DESIGN: Retrospective cohort study.
SETTING: The Malaysian Non-Communicable Disease Surveillance (MyNCDS-1) 2005/2006.
PARTICIPANTS: A total of 2525 adults (1013 men and 1512 women), aged 24-64 years, who participated in the MyNCDS-1 2005/2006.
METHODS: Participants' anthropometric indices, blood pressure, fasting lipid profile and fasting blood glucose levels were evaluated to determine the prevalence of metabolic syndrome by the Harmonized criteria. Participants' mortality status were followed up for 13 years from 2006 to 2018. Mortality data were obtained via record linkage with the Malaysian National Registration Department. The Cox proportional hazards regression model was applied to determine association between metabolic syndrome (MetS) and risk of CVD mortality and all-cause mortality with adjustment for selected sociodemographic and lifestyle behavioural factors.
RESULTS: The overall point prevalence of MetS was 30.6% (95% CI: 28.0 to 33.3). Total follow-up time was 31 668 person-years with 213 deaths (111 (11.3%) in MetS subjects and 102 (6.1%) in non-MetS subjects) from all-causes, and 50 deaths (33 (2.9%) in MetS group and 17 (1.2%) in non-MetS group) from CVD. Metabolic syndrome was associated with a significantly increased hazard of CVD mortality (adjusted HR: 2.18 (95% CI: 1.03 to 4.61), p=0.041) and all-cause mortality (adjusted HR: 1.47 (95% CI: 1.00 to 2.14), p=0.048). These associations remained significant after excluding mortalities in the first 2 years.
CONCLUSIONS: Our study shows that individuals with MetS have a higher hazard of death from all-causes and CVD compared with those without MetS. It is thus imperative to prescribe individuals with MetS, a lifestyle intervention along with pharmacological intervention to improve the individual components of MetS and reduce this risk.
METHOD: In-depth interviews (IDIs) will be conducted with Malaysian healthcare providers and cancer survivors and findings will be analysed thematically. The insights will be used in a subsequent phase to co-design a guideline to maintain the delivery of quality cancer care in Malaysia via a three-round modified Delphi survey with a broad range of cancer stakeholders.
EXPECTED RESULTS: Findings derived from IDIs and existing literature will be included for rating across three rounds by the expert panel. Feedback provided will be refined until consensus on the best practises for cancer care continuity during crises is achieved.
CONCLUSION: The output of the present study is not only expected to ensure the continuity of delivery of high-quality cancer care in Malaysia during the ongoing pandemic but also to be adapted during unforeseen crises in the near future.
POLICY SUMMARY STATEMENT: Collaborative work between policy makers, public health physicians, members of the multidisciplinary oncology team as well as cancer survivors is vital in developing an evidenced- based contingency plan for maintaining access to cancer care.
OBJECTIVES: This study reviewed the scope of diabetes datasets, health information ecosystems, and human resource capacity in four countries to assess whether a diabetes phenotyping algorithm (developed under a companion study) could be successfully applied.
METHODS: The capacity assessment was undertaken with four countries: Trinidad, Malaysia, Kenya, and Rwanda. Diabetes programme staff completed a checklist of available diabetes data variables and then participated in semi-structured interviews about Health Information System (HIS) ecosystem conditions, diabetes programme context, and human resource needs. Descriptive analysis was undertaken.
RESULTS: Only Malaysia collected the full set of the required diabetes data for the diabetes algorithm, although all countries did collect the required diabetes complication data. An HIS ecosystem existed in all settings, with variations in data hosting and sharing. All countries had access to HIS or ICT support, and epidemiologists or biostatisticians to support dataset preparation and algorithm application.
CONCLUSIONS: Malaysia was found to be most ready to apply the phenotyping algorithm. A fundamental impediment in the other settings was the absence of several core diabetes data variables. Additionally, if countries digitise diabetes data collection and centralise diabetes data hosting, this will simplify dataset preparation for algorithm application. These issues reflect common LMIC health systems' weaknesses in relation to diabetes care, and specifically highlight the importance of investment in improving diabetes data, which can guide population-tailored prevention and management approaches.
Methods: This quasi-experimental study will assess community member and community health volunteer knowledge, attitudes, and practices on noncommunicable disease prevention, risk factors, and health-seeking behavior in three geographical areas of Kuala Lumpur, each representing a different ethnicity (Malay, Indian, and Chinese). Assessment will take place before and after a 9-month intervention period, comparing intervention areas with matched control geographies. We plan to engage 2880 community members and 45 community health volunteers across the six geographic areas. A digital health needs assessment will inform modification of digital health tools to support project aims. Intervention co-creation will use a discrete choice experiment to identify community preferences among evidence-based intervention options, building from data collected on community knowledge, attitudes, and practices. Community health volunteers will work with local businesses and other stakeholders to effect change in obesogenic environments and NCD risk. The study has been approved by the Malaysian Ministry of Health Medical Research Ethical Committee.
Discussion: The Better Health Programme Malaysia anticipates a bottom-up approach that relies on community health volunteers collaborating with local businesses to implement activities that address obesogenic environments and improve community knowledge, attitudes, and practices related to NCD risk. The planned co-creation process will determine which interventions will be most locally relevant, feasible, and needed. The effort aims to empower community members and community health volunteers to drive change that improves their own health and wellbeing. The learnings can be useful nationally and sub-nationally in Malaysia, as well as across similar settings that are working with community stakeholders to reduce noncommunicable disease risk.
Trial registration: National Medical Research Register, Malaysia; NMRR-20-1004-54787 (IIR); July 7, 2020.
METHODS: As data on policy indicators were straightforward and fully available, we focused on studying 25 non-policy indicators: 23 GMFs and 2 PMIs. Gathering data availability of the target indicators was conducted among NCD surveillance experts from the six selected countries during May-June 2020. Our research team found information regarding whether the country had no data at all, was using WHO estimates, was providing 'expert judgement' for the data, or had actual data available for each target indicator. We triangulated their answers with several WHO data sources, including the WHO Health Observatory Database and various WHO Global Reports on health behaviours (tobacco, alcohol, diet, and physical activity) and NCDs. We calculated the percentages of the indicators that need improvement by both indicator category and country.
RESULTS: For all six studied countries, the health-service indicators, based on responses to the facility survey, are the most lacking in data availability (100% of this category's indicators), followed by the health-service indicators, based on the population survey responses (57%), the mortality and morbidity indicators (50%), the behavioural risk indicators (30%), and the biological risk indicators (7%). The countries that need to improve their NCD surveillance data availability the most are Cambodia (56% of all indicators) and Lao PDR (56%), followed by Malaysia (36%), Vietnam (36%), Myanmar (32%), and Thailand (28%).
CONCLUSION: Some of the non-policy GMF and PMI indicators lacked data among the six studied countries. To achieve the global NCDs targets, in the long run, the six countries should collect their own data for all indicators and begin to invest in and implement the facility survey and the population survey to track NCDs-related health services improvements once they have implemented the behavioural and biological Health Risks Population Survey in their countries.
METHODS: One million T2D people aged 40-79 registered in the National Diabetes Registry (2009-2018) were linked to death records (censored on 31 December 2019). Standardized absolute mortality rates and standardized mortality ratios (SMRs) were estimated relative to the Malaysian general population, and standardized to the 2019 registry population with respect to sex, age group, and disease duration.
RESULTS: Overall all-cause standardized mortality rates were unchanged in both sexes. Rates increased in males aged 40-49 (annual average percent change [AAPC]: 2.46 % [95 % CI 0.42 %, 4.55 %]) and 50-59 (AAPC: 1.91 % [95 % CI 0.73 %, 3.10 %]), and females aged 40-49 (AAPC: 3.39 % [95 % CI 1.32 %, 5.50 %]). In both sexes, rates increased among those with 1) > 15 years disease duration, 2) prior cardiovascular disease, and 3) Bumiputera (Malay/native) ethnicity. The overall SMR was 1.83 (95 % CI 1.80, 1.86) for males and 1.85 (95 % CI 1.82, 1.89) for females, being higher in younger age groups and showed an increasing trend in those with either > 15 years disease duration or prior cardiovascular disease.
CONCLUSIONS: Mortality trends worsened in certain T2D population in Malaysia.
MATERIAL AND METHODS: This was a five-year retrospective open cohort study using secondary data from the National Diabetes Registry. The study setting was all public health clinics (n = 47) in the state of Negeri Sembilan, Malaysia. Time to treatment intensification was defined as the number of years from the index year until the addition of another oral antidiabetic drug or initiation of insulin. Life table survival analysis based on best-worst case scenarios was used to determine the time to treatment intensification. Discrete-time proportional hazards model was fitted for the factors associated with treatment intensification.
RESULTS: The mean follow-up duration was 2.6 (SD 1.1) years. Of 7,646 patients, the median time to treatment intensification was 1.29 years (15.5 months), 1.58 years (19.0 months) and 2.32 years (27.8 months) under the best-, average- and worst-case scenarios respectively. The proportion of patients with treatment intensification was 45.4% (95% CI: 44.2-46.5), of which 34.6% occurred only after one year. Younger adults, overweight, obesity, use of antiplatelet medications and poorer HbA1c were positively associated with treatment intensification. Patients treated with more oral antidiabetics were less likely to have treatment intensification.
CONCLUSION: Clinical inertia is present in the management of T2D patients in Malaysian public health clinics. We recommend further studies in lower- and middle-income countries to explore its causes so that targeted strategies can be developed to address this issue.
METHODS: A five-year retrospective cohort study was conducted using data from the National Diabetes Registry. Type 2 diabetes patients aged ≥18 years and had ≥2 clinical audits between 2013 and 2017 were included in the analysis. The first audit information formed the baseline characteristics, and the last audit information was used for comparison. Individualized A1C, blood pressure, and LDL-cholesterol goals were adapted from Malaysian Clinical Practice Guidelines on Type 2 Diabetes Management 2020, American Diabetes Association 2020, and European Association for the Study of Diabetes 2019.
RESULTS: Of the 18 341 patients, 55.8% were female and 64.9% Malay ethnicity. The baseline mean age was 59.3 ± 10.6 years. During an average of 2.5 person-years of follow-up, the mean body mass index dropped by 0.16 kg/m2 to 27.9 kg/m2 , A1C increased by 0.16% to 8.0%, systolic blood pressure increased by 1.4 mm Hg to 136.2 mm Hg, diastolic blood pressure decreased by 1.0 mm Hg to 77.3 mm Hg and LDL-cholesterol reduced by 0.12 mmol/L to 2.79 mmol/L, P
Methods: This study combined the use of secondary data and a qualitative multicase study approach applying observations in 10 randomly selected Ministry of Health (MOH) health clinics in Kuala Lumpur and Selangor and semistructured interviews of the family medicine specialists from the same clinics.
Results: Although there are specific MOH guidelines for diabetes care, some clinics had introduced innovations for diabetes care such as the novel 'personalized care', 'one-stop-centre' and utilization of patients' waiting time for health education. Analysis showed that there was room for improvement in terms of task shifting to free precious time of staff with specialized functions, streamlining appointments for various examinations, increasing continuity of consultations with same doctors, and monitoring of performance.
Conclusion: We contend that there is a potential for increased effectiveness and efficiency of primary diabetes care in Malaysia without increasing the resources - a potential that may be tapped into by systematic learning from ongoing innovation.