The Determinants of Fruit and

Vegetable Consumption: A Focus on

Individual AttitudesLiam Mc Morrow, PhD Student

Prof Anne Ludbrook, Dr. Jennie Macdiarmid, Dr. Damiola Olajide

Funded by Rowett Institute of Nutrition and Health

Health Survey Users’ Conference, London

15/7/2014

1

Background

• Non price determinants of food choices:

– Information

– culture

– taste

– access

– health shocks

– habit formation

– risk preferences

– cues

• Attitudes towards healthy eating

2

Background

• Scotland - Sickman of Europe

– Mortality rates for working aged males are 20% higher than Western European average (Whyte and Ajetunmobi , 2012).

• Obesity rates in Scotland are amongst the highest in the developed world (WHO, 2013)

– Over 27% of the Scottish population were classified as obese in 2011

– If trends continue along the current trajectory, 40% of the Scottish population will be obese by 2030 (Scottish Government, 2010)

Background

• A large proportion of Scotland’s poor health has been linked to their poor diet (Scottish Government, 2012).

• Poor diet related ill health cost the NHS in the UK £5.8billion in 2006/2007

– compared with smoking (£3.3billion), physical inactivity (£0.9billion), and alcohol (£3.3billion) (Scarborough et al., 2011)

• Economic rationale for intervention

Background

• Why are we interested in attitudes?

– Knowledge and action gap

– 87% of Scottish adults are aware of the five-a-day

policy

– 20% of men and 23% women eat five-a-day

Background

• Attitudes impact on healthy eating:

– Mediate the education - diet relationship (Le et al., 2013)

– Associated with higher dietary quality across four measures (Emery, 2013)

– Attitudes eliminated the relationship between more expensive supermarkets and diet quality (Aggrawal et al., in press)

– Attitudes help explain gender and age disparities in diet. (Wardle et al., 2004; Trail et al., 2011)

6

Background

• Studies investigating the determinants of fruit

and vegetable (FV) consumption:

– England (Thompson et al.,1999)

– Australia (Sodergen et al., 2012)

– Canada (Dehgham et al., 2011)

– Japan (Asano et al., 2009)

Research Questions

• What role do attitudes towards healthy eating

play in making healthy food choices?

• Are the determinants of healthy eating

different when considered separately?

8

Economic Framework

• Grossman model provides economic

theoretical underpinning

9

Utility

DietHealth

Data

• Scottish Health Survey 2008-2011

– Nationally representative cross-section (n=28,785)– Everyone completes fruit and vegetable questions

– Knowledge, Attitudes, and Motivation (n=8,404)– Attitudes towards healthy eating

– Eating Habits Module– Derive Dietary Quality Index (n=3,362)

– No overlap with attitudes

– Demographic variables

– Socioeconomic variables

– Lifestyle behaviours

10

Data

• Knowledge, Attitudes, and Motivation (KAM)

– Barriers to healthy eating:

• People – friends, colleagues, family

• Lack of information – changes to make, cooking

• Supply – supermarket, canteens and restaurants

• Price – too expensive

• Time

• Lack of willpower

• Hedonics – taste, too boring

• Other barriers

Data

• Eating Habits Module

• Dependent variable

– If the individual self-reports eating five or more

portions of fruit and vegetables.

– Highly correlated with dietary quality index (DQI)

Five a day No. of F&V No. of Veg No. of Fruit

DQI Score 0.6488* 0.6103* 0.2959* 0.5410*

Methods

• Regression analysis - Probit Model

– Probability the individual eats five portions of fruit

and vegetables a day given their demographic,

socioeconomic (Xi), lifestyle (Li), and attitudinal

factors (Ai).

– Y = 1 if individual eats five-a-day

– Y=0 if individual does not eat five-a-day

� � � 1 �, �, � � � ���� � ��� � ��� ���

13

Descriptive Statistics

• Who eats five-a-day?

– 21% of males and 24% of females

– 26% of 55-64 year olds eat five-a-day compared to 16% of 15-24 year olds

– 28% of individuals in remote rural areas eat five-a-day compared to 21% of in primary cities

– 31% in top income quintile eat five-a-day compared to 16% in bottom income quintile

– 36% with a college degree eat five-a-day compared to 15% with no qualifications

Descriptive Statistics

Dependent Variables five-a-day 2.5 potions-a-day

N Mean (se) % (se) % (se)

FV 8319 3.36 (2.46) 23.73% (0.42) 60.12% (0.49)

Fruit 8319 1.96 (1.77) 7.26% (0.26) 34.30% (0.47)

Vegetables 8319 1.40 (1.33) 2.03% (0.14) 16.49% (0.37)

Descriptive Statistics

Attitudes KAM Sample Eat five-a-day

N % N %

People 309 3.68% 69 22.33%

Lack of Information 953 11.33% 144 15.11%

Supply 924 10.99% 242 26.19%

Price 1376 16.37% 277 20.13%

Time 616 7.33% 132 21.43%

Lack of Willpower 2759 32.81% 607 22.00%

Hedonics 1080 12.84% 151 13.98%

Other Barriers 358 4.26% 98 27.45%

Results

• Probability of eating five-a-day:

– Males are 4.34% less likely to eat five-a-day

– 16-24 year olds are 12.4% less likely compared to

75+ age group

– Remote rural areas are 5.35% more likely to eat

five-a-day compared to primary cities

Results

• Probability of eating five-a-day:

– All income quintiles are statistically significantly

less likely than top quintile.

– All educational categories are statistically

significantly more likely than no qualifications

– Favourable lifestyle factors increase probability of

eating five-a-day

– Economic activity and marital status have no

statistically significant effect on eating five-a-day

Results

• Attitudinal Effect on eating five-a-day:

– Lack of willpower (-2.97%)

– Lack of information (-4.77%)

– Hedonics (-5.57%)

– All other attitudinal variables were insignificant

Results

• Differences between determinants of fruit and

vegetables (2.5 or more portions):

• Males are less likely to eat fruit but not veg

• Older age groups are more likely to eat fruit but not veg

• Income effect mostly disappears when FV are split

– Only exception is the bottom quintile are significantly less

likely to eat fruit

• Smokers are 11% less likely to eat fruit but not

significantly less likely to eat veg

Results - Hedonics

0%

1%

2%

3%

4%

5%

6%

7%

8%

9%

10%

Five-a-day* 2.5 Fruit* 2.5 Veg*

Results – Lack of willpower

0%

1%

2%

3%

4%

5%

6%

7%

8%

9%

10%

Five-a-day* 2.5 Fruit* 2.5 Veg*

Results – Lack of information

0%

1%

2%

3%

4%

5%

6%

7%

8%

9%

10%

Five-a-day* 2.5 Fruit 2.5 Veg*

Attitudes over time

0.00%

5.00%

10.00%

15.00%

20.00%

25.00%

30.00%

35.00%

40.00%1

99

6 (

n=

18

10

)

19

97

(n

=1

79

5)

19

98

(n

=1

79

3)

19

99

(n

=8

80

)

20

00

20

01

20

02

20

03

(n

=1

72

0)

20

04

(n

=1

78

4)

20

05

(n

=1

82

2)

20

06

(n

=1

75

9)

20

07

(n

=1

90

8)

20

08

(n

=1

83

7)

20

09

(n

=2

02

0)

20

10

(n

=2

27

6)

20

11

(n

=2

27

5)

Health Education Population Survey Scottish Health Survey

Lack of information

Lack of willpower

Hedonics

Conclusions

– Demographic, socioeconomic, and lifestyle variables impact on FV, as previously reported in the literature.

– Attitudinal factors should be considered when designing interventions to increase fruit and vegetable consumption.

– Hedonics impacts on both fruit and vegetable consumption

– Lack of willpower is a significant determinant of consuming 2.5 portions or more of fruit and vegetables.

– Lack of information is a significant determinant of consuming 2.5 portions or more of vegetables only.

Thank you

• Liam Mc Morrow

• r03lm12@abdn.ac.uk

Descriptive Statistics (1)

27

N Mean FV (se) Mean Fruit (se) Mean Veg (se)

Gender Female* 4,838 3.47 (2.46) 2.06 (1.77) 1.41 (1.31)

Men 3,481 3.21 (2.46) 1.83 (1.75) 1.38 (1.36)

Age Groups 16-25 * 572 2.66 (2.49) 1.40 (1.57) 1.26 (1.53)

25-34 1,101 3.33 (2.63) 1.83 (1.78) 1.50 (1.5)

35-44 1,373 3.21 (2.56) 1.80 (1.77) 1.41 (1.44)

45-54 1,401 3.42 (2.5) 1.94 (1.8) 1.48 (1.33)

55-64 1,476 3.59 (2.57) 2.13 (1.92) 1.45 (1.31)

65-74 1,308 3.49 (2.3) 2.13 (1.69) 1.36 (1.83)

75+ 1,088 3.40 (2.04) 2.19 (1.56) 1.20 (1.03)

Income Quintiles Top Quintile * 1,523 4.10 (2.68) 2.40 (1.93) 1.70 (1.43)

2nd Quintile 1,488 3.66 (2.5) 2.11 (1.8) 1.54 (1.38)

3rd Quintile 1,459 3.31 (2.33) 1.97 (1.72) 1.34 (1.26)

4th Quintile 1,386 3.04 (2.3) 1.77 (1.65) 1.27 (1.28)

5th Quintile (lowest income) 1,509 2.68 (2.29) 1.52 (1.62) 1.16 (1.24)

No Income Reported 954 3.34 (2.36) 2.02 (1.7) 1.32 (1.28)

Descriptive Statistics (2)

N Mean FV (se) Mean Fruit (se) Mean Veg (se)

Educational

Qualification HNC/D791 3.34 (2.37) 1.91 (1.66) 1.47 (1.32)

Higher grade 1,112 3.37 (2.49) 1.90 (1.78) 1.47 (1.42)

Standard grade 1,433 2.87 (2.32) 1.69 (1.72) 1.18 (1.2)

Other school level 760 3.31 (2.28) 1.96 (1.63) 1.35 (1.25)

No qualifications 2,099 2.75 (2.01) 1.66 (1.62) 1.09 (1.06)

Smoking

Status Never smoked*3,686 3.67 (2.49) 2.21 (1.8) 1.46 (1.33)

Used to smoke occasionally 389 3.80 (2.47) 2.12 (1.77) 1.61 (1.35)

Used to smoke regularly 2,080 3.52 (2.35) 2.10 (1.74) 1.42 (1.29)

Current smoker 2,164 2.60 (2.36) 1.37 (1.58) 1.23 (1.34)

Exercise No exercise* 1,784 2.83 (2.18) 1.73 (1.67) 1.01 (1.08)

Less than 1 hour 955 2.99 (2.17) 1.80 (1.63) 1.20 (1.11)

1-3 hours 1,338 3.22 (2.24) 1.85 (1.67) 1.38 (1.21)

3-5 hours 876 3.53 (2.5) 2.05 (1.72) 1.48 (1.42)

5-7 hours 659 3.57 (2.36) 2.10 (1.71) 1.47 (1.36)

7 hours or more 2,707 3.80 (2.75) 2.17 (1.91) 1.63 (1.51)

Alcohol

Consumption

No alcohol* 1,328 3.25 (2.54) 1.94 (1.74) 1.32 (1.47)

Within limit 5,283 3.40 (2.44) 2.01 (1.77) 1.39 (1.29)

Within double limit 1,148 3.59 (2.5) 2.00 (1.71) 1.58 (1.37)

Over double limit 560 2.77 (2.31) 1.45 (1.68) 1.32 (1.24)

Descriptive Statistics (3)

N Mean FV (se) Mean Fruit (se) Mean Veg (se)

Perceived barriers to

healthy eatingPeople 305 3.20 (2.39) 1.80 (1.82) 1.40 (1.2)

Information944 2.63 (2.2) 1.53 (1.58) 1.10 (1.21)

Supply909 3.53 (2.69) 2.05 (1.85) 1.48 (1.45)

Hedonics1,070 2.55 (2.18) 1.47 (1.57) 1.08 (1.19)

Price1,365 2.98 (2.39) 1.67 (1.69) 1.31 (1.32)

Time606 3.12 (2.39) 1.81 (1.66) 1.32 (1.39)

Lack of willpower2,737 3.18 (2.41) 1.86 (1.76) 1.32 (1.26)

Other barriers355 3.48 (3.03) 2.08 (2.01) 1.40 (1.59)

Probit model (1)FV Fruit Vegetables

M.E (se) M.E (se) M.E (se)

Gender

Men -4.34%* (0.01) -7.37%* (0.01) -0.90% (0.01)

Age Groups

25-34 7.14%* (0.02) 6.88%* (0.03) 5.77%* (0.02)

35-44 6.75%* (0.03) 5.60% (0.03) 3.72% (0.02)

45-54 8.85%* (0.03) 11.06%* (0.03) 4.64% (0.02)

55-64 12.3%* (0.03) 13.12%* (0.03) 4.86% (0.02)

65-74 12.24%* (0.03) 16.3%* (0.04) 2.28% (0.03)

75+ 12.4%* (0.04) 19.71%* (0.04) 3.03% (0.03)

Urban/Rural Location

Urban town -0.16% (0.01) -0.83% (0.02) 1.07% (0.01)

Small accessible town 1.77% (0.02) -1.23% (0.02) 4.9%* (0.02)

Small remote town 1.58% (0.03) 1.94% (0.03) 0.62% (0.03)

Accessible rural 0.38% (0.02) 0.02% (0.02) 0.66% (0.02)

Remote rural 5.35%* (0.02) 6.31%* (0.03) 2.81% (0.02)

Marital status

Living as married -0.77% (0.02) -2.58% (0.02) 2.20% (0.02)

Single -0.85% (0.02) -0.38% (0.02) 0.65% (0.02)

Separated -3.56% (0.03) -6.49%* (0.03) 2.98% (0.03)

Divorced -0.20% (0.02) -0.60% (0.02) 0.83% (0.02)

Widowed -0.85% (0.02) 1.11% (0.02) -0.66% (0.02)

Probit model (2)

FV Fruit Vegetables

M.E (se) M.E (se) M.E (se)

Economic activity

Full time education 5.31% (0.04) 1.80% (0.04) 7.59% (0.04)

Unable to work 2.94% (0.03) 1.13% (0.03) -2.06% (0.02)

Looking for work -3.18% (0.03) -3.29% (0.04) -2.28% (0.03)

Retired 0.04% (0.02) 0.94% (0.03) -1.28% (0.02)

Homemaker -1.20% (0.02) -4.97% (0.03) 3.14% (0.02)

Doing something else 1.24% (0.06) -0.58% (0.08) 3.25% (0.05)

Income Quintiles

2nd Quintile -4.56%* (0.02) -2.52% (0.02) -1.04% (0.02)

3rd Quintile -4.29%* (0.02) -4.04% (0.02) -2.91% (0.02)

4th Quintile -6.1%* (0.02) -3.87% (0.02) -2.51% (0.02)

5th Quintile -6.86%* (0.02) -5.76%* (0.03) -3.27% (0.02)

No Income Reported -5.26%* (0.02) -1.92% (0.03) -3.77% (0.02)

Educational Qualification

HNC/D -6.44%* (0.02) -6.29%* (0.02) -2.88% (0.02)

Higher grade -8.04%* (0.02) -8.24%* (0.02) -4.%* (0.02)

Standard grade -11.29%* (0.02) -7.89%* (0.02) -9.88%* (0.02)

Other school level -13.7%* (0.02) -11.68%* (0.02) -4.7%* (0.02)

No qualifications -15.81%* (0.02) -14.34%* (0.02) -9.92%* (0.02)

Probit Model (3)FV Fruit Vegetables

M.E (se) M.E (se) M.E (se)

Smoking status

Smoked occasionally -1.13% (0.03) -1.21% (0.03) 3.48% (0.03)

Smoked regularly -0.73% (0.01) 0.25% (0.02) 1.22% (0.01)

Current smoker -7.93%* (0.01) -11.2%* (0.02) -2.08% (0.01)

Exercise

Less than 1 hour 0.53% (0.02) 0.31% (0.02) 1.03% (0.02)

1-3 hours 2.13% (0.02) -1.23% (0.02) 2.18% (0.01)

3-5 hours 5.66%* (0.02) 4.41% (0.03) 5.07%* (0.02)

5-7 hours 6.%* (0.02) 8.26%* (0.03) 2.79% (0.02)

7 hours or more 11.2%* (0.02) 9.44%* (0.02) 7.69%* (0.01)

Alcohol consumption

Within limit -2.62% (0.02) -0.21% (0.02) -5.3%* (0.02)

Within double limit -2.34% (0.02) -0.85% (0.02) -3.80% (0.02)

Over double limit -12.19%* (0.02) -10.61%* (0.03) -9.72%* (0.02)

Probit model (4)

FV Fruit Vegetables

M.E (se) M.E (se) M.E (se)

Perceived barriers to healthy eating

People -2.77% (0.03) -4.64% (0.03) -1.94% (0.03)

Lack of information -4.6%* (0.02) -3.59% (0.02) -3.62%* (0.02)

Lack of supply 2.78% (0.02) 3.25% (0.02) 0.74% (0.02)

Hedonics -5.96%* (0.02) -6.96%* (0.02) -5.95%* (0.02)

Price 0.01% (0.02) -0.14% (0.02) -1.33% (0.01)

Time -2.46% (0.02) -2.60% (0.02) -1.91% (0.02)

Lack of willpower -2.68%* (0.01) -4.7%* (0.01) -2.54%* (0.01)

Other barriers 2.65% (0.03) 0.28% (0.03) -1.48% (0.02)

Number of children

1 child -3.40% (0.02) -3.83% (0.02) 0.04% (0.02)

2 children -2.68% (0.02) 2.84% (0.03) -4.05%* (0.02)

3 or more children -6.33% (0.05) -4.22% (0.05) -2.99% (0.04)

Year

2009 0.29% (0.02) -1.85% (0.02) 2.53% (0.01)

2010 -0.96% (0.02) -1.64% (0.02) 3.9%* (0.01)

2011 -2.71% (0.02) -4.39%* (0.02) 2.74% (0.01)

DQI Correlations

Five a day No. of F&V No. of Veg No. of Fruit

DQI Score 0.6488* 0.6103* 0.2959* 0.5410*

Fish 0.1345* 0.1987* 0.1231* 0.1640*

No red meat 0.1149* 0.1351* 0.0454* 0.1240*

Starch -0.02 -0.02 -0.01 -0.02

Fibre 0.3123* 0.3719* 0.1903* 0.3134*

No sugar 0.1008* 0.1214* 0.0831* 0.0887*

No fatty foods 0.1301* 0.1514* 0.1052* 0.1153*

No soft drink 0.00 0.0177* -0.0182* 0.0492*

Five-a-day 1.0000* 0.7732* 0.3793* 0.6795*

* Indicates 95% significance

34