SummaryBackgroundThe Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017 comparative risk assessment (CRA) is a comprehensive approach to risk factor quantification that offers a useful tool for synthesising evidence on risks and risk–outcome associations. With each annual GBD study, we update the GBD CRA to incorporate improved methods, new risks and risk–outcome pairs, and new data on risk exposure levels and risk–outcome associations.MethodsWe used the CRA framework developed for previous iterations of GBD to estimate levels and trends in exposure, attributable deaths, and attributable disability-adjusted life-years (DALYs), by age group, sex, year, and location for 84 behavioural, environmental and occupational, and metabolic risks or groups of risks from 1990 to 2017. This study included 476 risk–outcome pairs that met the GBD study criteria for convincing or probable evidence of causation. We extracted relative risk and exposure estimates from 46 749 randomised controlled trials, cohort studies, household surveys, census data, satellite data, and other sources. We used statistical models to pool data, adjust for bias, and incorporate covariates. Using the counterfactual scenario of theoretical minimum risk exposure level (TMREL), we estimated the portion of deaths and DALYs that could be attributed to a given risk. We explored the relationship between development and risk exposure by modelling the relationship between the Socio-demographic Index (SDI) and risk-weighted exposure prevalence and estimated expected levels of exposure and risk-attributable burden by SDI. Finally, we explored temporal changes in risk-attributable DALYs by decomposing those changes into six main component drivers of change as follows: (1) population growth; (2) changes in population age structures; (3) changes in exposure to environmental and occupational risks; (4) changes in exposure to behavioural risks; (5) changes in exposure to metabolic risks; and (6) changes due to all other factors, approximated as the risk-deleted death and DALY rates, where the risk-deleted rate is the rate that would be observed had we reduced the exposure levels to the TMREL for all risk factors included in GBD 2017.FindingsIn 2017, 34·1 million (95% uncertainty interval [UI] 33·3–35·0) deaths and 1·21 billion (1·14–1·28) DALYs were attributable to GBD risk factors. Globally, 61·0% (59·6–62·4) of deaths and 48·3% (46·3–50·2) of DALYs were attributed to the GBD 2017 risk factors. When ranked by risk-attributable DALYs, high systolic blood pressure (SBP) was the leading risk factor, accounting for 10·4 million (9·39–11·5) deaths and 218 million (198–237) DALYs, followed by smoking (7·10 million [6·83–7·37] deaths and 182 million [173–193] DALYs), high fasting plasma glucose (6·53 million [5·23–8·23] deaths and 171 million [144–201] DALYs), high body-mass index (BMI; 4·72 million [2·99–6·70] deaths and 148 million [98·6–202] DALYs), and short gestation for birthweight (1·43 million [1·36–1·51] deaths and 139 million [131–147] DALYs). I...

AIMTo identify health and psychosocial problems associated with bullying victimization and conduct a meta-analysis summarizing the causal evidence.METHODSA systematic review was conducted using PubMed, EMBASE, ERIC and PsycINFO electronic databases up to 28 February 2015. The study included published longitudinal and cross-sectional articles that examined health and psychosocial consequences of bullying victimization. All meta-analyses were based on quality-effects models. Evidence for causality was assessed using Bradford Hill criteria and the grading system developed by the World Cancer Research Fund.RESULTSOut of 317 articles assessed for eligibility, 165 satisfied the predetermined inclusion criteria for meta-analysis. Statistically significant associations were observed between bullying victimization and a wide range of adverse health and psychosocial problems. The evidence was strongest for causal associations between bullying victimization and mental health problems such as depression, anxiety, poor general health and suicidal ideation and behaviours. Probable causal associations existed between bullying victimization and tobacco and illicit drug use.CONCLUSIONStrong evidence exists for a causal relationship between bullying victimization, mental health problems and substance use. Evidence also exists for associations between bullying victimization and other adverse health and psychosocial problems, however, there is insufficient evidence to conclude causality. The strong evidence that bullying victimization is causative of mental illness highlights the need for schools to implement effective interventions to address bullying behaviours.

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The need for an integrated approach to studying bullying behaviors, both traditional and cyber, in adolescents is increasingly evident. The definitional criteria of bullying are well established in the traditional bullying literature and include (i) intention, (ii) repetition, and (iii) power imbalance. There is emerging evidence that these same criteria can be broadly applied to cyberbullying behaviors; however, important additional elements may include anonymity and publicity in a cyber-act. Fundamental to integrating traditional and cyberbullying are the measurement tools used to capture the extent and range of bullying behaviors. Self-report surveys are widely adopted as a method for measuring the prevalence of bullying victimization and perpetration. The current paper reviews the definitional and measurement issues relating to traditional and cyberbullying among school-aged youth. We conclude that both traditional and cyberbullying behaviors should be measured simultaneously. Operationalizing components of the definitional criteria in self-report surveys will result in more consistent and reliable measurement across all bullying behaviors.

Background: Bullying victimisation is a global public health problem that has been predominantly studied in high income countries. This study aimed to estimate the population level prevalence of bullying victimisation and its association with peer and parental supports amongst adolescents across low and middle income to high income countries (LMICÀ ÀHICs). Methods: Data were drawn from the Global School-based Student Health Survey of school children aged 12À17 years, between 2003 and 2015, in 83 LMICÀ ÀHICs in the six World Health Organization (WHO) regions. We estimated the weighted prevalence of bullying victimisation at country, region and global level. We used multiple binary logistic regression models to estimate the adjusted association of age, gender, socioeconomic status, and parental support and peer support, and country level variables (GDP and government expenditure on education) with adolescent bullying victimisation. Findings: Of the 317,869 adolescents studied, 151,036 (48%) were males, and 166,833 (52%) females. The pooled prevalence of bullying victimisation on one or more days in the past 30 days amongst adolescents aged 12À17 years was 30¢5% (95% CI: 30¢2À31¢0%). The highest prevalence was observed in the Eastern Mediterranean Region (45¢1%, 44¢3À46¢0%) and African region (43¢5%, 43¢0À44¢3%), and the lowest in Europe (8¢4%, 8¢0À9¢0%). Bullying victimisation was associated with male gender (OR: 1¢21; 1¢11À1¢32), below average socio-economic status (OR: 1¢47, 1¢35À1¢61), and younger age (OR: 1¢11, 1¢0À1¢24). Higher levels of peer support (0¢51, 0¢46À0¢57), higher levels of parental support (e.g., understanding children's problems (OR: 0¢85, 0¢77À0¢95), and knowing the importance of free time spent with children (OR: 0¢77, 0¢70À0¢85)), were significantly associated with a reduced risk of bullying victimisation. Interpretations: Bullying victimisation is prevalent amongst adolescents globally, particularly in the Eastern Mediterranean and African regions. Parental and peer supports are protective factors against bullying victimisation. A reduction in bullying victimisation may be facilitated by family and peer based interventions aimed at increasing social connectedness of adolescents.