Peter T Baltrus, Chaohua Li, Megan Douglas, Robina Josiah Willock, Ashley Daniel, Dominic Mack, Anne H Gaglioti
{"title":"COVID-19 大流行初期的邻里生态、病例和死亡人数:对当前和未来流行病的启示?","authors":"Peter T Baltrus, Chaohua Li, Megan Douglas, Robina Josiah Willock, Ashley Daniel, Dominic Mack, Anne H Gaglioti","doi":"10.14423/SMJ.0000000000001757","DOIUrl":null,"url":null,"abstract":"<p><strong>Objectives: </strong>The coronavirus disease 2019 (COVID-19) pandemic has disproportionately affected Black and Latinx communities. Ecologic analyses have shown that counties with a higher percentage of Latinx and Black people have worse COVID-19 outcome rates. Few ecologic analyses have been published at the neighborhood (census tract) level. We sought to determine whether certain sociodemographic neighborhood ecologies were associated with COVID-19 case and death rates in metropolitan Atlanta, Georgia.</p><p><strong>Methods: </strong>We used census data and principal-component analysis to identify unique neighborhood ecologies. We then estimated correlation coefficients to determine whether the neighborhood profiles produced by a principal-component analysis were correlated with COVID-19 case and death rates. We conducted geographically weighted regression models to assess how correlation coefficients varied spatially for neighborhood ecologies and COVID-19 outcomes.</p><p><strong>Results: </strong>We identified two unique neighborhood profiles: (1) high percentage of residents, Hispanic ethnicity, without a high school diploma, without health insurance, living in crowded households, and lower percentage older than 65 years; and (2) high percentage of residents, Black race, living in poverty, unemployed, and households receiving Supplemental Nutrition Assistance Program benefits. Profile 1 was associated with COVID-19 case rate (Pearson <i>r</i> = 0.462, <i>P</i> < 0.001) and profile 2 was associated with COVID-19 death rate (Spearman <i>r</i> = 0.279, <i>P</i> < 0.001). Correlations between neighborhood profiles and COVID-19 outcomes varied spatially.</p><p><strong>Conclusions: </strong>Neighborhoods were differentially at risk of COVID-19 cases or deaths depending on their sociodemographic ecology at the beginning of the COVID-19 pandemic. Prevention methods and interventions may need to consider different social determinants of health when addressing potential cases and deaths during future emergent epidemics.</p>","PeriodicalId":22043,"journal":{"name":"Southern Medical Journal","volume":"117 11","pages":"640-645"},"PeriodicalIF":1.0000,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11534281/pdf/","citationCount":"0","resultStr":"{\"title\":\"Neighborhood Ecologies, Cases, and Deaths during the Beginning of the COVID-19 Pandemic: Lessons for Current and Future Epidemics?\",\"authors\":\"Peter T Baltrus, Chaohua Li, Megan Douglas, Robina Josiah Willock, Ashley Daniel, Dominic Mack, Anne H Gaglioti\",\"doi\":\"10.14423/SMJ.0000000000001757\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Objectives: </strong>The coronavirus disease 2019 (COVID-19) pandemic has disproportionately affected Black and Latinx communities. Ecologic analyses have shown that counties with a higher percentage of Latinx and Black people have worse COVID-19 outcome rates. Few ecologic analyses have been published at the neighborhood (census tract) level. We sought to determine whether certain sociodemographic neighborhood ecologies were associated with COVID-19 case and death rates in metropolitan Atlanta, Georgia.</p><p><strong>Methods: </strong>We used census data and principal-component analysis to identify unique neighborhood ecologies. We then estimated correlation coefficients to determine whether the neighborhood profiles produced by a principal-component analysis were correlated with COVID-19 case and death rates. We conducted geographically weighted regression models to assess how correlation coefficients varied spatially for neighborhood ecologies and COVID-19 outcomes.</p><p><strong>Results: </strong>We identified two unique neighborhood profiles: (1) high percentage of residents, Hispanic ethnicity, without a high school diploma, without health insurance, living in crowded households, and lower percentage older than 65 years; and (2) high percentage of residents, Black race, living in poverty, unemployed, and households receiving Supplemental Nutrition Assistance Program benefits. Profile 1 was associated with COVID-19 case rate (Pearson <i>r</i> = 0.462, <i>P</i> < 0.001) and profile 2 was associated with COVID-19 death rate (Spearman <i>r</i> = 0.279, <i>P</i> < 0.001). Correlations between neighborhood profiles and COVID-19 outcomes varied spatially.</p><p><strong>Conclusions: </strong>Neighborhoods were differentially at risk of COVID-19 cases or deaths depending on their sociodemographic ecology at the beginning of the COVID-19 pandemic. Prevention methods and interventions may need to consider different social determinants of health when addressing potential cases and deaths during future emergent epidemics.</p>\",\"PeriodicalId\":22043,\"journal\":{\"name\":\"Southern Medical Journal\",\"volume\":\"117 11\",\"pages\":\"640-645\"},\"PeriodicalIF\":1.0000,\"publicationDate\":\"2024-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11534281/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Southern Medical Journal\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.14423/SMJ.0000000000001757\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"MEDICINE, GENERAL & INTERNAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Southern Medical Journal","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.14423/SMJ.0000000000001757","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"MEDICINE, GENERAL & INTERNAL","Score":null,"Total":0}
Neighborhood Ecologies, Cases, and Deaths during the Beginning of the COVID-19 Pandemic: Lessons for Current and Future Epidemics?
Objectives: The coronavirus disease 2019 (COVID-19) pandemic has disproportionately affected Black and Latinx communities. Ecologic analyses have shown that counties with a higher percentage of Latinx and Black people have worse COVID-19 outcome rates. Few ecologic analyses have been published at the neighborhood (census tract) level. We sought to determine whether certain sociodemographic neighborhood ecologies were associated with COVID-19 case and death rates in metropolitan Atlanta, Georgia.
Methods: We used census data and principal-component analysis to identify unique neighborhood ecologies. We then estimated correlation coefficients to determine whether the neighborhood profiles produced by a principal-component analysis were correlated with COVID-19 case and death rates. We conducted geographically weighted regression models to assess how correlation coefficients varied spatially for neighborhood ecologies and COVID-19 outcomes.
Results: We identified two unique neighborhood profiles: (1) high percentage of residents, Hispanic ethnicity, without a high school diploma, without health insurance, living in crowded households, and lower percentage older than 65 years; and (2) high percentage of residents, Black race, living in poverty, unemployed, and households receiving Supplemental Nutrition Assistance Program benefits. Profile 1 was associated with COVID-19 case rate (Pearson r = 0.462, P < 0.001) and profile 2 was associated with COVID-19 death rate (Spearman r = 0.279, P < 0.001). Correlations between neighborhood profiles and COVID-19 outcomes varied spatially.
Conclusions: Neighborhoods were differentially at risk of COVID-19 cases or deaths depending on their sociodemographic ecology at the beginning of the COVID-19 pandemic. Prevention methods and interventions may need to consider different social determinants of health when addressing potential cases and deaths during future emergent epidemics.
期刊介绍:
As the official journal of the Birmingham, Alabama-based Southern Medical Association (SMA), the Southern Medical Journal (SMJ) has for more than 100 years provided the latest clinical information in areas that affect patients'' daily lives. Now delivered to individuals exclusively online, the SMJ has a multidisciplinary focus that covers a broad range of topics relevant to physicians and other healthcare specialists in all relevant aspects of the profession, including medicine and medical specialties, surgery and surgery specialties; child and maternal health; mental health; emergency and disaster medicine; public health and environmental medicine; bioethics and medical education; and quality health care, patient safety, and best practices. Each month, articles span the spectrum of medical topics, providing timely, up-to-the-minute information for both primary care physicians and specialists. Contributors include leaders in the healthcare field from across the country and around the world. The SMJ enables physicians to provide the best possible care to patients in this age of rapidly changing modern medicine.