Regional inequalities in adiposity in England: distributional analysis of the contribution of individual-level characteristics and the small area obesogenic environment

Davillas, Apostolos; Jones, Andrew M.

doi:10.1016/j.ehb.2020.100887

Cited by 14 publications

(7 citation statements)

References 59 publications

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“…In contrast, the slower fall in cigarette smoking prevalence among men with obesity, albeit from a lower prevalence in the first survey period (2003‐2006), and the marginal increase in inactivity prevalence among women with overweight, may, to some extent, reflect influences of living in obesogenic environments (32): i.e., neighborhoods with higher socioeconomic deprivation, geographic barriers to PA, and lower air quality that may influence adiposity levels over and above other individual characteristics (33). Reverse causality, i.e., a reluctance of smokers to tolerate post‐cessation weight gain (34) and the fact that higher adiposity in itself is a risk factor for smoking (35) which makes it more difficult to quit, is also a potential contributory factor for the slower decline in current smoking levels among men with obesity.…”

Section: Discussionmentioning

confidence: 99%

Trends in cardiovascular disease risk factors by BMI category among adults in England, 2003‐2018

Scholes

Fat

Mindell

2021

Obesity

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Individual-level epidemiologic studies have documented the higher rates of cardiovascular disease (CVD) outcomes associated independently with modifiable risk factors (1,2). For example, excess body weight accounted for approximately 4 million deaths worldwide in 2015, and CVD accounted for nearly 70% of deaths related to high BMI, of which more than 60% occurred among persons with obesity (3). At the population level, halting the rises in diabetes and obesity and reducing levels of other CVD risk factors such as current tobacco use, harmful alcohol consumption, insufficient physical activity (PA), intake of salt/sodium, and high blood pressure (BP) are major World Health Organization global targets for reducing overall mortality from the four main noncommunicable diseases by 25% in 2025, relative to 2010 levels (4). Obesity prevalence among adults has markedly increased in England over the past 25 years, rising from 16% in 1994 to 28% in 2018 (5), with contributory factors that include increases in the availability and affordability of energy-dense foods (3) and environmental barriers to PA. At the same time, prevention efforts via

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Section: Discussionmentioning

confidence: 99%

Trends in cardiovascular disease risk factors by BMI category among adults in England, 2003‐2018

Scholes

Fat

Mindell

2021

Obesity

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“…In contrast, the slower fall in cigarette smoking prevalence among men with obesity, albeit from a lower prevalence in the first survey period (2003–06), and the marginal increase in inactivity prevalence among women with overweight, may to some extent reflect influences of living in obesogenic environments (32): i.e. neighbourhoods with higher socioeconomic deprivation, geographic barriers to PA, and lower air quality that may influence adiposity levels over and above other individual characteristics (33). Reverse causality, i.e.…”

Section: Divergent Trends In Cvd Risk Factor Prevalence By Bmi Categorymentioning

confidence: 99%

Trends in cardiovascular disease risk factors by body mass index category among adults in England 2003-18: analysis of repeated cross-sectional national health surveys

Scholes

Fat

Mindell

2020

Preprint

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Objective. Favourable trends in cardiovascular disease (CVD) risk factors at the population level potentially mask differences within high- and low-risk groups. Data from annual, repeated cross-sectional surveys (Health Survey for England 2003-18) was used to examine trends in the prevalence of key CVD risk factors by body mass index (BMI) category among adults aged 16 years or older (n=115,860). Methods. Six risk factors were investigated: (i) current cigarette smoking; (ii) physical inactivity (<30 minutes of moderate-to-vigorous physical activity per week); (iii) drinking above recommended daily alcohol limits; (iv) hypertension (measured blood pressure ≥140/90mmHg or use of medicine prescribed for high blood pressure); (v) total diabetes (reported diagnosed or elevated glycated haemoglobin); and (vi) raised total cholesterol (≥5mmol/L). Age-standardised risk factor prevalence was computed in each four-year time period (2003-06; 2007-10; 2011-14; 2015-18) in all adults and by BMI category (normal-weight; overweight; obesity). Change in risk factor prevalence on the absolute scale was computed as the difference between the first and last time-periods, expressed in percentage points (PP). Results. Risk factor change varied by BMI category in a number of cases. Current smoking prevalence fell more sharply for normal-weight men (-8.1 PP; 95% CI: -10.3, -5.8) versus men with obesity (-3.8 PP; 95% CI: -6.2, -1.4). Hypertension remained at a stable level among normal-weight men but decreased among men with obesity (-4.1 PP; 95% CI: -7.1, -1.0). Total diabetes remained at a stable level among normal-weight adults, but increased among adults with obesity (men: 3.5 PP; 95% CI: 1.2, 5.7; women: 3.6 PP; 95% CI: 1.8, 5.4). Raised total cholesterol decreased in all BMI groups, but fell more sharply among women with obesity (-21 PP; 95% CI: -25, -17) versus their normal-weight counterparts (-16 PP; 95% CI: -18, -14). Conclusions. Relative to adults with normal weight, greater reductions in hypertension and raised total cholesterol among adults with overweight and obesity reflect at least in part improvements in screening, treatment and control among those at highest cardiovascular risk. Higher levels of risk factor prevalence among adults with overweight and obesity, in parallel with rising diabetes, highlight the importance of national prevention efforts to combat the public health impact of excess adiposity.

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“…Prior studies documenting the widening distribution have been descriptive in nature (Green et al, 2016). There has been some examination of how demographic, social, behavioural, and health-related characteristics vary across the entire BMI distribution (Aizawa, 2019;Bann et al, 2020;Basu et al, 2015;Bottai et al, 2014;Davillas & Jones, 2020;Dutton & Mclaren, 2016;Norris et al, 2020;Ouyang et al, 2015;Siddiqi et al, 2018). This has been important in progressing thinking away from dichotomous measures of risk, towards conceptualising risk as operating throughout an entire BMI distribution and providing more detailed investigation of non-linear relationships (Basu et al, 2015;Siddiqi et al, 2018).…”

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confidence: 99%

Explaining the widening distribution of Body Mass Index: A decomposition analysis of trends for England, 2002–2004 and 2012–2014

Green

Rowe

2020

Area

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While there is increasing international evidence for the widening of the distribution of body mass index (BMI), there has been little attempt to explain this trend.The aim of our study is to examine whether the trend can be explained by compositional changes within the population or contextual changes in the relationships between explanatory variables and BMI. Data from the Health Survey for England for 2002-2004 and 2012-2014 were used. BMI was our outcome variable and explanatory variables included age, sex, race, education, occupation, and physical activity. We examined how predictors of BMI varied at the 10th, 50th, and 90th percentiles using unconditional quantile regressions. Oaxaca-Blinder type decomposition analysis was then applied to examine whether contextual or compositional explanations accounted for changes in the distribution between time periods. We found that changes in the nature of relationships observed by our coefficient values accounted for the majority of the difference in BMI at the 90th percentile in 2012-2014 compared to 2002-2004. Race, physical activity, and socio-economic status were the primary reasons for explaining the continued growth of the right tail of the BMI distribution. Compositional changes in the population were less influential, but may have offset some of the contextual changes to relationships. Changing relationships between predictors of BMI reflect systematic changes in the determinants of BMI, leading to the widening of the BMI distribution. Our results demonstrate the importance of multi-tiered policies aimed at tackling the varying influences across the BMI distribution.

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Regional inequalities in adiposity in England: distributional analysis of the contribution of individual-level characteristics and the small area obesogenic environment

Cited by 14 publications

References 59 publications

Trends in cardiovascular disease risk factors by BMI category among adults in England, 2003‐2018

Trends in cardiovascular disease risk factors by BMI category among adults in England, 2003‐2018

Trends in cardiovascular disease risk factors by body mass index category among adults in England 2003-18: analysis of repeated cross-sectional national health surveys

Explaining the widening distribution of Body Mass Index: A decomposition analysis of trends for England, 2002–2004 and 2012–2014

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