Chronic disease concordance within Indian households: A cross-sectional study

Abstract

BackgroundThe household is a potentially important but understudied unit of analysis and intervention in chronic disease research. We sought to estimate the association between living with someone with a chronic condition and one’s own chronic condition status.Methods and findingsWe conducted a cross-sectional analysis of population-based household- and individual-level data collected in 4 socioculturally and geographically diverse settings across rural and urban India in 2013 and 2014. Of 10,703 adults ages 18 years and older with coresiding household members surveyed, data from 7,522 adults (mean age 39 years) in 2,574 households with complete covariate information were analyzed. The main outcome measures were diabetes (fasting plasma glucose ≥ 126 mg/dL or taking medication), common mental disorder (General Health Questionnaire score ≥ 12), hypertension (blood pressure ≥ 140/90 mmHg or taking medication), obesity (body mass index ≥ 30 kg/m2), and high cholesterol (total blood cholesterol ≥ 240 mg/dL or taking medication). Logistic regression with generalized estimating equations was used to model associations with adjustment for a participant’s age, sex, education, marital status, religion, and study site. Inverse probability weighting was applied to account for missing data. We found that 44% of adults had 1 or more of the chronic conditions examined. Irrespective of familial relationship, adults who resided with another adult with any chronic condition had 29% higher adjusted relative odds of having 1 or more chronic conditions themselves (adjusted odds ratio [aOR] = 1.29; 95% confidence interval [95% CI] 1.10–1.50). We also observed positive statistically significant associations of diabetes, common mental disorder, and hypertension with any chronic condition (aORs ranging from 1.19 to 1.61) in the analysis of all coresiding household members. Associations, however, were stronger for concordance of certain chronic conditions among coresiding household members. Specifically, we observed positive statistically significant associations between living with another adult with diabetes (aOR = 1.60; 95% CI 1.23–2.07), common mental disorder (aOR = 2.69; 95% CI 2.12–3.42), or obesity (aOR = 1.82; 95% CI 1.33–2.50) and having the same condition. Among separate analyses of dyads of parents and their adult children and dyads of spouses, the concordance between the chronic disease status was striking. The associations between common mental disorder, hypertension, obesity, and high cholesterol in parents and those same conditions in their adult children were aOR = 2.20 (95% CI 1.28–3.77), 1.58 (95% CI 1.15–2.16), 4.99 (95% CI 2.71–9.20), and 2.57 (95% CI 1.15–5.73), respectively. The associations between diabetes and common mental disorder in husbands and those same conditions in their wives were aORs = 2.28 (95% CI 1.52–3.42) and 3.01 (95% CI 2.01–4.52), respectively. Relative odds were raised even across different chronic condition phenotypes; specifically, we observed positive statistically significant associations b...

Spousal cardiometabolic risk factors and incidence of type 2 diabetes: a prospective analysis from the English Longitudinal Study of Ageing

“…The much lower number of individuals with new type 2 diabetes in the Framingham cohort [20] and in our own study (both n < 770) may partly explain why neither was able to replicate the findings from the much larger Swedish and US studies [19,26]. In addition, however, cross-sectional studies have reported inconsistent findings with respect to the statistical significance of the risk of type 2 diabetes among individuals whose spouses have the disease [15,16,27,28].…”

Use of an Electronic Clinical Decision Support System in Primary Care to Assess Inappropriate Polypharmacy in Young Seniors With Multimorbidity: Observational, Descriptive, Cross-Sectional Study

“…There is also a paucity of evidence about how clusters of conditions develop and change over time, meaning it can be difficult to predict how the disease burden might change over the course of a patient's life, and difficult to identify when interventions might be best applied. 146 Additionally, it has been established that certain chronic conditions tend to cluster in families and communities, 147,148 but it remains uncertain whether multimorbidity per se also clusters in this way.…”

“…However, there is also growing evidence to suggest that factors that operate at the household level can also be drivers of disease risk -individuals who live with people with a chronic physical or mental health condition have been found to be at an increased risk of experiencing the same condition themselves, in both HICs 397, 398,399 and LMICs. 400 Although living with others and having a large social network may be protective for multimorbidity (as noted in Section 3.2.2), it will be valuable to consider whether factors that operate at the household level can also influence multimorbidity clusters in a similar manner as to single conditions.…”

Trajectories of obesity by spousal diabetes status in the English Longitudinal Study of Ageing

“…Cobb et al [2] suggest that an individual has almost double the risk of becoming obese if their spouse becomes obese. From a cross-sectional perspective, Patel et al [14] suggest that obesity is associated with spousal diabetes status. We extend these observations using longitudinal data on age-related obesity trajectories by spousal diabetes status.…”