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Background: No previous research of university students in Finland assessed lifestyle behavioral risk factors (BRFs), grouped students into clusters, appraised the relationships of the clusters with their mental well-being, whilst controlling for confounders. The current study undertook this task. Methods: Students at the University of Turku (n = 1177, aged 22.96 ± 5.2 years) completed an online questionnaire that tapped information on sociodemographic variables (age, sex, income sufficiency, accommodation during the semester), four BRFs [problematic alcohol consumption, smoking, food consumption habits, moderate-to-vigorous physical activity (MVPA)], as well as depressive symptoms and stress. Two-step cluster analysis of the BRFs using log-likelihood distance measure categorized students into well-defined clusters. Two regression models appraised the associations between cluster membership and depressive symptoms and stress, controlling for sex, income sufficiency and accommodation during the semester. Results: Slightly more than half the study participants (56.8%) had always/mostly sufficient income and 33% lived with parents/partner. Cluster analysis of BRFs identified three distinct student clusters, namely Cluster 1 (Healthy Group), Cluster 2 (Smokers), and Cluster 3 (Nonsmokers but Problematic Drinkers). Age, sex and MVPA were not different across the clusters, but Clusters 1 and 3 comprised significantly more respondents with always/mostly sufficient income and lived with their parents/partner during the semester. All members in Clusters 1 and 3 were non-smokers, while all Cluster 2 members comprised occasional/daily smokers. Problematic drinking was significantly different between clusters (Cluster 1 = 0%, Cluster 2 = 54%, Cluster 3 = 100%). Cluster 3 exhibited significantly healthier nutrition habits than both other clusters. Regression analysis showed: (1) males and those with sufficient income were significantly less likely to report depressive symptoms o, CC BY 4.0 DEED© The Author(s) 2024.Correspondence Address: S. Suominen; School of Health Sciences, University of Skövde, Skövde, 541 28, Sweden; email: sakari.suominen@his.seRene Sebena was supported by the Slovak Research and Development Agency under the contract No. APVV-19-0284. Open access funding provided by University of Skövde.

Background: No previous research of university students in Finland assessed lifestyle behavioral risk factors (BRFs), grouped students into clusters, appraised the relationships of the clusters with their mental well-being, whilst controlling for confounders. The current study undertook this task. Methods: Students at the University of Turku (n = 1177, aged 22.96 ± 5.2 years) completed an online questionnaire that tapped information on sociodemographic variables (age, sex, income sufficiency, accommodation during the semester), four BRFs [problematic alcohol consumption, smoking, food consumption habits, moderate-to-vigorous physical activity (MVPA)], as well as depressive symptoms and stress. Two-step cluster analysis of the BRFs using log-likelihood distance measure categorized students into well-defined clusters. Two regression models appraised the associations between cluster membership and depressive symptoms and stress, controlling for sex, income sufficiency and accommodation during the semester. Results: Slightly more than half the study participants (56.8%) had always/mostly sufficient income and 33% lived with parents/partner. Cluster analysis of BRFs identified three distinct student clusters, namely Cluster 1 (Healthy Group), Cluster 2 (Smokers), and Cluster 3 (Nonsmokers but Problematic Drinkers). Age, sex and MVPA were not different across the clusters, but Clusters 1 and 3 comprised significantly more respondents with always/mostly sufficient income and lived with their parents/partner during the semester. All members in Clusters 1 and 3 were non-smokers, while all Cluster 2 members comprised occasional/daily smokers. Problematic drinking was significantly different between clusters (Cluster 1 = 0%, Cluster 2 = 54%, Cluster 3 = 100%). Cluster 3 exhibited significantly healthier nutrition habits than both other clusters. Regression analysis showed: (1) males and those with sufficient income were significantly less likely to report depressive symptoms o, CC BY 4.0 DEED© The Author(s) 2024.Correspondence Address: S. Suominen; School of Health Sciences, University of Skövde, Skövde, 541 28, Sweden; email: sakari.suominen@his.seRene Sebena was supported by the Slovak Research and Development Agency under the contract No. APVV-19-0284. Open access funding provided by University of Skövde.

Background: No previous research of university students in Finland assessed lifestyle behavioral risk factors (BRFs), grouped students into clusters, appraised the relationships of the clusters with their mental well-being, whilst controlling for confounders. The current study undertook this task. Methods: Students at the University of Turku (n = 1177, aged 22.96 ± 5.2 years) completed an online questionnaire that tapped information on sociodemographic variables (age, sex, income sufficiency, accommodation during the semester), four BRFs [problematic alcohol consumption, smoking, food consumption habits, moderate-to-vigorous physical activity (MVPA)], as well as depressive symptoms and stress. Two-step cluster analysis of the BRFs using log-likelihood distance measure categorized students into well-defined clusters. Two regression models appraised the associations between cluster membership and depressive symptoms and stress, controlling for sex, income sufficiency and accommodation during the semester. Results: Slightly more than half the study participants (56.8%) had always/mostly sufficient income and 33% lived with parents/partner. Cluster analysis of BRFs identified three distinct student clusters, namely Cluster 1 (Healthy Group), Cluster 2 (Smokers), and Cluster 3 (Nonsmokers but Problematic Drinkers). Age, sex and MVPA were not different across the clusters, but Clusters 1 and 3 comprised significantly more respondents with always/mostly sufficient income and lived with their parents/partner during the semester. All members in Clusters 1 and 3 were non-smokers, while all Cluster 2 members comprised occasional/daily smokers. Problematic drinking was significantly different between clusters (Cluster 1 = 0%, Cluster 2 = 54%, Cluster 3 = 100%). Cluster 3 exhibited significantly healthier nutrition habits than both other clusters. Regression analysis showed: (1) males and those with sufficient income were significantly less likely to report depressive symptoms o, CC BY 4.0 DEED© The Author(s) 2024.Correspondence Address: S. Suominen; School of Health Sciences, University of Skövde, Skövde, 541 28, Sweden; email: sakari.suominen@his.seRene Sebena was supported by the Slovak Research and Development Agency under the contract No. APVV-19-0284. Open access funding provided by University of Skövde.

Background: No previous research of university students in Finland assessed lifestyle behavioral risk factors (BRFs), grouped students into clusters, appraised the relationships of the clusters with their mental well-being, whilst controlling for confounders. The current study undertook this task. Methods: Students at the University of Turku (n = 1177, aged 22.96 ± 5.2 years) completed an online questionnaire that tapped information on sociodemographic variables (age, sex, income sufficiency, accommodation during the semester), four BRFs [problematic alcohol consumption, smoking, food consumption habits, moderate-to-vigorous physical activity (MVPA)], as well as depressive symptoms and stress. Two-step cluster analysis of the BRFs using log-likelihood distance measure categorized students into well-defined clusters. Two regression models appraised the associations between cluster membership and depressive symptoms and stress, controlling for sex, income sufficiency and accommodation during the semester. Results: Slightly more than half the study participants (56.8%) had always/mostly sufficient income and 33% lived with parents/partner. Cluster analysis of BRFs identified three distinct student clusters, namely Cluster 1 (Healthy Group), Cluster 2 (Smokers), and Cluster 3 (Nonsmokers but Problematic Drinkers). Age, sex and MVPA were not different across the clusters, but Clusters 1 and 3 comprised significantly more respondents with always/mostly sufficient income and lived with their parents/partner during the semester. All members in Clusters 1 and 3 were non-smokers, while all Cluster 2 members comprised occasional/daily smokers. Problematic drinking was significantly different between clusters (Cluster 1 = 0%, Cluster 2 = 54%, Cluster 3 = 100%). Cluster 3 exhibited significantly healthier nutrition habits than both other clusters. Regression analysis showed: (1) males and those with sufficient income were significantly less likely to report depressive symptoms o, CC BY 4.0 DEED© The Author(s) 2024.Correspondence Address: S. Suominen; School of Health Sciences, University of Skövde, Skövde, 541 28, Sweden; email: sakari.suominen@his.seRene Sebena was supported by the Slovak Research and Development Agency under the contract No. APVV-19-0284. Open access funding provided by University of Skövde.

Background: No previous research of university students in Finland assessed lifestyle behavioral risk factors (BRFs), grouped students into clusters, appraised the relationships of the clusters with their mental well-being, whilst controlling for confounders. The current study undertook this task. Methods: Students at the University of Turku (n = 1177, aged 22.96 ± 5.2 years) completed an online questionnaire that tapped information on sociodemographic variables (age, sex, income sufficiency, accommodation during the semester), four BRFs [problematic alcohol consumption, smoking, food consumption habits, moderate-to-vigorous physical activity (MVPA)], as well as depressive symptoms and stress. Two-step cluster analysis of the BRFs using log-likelihood distance measure categorized students into well-defined clusters. Two regression models appraised the associations between cluster membership and depressive symptoms and stress, controlling for sex, income sufficiency and accommodation during the semester. Results: Slightly more than half the study participants (56.8%) had always/mostly sufficient income and 33% lived with parents/partner. Cluster analysis of BRFs identified three distinct student clusters, namely Cluster 1 (Healthy Group), Cluster 2 (Smokers), and Cluster 3 (Nonsmokers but Problematic Drinkers). Age, sex and MVPA were not different across the clusters, but Clusters 1 and 3 comprised significantly more respondents with always/mostly sufficient income and lived with their parents/partner during the semester. All members in Clusters 1 and 3 were non-smokers, while all Cluster 2 members comprised occasional/daily smokers. Problematic drinking was significantly different between clusters (Cluster 1 = 0%, Cluster 2 = 54%, Cluster 3 = 100%). Cluster 3 exhibited significantly healthier nutrition habits than both other clusters. Regression analysis showed: (1) males and those with sufficient income were significantly less likely to report depressive symptoms o, CC BY 4.0 DEED© The Author(s) 2024.Correspondence Address: S. Suominen; School of Health Sciences, University of Skövde, Skövde, 541 28, Sweden; email: sakari.suominen@his.seRene Sebena was supported by the Slovak Research and Development Agency under the contract No. APVV-19-0284. Open access funding provided by University of Skövde.

Migrant health depends on factors both at the origin and at the destination. Health-related behaviors established before migration may change at the destination. We compare the mortality rates from alcohol- and smokingrelated causes and cardiovascular diseases (CVD) of Finnish migrants in Sweden to matched controls in both Sweden and Finland with similar sociodemographic characteristics. Migrant mortality rates from behavioral risk factors lie in-between the rates of non-migrants in the origin and destination. A longer duration of residence is associated with lower mortality and with mortality patterns more similar to Swedes for men. For women, a longer duration of residence is associated with higher mortality, in particular smoking-related mortality, with no tendency of a gradual convergence. The density of Finnish migrants in the local area is modestly associated with mortality. However, CVD mortality tends to be higher and more similar to the level in Finland for migrants in areas with a higher density of Finnish migrants. The results suggest that behavioral changes can reduce mortality differences between migrants and natives and that this can be either beneficial or detrimental to migrant health.

Background Prevention and control of cardiometabolic conditions and cardiovascular disease (CVD) in China may contribute to sustainable CVD reduction globally, given the fact that one-fifth of the worldwide population is in China. Knowing the distribution of behavioral risk factors (e.g., smoking and physical inactivity), especially at a national level in China, would be extremely relevant to the field of public health and CVD prevention. The objectives of this study were to investigate the nationwide prevalence of obesity, smoking, heavy drinking, and physical inactivity in Chinese adults, and further explore whether cardiometabolic conditions would modify the distribution of behavioral risk factors. Methods This population-based study is based on the China Health and Retirement Longitudinal Study (2011-2012), including 17,302 adults (>= 45 years, mean age 59.67 years, female 51.66%) from 25 provinces in China. Data on demographics, lifestyle factors, health status and history of diseases were collected via structured interviews and laboratory tests. Smoking, heavy drinking, obesity, and physical inactivity were defined following standard guidelines. We performed descriptive analysis and logistic regressions in this study. Results The overall prevalence of heavy drinking, obesity, current smoking, and physical inactivity among middle-aged and older adults was 7.23% (95% confidence interval 6.53-7.29%), 11.53% (10.43-12.62%), 27.46% (26.30-28.62%), and 44.06% (41.19-46.92%), respectively. The prevalence varied between rural and urban areas as well as among geographic areas, with higher prevalence in the Northern and Northeastern regions. Heavy drinking and obesity were significantly associated with incident hypertension, diabetes, and high cholesterol; while current smoking was significantly associated with incident hypertension. Compared with healthy individuals, participants who self-reported a diagnosis of hypertension, high cholesterol, or diabetes were less, QC 20200818

BACKGROUND: Prevention and control of cardiometabolic conditions and cardiovascular disease (CVD) in China may contribute to sustainable CVD reduction globally, given the fact that one-fifth of the worldwide population is in China. Knowing the distribution of behavioral risk factors (e.g., smoking and physical inactivity), especially at a national level in China, would be extremely relevant to the field of public health and CVD prevention. The objectives of this study were to investigate the nationwide prevalence of obesity, smoking, heavy drinking, and physical inactivity in Chinese adults, and further explore whether cardiometabolic conditions would modify the distribution of behavioral risk factors. METHODS: This population-based study is based on the China Health and Retirement Longitudinal Study (2011-2012), including 17,302 adults (≥45 years, mean age 59.67 years, female 51.66%) from 25 provinces in China. Data on demographics, lifestyle factors, health status and history of diseases were collected via structured interviews and laboratory tests. Smoking, heavy drinking, obesity, and physical inactivity were defined following standard guidelines. We performed descriptive analysis and logistic regressions in this study. RESULTS: The overall prevalence of heavy drinking, obesity, current smoking, and physical inactivity among middle-aged and older adults was 7.23% (95% confidence interval 6.53-7.29%), 11.53% (10.43-12.62%), 27.46% (26.30-28.62%), and 44.06% (41.19-46.92%), respectively. The prevalence varied between rural and urban areas as well as among geographic areas, with higher prevalence in the Northern and Northeastern regions. Heavy drinking and obesity were significantly associated with incident hypertension, diabetes, and high cholesterol; while current smoking was significantly associated with incident hypertension. Compared with healthy individuals, participants who self-reported a diagnosis of hypertension, high cholesterol, or diabetes were less li

BACKGROUND: Prevention and control of cardiometabolic conditions and cardiovascular disease (CVD) in China may contribute to sustainable CVD reduction globally, given the fact that one-fifth of the worldwide population is in China. Knowing the distribution of behavioral risk factors (e.g., smoking and physical inactivity), especially at a national level in China, would be extremely relevant to the field of public health and CVD prevention. The objectives of this study were to investigate the nationwide prevalence of obesity, smoking, heavy drinking, and physical inactivity in Chinese adults, and further explore whether cardiometabolic conditions would modify the distribution of behavioral risk factors. METHODS: This population-based study is based on the China Health and Retirement Longitudinal Study (2011-2012), including 17,302 adults (≥45 years, mean age 59.67 years, female 51.66%) from 25 provinces in China. Data on demographics, lifestyle factors, health status and history of diseases were collected via structured interviews and laboratory tests. Smoking, heavy drinking, obesity, and physical inactivity were defined following standard guidelines. We performed descriptive analysis and logistic regressions in this study. RESULTS: The overall prevalence of heavy drinking, obesity, current smoking, and physical inactivity among middle-aged and older adults was 7.23% (95% confidence interval 6.53-7.29%), 11.53% (10.43-12.62%), 27.46% (26.30-28.62%), and 44.06% (41.19-46.92%), respectively. The prevalence varied between rural and urban areas as well as among geographic areas, with higher prevalence in the Northern and Northeastern regions. Heavy drinking and obesity were significantly associated with incident hypertension, diabetes, and high cholesterol; while current smoking was significantly associated with incident hypertension. Compared with healthy individuals, participants who self-reported a diagnosis of hypertension, high cholesterol, or diabetes were less li

Background: Prevention and control of cardiometabolic conditions and cardiovascular disease (CVD) in China may contribute to sustainable CVD reduction globally, given the fact that one-fifth of the worldwide population is in China. Knowing the distribution of behavioral risk factors (e.g., smoking and physical inactivity), especially at a national level in China, would be extremely relevant to the field of public health and CVD prevention. The objectives of this study were to investigate the nationwide prevalence of obesity, smoking, heavy drinking, and physical inactivity in Chinese adults, and further explore whether cardiometabolic conditions would modify the distribution of behavioral risk factors. Methods: This population-based study is based on the China Health and Retirement Longitudinal Study (2011-2012), including 17,302 adults (>= 45 years, mean age 59.67 years, female 51.66%) from 25 provinces in China. Data on demographics, lifestyle factors, health status and history of diseases were collected via structured interviews and laboratory tests. Smoking, heavy drinking, obesity, and physical inactivity were defined following standard guidelines. We performed descriptive analysis and logistic regressions in this study. Results: The overall prevalence of heavy drinking, obesity, current smoking, and physical inactivity among middle-aged and older adults was 7.23% (95% confidence interval 6.53-7.29%), 11.53% (10.43-12.62%), 27.46% (26.30-28.62%), and 44.06% (41.19-46.92%), respectively. The prevalence varied between rural and urban areas as well as among geographic areas, with higher prevalence in the Northern and Northeastern regions. Heavy drinking and obesity were significantly associated with incident hypertension, diabetes, and high cholesterol; while current smoking was significantly associated with incident hypertension. Compared with healthy individuals, participants who self-reported a diagnosis of hypertension, high cholesterol, or diabetes were le

BACKGROUND: Prevention and control of cardiometabolic conditions and cardiovascular disease (CVD) in China may contribute to sustainable CVD reduction globally, given the fact that one-fifth of the worldwide population is in China. Knowing the distribution of behavioral risk factors (e.g., smoking and physical inactivity), especially at a national level in China, would be extremely relevant to the field of public health and CVD prevention. The objectives of this study were to investigate the nationwide prevalence of obesity, smoking, heavy drinking, and physical inactivity in Chinese adults, and further explore whether cardiometabolic conditions would modify the distribution of behavioral risk factors. METHODS: This population-based study is based on the China Health and Retirement Longitudinal Study (2011-2012), including 17,302 adults (≥45 years, mean age 59.67 years, female 51.66%) from 25 provinces in China. Data on demographics, lifestyle factors, health status and history of diseases were collected via structured interviews and laboratory tests. Smoking, heavy drinking, obesity, and physical inactivity were defined following standard guidelines. We performed descriptive analysis and logistic regressions in this study. RESULTS: The overall prevalence of heavy drinking, obesity, current smoking, and physical inactivity among middle-aged and older adults was 7.23% (95% confidence interval 6.53-7.29%), 11.53% (10.43-12.62%), 27.46% (26.30-28.62%), and 44.06% (41.19-46.92%), respectively. The prevalence varied between rural and urban areas as well as among geographic areas, with higher prevalence in the Northern and Northeastern regions. Heavy drinking and obesity were significantly associated with incident hypertension, diabetes, and high cholesterol; while current smoking was significantly associated with incident hypertension. Compared with healthy individuals, participants who self-reported a diagnosis of hypertension, high cholesterol, or diabetes were less li

BACKGROUND: Prevention and control of cardiometabolic conditions and cardiovascular disease (CVD) in China may contribute to sustainable CVD reduction globally, given the fact that one-fifth of the worldwide population is in China. Knowing the distribution of behavioral risk factors (e.g., smoking and physical inactivity), especially at a national level in China, would be extremely relevant to the field of public health and CVD prevention. The objectives of this study were to investigate the nationwide prevalence of obesity, smoking, heavy drinking, and physical inactivity in Chinese adults, and further explore whether cardiometabolic conditions would modify the distribution of behavioral risk factors. METHODS: This population-based study is based on the China Health and Retirement Longitudinal Study (2011-2012), including 17,302 adults (≥45 years, mean age 59.67 years, female 51.66%) from 25 provinces in China. Data on demographics, lifestyle factors, health status and history of diseases were collected via structured interviews and laboratory tests. Smoking, heavy drinking, obesity, and physical inactivity were defined following standard guidelines. We performed descriptive analysis and logistic regressions in this study. RESULTS: The overall prevalence of heavy drinking, obesity, current smoking, and physical inactivity among middle-aged and older adults was 7.23% (95% confidence interval 6.53-7.29%), 11.53% (10.43-12.62%), 27.46% (26.30-28.62%), and 44.06% (41.19-46.92%), respectively. The prevalence varied between rural and urban areas as well as among geographic areas, with higher prevalence in the Northern and Northeastern regions. Heavy drinking and obesity were significantly associated with incident hypertension, diabetes, and high cholesterol; while current smoking was significantly associated with incident hypertension. Compared with healthy individuals, participants who self-reported a diagnosis of hypertension, high cholesterol, or diabetes were less li

BACKGROUND: Prevention and control of cardiometabolic conditions and cardiovascular disease (CVD) in China may contribute to sustainable CVD reduction globally, given the fact that one-fifth of the worldwide population is in China. Knowing the distribution of behavioral risk factors (e.g., smoking and physical inactivity), especially at a national level in China, would be extremely relevant to the field of public health and CVD prevention. The objectives of this study were to investigate the nationwide prevalence of obesity, smoking, heavy drinking, and physical inactivity in Chinese adults, and further explore whether cardiometabolic conditions would modify the distribution of behavioral risk factors. METHODS: This population-based study is based on the China Health and Retirement Longitudinal Study (2011-2012), including 17,302 adults (≥45 years, mean age 59.67 years, female 51.66%) from 25 provinces in China. Data on demographics, lifestyle factors, health status and history of diseases were collected via structured interviews and laboratory tests. Smoking, heavy drinking, obesity, and physical inactivity were defined following standard guidelines. We performed descriptive analysis and logistic regressions in this study. RESULTS: The overall prevalence of heavy drinking, obesity, current smoking, and physical inactivity among middle-aged and older adults was 7.23% (95% confidence interval 6.53-7.29%), 11.53% (10.43-12.62%), 27.46% (26.30-28.62%), and 44.06% (41.19-46.92%), respectively. The prevalence varied between rural and urban areas as well as among geographic areas, with higher prevalence in the Northern and Northeastern regions. Heavy drinking and obesity were significantly associated with incident hypertension, diabetes, and high cholesterol; while current smoking was significantly associated with incident hypertension. Compared with healthy individuals, participants who self-reported a diagnosis of hypertension, high cholesterol, or diabetes were less li

BACKGROUND: Prevention and control of cardiometabolic conditions and cardiovascular disease (CVD) in China may contribute to sustainable CVD reduction globally, given the fact that one-fifth of the worldwide population is in China. Knowing the distribution of behavioral risk factors (e.g., smoking and physical inactivity), especially at a national level in China, would be extremely relevant to the field of public health and CVD prevention. The objectives of this study were to investigate the nationwide prevalence of obesity, smoking, heavy drinking, and physical inactivity in Chinese adults, and further explore whether cardiometabolic conditions would modify the distribution of behavioral risk factors. METHODS: This population-based study is based on the China Health and Retirement Longitudinal Study (2011-2012), including 17,302 adults (≥45 years, mean age 59.67 years, female 51.66%) from 25 provinces in China. Data on demographics, lifestyle factors, health status and history of diseases were collected via structured interviews and laboratory tests. Smoking, heavy drinking, obesity, and physical inactivity were defined following standard guidelines. We performed descriptive analysis and logistic regressions in this study. RESULTS: The overall prevalence of heavy drinking, obesity, current smoking, and physical inactivity among middle-aged and older adults was 7.23% (95% confidence interval 6.53-7.29%), 11.53% (10.43-12.62%), 27.46% (26.30-28.62%), and 44.06% (41.19-46.92%), respectively. The prevalence varied between rural and urban areas as well as among geographic areas, with higher prevalence in the Northern and Northeastern regions. Heavy drinking and obesity were significantly associated with incident hypertension, diabetes, and high cholesterol; while current smoking was significantly associated with incident hypertension. Compared with healthy individuals, participants who self-reported a diagnosis of hypertension, high cholesterol, or diabetes were less li

The aim of this study was to investigate the prevalence and correlates of behavioral non-communicable disease (NCD) risk factors among a national sample of school-going adolescents in the Seychelles. Cross-sectional data were analyzed from 2540 school adolescents (median age 14 years, interquartile range = 2), in the Seychelles “Global School-Based Student Health Survey (GSHS)” in 2015. Behavioral NCD risk factors (current tobacco use, current alcohol use, inadequate fruit and vegetable consumption, soft drink consumption, overweight or obesity, physical inactivity, and leisure-time sedentary behavior) were assessed by self-report. Among the seven individual behavioral risk factors, the highest prevalence was physical inactivity (82.7%), followed by daily soft drink consumption (68.3%), inadequate fruit and vegetable consumption (60.9%), leisure-time sedentary behavior (51.0%), current alcohol use (47.6%), overweight or obesity (28.2%), and current tobacco use (23.4%). The total mean number of behavioral NCD risk factors was 3.6 (Standard Deviation = 1.3), and the proportion of co-occurrence of having three or more behavioral NCD risk factors was 80.7%. In adjusted linear regression analysis, male sex, older age, and psychological distress were positively, and school attendance and peer support were negatively associated with the total number of behavioral NCD risk factors. A high prevalence of multiple behavioral NCD risk factors were found and several associated factors were identified, such as male sex, older age, psychological distress, school truancy, and lack of peer support, which may help in aiding intervention programs in this population

The aim of this study was to investigate the prevalence and correlates of behavioral non-communicable disease (NCD) risk factors among a national sample of school-going adolescents in the Seychelles. Cross-sectional data were analyzed from 2540 school adolescents (median age 14 years, interquartile range = 2), in the Seychelles “Global School-Based Student Health Survey (GSHS)” in 2015. Behavioral NCD risk factors (current tobacco use, current alcohol use, inadequate fruit and vegetable consumption, soft drink consumption, overweight or obesity, physical inactivity, and leisure-time sedentary behavior) were assessed by self-report. Among the seven individual behavioral risk factors, the highest prevalence was physical inactivity (82.7%), followed by daily soft drink consumption (68.3%), inadequate fruit and vegetable consumption (60.9%), leisure-time sedentary behavior (51.0%), current alcohol use (47.6%), overweight or obesity (28.2%), and current tobacco use (23.4%). The total mean number of behavioral NCD risk factors was 3.6 (Standard Deviation = 1.3), and the proportion of co-occurrence of having three or more behavioral NCD risk factors was 80.7%. In adjusted linear regression analysis, male sex, older age, and psychological distress were positively, and school attendance and peer support were negatively associated with the total number of behavioral NCD risk factors. A high prevalence of multiple behavioral NCD risk factors were found and several associated factors were identified, such as male sex, older age, psychological distress, school truancy, and lack of peer support, which may help in aiding intervention programs in this population

Objetivo El objetivo de este trabajo fue estimar la prevalencia de la inactividad física en Galicia en el tiempo libre en 2007-2011, así como el impacto que supone en ella el considerar otras actividades cotidianas. Métodos Estudios transversales en mayores de 15 años (n = 19235). La actividad física se caracterizó mediante el cuestionario Minnesota. En el año 2011 se estimó la inactividad física considerando otras actividades cotidianas. Resultados Entre 2007 y 2011, la prevalencia de inactividad física en el tiempo libre en Galicia fue estable (p = 0,249), próxima al 50%, y más alta en las mujeres y en la población que trabaja o estudia. La inactividad física disminuyó (47% a 16%) cuando se tuvieron en cuenta las actividades cotidianas. Conclusiones La prevalencia de inactividad física fue alta y estable en los años estudiados. Tener en cuenta otras actividades de la vida cotidiana hizo disminuir de forma importante esta prevalencia., Objective To estimate the prevalence of physical inactivity during leisure time in Galicia (Spain) between 2007 and 2011 and to assess the impact of including non-leisure time activities in the definition of physical inactivity. Methods A cross-sectional study was conducted in the population aged 16 years and older (n = 19,235). Physical activity was assessed by the Minnesota Questionnaire. In 2011, inactivity was estimated by including daily activities. Results Between 2007 and 2011, the prevalence of inactivity in Galicia remained stable (p = 0.249) and close to 50%. This prevalence was higher among women and those who worked or were in education. Inactivity decreased from 47% to 16% when non-leisure time activities were included in the definition. Conclusions Between 2007 and 2011 in Galicia, the prevalence of inactivity remained high and stable. This prevalence was significantly decreased when non-leisure time activities were included in the definition.

BackgroundTo evaluate the effectiveness of interventions used in primary care to improve health literacy for change in smoking, nutrition, alcohol, physical activity and weight (SNAPW).MethodsA systematic review of intervention studies that included outcomes for health literacy and SNAPW behavioral risk behaviors implemented in primary care settings.We searched the Cochrane Library, Johanna Briggs Institute, Medline, Embase, CINAHL, Psychinfo, Web of Science, Scopus, APAIS, Australasian Medical Index, Google Scholar, Community of Science and four targeted journals (Patient Education and Counseling, Health Education and Behaviour, American Journal of Preventive Medicine and Preventive Medicine).Study inclusion criteria: Adults over 18 years; undertaken in a primary care setting within an Organisation for Economic Co-operation and Development (OECD) country; interventions with at least one measure of health literacy and promoting positive change in smoking, nutrition, alcohol, physical activity and/or weight; measure at least one outcome associated with health literacy and report a SNAPW outcome; and experimental and quasi-experimental studies, cohort, observational and controlled and non-controlled before and after studies.Papers were assessed and screened by two researchers (JT, AW) and uncertain or excluded studies were reviewed by a third researcher (MH). Data were extracted from the included studies by two researchers (JT, AW). Effectiveness studies were quality assessed. A typology of interventions was thematically derived from the studies by grouping the SNAPW interventions into six broad categories: individual motivational interviewing and counseling; group education; multiple interventions (combination of interventions); written materials; telephone coaching or counseling; and computer or web based interventions. Interventions were classified by intensity of contact with the subjects (High ≥ 8 points of contact/hours; Moderate >3 and

BackgroundTo evaluate the effectiveness of interventions used in primary care to improve health literacy for change in smoking, nutrition, alcohol, physical activity and weight (SNAPW).MethodsA systematic review of intervention studies that included outcomes for health literacy and SNAPW behavioral risk behaviors implemented in primary care settings.We searched the Cochrane Library, Johanna Briggs Institute, Medline, Embase, CINAHL, Psychinfo, Web of Science, Scopus, APAIS, Australasian Medical Index, Google Scholar, Community of Science and four targeted journals (Patient Education and Counseling, Health Education and Behaviour, American Journal of Preventive Medicine and Preventive Medicine).Study inclusion criteria: Adults over 18 years; undertaken in a primary care setting within an Organisation for Economic Co-operation and Development (OECD) country; interventions with at least one measure of health literacy and promoting positive change in smoking, nutrition, alcohol, physical activity and/or weight; measure at least one outcome associated with health literacy and report a SNAPW outcome; and experimental and quasi-experimental studies, cohort, observational and controlled and non-controlled before and after studies.Papers were assessed and screened by two researchers (JT, AW) and uncertain or excluded studies were reviewed by a third researcher (MH). Data were extracted from the included studies by two researchers (JT, AW). Effectiveness studies were quality assessed. A typology of interventions was thematically derived from the studies by grouping the SNAPW interventions into six broad categories: individual motivational interviewing and counseling; group education; multiple interventions (combination of interventions); written materials; telephone coaching or counseling; and computer or web based interventions. Interventions were classified by intensity of contact with the subjects (High ≥ 8 points of contact/hours; Moderate >3 and

SummaryMany falls occur among older adults with no traditional risk factors. We examined potential independent effects of lifestyle on fall risk. Not smoking and going outdoors frequently or infrequently were independently associated with more falls, indicating lifestyle-related behavioral and environmental risk factors are important causes of falls in older women.IntroductionPhysical and lifestyle risk factors for falls and population attributable risks (PAR) were examined.MethodsWe conducted a 4-year prospective study of 8,378 community-dwelling women (mean age = 71 years, SD = 3) enrolled in the Study of Osteoporotic Fractures. Data on number of falls were self-reported every 4 months. Fall rates were calculated (# falls/woman-years). Poisson regression was used to estimate relative risks (RR).ResultsPhysical risk factors (p < or = 0.05 for all) included tall height (RR = 0.89 per 5 in.), dizziness (RR = 1.16), fear of falling (RR = 1.20), self-reported health decline (RR = 1.19), difficulty with Instrumental Activities of Daily Living (IADLs) (RR = 1.12, per item), fast usual-paced walking speed (RR = 1.18, per 2 SD), and use of antidepressants (RR = 1.20), benzodiazepines (RR = 1.11), or anticonvulsants (RR = 1.62). Protective physical factors (p < or = 0.05 for all) included good visual acuity (RR = 0.87, per 2 SD) and good balance (RR = 0.85 vs. poor). Lifestyle predicted fewer falls including current smoking (RR = 0.76), going outdoors at least twice weekly but not more than once a day (RR = 0.89 and vs. twice daily). High physical activity was associated with more falls but only among IADL impaired women. Five potentially modifiable physical risk factors had PAR > or = 5%.ConclusionsFall interventions addressing modifiable physical risk factors with PAR > or = 5% while considering environmental/behavioral risk factors are indicated.

Many falls occur among older adults with no traditional risk factors. We examined potential independent effects of lifestyle on fall risk. Not smoking and going outdoors frequently or infrequently were independently associated with more falls, indicating lifestyle-related behavioral and environmental risk factors are important causes of falls in older women. Physical and lifestyle risk factors for falls and population attributable risks (PAR) were examined. We conducted a 4-year prospective study of 8,378 community-dwelling women (mean age = 71 years, SD = 3) enrolled in the Study of Osteoporotic Fractures. Data on number of falls were self-reported every 4 months. Fall rates were calculated (# falls/woman-years). Poisson regression was used to estimate relative risks (RR). Physical risk factors (p ≤ 0.05 for all) included tall height (RR = 0.89 per 5 in.), dizziness (RR = 1.16), fear of falling (RR = 1.20), self-reported health decline (RR = 1.19), difficulty with Instrumental Activities of Daily Living (IADLs) (RR = 1.12, per item), fast usual-paced walking speed (RR = 1.18, per 2 SD), and use of antidepressants (RR = 1.20), benzodiazepines (RR = 1.11), or anticonvulsants (RR = 1.62). Protective physical factors (p ≤ 0.05 for all) included good visual acuity (RR = 0.87, per 2 SD) and good balance (RR = 0.85 vs. poor). Lifestyle predicted fewer falls including current smoking (RR = 0.76), going outdoors at least twice weekly but not more than once a day (RR = 0.89 and vs. twice daily). High physical activity was associated with more falls but only among IADL impaired women. Five potentially modifiable physical risk factors had PAR ≥ 5%. Fall interventions addressing modifiable physical risk factors with PAR ≥ 5% while considering environmental/behavioral risk factors are indicated.

Many falls occur among older adults with no traditional risk factors. We examined potential independent effects of lifestyle on fall risk. Not smoking and going outdoors frequently or infrequently were independently associated with more falls, indicating lifestyle-related behavioral and environmental risk factors are important causes of falls in older women. Physical and lifestyle risk factors for falls and population attributable risks (PAR) were examined. We conducted a 4-year prospective study of 8,378 community-dwelling women (mean age = 71 years, SD = 3) enrolled in the Study of Osteoporotic Fractures. Data on number of falls were self-reported every 4 months. Fall rates were calculated (# falls/woman-years). Poisson regression was used to estimate relative risks (RR). Physical risk factors (p ≤ 0.05 for all) included tall height (RR = 0.89 per 5 in.), dizziness (RR = 1.16), fear of falling (RR = 1.20), self-reported health decline (RR = 1.19), difficulty with Instrumental Activities of Daily Living (IADLs) (RR = 1.12, per item), fast usual-paced walking speed (RR = 1.18, per 2 SD), and use of antidepressants (RR = 1.20), benzodiazepines (RR = 1.11), or anticonvulsants (RR = 1.62). Protective physical factors (p ≤ 0.05 for all) included good visual acuity (RR = 0.87, per 2 SD) and good balance (RR = 0.85 vs. poor). Lifestyle predicted fewer falls including current smoking (RR = 0.76), going outdoors at least twice weekly but not more than once a day (RR = 0.89 and vs. twice daily). High physical activity was associated with more falls but only among IADL impaired women. Five potentially modifiable physical risk factors had PAR ≥ 5%. Fall interventions addressing modifiable physical risk factors with PAR ≥ 5% while considering environmental/behavioral risk factors are indicated.

SummaryMany falls occur among older adults with no traditional risk factors. We examined potential independent effects of lifestyle on fall risk. Not smoking and going outdoors frequently or infrequently were independently associated with more falls, indicating lifestyle-related behavioral and environmental risk factors are important causes of falls in older women.IntroductionPhysical and lifestyle risk factors for falls and population attributable risks (PAR) were examined.MethodsWe conducted a 4-year prospective study of 8,378 community-dwelling women (mean age = 71 years, SD = 3) enrolled in the Study of Osteoporotic Fractures. Data on number of falls were self-reported every 4 months. Fall rates were calculated (# falls/woman-years). Poisson regression was used to estimate relative risks (RR).ResultsPhysical risk factors (p < or = 0.05 for all) included tall height (RR = 0.89 per 5 in.), dizziness (RR = 1.16), fear of falling (RR = 1.20), self-reported health decline (RR = 1.19), difficulty with Instrumental Activities of Daily Living (IADLs) (RR = 1.12, per item), fast usual-paced walking speed (RR = 1.18, per 2 SD), and use of antidepressants (RR = 1.20), benzodiazepines (RR = 1.11), or anticonvulsants (RR = 1.62). Protective physical factors (p < or = 0.05 for all) included good visual acuity (RR = 0.87, per 2 SD) and good balance (RR = 0.85 vs. poor). Lifestyle predicted fewer falls including current smoking (RR = 0.76), going outdoors at least twice weekly but not more than once a day (RR = 0.89 and vs. twice daily). High physical activity was associated with more falls but only among IADL impaired women. Five potentially modifiable physical risk factors had PAR > or = 5%.ConclusionsFall interventions addressing modifiable physical risk factors with PAR > or = 5% while considering environmental/behavioral risk factors are indicated.

While physiologic risk factors for injury in military training populations have been well-established, knowledge of behavioral risk factors is limited. This study investigated the association of health risk behaviors with injuries sustained by men and women in Army basic training. Self-reported questionnaire data on health risk behaviors collected on entry to training were linked to medical data on injuries occurring during the 9-week training period. Multivariate survival analysis tested the association of training-related injury with a risk-taking index consisting of five individual health risk behaviors (cigarette use, smokeless tobacco use, alcohol use, weight control practices, and diet/lifestyle choices). Analyses were conducted separately for men and women, and models controlled for demographic, physical fitness, and physiologic characteristics. Among this sample of 1,156 young mean and 746 women (median age: 19), cumulative injury incidence was 4.2 trainees/1,000 trainee-days for mean and 9.3 trainees/1,000 trainee-days for women. Males in both the lowest (Hazard ratio (HR)=1.73, 95%CI:1.47,2.05) and highest (HR=1.92, 95%CI:1.57,2.34) risk-taking index categories had greater risk of training-related injury compared to persons within one standard deviation of the mean risk index score. Cigarette use was independently associated with training-related injury; males in the medium risk cigarette use index category had 1.8 times the risk of a training-related injury compared to the low risk category (HR=1.77, 95%CI:1.31 ,2.40). An association between the combined risk-taking index and injury was not seen among females. However, females in the high risk cigarette use category (HR=1.53, 95%CI:1.1 0,2.12) and females in the medium (HR=1.08, 95%CI:1.03, 1.14) and high risk (HR: 1.52, 95%CI:1.21, 1.93) diet/lifestyle categories had higher risk of training-related injury compared to females in low risk categories., Doctoral dissertation

peer-reviewed, Background Osteoporosis constitutes a major public health concern and its underlying pathogenesis is complex and multifactorial. Although hereditary factors strongly contribute to bone health, behavioural factors can modulate the genetically determined pattern of skeletal modelling and remodelling. Aims The aim of this study was to investigate the effect(s) of behavioural risk factors on osteoporosis in Irish women. Methods Pre- and post-menopausal adult women (n = 189; 44 ± 15y) participated in this cross-sectional study. Demographic, anthropometric and lifestyle data were collected during a single clinic visit. Dietary calcium intake and lifetime physical activity (PA) was assessed for each subject. Lumbar and femoral bone mineral density (BMD) was measured by dual energy X-ray absorptiometry (DXA). Multivariate analysis was used to determine the independent predictors of low BMD. Results Low BMD was present in 59% of subjects (42% pre- and 77% postmenopausal). Smoking was the strongest behavioural predictor of lumbar and femoral BMD. Age, height, family history, smoking, metabolic (MET) and mechanical (MECH) PA (lifetime) and weight (body mass) accounted for 39% of the variance in lumbar BMD. Age, height, family history, alcohol consumption, MET and MECH PA (lifetime) and weight accounted for 41% of the variance in femoral BMD. Conclusions Prevalence of osteopenia and osteoporosis is high in Irish women and is associated with modifiable risk factors. A clearer focus should be paid to educating Irish women on preventative health behaviours for osteoporosis in order to curb the prevalence of this disease and the human and fiscal costs associated with it.