Natália Cecília de França , Guaracyane Lima Campêlo , João Mário Santos de França , Eleydiane Gomes Vale , Thaísa França Badagnan
{"title":"对巴西第一波感染期间与COVID-19诊断和相关症状相关的健康状况的社会经济不平等进行分解分析","authors":"Natália Cecília de França , Guaracyane Lima Campêlo , João Mário Santos de França , Eleydiane Gomes Vale , Thaísa França Badagnan","doi":"10.1016/j.econ.2021.09.002","DOIUrl":null,"url":null,"abstract":"<div><p>Recent studies have shown that COVID-19 affects different population groups asymmetrically. This work uses data from the National Survey of Households—PNAD COVID-19/IBGE—to quantify the socioeconomic inequality in health during the first wave of COVID-19 infections in Brazil. We use the concentration curve, the concentration index, and a decomposition analysis to verify the factors that most influence the inequalities in the specified health variables. We find a positive concentration index for the incidence rate, indicating a greater concentration of diagnoses (number of tests) among groups with higher income levels. When considering symptoms similar to a COVID-19 infection, inequality practically disappears. Among people with higher income, a pre-existing disease has a more significant contribution to the concentration of COVID-19 in the presence of correlated symptoms than in its diagnosis. Tests of dominance support the findings. Moreover, the decomposition results show that if the inequalities were explained only by race (non-white) and place of living (North and Northeast), there would be a concentration of COVID-19 among the poorest.</p></div>","PeriodicalId":100389,"journal":{"name":"EconomiA","volume":"22 3","pages":"Pages 251-264"},"PeriodicalIF":0.0000,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1517758021000163/pdfft?md5=1bb4525747fa6d9d6339eb99180fb94a&pid=1-s2.0-S1517758021000163-main.pdf","citationCount":"1","resultStr":"{\"title\":\"A decomposition analysis for socioeconomic inequalities in health status associated with the COVID-19 diagnosis and related symptoms during Brazil's first wave of infections\",\"authors\":\"Natália Cecília de França , Guaracyane Lima Campêlo , João Mário Santos de França , Eleydiane Gomes Vale , Thaísa França Badagnan\",\"doi\":\"10.1016/j.econ.2021.09.002\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Recent studies have shown that COVID-19 affects different population groups asymmetrically. This work uses data from the National Survey of Households—PNAD COVID-19/IBGE—to quantify the socioeconomic inequality in health during the first wave of COVID-19 infections in Brazil. We use the concentration curve, the concentration index, and a decomposition analysis to verify the factors that most influence the inequalities in the specified health variables. We find a positive concentration index for the incidence rate, indicating a greater concentration of diagnoses (number of tests) among groups with higher income levels. When considering symptoms similar to a COVID-19 infection, inequality practically disappears. Among people with higher income, a pre-existing disease has a more significant contribution to the concentration of COVID-19 in the presence of correlated symptoms than in its diagnosis. Tests of dominance support the findings. Moreover, the decomposition results show that if the inequalities were explained only by race (non-white) and place of living (North and Northeast), there would be a concentration of COVID-19 among the poorest.</p></div>\",\"PeriodicalId\":100389,\"journal\":{\"name\":\"EconomiA\",\"volume\":\"22 3\",\"pages\":\"Pages 251-264\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S1517758021000163/pdfft?md5=1bb4525747fa6d9d6339eb99180fb94a&pid=1-s2.0-S1517758021000163-main.pdf\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"EconomiA\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1517758021000163\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"EconomiA","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1517758021000163","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A decomposition analysis for socioeconomic inequalities in health status associated with the COVID-19 diagnosis and related symptoms during Brazil's first wave of infections
Recent studies have shown that COVID-19 affects different population groups asymmetrically. This work uses data from the National Survey of Households—PNAD COVID-19/IBGE—to quantify the socioeconomic inequality in health during the first wave of COVID-19 infections in Brazil. We use the concentration curve, the concentration index, and a decomposition analysis to verify the factors that most influence the inequalities in the specified health variables. We find a positive concentration index for the incidence rate, indicating a greater concentration of diagnoses (number of tests) among groups with higher income levels. When considering symptoms similar to a COVID-19 infection, inequality practically disappears. Among people with higher income, a pre-existing disease has a more significant contribution to the concentration of COVID-19 in the presence of correlated symptoms than in its diagnosis. Tests of dominance support the findings. Moreover, the decomposition results show that if the inequalities were explained only by race (non-white) and place of living (North and Northeast), there would be a concentration of COVID-19 among the poorest.