In 2011, WHO member states signed up to the 25 × 25 initiative, a plan to cut mortality due to non-communicable diseases by 25% by 2025. However, socioeconomic factors influencing non-communicable diseases have not been included in the plan. In this study, we aimed to compare the contribution of socioeconomic status to mortality and years-of-life-lost with that of the 25 × 25 conventional risk factors. We did a multicohort study and meta-analysis with individual-level data from 48 independent prospective cohort studies with information about socioeconomic status, indexed by occupational position, 25 × 25 risk factors (high alcohol intake, physical inactivity, current smoking, hypertension, diabetes, and obesity), and mortality, for a total population of 1 751 479 (54% women) from seven high-income WHO member countries. We estimated the association of socioeconomic status and the 25 × 25 risk factors with all-cause mortality and cause-specific mortality by calculating minimally adjusted and mutually adjusted hazard ratios [HR] and 95% CIs. We also estimated the population attributable fraction and the years of life lost due to suboptimal risk factors. During 26·6 million person-years at risk (mean follow-up 13·3 years [SD 6·4 years]), 310 277 participants died. HR for the 25 × 25 risk factors and mortality varied between 1·04 (95% CI 0·98-1·11) for obesity in men and 2 ·17 (2·06-2·29) for current smoking in men. Participants with low socioeconomic status had greater mortality compared with those with high socioeconomic status (HR 1·42, 95% CI 1·38-1·45 for men; 1·34, 1·28-1·39 for women); this association remained significant in mutually adjusted models that included the 25 × 25 factors (HR 1·26, 1·21-1·32, men and women combined). The population attributable fraction was highest for smoking, followed by physical inactivity then socioeconomic status. Low socioeconomic status was associated with a 2·1-year reduction in life expectancy between ages 40 and 85 years, the corresponding years-of-life-lost were 0·5 years for high alcohol intake, 0·7 years for obesity, 3·9 years for diabetes, 1·6 years for hypertension, 2·4 years for physical inactivity, and 4·8 years for current smoking. Socioeconomic circumstances, in addition to the 25 × 25 factors, should be targeted by local and global health strategies and health risk surveillance to reduce mortality. European Commission, Swiss State Secretariat for Education, Swiss National Science Foundation, the Medical Research Council, NordForsk, Portuguese Foundation for Science and Technology.

This descriptive scoping aims to understand how the prevalence of cyberbullying has been estimated across studies. A systematic scoping review of cyberbullying empirical studies was conducted by using three bibliographic databases to search for papers published between January 2004 and August 2014. A protocol was defined to identify the relevant papers. Papers selected were included in a data sheet developed by the authors to record specific findings. In total, 159 studies were included in the scoping review. Most of the prevalence studies were conducted in the last 4 years, mainly in North America (n = 77) and in Europe (n = 65). High methodological heterogeneity was found among the studies, which may contribute to explain variability in prevalence estimates. Cyberbullying experiences were assessed through several different perspectives: focused only on victims, focused only on perpetrators, or focused on both victims and perpetrators (without differentiating between if they are victims or perpetrators). Most of the studies tend to assess cybervictimization experiences. However, even considering the same perspective, the same country, and the same recall period, a high variability in the estimates was observed. As a main conclusion, the way in which the prevalence of cyberbullying is estimated is influenced by methodological research options.

Residing in socioeconomically deprived neighborhoods may pose substantial physiological stress, which can then lead to higher allostatic load (AL), a marker of biological wear and tear that precedes disease. The aim of the present study was to map the current evidence about the relationship between neighborhood socioeconomic deprivation and AL. A scoping review approach was chosen to provide an overview of the type, quantity, and extent of research available. The review was conducted using three bibliographic databases (PubMed, SCOPUS, and Web of Science) and a standardized protocol. Fourteen studies were identified. Studies were predominantly from the USA, cross-sectional, focused on adults, and involved different races and ethnic groups. A wide range of measures of AL were identified: the mode of the number of biomarkers per study was eight but with large variability (range: 6–24). Most studies (n = 12) reported a significant association between neighborhood deprivation and AL. Behaviors and environmental stressors seem to mediate this relationship and associations appear more pronounced among Blacks, men, and individuals with poor social support. Such conclusions have important public health implications as they enforce the idea that neighborhood environment should be improved to prevent physiological dysregulation and consequent chronic diseases.

Objective To assess the association of low socioeconomic status and risk factors for non-communicable diseases (diabetes, high alcohol intake, high blood pressure, obesity, physical inactivity, smoking) with loss of physical functioning at older ages. Design Multi-cohort population based study. Setting 37 cohort studies from 24 countries in Europe, the United States, Latin America, Africa, and Asia, 1990-2017. Participants 109 107 men and women aged 45-90 years. Main outcome measure Physical functioning assessed using the walking speed test, a valid index of overall functional capacity. Years of functioning lost was computed as a metric to quantify the difference in walking speed between those exposed and unexposed to low socioeconomic status and risk factors. Results According to mixed model estimations, men aged 60 and of low socioeconomic status had the same walking speed as men aged 66.6 of high socioeconomic status (years of functioning lost 6.6 years, 95% confidence interval 5.0 to 9.4). The years of functioning lost for women were 4.6 (3.6 to 6.2). In men and women, respectively, 5.7 (4.4 to 8.1) and 5.4 (4.3 to 7.3) years of functioning were lost by age 60 due to insufficient physical activity, 5.1 (3.9 to 7.0) and 7.5 (6.1 to 9.5) due to obesity, 2.3 (1.6 to 3.4) and 3.0 (2.3 to 4.0) due to hypertension, 5.6 (4.2 to 8.0) and 6.3 (4.9 to 8.4) due to diabetes, and 3.0 (2.2 to 4.3) and 0.7 (0.1 to 1.5) due to tobacco use. In analyses restricted to high income countries, the number of years of functioning lost attributable to low socioeconomic status by age 60 was 8.0 (5.7 to 13.1) for men and 5.4 (4.0 to 8.0) for women, whereas in low and middle income countries it was 2.6 (0.2 to 6.8) for men and 2.7 (1.0 to 5.5) for women. Within high income countries, the number of years of functioning lost attributable to low socioeconomic status by age 60 was greater in the United States than in Europe. Physical functioning continued to decline as a function of unfavourable risk factors between ages 60 and 85. Years of functioning lost were greater than years of life lost due to low socioeconomic status and non-communicable disease risk factors. Conclusions The independent association between socioeconomic status and physical functioning in old age is comparable in strength and consistency with those for established non-communicable disease risk factors. The results of this study suggest that tackling all these risk factors might substantially increase life years spent in good physical functioning.

Background: This systematic review aimed to summarize evidence reporting epigenetic and/or neuro-immuno-endocrine embedding of adverse childhood events (ACEs) in children, with a particular focus on the short-term biological effect of those experiences.Methods: A search was conducted in PsycINFO®, PubMed®, Isi Web of Knowledge and Scopus, until July 2019, to identify papers reporting the short-term biological effects of exposure to ACEs.Results: The search identified 58 studies, that were included in the review. Regarding exposure, the type of ACE more frequently reported was sexual abuse (n = 26), followed by life stressors (n = 20) and physical abuse (n = 19). The majority (n = 17) of studies showed a positive association between ACEs and biomarkers of the immune system. Regarding DNA methylation 18 studies showed more methylation in participants exposed to ACEs. Two studies presented the effect of ACEs on telomere length and showed that exposure was associated with shorter telomere length.Conclusion: Overall the associations observed across studies followed the hypothesis that ACEs are associated with biological risk already at early ages. This is supporting evidence that ACEs appear to get “under the skin” and induce physiological changes and these alterations might be strongly associated with later development of disease.

Living in deprived neighbourhoods may have biological consequences, but few studies have assessed this empirically. We examined the association between neighbourhood deprivation and allostatic load, a biological marker of wear and tear, taking into account individual’s socioeconomic position. We analysed data from three cohort studies (CoLaus-Switzerland; EPIPorto-Portugal; Whitehall II-UK) comprising 16,364 participants. We defined allostatic load using ten biomarkers of dysregulated metabolic, cardiovascular, and inflammatory systems (body mass index; waist circumference; total, high and low density lipoprotein cholesterol; triglycerides; glucose; systolic and diastolic blood pressure; C-reactive protein). Mixed Poisson regression models were fitted to examine associations with neighbourhood deprivation (in quintiles, Q1-least deprived as reference). After adjustment for confounding variables, participants living in the most deprived quintile had 1.13 times higher allostatic load than those living in the least deprived quintile (Relative Risk, RR, for Q2 RR = 1.06, 95% CI 1.03-1.09; Q3 = 1.06, 1.03–1.10; Q4 = 1.09, 1.06–1.12; Q5 = 1.13, 1.09–1.16). This association was partially modified by individual’s socioeconomic position, such that the relative risk was higher in participants with low socioeconomic position (Q5 vs Q1 1.16, 1.11–1.22) than those with high socioeconomic position (Q5 vs Q1 1.07, 1.01–1.13). Neighbourhood deprivation is associated with biological wear and tear, suggesting that neighbourhood-level interventions may yield health gains.