Associations of Four Community Factors With Longitudinal Change in Hemoglobin A1c Levels in Patients With Type 2 Diabetes

Hirsch, Annemarie G.; Durden, T. Elizabeth; Nordberg, Cara; Berger, Andrea; Schwartz, Brian S.

doi:10.2337/dc17-1200

Cited by 16 publications

(14 citation statements)

References 37 publications

(41 reference statements)

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“…Associations between the accessibility of unfavourable food environments and higher pre valence of type 2 diabetes [22][23][24] and between a healthy food environment and lower risk of type 2 diabetes have previously been established. 25,26 Despite the evidence generated thus far, some am biguity remains in the association between exposure to food environments and type 2 diabetes. Evidence is especially…”

Section: Introductionmentioning

confidence: 99%

Are exposures to ready-to-eat food environments associated with type 2 diabetes? A cross-sectional study of 347 551 UK Biobank adult participants

Sarkar

Webster

Gallacher

2018

The Lancet Planetary Health

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Background Rapid urbanisation and associated socioeconomic transformations have modified current lifestyles, shifting dietary preferences towards ready-to-eat, calorie-dense food of poor nutritional quality. The effect of ready-toeat food environments that sell food for instant consumption on the risk of type 2 diabetes has received scant attention. We therefore aimed to examine the association between exposure to ready-to-eat food environments and type 2 diabetes in a large and diverse population sample. Methods We conducted a cross-sectional study of adult male and female participants from the baseline phase of the UK Biobank cohort. Participants in this cohort were aged 37-73 years and resided in one of 21 cities in the UK. Readyto-eat food environments, which we determined from a modelled and linked built environment database, were objectively measured within 1-km catchment areas of the residential streets of participants and were expressed as metrics of density and proximity to the participants' homes. We used logistic regression models to examine the associations between exposure to ready-to-eat food environments and the odds of type 2 diabetes, adjusting for individual covariates such as physical activity. As sensitivity analyses, we investigated the associations between the street distance to the nearest ready-to-eat food outlet and type 2 diabetes. We also tested post hoc for effect modification by sex, income, body-mass index, and location of the UK Biobank collection centre. Findings Of 502 635 UK Biobank participants enrolled between March 13, 2006, and Oct 1, 2010, the sample analysed included 347 551 (69•1%) participants. The density of ready-to-eat food environments within a 1-km catchment area was associated with higher odds of type 2 diabetes for participants in the groups with highest exposure to restaurants and cafeterias (odss ratio 1•129, 95% CI 1•05-1•21; p=0•0007) and a composite measure of ready-to-eat outlet density (1•112, 1•02-1•21; p=0•0134) compared with those with no exposure. Exposure to hot and cold takeaways was only significantly associated with higher odds of type 2 diabetes at the second highest exposure category that we examined (1•076, 1•01-1•14; p=0•0171), representing a density of 0•75-2•15 units per km². A protective effect with distance decay was observed: participants in the highest quintile of street distance to nearest ready-to-eat food outlet reported lower odds of type 2 diabetes than those in the lowest quintile (0•842, 0•78-0•91; p<0•0001 for restaurants and cafeterias; and 0•913, 0•85-0•98; p=0•0173 for hot and cold takeaways). These effects were most pronounced in overweight participants (p=0•0329), but there was no evidence of interaction by sex, income, or UK Biobank collection centre. Interpretation Access to ready-to-eat food environments was positively associated with type 2 diabetes. Top-down policies aimed at minimising unhealthy food access could potentially reduce unhealthy consumption and risks of chronic diseases. Further long-term studies are needed t...

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Section: Introductionmentioning

confidence: 99%

Are exposures to ready-to-eat food environments associated with type 2 diabetes? A cross-sectional study of 347 551 UK Biobank adult participants

Sarkar

Webster

Gallacher

2018

The Lancet Planetary Health

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“…Neighborhood walkability has been related to lower incidence or prevalence of diabetes or hypertension in numerous studies (Bilal et al, 2018; Malambo et al, 2016; Sarkar et al, 2018), but little research has examined how it relates to control of these conditions. Two recent studies have related neighborhood land-use mix and a factor-derived physical activity favorability score to better glycemic control in urban populations with diabetes (Tabaei et al, 2017; Hirsch et al, 2018).…”

Section: Discussionmentioning

confidence: 99%

Identifying neighborhood characteristics associated with diabetes and hypertension control in an urban African-American population using geo-linked electronic health records

Lê‐Scherban

Ballester

Castro

et al. 2019

Preventive Medicine Reports

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For health care providers, information on community-level social determinants of health is most valuable when it is specific to the populations and health outcomes for which they are responsible. Diabetes and hypertension are highly prevalent conditions whose management requires an interplay of clinical treatment and behavioral modifications that may be sensitive to community conditions. We used geo-linked electronic health records from 2016 of African American patients of a network of federally qualified health centers in Philadelphia, PA to examine cross-sectional associations between characteristics of patients' residential neighborhoods and hypertension and diabetes control ( n = 1061 and n = 2633, respectively). Hypertension and diabetes control were defined to align with the Health Resources and Services Administration (HRSA) Uniform Data System (UDS) reporting requirements for HRSA-funded health centers. We examined associations with nine measures of neighborhood socioeconomic status (poverty, education, deprivation index), social environment (violent crime, perceived safety and social capital, racial segregation), and built environment (land-use mix, intersection density). In demographics-adjusted log-binomial regression models accounting for neighborhood-level clustering, poor diabetes and hypertension control were more common in highly segregated neighborhoods (i.e., high proportion of African American residents relative to the mean for Philadelphia; prevalence ratio = 1.27 [1.02–1.57] for diabetes, 1.22 [1.12–1.33] for hypertension) and less common in more walkable neighborhoods (i.e., higher retail land use). Neighborhood deprivation was also weakly associated with poor hypertension control. An important consideration in making geographic information actionable for providers is understanding how specific community-level determinants affect the patient population beyond individual-level determinants.

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“…Using previously reported methods, 20 we used Geisinger electronic health record (EHR) data from 1.6 million individuals to identify new onset type 2 diabetes from 2008 to 2016. Individuals represent the general population in the region with high residential stability.…”

Section: Methodsmentioning

confidence: 99%

“…19 In Pennsylvania, communities are defined administratively as townships, boroughs, and cities using census minor civil division boundaries. 20 In combination, these two definitions provide an opportunity to evaluate experientially and behaviourally relevant geographies as well as to further subdivide the broad category of ‘rural’, which includes a range of communities that vary in their associations with health outcomes. 21 22 …”

Section: Introductionmentioning

confidence: 99%

Association of community types and features in a case–control analysis of new onset type 2 diabetes across a diverse geography in Pennsylvania

et al. 2021

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ObjectivesTo 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.DesignNested case–control study within the open dynamic cohort of health system patients.SettingLarge, integrated health system in 37 counties in central and northeastern Pennsylvania, USA.Participants and analysisWe 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.ResultsBorough 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.ConclusionsUrban 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.

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Associations of Four Community Factors With Longitudinal Change in Hemoglobin A1c Levels in Patients With Type 2 Diabetes

Abstract: Community domains were associated with HbA change and blunted TI effectiveness.

Cited by 16 publications

References 37 publications

Are exposures to ready-to-eat food environments associated with type 2 diabetes? A cross-sectional study of 347 551 UK Biobank adult participants

Are exposures to ready-to-eat food environments associated with type 2 diabetes? A cross-sectional study of 347 551 UK Biobank adult participants

Identifying neighborhood characteristics associated with diabetes and hypertension control in an urban African-American population using geo-linked electronic health records

Association of community types and features in a case–control analysis of new onset type 2 diabetes across a diverse geography in Pennsylvania

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