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Clynes S, Moran A, Cardel M, Foster G, Phelan S. Weight Loss Maintainers Sustain High Diet Quality in Diverse Residential Retail Food Environments. J Acad Nutr Diet 2024; 124:957-963.e3. [PMID: 38556111 DOI: 10.1016/j.jand.2024.03.012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2023] [Revised: 03/09/2024] [Accepted: 03/27/2024] [Indexed: 04/02/2024]
Abstract
BACKGROUND The relationship between the retail food environment and diet quality has received minimal investigation among weight loss maintainers. OBJECTIVE The aim of this study was to investigate the association between the residential retail food environment and diet quality in weight loss maintainers from WeightWatchers in the United States. DESIGN Cross-sectional data were collected between January 2018 and February 2020. The Retail Food Environment Index (RFEI), based on geocoded home addresses, classified the environment as follows: RFEI <1.6 = healthiest; RFEI 1.6 to <2.5 = moderately healthy; RFEI 2.5 to <4.0 = moderately unhealthy; RFEI ≥4.0 = least healthy. Dietary data were obtained using a food frequency questionnaire. PARTICIPANTS/SETTING Adult participants (n = 1,159) who had lost weight using WeightWatchers and maintained ≥9.1-kg weight loss for ≥1 year (mean 24.7-kg loss for 3.4 years). MAIN OUTCOME MEASURES Healthy Eating Index 2015 (HEI-2015) component and total scores (0-100; higher scores indicate better alignment with the 2015-2020 Dietary Guidelines for Americans). STATISTICAL ANALYSES PERFORMED Regression models included RFEI category, the independent variable, and HEI-2015 and component scores (outcomes) controlling for age, sex, race and ethnicity, educational attainment, and household income. RESULTS Compared with individuals living in the healthiest food environments (mean HEI-2015 score = 71.5) those in the unhealthiest environments had a mean HEI-2015 score of 70.1 (95% CI 68.8 to 71.3), those in moderately unhealthy environments had a score of 71.3 (95% CI 70.3 to 73.1) and those in moderately healthy environments had a score of 70.3 (95% CI 68.9 to 71.2), indicating a nonlinear relationship. Compared with those in the healthiest environments, those in the least healthy environments had an approximately 0.47 lower added sugar HEI-2015 component score (95% CI -0.86 to -0.08), indicating approximately 5% higher added sugar intake. CONCLUSIONS Weight loss maintainers maintained high diet quality in diverse retail food environments. Compared with those in the healthiest food environments, those in the least healthy had a higher consumption of added sugars.
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Affiliation(s)
- Sasha Clynes
- Department of Health Policy, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland.
| | - Alyssa Moran
- Department of Health Policy, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
| | - Michelle Cardel
- WeightWatchers, New York, New York; Department of Health Outcomes and Biomedical Informatics, University of Florida College of Medicine, Gainesville, Florida
| | - Gary Foster
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Suzanne Phelan
- Departments of Kinesiology and Public Health and Center for Health Research, California Polytechnic State University, San Luis Obispo, California
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Sersli S, Shareck M. Is alcohol outlet availability associated with binge drinking in Canadian young adults? Findings from British Columbia and Quebec. CANADIAN JOURNAL OF PUBLIC HEALTH = REVUE CANADIENNE DE SANTE PUBLIQUE 2024; 115:567-576. [PMID: 38918359 DOI: 10.17269/s41997-024-00905-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/17/2024] [Accepted: 05/29/2024] [Indexed: 06/27/2024]
Abstract
OBJECTIVES Alcohol availability is associated with alcohol consumption and related harms, but there is less evidence on associations with heavy episodic drinking (HED), a drinking pattern prevalent among young adults. This study aimed to assess the associations between alcohol availability and HED among young Canadians. METHODS We used a population-based sample of Canadian urban-dwelling young adult drinkers (18‒29 years) from the cross-sectional Canadian Community Health Survey (CCHS; cycles 2015‒2019). We linked data from CCHS respondents in British Columbia and Quebec with two measures of alcohol availability for both offsite and onsite outlets: density (AOD) and accessibility (SAI) within dissemination areas (N = 1,067,747). We used logistic regression to estimate the associations between alcohol availability and monthly HED, adjusting for covariates. RESULTS The associations between availability and HED differed by province, and availability measure. In British Columbia, offsite and onsite accessibility using SAI was inversely associated with HED. For example, living in neighbourhoods with medium alcohol accessibility (as compared to low) was significantly associated with reduced odds of HED (offsite OR = 0.33, 95% CI 0.17‒0.64; onsite OR = 0.49, 95% CI 0.27‒0.89). In Quebec, offsite availability was positively associated with HED using SAI (although not statistically significant) while no clear trend was seen for onsite availability. CONCLUSION Results were consistent with previous evidence. Restricting spatial availability of alcohol remains an important public health strategy for decreasing the ease/convenience of access. Understanding why patterns of availability and drinking differ across regions could inform regionally tailored policies.
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Affiliation(s)
- Stephanie Sersli
- Faculté de médecine et des sciences de la santé, Département des sciences de la santé communautaire, Université de Sherbrooke, Sherbrooke, Québec, Canada
- Centre de Recherche du Centre Hospitalier Universitaire de Sherbrooke (CRCHUS), Sherbrooke, Québec, Canada
| | - Martine Shareck
- Faculté de médecine et des sciences de la santé, Département des sciences de la santé communautaire, Université de Sherbrooke, Sherbrooke, Québec, Canada.
- Centre de Recherche du Centre Hospitalier Universitaire de Sherbrooke (CRCHUS), Sherbrooke, Québec, Canada.
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Lang IM, Antonakos CL, Judd SE, Colabianchi N. Intake of Snacks and Sweets in a National Study of Built and Social Environments: the REasons for Geographic And Racial Differences in Stroke Study. J Nutr 2024; 154:2300-2314. [PMID: 38795742 DOI: 10.1016/j.tjnut.2024.05.017] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2023] [Revised: 05/16/2024] [Accepted: 05/20/2024] [Indexed: 05/28/2024] Open
Abstract
BACKGROUND Few national studies across the United States' rural-urban continuum examine neighborhood effects on snacks and sweets intake among adults. OBJECTIVES This study examines associations of urbanicity/rurality-tailored measures of food store availability and neighborhood socioeconomic status (NSES) with the intake of snacks and sweets in a national sample of middle and older age adults. METHODS This cross-sectional study used food frequency questionnaire data collected in the REasons for Geographic And Racial Differences in Stroke study (N = 21,204). What We Eat in America food group categorizations guided outcome classification into 1 main category (total snacks and sweets) and 4 subcategories (savory snacks and crackers; sweet bakery products; candy and desserts; nutrition bars and low-fat snacks and sweets). NSES and food store availability were determined using geographic information systems. Food store availability was characterized as geographic access to primary food stores (e.g., supermarkets, supercenters, and select food retailers) in urbanicity/rurality-tailored neighborhood-based buffers. Multiple linear regression was used to predict each outcome. RESULTS Living in neighborhoods with a high density of primary food stores was associated with 8.6%, 9.5%, and 5.8% lower intake of total snacks and sweets, sweet bakery products, and candy and desserts, respectively. Living in the highest NSES quartile was associated with 11.3%, 5.8%, and 18.9% lower intake of total snacks and sweets, savory snacks and crackers, and sweet bakery products, respectively. Depending on primary food store availability, higher household income was associated with significantly greater intake of nutrition bars and low-fat snacks and sweets. Living in a United States Department of Agriculture-defined food desert was not associated with intake. CONCLUSIONS In a geographically diverse sample of middle and older age United States adults, living in neighborhoods with no primary food stores or neighborhoods of low-SES was associated with higher intake of total snacks and sweets and subgroups of snacks and sweets.
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Affiliation(s)
- Ian-Marshall Lang
- School of Kinesiology, University of Michigan, Ann Arbor, MI, United States
| | - Cathy L Antonakos
- School of Kinesiology, University of Michigan, Ann Arbor, MI, United States
| | - Suzanne E Judd
- Department of Biostatistics, University of Alabama at Birmingham, Birmingham, AL, United States
| | - Natalie Colabianchi
- School of Kinesiology, University of Michigan, Ann Arbor, MI, United States; Institute for Social Research, University of Michigan, Ann Arbor, MI, United States.
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Rummo PE, Kanchi R, Adhikari S, Titus AR, Lee DC, McAlexander T, Thorpe LE, Elbel B. Influence of the food environment on obesity risk in a large cohort of US veterans by community type. Obesity (Silver Spring) 2024; 32:788-797. [PMID: 38298108 DOI: 10.1002/oby.23975] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/24/2023] [Revised: 11/30/2023] [Accepted: 12/01/2023] [Indexed: 02/02/2024]
Abstract
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.
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Affiliation(s)
- Pasquale E Rummo
- Department of Population Health, NYU Grossman School of Medicine, New York, New York, USA
| | - Rania Kanchi
- Department of Population Health, NYU Grossman School of Medicine, New York, New York, USA
| | - Samrachana Adhikari
- Department of Population Health, NYU Grossman School of Medicine, New York, New York, USA
| | - Andrea R Titus
- Department of Population Health, NYU Grossman School of Medicine, New York, New York, USA
| | - David C Lee
- Department of Population Health, NYU Grossman School of Medicine, New York, New York, USA
- Department of Emergency Medicine, NYU Langone Health, New York, New York, USA
| | - Tara McAlexander
- Dornsife School of Public Health, Drexel University, Philadelphia, Pennsylvania, USA
| | - Lorna E Thorpe
- Department of Population Health, NYU Grossman School of Medicine, New York, New York, USA
| | - Brian Elbel
- Department of Population Health, NYU Grossman School of Medicine, New York, New York, USA
- NYU Wagner Graduate School of Public Service, New York, New York, USA
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5
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Algur Y, Rummo PE, McAlexander TP, De Silva SSA, Lovasi GS, Judd SE, Ryan V, Malla G, Koyama AK, Lee DC, Thorpe LE, McClure LA. Assessing the association between food environment and dietary inflammation by community type: a cross-sectional REGARDS study. Int J Health Geogr 2023; 22:24. [PMID: 37730612 PMCID: PMC10510199 DOI: 10.1186/s12942-023-00345-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2023] [Accepted: 09/06/2023] [Indexed: 09/22/2023] Open
Abstract
BACKGROUND Communities in the United States (US) exist on a continuum of urbanicity, which may inform how individuals interact with their food environment, and thus modify the relationship between food access and dietary behaviors. OBJECTIVE This cross-sectional study aims to examine the modifying effect of community type in the association between the relative availability of food outlets and dietary inflammation across the US. METHODS Using baseline data from the REasons for Geographic and Racial Differences in Stroke study (2003-2007), we calculated participants' dietary inflammation score (DIS). Higher DIS indicates greater pro-inflammatory exposure. We defined our exposures as the relative availability of supermarkets and fast-food restaurants (percentage of food outlet type out of all food stores or restaurants, respectively) using street-network buffers around the population-weighted centroid of each participant's census tract. We used 1-, 2-, 6-, and 10-mile (~ 2-, 3-, 10-, and 16 km) buffer sizes for higher density urban, lower density urban, suburban/small town, and rural community types, respectively. Using generalized estimating equations, we estimated the association between relative food outlet availability and DIS, controlling for individual and neighborhood socio-demographics and total food outlets. The percentage of supermarkets and fast-food restaurants were modeled together. RESULTS Participants (n = 20,322) were distributed across all community types: higher density urban (16.7%), lower density urban (39.8%), suburban/small town (19.3%), and rural (24.2%). Across all community types, mean DIS was - 0.004 (SD = 2.5; min = - 14.2, max = 9.9). DIS was associated with relative availability of fast-food restaurants, but not supermarkets. Association between fast-food restaurants and DIS varied by community type (P for interaction = 0.02). Increases in the relative availability of fast-food restaurants were associated with higher DIS in suburban/small towns and lower density urban areas (p-values < 0.01); no significant associations were present in higher density urban or rural areas. CONCLUSIONS The relative availability of fast-food restaurants was associated with higher DIS among participants residing in suburban/small town and lower density urban community types, suggesting that these communities might benefit most from interventions and policies that either promote restaurant diversity or expand healthier food options.
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Affiliation(s)
- Yasemin Algur
- Department of Epidemiology and Biostatistics, Drexel University Dornsife School of Public Health, Nesbitt Hall, 3215 Market Street, Philadelphia, PA, 19104, USA.
| | - Pasquale E Rummo
- Department of Population Health, New York University Grossman School of Medicine, New York, NY, USA
| | - Tara P McAlexander
- Department of Epidemiology and Biostatistics, Drexel University Dornsife School of Public Health, Nesbitt Hall, 3215 Market Street, Philadelphia, PA, 19104, USA
| | - S Shanika A De Silva
- Department of Epidemiology and Biostatistics, Drexel University Dornsife School of Public Health, Nesbitt Hall, 3215 Market Street, Philadelphia, PA, 19104, USA
| | - Gina S Lovasi
- Department of Epidemiology and Biostatistics, Drexel University Dornsife School of Public Health, Nesbitt Hall, 3215 Market Street, Philadelphia, PA, 19104, USA
| | - Suzanne E Judd
- Department of Biostatistics, The University of Alabama at Birmingham School of Public Health, Birmingham, AL, USA
| | - Victoria Ryan
- Department of Epidemiology and Biostatistics, Drexel University Dornsife School of Public Health, Nesbitt Hall, 3215 Market Street, Philadelphia, PA, 19104, USA
| | - Gargya Malla
- Department of Epidemiology, The University of Alabama at Birmingham School of Public Health, Birmingham, AL, USA
| | - Alain K Koyama
- Division of Diabetes Translation, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - David C Lee
- Department of Population Health, New York University Grossman School of Medicine, New York, NY, USA
- Department of Emergency Medicine, New York University Grossman School of Medicine, New York, NY, USA
| | - Lorna E Thorpe
- Department of Population Health, New York University Grossman School of Medicine, New York, NY, USA
| | - Leslie A McClure
- Department of Epidemiology and Biostatistics, Drexel University Dornsife School of Public Health, Nesbitt Hall, 3215 Market Street, Philadelphia, PA, 19104, USA
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Tewahade S, Berrigan D, Slotman B, Stinchcomb DG, Sayer RD, Catenacci VA, Ostendorf DM. Impact of the built, social, and food environment on long-term weight loss within a behavioral weight loss intervention. Obes Sci Pract 2023; 9:261-273. [PMID: 37287525 PMCID: PMC10242259 DOI: 10.1002/osp4.645] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2022] [Revised: 10/04/2022] [Accepted: 10/10/2022] [Indexed: 11/10/2022] Open
Abstract
Background Behavioral weight loss interventions can lead to an average weight loss of 5%-10% of initial body weight, however there is wide individual variability in treatment response. Although built, social, and community food environments can have potential direct and indirect influences on body weight (through their influence on physical activity and energy intake), these environmental factors are rarely considered as predictors of variation in weight loss. Objective Evaluate the association between built, social, and community food environments and changes in weight, moderate-to-vigorous physical activity (MVPA), and dietary intake among adults who completed an 18-month behavioral weight loss intervention. Methods Participants included 93 adults (mean ± SD; 41.5 ± 8.3 years, 34.4 ± 4.2 kg/m2, 82% female, 75% white). Environmental variables included urbanicity, walkability, crime, Neighborhood Deprivation Index (includes 13 social economic status factors), and density of convenience stores, grocery stores, and limited-service restaurants at the tract level. Linear regressions examined associations between environment and changes in body weight, waist circumference (WC), MVPA (SenseWear device), and dietary intake (3-day diet records) from baseline to 18 months. Results Grocery store density was inversely associated with change in weight (β = -0.95; p = 0.02; R 2 = 0.062) and WC (β = -1.23; p < 0.01; R 2 = 0.109). Participants living in tracts with lower walkability demonstrated lower baseline MVPA and greater increases in MVPA versus participants with higher walkability (interaction p = 0.03). Participants living in tracts with the most deprivation demonstrated greater increases in average daily steps (β = 2048.27; p = 0.02; R 2 = 0.039) versus participants with the least deprivation. Limited-service restaurant density was associated with change in % protein intake (β = 0.39; p = 0.046; R 2 = 0.051). Conclusion Environmental factors accounted for some of the variability (<11%) in response to a behavioral weight loss intervention. Grocery store density was positively associated with weight loss at 18 months. Additional studies and/or pooled analyses, encompassing greater environmental variation, are required to further evaluate whether environment contributes to weight loss variability.
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Affiliation(s)
- Selam Tewahade
- Department of EpidemiologyColorado School of Public HealthUniversity of Colorado Anschutz Medical CampusAuroraColoradoUSA
| | - David Berrigan
- Division of Cancer Control and Population SciencesNational Cancer InstituteBethesdaMarylandUSA
| | | | | | - R. Drew Sayer
- Department of Nutrition SciencesUniversity of Alabama at BirminghamBirminghamAlabamaUSA
| | - Victoria A. Catenacci
- Division of Endocrinology, Metabolism, and DiabetesDepartment of MedicineUniversity of Colorado Anschutz Medical CampusAuroraColoradoUSA
- Anschutz Health and Wellness CenterDepartment of MedicineUniversity of Colorado Anschutz Medical CampusAuroraColoradoUSA
| | - Danielle M. Ostendorf
- Division of Endocrinology, Metabolism, and DiabetesDepartment of MedicineUniversity of Colorado Anschutz Medical CampusAuroraColoradoUSA
- Anschutz Health and Wellness CenterDepartment of MedicineUniversity of Colorado Anschutz Medical CampusAuroraColoradoUSA
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Son H, Zhang D, Shen Y, Jaysing A, Zhang J, Chen Z, Mu L, Liu J, Rajbhandari‐Thapa J, Li Y, Pagán JA. Social Determinants of Cardiovascular Health: A Longitudinal Analysis of Cardiovascular Disease Mortality in US Counties From 2009 to 2018. J Am Heart Assoc 2023; 12:e026940. [PMID: 36625296 PMCID: PMC9939060 DOI: 10.1161/jaha.122.026940] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/11/2023]
Abstract
Background Disparities in cardiovascular disease (CVD) outcomes persist across the United States. Social determinants of health play an important role in driving these disparities. The current study aims to identify the most important social determinants associated with CVD mortality over time in US counties. Methods and Results The authors used the Agency for Healthcare Research and Quality's database on social determinants of health and linked it with CVD mortality data at the county level from 2009 to 2018. The age-standardized CVD mortality rate was measured as the number of deaths per 100 000 people. Penalized generalized estimating equations were used to select social determinants associated with county-level CVD mortality. The analytic sample included 3142 counties. The penalized generalized estimating equation identified 17 key social determinants of health including rural-urban status, county's racial composition, income, food, and housing status. Over the 10-year period, CVD mortality declined at an annual rate of 1.08 (95% CI, 0.74-1.42) deaths per 100 000 people. Rural counties and counties with a higher percentage of Black residents had a consistently higher CVD mortality rate than urban counties and counties with a lower percentage of Black residents. The rural-urban CVD mortality gap did not change significantly over the past decade, whereas the association between the percentage of Black residents and CVD mortality showed a significant diminishing trend over time. Conclusions County-level CVD mortality declined from 2009 through 2018. However, rural counties and counties with a higher percentage of Black residents continued to experience higher CVD mortality. Median income, food, and housing status consistently predicted higher CVD mortality.
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Affiliation(s)
- Heejung Son
- Department of Epidemiology & Biostatistics, College of Public HealthUniversity of GeorgiaAthensGA
| | - Donglan Zhang
- Division of Health Services Research, Department of Foundations of MedicineNew York University Long Island School of MedicineMineolaNY
| | - Ye Shen
- Department of Epidemiology & Biostatistics, College of Public HealthUniversity of GeorgiaAthensGA
| | - Anna Jaysing
- Division of Health Services Research, Department of Foundations of MedicineNew York University Long Island School of MedicineMineolaNY
| | - Jielu Zhang
- Department of GeographyUniversity of GeorgiaAthensGA
| | - Zhuo Chen
- Department of Health Policy and Management, College of Public HealthUniversity of GeorgiaAthensGA
| | - Lan Mu
- Department of GeographyUniversity of GeorgiaAthensGA
| | - Junxiu Liu
- Department of Population Health Science and PolicyIcahn School of Medicine at Mount SinaiNew YorkNY
| | - Janani Rajbhandari‐Thapa
- Department of Health Policy and Management, College of Public HealthUniversity of GeorgiaAthensGA
| | - Yan Li
- Department of Population Health Science and PolicyIcahn School of Medicine at Mount SinaiNew YorkNY
- School of Public HealthShanghai Jiao Tong University School of MedicineShanghaiChina
| | - José A. Pagán
- Department of Public Health Policy and Management, School of Global Public HealthNew York UniversityNew YorkNY
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India-Aldana S, Kanchi R, Adhikari S, Lopez P, Schwartz MD, Elbel BD, Rummo PE, Meeker MA, Lovasi GS, Siegel KR, Chen Y, Thorpe LE. Impact of land use and food environment on risk of type 2 diabetes: A national study of veterans, 2008-2018. ENVIRONMENTAL RESEARCH 2022; 212:113146. [PMID: 35337829 PMCID: PMC10424702 DOI: 10.1016/j.envres.2022.113146] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/07/2022] [Revised: 02/20/2022] [Accepted: 03/17/2022] [Indexed: 06/14/2023]
Abstract
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.
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Affiliation(s)
- Sandra India-Aldana
- Division of Epidemiology, Department of Population Health, NYU Grossman School of Medicine, 180 Madison Avenue, 5th Fl., New York, NY, 10016, USA
| | - Rania Kanchi
- Division of Epidemiology, Department of Population Health, NYU Grossman School of Medicine, 180 Madison Avenue, 5th Fl., New York, NY, 10016, USA
| | - Samrachana Adhikari
- Division of Biostatistics, Department of Population Health, NYU Grossman School of Medicine, 180 Madison Avenue, 5th Fl., New York, NY, 10016, USA
| | - Priscilla Lopez
- Division of Epidemiology, Department of Population Health, NYU Grossman School of Medicine, 180 Madison Avenue, 5th Fl., New York, NY, 10016, USA
| | - Mark D Schwartz
- Division of Comparative Effectiveness and Decision Science, Department of Population Health, NYU Grossman School of Medicine, 180 Madison Avenue, 9th Fl., New York, NY, 10016, USA; VA New York Harbor Healthcare System, 423 E 23rd, New York, NY, 10010, USA
| | - Brian D Elbel
- Division of Health and Behavior, Section on Health Choice, Policy and Evaluation, Department of Population Health, NYU Grossman School of Medicine, 180 Madison Avenue, 3rd Fl., New York, NY, 10016, USA; NYU Wagner Graduate School of Public Service, 295 Lafayette Street, New York, NY, 10012, USA
| | - Pasquale E Rummo
- Division of Epidemiology, Department of Population Health, NYU Grossman School of Medicine, 180 Madison Avenue, 5th Fl., New York, NY, 10016, USA
| | - Melissa A Meeker
- Drexel University Dornsife School of Public Health, 3215 Market St, Philadelphia, PA 19104, USA
| | - Gina S Lovasi
- Drexel University Dornsife School of Public Health, 3215 Market St, Philadelphia, PA 19104, USA
| | - Karen R Siegel
- Division of Diabetes Translation, Centers for Disease Control and Prevention, Atlanta, GA, 30341, USA
| | - Yu Chen
- Division of Epidemiology, Department of Population Health, NYU Grossman School of Medicine, 180 Madison Avenue, 5th Fl., New York, NY, 10016, USA; Department of Environmental Medicine, NYU Grossman School of Medicine, New York, NY, USA
| | - Lorna E Thorpe
- Division of Epidemiology, Department of Population Health, NYU Grossman School of Medicine, 180 Madison Avenue, 5th Fl., New York, NY, 10016, USA.
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9
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Thorpe LE, Adhikari S, Lopez P, Kanchi R, McClure LA, Hirsch AG, Howell CR, Zhu A, Alemi F, Rummo P, Ogburn EL, Algur Y, Nordberg CM, Poulsen MN, Long L, Carson AP, DeSilva SA, Meeker M, Schwartz BS, Lee DC, Siegel KR, Imperatore G, Elbel B. Neighborhood Socioeconomic Environment and Risk of Type 2 Diabetes: Associations and Mediation Through Food Environment Pathways in Three Independent Study Samples. Diabetes Care 2022; 45:798-810. [PMID: 35104336 PMCID: PMC9016733 DOI: 10.2337/dc21-1693] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/12/2021] [Accepted: 01/05/2022] [Indexed: 02/03/2023]
Abstract
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.
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Affiliation(s)
- Lorna E. Thorpe
- Department of Population Health, New York University Grossman School of Medicine, New York, NY
| | - Samrachana Adhikari
- Department of Population Health, New York University Grossman School of Medicine, New York, NY
| | - Priscilla Lopez
- Department of Population Health, New York University Grossman School of Medicine, New York, NY
| | - Rania Kanchi
- Department of Population Health, New York University Grossman School of Medicine, New York, NY
| | - Leslie A. McClure
- Department of Epidemiology and Biostatistics, Drexel University Dornsife School of Public Health, Philadelphia, PA
| | | | - Carrie R. Howell
- Division of Preventive Medicine, University of Alabama at Birmingham School of Medicine, Birmingham, AL
| | - Aowen Zhu
- Department of Epidemiology, University of Alabama at Birmingham School of Public Health, Birmingham, AL
| | - Farrokh Alemi
- Department of Health Administration and Policy, George Mason University, Fairfax, VA
| | - Pasquale Rummo
- Department of Population Health, New York University Grossman School of Medicine, New York, NY
| | - Elizabeth L. Ogburn
- Department of Biostatistics, Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD
| | - Yasemin Algur
- Department of Epidemiology and Biostatistics, Drexel University Dornsife School of Public Health, Philadelphia, PA
| | - Cara M. Nordberg
- Department of Population Health Sciences, Geisinger, Danville, PA
| | | | - Leann Long
- Department of Biostatistics, University of Alabama at Birmingham School of Public Health, Birmingham, AL
| | - April P. Carson
- Department of Epidemiology, University of Alabama at Birmingham School of Public Health, Birmingham, AL
| | - Shanika A. DeSilva
- Department of Epidemiology and Biostatistics, Drexel University Dornsife School of Public Health, Philadelphia, PA
| | - Melissa Meeker
- Department of Epidemiology and Biostatistics, Drexel University Dornsife School of Public Health, Philadelphia, PA
| | - Brian S. Schwartz
- Department of Population Health Sciences, Geisinger, Danville, PA
- Department of Environmental Health and Engineering, Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD
| | - David C. Lee
- Department of Population Health, New York University Grossman School of Medicine, New York, NY
- Department of Emergency Medicine, New York University Grossman School of Medicine, New York, NY
| | - Karen R. Siegel
- Division of Diabetes Translation, National Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control and Prevention, Atlanta, GA
| | - Giuseppina Imperatore
- Division of Diabetes Translation, National Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control and Prevention, Atlanta, GA
| | - Brian Elbel
- Department of Population Health, New York University Grossman School of Medicine, New York, NY
- New York University Wagner Graduate School of Public Service, New York, NY
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Kanchi R, Lopez P, Rummo PE, Lee DC, Adhikari S, Schwartz MD, Avramovic S, Siegel KR, Rolka DB, Imperatore G, Elbel B, Thorpe LE. Longitudinal Analysis of Neighborhood Food Environment and Diabetes Risk in the Veterans Administration Diabetes Risk Cohort. JAMA Netw Open 2021; 4:e2130789. [PMID: 34714343 PMCID: PMC8556617 DOI: 10.1001/jamanetworkopen.2021.30789] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/04/2021] [Accepted: 08/20/2021] [Indexed: 11/25/2022] Open
Abstract
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.
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Affiliation(s)
- Rania Kanchi
- Department of Population Health, NYU Langone Health, New York, New York
| | - Priscilla Lopez
- Department of Population Health, NYU Langone Health, New York, New York
| | - Pasquale E. Rummo
- Department of Population Health, NYU Langone Health, New York, New York
| | - David C. Lee
- Department of Population Health, NYU Langone Health, New York, New York
- Department of Emergency Medicine, NYU Langone Health, New York, New York
| | | | - Mark D. Schwartz
- Department of Population Health, NYU Langone Health, New York, New York
- VA New York Harbor Healthcare System, New York, New York
| | - Sanja Avramovic
- Department of Health Administration and Policy, George Mason University, Fairfax, Virginia
| | - Karen R. Siegel
- Division of Diabetes Translation, Centers for Disease Control and Prevention, Atlanta, Georgia
| | - Deborah B. Rolka
- Division of Diabetes Translation, Centers for Disease Control and Prevention, Atlanta, Georgia
| | - Giuseppina Imperatore
- Division of Diabetes Translation, Centers for Disease Control and Prevention, Atlanta, Georgia
| | - Brian Elbel
- Department of Population Health, NYU Langone Health, New York, New York
- NYU Wagner Graduate School of Public Service, New York, New York
| | - Lorna E. Thorpe
- Department of Population Health, NYU Langone Health, New York, New York
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