Infant mortality (IM) and birth outcomes, key population health indicators, have lifelong implications for individuals, and are unequally distributed globally. Even among western industrialized nations, striking cross-country and within-country patterns are evident. We sought to better understand these variations across and within the United States of America (USA) and Western Europe (WE), by conceptualizing a social determinants of IM/birth outcomes framework, and systematically reviewing the empirical literature on hypothesized social determinants (e.g., social policies, neighbourhood deprivation, individual socioeconomic status (SES)) and intermediary determinants (e.g., health behaviours). To date, the evidence suggests that income inequality and social policies (e.g., maternal leave policies) may help to explain cross-country variations in IM/birth outcomes. Within countries, the evidence also supports neighbourhood SES (USA, WE) and income inequality (USA) as social determinants. By contrast, within-country social cohesion/social capital has been underexplored. At the individual level, mixed associations have been found between individual SES, race/ethnicity, and selected intermediary factors (e.g., psychosocial factors) with IM/birth outcomes. Meanwhile, this review identifies several methodological gaps, including the underuse of prospective designs and the presence of residual confounding in a number of studies. Ultimately, addressing such gaps including through novel approaches to strengthen causal inference and implementing both health and non-health policies may reduce inequities in IM/birth outcomes across the western developed world.

Autism Spectrum Disorders (ASD) is a spectrum of highly heritable neurodevelopmental disorders in which known mutations contribute to disease risk in 20% of cases. Here, we report the results of the largest blood transcriptome study to date that aims to identify differences in 170 ASD cases and 115 age/sex-matched controls and to evaluate the utility of gene expression profiling as a tool to aid in the diagnosis of ASD. The differentially expressed genes were enriched for the neurotrophin signaling, long-term potentiation/depression, and notch signaling pathways. We developed a 55-gene prediction model, using a cross-validation strategy, on a sample cohort of 66 male ASD cases and 33 age-matched male controls (P1). Subsequently, 104 ASD cases and 82 controls were recruited and used as a validation set (P2). This 55-gene expression signature achieved 68% classification accuracy with the validation cohort (area under the receiver operating characteristic curve (AUC): 0.70 [95% confidence interval [CI]: 0.62–0.77]). Not surprisingly, our prediction model that was built and trained with male samples performed well for males (AUC 0.73, 95% CI 0.65–0.82), but not for female samples (AUC 0.51, 95% CI 0.36–0.67). The 55-gene signature also performed robustly when the prediction model was trained with P2 male samples to classify P1 samples (AUC 0.69, 95% CI 0.58–0.80). Our result suggests that the use of blood expression profiling for ASD detection may be feasible. Further study is required to determine the age at which such a test should be deployed, and what genetic characteristics of ASD can be identified.

Parents who adopt alternative vaccination schedules can be classified in defined subgroups based on their decision-making approaches, and many describe considered reasons to support their actions. Communications that acknowledge and address those reasons may be better able to engage parents and ultimately enhance the process of decision making about vaccines.

Purpose Spillover effects of illness on family members can be substantial. The purpose of this study was to identify the domains of family members’ health and well-being that are affected when a relative has a chronic health condition. Methods Semi-structured telephone interviews were conducted in February, 2012 with 49 individuals whose relatives had any of five chronic health conditions (arthritis, cancer, Alzheimer’s disease/dementia, cerebral palsy, and depression), purposively sampled to include different relationships with the ill relative (parent, child, spouse). Subjects were queried on whether and how having an ill relative affected their health and well-being; they were also asked about their caregiving responsibilities and the relative’s health. Interview data were analyzed using thematic analysis. Results Family members in our sample reported experiencing psychological and non-health effects from having an ill relative, and secondarily somatic effects. Effects on emotional health were most commonly reported as psychological spillover; non-health effects frequently included changes in daily activities and provision of caregiving. Spouses of patients reported the broadest range of spillover domains affected and adolescents of ill parents the fewest. Family members reported experiencing effects that were perceived as both positive and negative. Conclusions Spillover of illness onto family members encompasses a wide range of domains of health and well-being, extending beyond those included in many existing health-related quality of life measures. Outcomes measurement efforts should be expanded to adequately capture these health and well-being outcomes for analysis, to ensure that the benefits of interventions are accurately estimated and conclusions are valid.

Objective Despite multiple risk factors, women experiencing homelessness are screened for cervical cancer at a lower rate than women in the general US population. We report on the design of a stated preference study to assess homeless women's preferences for cervical cancer screening interventions, to inform efforts to overcome this disparity. Methods We conducted focus groups with homeless women (n=8) on cervical cancer screening decisions, and analyzed data using thematic analysis. We applied inclusion criteria to select factors for a stated preference survey: importance to women, relevance to providers, feasibility, and consistency with clinical experience. We conducted pre-tests (n=35) to assess survey procedures (functionality, recruitment, administration) and content (understanding, comprehension, wording/language, length). Results We chose best-worst scaling (BWS, also known as object scaling) to identify decision-relevant screening intervention factors. We chose an experimental design with 11 “objects” (i.e., factors relevant to women's screening decision) presented in 11 subsets of 5 objects each. Of 25 objects initially identified, we selected 11 for the BWS instrument: provider-related factors: attitude, familiarity, and gender; setting-related: acceptance and cost; procedure-related: explanation during visit and timing/convenience of visit; personal fears/barriers: concerns about hygiene, addiction, and delivery/fear of results; and a general factor of feeling overwhelmed. Conclusions Good practices for the development of stated preference surveys include considered assessment of the experimental design used and the preference factors included, and pretesting of presentation format. We demonstrate the development of a best-worst scaling study of homeless women's cervical cancer screening intervention preferences. Subsequent research will identify screening priorities to inform intervention design.