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Understanding how child and adolescent health is influenced by fluctuations in socioeconomic status has important public health and policy implications, as children are often subjected to both micro and macro-level socioeconomic events. This study provides the first systematic review to date on the relationship between changes in household or parental socioeconomic status and subsequent child and adolescent health outcomes. Eighty articles were identified for inclusion in this review, examining 85 different socioeconomic exposures in five categories: Income (n = 64), Employment (n = 14), Socioeconomic Mobility (n = 3), Education (n = 2), and Food Insecurity (n = 2). The health outcomes analyzed by these eighty articles were separated into eight discrete categories, with many articles examining outcomes in more than one category: Anthropometric Measurements (n = 21), Cognition and Development (n = 15), Dental Health (n = 3), Health Behaviours (n = 9), Mental Health (n = 12), Overall Parent/Guardian Assessed health (n = 6); Physical Health Outcomes (n = 11), and Socio-Emotional Behaviour (n = 30). Several consistent patterns emerged in the literature, such as a link between increased income and improved, or decreased income and deteriorating, cognition, dental health, and physical health. The results of this review suggest a need to replicate current studies in diverse geographies to expand generalizability and clarify regional patterns. There should also be an effort to go beyond income, and employment, to assess the relationship between less frequently studied socioeconomic exposures and child health outcomes. Supplementary Information The online version contains supplementary material available at 10.1007/s40894-021-00151-8.

The analysis and prediction of life expectancy trends hold an important role in many aspects of our society. On a macro level, governments rely on life expectancy data to make decisions about public welfare programs, health care, retirement age, and pension programs. On an individual level, many people take life expectancy data into account when planning their retirements and making decisions about their future. Currently, two main schools of thought dominate the debate on the trajectory of life expectancy trends. The Olshansky School argues that global human life expectancy is reaching its absolute limit and predicts that a worldwide plateau in life expectancy will soon be reached. The Vaupel School, however, believes that such a plateau is nowhere in sight, and that humans possess no biological barrier that will prevent life expectancy from increasing indefinitely. In this commentary, I build upon the evidence generated by the Vaupel School by introducing socioeconomic factors into the debate and I argue that with consistent improvements to medical technology and general prosperity we will not encounter a biological limit to human life expectancy in our lifetimes.

Background In this paper we examine the relationship between social capital and two mental health outcomes—self-rated mental health (SRMH) and heavy episodic drinking (HED)—among the Indigenous populations of Canada. We operationalize a unique definition of social capital from Indigenous specific sources that allows for an analysis of the importance of access to Indigenous networks and communities. We also examine gender variations in the relationship between social capital and the two outcomes, as there is a noticeable lack of research examining the influence of gender in the recent literature on the mental health of Indigenous populations in Canada. Methods Using data from the 2012 cycle of the Aboriginal Peoples Survey, logistic regression models were estimated to assess if gender was a significant predictor of either SRMH or HED among the entire Indigenous sample. The sample was then stratified by gender and the relationship between two social capital variables—one general and one indigenous-specific—and each mental health outcome was assessed separately among male and female respondents. All analyses were also further stratified into specific Indigenous groups—First Nations, Métis, or Inuit—to account for the unique cultures, histories, and socioeconomic positions of the three populations. Results Female respondents were more likely to report fair or poor SRMH in the total sample as well as the First Nations and Métis subsamples (OR = 1.48, CI = 1.14–1.91; OR = 1.63, CI = 1.12–2.36; OR = 1.44, CI = 1.01–2.05 respectively). However, female respondents were less likely than males to engage in weekly HED in all three of the same populations (OR = 0.43, CI = 0.35–0.54, all respondents; OR = 0.42, CI = 0.31–0.58, First nations; OR = 0.39, CI = 0.27–0.56, Métis). Social capital from sources specific to Indigenous communities was associated with lower odds of weekly HED, but only among Indigenous men. Meanwhile the strength of family ties was associated with lower odds of reporting fair/poor SRMH among both Indigenous men and women. However, these results vary in strength and significance among the different Indigenous populations of Canada. Conclusions The results of this paper address a critical gap in the literature on gender differences in SRMH and HED among the Indigenous populations of Canada, and reveal gendered variations in the relationship between social capital and SRMH and HED. These findings support further investigation into the role that social capital and particularly Indigenous-specific forms of social capital may play as a determinant of health. This research could contribute to future mental health initiatives aimed at strengthening the social capital of Indigenous populations and promoting resilient Indigenous communities with strong social connections.

In their 2015 study, Sharon Green-Hennessy and Kevin D. Hennessy addressed an important gap in the literature on seclusion and restraint use in child and adolescent residential treatment centers (RTCs). Their analysis revealed that several facility-level characteristics-such as facility size and ownership-predicted the use of seclusion/restraint in child/adolescent RTCs. The authors also examined patient demographic variables that were significant predictors of seclusion/restraint in prior research on individual patients within facilities. However, Green-Hennessy and Hennessy did not find any relationship between these demographic variables and seclusion/restraint. In this commentary I argue that the null relationship between patient demographics and seclusion/restraint was a result of an ecological fallacy. Rather than attempting to use aggregate patient data to infer individual-level processes, this patient data should be used to study aggregate effects. I demonstrate that by re-conceptualizing these patient demographics as indicative of facility characteristics, rather than patient characteristics, new information can be gleaned about the types of facilities that use seclusion/restraint. The arguments presented here have broader implications for future research in this field that relies on aggregate patient data.