Providing care for people with T2D and obesity requires a whole-person approach, with attention to both medical risk factors and the environment.

Genetic & Socioeconomic Risk Factors Linked With Metabolic Disease Prevalence

Many factors—such as genetics, socioeconomic status, and lifestyle/behavior— are known to influence the risk for metabolic disease in isolation, but these factors are rarely examined in concert, according to Sara Jane Cromer, MD. “In particular, the ways in which one risk factor may play a greater role in people who also have another risk factor has not been thoroughly described and quantified,” she says.

For a study published in Diabetes Care, Dr. Cromer; Miriam S. Udler, MD, PhD; and colleagues examined the correlation of genetic and socioeconomic risk for type 2 diabetes (T2D) and obesity in two biobanks and among individuals of different genetic ancestry.

“We examined two risk factors—genetic and area-level socioeconomic measures —to understand the risk for metabolic disease in people with one or both factors,” Dr. Udler says. “We assessed the link between these factors and the prevalence of T2D and obesity in two large biobanks, containing both clinical and genetic information for tens of thousands of individuals in the United States and England.” The cohort in one biobank, the Mass General Brigham Biobank, included approximately 30,000 people, while the other, in the UK Biobank, contained around 230,000 adult volunteers.

Area-Level Educational Attainment Most Strongly Linked With Disease

The study team analyzed population subgroups with genetic evidence of European, African, admixed American (predominantly identifying as Hispanic or other race/ethnicity), and Central or South Asian Ancestry. Genetic risk was measured using polygenic scores, which considered the combined disease risk contributed by thousands of common genetic variants across a person’s genome.

Socioeconomic risk was examined using multiple area-level socioeconomic measures (neighborhood-level measures of income, employment, educational attainment, and more complex deprivation indices). “Since we found that area-level educational attainment most strongly correlated with disease, we used this as our primary socioeconomic measure,” Dr. Cromer explains. The researchers then used multivariable logistic regression to calculate ORs and 95% CIs and calculated the relative excess risk due to interaction to examine for additive interactions between risk factors.

“We observed that both genetic and socioeconomic risks are associated with increased prevalence of T2D and obesity,” Dr. Cromer notes. “However, the combination of both factors is especially detrimental, with the absolute increase in disease prevalence with unfavorable socioeconomic risk much greater in those with higher underlying genetic risk (Graphic).

Care for People with T2D % Obesity Requires ‘Whole-Person Approach’

For those people at high genetic risk, the absolute increase in the prevalence of disease with increasing socioeconomic risk was greater, with 13.2% and 16.7% of T2D and obesity prevalence, respectively, attributable to the co-occurrence of both factors or the additive effects of both socioeconomic and genetic risk, the study authors explain.  Findings were similar in people from different genetic ancestry groups, the authors note.

Providing care for people with T2D and obesity requires a whole-person approach, according to the study authors, with attention to both medical risk factors and the environment in which an individual lives. “Policy efforts may have the greatest impact among individuals at highest genetic risk,” they add.

“Our research indicates that combined high genetic and area-level risk is correlated with more than three time the prevalence of T2D and obesity, and in some populations, there is evidence of positive additive interactions between these factors.”

The study team would like to see further research focus on determining the contributions and interactions of genetic and socioeconomic risk in conjunction with other risk factors, such as lifestyle behaviors, and to understand whether interventions targeting area-level socioeconomic risk can impact metabolic disease prevalence.