.1 (17.2–21.3) 8 677 78.5 (76.3–80.6)

Cert/Dip 67 4.5 (2.9–7.1) 310 16.5 (13.7–19.7) 1 466 79.0 (75.4–82.2)

Bachelor + 18 7.9 (4.3–14.1) 25 10.7 (4.9–21.7) 308 81.4 (68.4–89.9)

2010

None 49 2.5 (1.6–3.9) 314 16.0 (12.9–19.7) 1 698 81.5 (77.2–85.1)

Primary 111 3.2 (2.3–4.5) 775 21.1 (18.6–23.9) 2 993 75.6 (72.7–78.3)

Secondary 167 2.5 (1.7–3.6) 1 378 17.5 (15.2–20.0) 7 892 80.0 (77.4–82.4)

Cert/Dip 33 3.9 (2.0–7.3) 156 17.7 (13.5–22.8) 945 78.4 (72.9–83.1)

Bachelor + 9 5.4 (2.4–11.6) 21 16.4 (8.6–29.0) 212 78.2 (66.0–86.9)

2012

None 59 3.1 (2.1–4.5) 316 17.7 (14.8–20.9) 1 572 79.3 (76.0–82.2)

Primary 120 2.5 (1.9–3.3) 968 26.4 (23.7–29.3) 2 965 71.1 (68.2–73.8)

Secondary 200 2.3 (1.8–3.0) 1 621 19.1 (17.2–21.3) 8 677 78.5 (76.3–80.6)

Cert/Dip 67 4.5 (2.9–7.1) 310 16.5 (13.7–19.7) 1 466 79.0 (75.4–82.2)

Bachelor + 18 7.9 (4.3–14.1) 25 10.7 (4.9–21.7) 308 81.4 (68.4–89.9)

Estimated prevalence of smoking for those who have at least a Bachelor‟s degree and for

past smoking is affected by small sample size. For the years 2008 and 2012, those with

primary level education have the highest percentage of current smokers, which is significantly

higher than that for those with no education, secondary-level education, and certificate- or

diploma-level education, which have similar prevalences for all three study periods.


4.9.5.1 Discussion

A comparison between the 2012 NiDS and 2012 SANHANES shows that even if the

prevalence rates are not exact, they are similar in all aspects. It also shows that smoking

prevalence by the three demographic characteristics (gender, age and race) has dramatically

decreased between 1998 and 2012.

Table 81: Comparison of smoking prevalence (ever smoked) 1998 SADHS, 2012 SANHANES and 2012 NiDS by gender, age groups and race

Characteristic 1998 SADHS 2012 SANHANES 2012 NiDS

Females 24.4 10.1 9.8

Males 52.6 32.8 37.6

15–24 23.9 12.8 12.5

25–34 50.4 21.4 25.7

35–44 55.9 24.1 27.3

45–54 53.3 27.1 28.6

55–64 54.5 29.6 25.1

65+ 59.0 18.8 20.9

African 43.4 17.4 18.1

Coloured 58.9 44.9 48.1

Indian 54.3 25.2 21.3

White 55.4 24.5 35.4

The high-risk groups in terms of the three characteristics are male gender, Coloured and

White races, and the age groups 25 to 54 years, among which the prevalence of current daily

smoking is highest.

Table 82: Demographic and social factors associated with ever smoking

Characteristic

2008 2010 2012

Odds Ratio (OR)

Prob.* Odds Ratio

(OR) Prob.

*

Odds Ratio (OR)

Prob.*

Gender cf.: Female

Male 7.10 0.000 7.72 0.000 8.82 0.000

Age group cf.: 15-24 years

25-34 2.59 0.000 2.81 0.000 3.56 0.000

35-44 2.67 0.000 3.00 0.000 3.32 0.000

45-54 2.65 0.000 3.54 0.000 3.43 0.000

55-64 2.31 0.000 2.99 0.000 3.14 0.000

65+ 1.41 0.000 1.53 0.000 1.95 0.000

Race cf.: African

Coloured 6.86 0.000 6.40 0.000 6.24 0.000

Indian 1.51 0.017 2.03 0.000 1.52 0.034

White 5.30 0.000 3.93 0.000 4.60 0.000

Geographic type cf.:Traditional

Urban 1.80 0.000 1.61 0.000 1.70 0.000

Farms

1.79

0.000

1.67

0.000

1.50

0.000


Characteristic

2008 2010 2012

Odds Ratio (OR)

Prob.* Odds Ratio

(OR) Prob.

*

Odds Ratio (OR)

Prob.*


Primary 1.15 0.058 1.08 0.326 1.14 0.114

Secondary 0.67 0.000 0.72 0.000 0.63 0.000

Cert/Dip 0.47 0.000 0.49 0.000 0.46 0.000

Bachelor+ 0.32 0.000 0.20 0.000 0.17 0.000


All other factors being equal, it appears that the odds of ever being a smoker is similar for

those aged 24 to 64 years compared with those in the age group 15-24 years. The odds of

smoking for males are more than seven times the odds of smoking for females in the three

study periods, and the respective odds of smoking for Coloureds and Whites are at least six

and four times the odds of smoking for Africans. For those with at least secondary-level

education, the odds of smoking compared with those with no education decreases as the

level of education increases.

4.9.6 Systolic and diastolic BP by smoking status

Table 83: Systolic and diastolic BP by smoking status

Type of BP Ever Smoked 2008 2010 2012

Mean (95% CI)

Systolic

Past smoker 127.3 (123.9–130.6) 130.2 (126.6–133.7) 129.7 (123.9–135.5)

Current smoker 125.5 (124.2–126.7) 125.4 (123.8–127.1) 125.3 (124.0–126.6)

Never smoked 122.3 (121.5–123.1) 121.9 (121.3–122.6) 121.5 (120.8–122.1)

Diastolic

Past smoker 81.9 (79.9–83.8) 83.5 (80.9–86.1) 82.2 (79.5–84.8)

Current smoker 80.0 (79.1–80.9) 80.7 (79.6–81.8) 82.4 (81.5–83.2)

Never smoked 79.1 (78.5–79.7) 79.5 (79.1–80.0) 80.3 (79.8–80.8)

The mean of the two types of blood pressures for those who are past smokers is significantly

higher than that of those who have never smoked, except for diastolic BP in the 2012 wave of

the study. Current smokers also had mean systolic blood pressure that was significantly

higher than that of those who have never smoked, but the current smokers‟ mean diastolic

BP, although higher, was not significantly different from that of those who have never

smoked, except for the 2012 wave of the study.

4.9.7 Prevalence of blood pressure status by smoking status

Table 84: Distribution of blood pressure status by smoking status

Year Ever smoked

Blood pressure status

Normal Prehypertension Raised BP


2008

Past smoker 189 34.6 (28.8–40.8) 189 32.2 (26.8–38.2) 215 33.2 (26.7–40.4)

Current smoker

914 36.5 (33.4–39.7) 1 000 37.3 (34.2–40.5) 940 26.2 (23.8–28.8)

Never smoked 4 279 42.7 (40.6–44.7) 3 202 32.2 (30.6–33.8) 2 882 25.2 (23.6–26.9)

Total 5 382 41.0 (39.0–43.0) 4 391 33.2 (31.7–34.8) 4 037 25.8 (24.3–27.2)


Year Ever smoked

Blood pressure status

Normal Prehypertension Raised BP


2010

Past smoker 90 25.4 (17.8–34.9) 110 37.3 (25.7–50.5) 128 37.4 (28.1–47.6)

Current smoker

683 32.9 (29.1–36.8) 852 38.9 (35.2–42.6) 718 28.3 (24.9–31.9)

Never smoked 4 878 39.7 (38.0–41.4) 4 211 35.2 (33.5–36.9) 3 150 25.1 (23.7–26.5)

Total 5 651 38.1 (36.3–39.9) 5 173 35.9 (34.3–37.6) 3 996 26.0 (24.6–27.4)

2012

Past smoker 135 34.9 (28.1–42.4) 142 29.8 (23.3–37.2) 170 35.3 (27.1–44.4)

Current smoker

980 30.0 (26.7–33.5) 1 147 41.0 (36.5–45.6) 1 033 29.0 (25.9–32.3)

Never smoked 6 187 40.8 (39.0–42.7) 4 755 33.9 (32.4–35.4) 3 770 25.3 (23.8–26.9)

Total 7 302 38.5 (36.9–40.2) 6 044 35.2 (33.7–36.6) 4 973 26.3 (24.8–27.9)

The prevalence of raised BP is lowest in those who have never smoked and highest in those

who are past smokers, but there is no significant difference in the percentages of raised BP

between current smokers and those who have never smoked for the three study periods;

however, there appears to be a significant difference in the prevalence of raised BP between

those who have never smoked and past smokers. As shown on Table 76, the prevalence of

heavy smoking was higher in past smokers compared with current smokers.

4.10 Comparing hypertension prevalence by districts using multilevel analysis

In this section, prevalence of hypertension (raised BP or on hypertension medication) is

compared across the South African health districts. It is assumed that the districts differ in

many aspects relating to the distribution of the risk factors for hypertension. In this regard, it

may be possible that the districts show variation according to age, gender, race, alcohol use,

smoking status and the level of physical inactivity, among other factors. Therefore, instead of

comparing the crude prevalence rates of the districts, an adjustment based on the risk factors

is done before comparing the prevalence rates across the districts. In this multilevel analysis,

adjustment is done for the known risk factors, but also takes cognisance of other

unmeasured or unknown risk factors that are associated with the outcome of interest

(prevalence of hypertension). These unknown risk factors are group-specific (in this case

district-specific) and are considered to be random because, again, they differ from district to

district. In this type of analysis, there is estimation of each district‟s prevalence rate and the

overall prevalence rate for all the districts. The measure for the effect of the district on the

prevalence of hypertension is defined as the difference between the overall prevalence rate

and the district-specific prevalence rate. A district with an average prevalence rate is one in

which the difference is equal to zero. If the difference for a specific district is higher than zero,

the prevalence for that district is higher than average, and vice versa.


Table 85: Adjusted odds ratios for risk factors of hypertension

Characteristic 2008 2012

Odds Ratio (OR) Prob.*

Odds Ratio (OR) Prob.*

Gender cf.: Male

Female 0.91 (0.81, 1.01) 0.082 0.89 (0.81, 0.97) 0.009

Race cf.: African

Coloured 1.43 (1.20, 1.72) 0.000 1.48 (1.27, 1.72) 0.000

Indian 0.91 (0.60, 1.38) 0.665 1.27 (0.88, 1.85) 0.204

White 0.83 (0.64, 1.07) 0.154 0.65 (0.51, 0.83) 0.001

Age group cf.: 15-24 years

25-34 2.12 (1.80, 2.49) 0.000 2.08 (1.82, 2.37) 0.000

35-44 4.56 (3.85, 5.40) 0.000 3.86 (3.35, 4.44) 0.000

45-54 9.88 (8.24, 11.86) 0.000 8.46 (7.28, 9.84) 0.000

55-64 16.46 (13.43, 20.18) 0.000 17.04 (14.37, 20.20) 0.000

65+ 23.85 (19.09, 29.80) 0.000 24.69 (20.38, 29.92) 0.000

BMI level cf.: Normal

Underweight 0.83 (0.66, 1.04) 0.102 0.69 (0.55, 0.87) 0.002

Overweight 1.36 (1.21, 1.52) 0.000 1.45 (1.31, 1.59) 0.000

Obese 2.23 (1.99, 2.50) 0.000 2.58 (2.33, 2.85) 0.000

Smoking history cf.: Never smoked

Past 0.83 (0.39, 1.75) 0.619 1.62 (0.75, 3.49) 0.219

Current 0.81 (0.37, 1.75) 0.585 1.55 (0.69, 3.47) 0.290

Number of cigarettes smoked per day

cf.: None

<20 1.14 (0.53, 2.45) 0.740 0.60 (0.27, 1.34) 0.214

>20 0.87 (0.39, 1.91) 0.720 0.82 (0.36, 1.87) 0.636

Standard alcohol drinks taken cf.: None

<5 1.02 (0.89, 1.17) 0.768 1.25 (1.11, 1.41) 0.000

5+ 1.42 (1.21, 1.66) 0.000 1.47 (1.28, 1.69) 0.000

Physical inactivity cf.: 3+ times

<3 times per week 0.99 (0.86, 1.16) 0.937 1.12 (0.99, 1.27) 0.077


Urban 1.26 (1.1, 1.44) 0.001 1.04 (0.93, 1.17) 0.503

Farms 1.29 (1.09, 1.52) 0.003 0.99 (0.85, 1.16) 0.924

Household income 0.99 (0.99, 0.99) 0.044 0.99 (0.99, 0.99) 0.002

Employment category cf.: Not Economically Active

Unemployed Discouraged 0.98 (0.81, 1.18) 0.822 0.82 (0.64, 1.06) 0.123

Unemployed Strictly 0.84 (0.72, 0.98) 0.030 0.93 (0.82, 1.05) 0.224

Employed 0.88 (0.79, 0.99) 0.030 0.94 (0.85, 1.03) 0.187

Variance of random effects (district) 0.069 (0.046, 0.106) 0.074 (0.045, 0.122)

Likelihood Ratio test vs. logistic reg. 48.82 0.000 126.61 0.000



The single factor that was found to be strongly associated with hypertension was age, with

the odds of having hypertension being more than double from one age group to the next for

both the 2008 and the 2012 study periods. Body Mass Index was also strongly associated

with hypertension, with results from the 2012 wave showing that those who were obese were

58% more likely to be hypertensive compared with those who had normal BMI. There were

marginal gender effects in 2008, although in 2012, there were significant differences in the

odds of hypertension between females and males, with females being between 9% and 11%

less likely than males to develop hypertension. Other factors found to have an association

with hypertension were race, geographical type of dwelling (2008 only), employment status

(2008 only), alcohol use based on the number of standard alcohol drinks consumed, and

household income.

Risk factors that did not show any association with hypertension were physical exercise,

smoking history and the number of cigarettes smoked, marital status and education level.

The likelihood ratio (LR) of 48.82 and 126.61 for 2008 and 2012 multilevel models for testing

their difference with logistic regression show that a multilevel model is necessary. That is,

after adjusting for known and available risk factors for hypertension, there exist other

unmeasured/unaccounted factors between the districts that are associated with differences in

prevalence of hypertension between the districts. The level of variability, however, is minimal

given the size of the variance (0.069 and 0.074 for 2008 and 2012 respectively) for the

districts‟ random effects. This is also indicated by the caterpillar plots in Figure 26 and Figure

27, where it is seen that the 95% CI for the random effects of many districts overlap.

As shown in the two figures, eight districts in 2008 and 10 districts in 2012 had estimated

hypertension prevalences that were significantly lower than the overall (national) prevalence,

while eight and 10 districts had estimated prevalences that were significantly higher than the

overall prevalence for 2008 and 2012 respectively. In other words, those districts in which

hypertension prevalences minus the overall prevalence were below zero had lower-than-

average prevalences, while those districts in which difference in prevalences between the

specific district prevalence and the overall prevalence was above zero had hypertension

prevalences that were above average.


Figure 26: Random effects for districts: 2008

DC22

DC43DC21

DC12

DC10

DC25

ETH

DC48

DC14

DC13

DC26

DC27

DC15

DC1

MAN

DC23

NMA

DC5DC24

DC9

DC35

BUF

TSH

DC33

DC45

DC30

DC31

DC20

DC36

CPT

DC28

DC18

DC47

DC34

EKU

DC38

DC19

DC7

DC2

DC39

DC40

DC3

DC44

JHB

DC4

DC32

DC16

DC6

DC8

DC42

DC29

DC37

-1.3 -.65

0

.651.3

Random effects for districts: 2008

0

2

4

6

8

10

12

14

16

18

20

22

24

26

28

30

32

34

36

38

40

42

44

46

48

50

52

Po

sitio

n o

f d

istr

ict


Figure 27: Random effects for districts: 2012

Most of the districts (about 30) had prevalences of hypertension that did not differ

significantly from the overall (national) prevalence since their 95% CI crossed the zero line. In

2008, it can be seen that all the districts in Limpopo had lower prevalence of hypertension

than average, while in 2012, four of the five districts in the same province showed similar

results. Two districts (Overberg and Central Karoo) in the Western Cape had above-average

prevalence of hypertension in 2008 as well as in 2012. RS Mompati in North West Province

appeared to have an above-average prevalence rate of hypertension in both 2008 and 2012,

while OR Tambo in the Eastern Cape is the only district that showed prevalence below

average in 2008, but an above-average prevalence in 2012.

DC47DC30DC36DC35

DC8DC34DC32DC6DC25DC43DC26DC44DC33DC29DC40DC14CPTDC31TSHDC12JHBDC42DC37DC7DC27EKUDC23MANDC19DC9DC48DC24DC22DC45DC4DC28DC2DC1DC18DC13BUFDC20

ETHDC3DC16NMADC10DC38DC21DC15

DC39DC5

-1.3 -.65

0

.651.3

Random effects for districts: 2012

0

2

4

6

8

10

12

14

16

18

20

22

24

26

28

30

32

34

36

38

40

42

44

46

48

50

52

Po

sitio

n o

f d

istr

ict


Table 86: District with below and above average prevalence of hypertension in 2008 and 2012

Position

Below average (low prevalence) Above average (high prevalence) 2012

2008 2012 2008 2012

1 DC47 (Sekhukhune): LP

DC47 (Sekhukhune): LP

DC7(Pixley ka Seme): NC

DC5 (Central Karoo): WC

2 DC44 (A Nzo): EC DC30 (Gert Sibande): MP

DC12 (Amathole): EC

DC39 (RS Mompati): NW

3 DC34 (Vhembe): LP DC36 (Waterberg): LP DC1 (West Coast): WC

DC15 (OR Tambo): EC

4 DC36 (Waterberg): LP

DC35 (Capricorn): LP DC40 (Dr. K Kaunda): NW

DC21 (Ugu): KZN

5 DC33 (Mopani): LP DC8 (ZF Mgcawu): NC DC24 (uMzinyathi): KZN

DC38 (NM Molema): NW

6 DC15 (OR Tambo): EC

DC34 (Vhembe): LP DC5 (Central Karoo): WC

DC10 (Cacadu): EC

7 DC35 (Capricorn): LP DC32 (Ehlanzeni): MP DC45 (JT Gaetsewe): NC

NMA (N Mandela Bay): EC

8 DC42 (Sedibeng): GP

DC6 (Namakwa): NC DC3 (Overberg): WC

DC16 (Xhariep): FS

9 DC25 (Amajuba): KZN DC16* (Xhariep): FS

DC3 (Overberg): WC

10 DC43 (Harry Gwala): KZN

DC39* (RS

Mompati): NW ETH (eThekwini): KZN

*almost above zero line

4.11 Other Non-communicable diseases

Self-reported prevalence of other non-communicable diseases, namely diabetes, asthma,

stroke, heart diseases and cancer, are reported. Many of the estimates for the prevalence of

these non-communicable diseases are unreliable as can be seen from the wide confidence

intervals, which is a result of the relatively small sample sizes occasioned by further

disaggregation.

4.11.1 Diabetes

4.11.1.1 Prevalence of diabetes by gender

Between 2008 and 2012, the self-reported prevalence of diabetes increased for both males

and females, but females were more likely to self-report diagnosis compared with males.


Table 87: Comparing diabetes self-reported prevalence by gender: NiDS and GHS

Year Gender

Diagnoses with diabetes

NiDS GHS


2008

Female 432 4.4 (3.7–5.1)

Male 175 2.5 (1.9–3.1)

Total 607 3.5 (3.1–4.0)

2010

Female 452 4.1 (3.4–4.9) 1 559 3.9 (3.7–4.2)

Male 202 2.9 (2.3–3.6) 870 2.7 (2.4–2.9)

Total 654 3.5 (3.1–4.1) 2 429 3.3 (3.1–3.5)

2012

Female 630 5.4 (4.7–6.2) 1 782 4.5 (4.3–4.8)

Male 230 3.6 (2.7–4.8) 1 014 3.3 (3.0–3.7)

Total 860 4.6 (4.0–5.2) 2 796 3.9 (3.7–4.2)

Estimates from the GHS tend to be lower than those of the NiDS. The respective sample

sizes used are higher in the GHS than in the NiDS. In no combination of gender and survey

year do the estimates from the NiDS and the GHS overlap. The self-reported estimates and

95% CI from the 2012 SANHANES were 6.0 (5.2–7.4) and 4.0 (3.3–4.8) for females and

males respectively, which were similar to those of the 2012 NiDS. The self-reported

prevalences for diagnosis with diabetes according to the 1998 SADHS were 0.92% and

0.65% for females and males respectively, which shows that self-reporting for diabetes has

increased over the years.

Figure 28: Self-reported prevalence of diagnosis with diabetes by gender: GHS

2.5

3.0

3.5

4.0

4.5

2009 2010 2011 2012 2013

Year

Female Male All

Self-reported prevalence of diagnosis with diabetes by gender


4.11.1.2 Prevalence of diabetes (NiDS and GHS) by age group

Table 88: Self-reported prevalence (%) and 95% CI of diabetes by age group: NiDS and GHS

Year

Age group

Diagnoses with diabetes

NiDS GHS


2010

15-24 15 0.3 (0.1–0.6) 42 0.2 (0.1–0.3)

25-34 19 1.1 (0.5–2.6) 60 0.4 (0.3–0.6)

35-44 64 2.6 (1.7–3.8) 229 2.0 (1.7–2.4)

45-54 153 5.1 (4.0–6.5) 608 6.2 (5.6–6.8)

55-64 208 12.4 (10.0–15.3) 697 11.3 (10.4–12.4)

65+ 195 13.3 (10.3–17.1) 793 14.6 (13.3–16.0)

Total 654 3.5 (3.1–4.1) 2 429 3.3 (3.1–3.5)

2012

15-24 16 0.2 (0.1–0.4) 49 0.4 (0.2–0.9)

25-34 28 0.8 (0.4–1.6) 78 0.8 (0.5–1.3)

35-44 83 4.2 (2.4–7.2) 269 2.4 (2.1–2.8)

45-54 217 7.9 (6.3–9.8) 639 6.9 (6.3–7.6)

55-64 266 14.9 (12.5–17.7) 889 13.3 (12.3–14.4)

65+ 250 15.4 (12.3–19.1) 872 15.7 (14.5–16.9)

Total 860 4.6 (4.0–5.2) 2 796 3.9 (3.7–4.2)

For the study periods shown, only the estimates for the three older age groups (45-54

upwards) for the NiDS and the last four age groups in the the GHS may be reliable, since for

the other younger age groups, sample sizes are relatively small. Self-reporting for diagnosis

with diabetes is significantly higher for the 55-64 and the 65 years or older age groups

compared with the 45-54 years age group.

As for the blood pressure estimates, the sample sizes in the GHS are substantially higher

than those in the NiDS, especially for the four older age groups. The estimates for the older

three age groups are also similar in the two studies, although in all instances, those from the

NiDS are slightly higher than those from the GHS.


Table 89: Self-reported prevalence of diagnosis with diabetes by gender and age groups: 2012 SANHANES

Age group Females Males

N Prevalence N Prevalence

15–24 2 334 1.0 (0.5–1.8) 1 992 0.3 (0.1–0.7)

25–34 1 761 1.4 (0.9–2.2) 1 273 0.8 (0.4–1.8)

35–44 1 543 3.2 (2.3–4.6) 975 2.5 (1.5–4.2)

45–54 1 394 12.0 (9.2–15.3) 910 9.8 (6.9–13.8)

55–64 1 026 19.0 (13.8–25.4) 721 12.7 (9.6–16.5)

65+ 940 17.1 (13.5–21.3) 479 15.7 (10.9–22.0)

Total 8 998 6.0 (5.2–7.0) 6 350 4.0 (3.3–4.8)

N is overall sample size rather than number in the sample with diabetes

The 2012 SANHANES estimates for self-reported diagnosis with diabetes, although further

disaggregated by gender, show that they could be slightly higher but comparable to those of

the NiDS and the GHS, especially for those aged 45 years and older.

Figure 29: Self-reported prevalence of diabetes by age group: GHS

Prevalence between the youngest two age groups is almost the same for five years of the

GHS. The gap between the prevalence in the oldest three age groups is more pronounced

than that in the youngest three age groups. There is not much difference in the self-reported

prevalence of diabetes between the survey years for each gender and overall.

0

5

10

15

2009 2010 2011 2012 2013

Year

15-24 25-34 35-44 45-54 55-64 65+ All

Self-reported prevalence of diabetes by age group


4.11.2 Stroke

Table 90: Self-reported prevalence (%) and 95% CI of stroke

Year Diagnosis with stroke

n Prevalence (95% CI)

2008: NiDS 156 0.9 (0.6–1.2)

2010: NiDS 144 0.7 (0.5–0.9)

2012: NiDS 205 0.8 (0.7–1.1)

2013: GHS 385 0.4 (0.3– 0.5)

Prevalence for self-reporting diagnosis with stroke is very low (<1%) for all three study

periods in the NiDS. The overall estimate for prevalence of stroke in the GHS 2013 is

significantly lower than those from any wave in the NiDS. The estimated prevalences from

the 2012 SANHANES were 1.9% for females and 1.7% for males, and therefore on average

higher than that estimated from either the NiDS or the GHS. In the 1998 SADHS, the

prevalences were 234/100 000 (0.234%) and 135/100 000 (0.135%) for females and males

respectively.

4.11.3 Asthma

4.11.3.1 Prevalence of asthma by gender (NiDS and GHS)

Table 91: Self-reported prevalence (%) and 95% CI of asthma by gender

Year Gender

Diagnosis with asthma

NiDS GHS


2008

Female 371 4.0 (3.4–4.8)

Male 190 2.8 (2.3–3.5)

Total 561 3.5 (3.0–4.1)

2010

Female 328 3.9 (2.9–5.3) 1 107 2.9 (2.7–3.1)

Male 180 2.9 (2.0–4.1) 624 2.0 (1.8–2.2)

Total 508 3.4 (2.5–4.6) 1 731 2.4 (2.3–2.6)

2012

Female 457 5.2 (4.2–6.4) 1 141 3.4 (3.1–3.7)

Male 194 2.5 (1.9–3.3) 641 2.3 (2.0–2.7)

Total 651 4.0 (3.2–4.9) 1 782 2.9 (2.6–3.2)

Self-reporting for asthma is slightly lower for males than for females and is significantly so in

the 2012 study year for the NiDS results and for both the 2010 and 2012 GHS results. There

was also a slight increase in self-reporting for both genders between the 2010 and 2012

study years, as shown by results from the GHS. In the 1998 SADHS, the self-reported

prevalences were 580/100 000 (0.58%) and 638/100 000 (0.638%) for females and males

respectively.


Figure 30: Self-reported prevalence of diagnosis with asthma by gender: GHS

The GHS data for the years 2009 to 2013 show that females are slightly more likely to self-

report diagnosis with asthma compared with males.

4.11.3.2 Prevalence of asthma (NiDS and GHS) by age group

The estimates from the NiDS are higher than those from the GHS, although for all age

groups – except in the 15-24 age groups in 2010 – the confidence intervals overlap. The

1998 SADHS shows that on average, the prevalence of self-reporting diagnosis with asthma

was higher among males than among females, but it is also evident that self-reporting for

diagnosis with asthma increased between 1998 and 2012.

2.5

3.5

3.0

2.0

2009 2010 2011 2012 2013

Year

Female Male All

Self-reported prevalence of diagnosis with asthma by gender


Table 92: Self-reported prevalence of asthma by age group

Year Age group

Diagnoses with asthma

NiDS GHS


2008

15-24 113 2.8 (2.1–3.6)

25-34 64 2.2 (1.6–3.2)

35-44 100 3.6 (2.7–4.8)

45-54 121 5.4 (4.1–7.0)

55-64 94 5.5 (4.0–7.7)

65+ 66 4.7 (2.9–7.3)

Total 558 3.5 (3.0–4.0)

2010

15-24 92 2.5 (1.6–3.9) 269 1.3 (1.1– 1.5)

25-34 70 2.9 (1.7–4.7) 233 1.6 (1.4– 1.9)

35-44 67 2.0 (1.4–3.0) 277 2.3 (2.0– 2.6)

45-54 115 5.1 (3.7–7.1) 357 3.7 (3.2– 4.2)

55-64 86 6.0 (4.1–8.6) 293 4.5 (3.9– 5.2)

65+ 78 6.6 (2.3–17.1) 302 5.3 (4.6– 6.1)

Total 508 3.4 (2.5–4.6) 1731 2.4 (2.3– 2.6)

2012

15-24 135 3.3 (2.2–4.9) 317 2.0 (1.7– 2.5)

25-34 87 2.8 (2.0–3.9) 285 2.3 (1.8– 2.8)

35-44 87 3.4 (2.3–5.1) 242 2.3 (2.0– 2.7)

45-54 126 5.6 (4.2–7.5) 352 4.3 (3.7– 5.0)

55-64 118 6.1 (4.6–7.9) 300 4.4 (3.9– 5.1)

65+ 98 6.3 (3.8–10.1) 286 4.8 (4.2– 5.6)

Total 651 4.0 (3.2–4.9) 1782 2.9 (2.6– 3.2)

Table 93: Self-reported prevalence for asthma by age group and gender as reported in 1998 SADHS

1998 SADHS*

Age group Females Male

15-24 0.24 0.37

25-34 0.53 0.42

35-44 0.32 0.35

45-54 1.09 1.35

55-64 1.03 0.92

65+ 0.82 1.37

Total 0.58 0.64

* Values converted from per 100 000 to per 100


Figure 31: Self-reported prevalence of diagnosis with asthma by age group: GHS

As for the other NCDs, the prevalence of asthma in the three younger age groups is lower

than in the older three age groups. In the year 2011, those in the age group 55-64 years had

the highest self-reported prevalence of asthma. The self-reported prevalence for those aged

65 years and older seems to be decreasing by the year.

4.11.4 Cancer

Data on self-reported diagnosis with cancer for the GHS were available from 2009 onwards.

4.11.4.1 Prevalence of cancer by gender

Table 94: Self-reported prevalence of cancer by gender: NiDS and GHS

Year Gender NiDS GHS


2008

Female 24 0.92 (0.63–1.35)

Male 68 0.46 (0.23–0.92)

Total 92 0.72 (0.49–1.05)

2010

Female 56 0.99 (0.61–1.62) 205 0.63 (0.50–0.79)

Male 19 0.32 (0.17–0.59) 118 0.41 (0.31–0.52)

Total 75 0.68 (0.46–1.02) 323 0.52 (0.44–0.62)

2012

Female 77 0.77 (0.53–1.11) 178 0.65 (0.48–0.88)

Male 26 0.41 (0.24–0.70) 98 0.51 (0.27–0.94)

Total 103 0.61 (0.45–0.82) 276 0.58 (0.40–0.85)

The self-reporting for cancer by gender is highest among females than among males and

overall, it decreased slightly between 2008 and 2012.

1

2

3

4

5

6

Pre

va

lence

(%

)

2009 2010 2011 2012 2013

Year

15-24 25-34 35-44 45-54 55-64 65+ All

Self-reported prevalence of diagnosis with asthma by age group

Pre

va

lence

(%

)


Figure 32: Self-reported prevalence of diagnosis with cancer by gender: GHS

4.11.4.2 Prevalence of cancer (NiDS and GHS) by age group

Table 95: Self-reported prevalence (%) and 95% CI of cancer by age group

Year Age group NiDS GHS


2008

15-24 4 0.04 (0.01–0.13)

25-34 6 0.20 (0.06–0.59)

35-44 19 0.84 (0.45–1.57)

45-54 25 1.62 (0.82–3.16)

55-64 17 0.99 (0.50–1.95)

65+ 21 2.95 (1.60–5.38)

Total 92 0.72 (0.49–1.05)

2010

15-24 3 0.01 (0.00–0.05) 19 0.11 (0.07–0.19)

25-34 5 0.32 (0.08–1.28) 23 0.19 (0.12–0.31)

35-44 14 0.57 (0.25–1.29) 38 0.27 (0.19–0.40)

45-54 13 0.78 (0.34–1.80) 86 1.02 (0.75–1.40)

55-64 16 1.49 (0.60–3.66) 58 1.27 (0.84–1.91)

65+ 24 3.67 (1.99–6.67) 99 2.16 (1.65–2.84)

Total 75 0.68 (0.46–1.02) 323 0.52 (0.44–0.62)

2012

15-24 6 0.10 (0.03–0.29) 19 0.26 (0.07–0.91)

25-34 5 0.16 (0.06–0.47) 35 0.46 (0.19–1.14)

35-44 10 0.48 (0.19–1.23) 32 0.42 (0.25–0.72)

45-54 31 1.25 (0.72–2.17) 55 0.73 (0.50–1.05)

55-64 22 1.17 (0.66–2.06) 59 1.13 (0.74–1.70)

65+ 29 2.39 (1.33–4.26) 76 1.72 (1.29–2.30)

Total 103 0.61 (0.45–0.82) 276 0.58 (0.40–0.85)

.70

.30

.40

.50

.60

Pre

va

lence

(%

)

2009 2010 2011 2012 2013

Year

Female Male All

Self-reported prevalence of diagnosis with cancer by gender

Pre

va

lence

(%

)


Overall, self-reported diagnosis with cancer is very low (less than 1%), but increases with age

for each year and survey. The respective prevalences by age are slightly lower in the GHS

compared with those of the NiDS.

Figure 33: Self-reported prevalence of diagnosis with cancer by age group: GHS

The self-reported prevalence of cancer increases distinctly with age.

Table 96: Self-reported diagnosis with cancer as reported in 1998 SADHS

1998 SADHS: cancer

Age group Females Male

15-24 0.00 0.04

25-34 0.00 0.12

35-44 0.18 0.00

45-54 0.28 0.38

55-64 0.10 0.00

65+ 0.41 0.95

Total 0.13 0.17

0

.5

1

1.5

2

2009 2010 2011 2012 2013

Year

15-24 25-34 35-44 45-54 55-64 65+ All

Self-reported prevalence of diagnosis with cancer by age group


4.11.5 Heart problems: NiDS

Table 97: Self-reported prevalence of heart problems by gender

Year Gender Diagnosis with heart problems

n Prevalence

2008

Female 350 3.7 (3.2–4.2)

Male 140 2.2 (1.6–2.9)

Total 490 3.0 (2.6–3.5)

2010

Female 252 2.3 (1.9–3.0)

Male 73 1.2 (0.8–1.9)

Total 325 1.8 (1.5–2.3)

2012

Female 364 2.8 (2.3–3.3)

Male 137 2.4 (1.7–3.3)

Total 501 2.6 (2.1–3.1)

There is a higher prevalence of females self-reporting heart problems than males for all three

study periods. The difference in self-reported diagnosis with a heart problem between

females and males was smallest in the 2012 study year.

Table 98: Prevalence of self-reported diagnosis with heart problem/disease in 1998 SADHS and 2012 SANHANES

Age group

1998 SADHS 2012 SANHANES

Females Males Females Males

15-24 0.50 0.25 0.3 0.2

25-34 1.87 0.70 1.4 0.8

35-44 1.61 1.49 3.0 1.2

45-54 2.45 0.74 3.5 1.9

55-64 2.69 1.65 9.5 6.1

65+ 2.81 0.79 6.4 4.4

Total 1.74 0.80 2.9 1.5


Table 99: Self-reported prevalence of heart problems by age group

Year Age group

Diagnosis with heart problem

Yes

n Prevalence (95% CI)

2008

15-24 44 1.3 (0.8–2.0)

25-34 40 1.5 (1.0–2.3)

35-44 62 2.1 (1.5–3.0)

45-54 111 4.9 (3.7–6.3)

55-64 115 7.6 (5.8–9.8)

65+ 117 8.3 (5.9–11.5)

Total 489 3.0 (2.6–3.5)

2010

15-24 17 0.3 (0.2–0.6)

25-34 16 0.8 (0.4–1.5)

35-44 38 0.9 (0.5–1.5)

45-54 71 2.6 (1.8–3.7)

55-64 80 5.9 (3.8–8.9)

65+ 103 7.6 (5.3–10.7)

Total 325 1.8 (1.5–2.3)

2012

15-24 33 0.6 (0.3–1.0)

25-34 36 0.8 (0.5–1.3)

35-44 61 2.5 (1.5–4.3)

45-54 112 4.0 (2.8–5.5)

55-64 115 6.2 (4.4–8.6)

65+ 144 9.0 (6.6–12.2)

Total 501 2.6 (2.1–3.1)

The self-reported diagnosis with a heart problem increases with age for the three study

periods, and is lowest in 2010 for nearly all the respective age groups.


Figure 34: Prevalence of self-reported NCDs by gender: NiDS

Self-reported prevalence of each NCD is in most instances higher among females than

among males.

Figure 35: Prevalence of self-reported NCDs by age group: NiDS

17.8

8.2

4.4

2.5

4.0

2.8

3.7

2.2

0.9

0.9

0.9

0.5

15.0

7.0

4.1

2.9

3.9

2.9

2.3

1.2

0.9

0.4

1.0

0.3

20.7

10.7

5.4

3.6

5.2

2.5

2.8

2.4

1.1

0.5

0.8

0.4

0 5 101520 0 5 101520 0 5 101520

Hypertension

Diabetes

Asthma

Heart problem

Stroke

Cancer

Hypertension

Diabetes

Asthma

Heart problem

Stroke

Cancer

Hypertension

Diabetes

Asthma

Heart problem

Stroke

Cancer

2008 2010 2012

Male Female

No

n-c

om

mu

nic

able

dis

ease

(N

CD

)

Prevalence (%)

Prevalence of self-reported NCDs by gender: NiDS

13.641.3

36.825.7

13.94.5

1.5

3.510.012.0

6.02.41.60.63.54.75.55.43.62.22.8

3.08.37.64.92.11.51.3

11.342.2

31.320.5

8.84.0

0.9

3.513.312.4

5.12.61.10.33.46.66.05.1

2.02.92.5

1.87.65.9

2.60.90.80.3

16.153.7

45.328.2

13.95.5

1.0

4.615.414.9

7.94.2

0.80.24.06.36.15.63.42.83.3

2.69.06.24.02.50.80.6

0 20 40 60 0 20 40 60 0 20 40 60

Hypertension

Diabetes

Asthma

Heart problems

Hypertension

Diabetes

Asthma

Heart problems

Hypertension

Diabetes

Asthma

Heart problems

2008 2010 2012

15-24 25-34 35-44 45-54 55-64 65+ All

No

n-c

om

mu

nic

able

dis

ease

(N

CD

)

Prevalence (%)

Prevalence of self-reported NCDs by age group: NiDS

Non-c

om

mun

icab

le d

isease (

NC

D)

Non-c

om

mun

icab

le d

isease (

NC

D)


For the four NCDs (hypertension, heart problems, asthma and diabetes), the prevalence

among those in the age group 45-54 years and older is more than the average for all the age

groups, for all the three study years. For heart problems, diabetes and hypertension, the

prevalence of self-reported diagnosis increases with age.

4.11.6 Discussion: Self-reported prevalence of certain NCDs

The estimated self-reported prevalences of NCDs found in the NiDS tend to be higher than

those of the GHS and are broadly comparable with the SANHANES results. As can be seen

from the results for hypertension, where measured prevalence is available from the same

survey, self-reports of NCDs are much lower than actual disease prevalence and the gap

differs according to gender and age category. Self-reported prevalence should thus be

interpreted with caution and in future, alternative methods such as symptomatic diagnosis

should be considered.43

5. Concluding remarks

The self-reported prevalence of hypertension estimated from both the NiDS and the GHS

shows that it is higher in females than in males and also increases with age. This is

consistent with what was found in the 1998 SADHS, as well as in the 2012 SANHANES,

where the prevalence for females was more than double that of males. This is contrary to

actual hypertension (systolic ≥140/diastolic≥90 or on medication for hypertension) where

although the prevalence is still higher in females than in males, the differences in

prevalences between the genders is not as marked as with self-reported hypertension. It has

been reported elsewhere44 that health-seeking behaviour is higher among females and this

explains why the difference in females‟ and males‟ self-reported hypertension is relatively

higher than that of the measured hypertension. This finding is useful because it confirms a

gender bias in using self-reported disease status for planning health intervention

programmes.

The NiDS data did not show much difference in the estimated prevalences of hypertension

and raised blood pressure as well as in the mean systolic and diastolic BPs between the

NiDS study years. However, when compared with the 1998 SADHS, the estimated metrics

have all increased between 1998 and 2008. Nonetheless, it may be difficult to infer that the

prevalences and the means have reached a plateau.

Statistical modelling showed that the factors that were strongly associated with hypertension

were age, BMI, race, alcohol use and gender. Physical inactivity and smoking were not found

to be associated with hypertension. However, this does not imply they are not risk factors for

hypertension, but should be seen as confounding risk factors since they are strongly

associated with gender, race and BMI, which in turn are strongly associated with

hypertension.

The analysis of hypertension by district showed that although the prevalences of many

districts did not differ significantly from each other after jointly adjusting for known risk factors,

some districts had lower and others had higher prevalences than the overall (national)

average. Specifically, in 2008 all five districts in Limpopo and in 2012 four of the districts in

the same province had prevalences that were significantly lower than the overall prevalence.

Two districts (Overberg and Central Karoo) in the Western Cape and RS Mompati in North

West Province had prevalences that were higher than the overall national prevalence for the

two study periods. It would therefore be of interest to investigate whether there is a particular


factor that can be associated with relatively lower hypertension in Limpopo, and with the

relatively higher than expected prevalence in Central Karoo and Overberg districts in the

Western Cape as well as RS Mompati in North West.

It appears, therefore, that the priority target population groups for reducing elevated blood

pressures are those aged 35 years and older, females, Coloureds and farm dwellers as well

as those with no education or primary-level education. Some districts may also require

prioritisation for intervention.

Mean BMIs and prevalences of obesity increased slightly between 2008 and 2012 for both

genders, and for each race, Africans followed by Coloureds had the widest gap in mean BMI

and prevalence of obesity by gender. There were no statistically significant differences in the

mean BMI and the prevalence of obesity by gender in Whites. The need for intervention to

reduce obesity in Whites is therefore the same for both genders, but in Africans and

Coloureds, females should be the target group. Urban dwellers may have a greater need to

reduce obesity compared with dwellers in traditional settings. In terms of other risk factors for

NCDs, the need to increase physical activity is highest in females and Africans, while males

should be the main target group for reducing alcohol use and smoking.

The self-reported prevalences of NCDs showed that hypertension is the leading condition

followed by diabetes. Self-reporting of cancer and heart problems was unrealistically low. It is

suspected that the low prevalence of cancer self-reporting may arise from specialised

diagnostics being required, unlike blood pressure or diabetes testing that is routinely done by

clinicians and nurses who encounter most of those seeking healthcare. When compared with

results from the 1998 SADHS, both the NiDS and the GHS showed that prevalences of self-

reporting have increased, and this may imply that there has been improvement in the

accessibility of health services or that the population‟s health-seeking behaviour has

improved over the years, in addition to increasing actual disease prevalence. Nevertheless,

the pattern of self-reporting is still higher in females than in males as found in the 1998

SADHS. Intervention efforts must therefore target males to improve their health-seeking

behaviour.


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