Associations of four indexes of social determinants of health and two community typologies with new onset type 2 diabetes across a diverse geography in Pennsylvania.
Associations of four indexes of social determinants of health and two community typologies with new onset type 2 diabetes across a diverse geography in Pennsylvania.
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DOI：
10.1371/journal.pone.0274758
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发表时间：
2022
期刊：
影响因子：
3.7
通讯作者：
Hirsch, Annemarie G.
中科院分区：
文献类型：
--
作者：
Schwartz, Brian S.;Kolak, Marynia;Pollak, Jonathan S.;Poulsen, Melissa N.;Bandeen-Roche, Karen;Moon, Katherine A.;DeWalle, Joseph;Siegel, Karen R.;Mercado, Carla, I;Imperatore, Giuseppina;Hirsch, Annemarie G.
评估2型糖尿病（T2 D）发病的地理差异需要在相关的空间尺度上采用多维方法来表征可能影响这种健康结果的社区类型和特征。使用Geisinger电子健康记录（2008-2016），我们在宾夕法尼亚州的37个县进行了新发T2 D的巢式病例对照研究。该研究包括15，888例T2 D病例和79，435例无糖尿病的对照，年龄，性别和诊断或就诊年份的频率匹配为1：5。我们的特点是患者的居住人口普查区的健康的社会决定因素（SDOH）的四个方面，并到7类SDOH人口普查区类型以前产生的整个美国的降维技术。最后，由于SDOH人口普查区类型学将研究区域83%的人口普查区分为两个异质类别，称为农村负担得起的和郊区富裕的，以进一步描绘与T2 D相关的地理，我们将这两个类型学类别细分为行政社区类型（美国人口普查局的乡镇，自治市，城市的小型民事划分）。我们使用广义估计方程来检查1）4个SDOH指数，2）SDOH普查区类型，和3）改良类型与新发T2 D的几率的关联，控制个人水平的混杂变量。两个SDOH维度，更高的社会经济优势和更高的流动性（老年人和残疾成年人较少的区域）与T2 D的低几率独立相关。与农村负担得起的作为参考组相比，居住在极端贫困地区（比值比[95%置信区间] = 1.11 [1.02，1.21]）或多语种工作（1.07 [1.03，1.23]）与新发T2 D的几率较高相关。郊区富裕样与T2 D的较低几率相关（0.92 [0.87，0.97]）。在修改后的类型学中，在郊区富裕类城市（与农村负担得起类乡镇）中观察到最强的关联（1.37 [1.15，1.63]），其次是农村负担得起类城市（1.20 [1.05，1.36]）。我们的结论是，在评估T2 D发病的地理差异，这是有益的，进行多个维度的SDOH的同时评估。与修改后的类型学协会表明，在评估地理健康差异时，纳入政府，行为和经验相关的社区定义的重要性。
Evaluation of geographic disparities in type 2 diabetes (T2D) onset requires multidimensional approaches at a relevant spatial scale to characterize community types and features that could influence this health outcome. Using Geisinger electronic health records (2008–2016), we conducted a nested case-control study of new onset T2D in a 37-county area of Pennsylvania. The study included 15,888 incident T2D cases and 79,435 controls without diabetes, frequency-matched 1:5 on age, sex, and year of diagnosis or encounter. We characterized patients’ residential census tracts by four dimensions of social determinants of health (SDOH) and into a 7-category SDOH census tract typology previously generated for the entire United States by dimension reduction techniques. Finally, because the SDOH census tract typology classified 83% of the study region’s census tracts into two heterogeneous categories, termed rural affordable-like and suburban affluent-like, to further delineate geographies relevant to T2D, we subdivided these two typology categories by administrative community types (U.S. Census Bureau minor civil divisions of township, borough, city). We used generalized estimating equations to examine associations of 1) four SDOH indexes, 2) SDOH census tract typology, and 3) modified typology, with odds of new onset T2D, controlling for individual-level confounding variables. Two SDOH dimensions, higher socioeconomic advantage and higher mobility (tracts with fewer seniors and disabled adults) were independently associated with lower odds of T2D. Compared to rural affordable-like as the reference group, residence in tracts categorized as extreme poverty (odds ratio [95% confidence interval] = 1.11 [1.02, 1.21]) or multilingual working (1.07 [1.03, 1.23]) were associated with higher odds of new onset T2D. Suburban affluent-like was associated with lower odds of T2D (0.92 [0.87, 0.97]). With the modified typology, the strongest association (1.37 [1.15, 1.63]) was observed in cities in the suburban affluent-like category (vs. rural affordable-like–township), followed by cities in the rural affordable-like category (1.20 [1.05, 1.36]). We conclude that in evaluating geographic disparities in T2D onset, it is beneficial to conduct simultaneous evaluation of SDOH in multiple dimensions. Associations with the modified typology showed the importance of incorporating governmentally, behaviorally, and experientially relevant community definitions when evaluating geographic health disparities.
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影响因子：
10.4
作者：
Gee, Gilbert C;Payne-Sturges, Devon C
通讯作者：
Payne-Sturges, Devon C
影响因子：
5.5
作者：
Hipp JA;Chalise N
通讯作者：
Chalise N
DOI：
10.1097/phh.0000000000000800
发表时间：
2019-07-01
影响因子：
3.3
作者：
Chang, Man-Huei;Beckles, Gloria L.;Truman, Benedict I.
通讯作者：
Truman, Benedict I.
影响因子：
12.7
作者：
Gaskin DJ;Thorpe RJ Jr;McGinty EE;Bower K;Rohde C;Young JH;LaVeist TA;Dubay L
通讯作者：
Dubay L
影响因子：
5.1
作者：
Gluschkoff, K.;Elovainio, M.;Hintsa, T.
通讯作者：
Hintsa, T.