Full access

Articles

Published Online: 11 April 2023

Differences in Social Determinants of Health Underlie Racial/Ethnic Disparities in Psychological Health and Well-Being: Study of 11,143 Older Adults

Dylan J. Jester, Ph.D., M.P.H. [email protected], Jordan N. Kohn, Ph.D., Lize Tibiriçá, Psy.D., Michael L. Thomas, Ph.D., Lauren L. Brown, Ph.D., M.P.H., James D. Murphy, M.D., M.Sc., and Dilip V. Jeste, M.D.Authors Info & Affiliations

Publication: American Journal of Psychiatry

Volume 180, Number 7

https://doi.org/10.1176/appi.ajp.20220158

CME

PDF/EPUB

Abstract

Objective:

The authors sought to determine the impact of selected social determinants of health (SDoH) on psychological health and well-being (defined as depression, cognition, and self-rated health) among Black and Hispanic/Latinx adults relative to White adults 51–89 years of age.

Methods:

Disparities in depressive symptomatology, cognition, and self-rated health were measured among 2,306 non–Hispanic/Latinx Black, 1,593 Hispanic/Latinx, and 7,244 non–Hispanic/Latinx White adults who participated in the Health and Retirement Study (N=11,143). Blinder-Oaxaca decomposition was used to examine whether differences in selected SDoH explained a larger share of the disparities than age, sex, measures of health, health behaviors, and health care utilization. Selected SDoH included education, parental education, number of years worked, marital status, veteran status, geographic residence, nativity status, income, and insurance coverage.

Results:

Black and Hispanic/Latinx adults reported worse depressive symptomatology, cognition, and self-rated health than White adults. Selected SDoH were associated with a larger proportion of the Black–White disparities in depressive symptomatology (51%), cognition (39%), and self-rated health (37%) than were age, sex, measures of health, health behaviors, and health care utilization. SDoH were associated with a larger proportion of the Hispanic/Latinx–White disparity in cognition (76%) and self-rated health (75%), but age and physical health correlated with the disparity in depressive symptomatology (28%). Education, parental education, years worked, income, and insurance parity were SDoH associated with these disparities.

Conclusions:

Differences in SDoH underlie racial/ethnic disparities in depression, cognition, and self-rated health among older adults. Education, income, number of years worked, and insurance parity are key SDoH.

The tenets of social epidemiology suggest that where and how we live, work, play, and age affect our health and well-being (1). While some social determinants of health (SDoH) are modifiable (e.g., health behaviors) or related to our lived environment (e.g., affordability of and access to health care), others are difficult to change in older age (e.g., childhood education quality, nativity status, occupational history, and income). It is well established that Black and Hispanic/Latinx adults in the United States experience poorer health outcomes and have lower health care utilization compared with White adults (2, 3). Disparities in one domain of health may intersect with and precipitate disparities in another domain (2), and while some health disparities compound over time (i.e., cumulative disadvantage) (4), others are triggered by a decline in health or are persistent across the lifespan (2). The origins of most health disparities are complex and difficult to disentangle because overt and covert (structural) racism (5) and discrimination have shaped SDoH among racially and ethnically marginalized adults in the United States.

Black adults are more likely than White adults to have multiple chronic diseases, while Hispanic/Latinx adults are less likely than both Black and White adults to have multimorbidity (6). In analyses of the Health and Retirement Study (HRS), it was shown that Black adults developed multimorbidity at an earlier age than White adults and that both Black and Hispanic/Latinx adults were more likely than White adults to experience severe and persistent functional disability (2, 7, 8). In addition to poorer physical health, marginalized older adults often report worse mental health, although Black and Hispanic/Latinx older adults are less likely than White older adults to be screened for or diagnosed with depression (9). This may be due to disparities in mental health care initiation and adequacy (10) or beliefs surrounding mental illness, stigma, and preferences for treatment (11). Depressive symptomatology is thought to be greater among Black and Hispanic/Latinx adults than among White adults 50 to 75 years of age; however, this disparity narrows substantially between ages 76 and 90 (12). In addition to having greater depressive symptomatology, Black older adults may be more socially disconnected, have greater perceived isolation, and have smaller social networks (13). Some studies suggest that the rate of loneliness is higher among Hispanic/Latinx adults than among White adults (14), while other studies do not show this relationship (15). Deficits in cognition among marginalized adults have been linked to poor early-life educational quality and literacy in addition to other health, psychosocial, and socioeconomic factors (16, 17). While these findings paint a picture of poorer health and well-being among Black and Hispanic/Latinx adults, the healthy immigrant paradox (18) suggests that immigrants and migrants may appear healthier than their U.S.-born counterparts, and differences in these outcomes may exist across ethnic subgroups.

Understanding the effects of SDoH on psychological health and well-being across racial and ethnic groups is crucial for the development of primordial prevention strategies (e.g., policies targeting socioenvironmental risk factors at an early age to prevent downstream disadvantage and morbidity). Several SDoH are known to affect psychological health and well-being (operationalized in this study as depressive symptomatology, cognition, and self-rated health). Education and income indirectly influence health and well-being through differences in health behaviors, diet, environmental exposures, and access to health care (19–21) and have direct effects on factors such as cognitive reserve (22) and allostatic load (23). Beyond socioeconomic status and health care access, other SDoH, such as marital status (with depressed affect, loneliness, and social isolation as possible mechanisms) (24), veteran status (potentially associated with increased allostatic load, posttraumatic stress disorder, and substance abuse) (25), nativity status (resulting in acculturation and perceived discrimination) (20, 26), and geographic place of residence (e.g., exposure to the “Southern diet” in the United States and differential access to quality education, health care, and jobs) (27, 28), are known to influence health and well-being. Whether SDoH explain a larger proportion of the Black–White and Hispanic/Latinx–White disparities in psychological health and well-being compared with other well-known correlates of health is less well understood.

Using data from the HRS, we posit that selected SDoH (i.e., education, parental education, number of years worked, marital status, veteran status, geographic residence, nativity status, income, and health insurance coverage) will explain a larger share of the disparities in depressive symptomatology, cognition, and self-rated health among Black and Hispanic/Latinx adults compared with White adults than age, sex, measures of health, health behaviors, and health care utilization. By identifying the primary SDoH that drive racial and ethnic disparities in psychological health and well-being, government agencies and health care systems can better allocate resources to interventions and policies that will appreciably reduce health inequities.

Methods

Methodological references, detailed descriptions of the study variables, and model specifications are provided in the online supplement.

Participants

The HRS is a publicly available prospective cohort study of adults ≥51 years of age in the United States that started in 1992 with assessments occurring every 2 years. Black adults were oversampled from the southern portion of the United States, and Hispanic/Latinx adults were oversampled from the western portion of the United States. We utilized the RAND HRS longitudinal file because it contains imputed variables (e.g., cognition and wealth and income), which were crucial for modeling. We used data from wave 13 (2016) of the HRS.

Few participants age 90 or older identified as Black or Hispanic/Latinx, and therefore participants in the Baby Boomer and Silent Generation cohorts were selected (born between 1928 and 1964). After excluding participants based on their birth year, participants identifying their race as “other” and not identifying as Hispanic/Latinx and those without scores on the 8-item Center for Epidemiologic Studies Depression Scale (CES-D) or the Modified Telephone Interview for Cognitive Status (TICS-M) were excluded (see Figure S1 in the online supplement). A final sample of 11,143 adults was retained as our analytic sample (2,306 non–Hispanic/Latinx Black, 1,593 Hispanic/Latinx, and 7,244 non–Hispanic/Latinx White adults). Participants identifying as Black, “other,” or White and Hispanic/Latinx were categorized as Hispanic/Latinx.

Outcomes and Measures

We operationalized psychological health and well-being as depressive symptomatology, cognition, and self-rated health. Depressive symptomatology was measured by the CES-D (range, 0–8). Global cognition was measured with the total cognition score from the TICS-M (range, 0–30). Participants were asked to rate their general health from 1 (excellent) to 5 (poor).

Selected Social Determinants of Health

Selected SDoH included education (years), mother’s education (years), father’s education (years), number of years worked (years), marital status (dummy coded with 1 indicating married, married with an absent spouse, or partnered and 0 indicating separated, divorced, widowed, or never married), veteran status (yes [1] or no [0]), southern U.S. resident (dummy coded with 1 indicating south and 0 indicating northeast, midwest, west, or other U.S. resident), nativity status (non-U.S. born [1] or U.S. born [0]), annual household income (in U.S. dollars, natural-log transformed), employer-sponsored health insurance coverage (yes [1] or no [0]), Medicare coverage (yes [1] or no [0]), and Medicaid coverage (yes [1] or no [0]).

Statistical Analysis

Participant characteristics are reported with descriptive statistics, and unadjusted differences between racial/ethnic groups were examined with analysis of variance or chi-square tests. For both continuous and categorical variables, effect sizes, computed as Cohen’s d, were used to compare groups of Black and White adults and groups of Hispanic/Latinx and White adults (see Methods section in the online supplement).

To determine whether SDoH explained much of the Black–White and Hispanic/Latinx–White disparities in depressivesymptomatology, cognition, and self-rated health, twofold Blinder-Oaxaca decomposition was used with reference coefficients recovered from a pooled regression model that included group membership in the model, as recommended by Jann (29). Blinder-Oaxaca decomposition was used to estimate the magnitude of the disparity between Black and White participants and then between Hispanic/Latinx and White participants. Next, the disparity was decomposed into a characteristics effect (i.e., variance explained by differences in the characteristics of each group) and a coefficients effect (i.e., variance explained by differences in beta coefficients when linear regressions are conducted for each group).

As an example, assume that Black participants were younger than White participants in the HRS. The characteristics effect would determine what proportion of the disparity in cognition was explained by the younger age of the Black participants. The coefficients effect would determine what proportion of the disparity in cognition was driven by differences in the beta coefficients for age. Because no simple explanation exists for why a beta coefficient differs by race/ethnicity, the coefficients effect is often referred to as the “unexplained” effect. In labor economics, the coefficients effect often represents discrimination. However, in our study, the coefficients effect could represent nonequivalent effects of the covariates (e.g., 1 year of education does not have an equivalent effect across groups), testing biases by group (e.g., questions in the CES-D may be culturally specific), or error variance due to unobserved constructs. In this report, the results focus on the characteristics effects.

To improve interpretability of the results, estimates were converted to shares, which represent the proportion of the disparity that the covariate explains. A positive share for age would suggest that if Black and White adults were the same age, the disparity in cognition would decrease. In contrast, a negative share would indicate that if Black and White adults were the same age, the disparity in cognition would increase. Shares that exceed 100% indicate that the marginalized group would be better off than White adults if characteristics were equivalent. Rather than reporting p values, 95% confidence intervals were calculated. Share intervals that contained 0% were considered null effects.

Results

Table 1 summarizes the comparisons among Black, Hispanic/Latinx, and White participants. Notably, most differences between Black or Hispanic/Latinx adults and White adults were small (d<0.20) or small to medium (0.20≤d<0.50) effect sizes. Black adults differed from White adults with medium (0.50≤d<0.80) or large (d≥0.80) effect sizes on age, income, and cognition. Hispanic/Latinx adults differed from White adults with medium or large effect sizes for age, education, parental education, number of years worked, nativity status, income, Medicaid coverage, doctor visits, and cognition. The characteristics of excluded participants were similar to those of the included participants (see Table S1 in the online supplement).

TABLE 1. Comparisons of racial/ethnic groups in a study evaluating the influence of social determinants of health on psychological health and well-being in older adults^a

Variable	White (N=7,244)		Black (N=2,306)		Hispanic/Latinx (N=1,593)		p	Black vs. White	Hispanic/Latinx vs. White
	Race/Ethnicity						Significance and Effect Size Estimate (Cohen’s d)^b
Social determinants of health
	Mean	SD	Mean	SD	Mean	SD
Education (years)	13.49	2.53	12.59	2.85	10.07	4.46	<0.001	0.35	1.15
Mother’s education (years)	11.03	3.03	9.92	3.58	6.03	4.55	<0.001	0.35	1.50
Father’s education (years)	10.65	3.63	8.98	3.98	6.20	4.82	<0.001	0.45	1.16
Number of years worked	34.82	16.45	26.54	17.73	21.06	16.88	<0.001	0.49	0.83
Annual household income (natural-log USD)	10.8	0.99	10.26	1.16	10.13	1.07	<0.001	0.52	0.66
	Median		Median		Median
Annual household income (USD)	47,673		28,975		25,200
	%	N	%	N	%	N
Marital status							<0.001
Married or partnered	63	4,534	42	968	59	943		0.37	0.06
Divorced or separated	13	917	26	601	18	287		0.32	0.12
Widowed	21	1,517	19	447	16	252		0.04	0.10
Never married	4	270	12	285	7	107		0.32	0.12
Veteran	20	1,478	15	340	8	127	<0.001	0.12	0.24
U.S. geographic location							<0.001
Northeast	14	1,002	15	357	14	221		0.04	0.00
Midwest	28	1,995	17	385	5	84		0.22	0.41
South	40	2,915	60	1,384	40	629		0.35	0.02
West	18	1,325	8	179	40	642		0.24	0.41
Other	<1	4	0	0	1	14		0.02	0.14
Non-U.S. born	5	326	7	154	61	968	<0.001	0.08	1.54
Current or previous employer insurance coverage	21	1,525	24	550	18	275	<0.001	0.06	0.06
Government program insurance coverage	84	6,007	73	1,665	67	1,045	<0.001	0.22	0.32
Medicare	81	5,829	65	1,471	58	902	<0.001	0.35	0.43
Medicaid	6	451	19	434	26	398	<0.001	0.39	0.52
Veterans Administration	7	502	7	170	4	55	<0.001	0.02	0.10
Demographic characteristics
	Mean	SD	Mean	SD	Mean	SD
Age (years)	71.43	9.79	65.99	10.46	65.48	10.48	<0.001	0.55	0.60
	%	N	%	N	%	N
Demographic cohort							<0.001	0.41	0.39
Silent Generation (1928–1945)	76	4,298	15	837	10	544
Baby Boomers (1946–1964)	54	2,946	27	1,469	19	1,049
Male	43	3,115	40	918	44	708	0.007	0.06	0.02
Spanish-language survey preference	<1	13	0	0	50	797	<0.001	0.04	1.76
Physical health measures
	Mean	SD	Mean	SD	Mean	SD
Self-rated health (1 [excellent] to 5 [poor])	2.82	1.03	3.10	1.04	3.24	1.07	<0.001	0.27	0.40
Body mass index	28.23	5.91	30.19	6.60	29.23	5.76	<0.001	0.32	0.17
Impaired activities of daily living (0–5)	0.26	0.77	0.44	0.99	0.46	1.07	<0.001	0.21	0.23
Impaired instrumental activities of daily living (0–5)	0.23	0.67	0.34	0.85	0.40	0.96	<0.001	0.15	0.23
Chronic conditions (0–8)	2.43	1.52	2.37	1.53	2.09	1.55	<0.001	0.04	0.22
	%	N	%	N	%	N
Hypertension	62	4,450	76	1,740	61	974	<0.001	0.26	0.00
Diabetes mellitus	24	1,722	34	785	37	583	<0.001	0.20	0.22
Cancer or malignancy (excluding skin cancer)	20	1,462	13	310	9	144	<0.001	0.14	0.22
Chronic lung disease	12	895	10	225	7	109	<0.001	0.06	0.14
Cardiovascular disease	30	2,183	22	506	18	289	<0.001	0.16	0.20
Stroke or transient ischemic attack	9	685	10	234	7	111	0.002	0.02	0.06
Psychiatric disorder	20	1,455	15	341	21	327	<0.001	0.12	0.00
Arthritis or rheumatism	65	4,720	58	1,326	49	785	<0.001	0.14	0.26
Ever diagnosed with a sleep disorder	16	1,187	16	359	14	223	0.05	0.02	0.06
Mental health and cognition measures
	Mean	SD	Mean	SD	Mean	SD
CES-D total score	1.29	1.86	1.73	1.97	1.89	2.24	<0.001	0.23	0.31
Total cognition (TICS-M)	22.93	4.69	20.12	5.22	19.87	5.06	<0.001	0.58	0.64
Mental status summary score	13.10	2.17	11.52	2.77	11.33	2.72	<0.001	0.68	0.78
Total word recall	9.83	3.34	8.61	3.32	8.53	3.24	<0.001	0.37	0.39
Immediate word recall	5.39	1.64	4.99	1.63	4.75	1.62	<0.001	0.24	0.39
Delayed word recall	4.44	1.92	3.61	1.96	3.78	1.85	<0.001	0.43	0.34
	%	N	%	N	%	N
Clinical depression (CES-D score ≥3)	18	1,331	26	590	28	452	<0.001	0.16	0.20
Felt lonely	15	1,121	20	453	22	352	<0.001	0.10	0.14
Alzheimer’s disease or related dementia diagnosis	2	164	3	61	3	54	0.03	0.02	0.06
Health behaviors and health care utilization (past 2 years)
	%	N	%	N	%	N
Ever smoked cigarettes	56	4,049	54	1,247	50	798	<0.001	0.04	0.08
Physical activity ≥once/week	72	5,169	64	1,463	68	1,071	<0.001	0.14	0.06
Hospital stay	28	2,031	28	628	21	329	<0.001	0.02	0.12
Nursing home stay	4	310	3	71	2	27	<0.001	0.06	0.10
Doctor visit	95	6,845	89	2,040	76	1,200	<0.001	0.20	0.54
Dental visit	69	4,988	51	1,173	57	900	<0.001	0.32	0.20
Utilized home health care	9	625	10	239	7	103	<0.001	0.06	0.06
Received outpatient surgery	24	1,735	15	346	13	211	<0.001	0.18	0.20
Regular use of prescription drugs	86	6,248	82	1,890	76	1,200	<0.001	0.10	0.22
	Mean	SD	Mean	SD	Mean	SD
Alcohol consumption (days/week)	1.40	2.20	0.81	1.57	0.71	1.48	<0.001	0.28	0.33
Hospital stays (number)	0.54	1.72	0.61	2.53	0.47	2.50	0.12	0.03	0.04
Nursing home stays (number)	0.06	0.61	0.05	0.42	0.02	0.18	0.008	0.03	0.08
Doctor visits (number)	10.61	17.15	9.35	23.17	6.92	16.50	<0.001	0.07	0.22

Household income reflects total income for the last calendar year and is the sum of participant and spouse earnings, pensions and annuities, Social Security income, Social Security disability, Social Security retirement, unemployment and workers compensation, other government transfers, household capital income, and other income. Reported or imputed household income of $0 was set to missing (N=176) to calculate the natural-log transformation. Marital status is truncated in this table for ease of interpretation, but all levels were analyzed with chi-square tests. Total cognition (range, 0–35) was the sum of the mental status and total word recall scores. The mental status score (range, 0–15) was the sum of scores from the serial 7’s (0–5 points), backward counting from 20 (0–2 points), object (0–2 points), date (0–4 points), and U.S. president and vice president naming (0–2 points) tasks. The total word recall score (range, 0–20) was the sum of the immediate and delayed word recall scores. The immediate word recall score (range, 0–10) was the count of correctly identified words from a 10-word list of nouns, and the delayed word recall score (range, 0–10) was the count of correctly identified words from a 10-word list of nouns after 5 minutes, during which time the participant answered other survey questions. Physical activity included vigorous, moderate, or light activities that occurred at least once per week. Denominators used to calculate proportions excluded those with missingness. CES-D=8-item Center for Epidemiologic Studies Depression Scale; TICS-M=Telephone Interview for Cognitive Status–Modified.

The p values come from analysis of variance for continuous variables and chi-square tests for categorical variables. Effect sizes are the absolute value of Cohen’s d (negative values are not reported for ease of interpretation). Small effect sizes are in the range of d<0.20; small to medium, 0.20≤d<0.50; medium, 0.50≤d<0.80; and large, d≥0.80.

Decomposition of Black–White Disparities

If Black and White adults had similar characteristics, 138% of the disparity in depressive symptomatology, 14% of the disparity in cognition, and 85% of the disparity in self-rated health would be attenuated (Table 2). That is, the majority of the disparities in depressive symptomatology and self-rated health were associated with differences in the characteristics of each group, while differences in cognition were largely unexplained and thus due to other variables not captured in this study. A share of 138% for depressive symptomatology suggests that if the characteristics between Black and White adults were equivalent, Black adults would have fewer depressive symptoms than White adults.

TABLE 2. Decomposition of disparities between Black and White adults, ages 51–89, on measures of depression, cognition, and self-rated health^a

Characteristic	Depression (CES-D)		Cognition (TICS-M)		Self-Rated Health(1 [excellent]– 5 [poor])
	Mean		Mean		Mean
Non–Hispanic/Latinx Black	1.568		20.759		3.029
Non–Hispanic/Latinx White	1.210		23.238		2.774
Unadjusted disparity	0.358		2.479		0.254
	Estimate	Share (%)	Estimate	Share (%)	Estimate	Share (%)
Aggregate decomposition of disparity
Characteristics effect (explained)	0.495	138	0.345	14	0.217	85
Coefficients effect (unexplained)	−0.137	−38	2.134	86	0.038	15
Subaggregate characteristics effects
Social determinants of health		51		39		37
Education (years)	0.007	2	0.275	11^b	0.012	5^b
Mother’s education (years)	0.001	0	0.020	1	0.011	4
Father’s education (years)	0.008	2	0.064	3	0.009	4
Number of years worked	0.043	12^b	0.145	6^b	0.018	7^b
Married	0.079	22^b	−0.049	−2	−0.009	−3
Veteran status	0.000	0	0.006	0	0.001	0
Southern U.S. resident	−0.003	−1	0.018	1	−0.001	0
Non-U.S. born	0.002	1	0.001	0	0.000	0
Annual income (natural-log USD)	0.022	6	0.224	9^b	0.040	16^b
Employer-sponsored health insurance	−0.007	−2	0.000	0	−0.002	−1
Medicaid reimbursed	0.014	4	0.097	4^b	0.003	1
Medicare reimbursed	0.015	4	0.155	6^b	0.011	4
Demographic characteristics		44		−31		8
Age	0.152	42^b	−0.740	−30^b	0.022	9^b
Male	0.006	2	−0.037	−1	−0.002	−1
Physical health measures		28		1		7
Self-rated health	0.103	29^b	0.053	2^b	–	–
Impaired activities of daily living	0.030	8^b	0.010	0	0.015	6^b
Impaired instrumental activities of daily living	0.016	5^b	0.053	2^b	0.004	2
Chronic conditions	−0.011	−3	−0.003	0	−0.014	−5
Body mass index	−0.038	−11^b	−0.079	−3^b	0.014	5^b
Sleep disorder diagnosis	−0.001	0	0.001	0	−0.001	0
Mental health and cognition measures		12		1		25
CES-D score (no loneliness item)	–	–	0.012	1	0.041	16^b
Felt lonely	–	–	0.015	1	0.000	0
Total cognition (TICS-M)	0.045	12^b	–	–	0.024	9^b
Alzheimer’s disease or related dementia diagnosis	0.000	0	0.001	0	0.000	0
Health behaviors and health care utilization		3		4		7
Ever smoked cigarettes	−0.001	0	−0.004	0	−0.002	−1
Alcohol consumption (days/week)	−0.005	−1	0.024	1	0.013	5^b
Physical activity ≥once/week	0.011	3^b	0.039	2^b	0.014	5^b
Doctor visit in past 2 years	0.007	2	0.049	2^b	−0.002	−1
Hospitalization in past 2 years	0.000	0	−0.006	0	−0.005	−2

The first three rows list the unadjusted disparity for the corresponding racial/ethnic group compared with White adults. The aggregate decomposition of disparity represents the characteristics effects and coefficients effects after adjusting for all variables listed in the table. Subaggregate characteristics effects represent the amount of disparity that each variable explains (estimate) and the value represented as a percentage (share). For details on the variables, see footnote a in Table 1. All values rounded to 0.000 have no directionality labeled. Proportions were calculated with unrounded estimates (10 digits). CES-D=8-item Center for Epidemiologic Studies Depression Scale; TICS-M=Telephone Interview for Cognitive Status–Modified.

Indicates that the 95% confidence interval does not contain 0%.

Selected SDoH accounted for the largest share of the disparities in depressive symptomatology (51%), cognition (39%), and self-rated health (37%) among Black adults (Figure 1). Marital status (share=22%, 95% CI=16–28) and number of years worked (share=12%, 95% CI=6–18) explained a significant amount of the disparity in depressive symptomatology. Significant proportions of the disparities in cognition and self-rated health were explained by education (share=11%, 95% CI=8–14; share=5%, 95% CI=2–8, respectively), income (share=9%, 95% CI=7–11; share=16%, 95% CI=11–21, respectively), and number of years worked (share=6%, 95% CI=4–8; share=7%, 95% CI=3–12, respectively). Additionally, Medicare coverage (share=6%, 95% CI=4–9) and Medicaid coverage (share=4%, 95% CI=2–6) were associated with the disparity in cognition.

FIGURE 1. Black–White unadjusted health disparities in depression, cognition, and self-rated health measures that would be reduced if participant characteristics in particular domains were equivalent across groups

Decomposition of Hispanic/Latinx–White Disparities

If Hispanic/Latinx and White adults had similar characteristics, 105% of the disparity in depressive symptomatology, 64% of the disparity in cognition, and 92% of the disparity in self-rated health would be attenuated (Table 3). That is, the majority of the disparities in all outcomes were associated with differences in the characteristics of each group. A share of 105% for depressive symptomatology suggests that if the characteristics between Hispanic/Latinx and White adults were equivalent, Hispanic/Latinx adults would have fewer depressive symptoms than White adults.

TABLE 3. Decomposition of disparities between Hispanic/Latinx and White adults, ages 51–89, on measures of depression, cognition, and self-rated health^a

Characteristic	Depression (CES-D)		Cognition (TICS-M)		Self-Rated Health(1 [excellent]–5 [poor])
	Mean		Mean		Mean
Hispanic/Latinx	1.704		20.497		3.174
Non–Hispanic/Latinx White	1.210		23.238		2.774
Unadjusted disparity	0.494		2.742		0.400
	Estimate	Share (%)	Estimate	Share (%)	Estimate	Share (%)
Aggregate decomposition of disparity
Characteristics effect (explained)	0.519	105	1.751	64	0.366	92
Coefficients effect (unexplained)	−0.026	−5	0.990	36	0.034	8
Subaggregate characteristics effects
Social determinants of health		28		76		75
Education (years)	0.012	2	1.110	40^b	0.063	16^b
Mother’s education (years)	−0.029	−6	0.032	1	0.056	14^b
Father’s education (years)	0.024	5	0.142	5	0.039	10^b
Number of years worked	0.058	12^b	0.272	10^b	0.036	9^b
Married	0.015	3	−0.004	0	−0.002	0
Veteran	−0.002	0	−0.004	0	0.005	1
Southern U.S. resident	0.000	0	−0.001	0	0.000	0
Non-U.S. born	−0.020	−4	−0.067	−2	0.022	6
Annual income (natural-log USD)	0.028	6	0.304	11^b	0.059	15^b
Employer-sponsored health insurance	0.002	0	0.001	0	0.001	0
Medicaid reimbursed	0.028	6	0.110	4^b	−0.003	−1
Medicare reimbursed	0.022	4	0.196	7^b	0.022	6^b
Demographic characteristics		32		−26		5
Age	0.162	33^b	−0.743	−27^b	0.019	5
Male	−0.006	−1	0.026	1	0.002	0
Physical health measures		35		4		−7
Self-rated health	0.162	33^b	0.076	3^b	–	–
Impaired activities of daily living	0.046	9^b	−0.002	0	0.023	6^b
Impaired instrumental activities of daily living	0.045	9^b	0.110	4^b	0.008	2
Chronic conditions	−0.052	−11^b	−0.027	−1	−0.060	−15^b
Body mass index	−0.023	−5^b	−0.041	−1^b	0.007	2
Sleep disorder diagnosis	−0.007	−1	0.004	0	−0.004	−1
Mental health and cognition measures		9		3		19
CES-D score (no loneliness item)	–	–	0.015	1	0.054	14^b
Felt lonely	–	–	0.029	1	−0.002	0
Total cognition (TICS-M)	0.043	9^b	–	–	0.024	6^b
Alzheimer’s disease or related dementia diagnosis	0.000	0	0.041	2	0.000	0
Health behaviors and health care utilization		2		6		−1
Ever smoked cigarettes	−0.003	−1	−0.004	0	−0.002	−1
Alcohol consumption (days/week)	−0.002	0	0.035	1	0.015	4^b
Physical activity ≥once/week	0.005	1	0.016	1	0.006	2
Doctor visits in past 2 years	0.010	2	0.145	5^b	−0.005	−1
Hospitalizations in past 2 years	0.000	0	−0.022	−1	−0.017	−4^b

Indicates that the 95% confidence interval does not contain 0%.

Selected SDoH accounted for the largest share of the disparities in cognition (76%) and self-rated health (75%) but not for depressive symptomatology (28%) among Hispanic/Latinx adults (Figure 2). Interestingly, number of years worked (share=12%, 95% CI=5–19) was the only social determinant associated with depressive symptomatology among Hispanic/Latinx adults. As with Black adults, differences in education (share=40%, 95% CI=34–47), income (share=11%, 95% CI=8–14), number of years worked (share=10%, 95% CI=6–13), Medicare coverage (share=7%, 95% CI=4–11), and Medicaid coverage (share=4%, 95% CI=1–7) explained the largest proportions of the disparity in cognition. Additionally, Hispanic/Latinx adults’ poorer self-rated health was associated with level of education (share=16%, 95% CI=9–23), number of years worked (share=9%, 95% CI=5–13), and income (share=15%, 95% CI=11–19). Poorer self-rated health among Hispanic/Latinx adults, unlike that of Black adults, was also related to their mothers’ education (share=14%, 95% CI=3–25), fathers’ education (share=10%, 95% CI=2–18), and Medicare coverage (share=6%, 95% CI=2–9).

FIGURE 2. Hispanic/Latinx–White unadjusted health disparities in depression, cognition, and self-rated health measures that would be reduced if participant characteristics in particular domains were equivalent across groups

Sensitivity Analyses

Sensitivity analyses were conducted to determine whether the Hispanic/Latinx–White comparison differed by nativity status. No appreciable differences were found. Threefold decomposition was conducted to consider the interaction between the characteristics effects and coefficients effects. All findings in this analysis were consistent with or more pronounced than those in the initial analysis.

Discussion

Our hypotheses were fully supported for the Black–White disparities in depressive symptomatology, cognition, and self-rated health, with SDoH explaining the largest share of each disparity (51%, 39%, and 37%, respectively). For the Hispanic/Latinx–White comparisons, the findings were less straightforward; SDoH did not account for the largest share in depressive symptomatology (age and physical health primarily accounted for this disparity), but they were associated with the largest proportions of the disparities in cognition (76%) and self-rated health (75%). These effects were larger than what was reported for the Black–White comparison (39% and 37%, respectively), suggesting that disparities in cognition and self-rated health are more likely to be associated with differences in selected SDoH for Hispanic/Latinx adults than for Black adults. Because many SDoH are difficult to change in older age, primordial prevention strategies are needed to target health and health care access in early childhood and need to be carried throughout adulthood (e.g., policies aimed at educational quality, income inequality, insurance parity, and workers at risk of leaving the workforce).

In addition to the anticipated and well-documented effects of education and income inequity (20–22), number of years worked was associated with disparities in depressive symptomatology, cognition, and self-rated health among Black and Hispanic/Latinx adults. Number of years worked may index several factors, such as age, the ability to find and maintain employment, and disability status, all of which may correlate with psychological health and well-being. Although Black and Hispanic/Latinx adults were on average 6 years younger than White adults, they worked for 8 and 13 fewer years than White adults, respectively. This suggests that inequities in number of years worked were not explained by differences in age alone. It may be that physical functioning, ability to find and maintain adequate employment to meet financial needs (30), and familial caregiving responsibilities (31) contributed to the lower number of years worked among marginalized adults.

Given that most Black and Hispanic/Latinx older adults should be covered by Medicare in the United States, it is disconcerting that lower health care coverage and utilization was found among Black and Hispanic/Latinx adults. Although overall coverage and utilization rates among marginalized adults improved as a result of the Affordable Care Act (3), Black adults saw the smallest benefit (19). Several explanations for poorer health care coverage and utilization may exist, including de facto segregation of health care facilities and historical traumas. Although sanctioned forms of hospital segregation were eliminated in the 1960s, structural racism remains, partly due to housing segregation and other socioeconomic pressures (32). In addition to geographical location having an impact on access, health care coverage and utilization are also affected by distrust of medical systems by communities of color as a result of historical traumas (e.g., the Tuskegee syphilis experiment in Black men and forced sterilization of Latinas), age (i.e., beneficiary status), and willingness of employers to sponsor health insurance for blue-collar or unskilled workers—among whom Black and Hispanic/Latinx adults are disproportionately represented in the U.S. workforce (30). Furthermore, immigrants must be lawful permanent residents in the United States to receive Medicare, suggesting that nativity status may have had an indirect impact on these constructs through insurance parity.

One area of health that deserves greater attention is cognition, given the perpetuation of structural racism (5) despite the end of legal racial segregation and recent societal trends of improved access to education and health care. Our study found that the Black–White disparity in cognition was more difficult to explain (86% unexplained) than the Hispanic/Latinx–White disparity in cognition (36% unexplained). Participants’, mothers’, and fathers’ education in years were associated with the disparity to a greater extent among Hispanic/Latinx adults than among Black adults. This phenomenon suggests that 1 year of education is not equivalent among Black, Hispanic/Latinx, and White adults and that improving educational attainment (years alone) may not ameliorate cognitive disparities among Black adults in later life. The quality of education that Black older adults received in the Jim Crow era may have affected the comparability of years of education. Additionally, reading level (16), ageism, racism, xenophobia, and test bias are other relevant factors when measuring cognition among marginalized populations (33, 34) but were not accounted for in our study. Beyond education and discrimination, income and insurance parity correlated with cognition among Black and Hispanic/Latinx adults, meaning that health care access and utilization may influence these disparities. Language fluency and acculturation may also affect cognitive performance, particularly on measures that assess word recall and recognition if participants were tested in a nonnative language. Moreover, telephone and Internet assessments may not generalize as well to older adults from lower socioeconomic backgrounds. Understanding how SDoH map onto cognitive trajectories will be increasingly important, given the large and growing proportion of marginalized adults diagnosed with Alzheimer’s disease and related dementias (35).

Depressive symptomatology and self-rated health are constructs intimately related to psychological health and well-being. The Black–White mental health paradox suggests that Black adults have lower or similar rates of mental health disorders relative to White adults despite poorer physical health and being subjected to greater adversities (36). In our study and other studies that use the HRS (37), Black and Hispanic/Latinx adults endorsed greater depressive symptomatology and rated their health as poorer than White adults. Although the CES-D is commonly used to identify clinically significant depression, symptomatology cannot be directly related to psychiatric disorders. For example, Black adults may endorse greater symptomatology than White adults but may not meet the clinical threshold for major depressive disorder, as the criteria may be culturally, racially, or ethnically specific (see the Discussion and Reference sections in the online supplement). Interestingly, marital status was associated with the disparity in depressive symptomatology among Black adults, whereas age and physical health were associated with the disparity among Hispanic/Latinx adults. Being married is protective against depression (38), and the literature suggests that higher socioeconomic status, greater physical health, and being married may attenuate depression among Black and White adults (39). Although our study showed a relationship between physical health and depressive symptomatology, only a modest effect of income was reported. Rather, our study suggests that number of years worked was more strongly associated than income with the Black–White and Hispanic/Latinx–White disparities in depressive symptomatology. This provides further evidence that number of years worked remains a unique social determinant of health that operates independently from age and socioeconomic status, such that finding stable employment throughout one’s life may have a similar effect on psychological health and well-being whether at $20,000 or $200,000 per annum. Furthermore, others have proposed that chronic stress exposure and stress appraisal may explain the Black–White disparity in depressive symptomatology observed in the HRS (37). These constructs are likely along the causal pathway between SDoH and depressive symptomatology and should be investigated further.

Disparities in self-rated health were associated with differences in the characteristics of Black (85% explained) and Hispanic/Latinx (92% explained) adults. Inequities in selected SDoH accounted for a greater proportion of the disparities in self-rated health than age, sex, measures of health, health behaviors, and health care utilization. SDoH such as low educational attainment and income may have an impact on self-rated health through poor neighborhood safety and low physical activity (40). Our study provides nuance to these findings because self-rated health was not exclusively related to education and income. Self-rated health was also associated with number of years worked (among Black and Hispanic/Latinx adults) and parental education levels (among Hispanic/Latinx adults). Moreover, in line with the cumulative disadvantage theory (4), we found that inequities in cognition and depressive symptomatology were strongly associated with the disparity in self-rated health and that inequities in self-rated health were also associated with the disparities in depressive symptomatology among Black and Hispanic/Latinx adults.

This study has several limitations. Comparing Black and Hispanic/Latinx adults with White adults is arbitrary. Clinicians should refrain from viewing White adults as the gold standard of health and should work alongside their patients to develop culturally sensitive and appropriate treatment goals. Blinder-Oaxaca decomposition and the theory from which it developed assumes that one group is marginalized and that this marginalization can be explained through observed and unobserved effects. When using Blinder-Oaxaca decomposition to study disparities between two marginalized groups, it loses much of the meaning. Although we could not use Blinder-Oaxaca decomposition to adequately measure disparities between marginalized communities (i.e., to compare Black with Hispanic/Latinx adults), we believe that this topic deserves further investigation.

Our findings should be understood in the context of some level of selection bias and overrepresentation of specific ethnic subgroups. The majority of the Hispanic/Latinx participants were oversampled from the western portion of the United States and are disproportionately of Mexican ancestry. The Black participants were oversampled from the southern portion of the United States, where education, income, and health care access—historically—are particularly inequitable.

This study had a cross-sectional design and thus cannot be used to infer causality. Additionally, our definition of psychological health and well-being was limited to measures from a single scale of depressive symptomatology, a single item of self-rated health with five possible responses, and a single scale of cognitive function. Finally, using splines in future analyses may better control for nonlinear effects of age. (See the Discussion and Reference sections in the online supplement for additional material.)

In summary, we found strong evidence that selected SDoH accounted for larger proportions of Black–White disparities in depressive symptomatology, cognition, and self-rated health than each of the other four domains (demographics, physical health, mental health and cognition, and health behaviors and health care utilization). Conversely, selected SDoH were associated with larger proportions of the Hispanic/Latinx–White disparities in cognition and self-rated health, but other factors, such as age and physical health, were related to the disparity in depressive symptomatology.

Supplementary Material

File (appi.ajp.20220158.ds001.pdf)

View/Download
240.18 KB

REFERENCES

Braveman P, Egerter S, Williams DR: The social determinants of health: coming of age. Annu Rev Public Health 2011; 32:381–398

Format	RIS (ProCite, Reference Manager) EndNote BibTex Medlars RefWorks
Direct importt
Citation style
Style

Copy to clipboard
Tips for downloading citations

Abstract

Objective:

Methods:

Results:

Conclusions:

Methods

Participants

Outcomes and Measures

Selected Social Determinants of Health

Statistical Analysis

Results

Decomposition of Black–White Disparities

Decomposition of Hispanic/Latinx–White Disparities

Sensitivity Analyses

Discussion

Supplementary Material

REFERENCES

Information

Published In

History

Keywords

Authors

Details

Notes

Competing Interests

Funding Information

Metrics

Citations

Export Citations

View options

PDF/EPUB

Login options

Purchase Options

Not a subscriber?

Figures

Other

Share

Share article link

Share