BMJ Open · Correction Zhu J, Coombs N, Stamatakis E. Temporal trends in socioeconomic inequalities in obesity prevalence among economically-active working age adults in Scotland

For peer review only

Temporal trends in socioeconomic inequalities in obesity

prevalence among working-age adults in Scotland between

1995 and 2011

Journal: BMJ Open

Manuscript ID: bmjopen-2014-006739

Article Type: Research

Date Submitted by the Author: 25-Sep-2014

Complete List of Authors: Zhu, Jin; University College London, Department of Epidemiology and Public Health; Coombs, Ngaire; University College London, Department of Epidemiology

and Public Health Stamatakis, Emmanuel; University of Sydney, Charles Perkins Centre

<b>Primary Subject Heading</b>:

Epidemiology

Secondary Subject Heading: Public health

Keywords: EPIDEMIOLOGY, PUBLIC HEALTH, PREVENTIVE MEDICINE, SOCIAL MEDICINE

For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml

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Title: Temporal trends in socioeconomic inequalities in obesity prevalence among working-

age adults in Scotland between 1995 and 2011

Authors: Jin Zhu1, Ngaire Coombs

1, Emmanouil Stamatakis

1 2 3

1Department of Epidemiology and Public Health, University College London, London, UK;

2Discipline of Exercise and Sport Sciences, Faculty of Health Sciences, University of

Sydney;

3Charles Perkins Centre, University of Sydney, Australia

Correspondence: Jin Zhu, Department of Epidemiology and Public Health, University

College London, 1-19 Torrington Place, London WC1E 6BT, UK.

e-mail: [email protected]; [email protected]

Tel: +44 079 1203 4453

Keywords

Obesity, Scottish Health Survey, temporal trends, socioeconomic inequalities, Index of

inequality

Word count:

Main text: 2,932

Abstract: 245

Non text material: 3 tables and 3 figures

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ABSTRACT

Background

Obesity has been an alarming public health issue in the United Kingdom. Socioeconomic

inequalities in obesity have been well studied, however limited studies addressed inequality

trends over time and none of them in Scotland.

Methods

We used nationally-representative data from the Scottish Health Survey (SHeS) across four

time points between 1995 and 2010/11. Respondents were economically active adults aged

16-65 years (N=27,059, 12,218 men). Socioeconomic position (SEP) was assessed by highest

educational qualification, occupational social class, and household income (2003 and 2010/11

only) as well as a composite SEP score. We carried out sex-stratified logistic regression

analyses (adjusted for age, smoking status, alcohol consumption, self-rated general health and

physical activity) and we computed the relative index of inequality (RII).

Results

Between 1995 and 2010/11, obesity prevalence increased in both men (from 17.0% in 1995

to 30.2% in 2010/11, 2010/11 prevalence OR of compared with 1995=2.07; 95%CI 1.83 to

2.34) and women (from 18.4% to 30.2%; OR=1.85; 95%CI 1.66 to 2.17). Increase in obesity

prevalence was observed across all socioeconomic strata, within which the most rapid

increase was amongst males from the highest socioeconomic groups. RII showed that

educational inequalities in obesity narrowed for both men (P=0.007) and women (P=0.008).

Income inequalities in obesity between 2003 and 2010/11 in women were also reduced

(P=0.046) on the relative scale.

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Conclusion:

Obesity prevalence in Scotland increased substantially between 1995 and 2010/11, although

socioeconomic inequalities have decreased due to the more rapid increase in the higher

socioeconomic strata.

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ARTICLE SUMMARY

Key messages

• Few studies have estimated changes in temporal obesity prevalence trends by

socioeconomic position (SEP) and none of them in Scottish adults. Most studies

examining the association between socioeconomic position and obesity use narrow

SEP definitions. Mixed results were reported in developed countries.

• This study found that the obesity prevalence increased considerably over the study

period (1995 to 2010/11) in the adults living in Scottish.

• Socioeconomic inequalities in obesity reduced due to more rapid increases in

prevalence among higher SEP groups.

• Among all three SEP markers (education, occupational social class and income),

education is the most consistent indicator in revealing obesity patterns.

• Although the socioeconomic gap in obesity prevalence is still substantial in the most

recent years, our results suggest that anti-obesity interventions should target all SEP

groups.

Strengths and limitations

Strengths

• Large sample drawn from nationally representative surveys over a 16 year period.

• The inclusion of multiple SEP indicators and a SEP score.

Limitations

• The response rate reduced in recent years and sample in this study could not be

weighted.

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INTRODUCTION

Obesity prevalence has doubled globally between 1980 and 2008. 1 In Great Britain, adult

obesity prevalence increased three fold between 1980 and 2002, from 6% of men and 8% of

women to 23% and 25% respectively,2 with higher prevalence in Scotland than in England.2,3

Obesity is closely associated with many morbidities and major chronic diseases including

hypertension, cardiovascular diseases, diabetes mellitus, depression and cancer.4,5 Directly or

indirectly, it is responsible for 30,000 deaths and 18 million days sickness leave annually in

the UK.5

The association between socioeconomic position (usually defined through educational

attainment, occupational class or income) and obesity is well-documented.6,7,8 A review of the

literature in 1989 reported inverse associations between socioeconomic position and obesity

for women in most studies, but mixed findings for men and children.6 Another review in 2012

found inverse associations between occupation and weight gain, with less consistent

associations for education and income.7 In developed countries, strong inverse associations

were observed between SEP and weight gain, people that are socioeconomically

disadvantaged are more likely to be obese compared to their advantaged counterparts.8

Few studies have estimated changes in obesity prevalence between socioeconomic strata over

time and none of them in Scottish adults. In the UK, Wardle and Boniface9 analyzed cross-

sectional data sets from Health Survey for England (HSE) between 1993/1994 and 2002/2003

and found a similar increase in obesity prevalence across the socioeconomic groups.

Zaninotto and colleagues10 also reported comparable increases in obesity prevalence for

manual and non-manual social classes in England between 1994 and 2004. Mixed results

were reported in non-UK developed countries. In the US, Zhang and Wang11 found that in

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spite of the overall increase in obesity prevalence in the general population between 1971 and

2000, socioeconomic disparities in obesity largely reduced over the study period. In Sweden,

a cohort study which followed up 6,069 participants for 17 years also showed a decline in

inequalities in obesity. 12 An increase in socioeconomic inequalities in obesity prevalence

was found in Belgian men between 1997 and 2004.13

Most studies examining the association between SEP and obesity use only one indicator of

SEP.10,11,14 Different SEP indicators describe different aspects of social gradient and are

differentially associated with the population obesity patterning and have different strengths

and limitations.7,15,16 Using multiple SEP indicators provides a more comprehensive picture of

how the relative position in the social ladder may be associated with obesity risk allowing

better descriptions of the socioeconomic patterning and trends in obesity. Further, composite

indicators that are structured using several SEP markers increase accuracy and reduce

measurement error compared with using individual markers.17

The aim of the study was to investigate the temporal trends in socioeconomic inequalities in

adult obesity in Scottish population between 1995 and 2010/11 using multiple socioeconomic

indicators (education, occupational social class and household income) as well as a composite

SEP score. To our knowledge, this is the first study to investigate socioeconomic inequalities

in obesity prevalence over time in the Scottish adult population.

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METHODS AND MATERIALS

Study Sample

This study uses data from the Scottish Health Survey (SHeS) conducted between 1995 and

2011. The survey design has been described in detail elsewhere.18 In summary, a nationally

representative sample was drawn from private households in Scotland using two-stage

stratified sampling with the first stage selected by postcode sectors and the second stage by

household address.19 The response rate was 81% over all in 199519 and gradually dropped to

56% in 2011.20 Analyses were performed across four distinct time points (1995, 1998, 2003

and 2010/11). 2010 and 2011 were combined due to the smaller sample size in the more

recent SHeSs. Analyses were restricted to adults aged 16 to 65 who were economically active

to allow the comparison between SEP indicators (highest education, occupational class and

income). Individuals with missing values on obesity and socioeconomic indicators were

excluded from the analysis.

Data Handling

Obesity

Height (m) and weight (kg) were measured by trained technicians. Body mass index (BMI)

was calculated by dividing weight in kilograms by height in meters squared. Obesity was

defined as a BMI ≥ 30 kg/m².21

Socioeconomic Position

We used three indicators of SEP: education level, occupational social class and household

income. Participants education levels were grouped into three levels: i) Limited/GCSE

(grouped together due to small sample size in Limited education group) – for those who

finished education at age 16 or under; ii) A Level – for those who finished education at age

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17 or 18; and iii) Tertiary – for those who finished education at 19 or over. Occupational

social class was categorized by Registrar General’s Social Class.22 Due to unequal sample

size, the participants were then collapsed into four groups of roughly comparable size: i)

Semi-skilled or unskilled manual; ii) Skilled manual; iii) Skilled non-manual; and ix)

Professional or managerial. Household income was recorded on the continuous scale from

which it was also divided into time point-specific quartiles. To examine the combined power

of the three SEP markers, we developed a composite SEP score. Like previously,23,24 the

composite SEP score was calculated by adding up scores from all three SEP markers (each of

them have four groups, coded from 0 to 3). Only a small number of respondents reported

limited education, but for the calculation of the composite SEP score limited and GCSE level

education were separated into two independent groups to make the number of categories

comparable with the other SEP indicators. This resulted in a SEP score ranging from 0 to 9.

To increase the power, the SEP score was collapsed into 4 groups to create groups of roughly

equal size. All socioeconomic variables in these analyses are coded in ascending order from

the most to the least deprived.

Demographic and Contextual variables

Information was also collected on age (years), sex, smoking status (never regular smoker, ex-

smoker, current smoker), alcohol consumption (never drank, ex-drinker, ≤once every couple

of months, 1 to 2 times a month, 1 to 4 times a week, 5 or more times a week), self-assessed

general health (very good/good, fair, bad/very bad), and self-reported physical activity (no or

yes based on if the individual meets UK physical activity guidelines). These variables have

been found to be associated with obesity2,25,26,27,28,29,30,31 and may have changed over time32 and

were therefore considered to be potential confounders. Data was also collected on ethnicity

which is also associated with obesity.33 However, due to the small ethnic minority population

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in Scotland the sample size of some ethnic minority groups in the study population were too

small (≤0.6%) to be considered as a confounder.

Statistical Methods

All analyses were conducted using statistical software STATA11 (StataCrop.2009). Previous

studies have found that socioeconomic inequalities in obesity prevalence are stronger and

more consistent in women than that in men,26,28 therefore analyses were stratified by sex.

Descriptive univariate analyses included oneway ANOVA and Chi square tests. Like in

previous analyses of this type,34,35 multiple logistic regression analyses were conducted to

investigate the independent effect of time point (1993 (referent), 1998, 2003 and 2010/11) on

the odds for obesity, which was the outcome. Model 1 adjusted for age only; model 2 was

additionally adjusted for smoking status, alcohol consumption, self-rated general health, and

self-reported physical activity; and model 3 was also adjusted for socioeconomic position

(education, occupational social class, income). Data on income was only available from 2003

onwards, therefore separate regression models were run to test the effect of income and SEP

score on the odds of obesity from SHeS 2003 to SHeS 2010/11. Between SHeS 2003 and

2010/11, in a separate model, SEP score was adjusted for instead of individual SEP

indicators.

To examine the obesity prevalence within each SEP stratum over the study survey period,

age-standardized obesity prevalence was calculated following the direct method. The overall

study sample (SHeSs 1995, 1998, 2003 and 2010/11) was used as the standard population

distribution. Temporal trends in obesity prevalence within each SEP stratum were estimated

by Chi square test and Chi square test for trends.

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To measure the magnitude of socioeconomic inequalities in obesity, Relative Index of

Inequality (RII)36,37,38,39 was calculated for each SEP marker and the SEP score. RII measures

risk ratio, it is a regression based index that compares rate of occurrence between those at the

lowest SEP level and those at the top. RII is used for making socioeconomic comparisons

over time in terms of disease prevalence or occurrence.28,36,38,40,41 In this analysis, the lowest

(most disadvantaged) SEP group was set as the reference group. One of the advantage of RII

is that it is not dependent on the comparison groups being equal or roughly equal in size.28,36

To achieve this, a Ridit-score42 was calculated as the mid-point of the cumulative distribution

of sample in each SEP stratum (percentage participants in the lower SEP level + ½

percentage participants from the next level up). For example, if the percentage of the sample

in the lowest education category was 20%, the ridit-score for this category would be 10%

(20%/2). If the percentage of the sample in the second lowest education category was 30%,

the ridit-score for this category would be 35% (20%+30%/2).36,39

Age adjusted generalized linear models (log-binomial regression) were used to model RII as

guided by Ernstsen and colleagues.39 RII was modelled by log arithmic link function. The

temporal trends of RII were assessed by adding a two way interaction term between the ridit-

score and survey years. Gender differences in SEP inequality were assessed by inserting a

two way interaction term between the ridit-score and gender. To find out if the differences in

SEP inequality between genders have changed over time, a three way interaction term was

also included in the model (the ridit-score by sex and by survey year) including all other two

interaction terms. For example, a positive significant result of the three way interaction term

would suggest a bigger increase in RII in women than in men over the study period.39

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RESULTS

Descriptive statistics

Table 1 gives the summary of characteristics of participants in each SHeS survey. The total

sample size for this study was 27,059 (12,218 men; 14,841 women). During the study period,

there was a steady increase in the mean age for both sexes. The mean BMI increased (from

26.3 to 28.0 in men and from 25.9 to 27.9 in women) as did the percentage obese (from

17.0% to 30.2% in men and from 18.4% to 30.2% in women).

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Table 1. Descriptive characteristics of participants aged 16-65 in Scottish Health Survey

1995, 1998, 2003, 2010-2011

N=27,059

Survey years

Population (%) Mean (s.d.)

SHeS1995 SHeS1998 SHeS2003 SHeS(2010/11) p

Men

N

*N

Age: Mean(s.d.)

BMI: Mean(s.d.)

*Overweight%

Obese%

3,074

41.4(12.8)

26.3(4.1)

42.6

17.0

2,935 2,259

2,044

42.4(12.8) 43.9(12.8)

26.8(4.3) 27.3(4.4)

44.5 45.3

20.0 23.9

3,950

3,485

44.3(13.0)<0.001†

28.0(4.9) <0.001†

42.1 <0.001ℓ

30.2 <0.001∂

Education%

Limited/GCSE

A level

Tertiary

67.5

14.7

17.8

63.6 57.0

14.5 16.5

21.9 26.5

<0.001‡

51.0

19.7

29.3

Occupation%

Semi/Un-skilled

Skilled manual

Skilled non-manual

Professional/Manager

22.2

36.9

10.3

30.6

22.8 21.2

35.8 31.1

10.6 10.8

30.8 36.9

<0.001‡

22.2

30.6

11.3

35.9

Household Income%

Quartile 1

Quartile2

Quartile 3

Quartile 4

−

−

−

−

− 20.2

− 19.0

− 28.5

− 32.3

<0.001‡

25.1

22.7

26.2

26.0

Women

N(1995-2011)

*N

Age: Mean(s.d.)

BMI: Mean(s.d.)

*Overweight%

Obese%

3,634

41.4(12.7)

25.9(5.0)

30.8

18.4

3,562 2,760

2,467

42.2(12.8) 44.0(12.6)

26.6(5.3) 27.3(5.7)

31.7 35.3

22.7 25.6

4,885

4,251

44.3(12.8)<0.001†

27.9(6.1)<0.001†

33.0 <0.001ℓ

30.2 <0.001∂

Education%

Limited/GCSE

A level

Tertiary

65.2

17.8

17.0

61.1 54.6

18.6 20.7

20.3 24.7

<0.001‡

46.9

23.8

29.4

Occupation%

Semi/Un-skilled

Skilled manual

Skilled non-manual


29.1

9.6

35.4

25.9

29.4 26.2

9.4 8.2

32.9 32.3

28.3 33.3

<0.001‡

26.8

7.9

29.4

35.9

Household Income%

Quartile 1

Quartile2

Quartile 3

Quartile 4

−

−

−

−

− 24.4

− 21.4

− 26.7

− 27.5

<0.001‡

27.2

24.9

24.9

23.0

*N: Population for socioeconomic position score (SEP score) analysis (SHeS2003 and SHeS2010-

2011) Note: Participants economically inactive are excluded from the analysis; *Overweight:

overweight excluding obesity; †:based on One-way analysis of variance; ℓ: based on x² test on

categorical variable with 3 BMI groups; ∂:based on x² test for trend; ‡:based on x² test

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Temporal trends in obesity

Table 2a and Table 2b present the multivariable adjusted odds ratios (ORs) and 95%

confidence intervals of obesity prevalence in men and women from 1995 to 2010/11 and

from 2003 to 2010/11 respectively. In Table 2a, after adjusting for education and

occupational social class as well as other known potential confounding factors, the odds of

being obese in 2010/11 were 2.07(1.83,2.34) higher than in 1995 for men (p<0.001) and

1.85(1.66,2.07) for women (p<0.001). As Table 2b shows, the odds of being obese in

2010/11 was 33-38% higher for male (p values <0.001) and 16% higher for female (p=0.014

and 0.018) compared to 2003, even when analyses were adjusted for household income

(Model 3a) and SEP score (Model 3b).

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Table 2. Odds ratios for obesity in men and women from 1995 to 2010/11

Table 2a.

Odds ratios for obesity ORs (95% C.I.) P value

1995-2010/11 *Model 1 †Model 2 ‡Model 3

Men

SHeS1995 1 1 1

SHeS1998 1.19(1.04,1.36)

p=0.01

1.22(1.07, 1.40)

p=0.003

1.25(1.09,1,42)

p=0.001

SHeS2003 1.44(1.25,1.65)

p <0.001

1.47(1.28,1.69)

p <0.001

1.53(1.33,1.76)

p<0.001

SHeS2010-2011 1.98(1.76,2.22)

p<0.001

1.96(1.74,2.21)

p <0.001

2.07(1.83,2.34)

p<0.001

Overall p value <0.001 <0.001 <0.001

Women

SHeS1995 1 1 1

SHeS1998 1.29(1.15,1.44)

p<0.001

1.32(1.17,1.48)

p <0.001

1.33(1.18,1.50)

p<0.001

SHeS2003 1.44(1.28,1.63)

p<0.001

1.49(1.31,1.68)

p<0.001

1.54(1.36,1.74)

p<0.001

SHeS2010-2011 1.81(1.63,2.01)

p<0.001

1.75(1.57,1.95)

p<0.001

1.85(1.66,2.07)

p<0.001

Overall p value <0.001 <0.001 <0.001

Table 2b.

Odds ratio for obesity ORs (95% C.I.) P value

2003-2010/11 *Model 1 †Model 2 ‡Model 3a ‡Model 3b

Men

SHeS2003 1 1 1 1

SHeS2010-2011 1.38(1.21,1.56)

p<0.001

1.33(1.16,1.52)

p<0.001

1.38(1.21,1.58)

p<0.001

1.33(1.17,1.52)

p<0.001

Overall p value <0.001 <0.001 <0.001 <0.001

Women

SHeS2003 1 1 1 1

SHeS2010-2011 1.23(1.10,1.38)

p<0.001

1.15(1.02,1.29)

p=0.024

1.16(1.03,1.31)

p=0.014

1.16(1.03,1.30)

p=0.018

Overall p value <0.001 <0.001 <0.001 <0.001

Table 2a: *Model 1: Adjusted for age. †Model 2: Adjusted for age, smoking status, alcohol

consumption, self-rated general health and physical activity. ‡Model 3: Adjusted for variables in

model 2 + education + occupational social class.

Table 2b: *Model 1: adjusted for age. †Model 2: Adjusted for age, smoking status, alcohol

consumption, self-rated general health and physical activity. ‡Model 3a: Adjusted for age, smoking

status, alcohol consumption, self-rated general health, physical activity, education, occupational

social class and income. ‡Model 3b: adjusted for age, smoking status, alcohol consumption, self-

rated general health, physical activity and socioeconomic position score (SEP score).

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Age standardized temporal trends of obesity prevalence by SEP indicators

Figures 1 and 2 present the age standard obesity prevalence and temporal trends by SEP

indicators for economically active Scottish men and women respectively. There was an

inverse gradient in obesity prevalence among education groups with men in higher education

groups having lower obesity prevalence (Figure 1a). Male obesity prevalence increased in all

occupational groups over the study period, with the largest increase between1998 and 2003

seen for the skilled-manual group (from 20% to 26%) and the largest increase between 2003

and 2010/11 for men doing professional/managerial jobs (from 22% to 31%) (Figure 1b).

Statically significant increases in male obesity between 2003 and 2010/11 were observed for

the top and the bottom income quartiles only (Figure 1c) and all SEP groups apart from SEP

score 2 (second most deprived) (Figure 1d). For women (Figure 2) similar results were

observed for education and occupational social class (Figures 2a and 2b). Between 2003 and

2010/11, the increase in the prevalence of female obesity by household income were not

significant apart from in income quartile 3 (p=0.001) (Figure 2c), and for composite SEP

score an increase was only seen for SEP score 3 (p<0.001) (Figure 2d).

Relative Index of Inequality (RII)

Figure 3a and 3b present the results of RII and their trends in obesity in males and females

respectively. In men, those in the highest educational category had significantly lower risks

of being obese than those in the lowest educational category in all survey years (all RIIs <1)

(Figure 3a). No difference was observed for other SEP indicators. In women, lower risks of

being obese were found for those at top SEP compared to their counterparts at the bottom for

all SEP indicators in all survey years (all RIIs <1) (Figure 3b). A reduction in inequality in

the risk of obesity over time was seen for education among both men (p=0.007) and women

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(p=0.008) between 1995 and 2010/11. A reduction in inequality in the risk of obesity was

also seen for household income among women only between 2003 and 2010/11 (p=0.046).

Sex differences

Table 3 illustrates gender differences in socioeconomic inequalities in obesity and their

changes over the study period. There was no gender difference in educational inequalities in

obesity (all p>0.05). However, there were sex differences when comparing obesity

inequalities by occupational social class, household income and SEP score (most RII p

values<0.05). The change of socioeconomic inequalities over time was similar for both men

and women on the relative scale (all p values >0.05).

Table 3. Gender differences in RII in obesity and their temporal trends

Relative Index of Inequality

*Gender

differences

SHeS1995

SHeS1998

SHeS2003

SHeS2010/2011

*Time trends

Education

0.98(0.60,1.59)

P=0.932

0.82(0.55,1.25)

P=0.362

0.89(0.60,1.33)

P=0.577

0.88(0.69,1.13)

P=0.322

0.98(0.84,1.15)

P=0.832

Occupational

social class

0.52(0.35,0.75)

P=0.001

0.77(0.55,1.08)

P=0.126

0.76(0.54,1.06)

P=0.106

0.63(0.50,0.78)

p<0.001

1.02(0.90,1.17)

P=0.722

Household

income

− − 0.45(0.31,0.64)

p<0.001

0.59(0.47,0.76)

p<0.001

1.34(0.87,2.06)

P=0.191

SEP score

− − 0.56(0.39,0.81)

P=0.002

0.59(0.46,0.75)

p<0.001

1.05(0.68,1.62)

P=0.830

*Gender differences: result from the two way interaction term – ridit score* gender

* Time trends: result from the three way interaction term – ridit score*gender*survey

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DISCUSSION

To our knowledge, this is the first study that looked at obesity prevalence and its

socioeconomic disparities over time in the Scottish adult population. Obesity prevalence in

Scotland was socioeconomically patterned throughout the study period; despite the

socioeconomic indicator used, higher SEP was associated with a lower risk of being obese.

The effect was more indicative and consistent in females which is supported by previous

studies.26,43 In men, only educational inequalities in obesity were significant (RIIs in all

years), however in women obesity inequalities were significant by all SEP indicators in all

years. Increases in obesity prevalence were greatest in recent years (2003-2010/11), among

the highest SEP groups, particularly in male occupational groups. For example between 2003

and 2010/11, the prevalence of male obesity increased by 9% in those with

professional/managerial jobs, but by only 4% in semi/un-skilled workers. On the relative

scale, socioeconomic inequalities in obesity in Scotland became narrower between

educational groups for both sexes and between income groups for females. Previous studies

in English adults did not find evidence of changes in socioeconomic differences in obesity9

but predicted a larger increase in 2012 in obesity prevalence in manual classes compared with

non-manual classes based on the trend between 1999 and 2004.10 Our study however

contradicts this. Some other studies have also found that although higher obesity prevalence

was found in low SEP groups, the prevalence of obesity was increasing fastest in higher SEP

groups.11,12,44,45

In line with the findings from previous studies in developed countries and in the UK,10,44 the

obesity prevalence in Scotland increased markedly between 1995 and 2010/11. In 1995, the

obesity prevalence was higher in women (18.4%) than in men (17.0%) which agrees with

previous findings in the UK.2 However, during the study period, there was a more rapid

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increased in obesity prevalence among men than women. By 2010/11 the prevalence of

obesity was the same for both men and women (both 30.2%). Higher male prevalence of

obesity has been reported in Norweigian adults (13% for men and 11% for women) in 2001.46

In England, similar findings were reported by Howel,47 between 1991 and 2006, male obesity

prevalence increased more than for females resulted in disappearing differences in obesity

prevalence between men and women.

The results from this study reflect that among all three SEP markers, education is the most

consistent indicator in revealing obesity patterns. In this study, inequalities in obesity were

observed between educational strata across all time points for both sexes. Significant

disparities in other SEP groups such as occupational classes and household income quartiles

were only seen in women not in men. Education is the only SEP marker that does not show

differences in predicting SEP inequalities between men and women (See Table3). The robust

effect of education is probably due to its relative stability over adult life.11,48

Strengths of the study include the large sample drawn from nationally representative surveys

over a 16 year period, giving a comprehensive picture of the prevalence, patterns,

socioeconomic inequalities and temporal trends in obesity among Scottish adults. The

inclusion of three commonly used SEP markers plus a derived SEP score allowed the

identification of trends by multiple SEP indicators. The SEP score takes consideration of

multiple aspects of socioeconomic disadvantage, hence reducing bias in the results.17

There are a few limitations to this study. The response rate reduced between 1995 (81%) and

2011 (56%) and the sample in this study could not be weighted for non-response due to the

unavailability of weight factors in the early SHeS surveys (1995 and 1998). Economically

inactive participants were excluded from the analyses to enable harmonisation of the included

datasets. As non-respondents and economically inactive participants are more likely to belong

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to lower SEP groups, and given that lower SEP groups have a higher prevalence of obesity,

38,49 the results may be prone to underestimation of overall obesity prevalence rates and for

those at lower SEP. If this is the case, reductions in SEP inequalities in obesity may have

been over estimated.

Conflicts of Interests

The authors have no conflicts of interest to declare.

Contributorship Statement

JZ designed the project, planned and conducted all analyses, wrote the first draft of the

manuscript and rewrote new drafts based on input from co-authors. NC supervised and

designed the project, planned the analyses and gave input on manuscript drafts. ES

conceived the initial idea and supervised and designed the project, planned the analyses and

gave input on manuscript drafts. All authors read and approved the final version of the

manuscript.

Acknowledgements

ES and NC are funded by the National Institute for Health Research through a Career

Development Fellowship (ES). The views expressed in this article are those of the authors

and not the English Department of Health or the National Institute for Health Research.

Ethics and data sharing

Scottish Health Survey (SHeS) has been approved by a Multi-Centre Research Ethics

Committee. SHeS data sets are publically accessible and can be downloaded from UK data

service at www.data-archive.ac.uk. No additional data available. Researchers are not required

to obtain ethical approval to carry out their studies using the data.

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176x179mm (300 x 300 DPI)

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164x176mm (300 x 300 DPI)

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164x193mm (300 x 300 DPI)

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STROBE checklist

Item

No Recommendation

Title and abstract 1 (a) Indicate the study’s design with a commonly used term in the title or the

abstract…………………………………………………..…………..Page 1

(b) Provide in the abstract an informative and balanced summary of what was

done and what was found……………………………………………Page 2

Introduction

Background/rationale 2 Explain the scientific background and rationale for the investigation being

reported………………………………………………………………Page 5-6

Objectives 3 State specific objectives, including any prespecified hypotheses…..Page 6

Methods

Study design 4 Present key elements of study design early in the paper…………Page 2, 9-10

Setting 5 Describe the setting, locations, and relevant dates, including periods of

recruitment, exposure, follow-up, and data collection………Page 7, see ref 18

Participants 6 Cross-sectional study—Give the eligibility criteria, and the sources and

methods of selection of participants………………………………….Page 7

Variables 7 Clearly define all outcomes, exposures, predictors, potential confounders, and

effect modifiers. Give diagnostic criteria, if applicable……………..Page 7-8

Data sources/

measurement

8* For each variable of interest, give sources of data and details of methods of

assessment (measurement). Describe comparability of assessment methods if

there is more than one group…………………………………………Page 7-8

Bias 9 Describe any efforts to address potential sources of bias……Page 7, See ref 18

Study size 10 Explain how the study size was arrived at……………………………Page 11

Quantitative

variables

11 Explain how quantitative variables were handled in the analyses. If applicable,

describe which groupings were chosen and why……………………..Page 7-8

Statistical methods 12 (a) Describe all statistical methods, including those used to control for

confounding…………………………………………………………..Page 9-10

(b) Describe any methods used to examine subgroups and interactions..Page 10

(c) Explain how missing data were addressed………………………….Page 7

(d)Cross-sectional study—If applicable, describe analytical methods taking

account of sampling strategy……………………………………………N/A

(e) Describe any sensitivity analyses……………………………………N/A

Continued on next page

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Results

Participants 13* (a) Report numbers of individuals at each stage of study—eg numbers potentially

eligible, examined for eligibility, confirmed eligible, included in the study, completing

follow-up, and analysed…………………………………………………………….N/A

(b) Give reasons for non-participation at each stage……………………………….N/A

(c) Consider use of a flow diagram…………………………………………………N/A

Descriptive

data

14* (a) Give characteristics of study participants (eg demographic, clinical, social) and

information on exposures and potential confounders……………………….Page 11-12

(b) Indicate number of participants with missing data for each variable of interest...N/A

(c) Cohort study—Summarise follow-up time (eg, average and total amount)…….N/A

Outcome data 15* Cross-sectional study—Report numbers of outcome events or summary measures…

……………………………………………………………………………….Page 11-12

Main results 16 (a) Give unadjusted estimates and, if applicable, confounder-adjusted estimates and

their precision (eg, 95% confidence interval). Make clear which confounders were

adjusted for and why they were included……………………………………Page 13-16

(b) Report category boundaries when continuous variables were categorized….Page 12

(c) If relevant, consider translating estimates of relative risk into absolute risk for a

meaningful time period……………………………………………………………..N/A

Other analyses 17 Report other analyses done—eg analyses of subgroups and interactions, and sensitivity

analyses…………………………………………………………………..........Page 16

Discussion

Key results 18 Summarise key results with reference to study objectives……………………..Page 17

Limitations 19 Discuss limitations of the study, taking into account sources of potential bias or

imprecision. Discuss both direction and magnitude of any potential bias….Page 18-19

Interpretation 20 Give a cautious overall interpretation of results considering objectives, limitations,

multiplicity of analyses, results from similar studies, and other relevant

evidence…………………………………………………………………….......Page 18

Generalisability 21 Discuss the generalisability (external validity) of the study results…………Page 17-18

Other information

Funding 22 Give the source of funding and the role of the funders for the present study and, if

applicable, for the original study on which the present article is based………..Page 19

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prevalence among working-age adults in Scotland between

1995 and 2011: a population-based repeated cross-

sectional study

Journal: BMJ Open

Manuscript ID: bmjopen-2014-006739.R1


Date Submitted by the Author: 25-Jan-2015

Complete List of Authors: Zhu, Jin; University College London, Department of Epidemiology and Public Health; Coombs, Ngaire; University College London, Department of Epidemiology and Public Health Stamatakis, Emmanuel; University of Sydney, Charles Perkins Centre


Epidemiology

Secondary Subject Heading: Public health, Epidemiology



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Title: Temporal trends in socioeconomic inequalities in obesity prevalence among working-

age adults in Scotland between 1995 and 2011: a population-based repeated cross-sectional

study



1 2 3



Sydney;





Tel: +44 079 1203 4453

Keywords


inequality

Word count:

Main text: 3,151

Abstract: 245


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2

ABSTRACT

Objectives




Methods








Results


to 30.2% in 2010/11, 2010/11 OR of compared with 1995=2.07; 95%CI 1.83 to 2.34) and

women (from 18.4% to 30.2%; OR=1.85; 95%CI 1.66 to 2.07). Increase in obesity

prevalence was observed across all socioeconomic strata, within which the most rapid





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Conclusion:




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ARTICLE SUMMARY

Key messages






period (1995 to 2010/11) in the adults living in Scottish.





• Although the socioeconomic gap in obesity prevalence is still substantial in the most


groups.


Strengths



Limitations


weighted.

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INTRODUCTION

In Great Britain, adult obesity prevalence increased three fold between 1980 and 2002 with

higher prevalence in Scotland than in England.1,2 Obesity is closely associated with many

morbidities and major chronic diseases including hypertension, cardiovascular diseases,

diabetes mellitus, depression and cancer.3,4








disadvantaged are more likely to be obese compared to their advantaged counterparts.7 The

socioeconomic disparities in obesity probably resulted partially from the differences in

obesity related health behaviours such as the choices of diet and levels of physical activities

between SEP strata. People from lower socioeconomic background are likely to consume

more unhealthy food such as cheaper but high energy dense food 8 but less likely to

participate in leisure time physical activity and more likely to be sedentary than their

advantages counterparts.9,10,11 Education may be linked to obesity through individual’s beliefs,

knowledge and health behaviours.12,13 Occupational status implies influences on weight

control through self-autonomy, shared peer beliefs and financial ability.13Income level

represents the material resource available for healthy food and healthy life style as well as

advantages in the access to health care. 13,14

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Studying the temporal trends of such inequalities will promote a better understanding of

potential driving force from the population level. Only few studies have estimated changes in

obesity prevalence between socioeconomic strata over time and none of them in Scottish

adults. In the UK, Wardle and Boniface15 analyzed cross-sectional data sets from Health

Survey for England (HSE) between 1993/1994 and 2002/2003 and found a similar increase in

obesity prevalence across the socioeconomic groups on the absolute scale. Zaninotto and

colleagues16 also reported comparable increases in obesity prevalence for manual and non-

manual social classes but predicted a widening inequality trend based on the extrapolation of

linear trend in England between 1993 and 2004. Mixed results were reported in non-UK

developed countries. In the US, Zhang and Wang17 found that in spite of the overall increase

in obesity prevalence in the general population between 1971 and 2000, socioeconomic

disparities in obesity largely reduced over the study period on both absolute and relative

scale. In Sweden, a cohort study which followed up 6,069 participants for 17 years also

showed a decline in inequalities in obesity based on concentration index. 18 A relative increase

in socioeconomic inequalities in obesity prevalence was found in Belgian men between 1997

and 2004.19









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SEP score. It is hypothesized that socioeconomic inequalities in adult obesity widened

throughout the study period in Scotland. This article is going to investigate the overall trends

in adult obesity prevalence in Scotland between 1995 and 2010/2011 and temporal trends in

each socioeconomic group as well as in inequalities between SEP groups by commonly used

SEP indicators and a derived SEP score. Gender difference is also going to be analyzed.

To our knowledge, this is the first study to investigate socioeconomic inequalities in obesity

prevalence over time in the Scottish adult population.

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Study Sample



representative sample was drawn from private households in Scotland using two-stage

stratified sampling with the first stage selected by postcode sectors and the second stage by

household address.25 The response rate was 81% over all in 199525 and gradually dropped to

56% in 2011.26 Analyses were performed across four distinct time points (1995, 1998, 2003

and 2010/11). 2010 and 2011 were combined due to the smaller sample size in the more

recent SHeSs. Analyses were restricted to adults aged 16 to 65 who were economically active

to allow the comparison between SEP indicators (highest education, occupational class and

income). Non-respondents and unemployed are excluded from the study, given that they are

more likely to belong to lower SEP groups and have a higher prevalence of obesity, 27,28 the

results may be prone to underestimation of overall obesity prevalence rates and for those at

lower SEP. In this study, non-respondents and unemployed are only 6.7% within the study

sample, other socioeconomic indicators also have missing value are education (2.6%) and

income (13.8%). BMI is not available in 12.3% of study population. The final sample

includes 27,059 men and women, a total 18.5% sample reduction. Details of missing value

are included in S1-Supplementary Table 1.

Data Handling

Obesity




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income. Participants education levels were grouped into three levels: i) Limited/GCSE

(grouped together due to small sample size in Limited education group) – for those who

finished education at age 16 or under; ii) A Level – for those who finished education at age

17 or 18; and iii) Tertiary – for those who finished education at 19 or over. Occupational

social class was categorized by Registrar General’s Social Class.30 Due to unequal sample

size, the participants were then collapsed into four groups of roughly comparable size: i)

Semi-skilled or unskilled manual; ii) Skilled manual; iii) Skilled non-manual; and ix)

Professional or managerial. Household income was recorded on the continuous scale from

which it was also divided into time point-specific quartiles. To examine the combined power

of the three SEP markers, we developed a composite SEP score. Like previously,11,31 the

composite SEP score was calculated by adding up scores from all three SEP markers (each of

them have four groups, coded from 0 to 3). Only a small number of respondents reported

limited education, but for the calculation of the composite SEP score limited and GCSE level

education were separated into two independent groups to make the number of categories

comparable with the other SEP indicators. This resulted in a SEP score ranging from 0 to 9.

To increase the power, the SEP score was collapsed into 4 groups to create groups of roughly

equal size. All socioeconomic variables in these analyses are coded in ascending order from

the most to the least deprived.




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Statistical Methods







the odds for obesity, which was the outcome. Model 1 adjusted for age only; model 2 was

additionally adjusted for smoking status, alcohol consumption, self-rated general health, and

self-reported physical activity; and model 3 was also adjusted for socioeconomic position





indicators.

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Inequality (RII) and Slope Index of Inequality (SII)27,42,43,44 were calculated for each SEP

marker and the SEP score. RII and SII measure risk ratio and risk difference respectively,

they are regression based index that compare rate of occurrence between those at the lowest

SEP level and those at the top. They are used for making socioeconomic comparisons over

time in terms of disease prevalence or occurrence.27,34,42,45,46 In this analysis, the lowest (most

disadvantaged) SEP group was set as the reference group instead of the highest.34,44 One of the

advantages of RII and SII is that it is not dependent on the comparison groups being equal or

roughly equal in size.34,42 To achieve this, a Ridit-score47 was calculated as the mid-point of

the cumulative distribution of sample in each SEP stratum (percentage participants in the

lower SEP level + ½ percentage participants from the next level up). For example, if the

percentage of the sample in the lowest education category was 20%, the ridit-score for this

category would be 10% (20%/2). If the percentage of the sample in the second lowest

education category was 30%, the ridit-score for this category would be 35%

(20%+30%/2).42,44 There was no significant trend emerged for SII over the study years.

Relevant methods and results of SII are shown in S2-Supplementary Document and S3-

Supplementary Figure 1.

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two way interaction term between the ridit-score and gender. To find out if the differences in


also included in the model (the ridit-score by sex and by survey year) including all other two



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RESULTS







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1995, 1998, 2003, 2010-2011

N=27,059

Survey years



Men

N

*N

Age: Mean(s.d.)

BMI: Mean(s.d.)

*Overweight%

Obese%

3,074

41.4(12.8)

26.3(4.1)

42.6

17.0

2,935 2,259

2,044

42.4(12.8) 43.9(12.8)

26.8(4.3) 27.3(4.4)

44.5 45.3

20.0 23.9

3,950

3,485

44.3(13.0)<0.001†

28.0(4.9) <0.001†

42.1 <0.001ℓ

30.2 <0.001∂

Education%

Limited/GCSE

A level

Tertiary

67.5

14.7

17.8

63.6 57.0

14.5 16.5

21.9 26.5

<0.001‡

51.0

19.7

29.3

Occupation%

Semi/Un-skilled

Skilled manual

Skilled non-manual


22.2

36.9

10.3

30.6

22.8 21.2

35.8 31.1

10.6 10.8

30.8 36.9

<0.001‡

22.2

30.6

11.3

35.9

Household Income%

Quartile 1

Quartile2

Quartile 3

Quartile 4

−

−

−

−

− 20.2

− 19.0

− 28.5

− 32.3

<0.001‡

25.1

22.7

26.2

26.0

Women

N(1995-2011)

*N

Age: Mean(s.d.)

BMI: Mean(s.d.)

*Overweight%

Obese%

3,634

41.4(12.7)

25.9(5.0)

30.8

18.4

3,562 2,760

2,467

42.2(12.8) 44.0(12.6)

26.6(5.3) 27.3(5.7)

31.7 35.3

22.7 25.6

4,885

4,251

44.3(12.8)<0.001†

27.9(6.1)<0.001†

33.0 <0.001ℓ

30.2 <0.001∂

Education%

Limited/GCSE

A level

Tertiary

65.2

17.8

17.0

61.1 54.6

18.6 20.7

20.3 24.7

<0.001‡

46.9

23.8

29.4

Occupation%

Semi/Un-skilled

Skilled manual

Skilled non-manual


29.1

9.6

35.4

25.9

29.4 26.2

9.4 8.2

32.9 32.3

28.3 33.3

<0.001‡

26.8

7.9

29.4

35.9

Household Income%

Quartile 1

Quartile2

Quartile 3

Quartile 4

−

−

−

−

− 24.4

− 21.4

− 26.7

− 27.5

<0.001‡

27.2

24.9

24.9

23.0





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Table 2a.



Men

SHeS1995 1 1 1

SHeS1998 1.19(1.04,1.36)

p=0.01

1.22(1.07, 1.40)

p=0.003

1.25(1.09,1,42)

p=0.001

SHeS2003 1.44(1.25,1.65)

p <0.001

1.47(1.28,1.69)

p <0.001

1.53(1.33,1.76)

p<0.001

SHeS2010-2011 1.98(1.76,2.22)

p<0.001

1.96(1.74,2.21)

p <0.001

2.07(1.83,2.34)

p<0.001

Overall p value <0.001 <0.001 <0.001

Women

SHeS1995 1 1 1

SHeS1998 1.29(1.15,1.44)

p<0.001

1.32(1.17,1.48)

p <0.001

1.33(1.18,1.50)

p<0.001

SHeS2003 1.44(1.28,1.63)

p<0.001

1.49(1.31,1.68)

p<0.001

1.54(1.36,1.74)

p<0.001

SHeS2010-2011 1.81(1.63,2.01)

p<0.001

1.75(1.57,1.95)

p<0.001

1.85(1.66,2.07)

p<0.001

Overall p value <0.001 <0.001 <0.001

Table 2b.



Men

SHeS2003 1 1 1 1

SHeS2010-2011 1.38(1.21,1.56)

p<0.001

1.33(1.16,1.52)

p<0.001

1.38(1.21,1.58)

p<0.001

1.33(1.17,1.52)

p<0.001

Overall p value <0.001 <0.001 <0.001 <0.001

Women

SHeS2003 1 1 1 1

SHeS2010-2011 1.23(1.10,1.38)

p<0.001

1.15(1.02,1.29)

p=0.024

1.16(1.03,1.31)

p=0.014

1.16(1.03,1.30)

p=0.018

Overall p value <0.001 <0.001 <0.001 <0.001


consumption, self-rated general health and physical acKvity. ‡Model 3: Adjusted for variables in



consumption, self-rated general health and physical acKvity. ‡Model 3a: Adjusted for age, smoking




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(p=0.008) between 1995 and 2010/11 as well as for household income among women only

between 2003 and 2010/11 (p=0.046).

Sex differences









*Gender

differences

SHeS1995

SHeS1998

SHeS2003

SHeS2010/2011

*Time trends

Education

0.98(0.60,1.59)

P=0.932

0.82(0.55,1.25)

P=0.362

0.89(0.60,1.33)

P=0.577

0.88(0.69,1.13)

P=0.322

0.98(0.84,1.15)

P=0.832

Occupational

social class

0.52(0.35,0.75)

P=0.001

0.77(0.55,1.08)

P=0.126

0.76(0.54,1.06)

P=0.106

0.63(0.50,0.78)

p<0.001

1.02(0.90,1.17)

P=0.722

Household

income

− − 0.45(0.31,0.64)

p<0.001

0.59(0.47,0.76)

p<0.001

1.34(0.87,2.06)

P=0.191

SEP score

− − 0.56(0.39,0.81)

P=0.002

0.59(0.46,0.75)

p<0.001

1.05(0.68,1.62)

P=0.830



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DISCUSSION


socioeconomic disparities over time in the Scottish adult population. The results of this study

provided evidence for the broad audience including public health researchers, policy makers,

health care service providers in inspiring future research studies, shaping health care policies

and services as well as re-structuring living environment that aims to target the current obese

epidemic from the population level. Obesity prevalence in Scotland was socioeconomically

patterned throughout the study period; higher SEP was associated with a lower risk of being

obese. On the relative scale, socioeconomic inequalities in obesity in Scotland became

narrower between educational groups for both sexes and between income groups for females.

This is due to the greater increase in obesity prevalence among the highest SEP groups in

recent years (2003-2010/11). Previous experience of targeting obesity prevalence such as

promoting healthy diet and encouraging physical activity focused on lower SEP groups.48 The

results of this study suggest that the effectiveness of current policies and measures in

Scotland needs to be re-assessed to target the obese epidemic from population level including

those economically better-off.


obesity prevalence in Scotland increased markedly between 1995 and 2010/11. Population

aging probably explains part of the reason. During study period, male obesity prevalence

increased faster (from17% to 30.2%) than for females (from 18.4% to 30.2%). The SEP

inequalities in obesity were more indicative and consistent in females (significant by all SEP

indicators in all years) than in male (only educational inequalities in obesity were significant:

RIIs in all years). Gender difference is probably resulted from differences in environment,

beliefs, work stress, peer pressure etc., such as in high SEP groups female concern more

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about their weight gain than their male counterparts and in manual group physical demand is

much higher in male while not exact the same for female.13 Further studies are needed to

investigate the exact determinants.


consistent indicator in revealing obesity patterns. Education is the only SEP marker that does

not show differences in predicting SEP inequalities between men and women (See Table3).

The robust effect of education is probably due to its relative stability over adult life, easy to

collect, less missing value and less measurement bias.17,49









unavailability of weight factors in the early SHeS surveys (1995 and 1998). A small

proportion of non-respondents and unemployed (6.7%) were excluded from the analyses that

might cause underestimation of obesity prevalence for those at lower SEP and over

estimation of the reduction in SEP inequalities in obesity.

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manuscript.

Acknowledgements









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164x171mm (300 x 300 DPI)

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S1: Supplementary Table 1: Missing Value for SHeSs 1995-2011 (Scottish adults 16-65 years)

SHeSs 1995-

2011

Age: 16-65 yrs

1995 1998 2003 2010 2011 Total

Sample Size

Missing Value

(%)

Sample Size

Missing Value

(%)

Sample Size

Missing Value

(%)

Sample Size

Missing Value

(%)

Sample Size

Missing Value

(%)

Sample Size

Missing Value

(%)

Sample size 7,932 7,737 6,326 5,504 5,721 33,220

17,551(Income)

Sample size for

analysis

Miss value (%)

6,708

1,224(15.4%)

6,497

1,240(16.0%)

5,019

1,307(20.7%)

4,348

1,156(21.0%)

4,487

1,234(21.6)

27,059

6,161(18.5%)

Age 7,932 7,737 6,326 5,504 5,721 33,220

Sex: Male

Female

3,524

4,408

3,433

4,304

2,812

3,514

2,352

3,152

2,475

3,246

33,220

BMI

Missing Value

(%)

7,308

624 (7.9%)

7,009

728(9.4%)

5,351

975(15.4%)

4,678

826(15%)

4,792

929(16.2%)

29,138

4,082(12.3%)

Education

Missing value

(%)

7,772

160(2.0%)

7,567

170(2.2%)

6,129

197(3.1%)

5,340

164(3.0%)

5,561

160(2.8%)

32,369

851(2.6%)

Occupation

Missing value

(%)

7,288

644(8.1%)

7,170

567(7.3%)

6,017

309(4.9%)

5,190

314(5.7%)

5,423

298(5.2%)

31,088

2,212(6.7%)

Income

Missing value

(%)

Not available Not available 5,597

729(11.5%)

4,723

781(14.2%)

4,801

920(16.1%)

15,121

2,430(13.8%)

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S2: Supplementary Document (SII)

Slope Index of Inequality (SII)

Age adjusted generalized linear models (log-binomial regression) were used to model SII

adjusted for age, stratified by gender and survey years. SII was modelled by identity link

function. S3-Supplementary Figures 1a and 1b give the results of Slope Index of Inequalities

(SII) as well as their trends over study years in men and women. SII indicates Risk Difference

(RD) between SEP extremities. P<0.05 means a marked more (RD>0) or less (RD<0) risk of

being obese for those at the top SEP than their counterparts at the bottom. A significant p

value for trends means a noticed narrowed or widened gap between the top and the

bottom SEP in obesity risk over time on an absolute scale.

The results from Supplementary Figure 1a show that, In Scotland, men at the highest SEP

were found with less percentage of obese individuals when compared to their counterparts

in the lowest SEP level. The SII for male was only significant when measured by education

but not by occupational class, household income or SEP score. The results from

Supplementary Figure 1b suggest a significant reduction in obesity in absolute numbers for

Scottish women at top level SEP compared to their counterparts at the bottom in all survey

years by all four SEP markers. There was no significant trend emerged for SII over the study

years for either genders which means the socioeconomic inequalities in obesity was not

changed on the absolute scale for both genders over the study survey period.

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167x193mm (300 x 300 DPI)

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STROBE checklist

Item

No Recommendation


abstract…………………………………………………..…………..Page 1


done and what was found……………………………………………Page 2-3

Introduction


reported………………………………………………………………Page 5-6


Methods








Data sources/

measurement






Quantitative

variables


describe which groupings were chosen and why…………………..Page 10-12


confounding………………………………………………………….Page 10-12







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Results






Descriptive

data



(b) Indicate number of participants with missing data for each variable of

interest……………………………………………………………………………Page 8



……………………………………………………………………………….Page 15-18




(b) Report category boundaries when continuous variables were categorized..Page 9,14




analyses…………………………………………………………………..........Page 17

Discussion



imprecision. Discuss both direction and magnitude of any potential bias…....Page 8, 20



evidence……………………………………………………………………...Page 19-20


Other information



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prevalence among economically-active working-age adults

in Scotland between 1995 and 2011: a population-based

repeated cross-sectional study

Journal: BMJ Open

Manuscript ID: bmjopen-2014-006739.R2


Date Submitted by the Author: 19-Mar-2015

Complete List of Authors: Zhu, Jin; University College London, Department of Epidemiology and Public Health; Coombs, Ngaire; University College London, Department of Epidemiology and Public Health Stamatakis, Emmanuel; University of Sydney, Charles Perkins Centre


Epidemiology

Secondary Subject Heading: Public health, Epidemiology



BMJ Open on D



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1

Title: Temporal trends in socioeconomic inequalities in obesity prevalence among

economically-active working-age adults in Scotland between 1995 and 2011: a population-

based repeated cross-sectional study



1 2 3



Sydney;





Tel: +44 079 1203 4453

Keywords


inequality

Word count:

Main text: 3,207

Abstract: 248


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2

ABSTRACT

Objectives




Methods








Results


to 30.2% in 2010/11, 2010/11 Odds Ratio (OR) of obesity compared with 1995=2.07; 95%CI

1.83 to 2.34) and women (from 18.4% to 30.2%; OR=1.85; 95%CI 1.66 to 2.07). Increase in

obesity prevalence was observed across all socioeconomic strata, within which the most rapid





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3

Conclusion:




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4

ARTICLE SUMMARY

Key messages






period (1995 to 2010/11) in the adults living in Scotland.





• Although the socioeconomic gap in obesity prevalence is still substantial in most


groups.


Strengths



Limitations


weighted.

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5

INTRODUCTION

In Great Britain, adult obesity prevalence increased three fold between 1980 and 2002 with

higher prevalence in Scotland than in England.1,2 Obesity is closely associated with many

morbidities and major chronic diseases including hypertension, cardiovascular diseases,

diabetes mellitus, depression and cancer.3,4








disadvantaged are more likely to be obese compared to their advantaged counterparts.7 The

socioeconomic disparities in obesity arguably resulted partially from the differences in

obesity related health behaviours such as the choices of diet and levels of physical activities

between SEP strata. People from lower socioeconomic background are likely to consume

more unhealthy food such as cheaper but high energy dense food 8 but less likely to

participate in leisure time physical activity and more likely to be sedentary than their

advantaged counterparts.9,10,11 Education may be linked to obesity through individual’s beliefs,

knowledge and health behaviours.12,13 Occupational status implies influences on weight

control through self-autonomy, shared peer beliefs and financial ability.13Income level

represents the material resource available for healthy food and healthy life style as well as

advantages in the access to health care. 13,14

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Studying the temporal trends of such inequalities will promote a better understanding of

potential driving force from the population level. Only few studies have estimated changes in

obesity prevalence between socioeconomic strata over time and none of them in Scottish

adults. In the UK, Wardle and Boniface15 analyzed cross-sectional data sets from Health

Survey for England (HSE) between 1993/1994 and 2002/2003, they found a similar increase

in obesity prevalence across the socioeconomic groups on the absolute scale. Zaninotto and

colleagues16 also reported comparable increases in obesity prevalence for manual and non-

manual social classes but predicted a widening inequality trend based on the extrapolation of

linear trend in England between 1993 and 2004. Mixed results were reported in non-UK

developed countries. In the US, Zhang and Wang17 found that in spite of the overall increase

in obesity prevalence in the general population between 1971 and 2000, socioeconomic

disparities in obesity largely reduced over the study period on both absolute and relative

scale. In Sweden, a cohort study which followed up 6,069 participants for 17 years also

showed a decline in inequalities in obesity based on concentration index. 18 A relative increase

in socioeconomic inequalities in obesity prevalence was found in Belgian men between 1997

and 2004.19









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SEP score. It is hypothesized that socioeconomic inequalities in adult obesity have widened

throughout the study period in Scotland. This article is going to investigate the overall trends

in adult obesity prevalence in Scotland between 1995 and 2010/2011 and temporal trends in

each socioeconomic group as well as in inequalities between SEP groups by commonly used

SEP indicators and a derived SEP score. Gender difference is also going to be analyzed.

To our knowledge, this is the first study to investigate socioeconomic inequalities in obesity

prevalence over time in the Scottish adult population.

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8


Study Sample



representative sample was drawn from private households in Scotland using a two-stage

stratified sampling system with the first stage selected by postcode sectors and the second

stage by household address.25 The response rate was 81% over all in 199525 and gradually

dropped to 56% in 2011.26 Analyses were performed across four distinct time points (1995,

1998, 2003 and 2010/11). 2010 and 2011 were combined due to the smaller sample size in

the more recent SHeSs. Analyses were restricted to adults aged 16 to 65 who were

economically active to allow the comparison between SEP indicators (highest education,

occupational class and income). Non-respondents, refused and armed forces are excluded

from the study, given that these numbers include unemployed, and unemployed are more

likely to belong to lower SEP groups and have a higher prevalence of obesity, 27,28 the results

may be prone to underestimation of overall obesity prevalence rates and for those at lower

SEP. In this study, total missing value including unemployed for occupational social class is

only 6.7% within the study sample. These are population based surveys over 16 years period

with large sample sizes, the affect of excluding unemployed makes minimal impact, therefore

study results are deemed robust. Other socioeconomic indicators also have missing value are

education (2.6%) and income (13.8%). BMI is not available in 12.3% of study population.

The final sample includes 27,059 men and women, a total 18.5% sample reduction. Details of

missing value are included in S1-Supplementary Table 1.

Data Handling

Obesity

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9






income. Participants education levels were grouped into three levels: i) Limited/Standard

Grade (grouped together due to small sample size in Limited education group) – for those

who finished education at age 16 or under; ii) Higher/Advanced Higher – for those who

finished education at age 17 or 18; and iii) Tertiary – for those who finished education at 19

or over. Occupational social class was categorized by Registrar General’s Social Class.30 Due

to unequal sample size, the participants were then collapsed into four groups of roughly

comparable size: i) Semi-skilled or unskilled manual; ii) Skilled manual; iii) Skilled non-

manual; and iv) Professional or managerial. Household income was recorded on the

continuous scale from which it was also divided into time point-specific quartiles. To

examine the combined power of the three SEP markers, we developed a composite SEP

score. Like previously,11,31 the composite SEP score was calculated by adding up scores from

all three SEP markers (each of them have four groups, coded from 0 to 3). Only a small

number of respondents reported limited education, but for the calculation of the composite

SEP score limited and Standard Grade level education were separated into two independent

groups to make the number of categories comparable with the other SEP indicators. This

resulted in a SEP score ranging from 0 to 9. To increase the power, the SEP score was

collapsed into 4 groups to create groups of roughly equal size. All socioeconomic variables in

these analyses are coded in ascending order from the most to the least deprived.

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10












Statistical Methods







the odds for obesity, which was the outcome. Model 1 was adjusted for age only; model 2

was additionally adjusted for smoking status, alcohol consumption, self-rated general health,

and self-reported physical activity; and model 3 was also adjusted for socioeconomic position




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indicators.







Inequality (RII) and Slope Index of Inequality (SII)27,42,43,44 were calculated for each SEP

marker and the SEP score. RII and SII measure risk ratio and risk difference respectively,

they are regression based index that compare rate of occurrence between those at the lowest

SEP level and those at the top. They are used for making socioeconomic comparisons over

time in terms of disease prevalence or occurrence.27,34,42,45,46 In this analysis, the lowest (most

disadvantaged) SEP group was set as the reference group instead of the highest.34,44 One of the

advantages of RII and SII is that it is not dependent on the comparison groups being equal or

roughly equal in size.34,42 To achieve this, a Ridit-score47 was calculated as the mid-point of

the cumulative distribution of sample in each SEP stratum (percentage participants in the

lower SEP level + ½ percentage participants from the next level up). For example, if the

percentage of the sample in the lowest education category was 20%, the Ridit-score for this

category would be 10% (20%/2). If the percentage of the sample in the second lowest

education category was 30%, the Ridit-score for this category would be 35%

(20%+30%/2).42,44 There was no significant trend emerged for SII over the study years.

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Relevant methods and results of SII are shown in S2-Supplementary Document and S3-

Supplementary Figure 1.





two way interaction term between the Ridit-score and gender. To find out if the differences in


also included in the model (the Ridit-score by sex and by survey year) including all other two



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13

RESULTS







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14


1995, 1998, 2003, 2010-2011

N=27,059

Survey years



Men

N

*N

Age: Mean(s.d.)

BMI: Mean(s.d.)

*Overweight%

Obese%

3,074

41.4(12.8)

26.3(4.1)

42.6

17.0

2,935 2,259

2,044

42.4(12.8) 43.9(12.8)

26.8(4.3) 27.3(4.4)

44.5 45.3

20.0 23.9

3,950

3,485

44.3(13.0)<0.001†

28.0(4.9) <0.001†

42.1 <0.001ℓ

30.2 <0.001∂

Education%

Limited/Standard Grade

Higher/Advanced Higher

Tertiary

67.5

14.7

17.8

63.6 57.0

14.5 16.5

21.9 26.5

<0.001‡

51.0

19.7

29.3

Occupation%

Semi/Un-skilled

Skilled manual

Skilled non-manual


22.2

36.9

10.3

30.6

22.8 21.2

35.8 31.1

10.6 10.8

30.8 36.9

<0.001‡

22.2

30.6

11.3

35.9

Household Income%

Quartile 1

Quartile2

Quartile 3

Quartile 4

−

−

−

−

− 20.2

− 19.0

− 28.5

− 32.3

<0.001‡

25.1

22.7

26.2

26.0

Women

N(1995-2011)

*N

Age: Mean(s.d.)

BMI: Mean(s.d.)

*Overweight%

Obese%

3,634

41.4(12.7)

25.9(5.0)

30.8

18.4

3,562 2,760

2,467

42.2(12.8) 44.0(12.6)

26.6(5.3) 27.3(5.7)

31.7 35.3

22.7 25.6

4,885

4,251

44.3(12.8)<0.001†

27.9(6.1)<0.001†

33.0 <0.001ℓ

30.2 <0.001∂

Education%

Limited/Standard Grade

Higher/Advanced Higher

Tertiary

65.2

17.8

17.0

61.1 54.6

18.6 20.7

20.3 24.7

<0.001‡

46.9

23.8

29.4

Occupation%

Semi/Un-skilled

Skilled manual

Skilled non-manual


29.1

9.6

35.4

25.9

29.4 26.2

9.4 8.2

32.9 32.3

28.3 33.3

<0.001‡

26.8

7.9

29.4

35.9

Household Income%

Quartile 1

Quartile2

Quartile 3

Quartile 4

−

−

−

−

− 24.4

− 21.4

− 26.7

− 27.5

<0.001‡

27.2

24.9

24.9

23.0





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15











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Table 2a.



Men

SHeS1995 1 1 1

SHeS1998 1.19(1.04,1.36)

p=0.01

1.22(1.07, 1.40)

p=0.003

1.25(1.09,1,42)

p=0.001

SHeS2003 1.44(1.25,1.65)

p <0.001

1.47(1.28,1.69)

p <0.001

1.53(1.33,1.76)

p<0.001

SHeS2010-2011 1.98(1.76,2.22)

p<0.001

1.96(1.74,2.21)

p <0.001

2.07(1.83,2.34)

p<0.001

Overall p value <0.001 <0.001 <0.001

Women

SHeS1995 1 1 1

SHeS1998 1.29(1.15,1.44)

p<0.001

1.32(1.17,1.48)

p <0.001

1.33(1.18,1.50)

p<0.001

SHeS2003 1.44(1.28,1.63)

p<0.001

1.49(1.31,1.68)

p<0.001

1.54(1.36,1.74)

p<0.001

SHeS2010-2011 1.81(1.63,2.01)

p<0.001

1.75(1.57,1.95)

p<0.001

1.85(1.66,2.07)

p<0.001

Overall p value <0.001 <0.001 <0.001

Table 2b.



Men

SHeS2003 1 1 1 1

SHeS2010-2011 1.38(1.21,1.56)

p<0.001

1.33(1.16,1.52)

p<0.001

1.38(1.21,1.58)

p<0.001

1.33(1.17,1.52)

p<0.001

Overall p value <0.001 <0.001 <0.001 <0.001

Women

SHeS2003 1 1 1 1

SHeS2010-2011 1.23(1.10,1.38)

p<0.001

1.15(1.02,1.29)

p=0.024

1.16(1.03,1.31)

p=0.014

1.16(1.03,1.30)

p=0.018

Overall p value <0.001 <0.001 <0.001 <0.001


consumption, self-rated general health and physical acJvity. ‡Model 3: Adjusted for variables in



consumption, self-rated general health and physical acJvity. ‡Model 3a: Adjusted for age, smoking




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(p=0.008) between 1995 and 2010/11 as well as for household income among women only

between 2003 and 2010/11 (p=0.046).

Sex differences









*Gender

differences

SHeS1995

SHeS1998

SHeS2003

SHeS2010/2011

*Time trends

Education

0.98(0.60,1.59)

P=0.932

0.82(0.55,1.25)

P=0.362

0.89(0.60,1.33)

P=0.577

0.88(0.69,1.13)

P=0.322

0.98(0.84,1.15)

P=0.832

Occupational

social class

0.52(0.35,0.75)

P=0.001

0.77(0.55,1.08)

P=0.126

0.76(0.54,1.06)

P=0.106

0.63(0.50,0.78)

p<0.001

1.02(0.90,1.17)

P=0.722

Household

income

− − 0.45(0.31,0.64)

p<0.001

0.59(0.47,0.76)

p<0.001

1.34(0.87,2.06)

P=0.191

SEP score

− − 0.56(0.39,0.81)

P=0.002

0.59(0.46,0.75)

p<0.001

1.05(0.68,1.62)

P=0.830



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DISCUSSION


socioeconomic disparities over time in the Scottish adult population. Obesity prevalence in

Scotland was socioeconomically patterned throughout the study period; higher SEP was

associated with a lower risk of being obese. Previous experience of targeting obesity

prevalence such as promoting healthy diet and encouraging physical activity focused on

lower SEP groups.48 The results of this study provided evidence for the broad audience

including public health researchers, policy makers, health care service providers in inspiring

future research studies, shaping health care policies and services as well as re-structuring

living environment that aims to target the current obese epidemic from the population level.

On the relative scale, socioeconomic inequalities in obesity in Scotland became narrower

between educational groups for both sexes and between income groups for females. This is

due to the greater increase in obesity prevalence among the highest SEP groups in recent

years (2003-2010/11). Such results suggest that the effectiveness of current policies and

measures in Scotland needs to be re-assessed to target the obese epidemic from population

level including those economically better-off.


obesity prevalence in Scotland increased markedly between 1995 and 2010/11. Population

aging probably explains part of the reason. During study period, male obesity prevalence

increased faster (from17% to 30.2%) than for females (from 18.4% to 30.2%). The SEP

inequalities in obesity were more indicative and consistent in females (significant by all SEP

indicators in all years) than in male (only educational inequalities in obesity were significant:

RIIs in all years). Gender difference is probably resulted from differences in environment,

beliefs, work stress, peer pressure etc., such as in high SEP groups female concern more

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about their weight gain than their male counterparts and in manual group physical demand is

much higher in male while not exact the same for female.13 Further studies are needed to

investigate the exact determinants.


consistent indicator in revealing obesity patterns. Education is the only SEP marker that does

not show differences in predicting SEP inequalities between men and women (See Table3).

The robust effect of education is probably due to its relative stability over adult life, easy to

collect, less missing value and less measurement bias.17,49









unavailability of weight factors in the early SHeS surveys (1995 and 1998). S1-

Supplementary Table 1 shows a total 18.5% of sample reduction mainly from missing values

in BMI and income. Missing value in occupational social class includes unemployed (6.7%)

might cause underestimation of obesity prevalence for those at lower SEP and over

estimation of the reduction in SEP inequalities in obesity.

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manuscript.

Acknowledgements









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REFERENCES




Obesity Forum 2003









8. Galobardes B, Morabia A, Bernstein M. Diet and socioeconomic position: does the

use of different indicator matter? International Epidemiological Association 2001; 30:

334-340.









Community Health. 2009; 63(9): 734-740.

12. Duncan GJ, PhD, Daly MC, McDonough P, Williams DR. Optimal Indicators of

Socioeconomic Status for Health Research. American Journal of Public Health 2002;

92(7): 1151-1157.



1299-1304.

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14. Winkleby MA, Jatulis DE, Frank E, Fortmann SP. Socioeconomic status and health:

how education, income, and occupation contribute to risk factors for cardiovascular

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1997; 349: 1655-1659.




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Medicine 2008; 358(23):2468.






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Biostatistics 2006; 7(2): 213–224.



87-103.







765.






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Medicine 2010; 70: 221–231.



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Figure 1. Age-standardized temporal trends of obesity prevalence in Scottish men aged 16 to 65 years (95% C.I.)

171x178mm (300 x 300 DPI)

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Figure 2. Age-standardized temporal trends of obesity prevalence in Scottish women aged 16 to 65 years (95% C.I.)

167x183mm (300 x 300 DPI)

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RII

164x193mm (300 x 300 DPI)

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S1: Supplementary Table 1: Missing Value for SHeSs 1995-2011 (Scottish adults 16-65 years)

SHeSs 1995-2011 Age: 16-65 yrs

1995 1998 2003 2010 2011 Total

Sample Size Missing Value (%)






Sample size 7,932 7,737 6,326 5,504 5,721 33,220 17,551(Income)

Sample size for analysis Miss value (%)

6,708 1,224(15.4%)

6,497 1,240(16.0%)

5,019 1,307(20.7%)

4,348 1,156(21.0%)

4,487 1,234(21.6)

27,059 6,161(18.5%)

Age 7,932 7,737 6,326 5,504 5,721 33,220

Sex: Male Female

3,524 4,408

3,433 4,304

2,812 3,514

2,352 3,152

2,475 3,246

33,220

BMI Missing Value (%)

7,308 624 (7.9%)

7,009 728(9.4%)

5,351 975(15.4%)

4,678 826(15%)

4,792 929(16.2%)

29,138 4,082(12.3%)

Education Missing value (%)

7,772 160(2.0%)

7,567 170(2.2%)

6,129 197(3.1%)

5,340 164(3.0%)

5,561 160(2.8%)

32,369 851(2.6%)

Occupation Missing value (%)

7,288 644(8.1%)

7,170 567(7.3%)

6,017 309(4.9%)

5,190 314(5.7%)

5,423 298(5.2%)

31,088 2,212(6.7%)

Income Missing value (%)

Not available Not available 5,597 729(11.5%)

4,723 781(14.2%)

4,801 920(16.1%)

15,121 2,430(13.8%)

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S2: Supplementary Document (SII)

Slope Index of Inequality (SII)

Age adjusted generalized linear models (log-binomial regression) were used to model SII

adjusted for age, stratified by gender and survey years. SII was modelled by identity link

function. S3-Supplementary Figures 1a and 1b give the results of Slope Index of Inequalities

(SII) as well as their trends over study years in men and women. SII indicates Risk Difference

(RD) between SEP extremities. P<0.05 means a marked more (RD>0) or less (RD<0) risk of

being obese for those at the top SEP than their counterparts at the bottom. A significant p

value for trends means a noticed narrowed or widened gap between the top and the

bottom SEP in obesity risk over time on an absolute scale.

The results from Supplementary Figure 1a show that, In Scotland, men at the highest SEP

were found with less percentage of obese individuals when compared to their counterparts

in the lowest SEP level. The SII for male was only significant when measured by education

but not by occupational class, household income or SEP score. The results from

Supplementary Figure 1b suggest a significant reduction in obesity in absolute numbers for

Scottish women at top level SEP compared to their counterparts at the bottom in all survey

years by all four SEP markers. There was no significant trend emerged for SII over the study

years for either genders which means the socioeconomic inequalities in obesity was not

changed on the absolute scale for both genders over the study survey period.

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167x193mm (300 x 300 DPI)

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STROBE checklist

Item

No Recommendation


abstract…………………………………………………..…………..Page 1


done and what was found……………………………………………Page 2-3

Introduction


reported………………………………………………………………Page 5-6


Methods








Data sources/

measurement






Quantitative

variables


describe which groupings were chosen and why…………………..Page 10-12


confounding………………………………………………………….Page 10-12







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Results






Descriptive

data



(b) Indicate number of participants with missing data for each variable of

interest……………………………………………………………………………Page 8



……………………………………………………………………………….Page 15-18




(b) Report category boundaries when continuous variables were categorized..Page 9,14




analyses…………………………………………………………………..........Page 17

Discussion



imprecision. Discuss both direction and magnitude of any potential bias…....Page 8, 20



evidence……………………………………………………………………...Page 19-20


Other information



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Correction

Zhu J, Coombs N, Stamatakis E. Temporal trends in socioeconomic inequalities in obesityprevalence among economically-active working age adults in Scotland between 1995 and2011: a population-based repeated cross-sectional study. BMJ Open 2015;5:e006739. The firstname of the last author of this paper was misspelt. Emmanuel Stamatakis is the correctname.

BMJ Open 2015;5:e006739. doi:10.1136/bmjopen-2014-006739corr1

BMJ Open 2015;5:e006739. doi:10.1136/bmjopen-2014-006739corr1 1

Miscellaneous

http://crossmark.crossref.org/dialog/?doi=10.1136/bmjopen-2014-006739corr1&domain=pdf&date_stamp=2015-08-03

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Documents

BMJ Open · Correction Zhu J, Coombs N, Stamatakis E. Temporal trends in socioeconomic inequalities in obesity prevalence among economically-active working age adults in Scotland