The gap-closing estimand: A causal approach to study interventions that close disparities across social categories

A Calibrated Sensitivity Analysis for Weighted Causal Decompositions

Disparities in health or well-being experienced by minority groups can be difficult to study using the traditional exposure-outcome paradigm in causal inference, since potential outcomes in variables such as race or sexual minority status are challenging to interpret. Causal decomposition analysis addresses this gap by positing causal effects on disparities under interventions to other intervenable exposures that may play a mediating role in the disparity. While invoking weaker assumptions than causal mediation approaches, decomposition analyses are often conducted in observational settings and require uncheckable assumptions that eliminate unmeasured confounders. Leveraging the marginal sensitivity model, we develop a sensitivity analysis for weighted causal decomposition estimators and use the percentile bootstrap to construct valid confidence intervals for causal effects on disparities. We also propose a two-parameter reformulation that enhances interpretability and facilitates an intuitive understanding of the plausibility of unmeasured confounders and their effects. We illustrate our framework on a study examining the effect of parental support on disparities in suicidal ideation among sexual minority youth. We find that the effect is small and sensitive to unmeasured confounding, suggesting that further screening studies are needed to identify mitigating interventions in this vulnerable population.

A hypothetical intervention to reduce inequities in anxiety for Multiracial people: simulating an intervention on childhood adversity

Multiracial people report higher mean Adverse Childhood Experience (ACE) scores and prevalence of anxiety than other racial groups. Studies using statistical interactions to test if associations between ACEs and anxiety are greater for this group than others have shown mixed results. Using data from waves 1 (1995-1997) through 4 (2008-2009) of the National Longitudinal Study of Adolescent to Adult Health (Add Health), we simulated a stochastic intervention over 1000 resampled datasets to estimate the race-specific cases averted per 1000 of anxiety if all racial groups had the same exposure distribution of ACEs as Whites. Simulated cases averted were greatest for the Multiracial group, (median = -4.17 cases per 1000; 95% CI; -7.42 to -1.86). The model also predicted smaller risk reductions for Black participants (-0.76; 95% CI, -1.53 to -0.19). CIs around estimates for other racial groups included the null. An intervention to reduce racial disparities in exposure to ACEs could help reduce the inequitable burden of anxiety on the Multiracial population. Stochastic methods support consequentialist approaches to racial health equity, and can encourage greater dialogue between public health researchers, policymakers, and practitioners. This article is part of a Special Collection on Mental Health.

CARDIA sleep ancillary study: study design and methods

Sleep and circadian disturbances are common and are experienced more often by Black compared to White individuals. We conducted an observational study of sleep that was ancillary to an ongoing cohort study, Coronary Artery Disease in Young Adults (CARDIA). The goal of the ancillary study will be to examine potential determinants of sleep/circadian disparities between Black and White adults in future analyses. Herein we describe the study design and methodology. Our ancillary study coincided with the Year 35 examination of the CARDIA study and was conducted in two phases (due to the SARS-COV-2 pandemic). Phase 1 involved only questionnaires to assess chronotype, restless legs syndrome, and the household sleep environment. Phase 2 involved three additional questionnaires to assess sleep quality, daytime sleepiness and insomnia symptoms, as well as two sleep devices. Participants wore a wrist activity monitor to assess sleep-wake patterns and light levels for 7 days and a home sleep apnea test for 1 night. A subset also had devices objectively record light, temperature, and sound levels in their bedrooms for 7 days. Sample sizes ranged based on assessment from 2200 to 2400, completing Phase 1 questionnaires, 899 with valid wrist actigraphy data, and 619 with a valid sleep apnea test. The data will be part of the full CARDIA dataset, which is available to researchers.

The care of non-institutionalized ADL-dependent people in the Orcasitas neighborhood of Madrid (Spain) during the Covid-19 pandemic and its relationship with social inequalities, intergenerational dependency and survival

Background

Mortality among people with dependency to perform basic activities of daily living (ADL) is higher than that of non-dependent people of the same age. Understanding the evolutionary course and factors involved in non-institutionalized ADL dependency, including the influence of the family structure that supports this population, would contribute to improved health planning.

Methods

A longitudinal study carried out in the ADL-dependent population of the Orcasitas neighborhood, Madrid (Spain), between June 2020, when the nationwide COVID-19 lockdown ended, and June 2023. A total of 127 patients participated in the study, 78.7% of whom were women and 21.3% were men. Risk analysis was performed via odds ratios (OR) and hazard ratios (HR). Survival analysis was performed using Cox regression.

Results

A total of 54.33% of the ADL-dependent persons did not live with their adult children and 45.67% did, being associated living independently with economic capacity and the married marital status but not with the dependency level. In women, being married increased the probability of living independently of their adult children (OR = 12.632; 95% CI = 3.312-48.178). Loss of mobility (OR = 0.398; 95% CI = 0.186-0.853), economic capacity of the dependent (HR = 0.596; 95% CI = 0.459-0.774), and living independently and having better economic capacity (HR = 0.471; 95% CI = 0.234-0.935) were associated with 3-year survival. Those who lived with their adult children had a worse autonomy profile and higher mortality (HR = 1.473; 95% CI = 1.072-2.024). Not being employed, not being married, and not owning a home were significantly associated with being an essential family caregiver. Caregivers were mostly women (OR = 1.794; 95% CI = 1.011-3.182).

Conclusion

Among ADL-dependent persons, economic capacity influenced the ability to living independently and affected survival after 3 years. Loss of mobility (wheelchair use) was a predictor of mortality. Social inequalities promote that adult children end up as essential family caregivers. This generates reverse dependency and maintains a vulnerability that is transmitted from generation to generation, perpetuating social and gender inequalities. Dependent parent care in this cohort maintained an archaic pattern in which the eldest daughter cared for her parents. This study made it possible to show that ADL dependence is accompanied by complex interrelationships that must be considered in socio-health planning.

Inequality in the shadow: The role of private tutoring in SES achievement gaps

Despite the rapid growth of private tutoring, previous studies have not systematically addressed its implications for socioeconomic status (SES) disparities in education, as they have only separately examined differential access to and the effects of private tutoring. This study directly estimates the causal contribution of private tutoring to SES disparities in educational achievement and cognitive ability among Chinese middle school students. Using nationally representative longitudinal data and a novel gap-closing approach, we find that unequal access to private tutoring does not uniformally result in significant learning gaps between high- and low-SES students. When comparing disadvantaged students with their most socioeconomically advantaged peers, we find that the proportions of SES disparities attributed to differences in participation in and intensity of private tutoring increase with these differences. These findings have important policy implications for reducing SES disparities in learning outcomes.

Evaluating Effects of Multilevel Interventions on Disparity in Health and Healthcare Decisions

In this paper, we introduce an analytic approach for assessing effects of multilevel interventions on disparity in health outcomes and health-related decision outcomes (i.e., a treatment decision made by a healthcare provider). We outline common challenges that are encountered in interventional health disparity research, including issues of effect scale and interpretation, choice of covariates for adjustment and its impact on effect magnitude, and the methodological challenges involved with studying decision-based outcomes. To address these challenges, we introduce total effects of interventions on disparity for the entire sample and the treated sample, and corresponding direct effects that are relevant for decision-based outcomes. We provide weighting and g-computation estimators in the presence of study attrition and sketch a simulation-based procedure for sample size determinations based on precision (e.g., confidence interval width). We validate our proposed methods through a brief simulation study and apply our approach to evaluate the RICH LIFE intervention, a multilevel healthcare intervention designed to reduce racial and ethnic disparities in hypertension control.

Environmental inequality and disparities in school readiness: The role of neurotoxic lead

Developmental science has increasingly scrutinized how environmental hazards influence child outcomes, but few studies examine how contaminants affect disparities in early skill formation. Linking research on environmental inequality and early childhood development, this study assessed whether differences in exposure to neurotoxic lead explain sociodemographic gaps in school readiness. Using panel data tracking a representative sample of 1266 Chicago children (50% female, 16% White, 30% Black, 49% Hispanic, μage  = 5.2 months at baseline, collected 1994-2002), analyses quantified the contribution of lead contamination to class and racial disparities in vocabulary skills and attention problems at ages 4 and 5. Results suggested that lead contamination explains 15%-25% and 33%-66% of the disparities in each outcome, respectively, although imprecise estimates preclude drawing firm inferences about attention problems.

Recent Developments in Causal Inference and Machine Learning

This article reviews recent advances in causal inference relevant to sociology. We focus on a selective subset of contributions aligning with four broad topics: causal effect identification and estimation in general, causal effect heterogeneity, causal effect mediation, and temporal and spatial interference. We describe how machine learning, as an estimation strategy, can be effectively combined with causal inference, which has been traditionally concerned with identification. The incorporation of machine learning in causal inference enables researchers to better address potential biases in estimating causal effects and uncover heterogeneous causal effects. Uncovering sources of effect heterogeneity is key for generalizing to populations beyond those under study. While sociology has long emphasized the importance of causal mechanisms, historical and life-cycle variation, and social contexts involving network interactions, recent conceptual and computational advances facilitate more principled estimation of causal effects under these settings. We encourage sociologists to incorporate these insights into their empirical research.

COVID-19 Mortality by Race and Ethnicity in US Metropolitan and Nonmetropolitan Areas, March 2020 to February 2022

Importance

Prior research has established that Hispanic and non-Hispanic Black residents in the US experienced substantially higher COVID-19 mortality rates in 2020 than non-Hispanic White residents owing to structural racism. In 2021, these disparities decreased.

Objective

To assess to what extent national decreases in racial and ethnic disparities in COVID-19 mortality between the initial pandemic wave and subsequent Omicron wave reflect reductions in mortality vs other factors, such as the pandemic's changing geography.

Design, Setting, and Participants

This cross-sectional study was conducted using data from the US Centers for Disease Control and Prevention for COVID-19 deaths from March 1, 2020, through February 28, 2022, among adults aged 25 years and older residing in the US. Deaths were examined by race and ethnicity across metropolitan and nonmetropolitan areas, and the national decrease in racial and ethnic disparities between initial and Omicron waves was decomposed. Data were analyzed from June 2021 through March 2023.

Exposures

Metropolitan vs nonmetropolitan areas and race and ethnicity.

Main Outcomes and Measures

Age-standardized death rates.

Results

There were death certificates for 977 018 US adults aged 25 years and older (mean [SD] age, 73.6 [14.6] years; 435 943 female [44.6%]; 156 948 Hispanic [16.1%], 140 513 non-Hispanic Black [14.4%], and 629 578 non-Hispanic White [64.4%]) that included a mention of COVID-19. The proportion of COVID-19 deaths among adults residing in nonmetropolitan areas increased from 5944 of 110 526 deaths (5.4%) during the initial wave to a peak of 40 360 of 172 515 deaths (23.4%) during the Delta wave; the proportion was 45 183 of 210 554 deaths (21.5%) during the Omicron wave. The national disparity in age-standardized COVID-19 death rates per 100 000 person-years for non-Hispanic Black compared with non-Hispanic White adults decreased from 339 to 45 deaths from the initial to Omicron wave, or by 293 deaths. After standardizing for age and racial and ethnic differences by metropolitan vs nonmetropolitan residence, increases in death rates among non-Hispanic White adults explained 120 deaths/100 000 person-years of the decrease (40.7%); 58 deaths/100 000 person-years in the decrease (19.6%) were explained by shifts in mortality to nonmetropolitan areas, where a disproportionate share of non-Hispanic White adults reside. The remaining 116 deaths/100 000 person-years in the decrease (39.6%) were explained by decreases in death rates in non-Hispanic Black adults.

Conclusions and Relevance

This study found that most of the national decrease in racial and ethnic disparities in COVID-19 mortality between the initial and Omicron waves was explained by increased mortality among non-Hispanic White adults and changes in the geographic spread of the pandemic. These findings suggest that despite media reports of a decline in disparities, there is a continued need to prioritize racial health equity in the pandemic response.