Journal of Urban Health-Bulletin of the New York Academy of Medicine最新文献

{"title":"The Relationship between Noise Pollution and Depression and Implications for Healthy Aging: A Spatial Analysis Using Routinely Collected Primary Care Data.","authors":"Dialechti Tsimpida, Anastasia Tsakiridi","doi":"10.1007/s11524-024-00945-w","DOIUrl":"10.1007/s11524-024-00945-w","url":null,"abstract":"<p><p>Environmental noise is a significant public health concern, ranking among the top environmental risks to citizens' health and quality of life. Despite extensive research on atmospheric pollution's impact on mental health, spatial studies on noise pollution effects are lacking. This study fills this gap by exploring the association between noise pollution and depression in England, with a focus on localised patterns based on area deprivation. Depression prevalence, defined as the percentage of patients with a recorded depression diagnosis, was calculated for small areas within Cheshire and Merseyside ICS using the Quality and Outcomes Framework Indicators dataset for 2019. Strategic noise mapping for rail and road noise (Lden) was used to measure 24-h annual average noise levels, with adjustments for evening and night periods. The English Index of Multiple Deprivation (IMD) was employed to represent neighborhood deprivation. Geographically weighted regression and generalised structural equation spatial modeling (GSESM) assessed the relationships between transportation noise, depression prevalence, and IMD at the Lower Super Output Area level. The study found that while transportation noise had a low direct effect on depression levels, it significantly mediated other factors associated with depression. Notably, GSESM showed that health deprivation and disability were strongly linked (0.62) to depression through the indirect effect of noise, especially where transportation noise exceeds 55 dB on a 24-h basis. Understanding these variations is crucial for developing noise mitigation strategies. This research offers new insights into noise, deprivation, and mental health, supporting targeted interventions to improve quality of life and address health inequalities.</p>","PeriodicalId":49964,"journal":{"name":"Journal of Urban Health-Bulletin of the New York Academy of Medicine","volume":" ","pages":"101-112"},"PeriodicalIF":4.3,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11865392/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142985245","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Effect of Perceived Neighborhood Environment on Cannabis Use during Pregnancy among African American Women.","authors":"Ban Al-Sahab, Cassandra LaMarche, Xiaoyu Liang, Rhonda Dailey, Dawn P Misra","doi":"10.1007/s11524-024-00958-5","DOIUrl":"10.1007/s11524-024-00958-5","url":null,"abstract":"<p><p>Environmental context is an important predictor of health behavior. Understanding its effect on cannabis use among pregnant women is yet to be understood. The aim of the study is to assess the impact of perceived neighborhood environment on prenatal cannabis use and explore the mediating role of stress. Data are from the Life-Course Influences on Fetal Environments Study (LIFE), a retrospective cohort of postpartum African American women in Metropolitan Detroit, Michigan (2009-2011). Prenatal cannabis use was defined as self-reported ever use during pregnancy. Three perceived neighborhood scales were considered: social cohesion and trust, social disorder, and danger and safety. Out of 1,369 women, 151 (11.0%) self-reported using cannabis during pregnancy. After adjusting for age, marital status, income, years of education, and general social support scale, the odds of cannabis use significantly increased among the lowest quartiles of all the neighborhood scales suggesting higher cannabis use among women who perceived their neighborhoods to have the worst conditions. Compared to the highest quartile, the odds ratio (OR) for the lowest quartiles for social cohesion and trust, social disorder, and danger and safety were 1.77 (95% confidence interval (CI): 1.04-3.03), 1.83 (95% CI: 1.15-2.91), and 1.93 (95% CI: 1.12-3.31) respectively. Evidence of mediation by perceived stress was only present between the association of perceived levels of safety and danger with cannabis use during pregnancy. Future prospective studies are warranted to understand the causal associations between individual correlates and social and physical environmental factors of prenatal cannabis use.</p>","PeriodicalId":49964,"journal":{"name":"Journal of Urban Health-Bulletin of the New York Academy of Medicine","volume":" ","pages":"139-151"},"PeriodicalIF":4.3,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11865413/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143015154","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Historical Redlining and Community-Reported Housing Quality: A Spatial Analysis.","authors":"Salvatore Milletich, Andres Manrique, Sonia Karsan, Tamara Spikes, Anuj Nanavanti, Jared Bailey, Eric Coker, Christine C Ekenga","doi":"10.1007/s11524-024-00935-y","DOIUrl":"10.1007/s11524-024-00935-y","url":null,"abstract":"<p><p>Historical redlining, a racially discriminatory practice implemented by the US government in the 1930s, has been associated with present-day environmental outcomes. However, there is limited research examining the relationship between historical redlining and contemporary housing quality. The objective of the present study was to investigate the relationship between historical redlining and contemporary housing quality in Atlanta, Georgia. Spatial patterns of housing code violation complaints from 2015 to 2019 were examined using point-pattern and spatial cluster analyses. We used Bayesian hierarchical models, accounting for spatial autocorrelation, to estimate associations between historical redlining and housing complaints, after adjusting for contemporary neighborhood characteristics, such as poverty, median structure age, vacant and renter-occupied properties, and residential racial segregation. A total of 48,626 housing code violation complaints were reported during the study period, including 6531 complaints deemed \"hazardous.\" Historical redlining was a statistically significant predictor of housing complaints. We observed a 167% increased risk (IRR = 2.67, 95% confidence interval = 1.49, 4.77) of housing complaints for historically redlined neighborhoods compared to neighborhoods historically graded as \"best\" or \"still desirable,\" after adjusting for neighborhood characteristics. Redlined neighborhoods also had an increased risk of \"hazardous\" housing complaints (IRR = 1.94, 95% confidence interval = 1.11, 3.40), after adjusting for contemporary neighborhood characteristics. Historically redlined neighborhoods exhibited disproportionately higher rates of housing code violation complaints. Spatial analysis of housing code violation complaints can provide insights into housing quality and inform interventions targeted at addressing the environmental legacy of structural racism.</p>","PeriodicalId":49964,"journal":{"name":"Journal of Urban Health-Bulletin of the New York Academy of Medicine","volume":" ","pages":"49-60"},"PeriodicalIF":4.3,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11865398/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142957994","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Analyzing and Optimizing the Distribution of Blood Lead Level Testing for Children in New York City: A Data-Driven Approach.","authors":"Khalifa Afane, Juntao Chen","doi":"10.1007/s11524-024-00920-5","DOIUrl":"10.1007/s11524-024-00920-5","url":null,"abstract":"<p><p>This study investigates blood lead level (BLL) rates and testing among children under 6 years of age across the 42 neighborhoods in New York City from 2005 to 2021. Despite a citywide general decline in BLL rates, disparities at the neighborhood level persist and are not addressed in the official reports, highlighting the need for this comprehensive analysis. In this paper, we analyze the current BLL testing distribution and cluster the neighborhoods using a k-medoids clustering algorithm. We propose an optimized approach that improves resource allocation efficiency by accounting for case incidences and neighborhood risk profiles using a grid search algorithm. Our findings demonstrate statistically significant improvements in case detection and enhanced fairness by focusing on under-served and high-risk groups. Additionally, we propose actionable recommendations to raise awareness among parents, including outreach at local daycare centers and kindergartens, among other venues.</p>","PeriodicalId":49964,"journal":{"name":"Journal of Urban Health-Bulletin of the New York Academy of Medicine","volume":" ","pages":"92-100"},"PeriodicalIF":4.3,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11865405/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142394812","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Association of Involuntary Displacement of People Experiencing Homelessness and Crime in Denver, CO: A Spatiotemporal Analysis.","authors":"Pranav Padmanabhan, Cole Jurecka, Samantha K Nall, Jesse L Goldshear, Joshua A Barocas","doi":"10.1007/s11524-024-00924-1","DOIUrl":"10.1007/s11524-024-00924-1","url":null,"abstract":"<p><p>In 2022, approximately 580,000 people experienced homelessness in the United States. In response, many cities have implemented \"camping ban\" policies enforced by involuntary displacement of homeless encampments. Displacement has been cited as a strategy to protect public health and safety. However, there is mixed evidence that displacement is effective in reducing crime, while it is associated with other adverse health outcomes. To evaluate the neighborhood-level association between displacement and crime, we performed a retrospective (November 2019 to July 2023) pre-post spatiotemporal analysis using administrative data from Denver, CO. We used the Knox test statistic to detect excess clustering and change in total crime, as well as crime stratified by the National Incident-Based Reporting System (NIBRS) category, within spatiotemporal proximity to displacement events. We found that, on average, clustering of crime is high both before and after displacement. Within a 0.25-mile radius, displacement is associated with a statistically significant but modest decrease in crime, between - 9.3% within 7 days (p < 0.001) and - 3.9% within 21 days (p = 0.002). We found no consistent change in composite crime at a 0.5- or 0.75-mile radius. Hyperlocal decreases were driven by significant decreases in public disorder and auto theft, while crimes against persons increased and displayed high clustering post-displacement. There were no changes in any other offense type. Involuntary displacement is not consistently associated with changes in clustering of crime and may exacerbate violence in nearby areas.</p>","PeriodicalId":49964,"journal":{"name":"Journal of Urban Health-Bulletin of the New York Academy of Medicine","volume":" ","pages":"8-18"},"PeriodicalIF":4.3,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11865378/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142479269","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Expanded Naloxone Distribution by Opioid Overdose Prevention Programs to High-Need Populations and Neighborhoods in New York City.","authors":"Czarina N Behrends, Andrew J Trinidad, Michelle L Nolan, Jennifer Dolatshahi, Alexandra Kingsepp, Ashly E Jordan, Alice E Welch, Alex Harocopos, Leah C Shaw, Traci C Green, Brandon D L Marshall, Bruce R Schackman","doi":"10.1007/s11524-024-00951-y","DOIUrl":"https://doi.org/10.1007/s11524-024-00951-y","url":null,"abstract":"<p><p>From 2014 to 2017, the drug overdose death rate per 100,000 in New York City (NYC) increased by 81%, with 57% of overdoses in 2017 involving the opioid fentanyl. In response, overdose education and naloxone dispensing (OEND) efforts were expanded in NYC, informed by neighborhood-level and population-level opioid overdose fatality rates. We describe the demographic and geographical distribution of naloxone by NYC opioid overdose prevention programs (OOPPs; the primary distributor of naloxone to laypersons in NYC) as OEND was expanded in NYC. We developed and examined a measure of high-need naloxone distribution defined by OEND in a high-priority neighborhood, to a high-need population, or from a high-priority OOPP (i.e., syringe services programs, criminal legal-related programs, programs for unhoused people, substance use disorder treatment programs, etc.). We reported recipient-level naloxone dispensing data by OOPP type from April 2018 to March 2019 using descriptive statistics and age-adjusted population rates. We conducted univariable logistic regression analyses to identify predictors of naloxone receipt by race/ethnicity. Of the 69,333 naloxone recipients, 97.3% met our definition for high-need naloxone dispensing, with 55.8% residing in one of 13 high-priority neighborhoods. Naloxone receipt by race/ethnicity varied by OOPP type. Program goals to expand naloxone distribution to high-need populations were met. We observed racial/ethnic differences in receipt of naloxone by program type, which supports using a variety of OOPP program types to reach racially diverse populations.</p>","PeriodicalId":49964,"journal":{"name":"Journal of Urban Health-Bulletin of the New York Academy of Medicine","volume":" ","pages":""},"PeriodicalIF":4.3,"publicationDate":"2025-01-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143015156","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Social Vulnerability and Biological Aging in New York City: An Electronic Health Records-Based Study.","authors":"Pablo Knobel, Elena Colicino, Itai Kloog, Rachel Litke, Kevin Lane, Alex Federman, Charles Mobbs, Maayan Yitshak Sade","doi":"10.1007/s11524-024-00948-7","DOIUrl":"10.1007/s11524-024-00948-7","url":null,"abstract":"<p><p>Chronological age is not an accurate predictor of morbidity and mortality risk, as individuals' aging processes are diverse. Phenotypic age acceleration (PhenoAgeAccel) is a validated biological age measure incorporating chronological age and biomarkers from blood samples commonly used in clinical practice that can better reflect aging-related morbidity and mortality risk. The heterogeneity of age-related decline is not random, as environmental exposures can promote or impede healthy aging. Social Vulnerability Index (SVI) is a composite index accounting for different facets of the social, economic, and demographic environment grouped into four themes: socioeconomic status, household composition and disability, minority status and language, and housing and transportation. We aim to assess the concurrent and combined associations of the four SVI themes on PhenoAgeAccel and the differential effects on disadvantaged groups. We use electronic health records data from 31,913 patients from the Mount Sinai Health System (116,952 person-years) and calculate PhenoAge for years with available laboratory results (2011-2022). PhenoAge is calculated as a weighted linear combination of lab results, and PhenoAgeAccel is the differential between PhenoAge and chronological age. A decile increase in the mixture of SVI dimensions was associated with an increase of 0.23 years (95% CI 0.21, 0.25) in PhenoAgeAccel. The socioeconomic status dimension was the main driver of the association, accounting for 61% of the weight. Interaction models revealed a more substantial detrimental association for women and racial and ethnic minorities with differences in leading SVI themes. These findings suggest that neighborhood-level social vulnerability increases the biological age of its residents, increasing morbidity and mortality risks. Socioeconomic status has the larger detrimental role among the different facets of social environment.</p>","PeriodicalId":49964,"journal":{"name":"Journal of Urban Health-Bulletin of the New York Academy of Medicine","volume":" ","pages":""},"PeriodicalIF":4.3,"publicationDate":"2025-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142985237","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Is Income and Racial Residential Segregation Associated with 13-Year Changes in Body Mass Index? A Longitudinal Analysis in the Brazilian Pró-Saúde Cohort Study.","authors":"Joanna M N Guimarães, Ana Paula Vasconcelos, Marcelo Cunha, Eduardo Faerstein","doi":"10.1007/s11524-024-00949-6","DOIUrl":"https://doi.org/10.1007/s11524-024-00949-6","url":null,"abstract":"<p><p>Neighborhoods or residential environments have physical and social attributes which may contribute to inequalities in the overweight and obesity pandemic. We examined the longitudinal associations of baseline neighborhood-level income and racial residential segregation (using the Gi* statistic: low, medium, high) with changes in body mass index (BMI in kg/m²), using geocoded data from 1821 civil servants in the municipality of Rio de Janeiro, Brazil, followed-up for approximately 13 years (baseline wave 1: 1999, wave 2: 2001-2002, wave 3: 2006-2007, wave 4: 2012-2013). Linear mixed effects models using BMI measured in all four study waves were performed, accounting for gender, race, length of residence, education and time-dependent age, and per capita family income. After adjustments, both income and racial segregation were positively associated with BMI differences (but not BMI changes) over time, in a dose-response pattern. For income segregation, mean differences in BMI for participants living in high and medium vs. low segregated neighborhoods were 1.04 kg/m² (β = 1.04; 95% CI 0.47, 1.62) and 0.86 kg/m² (0.86; 0.33, 1.39), respectively. For racial segregation, mean differences in BMI for participants living in high and medium vs low segregated neighborhoods were 0.71 kg/m² (0.71; 0.14, 1.29) and 0.30 kg/m² (0.30; - 0.24, 0.83), respectively. We also showed a moderate to strong correlation between racial and income segregation at baseline. Strategies to reduce BMI and obesity-related health inequalities should include special efforts aimed at segregated neighborhoods and its obesogenic environments.</p>","PeriodicalId":49964,"journal":{"name":"Journal of Urban Health-Bulletin of the New York Academy of Medicine","volume":" ","pages":""},"PeriodicalIF":4.3,"publicationDate":"2025-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142933296","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Neighborhood Factors as Correlates of Alcohol Use in the N2 Cohort Study of Black Sexually Minoritized Men and Transgender Women.","authors":"Tyrone Moline, Dustin T Duncan, Justin Knox, Seann Regan, Christina A Mehranbod, Cho-Hee Shrader, John A Schneider, Byoungjun Kim","doi":"10.1007/s11524-024-00942-z","DOIUrl":"10.1007/s11524-024-00942-z","url":null,"abstract":"<p><p>Sexually minoritized men (SMM), transgender women (TW), and particularly Black SMM and Black TW may be disproportionately impacted by alcohol-related problems. Few studies have empirically examined neighborhood factors that may contribute to alcohol use, specifically among these populations. Using data from the N2 longitudinal cohort study in Chicago, IL, survey data from the second wave of longitudinal assessment (n = 126) and GPS mobility data from enrollment were used to evaluate neighborhood alcohol outlet availability, neighborhood disorder, and neighborhood poverty as correlates of individual alcohol use. Neighborhood exposures were measured using 200-m-derived activity space areas, created from GPS data, using publicly accessible geospatial contextual data. Separate multivariable quasi-poison regression models tested for association between neighborhood alcohol outlet density (AOD), measured separately for on-premise (e.g., bars) and off-premise consumption outlets (e.g., liquor stores), neighborhood poverty (defined as the percentage of neighborhood areas at 150% or greater of the US poverty line), exposure to vacant buildings, and neighborhood violent crime density. Separate analytical models found no significant effect between alcohol use and exposure to on-premise consumption venue AOD (risk ratio (RR) = 0.99, p = 0.57), off-premise consumption AOD (RR = 0.94, p = 0.56), neighborhood poverty (RR = 1.04, p = 0.07), or neighborhood violent crime (RR = 1.00, p = 0.94). Exposure to higher levels of vacant buildings (RR = 1.03, p = 0.04) was found to be significantly associated with increased alcohol use. Among this population, opposed to geospatial access, neighborhood measurements indicative of disorder may have a greater influence on shaping alcohol use.</p>","PeriodicalId":49964,"journal":{"name":"Journal of Urban Health-Bulletin of the New York Academy of Medicine","volume":" ","pages":""},"PeriodicalIF":4.3,"publicationDate":"2024-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142865802","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Drug Overdose Death among Residents of Urban Census Tracts: How Granular Geographical Analyses Uncover Socioenvironmental Correlates in Cuyahoga County, Ohio.","authors":"Ryan McMaster, Luma Masarweh-Zawahri, Karen Coen Flynn, Vaishali S Deo, Daniel J Flannery","doi":"10.1007/s11524-024-00939-8","DOIUrl":"https://doi.org/10.1007/s11524-024-00939-8","url":null,"abstract":"<p><p>Geostatistical data aggregated at state, county, municipality, or ZIP code levels often are utilized for assessing drug overdose epidemic impact and planning resource distribution. Data aggregated at these levels may obscure critical disparities among populations experiencing high rates of drug-related mortality (DRM), especially in densely populated urban areas. Our research was centered on Cuyahoga County (Cleveland), OH, which ranks 15th in the USA for drug-related mortality. This study built on recent efforts that adopted a finer geographical lens by examining DRM rates at the census tract level. Our investigation used Cuyahoga County census tracts with high and low DRM rates and compared them with Cuyahoga County census tracts with high and low levels of opportunity as developed by a publicly available, statewide opportunity index. Analyzing DRM data from 2014 to 2022, we found that the odds of an individual experiencing DRM in low-opportunity areas were quadruple the odds for someone in high-opportunity zones. Our findings highlight the critical need for more granular geographic analysis in urban areas, where heterogenous socioenvironmental conditions appear to correlate with significant heterogeneity in the ways in which residents experience the risk of dying from a drug overdose. By focusing on smaller areas, this approach provides a clearer understanding of the DRM landscape that could facilitate the prioritization of more targeted, culturally centered, public health interventions.</p>","PeriodicalId":49964,"journal":{"name":"Journal of Urban Health-Bulletin of the New York Academy of Medicine","volume":" ","pages":""},"PeriodicalIF":4.3,"publicationDate":"2024-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142774213","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}