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      Transforming global approaches to chronic disease prevention and management across the lifespan: integrating genomics, behavior change, and digital health solutions

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          Abstract

          Chronic illnesses are a major threat to global population health through the lifespan into older age. Despite world-wide public health goals, there has been a steady increase in chronic and non-communicable diseases (e.g., cancer, cardiovascular and metabolic disorders) and strong growth in mental health disorders. In 2010, 67% of deaths worldwide were due to chronic diseases and this increased to 74% in 2019, with accelerated growth in the COVID-19 era and its aftermath. Aging and wellbeing across the lifespan are positively impacted by the presence of effective prevention and management of chronic illness that can enhance population health. This paper provides a short overview of the journey to this current situation followed by discussion of how we may better address what the World Health Organization has termed the “tsunami of chronic diseases.” In this paper we advocate for the development, validation, and subsequent deployment of integrated: 1. Polygenic and multifactorial risk prediction tools to screen for those at future risk of chronic disease and those with undiagnosed chronic disease. 2. Advanced preventive, behavior change and chronic disease management to maximize population health and wellbeing. 3. Digital health systems to support greater efficiencies in population-scale health prevention and intervention programs. It is argued that each of these actions individually has an emerging evidence base. However, there has been limited research to date concerning the combined population-level health effects of their integration. We outline the conceptual framework within which we are planning and currently conducting studies to investigate the effects of their integration.

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          Global burden of 369 diseases and injuries in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019

          Summary Background In an era of shifting global agendas and expanded emphasis on non-communicable diseases and injuries along with communicable diseases, sound evidence on trends by cause at the national level is essential. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) provides a systematic scientific assessment of published, publicly available, and contributed data on incidence, prevalence, and mortality for a mutually exclusive and collectively exhaustive list of diseases and injuries. Methods GBD estimates incidence, prevalence, mortality, years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life-years (DALYs) due to 369 diseases and injuries, for two sexes, and for 204 countries and territories. Input data were extracted from censuses, household surveys, civil registration and vital statistics, disease registries, health service use, air pollution monitors, satellite imaging, disease notifications, and other sources. Cause-specific death rates and cause fractions were calculated using the Cause of Death Ensemble model and spatiotemporal Gaussian process regression. Cause-specific deaths were adjusted to match the total all-cause deaths calculated as part of the GBD population, fertility, and mortality estimates. Deaths were multiplied by standard life expectancy at each age to calculate YLLs. A Bayesian meta-regression modelling tool, DisMod-MR 2.1, was used to ensure consistency between incidence, prevalence, remission, excess mortality, and cause-specific mortality for most causes. Prevalence estimates were multiplied by disability weights for mutually exclusive sequelae of diseases and injuries to calculate YLDs. We considered results in the context of the Socio-demographic Index (SDI), a composite indicator of income per capita, years of schooling, and fertility rate in females younger than 25 years. Uncertainty intervals (UIs) were generated for every metric using the 25th and 975th ordered 1000 draw values of the posterior distribution. Findings Global health has steadily improved over the past 30 years as measured by age-standardised DALY rates. After taking into account population growth and ageing, the absolute number of DALYs has remained stable. Since 2010, the pace of decline in global age-standardised DALY rates has accelerated in age groups younger than 50 years compared with the 1990–2010 time period, with the greatest annualised rate of decline occurring in the 0–9-year age group. Six infectious diseases were among the top ten causes of DALYs in children younger than 10 years in 2019: lower respiratory infections (ranked second), diarrhoeal diseases (third), malaria (fifth), meningitis (sixth), whooping cough (ninth), and sexually transmitted infections (which, in this age group, is fully accounted for by congenital syphilis; ranked tenth). In adolescents aged 10–24 years, three injury causes were among the top causes of DALYs: road injuries (ranked first), self-harm (third), and interpersonal violence (fifth). Five of the causes that were in the top ten for ages 10–24 years were also in the top ten in the 25–49-year age group: road injuries (ranked first), HIV/AIDS (second), low back pain (fourth), headache disorders (fifth), and depressive disorders (sixth). In 2019, ischaemic heart disease and stroke were the top-ranked causes of DALYs in both the 50–74-year and 75-years-and-older age groups. Since 1990, there has been a marked shift towards a greater proportion of burden due to YLDs from non-communicable diseases and injuries. In 2019, there were 11 countries where non-communicable disease and injury YLDs constituted more than half of all disease burden. Decreases in age-standardised DALY rates have accelerated over the past decade in countries at the lower end of the SDI range, while improvements have started to stagnate or even reverse in countries with higher SDI. Interpretation As disability becomes an increasingly large component of disease burden and a larger component of health expenditure, greater research and development investment is needed to identify new, more effective intervention strategies. With a rapidly ageing global population, the demands on health services to deal with disabling outcomes, which increase with age, will require policy makers to anticipate these changes. The mix of universal and more geographically specific influences on health reinforces the need for regular reporting on population health in detail and by underlying cause to help decision makers to identify success stories of disease control to emulate, as well as opportunities to improve. Funding Bill & Melinda Gates Foundation.
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            Global, regional, and national burden of 12 mental disorders in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019

            (2022)
            Summary Background The mental disorders included in the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 were depressive disorders, anxiety disorders, bipolar disorder, schizophrenia, autism spectrum disorders, conduct disorder, attention-deficit hyperactivity disorder, eating disorders, idiopathic developmental intellectual disability, and a residual category of other mental disorders. We aimed to measure the global, regional, and national prevalence, disability-adjusted life-years (DALYS), years lived with disability (YLDs), and years of life lost (YLLs) for mental disorders from 1990 to 2019. Methods In this study, we assessed prevalence and burden estimates from GBD 2019 for 12 mental disorders, males and females, 23 age groups, 204 countries and territories, between 1990 and 2019. DALYs were estimated as the sum of YLDs and YLLs to premature mortality. We systematically reviewed PsycINFO, Embase, PubMed, and the Global Health Data Exchange to obtain data on prevalence, incidence, remission, duration, severity, and excess mortality for each mental disorder. These data informed a Bayesian meta-regression analysis to estimate prevalence by disorder, age, sex, year, and location. Prevalence was multiplied by corresponding disability weights to estimate YLDs. Cause-specific deaths were compiled from mortality surveillance databases. The Cause of Death Ensemble modelling strategy was used to estimate death rate by age, sex, year, and location. The death rates were multiplied by the years of life expected to be remaining at death based on a normative life expectancy to estimate YLLs. Deaths and YLLs could be calculated only for anorexia nervosa and bulimia nervosa, since these were the only mental disorders identified as underlying causes of death in GBD 2019. Findings Between 1990 and 2019, the global number of DALYs due to mental disorders increased from 80·8 million (95% uncertainty interval [UI] 59·5–105·9) to 125·3 million (93·0–163·2), and the proportion of global DALYs attributed to mental disorders increased from 3·1% (95% UI 2·4–3·9) to 4·9% (3·9–6·1). Age-standardised DALY rates remained largely consistent between 1990 (1581·2 DALYs [1170·9–2061·4] per 100 000 people) and 2019 (1566·2 DALYs [1160·1–2042·8] per 100 000 people). YLDs contributed to most of the mental disorder burden, with 125·3 million YLDs (95% UI 93·0–163·2; 14·6% [12·2–16·8] of global YLDs) in 2019 attributable to mental disorders. Eating disorders accounted for 17 361·5 YLLs (95% UI 15 518·5–21 459·8). Globally, the age-standardised DALY rate for mental disorders was 1426·5 (95% UI 1056·4–1869·5) per 100 000 population among males and 1703·3 (1261·5–2237·8) per 100 000 population among females. Age-standardised DALY rates were highest in Australasia, Tropical Latin America, and high-income North America. Interpretation GBD 2019 showed that mental disorders remained among the top ten leading causes of burden worldwide, with no evidence of global reduction in the burden since 1990. The estimated YLLs for mental disorders were extremely low and do not reflect premature mortality in individuals with mental disorders. Research to establish causal pathways between mental disorders and other fatal health outcomes is recommended so that this may be addressed within the GBD study. To reduce the burden of mental disorders, coordinated delivery of effective prevention and treatment programmes by governments and the global health community is imperative. Funding Bill & Melinda Gates Foundation, Australian National Health and Medical Research Council, Queensland Department of Health, Australia.
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              The global burden of disease attributable to alcohol and drug use in 195 countries and territories, 1990–2016: a systematic analysis for the Global Burden of Disease Study 2016

              Summary Background Alcohol and drug use can have negative consequences on the health, economy, productivity, and social aspects of communities. We aimed to use data from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2016 to calculate global and regional estimates of the prevalence of alcohol, amphetamine, cannabis, cocaine, and opioid dependence, and to estimate global disease burden attributable to alcohol and drug use between 1990 and 2016, and for 195 countries and territories within 21 regions, and within seven super-regions. We also aimed to examine the association between disease burden and Socio-demographic Index (SDI) quintiles. Methods We searched PubMed, EMBASE, and PsycINFO databases for original epidemiological studies on alcohol and drug use published between Jan 1, 1980, and Sept 7, 2016, with out language restrictions, and used DisMod-MR 2.1, a Bayesian meta-regression tool, to estimate population-level prevalence of substance use disorders. We combined these estimates with disability weights to calculate years of life lived with disability (YLDs), years of life lost (YLLs), and disability-adjusted life-years (DALYs) for 1990–2016. We also used a comparative assessment approach to estimate burden attributable to alcohol and drug use as risk factors for other health outcomes. Findings Globally, alcohol use disorders were the most prevalent of all substance use disorders, with 100·4 million estimated cases in 2016 (age-standardised prevalence 1320·8 cases per 100 000 people, 95% uncertainty interval [95% UI] 1181·2–1468·0). The most common drug use disorders were cannabis dependence (22·1 million cases; age-standardised prevalence 289·7 cases per 100 000 people, 95% UI 248·9–339·1) and opioid dependence (26·8 million cases; age-standardised prevalence 353·0 cases per 100 000 people, 309·9–405·9). Globally, in 2016, 99·2 million DALYs (95% UI 88·3–111·2) and 4·2% of all DALYs (3·7–4·6) were attributable to alcohol use, and 31·8 million DALYs (27·4–36·6) and 1·3% of all DALYs (1·2–1·5) were attributable to drug use as a risk factor. The burden of disease attributable to alcohol and drug use varied substantially across geographical locations, and much of this burden was due to the effect of substance use on other health outcomes. Contrasting patterns were observed for the association between total alcohol and drug-attributable burden and SDI: alcohol-attributable burden was highest in countries with a low SDI and middle-high middle SDI, whereas the burden due to drugs increased with higher S DI level. Interpretation Alcohol and drug use are important contributors to global disease burden. Effective interventions should be scaled up to prevent and reduce substance use disease burden. Funding Bill & Melinda Gates Foundation and Australian National Health and Medical Research Council.
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                Author and article information

                Contributors
                Journal
                Front Public Health
                Front Public Health
                Front. Public Health
                Frontiers in Public Health
                Frontiers Media S.A.
                2296-2565
                13 October 2023
                2023
                : 11
                : 1248254
                Affiliations
                [1] 1Vice Chancellor’s Office, Federation University , Ballarat, VIC, Australia
                [2] 2Institute of Health and Wellbeing, Federation University , Ballarat, VIC, Australia
                [3] 3Health Innovation and Transformation Centre (HITC), Federation University , Ballarat, VIC, Australia
                [4] 4Center for Community Health and Aging, Texas A&M University, School of Public Health , College Station, TX, United States
                [5] 5National Problem Gambling Clinic , London, United Kingdom
                [6] 6Department of Psychiatry, University of Cambridge , Cambridge, United Kingdom
                [7] 7Faculty of Brain Sciences, University College London , London, United Kingdom
                [8] 8Department of Psychiatry, Faculty of Medicine, University of Southampton , Southampton, United Kingdom
                [9] 9Southern Gambling Service, and Southern Health NHS Foundation Trust , Southampton, United Kingdom
                Author notes

                Edited by: Kathleen Potempa, University of Michigan, United States

                Reviewed by: Rajvi Jayant Wani, Amgen (Canada), Canada

                *Correspondence: Colette J Browning, c.browning@ 123456federation.edu.au
                Article
                10.3389/fpubh.2023.1248254
                10613497
                37905238
                8931c0f2-da81-4357-bcab-9d40c9e3340c
                Copyright © 2023 Thomas, Browning, Charchar, Klein, Ory, Bowden-Jones and Chamberlain.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 26 June 2023
                : 18 September 2023
                Page count
                Figures: 1, Tables: 0, Equations: 0, References: 75, Pages: 7, Words: 6353
                Categories
                Public Health
                Perspective
                Custom metadata
                Aging and Public Health

                chronic diseases,prevention,genomics,risk prediction,behavior change,digital health,healthy aging

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