Socioeconomic disparities in health outcomes in the United States in the late 2010s: results from four national population-based studies
Background Despite the importance of monitoring health disparities by multiple socioeconomic categories, there have been no recent updates on the prevalence of general health indicators by socioeconomic categories. The present study aims to update the prevalence estimates of health indicators by edu...
Ausführliche Beschreibung
Autor*in: |
Kim, Yeonwoo [verfasserIn] |
---|
Format: |
E-Artikel |
---|---|
Sprache: |
Englisch |
Erschienen: |
2023 |
---|
Schlagwörter: |
---|
Anmerkung: |
© The Author(s) 2023 |
---|
Übergeordnetes Werk: |
Enthalten in: Archives of public health - Bruxelles : Archives, 1997, 81(2023), 1 vom: 04. Feb. |
---|---|
Übergeordnetes Werk: |
volume:81 ; year:2023 ; number:1 ; day:04 ; month:02 |
Links: |
---|
DOI / URN: |
10.1186/s13690-023-01026-1 |
---|
Katalog-ID: |
SPR051420546 |
---|
LEADER | 01000caa a22002652 4500 | ||
---|---|---|---|
001 | SPR051420546 | ||
003 | DE-627 | ||
005 | 20230510062143.0 | ||
007 | cr uuu---uuuuu | ||
008 | 230508s2023 xx |||||o 00| ||eng c | ||
024 | 7 | |a 10.1186/s13690-023-01026-1 |2 doi | |
035 | |a (DE-627)SPR051420546 | ||
035 | |a (SPR)s13690-023-01026-1-e | ||
040 | |a DE-627 |b ger |c DE-627 |e rakwb | ||
041 | |a eng | ||
100 | 1 | |a Kim, Yeonwoo |e verfasserin |4 aut | |
245 | 1 | 0 | |a Socioeconomic disparities in health outcomes in the United States in the late 2010s: results from four national population-based studies |
264 | 1 | |c 2023 | |
336 | |a Text |b txt |2 rdacontent | ||
337 | |a Computermedien |b c |2 rdamedia | ||
338 | |a Online-Ressource |b cr |2 rdacarrier | ||
500 | |a © The Author(s) 2023 | ||
520 | |a Background Despite the importance of monitoring health disparities by multiple socioeconomic categories, there have been no recent updates on the prevalence of general health indicators by socioeconomic categories. The present study aims to update the prevalence estimates of health indicators by education and income categories across three age groups (children, young and middle-aged adults, and older adults) in the late 2010s by using four nationally representative data sources. We also examine socioeconomic differences in health by race/ethnicity subgroups. Methods Data were obtained from four nationally representative data sources from the U.S.: The National Health Interview Survey (2015–2018); the National Health and Nutrition Examination Survey, NHANES (2017–2020); the Behavioral Risk Factor Surveillance System (2016–2020); and the Health & Retirement Study (2016). Respondent-rated health and obesity were selected as the health indicators of interest. Socioeconomic factors included percentages of the federal poverty level and years of educational attainment. We conducted logistic regression analyses to calculate adjusted prevalence rates of respondent-rated (or measured, in the case of obesity in NHANES) poor health and obesity by income and education categories after controlling for sociodemographic characteristics. The complex sampling designs were accounted for in all analyses. Results Prevalence rates across racial/ethnic groups and age groups demonstrated clear and consistent socioeconomic gradients in respondent-rated poor health, with the highest rates among those in the lowest income and education categories, and decreased rates as income and education levels increased. On the other hand, there were less evident socioeconomic differences in obesity rates across all data sources, racial/ethnic groups, and age groups. Conclusions Our results confirmed earlier, persistent evidence indicating socioeconomic disparities in respondent-rated poor health across all age and race/ethnicity groups by using four nationally representative datasets. In comparison to a decade earlier, socioeconomic disparities in poor health appeared to shrink while they emerged or increased for obesity. The results suggest an urgent need for action to alleviate pervasive health disparities by socioeconomic status. Further research is needed to investigate potentially modifiable factors underlying socioeconomic disparities in health, which may help design targeted health promotion programs. | ||
650 | 4 | |a Socioeconomic disparities |7 (dpeaa)DE-He213 | |
650 | 4 | |a Health disparities |7 (dpeaa)DE-He213 | |
650 | 4 | |a Respondent-rated health |7 (dpeaa)DE-He213 | |
700 | 1 | |a Vazquez, Christian |4 aut | |
700 | 1 | |a Cubbin, Catherine |4 aut | |
773 | 0 | 8 | |i Enthalten in |t Archives of public health |d Bruxelles : Archives, 1997 |g 81(2023), 1 vom: 04. Feb. |w (DE-627)378128086 |w (DE-600)2133388-9 |x 2049-3258 |7 nnns |
773 | 1 | 8 | |g volume:81 |g year:2023 |g number:1 |g day:04 |g month:02 |
856 | 4 | 0 | |u https://dx.doi.org/10.1186/s13690-023-01026-1 |z kostenfrei |3 Volltext |
912 | |a GBV_USEFLAG_A | ||
912 | |a SYSFLAG_A | ||
912 | |a GBV_SPRINGER | ||
912 | |a GBV_ILN_11 | ||
912 | |a GBV_ILN_20 | ||
912 | |a GBV_ILN_22 | ||
912 | |a GBV_ILN_23 | ||
912 | |a GBV_ILN_24 | ||
912 | |a GBV_ILN_31 | ||
912 | |a GBV_ILN_39 | ||
912 | |a GBV_ILN_40 | ||
912 | |a GBV_ILN_60 | ||
912 | |a GBV_ILN_62 | ||
912 | |a GBV_ILN_63 | ||
912 | |a GBV_ILN_65 | ||
912 | |a GBV_ILN_69 | ||
912 | |a GBV_ILN_73 | ||
912 | |a GBV_ILN_74 | ||
912 | |a GBV_ILN_95 | ||
912 | |a GBV_ILN_110 | ||
912 | |a GBV_ILN_151 | ||
912 | |a GBV_ILN_161 | ||
912 | |a GBV_ILN_170 | ||
912 | |a GBV_ILN_206 | ||
912 | |a GBV_ILN_213 | ||
912 | |a GBV_ILN_230 | ||
912 | |a GBV_ILN_285 | ||
912 | |a GBV_ILN_293 | ||
912 | |a GBV_ILN_602 | ||
912 | |a GBV_ILN_2003 | ||
912 | |a GBV_ILN_2014 | ||
912 | |a GBV_ILN_4012 | ||
912 | |a GBV_ILN_4037 | ||
912 | |a GBV_ILN_4112 | ||
912 | |a GBV_ILN_4125 | ||
912 | |a GBV_ILN_4126 | ||
912 | |a GBV_ILN_4249 | ||
912 | |a GBV_ILN_4305 | ||
912 | |a GBV_ILN_4306 | ||
912 | |a GBV_ILN_4322 | ||
912 | |a GBV_ILN_4323 | ||
912 | |a GBV_ILN_4324 | ||
912 | |a GBV_ILN_4325 | ||
912 | |a GBV_ILN_4367 | ||
912 | |a GBV_ILN_4700 | ||
951 | |a AR | ||
952 | |d 81 |j 2023 |e 1 |b 04 |c 02 |
author_variant |
y k yk c v cv c c cc |
---|---|
matchkey_str |
article:20493258:2023----::oieooidsaiisnelhucmsnhuiesaeiteae00rslsrmor |
hierarchy_sort_str |
2023 |
publishDate |
2023 |
allfields |
10.1186/s13690-023-01026-1 doi (DE-627)SPR051420546 (SPR)s13690-023-01026-1-e DE-627 ger DE-627 rakwb eng Kim, Yeonwoo verfasserin aut Socioeconomic disparities in health outcomes in the United States in the late 2010s: results from four national population-based studies 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2023 Background Despite the importance of monitoring health disparities by multiple socioeconomic categories, there have been no recent updates on the prevalence of general health indicators by socioeconomic categories. The present study aims to update the prevalence estimates of health indicators by education and income categories across three age groups (children, young and middle-aged adults, and older adults) in the late 2010s by using four nationally representative data sources. We also examine socioeconomic differences in health by race/ethnicity subgroups. Methods Data were obtained from four nationally representative data sources from the U.S.: The National Health Interview Survey (2015–2018); the National Health and Nutrition Examination Survey, NHANES (2017–2020); the Behavioral Risk Factor Surveillance System (2016–2020); and the Health & Retirement Study (2016). Respondent-rated health and obesity were selected as the health indicators of interest. Socioeconomic factors included percentages of the federal poverty level and years of educational attainment. We conducted logistic regression analyses to calculate adjusted prevalence rates of respondent-rated (or measured, in the case of obesity in NHANES) poor health and obesity by income and education categories after controlling for sociodemographic characteristics. The complex sampling designs were accounted for in all analyses. Results Prevalence rates across racial/ethnic groups and age groups demonstrated clear and consistent socioeconomic gradients in respondent-rated poor health, with the highest rates among those in the lowest income and education categories, and decreased rates as income and education levels increased. On the other hand, there were less evident socioeconomic differences in obesity rates across all data sources, racial/ethnic groups, and age groups. Conclusions Our results confirmed earlier, persistent evidence indicating socioeconomic disparities in respondent-rated poor health across all age and race/ethnicity groups by using four nationally representative datasets. In comparison to a decade earlier, socioeconomic disparities in poor health appeared to shrink while they emerged or increased for obesity. The results suggest an urgent need for action to alleviate pervasive health disparities by socioeconomic status. Further research is needed to investigate potentially modifiable factors underlying socioeconomic disparities in health, which may help design targeted health promotion programs. Socioeconomic disparities (dpeaa)DE-He213 Health disparities (dpeaa)DE-He213 Respondent-rated health (dpeaa)DE-He213 Vazquez, Christian aut Cubbin, Catherine aut Enthalten in Archives of public health Bruxelles : Archives, 1997 81(2023), 1 vom: 04. Feb. (DE-627)378128086 (DE-600)2133388-9 2049-3258 nnns volume:81 year:2023 number:1 day:04 month:02 https://dx.doi.org/10.1186/s13690-023-01026-1 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER 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_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 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_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4367 GBV_ILN_4700 AR 81 2023 1 04 02 |
spelling |
10.1186/s13690-023-01026-1 doi (DE-627)SPR051420546 (SPR)s13690-023-01026-1-e DE-627 ger DE-627 rakwb eng Kim, Yeonwoo verfasserin aut Socioeconomic disparities in health outcomes in the United States in the late 2010s: results from four national population-based studies 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2023 Background Despite the importance of monitoring health disparities by multiple socioeconomic categories, there have been no recent updates on the prevalence of general health indicators by socioeconomic categories. The present study aims to update the prevalence estimates of health indicators by education and income categories across three age groups (children, young and middle-aged adults, and older adults) in the late 2010s by using four nationally representative data sources. We also examine socioeconomic differences in health by race/ethnicity subgroups. Methods Data were obtained from four nationally representative data sources from the U.S.: The National Health Interview Survey (2015–2018); the National Health and Nutrition Examination Survey, NHANES (2017–2020); the Behavioral Risk Factor Surveillance System (2016–2020); and the Health & Retirement Study (2016). Respondent-rated health and obesity were selected as the health indicators of interest. Socioeconomic factors included percentages of the federal poverty level and years of educational attainment. We conducted logistic regression analyses to calculate adjusted prevalence rates of respondent-rated (or measured, in the case of obesity in NHANES) poor health and obesity by income and education categories after controlling for sociodemographic characteristics. The complex sampling designs were accounted for in all analyses. Results Prevalence rates across racial/ethnic groups and age groups demonstrated clear and consistent socioeconomic gradients in respondent-rated poor health, with the highest rates among those in the lowest income and education categories, and decreased rates as income and education levels increased. On the other hand, there were less evident socioeconomic differences in obesity rates across all data sources, racial/ethnic groups, and age groups. Conclusions Our results confirmed earlier, persistent evidence indicating socioeconomic disparities in respondent-rated poor health across all age and race/ethnicity groups by using four nationally representative datasets. In comparison to a decade earlier, socioeconomic disparities in poor health appeared to shrink while they emerged or increased for obesity. The results suggest an urgent need for action to alleviate pervasive health disparities by socioeconomic status. Further research is needed to investigate potentially modifiable factors underlying socioeconomic disparities in health, which may help design targeted health promotion programs. Socioeconomic disparities (dpeaa)DE-He213 Health disparities (dpeaa)DE-He213 Respondent-rated health (dpeaa)DE-He213 Vazquez, Christian aut Cubbin, Catherine aut Enthalten in Archives of public health Bruxelles : Archives, 1997 81(2023), 1 vom: 04. Feb. (DE-627)378128086 (DE-600)2133388-9 2049-3258 nnns volume:81 year:2023 number:1 day:04 month:02 https://dx.doi.org/10.1186/s13690-023-01026-1 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER 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_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 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_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4367 GBV_ILN_4700 AR 81 2023 1 04 02 |
allfields_unstemmed |
10.1186/s13690-023-01026-1 doi (DE-627)SPR051420546 (SPR)s13690-023-01026-1-e DE-627 ger DE-627 rakwb eng Kim, Yeonwoo verfasserin aut Socioeconomic disparities in health outcomes in the United States in the late 2010s: results from four national population-based studies 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2023 Background Despite the importance of monitoring health disparities by multiple socioeconomic categories, there have been no recent updates on the prevalence of general health indicators by socioeconomic categories. The present study aims to update the prevalence estimates of health indicators by education and income categories across three age groups (children, young and middle-aged adults, and older adults) in the late 2010s by using four nationally representative data sources. We also examine socioeconomic differences in health by race/ethnicity subgroups. Methods Data were obtained from four nationally representative data sources from the U.S.: The National Health Interview Survey (2015–2018); the National Health and Nutrition Examination Survey, NHANES (2017–2020); the Behavioral Risk Factor Surveillance System (2016–2020); and the Health & Retirement Study (2016). Respondent-rated health and obesity were selected as the health indicators of interest. Socioeconomic factors included percentages of the federal poverty level and years of educational attainment. We conducted logistic regression analyses to calculate adjusted prevalence rates of respondent-rated (or measured, in the case of obesity in NHANES) poor health and obesity by income and education categories after controlling for sociodemographic characteristics. The complex sampling designs were accounted for in all analyses. Results Prevalence rates across racial/ethnic groups and age groups demonstrated clear and consistent socioeconomic gradients in respondent-rated poor health, with the highest rates among those in the lowest income and education categories, and decreased rates as income and education levels increased. On the other hand, there were less evident socioeconomic differences in obesity rates across all data sources, racial/ethnic groups, and age groups. Conclusions Our results confirmed earlier, persistent evidence indicating socioeconomic disparities in respondent-rated poor health across all age and race/ethnicity groups by using four nationally representative datasets. In comparison to a decade earlier, socioeconomic disparities in poor health appeared to shrink while they emerged or increased for obesity. The results suggest an urgent need for action to alleviate pervasive health disparities by socioeconomic status. Further research is needed to investigate potentially modifiable factors underlying socioeconomic disparities in health, which may help design targeted health promotion programs. Socioeconomic disparities (dpeaa)DE-He213 Health disparities (dpeaa)DE-He213 Respondent-rated health (dpeaa)DE-He213 Vazquez, Christian aut Cubbin, Catherine aut Enthalten in Archives of public health Bruxelles : Archives, 1997 81(2023), 1 vom: 04. Feb. (DE-627)378128086 (DE-600)2133388-9 2049-3258 nnns volume:81 year:2023 number:1 day:04 month:02 https://dx.doi.org/10.1186/s13690-023-01026-1 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER 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_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 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_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4367 GBV_ILN_4700 AR 81 2023 1 04 02 |
allfieldsGer |
10.1186/s13690-023-01026-1 doi (DE-627)SPR051420546 (SPR)s13690-023-01026-1-e DE-627 ger DE-627 rakwb eng Kim, Yeonwoo verfasserin aut Socioeconomic disparities in health outcomes in the United States in the late 2010s: results from four national population-based studies 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2023 Background Despite the importance of monitoring health disparities by multiple socioeconomic categories, there have been no recent updates on the prevalence of general health indicators by socioeconomic categories. The present study aims to update the prevalence estimates of health indicators by education and income categories across three age groups (children, young and middle-aged adults, and older adults) in the late 2010s by using four nationally representative data sources. We also examine socioeconomic differences in health by race/ethnicity subgroups. Methods Data were obtained from four nationally representative data sources from the U.S.: The National Health Interview Survey (2015–2018); the National Health and Nutrition Examination Survey, NHANES (2017–2020); the Behavioral Risk Factor Surveillance System (2016–2020); and the Health & Retirement Study (2016). Respondent-rated health and obesity were selected as the health indicators of interest. Socioeconomic factors included percentages of the federal poverty level and years of educational attainment. We conducted logistic regression analyses to calculate adjusted prevalence rates of respondent-rated (or measured, in the case of obesity in NHANES) poor health and obesity by income and education categories after controlling for sociodemographic characteristics. The complex sampling designs were accounted for in all analyses. Results Prevalence rates across racial/ethnic groups and age groups demonstrated clear and consistent socioeconomic gradients in respondent-rated poor health, with the highest rates among those in the lowest income and education categories, and decreased rates as income and education levels increased. On the other hand, there were less evident socioeconomic differences in obesity rates across all data sources, racial/ethnic groups, and age groups. Conclusions Our results confirmed earlier, persistent evidence indicating socioeconomic disparities in respondent-rated poor health across all age and race/ethnicity groups by using four nationally representative datasets. In comparison to a decade earlier, socioeconomic disparities in poor health appeared to shrink while they emerged or increased for obesity. The results suggest an urgent need for action to alleviate pervasive health disparities by socioeconomic status. Further research is needed to investigate potentially modifiable factors underlying socioeconomic disparities in health, which may help design targeted health promotion programs. Socioeconomic disparities (dpeaa)DE-He213 Health disparities (dpeaa)DE-He213 Respondent-rated health (dpeaa)DE-He213 Vazquez, Christian aut Cubbin, Catherine aut Enthalten in Archives of public health Bruxelles : Archives, 1997 81(2023), 1 vom: 04. Feb. (DE-627)378128086 (DE-600)2133388-9 2049-3258 nnns volume:81 year:2023 number:1 day:04 month:02 https://dx.doi.org/10.1186/s13690-023-01026-1 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER 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_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 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_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4367 GBV_ILN_4700 AR 81 2023 1 04 02 |
allfieldsSound |
10.1186/s13690-023-01026-1 doi (DE-627)SPR051420546 (SPR)s13690-023-01026-1-e DE-627 ger DE-627 rakwb eng Kim, Yeonwoo verfasserin aut Socioeconomic disparities in health outcomes in the United States in the late 2010s: results from four national population-based studies 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2023 Background Despite the importance of monitoring health disparities by multiple socioeconomic categories, there have been no recent updates on the prevalence of general health indicators by socioeconomic categories. The present study aims to update the prevalence estimates of health indicators by education and income categories across three age groups (children, young and middle-aged adults, and older adults) in the late 2010s by using four nationally representative data sources. We also examine socioeconomic differences in health by race/ethnicity subgroups. Methods Data were obtained from four nationally representative data sources from the U.S.: The National Health Interview Survey (2015–2018); the National Health and Nutrition Examination Survey, NHANES (2017–2020); the Behavioral Risk Factor Surveillance System (2016–2020); and the Health & Retirement Study (2016). Respondent-rated health and obesity were selected as the health indicators of interest. Socioeconomic factors included percentages of the federal poverty level and years of educational attainment. We conducted logistic regression analyses to calculate adjusted prevalence rates of respondent-rated (or measured, in the case of obesity in NHANES) poor health and obesity by income and education categories after controlling for sociodemographic characteristics. The complex sampling designs were accounted for in all analyses. Results Prevalence rates across racial/ethnic groups and age groups demonstrated clear and consistent socioeconomic gradients in respondent-rated poor health, with the highest rates among those in the lowest income and education categories, and decreased rates as income and education levels increased. On the other hand, there were less evident socioeconomic differences in obesity rates across all data sources, racial/ethnic groups, and age groups. Conclusions Our results confirmed earlier, persistent evidence indicating socioeconomic disparities in respondent-rated poor health across all age and race/ethnicity groups by using four nationally representative datasets. In comparison to a decade earlier, socioeconomic disparities in poor health appeared to shrink while they emerged or increased for obesity. The results suggest an urgent need for action to alleviate pervasive health disparities by socioeconomic status. Further research is needed to investigate potentially modifiable factors underlying socioeconomic disparities in health, which may help design targeted health promotion programs. Socioeconomic disparities (dpeaa)DE-He213 Health disparities (dpeaa)DE-He213 Respondent-rated health (dpeaa)DE-He213 Vazquez, Christian aut Cubbin, Catherine aut Enthalten in Archives of public health Bruxelles : Archives, 1997 81(2023), 1 vom: 04. Feb. (DE-627)378128086 (DE-600)2133388-9 2049-3258 nnns volume:81 year:2023 number:1 day:04 month:02 https://dx.doi.org/10.1186/s13690-023-01026-1 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER 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_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 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_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4367 GBV_ILN_4700 AR 81 2023 1 04 02 |
language |
English |
source |
Enthalten in Archives of public health 81(2023), 1 vom: 04. Feb. volume:81 year:2023 number:1 day:04 month:02 |
sourceStr |
Enthalten in Archives of public health 81(2023), 1 vom: 04. Feb. volume:81 year:2023 number:1 day:04 month:02 |
format_phy_str_mv |
Article |
institution |
findex.gbv.de |
topic_facet |
Socioeconomic disparities Health disparities Respondent-rated health |
isfreeaccess_bool |
true |
container_title |
Archives of public health |
authorswithroles_txt_mv |
Kim, Yeonwoo @@aut@@ Vazquez, Christian @@aut@@ Cubbin, Catherine @@aut@@ |
publishDateDaySort_date |
2023-02-04T00:00:00Z |
hierarchy_top_id |
378128086 |
id |
SPR051420546 |
language_de |
englisch |
fullrecord |
<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">SPR051420546</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230510062143.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">230508s2023 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1186/s13690-023-01026-1</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)SPR051420546</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(SPR)s13690-023-01026-1-e</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Kim, Yeonwoo</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Socioeconomic disparities in health outcomes in the United States in the late 2010s: results from four national population-based studies</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2023</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">© The Author(s) 2023</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Background Despite the importance of monitoring health disparities by multiple socioeconomic categories, there have been no recent updates on the prevalence of general health indicators by socioeconomic categories. The present study aims to update the prevalence estimates of health indicators by education and income categories across three age groups (children, young and middle-aged adults, and older adults) in the late 2010s by using four nationally representative data sources. We also examine socioeconomic differences in health by race/ethnicity subgroups. Methods Data were obtained from four nationally representative data sources from the U.S.: The National Health Interview Survey (2015–2018); the National Health and Nutrition Examination Survey, NHANES (2017–2020); the Behavioral Risk Factor Surveillance System (2016–2020); and the Health & Retirement Study (2016). Respondent-rated health and obesity were selected as the health indicators of interest. Socioeconomic factors included percentages of the federal poverty level and years of educational attainment. We conducted logistic regression analyses to calculate adjusted prevalence rates of respondent-rated (or measured, in the case of obesity in NHANES) poor health and obesity by income and education categories after controlling for sociodemographic characteristics. The complex sampling designs were accounted for in all analyses. Results Prevalence rates across racial/ethnic groups and age groups demonstrated clear and consistent socioeconomic gradients in respondent-rated poor health, with the highest rates among those in the lowest income and education categories, and decreased rates as income and education levels increased. On the other hand, there were less evident socioeconomic differences in obesity rates across all data sources, racial/ethnic groups, and age groups. Conclusions Our results confirmed earlier, persistent evidence indicating socioeconomic disparities in respondent-rated poor health across all age and race/ethnicity groups by using four nationally representative datasets. In comparison to a decade earlier, socioeconomic disparities in poor health appeared to shrink while they emerged or increased for obesity. The results suggest an urgent need for action to alleviate pervasive health disparities by socioeconomic status. Further research is needed to investigate potentially modifiable factors underlying socioeconomic disparities in health, which may help design targeted health promotion programs.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Socioeconomic disparities</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Health disparities</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Respondent-rated health</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Vazquez, Christian</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Cubbin, Catherine</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="t">Archives of public health</subfield><subfield code="d">Bruxelles : Archives, 1997</subfield><subfield code="g">81(2023), 1 vom: 04. Feb.</subfield><subfield code="w">(DE-627)378128086</subfield><subfield code="w">(DE-600)2133388-9</subfield><subfield code="x">2049-3258</subfield><subfield code="7">nnns</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:81</subfield><subfield code="g">year:2023</subfield><subfield code="g">number:1</subfield><subfield code="g">day:04</subfield><subfield code="g">month:02</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://dx.doi.org/10.1186/s13690-023-01026-1</subfield><subfield code="z">kostenfrei</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_SPRINGER</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_11</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_20</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_22</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_23</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_24</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_31</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_39</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_40</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_60</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_62</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_63</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_65</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_69</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_73</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_74</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_95</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_110</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_151</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_161</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_170</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_206</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_213</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_230</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_285</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_293</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_602</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2003</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2014</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4012</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4037</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4112</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4125</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4126</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4249</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4305</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4306</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4322</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4323</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4324</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4325</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4367</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4700</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">81</subfield><subfield code="j">2023</subfield><subfield code="e">1</subfield><subfield code="b">04</subfield><subfield code="c">02</subfield></datafield></record></collection>
|
author |
Kim, Yeonwoo |
spellingShingle |
Kim, Yeonwoo misc Socioeconomic disparities misc Health disparities misc Respondent-rated health Socioeconomic disparities in health outcomes in the United States in the late 2010s: results from four national population-based studies |
authorStr |
Kim, Yeonwoo |
ppnlink_with_tag_str_mv |
@@773@@(DE-627)378128086 |
format |
electronic Article |
delete_txt_mv |
keep |
author_role |
aut aut aut |
collection |
springer |
remote_str |
true |
illustrated |
Not Illustrated |
issn |
2049-3258 |
topic_title |
Socioeconomic disparities in health outcomes in the United States in the late 2010s: results from four national population-based studies Socioeconomic disparities (dpeaa)DE-He213 Health disparities (dpeaa)DE-He213 Respondent-rated health (dpeaa)DE-He213 |
topic |
misc Socioeconomic disparities misc Health disparities misc Respondent-rated health |
topic_unstemmed |
misc Socioeconomic disparities misc Health disparities misc Respondent-rated health |
topic_browse |
misc Socioeconomic disparities misc Health disparities misc Respondent-rated health |
format_facet |
Elektronische Aufsätze Aufsätze Elektronische Ressource |
format_main_str_mv |
Text Zeitschrift/Artikel |
carriertype_str_mv |
cr |
hierarchy_parent_title |
Archives of public health |
hierarchy_parent_id |
378128086 |
hierarchy_top_title |
Archives of public health |
isfreeaccess_txt |
true |
familylinks_str_mv |
(DE-627)378128086 (DE-600)2133388-9 |
title |
Socioeconomic disparities in health outcomes in the United States in the late 2010s: results from four national population-based studies |
ctrlnum |
(DE-627)SPR051420546 (SPR)s13690-023-01026-1-e |
title_full |
Socioeconomic disparities in health outcomes in the United States in the late 2010s: results from four national population-based studies |
author_sort |
Kim, Yeonwoo |
journal |
Archives of public health |
journalStr |
Archives of public health |
lang_code |
eng |
isOA_bool |
true |
recordtype |
marc |
publishDateSort |
2023 |
contenttype_str_mv |
txt |
author_browse |
Kim, Yeonwoo Vazquez, Christian Cubbin, Catherine |
container_volume |
81 |
format_se |
Elektronische Aufsätze |
author-letter |
Kim, Yeonwoo |
doi_str_mv |
10.1186/s13690-023-01026-1 |
title_sort |
socioeconomic disparities in health outcomes in the united states in the late 2010s: results from four national population-based studies |
title_auth |
Socioeconomic disparities in health outcomes in the United States in the late 2010s: results from four national population-based studies |
abstract |
Background Despite the importance of monitoring health disparities by multiple socioeconomic categories, there have been no recent updates on the prevalence of general health indicators by socioeconomic categories. The present study aims to update the prevalence estimates of health indicators by education and income categories across three age groups (children, young and middle-aged adults, and older adults) in the late 2010s by using four nationally representative data sources. We also examine socioeconomic differences in health by race/ethnicity subgroups. Methods Data were obtained from four nationally representative data sources from the U.S.: The National Health Interview Survey (2015–2018); the National Health and Nutrition Examination Survey, NHANES (2017–2020); the Behavioral Risk Factor Surveillance System (2016–2020); and the Health & Retirement Study (2016). Respondent-rated health and obesity were selected as the health indicators of interest. Socioeconomic factors included percentages of the federal poverty level and years of educational attainment. We conducted logistic regression analyses to calculate adjusted prevalence rates of respondent-rated (or measured, in the case of obesity in NHANES) poor health and obesity by income and education categories after controlling for sociodemographic characteristics. The complex sampling designs were accounted for in all analyses. Results Prevalence rates across racial/ethnic groups and age groups demonstrated clear and consistent socioeconomic gradients in respondent-rated poor health, with the highest rates among those in the lowest income and education categories, and decreased rates as income and education levels increased. On the other hand, there were less evident socioeconomic differences in obesity rates across all data sources, racial/ethnic groups, and age groups. Conclusions Our results confirmed earlier, persistent evidence indicating socioeconomic disparities in respondent-rated poor health across all age and race/ethnicity groups by using four nationally representative datasets. In comparison to a decade earlier, socioeconomic disparities in poor health appeared to shrink while they emerged or increased for obesity. The results suggest an urgent need for action to alleviate pervasive health disparities by socioeconomic status. Further research is needed to investigate potentially modifiable factors underlying socioeconomic disparities in health, which may help design targeted health promotion programs. © The Author(s) 2023 |
abstractGer |
Background Despite the importance of monitoring health disparities by multiple socioeconomic categories, there have been no recent updates on the prevalence of general health indicators by socioeconomic categories. The present study aims to update the prevalence estimates of health indicators by education and income categories across three age groups (children, young and middle-aged adults, and older adults) in the late 2010s by using four nationally representative data sources. We also examine socioeconomic differences in health by race/ethnicity subgroups. Methods Data were obtained from four nationally representative data sources from the U.S.: The National Health Interview Survey (2015–2018); the National Health and Nutrition Examination Survey, NHANES (2017–2020); the Behavioral Risk Factor Surveillance System (2016–2020); and the Health & Retirement Study (2016). Respondent-rated health and obesity were selected as the health indicators of interest. Socioeconomic factors included percentages of the federal poverty level and years of educational attainment. We conducted logistic regression analyses to calculate adjusted prevalence rates of respondent-rated (or measured, in the case of obesity in NHANES) poor health and obesity by income and education categories after controlling for sociodemographic characteristics. The complex sampling designs were accounted for in all analyses. Results Prevalence rates across racial/ethnic groups and age groups demonstrated clear and consistent socioeconomic gradients in respondent-rated poor health, with the highest rates among those in the lowest income and education categories, and decreased rates as income and education levels increased. On the other hand, there were less evident socioeconomic differences in obesity rates across all data sources, racial/ethnic groups, and age groups. Conclusions Our results confirmed earlier, persistent evidence indicating socioeconomic disparities in respondent-rated poor health across all age and race/ethnicity groups by using four nationally representative datasets. In comparison to a decade earlier, socioeconomic disparities in poor health appeared to shrink while they emerged or increased for obesity. The results suggest an urgent need for action to alleviate pervasive health disparities by socioeconomic status. Further research is needed to investigate potentially modifiable factors underlying socioeconomic disparities in health, which may help design targeted health promotion programs. © The Author(s) 2023 |
abstract_unstemmed |
Background Despite the importance of monitoring health disparities by multiple socioeconomic categories, there have been no recent updates on the prevalence of general health indicators by socioeconomic categories. The present study aims to update the prevalence estimates of health indicators by education and income categories across three age groups (children, young and middle-aged adults, and older adults) in the late 2010s by using four nationally representative data sources. We also examine socioeconomic differences in health by race/ethnicity subgroups. Methods Data were obtained from four nationally representative data sources from the U.S.: The National Health Interview Survey (2015–2018); the National Health and Nutrition Examination Survey, NHANES (2017–2020); the Behavioral Risk Factor Surveillance System (2016–2020); and the Health & Retirement Study (2016). Respondent-rated health and obesity were selected as the health indicators of interest. Socioeconomic factors included percentages of the federal poverty level and years of educational attainment. We conducted logistic regression analyses to calculate adjusted prevalence rates of respondent-rated (or measured, in the case of obesity in NHANES) poor health and obesity by income and education categories after controlling for sociodemographic characteristics. The complex sampling designs were accounted for in all analyses. Results Prevalence rates across racial/ethnic groups and age groups demonstrated clear and consistent socioeconomic gradients in respondent-rated poor health, with the highest rates among those in the lowest income and education categories, and decreased rates as income and education levels increased. On the other hand, there were less evident socioeconomic differences in obesity rates across all data sources, racial/ethnic groups, and age groups. Conclusions Our results confirmed earlier, persistent evidence indicating socioeconomic disparities in respondent-rated poor health across all age and race/ethnicity groups by using four nationally representative datasets. In comparison to a decade earlier, socioeconomic disparities in poor health appeared to shrink while they emerged or increased for obesity. The results suggest an urgent need for action to alleviate pervasive health disparities by socioeconomic status. Further research is needed to investigate potentially modifiable factors underlying socioeconomic disparities in health, which may help design targeted health promotion programs. © The Author(s) 2023 |
collection_details |
GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER 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_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 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_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4367 GBV_ILN_4700 |
container_issue |
1 |
title_short |
Socioeconomic disparities in health outcomes in the United States in the late 2010s: results from four national population-based studies |
url |
https://dx.doi.org/10.1186/s13690-023-01026-1 |
remote_bool |
true |
author2 |
Vazquez, Christian Cubbin, Catherine |
author2Str |
Vazquez, Christian Cubbin, Catherine |
ppnlink |
378128086 |
mediatype_str_mv |
c |
isOA_txt |
true |
hochschulschrift_bool |
false |
doi_str |
10.1186/s13690-023-01026-1 |
up_date |
2024-07-03T21:42:10.776Z |
_version_ |
1803595736184520704 |
fullrecord_marcxml |
<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">SPR051420546</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230510062143.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">230508s2023 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1186/s13690-023-01026-1</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)SPR051420546</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(SPR)s13690-023-01026-1-e</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Kim, Yeonwoo</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Socioeconomic disparities in health outcomes in the United States in the late 2010s: results from four national population-based studies</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2023</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">© The Author(s) 2023</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Background Despite the importance of monitoring health disparities by multiple socioeconomic categories, there have been no recent updates on the prevalence of general health indicators by socioeconomic categories. The present study aims to update the prevalence estimates of health indicators by education and income categories across three age groups (children, young and middle-aged adults, and older adults) in the late 2010s by using four nationally representative data sources. We also examine socioeconomic differences in health by race/ethnicity subgroups. Methods Data were obtained from four nationally representative data sources from the U.S.: The National Health Interview Survey (2015–2018); the National Health and Nutrition Examination Survey, NHANES (2017–2020); the Behavioral Risk Factor Surveillance System (2016–2020); and the Health & Retirement Study (2016). Respondent-rated health and obesity were selected as the health indicators of interest. Socioeconomic factors included percentages of the federal poverty level and years of educational attainment. We conducted logistic regression analyses to calculate adjusted prevalence rates of respondent-rated (or measured, in the case of obesity in NHANES) poor health and obesity by income and education categories after controlling for sociodemographic characteristics. The complex sampling designs were accounted for in all analyses. Results Prevalence rates across racial/ethnic groups and age groups demonstrated clear and consistent socioeconomic gradients in respondent-rated poor health, with the highest rates among those in the lowest income and education categories, and decreased rates as income and education levels increased. On the other hand, there were less evident socioeconomic differences in obesity rates across all data sources, racial/ethnic groups, and age groups. Conclusions Our results confirmed earlier, persistent evidence indicating socioeconomic disparities in respondent-rated poor health across all age and race/ethnicity groups by using four nationally representative datasets. In comparison to a decade earlier, socioeconomic disparities in poor health appeared to shrink while they emerged or increased for obesity. The results suggest an urgent need for action to alleviate pervasive health disparities by socioeconomic status. Further research is needed to investigate potentially modifiable factors underlying socioeconomic disparities in health, which may help design targeted health promotion programs.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Socioeconomic disparities</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Health disparities</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Respondent-rated health</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Vazquez, Christian</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Cubbin, Catherine</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="t">Archives of public health</subfield><subfield code="d">Bruxelles : Archives, 1997</subfield><subfield code="g">81(2023), 1 vom: 04. Feb.</subfield><subfield code="w">(DE-627)378128086</subfield><subfield code="w">(DE-600)2133388-9</subfield><subfield code="x">2049-3258</subfield><subfield code="7">nnns</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:81</subfield><subfield code="g">year:2023</subfield><subfield code="g">number:1</subfield><subfield code="g">day:04</subfield><subfield code="g">month:02</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://dx.doi.org/10.1186/s13690-023-01026-1</subfield><subfield code="z">kostenfrei</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_SPRINGER</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_11</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_20</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_22</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_23</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_24</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_31</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_39</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_40</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_60</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_62</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_63</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_65</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_69</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_73</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_74</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_95</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_110</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_151</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_161</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_170</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_206</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_213</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_230</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_285</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_293</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_602</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2003</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2014</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4012</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4037</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4112</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4125</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4126</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4249</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4305</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4306</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4322</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4323</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4324</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4325</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4367</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4700</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">81</subfield><subfield code="j">2023</subfield><subfield code="e">1</subfield><subfield code="b">04</subfield><subfield code="c">02</subfield></datafield></record></collection>
|
score |
7.398242 |