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Background: Previous literature has examined the societal costs of mental illness, but few studies have estimated the costs associated with mental well-being. In this study, a prospective analysis was conducted on Danish data to determine 1) the association between mental well-being (measured in 2016) and government expenditure in 2017, specifially healthcare costs and sickness benefit transfers. Methods: Data stem from a Danish population-based survey of 3,508 adults (aged 16 + years) in 2016, which was linked to Danish registry data. A validated scale (WEMWBS) was used for the assessment of mental well-being. Costs are expressed in USD PPP. A two-part model was applied to predict costs in 2017, adjusting for sociodemographics, health status (including psychiatric morbidity and health behaviour), as well as costs in the previous year (2016). Results: Each point increase in mental well-being (measured in 2016) was associated with lower healthcare costs ($− 42.5, 95% CI = $− 78.7, $− 6.3) and lower costs in terms of sickness benefit transfers ($− 23.1, 95% CI = $− 41.9, $− 4.3) per person in 2017. Conclusions: Estimated reductions in costs related to mental well-being add to what is already known about potential savings related to the prevention of mental illness. It does so by illustrating the savings that could be made by moving from lower to higher levels of mental well-being both within and beyond the clinical range. Our estimates pertain to costs associated with those health-related outcomes that were included in the study, but excluding other social and economic outcomes and benefits. They cover immediate cost estimates (costs generated the year following mental well-being measurement) and not those that could follow improved mental well-being over the longer term. They may therefore be considered conservative from a societal perspective. Population approaches to mental health promotion are necessary, not only to potentiate disease prevention strategies, but also to reduce costs related to lower levels of mental well-being in the non-mental illness population. Our results suggest that useful reductions in both health care resource use and costs, as well as in costs due to sick leave from the workplace, could be achieved from investment in mental well-being promotion within a year.

BACKGROUND: Previous literature has examined the societal costs of mental illness, but few studies have estimated the costs associated with mental well-being. In this study, a prospective analysis was conducted on Danish data to determine 1) the association between mental well-being (measured in 2016) and government expenditure in 2017, specifially healthcare costs and sickness benefit transfers. METHODS: Data stem from a Danish population-based survey of 3,508 adults (aged 16 + years) in 2016, which was linked to Danish registry data. A validated scale (WEMWBS) was used for the assessment of mental well-being. Costs are expressed in USD PPP. A two-part model was applied to predict costs in 2017, adjusting for sociodemographics, health status (including psychiatric morbidity and health behaviour), as well as costs in the previous year (2016). RESULTS: Each point increase in mental well-being (measured in 2016) was associated with lower healthcare costs ($- 42.5, 95% CI = $- 78.7, $- 6.3) and lower costs in terms of sickness benefit transfers ($- 23.1, 95% CI = $- 41.9, $- 4.3) per person in 2017. CONCLUSIONS: Estimated reductions in costs related to mental well-being add to what is already known about potential savings related to the prevention of mental illness. It does so by illustrating the savings that could be made by moving from lower to higher levels of mental well-being both within and beyond the clinical range. Our estimates pertain to costs associated with those health-related outcomes that were included in the study, but excluding other social and economic outcomes and benefits. They cover immediate cost estimates (costs generated the year following mental well-being measurement) and not those that could follow improved mental well-being over the longer term. They may therefore be considered conservative from a societal perspective. Population approaches to mental health promotion are necessary, not only to potentiate disease prevention strategies, but also to reduce costs related to lower levels of mental well-being in the non-mental illness population. Our results suggest that useful reductions in both health care resource use and costs, as well as in costs due to sick leave from the workplace, could be achieved from investment in mental well-being promotion within a year.

Background: Previous literature has examined the societal costs of mental illness, but few studies have estimated the costs associated with mental well-being. In this study, a prospective analysis was conducted on Danish data to determine 1) the association between mental well-being (measured in 2016) and government expenditure in 2017, specifially healthcare costs and sickness benefit transfers. Methods: Data stem from a Danish population-based survey of 3,508 adults (aged 16 + years) in 2016, which was linked to Danish registry data. A validated scale (WEMWBS) was used for the assessment of mental well-being. Costs are expressed in USD PPP. A two-part model was applied to predict costs in 2017, adjusting for sociodemographics, health status (including psychiatric morbidity and health behaviour), as well as costs in the previous year (2016). Results: Each point increase in mental well-being (measured in 2016) was associated with lower healthcare costs ($− 42.5, 95% CI = $− 78.7, $− 6.3) and lower costs in terms of sickness benefit transfers ($− 23.1, 95% CI = $− 41.9, $− 4.3) per person in 2017. Conclusions: Estimated reductions in costs related to mental well-being add to what is already known about potential savings related to the prevention of mental illness. It does so by illustrating the savings that could be made by moving from lower to higher levels of mental well-being both within and beyond the clinical range. Our estimates pertain to costs associated with those health-related outcomes that were included in the study, but excluding other social and economic outcomes and benefits. They cover immediate cost estimates (costs generated the year following mental well-being measurement) and not those that could follow improved mental well-being over the longer term. They may therefore be considered conservative from a societal perspective. Population approaches to mental health promotion are necessary, not only to potentiate disease prevention strategies, but also to reduce costs related to lower levels of mental well-being in the non-mental illness population. Our results suggest that useful reductions in both health care resource use and costs, as well as in costs due to sick leave from the workplace, could be achieved from investment in mental well-being promotion within a year.

Physical activity, sedentary behavior, and sleep are important predictors of children's health. This paper aimed to investigate socioeconomic disparities in physical activity, sedentary behavior, and sleep across the WHO European region. This cross-sectional study used data on 124,700 children aged 6 to 9 years from 24 countries participating in the WHO European Childhood Obesity Surveillance Initiative between 2015 and 2017. Socioeconomic status (SES) was measured through parental education, parental employment status, and family perceived wealth. Overall, results showed different patterns in socioeconomic disparities in children's movement behaviors across countries. In general, high SES children were more likely to use motorized transportation. Low SES children were less likely to participate in sports clubs and more likely to have more than 2 h/day of screen time. Children with low parental education had a 2.24 [95% CI 1.94-2.58] times higher risk of practising sports for less than 2 h/week. In the pooled analysis, SES was not significantly related to active play. The relationship between SES and sleep varied by the SES indicator used. Importantly, results showed that low SES is not always associated with a higher prevalence of "less healthy" behaviors. There is a great diversity in SES patterns across countries which supports the need for country-specific, targeted public health interventions. ; The authors gratefully acknowledge support from a grant from the Russian Government in the context of the WHO European Office for the Prevention and Control of NCDs. Data collection in the countries was made possible through funding from: Croatia: Ministry of Health, Croatian Institute of Public Health and WHO Regional Office for Europe. Albania: World Health Organization (WHO) Country Office Albania and the WHO Regional Office for Europe. Bulgaria: WHO Regional Office for Europe. Czech Republic: Ministry of Health of the Czech Republic, grant nr. AZV MZČR 17-31670 A and MZČR–RVO EÚ 00023761. Denmark: The Danish Ministry of Health. France: Santé publique France, the French Agency for Public Health. Georgia: WHO. Ireland: Health Service Executive. Italy: Italian Ministry of Health; Italian National Institute of Health (Istituto Superiore di Sanità). Kazakhstan: the Ministry of Health of the Republic of Kazakhstan within the scientific and technical program. Kyrgyzstan: World Health Organization. Latvia: Centre for Disease Prevention and Control, Ministry of Health, Latvia. Lithuania: Science Foundation of Lithuanian University of Health Sciences and Lithuanian Science Council and WHO. Malta: Ministry of Health. Montenegro: WHO and Institute of Public Health of Montenegro. Poland: National Health Programme, Ministry of Health. Portugal: Ministry of Health Institutions, the National Institute of Health, Directorate General of Health, Regional Health Directorates and the kind technical support from the Center for Studies and Research on Social Dynamics and Health (CEIDSS). Romania: Ministry of Health. Russian Federation: WHO. San Marino: Health Ministry. Spain: the Spanish Agency for Food Safety & Nutrition. Tajikistan: WHO Country Office in Tajikistan and Ministry of Health and Social Protection; Turkmenistan: WHO Country Office in Turkmenistan and Ministry of Health. Turkey: Turkish Ministry of Health and World Bank. Austria: Federal Ministry of Labor, Social Affairs, Health and Consumer Protection of Austria. ; info:eu-repo/semantics/publishedVersion