- Email: [email protected]
Black–white differences in self-rated health, 1972–2015
Economics Letters 154 (2017) 69–73
Contents lists available at ScienceDirect
Economics Letters journal homepage: www.elsevier.com/locate/ecolet
Black–white differences in self-rated health, 1972–2015 Owen Thompson 1 University of Wisconsin, Milwaukee, United States
highlights • The black–white gap in self-rated health declined by approximately 50% between 1972 and 2015. • This decline was not due to relative changes in the demographic or socioeconomic characteristics of blacks and whites. • The most rapid convergence occurred across the 1947 through 1974 birth cohorts.
article
info
Article history: Received 19 December 2016 Received in revised form 8 February 2017 Accepted 17 February 2017 Available online 22 February 2017
a b s t r a c t This paper documents that the black–white gap in self-rated health declined by approximately 50% between 1972 and 2015. © 2017 Elsevier B.V. All rights reserved.
Keywords: Race Self-rated health Disparities
1. Introduction Across a diverse set of measures, African-Americans experience worse health than whites in the US (Adler and Rehkopf, 2008). Such racial health disparities are of interest to economists, both because health is a direct source of individual well-being and because health is an important human capital characteristic that influences labor supply and earnings throughout the life course. While the existence of racial disparities in health are wellestablished, less is known about how these disparities have changed over time. Boustan and Margo (2016) review the literature on long-run trends in racial health disparities in the US, and report substantial convergence in the life expectancy of blacks and whites, especially between 1940 and 1960, as well as substantial racial convergence in infant mortality rates between 1920 and 1945. Boustan and Margo (2016) find less clarity in the literature on racial convergence in chronic condition prevalence, and more generally data constraints have prevented extensive analyses of trends in race-specific morbidity measures. This paper provides new evidence on how racial disparities in non-mortality health outcomes have changed over time by analyzing black–white differences in self-rated health between 1972 and E-mail address: [email protected]. 1 The data and code needed to replicate the results of this paper are available on the author’s homepage. http://dx.doi.org/10.1016/j.econlet.2017.02.026 0165-1765/© 2017 Elsevier B.V. All rights reserved.
2015, and finds large reductions in black–white self-rated health differences over this period. The remainder of the paper describes the utilized data (Section 2), reports the results (Section 3), and concludes (Section 4). 2. Data Data is drawn from the 1972–2015 waves National Health Interview Survey (NHIS). The NHIS collects a wide range of health related information in an annual cross-section of approximately 50,000 respondents. When sampling weights are applied, as is done throughout the analysis below, the NHIS is representative of the civilian, non-institutionalized US population. I restrict each annual sample to individuals who were ages 18 and over and who self-identified as either black or non-Hispanic white. I measure health using self-rated health (SRH), specifically respondent’s answer to a question asking them whether their health was ‘‘poor’’, ‘‘fair’’, ‘‘good’’, ‘‘very good’’ or ‘‘excellent’’. SRH was selected as the primary health measure because it has been asked in a generally consistent manner in each NHIS wave since 1972, and because unlike specific health conditions SRH does not require any formal diagnosis, which prevents confounding morbidity with health care access (see Chatterji et al., 2012). Previous studies have documented that SRH is strongly correlated with mortality, even after controlling for clinical health assessments
70
O. Thompson / Economics Letters 154 (2017) 69–73
Fig. 1. Semi-continuous self-rated health by year and race.
Fig. 2. Poor or fair self-rated health by year and race.
(Idler and Benyamini, 1999), and that this association is similar across racial groups (McGee et al., 1999). Annual NHIS waves were harmonized by Minnesota Population Center (2016), and while SRH data was collected in a generally consistent manner across NHIS waves, there was one significant redesign in 1982, when the number of possible health ratings was reduced from five to four (the eliminated option was ‘‘very good’’).2 To account for this, I present results using both the semicontinuous SRH measure and a binary indicator for ‘‘poor’’ or ‘‘fair’’ SRH, which can be measured in a fully consistent manner across NHIS wave, and the results with these two measures are very similar. In addition to SRH, I utilize several variables measuring basic demographic and socioeconomic characteristics, and I describe these variables as needed below. 2 This redesign also changed the phrasing of the survey question by eliminating language asking individuals to rate their health ‘‘compared to other persons of similar age’’. The impact of this rephrasing appears to be minimal however, as no clear post-1982 break is apparent in the figures presented below.
3. Results The first panel of Fig. 1 displays means of the semi-continuous SRH measure among blacks and whites for each year from 1972– 2015, while the first panel of Fig. 2 reports similar means for the binary indicator of poor or fair SRH.3 Fig. 1 shows that among whites the mean SRH level increased modestly in the 1970s before stabilizing at approximately 3.8 in the early 1980s, while among blacks the mean SRH level increased from approximately 3.2 in the early 1970s to 3.6 by the year 2000 and is relatively stable thereafter. Similarly, Fig. 2 shows that among whites the prevalence of poor or fair SRH fell from approximately .17 in the 1970s to approximately .12 in 2015, while among blacks the prevalence 3 The means in Fig. 1 are calculated with numerical values of 1–5 assigned to each SRH response, with higher numbers corresponding to better SRH. 95% confidence intervals are also shown, calculated using standard errors equal to the ratio of the race and year specific standard deviation and the square root of the race and year specific sample size.
O. Thompson / Economics Letters 154 (2017) 69–73
71
Fig. 3. Conditional self-rated health gaps by year.
Fig. 4. Black–white self-rated health gap by birth cohort.
of poor or fair SRH fell from approximately .30 in the 1970s to .17 in 2015. The second panels of Figs. 1 and 2 display trends in the black– white difference in semi-continuous SRH and poor or fair SRH, respectively. In both cases there were reductions of approximately 50% in the black–white SRH gap. Specifically, for the semicontinuous SRH measure shown in Fig. 1 the black–white gap declined from over .40 in the 1970s to approximately .20 in 2015, while for the binary indicator of poor or fair SRH shown in Fig. 2 the black–white gap declined from approximately .13 in the 1970s to approximately .06 in 2015. It may be informative to examine the black–white SRH gap conditional on various individual characteristics in addition to the unconditional means shown in Figs. 1 and 2. To do so I estimate the following regression separately for each year from 1972–2015: SRHi = α + β Blacki + Xi′ γ + εi
(1)
where SRH i denotes a measure of SRH for individual i, Blacki is an indicator of whether individual i is black, and Xi is a vector
of individual level controls. The coefficient on the black indicator variable estimates the black–white difference in SRH in a given year, conditional on the control variables in the X vector. Fig. 3 plots the coefficients on the black indicator variable from this regression with different vectors of control variables. The first panel of Fig. 3 uses the semi-continuous SRH measure, while the second panel uses the binary indicator of poor or fair SRH. The solid lines in Fig. 3 show results when conditioning on basic demographic characteristics, specifically gender, age indicators, and four region of residence indicators. For both SRH measures, the results are qualitatively similar to the unconditional trends shown in Figs. 1 and 2, although I do note that the raw size of the SRH gap is modestly larger when demographic controls are included, and the amount of convergence is modestly smaller. These differences primarily reflect black NHIS respondents having lower average ages than white respondents, differences which become larger over the course of the study period.4 The different age profiles of black and 4 In the full sample the mean age of black respondents is 43.88 years, relative to a mean of 47.17 years for white respondents, a difference of 3.29 years. These
72
O. Thompson / Economics Letters 154 (2017) 69–73 Table 1 Trends in self-rated health by race and survey year or cohort. (1)
(2)
(3)
−12.367***
−10.004*** (0.372) 0.004*** (0.000) 0.005*** (0.000) 2,152,146 0.111
−8.888***
(0.393) 0.002*** (0.000) 0.006*** (0.000) 2,152,146 0.009
(0.000) 0.004*** (0.000) 1,819,535 0.198
Observations R-squared
10.726*** (1.548) 0.017*** (0.000) −0.006*** (0.001) 527,110 0.025
13.497*** (1.541) 0.011*** (0.000) −0.007*** (0.001) 527,110 0.045
25.498*** (1.699) −0.010*** (0.000) −0.013*** (0.001) 432,935 0.132
Panel C: By birth cohort 1936–1982 Black
−19.239***
−20.395*** (0.425) 0.001*** (0.000) 0.010*** (0.000) 1,421,370 0.066 Y N
−17.893***
Panel A: By survey year Black Survey year Black × Survey year Observations R-squared Panel B: By birth cohort 1910–1935 Black Cohort Black × Birth cohort
Cohort Black × Birth cohort Observations R-squared Demographic controls SES controls
(0.430) 0.012*** (0.000) 0.010*** (0.000) 1,421,370 0.036 N N
(0.391)
−0.013***
(0.459)
−0.014*** (0.000) 0.009*** (0.000) 1,209,897 0.174 Y Y
Notes: Dependent variable in all specifications is self-rated health. Demographic controls include gender, age indicators, and four region of residence indicators. SES controls include 9 education categories and 47 household income categories. Robust standard errors reported in parentheses. * Indicate statistical significance at the 10% level. ** Indicate statistical significance at the 5% level. *** Indicate statistical significance at the 1% level.
white NHIS respondents may reflect differential mortality, racial differences in non-response not fully accounted for by sampling weights, or other factors, but for present purposes it is sufficient to note that there was a substantial narrowing of the black–white SRH gap between 1972 and 2015 even after conditioning on age and other demographic characteristics. The dashed lines in Fig. 3 show results when indicators for 9 education categories and 47 household income categories are included as control variables in addition to the described demographic characteristics. The results show that for both SRH measures, the racial gap is considerably smaller after conditioning on SES, but that the relative magnitude of black–white convergence is similar to the baseline models. Specifically, the conditional black– white difference in the semi-continuous SRH measure falls from approximately .20 in the 1970s to around .10 by the mid 2000s, a reduction of approximately 50%, with qualitatively similar findings for the binary measure of poor or fair SRH. These results suggest that the documented convergence is not driven by relative improvements in the SES of blacks. Figs. 1–3 analyzed race-specific trends in SRH across survey years, but it is also possible to analyze trends across birth cohorts.5 differences are somewhat larger in later NHIS waves: Within the 1972–1994 NHIS waves the mean age of black respondents is 2.67 years lower than that of white respondents, while within the 1995–2015 waves the mean age of black respondents is 4.08 years lower than that of white respondents. 5 Because survey year, age, and birth cohort are perfectly collinear (year = cohort + age), the models from Fig. 3 that included age controls implicitly held birth cohort constant as well, and in general it is not possible to simultaneously identify independent effects for year, age and cohort. Given this, I emphasize that the reported trends are purely descriptive in nature, and do not identify any plausibly ‘causal’ effect of survey year independent of age and cohort, or any plausibly ‘causal’ effect of cohort independent of age and survey year.
Fig. 4 does so by reporting the results of estimating Eq. (1) separately within each birth cohort from 1910 through 1982 rather than within each calendar year from 1972–2015.6 The first panel of Fig. 4 uses the semi-continuous SRH measure, and indicates that the black–white SRH gap actually grew moderately larger for cohorts born between 1910 and approximately 1935, but then declined substantially from 1935 through 1982. The most rapid convergence occurs between the 1947 and 1974 cohorts, when the black–white gap in SRH declined from over .50 to less than .20. The second panel of Fig. 4 uses the binary indicator of poor or fair SRH, and has generally similar findings, with a black–white gap of approximately .18 for cohorts born before 1935, which declines to less than .05 by the 1970 cohort. It is noteworthy that the strongest trends in Fig. 4 are observed across cohorts that were children and young adults during the Civil Rights Movement and subsequent federal policy changes. Previous research has found beneficial health impacts from access to desegregated health care facilities (Chay et al., 2009) and improvements in relative black school quality (Frisvold and Golberstein, 2013), and the documented reductions in the black–white SRH gap over time may partially reflect these and related factors.7 However, I emphasize that additional research would be needed to rigorously evaluate any potential explanations for the observed cohort trends. 6 No additional controls are included, but the results are similar when conditioning on age or survey year as well as on additional demographic or SES related characteristics. 1910 and 1982 are respectively the 5th and 95th percentiles of the cohort distribution in the full sample. 7 The cohort trends shown in Fig. 4 are modestly stronger within the South than outside of the South, but the scope for regional disaggregation is limited because the NHIS only collects information on region of residence, not region of origin.
O. Thompson / Economics Letters 154 (2017) 69–73
A final issue is that while Figs. 1–4 reported 95% confidence intervals for each year/cohort, statistical tests of whether the trends achieve significance were not conducted. Table 1 reports the results of specifications that pool data from all years/cohorts of the study period, then regress SRH onto a black indicator, a linear year or cohort variable, and an interaction between black and year or cohort (for the cohort models separate cohort-black interactions are estimated before and after the 1935 cohort). In all cases the coefficients on the interactions are highly statistically significant, indicating that the documented trends are very unlikely to be due to sampling error. 4. Conclusion This paper has documented that the black–white gap in SRH fell by approximately 50% between 1972 and 2015. This convergence is not explained by changes in the demographics or relative SES levels of blacks and whites. Cohort-based analyses indicate that the most rapid convergence occurred across the 1947–1974 cohorts. Future
73
research exploring potential explanations for these reductions in the black–white SRH gap is warranted. References Adler, N., Rehkopf, D., 2008. US disparities in health: Descriptions, causes, and mechanisms. Annu. Rev. Public Health 29, 235–252. Boustan, L., Margo, R., 2016. Racial differences in health in the United States. In: The Oxford Handbook of Economics and Human Biology. Oxford University Press. Chatterji, P., Joo, H., Lahiri, K., 2012. Beware of being unaware: Racial/ethnic disparities in chronic illness in the USA. Health Econ. 21 (9), 1040–1060. Chay, K., Guryan, J., Mazumder, B., 2009. Birth cohort and the black–white achievement gap: The roles of access and health soon after birth. NBER WP #15078. Frisvold, D., Golberstein, E., 2013. The effect of school quality on black–white health differences: Evidence from segregated southern schools. Demography 50 (6), 1989–2012. Idler, E., Benyamini, Y., 1999. Community studies reporting association between self-rated health and mortality. Res. Aging 21, 392–401. McGee, D., et al., 1999. Self-reported health status and mortality in a multiethnic US cohort. Am. J. Epidemiol. 149 (1), 41–46. Minnesota Population Center, 2016. Integrated Health Interview Series, Version 6.21. University of Minnesota, Minneapolis.
Contents lists available at ScienceDirect
Economics Letters journal homepage: www.elsevier.com/locate/ecolet
Black–white differences in self-rated health, 1972–2015 Owen Thompson 1 University of Wisconsin, Milwaukee, United States
highlights • The black–white gap in self-rated health declined by approximately 50% between 1972 and 2015. • This decline was not due to relative changes in the demographic or socioeconomic characteristics of blacks and whites. • The most rapid convergence occurred across the 1947 through 1974 birth cohorts.
article
info
Article history: Received 19 December 2016 Received in revised form 8 February 2017 Accepted 17 February 2017 Available online 22 February 2017
a b s t r a c t This paper documents that the black–white gap in self-rated health declined by approximately 50% between 1972 and 2015. © 2017 Elsevier B.V. All rights reserved.
Keywords: Race Self-rated health Disparities
1. Introduction Across a diverse set of measures, African-Americans experience worse health than whites in the US (Adler and Rehkopf, 2008). Such racial health disparities are of interest to economists, both because health is a direct source of individual well-being and because health is an important human capital characteristic that influences labor supply and earnings throughout the life course. While the existence of racial disparities in health are wellestablished, less is known about how these disparities have changed over time. Boustan and Margo (2016) review the literature on long-run trends in racial health disparities in the US, and report substantial convergence in the life expectancy of blacks and whites, especially between 1940 and 1960, as well as substantial racial convergence in infant mortality rates between 1920 and 1945. Boustan and Margo (2016) find less clarity in the literature on racial convergence in chronic condition prevalence, and more generally data constraints have prevented extensive analyses of trends in race-specific morbidity measures. This paper provides new evidence on how racial disparities in non-mortality health outcomes have changed over time by analyzing black–white differences in self-rated health between 1972 and E-mail address: [email protected]. 1 The data and code needed to replicate the results of this paper are available on the author’s homepage. http://dx.doi.org/10.1016/j.econlet.2017.02.026 0165-1765/© 2017 Elsevier B.V. All rights reserved.
2015, and finds large reductions in black–white self-rated health differences over this period. The remainder of the paper describes the utilized data (Section 2), reports the results (Section 3), and concludes (Section 4). 2. Data Data is drawn from the 1972–2015 waves National Health Interview Survey (NHIS). The NHIS collects a wide range of health related information in an annual cross-section of approximately 50,000 respondents. When sampling weights are applied, as is done throughout the analysis below, the NHIS is representative of the civilian, non-institutionalized US population. I restrict each annual sample to individuals who were ages 18 and over and who self-identified as either black or non-Hispanic white. I measure health using self-rated health (SRH), specifically respondent’s answer to a question asking them whether their health was ‘‘poor’’, ‘‘fair’’, ‘‘good’’, ‘‘very good’’ or ‘‘excellent’’. SRH was selected as the primary health measure because it has been asked in a generally consistent manner in each NHIS wave since 1972, and because unlike specific health conditions SRH does not require any formal diagnosis, which prevents confounding morbidity with health care access (see Chatterji et al., 2012). Previous studies have documented that SRH is strongly correlated with mortality, even after controlling for clinical health assessments
70
O. Thompson / Economics Letters 154 (2017) 69–73
Fig. 1. Semi-continuous self-rated health by year and race.
Fig. 2. Poor or fair self-rated health by year and race.
(Idler and Benyamini, 1999), and that this association is similar across racial groups (McGee et al., 1999). Annual NHIS waves were harmonized by Minnesota Population Center (2016), and while SRH data was collected in a generally consistent manner across NHIS waves, there was one significant redesign in 1982, when the number of possible health ratings was reduced from five to four (the eliminated option was ‘‘very good’’).2 To account for this, I present results using both the semicontinuous SRH measure and a binary indicator for ‘‘poor’’ or ‘‘fair’’ SRH, which can be measured in a fully consistent manner across NHIS wave, and the results with these two measures are very similar. In addition to SRH, I utilize several variables measuring basic demographic and socioeconomic characteristics, and I describe these variables as needed below. 2 This redesign also changed the phrasing of the survey question by eliminating language asking individuals to rate their health ‘‘compared to other persons of similar age’’. The impact of this rephrasing appears to be minimal however, as no clear post-1982 break is apparent in the figures presented below.
3. Results The first panel of Fig. 1 displays means of the semi-continuous SRH measure among blacks and whites for each year from 1972– 2015, while the first panel of Fig. 2 reports similar means for the binary indicator of poor or fair SRH.3 Fig. 1 shows that among whites the mean SRH level increased modestly in the 1970s before stabilizing at approximately 3.8 in the early 1980s, while among blacks the mean SRH level increased from approximately 3.2 in the early 1970s to 3.6 by the year 2000 and is relatively stable thereafter. Similarly, Fig. 2 shows that among whites the prevalence of poor or fair SRH fell from approximately .17 in the 1970s to approximately .12 in 2015, while among blacks the prevalence 3 The means in Fig. 1 are calculated with numerical values of 1–5 assigned to each SRH response, with higher numbers corresponding to better SRH. 95% confidence intervals are also shown, calculated using standard errors equal to the ratio of the race and year specific standard deviation and the square root of the race and year specific sample size.
O. Thompson / Economics Letters 154 (2017) 69–73
71
Fig. 3. Conditional self-rated health gaps by year.
Fig. 4. Black–white self-rated health gap by birth cohort.
of poor or fair SRH fell from approximately .30 in the 1970s to .17 in 2015. The second panels of Figs. 1 and 2 display trends in the black– white difference in semi-continuous SRH and poor or fair SRH, respectively. In both cases there were reductions of approximately 50% in the black–white SRH gap. Specifically, for the semicontinuous SRH measure shown in Fig. 1 the black–white gap declined from over .40 in the 1970s to approximately .20 in 2015, while for the binary indicator of poor or fair SRH shown in Fig. 2 the black–white gap declined from approximately .13 in the 1970s to approximately .06 in 2015. It may be informative to examine the black–white SRH gap conditional on various individual characteristics in addition to the unconditional means shown in Figs. 1 and 2. To do so I estimate the following regression separately for each year from 1972–2015: SRHi = α + β Blacki + Xi′ γ + εi
(1)
where SRH i denotes a measure of SRH for individual i, Blacki is an indicator of whether individual i is black, and Xi is a vector
of individual level controls. The coefficient on the black indicator variable estimates the black–white difference in SRH in a given year, conditional on the control variables in the X vector. Fig. 3 plots the coefficients on the black indicator variable from this regression with different vectors of control variables. The first panel of Fig. 3 uses the semi-continuous SRH measure, while the second panel uses the binary indicator of poor or fair SRH. The solid lines in Fig. 3 show results when conditioning on basic demographic characteristics, specifically gender, age indicators, and four region of residence indicators. For both SRH measures, the results are qualitatively similar to the unconditional trends shown in Figs. 1 and 2, although I do note that the raw size of the SRH gap is modestly larger when demographic controls are included, and the amount of convergence is modestly smaller. These differences primarily reflect black NHIS respondents having lower average ages than white respondents, differences which become larger over the course of the study period.4 The different age profiles of black and 4 In the full sample the mean age of black respondents is 43.88 years, relative to a mean of 47.17 years for white respondents, a difference of 3.29 years. These
72
O. Thompson / Economics Letters 154 (2017) 69–73 Table 1 Trends in self-rated health by race and survey year or cohort. (1)
(2)
(3)
−12.367***
−10.004*** (0.372) 0.004*** (0.000) 0.005*** (0.000) 2,152,146 0.111
−8.888***
(0.393) 0.002*** (0.000) 0.006*** (0.000) 2,152,146 0.009
(0.000) 0.004*** (0.000) 1,819,535 0.198
Observations R-squared
10.726*** (1.548) 0.017*** (0.000) −0.006*** (0.001) 527,110 0.025
13.497*** (1.541) 0.011*** (0.000) −0.007*** (0.001) 527,110 0.045
25.498*** (1.699) −0.010*** (0.000) −0.013*** (0.001) 432,935 0.132
Panel C: By birth cohort 1936–1982 Black
−19.239***
−20.395*** (0.425) 0.001*** (0.000) 0.010*** (0.000) 1,421,370 0.066 Y N
−17.893***
Panel A: By survey year Black Survey year Black × Survey year Observations R-squared Panel B: By birth cohort 1910–1935 Black Cohort Black × Birth cohort
Cohort Black × Birth cohort Observations R-squared Demographic controls SES controls
(0.430) 0.012*** (0.000) 0.010*** (0.000) 1,421,370 0.036 N N
(0.391)
−0.013***
(0.459)
−0.014*** (0.000) 0.009*** (0.000) 1,209,897 0.174 Y Y
Notes: Dependent variable in all specifications is self-rated health. Demographic controls include gender, age indicators, and four region of residence indicators. SES controls include 9 education categories and 47 household income categories. Robust standard errors reported in parentheses. * Indicate statistical significance at the 10% level. ** Indicate statistical significance at the 5% level. *** Indicate statistical significance at the 1% level.
white NHIS respondents may reflect differential mortality, racial differences in non-response not fully accounted for by sampling weights, or other factors, but for present purposes it is sufficient to note that there was a substantial narrowing of the black–white SRH gap between 1972 and 2015 even after conditioning on age and other demographic characteristics. The dashed lines in Fig. 3 show results when indicators for 9 education categories and 47 household income categories are included as control variables in addition to the described demographic characteristics. The results show that for both SRH measures, the racial gap is considerably smaller after conditioning on SES, but that the relative magnitude of black–white convergence is similar to the baseline models. Specifically, the conditional black– white difference in the semi-continuous SRH measure falls from approximately .20 in the 1970s to around .10 by the mid 2000s, a reduction of approximately 50%, with qualitatively similar findings for the binary measure of poor or fair SRH. These results suggest that the documented convergence is not driven by relative improvements in the SES of blacks. Figs. 1–3 analyzed race-specific trends in SRH across survey years, but it is also possible to analyze trends across birth cohorts.5 differences are somewhat larger in later NHIS waves: Within the 1972–1994 NHIS waves the mean age of black respondents is 2.67 years lower than that of white respondents, while within the 1995–2015 waves the mean age of black respondents is 4.08 years lower than that of white respondents. 5 Because survey year, age, and birth cohort are perfectly collinear (year = cohort + age), the models from Fig. 3 that included age controls implicitly held birth cohort constant as well, and in general it is not possible to simultaneously identify independent effects for year, age and cohort. Given this, I emphasize that the reported trends are purely descriptive in nature, and do not identify any plausibly ‘causal’ effect of survey year independent of age and cohort, or any plausibly ‘causal’ effect of cohort independent of age and survey year.
Fig. 4 does so by reporting the results of estimating Eq. (1) separately within each birth cohort from 1910 through 1982 rather than within each calendar year from 1972–2015.6 The first panel of Fig. 4 uses the semi-continuous SRH measure, and indicates that the black–white SRH gap actually grew moderately larger for cohorts born between 1910 and approximately 1935, but then declined substantially from 1935 through 1982. The most rapid convergence occurs between the 1947 and 1974 cohorts, when the black–white gap in SRH declined from over .50 to less than .20. The second panel of Fig. 4 uses the binary indicator of poor or fair SRH, and has generally similar findings, with a black–white gap of approximately .18 for cohorts born before 1935, which declines to less than .05 by the 1970 cohort. It is noteworthy that the strongest trends in Fig. 4 are observed across cohorts that were children and young adults during the Civil Rights Movement and subsequent federal policy changes. Previous research has found beneficial health impacts from access to desegregated health care facilities (Chay et al., 2009) and improvements in relative black school quality (Frisvold and Golberstein, 2013), and the documented reductions in the black–white SRH gap over time may partially reflect these and related factors.7 However, I emphasize that additional research would be needed to rigorously evaluate any potential explanations for the observed cohort trends. 6 No additional controls are included, but the results are similar when conditioning on age or survey year as well as on additional demographic or SES related characteristics. 1910 and 1982 are respectively the 5th and 95th percentiles of the cohort distribution in the full sample. 7 The cohort trends shown in Fig. 4 are modestly stronger within the South than outside of the South, but the scope for regional disaggregation is limited because the NHIS only collects information on region of residence, not region of origin.
O. Thompson / Economics Letters 154 (2017) 69–73
A final issue is that while Figs. 1–4 reported 95% confidence intervals for each year/cohort, statistical tests of whether the trends achieve significance were not conducted. Table 1 reports the results of specifications that pool data from all years/cohorts of the study period, then regress SRH onto a black indicator, a linear year or cohort variable, and an interaction between black and year or cohort (for the cohort models separate cohort-black interactions are estimated before and after the 1935 cohort). In all cases the coefficients on the interactions are highly statistically significant, indicating that the documented trends are very unlikely to be due to sampling error. 4. Conclusion This paper has documented that the black–white gap in SRH fell by approximately 50% between 1972 and 2015. This convergence is not explained by changes in the demographics or relative SES levels of blacks and whites. Cohort-based analyses indicate that the most rapid convergence occurred across the 1947–1974 cohorts. Future
73
research exploring potential explanations for these reductions in the black–white SRH gap is warranted. References Adler, N., Rehkopf, D., 2008. US disparities in health: Descriptions, causes, and mechanisms. Annu. Rev. Public Health 29, 235–252. Boustan, L., Margo, R., 2016. Racial differences in health in the United States. In: The Oxford Handbook of Economics and Human Biology. Oxford University Press. Chatterji, P., Joo, H., Lahiri, K., 2012. Beware of being unaware: Racial/ethnic disparities in chronic illness in the USA. Health Econ. 21 (9), 1040–1060. Chay, K., Guryan, J., Mazumder, B., 2009. Birth cohort and the black–white achievement gap: The roles of access and health soon after birth. NBER WP #15078. Frisvold, D., Golberstein, E., 2013. The effect of school quality on black–white health differences: Evidence from segregated southern schools. Demography 50 (6), 1989–2012. Idler, E., Benyamini, Y., 1999. Community studies reporting association between self-rated health and mortality. Res. Aging 21, 392–401. McGee, D., et al., 1999. Self-reported health status and mortality in a multiethnic US cohort. Am. J. Epidemiol. 149 (1), 41–46. Minnesota Population Center, 2016. Integrated Health Interview Series, Version 6.21. University of Minnesota, Minneapolis.