Neighborhood Environments and Diabetes Risk and Control

Residential mobility, neighborhood environment, and diabetes complications among socioeconomically disadvantaged patients in the United States

Residential mobility can affect health through changes in available resources, social support, or continuity of healthcare. This study sought to understand whether residential mobility and/or change in neighborhood environment among patients with diabetes were associated with diabetes-related complications. This retrospective study used electronic health record data from 19,853 adults aged 18-64 with a diabetes diagnosis seen in 110 safety-net clinics across the United States. Generalized estimating equations logistic regression models estimated whether moving (pre/post) and change in neighborhood environment (improving, worsening, similar) were associated with diagnoses of chronic diabetes-related complications. Post-move versus pre-move was associated with significantly higher probability of diabetes-related chronic complications (predicted probability: 13.16 vs 6.00, respectively), but no association was found by change in neighborhood environment. Those who moved had lower probability of chronic complications than those who did not move which could have been driven by pre-move circumstances among patients who moved. Residential mobility plays an important role in understanding diabetes-related complications while changes in neighborhood environment may be less important among low-income patients served by safety-net clinics. Moving may not be directly responsible for the development of diabetes-related chronic complications, but it may be an indicator for other factors of instability.

Influence of smoking on glycaemic control in individuals with type 1 diabetes using flash glucose monitoring and its mediating role in the relationship between socioeconomic status and glycaemic control

Objective

This study examined the influence of smoking on glycaemic control in individuals with type 1 diabetes (T1D) using flash continuous glucose monitoring (F-CGM) systems, as well as its potential mediating role in the relationship between socioeconomic status (SES) and glycaemic control.

Methods

This study included 378 subjects with T1D (18% smokers). Glucose metrics cloud downloads were obtained over a period of 14 days. Mean annual net income per person based on census tract data was used as a proxy for SES. Mediation analysis was performed using four-way effect decomposition procedures.

Results

Smokers exhibited significantly lower net income than non-smokers (p < 0.001). Compared to smokers, non-smokers showed better glycaemic control characterized as higher time in range (TIR) 70-180 mg/dL (p = 0.002) and lower glycosylated haemoglobin levels (p = 0.008). Mediation analysis revealed a significant mediating role of smoking in the relationship between SES and glycaemic control (TIR).

Conclusions

Our data suggest that smoking exerts a detrimental effect on glycaemic control in individuals with T1D using F-CGM systems. In addition, tobacco use partially mediates the relationship between SES and glycaemic control. Thus, adopting smoking cessation measures could lead to improved glycaemic control and help mitigate the impact of social inequalities on T1D.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40200-024-01535-y.

Association of neighborhood physical environment with falls and fear of falling in older adults: A prospective cohort study

OBJECTIVES

To explore the prospective association between physical environment characteristics of the neighborhood and risk of falls/fear of falling among community-dwelling older adults.

STUDY DESIGN

Prospective cohort analysis using data from the Seniors-ENRICA-2 cohort (metropolitan Madrid, Spain).

METHODS

At baseline (2015-17), a neighborhood physical characteristics score was developed using the Physical Activity Neighborhood Environment Scale and an additional indicator of distance to green areas. In the second wave of follow-up (2019-20) we collected self-reported incident falls and fear of falling, assessed with the Short Falls Efficacy Scale International. Adjusted odds ratios (OR) and 95 % confidence intervals (CI) for the association between neighborhood environment perception and incidence of falls/fear of falling were calculated using logistic regression.

RESULTS

Among 1823 participants, 27.7 % reported a fall during the previous year and 32.1 % were concerned about having a fall. Better neighborhood environment was associated with lower risk of falls (OR: 0.75; 95 %CI: 0.57-0.99) and fear of falling (0.73; 0.55-0.96). Specifically, low traffic intensity (0.68; 0.52-0.90) and sidewalks in good condition (0.75; 0.59-0.95) were associated with lower risk of falling. Moreover, available facilities for biking (0.77; 0.61-0.96), sidewalks in good condition (0.67; 0.52-0.86), night security (0.80; 0.60-0.99) and day security (0.62; 0.44-0.98) were independently associated with lower fear of falling.

CONCLUSIONS

Better neighborhood physical environments could play a key role in the prevention of falls and fear of falling among older adults. Policies aiming to improve residential environments can have broad implications for achieving healthy aging.

Effects of the leisure-time physical activity environment on odds of glycemic control among a nationwide cohort of United States veterans with a new type-2 diabetes diagnosis

OBJECTIVE

This study examined associations between access to leisure-time physical activity (LTPA) facilities and parks and repeated measures of glycated hemoglobin (A1C) over time, using follow-up tests among United States Veterans with newly diagnosed type-2 diabetes (T2D).

METHODS

Data were analyzed from 274,463 patients in the Veterans Administration Diabetes Risk cohort who were newly diagnosed with T2D between 2008 and 2018 and followed through 2023. Generalized estimating equations with a logit link function and binomial logistic regression were used to examine associations.

RESULTS

Patients were on average 60.5 years of age, predominantly male (95.0 %) and white (66.9 %), and had an average of 11.7 A1C tests during the study follow-up period. In high- and low-density urban communities, a one-unit higher LTPA facility density score was associated with 1 % and 3 % greater likelihood of in-range A1C tests during follow-up, respectively, but no association was observed among patients living in suburban/small town and rural communities. Across community types, closer park distance was not associated with subsequent greater odds of in-range A1C tests. Unexpectedly, in low-density urban areas, the likelihood of in-range A1C tests was 1 % lower at farther park distances.

CONCLUSIONS

These results suggest that broader access to LTPA facilities, but not park proximity, may contribute in small ways to maintaining glycemic control after T2D diagnosis in urban communities. Tailored interventions may be needed to promote patients' effective use of LTPA facilities and parks.

Adding social determinants of health to the equation: Development of a cardiometabolic disease staging model using clinical and social determinants of health to predict type 2 diabetes

AIMS

Identifying individuals at the highest risk of progression to type 2 diabetes (T2D) using clinical and social determinants of health (SDoH) measures will help prioritize prevention efforts. We aimed to investigate model performance after adding SDoH to a previously validated cardiometabolic disease staging diabetes risk prediction model.

MATERIALS AND METHODS

We developed a Bayesian predictive model using data [clinical factors: fasting glucose, blood pressure, body mass index, high-density lipoprotein cholesterol, triglycerides; individual SDoH: income, education, health insurance status, relationship status, self-reported stress and neighbourhood SDoH: census-tract level social vulnerability index] from the REasons for Geographic And Racial Differences in Stroke (REGARDS) study to predict T2D with external validation using the Coronary Artery Risk Development in Young Adults (CARDIA) study.

RESULTS

The analysis included 9907 REGARDS participants without T2D at baseline [mean age 63 years (SD 8.5), 54% female, 33% non-Hispanic Black] who completed a follow-up visit 10 years later. N = 1268 (12.8%) developed T2D. Adding SDoH to the clinical model modestly improved performance [Area Under the Curve: 0.802 vs. 0.804, p = 0.01]. Calibration plots indicated that the clinical model underpredicted risk in disadvantaged SDoH subgroups, whereas the clinical plus SDoH model improved prediction accuracy in subgroups. Classification tables revealed that the clinical plus SDoH model accurately reclassified individuals categorized as borderline risk in a clinical-only model.

CONCLUSION

Including SDoH in T2D risk prediction and stratification at the population level may aid in better classifying T2D risk among vulnerable populations, which has important implications for screening strategies.

Rurality and Neighborhood Socioeconomic Status are Associated With Overall and Cause-Specific Mortality and Hepatic Decompensation in Type 2 Diabetes

INTRODUCTION

Social determinants of health are key factors driving disease progression. In type 2 diabetes there is limited literature on how distal or intermediate factors (eg, those at the neighborhood level) influence cause-specific mortality or liver disease outcomes.

METHODS

This was a single-center retrospective study of patients with type 2 diabetes seen at an integrated healthcare system in the United States. The primary outcomes were overall mortality; death due to cardiovascular disease, cancer, or liver disease; or hepatic decompensation. The primary predictors were neighborhood-level (intermediate) factors measuring neighborhood poverty (Area Deprivation Index [ADI], affluence score, disadvantage score) and rurality (Rural-Urban Commuting Area scores). Associations were modeled using Cox proportional hazards or Fine-Grey competing risk models.

RESULTS

28,424 participants were included. Higher neighborhood poverty associated with increased overall mortality, with hazard ratio (HR) 1.11 (95% confidence interval 1.10-1.12, P < .001) per 10 points of ADI and HR 1.32 (95% CI 1.26-1.37, P < .001) for 10 points of disadvantage. Conversely, higher neighborhood affluence associated with lower overall mortality with HR 0.87 (95% CI 0.86-0.89, P < .001) per 10 points of affluence. Living in a rural region associated with increased overall mortality: HR 1.08 (95% CI 1.01-1.15, P = .031). Associations were consistent across cause-specific mortality, though effect sizes were larger for liver-related mortality than for other causes. Living in a more rural neighborhood was associated with increased risk of hepatic decompensation.

CONCLUSIONS

Intermediate neighborhood-level socioeconomic status was associated with overall and cause-specific mortality in type 2 diabetes, with larger effects on liver-related mortality than other causes.

Neighborhood retail food environment, diet quality and type 2 diabetes incidence in four Dutch cohorts

BACKGROUND

Current evidence on the associations between the food environment and type 2 diabetes (T2D) is inconsistent and did not investigate the behavioral mediating pathway.

OBJECTIVE

To investigate whether accessibility of food retailers in the residential neighborhood is associated with T2D incidence in four Dutch prospective cohorts, and whether this is mediated by diet quality.

DESIGN

In this prospective multi-cohort study we included four Dutch cohort studies (ntotal=10,249). Nearest distances from all participants' home to supermarkets, fast-food outlets and green grocers were calculated at baseline (2004-2012). Incidence of T2D during follow-up was assessed with cohort-specific measures. T2D incidence ratios (IR) adjusted for demographics, lifestyle and environmental factors were estimated using Poisson regression in each cohort, and results were pooled across cohorts using a random-effects model. In two cohorts (n=7,549), mediation by adherence to the Dutch Healthy Diet index 2015 (DHD15-index, range 0-13) was investigated using linear and Poisson regression analyses.

RESULTS

Over a mean follow-up of 7.5 years, 569 (5.6%) participants developed T2D. Mean(SD) age in the cohorts ranged from 41.1(12.9) to 67.4(6.8) years. No associations were observed between accessibility of different food retailers and T2D incidence (βsupermarket:0.02(-0.01;0.06), βfast-food:-0.01(-0.04;0.03), βgreen grocer:0.01(-0.05;0.07)). Mediation analyses indicated that every 100 meter living further from a supermarket or green grocer was associated with lower adherence to DHD15 (βsupermarket=-0.1 (95%CI:-0.3;0.0), βgreen grocer=-0.1 (95%CI:-0.1;0.0)), whereas living further away from fast-food associated with higher adherence (βfast-food=0.1 (95%CI: 0.0;0.2)). Higher adherence to DHD15 was associated with lower T2D incidence (IR=0.93 (95%CI: 0.88;0.99)).

CONCLUSIONS

Spatial accessibility of food retailers was not associated with risk of T2D. Nevertheless, consistent associations in hypothesized pathways were observed, such that spatial accessibility to healthier food retailers was associated with higher diet quality and spatial accessibility of unhealthier retailers with lower diet quality. Higher diet quality, in turn, was associated with lower T2D risk.

Connecting underlying factors in the associations between perceived neighborhood social environments and type 2 Diabetes: Serial mediation analyses

AIMS

This study tested direct and indirect associations between perceived neighborhood social environments and type 2 diabetes (T2D), serially mediated via health-related (physical activity [PA], body mass index [BMI]), psychosocial factors, and inflammation.

METHODS

Data came from the Midlife in the United States (MIDUS 3 [2013-2014] and MIDUS 3 Biomarker Project [2017-2022]; n = 518). T2D (yes/no) was based on the American Diabetes Association criteria. Perceived neighborhood social cohesion and safety were assessed separately (higher scores = more favorable neighborhoods). PA, BMI, perceived stress, depression, and c-reactive protein (CRP) were included as mediators in the associations between exposure and the outcome adjusting for covariates.

RESULTS

Higher social cohesion was indirectly related to lower likelihood of T2D, serially mediated through PA, BMI, and CRP (odds ratio [OR] = 1.00; 95 % bias-corrected confidence interval [BC CI] = 0.99, 1.00). Higher social cohesion and safety were indirectly associated with a lower likelihood of T2D, serially mediated via stress, depression, and CRP (Social cohesion: OR = 0.98; 95 % BC CI = 0.96, 1.00; and safety: OR = 0.98; 95 % BC CI = 0.96, 1.00, all p < 0.05).

CONCLUSIONS

This study may be the first to demonstrate underlying potential mechanisms through which socially cohesive and safe neighborhoods lower the risk of T2D. These pathways present potential targets for interventions to reduce the risk.

Built environment and chronic kidney disease: current state and future directions

PURPOSE OF REVIEW

Despite emerging studies on neighborhood-level risk factors for chronic kidney disease (CKD), our understanding of the causal links between neighborhood characteristics and CKD is limited. In particular, there is a gap in identifying modifiable neighborhood factors, such as the built environment, in preventing CKD, that could be targets for feasible place-based interventions.

RECENT FINDINGS

Most published studies on neighborhood factors and CKD have focused on a single social attribute, such as neighborhood disadvantage, while research on the role of the built environment is more nascent. Early studies on this topic have yielded inconsistent results, particularly regarding whether food deserts are an environmental risk factor for CKD onset. International studies have shown that walkable neighborhoods - characterized by features such as urban design, park access, and green spaces - can be protective against both the onset and progression of CKD. However, these findings are inconclusive and understudied in the context of United States, where neighborhood environments differ from those in other countries.

SUMMARY

Future research on modifiable neighborhood factors and CKD using advanced study designs and population-representative datasets can yield stronger evidence on potential causal associations and suggest feasible place-based interventions as strategies for preventing CKD. As an example, we demonstrated the potential of electronic health record-based studies to advance research in this area.

Role of Diabetes Self-management Education for Our Health Systems and Economy

CONTEXT

Diabetes mellitus is a global health burden, with factors contributing to its prevalence and costs. Educating people with diabetes improves outcomes and affects the economic burden on the individual and health systems.

EVIDENCE ACQUISITION

We included recent diabetes data from the Centers for Disease Control and Prevention and articles from PubMed and Ovid MEDLINE.

EVIDENCE SYNTHESIS

Diabetes prevalence in the United States increased from 10.3% in 2001 to 14.7% in 2021. Factors contributing are an aging population, increased obesity, and social determinants of health. Total costs for diabetes in 2022 reached $412.9 billion, consisting of 74% direct medical and around 26% indirect costs. The highest medical expenses were hospital inpatient services ($96.2 billion), and indirect costs were decreased productivity while at work ($35.8 billion). The effect on the health economy in the United States and globally is only increasing. Interventions to improve disease outcomes such as diabetes education programs that teach self-management skills, healthy lifestyle behaviors, and coping strategies have improved glycated hemoglobin A1c and other outcomes. The economic effect of education is not well studied. However, the Diabetes Prevention Program demonstrated the benefits of lifestyle-based education in preventing or delaying the development of type 2 diabetes in high-risk people and in being cost-effective long term.

CONCLUSION

High direct and indirect costs and the prevalence of diabetes require urgent global awareness and interventions from many angles. We encourage clinicians and agencies to prioritize the education of people living with diabetes to prevent and treat diabetes and its complications.

Unveiling inequalities: Racial, ethnic, and socioeconomic disparities in diabetes: Findings from the 2007-2020 NHANES data among U.S. adults

Objective

Despite persistent disparities in diabetes prevalence among racial and ethnic minorities, there remains a significant lack of understanding regarding the intersectionality of racial and ethnic groups and socioeconomic status (SES) with diabetes.

Methods

The data came from the National Health and Nutrition Examination Survey (NHANES; N = 30,754, mean age = 47.4) using cross-sectional survey cycles from 2007 to 2008 through 2017-2020. Diabetes status was self-reported by physician diagnosis. Sociodemographic factors included racial and ethnic groups and SES. Weighted Poisson models were used to examine the association of racial and ethnic groups and SES with diabetes, stratified by age groups (20-44, 45-64, 65-79), sex, and racial and ethnic groups for SES, separately.

Results

Non-Hispanic Black, Hispanic, and other adults had a 47 %, 31 %, and 76 % higher prevalence of diabetes than non-Hispanic White adults, while adults from low and middle SES compared to high SES had a 37 % and 22 % higher prevalence of diabetes. Non-Hispanic Black, Hispanic, and other adults aged 45-64 years had a 45 %, 34 %, and 78 % higher prevalence of diabetes, and low and middle SES had a 57 % and 32 % higher prevalence of diabetes. Similar patterns were observed for adults aged 65-79. Males among non-Hispanic Black, Hispanic, and other adults and females from low and middle-SES families had a higher prevalence of diabetes.

Conclusion

Minority groups, middle and older-aged adults, males from minority groups, and females from low SES had a greater prevalence of diabetes. Effective interventions should prioritize tailoring efforts to specific minoritized and low SES groups to address diabetes disparities.

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.

Time above range and no coefficient of variation is associated with diabetic retinopathy in individuals with type 1 diabetes and glycated hemoglobin within target

AIMS

This study aimed to investigate the association between glucose metrics and diabetic retinopathy in type 1 diabetes (T1D) patients using flash continuous glucose monitoring (FGM) systems, including those maintaining glycated hemoglobin (HbA1c) within the target range.

METHODS

We conducted a cross-sectional study involving 1070 T1D patients utilizing FGM systems. Data on clinical, anthropometric, and socioeconomic characteristics were collected and retinopathy was classified based on international standards.

RESULTS

Patients' mean age was 47.6 ± 15.0 years, with 49.4% of them being females. Within the cohort, 24.8% of patients presented some form of retinopathy. In the analysis involving the entire sample of subjects, male gender (OR = 1.51, p = 0.027), Time Above Range (TAR) > 250 mg/dL (OR = 1.07, p = 0.025), duration of diabetes (OR = 1.09, p < 0.001), smoking (OR = 2.30, p < 0.001), and history of ischemic stroke (OR = 5.59, p = 0.025) were associated with diabetic retinopathy. No association was observed between the coefficient of variation and diabetic retinopathy (p = 0.934). In patients with HbA1c < 7%, the highest quartile of TAR > 250 was independently linked to diabetic retinopathy (OR = 8.32, p = 0.040), in addition to smoking (OR = 2.90, p = 0.031), duration of diabetes (OR = 1.09, p < 0.001), and hypertension (OR = 2.35, p = 0.040).

CONCLUSION

TAR > 250 mg/dL significantly emerges as a modifiable factor associated with diabetic retinopathy, even among those patients maintaining recommended HbA1c levels. Understanding glucose metrics is crucial for tailoring treatment strategies for T1D patients.

Burden of vascular risk factors by age, sex, ethnicity and deprivation in young adults with and without newly diagnosed type 2 diabetes

AIMS

Do associations between age at diagnosis of type 2 diabetes and vascular risk factors vary by ethnicity and deprivation?

METHODS

Utilising the Clinical Practice Research Datalink, we matched 16-50-year-old individuals with newly diagnosed type 2 diabetes to ∼10 individuals without using sex, age and primary care practice. Differences in BMI, obesity, LDL-cholesterol, HbA1c, and hypertension between individuals with vs without type 2 diabetes across sex, age, ethnicity and deprivation quintiles were explored using generalised linear models.

RESULTS

We included 108,061 individuals (45.6% women) with newly diagnosed type 2 diabetes and 829,946 controls. BMI, obesity, LDL-cholesterol, and hypertension were higher in individuals with vs without type 2 diabetes. Across both sexes, all ethnic groups and deprivation quintiles, these differences were larger with an earlier age, particularly for BMI and obesity. Association between age and HbA1c were variable across subgroups. Differences in BMI, obesity, and hypertension (individuals with vs without diabetes) were largest in White individuals and with less deprivation.

CONCLUSIONS

The increased vascular risk phenotype associated with an earlier age of diagnosis of type 2 diabetes was consistent across ethnic and deprivation groups. Population-based strategies are needed to address the risk associated with early-onset type 2 diabetes, especially weight-management-based strategies.

Influence of Neighborhood Socioeconomic Deprivation on Effectiveness of an Intensive Lifestyle Intervention

OBJECTIVE

To assess the influence of neighborhood socioeconomic deprivation on the effectiveness of an intensive lifestyle intervention (ILI) in the Look AHEAD trial.

RESEARCH DESIGN AND METHODS

Look AHEAD randomized adults with overweight/obesity and type 2 diabetes to ILI for weight loss, or Diabetes Support and Education (DSE). We linked participant data from four study sites to the 2000 United States Census to generate a neighborhood socioeconomic deprivation score. We analyzed the effect of neighborhood deprivation in tertiles on various clinical outcomes including weight and HbA1c changes over 4 years using a mixed-effects linear model with random intercept and an interaction term between deprivation tertile and study arm over 4 years.

RESULTS

Among 1213 participants at baseline, the mean age was 60 years, 41% were male, and 65% identified as White, 26% as Black, and 4% as Hispanic. Most participants had a college degree (84%) and reported an annual income over $40,000 (75%). The deprivation score ranged from -12.04 to -2.61 in the most deprived tertile and 2.01 to 18.69 in the least deprived tertile (the lower the score, the higher the deprivation). There were no statistically significant treatment differences by deprivation score in weight or HbA1c changes over the 4-year period.

CONCLUSIONS

In this clinical trial population, an intensive lifestyle intervention was equally effective across levels of neighborhood socioeconomic deprivation. However, these findings may not extend to individuals with the lowest income and educational attainment who are not typically represented in clinical trials and for whom more research is needed.

Associations between neighborhood built-environment characteristics and hepatic steatosis: The Multi-Ethnic Study of Atherosclerosis

OBJECTIVE

To characterize the spatio-temporal association between features of the built environment and subclinical liver disease.

DESIGN

We used data from a large community-based population, the Multi-Ethnic Study of Atherosclerosis (2000-2002, N = 5542) with linked historical residential data that characterized past exposure to alcohol outlets (bars and liquor stores), healthy foods stores, and physical activity facilities (1990-2001). We examined whether and how past residential relate to hepatic steatosis (proxied by liver attenuation measured using computed tomography, with lower attenuation indicating higher hepatic steatosis). Hepatic steatosis is the most common.

RESULTS

We found significant associations between past residential exposure to neighborhood alcohol outlets, healthy food and physical activity resources, and hepatic steatosis. The spatial scale where the association between these features of the built environment and hepatic steatosis operate lies within 3 km (∼2 miles). The average association on liver attenuation per additional bar, liquor, healthy food store, and physical activity facility within a 2-mile buffer, were: -0.06 (95% CI -0.09, -0.03), -0.02 (95% CI -0.04, -0.009), 0.05 (95% CI 0.02, 0.07), 0.02 (95% CI 0.01, 0.04), respectively, in the preceding year of the measurement of hepatic steatosis. Furthermore, the association and spatial scale remains consistent ten years prior to the measurement of hepatic steatosis.

CONCLUSION

Our results suggest that modifying neighborhood environments (decreasing alcohol outlets and improving access to healthy food and physical activity) may represent an effective population-wide approach to reduce liver-related morbidity.

The association between neighborhood disadvantage and patient-reported outcomes in burn survivors

BACKGROUND

Burns can cause long-term complications including pain and poor physical function. While neighborhood disadvantage is associated with burn severity, its effect on long-term complications has not been investigated. We hypothesized that patients from areas of higher area of deprivation index (ADI) will report poorer long-term outcomes.

METHODS

We linked patient data from the Burn Model System with ADI state decile (1 = least, 10 = most disadvantaged) using year and residence at time of injury. We performed bivariate analyses to identify associations between ADI and patient and burn characteristics and multivariate regressions to determine whether ADI was associated with PROMIS-29 pain and physical function 6- and 24-months post-burn.

RESULTS

We included 780 patients; 69 % male, median age = 46 years, median ADI = 6, and median TBSA = 8 %. Multivariate regressions adjusting for TBSA, race, age, sex, anxiety, depression, and pain interference demonstrated that higher ADI was a significant predictor of higher pain intensity 6- (p = 0.001) and 24-months (p = 0.037) post-burn but not worse physical function 24-months post-burn (p = 0.089).

CONCLUSIONS

Higher neighborhood disadvantage was associated with higher long-term pain intensity post-burn. This study highlights the importance of socioeconomic factors that may impact long-term outcomes and the use of aggregate markers to identify patients at risk for worse outcomes.

Racial and economic segregation and diabetes mortality in the USA, 2016-2020

BACKGROUND

The purpose of this study was to examine the association between racial and economic segregation and diabetes mortality among US counties from 2016 to 2020.

METHODS

We conducted a cross-sectional ecological study that combined county-level diabetes mortality data from the National Vital Statistics System and sociodemographic information drawn from the 2016-2020 American Community Survey (n=2380 counties in the USA). Racialized economic segregation was measured using the Index Concentration at the Extremes (ICE) for income (ICEincome), race (ICErace) and combined income and race (ICEcombined). ICE measures were categorised into quintiles, Q1 representing the highest concentration and Q5 the lowest concentration of low-income, non-Hispanic (NH) black and low-income NH black households, respectively. Diabetes was ascertained as the underlying cause of death. County-level covariates included the percentage of people aged ≥65 years, metropolitan designation and population size. Multilevel Poisson regression was used to estimate the adjusted mean mortality rate and adjusted risk ratios (aRR) comparing Q1 and Q5.

RESULTS

Adjusted mean diabetes mortality rate was consistently greater in counties with higher concentrations of low-income (ICEincome) and low-income NH black households (ICEcombined). Compared with counties with the lowest concentration (Q1), counties with the highest concentration (Q5) of low-income (aRR 1.96; 95% CI 1.81 to 2.11 for ICEincome), NH black (aRR 1.32; 95% CI 1.18 to 1.47 for ICErace) and low-income NH black households (aRR 1.70; 95% CI 1.56 to 1.84 for ICEcombined) had greater diabetes mortality.

CONCLUSION

Racial and economic segregation is associated with diabetes mortality across US counties.

The built environment and its association with type 2 diabetes mellitus incidence: A systematic review and meta-analysis of longitudinal studies

This study aimed to systematically review longitudinal studies examining associations between the incidence of type 2 diabetes mellitus (T2DM) and built environmental factors. This review adhered to the 2020 PRISMA guidelines. Longitudinal studies examining associations between T2DM incidence and built environmental features were eligible. Built environment constructs corresponded to the following themes: 1) Walkability - factors such as sidewalks/footpaths, crosswalks, parks, and density of businesses and services; (2) Green/open space - size, greenness, and type of available public outdoor spaces; (3) Food environment - ratio of healthful food outlets (e.g., greengrocers, butchers, supermarkets, and health food shops) to unhealthful food outlets (e.g., fast-food outlets, sweet food retailers, and convenience stores). Five databases (e.g., Medline) were searched from inception until July 2023. Qualitative and quantitative synthesis were used to summarise key findings, including a meta-analysis of adjusted Hazard Ratios (aHR). Of 3,343 articles, 16 longitudinal studies from seven countries, published between 2015 and 2023, involving 13,403,902 baseline participants (median of 83,898), were included. In four of the five studies, unhealthful food environment was significantly associated with higher incident T2DM. Five of seven greenspace studies and two of four walkability studies showed that greater greenery and greater walkability were statistically significantly associated with lesser incident T2DM. In pooled analyses, greater T2DM incidence was associated with unhealthful relative to healthful food environments (pooled HR: 1.21; 95% CI: 1.04, 1.42), and T2DM incidence was inversely associated with green/open space environments (pooled HR: 0.82; 95% CI: 0.74, 0.92). Greater walkability was associated with a slight 2% lesser incidence of T2DM (pooled HR: 0.98; 95% CI: 0.98, 0.99). This review underscores consistency in the nature of associations between built environment features related to T2DM. We observed statistically significant inverse or "protective" associations between T2DM and walkability and healthful food environments. These results support calls for policies and guidelines that promote healthful food environments and walkability.

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.

A fair individualized polysocial risk score for identifying increased social risk in type 2 diabetes

Racial and ethnic minorities bear a disproportionate burden of type 2 diabetes (T2D) and its complications, with social determinants of health (SDoH) recognized as key drivers of these disparities. Implementing efficient and effective social needs management strategies is crucial. We propose a machine learning analytic pipeline to calculate the individualized polysocial risk score (iPsRS), which can identify T2D patients at high social risk for hospitalization, incorporating explainable AI techniques and algorithmic fairness optimization. We use electronic health records (EHR) data from T2D patients in the University of Florida Health Integrated Data Repository, incorporating both contextual SDoH (e.g., neighborhood deprivation) and person-level SDoH (e.g., housing instability). After fairness optimization across racial and ethnic groups, the iPsRS achieved a C statistic of 0.71 in predicting 1-year hospitalization. Our iPsRS can fairly and accurately screen patients with T2D who are at increased social risk for hospitalization.

The Automatic Context Measurement Tool (ACMT) to Compile Participant-Specific Built and Social Environment Measures for Health Research: Development and Usability Study

BACKGROUND

The environment shapes health behaviors and outcomes. Studies exploring this influence have been limited to research groups with the geographic information systems expertise required to develop built and social environment measures (eg, groups that include a researcher with geographic information system expertise).

OBJECTIVE

The goal of this study was to develop an open-source, user-friendly, and privacy-preserving tool for conveniently linking built, social, and natural environmental variables to study participant addresses.

METHODS

We built the automatic context measurement tool (ACMT). The ACMT comprises two components: (1) a geocoder, which identifies a latitude and longitude given an address (currently limited to the United States), and (2) a context measure assembler, which computes measures from publicly available data sources linked to a latitude and longitude. ACMT users access both of these components using an RStudio/RShiny-based web interface that is hosted within a Docker container, which runs on a local computer and keeps user data stored in local to protect sensitive data. We illustrate ACMT with 2 use cases: one comparing population density patterns within several major US cities, and one identifying correlates of cannabis licensure status in Washington State.

RESULTS

In the population density analysis, we created a line plot showing the population density (x-axis) in relation to distance from the center of the city (y-axis, using city hall location as a proxy) for Seattle, Los Angeles, Chicago, New York City, Nashville, Houston, and Boston with the distances being 1000, 2000, 3000, 4000, and 5000 m. We found the population density tended to decrease as distance from city hall increased except for Nashville and Houston, 2 cities that are notably more sprawling than the others. New York City had a significantly higher population density than the others. We also observed that Los Angeles and Seattle had similarly low population densities within up to 2500 m of City Hall. In the cannabis licensure status analysis, we gathered neighborhood measures such as age, sex, commute time, and education. We found the strongest predictive characteristic of cannabis license approval to be the count of female children aged 5 to 9 years and the proportion of females aged 62 to 64 years who were not in the labor force. However, after accounting for Bonferroni error correction, none of the measures were significantly associated with cannabis retail license approval status.

CONCLUSIONS

The ACMT can be used to compile environmental measures to study the influence of environmental context on population health. The portable and flexible nature of ACMT makes it optimal for neighborhood study research seeking to attribute environmental data to specific locations within the United States.

Associations between dimensions of the social environment and cardiometabolic health outcomes: a systematic review and meta-analysis

OBJECTIVES

The social environment (SE), that is, the social relationships and social context in which groups of people live and interact, is an understudied element of the broader living environment which impacts health. We aim to summarise the available evidence on the associations between SE and cardiometabolic disease (CMD) outcomes.

DESIGN

Systematic review and meta-analysis.

DATA SOURCES

PubMed, Scopus and Web of Science Core Collection were searched from inception to 28 February 2024.

ELIGIBILITY CRITERIA

We included studies for which determinants were SE factors such as area-level deprivation and social network characteristics and outcomes were type 2 diabetes mellitus and cardiovascular diseases incidence and prevalence.

DATA EXTRACTION AND SYNTHESIS

Titles and abstracts and full text were screened in duplicate. Data appraisal and extraction were based on the study protocol published in PROSPERO. Methodological quality was assessed with the Newcastle-Ottawa Scale. We synthesised the data through vote counting and meta-analyses.

RESULTS

From 10 143 records screened, 281 studies reporting 1108 relevant associations are included in this review. Of the 384 associations included in vote counting, 271 (71%) suggested that a worse SE is associated with a higher risk of CMD. 14 meta-analyses based on 180 associations indicated that worse SE was associated with increased odds of CMD outcomes, with 4 of them being statistically significant. For example, more economic and social disadvantage was associated with higher heart failure risk (OR 1.58, 95% CI 1.08 to 1.61; n=18; I2=95%). With the exception of two meta-analyses for men, meta-analysed sex-specific associations consistently showed results in the same direction as the overall meta-analyses.

CONCLUSION

Worse SE seems to be associated with increased odds of CMD outcomes, although certain SE dimensions are underexplored in relation to CMD.

PROSPERO REGISTRATION NUMBER

CRD42021223035.

Social Determinants of Health Phenotypes and Cardiometabolic Condition Prevalence Among Patients in a Large Academic Health System: Latent Class Analysis

Background

Adverse social determinants of health (SDoH) have been associated with cardiometabolic disease; however, disparities in cardiometabolic outcomes are rarely the result of a single risk factor.

Objective

This study aimed to identify and characterize SDoH phenotypes based on patient-reported and neighborhood-level data from the institutional electronic medical record and evaluate the prevalence of diabetes, obesity, and other cardiometabolic diseases by phenotype status.

Methods

Patient-reported SDoH were collected (January to December 2020) and neighborhood-level social vulnerability, neighborhood socioeconomic status, and rurality were linked via census tract to geocoded patient addresses. Diabetes status was coded in the electronic medical record using International Classification of Diseases codes; obesity was defined using measured BMI ≥30 kg/m2. Latent class analysis was used to identify clusters of SDoH (eg, phenotypes); we then examined differences in the prevalence of cardiometabolic conditions based on phenotype status using prevalence ratios (PRs).

Results

Complete data were available for analysis for 2380 patients (mean age 53, SD 16 years; n=1405, 59% female; n=1198, 50% non-White). Roughly 8% (n=179) reported housing insecurity, 30% (n=710) reported resource needs (food, health care, or utilities), and 49% (n=1158) lived in a high-vulnerability census tract. We identified 3 patient SDoH phenotypes: (1) high social risk, defined largely by self-reported SDoH (n=217, 9%); (2) adverse neighborhood SDoH (n=1353, 56%), defined largely by adverse neighborhood-level measures; and (3) low social risk (n=810, 34%), defined as low individual- and neighborhood-level risks. Patients with an adverse neighborhood SDoH phenotype had higher prevalence of diagnosed type 2 diabetes (PR 1.19, 95% CI 1.06-1.33), hypertension (PR 1.14, 95% CI 1.02-1.27), peripheral vascular disease (PR 1.46, 95% CI 1.09-1.97), and heart failure (PR 1.46, 95% CI 1.20-1.79).

Conclusions

Patients with the adverse neighborhood SDoH phenotype had higher prevalence of poor cardiometabolic conditions compared to phenotypes determined by individual-level characteristics, suggesting that neighborhood environment plays a role, even if individual measures of socioeconomic status are not suboptimal.

Neighborhood Environment and Poor Maternal Glycemic Control-Associated Complications of Gestational Diabetes Mellitus

Introduction

Risk of complications due to gestational diabetes mellitus is increasing in the U.S., particularly among individuals from racial minorities. Research has focused largely on clinical interventions to prevent complications, rarely on individuals' residential environments. This retrospective cohort study aims to examine the association between individuals' neighborhoods and complications of gestational diabetes mellitus.

Methods

Demographic and clinical data were extracted from electronic health records and linked to American Community Survey data from the U.S. Census Bureau for 2,047 individuals who had 2,164 deliveries in 2014-2018. Data were analyzed in 2021-2022 using Wilcoxon rank sum test and chi-square test for bivariate analyses and logistic regression for analysis of independent effects. All census tract-based variables used in the model were dichotomized at the median.

Results

Bivariate analysis showed that the average percentage of adults earning <$35,000 was higher in neighborhoods where individuals with complications were living than in neighborhoods where individuals without complications were living (30.40%±12.05 vs 28.94%±11.71, p=0.0145). Individuals who lived in areas with ≥8.9% of residents aged >25 years with less than high school diploma had a higher likelihood of complications than those who lived in areas with <8.9% of such residents (33.43% vs 29.02%, p=0.0272). Individuals who lived in neighborhoods that had ≥1.8% of households receiving public assistance were more likely to have complications than those who lived in areas where <1.8% of households received public assistance (33.33% vs 28.97%, p=0.0287). Logistic regression revealed that the odds of deliveries with complications were 44% higher for individuals with obesity (OR=1.44; 95% CI=1.17, 1.77), 35% greater for individuals residing in neighborhoods with higher percentages of households living below the poverty level (OR=1.35; 95% CI=1.09, 1.66), and 28% lower for individuals from neighborhoods where a higher percentage of households had no vehicles available for transportation to work (OR=0.72; 95% CI=0.59, 0.89).

Conclusions

Clinical interventions in concert with environmental changes could contribute to preventing maternal and neonatal complications of gestational diabetes mellitus.

Place-Based Measures of Inequity and Vision Difficulty and Blindness

Importance

Known social risk factors associated with poor visual and systemic health in the US include segregation, income inequality, and persistent poverty.

Objective

To investigate the association of vision difficulty, including blindness, in neighborhoods with measures of inequity (Theil H index, Gini index, and persistent poverty).

Design, Setting, and Participants

This cross-sectional study used data from the 2012-2016 American Community Survey and 2010 US census tracts as well as Theil H index, Gini index, and persistent poverty measures from PolicyMap. Data analysis was completed in July 2023.

Main Outcomes and Measures

The main outcome was the number of census tract residents reporting vision difficulty and blindness (VDB) and the association with the Theil H index, Gini index, or persistent poverty, assessed using logistic regression.

Results

In total, 73 198 census tracts were analyzed. For every 0.1-unit increase in Theil H index and Gini index, there was an increased odds of VDB after controlling for census tract-level median age, the percentage of the population that identified as female sex, the percentage of the population that identified as a member of a racial or ethnic minority group, state, and population size (Theil H index: odds ratio [OR], 1.14 [95% CI, 1.14-1.14; P < .001]; Gini index: OR, 1.15 [95% CI, 1.15-1.15; P < .001]). Persistent poverty was associated with an increased odds of VDB after controlling for census tract-level median age, the percentage of the population that identified as female sex, the percentage of the population that identified as a member of a racial or ethnic minority group, state, and population size compared with nonpersistent poverty (OR, 1.36; 95% CI, 1.35-1.36; P < .001).

Conclusions and Relevance

In this cross-sectional study, residential measures of inequity through segregation, income inequality, or persistent poverty were associated with a greater number of residents living with VDB. It is essential to understand and address how neighborhood characteristics can impact rates of VDB.

Community credit scores and community socioeconomic deprivation in association with type 2 diabetes across an urban to rural spectrum in Pennsylvania: a case-control study

Background

Area-level credit scores (the mean of credit scores for persons in a community) may be a unique indicator of community-level socioeconomic conditions associated with health outcomes. We analysed community credit scores (CCS) in association with new onset type 2 diabetes (T2D) across a geographically heterogeneous region of Pennsylvania and evaluated whether associations were independent of community socioeconomic deprivation (CSD), which is known to be related to T2D risk.

Methods

In a nested case-control study, we used medical records to identify 15 888 T2D cases from diabetes diagnoses, medication orders and laboratory test results and 79 435 diabetes-free controls frequency matched on age, sex and encounter year. CCS was derived from Equifax VantageScore V.1.0 data and categorised as 'good', 'high fair', 'low fair' and 'poor'. Individuals were geocoded and assigned the CCS of their residential community. Logistic regression models adjusted for confounding variables and stratified by community type (townships (rural/suburban), boroughs (small towns) and city census tracts). Independent associations of CSD were assessed through models stratified by high/low CSD and high/low CCS.

Results

Compared with individuals in communities with 'high fair' CCS, those with 'good' CCS had lower T2D odds (42%, 24% and 12% lower odds in cities, boroughs and townships, respectively). Stratified models assessing independent effects of CCS and CSD showed mainly consistent associations, indicating each community-level measure was independently associated with T2D.

Conclusion

CCS may capture novel, health-salient aspects of community socioeconomic conditions, though questions remain regarding the mechanisms by which it influences T2D and how these differ from CSD.

Modifying effect of urban parks on socioeconomic inequalities in diabetes prevalence: a cross-sectional population study of Madrid City, Spain

BACKGROUND

Evidence has shown contradicting results on how the density of urban green spaces may reduce socioeconomic inequalities in type 2 diabetes (equigenic hypothesis). The aim of this study is to test whether socioeconomic inequalities in diabetes prevalence are modified by park density.

METHODS

We designed a population-wide cross-sectional study of all adults registered in the primary healthcare centres in the city of Madrid, Spain (n=1 305 050). We obtained georeferenced individual-level data from the Primary Care Electronic Health Records, and census-tract level data on socioeconomic status (SES) and park density. We modelled diabetes prevalence using robust Poisson regression models adjusted by age, country of origin, population density and including an interaction term with park density, stratified by gender. We used this model to estimate the Relative Index of Inequality (RII) at different park density levels.

FINDINGS

We found an overall RII of 2.90 (95% CI 2.78 to 3.02) and 4.50 (95% CI 4.28 to 4.74) in men and women, respectively, meaning that the prevalence of diabetes was three to four and a half times higher in low SES compared with high SES areas. These inequalities were wider in areas with higher park density for both men and women, with a significant interaction only for women (p=0.008).

INTERPRETATION

We found an inverse association between SES and diabetes prevalence in both men and women, with wider inequalities in areas with more parks. Future works should study the mechanisms of these findings, to facilitate the understanding of contextual factors that may mitigate diabetes inequalities.

Diet in Food Insecurity: A Mediator of Metabolic Health?

Objective

Food insecurity (FI) is associated with poor metabolic health. It is assumed that energy intake and diet quality underlie this association. We tested the hypothesis that dietary factors (quantity and quality) mediate the association of FI with excess weight, waist circumference and glycemic control [glycohemoglobin (A1C)].

Methods

A mediation analysis was performed on data from the National Health And Nutrition Examination Survey using FI as an independent variable; body mass index (BMI), waist circumference, and A1C as metabolic outcome variables and total energy intake, macronutrients, and diet quality measured by the Healthy Eating Index-2015 (HEI-2015) as potential mediators.

Results

Despite a greater prevalence of obesity in participants experiencing FI, daily reported energy intake was similar in food-secure and -insecure subjects. In adjusted analyses of the overall cohort, none of the examined dietary factors mediated associations between FI and metabolic outcomes. In race-stratified analyses, total sugar consumption was a partial mediator of BMI in non-Hispanic Whites, while diet quality measures (HEI-2015 total score and added sugar subscore) were partial mediators of waist circumference and BMI, respectively, for those in the "other" ethnic group.

Conclusion

Dietary factors are not the main factors underlying the association of FI with metabolic health. Future studies should investigate whether other social determinants of health commonly present in the context of FI play a role in this association.

Impact of socioeconomic status on chronic control and complications of type 1 diabetes mellitus in users of glucose flash systems: a follow-up study

BACKGROUND

This study investigates the association between socioeconomic status (SES) and glycemic control in individuals with type 1 diabetes (T1D) using flash glucose monitoring (FGM) devices within a public health system where these technologies are freely available and utilized according to recommended guidelines.

METHODS

A follow-up study of 1060 adults (mean age 47.4 ± 15.0 years, 49.0% women) with T1D, receiving care at three Spanish university hospitals that regularly employ the FGM system. SES was assessed using the Spanish Deprivation Index and the average annual net income per person. Glycemic data were collected over a 14-day follow-up period, including baseline glycated hemoglobin (HbA1c) levels prior to sensor placement, the last available HbA1c levels, and FGM-derived glucose metrics. Individuals with sensor usage time < 70% were excluded. Chronic micro and macrovascular complications related to diabetes were documented. Regression models, adjusted for clinical variables, were employed to determine the impact of SES on optimal sensor control (defined as time in range (TIR) ≥ 70% with time below range < 4%) and disease complications.

RESULTS

The average follow-up was of 2 years. The mean TIR and the percentage of individuals with optimal control were higher in individuals in the highest SES quartile (64.9% ± 17.8% and 27.9%, respectively) compared to those in the lowest SES quartile (57.8 ± 17.4% and 12.1%) (p < 0.001). Regression models showed a higher risk of suboptimal control (OR 2.27, p < 0.001) and ischemic heart disease and/or stroke (OR 3.59, p = 0.005) in the lowest SES quartile. No association was observed between SES and the risk of diabetic nephropathy and retinopathy. FGM system improved HbA1c levels across all SES quartiles. Although individuals in the highest SES quartile still achieved a significantly lower value at the end of the follow-up 55 mmol/mol (7.2%) compared to those in the lowest SES quartile 60 mmol/mol (7.6%) (p < 0.001), the significant disparities in this parameter between the various SES groups were significantly reduced after FGM technology use.

CONCLUSIONS

Socioeconomic status plays a significant role in glycemic control and complications in individuals with T1D, extending beyond access to technology and its proper utilization. The free utilization of FGM technology helps alleviate the impact of social inequalities on glycemic control.

Age and sex differences in the association between neighborhood socioeconomic environment and incident diabetes: Results from the diabetes location, environmental attributes and disparities (LEAD) network

Objective

Worse neighborhood socioeconomic environment (NSEE) may contribute to an increased risk of type 2 diabetes (T2D). We examined whether the relationship between NSEE and T2D differs by sex and age in three study populations.

Research design and methods

We conducted a harmonized analysis using data from three independent longitudinal study samples in the US: 1) the Veteran Administration Diabetes Risk (VADR) cohort, 2) the REasons for Geographic and Racial Differences in Stroke (REGARDS) cohort, and 3) a case-control study of Geisinger electronic health records in Pennsylvania. We measured NSEE with a z-score sum of six census tract indicators within strata of community type (higher density urban, lower density urban, suburban/small town, and rural). Community type-stratified models evaluated the likelihood of new diagnoses of T2D in each study sample using restricted cubic splines and quartiles of NSEE.

Results

Across study samples, worse NSEE was associated with higher risk of T2D. We observed significant effect modification by sex and age, though evidence of effect modification varied by site and community type. Largely, stronger associations between worse NSEE and diabetes risk were found among women relative to men and among those less than age 45 in the VADR cohort. Similar modification by age group results were observed in the Geisinger sample in small town/suburban communities only and similar modification by sex was observed in REGARDS in lower density urban communities.

Conclusions

The impact of NSEE on T2D risk may differ for males and females and by age group within different community types.

Demographic, social and geographic factors associated with glycaemic control among US Veterans with new onset type 2 diabetes: a retrospective cohort study

OBJECTIVES

This study evaluated whether a range of demographic, social and geographic factors had an influence on glycaemic control longitudinally after an initial diagnosis of diabetes.

DESIGN, SETTING AND PARTICIPANTS

We used the US Veterans Administration Diabetes Risk national cohort to track glycaemic control among patients 20-79-year old with a new diagnosis of type 2 diabetes.

PRIMARY OUTCOME AND METHODS

We modelled associations between glycaemic control at follow-up clinical assessments and geographic factors including neighbourhood race/ethnicity, socioeconomic, land use and food environment measures. We also adjusted for individual demographics, comorbidities, haemoglobin A1c (HbA1c) at diagnosis and duration of follow-up. These factors were analysed within strata of community type: high-density urban, low-density urban, suburban/small town and rural areas.

RESULTS

We analysed 246 079 Veterans who developed a new type 2 diabetes diagnosis in 2008-2018 and had at least 2 years of follow-up data available. Across all community types, we found that lower baseline HbA1c and female sex were strongly associated with a higher likelihood of within-range HbA1c at follow-up. Surprisingly, patients who were older or had more documented comorbidities were more likely to have within-range follow-up HbA1c results. While there was variation by community type, none of the geographic measures analysed consistently demonstrated significant associations with glycaemic control across all community types.

Care Management Processes Important for High-Quality Diabetes Care

OBJECTIVE

Identify the improvement in diabetes performance measures and population-based clinical outcomes resulting from changes in care management processes (CMP) in primary care practices over 3 years.

RESEARCH DESIGN AND METHODS

This repeated cross-sectional study tracked clinical performance measures for all diabetes patients seen in a cohort of 330 primary care practices in 2017 and 2019. Unit of analysis was patient-year with practice-level CMP exposures. Causal inference is based on dynamic changes in individual CMPs between years by practice. We used the Bayesian method to simultaneously estimate a five-outcome model: A1c, systolic and diastolic blood pressure, guideline-based statin use, and Optimal Diabetes Care (ODC). We control for unobserved time-invariant practice characteristics and secular change. We modeled correlation of errors across outcomes. Statistical significance was identified using 99% Bayesian credible intervals (analogous to P < 0.01).

RESULTS

Implementation of 18 of 62 CMPs was associated with statistically significant improvements in patient outcomes. Together, these resulted in 12.1% more patients meeting ODC performance measures. Different CMPs affected different outcomes. Three CMPs accounted for 47% of the total ODC improvement, 68% of A1c decrease, 21% of SBP reduction, and 55% of statin use increase: 1) systems for identifying and reminding patients due for testing, 2) after-visit follow-up by a nonclinician, and 3) guideline-based clinician reminders for preventive services during a clinic visit.

CONCLUSIONS

Effective quality improvement in primary care focuses on practice redesign that clearly improves diabetes outcomes. Tailoring CMP adoption in primary care provides effective improvement in ODC performance through focused changes in diabetes outcomes.

Racial and Ethnic Inequities in Development of Type 2 Diabetes After Gestational Diabetes Mellitus

OBJECTIVE

To estimate racial and ethnic disparities in type 2 diabetes mellitus after gestational diabetes mellitus (GDM) and to investigate baseline pregnancy clinical and social or structural characteristics as mediators.

METHODS

We conducted a retrospective cohort of individuals with GDM using linked 2009-2011 New York City birth and hospital data and 2009-2017 New York City A1c Registry data. We ascertained GDM and pregnancy characteristics from birth and hospital records. We classified type 2 diabetes as two hemoglobin A 1c test results of 6.5% or higher. We grouped pregnancy characteristics into clinical (body mass index [BMI], chronic hypertension, gestational hypertension, preeclampsia, preterm delivery, caesarean, breastfeeding, macrosomia, shoulder dystocia) and social or structural (education, Medicaid insurance, prenatal care, and WIC [Special Supplemental Nutrition Program for Women, Infants, and Children] participation). We used Cox proportional hazards models to estimate associations between race and ethnicity and 8-year type 2 diabetes incidence, and we tested mediation of pregnancy characteristics, additionally adjusting for age and nativity (U.S.-born vs foreign-born).

RESULTS

The analytic data set included 22,338 patients with GDM. The 8-year type 2 diabetes incidence was 11.7% overall and 18.5% in Black, 16.8% in South and Southeast Asian, 14.6% in Hispanic, 5.5% in East and Central Asian, and 5.4% in White individuals with adjusted hazard ratios of 4.0 (95% CI 2.4-3.9), 2.9 (95% CI 2.4-3.3), 3.3 (95% CI 2.7-4.2), and 1.0 (95% CI 0.9-1.4) for each group compared with White individuals. Clinical and social or structural pregnancy characteristics explained 9.3% and 23.8% of Black, 31.2% and 24.7% of Hispanic, and 7.6% and 16.3% of South and Southeast Asian compared with White disparities. Associations between education, Medicaid insurance, WIC participation, and BMI and type 2 diabetes incidence were more pronounced among White than Black, Hispanic, and South and Southeast Asian individuals.

CONCLUSION

Population-based racial and ethnic inequities are substantial in type 2 diabetes after GDM. Characteristics at the time of delivery partially explain disparities, creating an opportunity to intervene on life-course cardiometabolic inequities, whereas weak associations of common social or structural measures and BMI in Black, Hispanic and South and Southeast Asian individuals demonstrate the need for greater understanding of how structural racism influences postpartum cardiometabolic risk in these groups.

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.

Advancing health equity through implementation science: Identifying and examining measures of the outer setting

BACKGROUND

Implementation science (IS) could accelerate progress toward achieving health equity goals. However, the lack of attention to the outer setting where interventions are implemented limits applicability and generalizability of findings to different populations, settings, and time periods. We developed a data resource to assess outer setting across seven centers funded by the National Cancer Institute's IS Centers in Cancer Control (ISC3) Network Program.

OBJECTIVE

To describe the development of the Outer Setting Data Resource and characterize the county-level outer context across Centers.

METHODS

Our Data Resource captures seven key environments, including: (1) food; (2) physical; (3) economic; (4) social; (5) health care; (6) cancer behavioral and screening; and (7) cancer-related policy. Data were obtained from public sources including the US Census and American Community Survey. We present medians and interquartile ranges based on the distribution of all counties in the US, all ISC3 centers, and within each Center for twelve selected measures. Distributions of each factor are compared with the national estimate using single sample sign tests.

RESULTS

ISC3 centers' catchment areas include 458 counties and over 126 million people across 28 states. The median percentage of population living within ½ mile of a park is higher in ISC3 counties (38.0%, interquartile range (IQR): 16.0%-59.0%) compared to nationally (18.0%, IQR: 7.0%-38.0%; p < 0.0001). The median percentage of households with no broadband access is significantly lower in ISC3 counties (28.4%, IQR: 21.4%-35.6%) compared the nation overall (32.8%, IQR: 25.8%-41.2%; p < 0.0001). The median unemployment rate was significantly higher in ISC3 counties (5.2%, IQR: 4.1%-6.4%) compared to nationally (4.9%, 3.6%-6.3%, p = 0.0006).

CONCLUSIONS

Our results indicate that the outer setting varies across Centers and often differs from the national level. These findings demonstrate the importance of assessing the contextual environment in which interventions are implemented and suggest potential implications for intervention generalizability and scalability.

Perceived neighborhood social cohesion and type 2 diabetes mellitus by age, sex/gender, and race/ethnicity in the United States

In prior research, perceived low neighborhood social cohesion (nSC) has been associated with prevalence of type 2 diabetes mellitus (T2DM); however, few studies have investigated the nSC-T2DM relationship among a large, racially/ethnically diverse, and nationally representative sample of the U.S. population. We used National Health Interview Survey (2013-2018) data to determine overall, age-, sex/gender-, and racial/ethnic-specific associations between nSC and T2DM among 170,432 adults. Self-reported nSC was categorized as low, medium, and high. T2DM was determined by participants being told they had diabetes by a health professional. We used Poisson regression with robust variance to estimate prevalence ratios (PRs) and 95% confidence intervals (CI) while adjusting for confounders. Mean age was 47.4 ± 0.1 years, 52% were women, and 69% self-identified as Non-Hispanic (NH)-White. Low vs. high nSC was associated with a higher prevalence of T2DM (PR = 1.22 [95% CI: 1.16-1.27]), after adjustment. A higher prevalence of T2DM was observed among participants 31-49 years old who perceived low vs. high nSC (PR = 1.36 [95% CI: 1.20-1.54]) and among participants ≥50 years old (PR = 1.18 [95% CI: 1.13-1.24]). Hispanic/Latinx women 18-30 years old in neighborhoods with low vs. high social cohesion had a higher prevalence of T2DM (PR = 3.70 [95% CI: 1.40-9.80]), whereas NH-Black women 18-30 years old in neighborhoods with medium vs. high social cohesion had a lower prevalence of T2DM (PR = 0.35 [95% CI: 0.14-0.89]). Our findings support the literature by demonstrating an association between neighborhood environment and T2DM as well as extend it by identifying determinants for intervention for T2DM.

Cumulative Risk Evaluation of Phthalates Under TSCA

The U.S. Environmental Protection Agency (EPA) is currently conducting separate Toxic Substances Control Act (TSCA) risk evaluations for seven phthalates: dibutyl phthalate (DBP), butyl benzyl phthalate (BBP), di(2-ethylhexyl) phthalate (DEHP), diisobutyl phthalate (DIBP), dicyclohexyl phthalate (DCHP), di-isodecyl phthalate (DIDP), and diisononyl phthalate (DINP). Phthalates are highly abundant plastic additives used primarily to soften materials and make them flexible, and biomonitoring shows widespread human exposure to a mixture of phthalates. Evidence supports biological additivity of phthalate mixture exposures, including the enhancement of toxicity affecting common biological targets. Risk estimates based on individual phthalate exposure may not be protective of public health. Thus, a cumulative risk approach is warranted. While EPA initially did not signal that it would incorporate cumulative risk assessment (CRA) as part of its current risk evaluation for the seven phthalates, the agency recently announced that it is reconsidering if CRA for phthalates would be appropriate. Based on our review of existing chemical mixtures risk assessment guidance, current TSCA scoping documents for the seven phthalates, and pertinent peer-reviewed literature, we delineate a CRA approach that EPA can easily implement for phthalates. The strategy for using CRA to inform TSCA risk evaluation for existing chemicals is based upon integrative physiology and a common adverse health outcome algorithm for identifying and grouping relevant nonchemical and chemical stressors. We recommend adjustments for how hazard indices (HIs) or margins of exposure (MOEs) based on CRA are interpreted for determining "unreasonable risk" under TSCA.

Exercise facility availability and incidence of type 2 diabetes and complications in Spain: A population-based retrospective cohort 2015-2018

BACKGROUND

To study the association between exercise facility availability and type 2 diabetes incidence and its complications, and to explore effect modification by socioeconomic status (SES) and sex in the Madrid adult population.

METHODS

A multilevel longitudinal design, based on a population-based retrospective cohort including 1,214,281 residents of Madrid (Spain) aged 40-75 years from 2015 to 2018. Outcomes were type 2 diabetes incidence and macrovascular (cardiac ischemia and/or stroke) and microvascular (chronic kidney disease, retinopathy, and/or peripheral vascular disease) complications in those with diabetes at baseline. Exercise facility availability was defined as the count of exercise facilities in a 1000 m street network buffer around each participant's residence. Poisson regression models with robust standard errors were used to estimate the risk ratios (RR). Interactions were explored with SES tertiles and by sex.

RESULTS

Residents living in areas with lower exercise facility availability showed higher risk of type 2 diabetes (RR_tertile3vs1 = 1.25, CI95% 1.21-1.30) as well as macrovascular (RR_Tertile3vs1 = 1.09 CI95% 1.00-1.19), and microvascular (RR_Tertile3vs1 = 1.10 CI95% 1.01-1.19) complications. Associations were strongest in low SES areas for type 2 diabetes (RR_{tertile3vs1-LOW-SES} = 1.22, CI95% 1.12-1.32; RR_{tertile3vs1-HIGH-SES} = 0.91, CI95% 0.85-0.98) and microvascular complications (RR_{tertile3vs1-LOW-SES} = 1.12, CI95% 0,94-1,33; RR_{tertile3vs1-HIGH-SES} = 0.88, CI95% 0.73-1.05).

CONCLUSIONS

Living in areas with lower availability of exercise facilities was associated with a greater risk of type 2 diabetes and its complications. Increasing exercise opportunities, particularly in low SES areas, could help reduce the social gradient of diabetes and its complications.

A decade of socioeconomic inequality in type 2 diabetes area-level prevalence: an unshakeable status quo?

AIMS

It is well known that there is a socioeconomic gradient in the prevalence of many chronic diseases, including type 2 diabetes (T2DM). We present a simple assessment of the macro-level association between area socioeconomic disadvantage and the area-level prevalence of T2DM in Danish municipalities and the development in this relationship over the last decade.

METHODS

We used readily available public data on the socioeconomic composition of municipalities and T2DM prevalence to illustrate this association and report the absolute and relative summary measures of socioeconomic inequality over the time period 2008-2018.

RESULTS

The results show a persistent relationship between municipality socioeconomic disadvantage and T2DM prevalence across all analyses, with a modelled gap in T2DM prevalence between the most and least disadvantaged municipalities, the slope index of inequality, of 1.23 [0.97;1.49] in 2018.

CONCLUSIONS

These results may be used to indicate areas with specific needs, to encourage systematic monitoring of socioeconomic gradients in health, and to provide a descriptive backdrop for a discussion of how to tackle these socioeconomic and geographic inequalities, which seem to persist even in the context of the comprehensive welfare systems in Scandinavia.

Perspective: Acknowledging a Hierarchy of Social Needs in Diabetes Clinical Care and Prevention

The evidence of suboptimal social determinants of health (SDoH) on poor health outcomes has resulted in widespread calls for research to identify ways to measure and address social needs to improve health outcomes and reduce disparities. While assessing SDoH has become increasingly important in diabetes care and prevention research, little guidance has been offered on how to address suboptimal determinants in diabetes-related clinical care, prevention efforts, medical education and research. Not surprisingly, many patients experience multiple social needs - some that are more urgent (housing) than others (transportation/resources), therefore the order in which these needs are addressed needs to be considered in the context of diabetes care/outcomes. Here we discuss how conceptualizing diabetes related health through the lens of Maslow's hierarchy of needs has potential to help prioritize individual social needs that should be addressed to improve outcomes in the context of population-level determinants in the communities where people live.

A Cluster Randomized Controlled Trial Comparing Diabetes Prevention Program Interventions for Overweight/Obese Marshallese Adults

This study compared the effectiveness of two Diabetes Prevention Program (DPP) interventions on weight loss among overweight and obese Marshallese adults. The study was a two-arm cluster randomized controlled trial conducted in 30 churches in Arkansas and Oklahoma. Marshallese adults with a body mass index ≥25 kg/m2 were eligible for the study. The study sample included 380 participants. Participants received either a faith-based adaptation of the DPP or a family-focused adaptation of the DPP, each delivered over 24 weeks. The primary outcome was weight change from baseline. Secondary outcomes included changes in Hemoglobin A1c, blood pressure, dietary intake, family support for healthy behaviors, and physical activity. Outcomes were examined longitudinally using general linear mixed effects regression models, adjusting for baseline outcomes, sociodemographic covariates, and clustering of participants within churches. Reductions in weight were small for both groups. Overall, only 7.1% of all participants lost 5% or more of their baseline body weight. There were no significant differences in weight loss between the 2 arms at 6 months (P = .3599) or at 12 months (P = .3207). Significant differences in systolic and diastolic blood pressure were found between the 2 arms at 6 months (P = .0293; P = .0068, respectively). Significant within-arm changes were found for sugar-sweetened beverage consumption and family support for both arms at both follow-ups. Both interventions achieved a modest weight loss. While even modest weight loss can be clinically significant, future research is needed to identify chronic disease prevention interventions that can successfully reduce weight for this at-risk population.

Association of Area Deprivation Index and hypertension, diabetes, dyslipidemia, and Obesity: A Cross-Sectional Study of the HABS-HD Cohort

Objective: This study aims to investigate the association between neighborhood deprivation and the prevalence of major cardiovascular disease (CVD) risk factors (hypertension, diabetes, dyslipidemia, and obesity) in a Mexican American (MA) population compared to NonHispanic Whites (NHW). Method: A cross-sectional analysis was conducted to include 1,867 subjects (971 MA and 896 NHW). Participants underwent a clinical interview, neuropsychological exam battery, functional examination, MRI of the head, amyloid PET scan, and blood draw for clinical and biomarker analysis. We use the Area Deprivation Index (ADI) Model to assign an ADI score to participants based on their neighborhoods. Descriptive, Cochran-Armitage test for trend, and odds ratio statistical analysis were applied. Results: Our results suggest that NHW had higher odds of having HTN, DM, and obesity in the most deprived neighborhoods, while MA showed no increased odds. The study also found that neighborhood deprivation contributed to diabetes in both MA and NHW and was associated with obesity in NHW. Conclusions: These findings highlighted the importance of addressing both individual and societal factors in efforts to reduce cardiovascular risk. Future research should explore the relationship between socio-economic status and cardiovascular risk in more detail to inform the development of targeted interventions.

The urban built environment and adult BMI, obesity, and diabetes in Latin American cities

Latin America is the world's most urbanized region and its heterogeneous urban development may impact chronic diseases. Here, we evaluated the association of built environment characteristics at the sub-city -intersection density, greenness, and population density- and city-level -fragmentation and isolation- with body mass index (BMI), obesity, and type 2 diabetes (T2D). Data from 93,280 (BMI and obesity) and 122,211 individuals (T2D) was analysed across 10 countries. Living in areas with higher intersection density was positively associated with BMI and obesity, whereas living in more fragmented and greener areas were negatively associated. T2D was positively associated with intersection density, but negatively associated with greenness and population density. The rapid urban expansion experienced by Latin America provides unique insights and vastly expand opportunities for population-wide urban interventions aimed at reducing obesity and T2D burden.

Associations between the urban exposome and type 2 diabetes: Results from penalised regression by least absolute shrinkage and selection operator and random forest models

BACKGROUND

Type 2 diabetes (T2D) is thought to be influenced by environmental stressors such as air pollution and noise. Although environmental factors are interrelated, studies considering the exposome are lacking. We simultaneously assessed a variety of exposures in their association with prevalent T2D by applying penalised regression Least Absolute Shrinkage and Selection Operator (LASSO), Random Forest (RF), and Artificial Neural Networks (ANN) approaches. We contrasted the findings with single-exposure models including consistently associated risk factors reported by previous studies.

METHODS

Baseline data (n = 14,829) of the Occupational and Environmental Health Cohort study (AMIGO) were enriched with 85 exposome factors (air pollution, noise, built environment, neighbourhood socio-economic factors etc.) using the home addresses of participants. Questionnaires were used to identify participants with T2D (n = 676(4.6 %)). Models in all applied statistical approaches were adjusted for individual-level socio-demographic variables.

RESULTS

Lower average home values, higher share of non-Western immigrants and higher surface temperatures were related to higher risk of T2D in the multivariable models (LASSO, RF). Selected variables differed between the two multi-variable approaches, especially for weaker predictors. Some established risk factors (air pollutants) appeared in univariate analysis but were not among the most important factors in multivariable analysis. Other established factors (green space) did not appear in univariate, but appeared in multivariable analysis (RF). Average estimates of the prediction error (logLoss) from nested cross-validation showed that the LASSO outperformed both RF and ANN approaches.

CONCLUSIONS

Neighbourhood socio-economic and socio-demographic characteristics and surface temperature were consistently associated with the risk of T2D. For other physical-chemical factors associations differed per analytical approach.

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.

Associations of four indexes of social determinants of health and two community typologies with new onset type 2 diabetes across a diverse geography in Pennsylvania

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.

Inequalities by Income in the Prevalence of Cardiovascular Disease and Its Risk Factors in the Adult Population of Catalonia

Background Understanding the magnitude of cardiovascular disease (CVD) inequalities is the first step toward addressing them. The linkage of socioeconomic and clinical data in universal health care settings provides critical information to characterize CVD inequalities. Methods and Results We employed a prospective cohort design using electronic health records data from all residents of Catalonia aged 18+ between January and December of 2019 (N=6 332 228). We calculated age-adjusted sex-specific prevalence of 5 CVD risk factors (diabetes, hypertension, hyperlipidemia, obesity, and smoking), and 4 CVDs (coronary heart disease, cerebrovascular disease, atrial fibrillation, and heart failure). We categorized income into high, moderate, low, and very low according to individual income (tied to prescription copayments) and receipt of welfare support. We found large inequalities in CVD and CVD risk factors among men and women. CVD risk factors with the largest inequalities were diabetes, smoking, and obesity, with prevalence rates 2- or 3-fold higher for those with very low (versus high) income. CVDs with the largest inequalities were cerebrovascular disease and heart failure, with prevalence rates 2 to 4 times higher for men and women with very low (versus high) income. Inequalities varied by age, peaking at midlife (30-50 years) for most diseases, while decreasing gradually with age for smoking. Conclusions We found wide and heterogeneous inequalities by income in 5 CVD risk factors and 4 CVD. Our findings in a region with a high-quality public health care system and universal coverage stress that strong equity-promoting policies are necessary to reduce disparities in CVD.

Latent growth trajectories of county-level diabetes prevalence in the United States, 2004–2017, and associations with overall environmental quality

The prevalence of type 2 diabetes (T2D) has increased in the United States, and recent studies suggest that environmental factors contribute to T2D risk. We sought to understand if environmental factors were associated with the rate and magnitude of increase in diabetes prevalence at the county level.

An international comparative study of active living environments and hospitalization for Wales and Canada

Rationale: Previous studies indicate active living environments (ALEs) are associated with higher physical activity levels across different geographic contexts, and could lead to reductions in hospital burden. Both Wales UK and Canada have advanced data infrastructure that allows record linkage between survey data and administrative health information.

Objective

To assess the relationship between ALEs and hospitalization in Wales and Canada.

Methods

We performed a population-based comparison using individual-level survey data from the Welsh Health Survey (N = 9968) linked to the Patient Episode Database for Wales, and the Canadian Community Health Survey (N = 40,335) linked to the Discharge Abstract Database. Using equivalent protocols and open-source data for street networks, destinations, and residential density, we derived 5-class measures of the ALE for Wales and Canada (classed 1 through 5, considered least favourable to most favourable for active living, respectively). We evaluated relationships of ALEs to health, behaviours and hospitalization using multivariate regression (reference group was the lowest ALE class 1, considered least favourable for active living).

Results

For Canada, those living in the highest ALE class 5 had lower odds of all-cause hospitalization (OR 0.66, 95% CI 0.54 to 0.81; as compared to the lowest ALE class 1). In contrast, those living in the highest ALE class 5 in Wales had higher odds of all-cause hospitalization (OR 1.37, 95% CI 1.04 to 1.80). The relationship between ALEs and cardiometabolic hospitalization was inconclusive for Canada (OR 0.75, 95% CI 0.50 to 1.12), but we observed higher odds of cardiometabolic hospitalization for respondents living in higher ALE classes for Wales (OR 1.46, 95% CI 1.10 to 1.78; comparing ALE class 4 to ALE class 1).

Conclusion

Canadian respondents living in high ALE neighbourhoods that are understood to be favourable for active living had lower odds of all-cause hospitalization, whereas Welsh respondents living in high ALEs that were deemed favourable for active living exhibited higher odds of all-cause hospitalization. Environments which promote physical activity in one geographic context may not do so in another. There remains a need to identify relevant context-specific factors that encourage active living.