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 �, �, � � � ���� � ��� � ��� ���
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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.
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