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

中文翻译：

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印度家庭中的慢性病一致性：一项横断面研究

背景

在慢性疾病研究中，家庭是一个潜在的重要但未被充分研究和分析的单元。我们试图估计与患有慢性病的人生活和自己的慢性病状态之间的关联。

方法和发现

我们对2013年和2014年在印度农村和城市的4种社会文化和地理环境下收集的基于人口的家庭和个人水平数据进行了横断面分析。在调查的10703名18岁以上的成年人中，有核心家庭成员进行了调查，分析了来自2574个家庭的7,522名成年人（平均年龄39岁）的数据，并提供了完整的协变量信息。主要结局指标包括糖尿病（空腹血糖≥126 mg / dL或正在服药），常见精神障碍（一般健康状况调查表评分≥12），高血压（血压≥140/90 mmHg或正在服药），肥胖症（体重）指数≥30 kg / m ²）和高胆固醇（总血胆固醇≥240 mg / dL或正在服药）。使用具有广义估计方程的逻辑回归，对参与者的年龄，性别，教育程度，婚姻状况，宗教信仰和研究地点进行调整后，对关联进行建模。应用逆概率加权来说明丢失的数据。我们发现44％的成年人患有1种或以上的慢性病。无论家族关系如何，与另一位患有任何慢性病的成年人同住的成年人自身具有1种或多种慢性病的经调整的相对几率要高29％（经调整的几率[aOR] = 1.29； 95％的置信区间[95％CI] 1.10） –1.50）。我们还观察到糖尿病，常见精神障碍和高血压与任何慢性疾病（aOR范围为1）之间存在统计学上的显着正相关。19至1.61）中的所有核心家庭成员的分析。但是，在核心家庭成员中，某些慢性病的协调性较强。具体而言，我们观察到与另一位糖尿病成年人（aOR = 1.60; 95％CI 1.23–2.07），常见精神障碍（aOR = 2.69; 95％CI 2.12–3.42）或肥胖（aOR = 1.82）之间存在统计学上的显着正相关性。 ； 95％CI 1.33–2.50），并且条件相同。在对父母及其成年子女的双胞胎和配偶双胞胎的单独分析中，慢性病状态之间的一致性令人吃惊。父母与成年子女相同条件下的常见精神障碍，高血压，肥胖和高胆固醇之间的相关性分别为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）和2.57（95％CI 1.15-5.73）。糖尿病与丈夫的常见精神障碍以及其妻子的相同状况之间的关联分别为aOR = 2.28（95％CI 1.52–3.42）和3.01（95％CI 2.01–4.52）。即使在不同的慢性病表型之间，相对几率也有所提高。具体而言，我们在所有核心成年人（aOR = 1.24； 95％CI 1.02-1.52）的总样本中观察到高血压与肥胖之间的统计学显着正相关，在成年父母样本中，高胆固醇和糖尿病（aOR = 2.02； 95％） CI 1.08–3.78），以及配偶样本中的高血压和糖尿病（aOR = 1.51； 95％CI 1.05–2.17）。在所有检查的协会中，只有成年双亲中高血压与糖尿病之间的关系在统计学上显着为负（aOR = 0.62； 95％CI 0.40–0.94）。二进位分析和针对特定地点的分析中相对较小的样本在解释不同二分体类型和地理位置之间的关联之间的质量差异时需要谨慎。由于分析的横断面性质，调查结果未提供有关家庭成员中发生的慢性病的病因学信息。

结论

我们观察到印度不同地区的成年人中慢性病的强烈一致性。这些数据提供了早期证据，表明以家庭为基础的慢性病研究方法可能会推动公共卫生策略预防和控制慢性病。

试用注册

印度临床试验注册中心CTRI / 2013/10/004049; http://ctri.nic.in/Clinicaltrials/login.php