A clinician's guide to obesity prevention in the UK

Across the UK, people's lives are being cut short because of obesity, and the lives of the most deprived members of our communities are being cut the most. The role of the medical professional in managing overweight and obesity is extensive, but, for many patients, maintaining a healthy weight needs to be supported by creating environments that help people to stay healthy in the first place. The building blocks of health are the environmental, commercial, economic and social factors that largely determine our health and wellbeing and impact our capability, opportunity and motivation to maintain healthy-weight behaviours. Although the role of the healthcare professional generally is to focus on the individual patient, clinicians can still influence these building blocks. Clinicians have the skills to create change, they often hold power in organisations with local to international impact and there are actions, big or small, that every clinician can take to improve obesity prevention. Here, we outline an environmental-behavioural framework for the primary prevention of obesity and consider the role of clinicians in catalysing change.

Measuring Obesogenicity and Assessing Its Impact on Child Obesity: A Cross-Sectional Ecological Study for England Neighbourhoods

Both major influences on changing obesity levels (diet and physical activity) may be mediated by the environment, with environments that promote higher weight being denoted obesogenic. However, while many conceptual descriptions and definitions of obesogenic environments are available, relatively few attempts have been made to quantify obesogenic environments (obesogenicity). The current study is an ecological study (using area units as observations) which has as its main objective to propose a methodology for obtaining a numeric index of obesogenic neighbourhoods, and assess this methodology in an application to a major national dataset. One challenge in such a task is that obesogenicity is a latent aspect, proxied by observed environment features, such as poor access to healthy food and recreation, as well as socio-demographic neighbourhood characteristics. Another is that obesogenicity is potentially spatially clustered, and this feature should be included in the methodology. Two alternative forms of measurement model (i.e., models representing a latent quantity using observed indicators) are considered in developing the obesogenic environment index, and under both approaches we find that both food and activity indicators are pertinent to measuring obesogenic environments (though with varying relevance), and that obesogenic environments are spatially clustered. We then consider the role of the obesogenic environment index in explaining obesity and overweight rates for children at ages 10-11 in English neighbourhoods, along with area deprivation, population ethnicity, crime levels, and a measure of urban-rural status. We find the index of obesogenic environments to have a significant effect in elevating rates of child obesity and overweight. As a major conclusion, we establish that obesogenic environments can be measured using appropriate methods, and that they play a part in explaining variations in child weight indicators; in short, area context is relevant.

Impact of Obesogenic Environments on Sugar-Sweetened Beverage Consumption among Preschoolers: Findings from a Cross-Sectional Survey in Beijing

The excessive consumption of sugar-sweetened beverages (SSBs) has been proven to be critical for obesity among preschoolers. This study aimed to describe the SSB consumption rates among preschoolers in the Dongcheng District of Beijing, China, and to explore the association between obesogenic environmental determinants and consumption. We applied a stratified cluster sampling method and recruited 3057 primary caregivers of preschoolers in June 2019 to participate in the survey. The caregivers reported their children’s consumption rates of six categories of SSBs and their exposure rates to SSB-related obesogenic environments. The associations between them were tested using multivariate logistic regression models. The mean (SD) age of the children was 5.6 (0.6) years and nearly half (48.3%) were girls. About 84.5% of the children had consumed SSBs over the past three months, and sugar-sweetened milk beverages had the highest consumption rate. Higher exposure to advertisements for the corresponding SSB categories in children, higher frequency rates of consuming SSBs and of taking children to fast-food restaurants in caregivers, and lower frequency rates of reading the Nutrition Facts Panels by caregivers were associated with higher SSB consumption rates among children (p < 0.05 in all of the SSB categories investigated, except for the Nutrition Facts Panel reading behaviors for the sports and energy beverages). SSB consumption among preschoolers is of concern, and comprehensive policy actions and education are urgently needed.

Precision nutrition: hype or hope for public health interventions to reduce obesity?

High-income countries are experiencing an obesity epidemic that follows a socioeconomic gradient, affecting groups of lower socioeconomic status disproportionately. Recent clinical findings have suggested new perspectives for the prevention and treatment of obesity, using personalized dietary approaches. Precision nutrition (PN), also called personalized nutrition, has been developed to deliver more preventive and practical dietary advice than ‘one-size-fits-all’ guidelines. With interventions becoming increasingly plausible at a large scale thanks to artificial intelligence and smartphone applications, some have begun to view PN as a novel way to deliver the right dietary intervention to the right population. We argue that large-scale PN, if taken alone, might be of limited interest from a public health perspective. Building on Geoffrey Rose’s theory regarding the differences in individual and population causes of disease, we show that large-scale PN can only address some individual causes of obesity (causes of cases). This individual-centred approach is likely to have a small impact on the distribution of obesity at a population level because it ignores the population causes of obesity (causes of incidence). The latter are embedded in the populations’ social, cultural, economic and political contexts that make environments obesogenic. Additionally, the most socially privileged groups in the population are the most likely to respond to large-scale PN interventions. This could have the undesirable effect of widening social inequalities in obesity. We caution public health actors that interventions based only on large-scale PN are unlikely, despite current expectations, to improve dietary intake or reduce obesity at a population level.

Associations between Obesity, Obesogenic Environments, and Structural Racism Vary by County-Level Racial Composition

Obesity rates in the U.S. are associated with area-level, food-related characteristics. Studies have previously examined the role of structural racism (policies/practices that advantaged White Americans and deprived other racial/ethnic minority groups), but racial inequalities in socioeconomic status (SES) is a novel indicator. The aim of this study is to determine the associations between racial inequalities in SES with obesity and obesogenic environments. Data from 2007–2014 County Health Rankings and 2012–2016 County Business Patterns were combined to assess the associations between relative SES comparing Blacks to Whites with obesity, and number of grocery stores and fast food restaurants in U.S. counties. Random effects linear and Poisson regressions were used and stratified by county racial composition. Racial inequality in poverty, unemployment, and homeownership were associated with higher obesity rates. Racial inequality in median income, college graduates, and unemployment were associated with fewer grocery stores and more fast food restaurants. Associations varied by county racial composition. The results demonstrate that a novel indicator of structural racism on the county-level is associated with obesity and obesogenic environments. Associations vary by SES measure and county racial composition, suggesting the ability for targeted interventions to improve obesogenic environments and policies to eliminate racial inequalities in SES.

Gender empowerment, inequalities and the prevalence of adult female obesity: An empirical analysis using new data, 1990-2013

Aims: Do gender inequality and gender discrimination explain female obesity? Discrimination denies access to choose and constrains agency. Scope: Using the Global Burden of Disease data on overweight and obesity share of the adult female population for almost 160 countries over a 24-year period, we find that female empowerment has no effect on the population share that is overweight, but it reduces the obese share of women. The substantive impact is, however, slight and the results are not robust to testing a sample of only developing countries. Political freedoms for women in general, however, show positive effects on the prevalence of obesity, results that are again substantively meagre. Higher levels of income inequality and a measure of health inequality predict lower levels of female obesity independently of the controls, which raises some doubt about large arguments linking generalized inequality to obesogenic environments. Results: In so far as our measures of female empowerment capture greater access to rights and agency, they are poor predictors of the prevalence of obesity. The results suggest that local-level idiosyncrasies matter a lot more than do macro-level factors. Conclusions: Any conclusion should be treated tentatively given the short temporal domain examined here and uncertainties in the data. While promoting rights and equity for women are still intrinsically valuable and moral, the task of reducing obesity per se may require more targeted public action promoting healthier lifestyles and consumption among vulnerable groups.

'I'm not trusted in the kitchen': food environments and food behaviours of young people attending school and college

BACKGROUND

Food behaviours are important in the context of health and obesity. The aim was to explore the environments and food behaviours of a sample of young people in the North East of England to further understanding of the relationship between eating behaviours and environmental context.

METHODS

Focus groups were conducted with four groups of young people aged 16-20 years (n = 40; 28 male, 12 female) between November 2006 and June 2007. Analysis was informed by grounded theory methods and was an iterative process of identifying themes across the transcripts.

RESULTS

Topics explored included: their main environment, home food responsibility and cooking, food outside of the home, where food was purchased/obtained and where food was eaten and with whom. Emergent themes included: the value for money in food purchases, time convenience, the car as a means of accessing food and health perceptions.

CONCLUSIONS

The complexities of the food environment were illustrated. This work has highlighted the importance of the home food environment and parents, and indicated the importance of factors such as time and cost in this age group's food choices. The behavioural norms around food behaviours merit further exploration for this population in transition between adolescence and adulthood.

Creating 'obesogenic realities'; do our methodological choices make a difference when measuring the food environment?

BACKGROUND

The use of Geographical Information Systems (GIS) to objectively measure 'obesogenic' food environment (foodscape) exposure has become common-place. This increase in usage has coincided with the development of a methodologically heterogeneous evidence-base, with subsequent perceived difficulties for inter-study comparability. However, when used together in previous work, different types of food environment metric have often demonstrated some degree of covariance. Differences and similarities between density and proximity metrics, and within methodologically different conceptions of density and proximity metrics need to be better understood.

METHODS

Frequently used measures of food access were calculated for North East England, UK. Using food outlet data from local councils, densities of food outlets per 1000 population and per km² were calculated for small administrative areas. Densities (counts) were also calculated based on population-weighted centroids of administrative areas buffered at 400/800/1000 m street network and Euclidean distances. Proximity (street network and Euclidean distances) from these centroids to the nearest food outlet were also calculated. Metrics were compared using Spearman's rank correlations.

RESULTS

Measures of foodscape density and proximity were highly correlated. Densities per km² and per 1000 population were highly correlated (r(s) = 0.831). Euclidean and street network based measures of proximity (r(s) = 0.865) and density (r(s) = 0.667-0.764, depending on neighbourhood size) were also highly correlated. Density metrics based on administrative areas and buffered centroids of administrative areas were less strongly correlated (r(s) = 0.299-0.658).

CONCLUSIONS

Density and proximity metrics were largely comparable, with some exceptions. Whilst results suggested a substantial degree of comparability across existing studies, future comparability could be ensured by moving towards a more standardised set of environmental metrics, where appropriate, lessening the potential pitfalls of methodological variation between studies. The researchers' role in creating their own obesogenic 'reality' should be better understood and acknowledged.