INTRODUCTION: Inequitable access to leisure-time physical activity (LTPA) resources may explain geographic disparities in type 2 diabetes (T2D). We evaluated whether the neighborhood socioeconomic environment (NSEE) affects T2D through the LTPA environment. RESEARCH DESIGN AND METHODS: We conducted analyses in three study samples: the national Veterans Administration Diabetes Risk (VADR) cohort comprising electronic health records (EHR) of 4.1 million T2D-free veterans, the national prospective cohort REasons for Geographic and Racial Differences in Stroke (REGARDS) (11 208 T2D free), and a case-control study of Geisinger EHR in Pennsylvania (15 888 T2D cases). New-onset T2D was defined using diagnoses, laboratory and medication data. We harmonized neighborhood-level variables, including exposure, confounders, and effect modifiers. We measured NSEE with a summary index of six census tract indicators. The LTPA environment was measured by physical activity (PA) facility (gyms and other commercial facilities) density within street network buffers and population-weighted distance to parks. We estimated natural direct and indirect effects for each mediator stratified by community type. RESULTS: The magnitudes of the indirect effects were generally small, and the direction of the indirect effects differed by community type and study sample. The most consistent findings were for mediation via PA facility density in rural communities, where we observed positive indirect effects (differences in T2D incidence rates (95% CI) comparing the highest versus lowest quartiles of NSEE, multiplied by 100) of 1.53 (0.25, 3.05) in REGARDS and 0.0066 (0.0038, 0.0099) in VADR. No mediation was evident in Geisinger. CONCLUSIONS: PA facility density and distance to parks did not substantially mediate the relation between NSEE and T2D. Our heterogeneous results suggest that approaches to reduce T2D through changes to the LTPA environment require local tailoring.

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.

OBJECTIVE: We examined whether relative availability of fast-food restaurants and supermarkets mediates the association between worse neighborhood socioeconomic conditions and risk of developing type 2 diabetes (T2D). RESEARCH DESIGN AND METHODS: As part of the Diabetes Location, Environmental Attributes, and Disparities Network, three academic institutions used harmonized environmental data sources and analytic methods in three distinct study samples: (1) the Veterans Administration Diabetes Risk (VADR) cohort, a national administrative cohort of 4.1 million diabetes-free veterans developed using electronic health records (EHRs); (2) Reasons for Geographic and Racial Differences in Stroke (REGARDS), a longitudinal, epidemiologic cohort with Stroke Belt region oversampling (N = 11,208); and (3) Geisinger/Johns Hopkins University (G/JHU), an EHR-based, nested case-control study of 15,888 patients with new-onset T2D and of matched control participants in Pennsylvania. A census tract-level measure of neighborhood socioeconomic environment (NSEE) was developed as a community type-specific z-score sum. Baseline food-environment mediators included percentages of (1) fast-food restaurants and (2) food retail establishments that are supermarkets. Natural direct and indirect mediating effects were modeled; results were stratified across four community types: higher-density urban, lower-density urban, suburban/small town, and rural. RESULTS: Across studies, worse NSEE was associated with higher T2D risk. In VADR, relative availability of fast-food restaurants and supermarkets was positively and negatively associated with T2D, respectively, whereas associations in REGARDS and G/JHU geographies were mixed. Mediation results suggested that little to none of the NSEE-diabetes associations were mediated through food-environment pathways. CONCLUSIONS: Worse neighborhood socioeconomic conditions were associated with higher T2D risk, yet associations are likely not mediated through food-environment pathways.

Background: While there are known individual-level risk factors for kidney disease at time of type 2 diabetes diagnosis, little is known regarding the role of community context. We evaluated the association of community socioeconomic deprivation (CSD) and community type with estimated glomerular filtration rate (eGFR) when type 2 diabetes is diagnosed. Method(s): This was a retrospective cohort study of 13,144 adults with newly diagnosed type 2 diabetes in Pennsylvania. The outcome was the closest eGFR measurement within one year prior to and two weeks after type 2 diabetes diagnosis, calculated using the Chronic Kidney Disease Epidemiology Collaboration (CKD-Epi) equation. We used adjusted multinomial regression models to estimate associations of CSD (quartile 1, least deprivation) and community type (township, borough, city) with eGFR and used adjusted generalized estimating equation models to evaluate whether community features were associated with the absence of diabetes screening in the years prior to type 2 diabetes diagnosis. Result(s): Of the participants, 1279 (9.7%) had hyperfiltration and 1377 (10.5%) had reduced eGFR. Women were less likely to have hyperfiltration and more likely to have reduced eGFR. Black (versus White) race was positively associated with hyperfiltration when the eGFR calculation was corrected for race but inversely associated without the correction. Medical Assistance (ever versus never) was positively associated with reduced eGFR. Higher CSD and living in a city were each positively associated (odds ratio [95% confidence interval]) with reduced eGFR (CSD quartiles 3 and 4 versus quartile 1, 1.23 [1.04, 1.46], 1.32 [1.11, 1.58], respectively; city versus township, 1.38 [1.15, 1.65]). These features were also positively associated with the absence of a type 2 diabetes screening measure. Conclusion(s): In a population-based sample, more than twenty percent had hyperfiltration or reduced eGFR at time of type 2 diabetes diagnosis. Individual- and community-level factors were associated with these outcomes. Copyright © 2021 The Authors

Salutogenic effects of living near aquatic areas (blue space) remain underexplored, particularly in non-coastal and non-urban areas. We evaluated associations of residential proximity to inland freshwater blue space with new onset type 2 diabetes (T2D) in central and northeast Pennsylvania, USA, using medical records to conduct a nested case-control study. T2D cases (n = 15,888) were identified from diabetes diagnoses, medication orders, and laboratory test results and frequency-matched on age, sex, and encounter year to diabetes-free controls (n = 79,435). We calculated distance from individual residences to the nearest lake, river, tributary, or large stream, and residence within the 100-year floodplain. Logistic regression models adjusted for community socioeconomic deprivation and other confounding variables and stratified by community type (townships [rural/suburban], boroughs [small towns], city census tracts). Compared to individuals living ≥ 1.25 miles from blue space, those within 0.25 miles had 8% and 17% higher odds of T2D onset in townships and boroughs, respectively. Among city residents, T2D odds were 38–39% higher for those living 0.25 to < 0.75 miles from blue space. Residing within the floodplain was associated with 16% and 14% higher T2D odds in townships and boroughs. A post-hoc analysis demonstrated patterns of lower residential property values with nearer distance to the region's predominant waterbody, suggesting unmeasured confounding by socioeconomic disadvantage. This may explain our unexpected findings of higher T2D odds with closer proximity to blue space. Our findings highlight the importance of historic and economic context and interrelated factors such as flood risk and lack of waterfront development in blue space research.

Greenness may impact blood pressure (BP), though evidence is limited among individuals with type 2 diabetes (T2D), for whom BP management is critical. We evaluated associations of residential greenness with BP among individuals with T2D in geographically diverse communities in Pennsylvania. To address variation in greenness type, we evaluated modification of associations by percent forest. We obtained systolic (SBP) and diastolic (DBP) BP measurements from medical records of 9593 individuals following diabetes diagnosis. Proximate greenness was estimated within 1250-m buffers surrounding individuals' residences using the normalized difference vegetation index (NDVI) prior to blood pressure measurement. Percent forest was calculated using the U.S. National Land Cover Database. Linear mixed models with robust standard errors accounted for spatial clustering; models were stratified by community type (townships/boroughs/cities). In townships, the greenest communities, an interquartile range increase in NDVI was associated with reductions in SBP of 0.87 mmHg (95% CI: -1.43, -0.30) and in DBP of 0.41 mmHg (95% CI: -0.78, -0.05). No significant associations were observed in boroughs or cities. Evidence for modification by percent forest was weak. Findings suggest a threshold effect whereby high greenness may be necessary to influence BP in this population and support a slight beneficial impact of greenness on cardiovascular disease risk.

OBJECTIVES: To evaluate associations of community types and features with new onset type 2 diabetes in diverse communities. Understanding the location and scale of geographic disparities can lead to community-level interventions. DESIGN: Nested case-control study within the open dynamic cohort of health system patients. SETTING: Large, integrated health system in 37 counties in central and northeastern Pennsylvania, USA. PARTICIPANTS AND ANALYSIS: We used electronic health records to identify persons with new-onset type 2 diabetes from 2008 to 2016 (n=15 888). Persons with diabetes were age, sex and year matched (1:5) to persons without diabetes (n=79 435). We used generalised estimating equations to control for individual-level confounding variables, accounting for clustering of persons within communities. Communities were defined as (1) townships, boroughs and city census tracts; (2) urbanised area (large metro), urban cluster (small cities and towns) and rural; (3) combination of the first two; and (4) county. Community socioeconomic deprivation and greenness were evaluated alone and in models stratified by community types. RESULTS: Borough and city census tract residence (vs townships) were associated (OR (95% CI)) with higher odds of type 2 diabetes (1.10 (1.04 to 1.16) and 1.34 (1.25 to 1.44), respectively). Urbanised areas (vs rural) also had increased odds of type 2 diabetes (1.14 (1.08 to 1.21)). In the combined definition, the strongest associations (vs townships in rural areas) were city census tracts in urban clusters (1.41 (1.22 to 1.62)) and city census tracts in urbanised areas (1.33 (1.22 to 1.45)). Higher community socioeconomic deprivation and lower greenness were each associated with increased odds. CONCLUSIONS: Urban residence was associated with higher odds of type 2 diabetes than for other areas. Higher community socioeconomic deprivation in city census tracts and lower greenness in all community types were also associated with type 2 diabetes.

BACKGROUND: Diabetes prevalence and incidence vary by neighborhood socioeconomic environment (NSEE) and geographic region in the United States. Identifying modifiable community factors driving type 2 diabetes disparities is essential to inform policy interventions that reduce the risk of type 2 diabetes. OBJECTIVE: This paper aims to describe the Diabetes Location, Environmental Attributes, and Disparities (LEAD) Network, a group funded by the Centers for Disease Control and Prevention to apply harmonized epidemiologic approaches across unique and geographically expansive data to identify community factors that contribute to type 2 diabetes risk. METHODS: The Diabetes LEAD Network is a collaboration of 3 study sites and a data coordinating center (Drexel University). The Geisinger and Johns Hopkins University study population includes 578,485 individuals receiving primary care at Geisinger, a health system serving a population representative of 37 counties in Pennsylvania. The New York University School of Medicine study population is a baseline cohort of 6,082,146 veterans who do not have diabetes and are receiving primary care through Veterans Affairs from every US county. The University of Alabama at Birmingham study population includes 11,199 participants who did not have diabetes at baseline from the Reasons for Geographic and Racial Differences in Stroke (REGARDS) study, a cohort study with oversampling of participants from the Stroke Belt region. RESULTS: The Network has established a shared set of aims: evaluate mediation of the association of the NSEE with type 2 diabetes onset, evaluate effect modification of the association of NSEE with type 2 diabetes onset, assess the differential item functioning of community measures by geographic region and community type, and evaluate the impact of the spatial scale used to measure community factors. The Network has developed standardized approaches for measurement. CONCLUSIONS: The Network will provide insight into the community factors driving geographical disparities in type 2 diabetes risk and disseminate findings to stakeholders, providing guidance on policies to ameliorate geographic disparities in type 2 diabetes in the United States. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/21377.

Parent-based HIV prevention programming may play an important role in reaching youths early to help establish lifelong patterns of safe and healthy sexual behaviors. Families Matter! is a 5-session, evidence-based behavioral intervention designed for primary caregivers of children aged 9 to 12 years to promote positive parenting and effective parent-child communication about sexuality and sexual risk reduction. The program's 5-step capacity-building model was implemented with local government, community, and faith-based partners in 8 sub-Saharan African countries with good intervention fidelity and high levels of participant retention. Families Matter! may be useful in other resource-constrained settings.

We examine efficacy of the Parents Matter! Program (PMP), a program to teach African-American parents of preadolescents sexual communication and HIV-prevention skills, through a multicenter, randomized control trial. A total of 1115 parent-child participants were randomized to one of three intervention arms (enhanced, brief, control). Percentages and 95% confidence intervals compare parents' perception of child readiness to learn about sexual issues, communication effectiveness, and dyad concordance from baseline to 12 months postintervention. Wilcoxon rank sum tests compare the changes in scores measuring communication content in HIV/AIDS, abstinence, and condom use. Compared to control, parents in the enhanced arm increased perception of child readiness to learn about sex (16% vs. 29%; p < .001), and a greater proportion of parent-child dyads reported concordant responses on communication topics: HIV/AIDS (15%, 95% CI = 8-21%; p < .001), abstinence (13%, 95% CI = 7-20%; p < .001), condoms (15%, 95% CI = 9-22%; p < .001). Increases in communication scores in HIV/AIDS, abstinence, and condom use were greater in the enhanced arm than control (p < 0.01). We conclude that the enhanced PMP can help parents educate children about HIV and prepare children to avoid sexual risk.

Evidence-based interventions (EBIs) are critical for effective HIV prevention, but time and resources required to develop and evaluate new interventions are limited. Alternatively, existing EBIs can be adapted for new settings if core elements remain intact. We describe the process of adapting the Parents Matter! Program, an EBI originally developed for African American parents to promote effective parent-child communication about sexual risk reduction and parenting skills, for use in rural Kenya. A systematic process was used to assess the community's needs, identify potential EBIs, identify and make adaptations, pilot-test the adapted intervention, and implement and monitor the adapted EBI. Evaluation results showed the adapted EBI retained its effectiveness, successfully increasing parent-child sexual communication and parenting skills. Our experience suggests an EBI can be successfully adapted for a new context if it is relevant to local needs, the process is led by a multidisciplinary team with community representation, and pilot-testing and early implementation are well monitored.

This study explored parent-child communication about HIV/AIDS among two populations disproportionately affected by HIV. Similar computer-assisted surveys were completed by parents of pre-teens, including 1,115 African American parents of 9-12-year-old children in southeastern US and 403 parents of 10-12-year-old children in Nyanza Province, Kenya. Multivariate analyses identified factors associated with parental report of ever talking to their child about HIV/AIDS. Twenty-nine percent of US parents and 40% in Kenya had never talked to their pre-teen about HIV/AIDS. In both countries, communication was more likely if parents perceived their child to be ready to learn about sex topics, had gotten information to educate their child about sex, and had greater sexual communication responsiveness (skill, comfort, and confidence communicating about sexuality). Programs are needed that help parents assess children's readiness to learn about sexual issues; access accurate information about adolescent sexual risks; and acquire the responsiveness needed to discuss sexual issues, including HIV/AIDS.