BackgroundThere is a lack of evidence regarding clusters of health-related behaviors among adolescents from low, lower-middle, and upper-middle income countries. This study aimed to identify clustering patterns of health-related behaviors (diet, physical activity [PA] and sedentary behavior [SB]) and association with sociodemographic variables among a population-based sample of Brazilian adolescents.MethodsCross-sectional data from the 2015 National School-Based Health Survey (PeNSE). A total of 102,072 (females: 51.7%) students in ninth-grade (age: 14.3 ± 1.1 years-old) enrolled in public and private schools were investigated in this study. Healthy and unhealthy diet, PA and SB were measured using a validated questionnaire. Two-step cluster analysis was conducted to identify lifestyle patterns. The methodology for complex analysis and weighting was used to inferential statistical procedures. Multinomial logistic regression assessed associations between sociodemographic factors and the clusters.ResultsThree reliable and meaningful clusters were identified and labelled as follows: (1) health-promoting SB and diet (32.6%); (2) health-promoting PA and diet (44.9%), and (3) health-risk (22.5%). Compared to boys, girls were less likely to be in clusters 1 (OR = 0.85; 95% CI = 0.78–0.93, p < 0.001) and 2 (OR = 0.43; 95% CI = 0.40–0.46, p < 0.001) than the health-risk cluster. Higher socioeconomic status was positively associated with health-promoting PA and diet, and negatively related to health-promoting SB and diet. Older adolescents were more likely to be in cluster 1 than in cluster 3, compared to younger adolescents.ConclusionApproximately one-quarter of the population (health-risk cluster) reported engaging in multiple risk behaviors. Interventions may need to be tailored to specific adolescent groups, especially considering sociodemographic differences.Electronic supplementary materialThe online version of this article (10.1186/s12889-018-6203-1) contains supplementary material, which is available to authorized users.
Among smokers, mortality rates were linearly related to the number of cigarettes smoked. Former-smokers had only moderately higher overall mortality rates compared with never-smokers (HR 1.16, 1.07 to 1.25), chiefly due to continued increased risks of death from cancer (1.21, 1.03 to 1.42) and respiratory disease (1.60, 1.29 to 1.98). Conclusions Among men who survived into their 70s, continuing to smoke is associated with persistent excess vascular and non-vascular mortality.
HighlightsThe co-occurrence of obesogenic behaviors is associated to body image indicators.Risk behaviors combined may set the adolescent at risk for psychological health.Adolescents in healthy clusters perceive themselves as having normal weight.Girls engaging in healthy clusters are less likely to use pills to control weight.
The aim of this study was to identify evidence about the prevalence of the community and environment indicators related to physical activity (PA) among young Brazilian people. A systematic review was carried out using eight databases (PubMed, Scopus, Web of Science, LILACS, SPORTDiscus, BIREME, Scielo, and Google Scholar) with descriptors in Portuguese and English. Community and environment Indicators included access, presence, proximity, quality, safety and pollution of/in spaces, facilities, programs available for PA among young people (up to 18 years-old), which may be measured subjectively and/or objectively. A total of 23 documents were included, representing 15 different studies. There were more studies in the South region (n=8), followed by the Northeast (n=3) and Southeast (n=3). Self-reported instruments were more frequently used (n=15). The studies reported prevalence of perception (positive and/or barrier) for access to facilities, programs and/or parks (n=13); presence of sidewalks and bicycle lanes (n=4); proximity to residence (n=5); quality (n=5); safety from crime and traffic (n=14) and pollution (n=6); number of spaces and/or facilities around the residence (n=1); and observation of adolescents using public spaces for PA (n=3). The prevalence rates showed high variability according to environmental indicator. No studies are available for the North and Midwest of the country. Distinct environmental measures were used in selfreported studies, impairing data comparability. To date, no studies have been identified that provide information about the prevalence of combined environmental measures (perceived and objective).
Background: The interaction between physical activity (PA), diet, and sedentary behavior (SB) plays an important role on health-related outcomes. This scoping review (Prospero CRD42018094826) aims to identify and appraise clusters of PA, diet, and SB among youth (0–19 years) according to country income. Methods: Five databases were searched. Fifty-seven articles met the inclusion criteria. Results: Fifty-five cluster types were identified, with greater variety in high-income than lower income countries. The most prevalent profiles were “High SB and consumption of sugar, salt, and beverages (SSB)” (n = 17) and “High PA” (n = 13–5), both of which presented in all income countries. The healthiest profile, “High PA and fruit and vegetables (F&V); Low SB and SSB” (n = 12), was present in upper-middle and high-income countries, while the unhealthiest “Low PA and F&V; High SB and SSB” (n = 6) was present only in high-income countries. Conclusions: High SB and unhealthy diet (SSB) were more prevalent in clusters, mainly in high-income countries. The results support the need for multi-component actions targeting more than one behavior at the same time.
Background: the relationship between behavior clusters and weight status, mainly in low- and middle-income countries, remains unclear. This study aimed to examine the association between profiles of physical activity (PA), diet and sedentary behavior (SB) with weight status in adolescents from a southern Brazilian city, according to sex. Methods: data from the Movimente Intervention study were analyzed (n = 812 / mean age 13.0 years (sd 1.04). Data on SB hours per day, PA minutes per week and weekly consumption frequencies of fruits, vegetables, salty snacks, candies and soda were self-reported on the validated Movimente questionnaire. Classes of healthy and unhealthy behaviors were derived by latent class analysis. Logistic regression analysis was used to estimate the associations between adolescents’ weight status and classes. Results: two classes were identified for the whole sample and for boys and girls. All classes had high probabilities of engaging high time in SB. Male adolescents in the unhealthy class had low probabilities of being active and high probability of consuming a low-quality diet. In contrast, girls’ healthiest profile presented lower probabilities of being active compared to boys’ healthiest profiles. No association was found between weight status and classes. Conclusion: All classes had at least one unhealthy behavior, for both the whole sample, and for girls and boys. Girls’ profiles were unhealthier compared to boys’ profiles. Hence, it is recommended that intervention strategies to change behaviors need to be distinct according to sex, targeting more than one obesogenic behavior at the same time.
Objective: To determine the prevalence of smoking, as well as its association with sociodemographic factors, alcohol consumption, and stress levels, among industrial workers in Brazil. Methods: This was a nationwide survey, conducted in 24 capitals in Brazil through the application of a pre-tested questionnaire. The response to the question “What is your smoking status?” was the outcome variable. To determine the associations, we performed Poisson regression analyses in which the inputs were blocks of variables: block 1 (age and marital status); block 2 (level of education and gross family income); block 3 (geographic region); and block 4 (alcohol consumption and stress level). All analyses were stratified by gender. Results: The sample consisted of 47,328 workers ≥ 18 years of age, of whom 14,577 (30.8%) were women. The prevalence of smoking was 13.0% (15.2% in men and 7.9% in women). Advancing age, alcohol consumption, and a high stress level were positively associated with smoking. A lower risk of smoking was associated with being married, having a higher level of education, and living in the northeastern region of the country (versus the southern region). Conclusions: The prevalence of smoking was greater in men than in women. Alcohol consumption and high stress levels appear to promote smoking.
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