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 concentratio...
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Autor*in:	França, Natália Cecília de [verfasserIn] Lima Campêlo, Guaracyane [verfasserIn] França, João Mário Santos de [verfasserIn] Vale, Eleydiane Maria Gomes [verfasserIn] Badagnan, Thaísa França [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2021

Rechteinformationen:	Open Access Namensnennung - Nicht kommerziell - Keine Bearbeitungen 4.0 International ; CC BY-NC-ND 4.0

Schlagwörter:	COVID-19 Decomposition analysis Health inequality Pre-existing disease Socioeconomic factors

Übergeordnetes Werk:	Enthalten in: Economia - Bingley, United Kingdom : Emerald, 2000, 22(2021), 3 vom: Dez., Seite 251-264
Übergeordnetes Werk:	volume:22 ; year:2021 ; number:3 ; month:12 ; pages:251-264

Links:	Link aufrufen Link aufrufen Link aufrufen

DOI / URN:	10.1016/j.econ.2021.09.002

Katalog-ID:	1796235393

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allfields	10.1016/j.econ.2021.09.002 doi 10419/266984 hdl (DE-627)1796235393 (DE-599)KXP1796235393 DE-627 ger DE-627 rda eng D31 I14 I18 jelc França, Natália Cecília de verfasserin (DE-588)1256767905 (DE-627)1800848439 aut 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 Natália Cecília de França, Guaracyane Lima Campêlo, João Mário Santos de França, Eleydiane Gomes Vale, Thaísa França Badagnan 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier DE-206 Open Access Controlled Vocabulary for Access Rights http://purl.org/coar/access_right/c_abf2 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. DE-206 Namensnennung - Nicht kommerziell - Keine Bearbeitungen 4.0 International CC BY-NC-ND 4.0 cc https://creativecommons.org/licenses/by-nc-nd/4.0/ COVID-19 (dpeaa)DE-206 Decomposition analysis (dpeaa)DE-206 Health inequality (dpeaa)DE-206 Pre-existing disease (dpeaa)DE-206 Socioeconomic factors (dpeaa)DE-206 Lima Campêlo, Guaracyane verfasserin (DE-588)116297592X (DE-627)1027073603 (DE-576)507725158 aut França, João Mário Santos de verfasserin (DE-588)142321036 (DE-627)635121549 (DE-576)330104748 aut Vale, Eleydiane Maria Gomes verfasserin (DE-588)115496857X (DE-627)1016282184 (DE-576)501343237 aut Badagnan, Thaísa França verfasserin aut Enthalten in Economia Bingley, United Kingdom : Emerald, 2000 22(2021), 3 vom: Dez., Seite 251-264 Online-Ressource (DE-627)578536218 (DE-600)2451788-4 (DE-576)286025949 2358-2820 nnns volume:22 year:2021 number:3 month:12 pages:251-264 https://www.sciencedirect.com/science/article/pii/S1517758021000163/pdfft?md5=1bb4525747fa6d9d6339eb99180fb94a&pid=1-s2.0-S1517758021000163-main.pdf Verlag kostenfrei https://doi.org/10.1016/j.econ.2021.09.002 Resolving-System kostenfrei http://hdl.handle.net/10419/266984 Resolving-System kostenfrei GBV_USEFLAG_U GBV_ILN_26 ISIL_DE-206 SYSFLAG_1 GBV_KXP SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_138 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_647 GBV_ILN_702 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 GBV_ILN_2403 GBV_ILN_2403 ISIL_DE-LFER AR 22 2021 3 12 251-264 26 01 0206 4097316354 x1z 22-03-22 2403 01 DE-LFER 4113025886 00 --%%-- --%%-- n --%%-- l01 07-04-22 2403 01 DE-LFER https://doi.org/10.1016/j.econ.2021.09.002 2403 01 DE-LFER https://www.sciencedirect.com/science/article/pii/S1517758021000163/pdfft?md5=1bb4525747fa6d9d6339eb99180fb94a&pid=1-s2.0-S1517758021000163-main.pdf
spelling	10.1016/j.econ.2021.09.002 doi 10419/266984 hdl (DE-627)1796235393 (DE-599)KXP1796235393 DE-627 ger DE-627 rda eng D31 I14 I18 jelc França, Natália Cecília de verfasserin (DE-588)1256767905 (DE-627)1800848439 aut 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 Natália Cecília de França, Guaracyane Lima Campêlo, João Mário Santos de França, Eleydiane Gomes Vale, Thaísa França Badagnan 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier DE-206 Open Access Controlled Vocabulary for Access Rights http://purl.org/coar/access_right/c_abf2 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. DE-206 Namensnennung - Nicht kommerziell - Keine Bearbeitungen 4.0 International CC BY-NC-ND 4.0 cc https://creativecommons.org/licenses/by-nc-nd/4.0/ COVID-19 (dpeaa)DE-206 Decomposition analysis (dpeaa)DE-206 Health inequality (dpeaa)DE-206 Pre-existing disease (dpeaa)DE-206 Socioeconomic factors (dpeaa)DE-206 Lima Campêlo, Guaracyane verfasserin (DE-588)116297592X (DE-627)1027073603 (DE-576)507725158 aut França, João Mário Santos de verfasserin (DE-588)142321036 (DE-627)635121549 (DE-576)330104748 aut Vale, Eleydiane Maria Gomes verfasserin (DE-588)115496857X (DE-627)1016282184 (DE-576)501343237 aut Badagnan, Thaísa França verfasserin aut Enthalten in Economia Bingley, United Kingdom : Emerald, 2000 22(2021), 3 vom: Dez., Seite 251-264 Online-Ressource (DE-627)578536218 (DE-600)2451788-4 (DE-576)286025949 2358-2820 nnns volume:22 year:2021 number:3 month:12 pages:251-264 https://www.sciencedirect.com/science/article/pii/S1517758021000163/pdfft?md5=1bb4525747fa6d9d6339eb99180fb94a&pid=1-s2.0-S1517758021000163-main.pdf Verlag kostenfrei https://doi.org/10.1016/j.econ.2021.09.002 Resolving-System kostenfrei http://hdl.handle.net/10419/266984 Resolving-System kostenfrei GBV_USEFLAG_U GBV_ILN_26 ISIL_DE-206 SYSFLAG_1 GBV_KXP SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_138 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_647 GBV_ILN_702 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 GBV_ILN_2403 GBV_ILN_2403 ISIL_DE-LFER AR 22 2021 3 12 251-264 26 01 0206 4097316354 x1z 22-03-22 2403 01 DE-LFER 4113025886 00 --%%-- --%%-- n --%%-- l01 07-04-22 2403 01 DE-LFER https://doi.org/10.1016/j.econ.2021.09.002 2403 01 DE-LFER https://www.sciencedirect.com/science/article/pii/S1517758021000163/pdfft?md5=1bb4525747fa6d9d6339eb99180fb94a&pid=1-s2.0-S1517758021000163-main.pdf
allfields_unstemmed	10.1016/j.econ.2021.09.002 doi 10419/266984 hdl (DE-627)1796235393 (DE-599)KXP1796235393 DE-627 ger DE-627 rda eng D31 I14 I18 jelc França, Natália Cecília de verfasserin (DE-588)1256767905 (DE-627)1800848439 aut 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 Natália Cecília de França, Guaracyane Lima Campêlo, João Mário Santos de França, Eleydiane Gomes Vale, Thaísa França Badagnan 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier DE-206 Open Access Controlled Vocabulary for Access Rights http://purl.org/coar/access_right/c_abf2 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. DE-206 Namensnennung - Nicht kommerziell - Keine Bearbeitungen 4.0 International CC BY-NC-ND 4.0 cc https://creativecommons.org/licenses/by-nc-nd/4.0/ COVID-19 (dpeaa)DE-206 Decomposition analysis (dpeaa)DE-206 Health inequality (dpeaa)DE-206 Pre-existing disease (dpeaa)DE-206 Socioeconomic factors (dpeaa)DE-206 Lima Campêlo, Guaracyane verfasserin (DE-588)116297592X (DE-627)1027073603 (DE-576)507725158 aut França, João Mário Santos de verfasserin (DE-588)142321036 (DE-627)635121549 (DE-576)330104748 aut Vale, Eleydiane Maria Gomes verfasserin (DE-588)115496857X (DE-627)1016282184 (DE-576)501343237 aut Badagnan, Thaísa França verfasserin aut Enthalten in Economia Bingley, United Kingdom : Emerald, 2000 22(2021), 3 vom: Dez., Seite 251-264 Online-Ressource (DE-627)578536218 (DE-600)2451788-4 (DE-576)286025949 2358-2820 nnns volume:22 year:2021 number:3 month:12 pages:251-264 https://www.sciencedirect.com/science/article/pii/S1517758021000163/pdfft?md5=1bb4525747fa6d9d6339eb99180fb94a&pid=1-s2.0-S1517758021000163-main.pdf Verlag kostenfrei https://doi.org/10.1016/j.econ.2021.09.002 Resolving-System kostenfrei http://hdl.handle.net/10419/266984 Resolving-System kostenfrei GBV_USEFLAG_U GBV_ILN_26 ISIL_DE-206 SYSFLAG_1 GBV_KXP SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_138 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_647 GBV_ILN_702 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 GBV_ILN_2403 GBV_ILN_2403 ISIL_DE-LFER AR 22 2021 3 12 251-264 26 01 0206 4097316354 x1z 22-03-22 2403 01 DE-LFER 4113025886 00 --%%-- --%%-- n --%%-- l01 07-04-22 2403 01 DE-LFER https://doi.org/10.1016/j.econ.2021.09.002 2403 01 DE-LFER https://www.sciencedirect.com/science/article/pii/S1517758021000163/pdfft?md5=1bb4525747fa6d9d6339eb99180fb94a&pid=1-s2.0-S1517758021000163-main.pdf
allfieldsGer	10.1016/j.econ.2021.09.002 doi 10419/266984 hdl (DE-627)1796235393 (DE-599)KXP1796235393 DE-627 ger DE-627 rda eng D31 I14 I18 jelc França, Natália Cecília de verfasserin (DE-588)1256767905 (DE-627)1800848439 aut 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 Natália Cecília de França, Guaracyane Lima Campêlo, João Mário Santos de França, Eleydiane Gomes Vale, Thaísa França Badagnan 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier DE-206 Open Access Controlled Vocabulary for Access Rights http://purl.org/coar/access_right/c_abf2 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. DE-206 Namensnennung - Nicht kommerziell - Keine Bearbeitungen 4.0 International CC BY-NC-ND 4.0 cc https://creativecommons.org/licenses/by-nc-nd/4.0/ COVID-19 (dpeaa)DE-206 Decomposition analysis (dpeaa)DE-206 Health inequality (dpeaa)DE-206 Pre-existing disease (dpeaa)DE-206 Socioeconomic factors (dpeaa)DE-206 Lima Campêlo, Guaracyane verfasserin (DE-588)116297592X (DE-627)1027073603 (DE-576)507725158 aut França, João Mário Santos de verfasserin (DE-588)142321036 (DE-627)635121549 (DE-576)330104748 aut Vale, Eleydiane Maria Gomes verfasserin (DE-588)115496857X (DE-627)1016282184 (DE-576)501343237 aut Badagnan, Thaísa França verfasserin aut Enthalten in Economia Bingley, United Kingdom : Emerald, 2000 22(2021), 3 vom: Dez., Seite 251-264 Online-Ressource (DE-627)578536218 (DE-600)2451788-4 (DE-576)286025949 2358-2820 nnns volume:22 year:2021 number:3 month:12 pages:251-264 https://www.sciencedirect.com/science/article/pii/S1517758021000163/pdfft?md5=1bb4525747fa6d9d6339eb99180fb94a&pid=1-s2.0-S1517758021000163-main.pdf Verlag kostenfrei https://doi.org/10.1016/j.econ.2021.09.002 Resolving-System kostenfrei http://hdl.handle.net/10419/266984 Resolving-System kostenfrei GBV_USEFLAG_U GBV_ILN_26 ISIL_DE-206 SYSFLAG_1 GBV_KXP SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_138 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_647 GBV_ILN_702 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 GBV_ILN_2403 GBV_ILN_2403 ISIL_DE-LFER AR 22 2021 3 12 251-264 26 01 0206 4097316354 x1z 22-03-22 2403 01 DE-LFER 4113025886 00 --%%-- --%%-- n --%%-- l01 07-04-22 2403 01 DE-LFER https://doi.org/10.1016/j.econ.2021.09.002 2403 01 DE-LFER https://www.sciencedirect.com/science/article/pii/S1517758021000163/pdfft?md5=1bb4525747fa6d9d6339eb99180fb94a&pid=1-s2.0-S1517758021000163-main.pdf
allfieldsSound	10.1016/j.econ.2021.09.002 doi 10419/266984 hdl (DE-627)1796235393 (DE-599)KXP1796235393 DE-627 ger DE-627 rda eng D31 I14 I18 jelc França, Natália Cecília de verfasserin (DE-588)1256767905 (DE-627)1800848439 aut 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 Natália Cecília de França, Guaracyane Lima Campêlo, João Mário Santos de França, Eleydiane Gomes Vale, Thaísa França Badagnan 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier DE-206 Open Access Controlled Vocabulary for Access Rights http://purl.org/coar/access_right/c_abf2 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. DE-206 Namensnennung - Nicht kommerziell - Keine Bearbeitungen 4.0 International CC BY-NC-ND 4.0 cc https://creativecommons.org/licenses/by-nc-nd/4.0/ COVID-19 (dpeaa)DE-206 Decomposition analysis (dpeaa)DE-206 Health inequality (dpeaa)DE-206 Pre-existing disease (dpeaa)DE-206 Socioeconomic factors (dpeaa)DE-206 Lima Campêlo, Guaracyane verfasserin (DE-588)116297592X (DE-627)1027073603 (DE-576)507725158 aut França, João Mário Santos de verfasserin (DE-588)142321036 (DE-627)635121549 (DE-576)330104748 aut Vale, Eleydiane Maria Gomes verfasserin (DE-588)115496857X (DE-627)1016282184 (DE-576)501343237 aut Badagnan, Thaísa França verfasserin aut Enthalten in Economia Bingley, United Kingdom : Emerald, 2000 22(2021), 3 vom: Dez., Seite 251-264 Online-Ressource (DE-627)578536218 (DE-600)2451788-4 (DE-576)286025949 2358-2820 nnns volume:22 year:2021 number:3 month:12 pages:251-264 https://www.sciencedirect.com/science/article/pii/S1517758021000163/pdfft?md5=1bb4525747fa6d9d6339eb99180fb94a&pid=1-s2.0-S1517758021000163-main.pdf Verlag kostenfrei https://doi.org/10.1016/j.econ.2021.09.002 Resolving-System kostenfrei http://hdl.handle.net/10419/266984 Resolving-System kostenfrei GBV_USEFLAG_U GBV_ILN_26 ISIL_DE-206 SYSFLAG_1 GBV_KXP SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_138 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_647 GBV_ILN_702 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 GBV_ILN_2403 GBV_ILN_2403 ISIL_DE-LFER AR 22 2021 3 12 251-264 26 01 0206 4097316354 x1z 22-03-22 2403 01 DE-LFER 4113025886 00 --%%-- --%%-- n --%%-- l01 07-04-22 2403 01 DE-LFER https://doi.org/10.1016/j.econ.2021.09.002 2403 01 DE-LFER https://www.sciencedirect.com/science/article/pii/S1517758021000163/pdfft?md5=1bb4525747fa6d9d6339eb99180fb94a&pid=1-s2.0-S1517758021000163-main.pdf
language	English
source	Enthalten in Economia 22(2021), 3 vom: Dez., Seite 251-264 volume:22 year:2021 number:3 month:12 pages:251-264
sourceStr	Enthalten in Economia 22(2021), 3 vom: Dez., Seite 251-264 volume:22 year:2021 number:3 month:12 pages:251-264
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topic_facet	COVID-19 Decomposition analysis Health inequality Pre-existing disease Socioeconomic factors
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container_title	Economia
authorswithroles_txt_mv	França, Natália Cecília de @@aut@@ Lima Campêlo, Guaracyane @@aut@@ França, João Mário Santos de @@aut@@ Vale, Eleydiane Maria Gomes @@aut@@ Badagnan, Thaísa França @@aut@@
publishDateDaySort_date	2021-12-01T00:00:00Z
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spellingShingle	França, Natália Cecília de jelc D31 misc COVID-19 misc Decomposition analysis misc Health inequality misc Pre-existing disease misc Socioeconomic factors 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
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topic_title	D31 I14 I18 jelc 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 Natália Cecília de França, Guaracyane Lima Campêlo, João Mário Santos de França, Eleydiane Gomes Vale, Thaísa França Badagnan COVID-19 (dpeaa)DE-206 Decomposition analysis (dpeaa)DE-206 Health inequality (dpeaa)DE-206 Pre-existing disease (dpeaa)DE-206 Socioeconomic factors (dpeaa)DE-206
topic	jelc D31 misc COVID-19 misc Decomposition analysis misc Health inequality misc Pre-existing disease misc Socioeconomic factors
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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
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title_full	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 Natália Cecília de França, Guaracyane Lima Campêlo, João Mário Santos de França, Eleydiane Gomes Vale, Thaísa França Badagnan
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title_sort	decomposition analysis for socioeconomic inequalities in health status associated with the covid-19 diagnosis and related symptoms during brazil's first wave of infections
title_auth	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
abstract	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.
abstractGer	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.
abstract_unstemmed	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.
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title_short	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
url	https://www.sciencedirect.com/science/article/pii/S1517758021000163/pdfft?md5=1bb4525747fa6d9d6339eb99180fb94a&pid=1-s2.0-S1517758021000163-main.pdf https://doi.org/10.1016/j.econ.2021.09.002 http://hdl.handle.net/10419/266984
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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

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