Associations of Residential Socioeconomic, Food, and Built Environments With Glycemic Control in Persons With Diabetes in New York City From 2007-2013

Association between area-level walkability and glycated haemoglobin: a Portuguese population-based study

Diabetes poses a substantial disease burden, prompting preventive interventions. Physical inactivity, a major risk factor for type 2 diabetes, can potentially be mitigated by enhancing area-level walkability. Despite this, limited population-based studies have investigated the link between walkability and objective diabetes measures. Our study aims to estimate the association between area-level walkability and individual glycated haemoglobin levels in the Portuguese adult population without the diagnosis of diabetes. Data from the 2011 census and an updated street map were obtained to construct a walkability index based on residential density, land-use mix, and street connectivity. Individual health data were sourced from The National Health Examination Survey (INSEF) 2015, a representative survey of the Portuguese adult population. Gamma regression was employed for estimation of the main associations, revealing that residing in moderately walkable areas significantly reduced average glycated haemoglobin levels (Exp(β) = 0.906; 95% CI: 0.821, 0.999) compared to the least walkable areas. The association was less pronounced and not statistically significant for the third tertile of walkability (Exp(β) = 0.919; 95% CI: 0.822, 1.028). Our findings highlight a nonlinear protective association between walkability and glycated haemoglobin, emphasizing the potential policy implications for urban planning, diabetes prevention, and health promotion.

Association of neighbourhood walkability and haemoglobin A1c levels among Latino and non-Hispanic White patients with diabetes

BACKGROUND

Neighbourhood walkability can benefit cardiovascular health. Latino patients are more likely than non-Hispanic White patients to have diabetes, and evidence has shown better diabetes-related outcomes for patients living in neighbourhoods conducive to physical activity. Our objective was to determine whether neighbourhood walkability was associated with haemoglobin A1c (HbA1c) levels among English- and Spanish-preferring Latino patients compared to non-Hispanic White patients.

METHODS

We used electronic health record data from patients in the OCHIN, Inc. network of community health centres (CHC) linked to public walkability data. Patients included those age ≥ 18 with ≥ 1 address recorded, with a study clinic visit from 2012 to 2020, and a type 2 diabetes diagnosis (N = 159,289). Generalized estimating equations logistic regression, adjusted for relevant covariates, was used to model the primary binary outcome of always having HbA1c < 7 by language/ethnicity and walkability score.

RESULTS

For all groups, the walkability score was not associated with higher odds and prevalence of always having HbA1c < 7. Non-Hispanic White patients were most likely to have HbA1c always < 7 (prevalence ranged from 32.8% [95%CI = 31.2-34.1] in the least walkable neighbourhoods to 33.4% [95% CI 34.4-34.7] in the most walkable), followed by English-preferring Latinos (28.6% [95%CI = 25.4-31.8]-30.7% [95% CI 29.0-32.3]) and Spanish-preferring Latinos (28.3% [95% CI 26.1-30.4]-29.3% [95% CI 28.2-30.3]).

CONCLUSIONS

While walkability score was not significantly associated with glycaemic control, control appeared to increase with walkability, suggesting other built environment factors, and their interaction with walkability and clinical care, may play key roles. Latino patients had a lower likelihood of HbA1c always < 7, demonstrating an opportunity for equity improvements in diabetes care.

Neighborhood built and food environment in relation to glycemic control in people with type 2 diabetes in the moving to health study

OBJECTIVE

To examine whether built environment and food metrics are associated with glycemic control in people with type 2 diabetes.

RESEARCH DESIGN AND METHODS

We included 14,985 patients with type 2 diabetes using electronic health records from Kaiser Permanente Washington. Patient addresses were geocoded with ArcGIS using King County and Esri reference data. Built environment exposures estimated from geocoded locations included residential unit density, transit threshold residential unit density, park access, and having supermarkets and fast food restaurants within 1600-m Euclidean buffers. Linear mixed effects models compared mean changes of HbA1c from baseline at 1, 3 (primary) and 5 years by each built environment variable.

RESULTS

Patients (mean age = 59.4 SD = 13.2, 49.5% female, 16.6% Asian, 9.8% Black, 5.5% Latino/Hispanic, 57.1% White, 20% insulin dependent, mean BMI = 32.7±7.7) had an average of 6 HbA1c measures available. Participants in the 1st tertile of residential density (lowest) had a greater decline in HbA1c (-0.42, -0.43, and -0.44 in years 1, 3, and 5 respectively) than those in the 3rd tertile (HbA1c = -0.37 at 1- and 3-years and -0.36 at 5-years; all p-values <0.05). Having any supermarkets within 1600 m of home was associated with a greater decrease in HbA1c at 1-year and 3-years compared to having none (all p-values <0.05).

CONCLUSIONS

Lower residential density and better proximity to supermarkets may benefit HbA1c control in people with people with type 2 diabetes. However, effects were small and indicate limited clinical significance.

Social determinants of health and diabetes: using a nationally representative sample to determine which social determinant of health model best predicts diabetes risk

OBJECTIVES

Social determinants of health (SDOH) research demonstrates poverty, access to healthcare, discrimination, and environmental factors influence health outcomes. Several models are commonly used to assess SDOH, yet there is limited understanding of how these models differ regarding their ability to predict the influence of social determinants on diabetes risk. This study compares the utility of four SDOH models for predicting diabetes disparities.

STUDY DESIGN

We utilized The National Longitudinal Study of Adolescent to Adulthood (Add Health) to compare SDOH models and their ability to predict risk of diabetes and obesity.

METHODS

Previous literature has identified the World Health Organization (WHO), Healthy People, County Health Rankings, and Kaiser Family Foundation as the conventional SDOH models. We used these models to operationalize SDOH using the Add Health dataset. Add Health data were used to perform logistic regressions for HbA1c and linear regressions for body mass index (BMI).

RESULTS

The Kaiser model accounted for the largest proportion of variance (19%) in BMI. Race/ethnicity was a consistent factor predicting BMI across models. Regarding HbA1c, the Kaiser model also accounted for the largest proportion of variance (17%). Race/ethnicity and wealth was a consistent factor predicting HbA1c across models.

CONCLUSION

Policy and practice interventions should consider these factors when screening for and addressing the effects of SDOH on diabetes risk. Specific SDOH models can be constructed for diabetes based on which determinants have the largest predictive value.

An Integrative Review of Social Determinants of Glycemic Targets Achievement in Adults with Type 2 Diabetes in the United States

Several individual social determinants of health have been identified as significant factors contributing to achieving glycemic targets (glycated hemoglobin < 7). However, it remains unclear how these social variables individually or collectively contribute to glycemic targets among adults with type 2 diabetes (T2D) in the United States (U.S.) The purpose of the current integrative review (IR) was to describe and synthesize findings from studies on social determinants of glycemic target achievement in adults with T2D in the U.S. and integrate them into the United States Department of Health and Human Services Conceptual Framework. The databases searched included PubMed, CINAHL Plus with Full Text, Medline with Full Text [EBSCO], Google Scholar, bibliography, and hand searching. A total of 948 records were identified. After excluding duplicates and irrelevant studies based on inclusion and exclusion criteria through title, abstract, and full-text screening, 13 studies were finally included in this IR. The results revealed that race/ethnicity, economic access and stability, educational access and quality, healthcare access and quality, neighborhood and built environment, and social and community context contribute to glycemic target achievement among adult patients with T2D in the U.S. Integrating findings from key studies on social determinants of glycemic health may contribute to developing interventions aimed at reducing and eventually eradicating health disparities for individuals with and at risk for T2D in the U.S.

Chicago Neighborhood Context and Racial/Ethnic Disparities in Maternal Diabetes

OBJECTIVES

To determine if rates of maternal diabetes vary by race, ethnicity, and neighborhood hardship.

METHODS

We conducted a secondary analysis of live births in Chicago from 2010 to 2017. Our sample was restricted to Non-Hispanic White, Non-Hispanic Black, Mexican, Non-Hispanic Asian, and Other Hispanic mothers between the ages of 15 and 50, with singleton births. The addresses of mothers were geocoded to specific neighborhoods, which we stratified into tertiles using the Economic Hardship Index. We used generalized logit mixed models to examine the interaction between race/ethnicity, neighborhood economic hardship, and maternal diabetes.

RESULTS

In our cohort of 299,053 mothers, 4.75% were diagnosed with gestational diabetes. Asian mothers had the highest frequency of gestational diabetes (8.3%), followed by Mexican mothers (6.8%). Within their respective racial/ethnic groups, Asian and Mexican mothers living in medium hardship neighborhoods had the highest odds of gestational diabetes compared to the reference group (OR 2.80, 95%CI 2.53, 3.19; OR 2.30, 95%CI 2.12, 2.49 respectively). Overall rates of preexisting diabetes were 0.9% and were highest among Mexican and Black mothers (1.26% and 1.06%, respectively). Asian mothers in medium hardship neighborhoods had the greatest odds of preexisting diabetes, among all Asian mothers and compared to the reference (OR 4.71 95% CI 3.60, 6.16).

CONCLUSIONS

For racial and ethnic minoritized mothers, gestational and preexisting diabetes do not increase in a step-wise fashion with neighborhood hardship; rates were often higher in low and medium hardship neighborhoods.

Neighbourhood deprivation in childhood and adulthood and risk of arterial stiffness: the Cardiovascular Risk in Young Finns study

Purpose: Individual socioeconomic status is associated with increased arterial stiffness, but limited data are available on the relations of neighbourhood deprivation with this vascular measure. We prospectively examined whether neighbourhood deprivation in childhood and adulthood predicts arterial stiffness indicated by pulse wave velocity (PWV).Materials and methods: The study population comprised 1,761 participants aged 3-18 years at baseline (1980) from the longitudinal Cardiovascular Risk in Young Finns cohort study. PWV was measured in 2007 by whole-body impedance cardiography at ages 30-45 years. Cumulative lifetime neighbourhood deprivation was assessed using data from socioeconomic circumstances in participants' lifetime residential neighbourhoods, categorised as low versus high deprivation.Results: High deprivation in childhood and adulthood was associated with higher PWV in adulthood after adjustment for age, sex, and place of birth (mean difference = 0.57 m/s, 95%CI = 0.26-0.88, P for trend = 0.0004). This association was attenuated but remained statistically significant after further adjustment for childhood parental socioeconomic status and adulthood individual socioeconomic status (mean difference = 0.37 m/s, 95%CI = 0.05-0.70, P for trend 0.048). Also, low individual socioeconomic status in adulthood was associated with higher PWV when adjusted for age, sex, place of birth, parental socioeconomic status in childhood, and lifetime neighbourhood deprivation (mean difference = 0.54 m/s, 95%CI = 0.23-0.84, P for trend 0.0001).Conclusion: These findings suggest that lifetime neighbourhood deprivation and low adulthood socioeconomic status are independent risk factors for increased arterial stiffness in adulthood.

The role of neighborhood inequalities on diabetes prevention care: a mini-review

An emerging research niche has focused on the link between social determinants of health and diabetes mellitus, one of the most prevalent non-communicable diseases in modern society. The aim of the present mini-review is to explore and summarize current findings in this field targeting high-income countries. In the presence of disadvantaged neighborhood factors (including socioeconomic status, food environment, walkability and neighborhood aesthetics), diabetes prevention and care are affected at a multidimensional level. The vast majority of the included studies suggest that, besides individual risk factors, aggregated neighborhood inequalities should be tackled to implement effective evidence-based policies for diabetes mellitus.

Cumulative Experience of Neighborhood Walkability and Change in Weight and Waist Circumference in REGARDS

Neighborhood walkability-features of the built environment that promote pedestrian activity-has been associated with greater physical activity and lower body mass index (BMI; calculated as weight (kg)/height (m)2) among neighborhood residents. However, much of the literature has been cross-sectional and only a few cohort studies have assessed neighborhood features throughout follow-up. Using data from the Reasons for Geographic and Racial Differences in Stroke Study (2003-2016) and a neighborhood walkability index (NWI) measured annually during follow-up, we assessed whether the cumulative experience of neighborhood walkability (NWI-years) predicted BMI and waist circumference after approximately 10 years of follow-up, controlling for these anthropometric measures at enrollment. Analyses were adjusted for individual-level sociodemographic covariates and the cumulative experience of neighborhood poverty rate and neighborhood greenspace coverage. Almost a third (29%) of participants changed address at least once during follow-up. The first change of residence, on average, brought the participants to neighborhoods with higher home values and lower NWI scores than their originating neighborhoods. Compared with those having experienced the lowest quartile of cumulative NWI-years, those who experienced the highest quartile had 0.83 lower BMI (95% confidence interval, -1.5, -0.16) and 1.07-cm smaller waist circumference (95% confidence interval, -1.96, -0.19) at follow-up. These analyses provide additional longitudinal evidence that residential neighborhood features that support pedestrian activity are associated with lower adiposity.

The Impact of Neighborhoods on Diabetes Risk and Outcomes: Centering Health Equity

Neighborhood environments significantly influence the development of diabetes risk factors, morbidity, and mortality throughout an individual's life. The social, economic, and physical environments of a neighborhood all affect the health risks of individuals and communities and also affect population health inequities. Factors such as access to healthy food, green spaces, safe housing, and transportation options can impact the health outcomes of residents. Social factors, including social cohesion and neighborhood safety, also play an important role in shaping neighborhood environments and can influence the development of diabetes. Therefore, understanding the complex relationships between neighborhood environments and diabetes is crucial for developing effective strategies to address health disparities and promote health equity. This review presents landmark findings from studies that examined associations between neighborhood socioeconomic, built and physical, and social environmental factors and diabetes-related risk and outcomes. Our framework emphasizes the historical context and structural and institutional racism as the key drivers of neighborhood environments that ultimately shape diabetes risk and outcomes. To address health inequities in diabetes, we propose future research areas that incorporate health equity principles and place-based interventions.

Neighborhood-Level Risk Factors for Severe Hyperglycemia among Emergency Department Patients without a Prior Diabetes Diagnosis

A person's place of residence is a strong risk factor for important diagnosed chronic diseases such as diabetes. It is unclear whether neighborhood-level risk factors also predict the probability of undiagnosed disease. The objective of this study was to identify neighborhood-level variables associated with severe hyperglycemia among emergency department (ED) patients without a history of diabetes. We analyzed patients without previously diagnosed diabetes for whom a random serum glucose value was obtained in the ED. We defined random glucose values ≥ 200 mg/dL as severe hyperglycemia, indicating probable undiagnosed diabetes. Patient addresses were geocoded and matched with neighborhood-level socioeconomic measures from the American Community Survey and claims-based surveillance estimates of diabetes prevalence. Neighborhood-level exposure variables were standardized based on z-scores, and a series of logistic regression models were used to assess the association of selected exposures and hyperglycemia adjusting for biological and social individual-level risk factors for diabetes. Of 77,882 ED patients without a history of diabetes presenting in 2021, 1,715 (2.2%) had severe hyperglycemia. Many geospatial exposures were associated with uncontrolled hyperglycemia, even after controlling for individual-level risk factors. The most strongly associated neighborhood-level variables included lower markers of educational attainment, higher percentage of households where limited English is spoken, lower rates of white-collar employment, and higher rates of Medicaid insurance. Including these geospatial factors in risk assessment models may help identify important subgroups of patients with undiagnosed disease.

Influence of Gestational Diabetes Mellitus on Diabetes Risk and Glycemic Control in a Retrospective Population-Based Cohort

OBJECTIVE

Racial/ethnic-specific estimates of the influence of gestational diabetes mellitus (GDM) on type 2 diabetes remain underexplored in large population-based cohorts. We estimated racial/ethnic differences in the influence of GDM on diabetes risk and glycemic control in a multiethnic, population-based cohort of postpartum women.

RESEARCH DESIGN AND METHODS

Hospital discharge and vital registry data for New York City (NYC) births between 2009 and 2011 were linked with NYC A1C Registry data between 2009 and 2017. Women with baseline diabetes (n = 2,810) were excluded for a final birth cohort of 336,276. GDM on time to diabetes onset (two A1C tests of ≥6.5% from 12 weeks postpartum onward) or glucose control (first test of A1C <7.0% following diagnosis) was assessed using Cox regression with a time-varying exposure. Models were adjusted for sociodemographic and clinical factors and stratified by race/ethnicity.

RESULTS

The cumulative incidence for diabetes was 11.8% and 0.6% among women with and without GDM, respectively. The adjusted hazard ratio (aHR) of GDM status on diabetes risk was 11.5 (95% CI 10.8, 12.3) overall, with slight differences by race/ethnicity. GDM was associated with a lower likelihood of glycemic control (aHR 0.85; 95% CI 0.79, 0.92), with the largest negative influence among Black (aHR 0.77; 95% CI 0.68, 0.88) and Hispanic (aHR 0.84; 95% CI 0.74, 0.95) women. Adjustment for screening bias and loss to follow-up modestly attenuated racial/ethnic differences in diabetes risk but had little influence on glycemic control.

CONCLUSIONS

Understanding racial/ethnic differences in the influence of GDM on diabetes progression is critical to disrupt life course cardiometabolic disparities.

Structural Racism as an Upstream Social Determinant of Diabetes Outcomes: A Scoping Review

OBJECTIVE

To evaluate the evidence on the role of structural racism as an upstream factor impacting diabetes outcomes, identify current gaps, and recommend areas for future work.

RESEARCH DESIGN AND METHODS

A reproducible search of Medline and Ovid was used. Structural factors based on the World Health Organization social determinants of health framework (governance, macroeconomic policy, social policy, public policy, and cultural and societal values) had to be included as measured variables or contextual factors discussed as upstream influences. Outcomes included 1) hemoglobin A1c (HbA1c), 2) LDL, 3) BMI, 4) quality of life, 5) self-efficacy, 6) mortality, 7) years of life lost, and 8) self-care behaviors.

RESULTS

Thirteen articles were included for final synthesis. Ten studies focused on governance, two on social policies, one on public policies, and one on cultural and societal values. Results highlight significant associations between structural racism and poorer clinical outcomes (HbA1c and blood pressure), worse self-care behaviors (diet and physical activity), lower standards of care, higher mortality, and more years of life lost for adults with diabetes.

CONCLUSIONS

There is a paucity of work investigating the relationship between structural racism and diabetes outcomes. Five areas for future work include 1) more rigorous research on the relationship between structural racism, downstream social determinants, and health outcomes in diabetes, 2) policy assessments specific to diabetes outcomes, 3) research designed to examine pathways and mechanisms of influence, 4) intervention development to mitigate the impact of structural racism, and 5) tracking and monitoring of change over time.

Cross-Sectional Study of Location-Based Built Environments, Physical Activity, Dietary Intake, and Body Mass Index in Adult Twins

We examined relationships between walkability and health behaviors between and within identical twin pairs, considering both home (neighborhood) walkability and each twin's measured activity space. Continuous activity and location data (via accelerometry and GPS) were obtained in 79 pairs over 2 weeks. Walkability was estimated using Walk Score^® (WS); home WS refers to neighborhood walkability, and GPS WS refers to the mean of individual WSs matched to every GPS point collected by each participant. GPS WS was assessed within (WHN) and out of the neighborhood (OHN), using 1-mile Euclidean (air1mi) and network (net1mi) buffers. Outcomes included walking and moderate-to-vigorous physical activity (MVPA) bouts, dietary energy density (DED), and BMI. Home WS was associated with WHN GPS WS (b = 0.71, SE = 0.03, p < 0.001 for air1mi; b = 0.79, SE = 0.03, p < 0.001 for net1mi), and OHN GPS WS (b = 0.18, SE = 0.04, p < 0.001 for air1mi; b = 0.22, SE = 0.04, p < 0.001 for net1mi). Quasi-causal relationships (within-twin) were observed for home and GPS WS with walking (ps < 0.01), but not MVPA, DED, or BMI. Results support previous literature that neighborhood walkability has a positive influence on walking.

Neighbourhood walkability is associated with risk of gestational diabetes: A cross-sectional study in New York City

BACKGROUND

Despite the links between neighbourhood walkability and physical activity, body size and risk of diabetes, there are few studies of neighbourhood walkability and risk of gestational diabetes (GD).

OBJECTIVES

Assess whether higher neighbourhood walkability is associated with lower risk of GD in New York City (NYC).

METHODS

Cross-sectional analyses of a neighbourhood walkability index (NWI) score and density of walkable destinations (DWD) and risk of GD in 109,863 births recorded in NYC in 2015. NWI and DWD were measured for the land area of 1 km radius circles around the geographic centroid of each Census block of residence. Mixed generalised linear models, with robust standard error estimation and random intercepts for NYC Community Districts, were used to estimate risk ratios for GD for increasing quartiles of each of the neighbourhood walkability measures after adjustment for the pregnant individual's age, race and ethnicity, parity, education, nativity, and marital status and the neighbourhood poverty rate.

RESULTS

Overall, 7.5% of pregnant individuals experienced GD. Risk of GD decreased across increasing quartiles of NWI, with an adjusted risk ratio of 0.81 (95% Confidence Interval (CI) 0.75, 0.87) comparing those living in areas in the 4th quartile of NWI to those in the first quartile. Similarly, for comparisons of the 4th to 1st quartile of DWD, the adjusted risk ratio for GD was 0.77 (95% CI 0.71, 0.84).

CONCLUSIONS

These analyses find support for the hypothesis that higher neighbourhood walkability is associated with a lower risk of GD. The analyses provide further health related support for urban design policies to increase walkability.

Impact of Contextual-Level Social Determinants of Health on Newer Antidiabetic Drug Adoption in Patients with Type 2 Diabetes

BACKGROUND

We aimed to investigate the association between contextual-level social determinants of health (SDoH) and the use of novel antidiabetic drugs (ADD), including sodium-glucose cotransporter-2 inhibitors (SGLT2i) and glucagon-like peptide-1 receptor agonists (GLP1a) for patients with type 2 diabetes (T2D), and whether the association varies across racial and ethnic groups.

METHODS

Using electronic health records from the OneFlorida+ network, we assembled a cohort of T2D patients who initiated a second-line ADD in 2015-2020. A set of 81 contextual-level SDoH documenting social and built environment were spatiotemporally linked to individuals based on their residential histories. We assessed the association between the contextual-level SDoH and initiation of SGTL2i/GLP1a and determined their effects across racial groups, adjusting for clinical factors.

RESULTS

Of 28,874 individuals, 61% were women, and the mean age was 58 (±15) years. Two contextual-level SDoH factors identified as significantly associated with SGLT2i/GLP1a use were neighborhood deprivation index (odds ratio [OR] 0.87, 95% confidence interval [CI] 0.81-0.94) and the percent of vacant addresses in the neighborhood (OR 0.91, 95% CI 0.85-0.98). Patients living in such neighborhoods are less likely to be prescribed with newer ADD. There was no interaction between race-ethnicity and SDoH on the use of newer ADD. However, in the overall cohort, the non-Hispanic Black individuals were less likely to use newer ADD than the non-Hispanic White individuals (OR 0.82, 95% CI 0.76-0.88).

CONCLUSION

Using a data-driven approach, we identified the key contextual-level SDoH factors associated with not following evidence-based treatment of T2D. Further investigations are needed to examine the mechanisms underlying these associations.

Association of community walkability and glycemic control among pregnant individuals with pregestational diabetes mellitus

BACKGROUND

Neighborhood walkability is a community-level social determinant of health that measures whether people who live in a neighborhood walk as a mode of transportation. Whether neighborhood walkability is associated with glycemic control among pregnant individuals with pregestational diabetes remains to be defined.

OBJECTIVE

This study aimed to evaluate the association between community-level neighborhood walkability and glycemic control as measured by hemoglobin A1c (A1C) among pregnant individuals with pregestational diabetes.

STUDY DESIGN

This was a retrospective analysis of pregnant individuals with pregestational diabetes enrolled in an integrated prenatal and diabetes care program from 2012 to 2016. Participant addresses were geocoded and linked at the census-tract level. The exposure was community walkability, defined by the US Environmental Protection Agency National Walkability Index (score range 1-20), which incorporates intersection density (design), proximity to transit stops (distance), and a mix of employment and household types (diversity). Individuals from neighborhoods that were the most walkable (score, 15.26-20.0) were compared with those from neighborhoods that were less walkable (score <15.26), as defined per national Environmental Protection Agency recommendations. The outcomes were glycemic control, including A1C <6.0% and <6.5%, measured both in early and late pregnancy, and mean change in A1C across pregnancy. Modified Poisson regression and linear regression were used, respectively, and adjusted for maternal age, body mass index at delivery, parity, race and ethnicity as a social determinant of health, insurance status, baseline A1C, gestational age at A1C measurement in early and late pregnancy, and diabetes type.

RESULTS

Among 417 pregnant individuals (33% type 1, 67% type 2 diabetes mellitus), 10% were living in the most walkable communities. All 417 individuals underwent A1C assessment in early pregnancy (median gestational age, 9.7 weeks; interquartile range, 7.4-14.1), and 376 underwent another A1C assessment in late pregnancy (median gestational age, 30.4 weeks; interquartile range, 27.8-33.6). Pregnant individuals living in the most walkable communities were more likely to have an A1C <6.0% in early pregnancy (15% vs 8%; adjusted relative risk, 1.46; 95% confidence interval, 1.00-2.16), and an A1C <6.5% in late pregnancy compared with those living in less walkable communities (13% vs 9%; adjusted relative risk, 1.33; 95% confidence interval, 1.08-1.63). For individuals living in the most walkable communities, the median A1C was 7.5 (interquartile range, 6.0-9.4) in early pregnancy and 5.9 (interquartile range, 5.4-6.4) in late pregnancy. For those living in less walkable communities, the median A1C was 7.3 (interquartile range, 6.2-9.2) in early pregnancy and 6.2 (interquartile range, 5.6-7.1) in late pregnancy. Change in A1C across pregnancy was not associated with walkability.

CONCLUSION

Pregnant individuals with pregestational diabetes mellitus living in more walkable communities had better glycemic control in both early and late pregnancy. Whether community-level interventions to enhance neighborhood walkability can improve glycemic control in pregnancy requires further study.

The National Clinical Care Commission Report to Congress: Background, Methods, and Foundational Recommendations

Since the first Federal Commission on Diabetes issued its report in 1975, the diabetes epidemic in the U.S. has accelerated, and efforts to translate advances in diabetes treatment into routine clinical practice have stalled. In 2021, the National Clinical Care Commission (NCCC) delivered a report to Congress that provided recommendations to leverage federal policies and programs to more effectively prevent and treat diabetes and its complications. In the five articles in this series, we present the NCCC's evidence-based recommendations to 1) reduce diabetes-related risks, prevent type 2 diabetes, and avert diabetes complications through changes in federal policies and programs affecting the general population; 2) prevent type 2 diabetes in at-risk individuals through targeted lifestyle and medication interventions; and 3) improve the treatment of diabetes and its complications to improve the health outcomes of people with diabetes. In this first article, we review the successes and limitations of previous federal efforts to combat diabetes. We then describe the establishment of and charge to the NCCC. We discuss the development of a hybrid conceptual model that guided the NCCC's novel all-of-government approach to address diabetes as both a societal and medical problem. We then review the procedures used by the NCCC to gather information from federal agencies, stakeholders, key informants, and the public and to conduct literature reviews. Finally, we review the NCCC's three foundational recommendations: 1) improve the coordination of non-health-related and health-related federal agencies to address the social and environmental conditions that are accelerating the diabetes epidemic; 2) ensure that all Americans at risk for and with diabetes have health insurance and access to health care; and 3) ensure that all federal policies and programs promote health equity in diabetes.

Pathways between neighbourhood factors, stress and glycaemic control in individuals with type 2 diabetes in Southeastern United States: a cross-sectional pathway analysis

OBJECTIVES

Understanding the pathway by which neighbourhood factors influence glycaemic control may be crucial to addressing health disparities in diabetes. This study aimed to examine if the pathway between neighbourhood factors and glycaemic control is mediated by stress.

DESIGN

Structured equation modelling (SEM) was used to investigate direct and indirect effects in the relationship between neighbourhood factors, stress and glycaemic control, with standardised estimates to allow comparison of paths.

PARTICIPANTS

Data was obtained from 615 adults with type 2 diabetes in the Southeastern United States.

PRIMARY AND SECONDARY OUTCOME MEASURES

The primary outcome variable was glycaemic control determined by glycated haemoglobin (HbA1c) within the prior 6 months. Neighbourhood factors included neighbourhood violence, aesthetic quality of the neighbourhood, access to healthy food, and social cohesion. Stress was measured using the perceived stress scale.

RESULTS

In the final model (χ²(158)=406.97, p<0.001, root mean square error of approximation=0.05, p-close 0.38, Comparative Fit Index=0.97, Tucker-Lewis index=0.96, the coefficient of determination=1.0), violence (r=0.79, p=0.006), neighbourhood aesthetics (r=0.74, p=0.02) and social cohesion (r=0.57, p=0.04) were significantly associated with higher perceived stress. Stress (r=0.06, p=0.004) was directly associated with higher glycaemic control. Significant indirect effects existed between violence and higher HbA1c (r=0.05, p=0.04). After controlling for other neighbourhood factors, there was no significant relationship between access to healthy food and either stress or glycaemic control.

CONCLUSIONS

While a number of neighbourhood factors were directly associated with stress, only neighbourhood violence had a significant indirect effect on glycaemic control via stress within the tested pathway. Future studies should examine individual-level stress management interventions and should consider community-level interventions targeting neighbourhood violence as strategies for addressing disparities in diabetes.

Food insecurity, diet quality, and suboptimal diabetes management among US adults with diabetes

INTRODUCTION

A healthy diet is recommended to support diabetes management, including HbA1c, blood pressure, and cholesterol (ABC) control, but food insecurity is a barrier to consuming a healthy diet. We determined the prevalence of food insecurity and diet quality among US adults with diabetes and the associations with ABC management.

RESEARCH DESIGN AND METHODS

Cross-sectional analyses were conducted among 2075 adults ≥20 years with diagnosed diabetes who participated in the 2013-2018 National Health and Nutrition Examination Surveys. Food insecurity was assessed using a standard questionnaire and diet quality was assessed using quartiles of the 2015 Healthy Eating Index. Adjusted ORs (aOR, 95% CI) were calculated from logistic regression models to determine the association between household food insecurity/diet quality and the ABCs while controlling for sociodemographic characteristics, healthcare utilization, smoking, medication for diabetes, blood pressure, or cholesterol, and body mass index.

RESULTS

Overall, 17.6% of adults had food insecurity/low diet quality; 14.2% had food insecurity/high diet quality; 33.1% had food security/low diet quality; and 35.2% had food security/high diet quality. Compared with adults with food security/high diet quality, those with food insecurity/low diet quality were significantly more likely to have HbA1c ≥7.0% (aOR=1.85, 95% CI 1.23 to 2.80) and HbA1c ≥8.0% (aOR=1.79, 95% CI 1.04 to 3.08); food insecurity/high diet quality was significantly associated with elevated HbA1c; and food security/low diet quality with elevated A1c.

CONCLUSIONS

Food insecurity, regardless of diet quality, was significantly associated with elevated A1c. For people with food insecurity, providing resources to reduce food insecurity could strengthen the overall approach to optimal diabetes management.

Diabetes And The Fragmented State Of US Health Care And Policy

Progress in the prevention and treatment of type 2 diabetes-the dominant form of diabetes-appears to have stalled in the US over the past decade, and diabetes-related morbidity has increased nationally. The most geographically and socioeconomically disadvantaged segments of the population have been especially hard hit, and interventions that reduce the risk for diabetes have not reached these populations. In this overview article we lay out how fragmentation in health policy and governance, payers and reimbursement design, and service delivery in the US has contributed to low accountability and coordination, and thus stagnation and persistent inequities. We also review the evidence regarding past, ongoing, and new reforms that may help address fragmentation, lower diabetes burdens, and narrow disparities.

Machine Learning Approaches for Measuring Neighborhood Environments in Epidemiologic Studies

Purpose of review

Innovations in information technology, initiatives by local governments to share administrative data, and growing inventories of data available from commercial data aggregators have immensely expanded the information available to describe neighborhood environments, supporting an approach to research we call Urban Health Informatics. This review evaluates the application of machine learning to this new wealth of data for studies of the effects of neighborhood environments on health.

Recent findings

Prominent machine learning applications in this field include automated image analysis of archived imagery such as Google Street View images, variable selection methods to identify neighborhood environment factors that predict health outcomes from large pools of exposure variables, and spatial interpolation methods to estimate neighborhood conditions across large geographic areas.

Summary

In each domain, we highlight successes and cautions in the application of machine learning, particularly highlighting legal issues in applying machine learning approaches to Google’s geo-spatial data.

Social Determinants of Health, Race, and Diabetes Population Health Improvement: Black/African Americans as a Population Exemplar

PURPOSE OF REVIEW

To summarize evidence of impact of social determinants of health (SDOH) on diabetes risk, morbidity, and mortality and to illustrate this impact in a population context.

RECENT FINDINGS

Key findings from the American Diabetes Association's scientific review of five SDOH domains (socioeconomic status, neighborhood and physical environment, food environment, health care, social context) are highlighted. Population-based data on Black/African American adults illustrate persisting diabetes disparities and inequities in the SDOH conditions in which this population is born, grows, lives, and ages, with historical contributors. SDOH recommendations from US national committees largely address a health sector response, including health professional education, SDOH measurement, and patient referral to services for social needs. Fewer recommendations address solutions for systemic racism and socioeconomic discrimination as root causes. SDOH are systemic, population-based, cyclical, and intergenerational, requiring extension beyond health care solutions to multi-sector and multi-policy approaches to achieve future population health improvement.

Neighborhood walkability, physical activity and changes in glycemic markers in people with type 2 diabetes: The Hoorn Diabetes Care System cohort

Studies investigating neighborhood walkability and physical activity in people with type 2 diabetes (T2D) mainly used self-report measures, and only few studies assessed the association with glycemic control. This study assessed the associations between objectively measured (i.e. GIS based) and subjectively measured (i.e. questionnaire-based) neighborhood walkability and changes in glycemic markers in people with T2D, and whether this association was mediated by device-measured physical activity (PA), in the Diabetes Care System Cohort (n = 1230). Neither objective or subjectively measured walkability was associated with glycemic control. In mediation analyses we observed no overall mediation by PA.

Individual and Community Social Determinants of Health Associated With Diabetes Management in a Mexican American Population

Background: Diabetes is a major health burden in Mexican American populations, especially among those in the Lower Rio Grande Valley (LRGV) in the border region of Texas. Understanding the roles that social determinants of health (SDOH) play in diabetes management programs, both at the individual and community level, may inform future intervention strategies.

Methods: This study performed a secondary data analysis on 1,568 individuals who participated in Salud y Vida (SyV), a local diabetes and chronic disease management program, between October 2013 and September 2018 recruited from a local clinic. The primary outcome was the reduction of hemoglobin A1C (HbA1C) at the last follow-up visit compared to the baseline. In addition to age, gender, insurance status, education level and marital status, we also investigated 15 community (census tract) SDOH using the American Community Survey. Because of the high correlation in the community SDOH, we developed the community-level indices representing different domains. Using Bayesian multilevel spatial models that account for the geographic dependency, we were able to simultaneously investigate the individual- and community-level SDOH that may impact HbA1C reduction.

Results: After accounting for the diabetes self-management education classes taken by the participants and their length of stay in the program, we found that older age at baseline, being married (compared to being widowed or divorced) and English speaking (compared to Spanish) were significantly associated with greater HbA1C reduction. Moreover, we found that the community level SDOH were also highly associated with HbA1C reduction. With every percentile rank decrease in the socioeconomic advantage index, we estimated an additional 0.018% reduction in HbA1C [95% CI (−0.028, −0.007)]. Besides the socioeconomic advantage index, urban core opportunity and immigrant's cohesion and accessibility indices were also statistically associated with HbA1C reduction.

Conclusion: To our knowledge, our study is the first to utilize Bayesian multilevel spatial models and simultaneously investigate both individual- and community-level SDOH in the context of diabetes management. Our findings suggest that community SDOH play an important role in diabetes control and management, and the need to consider community and neighborhood context in future interventions programs to maximize their overall effectiveness.

Neighborhood context and kidney disease in Philadelphia

Neighborhood context might influence the risk of chronic kidney disease (CKD), a condition that impacts approximately 10% of the United States population and is associated with significant morbidity, mortality, and costs. We included a sample of 23,692 individuals in Philadelphia, Pennsylvania, who were seen in a large academic primary care practice between January 1, 2016 and December 31, 2017. We used generalized linear equations to estimate the associations between indicators of neighborhood context (e.g., proximity to healthy foods stores, neighborhood walkability, social capital, crime rate, socioeconomic status) and CKD, adjusted for age, sex, race/ethnicity, and insurance coverage. Among those with CKD, secondary outcomes were poor glycemic control (hemoglobin A1c ≥ 6.5%) and uncontrolled blood pressure (systolic ≥ 140 mm Hg and/or diastolic ≥ 90 mm Hg). The cohort represented residents from 97% of Philadelphia census tracts. CKD prevalence was 10%. When all neighborhood context metrics were considered collectively, only lower neighborhood socioeconomic index (a composite assessment of neighborhood income, educational attainment, and occupation) was associated with a higher risk of CKD (lowest tertile vs. highest tertile: adjusted relative risk [aRR] 1.46 [1.25, 1.69]; mid-tertile vs. highest-tertile: aRR 1.35 [1.25, 1.52]). Among those with CKD, compared to residence in the most walkable neighborhoods (i.e., where most essential resources are accessible by foot), residence in neighborhoods with mid-level WalkScore® (i.e., where only some essential neighborhood resources are accessible by foot) was independently associated with poor glycemic control (aRR 1.20, 95% CI 1.01-1.42). These findings suggest a potential role for measures of neighborhood socioeconomic status in identifying communities that would benefit from screening and treatment for CKD. Studies are also needed to determine mechanisms to explain why residence in neighborhoods not easily navigated by foot or car might hinder glycemic control among people with CKD.

Social Determinants of Poor Management of Type 2 Diabetes Among the Insured

PURPOSE OF REVIEW

Even with insurance coverage increasing over time among the population with diabetes, a large proportion continues to have poorly controlled disease. The purpose of this narrative literature review is to describe the social determinants of poor management of type 2 diabetes among the insured population and illustrate drivers of poor outcomes beyond insurance coverage.

RECENT FINDINGS

Despite the provision of health insurance, social determinants play a significant role in shaping diabetes outcomes, especially for economic instability (employment, out-of-pocket expenses associated with diabetes management), food insecurity, education and literacy, access to quality health care (health systems designed to effectively manage chronic disease), neighborhood and the built environment (segregated neighborhoods, socioeconomic conditions of communities, housing), and social and community context (discrimination, social support). Multiple social determinants shape poor diabetes outcomes among the insured. These determinants are now being further exacerbated by the COVID-19 pandemic, which has created the worst economic crisis for US families since the Great Depression. The evidence of this review points to the imperative need for more multilevel intervention approaches to address these determinants in the management of diabetes.

Design and methods of NYC care calls: An effectiveness trial of telephone-delivered type 2 diabetes self-management support

Although problems with type 2 diabetes (T2D) self-management and treatment adherence often co-occur with emotional distress, few translatable intervention approaches are available that can target these related problems in primary care practice settings. The New York City (NYC) Care Calls study is a randomized controlled trial that tests the effectiveness of structured support for diabetes self-management and distress management, delivered via telephone by health educators, in improving glycemic control, self-management and emotional well-being among predominantly ethnic minority and socioeconomically disadvantaged adults with suboptimally controlled T2D. English- and Spanish-speaking adults treated for T2D in NYC primary care practices were recruited based on having an A1C ≥ 7.5% despite being prescribed medications for diabetes. Participants (N = 812) were randomly assigned to a telephonic intervention condition with a stepped protocol of 6-12 phone calls over 1 year, delivered by a health educator, or to a comparison condition of enhanced usual care. The primary outcome is change in A1C over one year, measured at baseline and again approximately 6- and 12-months later. Secondary outcomes measured on the same schedule include blood pressure, patient-reported emotional distress, treatment adherence and self-management behaviors. A comprehensive effectiveness evaluation is guided by the RE-AIM framework (Reach, Effectiveness, Adoption, Implementation, Maintenance) to gather data that can inform dissemination and implementation of the intervention, if successful. This paper describes the study rationale, trial design, and methodology.

Systematic review and meta-analysis of patient race/ethnicity, socioeconomics, and quality for adult type 2 diabetes

OBJECTIVE

To review the evidence of the association between performance in eight indicators of diabetes care and a patient's race/ethnicity and socioeconomic characteristics.

DATA SOURCE

Studies of adult patients with type 2 diabetes in MEDLINE published between January 1, 2000, and December 31, 2018.

STUDY DESIGN

Systematic review and meta-analysis of regression-based studies including race/ethnicity and income or education as explanatory variables. Meta-analysis was used to quantify differences in performance associated with patient race/ethnicity or socioeconomic characteristics. The systematic review was used to identify potential mechanisms of disparities.

DATA COLLECTION

Two coauthors separately conducted abstract screening, study exclusions, data extraction, and scoring of retained studies. Estimates in retained studies were extracted and, where applicable, were standardized and converted to odds ratios and standard errors.

PRINCIPAL FINDINGS

Performance in intermediate outcomes and process measures frequently exhibited differences by race/ethnicity even after adjustment for socioeconomic, lifestyle, and health factors. Meta-analyses showed black patients had lower odds of HbA1c and blood pressure (BP) control (OR range: 0.67-0.68, P < .05) but higher odds of receiving eye or foot examination (OR range: 1.22-1.47, P < .05) relative to white patients. A high school degree or more was associated with higher odds of HbA1c control and receipt of eye examinations compared to patients without a degree. Meta-analyses of income included a handful of studies and were inconsistently associated with diabetes care performance. Differences in diabetes performance appear to be related to access-related factors such as uninsurance or lacking a usual source of care; food insecurity and trade-offs at very low incomes; and lower adherence among younger and healthier diabetes patients.

CONCLUSIONS

Patient race/ethnicity and education were associated with differences in diabetes quality measures. Depending on the approach used to rate providers, not adjusting for these patient characteristics may penalize or reward providers based on the populations they serve.

Residential mobility and chronic disease among World Trade Center Health Registry enrollees, 2004-2016

Residential mobility is hypothesized to impact health through changes to the built environment and disruptions in social networks, and may vary by neighborhood deprivation exposure. However, there are few longitudinal investigations of residential mobility in relation to health outcomes. This study examined enrollees from the World Trade Center Health Registry, a longitudinal cohort of first responders and community members in lower Manhattan on September 11, 2001. Enrollees who completed ≥2 health surveys between 2004 and 2016 and did not have diabetes (N = 44,089) or hypertension (N = 35,065) at baseline (i.e., 2004) were included. Using geocoded annual home addresses, residential mobility was examined using two indicators: moving frequency and displacement. Moving frequency was defined as the number of times someone was recorded as living in a different neighborhood; displacement as any moving to a more disadvantaged neighborhood. We fit adjusted Cox proportional hazards models with time-dependent exposures (moving frequency and displacement) and covariates to evaluate associations with incident diabetes and hypertension. From 2004 to 2016, the majority of enrollees never moved (54.5%); 6.5% moved ≥3 times. Those who moved ≥3 times had a similar hazard of diabetes (hazard ratio (HR) = 0.78; 95% Confidence Interval (CI): 0.40, 1.53) and hypertension (HR = 0.99; 95% CI: 0.68, 1.43) compared with those who never moved. Similarly, displacement was not associated with diabetes or hypertension. Residential mobility was not associated with diabetes or hypertension among a cohort of primarily urban-dwelling adults.

Neighborhood Environment Characteristics and Control of Hypertension and Diabetes in a Primary Care Patient Sample

BACKGROUND

Hypertension control and diabetes control are important for reducing cardiovascular disease burden. A growing body of research suggests an association between neighborhood environment and hypertension or diabetes control among patients engaged in clinical care.

OBJECTIVE

To investigate whether neighborhood conditions (i.e., healthy food availability, socioeconomic status (SES), and crime) were associated with hypertension and diabetes control.

DESIGN

Cross-sectional analyses using electronic medical record (EMR) data, U.S. Census data, and secondary data characterizing neighborhood food environments. Multivariate logistic regression analyses adjusted for potential confounders. Analyses were conducted in 2017.

PARTICIPANTS

Five thousand nine hundred seventy adults receiving primary care at three Baltimore City clinics in 2010-2011.

MAIN MEASURES

Census tract-level neighborhood healthy food availability, neighborhood SES, and neighborhood crime. Hypertension control defined as systolic blood pressure < 140 mmHg and diastolic blood pressure < 90 mmHg. Diabetes control defined as HgbA1c < 7.

KEY RESULTS

Among patients with hypertension, neighborhood conditions were not associated with lower odds of blood pressure control after accounting for patient and physician characteristics. However, among patients with diabetes, in fully adjusted models accounting for patient and physician characteristics, we found that patients residing in neighborhoods with low and moderate SES had reduced odds of diabetes control (OR = 0.74 (95% CI = 0.57-0.97) and OR = 0.75 (95% CI = 0.57-0.98), respectively) compared to those living in high-SES neighborhoods.

CONCLUSIONS

Neighborhood disadvantage may contribute to poor diabetes control among patients in clinical care. Community-based chronic disease care management strategies to improve diabetes control may be optimally effective if they also address neighborhood SES among patients engaged in care.

U.S. county "food swamp" severity and hospitalization rates among adults with diabetes: A nonlinear relationship

The relationship between food environments and diabetes morbidity is vastly understudied, despite the well-recognized linkage between dietary quality and diabetes complications. Further, literature demonstrates that attributes of places can have nonlinear relationships with health outcomes. This study examines the extent to which "food swamps" are associated with greater rates of hospitalizations for complications among adults with diabetes over time as well as the linearity of this relationship. We conduct a longitudinal county-level analysis of 832 counties across 16 U.S. states in 2010, 2012, and 2014 using data from the USDA Food Environment Atlas and the AHRQ Health Care Cost and Utilization Project State Inpatient Databases. Food swamp severity is measured as the percentage of food outlets in a county that sell primarily unhealthy foods. Hierarchical linear mixed models with county random intercepts are estimated, controlling for area-level covariates and state and year fixed effects. Curvilinear relationships are explored by additively incorporating quadratic terms. We find that, over the study period, mean food swamp severity remained relatively stable. Mean hospitalization rates decreased from 296.72 to 262.82 hospitalizations per 1000 diabetic adults (p < 0.001). In adjusted models, greater food swamp severity was associated with higher hospitalization rates in a curvilinear manner (severity: β = 2.181, p = 0.02; severity2: β = -0.017, p = 0.04), plateauing at approximately 64% unhealthy outlets, a saturation point observed in 17% of observations. Policies that limit saturation of the environment with unhealthy outlets may help in the prevention of diabetic complications, but more saturated counties will likely require more extensive intervention.

Childhood Socioeconomic Disadvantage and Risk of Fatty Liver in Adulthood: The Cardiovascular Risk in Young Finns Study

Fatty liver is a preventable cause of liver failure, but early risk factors for adulthood fatty liver are poorly understood. We examined the association of childhood socioeconomic disadvantage with adulthood fatty liver and tested adulthood risk factors of fatty liver as possible mediators of this link. The study population comprised 2,042 participants aged 3-18 years at baseline (1980) from the longitudinal Cardiovascular Risk in Young Finns Study. Follow-up with repeated clinical examinations was 31 years. Childhood socioeconomic disadvantage was assessed using data from parents' socioeconomic position and socioeconomic circumstances in participants' residential neighborhoods, categorized as high versus low socioeconomic disadvantage. Fatty liver was determined by ultrasound during the last follow-up (2011) at ages 34-49 years. Childhood and adulthood risk factors, including metabolic biomarkers and lifestyle variables, were assessed in clinical examinations. A total of 18.9% of the participants had fatty liver in adulthood. High childhood socioeconomic disadvantage was associated with an increased risk of fatty liver (risk ratio [95% confidence interval], 1.42 [1.18-1.70]; P = 0.0002). This association was robust to adjustment for age, sex, and childhood risk factors of fatty liver, including high body mass index, elevated insulin, and low birth weight (1.33 [1.09-1.62]; P = 0.005). High childhood socioeconomic disadvantage was also associated with the development of risk factors of fatty liver in adulthood. Adulthood risk factors linking childhood socioeconomic disadvantage with fatty liver included waist circumference (proportion mediated of the total effect of childhood socioeconomic disadvantage, 45%), body mass index (40%), systolic blood pressure (29%), insulin (20%), physical activity (15%), triglycerides (14%), and red meat consumption (7%). Conclusion: Childhood socioeconomic disadvantage was associated with multiple risk factors of fatty liver and increased likelihood of fatty liver in adulthood.

Impact of a community-based approach to patient engagement in rural, low-income adults with type 2 diabetes

OBJECTIVE

This secondary analysis examined the relationships between Patient Activation Measure (PAM) scores, use of health services, and HgA1C.

DESIGN

A feasibility study was conducted for a community-based intervention for high-risk adults with uncontrolled diabetes. Data were collected at baseline and monthly, including PAM and modified Diabetes Self-Management Assessment Report Tool.

INTERVENTION

Participants (n = 58) were randomized to a 3-month nurse (RN) telephone management or community health worker (CHW) in-home intervention, focusing on medication adherence, timely follow-up, diabetes self-management coaching, and linkage to resources.

RESULTS

Sample was mostly female (73%), African-American (90%), low income (75%), high school education or less (80%), and mean age of 59 years. A positive association between PAM score and self-reported diabetes care recommendations was found (r = .356, p = .014) and significant correlation between baseline PAM score and HgA1C levels (r = -.306, p = .029). A paired samples t test showed statistically significant increases in PAM scores in the CHW intervention group (mean increase +8.5, CI [+2.49 to +14.65]); baseline (M = 60.31, SD = 13.3) to end of study ([M = 68.89, SD = 16.39], t(22) = 2.924, p = .008 [two-tailed]).

CONCLUSION

A community-based approach to diabetes management demonstrated a positive effect on patient activation. Although disparities in health care access among rural, low-income populations exist, community-based interventions show potential for improving patient engagement in diabetes management and recommended health services.

Neighborhood walkability and 12-year changes in cardio-metabolic risk: the mediating role of physical activity

BACKGROUND

Living in walkable neighborhoods may provide long-term cardio-metabolic health benefits to residents. Little empirical research has examined the behavioral mechanisms in this relationship. In this longitudinal study, we examined the potential mediating role of physical activity (baseline and 12-year change) in the relationships of neighborhood walkability with 12-year changes in cardio-metabolic risk markers.

METHODS

The Australian Diabetes, Obesity and Lifestyle study collected data from adults, initially aged 25+ years, in 1999-2000, 2004-05, and 2011-12. We used 12-year follow-up data from 2023 participants who did not change their address during the study period. Outcomes were 12-year changes in waist circumference, weight, systolic and diastolic blood pressure, fasting and 2-h postload plasma glucose, high-density lipoprotein cholesterol, and triglycerides. A walkability index was calculated, using dwelling density, intersection density, and destination density, within 1 km street-network buffers around participants' homes. Spatial data for calculating these measures were sourced around the second follow-up period. Physical activity was assessed by self-reported time spent in moderate-to-vigorous physical activity (including walking). Multilevel models, adjusting for potential confounders, were used to examine the total and indirect relationships. The joint-significance test was used to assess mediation.

RESULTS

There was evidence for relationships of higher walkability with smaller increases in weight (P = 0.020), systolic blood pressure (P < 0.001), and high-density lipoprotein cholesterol (P = 0.002); and, for relationships of higher walkability with higher baseline physical activity (P = 0.020), which, in turn, related to smaller increases in waist circumference (P = 0.006), weight (P = 0.020), and a greater increase in high-density lipoprotein cholesterol (P = 0.005). There was no evidence for a relationship of a higher walkability with a change in physical activity during the study period (P = 0.590).

CONCLUSIONS

Our mediation analysis has shown that the protective effects of walkable neighborhoods against obesity risk may be in part attributable to higher baseline physical activity levels. However, there was no evidence of mediation by increases in physical activity during the study period. Further research is needed to understand other behavioral pathways between walkability and cardio-metabolic health, and to investigate any effects of changes in walkability.

Development of a Neighborhood Walkability Index for Studying Neighborhood Physical Activity Contexts in Communities across the U.S. over the Past Three Decades

To examine how urban form shapes physical activity and health over time, a measure of neighborhood walkability is needed that can be linked to cohort studies with participants living across the United States (U.S.) that have been followed over the past decades. The Built Environment and Health-Neighborhood Walkability Index (BEH-NWI), a measure of neighborhood walkability that can be calculated for communities across the United States between 1990 and 2015, was conceptualized, developed, and tested using data from the New York City Tri-State Area. BEH-NWI measures were created for 1990 and 2010 using historical data on population density, street intersection density, density of rail stops, and density of pedestrian trip generating/supporting establishments. BEH-NWI scores were calculated for 1-km buffers around the 1990 residences of NYU Women's Health Study (NYUWHS) participants and NYC Department of Health and Mental Hygiene's Physical Activity and Transit (PAT) survey participants enrolled in 2011. Higher neighborhood BEH-NWI scores were significantly associated with greater self-reported walking per week (+ 0.31 MET-hours/week per unit BEH-NWI, 95% CI 0.23, 0.36) and lower body mass index (- 0.17 BMI units per unit BEH-NWI, 95% - 0.23, - 0.12) among NYUWHS participants. Higher neighborhood BEH-NWI scores were associated with significantly higher accelerometer-measured physical activity among PAT survey participants (39% more minutes of moderate-intensity equivalent activity/week across the interquartile range of BEH-NWI, 95% CI 21%, 60%). The BEH-NWI can be calculated using historical data going back to 1990, and BEH-NWI scores predict BMI, weekly walking, and physical activity in two NYC area datasets.

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

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.

Sleep and Environmental Factors Affecting Glycemic Control in People with Type 2 Diabetes Mellitus

PURPOSE OF REVIEW

Sleep and environmental factors both impact glycemic control in persons with type 2 diabetes mellitus (T2DM). This narrative article aims to review research within the past 5 years, focusing on chronotype, light, noise, and neighborhood disparities in relation to sleep in people with T2DM.

RECENT FINDINGS

Sleep quality and duration have been shown to impact glycemic control in patients with T2DM. Later chronotype can lead to poorer glycemic control due to disruption of circadian rhythms. Light exposure also has similar effects, likely due to its inherent influence on sleep quality. Environmental determinants, were associated with lower T2DM incidence, and noise and air pollution were associated with increased risks for T2DM. Findings were mixed; while most studies found that later chronotype, light/noise exposure, and neighborhood disadvantages were associated with poorer glycemic control in patients with T2DM, other environmental factors, such as green space, were not significantly associated with diabetes outcomes.

Neighborhood Environments and Diabetes Risk and Control

PURPOSE OF REVIEW

The objective of this review is to highlight the evidence on the association between contextual characteristics of residential environments and type 2 diabetes, to provide an overview of the methodological challenges and to outline potential topics for future research in this field.

RECENT FINDINGS

The link between neighborhood socioeconomic status or deprivation and diabetes prevalence, incidence, and control is robust and has been replicated in numerous settings, including in experimental and quasi-experimental studies. The association between characteristics of the built environment that affect physical activity, other aspects of the built environment, and diabetes risk is robust. There is also evidence for an association between food environments and diabetes risk, but some conflicting results have emerged in this area. While the evidence base on the association of neighborhood socioeconomic status and built and physical environments and diabetes is large and robust, challenges remain related to confounding due to neighborhood selection. Moreover, we also outline five paths forward for future research on the role of neighborhood environments on diabetes.

Using Indirect Measures to Identify Geographic Hot Spots of Poor Glycemic Control: Cross-sectional Comparisons With an A1C Registry

OBJECTIVE

Focusing health interventions in places with suboptimal glycemic control can help direct resources to neighborhoods with poor diabetes-related outcomes, but finding these areas can be difficult. Our objective was to use indirect measures versus a gold standard, population-based A1C registry to identify areas of poor glycemic control.

RESEARCH DESIGN AND METHODS

Census tracts in New York City (NYC) were characterized by race, ethnicity, income, poverty, education, diabetes-related emergency visits, inpatient hospitalizations, and proportion of adults with diabetes having poor glycemic control, based on A1C >9.0% (75 mmol/mol). Hot spot analyses were then performed, using the Getis-Ord Gi* statistic for all measures. We then calculated the sensitivity, specificity, positive and negative predictive values, and accuracy of using the indirect measures to identify hot spots of poor glycemic control found using the NYC A1C Registry data.

RESULTS

Using A1C Registry data, we identified hot spots in 42.8% of 2,085 NYC census tracts analyzed. Hot spots of diabetes-specific inpatient hospitalizations, diabetes-specific emergency visits, and age-adjusted diabetes prevalence estimated from emergency department data, respectively, had 88.9%, 89.6%, and 89.5% accuracy for identifying the same hot spots of poor glycemic control found using A1C Registry data. No other indirect measure tested had accuracy >80% except for the proportion of minority residents, which had 86.2% accuracy.

CONCLUSIONS

Compared with demographic and socioeconomic factors, health care utilization measures more accurately identified hot spots of poor glycemic control. In places without a population-based A1C registry, mapping diabetes-specific health care utilization may provide actionable evidence for targeting health interventions in areas with the highest burden of uncontrolled diabetes.