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Lozano PM, Bobb JF, Kapos FP, Cruz M, Mooney SJ, Hurvitz PM, Anau J, Theis MK, Cook A, Moudon AV, Arterburn DE, Drewnowski A. Residential Density Is Associated With BMI Trajectories in Children and Adolescents: Findings From the Moving to Health Study. AJPM FOCUS 2024; 3:100225. [PMID: 38682047 PMCID: PMC11046231 DOI: 10.1016/j.focus.2024.100225] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 05/01/2024]
Abstract
Introduction This study investigates the associations between built environment features and 3-year BMI trajectories in children and adolescents. Methods This retrospective cohort study utilized electronic health records of individuals aged 5-18 years living in King County, Washington, from 2005 to 2017. Built environment features such as residential density; counts of supermarkets, fast-food restaurants, and parks; and park area were measured using SmartMaps at 1,600-meter buffers. Linear mixed-effects models performed in 2022 tested whether built environment variables at baseline were associated with BMI change within age cohorts (5, 9, and 13 years), adjusting for sex, age, race/ethnicity, Medicaid, BMI, and residential property values (SES measure). Results At 3-year follow-up, higher residential density was associated with lower BMI increase for girls across all age cohorts and for boys in age cohorts of 5 and 13 years but not for the age cohort of 9 years. Presence of fast food was associated with higher BMI increase for boys in the age cohort of 5 years and for girls in the age cohort of 9 years. There were no significant associations between BMI change and counts of parks, and park area was only significantly associated with BMI change among boys in the age cohort of 5 years. Conclusions Higher residential density was associated with lower BMI increase in children and adolescents. The effect was small but may accumulate over the life course. Built environment factors have limited independent impact on 3-year BMI trajectories in children and adolescents.
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Affiliation(s)
- Paula Maria Lozano
- Kaiser Permanente Washington Health Research Institute, Seattle, Washington
| | - Jennifer F. Bobb
- Kaiser Permanente Washington Health Research Institute, Seattle, Washington
- Department of Biostatistics, School of Public Health, University of Washington, Seattle, Washington
| | - Flavia P. Kapos
- Department of Orthopaedic Surgery and Duke Clinical Research Institute, Duke School of Medicine, Durham, North Carolina
- Center for Child Health, Behavior and Development, Seattle Children's Research Institute, Seattle, Washington
| | - Maricela Cruz
- Kaiser Permanente Washington Health Research Institute, Seattle, Washington
- Department of Biostatistics, School of Public Health, University of Washington, Seattle, Washington
| | - Stephen J. Mooney
- Department of Epidemiology, School of Public Health, University of Washington, Seattle, Washington
- Harborview Injury Prevention & Research Center, University of Washington, Seattle, Washington
| | - Philip M. Hurvitz
- Urban Form Lab, Department of Urban Design and Planning, College of Built Environments, University of Washington, Seattle, Washington
- Center for Studies in Demography & Ecology, University of Washington, Seattle, Washington
| | - Jane Anau
- Kaiser Permanente Washington Health Research Institute, Seattle, Washington
| | - Mary Kay Theis
- Kaiser Permanente Washington Health Research Institute, Seattle, Washington
| | - Andrea Cook
- Kaiser Permanente Washington Health Research Institute, Seattle, Washington
- Department of Biostatistics, School of Public Health, University of Washington, Seattle, Washington
| | - Anne Vernez Moudon
- Urban Form Lab, Department of Urban Design and Planning, College of Built Environments, University of Washington, Seattle, Washington
| | - David E. Arterburn
- Kaiser Permanente Washington Health Research Institute, Seattle, Washington
| | - Adam Drewnowski
- Department of Epidemiology, School of Public Health, University of Washington, Seattle, Washington
- Center for Public Health Nutrition, University of Washington, Seattle, Washington
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Murthy VL, Mosley JD, Perry AS, Jacobs DR, Tanriverdi K, Zhao S, Sawicki KT, Carnethon M, Wilkins JT, Nayor M, Das S, Abel ED, Freedman JE, Clish CB, Shah RV. Metabolic liability for weight gain in early adulthood. Cell Rep Med 2024; 5:101548. [PMID: 38703763 PMCID: PMC11148768 DOI: 10.1016/j.xcrm.2024.101548] [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: 11/16/2022] [Revised: 03/27/2023] [Accepted: 04/10/2024] [Indexed: 05/06/2024]
Abstract
While weight gain is associated with a host of chronic illnesses, efforts in obesity have relied on single "snapshots" of body mass index (BMI) to guide genetic and molecular discovery. Here, we study >2,000 young adults with metabolomics and proteomics to identify a metabolic liability to weight gain in early adulthood. Using longitudinal regression and penalized regression, we identify a metabolic signature for weight liability, associated with a 2.6% (2.0%-3.2%, p = 7.5 × 10-19) gain in BMI over ≈20 years per SD higher score, after comprehensive adjustment. Identified molecules specified mechanisms of weight gain, including hunger and appetite regulation, energy expenditure, gut microbial metabolism, and host interaction with external exposure. Integration of longitudinal and concurrent measures in regression with Mendelian randomization highlights the complexity of metabolic regulation of weight gain, suggesting caution in interpretation of epidemiologic or genetic effect estimates traditionally used in metabolic research.
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Affiliation(s)
- Venkatesh L Murthy
- Division of Cardiovascular Medicine, Department of Medicine, University of Michigan, Ann Arbor, MI, USA.
| | - Jonathan D Mosley
- Vanderbilt Translational and Clinical Cardiovascular Research Center, Vanderbilt University School of Medicine, Nashville, TN, USA
| | - Andrew S Perry
- Vanderbilt Translational and Clinical Cardiovascular Research Center, Vanderbilt University School of Medicine, Nashville, TN, USA
| | - David R Jacobs
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN, USA
| | - Kahraman Tanriverdi
- Vanderbilt Translational and Clinical Cardiovascular Research Center, Vanderbilt University School of Medicine, Nashville, TN, USA
| | - Shilin Zhao
- Vanderbilt Translational and Clinical Cardiovascular Research Center, Vanderbilt University School of Medicine, Nashville, TN, USA
| | | | | | | | - Matthew Nayor
- Section of Cardiovascular Medicine, Department of Medicine, Boston University School of Medicine, Boston, MA, USA
| | - Saumya Das
- Cardiology Division, Massachusetts General Hospital, Boston, MA, USA
| | - E Dale Abel
- Department of Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Jane E Freedman
- Vanderbilt Translational and Clinical Cardiovascular Research Center, Vanderbilt University School of Medicine, Nashville, TN, USA
| | - Clary B Clish
- Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | - Ravi V Shah
- Vanderbilt Translational and Clinical Cardiovascular Research Center, Vanderbilt University School of Medicine, Nashville, TN, USA.
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Ávila Arcos MA, Shamah Levy T, Del Monte Vega MY, Chávez Villasana A, Ávila Curiel A. Convenience stores: an obesogenic promoter in a metropolitan area of northern Mexico? Front Nutr 2024; 11:1331990. [PMID: 38510710 PMCID: PMC10950971 DOI: 10.3389/fnut.2024.1331990] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2023] [Accepted: 02/21/2024] [Indexed: 03/22/2024] Open
Abstract
Introduction The prevalence of obesity in the Mexican school-age (5-11 years old) population increased from 8.9 to 18.1% between 1999 and 2022. Although overweight and obesity (OW + Ob) is a complex and multifactorial phenomenon, alongside its increasing trend, changes in eating patterns as a result of obesogenic environments that promote higher energy intake have been documented. The objective of the present study was to detect possible associations between schools and their proximity to and density of convenience stores in Monterrey, Mexico from 2015 to 2018. Materials and methods Anthropometric data were obtained from a subset of measurements of the National Registry of Weight and Height (RNPT) performed in the Monterrey Mexico metropolitan area in 2015 and 2018, and obesity prevalence was computed and classified into quintiles at the school level. Convenience store data were obtained from the National Directory of Economic Units (DNUE). The analyses consisted of densities within 400-800 m buffers, distance to the nearest stores, and cartographic visualization of the store's kernel density versus OW + Ob hotspots for both periods. Results A total of 175,804 children in 2015 and 175,964 in 2018 belonging to 1,552 elementary schools were included in the study; during this period, OW + Ob prevalence increased from 38.7 to 39.3%, and a directly proportional relationship was found between the quintiles with the higher OW + Ob prevalence and the number of stores for both radii. Hotspots of OW + Ob ranged from 63 to 91 between 2015 and 2018, and it was visually confirmed that such spots were associated with areas with a higher density of convenience stores regardless of socioeconomic conditions. Conclusion Although some relationships between the store's proximity/density and OW + Ob could be identified, more research is needed to gather evidence about this. However, due to the trends and the magnitude of the problem, guidelines aimed at limiting or reducing the availability of junk food and sweetened beverages on the school's periphery must be implemented to control the obesogenic environment.
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Affiliation(s)
- Marco Antonio Ávila Arcos
- Center for Research on Evaluation and Surveys, National Institute of Public Health of Mexico, Cuernavaca, Mexico
| | - Teresa Shamah Levy
- Center for Research on Evaluation and Surveys, National Institute of Public Health of Mexico, Cuernavaca, Mexico
| | - Marti Yareli Del Monte Vega
- Applied Nutrition and Nutritional Education Department, National Institute of Medical Sciences and Nutrition Salvador Zubirán, Mexico City, Mexico
| | - Adolfo Chávez Villasana
- Applied Nutrition and Nutritional Education Department, National Institute of Medical Sciences and Nutrition Salvador Zubirán, Mexico City, Mexico
| | - Abelardo Ávila Curiel
- Applied Nutrition and Nutritional Education Department, National Institute of Medical Sciences and Nutrition Salvador Zubirán, Mexico City, Mexico
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Saucy A, Ortega N, Tonne C. Residential relocation to assess impact of changes in the living environment on cardio-respiratory health: A narrative literature review with considerations for exposome research. ENVIRONMENTAL RESEARCH 2024; 244:117890. [PMID: 38081343 DOI: 10.1016/j.envres.2023.117890] [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: 09/27/2023] [Revised: 11/23/2023] [Accepted: 12/05/2023] [Indexed: 12/25/2023]
Abstract
Residential relocation studies have become increasingly valuable tools for evaluating the effects of changing living environments on human health, but little is known about their application to multiple aspects of the living environment and the most appropriate methodology. This narrative review explores the utility of residential relocation as a natural experiment for studying the impact of changing urban exposures on cardio-metabolic health in high-income settings. It provides a comprehensive overview of the use of residential relocation studies, evaluates their methodological approaches, and synthesizes findings related to health behaviors and cardio-metabolic outcomes. Our search identified 43 relevant studies published between January 1995 and February 2023, from eight countries, predominantly the USA, Canada, and Australia. The majority of eligible studies were published between 2012 and 2021 and examined changes in various domains of the living environment, such as walkability, the built and social environments, but rarely combinations of exposures. Included studies displayed heterogeneity in design and outcomes, 25 involving only movers and 18 considering both movers and non-movers. To mitigate the issue of residential self-selection bias, most studies employed a "change-in-change" design and adjusted for baseline covariates but only a fraction of them accounted for time-varying confounding. Relocation causes simultaneous changes in various features of the living environment, which presents an opportunity for exposome research to establish causal relationships, using large datasets with increased statistical power and a wide range of health outcomes, behaviors and biomarkers. Residential relocation is not a random process. Thus, studies focusing on living environment characteristics need to carefully select time-varying covariates and reference group. Overall, this review informs future research by guiding choices in study design, data requirements, and statistical methodologies. Ultimately, it contributes to the advancement of the urban exposome field and enhances our understanding of the complex relationship between urban environments and human health.
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Affiliation(s)
- Apolline Saucy
- Barcelona Institute for Global Health (ISGlobal), Barcelona, Spain; Universitat Pompeu Fabra, Barcelona, Spain; CIBER Epidemiología y Salud Pública, Madrid, Spain.
| | - Natalia Ortega
- Barcelona Institute for Global Health (ISGlobal), Barcelona, Spain; Institute of Primary Health Care (BIHAM), University of Bern, Bern, Switzerland; Population Health Laboratory (#PopHealthLab), University of Fribourg, Fribourg, Switzerland
| | - Cathryn Tonne
- Barcelona Institute for Global Health (ISGlobal), Barcelona, Spain; Universitat Pompeu Fabra, Barcelona, Spain; CIBER Epidemiología y Salud Pública, Madrid, Spain.
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Rosenberg DE, Cruz MF, Mooney SJ, Bobb JF, Drewnowski A, Moudon AV, Cook AJ, Hurvitz PM, Lozano P, Anau J, Theis MK, Arterburn DE. Neighborhood built and food environment in relation to glycemic control in people with type 2 diabetes in the moving to health study. Health Place 2024; 86:103216. [PMID: 38401397 PMCID: PMC10957299 DOI: 10.1016/j.healthplace.2024.103216] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/16/2023] [Revised: 01/05/2024] [Accepted: 02/16/2024] [Indexed: 02/26/2024]
Abstract
OBJECTIVE To examine whether built environment and food metrics are associated with glycemic control in people with type 2 diabetes. RESEARCH DESIGN AND METHODS We included 14,985 patients with type 2 diabetes using electronic health records from Kaiser Permanente Washington. Patient addresses were geocoded with ArcGIS using King County and Esri reference data. Built environment exposures estimated from geocoded locations included residential unit density, transit threshold residential unit density, park access, and having supermarkets and fast food restaurants within 1600-m Euclidean buffers. Linear mixed effects models compared mean changes of HbA1c from baseline at 1, 3 (primary) and 5 years by each built environment variable. RESULTS Patients (mean age = 59.4 SD = 13.2, 49.5% female, 16.6% Asian, 9.8% Black, 5.5% Latino/Hispanic, 57.1% White, 20% insulin dependent, mean BMI = 32.7±7.7) had an average of 6 HbA1c measures available. Participants in the 1st tertile of residential density (lowest) had a greater decline in HbA1c (-0.42, -0.43, and -0.44 in years 1, 3, and 5 respectively) than those in the 3rd tertile (HbA1c = -0.37 at 1- and 3-years and -0.36 at 5-years; all p-values <0.05). Having any supermarkets within 1600 m of home was associated with a greater decrease in HbA1c at 1-year and 3-years compared to having none (all p-values <0.05). CONCLUSIONS Lower residential density and better proximity to supermarkets may benefit HbA1c control in people with people with type 2 diabetes. However, effects were small and indicate limited clinical significance.
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Affiliation(s)
| | - Maricela F Cruz
- Kaiser Permanente Washington Health Research Institute, USA.
| | | | - Jennifer F Bobb
- Kaiser Permanente Washington Health Research Institute, USA.
| | | | | | - Andrea J Cook
- Kaiser Permanente Washington Health Research Institute, USA.
| | - Philip M Hurvitz
- University of Washington, Center for Studies in Demography and Ecology, USA.
| | - Paula Lozano
- Kaiser Permanente Washington Health Research Institute, USA.
| | - Jane Anau
- Kaiser Permanente Washington Health Research Institute, USA.
| | - Mary Kay Theis
- Kaiser Permanente Washington Health Research Institute, USA.
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Martin SS, Aday AW, Almarzooq ZI, Anderson CAM, Arora P, Avery CL, Baker-Smith CM, Barone Gibbs B, Beaton AZ, Boehme AK, Commodore-Mensah Y, Currie ME, Elkind MSV, Evenson KR, Generoso G, Heard DG, Hiremath S, Johansen MC, Kalani R, Kazi DS, Ko D, Liu J, Magnani JW, Michos ED, Mussolino ME, Navaneethan SD, Parikh NI, Perman SM, Poudel R, Rezk-Hanna M, Roth GA, Shah NS, St-Onge MP, Thacker EL, Tsao CW, Urbut SM, Van Spall HGC, Voeks JH, Wang NY, Wong ND, Wong SS, Yaffe K, Palaniappan LP. 2024 Heart Disease and Stroke Statistics: A Report of US and Global Data From the American Heart Association. Circulation 2024; 149:e347-e913. [PMID: 38264914 DOI: 10.1161/cir.0000000000001209] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/25/2024]
Abstract
BACKGROUND The American Heart Association (AHA), in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, nutrition, sleep, and obesity) and health factors (cholesterol, blood pressure, glucose control, and metabolic syndrome) that contribute to cardiovascular health. The AHA Heart Disease and Stroke Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, brain health, complications of pregnancy, kidney disease, congenital heart disease, rhythm disorders, sudden cardiac arrest, subclinical atherosclerosis, coronary heart disease, cardiomyopathy, heart failure, valvular disease, venous thromboembolism, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs). METHODS The AHA, through its Epidemiology and Prevention Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States and globally to provide the most current information available in the annual Statistical Update with review of published literature through the year before writing. The 2024 AHA Statistical Update is the product of a full year's worth of effort in 2023 by dedicated volunteer clinicians and scientists, committed government professionals, and AHA staff members. The AHA strives to further understand and help heal health problems inflicted by structural racism, a public health crisis that can significantly damage physical and mental health and perpetuate disparities in access to health care, education, income, housing, and several other factors vital to healthy lives. This year's edition includes additional global data, as well as data on the monitoring and benefits of cardiovascular health in the population, with an enhanced focus on health equity across several key domains. RESULTS Each of the chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics. CONCLUSIONS The Statistical Update represents a critical resource for the lay public, policymakers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.
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Myers CA. Impact of the Neighborhood Food Environment on Dietary Intake and Obesity: a Review of the Recent Literature. Curr Diab Rep 2023; 23:371-386. [PMID: 38008848 DOI: 10.1007/s11892-023-01529-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 11/08/2023] [Indexed: 11/28/2023]
Abstract
PURPOSE OF REVIEW The built environment impacts obesogenic behaviors and in turn body weight outcomes. This review summarizes recent research demonstrating environmental impacts on dietary intake and obesity with a specific focus on the neighborhood food environment. RECENT FINDINGS In the previous five years, an abundance of reviews and research studies have been undertaken to elucidate how the neighborhood food environment impacts diet and obesity. This includes studies using primary data collection and secondary data analyses in various populations across the globe. Taken together, current research presents mixed evidence on the impact of the neighborhood food environment on both dietary intake and obesity. While there is some evidence that certain features of the neighborhood food environment influence health behaviors and outcomes in particular populations, it is imperative to acknowledge the complexity of how neighborhood features interact and constantly evolve when considering place-based influences on health behaviors and outcomes.
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Affiliation(s)
- Candice A Myers
- Pennington Biomedical Research Center, Baton Rouge, LA, 70808, USA.
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8
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Tsao CW, Aday AW, Almarzooq ZI, Anderson CAM, Arora P, Avery CL, Baker-Smith CM, Beaton AZ, Boehme AK, Buxton AE, Commodore-Mensah Y, Elkind MSV, Evenson KR, Eze-Nliam C, Fugar S, Generoso G, Heard DG, Hiremath S, Ho JE, Kalani R, Kazi DS, Ko D, Levine DA, Liu J, Ma J, Magnani JW, Michos ED, Mussolino ME, Navaneethan SD, Parikh NI, Poudel R, Rezk-Hanna M, Roth GA, Shah NS, St-Onge MP, Thacker EL, Virani SS, Voeks JH, Wang NY, Wong ND, Wong SS, Yaffe K, Martin SS. Heart Disease and Stroke Statistics-2023 Update: A Report From the American Heart Association. Circulation 2023; 147:e93-e621. [PMID: 36695182 DOI: 10.1161/cir.0000000000001123] [Citation(s) in RCA: 1023] [Impact Index Per Article: 1023.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/26/2023]
Abstract
BACKGROUND The American Heart Association, in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, diet, and weight) and health factors (cholesterol, blood pressure, and glucose control) that contribute to cardiovascular health. The Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, congenital heart disease, rhythm disorders, subclinical atherosclerosis, coronary heart disease, heart failure, valvular disease, venous disease, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs). METHODS The American Heart Association, through its Epidemiology and Prevention Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States to provide the most current information available in the annual Statistical Update with review of published literature through the year before writing. The 2023 Statistical Update is the product of a full year's worth of effort in 2022 by dedicated volunteer clinicians and scientists, committed government professionals, and American Heart Association staff members. The American Heart Association strives to further understand and help heal health problems inflicted by structural racism, a public health crisis that can significantly damage physical and mental health and perpetuate disparities in access to health care, education, income, housing, and several other factors vital to healthy lives. This year's edition includes additional COVID-19 (coronavirus disease 2019) publications, as well as data on the monitoring and benefits of cardiovascular health in the population, with an enhanced focus on health equity across several key domains. RESULTS Each of the chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics. CONCLUSIONS The Statistical Update represents a critical resource for the lay public, policymakers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.
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Cruz M, Drewnowski A, Bobb JF, Hurvitz PM, Moudon AV, Cook A, Mooney SJ, Buszkiewicz JH, Lozano P, Rosenberg DE, Kapos F, Theis MK, Anau J, Arterburn D. Differences in Weight Gain Following Residential Relocation in the Moving to Health (M2H) Study. Epidemiology 2022; 33:747-755. [PMID: 35609209 PMCID: PMC9378543 DOI: 10.1097/ede.0000000000001505] [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] [Indexed: 11/27/2022]
Abstract
BACKGROUND Neighborhoods may play an important role in shaping long-term weight trajectory and obesity risk. Studying the impact of moving to another neighborhood may be the most efficient way to determine the impact of the built environment on health. We explored whether residential moves were associated with changes in body weight. METHODS Kaiser Permanente Washington electronic health records were used to identify 21,502 members aged 18-64 who moved within King County, WA between 2005 and 2017. We linked body weight measures to environment measures, including population, residential, and street intersection densities (800 m and 1,600 m Euclidian buffers) and access to supermarkets and fast foods (1,600 m and 5,000 m network distances). We used linear mixed models to estimate associations between postmove changes in environment and changes in body weight. RESULTS In general, moving from high-density to moderate- or low-density neighborhoods was associated with greater weight gain postmove. For example, those moving from high to low residential density neighborhoods (within 1,600 m) gained an average of 4.5 (95% confidence interval [CI] = 3.0, 5.9) lbs 3 years after moving, whereas those moving from low to high-density neighborhoods gained an average of 1.3 (95% CI = -0.2, 2.9) lbs. Also, those moving from neighborhoods without fast-food access (within 1600m) to other neighborhoods without fast-food access gained less weight (average 1.6 lbs [95% CI = 0.9, 2.4]) than those moving from and to neighborhoods with fast-food access (average 2.8 lbs [95% CI = 2.5, 3.2]). CONCLUSIONS Moving to higher-density neighborhoods may be associated with reductions in adult weight gain.
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Affiliation(s)
- Maricela Cruz
- Kaiser Permanente Washington Health Research Institute, 1730 Minor Ave. Suite 1600, Seattle, WA, 98101, USA
- Department of Biostatistics, School of Public Health, University of Washington, Seattle, WA, 98195, USA
| | - Adam Drewnowski
- Center for Public Health Nutrition, 305 Raitt Hall, #353410, University of Washington, Seattle, WA, 98195-3410, USA
- Department of Epidemiology, School of Public Health, University of Washington, Seattle, WA, 98195, USA
| | - Jennifer F. Bobb
- Kaiser Permanente Washington Health Research Institute, 1730 Minor Ave. Suite 1600, Seattle, WA, 98101, USA
- Department of Biostatistics, School of Public Health, University of Washington, Seattle, WA, 98195, USA
| | - Philip M Hurvitz
- Urban Form Lab, Department of Urban Design and Planning, College of Built Environments, University of Washington, 4333 Brooklyn Ave NE, Seattle, Washington 98195, USA
- Center for Studies in Demography and Ecology, University of Washington, Seattle, WA, 98195-3410, USA
| | - Anne Vernez Moudon
- Urban Form Lab, Department of Urban Design and Planning, College of Built Environments, University of Washington, 4333 Brooklyn Ave NE, Seattle, Washington 98195, USA
| | - Andrea Cook
- Kaiser Permanente Washington Health Research Institute, 1730 Minor Ave. Suite 1600, Seattle, WA, 98101, USA
- Department of Biostatistics, School of Public Health, University of Washington, Seattle, WA, 98195, USA
| | - Stephen J. Mooney
- Department of Epidemiology, School of Public Health, University of Washington, Seattle, WA, 98195, USA
| | - James H. Buszkiewicz
- Center for Public Health Nutrition, 305 Raitt Hall, #353410, University of Washington, Seattle, WA, 98195-3410, USA
- Department of Epidemiology, School of Public Health, University of Washington, Seattle, WA, 98195, USA
| | - Paula Lozano
- Kaiser Permanente Washington Health Research Institute, 1730 Minor Ave. Suite 1600, Seattle, WA, 98101, USA
| | - Dori E. Rosenberg
- Kaiser Permanente Washington Health Research Institute, 1730 Minor Ave. Suite 1600, Seattle, WA, 98101, USA
| | - Flavia Kapos
- Department of Epidemiology, School of Public Health, University of Washington, Seattle, WA, 98195, USA
| | - Mary Kay Theis
- Kaiser Permanente Washington Health Research Institute, 1730 Minor Ave. Suite 1600, Seattle, WA, 98101, USA
| | - Jane Anau
- Kaiser Permanente Washington Health Research Institute, 1730 Minor Ave. Suite 1600, Seattle, WA, 98101, USA
| | - David Arterburn
- Kaiser Permanente Washington Health Research Institute, 1730 Minor Ave. Suite 1600, Seattle, WA, 98101, USA
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Associations between neighborhood built environment, residential property values, and adult BMI change: The Seattle Obesity Study III. SSM Popul Health 2022; 19:101158. [PMID: 35813186 PMCID: PMC9260622 DOI: 10.1016/j.ssmph.2022.101158] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2021] [Revised: 06/24/2022] [Accepted: 06/25/2022] [Indexed: 11/25/2022] Open
Abstract
Objective To examine associations between neighborhood built environment (BE) variables, residential property values, and longitudinal 1- and 2-year changes in body mass index (BMI). Methods The Seattle Obesity Study III was a prospective cohort study of adults with geocoded residential addresses, conducted in King, Pierce, and Yakima Counties in Washington State. Measured heights and weights were obtained at baseline (n = 879), year 1 (n = 727), and year 2 (n = 679). Tax parcel residential property values served as proxies for individual socioeconomic status. Residential unit and road intersection density were captured using Euclidean-based SmartMaps at 800 m buffers. Counts of supermarket (0 versus. 1+) and fast-food restaurant availability (0, 1–3, 4+) were measured using network based SmartMaps at 1600 m buffers. Density measures and residential property values were categorized into tertiles. Linear mixed-effects models tested whether baseline BE variables and property values were associated with differential changes in BMI at year 1 or year 2, adjusting for age, gender, race/ethnicity, education, home ownership, and county of residence. These associations were then tested for potential disparities by age group, gender, race/ethnicity, and education. Results Road intersection density, access to food sources, and residential property values were inversely associated with BMI at baseline. At year 1, participants in the 3rd tertile of density metrics and with 4+ fast-food restaurants nearby showed less BMI gain compared to those in the 1st tertile or with 0 restaurants. At year 2, higher residential property values were predictive of lower BMI gain. There was evidence of differential associations by age group, gender, and education but not race/ethnicity. Conclusion Inverse associations between BE metrics and residential property values at baseline demonstrated mixed associations with 1- and 2-year BMI change. More work is needed to understand how individual-level sociodemographic factors moderate associations between the BE, property values, and BMI change. Strong, inverse cross-sectional relationships between the built environment, residential property values (a proxy for individual socioeconomic status), and measured BMI were observed. Measures of the built environment and residential property values showed modest and inconsistent associations with 1- and 2-year BMI change. There was suggestive evidence that age may moderate the association between urban density and 1- and 2-year BMI change while education may moderate the association between residential property values and 2-year BMI change.
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Tsao CW, Aday AW, Almarzooq ZI, Alonso A, Beaton AZ, Bittencourt MS, Boehme AK, Buxton AE, Carson AP, Commodore-Mensah Y, Elkind MSV, Evenson KR, Eze-Nliam C, Ferguson JF, Generoso G, Ho JE, Kalani R, Khan SS, Kissela BM, Knutson KL, Levine DA, Lewis TT, Liu J, Loop MS, Ma J, Mussolino ME, Navaneethan SD, Perak AM, Poudel R, Rezk-Hanna M, Roth GA, Schroeder EB, Shah SH, Thacker EL, VanWagner LB, Virani SS, Voecks JH, Wang NY, Yaffe K, Martin SS. Heart Disease and Stroke Statistics-2022 Update: A Report From the American Heart Association. Circulation 2022; 145:e153-e639. [PMID: 35078371 DOI: 10.1161/cir.0000000000001052] [Citation(s) in RCA: 2268] [Impact Index Per Article: 1134.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
BACKGROUND The American Heart Association, in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, diet, and weight) and health factors (cholesterol, blood pressure, and glucose control) that contribute to cardiovascular health. The Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, congenital heart disease, rhythm disorders, subclinical atherosclerosis, coronary heart disease, heart failure, valvular disease, venous disease, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs). METHODS The American Heart Association, through its Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States to provide the most current information available in the annual Statistical Update. The 2022 Statistical Update is the product of a full year's worth of effort by dedicated volunteer clinicians and scientists, committed government professionals, and American Heart Association staff members. This year's edition includes data on the monitoring and benefits of cardiovascular health in the population and an enhanced focus on social determinants of health, adverse pregnancy outcomes, vascular contributions to brain health, and the global burden of cardiovascular disease and healthy life expectancy. RESULTS Each of the chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics. CONCLUSIONS The Statistical Update represents a critical resource for the lay public, policymakers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.
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Buszkiewicz JH, Bobb JF, Kapos F, Hurvitz PM, Arterburn D, Moudon AV, Cook A, Mooney SJ, Cruz M, Gupta S, Lozano P, Rosenberg DE, Theis MK, Anau J, Drewnowski A. Differential associations of the built environment on weight gain by sex and race/ethnicity but not age. Int J Obes (Lond) 2021; 45:2648-2656. [PMID: 34453098 PMCID: PMC8608695 DOI: 10.1038/s41366-021-00937-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/21/2021] [Revised: 07/19/2021] [Accepted: 08/04/2021] [Indexed: 11/18/2022]
Abstract
OBJECTIVE To explore the built environment (BE) and weight change relationship by age, sex, and racial/ethnic subgroups in adults. METHODS Weight trajectories were estimated using electronic health records for 115,260 insured Kaiser Permanente Washington members age 18-64 years. Member home addresses were geocoded using ArcGIS. Population, residential, and road intersection densities and counts of area supermarkets and fast food restaurants were measured with SmartMaps (800 and 5000-meter buffers) and categorized into tertiles. Linear mixed-effect models tested whether associations between BE features and weight gain at 1, 3, and 5 years differed by age, sex, and race/ethnicity, adjusting for demographics, baseline weight, and residential property values. RESULTS Denser urban form and greater availability of supermarkets and fast food restaurants were associated with differential weight change across sex and race/ethnicity. At 5 years, the mean difference in weight change comparing the 3rd versus 1st tertile of residential density was significantly different between males (-0.49 kg, 95% CI: -0.68, -0.30) and females (-0.17 kg, 95% CI: -0.33, -0.01) (P-value for interaction = 0.011). Across race/ethnicity, the mean difference in weight change at 5 years for residential density was significantly different among non-Hispanic (NH) Whites (-0.47 kg, 95% CI: -0.61, -0.32), NH Blacks (-0.86 kg, 95% CI: -1.37, -0.36), Hispanics (0.10 kg, 95% CI: -0.46, 0.65), and NH Asians (0.44 kg, 95% CI: 0.10, 0.78) (P-value for interaction <0.001). These findings were consistent for other BE measures. CONCLUSION The relationship between the built environment and weight change differs across demographic groups. Careful consideration of demographic differences in associations of BE and weight trajectories is warranted for investigating etiological mechanisms and guiding intervention development.
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Affiliation(s)
- James H Buszkiewicz
- Center for Public Health Nutrition, 305 Raitt Hall, #353410, University of Washington, Seattle, WA, USA.
- Department of Epidemiology, School of Public Health, University of Washington, Seattle, WA, USA.
| | - Jennifer F Bobb
- Kaiser Permanente Washington Health Research Institute, Seattle, WA, USA
| | - Flavia Kapos
- Department of Epidemiology, School of Public Health, University of Washington, Seattle, WA, USA
| | - Philip M Hurvitz
- Urban Form Lab, Department of Urban Design and Planning, College of Built Environments, University of Washington, Seattle, WA, USA
- Center for Studies in Demography and Ecology, University of Washington, Raitt Hall, Seattle, WA, USA
| | - David Arterburn
- Kaiser Permanente Washington Health Research Institute, Seattle, WA, USA
| | - Anne Vernez Moudon
- Urban Form Lab, Department of Urban Design and Planning, College of Built Environments, University of Washington, Seattle, WA, USA
| | - Andrea Cook
- Kaiser Permanente Washington Health Research Institute, Seattle, WA, USA
| | - Stephen J Mooney
- Department of Epidemiology, School of Public Health, University of Washington, Seattle, WA, USA
| | - Maricela Cruz
- Kaiser Permanente Washington Health Research Institute, Seattle, WA, USA
| | - Shilpi Gupta
- Center for Public Health Nutrition, 305 Raitt Hall, #353410, University of Washington, Seattle, WA, USA
- Department of Epidemiology, School of Public Health, University of Washington, Seattle, WA, USA
| | - Paula Lozano
- Kaiser Permanente Washington Health Research Institute, Seattle, WA, USA
| | - Dori E Rosenberg
- Kaiser Permanente Washington Health Research Institute, Seattle, WA, USA
| | - Mary Kay Theis
- Kaiser Permanente Washington Health Research Institute, Seattle, WA, USA
| | - Jane Anau
- Kaiser Permanente Washington Health Research Institute, Seattle, WA, USA
| | - Adam Drewnowski
- Center for Public Health Nutrition, 305 Raitt Hall, #353410, University of Washington, Seattle, WA, USA
- Department of Epidemiology, School of Public Health, University of Washington, Seattle, WA, USA
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