Associations between PM2.5 and O3 exposures and new onset type 2 diabetes in regional and national samples in the United States.

BACKGROUND: Exposure to particulate matter ≤2.5 µm in diameter (PM2.5) and ozone (O3) has been linked to numerous harmful health outcomes. While epidemiologic evidence has suggested a positive association with type 2 diabetes (T2D), there is heterogeneity in findings. We evaluated exposures to PM2.5 and O3 across three large samples in the US using a harmonized approach for exposure assignment and covariate adjustment. METHODS: Data were obtained from the Veterans Administration Diabetes Risk (VADR) cohort (electronic health records [EHRs]), the Reasons for Geographic and Racial Disparities in Stroke (REGARDS) cohort (primary data collection), and the Geisinger health system (EHRs), and reflect the years 2003-2016 (REGARDS) and 2008-2016 (VADR and Geisinger). New onset T2D was ascertained using EHR information on medication orders, laboratory results, and T2D diagnoses (VADR and Geisinger) or report of T2D medication or diagnosis and/or elevated blood glucose levels (REGARDS). Exposure was assigned using pollutant annual averages from the Downscaler model. Models stratified by community type (higher density urban, lower density urban, suburban/small town, or rural census tracts) evaluated likelihood of new onset T2D in each study sample in single- and two-pollutant models of PM2.5 and O3. RESULTS: In two pollutant models, associations of PM2.5, and new onset T2D were null in the REGARDS cohort except for in suburban/small town community types in models that also adjusted for NSEE, with an odds ratio (95% CI) of 1.51 (1.01, 2.25) per 5 µg/m3 of PM2.5. Results in the Geisinger sample were null. VADR sample results evidenced nonlinear associations for both pollutants; the shape of the association was dependent on community type. CONCLUSIONS: Associations between PM2.5, O3 and new onset T2D differed across three large study samples in the US. None of the results from any of the three study populations found strong and clear positive associations.

Disparities in routine healthcare utilization disruptions during COVID-19 pandemic among veterans with type 2 diabetes.

BACKGROUND: While emerging studies suggest that the COVID-19 pandemic caused disruptions in routine healthcare utilization, the full impact of the pandemic on healthcare utilization among diverse group of patients with type 2 diabetes is unclear. The purpose of this study is to examine trends in healthcare utilization, including in-person and telehealth visits, among U.S. veterans with type 2 diabetes before, during and after the onset of the COVID-19 pandemic, by demographics, pre-pandemic glycemic control, and geographic region. METHODS: We longitudinally examined healthcare utilization in a large national cohort of veterans with new diabetes diagnoses between January 1, 2008 and December 31, 2018. The analytic sample was 733,006 veterans with recently-diagnosed diabetes, at least 1 encounter with veterans administration between March 2018-2020, and followed through March 2021. Monthly rates of glycohemoglobin (HbA1c) measurements, in-person and telehealth outpatient visits, and prescription fills for diabetes and hypertension medications were compared before and after March 2020 using interrupted time-series design. Log-linear regression model was used for statistical analysis. Secular trends were modeled with penalized cubic splines. RESULTS: In the initial 3 months after the pandemic onset, we observed large reductions in monthly rates of HbA1c measurements, from 130 (95%CI,110-140) to 50 (95%CI,30-80) per 1000 veterans, and in-person outpatient visits, from 1830 (95%CI,1640-2040) to 810 (95%CI,710-930) per 1000 veterans. However, monthly rates of telehealth visits doubled between March 2020-2021 from 330 (95%CI,310-350) to 770 (95%CI,720-820) per 1000 veterans. This pattern of increases in telehealth utilization varied by community type, with lowest increase in rural areas, and by race/ethnicity, with highest increase among non-hispanic Black veterans. Combined in-person and telehealth outpatient visits rebounded to pre-pandemic levels after 3 months. Despite notable changes in HbA1c measurements and visits during that initial window, we observed no changes in prescription fills rates. CONCLUSIONS: Healthcare utilization among veterans with diabetes was substantially disrupted at the onset of the pandemic, but rebounded after 3 months. There was disparity in uptake of telehealth visits by geography and race/ethnicity.

Impact of land use and food environment on risk of type 2 diabetes: A national study of veterans, 2008-2018.

BACKGROUND: Large-scale longitudinal studies evaluating influences of the built environment on risk for type 2 diabetes (T2D) are scarce, and findings have been inconsistent. OBJECTIVE: To evaluate whether land use environment (LUE), a proxy of neighborhood walkability, is associated with T2D risk across different US community types, and to assess whether the association is modified by food environment. METHODS: The Veteran's Administration Diabetes Risk (VADR) study is a retrospective cohort of diabetes-free US veteran patients enrolled in VA primary care facilities nationwide from January 1, 2008, to December 31, 2016, and followed longitudinally through December 31, 2018. A total of 4,096,629 patients had baseline addresses available in electronic health records that were geocoded and assigned a census tract-level LUE score. LUE scores were divided into quartiles, where a higher score indicated higher neighborhood walkability levels. New diagnoses for T2D were identified using a published computable phenotype. Adjusted time-to-event analyses using piecewise exponential models were fit within four strata of community types (higher-density urban, lower-density urban, suburban/small town, and rural). We also evaluated effect modification by tract-level food environment measures within each stratum. RESULTS: In adjusted analyses, higher LUE had a protective effect on T2D risk in rural and suburban/small town communities (linear quartile trend test p-value <0.001). However, in lower density urban communities, higher LUE increased T2D risk (linear quartile trend test p-value <0.001) and no association was found in higher density urban communities (linear quartile trend test p-value = 0.317). Particularly strong protective effects were observed for veterans living in suburban/small towns with more supermarkets and more walkable spaces (p-interaction = 0.001). CONCLUSION: Among veterans, LUE may influence T2D risk, particularly in rural and suburban communities. Food environment may modify the association between LUE and T2D.

Calibrating Local Population-Based Blood Pressure Data from NYC HANES 2013-2014.

New York City Health and Nutrition Examination Survey (NYC HANES) was a population-based cross-sectional survey of NYC adults conducted twice, in 2004 and again in 2013-2014, to monitor the health of NYC adults 20 years or older. While blood pressure was measured in both surveys, an auscultatory mercury sphygmomanometer was used to measure blood pressure in clinics in 2004, and an oscillometric LifeSource UA-789AC monitor was used in homes in 2013-2014. To assess comparability of blood pressure results across both surveys, we undertook a randomized study comparing blood pressure (BP) readings by the two devices. Blood pressure measuring protocols followed the 2013 Association for the Advancement in Medical instrumentation guidelines for non-invasive blood pressure device. Data from 167 volunteers were analyzed for this purpose.Paired t tests were used to test for significant difference in mean systolic and diastolic blood pressure between devices for overall and by mid-arm circumference categories. To test for systematic differences between the two devices, we generated Bland-Altman graphs. Sensitivity, specificity, and Kappa statistics were calculated to assess between-device agreement for high (≥ 130/80 mmHg) and not high (< 130/80 mmHg) blood pressure, with mercury set as the reference.Systolic and diastolic blood pressure measured by LifeSource UA-789AC were on average 2.0 and 1.1 mmHg higher, respectively, than those of the mercury sphygmomanometer systolic and diastolic blood pressure readings (P < 0.05). Sensitivity was 81%, specificity was 96%, and the Kappa coefficient was 75%. The Bland-Altman graphs showed that the between-device difference did not vary as a function of the average of the two devices for systolic blood pressure and was larger in the lower and upper ends for diastolic blood pressure. Given the observed differences in systolic and diastolic blood pressure readings between the two blood pressure measurement approaches, we calibrated NYC HANES 2013-2014 blood pressure data by predicting mercury blood pressure values from LifeSource blood pressure values. The mean systolic and diastolic blood pressure in NYC HANES 2013-2014 were lower when data were calibrated.

Is Intussusception a Middle-of-the-Night Emergency?

OBJECTIVES: Intussusception is the most common abdominal emergency in pediatric patients aged 6 months to 3 years. There is often a delay in diagnosis, as the presentation can be confused for viral gastroenteritis. Given this scenario, we questioned the practice of performing emergency reductions in children during the night when minimal support staff are available. Pneumatic reduction is not a benign procedure, with the most significant risk being bowel perforation. We performed this analysis to determine whether it would be safe to delay reduction in these patients until normal working hours when more support staff are available. METHODS: We performed a retrospective review of intussusceptions occurring between January 2010 and May 2015 at 2 tertiary care institutions. The medical record for each patient was evaluated for age at presentation, sex, time of presentation to clinician or the emergency department, and time to reduction. The outcomes of attempted reduction were documented, as well as time to surgery and surgical findings in applicable cases. A Wilcoxon rank test was used to compare the median time with nonsurgical intervention among those who did not undergo surgery to the median time to nonsurgical intervention among those who ultimately underwent surgery for reduction. Multivariable logistic regression was used to test the association between surgical intervention and time to nonsurgical reduction, adjusting for the age of patients. RESULTS: The median time to nonsurgical intervention was higher among patients who ultimately underwent surgery than among those who did not require surgery (17.9 vs 7.0 hours; P < 0.0001). The time to nonsurgical intervention was positively associated with a higher probability of surgical intervention (P = 0.002). CONCLUSIONS: Intussusception should continue to be considered an emergency, with nonsurgical reduction attempted promptly as standard of care.

Disparities in Sleep Problems by Sexual Orientation among New York City Adults: an Analysis of the New York City Health and Nutrition Examination Survey, 2013-2014.

We examined disparities in sleep problems by sexual orientation among a population-based sample of adults, using data from the New York City (NYC) Health and Nutrition Examination Survey (NYC HANES), a population-based, cross-sectional survey conducted in 2013-2014 (n = 1220). Two log binomial regression models were created to assess the relative prevalence of sleep problems by sexual orientation. In model 1, heterosexual adults served as the reference category, controlling for gender, age, race/ethnicity, education, marital status, and family income. And in model 2, heterosexual men served as the reference category, controlling for age, race/ethnicity, education, marital status, and family income. We found that almost 42% of NYC adults reported sleep problems in the past 2 weeks. Bisexual adults had 1.4 times the relative risk of sleep problems compared to heterosexual adults (p = 0.037). Compared to heterosexual men, heterosexual and bisexual women had 1.3 and 1.6 times the risk of sleep problems, respectively (p < 0.05). Overall, adults who self-identified as bisexual had a significantly greater risk of sleep problems than adults who self-identified as heterosexual.

Change in Obesity Prevalence among New York City Adults: the NYC Health and Nutrition Examination Survey, 2004 and 2013-2014.

The objective of this study was to measure change in obesity prevalence among New York City (NYC) adults from 2004 to 2013-2014 and assess variation across sociodemographic subgroups. We used objectively measured height and weight data from the NYC Health and Nutrition Examination Survey to calculate relative percent change in obesity (≥ 30 kg/m2) between 2004 (n = 1987) and 2013-2014 (n = 1489) among all NYC adults and sociodemographic subgroups. We also examined changes in self-reported proxies for energy imbalance. Estimates were age-standardized and statistical significance was evaluated using two-tailed T tests and multivariable regression (p < 0.05). Between 2004 and 2013-2014, obesity increased from 27.5 to 32.4% (p = 0.01). Prevalence remained stable and high among women (31.2 to 32.8%, p = 0.53), but increased among men (23.4 to 32.0%, p = 0.002), especially among non-Latino White men and men age ≥ 65 years. Black adults had the highest prevalence in 2013-2014 (37.1%) and Asian adults experienced the largest increase (20.1 to 29.2%, p = 0.06), especially Asian women. Foreign-born participants and participants lacking health insurance also had large increases in obesity. We observed increases in eating out and screen time over time and no improvements in physical activity. Our findings show increases in obesity in NYC in the past decade, with important sociodemographic differences.

Correction to: Change in Obesity Prevalence among New York City Adults: the NYC Health and Nutrition Examination Survey, 2004 and 2013-2014.

Readers should note the following two typographical errors in this article.

Change in Diabetes Prevalence and Control among New York City Adults: NYC Health and Nutrition Examination Surveys 2004-2014.

National examination surveys provide trend information on diabetes prevalence, diagnoses, and control. Few localities have access to such information. Using a similar design as the National Health and Nutrition Examination Survey (NHANES), two NYC Health and Nutrition Examination Surveys (NYC HANES) were conducted over a decade, recruiting adults ≥ 20 years using household probability samples (n = 1808 in 2004; n = 1246 in 2013-2014) and physical exam survey methods benchmarked against NHANES. Participants had diagnosed diabetes if told by a health provider they had diabetes, and undiagnosed diabetes if they had no diagnosis but a fasting plasma glucose ≥ 126 mg/dl or A1C ≥ 6.5%. We found that between 2004 and 2014, total diabetes prevalence (diagnosed and undiagnosed) in NYC increased from 13.4 to 16.0% (P = 0.089). In 2013-2014, racial/ethnic disparities in diabetes burden had widened; diabetes was highest among Asians (24.6%), and prevalence was significantly lower among non-Hispanic white adults (7.7%) compared to that among other racial/ethnic groups (P < 0.001). Among adults with diabetes, the proportion of cases diagnosed increased from 68.3 to 77.3% (P = 0.234), and diagnosed cases with very poor control (A1C > 9%), decreased from 26.9 to 18.0% (P = 0.269), though both were non-significant. While local racial/ethnic disparities in diabetes prevalence persist, findings suggest modest improvements in diabetes diagnosis and management.

Gender and Race Disparities in Cardiovascular Disease Risk Factors among New York City Adults: New York City Health and Nutrition Examination Survey (NYC HANES) 2013-2014.

While gender and racial/ethnic disparities in cardiovascular disease (CVD) risk factors have each been well characterized, few studies have comprehensively examined how patterns of major CVD risk factors vary and intersect across gender and major racial/ethnic groups, considered together. Using data from New York City Health and Nutrition Examination Survey 2013-2014-a population-based, cross-sectional survey of NYC residents ages 20 years and older-we measured prevalence of obesity, hypertension, hypercholesterolemia, smoking, and diabetes across gender and race/ethnicity groups for 1527 individuals. We used logistic regression with predicted marginal to estimate age-adjusted prevalence ratio by gender and race/ethnicity groups and assess for potential additive and multiplicative interaction. Overall, women had lower prevalence of CVD risk factors than men, with less hypertension (p = 0.040), lower triglycerides (p < 0.001), higher HDL (p < 0.001), and a greater likelihood of a heart healthy lifestyle, more likely not to smoke and to follow a healthy diet (p < 0.05). When further stratified by race/ethnicity, however, the female advantage was largely restricted to non-Latino white women. Non-Latino black women had significantly higher risk of being overweight or obese, having hypertension, and having diabetes than non-Latino white men or women, or than non-Latino black men (p < 0.05). Non-Latino black women also had higher total cholesterol compared to non-Latino black men (184.4 vs 170.5 mg/dL, p = 0.010). Despite efforts to improve cardiovascular health and narrow disparities, non-Latino black women continue to have a higher burden of CVD risk factors than other gender and racial/ethnic groups. This study highlights the importance of assessing for intersectionality between gender and race/ethnicity groups when examining CVD risk factors.

Declines in adult blood lead levels in New York City compared with the United States, 2004-2014.

OBJECTIVES: To assess changes in lead exposure in the New York City (NYC) adult population over a 10-year period and to contrast changes with national estimates, overall, and by socio-demographics and smoking status. METHODS: We used measurements of blood lead levels (BLLs) from NYC resident adults who participated in the NYC Health and Nutrition Examination Surveys (HANES) in 2004 and 2013-2014. We compared estimates of geometric means (GM), 95th percentiles, and prevalence of BLL ≥ 5 µg/dL overall and by subgroups over time, with adults who participated in the National HANES (NHANES) 2001-2004 and 2011-2014. RESULTS: The GM BLLs among NYC adults declined from 1.79 µg/dL in 2004 to 1.13 µg/dL in 2013-2014 (P < .0001). The declines over this period ranged from 30.1% to 43.2% across socio-demographic groups and smoking status (P < .0001 for all comparisons), and were slightly greater than declines observed nationally. The drop in prevalence of elevated BLLs (≥ 5 µg/dL) was also greater in NYC (4.8-0.5%), compared with NHANES (3.8-2.0%). By 2013-2014, NYC adults with lower annual family income (< $20,000) no longer had higher GM BLLs relative to those with higher incomes (≥ $75,000), a disparity improvement not observed nationally. Likewise, GM BLLs and 95th percentiles for non-Hispanic black adults in NYC were lower than GM BLLs for non-Hispanic white adults. Non-Hispanic Asian adults had the highest GM BLLs compared with other racial/ethnic groups, both in NYC in 2013-14 and nationally in 2011-2014 (1.37 µg/dL, P = .1048 and 1.22 µg/dL, P = .0004, respectively). CONCLUSION: The lessening of disparity in lead exposure across income groups and decreasing exposure at the high end of the distribution among non-Hispanic black and Asian adults in NYC suggest that regulatory and outreach efforts have effectively targeted these higher exposure risk groups. However, Asian adults still had the highest average BLL, suggesting a need for enhanced outreach to this group. Local surveillance remains an important tool to monitor BLLs of local populations and to inform initiatives to reduce exposures in those at highest risk.

Influence of the food environment on obesity risk in a large cohort of US veterans by community type.

OBJECTIVE: The aim of this study was to examine relationships between the food environment and obesity by community type. METHODS: Using electronic health record data from the US Veterans Administration Diabetes Risk (VADR) cohort, we examined associations between the percentage of supermarkets and fast-food restaurants with obesity prevalence from 2008 to 2018. We constructed multivariable logistic regression models with random effects and interaction terms for year and food environment variables. We stratified models by community type. RESULTS: Mean age at baseline was 59.8 (SD = 16.1) years; 93.3% identified as men; and 2,102,542 (41.8%) were classified as having obesity. The association between the percentage of fast-food restaurants and obesity was positive in high-density urban areas (odds ratio [OR] = 1.033; 95% CI: 1.028-1.037), with no interaction by time (p = 0.83). The interaction with year was significant in other community types (p < 0.001), with increasing odds of obesity in each follow-up year. The associations between the percentage of supermarkets and obesity were null in high-density and low-density urban areas and positive in suburban (OR = 1.033; 95% CI: 1.027-1.039) and rural (OR = 1.007; 95% CI: 1.002-1.012) areas, with no interactions by time. CONCLUSIONS: Many healthy eating policies have been passed in urban areas; our results suggest such policies might also mitigate obesity risk in nonurban areas.

Decline in use of high-risk agents for tight glucose control among older adults with diabetes in New York City: 2017-2022.

BACKGROUND: This study aimed to examine the prevalence of inappropriate tight glycemic control in older adults with type 2 diabetes and other chronic conditions in New York City, and to identify factors associated with this practice. METHODS: We conducted a retrospective cohort study using the INSIGHT Clinical Research Network. The study population included 11,728 and 15,196 older adults in New York City (age ≥ 75 years) with a diagnosis of type 2 diabetes, and at least one other chronic medical condition, in 2017 and 2022, respectively. The main outcome of interest was inappropriate tight glycemic control, defined as HbA1c <7.0% (<53 mmol/mol) with prescription of at least one high-risk agent (insulin or insulin secretagogue). RESULTS: The proportion of older adults with inappropriate tight glycemic control decreased by nearly 19% over a five-year period (19.4% in 2017 to 15.8% in 2022). There was a significant decrease in insulin (27.8% in 2017; 24.3% in 2022) and sulfonylurea (29.4% in 2017; 21.7% in 2022) medication prescription, and increase in use of GLP-1 agonists (1.8% in 2017; 11.4% in 2022) and SGLT-2 inhibitors (5.8% in 2017; 25.1% in 2022), among the total population. Factors associated with inappropriate tight glycemic control in 2022 included history of heart failure (adjusted odds ratio [aOR] 1.38), chronic kidney disease ([aOR] 1.93), colorectal cancer ([aOR] 1.38), acute myocardial infarction ([aOR] 1.28), "other" ([aOR] 0.72) or "unknown" ([aOR] 0.72) race, and a point increase in BMI ([aOR] 0.98). CONCLUSIONS: We found an encouraging trend toward less use of high-risk medication strategies for older adults with type 2 diabetes and multiple chronic conditions. However, one in six patients in 2022 still had inappropriate tight glycemic control, indicating a need for continued efforts to optimize diabetes management in this population.

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.

Mediation of an association between neighborhood socioeconomic environment and type 2 diabetes through the leisure-time physical activity environment in an analysis of three independent samples.

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

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.

Cardiovascular Disease Risk Factors Among Immigrant and US-Born Adults in New York City.

OBJECTIVES: Immigrant adults tend to have better health than native-born adults despite lower incomes, but the health advantage decreases with length of residence. To determine whether immigrant adults have a health advantage over US-born adults in New York City, we compared cardiovascular disease (CVD) risk factors among both groups. METHODS: Using data from the New York City Health and Nutrition Examination Survey 2013-2014, we assessed health insurance coverage, health behaviors, and health conditions, comparing adults ages ≥20 born in the 50 states or the District of Columbia (US-born) with adults born in a US territory or outside the United States (immigrants, following the National Health and Nutrition Examination Survey) and comparing US-born adults with (1) adults who immigrated recently (≤10 years) and (2) adults who immigrated earlier (>10 years). RESULTS: For immigrant adults, the mean time since arrival in the United States was 21.8 years. Immigrant adults were significantly more likely than US-born adults to lack health insurance (22% vs 12%), report fair or poor health (26% vs 17%), have hypertension (30% vs 23%), and have diabetes (20% vs 11%) but significantly less likely to smoke (18% vs 27%) (all P < .05). Comparable proportions of immigrant adults and US-born adults were overweight or obese (67% vs 63%) and reported CVD (both 7%). Immigrant adults who arrived recently were less likely than immigrant adults who arrived earlier to have diabetes or high cholesterol but did not differ overall from US-born adults. CONCLUSIONS: Our findings may help guide prevention programs and policy efforts to ensure that immigrant adults remain healthy.

Urban and rural differences in new onset type 2 diabetes: Comparisons across national and regional samples in the diabetes LEAD network.

Introduction: Geographic disparities in diabetes burden exist throughout the United States (US), with many risk factors for diabetes clustering at a community or neighborhood level. We hypothesized that the likelihood of new onset type 2 diabetes (T2D) would differ by community type in three large study samples covering the US. Research design and methods: We evaluated the likelihood of new onset T2D by a census tract-level measure of community type, a modification of RUCA designations (higher density urban, lower density urban, suburban/small town, and rural) in three longitudinal US study samples (REGARDS [REasons for Geographic and Racial Differences in Stroke] cohort, VADR [Veterans Affairs Diabetes Risk] cohort, Geisinger electronic health records) representing the CDC Diabetes LEAD (Location, Environmental Attributes, and Disparities) Network. Results: In the REGARDS sample, residing in higher density urban community types was associated with the lowest odds of new onset T2D (OR [95% CI]: 0.80 [0.66, 0.97]) compared to rural community types; in the Geisinger sample, residing in higher density urban community types was associated with the highest odds of new onset T2D (OR [95% CI]: 1.20 [1.06, 1.35]) compared to rural community types. In the VADR sample, suburban/small town community types had the lowest hazard ratios of new onset T2D (HR [95% CI]: 0.99 [0.98, 1.00]). However, in a regional stratified analysis of the VADR sample, the likelihood of new onset T2D was consistent with findings in the REGARDS and Geisinger samples, with highest likelihood of T2D in the rural South and in the higher density urban communities of the Northeast and West regions; likelihood of T2D did not differ by community type in the Midwest. Conclusions: The likelihood of new onset T2D by community type varied by region of the US. In the South, the likelihood of new onset T2D was higher among those residing in rural communities.

Neighborhood Socioeconomic Environment and Risk of Type 2 Diabetes: Associations and Mediation Through Food Environment Pathways in Three Independent Study Samples.

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

Metabolic syndrome among New York City (NYC) adults: change in prevalence from 2004 to 2013-2014 using New York City Health and Nutrition Examination Survey.

PURPOSE: In this study we aim to estimate the change in metabolic syndrome (MetS) prevalence among New York City (NYC) adults between 2004 and 2013-2014 and identify key subgroups at risk. METHODS: We analyzed data from NYC Health and Nutrition Examination Survey. MetS was defined as having at least three of the following: abdominal obesity, low HDL, elevated triglycerides, glucose dysregulation, and elevated blood pressure. We calculated age-standardized MetS prevalence, change in prevalence over time, and prevalence ratios by gender and race/ethnicity groups. We also tested for additive interaction. RESULTS: In 2013-2014 MetS prevalence among NYC adults was 24.4% (95% CI, 21.4-27.6). Adults 65+ years and Asian adults had the highest prevalence (45.6% and 33.8%, respectively). Abdominal obesity was the most prevalent MetS component in 2004 and 2013-2014 (50.7% each time). Between 2004 and 2013-2014, MetS decreased by 18.2% (P = .04) among women. The decrease paralleled similar declines in elevated triglycerides and glucose dysregulation. In 2013-14, non-Latino Black women had higher risk of MetS than non-Latino Black men and non-Latino White adults. CONCLUSION: Age and racial/ethnic disparities in MetS prevalence in NYC were persistent from 2004 to 2013-2014, with Asian adults and non-Latino Black women at particularly high risk.