G S Toteja, Sulaiman Ladhani, Panniyammakal Jeemon, Dimple Kondal, Shivani A. Patel, Vikram Patel, Prakash Chand Negi, Kashvi Kahol, Sathya Prakash Manimunda, Ajit Deshpande, Preet K Dhillon, Dorairaj Prabhakaran, and Anil J Purty
Background The 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 findings We 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 between hypertension and obesity in the total sample of all coresiding adults (aOR = 1.24; 95% CI 1.02–1.52), high cholesterol and diabetes in the adult-parent sample (aOR = 2.02; 95% CI 1.08–3.78), and hypertension and diabetes in the spousal sample (aOR = 1.51; 95% CI 1.05–2.17). Of all associations examined, only the relationship between hypertension and diabetes in the adult-parent dyads was statistically significantly negative (aOR = 0.62; 95% CI 0.40–0.94). Relatively small samples in the dyadic analysis and site-specific analysis call for caution in interpreting qualitative differences between associations among different dyad types and geographical locations. Because of the cross-sectional nature of the analysis, the findings do not provide information on the etiology of incident chronic conditions among household members. Conclusions We observed strong concordance of chronic conditions within coresiding adults across diverse settings in India. These data provide early evidence that a household-based approach to chronic disease research may advance public health strategies to prevent and control chronic conditions. Trial registration Clinical Trials Registry India CTRI/2013/10/004049; http://ctri.nic.in/Clinicaltrials/login.php, In a cross-sectional analysis, Shivani Patel and colleagues estimate the extent of chronic disease concordance within Indian households., Author summary Why was this study done? Prior research, largely set in high-income country settings, demonstrates the concordance of physical health and mental health outcomes among spouses and between parents and their adult children. These prior studies have examined neither disease concordance among coresiding adults who are not parent-child pairs or spouses nor the correspondence of different chronic conditions (e.g., husband’s diabetes status and wife’s common mental disorder status). Few have examined physical and mental health outcomes simultaneously. Understanding associations of shared and differing chronic conditions among all coresiding adults in households may shed light on new approaches to identify and treat chronic illness in low- and middle-income countries such as India. What did the researchers do and find? We examined 5 chronic disease conditions—hypertension, diabetes, obesity, common mental disorder, and high total blood cholesterol—in 7,522 adults living in 2,574 households in 4 diverse settings in India. We demonstrate that there is substantial concordance in diabetes, common mental disorder, and obesity among Indian adults residing in the same household regardless of relationship type. Correspondence across different chronic conditions was weaker. What do these findings mean? Adults who live with someone with diabetes, common mental disorder, or obesity are more likely to have that same condition. Addressing the burgeoning chronic disease burden in India will benefit from understanding and intervening upon mechanisms responsible for disease concordance within households in this setting.