Explore the vast range of titles available.

Rigorous analysis of levels and trends in exposure to leading risk factors and quantification of their effect on human health are important to identify where public health is making progress and in which cases current efforts are inadequate. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 provides a standardised and comprehensive assessment of the magnitude of risk factor exposure, relative risk, and attributable burden of disease. GBD 2019 estimated attributable mortality, years of life lost (YLLs), years of life lived with disability (YLDs), and disability-adjusted life-years (DALYs) for 87 risk factors and combinations of risk factors, at the global level, regionally, and for 204 countries and territories. GBD uses a hierarchical list of risk factors so that specific risk factors (eg, sodium intake), and related aggregates (eg, diet quality), are both evaluated. This method has six analytical steps. (1) We included 560 risk–outcome pairs that met criteria for convincing or probable evidence on the basis of research studies. 12 risk–outcome pairs included in GBD 2017 no longer met inclusion criteria and 47 risk–outcome pairs for risks already included in GBD 2017 were added based on new evidence. (2) Relative risks were estimated as a function of exposure based on published systematic reviews, 81 systematic reviews done for GBD 2019, and meta-regression. (3) Levels of exposure in each age-sex-location-year included in the study were estimated based on all available data sources using spatiotemporal Gaussian process regression, DisMod-MR 2.1, a Bayesian meta-regression method, or alternative methods. (4) We determined, from published trials or cohort studies, the level of exposure associated with minimum risk, called the theoretical minimum risk exposure level. (5) Attributable deaths, YLLs, YLDs, and DALYs were computed by multiplying population attributable fractions (PAFs) by the relevant outcome quantity for each age-sex-location-year. (6) PAFs and attributable burden for combinations of risk factors were estimated taking into account mediation of different risk factors through other risk factors. Across all six analytical steps, 30 652 distinct data sources were used in the analysis. Uncertainty in each step of the analysis was propagated into the final estimates of attributable burden. Exposure levels for dichotomous, polytomous, and continuous risk factors were summarised with use of the summary exposure value to facilitate comparisons over time, across location, and across risks. Because the entire time series from 1990 to 2019 has been re-estimated with use of consistent data and methods, these results supersede previously published GBD estimates of attributable burden. The largest declines in risk exposure from 2010 to 2019 were among a set of risks that are strongly linked to social and economic development, including household air pollution; unsafe water, sanitation, and handwashing; and child growth failure. Global declines also occurred for tobacco smoking and lead exposure. The largest increases in risk exposure were for ambient particulate matter pollution, drug use, high fasting plasma glucose, and high body-mass index. In 2019, the leading Level 2 risk factor globally for attributable deaths was high systolic blood pressure, which accounted for 10·8 million (95% uncertainty interval [UI] 9·51–12·1) deaths (19·2% [16·9–21·3] of all deaths in 2019), followed by tobacco (smoked, second-hand, and chewing), which accounted for 8·71 million (8·12–9·31) deaths (15·4% [14·6–16·2] of all deaths in 2019). The leading Level 2 risk factor for attributable DALYs globally in 2019 was child and maternal malnutrition, which largely affects health in the youngest age groups and accounted for 295 million (253–350) DALYs (11·6% [10·3–13·1] of all global DALYs that year). The risk factor burden varied considerably in 2019 between age groups and locations. Among children aged 0–9 years, the three leading detailed risk factors for attributable DALYs were all related to malnutrition. Iron deficiency was the leading risk factor for those aged 10–24 years, alcohol use for those aged 25–49 years, and high systolic blood pressure for those aged 50–74 years and 75 years and older. Overall, the record for reducing exposure to harmful risks over the past three decades is poor. Success with reducing smoking and lead exposure through regulatory policy might point the way for a stronger role for public policy on other risks in addition to continued efforts to provide information on risk factor harm to the general public. Bill & Melinda Gates Foundation.

A high proportion of vocational education students smoke tobacco, have inadequate nutrition (ie, low fruit and vegetable intake), drink alcohol at risky levels, or are physically inactive. The extent to which vocational education students will sign up for proactively offered online and telephone support services for multiple health risk behaviors is unknown. The aim of this study is to examine the uptake of proactively offered online and telephone support services for smoking, nutrition, alcohol consumption, and physical activity risk behaviors, individually and in combination, among vocational education students in the Technical and Further Education (TAFE) setting. The characteristics associated with the uptake of online or telephone services for smoking, nutrition, alcohol consumption, and physical activity risk behaviors were also examined. Vocational education students enrolled in a TAFE class in New South Wales, Australia, which ran for 6 months or more, were recruited to participate in a cluster randomized controlled trial from May 2018 to May 2019. In the intervention arm, participants who did not meet the Australian health guidelines for each of the smoking, nutrition, alcohol consumption, and physical activity risk behaviors were provided electronic feedback and proactively offered online and telephone support services. Uptake of support was measured by whether participants signed up for the online and telephone services they were offered. Vocational education students (N=551; mean age 25.7 years, SD 11.1; 310/551, 56.3% male) were recruited into the intervention arm. Uptake of the proactive offer of either online or telephone services was 14.5% (59/406) for fruit and vegetables, 12.7% (29/228) for physical activity, 6.8% (13/191) for smoking, and 5.5% (18/327) for alcohol use. Uptake of any online or telephone service for at least two health behaviors was 5.8% (22/377). Participants who were employed (odds ratio [OR] 0.10, 95% CI 0.01-0.72) and reported not being anxious (OR 0.11, 95% CI 0.02-0.71) had smaller odds of signing up for online or telephone services for smoking, whereas participants who reported not being depressed had greater odds (OR 10.25, 95% CI 1.30-80.67). Participants who intended to change their physical activity in the next 30 days had greater odds (OR 4.01, 95% CI 1.33-12.07) of signing up for online or telephone services for physical activity. Employed participants had smaller odds (OR 0.18, 95% CI 0.06-0.56) of signing up for support services for at least two behaviors. Although the uptake of proactively offered online and telephone support services is low, these rates appear to be higher than the self-initiated use of some of these services in the general population. Scaling up the proactive offer of online and telephone services may produce beneficial health outcomes. Australian New Zealand Clinical Trials Registry: ACTRN12618000723280; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=375001.

Objectives To explore the relationship between cumulative ecological risk and individual risky behavior and multiple forms of aggregated behaviors among adolescents, and examine the gender differences. Methods A large-scale, nationally representative, and students-based investigation was conducted in rural and urban areas of eight provinces in China from October to December 2021. A total of 22 868 adolescents with an average age of 14.64 years completely standardized questionnaire in which the sociodemographic characteristics, socio-ecological risk factors and risky behaviors were used to analyze. Results Of included students, 48.4% encountered the high level of social-ecological risk. The prevalence of breakfast intake not daily, alcohol use (AU), smoking, physical inactivity, prolonged screen time (ST) on weekdays and weekends, suicidal ideation, suicidal plan, suicidal attempt, and non-suicidal self-injury (NSSI) was 41.0%, 11.9%, 3.4%, 61.9%, 15.1%, 51.1%, 27.7%, 13.9%, 6.5% and 27.0% respectively. 22.2% of participants engaged in high-risk behaviors. All were significantly influences of increased cumulative ecological risk on individual behavior and low-risk clustering behaviors separately. The odds ratio of breakfast intake not daily, AU, smoking, physical inactivity, prolonged ST in weekday and weekend, suicidal ideation, suicidal plan, suicidal attempt, and NSSI for the adjusted model in low versus high level of cumulative ecological risk was respectively significant in both boy and girls, and the ratio of odds ratios (ROR) was separately 0.95 ( p  = 0.228), 0.67 ( p  < 0.001), 0.44 ( p  < 0.001), 0.60 ( p  < 0.001), 0.78 ( p  = 0.001), 0.83 ( p  = 0.001), 0.80 ( p  = 0.001), 0.83 ( p  = 0.022), 0.71 ( p  = 0.005), 0.75 ( p  = 0.001). Girls encountering a high level of cumulative ecological risk were more likely to engage in multiple forms of clustering risky behaviors than boys (RORs: 0.77, p  = 0.001). Conclusions Research and effective inventions at the social-ecological environment, based on the view of cumulative risk, are needed to promote the healthy development of behaviors in adolescence, and pay more attention to decreasing the occurrence of risky behaviours in girls than boys.

Background Adolescent health-risk behaviors are prevalent and tend to co-occur. This study aimed to identify patterns of health-risk behaviors among Chinese adolescents during the COVID-19 pandemic and explore the effects of individual and social factors on health-risk patterns. Methods This cross-sectional study investigated 1607 adolescents from four high schools in 2021 through stratified cluster random sampling. Latent class analysis was conducted to identify patterns of health-risk behaviors and logistic regression was used to examine the risk and protective factors of latent class membership. Results Four latent classes were identified: “Low risk” (81.6%), “Problematic Internet use” (7.8%), “Alcohol use” (8.5%), and “High risk” (2.1%). Relative to the “Low risk”, adolescents with higher levels of sensation seeking, deviant peer affiliation, and childhood abuse were more likely to be assigned to the “Problematic Internet use” class, while those with high degrees of parental monitoring and school connectedness were less likely to be in the “Problematic Internet use” class. Those with higher levels of sensation seeking and deviant peer affiliation, lower scores of parental monitoring and school connectedness were more likely to be assigned to the “Alcohol use” class, compared to the “Low risk”. Students in the “High risk” class were more likely to report higher levels of sensation seeking, deviant peer affiliation, and childhood abuse, but lower degrees of parental monitoring and school connectedness than the “Low risk” class. Conclusions This study identified patterns of multiple risk behaviors among Chinese high school students during the COVID-19 pandemic and found that multi-level individual and social factors affected latent classes of adolescent health-risk behaviors. These findings provide clues for designing effective interventions to reduce health-risk behaviors among adolescents.

Tobacco and cannabis use, alcohol consumption and inactivity are health risk behaviors (HRB) of crucial importance for health and wellbeing. The impact of the COVID-19 pandemic on university students’ engagement in HRB has yet received limited attention. We investigated whether HRB changed during the COVID-19 pandemic, assessed factors associated with change and profiles of HRB changes in university students. A web-based survey was conducted in May 2020, including 5021 students of four German universities (69% female, the mean age of 24.4 years (SD = 5.1)). Sixty-one percent of students reported consuming alcohol, 45.8% binge drinking, 44% inactivity, 19.4% smoking and 10.8% cannabis use. While smoking and cannabis use remained unchanged during the COVID-19 pandemic, 24.4% reported a decrease in binge drinking while 5.4% reported an increase. Changes to physical activity were most frequently reported, with 30.6% reporting an increase and 19.3% reporting a decrease in vigorous physical activity. Being female, younger age, being bored, not having a trusted person and depressive symptoms were factors associated with a change in HRB. Five substance use behavior profiles were identified, which also remained fairly unchanged. Efforts to promote student health and wellbeing continue to be required, also in times of the COVID-19 pandemic.

Scientific evidence reveals a high prevalence of health risk behaviour among university students. This calls for the creation of educational programmes that promote more knowledge about health. However, knowledge alone is not enough to change behaviours; other factors should be considered, including attitudes towards health. The objective of this cross-sectional study was to analyse the relationship between knowledge, attitudes and health risk behaviours among university students. For this, a previously validated self-report questionnaire was applied to a stratified sample of 840 students, by year of study (first- and third-year students) and their scientific area. In addition to sociodemographic issues, the questionnaire contains a health-related knowledge scale, an attitudes towards health scale, and questions about health risk behaviours. Students displayed poor knowledge about health, correctly answering 17.77 (SD = 4.59) questions out of a total of 36, and moderate scores concerning attitudes towards health (M = 2.61, SD = 0.48, range: 1–5). Students reported always engaging in, on average, 3.88 (SD = 1.45) of the seven behaviours subject to the analysis. Mediation analyses indicated that knowledge about health and attitudes towards health were statistically significant predictors of risky behaviours. Furthermore, it was indicated that attitudes towards health have a mediating effect between health knowledge and health risk behaviours. Findings from this study indicate that public health and education policies should promote healthy behaviours among university students, taking into account not only the level of knowledge but essentially the development of positive attitudes when facing behaviours which put health at risk.