Randomized experiments are often complicated because of treatment noncompliance. This challenge prevents researchers from identifying the mediated portion of the intention-to-treated (ITT) effect, which is the effect of the assigned treatment that is attributed to a mediator. One solution suggests identifying the mediated ITT effect on the basis of the average causal mediation effect among compliers when there is a single mediator. However, considering the complex nature of the mediating mechanisms, it is natural to assume that there are multiple variables that mediate through the causal path. Motivated by an empirical analysis of a data set collected in a randomized interventional study, we develop a method to estimate the mediated portion of the ITT effect when both multiple dependent mediators and treatment noncompliance exist. This enables researchers to make an informed decision on how to strengthen the intervention effect by identifying relevant mediators despite treatment noncompliance. We propose a nonparametric estimation procedure and provide a sensitivity analysis for key assumptions. We conduct a Monte Carlo simulation study to assess the finite sample performance of the proposed approach. The proposed method is illustrated by an empirical analysis of JOBS II data, in which a job training intervention was used to prevent mental health deterioration among unemployed individuals.

This commentary discusses causal estimands of same-age and same-grade comparisons for assessing grade-retention effects on student ability and performance. Using potential outcomes notation, we show that same-age and same-grade comparisons refer to different retention-promotion contrasts and therefore assess different causal questions. We also comment on deleting versus censoring records of students who dropped out of the study or do not belong to the treatment regimes under investigation. Whereas deleting entire student records potentially induces collider bias, censoring circumvents bias if censoring is ignorable given the observed pretreatment covariates.

Objectives

Socioeconomic status (SES) is among the strongest determinants of body mass index (BMI), particularly for women. For older populations, selection bias due to attrition is a large barrier to assessing the accumulation of inequality. Under multiple missing data mechanisms, we investigated the extent to which childhood and midlife SES affects BMI from midlife to old age and gender differences in the association.

Method

Data come from a longitudinal national study of 2,345 U.S. adults aged 40-54 at baseline. We used latent growth models to estimate BMI trajectory over a period of 20 years. We examined results under different missing data patterns and applied methods that account for nonrandom-selection bias.

Results

Compared with individuals who had higher childhood SES, individuals who had lower childhood SES have higher BMI in midlife and experience a faster increase in BMI between midlife and old age. The observed associations remain significant even after controlling for midlife SES. After addressing nonrandom selection, the gap in BMI between high and low childhood SES widens from midlife to old age for women.

Discussion

The findings provide new evidence of cumulative inequality among older adults, documenting increasing BMI inequality from midlife to old age, particularly for women from low-SES families.

Little is known about sociodemographic and macro-level predictors of persistent smoking when one has developed a health condition that is likely caused by smoking. We investigate the impact of gender, education, and tobacco control policies (TCPs) on persistent smoking among older Europeans. Respondents (aged 50 +) with a smoking history and at least one smoking-related health condition were pooled from the Survey of Health, Aging and Retirement in Europe (SHARE) and the English Longitudinal Study of Ageing (ELSA) from four waves from 2004 to 2013. We fitted gender-specific logistic regression models with two-way fixed effects (country and year) and tested interaction terms between gender, education, and TCPs. Although women are less likely to smoke than men, they were more likely to smoke persistently. The effects of education and general TCPs on persistent smoking were significant for women only. Compared to women with low levels of education, those with moderate education (odds ratio [OR] = .63; .49-.82) and high education (OR = .57; .34-.98) are less likely to be persistent smokers. TCPs are associated with a reduced risk of women's persistent smoking (OR = .70; .51-.95) and the association is stronger for those having less education. Older women, particularly those with low levels of education, are vulnerable to persistent smoking. TCPs might be effective in reducing persistent smoking for older women, with greater effects for less-educated women. Future studies are needed to understand mechanisms that explain gender differences in responsiveness to TCPs. Persistent smoking is a particularly harmful smoking behavior as it is associated with greater risks of comorbidity and mortality. By employing the framework of the multilevel social determinants of health, this study examined the behavior of persistent smoking among older adults in European countries. Women, especially women with low levels of education are vulnerable to persistent smoking. Moreover, TCPs, in general, are significantly related to a reduction in persistent smoking among older women only and the negative association is stronger for those having less education, indicating gender and socioeconomic differences in responsiveness to TCPs.

Background

Little is known about life-course factors that explain why some individuals continue smoking despite having smoking-related diseases.

Purpose

We examined (a) the extent to which early-life adversities are associated with the risk of recalcitrant smoking, (b) psychosocial factors that mediate the association, and (c) gender differences in the associations.

Methods

Data were from 4,932 respondents (53% women) who participated in the first and follow-up waves of the Midlife Development in the U.S. National Survey. Early-life adversities include low socioeconomic status (SES), abuse, and family instability. Potential mediators include education, financial strain, purpose in life, mood disorder, family problems/support, and marital status. We used sequential logistic regression models to estimate the effect of early-life adversities on the risk of each of the three stages on the path to recalcitrant smoking (ever-smoking, smoking-related illness, and recalcitrant smoking).

Results

For women, low SES (odds ratio [OR] = 1.29; 1.06-1.55) and family instability (OR = 1.73; 1.14-2.62) are associated with an elevated risk of recalcitrant smoking. Education significantly reduces the effect of childhood SES, yet the effect of family instability remains significant even after accounting for life-course mediators. For men, the effect of low SES on recalcitrant smoking is robust (OR = 1.48; 1.10-2.00) even after controlling for potential mediators. There are noteworthy life-course factors that independently affect recalcitrant smoking: for both genders, not living with a partner; for women, education; and for men, family problems.

Conclusions

The findings can help shape intervention programs that address the underlying factors of recalcitrant smoking.

Considering that causal mechanisms unfold over time, it is important to investigate the mechanisms over time, taking into account the time-varying features of treatments and mediators. However, identification of the average causal mediation effect in the presence of time-varying treatments and mediators is often complicated by time-varying confounding. This article aims to provide a novel approach to uncovering causal mechanisms in time-varying treatments and mediators in the presence of time-varying confounding. We provide different strategies for identification and sensitivity analysis under homogeneous and heterogeneous effects. Homogeneous effects are those in which each individual experiences the same effect, and heterogeneous effects are those in which the effects vary over individuals. Most importantly, we provide an alternative definition of average causal mediation effects that evaluates a partial mediation effect; the effect that is mediated by paths other than through an intermediate confounding variable. We argue that this alternative definition allows us to better assess at least a part of the mediated effect and provides meaningful and unique interpretations. A case study using ECLS-K data that evaluates kindergarten retention policy is offered to illustrate our proposed approach.

Objectives

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 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 socioeconomic status (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 versus Black women (30% reduction) and White women versus Black women (15%). Intervening on perceived discrimination would not substantially change initial disparities. Intervening on midlife SES would yield large disparity reductions: White men versus Black men (64%), White men versus Black women (60%), and White women versus 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.

Most objects in the visual world are partially occluded, buthumans can recognize them without difficulty. However, it re-mains unknown whether object recognition models like convo-lutional neural networks (CNNs) can handle real-world occlu-sion. It is also a question whether efforts to make these modelsrobust to constant mask occlusion are effective for real-worldocclusion. We test both humans and the above-mentionedcomputational models in a challenging task of object recogni-tion under extreme occlusion, where target objects are heavilyoccluded by irrelevant real objects in real backgrounds. Ourresults show that human vision is very robust to extreme oc-clusion while CNNs are not, even with modifications to han-dle constant mask occlusion. This implies that the ability tohandle constant mask occlusion does not entail robustness toreal-world occlusion. As a comparison, we propose anothercomputational model that utilizes object parts/subparts in acompositional manner to build robustness to occlusion. Thisperforms significantly better than CNN-based models on ourtask with error patterns similar to humans. These findings sug-gest that testing under extreme occlusion can better reveal therobustness of visual recognition, and that the principle of com-position can encourage such robustness.