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Field C, Wang XY, Costantine MM, Landon MB, Grobman WA, Venkatesh KK. Social Determinants of Health and Diabetes in Pregnancy. Am J Perinatol 2024. [PMID: 39209304 DOI: 10.1055/a-2405-2409] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 09/04/2024]
Abstract
Social determinants of health (SDOH) are the conditions in which people are born, grow, work, live, and age. SDOH are systemic factors that may explain, perpetuate, and exacerbate disparities in health outcomes for different populations and can be measured at both an individual and neighborhood or community level (iSDOH, nSDOH). In pregnancy, increasing evidence shows that adverse iSDOH and/or nSDOH are associated with a greater likelihood that diabetes develops, and that when it develops, there is worse glycemic control and a greater frequency of adverse pregnancy outcomes. Future research should not only continue to examine the relationships between SDOH and adverse pregnancy outcomes with diabetes but should determine whether multi-level interventions that seek to mitigate adverse SDOH result in equitable maternal care and improved patient health outcomes for pregnant individuals living with diabetes. KEY POINTS: · SDOH are conditions in which people are born, grow, work, live, and age.. · SDOH are systemic factors that may explain, perpetuate, and exacerbate disparities in health outcomes.. · SDOH can be measured at the individual and neighborhood level.. · Adverse SDOH are associated with worse outcomes for pregnant individuals living with diabetes.. · Interventions that mitigate adverse SDOH to improve maternal health equity and outcomes are needed..
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Affiliation(s)
- Christine Field
- Department of Obstetrics and Gynecology, The Ohio State University, Columbus, Ohio
| | - Xiao-Yu Wang
- Department of Obstetrics and Gynecology, The Ohio State University, Columbus, Ohio
| | - Maged M Costantine
- Department of Obstetrics and Gynecology, The Ohio State University, Columbus, Ohio
| | - Mark B Landon
- Department of Obstetrics and Gynecology, The Ohio State University, Columbus, Ohio
| | - William A Grobman
- Department of Obstetrics and Gynecology, Brown University, Providence, Rhode Island
| | - Kartik K Venkatesh
- Department of Obstetrics and Gynecology, The Ohio State University, Columbus, Ohio
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Li Z, Lu Y, Xie B, Wu Y. Large-scale greenway exposure reduces sedentary behavior: A natural experiment in China. Health Place 2024; 89:103283. [PMID: 38850725 DOI: 10.1016/j.healthplace.2024.103283] [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] [Received: 02/02/2024] [Revised: 05/25/2024] [Accepted: 05/29/2024] [Indexed: 06/10/2024]
Abstract
As a global public health problem, sedentary behavior has attracted more and more attention. Although numerous studies have demonstrated many benefits of green spaces to health, causal evidence on how green spaces affect people's sedentary behavior is scarce. This study used a natural experiment to evaluate the impact of greenway intervention on sedentary behavior. Two waves of data were collected in 2016 and 2019 (before and after the intervention) at East Lake Greenway (102-km-long) in Wuhan, China, with 1020 participants in 52 neighborhoods. We adopted three major methods to evaluate the impact of greenway intervention on sedentary behavior, including Propensity Score Matching and difference-in-difference (PSM-DID) method (with both individual and neighborhood variables to match samples), continuous treatment DID method (with distance to the greenway as the continuous treatment), and mediation analysis (with moderate to vigorous physical activity or MVPA, and walking time as the mediator). The results revealed that the greenway intervention significantly reduced participants' sedentary time and the intervention has a distance decay effect. The closer to the greenway, the greater decrease in sedentary time after the greenway opening. Furthermore, we found that MVPA and walking time mediate the impact of the greenway intervention on the change in sedentary behavior. The effect of greenway intervention was more beneficial for those under the age of 60, those who were employed, or those who were married. Our findings provided robust evidence that exposure to urban greenways affects sedentary behavior and such green infrastructures help protect public health in high-density urban areas.
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Affiliation(s)
- Zhenhua Li
- Department of Architecture and Civil Engineering, City University of Hong Kong, Hong Kong, China.
| | - Yi Lu
- Department of Architecture and Civil Engineering, City University of Hong Kong, Hong Kong, China.
| | - Bo Xie
- School of Urban Design, Wuhan University, Wuhan, 430072, China.
| | - Yihao Wu
- Department of Architecture, University of Cambridge, Cambridgeshire, UK.
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Deng S, Liang J, Peng Y, Liu W, Su J, Zhu S. Spatial analysis of the impact of urban built environment on cardiovascular diseases: a case study in Xixiangtang, China. BMC Public Health 2024; 24:2368. [PMID: 39217314 PMCID: PMC11366168 DOI: 10.1186/s12889-024-19884-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2024] [Accepted: 08/26/2024] [Indexed: 09/04/2024] Open
Abstract
BACKGROUND The built environment, as a critical factor influencing residents' cardiovascular health, has a significant potential impact on the incidence of cardiovascular diseases (CVDs). METHODS Taking Xixiangtang District in Nanning City, Guangxi Zhuang Autonomous Region of China as a case study, we utilized the geographic location information of CVD patients, detailed road network data, and urban points of interest (POI) data. Kernel density estimation (KDE) and spatial autocorrelation analysis were specifically employed to identify the spatial distribution patterns, spatial clustering, and spatial correlations of built environment elements and diseases. The GeoDetector method (GDM) was used to assess the impact of environmental factors on diseases, and geographically weighted regression (GWR) analysis was adopted to reveal the spatial heterogeneity effect of environmental factors on CVD risk. RESULTS The results indicate that the built environment elements and CVDs samples exhibit significant clustering characteristics in their spatial distribution, with a positive correlation between the distribution density of environmental elements and the incidence of CVDs (Moran's I > 0, p < 0.01). Further factor detection revealed that the distribution of healthcare facilities had the most significant impact on CVDs (q = 0.532, p < 0.01), followed by shopping and consumption (q = 0.493, p < 0.01), dining (q = 0.433, p < 0.01), and transportation facilities (q = 0.423, p < 0.01), while the impact of parks and squares (q = 0.174, p < 0.01) and road networks (q = 0.159, p < 0.01) was relatively smaller. Additionally, the interaction between different built environment elements exhibited a bi-factor enhancement effect on CVDs. In the local analysis, the spatial heterogeneity of different built environment elements on CVDs further revealed the regional differences and complexities. CONCLUSIONS The spatial distribution of built environment elements is significantly correlated with CVDs to varying degrees and impacts differently across regions, underscoring the importance of the built environment on cardiovascular health. When planning and improving urban environments, elements and areas that have a more significant impact on CVDs should be given priority consideration.
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Affiliation(s)
- Shuguang Deng
- School of Geographical and Planning, Nanning Normal University, Nanning, 530100, Guangxi, China
| | - Jinlong Liang
- School of Geographical and Planning, Nanning Normal University, Nanning, 530100, Guangxi, China.
| | - Ying Peng
- School of Architecture, Guangxi Arts University, Nanning, 530009, Guangxi, China
| | - Wei Liu
- Fatulty of Innovation and Design, City University of Macau, Macau, 999078, China
| | - Jinhong Su
- School of Geographical and Planning, Nanning Normal University, Nanning, 530100, Guangxi, China
| | - Shuyan Zhu
- School of Geographical and Planning, Nanning Normal University, Nanning, 530100, Guangxi, China
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Nwana N, Makram OM, Nicolas JC, Pan A, Gullapelli R, Parekh T, Javed Z, Titus A, Al-Kindi S, Guan J, Sun K, Jones SL, Maddock JE, Chang J, Nasir K. Neighborhood Walkability Is Associated With Lower Burden of Cardiovascular Risk Factors Among Cancer Patients. JACC CardioOncol 2024; 6:421-435. [PMID: 38983386 PMCID: PMC11229549 DOI: 10.1016/j.jaccao.2024.03.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2023] [Accepted: 03/19/2024] [Indexed: 07/11/2024] Open
Abstract
Background Modifiable cardiovascular risk factors constitute a significant cause of cardiovascular disease and mortality among patients with cancer. Recent studies suggest a potential link between neighborhood walkability and favorable cardiovascular risk factor profiles in the general population. Objectives This study aimed to investigate whether neighborhood walkability is correlated with favorable cardiovascular risk factor profiles among patients with a history of cancer. Methods We conducted a cross-sectional study using data from the Houston Methodist Learning Health System Outpatient Registry (2016-2022) comprising 1,171,768 adults aged 18 years and older. Neighborhood walkability was determined using the 2019 Walk Score and divided into 4 categories. Patients with a history of cancer were identified through International Classification of Diseases-10th Revision-Clinical Modification codes (C00-C96). We examined the prevalence and association between modifiable cardiovascular risk factors (hypertension, diabetes, smoking, dyslipidemia, and obesity) and neighborhood walkability categories in cancer patients. Results The study included 121,109 patients with a history of cancer; 56.7% were female patients, and 68.8% were non-Hispanic Whites, with a mean age of 67.3 years. The prevalence of modifiable cardiovascular risk factors was lower among participants residing in the most walkable neighborhoods compared with those in the least walkable neighborhoods (76.7% and 86.0%, respectively). Patients with a history of cancer living in very walkable neighborhoods were 16% less likely to have any risk factor compared with car-dependent-all errands neighborhoods (adjusted OR: 0.84, 95% CI: 0.78-0.92). Sensitivity analyses considering the timing of events yielded similar results. Conclusions Our findings demonstrate an association between neighborhood walkability and the burden of modifiable cardiovascular risk factors among patients with a medical history of cancer. Investments in walkable neighborhoods may present a viable opportunity for mitigating the growing burden of modifiable cardiovascular risk factors among patients with a history of cancer.
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Affiliation(s)
- Nwabunie Nwana
- Center for Health and Nature, Houston Methodist Research Institute, Houston, Texas, USA
- Center for Health Data Science and Analytics, Houston Methodist Research Institute, Houston, Texas, USA
| | - Omar Mohamed Makram
- Center for Health and Nature, Houston Methodist Research Institute, Houston, Texas, USA
| | - Juan C Nicolas
- Center for Health Data Science and Analytics, Houston Methodist Research Institute, Houston, Texas, USA
| | - Alan Pan
- Center for Health Data Science and Analytics, Houston Methodist Research Institute, Houston, Texas, USA
| | - Rakesh Gullapelli
- Center for Health Data Science and Analytics, Houston Methodist Research Institute, Houston, Texas, USA
| | - Tarang Parekh
- Center for Health Data Science and Analytics, Houston Methodist Research Institute, Houston, Texas, USA
| | - Zulqarnain Javed
- Center for Health Data Science and Analytics, Houston Methodist Research Institute, Houston, Texas, USA
| | - Anoop Titus
- Department of Internal Medicine, Saint Vincent Hospital, Worcester, Massachusetts, USA
| | - Sadeer Al-Kindi
- Center for Health and Nature, Houston Methodist Research Institute, Houston, Texas, USA
- Division of Cardiovascular Prevention and Wellness, Department of Cardiology, DeBakey Heart & Vascular Center, Houston Methodist, Houston, Texas, USA
| | - Jian Guan
- Neal Cancer Center, Houston Methodist, Houston, Texas, USA
| | - Kai Sun
- Neal Cancer Center, Houston Methodist, Houston, Texas, USA
| | - Stephen L Jones
- Center for Health Data Science and Analytics, Houston Methodist Research Institute, Houston, Texas, USA
| | - Jay E Maddock
- Center for Health and Nature, Houston Methodist Research Institute, Houston, Texas, USA
- Department of Environmental and Occupational Health, School of Public Health, Texas A&M University, College Station, Texas, USA
| | - Jenny Chang
- Neal Cancer Center, Houston Methodist, Houston, Texas, USA
| | - Khurram Nasir
- Center for Health Data Science and Analytics, Houston Methodist Research Institute, Houston, Texas, USA
- Division of Cardiovascular Prevention and Wellness, Department of Cardiology, DeBakey Heart & Vascular Center, Houston Methodist, Houston, Texas, USA
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Li M, Li Y, Liu Z, Hystad P, Rangarajan S, Tse LA, Lear SA, Ma Y, Chen M, Han G, Li R, Yusuf S, Liu L, Hu B, Li W. Associations of perceived built environment characteristics using NEWS questionnaires with all-cause mortality and major cardiovascular diseases: The prospective urban rural epidemiology (PURE)-China study. ENVIRONMENT INTERNATIONAL 2024; 187:108627. [PMID: 38636273 DOI: 10.1016/j.envint.2024.108627] [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: 12/14/2023] [Revised: 03/31/2024] [Accepted: 04/02/2024] [Indexed: 04/20/2024]
Abstract
BACKGROUND Despite increased literature focusing on the role of the built environment (BE) in health, few cohort studies have quantitatively analyzed neighborhood walkability environment in relation to the risk of death and cardiovascular disease (CVD). This longitudinal study aimed at evaluating the association between perceived BE attributeswith mortality and major CVD based on the Prospective Urban Rural Epidemiology study in China (PURE-China). METHODS The PURE-China study recruited 47,931 participants aged 35-70 years from 12 provinces of China between 2005 and 2009. The perceived BE information, including land use, street, aesthetics, and safety, was collected using the neighborhood environment walkability scale (NEWS) questionnaire, with higher scores indicating a more favorable rating. Two primary outcomes are all-cause mortality and major CVD event. The Cox frailty model with random intercepts was used to assess the association between the perceived total BE/subscales score and outcomes. RESULTS Of 32,163 participants included in this study, 19,253 (59.9 %) were women, and the mean (SD) age was 51.0 (9.5) years. After a median follow-up period of 11.7 years (IQR 9.4 - 12.2), we observed that one standard deviation higher of combined BE scores was related to a lower risk of all-cause mortality (HR = 0.85; 95 %CI, 0.80-0.90), and major CVD events (HR = 0.95; 95 %CI, 0.90-0.99). The subscales of perceived BE were related to a lower risk, although a few were not significant. Land use mix-diversity and safety from crime were the two most significant subscales. Stronger risks were observed among urban and female participants. CONCLUSION Favorable perceived BE characteristics were linked with a lower risk of all-cause mortality and major CVD events in Chinese population, especially in urban areas and females. Our findings can be used by policymakers to take action to mitigate the adverse effect of poor community conditions on health, such as improving local amenities and transport connectivity, providing building paths for walking, running and cycling.
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Affiliation(s)
- Mengya Li
- Medical Research & Biometrics Center, National Clinical Research Center for Cardiovascular Diseases, Fuwai Hospital, National Center for Cardiovascular Diseases, Peking Union Medical College & Chinese Academy of Medical Sciences Beijing, China
| | - Yang Li
- Medical Research & Biometrics Center, National Clinical Research Center for Cardiovascular Diseases, Fuwai Hospital, National Center for Cardiovascular Diseases, Peking Union Medical College & Chinese Academy of Medical Sciences Beijing, China; Interventional Center of Valvular Heart Disease, Beijing Anzhen Hospital, Capital Medical University, Beijing, China
| | - Zhiguang Liu
- Clinical Trial Unit, Beijing Anzhen Hospital, Capital Medical University, Beijing, China
| | - Perry Hystad
- School of Biological and Population Health Sciences, College of Public Health and Human Sciences, Oregon State University, Corvallis, OR, United States
| | - Sumathy Rangarajan
- Population Health Research Institute, McMaster University and Hamilton Health Sciences, Hamilton, Ontario, Canada
| | - Lap Ah Tse
- JC School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong SAR
| | - Scott A Lear
- Faculty of Health Sciences, Simon Fraser University, Vancouver, BC, Canada
| | - Yuanting Ma
- Dongguan Street Community Health Service Center, Xining, Qinghai Province, China
| | - Mengxin Chen
- Medical Research & Biometrics Center, National Clinical Research Center for Cardiovascular Diseases, Fuwai Hospital, National Center for Cardiovascular Diseases, Peking Union Medical College & Chinese Academy of Medical Sciences Beijing, China
| | - Guoliang Han
- Medical Research & Biometrics Center, National Clinical Research Center for Cardiovascular Diseases, Fuwai Hospital, National Center for Cardiovascular Diseases, Peking Union Medical College & Chinese Academy of Medical Sciences Beijing, China
| | - Ruotong Li
- Medical Research & Biometrics Center, National Clinical Research Center for Cardiovascular Diseases, Fuwai Hospital, National Center for Cardiovascular Diseases, Peking Union Medical College & Chinese Academy of Medical Sciences Beijing, China
| | - Salim Yusuf
- Population Health Research Institute, McMaster University and Hamilton Health Sciences, Hamilton, Ontario, Canada
| | - Lisheng Liu
- Beijing Hypertension League Institute, Beijing, China.
| | - Bo Hu
- Medical Research & Biometrics Center, National Clinical Research Center for Cardiovascular Diseases, Fuwai Hospital, National Center for Cardiovascular Diseases, Peking Union Medical College & Chinese Academy of Medical Sciences Beijing, China.
| | - Wei Li
- Medical Research & Biometrics Center, National Clinical Research Center for Cardiovascular Diseases, Fuwai Hospital, National Center for Cardiovascular Diseases, Peking Union Medical College & Chinese Academy of Medical Sciences Beijing, China.
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Carver A, Beare R, Knibbs LD, Mavoa S, Grocott K, Wheeler AJ, Srikanth V, Andrew NE. Exploring associations of greenery, air pollution and walkability with cardiometabolic health in people at midlife and beyond. Geriatr Gerontol Int 2024; 24 Suppl 1:208-214. [PMID: 38115171 PMCID: PMC11503538 DOI: 10.1111/ggi.14743] [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: 08/31/2023] [Revised: 10/25/2023] [Accepted: 11/04/2023] [Indexed: 12/21/2023]
Abstract
AIM To examine associations of neighborhood greenery, air pollution and walkability with cardiometabolic disease in adults aged ≥45 years in the Frankston-Mornington Peninsula region, Victoria, Australia. METHODS A cross-sectional, ecological study design was used. We assessed mean annual neighborhood greenery using the Normalized Difference Vegetation Index; air pollution (fine particulate matter of diameter ≤2.5 μm [PM2.5] and NO2) using land-use regression models; and walkability using Walk Score (possible values 0-100). Medically diagnosed diabetes (~95% type-2), heart disease and stroke were self-reported in the Australian Census (2021). Multivariable regression was used to model associations between environmental exposures and area-level (neighborhood) cardiometabolic disease prevalence (age group ≥45 years), with socioeconomic status, age and sex as covariates. Air pollution was examined as a mediator of associations between greenery and disease prevalence. RESULTS Our sample comprised 699 neighborhoods with the following mean (SD) values: Normalized Difference Vegetation Index 0.47 (0.09), PM2.5, 8.5 (0.6) μg/m3 and NO2, 5.2 (1.6) ppb. Disease prevalences were: heart disease, mean 8.9% (4.5%); diabetes, mean 10.3% (4.7%); and stroke, median 1.2% (range 0-10.9%). Greenery was negatively associated with diabetes (β = -5.85, 95% CI -9.53, -2.17) and stroke prevalence (β = -1.26, 95% CI -2.11, -0.42). PM2.5 and NO2 were positively associated with diabetes (β = 1.59, 95% CI 1.00, 2.18; β = 0.42, 95% CI 0.22, 0.62) and stroke prevalence (β = 0.15, 95% CI 0.01, 0.29; β = 0.06, 95% CI 0.01, 0.10). The association between greenery and diabetes was partially mediated by PM2.5 (mediated effect -5.38, 95% CI -7.84, -3.03). CONCLUSIONS Greenery and air pollutants were associated with lower and higher prevalence, respectively, of self-reported diabetes and, to a lesser extent, stroke. These ecological findings require further exploration with stronger, longitudinal study designs to inform public health policy and directions. Geriatr Gerontol Int 2024; 24: 208-214.
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Affiliation(s)
- Alison Carver
- National Centre for Healthy AgeingMelbourneVictoriaAustralia
- Peninsula Clinical School, Central Clinical school, Faculty of MedicineMonash UniversityMelbourneVictoriaAustralia
- Peninsula HealthMelbourneVictoriaAustralia
| | - Richard Beare
- National Centre for Healthy AgeingMelbourneVictoriaAustralia
- Peninsula Clinical School, Central Clinical school, Faculty of MedicineMonash UniversityMelbourneVictoriaAustralia
- Peninsula HealthMelbourneVictoriaAustralia
- Developmental ImagingMurdoch Children's Research InstituteMelbourneVictoriaAustralia
| | - Luke D Knibbs
- School of Public HealthThe University of SydneySydneyNew South WalesAustralia
- Public Health Research Analytics and Methods for Evidence, Public Health UnitSydney Local Health DistrictCamperdownNew South WalesAustralia
| | - Suzanne Mavoa
- Environmental Protection AuthorityMelbourneVictoriaAustralia
| | - Kaya Grocott
- University of MelbourneMelbourneVictoriaAustralia
| | | | - Velandai Srikanth
- National Centre for Healthy AgeingMelbourneVictoriaAustralia
- Peninsula Clinical School, Central Clinical school, Faculty of MedicineMonash UniversityMelbourneVictoriaAustralia
- Peninsula HealthMelbourneVictoriaAustralia
| | - Nadine E Andrew
- National Centre for Healthy AgeingMelbourneVictoriaAustralia
- Peninsula Clinical School, Central Clinical school, Faculty of MedicineMonash UniversityMelbourneVictoriaAustralia
- Peninsula HealthMelbourneVictoriaAustralia
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Field C, Grobman WA, Yee LM, Johnson J, Wu J, McNeil B, Mercer B, Simhan H, Reddy U, Silver RM, Parry S, Saade G, Chung J, Wapner R, Lynch CD, Venkatesh KK. Community-level social determinants of health and pregestational and gestational diabetes. Am J Obstet Gynecol MFM 2024; 6:101249. [PMID: 38070680 PMCID: PMC11184512 DOI: 10.1016/j.ajogmf.2023.101249] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2023] [Revised: 10/20/2023] [Accepted: 12/04/2023] [Indexed: 01/02/2024]
Abstract
BACKGROUND Individual adverse social determinants of health are associated with increased risk of diabetes in pregnancy, but the relative influence of neighborhood or community-level social determinants of health is unknown. OBJECTIVE This study aimed to determine whether living in neighborhoods with greater socioeconomic disadvantage, food deserts, or less walkability was associated with having pregestational diabetes and developing gestational diabetes. STUDY DESIGN We conducted a secondary analysis of the prospective Nulliparous Pregnancy Outcomes Study: Monitoring Mothers-To-Be. Home addresses in the first trimester were geocoded at the census tract level. The exposures (modeled separately) were the following 3 neighborhood-level measures of adverse social determinants of health: (1) socioeconomic disadvantage, defined by the Area Deprivation Index and measured in tertiles from the lowest tertile (ie, least disadvantage [T1]) to the highest (ie, most disadvantage [T3]); (2) food desert, defined by the United States Department of Agriculture Food Access Research Atlas (yes/no by low income and low access criteria); and (3) less walkability, defined by the Environmental Protection Agency National Walkability Index (most walkable score [15.26-20.0] vs less walkable score [<15.26]). Multinomial logistic regression was used to model the odds of gestational diabetes or pregestational diabetes relative to no diabetes as the reference, adjusted for age at delivery, chronic hypertension, Medicaid insurance status, and low household income (<130% of the US poverty level). RESULTS Among the 9155 assessed individuals, the mean Area Deprivation Index score was 39.0 (interquartile range, 19.0-71.0), 37.0% lived in a food desert, and 41.0% lived in a less walkable neighborhood. The frequency of pregestational and gestational diabetes diagnosis was 1.5% and 4.2%, respectively. Individuals living in a community in the highest tertile of socioeconomic disadvantage had increased odds of entering pregnancy with pregestational diabetes compared with those in the lowest tertile (T3 vs T1: 2.6% vs 0.8%; adjusted odds ratio, 2.52; 95% confidence interval, 1.41-4.48). Individuals living in a food desert (4.8% vs 4.0%; adjusted odds ratio, 1.37; 95% confidence interval, 1.06-1.77) and in a less walkable neighborhood (4.4% vs 3.8%; adjusted odds ratio, 1.33; 95% confidence interval, 1.04-1.71) had increased odds of gestational diabetes. There was no significant association between living in a food desert or a less walkable neighborhood and pregestational diabetes, or between socioeconomic disadvantage and gestational diabetes. CONCLUSION Nulliparous individuals living in a neighborhood with higher socioeconomic disadvantage were at increased odds of entering pregnancy with pregestational diabetes, and those living in a food desert or a less walkable neighborhood were at increased odds of developing gestational diabetes, after controlling for known covariates.
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Affiliation(s)
- Christine Field
- Department of Obstetrics and Gynecology, The Ohio State University, Columbus, OH (Drs Field and Grobman, Mr Wu, and Drs Lynch and Venkatesh).
| | - William A Grobman
- Department of Obstetrics and Gynecology, The Ohio State University, Columbus, OH (Drs Field and Grobman, Mr Wu, and Drs Lynch and Venkatesh)
| | - Lynn M Yee
- Department of Obstetrics and Gynecology, Northwestern University, Chicago, IL (Dr Yee)
| | - Jasmine Johnson
- Department of Obstetrics and Gynecology, Indiana University, Indianapolis, IN (Dr Johnson)
| | - Jiqiang Wu
- Department of Obstetrics and Gynecology, The Ohio State University, Columbus, OH (Drs Field and Grobman, Mr Wu, and Drs Lynch and Venkatesh)
| | | | - Brian Mercer
- Department of Obstetrics and Gynecology, Case Western Reserve University, Cleveland, OH (Dr Mercer)
| | - Hyagriv Simhan
- Department of Obstetrics and Gynecology, and Reproductive Sciences, University of Pittsburgh, Pittsburgh, PA (Dr Simhan)
| | - Uma Reddy
- Department of Obstetrics and Gynecology, Columbia University, New York, NY (Drs Reddy and Wapner)
| | - Robert M Silver
- Department of Obstetrics and Gynecology, University of Utah, Salt Lake City, UT (Dr Silver)
| | - Samuel Parry
- Department of Obstetrics and Gynecology, University of Pennsylvania, Philadelphia, PA (Dr Parry)
| | - George Saade
- Department of Obstetrics and Gynecology, University of Texas Medical Branch, Galveston, TX (Dr Saade)
| | - Judith Chung
- Department of Obstetrics and Gynecology, University of California, Irvine School of Medicine, Irvine, CA (Dr Chung)
| | - Ronald Wapner
- Department of Obstetrics and Gynecology, Columbia University, New York, NY (Drs Reddy and Wapner)
| | - Courtney D Lynch
- Department of Obstetrics and Gynecology, The Ohio State University, Columbus, OH (Drs Field and Grobman, Mr Wu, and Drs Lynch and Venkatesh)
| | - Kartik K Venkatesh
- Department of Obstetrics and Gynecology, The Ohio State University, Columbus, OH (Drs Field and Grobman, Mr Wu, and Drs Lynch and Venkatesh)
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Cardinali M, Beenackers MA, van Timmeren A, Pottgiesser U. The relation between proximity to and characteristics of green spaces to physical activity and health: A multi-dimensional sensitivity analysis in four European cities. ENVIRONMENTAL RESEARCH 2024; 241:117605. [PMID: 37956752 DOI: 10.1016/j.envres.2023.117605] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/28/2023] [Revised: 10/06/2023] [Accepted: 11/04/2023] [Indexed: 11/15/2023]
Abstract
INTRODUCTION Non-communicable diseases are the global disease burden of our time, with physical inactivity identified as one major risk factor. Green spaces are associated with increased physical activity of nearby residents. But there are still gaps in understanding which proximity and what characteristics of green spaces can trigger physical activity. This study aims to unveil these differences with a rigorous sensitivity analysis. METHODS We gathered data on self-reported health and physical activity from 1365 participants in selected neighbourhoods in Porto, Nantes, Sofia, and Høje-Taastrup. Spatial data were retrieved from OpenStreetMap. We followed the PRIGSHARE guidelines to control for bias. Around the residential addresses, we generated seven different green space indicators for 15 distances (100-1500 m) using the AID-PRIGSHARE tool. We then analysed each of these 105 green space indicators together with physical activity and health in 105 adjusted structural equation models. RESULTS Green space accessibility and green space uses indicators showed a pattern of significant positive associations to physical activity and indirect to health at distances of 1100 m or less, with a peak at 600 m for most indicators. Greenness in close proximity (100 m) had significant positive effects on physical activity and indirect effects on health. Surrounding greenness showed positive direct effects on health at 500-1100 m and so do green corridors in 800 m network distance. In contrast, a high quantity of green space uses, and surrounding greenness measured in a larger radius (1100-1500 m) showed a negative relationship with physical activity and indirect health effects. CONCLUSIONS Our results provide insight into how green space characteristics can influence health at different scales, with important implications for urban planners on how to integrate accessible green spaces into urban structures and public health decision-makers on the ability of green spaces to combat physical inactivity.
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Affiliation(s)
- Marcel Cardinali
- Faculty of Architecture and the Built Environment, TU Delft, P.O.Box 5043, 2600, GA, Delft, the Netherlands; Institute for Design Strategies, OWL University of Applied Sciences and Arts, 32756, Detmold, Germany.
| | - Mariëlle A Beenackers
- Department of Public Health, Erasmus MC, University Medical Centre Rotterdam, Rotterdam, the Netherlands
| | - Arjan van Timmeren
- Faculty of Architecture and the Built Environment, TU Delft, P.O.Box 5043, 2600, GA, Delft, the Netherlands
| | - Uta Pottgiesser
- Faculty of Architecture and the Built Environment, TU Delft, P.O.Box 5043, 2600, GA, Delft, the Netherlands; Institute for Design Strategies, OWL University of Applied Sciences and Arts, 32756, Detmold, Germany
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Fullin K, Keen S, Harris K, Magnani JW. Impact of Neighborhood on Cardiovascular Health: A Contemporary Narrative Review. Curr Cardiol Rep 2023; 25:1015-1027. [PMID: 37450260 DOI: 10.1007/s11886-023-01919-1] [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] [Accepted: 07/01/2023] [Indexed: 07/18/2023]
Abstract
PURPOSE OF REVIEW This review summarizes approaches towards neighborhood characterization in relation to cardiovascular health; contemporary investigations relating neighborhood factors to cardiovascular risk and disease; and initiatives to support community-based interventions to address neighborhood-based social determinants related to cardiovascular health. RECENT FINDINGS Neighborhoods may be characterized by Census-derived measures, geospatial data, historical databases, and metrics that incorporate data from electronic medical records and health information exchange databases. Current research has examined neighborhood determinants spanning racial segregation, access to healthcare and food, educational opportunities, physical and built environment, and social environment, and their relations to cardiovascular health and associated outcomes. Community-based interventions have potential to alleviate health disparities but remain limited by implementation challenges. Consideration of neighborhood context is essential in the design of interventions to prevent cardiovascular disease (CVD) and promote health equity. Partnership with community stakeholders may enhance implementation of programs addressing neighborhood-based health determinants.
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Affiliation(s)
- Kerianne Fullin
- Heart and Vascular Institute, University of Pittsburgh Medical Center, Pittsburgh, PA, USA
| | - Susan Keen
- Heart and Vascular Institute, University of Pittsburgh Medical Center, Pittsburgh, PA, USA
| | - Kathryn Harris
- Heart and Vascular Institute, University of Pittsburgh Medical Center, Pittsburgh, PA, USA
| | - Jared W Magnani
- Heart and Vascular Institute, University of Pittsburgh Medical Center, Pittsburgh, PA, USA.
- Center for Research On Health Care, Department of Medicine, University of Pittsburgh, 3609 Forbes Avenue, Second Floor, Pittsburgh, PA, 15213, USA.
- University of Pittsburgh School of Medicine, Pittsburgh, PA, USA.
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Field C, Lynch CD, Fareed N, Joseph JJ, Wu J, Thung SF, Gabbe SG, Landon MB, Grobman WA, Venkatesh KK. Association of community walkability and glycemic control among pregnant individuals with pregestational diabetes mellitus. Am J Obstet Gynecol MFM 2023; 5:100898. [PMID: 36787839 DOI: 10.1016/j.ajogmf.2023.100898] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2023] [Accepted: 01/31/2023] [Indexed: 02/13/2023]
Abstract
BACKGROUND Neighborhood walkability is a community-level social determinant of health that measures whether people who live in a neighborhood walk as a mode of transportation. Whether neighborhood walkability is associated with glycemic control among pregnant individuals with pregestational diabetes remains to be defined. OBJECTIVE This study aimed to evaluate the association between community-level neighborhood walkability and glycemic control as measured by hemoglobin A1c (A1C) among pregnant individuals with pregestational diabetes. STUDY DESIGN This was a retrospective analysis of pregnant individuals with pregestational diabetes enrolled in an integrated prenatal and diabetes care program from 2012 to 2016. Participant addresses were geocoded and linked at the census-tract level. The exposure was community walkability, defined by the US Environmental Protection Agency National Walkability Index (score range 1-20), which incorporates intersection density (design), proximity to transit stops (distance), and a mix of employment and household types (diversity). Individuals from neighborhoods that were the most walkable (score, 15.26-20.0) were compared with those from neighborhoods that were less walkable (score <15.26), as defined per national Environmental Protection Agency recommendations. The outcomes were glycemic control, including A1C <6.0% and <6.5%, measured both in early and late pregnancy, and mean change in A1C across pregnancy. Modified Poisson regression and linear regression were used, respectively, and adjusted for maternal age, body mass index at delivery, parity, race and ethnicity as a social determinant of health, insurance status, baseline A1C, gestational age at A1C measurement in early and late pregnancy, and diabetes type. RESULTS Among 417 pregnant individuals (33% type 1, 67% type 2 diabetes mellitus), 10% were living in the most walkable communities. All 417 individuals underwent A1C assessment in early pregnancy (median gestational age, 9.7 weeks; interquartile range, 7.4-14.1), and 376 underwent another A1C assessment in late pregnancy (median gestational age, 30.4 weeks; interquartile range, 27.8-33.6). Pregnant individuals living in the most walkable communities were more likely to have an A1C <6.0% in early pregnancy (15% vs 8%; adjusted relative risk, 1.46; 95% confidence interval, 1.00-2.16), and an A1C <6.5% in late pregnancy compared with those living in less walkable communities (13% vs 9%; adjusted relative risk, 1.33; 95% confidence interval, 1.08-1.63). For individuals living in the most walkable communities, the median A1C was 7.5 (interquartile range, 6.0-9.4) in early pregnancy and 5.9 (interquartile range, 5.4-6.4) in late pregnancy. For those living in less walkable communities, the median A1C was 7.3 (interquartile range, 6.2-9.2) in early pregnancy and 6.2 (interquartile range, 5.6-7.1) in late pregnancy. Change in A1C across pregnancy was not associated with walkability. CONCLUSION Pregnant individuals with pregestational diabetes mellitus living in more walkable communities had better glycemic control in both early and late pregnancy. Whether community-level interventions to enhance neighborhood walkability can improve glycemic control in pregnancy requires further study.
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Affiliation(s)
- Christine Field
- Division of Maternal Fetal Medicine, Department of Obstetrics and Gynecology, Ohio State University, Columbus, OH (Drs Field and Lynch, Mr Wu, and Drs Thung, Gabbe, Landon, Grobman, and Venkatesh).
| | - Courtney D Lynch
- Division of Maternal Fetal Medicine, Department of Obstetrics and Gynecology, Ohio State University, Columbus, OH (Drs Field and Lynch, Mr Wu, and Drs Thung, Gabbe, Landon, Grobman, and Venkatesh)
| | - Naleef Fareed
- Department of Biomedical Informatics, Ohio State University College of Medicine, Columbus, OH (Dr Fareed)
| | - Joshua J Joseph
- Division of Endocrinology, Diabetes and Metabolism, Department of Internal Medicine, Ohio State University College of Medicine, Columbus, OH (Dr Joseph)
| | - Jiqiang Wu
- Division of Maternal Fetal Medicine, Department of Obstetrics and Gynecology, Ohio State University, Columbus, OH (Drs Field and Lynch, Mr Wu, and Drs Thung, Gabbe, Landon, Grobman, and Venkatesh)
| | - Stephen F Thung
- Division of Maternal Fetal Medicine, Department of Obstetrics and Gynecology, Ohio State University, Columbus, OH (Drs Field and Lynch, Mr Wu, and Drs Thung, Gabbe, Landon, Grobman, and Venkatesh)
| | - Steven G Gabbe
- Division of Maternal Fetal Medicine, Department of Obstetrics and Gynecology, Ohio State University, Columbus, OH (Drs Field and Lynch, Mr Wu, and Drs Thung, Gabbe, Landon, Grobman, and Venkatesh)
| | - Mark B Landon
- Division of Maternal Fetal Medicine, Department of Obstetrics and Gynecology, Ohio State University, Columbus, OH (Drs Field and Lynch, Mr Wu, and Drs Thung, Gabbe, Landon, Grobman, and Venkatesh)
| | - William A Grobman
- Division of Maternal Fetal Medicine, Department of Obstetrics and Gynecology, Ohio State University, Columbus, OH (Drs Field and Lynch, Mr Wu, and Drs Thung, Gabbe, Landon, Grobman, and Venkatesh)
| | - Kartik K Venkatesh
- Division of Maternal Fetal Medicine, Department of Obstetrics and Gynecology, Ohio State University, Columbus, OH (Drs Field and Lynch, Mr Wu, and Drs Thung, Gabbe, Landon, Grobman, and Venkatesh)
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