PREVALENCE OF PHYSICAL INACTIVITY

FACTORS ASSOCIATED WITH PHYSICAL INACTIVITY AMONG FIRST YEAR UNDERGRADUATE STUDENTS OF

UNIVERSITI PUTRA MALAYSIA

GOJE MOHAMMEDGS34396

FACULTY OF MEDICINE AND HEALTH SCIENCES1

• INTRODUCTION• LITERATURE REVIEW• METHODOLOGY• RESULTS• DISCUSSION• CONCLUSIONS AND RECOMMENDATIONS• REFERENCES

• INTRODUCTION• LITERATURE REVIEW• METHODOLOGY• RESULTS• DISCUSSION• CONCLUSIONS AND RECOMMENDATIONS• REFERENCES

OUTLINE

2FACTORS ASSOCIATED WITH PHYSICAL INACTIVITY AMONG FIRST YEAR UNDERGRADUATE STUDENTS OF UPM

Physical activity is any bodily movement produced by skeletal muscles that requires energy expenditure (WHO 2014).

Physical inactivity

causes about 1.9 million preventable deaths per annum (WHO, 2002).

Increases the risk of all-cause mortality by 20-30% (Vuori, 2004).

Globally 31.1% (95% CI 30.9-31.2) of adults aged 15 and above were considered insufficiently active (WHO GHO, 2013)

Physical activity is any bodily movement produced by skeletal muscles that requires energy expenditure (WHO 2014).

Physical inactivity

causes about 1.9 million preventable deaths per annum (WHO, 2002).

Increases the risk of all-cause mortality by 20-30% (Vuori, 2004).

Globally 31.1% (95% CI 30.9-31.2) of adults aged 15 and above were considered insufficiently active (WHO GHO, 2013)

BACKGROUND


Prevalence of physical inactivity in Malaysia

Study Year Age group Prevalence NHMS II 1996 >18 YEARS 88.4%

MANS 2003 > 18 YEARS 85.6%

MyNCDs1 2005 25-64 Years 60.1%

NHMS III 2006 > 18 Years 43.7%


Studies indicating lack of sufficient physical activity in university population• 50% of university students from US and Canada are not sufficiently

active (Irwin, 2004)• 50-60% of University students from Europe also shown to be

insufficiently active (Steptoe et al., 1997; Stock, Wille and Kramer 2001)

• Only 48% of New Zealand University students made the new Zealand country guidelines of physical activity compared to (70%) of their age group in the general population (Sports an recreation, New Zealand 2003)

• 39% of Australian University Students also classified as insufficiently active (Leslie et al., 1999)

• No data on trends of physical inactivity among university students or there age group 18-25 in the general population.

Studies indicating lack of sufficient physical activity in university population• 50% of university students from US and Canada are not sufficiently

active (Irwin, 2004)• 50-60% of University students from Europe also shown to be

insufficiently active (Steptoe et al., 1997; Stock, Wille and Kramer 2001)

• Only 48% of New Zealand University students made the new Zealand country guidelines of physical activity compared to (70%) of their age group in the general population (Sports an recreation, New Zealand 2003)

• 39% of Australian University Students also classified as insufficiently active (Leslie et al., 1999)

• No data on trends of physical inactivity among university students or there age group 18-25 in the general population.

Problem Statements


Significant decline was shown between time spent doing Vigorous physical activity in high school (323.9+168.2) and University (206.2+192.2) P<0.001 and

time spend doing moderate physical activity in high school (197.8+188.0) and University (133.5+124.3) (Kim, Mike and Daniel Steel, 2001)

Strong evidence showed that physical activity alleviates mental health problems, in this study mental health problem as possible predictor of physical inactivity was studied.

Demographic , behavioural and environmental factors are studied to be associated with physical inactivity among college students (Waxman,2004; US DHHS 2010; Ismail, Chee, Nawaswi, Yusoff, Lim and James 2002; Lindner, 1999; Wang, Yang, Chen, Davis, Schwartz, and Tam 2004; Miller, Staten, Rayens and Noland 2005)

Significant decline was shown between time spent doing Vigorous physical activity in high school (323.9+168.2) and University (206.2+192.2) P<0.001 and

time spend doing moderate physical activity in high school (197.8+188.0) and University (133.5+124.3) (Kim, Mike and Daniel Steel, 2001)

Strong evidence showed that physical activity alleviates mental health problems, in this study mental health problem as possible predictor of physical inactivity was studied.

Demographic , behavioural and environmental factors are studied to be associated with physical inactivity among college students (Waxman,2004; US DHHS 2010; Ismail, Chee, Nawaswi, Yusoff, Lim and James 2002; Lindner, 1999; Wang, Yang, Chen, Davis, Schwartz, and Tam 2004; Miller, Staten, Rayens and Noland 2005)

Problem Statements

7FACTORS ASSOCIATED WITH PHYSICAL INACTIVITY AMONG UNDERGRADUATE STUDENTS OF UPM 7

To add value to the body of knowledge on physical activity

Findings may help to identify factors that can leads to physically inactivity and this will help them to be physically active throughout life.

To develop a healthy nation, a baseline data for health awareness and health promotion activities in the university.

To identify the modifiable risk factors of physical inactivity for intervention.

To add value to the body of knowledge on physical activity

Findings may help to identify factors that can leads to physically inactivity and this will help them to be physically active throughout life.

To develop a healthy nation, a baseline data for health awareness and health promotion activities in the university.

To identify the modifiable risk factors of physical inactivity for intervention.

Justification of Study


General Objectives


To determine the characteristics of respondents by their • Socio-demography• Environmental support• Physical activity readiness and medical history • Mental health status• Self-efficacy of physical activity• Body image perception/dissatisfaction

To determine the characteristics of respondents by their • Socio-demography• Environmental support• Physical activity readiness and medical history • Mental health status• Self-efficacy of physical activity• Body image perception/dissatisfaction

Specific Objectives

To determine the prevalence of physical inactivity and its associated factors among first year undergraduate students of the University Putra Malaysia.

To determine the prevalence of physical inactivity and its associated factors among first year undergraduate students of the University Putra Malaysia.

To determine the association between physical inactivity and..

• socio-demographic factors• environmental support• mental health status• self-efficacy of physical activity• body image perception/dissatisfaction

To determine the association between physical inactivity and..

• socio-demographic factors• environmental support• mental health status• self-efficacy of physical activity• body image perception/dissatisfaction

Specific Objectives…..


Alternative hypothesis


There is a significant association between physical inactivity among first year UPM students and……

• Socio-demographic factors (age, gender, family income and ethnicity)

• Environmental support (availability of recreational areas, playground, cycling track and side walk)

• Mental health status • Self-efficacy of physical activity • Body image perception and dissatisfaction

There is a significant association between physical inactivity among first year UPM students and……



• Mental health status • Self-efficacy of physical activity • Body image perception and dissatisfaction

Literature Review





• Mental health status • Mental health status

• Self-efficacy of physical activity • Self-efficacy of physical activity

• Body image perception and dissatisfaction • Body image perception and dissatisfaction


• Factors associated with Physical Inactivity

Socio-demographyVariable

Author Description Findings

Gender Kjelsas and Augestad, 2004

Cross-sectional, Undergrad,18-40years in Norway

Gender was shown to predict weekly hours of physical activity. Gender: Std. β=0.09, t=-2.19 P<0.05

Gender NYRB,1991 Cross-sectional, students

50% of males met the criterion for moderate to vigorous physical activity.Only 17% of the women met the criterion Participation is higher in males than females P<0.01


Socio-demographyVariable


Gender Vilhjalmsson and Thorlindsson, 1998

Cross-sectional, Icelandic adolescent 15-17years

Females less physically active than males β= -0.352, P<0.01

Gender Lasheras, Aznar, Merino, and López, 2001

Cross-sectional, Spanish Boys and Girls up to 15 years

Boys are more active than girls OR=0.38, 95% CI= 0.29-0.49, P<0.001


Socio-demographyVariable Author Description Findings

Income Gordon-Larsen, Nelson, Page, and Popkin, 2006

Longitudinal studyUS adolescents

Lower socioeconomic status with no access to physical activity facilities decreases physical activity

Income Saffer, Dave and Grossman, 2011

Cross-sectionalUS Adolescents 18 years

Income positively influences physical activity


Environment SupportVariable Author Description Findings

Environment Hooker, Wilson, Griffin, and Ainsworth, 2005

Cross-sectionalCollege students

Significant relationship between environment support and physical activity

Environmental support

Huston, Evenson, Bors, and Gizlice, 2003

Cross-sectionalAdolescents 18 years

Walk trails 1.62 (1.09-2.41), street light 1.57 (1.14-2.17), and access to places 2.94 (1.91-4.52), were associated with leisure –time physical activity.


Mental HealthVariable


Mental Health

Davidson et al., 2001

Cross-sectionalOutpatients.

Individuals with mental health problems are significantly less moderately active than the general population (Light-Exercise OR 0.54, 95% CI 0.39-0.77, Vigorous Exercise OR 0.26, 95%CI 0.17-0.39).

Mental Health

Brosnahan, Steffen, Lytle, Patterson, and Boostrom, 2004.

Cross-sectionalAdolescents 18 years

Engaging in physical education was inversely related with feeling sad (OR= 0.8, 95% CI 0.68 – 0.94) and doing more physical activity in a week was associated with a lower risk of considering suicide (OR= 0.72, 95% CI 0.65 – 0.79)


Self-efficacy

Variable Author Description Findings

Self-efficacy

Benight and Bandura, 2004

Self-efficacy is an essential part and a constant correlate of Bandura social cognitive theory of physical activity behaviour.

Self-efficacy

Trost et al., 1997

Prospective study, African American Adolescents

Self-efficacy was important predictor of both moderate and vigorous intensity physical activity.

Self-efficacy

Sreeramareddy, Kutty, Jabbar, and Boo, 201z

Exploratory survey, Malaysian Adolescents 18 years

self efficacy of physical activity is associated significantly with sufficient physical activity (OR 0.91, 95% CI 0.85-0.97)


Body Image PerceptionVariable Author Description Findings

Body image Laura and William, 2010; Lantz, Hardy and Ainsworth 1997.

Longitudinal, Students !7 years +

Body image perception can act as both motivator and barrier of exercise

Body image Korn, Gonen, Shaked and Golan, 2013

Cross-sectional Engagement in physical exercise contributes to positive body image(AOR 2.38, P<0.001)

Body image Caroline S et al., 2013

Body dissatisfaction was associated with low physical activity


CONCEPTUAL FRAMEWORK


ENVIRONMENTAL SUPPORT

PHYSICAL INACTIVITY

MENTAL HEALTH

SELF EFFICACY OF PHYSICAL ACTIVITY

BODY IMAGE PERCEPTION

SOCIO-DEMOGRAPHYSOCIO-DEMOGRAPHY

Figure 1. Conceptual frame work of factors associated with physical inactivity

Dependent Variable

Independent Variables

MethodologyStudy location University Putra Malaysia (UPM)

Study design Cross-sectional

Study population

Only full time, non pregnant, not disabled registered Malaysians students in serdang campus were included in this study

Sampling frame All faculties in UPM serdang campus

Sampling unit First year undergraduate student who met the inclusion criteria

Sample size estimation

Formula for hypothesis testing for two proportion (Lemeshow et al., 1990).

Sampling technique

Cluster Sampling


Variables


Dependent variable is physical inactivity Independent variables

• socio-demographic factors (age, gender, ethnicity and family income)

• environmental factors (availability of recreational areas, cycling track sports ground, street light, and side walk)

• physical activity readiness and medical history• mental health status• self-efficacy of physical activity• body image perception and dissatisfaction

Dependent variable is physical inactivity Independent variables

• socio-demographic factors (age, gender, ethnicity and family income)

• environmental factors (availability of recreational areas, cycling track sports ground, street light, and side walk)

• physical activity readiness and medical history• mental health status• self-efficacy of physical activity• body image perception and dissatisfaction

Study instrument


Section A: Self administered Scocio-demography questionnaire (age, gender ethnicity, family income, faculty, and contact details)

Section B: Physical Activity levels using the Malay short version of the (IPAQ-M, 2005).

Section C: Short Form of Environmental Support for Physical Activity Questionnaire (Brownson et al., 2001)

Section D: 7 items on Physical Activity Readiness questionnaire (Thomas, Reading, and Shephard, 1992)

Section A: Self administered Scocio-demography questionnaire (age, gender ethnicity, family income, faculty, and contact details)

Section B: Physical Activity levels using the Malay short version of the (IPAQ-M, 2005).

Section C: Short Form of Environmental Support for Physical Activity Questionnaire (Brownson et al., 2001)

Section D: 7 items on Physical Activity Readiness questionnaire (Thomas, Reading, and Shephard, 1992)

Study instrument


Section E: Mental health status using the Malaysian Mental Health Screening Instrument, “Saringan Status Kesihatan Mental-20 (SSKM – 20)” (Ministry of Health Malaysia, 2011).

Section F: 8 item likert scale Physical Activity Self-Efficacy Questionnaire (PASES) (Bartholomew, Loukas, Jowers, and Allua, 2006)

Section G: Body image perception and dissatisfaction using pictorial weight –based scale developed by (Harris, Bradlyn, Coffman, Gunel, and Cottrell, 2007)

Section H: 17 items on physical activity pattern in and around their college and faculty.

Section E: Mental health status using the Malaysian Mental Health Screening Instrument, “Saringan Status Kesihatan Mental-20 (SSKM – 20)” (Ministry of Health Malaysia, 2011).

Section F: 8 item likert scale Physical Activity Self-Efficacy Questionnaire (PASES) (Bartholomew, Loukas, Jowers, and Allua, 2006)

Section G: Body image perception and dissatisfaction using pictorial weight –based scale developed by (Harris, Bradlyn, Coffman, Gunel, and Cottrell, 2007)

Section H: 17 items on physical activity pattern in and around their college and faculty.

Data analysisData Analysis Using SPSS version (IBM, 2012)

Descriptive analyses

Frequency and percentage for qualitative variables and measure of central tendency and dispersion for quantitative variables

Chi-square test Association between the categorical variables

Level of significance

α= 0.05

Simple logistic regression

Crudes odds ratio and their 95% CI, if P<0.05

Multiple logistic regression

To determine the final predictors


Operational definitionPhysical inactivity

Low level of physical activity based on classification by IPAQ (IPAQ-M, 2005).

Physically active

High and moderate level of physical activity based on IPAQ classification (IPAQ-M, 2005).

Age Was based on self-report by respondents on date of data collection.

Gender Was simply classified as males and females based on self-report by respondents

Total family income

This is the sum of income of all members of a family in a month as reported by the respondents in this study.

Ethnicity Classified into four (4) groups (Malay, Chines, India and Others), base on self report by respondents.


Operational definitionEnvironment support

Based on self-report using (short form of environmental support for physical activity questionnaire).

Mental health in this study is based on self-report of SSKM-20.

Self-efficacy of physical activity

The is based on self report of PASES as reported by the respondents.

Body image perception

Classified based self-report by respondents using the weight based, pictorial scale adapted from Harris and colleagues (2008).


First year students in 7 faculties (n= 1284)First year students in 7 faculties (n= 1284)

Excluded

International students n=88

IPAQ completely n=

894

Refused n= 198

Eligible full time registered students n=1235

Final Analysis n = 894 Dropped

Returned Questionnaire n= 1037

Incomplete IPAQ

n= 143


Response rate: 72.3 %

Table 1: Sociodemographic distribution %Gender Male 22.6 Female 77.4Age group <20 years 71.4

>20 years 28.6Ethnicity Malay 79.5

Other tribes 20.5Family income <2500RM 51.5

>2500RM 48.5


Results

Table 2: Association between physical inactivity and the independent variables

Respondents characteristics Physical Activity levels χ2 p-value Inactive Active Gender (n=894) 54.82 0.001 Male 38 (18.8%) 164 (81.2%) Female 332 (48.9%) 360 (52.0%)

Age group 0.004 0.951

< 20 years 325 (41.6) 4575 (8.4)

> 20 years 40 (41.2) 57 (58.8)

Family income 97.81 0.001 < 2500 245 (62.7%) 146 (37.3%) > 2500 99 (26.9%) 269 (73.1%) Ethnicity 0.602 0.438

Malay 285 (40.7) 415 (59.3)

Non-Malays 85 (43.8) 109 (56.2)


Table 2: Association between physical inactivity and the independent variables

Respondents characteristics Physical Activity levels χ2 p-value Inactive Active Mental health 10.89 0.001

No 201 (37.0%) 342 (63.0%)

Yes 169 (48.1%) 182 (51.9%)

Self-efficacy 27.65 0.001Low 212 (50.7) 206 (49.3) High 158 (33.3) 316 (66.7)

Respondents current body 7.51 0.057 Underweight 47(38.5) 75 (61.5)

Normal weight 214 (43.5) 278 (56.5)

Overweight 63 (46.0) 74 (54.0)

Obese 46 (32.2) 97 (67.8)

Body Satisfaction 0.049 0.832Satisfied 134 (41.9) 186 (58.1)

Dissatisfied 236 (41.1) 338 (58.9)


Table 3: Factors associated with physical inactivity Variables Adjusted Odds Ratio 95% CI P-value

GenderMales 1.00

Females 4.39 2.66 - 7.24 <0.001*

Family income RM

> 2500 1 .00

< 2500 4.19 2.98 - 5.90 <0.001*

Mental health problem

No 1.00

Yes 1.63 1.15 - 2.31 0.006*

Self-efficacy

High self-efficacy 1.00

Low self-efficacy 1.77 1.26 - 2.50 <0.01*

Students are active in your collegeYes 1.00No 1.873 1.22-2.88 0.004*

Respondent current body

Underweight/Normal weight 1.00

Overweight/obese 1.52 1.01 - 2.28 0.041*


Prevalence of Physical InactivityThe prevalence of physical inactivity in this study (41.4%) is comparable with studies reported in NHMS III (43.7%) (MOH, 2008). The prevalence is much higher when compared with study by Hazizi et al, (2012), which shows only 14.9% prevalence of sedentary lifestyle among undergraduates in Malaysia

SociodemographyThe odds of being physically inactive is 4.3 times higher in females than males in this study, With the exception of Age and ethnicity, the alternative hypothesis for sociodemographic variables is accepted. This fining is comparable

• Physical activity levels decline more in girls than in boys (Dwyer et al., 2005; US DHHS, 2008; Malina, 1996)

• Women are shown to be less active than men at all ages (Crespo et al., 2001; National Centre for Health Statistics, 2012).


Discussion

• Female adolescence were 15 to 20 times less active than male adolescents (Sallis, 1993).

• The prevalence of physical inactivity in this study among gender (females 48%, males 18.8%), can be compared to findings by (Dan, Nasir, and Zalilah, 2007) which reveals that female (45.1%) in low physical activity category when compared to males (22.1%).

Family incomeWe accept our alternate hypothesis, and this can be compared with,• Low income alongside with other factors have also been

shown to be inversely associated with physical activity among Malaysian adults (Cheah, 2011), this is inconsistent with this findings in this study

• People with low income have also been shown to suffer excessively from physical inactivity related problems (CDC, 2000).


Environmental SupportA chi-square in this study has shown environmental support to significantly associate with physical inactivity but the final models fails to show a significant association and we fail to accept the alternative hypothesis and it is not consistent with findings which shows• Use of recreational facilities (OR=1.75; 95% CI: 1.56-

1.96) were shown to be associated with an increase probability of participating in high level of moderate to vigorous physical activity (Gordon-Larsen et al., 2000).

• In Malaysia, a significant association between use of facilities and physical activity behaviour has been shown (χ2 = 702,750, p=0.000)(Abd-Latif, Nor, Omar-fauzee, Ahmad and Karime, 2011).


Mental HealthFindings in this study shows that respondents with mental health probable cases are at higher risk of being physically inactive this has answered our hypothesis.

• Studies by have also shown gender difference on mental among university student and physical fitness influences mental health (P<0.05)

• A study by Brosnahan et al.,(2004) showed that engaging in physical education was inversely related with feeling sad (OR= 0.8, 95% CI 0.68 – 0.94) and doing more physical activity in a week was associated with a lower risk of considering suicide (OR= 0.72, 95% CI 0.65 – 0.79).

Self-efficacyThe odds of being physically inactive in this study (OR= 1.77, 95% CI=1.264-2.500, p<0.01) can be compared with study by Chiu, (2009) which reveals that self-efficacy was among the best predictors of physical activity (B=0.304, F (2, 1349) = 78.445, p = 0.00001).


Conclusion The prevalence of physical inactivity in this study was 41.4 %.

The prevalence was higher among females when compared with males.

Gender and family income are the only non- modifiable predictors The modifiable predictors are environmental support factors, those with mental health problems and low self-efficacy of physical activity, perception of overweight and obese body image.

Gender (Female), and family income (Low) were shown to be the strongest predictors of physical inactivity in this study.


Study LimitationsThe study design is cross sectional.

Recommendations

Increasing physical activity facilities, encouragement, pear support and human resource within the university environment will improve physical activity opportunities and participation.

The use of bicycle introduced in UPM within some colleges should be extended across the whole school.



Thank you for walking….. Thank you for being active

PREVALENCE OF PHYSICAL INACTIVITY

Health & Medicine

Transcript of PREVALENCE OF PHYSICAL INACTIVITY