Revisiting gender, socioeconomics, and hypertension comorbidities

A while back we published a paper examining how socioeconomic gender factors—employment, education, marital status, household size—relate to chronic disease comorbidities in people with hypertension, and whether those associations differ between males and females (Lindner & others, 2024). The study analyzed data from 74,748 people with hypertension drawn from the European Health Interview Survey (EHIS, 2013–2015) across 30 countries, stratified by national gender inequality.

Hypertension is one of the most prevalent chronic conditions worldwide and a major driver of comorbidity burden. What often goes unexamined is how the social context of being male or female—not just biology—shapes which other diseases accumulate alongside it. We identified 47 statistically significant sex differences in how socioeconomic factors relate to comorbidities like myocardial infarction, arthrosis, renal disease, and depression in people with hypertension. A few findings stood out:

• Marriage raises hypertension risk in women, not men. Married or partnered women with hypertension had 30% higher odds of the condition compared to single women; in men, only the loss of a partner (widowed/divorced) was associated with elevated risk.
• Employment and cardiac risk diverge by sex. Among employed people with hypertension, myocardial infarction associations were generally stronger in males—but in countries with high gender inequality, employed women actually showed higher cardiac odds than men, consistent with a double-burden hypothesis.
• Higher education paradoxically linked to arthrosis in women. Post-secondary-educated women with hypertension had significantly higher arthrosis odds; men did not, suggesting that professional and lifestyle factors interact with disease differently by sex.
• Country-level gender inequality amplifies these patterns. Effects were strongest in high Gender Inequality Index countries, pointing to structural gender context as a key modulator—not just individual-level biology.

I recently revisited the findings and built a new interactive visualization to make the structure of results more intuitive. The bipartite network below connects gender/socioeconomic factors (left) to comorbidities (right). Each link represents a statistically significant association from the logistic regression models. Color encodes which group showed the significant association (blue = male, orange = female, pink = both), line style encodes direction (solid = risk, dashed = protective), and the amber highlight marks associations where the odds ratio ratio (ORR) between sexes was itself significant—i.e., where the effect genuinely differed between males and females.

Hover over any node to see the exact odds ratios.

The picture that emerges is one of considerable sex heterogeneity. Living in a larger household (≥ 3 members) is consistently associated with higher odds of multiple comorbidities, but predominantly in females. Marital and widowhood statuses tend to be protective for both sexes against depression, while their protective associations with arthrosis appear specifically in males. Employment during the past year is linked to higher odds of chronic pulmonary disease and arthrosis in males—a pattern likely reflecting occupational exposure.

The amber highlights mark four associations where the ORR itself reached significance: household size and asthma, employment and myocardial infarction, education and arthrosis, and widowhood/divorce and renal disease. These are the associations most clearly patterned by biological sex, beyond what the individual OR estimates suggest.

The full analysis is available in (Lindner & others, 2024).