Trends in health behaviors of US adults with and without Diabetes: 2007-2018.

AIMS: Understanding health behaviors of people with diabetes can inform strategies to reduce diabetes-related burdens. METHODS: We used serial cross-sectional National Health and Nutrition Examination Surveys over 2007-2018 to characterize self-reported health behaviors among non-pregnant adults, with and without self-reported diabetes. We estimated weighted proportions meeting recommended health behaviors overall and by sociodemographic and glycemic levels. RESULTS: During 2007-2010, proportions of adults with diabetes meeting recommendations were: 61.9 % for added sugar consumption (<10 % of total calories), 17.2 % for physical activity, 68.2 % for weight management, 14.4 % avoided alcohol, 57.5 % avoided tobacco, 34.1 % got adequate sleep, and 97.5 % saw a healthcare provider (compared with 19.2 %, 33.6 %, 68.8 %, 8.5 %, 44.2 %, 33.0 %, and 82.6 % respectively, among those without diabetes). During 2015-2018, adjusted analyses showed more adults with diabetes met sleep (+16.7 percentage-points[pp]; 95 % CI: 10.6,22.8) and physical activity goals (+8.3 pp; 95 % CI: 3.8,12.8), and fewer met added sugar recommendations (-8.8 pp; 95 % CI -14.7, -2.9). Meeting added sugar, physical activity, and weight management varied by age, education, and glycemic level, but not race and ethnicity. CONCLUSIONS: During 2007-2018, there was some improvement in health behaviors. Improving self-management may require targeted interventions for different segments, like age groups or glycemic levels, among those with diabetes.

A Strategic Research Framework for Defeating Diabetes in India: A 21st-Century Agenda.

Indian people are at high risk for type 2 diabetes (T2DM) even at younger ages and lower body weights. Already 74 million people in India have the disease, and the proportion of those with T2DM is increasing across all strata of society. Unique aspects, related to lower insulin secretion or function, and higher hepatic fat deposition, accompanied by the rise in overweight (related to lifestyle changes) may all be responsible for this unrelenting epidemic of T2DM. Yet, research to understand the causes, pathophysiology, phenotypes, prevention, treatment, and healthcare delivery of T2DM in India seriously lags behind. There are major opportunities for scientific discovery and technological innovation, which if tapped can generate solutions for T2DM relevant to the country's context and make leading contributions to global science. We analyze the situation of T2DM in India, and present a four-pillar (etiology, precision medicine, implementation research, and health policy) strategic research framework to tackle the challenge. We offer key research questions for each pillar, and identify infrastructure needs. India offers a fertile environment for shifting the paradigm from imprecise late-stage diabetes treatment toward early-stage precision prevention and care. Investing in and leveraging academic and technological infrastructures, across the disciplines of science, engineering, and medicine, can accelerate progress toward a diabetes-free nation.

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

INTRODUCTION: A healthy diet is recommended to support diabetes management, including HbA1c, blood pressure, and cholesterol (ABC) control, but food insecurity is a barrier to consuming a healthy diet. We determined the prevalence of food insecurity and diet quality among US adults with diabetes and the associations with ABC management. RESEARCH DESIGN AND METHODS: Cross-sectional analyses were conducted among 2075 adults ≥20 years with diagnosed diabetes who participated in the 2013-2018 National Health and Nutrition Examination Surveys. Food insecurity was assessed using a standard questionnaire and diet quality was assessed using quartiles of the 2015 Healthy Eating Index. Adjusted ORs (aOR, 95% CI) were calculated from logistic regression models to determine the association between household food insecurity/diet quality and the ABCs while controlling for sociodemographic characteristics, healthcare utilization, smoking, medication for diabetes, blood pressure, or cholesterol, and body mass index. RESULTS: Overall, 17.6% of adults had food insecurity/low diet quality; 14.2% had food insecurity/high diet quality; 33.1% had food security/low diet quality; and 35.2% had food security/high diet quality. Compared with adults with food security/high diet quality, those with food insecurity/low diet quality were significantly more likely to have HbA1c ≥7.0% (aOR=1.85, 95% CI 1.23 to 2.80) and HbA1c ≥8.0% (aOR=1.79, 95% CI 1.04 to 3.08); food insecurity/high diet quality was significantly associated with elevated HbA1c; and food security/low diet quality with elevated A1c. CONCLUSIONS: Food insecurity, regardless of diet quality, was significantly associated with elevated A1c. For people with food insecurity, providing resources to reduce food insecurity could strengthen the overall approach to optimal diabetes management.

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.

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.

Evaluating Natural Experiments that Impact the Diabetes Epidemic: an Introduction to the NEXT-D3 Network.

PURPOSE OF REVIEW: Diabetes is an ongoing public health issue in the USA, and, despite progress, recent reports suggest acute and chronic diabetes complications are increasing. RECENT FINDINGS: The Natural Experiments for Translation in Diabetes 3.0 (NEXT-D3) Network is a 5-year research collaboration involving six academic centers (Harvard University, Northwestern University, Oregon Health & Science University, Tulane University, University of California Los Angeles, and University of California San Francisco) and two funding agencies (Centers for Disease Control and Prevention and National Institutes of Health) to address the gaps leading to persisting diabetes burdens. The network builds on previously funded networks, expanding to include type 2 diabetes (T2D) prevention and an emphasis on health equity. NEXT-D3 researchers use rigorous natural experiment study designs to evaluate impacts of naturally occurring programs and policies, with a focus on diabetes-related outcomes. NEXT-D3 projects address whether and to what extent federal or state legislative policies and health plan innovations affect T2D risk and diabetes treatment and outcomes in the USA; real-world effects of increased access to health insurance under the Affordable Care Act; and the effectiveness of interventions that reduce barriers to medication access (e.g., decreased or eliminated cost sharing for cardiometabolic medications and new medications such as SGLT-2 inhibitors for Medicaid patients). Overarching goals include (1) expanding generalizable knowledge about policies and programs to manage or prevent T2D and educate decision-makers and organizations and (2) generating evidence to guide the development of health equity goals to reduce disparities in T2D-related risk factors, treatment, and complications.

Use and Impact of Type 2 Diabetes Prevention Interventions.

INTRODUCTION: RCTs have found that type 2 diabetes can be prevented among high-risk individuals by metformin medication and evidence-based lifestyle change programs. The purpose of this study is to estimate the use of interventions to prevent type 2 diabetes in real-world clinical practice settings and determine the impact on diabetes-related clinical outcomes. METHODS: The analysis performed in 2020 used 2010‒2018 electronic health record data from 69,434 patients aged ≥18 years at high risk for type 2 diabetes in 2 health systems. The use and impact of prescribed metformin, lifestyle change program, bariatric surgery, and combinations of the 3 were examined. A subanalysis was performed to examine uptake and retention among patients referred to the National Diabetes Prevention Program. RESULTS: Mean HbA1c values declined from before to after intervention for patients who were prescribed metformin (-0.067%; p<0.001) or had bariatric surgery (-0.318%; p<0.001). Among patients referred to the National Diabetes Prevention Program lifestyle change program, the type 2 diabetes postintervention incidence proportion was 14.0% for nonattendees, 12.8% for some attendance, and 7.5% for those who attended ≥4 sessions (p<0.001). Among referred patients to the National Diabetes Prevention Program lifestyle change program, uptake was low (13% for 1‒3 sessions, 15% for ≥4 sessions), especially among males and Hispanic patients. CONCLUSIONS: Findings suggest that metformin and bariatric surgery may improve HbA1c levels and that participation in the National Diabetes Prevention Program may reduce type 2 diabetes incidence. Efforts to increase the use of these interventions may have positive impacts on diabetes-related health outcomes.

Categorizing community type for epidemiologic evaluation of community factors and chronic disease across the United States.

Existing classifications of community type do not differentiate urban cores from surrounding non-rural areas, an important distinction for analyses of community features and their impact on health. Inappropriately classified community types can introduce serious methodologic flaws in epidemiologic studies and invalid inferences from findings. To address this, we evaluate a modification of the United States Department of Agriculture's Rural Urban Commuting Area codes at the census tract, propose a four-level categorization of community type, and compare this with existing classifications for epidemiologic analyses. Compared to existing classifications, our method resulted in clearer geographic delineations of community types within urban areas.

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.

Is dietary intake of advanced glycation end products associated with mortality among adults with diabetes?

BACKGROUND AND AIMS: Prior studies suggest a positive association between dietary AGEs and adverse health outcomes but have not well-characterized AGEs intake and its association with mortality in a general adult population in the United States. METHODS AND RESULTS: We included 5474 adults with diabetes from the 2003 to 2018 National Health and Nutrition Examination Survey, a nationally representative sample of the non-institutionalized civilian population in the United States. Concordance to dietary guidelines (Healthy Eating Index 2015 [HEI-2015]) and intake of the AGE Nϵ-(carboxymethyl)lysine (CML) were estimated using an existing database and two 24-h food recalls. Multivariable Cox regression evaluated the association between AGEs intake and all-cause mortality. A secondary analysis measured CML, Nϵ-(1-carboxyethyl)lysine (CEL), and Nδ-(5-hydro-5-methyl-4-imidazolon-2-yl)-ornithine (MGH1) from an alternative database. Higher AGEs intake was associated with lower concordance to dietary guidelines (Means and standard errors of HEI-2015 score, by quartiles of AGEs intake: Q1 = 55.2 ± 0.6, Q2 = 54.1 ± 0.5, Q3 = 52.1 ± 0.5, Q4 = 49.0 ± 0.5; p < 0.001). There were 743 deaths among 3884 adults in the mortality analysis (mean follow-up = 3.8 years). AGEs intake was not significantly associated with all-cause mortality (Q2 vs. Q1: Hazard Ratio [HR] = 0.91 [0.69-1.21], Q3 vs. Q1: HR = 0.90 [0.63-1.27], Q4 vs. Q1: HR = 1.16 [0.84-1.60]). Results were similar in secondary analyses. CONCLUSION: While dietary AGEs intake was associated with concordance to dietary guidelines, it was not significantly associated with all-cause mortality among adults with diabetes. Further research may consider other health outcomes as well as the evaluating specific contribution of dietary AGEs to overall AGEs burden.

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.

Health Care Access and Use Among Adults with Diabetes During the COVID-19 Pandemic - United States, February-March 2021.

Diabetes affects approximately one in 10 persons in the United States† and is a risk factor for severe COVID-19 (1), especially when a patient's diabetes is not well managed (2). The extent to which the COVID-19 pandemic has affected diabetes care and management, and whether this varies across age groups, is currently unknown. To evaluate access to and use of health care, as well as experiences, attitudes, and behaviors about COVID-19 prevention and vaccination, a nonprobability, Internet-based survey was administered to 5,261 U.S. adults aged ≥18 years during February-March 2021. Among respondents, 760 (14%) adults who reported having diabetes currently managed with medication were included in the analysis. Younger adults (aged 18-29 years) with diabetes were more likely to report having missed medical care during the past 3 months (87%; 79) than were those aged 30-59 years (63%; 372) or ≥60 years (26%; 309) (p<0.001). Overall, 44% of younger adults reported difficulty accessing diabetes medications. Younger adults with diabetes also reported lower intention to receive COVID-19 vaccination (66%) compared with adults aged ≥60 years§ (85%; p = 0.001). During the COVID-19 pandemic, efforts to enhance access to diabetes care for adults with diabetes and deliver public health messages emphasizing the importance of diabetes management and COVID-19 prevention, including vaccination, are warranted, especially in younger adults.

Longitudinal Analysis of Neighborhood Food Environment and Diabetes Risk in the Veterans Administration Diabetes Risk Cohort.

Importance: Diabetes causes substantial morbidity and mortality among adults in the US, yet its incidence varies across the country, suggesting that neighborhood factors are associated with geographical disparities in diabetes. Objective: To examine the association between neighborhood food environment and risk of incident type 2 diabetes across different community types (high-density urban, low-density urban, suburban, and rural). Design, Setting, and Participants: This is a national cohort study of 4 100 650 US veterans without type 2 diabetes. Participants entered the cohort between 2008 and 2016 and were followed up through 2018. The median (IQR) duration of follow-up was 5.5 (2.6-9.8) person-years. Data were obtained from Veterans Affairs electronic health records. Incident type 2 diabetes was defined as 2 encounters with type 2 diabetes International Classification of Diseases, Ninth Revision or Tenth Revision codes, a prescription for diabetes medication other than metformin or acarbose alone, or 1 encounter with type 2 diabetes International Classification of Diseases Ninth Revision or Tenth Revision codes and 2 instances of elevated hemoglobin A1c (≥6.5%). Data analysis was performed from October 2020 to March 2021. Exposures: Five-year mean counts of fast-food restaurants and supermarkets relative to other food outlets at baseline were used to generate neighborhood food environment measures. The association between food environment and time to incident diabetes was examined using piecewise exponential models with 2-year interval of person-time and county-level random effects stratifying by community types. Results: The mean (SD) age of cohort participants was 59.4 (17.2) years. Most of the participants were non-Hispanic White (2 783 756 participants [76.3%]) and male (3 779 555 participants [92.2%]). The relative density of fast-food restaurants was positively associated with a modestly increased risk of type 2 diabetes in all community types. The adjusted hazard ratio (aHR) was 1.01 (95% CI, 1.00-1.02) in high-density urban communities, 1.01 (95% CI, 1.01-1.01) in low-density urban communities, 1.02 (95% CI, 1.01-1.03) in suburban communities, and 1.01 (95% CI, 1.01-1.02) in rural communities. The relative density of supermarkets was associated with lower type 2 diabetes risk only in suburban (aHR, 0.97; 95% CI, 0.96-0.99) and rural (aHR, 0.99; 95% CI, 0.98-0.99) communities. Conclusions and Relevance: These findings suggest that neighborhood food environment measures are associated with type 2 diabetes among US veterans in multiple community types and that food environments are potential avenues for action to address the burden of diabetes. Tailored interventions targeting the availability of supermarkets may be associated with reduced diabetes risk, particularly in suburban and rural communities, whereas restrictions on fast-food restaurants may help in all community types.

Population-Level Approaches to Preventing Type 2 Diabetes Globally.

Type 2 diabetes (T2DM) is increasingly considered an epidemic rooted in modern society as much as in individual behavior. Addressing the T2DM burden thus involves a dual approach, simultaneously addressing high-risk individuals and whole populations. Within this context, this article summarizes the evidence base, in terms of effectiveness and cost-effectiveness, for population-level approaches to prevent T2DM: (1) modifications to the food environment; (2) modifications to the built environment and physical activity; and (3) programs and policies to address social and economic factors. Existing knowledge gaps are also discussed.

Association of community socioeconomic deprivation with evidence of reduced kidney function at time of type 2 diabetes diagnosis.

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

Dietary Factors and Prevention: Risk of End-Stage Kidney Disease by Fruit and Vegetable Consumption.

BACKGROUND: The association between fruit and vegetable (FV) intake and the risk of end-stage kidney disease (ESKD) has not been examined in the general population and fully explored in chronic kidney disease (CKD). We prospectively evaluated this relationship in US representative sample of adults and evaluated consistency by the presence or absence, and severity, of CKD. METHODS: We used data from the Third National Health and Nutrition Examination Survey (1988-1994) linked with the US Renal Data System, including 14,725 adults aged ≥20 years and with follow-up for ESKD through 2008. Daily FV intake was ascertained using a food frequency questionnaire. We examined the association between selected categories of FV intake and ESKD using a Fine Gray competing risk model adjusting for sociodemographics, lifestyle, clinical and nutritional factors, estimated glomerular filtration rate, and albuminuria. We evaluated whether risk varied in individuals with severe versus any CKD. RESULTS: 230 participants (1.5%) developed ESKD during follow-up. In the adjusted model, compared to highest intake, those in lowest categories of FV intake had a higher risk of ESKD, for <2 times/day (1.45 [1.24-1.68], 2 to <3 times/day (1.40 [1.18-1.61]), 3 to <4 times/day (1.25 [1.04-1.46]), and 4 to <6 times/day (1.14 [0.97-1.31]). There was suggestion of heterogeneity (p for interaction = 0.03) with possible stronger inverse association in patients with CKD than those without CKD. After stratification, we obtained similar strong inverse association when we examined ESKD incidence across intake of FVs in participants with CKD stages 1-4 (n = 5,346) and specifically in those with CKD stages 3-4 (n = 1,084). CONCLUSIONS: Low intake of FVs was associated with higher risk of ESKD in US adults with and without CKD, supporting an emerging body of literature on the potential benefits of plant-rich diets for prevention of ESKD.

Association of Greenness with Blood Pressure among Individuals with Type 2 Diabetes across Rural to Urban Community Types in Pennsylvania, USA.

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

Consumption of Foods Derived from Subsidized Crops Remains Associated with Cardiometabolic Risk: An Update on the Evidence Using the National Health and Nutrition Examination Survey 2009-2014.

In this study, we examined the associations between the consumption of foods derived from crops subsidized under the 2008 United States (US) Farm Bill and cardiometabolic risk factors and whether the magnitude of these associations has changed since the 2002 US Farm Bill. Four federal databases were used to estimate daily consumption of the top seven subsidized commodities (corn, soybeans, wheat, rice, sorghum, dairy, and livestock) and to calculate a subsidy score (0-1 scale) for Americans' daily dietary intake during 2009-2014, with a higher score indicative of a higher proportion of the diet derived from subsidized commodities. The cardiometabolic risk factors included obesity, abdominal adiposity, hypertension, dyslipidemia, and dysglycemia. Linear and logistic regression models were adjusted for age, sex, race/ethnicity, the poverty-income ratio, the smoking status, educational attainment, physical activity, and daily calorie intake. During 2009-2014, adults with the highest subsidy score had higher probabilities of obesity, abdominal adiposity, and dysglycemia compared to the lowest subsidy score. After the 2002 Farm Bill (measured using data from 2001-2006), the subsidy score decreased from 56% to 50% and associations between consuming a highly-subsidized diet and dysglycemia did not change (p = 0.54), whereas associations with obesity (p = 0.004) and abdominal adiposity (p = 0.002) significantly attenuated by more than half. The proportion of calories derived from subsidized food commodities continues to be associated with adverse cardiometabolic risk factors, though the relationship with obesity and abdominal adiposity has weakened in recent years.

The Longitudinal Epidemiologic Assessment of Diabetes Risk (LEADR): Unique 1.4 M patient Electronic Health Record cohort.

BACKGROUND: The Longitudinal Epidemiologic Assessment of Diabetes Risk (LEADR) study uses a novel Electronic Health Record (EHR) data approach as a tool to assess the epidemiology of known and new risk factors for type 2 diabetes mellitus (T2DM) and study how prevention interventions affect progression to and onset of T2DM. We created an electronic cohort of 1.4 million patients having had at least 4 encounters with a healthcare organization for at least 24-months; were aged ≥18 years in 2010; and had no diabetes (i.e., T1DM or T2DM) at cohort entry or in the 12 months following entry. EHR data came from patients at nine healthcare organizations across the U.S. between January 1, 2010-December 31, 2016. RESULTS: Approximately 5.9% of the LEADR cohort (82,922 patients) developed T2DM, providing opportunities to explore longitudinal clinical care, medication use, risk factor trajectories, and diagnoses for these patients, compared with patients similarly matched prior to disease onset. CONCLUSIONS: LEADR represents one of the largest EHR databases to have repurposed EHR data to examine patients' T2DM risk. This paper is first in a series demonstrating this novel approach to studying T2DM. IMPLICATIONS: Chronic conditions that often take years to develop can be studied efficiently using EHR data in a retrospective design. LEVEL OF EVIDENCE: While much is already known about T2DM risk, this EHR's cohort's 160 M data points for 1.4 M people over six years, provides opportunities to investigate new unique risk factors and evaluate research hypotheses where results could modify public health practice for preventing T2DM.