METHODS: This is a cross-sectional study of seatbelt compliance of patients aged over 18 years, attending the emergency departments of five public hospitals in Singapore after road collisions from 2011-2014. Seatbelt data was obtained from paramedic and patient history.
RESULTS: There were 4,576 patients studied. Most were Singapore citizens (83.4 %) or permanent residents (2.4 %), with the largest non-resident groups from Malaysia, India, and China. Overall seatbelt compliance was 82.1 %. On univariate analysis, seatbelt compliance was higher in older patients (OR 1.02, 95 % CI 1.001-1.021, p risk factors for non-compliance. On multivariable analysis, older age (OR 1.01, 95 % CI 1.001-1.014, p = 0.03) was associated with compliance, while non-residents from China (OR 0.43, 95 % CI 0.18-0.99, p = 0.05), seat position (front passenger compared to driver, OR 0.64, 95 % CI 0.48-0.85, p = 0.002; rear passenger compared to driver, OR 0.067, 95 % CI 0.05-0.09, p
METHODS: An interdisciplinary and international Working Group was assembled. Existing literature and current measurement initiatives were reviewed. Serial guided discussions and validation surveys provided consumer input. A series of nine teleconferences, incorporating a modified Delphi process, were held to reach consensus on the proposed Standard Set.
RESULTS: The Working Group selected 24 outcome measures to evaluate care during pregnancy and up to 6 months postpartum. These include clinical outcomes such as maternal and neonatal mortality and morbidity, stillbirth, preterm birth, birth injury and patient-reported outcome measures (PROMs) that assess health-related quality of life (HRQoL), mental health, mother-infant bonding, confidence and success with breastfeeding, incontinence, and satisfaction with care and birth experience. To support analysis of these outcome measures, pertinent baseline characteristics and risk factor metrics were also defined.
CONCLUSIONS: We propose a set of outcome measures for evaluating the care that women and infants receive during pregnancy and the postpartum period. While validation and refinement via pilot implementation projects are needed, we view this as an important initial step towards value-based improvements in care.
METHODS: A cross-sectional study among 15,639 Malaysian adult males aged 18 years and above was conducted using proportional to size stratified sampling method. The socio-demographic variables examined were level of education, occupation, marital status, residential area, age group and monthly household income.
RESULTS: The prevalence of smoking among adult males in Malaysia was 46.5% (95% CI: 45.5-47.4%), which was 3% lower than a decade ago. Mean age of smoking initiation was 18.3 years, and mean number of cigarettes smoked daily was 11.3. Prevalence of smoking was highest among the Malays (55.9%) and those aged 21-30 years (59.3%). Smoking was significantly associated with level of education (no education OR 2.09 95% CI (1.67-2.60), primary school OR 1.95, 95% CI (1.65-2.30), secondary school OR 1.88, 95% CI (1.63-2.11), with tertiary education as the reference group). Marital status (divorce OR 1.67, 95% CI (1.22-2.28), with married as the reference group), ethnicity (Malay, OR 2.29, 95% CI ( 1.98-2.66; Chinese OR 1.23 95% CI (1.05-1.91), Other Bumis OR 1.75, 95% CI (1.46-2.10, others OR 1.48 95% CI (1.15-1.91), with Indian as the reference group), age group (18-20 years OR 2.36, 95% CI (1.90-2.94); 20-29 years OR 3.31 , 95% CI 2.82-3.89; 31-40 years OR 2.85 , 95% CI ( 2.47-3.28); 41-50 years OR 1.93, 95% CI (1.69-2.20) ; 51-60 years OR 1.32, 95% CI (1.15-1.51), with 60 year-old and above as the reference group) and residential area (rural OR 1.12 , 95% CI ( 1.03-1.22)) urban as reference.
CONCLUSION: The prevalence of smoking among Malaysian males remained high in spite of several population interventions over the past decade. Tobacco will likely remain a primary cause of premature mortality and morbidity in Malaysia. Continuous and more comprehensive anti-smoking policy measures are needed in order to further prevent the increasing prevalence of smoking among Malaysian men, particularly those who are younger, of Malay ethnicity, less educated, reside in rural residential area and with lower socio-economic status.
METHODS: We used Mendelian randomization approaches to evaluate the association of height and BMI on breast cancer risk, using data from the Consortium of Investigators of Modifiers of BRCA1/2 with 14 676 BRCA1 and 7912 BRCA2 mutation carriers, including 11 451 cases of breast cancer. We created a height genetic score using 586 height-associated variants and a BMI genetic score using 93 BMI-associated variants. We examined both observed and genetically determined height and BMI with breast cancer risk using weighted Cox models. All statistical tests were two-sided.
RESULTS: Observed height was positively associated with breast cancer risk (HR = 1.09 per 10 cm increase, 95% confidence interval [CI] = 1.0 to 1.17; P = 1.17). Height genetic score was positively associated with breast cancer, although this was not statistically significant (per 10 cm increase in genetically predicted height, HR = 1.04, 95% CI = 0.93 to 1.17; P = .47). Observed BMI was inversely associated with breast cancer risk (per 5 kg/m2 increase, HR = 0.94, 95% CI = 0.90 to 0.98; P = .007). BMI genetic score was also inversely associated with breast cancer risk (per 5 kg/m2 increase in genetically predicted BMI, HR = 0.87, 95% CI = 0.76 to 0.98; P = .02). BMI was primarily associated with premenopausal breast cancer.
CONCLUSION: Height is associated with overall breast cancer and BMI is associated with premenopausal breast cancer in BRCA1/2 mutation carriers. Incorporating height and BMI, particularly genetic score, into risk assessment may improve cancer management.
METHODS: We used the Global Burden of Diseases, Injuries, and Risk Factors Study 2021 (GBD 2021) analytical framework to compute age-specific tuberculosis mortality and incidence estimates for 204 countries and territories (1990-2021 inclusive). We quantified tuberculosis mortality among individuals without HIV co-infection using 22 603 site-years of vital registration data, 1718 site-years of verbal autopsy data, 825 site-years of sample-based vital registration data, 680 site-years of mortality surveillance data, and 9 site-years of minimally invasive tissue sample (MITS) diagnoses data as inputs into the Cause of Death Ensemble modelling platform. Age-specific HIV and tuberculosis deaths were established with a population attributable fraction approach. We analysed all available population-based data sources, including prevalence surveys, annual case notifications, tuberculin surveys, and tuberculosis mortality, in DisMod-MR 2.1 to produce internally consistent age-specific estimates of tuberculosis incidence, prevalence, and mortality. We also estimated age-specific tuberculosis mortality without HIV co-infection that is attributable to the independent and combined effects of three risk factors (smoking, alcohol use, and diabetes). As a secondary analysis, we examined the potential impact of the COVID-19 pandemic on tuberculosis mortality without HIV co-infection by comparing expected tuberculosis deaths, modelled with trends in tuberculosis deaths from 2015 to 2019 in vital registration data, with observed tuberculosis deaths in 2020 and 2021 for countries with available cause-specific mortality data.
FINDINGS: We estimated 9·40 million (95% uncertainty interval [UI] 8·36 to 10·5) tuberculosis incident cases and 1·35 million (1·23 to 1·52) deaths due to tuberculosis in 2021. At the global level, the all-age tuberculosis incidence rate declined by 6·26% (5·27 to 7·25) between 2015 and 2020 (the WHO End TB strategy evaluation period). 15 of 204 countries achieved a 20% decrease in all-age tuberculosis incidence between 2015 and 2020, eight of which were in western sub-Saharan Africa. When stratified by age, global tuberculosis incidence rates decreased by 16·5% (14·8 to 18·4) in children younger than 5 years, 16·2% (14·2 to 17·9) in those aged 5-14 years, 6·29% (5·05 to 7·70) in those aged 15-49 years, 5·72% (4·02 to 7·39) in those aged 50-69 years, and 8·48% (6·74 to 10·4) in those aged 70 years and older, from 2015 to 2020. Global tuberculosis deaths decreased by 11·9% (5·77 to 17·0) from 2015 to 2020. 17 countries attained a 35% reduction in deaths due to tuberculosis between 2015 and 2020, most of which were in eastern Europe (six countries) and central Europe (four countries). There was variable progress by age: a 35·3% (26·7 to 41·7) decrease in tuberculosis deaths in children younger than 5 years, a 29·5% (25·5 to 34·1) decrease in those aged 5-14 years, a 15·2% (10·0 to 20·2) decrease in those aged 15-49 years, a 7·97% (0·472 to 14·1) decrease in those aged 50-69 years, and a 3·29% (-5·56 to 9·07) decrease in those aged 70 years and older. Removing the combined effects of the three attributable risk factors would have reduced the number of all-age tuberculosis deaths from 1·39 million (1·28 to 1·54) to 1·00 million (0·703 to 1·23) in 2020, representing a 36·5% (21·5 to 54·8) reduction in tuberculosis deaths compared to those observed in 2015. 41 countries were included in our analysis of the impact of the COVID-19 pandemic on tuberculosis deaths without HIV co-infection in 2020, and 20 countries were included in the analysis for 2021. In 2020, 50 900 (95% CI 49 700 to 52 400) deaths were expected across all ages, compared to an observed 45 500 deaths, corresponding to 5340 (4070 to 6920) fewer deaths; in 2021, 39 600 (38 300 to 41 100) deaths were expected across all ages compared to an observed 39 000 deaths, corresponding to 657 (-713 to 2180) fewer deaths.
INTERPRETATION: Despite accelerated progress in reducing the global burden of tuberculosis in the past decade, the world did not attain the first interim milestones of the WHO End TB Strategy in 2020. The pace of decline has been unequal with respect to age, with older adults (ie, those aged >50 years) having the slowest progress. As countries refine their national tuberculosis programmes and recalibrate for achieving the 2035 targets, they could consider learning from the strategies of countries that achieved the 2020 milestones, as well as consider targeted interventions to improve outcomes in older age groups.
FUNDING: Bill & Melinda Gates Foundation.
METHODS: The NCVD involves more than 15 Ministry of Health (MOH) hospitals nationwide, universities and the National Heart Institute and enrolls patients presenting with ACS [ST-elevation myocardial infarction (STEMI), non-ST elevation myocardial infarction (NSTEMI) and unstable angina (UA)]. We analyzed ethnic differences across socio-demographic characteristics, hospital medications and invasive therapeutic procedures, treatment of STEMI and in-hospital clinical outcomes.
RESULTS: We enrolled 13,591 patients. The distribution of the NCVD population was as follows: 49.0% Malays, 22.5% Chinese, 23.1% Indians and 5.3% Others (representing other indigenous groups and non-Malaysian nationals). The mean age (SD) of ACS patients at presentation was 59.1 (12.0) years. More than 70% were males. A higher proportion of patients within each ethnic group had more than two coronary risk factors. Malays had higher body mass index (BMI). Chinese had highest rate of hypertension and hyperlipidemia. Indians had higher rate of diabetes mellitus (DM) and family history of premature CAD. Overall, more patients had STEMI than NSTEMI or UA among all ethnic groups. The use of aspirin was more than 94% among all ethnic groups. Utilization rates for elective and emergency percutaneous coronary intervention (PCI) and coronary artery bypass graft (CABG) were low among all ethnic groups. In STEMI, fibrinolysis (streptokinase) appeared to be the dominant treatment options (>70%) for all ethnic groups. In-hospital mortality rates for STEMI across ethnicity ranges from 8.1% to 10.1% (p = 0.35). Among NSTEMI/UA patients, the rate of in-hospital mortality ranges from 3.7% to 6.5% and Malays recorded the highest in-hospital mortality rate compared to other ethnic groups (p = 0.000). In binary multiple logistic regression analysis, differences across ethnicity in the age and sex-adjusted ORs for in-hospital mortality among STEMI patients was not significant; for NSTEMI/UA patients, Chinese [OR 0.71 (95% CI 0.55, 0.91)] and Indians [OR 0.57 (95% CI 0.43, 0.76)] showed significantly lower risk of in-hospital mortality compared to Malays (reference group).
CONCLUSIONS: Risk factor profiles and ACS stratum were significantly different across ethnicity. Despite disparities in risk factors, clinical presentation, medical treatment and invasive management, ethnic differences in the risk of in-hospital mortality was not significant among STEMI patients. However, Chinese and Indians showed significantly lower risk of in-hospital mortality compared to Malays among NSTEMI and UA patients.
METHODS: The population in this study consisted of all new smear positive PTB patients who were diagnosed at the chest clinic of Penang General Hospital between March 2010 and February 2011. During the study period, a standardized data collection form was used to obtain socio-demographic, clinical and treatment related data of the patients from their medical charts and TB notification forms (Tuberculosis Information System; TBIS). These data sources were reviewed at the time of the diagnosis of the patients and then at the subsequent follow-up visits until their final treatment outcomes were available. The treatment outcomes of the patients were reported in line with six outcome categories recommended by World Health Organization. Multiple logistic regression analysis was used to find the independent risk factors for unsuccessful treatment outcome and longer treatment duration. Data were analyzed using the PASW (Predictive Analysis SoftWare, version 19.0. Armonk, NY: IBM Corp).
RESULTS: Among the 336 PTB patients (236 male and 100 female) notified during the study period, the treatment success rate was 67.26% (n = 226). Out of 110 patients in unsuccessful outcome category, 30 defaulted from the treatment, 59 died and 21 were transferred to other health care facilities. The mean duration of TB treatment was 8.19 (SD 1.65) months. In multiple logistic regression analysis, risk factors for unsuccessful treatment outcome were foreign nationality, male gender and being illiterate. Similarly, risk factors for mortality due to TB included high-grade sputum and presence of lung cavities at the start of treatment, being alcoholic and elderly. Likewise, concurrent diabetes, presence of lung cavities at the start of the treatment and being a smoker were the significant predictors of longer treatment duration.
CONCLUSION: Our findings indicated that the treatment success rate among the new smear positive PTB patients was less than the success target set by World Health Organization. The proportion of patients in the successful outcome category may be increased by closely monitoring the treatment progress of the patients with aforementioned high risk characteristics. Similarly, more aggressive follow-up of the treatment defaulters and transferred out patients could also improve the TB treatment success rate.
METHODS: The national nephrology societies of the region; responded to the questionnaire; based on latest registries, acceptable community-based studies and society perceptions. The countries in the region were classified into Group 1 (High|higher-middle-income) and Group 2 (lower|lowermiddle income). Student t-test, Mann-Whitney U test and Fisher's exact test were used for comparison.
RESULTS: Fifteen countries provided the data. The average incidence of ESKD was estimated at 226.7 per million population (pmp), (Group 1 vs. Group 2, 305.8 vs. 167.8 pmp) and average prevalence at 940.8 pmp (Group 1 vs. Group 2, 1306 vs. 321 pmp). Group 1 countries had a higher incidence and prevalence of ESKD. Diabetes, hypertension and chronic glomerulonephritis were most common causes. The mean age in Group 2 was lower by a decade (Group 1 vs. Group 2-59.45 vs 47.7 years).
CONCLUSION: Haemodialysis was the most common kidney replacement therapy in both groups and conservative management of ESKD was the second commonest available treatment option within Group 2. The disease burden was expected to grow >20% in 50% of Group 1 countries and 78% of Group 2 countries along with the parallel growth in haemodialysis and peritoneal dialysis.
METHODS: A cohort of 686 women (376 Chinese, 186 Malay, and 124 Indian) with a singleton pregnancy attended a clinic visit at 26-28 weeks of gestation as part of the Growing Up in Singapore Towards healthy Outcomes mother-offspring cohort study. Self-reported sleep quality and sleep duration were assessed using the Pittsburgh Sleep Quality Index (PSQI). GDM was diagnosed based on a 75-g oral glucose tolerance test administered after an overnight fast (1999 WHO criteria). Multiple logistic regression was used to model separately the associations of poor sleep quality (PSQI score > 5) and short nocturnal sleep duration (<6 h) with GDM, adjusting for age, ethnicity, maternal education, body mass index, previous history of GDM, and anxiety (State-Trait Anxiety Inventory score).
RESULTS: In the cohort 296 women (43.1%) had poor sleep quality and 77 women (11.2%) were categorized as short sleepers; 131 women (19.1%) were diagnosed with GDM. Poor sleep quality and short nocturnal sleep duration were independently associated with increased risk of GDM (poor sleep, adjusted odds ratio [OR] = 1.75, 95% confidence interval [CI] 1.11 to 2.76; short sleep, adjusted OR = 1.96, 95% CI 1.05 to 3.66).
CONCLUSIONS: During pregnancy, Asian women with poor sleep quality or short nocturnal sleep duration exhibited abnormal glucose regulation. Treating sleep problems and improving sleep behavior in pregnancy could potentially reduce the risk and burden of GDM.
METHODS: Data from the web-based CSR were collected for cataract surgery performed from 2008 to 2013. Data was contributed by 36 Malaysian Ministry of Health public hospitals. Information on patient's age, ethnicity, cause of cataract, ocular and systemic comorbidity, type of cataract surgery performed, local anaesthesia and surgeon's status was noted. Combined procedures and type of hospital admission were recorded. PCR risk indicators were identified using logistic regression analysis to produce adjusted OR for the variables of interest.
RESULTS: A total of 150 213 cataract operations were registered with an overall PCR rate of 3.2%. Risk indicators for PCR from multiple logistic regression were advancing age, male gender (95% CI 1.04 to 1.17; OR 1.11), pseudoexfoliation (95% CI 1.02 to 1.82; OR 1.36), phacomorphic lens (95% CI 1.25 to 3.06; OR 1.96), diabetes mellitus (95% CI 1.13 to 1.29; OR 1.20) and renal failure (95% CI 1.09 to 1.55; OR 1.30). Surgical PCR risk factors were combined vitreoretinal surgery (95% CI 2.29 to 3.63; OR 2.88) and less experienced cataract surgeons. Extracapsular cataract extraction (95% CI 0.76 to 0.91; OR 0.83) and kinetic anaesthesia were associated with lower PCR rates.
CONCLUSIONS: This study was agreed with other studies for the risk factors of PCR with the exception of local anaesthesia given and type of cataract surgery. Better identification of high-risk patients for PCR decreases intraoperative complications and improves cataract surgical outcomes.
METHODS: Data from the Malaysian Elders Longitudinal Research subset of the Transforming Cognitive Frailty into Later-Life Self-Sufficiency cohort study was utilized. From 2013-2015, participants aged ≥55 years were selected from the electoral rolls of three parliamentary constituencies in Klang Valley. Risk categorisation was performed using baseline data. Falls prediction values were determined using follow-up data from wave 2 (2015-2016), wave 3 (2019) and wave 4 (2020-2022).
RESULTS: Of 1,548 individuals recruited, 737 were interviewed at wave 2, 858 at wave 3, and 742 at wave 4. Falls were reported by 13.4 %, 29.8 % and 42.9 % of the low-, intermediate- and high-risk groups at wave 2, 19.4 %, 25.5 % and 32.8 % at wave 3, and 25.8 %, 27.7 % and 27.0 % at wave 4, respectively. At wave 2, the algorithm generated a sensitivity of 51.3 % (95 %CI, 43.1-59.2) and specificity of 80.1 % (95 %CI, 76.6-83.2). At wave 3, sensitivity was 29.4 % (95 %CI, 23.1-36.6) and specificity was 81.6 % (95 %CI, 78.5-84.5). At wave 4, sensitivity was 26.0 % (95 %CI, 20.2-32.8) and specificity was 78.4 % (95 %CI, 74.7-81.8).
CONCLUSION: The algorithm has high specificity and low sensitivity in predicting falls, with decreasing sensitivity over time. Therefore, regular reassessments should be made to identify individuals at risk of falling.
METHODS AND RESULTS: We analyzed a cohort of children <5 years of age undergoing VSD closure at 60 global centers participating in the International Quality Improvement Collaborative for Congenital Heart Disease, 2015 to 2020. We calculated adjusted odds ratios (ORs) for in-hospital death and major infection and adjusted coefficients for duration of intensive care unit stay for 4 measures of malnutrition: severe wasting (weight-for-height Z score,