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: 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.
METHODS: We analysed data from 264,906 European adults from the EPIC prospective cohort study, aged between 40 and 70 years at the time of recruitment. Flexible parametric survival models were used to model risk of death conditional on risk factors, and survival functions and attributable fractions (AF) for deaths prior to age 70 years were calculated based on the fitted models.
RESULTS: We identified 11,930 deaths which occurred before the age of 70. The AF for premature mortality for smoking was 31 % (95 % confidence interval (CI), 31-32 %) and 14 % (95 % CI, 12-16 %) for poor diet. Important contributions were also observed for overweight and obesity measured by waist-hip ratio (10 %; 95 % CI, 8-12 %) and high blood pressure (9 %; 95 % CI, 7-11 %). AFs for physical inactivity and excessive alcohol intake were 7 % and 4 %, respectively. Collectively, the AF for all six risk factors was 57 % (95 % CI, 55-59 %), being 35 % (95 % CI, 32-37 %) among never smokers and 74 % (95 % CI, 73-75 %) among current smokers.
CONCLUSIONS: While smoking remains the predominant risk factor for premature death in Europe, poor diet, overweight and obesity, hypertension, physical inactivity, and excessive alcohol consumption also contribute substantially. Any attempt to minimise premature deaths will ultimately require all six factors to be addressed.
METHODS: A validated computer simulation model (the IMS CORE Diabetes Model) was used to estimate the long-term projection of costs and clinical outcomes. The model was populated with published characteristics of Thai patients with type 2 diabetes. Baseline risk factors were obtained from Thai cohort studies, while relative risk reduction was derived from a meta-analysis study conducted by the Canadian Agency for Drugs and Technology in Health. Only direct costs were taken into account. Costs of diabetes management and complications were obtained from hospital databases in Thailand. Both costs and outcomes were discounted at 3 % per annum and presented in US dollars in terms of 2014 dollar value. Incremental cost-effectiveness ratio (ICER) was calculated. One-way and probabilistic sensitivity analyses were also performed.
RESULTS: IGlar is associated with a slight gain in quality-adjusted life years (0.488 QALYs), an additional life expectancy (0.677 life years), and an incremental cost of THB119,543 (US$3522.19) compared with NPH insulin. The ICERs were THB244,915/QALY (US$7216.12/QALY) and THB176,525/life-year gained (LYG) (US$5201.09/LYG). The ICER was sensitive to discount rates and IGlar cost. At the acceptable willingness to pay of THB160,000/QALY (US$4714.20/QALY), the probability that IGlar was cost effective was less than 20 %.
CONCLUSIONS: Compared to treatment with NPH insulin, treatment with IGlar in type 2 diabetes patients who had uncontrolled blood glucose with oral anti-diabetic drugs did not represent good value for money at the acceptable threshold in Thailand.