THE FIVE COUNTRY STUDY 2014
Perceptions of Weight Control, the Causes of
Obesity & Support for Nutrition Policies in
Five countries
Tony Worsley
BACKGROUND
• Major economic and health changes are taking place in the Asia
Pacific Region.
• These affect people’s diets (e.g. Moodie et al. 2013, Popkin et al. 2012)
• Rising middle class in many countries; successful policies requires
civic engagement (Laverack 2010, Lobstein et al. 2013).
• Food & nutrition policymakers need to monitor the effects of their
policies.
• Little is known about food consumers’ views and experiences in
these countries.
BACKGROUND & AIMS
General aims of the survey
To describe:
1
Household food providers’ food & health behaviours & habits during
the nutrition transition.
2
Their views of food marketing, retailing & consumption, and food
policies.
Specific aims
1 Their interest in body weight control.
2 Their beliefs about the efficacy of weight control strategies.
3 Their perceptions of the causes of obesity.
4 Their support for food & nutrition policy options.
General hypotheses
1
Nutrition-economic transition: economic change drives changes in food consumption & nutrition status.
Populations new to ‘global markets’ will be less aware of dangers to nutrition status.
Australia & Singapore further into transition than Vietnam, Indonesia and Shanghai,
OzSin likely to be more critical than V.I.S.
2
Personal values: Self and other oriented values & Conformity security values (Schwartz POV)
Other oriented values will be positively linked to pro health & nutrition views.
3
Demographics: In line with literature,
Older people and women more likely to be concerned about factors which adversely affect nutrition status.
4
Ownership of electronic devices, surrogate index of economic transition into ‘consumer society’.
Higher electronic devise ownership, higher penetration of consumer society
METHODS
The samples
• Online survey administered by Global Market Insite using their
consumer panels.
• Approx. 800 respondents in each of Indonesia, Melbourne,
Singapore, Shanghai, Vietnam.
• Respondents were household food providers, representative of
main age groups in each country; approximately 40% were men.
• Samples were highly educated (middle class).
METHODS
Procedure
• Respondents contacted by email during December 2013 and
January 2014.
• Strong data quality checks e.g. rotation of items to avoid order effects.
• Points incentives redeemable for small cash amounts.
• Quota (convenience) sampling
METHODS
The Questionnaire
• Several sections composed of closed and open ended items: views and
experience of food marketing and supermarkets, perceived healthiness of beverages, views
of food skills required by consumers, dietary change attempts in previous year, personal
values & detailed demographics.
•
For this presentation:
–
–
–
–
Weight control issues (based on IFIC 2013)
Effectiveness of personal weight control strategies (previous work)
Perceived causes of obesity (Hardus et al. 2003)
Support for prevention policy options (Hardus et al. 2003)
• Binary and 5 point response scales: “%Yes” & % ratings 4+5 (definitely) reported here
Food providers’ levels of concern with their
body weight (% somewhat + very concerned).
Respondents were asked: Are you concerned about your weight at the moment?
Melbourne
n=769
Shanghai
n=807
Indonesia
n=788
Singapore
n=771
Vietnam
n=810
Total
n=3945
a) Not or a little concerned
50.1
50.8
55.5
34.0
36.2
45.23
b) Concerned
49.9
49.2
44.5
66.0
63.8
54.7
Chi Sq
P
170.70
<0.001
Food providers’ weight change goals
(% Yes)
Respondents were asked: Which of the following are you trying to do about your weight at
the moment?
Melbourne
Shanghai
Indonesia Singapore
Vietnam
Total
n=769
n=807
n=788
n=810
n=3945
n=771
Chi Sq
P
Trying to lose weight
87.6
63.2
74.1
79.6
53.6
70.8
182.63
<0.001
Trying to gain weight
3.3
2.2
13.6
6.1
26.0
10.8
197.82
<0.001
Trying to stay the same weight/no
action
Have you heard of the Body Mass
Index (BMI)? % Yes
9.1
34.6
12.3
14.3
20.4
18.4
7.839
0.098
83.9
55.0
60.8
91.4
69.4
71.9
379.08
<0.001
Food providers’ strategies to lose weight (% Yes).
Melbourne
Shanghai
Indonesia Singapore
Vietnam
Total
n=769
n=807
n=788
n=810
n=3945
n=771
Chi Sq
P
Are you trying to lose weight
87.6
63.2
74.1
79.6
53.6
70.8
182.63
<0.001
a) By dieting
14.9
10.8
20.3
11.9
16.3
15.0
104.71
<0.001
b) By exercising
23.9
39.7
17.9
32.5
23.1
27.0
c) By dieting and exercising
53.0
49.0
56.6
52.9
60.3
54.3
d) Other ways
8.2
0.6
5.2
2.6
0.3
3.7
Ten most effective weight loss strategies (%Yes)
Respondents were asked: How effective are the following actions that individuals can take
to maintain a healthy body weight?
Melbourne
Shanghai
Indonesia
Singapore
Vietnam
Total
n=769
n=807
n=788
n=771
n=810
n=3945
Chi Sq
P
Establish an exercise routine
87.6
87.5
92.1
84.8
84.7
87.4
42.50
<0.001
Walk more
88.8
86.9
90.1
79.6
83.2
85.7
75.73
<0.001
Avoid sugar sweetened soft drinks like Coca
Cola
Eat smaller portions of food
81.5
70.9
81.5
79.9
60.9
74.8
157.20
<0.001
85.2
61.3
77.0
74.4
63.5
72.1
190.94
<0.001
Eat breakfast every day
76.3
79.7
57.7
68.6
74.8
71.5
158.78
<0.001
Try not to eat sweetened foods like cakes or
confectionery
Eat foods with protein (e.g. meats, fish, eggs)
every day
Avoid alcoholic drinks
75.7
67.9
68.8
69.9
64.4
69.3
39.05
<0.001
72.4
70.8
70.2
64.5
57.3
67.0
112.80
<0.001
58.1
49.4
77.7
59.9
56.4
60.3
167.32
<0.001
Make a regular shopping list
65.1
57.9
54.8
50.6
61.4
58.0
68.64
<0.001
Don’t eat between meals
47.6
60.7
73.7
49.9
57.2
57.9
185.10
<0.001
Least effective weight loss strategies
Melbourne
Shanghai Indonesia
n=769
n=807
n=788
Singapore Vietnam
Total
n=771
n=3945
n=810
Chi Sq
P
Take diet pills
10.0
20.3
17.4
16.6
20.4
17.0
75.17
<0.001
Eat only with other people
18.1
27.5
12.6
19.6
19.1
19.4
168.55 <0.001
Use commercial meal replacements
19.0
31.2
29.6
21.9
30.5
26.5
138.52 <0.001
Substitute diet soft drinks for regular
soft drinks
Go on a slimming diet
23.5
31.7
46.8
29.3
62.6
39.0
424.29 <0.001
30.3
41.0
50.4
30.9
57.3
42.2
202.49 <0.001
Don’t eat in front of the TV or computer
40.2
58.4
32.9
42.5
51.6
45.2
189.12 <0.001
Don’t sit down for longer than 15-20
minutes at a time
Use smaller plates and dishes
43.8
68.9
40.0
42.0
47.7
48.6
222.84 <0.001
68.9
55.8
36.8
54.6
30.1
49.0
470.61 <0.001
Join organized weight-loss programs like
Weight Watchers
Weigh yourself regularly
47.6
NA
52.5
39.4
59.1
49.8
75.19
<0.001
39.0
47.5
56.7
52.0
53.8
49.9
87.13
<0.001
Differing support for weight loss strategies
High
Low
How effective are the following?
1 High
37.6%
2 Lower
62.4%
Don’t have second helpings
4.37
3.09
Try not to eat sweetened foods like
cakes or confectionery
4.51
3.45
Using smaller plates and dishes
4.12
2.84
Avoid sweetened soft drinks
4.62
3.63
Always make a shopping list before
major family shopping
4.26
3.22
Eat smaller portions
4.46
3.60
5 point scales
F Values
Variables associated with weight loss
effectiveness strategies
df=1,3951
180
160
140
120
100
80
60
40
20
0
1
High
Variables
Other oriented values
Conformity-security
values
OzSing vs VIS (high)
Electronics
Age (years)
Sex (male low)
2 Low
Mean
Mean
0.26
0.17
-0.16
-0.10
1.51
7.38
37.52
1.64
1.67
6.92
34.61
1.53
Factor analysis of weight loss strategy effectiveness
•
•
•
•
Avoid calories
Dieting
Eat less
Better habits - eat breakfast, eat protein, make a shopping list
Perceived causes of obesity
What do you think are the main causes of obesity? (% Definitely a Cause)
Melbourne
n=769
Shanghai
n=807
Indonesia
n=788
Singapore
n=771
Vietnam
n=810
Total
n=3945
Chi Sq
P
Overconsumption of sugar sweetened
drinks
People don’t do enough physical
activity
Eating oversized servings of foods
88.9
86.1
89.1
86.6
74.2
84.9
257.85
<0.001
89.5
88.7
89.6
82.9
70.4
84.1
395.08
<0.001
87.8
88.7
89.3
84.0
69.4
83.8
300.48
<0.001
Regular consumption of fast foods
89.6
79.7
79.6
87.0
70.9
81.2
270.07
<0.001
Lack of physical activity opportunities
66.6
87.0
81.6
76.9
70.5
76.6
238.76
<0.001
People aren’t aware of the dangers of
obesity
Lack of willpower
56.8
67.9
81.7
65.5
65.6
67.6
223.38
<0.001
72.7
69.5
61.2
73.8
54.8
66.3
315.36
<0.001
The promotion of unhealthy foods (in
stores, the mass media and online)
72.8
64.9
55.3
73.4
35.7
60.2
438.28
<0.001
Perceived causes of obesity (continued)
Melbourne
n=769
Shanghai
n=807
Indonesia
n=788
Singapore Vietnam
n=771
n=810
Total
n=3945
Chi Sq
P
Modern technology (e.g. cars,
computers, video games)
68.8
62.3
43.3
64.9
45.9
56.9
343.08
<0.001
Genes cause obesity
44.5
61.8
58.4
62.4
36.5
52.7
387.60
<0.001
The low cost of unhealthy food
71.4
41.3
57.1
62.1
30.1
52.1
400.97
<0.001
Lack of availability of healthy
foods
Lack of safe cycling and walking
paths
41.0
65.4
53.8
50.3
32.7
48.7
273.02
<0.001
31.5
21.1
34.9
43.3
27.7
31.6
132.65
<0.001
Causes of obesity clusters
What do you think are
the main causes of
obesity?
Eating oversized
servings of foods
Overconsumption of
sugar sweetened drinks
Regular consumption of
fast foods
People don’t do
enough physical activity
1 High
53.2%
2 Lower
46.8%
4.67
3.62
4.62
3.54
4.68
3.63
4.59
3.60
5 point scales
Variables associated with perceived causes of obesity clusters
250
df= 1, 3951
F Values
200
150
100
50
0
Variables
Factor analysis of perceived causes of obesity
• Fast food, no PA
• Specific environmental barriers
• Abstract barriers – genes, lack of availability, awareness, PA
opportunities
What can governments do to help us consume healthier foods
and drinks? (% Support)
Melbourne
n=769
Shanghai
n=807
Indonesia Singapore Vietnam Total
Chi Sq
n=788
n=771
n=810
n=3945
83.0
91.7
94.4
81.2
89.4
88.0
103.12
81.9
89.1
91.1
80.8
88.3
86.3
63.00
78.3
89.1
91.9
78.3
90.5
85.7
120.34
79.3
88.6
92.8
78.0
87.0
85.2
113.20
76.5
90.7
90.2
75.9
89.0
84.6
146.34
Provide incentives to encourage consumers to make 75.2
healthier choices
Ensure that children learn how to purchase and cook 78.7
foods at school
Help companies to reformulate foods to contain less 74.0
salt, sugar and saturated fat
86.9
81.0
75.7
85.4
80.9
75.14
86.5
78.6
74.7
84.1
80.6
57.19
84.1
82.4
74.1
81.7
79.3
46.63
Conduct media campaigns to encourage people to eat
healthier foods, like fruit and vegetables.
Make food labels carry clearer information about the
content of foods
Enforce the regulations on food safety in shops,
markets and restaurants
Subsidise the sales of fruits & vegetables, making
them cheaper.
Strictly enforce food safety regulations
What can governments do to help us consume
healthier foods and drinks?
Melbourne Shanghai
n=769
n=807
Indonesia Singapore
n=788
n=771
Vietnam Total
n=810
n=3945
Chi Sq
P
Allow vending machines to contain only healthy
food & drinks
Establish sms systems to remind people when to
eat healthier foods
Ban vending machines selling unhealthy food or
drinks in schools
Put a 20% tax on fizzy sugar sweetened beverages
56.8
76.5
81.9
67.7
74.1
71.5
170.70
<0.001
28.5
79.9
75.9
48.0
72.2
61.3
891.29
<0.001
61.6
68.6
60.2
54.3
51.7
59.3
85.64
<0.001
39.5
66.7
60.5
42.5
50.6
52.1
295.10
<0.001
There is little governments should do about the
availability of foods and beverages
Ban the advertising of any food products to
children
Ban all advertising of fizzy sugar sweetened
beverages
22.8
36.7
21.6
33.5
66.8
36.5
615.25
<0.001
38.1
43.4
27.8
34.0
27.0
34.0
132.90
<0.001
38.2
44.1
26.9
35.8
24.6
33.9
163.06
<0.001
Two kinds of shoppers & food marketing
Cluster 2 – stronger support
for control of food marketing
Cluster 1 weaker support for
control of food marketing
Variable
Cluster
1 mean
Cluster
2 mean
Reformulation
3.64
4.51
Media campaigns
3.93
4.82
Clearer food labels
3.79
4.88
Enforce food safety
3.80
4.83
Also, factor analysis of personal values:
• Self oriented values
• Other oriented values
• Conformity-security values
Variables associated with cluster differences
(df = 1, 3951)
Electronics
OzSin
Eat Breakfast, protein, shopping list
Not eat less
Dieting
Avoid calories
Abstract barriers
Specific env.barriers
Fast Food, no PA
Sex
Age (years)
Conformity security values
Other oriented values
Self oriented values
0
50
100
150
200
250
F value
300
350
400
450
Comparison of factor scores by clusters
0.6
0.5
0.4
Factor score means
0.3
0.2
0.1
0
-0.1
-0.2
Other oriented
values
Conformity
Fast Food, no PA
security values
-0.3
-0.4
Cluster 1
Cluster 2
Avoid calories
Eat Breakfast,
protein, shopping
list
Cluster 1 WEAK SUPPORT
Cluster 2 STRONG SUPPORT
DISCUSSION
Many respondents throughout the Region were concerned with their weights, women more
than men.
Many were attempting to control their weight. This is similar to the situation in the USA (IFIC
2013) and elsewhere.
The effectiveness of personal ways to avoid obesity were sensible and have a supporting
evidence base such as the emphasis on physical activities like walking, the avoidance of energydense products and the importance of healthy daily meal patterns such as breakfast taking. Food
and health policies could help people do these things.
It is important to engage at least part of the population (such as the rising middle class) if food
and nutrition policies are to be well founded, well supported and long lasting (Laverack 2010,
Lobstein et al. 2013).
DISCUSSION (continued)
There was much agreement about the principal causes of obesity.
Energy dense products were seen to be a common problem.
This is similar to concerns expressed by public health nutritionists (e.g. Moodie et al. 2013).
However, there were also major national differences, for example: Melbournians and Singaporeans shared
similar viewpoints in many areas.
The Vietnamese respondents underreported most of the causes of obesity.
Lack of awareness of the dangers of obesity was reported most by Indonesians and least by Melbournians.
This suggests Vietnamese and Indonesians may be less familiar with this condition.
This may relate to the relative recency of the economic and nutrition transitions or to different cultural
traditions in this country.
Importance of values and beliefs about obesity and weight control in support for policy actions.
CONCLUSION
There is a need to monitor these perceptions in order to assess
the effectiveness of national food policies and to assess the
effects of the economic and nutrition transitions.
An inaugural meeting to set up a monitoring system will be held
in Singapore in October 2014.
REFERENCES
International Food Information Council (IFIC) (2013). Food and Health Survey 2013. http://www.foodinfo@ific.org.
Hardus PM, van Vuuren CL, Crawford D and Worsley A (2003). Public perceptions of the causes and prevention of
obesity among primary school children. International Journal of Obesity, 27, 1465–1471. doi:10.1038/sj.ijo.0802463.
Laverack, G 2010, Influencing public health policy: to what extent can public action define the policy concerns of
government? Zeitschrift für Gesundheitswissenschaften, 18 (1), 21-28.
Lobstein, T, Brinsden, H, Landon, J, Kraak, V, Musicus, A, Macmullan, J (2013). INFORMAS and advocacy for public health
nutrition and obesity prevention. OBESITY Reviews, 14 (Supp. 1), 150-156.
Moodie, R, Stuckler, D, Monteiro, C, Sheron, N, Neal, B, Thamarangsi, T, et al. (2013). Profits and pandemics: prevention
of harmful effects of tobacco, alcohol, and ultra-processed food and drink industries.’ Lancet, 381, (9867), 670-679.
The Team
Dr Wei Wang
Dr Rani Sarmugam
Dr Judhiastuty Februhartanty
Ms Quynh Pham
Mr Charles Kefford
Mr Sean Calalang
Dr Anthony Lowe
Ms Stacey Ridley
Funding: Australian Research Council (DP1094493) & Deakin University
THANK YOU!
tonyw@deakin.edu.au
Support for bans and taxes
Self oriented
values
Associated factors
Avoid calories
OzSing
Eat less
Abstract barriers
Total R sq.
= 10.4%
Environmental
barriers
0
0.05
0.1
0.15
Std. Beta
0.2
0.25
Support for Nutrition Promotion
Eat breakfast, protein, shopping list
Total R
sq. = 40%
Associated factors
Fast food, no PA
OzSing vs Others
Avoid calories
Conformity-security values
Other oriented values
0
0.05
0.1
0.15
0.2
Std. Beta
0.25
0.3
0.35