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: 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.
OBJECTIVE: To identify the studies on premature cardiovascular disease (CVD) mortality and synthesise their findings on YLL based on the regional area, main CVD types, sex, and study time.
METHOD: We conducted a systematic review of published CVD mortality studies that reported YLL as an indicator for premature mortality measurement. A literature search for eligible studies was conducted in five electronic databases: PubMed, Scopus, Web of Science (WoS), and the Cochrane Central Register of Controlled Trials (CENTRAL). The Newcastle-Ottawa Scale was used to assess the quality of the included studies. The synthesis of YLL was grouped into years of potential life lost (YPLL) and standard expected years of life lost (SEYLL) using descriptive analysis. These subgroups were further divided into WHO (World Health Organization) regions, study time, CVD type, and sex to reduce the effect of heterogeneity between studies.
RESULTS: Forty studies met the inclusion criteria for this review. Of these, 17 studies reported premature CVD mortality using YPLL, and the remaining 23 studies calculated SEYLL. The selected studies represent all WHO regions except for the Eastern Mediterranean. The overall median YPLL and SEYLL rates per 100,000 population were 594.2 and 1357.0, respectively. The YPLL rate and SEYLL rate demonstrated low levels in high-income countries, including Switzerland, Belgium, Spain, Slovenia, the USA, and South Korea, and a high rate in middle-income countries (including Brazil, India, South Africa, and Serbia). Over the past three decades (1990-2022), there has been a slight increase in the YPLL rate and the SEYLL rate for overall CVD and ischemic heart disease but a slight decrease in the SEYLL rate for cerebrovascular disease. The SEYLL rate for overall CVD demonstrated a notable increase in the Western Pacific region, while the European region has experienced a decline and the American region has nearly reached a plateau. In regard to sex, the male showed a higher median YPLL rate and median SEYLL rate than the female, where the rate in males substantially increased after three decades.
CONCLUSION: Estimates from both the YPLL and SEYLL indicators indicate that premature CVD mortality continues to be a major burden for middle-income countries. The pattern of the YLL rate does not appear to have lessened over the past three decades, particularly for men. It is vitally necessary to develop and execute strategies and activities to lessen this mortality gap.
SYSTEMATIC REVIEW REGISTRATION: PROSPERO CRD42021288415.
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: 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: This study was based on data obtained from 3716 Malaysians aged ≥60 years as part of the National Health and Morbidity Survey (NHMS) 2018. QoL was measured using the Control, Autonomy, Self-realization and Pleasure 19-item (CASP-19) questionnaire. UI was measured using the Questionnaire Urinary Incontinence Diagnosis (QUID) score. Association between UI and QoL were examined using linear regression analysis, after controlling socio-demographic variables and comorbidities.
RESULTS: Overall, the prevalence of UI was 5.2%. By subtypes, the prevalence of stress UI and urge UI were both 2.0%, while that of mixed UI was 1.3%. The UI group rated their lives more negatively in all four domains of QoL compared with non-UI group. Those who were incontinent had lower standardized scores on control and autonomy domains of CASP-19 as well as total score. Results from linear regression analysis indicated that UI had a significantly negative impact on control and autonomy domains of QoL after controlling for socio-demographic factors and comorbidities.
CONCLUSION: UI contributes to a significant reduction on QoL of older persons. Healthcare providers need to be sensitive in evaluating and discussing UI, particularly with their older patients. Geriatr Gerontol Int 2020; 20: 38-42.
METHODS: We reviewed results for injuries from the GBD 2017 study. GBD 2017 measured injury-specific mortality and years of life lost (YLLs) using the Cause of Death Ensemble model. To measure non-fatal injuries, GBD 2017 modelled injury-specific incidence and converted this to prevalence and years lived with disability (YLDs). YLLs and YLDs were summed to calculate disability-adjusted life years (DALYs).
FINDINGS: In 1990, there were 4 260 493 (4 085 700 to 4 396 138) injury deaths, which increased to 4 484 722 (4 332 010 to 4 585 554) deaths in 2017, while age-standardised mortality decreased from 1079 (1073 to 1086) to 738 (730 to 745) per 100 000. In 1990, there were 354 064 302 (95% uncertainty interval: 338 174 876 to 371 610 802) new cases of injury globally, which increased to 520 710 288 (493 430 247 to 547 988 635) new cases in 2017. During this time, age-standardised incidence decreased non-significantly from 6824 (6534 to 7147) to 6763 (6412 to 7118) per 100 000. Between 1990 and 2017, age-standardised DALYs decreased from 4947 (4655 to 5233) per 100 000 to 3267 (3058 to 3505).
INTERPRETATION: Injuries are an important cause of health loss globally, though mortality has declined between 1990 and 2017. Future research in injury burden should focus on prevention in high-burden populations, improving data collection and ensuring access to medical care.
METHODS: In this study, we report and discuss the methods used in GBD 2017 for injury morbidity and mortality burden estimation. In summary, these methods included estimating cause-specific mortality for every cause of injury, and then estimating incidence for every cause of injury. Non-fatal disability for each cause is then calculated based on the probabilities of suffering from different types of bodily injury experienced.
RESULTS: GBD 2017 produced morbidity and mortality estimates for 38 causes of injury. Estimates were produced in terms of incidence, prevalence, years lived with disability, cause-specific mortality, years of life lost and disability-adjusted life-years for a 28-year period for 22 age groups, 195 countries and both sexes.
CONCLUSIONS: GBD 2017 demonstrated a complex and sophisticated series of analytical steps using the largest known database of morbidity and mortality data on injuries. GBD 2017 results should be used to help inform injury prevention policy making and resource allocation. We also identify important avenues for improving injury burden estimation in the future.
METHODS: Injury mortality was estimated using the GBD mortality database, corrections for garbage coding and CODEm-the cause of death ensemble modelling tool. Morbidity estimation was based on surveys and inpatient and outpatient data sets for 30 cause-of-injury with 47 nature-of-injury categories each. The Socio-demographic Index (SDI) is a composite indicator that includes lagged income per capita, average educational attainment over age 15 years and total fertility rate.
RESULTS: For many causes of injury, age-standardised DALY rates declined with increasing SDI, although road injury, interpersonal violence and self-harm did not follow this pattern. Particularly for self-harm opposing patterns were observed in regions with similar SDI levels. For road injuries, this effect was less pronounced.
CONCLUSIONS: The overall global pattern is that of declining injury burden with increasing SDI. However, not all injuries follow this pattern, which suggests multiple underlying mechanisms influencing injury DALYs. There is a need for a detailed understanding of these patterns to help to inform national and global efforts to address injury-related health outcomes across the development spectrum.
Methods: Cross-sectional data from 62 developing countries were used to run several multivariate linear regressions. R2 was used to compare the powers of MPI with income-poverties (income poverty gaps [IPG] at 1.9 and 3.1 USD) in explaining LE.
Results: Adjusting for controls, both MPI (β =-0.245, P<0.001) and IPG at 3.1 USD (β=-0.135, P=0.044) significantly correlates with LE, but not IPG at 1.9 USD (β=-0.147, P=0.135). MPI explains 12.1% of the variation in LE compared to only 3.2% explained by IPG at 3.1 USD. The effect of MPI on LE is higher on female (β=-0.210, P<0.001) than male (β=-0.177, P<0.001). The relative influence of the deprivation indictors on LE ranks as follows (most to least): Asset ownership, drinking water, cooking fuel, flooring, child school attendance, years of schooling, nutrition, mortality, improved sanitation, and electricity.
Conclusion: Interventions to reduce poverty and improve LE should be guided by MPI, not income poverty indices. Such policies should be female-oriented and prioritized based on the relative influence of the various poverty deprivation indicators on LE.
Methods: This observational study employs secondary data from various official sources of 12 states and one federal territory in Malaysia (2002-2014). Panel data of 78 observations (13 cross-sections at six points in time) were used in multivariate, fixed-effect, regressions to estimate the effects of socioeconomic variables on life expectancy at birth for male, female and both-gender.
Results: Poverty and income significantly determine female, male, and total life expectancies. Unemployment significantly determines female and total life expectancies, but not male. Income inequality and public spending on health (as a percentage of total health spending) do not significantly determine life expectancy. The coefficients of the multivariate regressions suggest that a 1% reduction in poverty, 1% reduction in unemployment, and around USD 23.20 increase in household monthly income prolong total life expectancy at birth by 17.9, 72.0, and 16.3 d, respectively. The magnitudes of the effects of the socioeconomic variables on life expectancy vary somewhat by gender.
Conclusion: Life expectancy in Malaysia is higher than the world average and higher than that in some developing countries in the region. However, it is far lower than the advanced world. Reducing poverty and unemployment and increasing income are three effective channels to enhance longevity.
Methods: Two hundred fifty-six patients with schizophrenia between the age of 18 and 65 years were randomly recruited. This cross-sectional study utilised the Calgary Depression Scale for Schizophrenia (CDSS), the Positive and Negative Syndrome Scale (PANSS) and the Psychotic Symptom Rating Scale (PSYRATS-AH). Univariate analysis was performed using an independent t-test or chi-square test, followed by binary logistic regression to determine the factors associated with increased suicidal risks.
Results: The socio-demographic factors associated with suicidal ideation included level of education (p=0.039); secondary-level education (OR=5.76, 95% CI:1.49, 22.34, p=0.011) and tertiary-level education (OR=9.30, 95% CI: 1.80, 48.12, p=0.008) posed a greater risk. A history of attempted suicide (OR=2.09, 95% CI: 1.01, 4.36, p=0.049) and the presence of co-morbid physical illnesses (OR=2.07, 95% CI: 1.02, 4.21, p=0.044) were also found to be associated with a suicidal ideation. Other significant factors associated with suicidal thoughts were concurrent depression (OR=9.68, 95% CI: 3.74, 25.05, p<0.001) and a higher PSYRATS score in emotional characteristics of auditory hallucinations (OR=1.13, 95% CI: 1.06, 1.21, p<0.001).
Conclusion: Suicide in schizophrenia appears to be more closely associated with certain socio-demographic factors and affective symptoms. Appropriate screening and treatment addressing these challenges must be emphasized if suicidal thoughts and actions are to be reduced.