Estimation and sensitivity analysis for causal decomposition in health disparity research

In the field of disparities research, there has been growing interest in developing a counterfactual-based decomposition analysis to identify underlying mediating mechanisms that help reduce disparities in populations. Despite rapid development in the area, most prior studies have been limited to regression-based methods, undermining the possibility of addressing complex models with multiple mediators and/or heterogeneous effects. We propose a novel estimation method that effectively addresses complex models. Moreover, we develop a sensitivity analysis for possible violations of an identification assumption. The proposed method and sensitivity analysis are demonstrated with data from the Midlife Development in the US study to investigate the degree to which disparities in cardiovascular health at the intersection of race and gender would be reduced if the distributions of education and perceived discrimination were the same across intersectional groups.

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Cardiovascular Health at the Intersection of Race and Gender: Identifying Life-Course Processes to Reduce Health Disparities

The Journals of Gerontology Series B ◽

10.1093/geronb/gbaa208 ◽

2020 ◽

Author(s):

Chioun Lee ◽

Soojin Park ◽

Jennifer M Boylan

Keyword(s):

Black Women ◽

Life Course ◽

Black Men ◽

White Women ◽

Cardiovascular Health ◽

Perceived Discrimination ◽

White Men ◽

Race And Gender ◽

And Gender ◽

Unmeasured Confounders

Abstract Objective Cardiovascular health (CVH) is associated with reductions in age-related disease and later-life mortality. Black adults, particularly Black women, are less likely to achieve ideal CVH. Guided by intersectionality and life-course approaches, we examine to what degree (a) disparities in CVH exist at the intersection of race and gender and (b) CVH disparities would be reduced if marginalized groups had the same levels of resources and adversities as privileged groups. Methods We used biomarker subsamples from the Midlife in the United States (MIDUS) core and Refresher studies (N = 1,948). Causal decomposition analysis was implemented to test hypothetical interventions to equalize the distribution of early-life adversities (ELAs), perceived discrimination, or midlife SES between marginalized and privileged groups. We conducted sensitivity analyses to determine to what degree unmeasured confounders would invalidate our findings. Results White women have the highest CVH score, followed by White men, Black men, and Black women. Intervening on ELAs would reduce the disparities: White men vs. Black women (30% of reduction) and White women vs. Black women (15%). Intervening on perceived discrimination would not substantially change initial disparities. Intervening on midlife SES would yield large disparity reductions: White men vs. Black men (64%), White men vs. Black women (60%), and White women vs. Black women (27%). These reductions are robust to unmeasured confounders. Discussion Providing economic security in adulthood for Blacks may help reduce racial disparities in CVH. Preventing exposure to ELAs among Black women may reduce their vulnerability to cardiovascular disease, compared to White adults.

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Women and ethnoracial minorities with poor cardiovascular health measures associated with a higher risk of developing mood disorder

BMC Medical Informatics and Decision Making ◽

10.1186/s12911-021-01674-9 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Aixia Guo ◽

Kari A. Stephens ◽

Yosef M. Khan ◽

James R. Langabeer ◽

Randi E. Foraker

Keyword(s):

Medical Records ◽

Cardiovascular Health ◽

Hemoglobin A1c ◽

American Heart ◽

The United States ◽

Outpatient Clinics ◽

Race And Gender ◽

Health Measures ◽

High Utility ◽

And Gender

Abstract Background Mood disorders (MDS) are a type of mental health illness that effects millions of people in the United States. Early prediction of MDS can give providers greater opportunity to treat these disorders. We hypothesized that longitudinal cardiovascular health (CVH) measurements would be informative for MDS prediction. Methods To test this hypothesis, the American Heart Association’s Guideline Advantage (TGA) dataset was used, which contained longitudinal EHR from 70 outpatient clinics. The statistical analysis and machine learning models were employed to identify the associations of the MDS and the longitudinal CVH metrics and other confounding factors. Results Patients diagnosed with MDS consistently had a higher proportion of poor CVH compared to patients without MDS, with the largest difference between groups for Body mass index (BMI) and Smoking. Race and gender were associated with status of CVH metrics. Approximate 46% female patients with MDS had a poor hemoglobin A1C compared to 44% of those without MDS; 62% of those with MDS had poor BMI compared to 47% of those without MDS; 59% of those with MDS had poor blood pressure (BP) compared to 43% of those without MDS; and 43% of those with MDS were current smokers compared to 17% of those without MDS. Conclusions Women and ethnoracial minorities with poor cardiovascular health measures were associated with a higher risk of development of MDS, which indicated the high utility for using routine medical records data collected in care to improve detection and treatment for MDS among patients with poor CVH.

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Cardiovascular Health at the Intersection of Race and Gender: Life-Course Processes to Reduce Health Disparities

Innovation in Aging ◽

10.1093/geroni/igaa057.1635 ◽

2020 ◽

Vol 4 (Supplement_1) ◽

pp. 506-507

Author(s):

Chioun Lee ◽

Soojin Park ◽

Jennifer Boylan

Keyword(s):

Black Women ◽

Black Men ◽

White Women ◽

Cardiovascular Health ◽

White Men ◽

The United States ◽

Economic Security ◽

Race And Gender ◽

And Gender ◽

Unmeasured Confounders

Abstract Objective: Higher cardiovascular health (CVH) scores are significantly associated with reductions in aging-related disease and mortality but racial minorities exhibit poor CVH. We examine the degree to which (a) disparities in CVH exist at the intersection of race and gender and (b) CVH disparities would be reduced if marginalized groups had the same levels of resources and adversities as privileged groups. Methods: We used biomarker subsamples from the Midlife in the United States (MIDUS) core study and Refresher studies (N=1,948). Causal decomposition analysis was implemented to test hypothetical interventions to equalize the distribution of early-life adversities (ELAs), perceived discrimination, or adult SES between marginalized and privileged groups. We conducted sensitivity analyses to determine to what degree unmeasured confounders would invalidate our findings. Results: White women have the highest CVH score, followed by White men, Black men, and Black women. Intervening on ELAs reduces the disparities: White men vs. Black women (30% of reduction) and White women vs. Black women (15%). Intervening on adult SES provides large disparity reductions: White men vs. Black men (79%), White men vs. Black women (70%), White women vs. Black men (25%), and White women vs. Black women (32%). Among these combinations, interventions on ELAs and adult SES are robust to unmeasured confounders. However, intervening on discrimination makes little change in initial disparities. Discussion: Economic security in midlife for Blacks helps reduce racial disparities in cardiovascular health. Preventing exposure to ELAs among Black women may reduce their vulnerability to cardiovascular disease, compared to Whites.

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Referral Patterns for Youths Identified at Risk for Suicide by Trained Gatekeepers

Crisis ◽

10.1027/0227-5910/a000114 ◽

2012 ◽

Vol 33 (2) ◽

pp. 113-119 ◽

Cited By ~ 10

Author(s):

Michael S. Rodi ◽

Lucas Godoy Garraza ◽

Christine Walrath ◽

Robert L. Stephens ◽

D. Susanne Condron ◽

...

Keyword(s):

Suicide Prevention ◽

Demographic Characteristics ◽

Service Access ◽

Referral Patterns ◽

Race And Gender ◽

Lee Smith ◽

Prevention Behavior ◽

Key Variables ◽

And Gender ◽

To Receive

Background: In order to better understand the posttraining suicide prevention behavior of gatekeeper trainees, the present article examines the referral and service receipt patterns among gatekeeper-identified youths. Methods: Data for this study were drawn from 26 Garrett Lee Smith grantees funded between October 2005 and October 2009 who submitted data about the number, characteristics, and service access of identified youths. Results: The demographic characteristics of identified youths are not related to referral type or receipt. Furthermore, referral setting does not seem to be predictive of the type of referral. Demographic as well as other (nonrisk) characteristics of the youths are not key variables in determining identification or service receipt. Limitations: These data are not necessarily representative of all youths identified by gatekeepers represented in the dataset. The prevalence of risk among all members of the communities from which these data are drawn is unknown. Furthermore, these data likely disproportionately represent gatekeepers associated with systems that effectively track gatekeepers and youths. Conclusions: Gatekeepers appear to be identifying youth across settings, and those youths are being referred for services without regard for race and gender or the settings in which they are identified. Furthermore, youths that may be at highest risk may be more likely to receive those services.

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