What social risk factors affect obesity rates?

Risk factors such as living alone, poverty, low level of education and unemployment have all been linked to increased rates of obesity

According to a study conducted in Obesity, social determinants of health (SDOH) have been associated with a higher likelihood of obesity – independent of clinical and demographic factors.

This is the first population-based study to examine this long-hypothesised connection, using a nationally representative sample of US adults.

What about Social Determinants of Health (SDOH)?

Researchers say that limited empirical data has suggested correlations between individual SDOH such as education, income, neighbourhood and food environment, and obesity.

However, the SDOH-obesity link has not been examined from an upstream, cumulative social disadvantage standpoint.

Author Khurram Nasir said: “Our findings call on healthcare providers and policymakers to develop novel care delivery models that allow for greater assessment of SDOH to inform patient care, and prioritise socially vulnerable populations in cardiovascular prevention programs for greatest population health benefits.

“Strong political will and partnerships between health systems and community stakeholders are needed to identify and address unfavourable SDOH, and alleviate the burden of obesity in underserved communities.”

Study parameters

Using the data from the National Health Interview Survey, nearly 165,000 adults aged 18 or older between 2013-2017 were questioned annually by the National Center for Health Statistics under the auspices of the Centres for Disease Control and Prevention.

For the study, overweight was defined as 25 with less than a body mass index (BMI) of 30 while obesity was defined as a BMI of greater than or equal to 30.

Obesity was then further categorised into three classes (obesity class 1 and 2, 30 kg/m² BMI greater than 40) and obesity class 3 (BMI equal to or a greater than 40) to further examine the association of SDOH and different levels of obesity.

In order to set up the SDOH framework, the team were required to adapt a previous model by the Kaiser Family Foundation. Individual SDOH were grouped into six domains, including economic stability; neighbourhood, physical environment and social cohesion; community and social context; food; education and health care system.

A total of 38 SDOH were collected to create a cumulative SDOH score, which was then divided into four quartiles to designate levels of SDOH burden.

Prevalence of overweight and obesity were studied across SDOH quartiles in the total population and by age, sex and race/ethnicity. Multinomial logistic regression models were used to analyse the association between SDOH quartiles and overweight/obesity, adjusting for relevant covariates.

Obesity higher for middle aged, Black adults

Results showed that there was an increase in obesity prevalence with increasing SDOH burden.

At nearly each quartile, overweight and obesity rates were higher for middle aged and non-Hispanic Black adults compared to their White counterparts, additional differences were observed by sex.

The authors of the study have noted that there is a need for future studies to assess the SDOH-obesity link with longitudinal study designs.

Future work should also include modelling the cumulative impact of multiple social determinants of health, with the possibility of even using machine-learning algorithms to help in this.

A similar correlation was found in an unrelated study, looking at the concept of “neighbourhood disadvantage” and levels of COVID infection. That research found a strong link between similar markers and likelihood of the virus, suggesting that there is scope for policymakers to examine these factors across public health.