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  • 1.
    Abarca-Gómez, Leandra
    et al.
    Caja Costarricense de Seguro Social, Costa Rica.
    Eiben, Gabriele
    University of Skövde, School of Health and Education. University of Skövde, Health and Education.
    Ezzati, Majid
    School of Public Health, Imperial College London, London, United Kingdom.
    Worldwide trends in body-mass index, underweight, overweight, and obesity from 1975 to 2016: a pooled analysis of 2416 population-based measurement studies in 128·9 million children, adolescents, and adults2017In: The Lancet, ISSN 0140-6736, E-ISSN 1474-547X, Vol. 390, no 10113, p. 2627-2642Article in journal (Refereed)
    Abstract [en]

    BACKGROUND: Underweight, overweight, and obesity in childhood and adolescence are associated with adverse health consequences throughout the life-course. Our aim was to estimate worldwide trends in mean body-mass index (BMI) and a comprehensive set of BMI categories that cover underweight to obesity in children and adolescents, and to compare trends with those of adults.

    METHODS: We pooled 2416 population-based studies with measurements of height and weight on 128·9 million participants aged 5 years and older, including 31·5 million aged 5-19 years. We used a Bayesian hierarchical model to estimate trends from 1975 to 2016 in 200 countries for mean BMI and for prevalence of BMI in the following categories for children and adolescents aged 5-19 years: more than 2 SD below the median of the WHO growth reference for children and adolescents (referred to as moderate and severe underweight hereafter), 2 SD to more than 1 SD below the median (mild underweight), 1 SD below the median to 1 SD above the median (healthy weight), more than 1 SD to 2 SD above the median (overweight but not obese), and more than 2 SD above the median (obesity).

    FINDINGS: Regional change in age-standardised mean BMI in girls from 1975 to 2016 ranged from virtually no change (-0·01 kg/m(2) per decade; 95% credible interval -0·42 to 0·39, posterior probability [PP] of the observed decrease being a true decrease=0·5098) in eastern Europe to an increase of 1·00 kg/m(2) per decade (0·69-1·35, PP>0·9999) in central Latin America and an increase of 0·95 kg/m(2) per decade (0·64-1·25, PP>0·9999) in Polynesia and Micronesia. The range for boys was from a non-significant increase of 0·09 kg/m(2) per decade (-0·33 to 0·49, PP=0·6926) in eastern Europe to an increase of 0·77 kg/m(2) per decade (0·50-1·06, PP>0·9999) in Polynesia and Micronesia. Trends in mean BMI have recently flattened in northwestern Europe and the high-income English-speaking and Asia-Pacific regions for both sexes, southwestern Europe for boys, and central and Andean Latin America for girls. By contrast, the rise in BMI has accelerated in east and south Asia for both sexes, and southeast Asia for boys. Global age-standardised prevalence of obesity increased from 0·7% (0·4-1·2) in 1975 to 5·6% (4·8-6·5) in 2016 in girls, and from 0·9% (0·5-1·3) in 1975 to 7·8% (6·7-9·1) in 2016 in boys; the prevalence of moderate and severe underweight decreased from 9·2% (6·0-12·9) in 1975 to 8·4% (6·8-10·1) in 2016 in girls and from 14·8% (10·4-19·5) in 1975 to 12·4% (10·3-14·5) in 2016 in boys. Prevalence of moderate and severe underweight was highest in India, at 22·7% (16·7-29·6) among girls and 30·7% (23·5-38·0) among boys. Prevalence of obesity was more than 30% in girls in Nauru, the Cook Islands, and Palau; and boys in the Cook Islands, Nauru, Palau, Niue, and American Samoa in 2016. Prevalence of obesity was about 20% or more in several countries in Polynesia and Micronesia, the Middle East and north Africa, the Caribbean, and the USA. In 2016, 75 (44-117) million girls and 117 (70-178) million boys worldwide were moderately or severely underweight. In the same year, 50 (24-89) million girls and 74 (39-125) million boys worldwide were obese.

    INTERPRETATION: The rising trends in children's and adolescents' BMI have plateaued in many high-income countries, albeit at high levels, but have accelerated in parts of Asia, with trends no longer correlated with those of adults.

    FUNDING: Wellcome Trust, AstraZeneca Young Health Programme.

  • 2.
    Chang, Angela Y.
    et al.
    Univ Washington, Inst Hlth Metr & Evaluat, Seattle, USA.
    Dalal, Koustuv
    University of Skövde, School of Health and Education. University of Skövde, Health and Education.
    Dieleman, Joseph L.
    Univ Washington, Inst Hlth Metr & Evaluat, Seattle, USA / Univ Washington, Dept Hlth Metr Sci, Seattle, USA.
    Past, present, and future of global health financing: a review of development assistance, government, out-of-pocket, and other private spending on health for 195 countries, 1995–20502019In: The Lancet, ISSN 0140-6736, E-ISSN 1474-547X, Vol. 393, no 10187, p. 2233-2260Article, review/survey (Refereed)
    Abstract [en]

    Background Comprehensive and comparable estimates of health spending in each country are a key input for health policy and planning, and are necessary to support the achievement of national and international health goals. Previous studies have tracked past and projected future health spending until 2040 and shown that, with economic development, countries tend to spend more on health per capita, with a decreasing share of spending from development assistance and out-of-pocket sources. We aimed to characterise the past, present, and predicted future of global health spending, with an emphasis on equity in spending across countries. Methods We estimated domestic health spending for 195 countries and territories from 1995 to 2016, split into three categories-government, out-of-pocket, and prepaid private health spending-and estimated development assistance for health (DAH) from 1990 to 2018. We estimated future scenarios of health spending using an ensemble of linear mixed-effects models with time series specifications to project domestic health spending from 2017 through 2050 and DAH from 2019 through 2050. Data were extracted from a broad set of sources tracking health spending and revenue, and were standardised and converted to inflation-adjusted 2018 US dollars. Incomplete or low-quality data were modelled and uncertainty was estimated, leading to a complete data series of total, government, prepaid private, and out-of-pocket health spending, and DAH. Estimates are reported in 2018 US dollars, 2018 purchasing-power parity-adjusted dollars, and as a percentage of gross domestic product. We used demographic decomposition methods to assess a set of factors associated with changes in government health spending between 1995 and 2016 and to examine evidence to support the theory of the health financing transition. We projected two alternative future scenarios based on higher government health spending to assess the potential ability of governments to generate more resources for health. Findings Between 1995 and 2016, health spending grew at a rate of 4.00% (95% uncertainty interval 3.89-4.12) annually, although it grew slower in per capita terms (2.72% [2.61-2.84]) and increased by less than $ 1 per capita over this period in 22 of 195 countries. The highest annual growth rates in per capita health spending were observed in upper-middle-income countries (5.55% [5.18-5.95]), mainly due to growth in government health spending, and in lower-middle-income countries (3.71% [3.10-4.34]), mainly from DAH. Health spending globally reached $ 8.0 trillion (7.8-8.1) in 2016 (comprising 8.6% [8.4-8.7] of the global economy and $ 10.3 trillion [10.1-10.6] in purchasing-power parity-adjusted dollars), with a per capita spending of US$ 5252 (5184-5319) in high-income countries, $ 491 (461-524) in upper-middle-income countries, $ 81 (74-89) in lower-middle-income countries, and $ 40 (38-43) in low-income countries. In 2016, 0.4% (0.3-0.4) of health spending globally was in low-income countries, despite these countries comprising 10.0% of the global population. In 2018, the largest proportion of DAH targeted HIV/AIDS ($ 9.5 billion, 24.3% of total DAH), although spending on other infectious diseases (excluding tuberculosis and malaria) grew fastest from 2010 to 2018 (6.27% per year). The leading sources of DAH were the USA and private philanthropy (excluding corporate donations and the Bill & Melinda Gates Foundation). For the first time, we included estimates of China's contribution to DAH ($ 644.7 million in 2018). Globally, health spending is projected to increase to $ 15.0 trillion (14.0-16.0) by 2050 (reaching 9.4% [7.6-11.3] of the global economy and $ 21.3 trillion [19.8-23.1] in purchasing-power parity-adjusted dollars), but at a lower growth rate of 1.84% (1.68-2.02) annually, and with continuing disparities in spending between countries. In 2050, we estimate that 0.6% (0.6-0.7) of health spending will occur in currently low-income countries, despite these countries comprising an estimated 15.7% of the global population by 2050. The ratio between per capita health spending in high-income and low-income countries was 130.2 (122.9-136.9) in 2016 and is projected to remain at similar levels in 2050 (125.9 [113.7-138.1]). The decomposition analysis identified governments' increased prioritisation of the health sector and economic development as the strongest factors associated with increases in government health spending globally. Future government health spending scenarios suggest that, with greater prioritisation of the health sector and increased government spending, health spending per capita could more than double, with greater impacts in countries that currently have the lowest levels of government health spending. Interpretation Financing for global health has increased steadily over the past two decades and is projected to continue increasing in the future, although at a slower pace of growth and with persistent disparities in per-capita health spending between countries. Out-of-pocket spending is projected to remain substantial outside of high-income countries. Many low-income countries are expected to remain dependent on development assistance, although with greater government spending, larger investments in health are feasible. In the absence of sustained new investments in health, increasing efficiency in health spending is essential to meet global health targets.

  • 3.
    Kivimäki, Mika
    et al.
    Department of Epidemiology and Public Health, University College London, London, United Kingdom / Faculty of Medicine, University of Helsinki, Helsinki, Finland.
    Jokela, Markus
    Institute of Behavioral Sciences, University of Helsinki, Helsinki, Finland.
    Nyberg, Solja T.
    Finnish Institute of Occupational Health, Helsinki, Tampere and Turku, Finland.
    Singh-Manoux, Archana
    Department of Epidemiology and Public Health, University College London, London, United Kingdom / Inserm U1018, Centre for Research in Epidemiology and Population Health, Villejuif, France.
    Fransson, Eleonor I.
    Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden / School of Health Sciences, Jönköping University, Jönköping, Sweden / Stress Research Institute, Stockholm University, Stockholm, Sweden.
    Alfredsson, Lars
    Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden / Centre for Occupational and Environmental Medicine, Stockholm County Council, Stockholm, Sweden.
    Bjorner, Jakob B.
    National Research Centre for the Working Environment, Copenhagen, Denmark.
    Borritz, Marianne
    Department of Occupational Medicine, Koege Hospital, Copenhagen, Denmark.
    Burr, Hermann
    Federal Institute for Occupational Safety and Health (BAuA), Berlin, Germany.
    Casini, Annalisa
    School of Public Health, Université libre de Bruxelles (ULB), Brussels, Belgium.
    Clays, Els
    Department of Public Health, Ghent University, Ghent, Belgium.
    De Bacquer, Dirk
    Department of Public Health, Ghent University, Ghent, Belgium.
    Dragano, Nico
    Institute for Medical Sociology, Medical Faculty, University of Düsseldorf, Düsseldorf, Germany.
    Erbel, Raimund
    Department of Cardiology, West-German Heart Center Essen, University Duisburg-Essen, Essen, Germany.
    Geuskens, Goedele A.
    TNO, Hoofddorp, Netherlands.
    Hamer, Mark
    Department of Epidemiology and Public Health, University College London, London, United Kingdom.
    Hooftman, Wendela E.
    TNO, Hoofddorp, Netherlands.
    Houtman, Irene L.
    TNO, Hoofddorp, Netherlands.
    Jöckel, Karl-Heinz
    Institute for Medical Informatics, Biometry, and Epidemiology, Faculty of Medicine, University Duisburg-Essen, Essen, Germany.
    Kittel, France
    School of Public Health, Université libre de Bruxelles (ULB), Brussels, Belgium.
    Knutsson, Anders
    Department of Health Sciences, Mid Sweden University, Sundsvall, Sweden.
    Koskenvuo, Markku
    Department of Public Health, University of Helsinki, Helsinki, Finland.
    Lunau, Thorsten
    Institute for Medical Sociology, Medical Faculty, University of Düsseldorf, Düsseldorf, Germany.
    Madsen, Ida E. H.
    National Research Centre for the Working Environment, Copenhagen, Denmark.
    Nielsen, Martin L.
    Unit of Social Medicine, Frederiksberg University Hospital, Copenhagen, Denmark.
    Nordin, Maria
    Stress Research Institute, Stockholm University, Stockholm, Sweden / Department of Psychology, Umeå University, Umeå, Sweden.
    Oksanen, Tuula
    Finnish Institute of Occupational Health, Helsinki, Tampere and Turku, Finland.
    Pejtersen, Jan H.
    The Danish National Centre for Social Research, Copenhagen, Denmark.
    Pentti, Jaana
    Finnish Institute of Occupational Health, Helsinki, Tampere and Turku, Finland.
    Rugulies, Reiner
    National Research Centre for the Working Environment, Copenhagen, Denmark / Department of Public Health and Department of Psychology, University of Copenhagen, Copenhagen, Denmark.
    Salo, Paula
    Finnish Institute of Occupational Health, Helsinki, Tampere and Turku, Finland / Department of Psychology, University of Turku, Turku, Finland.
    Shipley, Martin J.
    Department of Epidemiology and Public Health, University College London, London, United Kingdom.
    Siegrist, Johannes
    Institute for Medical Sociology, Medical Faculty, University of Düsseldorf, Düsseldorf, Germany.
    Steptoe, Andrew
    Department of Epidemiology and Public Health, University College London, London, United Kingdom.
    Suominen, Sakari B.
    University of Skövde, School of Health and Education. University of Skövde, Health and Education. Department of Public Health, University of Turku, Turku, Finland / Folkhälsan Research Center, Helsinki, Finland.
    Theorell, Töres
    Stress Research Institute, Stockholm University, Stockholm, Sweden.
    Vahtera, Jussi
    Finnish Institute of Occupational Health, Helsinki, Tampere and Turku, Finland / Department of Public Health, University of Turku, Turku, Finland / Turku University Hospital, Turku, Finland.
    Westerholm, Peter J. M.
    Occupational and Environmental Medicine, Uppsala University, Uppsala, Sweden.
    Westerlund, Hugo
    Stress Research Institute, Stockholm University, Stockholm, Sweden.
    O'Reilly, Dermot
    Centre for Public Health, Queen's University Belfast, Belfast, United Kingdom.
    Kumari, Meena
    Department of Epidemiology and Public Health, University College London, London, United Kingdom / Institute for Social and Economic Research, University of Essex, Colchester, United Kingdom.
    Batty, G. David
    Department of Epidemiology and Public Health, University College London, London, United Kingdom / Centre for Cognitive Ageing and Cognitive Epidemiology and Alzheimer Scotland Dementia Research Centre, University of Edinburgh, Edinburgh, United Kingdom.
    Ferrie, Jane E.
    Department of Epidemiology and Public Health, University College London, London, United Kingdom / School of Community and Social Medicine, University of Bristol, Bristol, United Kingdom.
    Virtanen, Marianna
    Finnish Institute of Occupational Health, Helsinki, Tampere and Turku, Finland.
    Long working hours and risk of coronary heart disease and stroke: a systematic review and meta-analysis of published and unpublished data for 603 838 individuals2015In: The Lancet, ISSN 0140-6736, E-ISSN 1474-547X, Vol. 386, no 10005, p. 1739-1746Article in journal (Refereed)
    Abstract [en]

    Background Long working hours might increase the risk of cardiovascular disease, but prospective evidence is scarce, imprecise, and mostly limited to coronary heart disease. We aimed to assess long working hours as a risk factor for incident coronary heart disease and stroke. Methods We identified published studies through a systematic review of PubMed and Embase from inception to Aug 20, 2014. We obtained unpublished data for 20 cohort studies from the Individual-Participant-Data Meta-analysis in Working Populations (IPD-Work) Consortium and open-access data archives. We used cumulative random-effects meta-analysis to combine effect estimates from published and unpublished data. Findings We included 25 studies from 24 cohorts in Europe, the USA, and Australia. The meta-analysis of coronary heart disease comprised data for 603 838 men and women who were free from coronary heart disease at baseline; the meta-analysis of stroke comprised data for 528 908 men and women who were free from stroke at baseline. Follow-up for coronary heart disease was 5.1 million person-years (mean 8.5 years), in which 4768 events were recorded, and for stroke was 3.8 million person-years (mean 7.2 years), in which 1722 events were recorded. In cumulative meta-analysis adjusted for age, sex, and socioeconomic status, compared with standard hours (35-40 h per week), working long hours (>= 55 h per week) was associated with an increase in risk of incident coronary heart disease (relative risk [RR] 1.13, 95% CI 1.02-1.26; p=0.02) and incident stroke (1.33, 1.11-1.61; p=0.002). The excess risk of stroke remained unchanged in analyses that addressed reverse causation, multivariable adjustments for other risk factors, and different methods of stroke ascertainment (range of RR estimates 1.30-1.42). We recorded a dose-response association for stroke, with RR estimates of 1.10 (95% CI 0.94-1.28; p=0.24) for 41-48 working hours, 1.27 (1.03-1.56; p=0.03) for 49-54 working hours, and 1.33 (1.11-1.61; p=0.002) for 55 working hours or more per week compared with standard working hours (p(trend)<0.0001). Interpretation Employees who work long hours have a higher risk of stroke than those working standard hours; the association with coronary heart disease is weaker. These findings suggest that more attention should be paid to the management of vascular risk factors in individuals who work long hours. 

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