Epidemiologic analysis of racial/ethnic disparities: Some fundamental issues and a cautionary example

http://dx.doi.org/10.1016/j.socscimed.2007.11.04

A further critique of the analytic strategy of adjusting for covariates to identify biologic mediation

BACKGROUND: Epidemiologic research is often devoted to etiologic investigation, and so techniques that may facilitate mechanistic inferences are attractive. Some of these techniques rely on rigid and/or unrealistic assumptions, making the biologic inferences tenuous. The methodology investigated here is effect decomposition: the contrast between effect measures estimated with and without adjustment for one or more variables hypothesized to lie on the pathway through which the exposure exerts its effect. This contrast is typically used to distinguish the exposure's indirect effect, through the specified intermediate variables, from its direct effect, transmitted via pathways that do not involve the specified intermediates. METHODS: We apply a causal framework based on latent potential response types to describe the limitations inherent in effect decomposition analysis. For simplicity, we assume three measured binary variables with monotonic effects and randomized exposure, and use difference contrasts as measures of causal effect. Previous authors showed that confounding between intermediate and the outcome threatens the validity of the decomposition strategy, even if exposure is randomized. We define exchangeability conditions for absence of confounding of causal effects of exposure and intermediate, and generate two example populations in which the no-confounding conditions are satisfied. In one population we impose an additional prohibition against unit-level interaction (synergism). We evaluate the performance of the decomposition strategy against true values of the causal effects, as defined by the proportions of latent potential response types in the two populations. RESULTS: We demonstrate that even when there is no confounding, partition of the total effect into direct and indirect effects is not reliably valid. Decomposition is valid only with the additional restriction that the population contain no units in which exposure and intermediate interact to cause the outcome. This restriction implies homogeneity of causal effects across strata of the intermediate. CONCLUSIONS: Reliable effect decomposition requires not only absence of confounding, but also absence of unit-level interaction and use of linear contrasts as measures of causal effect. Epidemiologists should be wary of etiologic inference based on adjusting for intermediates, especially when using ratio effect measures or when absence of interacting potential response types cannot be confidently asserted

A Difference-in-Differences Approach to Assess the Effect of a Heat Action Plan on Heat-Related Mortality, and Differences in Effectiveness According to Sex, Age, and Socioeconomic Status (Montreal, Quebec).

BackgroundThe impact of heat waves on mortality and health inequalities is well documented. Very few studies have assessed the effectiveness of heat action plans (HAPs) on health, and none has used quasi-experimental methods to estimate causal effects of such programs.ObjectivesWe developed a quasi-experimental method to estimate the causal effects associated with HAPs that allows the identification of heterogeneity across subpopulations, and to apply this method specifically to the case of the Montreal (Quebec, Canada) HAP.MethodsA difference-in-differences approach was undertaken using Montreal death registry data for the summers of 2000-2007 to assess the effectiveness of the Montreal HAP, implemented in 2004, on mortality. To study equity in the effect of HAP implementation, we assessed whether the program effects were heterogeneous across sex (male vs. female), age (≥ 65 years vs. < 65 years), and neighborhood education levels (first vs. third tertile). We conducted sensitivity analyses to assess the validity of the estimated causal effect of the HAP program.ResultsWe found evidence that the HAP contributed to reducing mortality on hot days, and that the mortality reduction attributable to the program was greater for elderly people and people living in low-education neighborhoods.ConclusionThese findings show promise for programs aimed at reducing the impact of extreme temperatures and health inequities. We propose a new quasi-experimental approach that can be easily applied to evaluate the impact of any program or intervention triggered when daily thresholds are reached. Citation: Benmarhnia T, Bailey Z, Kaiser D, Auger N, King N, Kaufman J. 2016. A difference-in-differences approach to assess the effect of a heat action plan on heat-related mortality, and differences in effectiveness according to sex, age, and socioeconomic status (Montreal, Quebec). Environ Health Perspect 124:1694-1699; http://dx.doi.org/10.1289/EHP203

Socioeconomic inequality in neonatal mortality in countries of low and middle income: a multicountry analysis

Background Neonatal mortality rates (NMRs) in countries of low and middle income have been only slowly decreasing; coverage of essential maternal and newborn health services needs to increase, particularly for disadvantaged populations. Our aim was to produce comparable estimates of changes in socioeconomic inequalities in NMR in the past two decades across these countries. Methods We used data from Demographic and Health Surveys (DHS) for countries in which a survey was done in 2008 or later and one about 10 years previously. We measured absolute inequalities with the slope index of inequality and relative inequalities with the relative index of inequality. We used an asset-based wealth index and maternal education as measures of socioeconomic position and summarised inequality estimates for all included countries with random-eff ects meta-analysis. Findings 24 low-income and middle-income countries were eligible for inclusion. In most countries, absolute and relative wealth-related and educational inequalities in NMR decreased between survey 1 and survey 2. In fi ve countries (Cameroon, Nigeria, Malawi, Mozambique, and Uganda), the diff erence in NMR between the top and bottom of the wealth distribution was reduced by more than two neonatal deaths per 1000 livebirths per year. By contrast, wealthrelated inequality increased by more than 1·5 neonatal deaths per 1000 livebirths per year in Ethiopia and Cambodia. Patterns of change in absolute and relative educational inequalities in NMR were similar to those of wealth-related NMR inequalities, although the size of educational inequalities tended to be slightly larger. Interpretation Socioeconomic inequality in NMR seems to have decreased in the past two decades in most countries of low and middle income. However, a substantial survival advantage remains for babies born into wealthier households with a high educational level, which should be considered in global eff orts to further reduce NMR

(Errors in statistical tests)3

In 2004, Garcia-Berthou and Alcaraz published "Incongruence between test statistics and P values in medical papers," a critique of statistical errors that received a tremendous amount of attention. One of their observations was that the final reported digit of p-values in articles published in the journal Nature departed substantially from the uniform distribution that they suggested should be expected. In 2006, Jeng critiqued that critique, observing that the statistical analysis of those terminal digits had been based on comparing the actual distribution to a uniform continuous distribution, when digits obviously are discretely distributed. Jeng corrected the calculation and reported statistics that did not so clearly support the claim of a digit preference. However delightful it may be to read a critique of statistical errors in a critique of statistical errors, we nevertheless found several aspects of the whole exchange to be quite troubling, prompting our own meta-critique of the analysis

Vulnerability to Heat-related Mortality: A Systematic Review, Meta-analysis, and Meta-regression Analysis

International audienceBACKGROUND: Addressing vulnerability to heat-related mortality is a necessary step in the development of policies dictated by heat action plans. We aimed to provide a systematic assessment of the epidemiologic evidence regarding vulnerability to heat-related mortality. METHODS: Studies assessing the association between high ambient temperature or heat waves and mortality among different subgroups and published between January 1980 and August 2014 were selected. Estimates of association for all the included subgroups were extracted. We assessed the presence of heterogeneous effects between subgroups conducting Cochran Q tests. We conducted random effect meta-analyses of ratios of relative risks (RRR) for high ambient temperature studies. We performed random effects meta-regression analyses to investigate factors associated with the magnitude of the RRR. RESULTS: Sixty-one studies were included. Using the Cochran Q test, we consistently found evidence of vulnerability for the elderly ages \textgreater85 years. We found a pooled RRR of 0.99 (95% confidence interval [CI] = 0.97, 1.01) for male sex, 1.02 (95% CI = 1.01, 1.03) for age \textgreater65 years, 1.04 (95% CI = 1.02, 1.07) for age \textgreater75 years, 1.03 (95% CI = 1.01, 1.05) for low individual socioeconomic status (SES), and 1.01 (95% CI = 0.99, 1.02) for low ecologic SES. CONCLUSIONS: We found strongest evidence of heat-related vulnerability for the elderly ages \textgreater65 and \textgreater75 years and low SES groups (at the individual level). Studies are needed to clarify if other subgroups (e.g., children, people living alone) are also vulnerable to heat to inform public health program

The Role of Adolescent Behaviors in the Female–Male Disparity in Obesity Incidence in US Black and White Young Adults

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/93675/1/oby.2009.362.pd

Counterfactual Theory in Social Epidemiology: Reconciling Analysis and Action for the Social Determinants of Health

Abstract There is a strong and growing interest in applying formal methods for causal inference with observational data in social epidemiology. A number of challenges in defining, identifying, and estimating counterfactual-based causal effects have been especially problematic in social epidemiology, particularly for commonly used exposures such as race, education, occupation, or socioeconomic position. The purpose of this article is to revisit these challenges in light of the conceptual and analytic advancements in causal inference over the last two decades. We focus on a central assumption for causal inference known as the stable unit treatment value assumption, which can be divided into two component assumptions: counterfactual consistency and the absence of interference. We give simple hypothetical examples to illustrate how and why these assumptions are often violated in research on the social determinants of health (e.g., education, race/ethnicity, socioeconomic position) and provide strategies that can be used to sidestep these assumptions. In particular, we note that a recently proposed mediation analysis strategy can be used to explore questions about health disparities in a more formal causal inference framework. We emphasize that a central obstacle to estimating causal effects variables such as race, education (e.g., high school versus no high school), or occupation is the need to identify an intervention (possibly hypothetical) that will lead to changes in the exposure of interest

A social epidemiology for Latin America: The need to go beyond just thinking about health inequities.

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