METHODS: Using the GBD 2019 methodology, international mortality data were collected from vital registration systems, verbal autopsies, and population-based cancer registry inputs modelled with mortality-to-incidence ratios (MIRs). Incidence was computed with mortality estimates and corresponding MIRs. Prevalence estimates were calculated using modelled survival and multiplied by disability weights to obtain years lived with disability (YLDs). Years of life lost (YLLs) were calculated as age-specific cancer deaths multiplied by the standard life expectancy at the age of death. The main outcome was DALYs (the sum of YLLs and YLDs). Estimates were presented globally and by Socio-demographic Index (SDI) quintiles (countries ranked and divided into five equal SDI groups), and all estimates were presented with corresponding 95% uncertainty intervals (UIs). For this analysis, we used the age range of 15-39 years to define adolescents and young adults.
FINDINGS: There were 1·19 million (95% UI 1·11-1·28) incident cancer cases and 396 000 (370 000-425 000) deaths due to cancer among people aged 15-39 years worldwide in 2019. The highest age-standardised incidence rates occurred in high SDI (59·6 [54·5-65·7] per 100 000 person-years) and high-middle SDI countries (53·2 [48·8-57·9] per 100 000 person-years), while the highest age-standardised mortality rates were in low-middle SDI (14·2 [12·9-15·6] per 100 000 person-years) and middle SDI (13·6 [12·6-14·8] per 100 000 person-years) countries. In 2019, adolescent and young adult cancers contributed 23·5 million (21·9-25·2) DALYs to the global burden of disease, of which 2·7% (1·9-3·6) came from YLDs and 97·3% (96·4-98·1) from YLLs. Cancer was the fourth leading cause of death and tenth leading cause of DALYs in adolescents and young adults globally.
INTERPRETATION: Adolescent and young adult cancers contributed substantially to the overall adolescent and young adult disease burden globally in 2019. These results provide new insights into the distribution and magnitude of the adolescent and young adult cancer burden around the world. With notable differences observed across SDI settings, these estimates can inform global and country-level cancer control efforts.
FUNDING: Bill & Melinda Gates Foundation, American Lebanese Syrian Associated Charities, St Baldrick's Foundation, and the National Cancer Institute.
METHODS: Estimates of diabetes prevalence and burden were computed in 204 countries and territories, across 25 age groups, for males and females separately and combined; these estimates comprised lost years of healthy life, measured in disability-adjusted life-years (DALYs; defined as the sum of years of life lost [YLLs] and years lived with disability [YLDs]). We used the Cause of Death Ensemble model (CODEm) approach to estimate deaths due to diabetes, incorporating 25 666 location-years of data from vital registration and verbal autopsy reports in separate total (including both type 1 and type 2 diabetes) and type-specific models. Other forms of diabetes, including gestational and monogenic diabetes, were not explicitly modelled. Total and type 1 diabetes prevalence was estimated by use of a Bayesian meta-regression modelling tool, DisMod-MR 2.1, to analyse 1527 location-years of data from the scientific literature, survey microdata, and insurance claims; type 2 diabetes estimates were computed by subtracting type 1 diabetes from total estimates. Mortality and prevalence estimates, along with standard life expectancy and disability weights, were used to calculate YLLs, YLDs, and DALYs. When appropriate, we extrapolated estimates to a hypothetical population with a standardised age structure to allow comparison in populations with different age structures. We used the comparative risk assessment framework to estimate the risk-attributable type 2 diabetes burden for 16 risk factors falling under risk categories including environmental and occupational factors, tobacco use, high alcohol use, high body-mass index (BMI), dietary factors, and low physical activity. Using a regression framework, we forecast type 1 and type 2 diabetes prevalence through 2050 with Socio-demographic Index (SDI) and high BMI as predictors, respectively.
FINDINGS: In 2021, there were 529 million (95% uncertainty interval [UI] 500-564) people living with diabetes worldwide, and the global age-standardised total diabetes prevalence was 6·1% (5·8-6·5). At the super-region level, the highest age-standardised rates were observed in north Africa and the Middle East (9·3% [8·7-9·9]) and, at the regional level, in Oceania (12·3% [11·5-13·0]). Nationally, Qatar had the world's highest age-specific prevalence of diabetes, at 76·1% (73·1-79·5) in individuals aged 75-79 years. Total diabetes prevalence-especially among older adults-primarily reflects type 2 diabetes, which in 2021 accounted for 96·0% (95·1-96·8) of diabetes cases and 95·4% (94·9-95·9) of diabetes DALYs worldwide. In 2021, 52·2% (25·5-71·8) of global type 2 diabetes DALYs were attributable to high BMI. The contribution of high BMI to type 2 diabetes DALYs rose by 24·3% (18·5-30·4) worldwide between 1990 and 2021. By 2050, more than 1·31 billion (1·22-1·39) people are projected to have diabetes, with expected age-standardised total diabetes prevalence rates greater than 10% in two super-regions: 16·8% (16·1-17·6) in north Africa and the Middle East and 11·3% (10·8-11·9) in Latin America and Caribbean. By 2050, 89 (43·6%) of 204 countries and territories will have an age-standardised rate greater than 10%.
INTERPRETATION: Diabetes remains a substantial public health issue. Type 2 diabetes, which makes up the bulk of diabetes cases, is largely preventable and, in some cases, potentially reversible if identified and managed early in the disease course. However, all evidence indicates that diabetes prevalence is increasing worldwide, primarily due to a rise in obesity caused by multiple factors. Preventing and controlling type 2 diabetes remains an ongoing challenge. It is essential to better understand disparities in risk factor profiles and diabetes burden across populations, to inform strategies to successfully control diabetes risk factors within the context of multiple and complex drivers.
FUNDING: Bill & Melinda Gates Foundation.
METHODS: This study included all deaths that occurred in Malaysia in 2018. The YLL was derived by adding the number of deaths from 113 specific diseases and multiplying it by the remaining life expectancy for that age and sex group. Data on life expectancy and mortality were collected from the Department of Statistics Malaysia.
RESULTS: In 2018, there were 3.5 million YLL in Malaysia. Group II (NCDs) caused 72.2% of total YLL. Ischaemic heart disease was the leading cause of premature mortality among Malaysians (17.7%), followed by lower respiratory infections (9.7%), road traffic injuries (8.7%), cerebrovascular disease (stroke) (8.0%), and diabetes mellitus (3.9%).
CONCLUSIONS: NCDs are a significant health concern in Malaysia and are the primary contributor to the overall burden of disease. These results are important in guiding the national health systems on how to design and implement effective interventions for NCDs, as well as how to prioritise and allocate healthcare resources. Key strategies to consider include implementing health promotion campaigns, adopting integrated care models, and implementing policy and regulatory measures. These approaches aim to enhance health outcomes and the managements of NCDs in Malaysia.
METHODS: The current study estimated the annual spending and lifetime spending of smokers in the target Asia-Pacific countries (Hong Kong, Malaysia, Thailand, South Korea, Singapore, and Australia) on purchasing cigarettes, as well as predicted the revenue that could be generated if smokers spent the money on investment instead of buying cigarettes. Smokers' spending on cigarettes and the potential revenue generated from investment were estimated based on the selling prices of cigarettes, Standards & Poor's 500 Index, and life expectancies of smokers. Data were extracted from reports released by the World Health Organization or government authorities.
RESULTS: The annual expenses (in US$) on purchasing one pack of cigarettes, in decreasing order, were: Australia ($5628.30), Singapore ($3777.75), Hong Kong ($2799.55), Malaysia ($1529.35), South Korea ($1467.30), and Thailand ($657.00). The lifetime spending on purchasing one pack of cigarettes each day were: Australia ($308993.67), Singapore ($207398.48), Hong Kong ($151735.61 for male and $166853.18 for female), South Korea ($80261.31), Malaysia ($72338.26), and Thailand ($31207.50).
CONCLUSIONS: The cost burden of smoking is high from a smoker's perspective. Smokers should recognize the high economic burden and quit smoking to enjoy better health and wealth.
METHODS: Period abridged life tables were constructed to derive the life expectancy of the Singapore population from 1965 to 2009 using data from the Department of Statistics and the Registry of Births and Deaths, Singapore.
RESULTS: All 3 of Singapore's main ethnic groups, and both genders, experienced an increase in life expectancy at birth and at 65 years from 1965 to 2009, though at substantially different rates. Although there has been a convergence in life expectancy between Indians and Chinese, the (substantial) gap between Malays and the other two ethnic groups has remained. Females continued to have a higher life expectancy at birth and at 65 years than males throughout this period, with no evidence of convergence.
CONCLUSIONS: Ethnic and gender differences in life expectancy persist in Singapore despite its rapid economic development. Targeted chronic disease prevention measures and health promotion activities focusing on people of Malay ethnicity and the male community may be needed to remedy this inequality.