Department of Geography and Geographic Information Science, University of Cincinnati, Cincinnati, Ohio.
Health Geography and Disease Modeling Laboratory, University of Cincinnati, Cincinnati, Ohio.
JAMA Netw Open. 2020 May 1;3(5):e203865. doi: 10.1001/jamanetworkopen.2020.3865.
Diabetes is a severe metabolic disorder affecting human health worldwide, with increasing prevalence in low- and middle-income countries. Gaps in knowledge regarding factors that lead to diabetes and its association with tuberculosis (TB) endemicity at the national scale still exist, mainly because of the lack of large-scale dual testing and appropriate evaluation methods.
To identify locations in India where diabetes prevalence is concentrated, examine the association of diabetes with sociodemographic and behavioral covariates, and uncover where high regional TB endemicity overlaps with diabetes.
DESIGN, SETTING, AND PARTICIPANTS: This cross-sectional study included 803 164 men aged 15 to 54 years and women aged 15 to 49 years who participated in the Demographic Health Survey (2015-2016), carried out by the India Ministry of Health and Family Welfare using a 2-stage clustered sampling, which included a diabetes estimation component. The survey was conducted from January 2015 to December 2016, and data analysis was conducted from July 2018 to January 2019.
Self-reported diabetes status.
Self-reported diabetes status was used to estimate the association of covariates, including educational level, sex, age, religion, marital status, alcohol use, tobacco use, obesity status, and household socioeconomic level, with diabetes prevalence. Additionally, regional tuberculosis endemicity level, estimated using the India TB report for 2014 from the Revised National TB Program, was included to evaluate the national extent of the spatial overlap of diabetes and TB.
Among 803 164 sampled individuals (691 982 [86.2%] women; mean [SD] age, 30.09 [9.97] years), substantial geographic variation in diabetes prevalence in India was found, with a concentrated burden at the southern coastline (cluster 1, Andhra Pradesh and Telangana: prevalence, 3.01% [1864 of 61 948 individuals]; cluster 2, Tamil Nadup and Kerala: prevalence, 4.32% [3429 of 79 435 individuals]; cluster 3, east Orissa: prevalence, 2.81% [330 of 11 758 individuals]; cluster 4, Goa: prevalence, 4.43% [83 of 1883 individuals]). Having obesity and overweight (odds ratio [OR], 2.44; 95% CI, 2.18-2.73; P < .001; OR, 1.66; 95% CI, 1.52-1.82; P < .001, respectively), smoking tobacco (OR, 3.04; 95% CI, 1.66-5.56; P < .001), and consuming alcohol (OR, 2.01; 95% CI, 1.37-2.95; P < .001) were associated with increased odds of diabetes. Regional TB endemicity and diabetes spatial distributions showed that there is a lack of consistent geographical overlap between these 2 diseases (eg, TB cluster 4: 60 213 TB cases; 186.79 diabetes cases in 20 183.88 individuals; 0.93% diabetes prevalence; TB cluster 8: 47 381 TB cases; 180.53 diabetes cases in 22 449.18 individuals; 0.80% diabetes prevalence; TB cluster 9: 37 620 TB cases, 601.45 diabetes cases in 12 879.36 individuals; 4.67% diabetes prevalence).
In this study, identifying spatial clusters of diabetes on the basis of a nationally representative survey suggests that India may face different levels of disease severity, and each region might need to implement control strategies that are more appropriate for its unique epidemiologic context.
重要性：糖尿病是一种严重的代谢紊乱疾病，影响着全球人类的健康，在中低收入国家的发病率呈上升趋势。由于缺乏大规模的双重检测和适当的评估方法，对于导致糖尿病的因素以及其与结核病（TB）流行地区之间的关联，在国家范围内仍存在知识上的差距。
目的：确定印度糖尿病流行集中的地区，研究糖尿病与社会人口学和行为因素的关联，并揭示高区域结核病流行地区与糖尿病的重叠情况。
设计、地点和参与者：这项横断面研究包括 803164 名年龄在 15 至 54 岁的男性和年龄在 15 至 49 岁的女性，他们参加了印度卫生部和家庭福利部进行的人口健康调查（2015-2016 年），采用两阶段聚类抽样，其中包括糖尿病估计部分。调查于 2015 年 1 月至 2016 年 12 月进行，数据分析于 2018 年 7 月至 2019 年 1 月进行。
暴露：自我报告的糖尿病状况。
主要结果和测量：使用自我报告的糖尿病状况来估计包括教育水平、性别、年龄、宗教、婚姻状况、饮酒、吸烟、肥胖状况和家庭社会经济水平在内的协变量与糖尿病流行率之间的关联。此外，还包括印度结核病报告 2014 年修订国家结核病规划的数据，用于评估糖尿病和结核病在全国范围内的空间重叠程度。
结果：在抽样的 803164 名个体中（691982 名女性；平均[SD]年龄，30.09[9.97]岁），发现印度糖尿病流行存在显著的地理差异，南部海岸线地区负担较重（簇 1：安得拉邦和特伦甘纳邦：患病率为 3.01%[61948 人中的 1864 人]；簇 2：泰米尔纳德邦和喀拉拉邦：患病率为 4.32%[79435 人中的 3429 人]；簇 3：东奥里萨邦：患病率为 2.81%[11758 人中的 330 人]；簇 4：果阿邦：患病率为 4.43%[1883 人中的 83 人]）。肥胖和超重（比值比[OR]，2.44；95%置信区间[CI]，2.18-2.73；P<0.001；OR，1.66；95%CI，1.52-1.82；P<0.001）、吸烟（OR，3.04；95%CI，1.66-5.56；P<0.001）和饮酒（OR，2.01；95%CI，1.37-2.95；P<0.001）与糖尿病患病风险增加相关。区域结核病流行和糖尿病空间分布表明，这两种疾病之间没有一致的地理重叠（例如，结核病簇 4：60213 例结核病病例；在 20183.88 人中，有 186.79 例糖尿病病例；糖尿病患病率为 0.93%；结核病簇 8：47381 例结核病病例；在 22449.18 人中，有 180.53 例糖尿病病例；糖尿病患病率为 0.80%；结核病簇 9：37620 例结核病病例，在 12879.36 人中，有 601.45 例糖尿病病例；糖尿病患病率为 4.67%）。
结论和相关性：在这项研究中，根据全国代表性调查确定糖尿病的空间聚类表明，印度可能面临不同程度的疾病严重程度，每个地区可能需要实施更适合其独特流行病学背景的控制策略。
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