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Mediation analysis has been receiving much attention from the scientific community in the last years, mainly due to its ability to disentangle causal pathways from exposures to outcomes. Particularly, causal mediation analysis for time-to-event outcomes has been widely discussed using accelerated failures times, Cox and Aalen models, with continuous or binary mediator. We derive general expressions for the Natural Direct Effect and Natural Indirect Effect for the time-to-event outcome when the mediator is modeled using generalized linear models, which includes existing procedures as particular cases. We also define a responsiveness measure to assess the variations in continuous exposures in the presence of ediation. We consider a community-based prospective cohort study that investigates the mediation of hepatitis B in the relationship between hepatitis C and liver cancer. We fit different models as well as distinct distributions and link functions associated to the mediator. We also notice that estimation of NDE and NIE using different models leads to non-contradictory conclusions despite their effect scales. The survival models provide a compelling framework that is appropriate to answer many research questions involving causal mediation analysis. The extensions through GLMs for the mediator may encompassa broad field of medical research, allowing the often necessary control for confounding.

Studies analyzing relations between cardiovascular diseases (CVDs) and environmental aspects in Latin American cities are relatively recent and limited, since most of them are conducted in high-income countries, analyzing mortality outcomes, and comprising large areas. This research focuses on adults with diabetes and/or hypertension under clinical follow-up who live in deprived areas. At the individual level we evaluated sociodemographic and cardiovascular risk factors from patient’s records, and at the neighborhood level, socioeconomic conditions from census data. A multilevel analysis was carried out to study CVD. More women than men were under clinical follow-up, but men had higher frequency, higher odds, and shorter time to CVD diagnosis. Multilevel analysis showed that residing in neighborhoods with worst socioeconomic conditions leads to higher odds of CVDs, even after controlling for individual variables: OR (CI95%) of CVD in quartile 2 (Q2) 3.9 (1.2-12.1); Q3 4.0 (1.3-12.3); Q4 2.3 (0.7-8.0) (vs. highest socioeconomic level quartile). Among individuals living in unequal contexts, we found differences in CVD, which makes visible inequalities within inequalities. Differences between women and men should be considered through a gender perspective. Resumo Os estudos que analisam as relações entre doenças cardiovasculares (DCVs) e aspectos ambientais em cidades latino-americanas são relativamente recentes e limitados. A maioria é realizada em países de alta renda analisando a mortalidade em grandes áreas. Esta investigação foca a população de adultos em acompanhamento clínico por diabetes e/ou hipertensão residentes em áreas carentes. No nível individual foram avaliados fatores sociodemográficos e de risco cardiovascular a partir dos prontuários médicos; e a partir de dados censitários, as condições socioeconômicas no nível da vizinhança. Mais mulheres do que homens estavam sob acompanhamento clínico, mas os homens apresentaram maior frequência, maior chance e menor tempo para diagnóstico de DCV. A análise multinível mostrou que residir em bairros com piores condições socioeconômicas leva a maiores chances de DCV, mesmo após o controle de variáveis individuais. As OR (IC95%) de DCV foram: Q2 OR 3,9 (1,2-12,1); Q3 OR 4,0 (1,3-12,3); Q4 OR 2,3 (0,7-8,0) (referência: quartil de maior nível socioeconômico). Entre os indivíduos que vivem em contextos desiguais, encontramos diferenças nas DCV, mostrando desigualdades dentro das desigualdades. Diferenças entre homens e mulheres devem ser abordadas com uma perspectiva de gênero.

Emerging evidence suggests that vicarious racial experiences of discrimination may negatively influence child health. Few studies have focus on childhood asthma symptoms and potential moderators of such relationship.We used two population-based cross-sectional studies from the Social Change Allergy and Asthma in Latin America project in Salvador, Brazil. A total of 1003 children and mothers interviewed in 2006 were included, of whom 873 were reached again in 2013. Vicarious racial discrimination was assessed in mothers by applying the Experiences of Discrimination scale. Data on wheeze and environmental exposures were collected with standardized questionnaires. Levels of allergen-specific IgE were measured to identify atopy. Generalized estimating equations were used to estimate the association between maternal discrimination and wheezing and asthma phenotypes. Interaction terms were evaluated to identify whether mothers' mental health and family social support modified such associations.Children whose mothers reported racial discrimination had greater odds of have asthma symptoms (OR 1.75; 95% CI 1.15-2.67) and non-atopic asthma (OR 1.92; 95% CI 1.09-3.40). When we considered effect modification by social support, we found a higher ORs when the level of social support was lower (OR 2.43; 95% IC 1.19-4.97) than when the level of social support was higher (OR 1.12; CI 0.64-1.96).Maternal discrimination was associated with asthma symptoms and with non-atopic phenotype among their children. Enjoying wider social support network appears to buffer the effect on asthmatic symptoms. Intervention on childhood asthma needs to incorporate strategies that target the family.

Background Immunologists often measure several correlated immunological markers, such as concentrations of different cytokines produced by different immune cells and/or measured under different conditions, to draw insights from complex immunological mechanisms. Although there have been recent methodological efforts to improve the statistical analysis of immunological data, a framework is still needed for the simultaneous analysis of multiple, often correlated, immune markers. This framework would allow the immunologists’ hypotheses about the underlying biological mechanisms to be integrated. Results We present an analytical approach for statistical analysis of correlated immune markers, such as those commonly collected in modern immuno-epidemiological studies. We demonstrate i) how to deal with interdependencies among multiple measurements of the same immune marker, ii) how to analyse association patterns among different markers, iii) how to aggregate different measures and/or markers to immunological summary scores, iv) how to model the inter-relationships among these scores, and v) how to use these scores in epidemiological association analyses. We illustrate the application of our approach to multiple cytokine measurements from 818 children enrolled in a large immuno-epidemiological study (SCAALA Salvador), which aimed to quantify the major immunological mechanisms underlying atopic diseases or asthma. We demonstrate how to aggregate systematically the information captured in multiple cytokine measurements to immunological summary scores aimed at reflecting the presumed underlying immunological mechanisms (Th1/Th2 balance and immune regulatory network). We show how these aggregated immune scores can be used as predictors in regression models with outcomes of immunological studies (e.g. specific IgE) and compare the results to those obtained by a traditional multivariate regression approach. Conclusion The proposed analytical approach may be especially useful to quantify complex immune responses in immuno-epidemiological studies, where investigators examine the relationship among epidemiological patterns, immune response, and disease outcomes. Electronic supplementary material The online version of this article (doi:10.1186/s12865-016-0149-9) contains supplementary material, which is available to authorized users.

Background Cardiovascular disease (CVD) has a disproportionate effect on mortality among the poorest people. We assessed the impact on CVD and all-cause mortality of the world's largest conditional cash transfer, Brazil’s Bolsa Família Programme (BFP). Methods We linked administrative data from the 100 Million Brazilian Cohort with BFP receipt and national mortality data. We followed individuals who applied for BFP between 1 January 2011 and 31 December 2015, until 31 December 2015. We used marginal structural models to estimate the effect of BFP on all-age and premature (30–69 years) CVD and all-cause mortality. We conducted stratified analyses by levels of material deprivation and access to healthcare. We checked the robustness of our findings by restricting the analysis to municipalities with better mortality data and by using alternative statistical methods. Results We studied 17 981 582 individuals, of whom 4 855 324 were aged 30–69 years. Three-quarters (76.2%) received BFP, with a mean follow-up post-award of 2.6 years. We detected 106 807 deaths by all causes, of which 60 893 were premature; and 23 389 CVD deaths, of which 15 292 were premature. BFP was associated with reductions in premature all-cause mortality [hazard ratio (HR) = 0.96, 95% CI = 0.94–0.98], premature CVD (HR = 0.96, 95% CI = 0.92–1.00) and all-age CVD (HR = 0.96, 95% CI = 0.93–1.00) but not all-age all-cause mortality (HR = 1.00, 95% CI = 0.98–1.02). In stratified and robustness analyses, BFP was consistently associated with mortality reductions for individuals living in the two most deprived quintiles. Conclusions BFP appears to have a small to null effect on premature CVD and all-cause mortality in the short term; the long-term impact remains unknown.