We measure well-being across 175 countries using a novel indicator: Pollution-and Education-Adjusted Healthy Lifetime Income (PEHLI). This indicator goes beyond the mere consideration of per capita gross domestic product (GDP) and can be interpreted as the income of the average person in an economy during the years that they spend in good health, adjusted for education and pollution in the given country. Our study addresses how incorporating health, education, and environmental quality reshapes crosscountry wellbeing assessments. Our analysis reveals significant differences in country rankings when compared to GDP-based measures. PEHLI ranks pollution-intensive countries lower and cleaner countries higher. Countries with better education levels in terms of attainment and opportunities also tend to rank higher under PEHLI. Across countries, incorporating health and education widens inequality, while incorporating pollution narrows it slightly; higherlatitude countries generally enjoy greater well-being. By adopting PEHLI, policymakers would gain a comprehensive framework for their decision-making processes that incorporates the well-being dimensions of health, longevity, education, and pollution into a single income-based measure.

Introduction Vision impairment (VI), multimorbidity and disabilities are common among older populations. Although the prevalence of VI and its associations are frequently reported, the incidence and risk factors are not well documented in India. The Longitudinal Eye Health, Ageing and Disability Study (LEADS) aims to: (a) determine the prevalence, causes, risk factors and impact of VI; (b) explore the associations between VI and sociodemographic risk factors, systemic health conditions (multimorbidity), physical performance, hearing, depression, social connectedness and cognitive function; and (c) evaluate the impact of eye interventions such as cataract surgery and refractive correction (for distance and near) on these conditions. Additionally, (d) to assess the annual incidence of and risk factors for VI among older people in the community.Methods and analysis Individuals aged ≥60 years are selected from seven districts across three regions in the states of Andhra Pradesh and Telangana in Southern India. A two-stage cluster random sampling method is used to enrol participants. Trained field investigators administered a set of questionnaires, including personal and sociodemographic information, ocular and systemic history, cognition, depression, hearing, falls and fear of falling. The Short Physical Performance Battery is used to assess physical performance. A comprehensive eye examination is conducted in makeshift clinics set up nearby. The examination included unaided and aided visual acuity for distance and near, using minimum logarithm of resolution charts, manual and auto refraction, slit lamp biomicroscopy and anterior and posterior segment imaging using a non-mydriatic fundus camera. The individuals will be examined at baseline (wave I) and then at a follow-up visit planned after 18–24 months (wave II).

Type 1 diabetes imposes a significant burden through morbidity, mortality, and high health care costs while also generating additional health, economic, and social costs, ranging from mental health conditions to risk of financial hardship to social stigma. Many of these outcomes may also spill over to families and caregivers. The economic literature increasingly recognizes the importance of including broader societal impacts in economic evaluations, including some guidelines for assessment of health interventions. However, in practice, societal impacts are incorporated in a limited way in assessments of type 1 diabetes therapies, most commonly through certain productivity-related measures, with limited consideration of broader impacts. In this article, we review the wider impacts of type 1 diabetes and examine how recent evaluations of novel technologies apply different perspectives. We find that economic assessments inconsistently incorporate broader societal impacts, such as psychosocial effects, informal caregiving, and long-term economic consequences. Consideration of a broader range of societal impacts may provide a more comprehensive evidence base for evaluating type 1 diabetes treatments and technologies, including in decisions related to their development, distribution, and reimbursement.

INTRODUCTION We characterized modifiable risk and protective factors for cognitive decline in India.METHODS Using the first nationally representative population-based longitudinal sample of N = 6168 older adults in India, we evaluated associations of risk factors (demographic characteristics, self-reported and objective health characteristics, health behaviors, and sensory function) for late-life cognitive decline with up to 6.4 years of follow-up (range: 2.8 to 6.4 years).RESULTS The mean rate of general cognitive decline was -0.029 SD per year and was progressively steeper with age. Most risk factors, particularly demographic and cardiovascular characteristics, were associated with steeper cognitive decline in expected directions: Associations of history of high cholesterol or heart attack on rate of cognitive decline, for example, were comparable to being 8 to 10 years older.DISCUSSION Most risk factors were associated with change in expected directions, highlighting the potential generalizability to India of previously identified risk factors for dementia.

Background:Lower respiratory infections (LRI) are a major cause of mortality in China, yet there is a striking lack of nationally representative studies and comprehensive evaluations of their long-term economic impact. This study aimed to quantify the long-term economic burden of LRI across China's 31 provinces and regions, and to assess the spatial distribution. Methods:We used an improved health-augmented macroeconomic model (HMM) to estimate the economic burden of LRI in mainland China from 2020 to 2040. The model captures the burden via two channels: (1) the impact of LRI-related mortality and morbidity on labor supply, and (2) the effect of treatment costs on physical capital accumulation. Data were sourced from the China Provincial Burden of Disease Study 2023, the Global Burden of Antimicrobial Resistance Study, and other publicly available literature. Findings:From 2020 to 2040, LRI are projected to impose a cumulative economic loss of CNY 363 billion (95% UI: 216-710). Marked regional disparities were observed: Guangdong incurred the highest absolute burden (CNY 35.6 billion); Guizhou reported the largest economic losses relative to 61‰ GDP; and per capita losses were greatest in Southwest China. Although East and Southwest China bore the largest overall losses, the disease burden was disproportionately concentrated in Southwest China, which accounted for 33.6% of DALYs but only 23.2% of the total economic loss. Middle-income regions experienced the highest total losses (CNY 174 billion), while per capita losses were most pronounced in low-income areas (CNY 426). Notably, the share of treatment-related costs increased with decreasing income levels, ranging from 21% in Northwest China to just 2% in East China. Interpretation:The economic burden of LRI in China is substantial and regionally inequitable, underscoring the substantial economic returns to targeted LRI prevention and control-particularly in under-resourced regions. Far from being a fiscal liability, such investments offer meaningful long-term economic returns and are essential to advancing health and economic equity nationwide. Funding:The study was supported by Horizon Europe (HORIZON-MSCA-2021-SE-01; project number 101086139-PoPMeD-SuSDeV), and Ministry of Science and Technology of the People's Republic of China (project number 2023ZD0506000).

Gross domestic product remains the dominant metric of progress, but new measures such as healthy lifetime income offer policymakers a clearer and more relevant view of well-being.

OBJECTIVES:This study characterises the use of type 1 diabetes (T1D) guidelines and protocols in Australian T1D clinics working with paediatric patients, and determines if management practices align with T1D-specific guidelines. METHODS:T1D clinic service leaders responded to an online survey on guidelines (e.g. glycated haemoglobin target levels, time in range targets, and technology uptake and management) and protocols (e.g. surgery) used. Responses were compared with T1D guidelines or protocols. RESULTS:A representative healthcare professional from 32 T1D services (16 metropolitan; 16 regional) from all Australian states and territories completed the survey. Most services (90%) reported glycated haemoglobin targets of <7% and a time in range of ≥70% (95%). Twenty-one services (72%) developed shared care plans, giving access to schools (91%), patients/families (81%) and general practitioners (71%), and with referrals to other health professionals (52%). Most (79%) clinics provided patients with International Society for Pediatric and Adolescent Diabetes/National Institute of Clinical Excellence guideline-aligned responses on managing out-of-range blood glucose level readings from T1D-related technologies. Regional clinics (68%) provided guideline-aligned responses less frequently than metropolitan clinics (91%). Services used combinations of state-based, national and locally developed protocols for patient management. CONCLUSIONS:This is the first Australia-wide study examining the protocols and guidelines followed for paediatric T1D management by T1D clinics. Most services reported management practices aligned with T1D guidelines. Greater sharing of care plans when referring patients to other services could improve care continuity. Increasing regional clinics' delivery of guideline-aligned information to patients on using T1D technology could support patient self-management. This survey provides a benchmark of diabetes guideline awareness and protocol usage in Australia.

BACKGROUND:Asthma is a major chronic respiratory disease with substantial health and economic consequences worldwide; however, there is little evidence for the long-term macroeconomic effects of asthma across countries. We aimed to estimate the global economic burden attributable to asthma from 2025 to 2050 across 154 countries and territories. METHODS:We estimated the long-term economic burden of asthma using a health-augmented macroeconomic model covering 154 countries and territories from 2025 to 2050. Projected labour losses were captured through reductions in the workforce due to premature death and reduced labour force participation due to disability. Physical capital accumulation was affected by asthma-related medical spending, which reduces savings and investment, measured as asthma-attributable health expenditure. In the model, this spending reduced disposable income and savings, thereby lowering investment and slowing capital accumulation over time FINDINGS: Between 2025 and 2050, our model predicted that asthma would incur costs of approximately US$863 billion (95% uncertainty interval [UI] 615-1396; 2024 US$), corresponding to an annual gross domestic product (GDP) decline of 0·036% (0·026-0·058). The projected economic burden differed markedly across the 154 countries. The USA bore the largest burden (US$471 billion [371-655]), followed by the UK (US$45 billion [28-84]) and China (US$44 billion [27-81]). Across income groups, high-income countries accounted for the greatest absolute losses (US$712 billion [525-1105]) and highest proportional GDP losses (0·054% [0·039-0·083]), whereas low-income countries incurred absolute losses of US$5 billion (2-11). In low-income and middle-income countries (LMICs), labour-related losses accounted for a larger share of total costs and declines in disease burden were slower. INTERPRETATION:Our findings suggest that asthma imposes a substantial and uneven macroeconomic burden across countries, with differences by income level and region. Productivity reductions dominate in LMICs, whereas physical capital-related effects are more important in high-income settings. Improving asthma prevention and control could yield economic gain. FUNDING:Noncommunicable Chronic Diseases-National Science and Technology Major Project; Non-profit Central Research Institute Fund of Chinese Academy of Medical Sciences; European Commission Horizon Europe.

Global life expectancy has risen since 1973 from 58 to over 73 years, while the share of people aged 65 years and older has doubled to 10% and is projected to reach 21% by 2073. This shift is linked to an epidemiological transition from infectious to chronic disease. Here, using Global Burden of Disease data, we reframe this transition by statistically grouping diseases on the basis of their impact over the life cycle, yielding four clusters: infant, early-adult, later-adult and aging-related. We show aging-related diseases are the largest part of the current global disease burden and the greatest lifetime burden for a newborn, even in low-income countries. Aging-related diseases possess two distinctive properties: a tight link between mortality and morbidity, and increasing returns, whereby reductions in their prevalence makes further gains even more attractive. The implications of this recasting of the epidemiological transition for health systems and aging research are discussed.

BACKGROUND:Frailty is a common syndrome among older adults, associated with multiple adverse health outcomes. Work harmonizing frailty measurement across 25 countries and regions and different socioeconomic environments is limited. A harmonized definition is needed to assess frailty across settings to inform comparative studies of health and healthcare. METHODS:Data on adults aged 50+ from 8 health and retirement surveys were analyzed: CHARLS (China), ELSA (England and Wales), ELSI (Brazil), HRS (USA), LASI (India), MHAS (Mexico), SHARE (Europe and Israel), and TILDA (Ireland). We produced a 30-item deficit accumulation frailty index (FI) from shared variables. We assessed within-survey distributions and, in 4 surveys with available data (HRS, MHAS, SHARE, and TILDA), association with mortality. RESULTS:A total of 184 715 participants were included; mean (SD) age was 65.1 (9.80) and 55.1% were female. Mean (SD) FI was 0.196 (0.133), and 39.2% were frail. Frailty distributions were right-skewed, with higher median FI for females than males (p < .0001). Kaplan-Meier analysis showed lower survival with greater frailty in studies with survival data. Hazard ratios (95% CI, p value) for severe frailty (FI ≥0.4) compared with non-frailty (FI <0.1) after adjustment for age, gender, and smoking status were 5.50 (4.89-6.19), 4.36 (3.67-5.18), 8.81 (6.44-12.05), and 3.97 (2.99-5.27) for HRS, MHAS, SHARE, and TILDA, respectively, all with p < .0001. CONCLUSIONS:This is a harmonized FI developed using data from multiple settings, with strong associations with mortality. This is a useful tool to better understand aging in a global context.

Social impact bonds (SIBs) are an innovative financing mechanism for public goods. In a SIB, an investor provides capital to a service provider for a social intervention. The investor receives a return based on the outcome of the intervention relative to a predetermined benchmark. We describe the basic structure of a SIB and provide some descriptive statistics for these financial instruments. We then consider a formal model of SIBs and examine their ability to finance positive net present value projects that traditional debt finance cannot. We find that SIBs expand the set of implementable projects if governments are pessimistic (relative to the private sector) about the probability an intervention would succeed or if the government is particularly averse to paying costs associated with a project that does not generate offsetting benefits. As both these features are present in various public programs, we conclude that SIBs are a real innovation in public finance and should be considered for projects when traditional debt finance has been rejected.

Introduction Emerging infectious diseases (EIDs) cause significant health and economic burdens in the USA and globally. Existing methods and analyses fall short of what is required to prioritise diseases for health technology research and development (R&D), including for medical countermeasure (MCM) development within rapid response frameworks by the Center for Biomedical Advanced Research and Development Authority, part of the Administration for Strategic Preparedness and Response within the U.S. Department of Health and Human Services.Methods We developed a method for quantifying and ranking health and economic disease burdens (‘full burdens’) and applied it to 15 high-priority EIDs for 223 countries and territories, including the USA and US territories, historically from 2000 to 2022 and prospectively from 2025 to 2034. Health burdens consisted of disability-adjusted life-year losses, converted into monetary values using the value of a statistical life-year. Economic burdens consisted of direct and indirect costs during the acute stage of illness for hospitalised cases. We computed unweighted and weighted burden measures, the latter controlling for global disparities in ability-to-pay to avoid EID burdens. We projected future disease burdens using Monte Carlo simulation.Results Pandemics caused the largest historical and projected unweighted and weighted full burdens in the USA and globally. Among non-pandemics, across unweighted and weighted burdens, dengue and cholera imposed the largest historical and projected full burdens globally; West Nile Virus imposed the largest historical and projected full burdens in the USA, and dengue imposed the largest historical full burdens in the US territories. Weighted full burdens exceeded five times the unweighted ones. Regionally, the Americas and Africa faced the largest per capita weighted burdens while the Western Pacific region faced the smallest.Conclusion R&D priority-setting, including MCM development, depends on multiple criteria, including disease burdens. Our full burden quantification methods and results, along with other such criteria, can inform optimal priority-setting.

INTRODUCTION:Type 1 diabetes (T1D) is a lifelong condition typically diagnosed in childhood. Clinical practice guidelines recommend comprehensive multidisciplinary team (MDT)-based care led by paediatric endocrinologists. However, experiences and opinions of health professionals about the implementation of T1D MDTs in Australia are currently unknown. AIMS:To describe health service teams caring for children and youth with T1D in Australia and to identify opportunities for service improvements from providers' perspectives. METHODS:Mixed-methods study co-designed with clinicians and consumers, including a survey of clinic leaders and semi-structured interviews. Survey questions covered modes of care delivery, team composition and outreach. Interview transcripts were thematically analysed using a hybrid inductive/deductive approach. RESULTS:Thirty-two T1D services leaders completed the survey; 16 were from major cities and 16 were from regional/rural areas across all Australian states and territories. The services provided care for ~51% of all <19-year-olds living with T1D. T1D services were multidisciplinary and commonly included dieticians (n = 29, 94%), nurse diabetes educators (n = 22, 71%) and general paediatricians (n = 21, 68%). Eight (29%) services had a dedicated psychologist. A quarter (25%) of regional/rural services had a paediatric endocrinologist compared with 100% of major city services (χ2 = 18.355; p < 0.001). All services offered telehealth consultations. Interviews revealed that services placed high value on having established cohesive teams skilled in T1D. Service leaders had concerns regarding workforce capacity and shortages, limited access to psychologists, inequitable access to insulin pumps and limited links with general practitioners. CONCLUSION:This mixed-methods study is the first Australia-wide exploration of T1D models of care that describes care provision from the clinicians' perspectives. A need exists to address current gaps to achieve the recommended MDT models of care for T1D. Understanding existing models of care will be essential to determine the future impacts of changes in policies, therapies and demands on paediatric T1D services.

Parkinson's disease (PD) is a growing global health concern. The goal of this research is to estimate the financial impact of PD in 31 provinces in the mainland of China from 2020 to 2040. The study gathered several datasets including China Statistical Yearbook, China Labor Statistical Yearbook, China Health Statistical Yearbook, and the Global Burden of Disease study 2023. We leveraged a health-augmented macroeconomic model to calculate the provincial economic toll of PD, taking into consideration the direct and indirect effects of PD-related deaths and illness on labor supply, and variations in educational background and work experience by sex and age. PD is expected to cause a substantial economic burden from 2020 to 2040, amounting to 473 billion Chinese yuan (CNY), which is 0.017% of the gross domestic product. The burden is highest in Jiangsu, Guangdong, and Shandong Provinces, whereas the burden proportion in the provincial gross domestic product is highest in Heilongjiang at 0.029%, and the economic burden per capita is highest in Shanghai at 868 CNY. A strong positive correlation between disability-adjusted life years and economic burden is found (Pearson correlation coefficient = 0.871, P-value < 0.001). These findings demonstrate the need for more specific regional health policies in line with the long-term care, diagnosis, and treatment for PD across China.

Depression is a major contributor to the global burden of diseases with substantial socioeconomic consequences. Here, to estimate the economic effects of depression, we developed a macroeconomic model using data from the World Bank and Global Burden of Disease Study 2021. The model estimated the impact of depression on labor force participation, educational attainment and work experience, adjusted for age and sex. The projected global economic burden from 2025 to 2050 is estimated at US$12 trillion (2024 US dollars), representing 0.460% of annual global gross domestic product. When suicide-related deaths attributable to depression are accounted for, based on an assumed 60% attribution rate representing the upper bound of estimates in the literature, the overall economic burden increases to US$14 trillion. The highest economic burdens are observed in the United States and China. Relative to regional gross domestic product, the impact is greatest in North America. Reduced labor force participation and productivity were identified as the predominant drivers of this cost. The macroeconomic burden of depression is substantial and inequitably distributed globally. These findings underscore the importance of addressing depression as a public health and economic concern. Reducing the health burden of depression could yield economic returns by supporting productivity and capital accumulation.

BACKGROUND:India is a country of 1·4 billion people that contributes to much of the global diabetes burden. Updated evidence on the state of the diabetes epidemic among middle-aged and older adults is imperative given that the risk of diabetes increases with age and that clinical and public health interventions can prevent diabetes complications. We aimed to estimate the prevalence, awareness, treatment, and control of diabetes in a nationally representative and state-representative sample of Indians aged 45 years and older. METHODS:We conducted a cross-sectional, nationally representative survey of adults in India aged 45 years and older and their spouses from 2017 to 2019. Our sample included 57 810 individuals and their spouses from 36 states and union territories, reflecting a representative sample of India as a nation and of each state and union territory. Participants had available data on glycated haemoglobin (HbA1c) measurement and non-missing information on diabetes diagnosis, household economic status, and BMI. Spouses younger than 45 years were excluded from the analysis. Our primary outcomes were diabetes prevalence and health service indicators recommended by WHO. Diabetes prevalence was defined as individuals self-reporting a previous diabetes diagnosis or having HbA1c of 6·5% or higher. Available data did not allow the identification of type 1 versus type 2 diabetes. Diabetes health service indicators were based on four core metrics recommended by WHO: (1) proportion diagnosed out of all individuals with diabetes (awareness) and, out of individuals with diagnosed diabetes, (2) proportion with glycaemic control (measured HbA1c <7·0%), (3) proportion with blood pressure control (measured blood pressure <140/90 mm Hg), and (4) proportion self-reporting use of lipid-lowering medications. Outcomes were assessed in the national sample; by state and union territory; and across individual-level characteristics of age, sex, rural versus urban area of residence, education, economic status, and BMI. FINDINGS:Diabetes prevalence among adults aged 45 years and older in India was 19·8% (95% CI 19·4-20·2), which amounted to 50·4 million people (49·4-51·4). Prevalence among men and women was similar (men, 19·6% [95% CI 19·0-20·2] and women, 20·1% [19·5-20·6]). Urban diabetes prevalence (30·0% [95% CI 29·1-30·8]) was approximately twice as high as rural prevalence (15·0% [14·6-15·5]). States with higher levels of economic development tended to have greater age-standardised prevalence (standardised regression coefficient for gross domestic product per capita 0·65 [95% CI 0·45-0·85]). Overall, 60·1% (59·0-61·2) of individuals were aware of their diabetes. Of individuals with diagnosed diabetes, 45·7% (44·3-47·2) achieved glycaemic control, 58·9% (57·5-60·4) achieved blood pressure control, and 6·4% (5·8-7·2) were taking a lipid-lowering medication. INTERPRETATION:Our findings emphasise the urgent need to scale up policies to better prevent, detect, manage, and control diabetes among middle-aged and older adults in India. FUNDING:US National Institute on Aging; Ministry of Health and Family Welfare, Government of India.

What will likely be the effect of the emergence of ChatGPT and other forms of artificial intelligence (AI) on the skill premium? To address this question, we develop a nested constant elasticity of substitution production function that distinguishes between industrial robots and AI. Industrial robots predominantly substitute for low-skill workers, whereas AI mainly helps to perform the tasks of high-skill workers. We show that AI reduces the skill premium as long as it is more substitutable for high-skill workers than low-skill workers are for high-skill workers.

This paper investigates the impact of early diagnostic confirmation on the COVID-19 pandemic in a developing country. Using a dataset of the first laboratory-confirmed cases across Chinese cities and an instrumental variable strategy to address endogeneity, we show that reducing the time to publicly confirm the first case in a city by one day led to reductions of 9.4 % in COVID-19 prevalence and 12.7 % in mortality over the subsequent six months. The impact was more pronounced in cities farther from the COVID-19 epicenter, with lower migration exposure, more responsive public health systems, and lower health system capacity utilization. Enhanced social distancing and a less overstressed health system likely drove these effects. Our findings underscore the importance of allocating resources to improve diagnostic technologies; strengthening public health emergency response systems to test for, diagnose, and announce cases of infection; and acting swiftly when facing a potential outbreak.

Analysis of population aging is typically framed in terms of chronological age. However, chronological age itself is not necessarily deeply informative about the aging process. This article reviews literature and conducts empirical analyses aimed at investigating whether chronological age is a reliable proxy for physiological functioning when used in models of economic behavior and outcomes. We show that chronological age is an unreliable proxy for physiological functioning due to appreciable differences in how aging unfolds across people, health domains, and over time. We further demonstrate that chronological age either fails to predict economic variables when used in lieu of physiological functioning or predicts additional effects on economic behavior and outcomes that are largely unrelated to physiological aging. Continued reliance on chronological age as a proxy for physiological functioning might impede the ability of societies to fully harness the benefits of increasing longevity.

IntroductionIn low- and middle-income countries, self-reported data on chronic cardiometabolic conditions such as high blood pressure and diabetes are commonly used in large-scale epidemiologic studies because implementing objective measures is challenging in these contexts. However, existing evidence suggests that the sensitivity of such measures may be low, and performance may differ by factors such as age, education, or income. We sought to confirm these prior findings and assess bias due to the use of self-reported data in hypothetical epidemiologic studies considering high blood pressure and diabetes as exposures, outcomes, and confounders.MethodsWe used data from the Longitudinal Aging Study in India (analytic N = 55,392) to assess the performance of self-reported data on high blood pressure and diabetes compared with objective measures, overall and stratified by basic demographic factors. We then compared regression coefficients from models considering self-reported and objective high blood pressure and diabetes as exposures, outcomes, and confounders. In all models, we examined whether the mode of data collection (self-report or objective) for other key variables in the model affected results.ResultsThe overall sensitivity of self-reported high blood pressure and diabetes was 0.514 and 0.570, respectively; specificity for the two conditions was 0.922 and 0.984. Sensitivity of both conditions increased with age, and was higher among women, those in urban settings, and those with higher educational attainment. Across almost all models considering high blood pressure and diabetes as either exposures or outcomes anti-conservative bias was observed when using self-reported vs. objective measures, regardless of the mode of data collection for other key variables. When high blood pressure and diabetes were considered as confounders, differences between using self-report and objective measures were minimal.DiscussionAnti-conservative bias due to the use of self-reported measures of chronic cardiometabolic conditions in surveys conducted in low- and middle-income contexts may be common. Future studies may seek to quantify the magnitude of anticipated bias in existing data resources and use quantitative bias analysis to formally estimate the potential implications of misclassification.