METHODS: This cross-sectional study was conducted from August to December 2020. Stratified sampling was employed to recruit 2983 low-income adults from households in the bottom 40% of the economic spectrum (B40) at six public, low-cost housing flats in the Federal Territory of Kuala Lumpur, Malaysia. Face-to-face interviews were conducted using a structured questionnaire to understand dietary practices, perceptions of healthy food availability and affordability, and factors affecting food purchasing decisions.
RESULTS: A staggering 89.5% of B40 adults were found to not consume adequate daily amounts of fruits and vegetables. In addition, 68.1% reported consuming sugar-sweetened beverages at least once per week, including commercially packed ready-to-drink beverages, sugar-added self-prepared drinks, and premixed drinks. Intake was statistically significantly higher among men (71.7%), Malays (70.3%), and Indians (69.9%). Bread and other commercially baked goods were the most common processed foods, and 52.9% of respondents consumed it at least once per week. Majorities reported that healthy foods were moderately available and priced. The top three reported factors affecting food purchase choices were price (79.4%), availability (75%), and taste (73%).
CONCLUSIONS: Adults in low-cost housing communities have unhealthy dietary patterns with low intake of fruits and vegetables and high intake of ultra-processed foods and calorie-dense local foods, with variations across gender and ethnicity. The study highlighted the need for educating low-income families on diet-disease relationships and possibilities for inexpensive, healthy eating that rely on minimally processed fresh foods. Policymakers engaging the food industry are advised to consider how to increase the affordability and availability of healthy foods in low-income communities in urban areas.
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.
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.
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.
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 rapid assessment used a mixed-method approach in three low-cost public flats in Kuala Lumpur targeting the B40, which is the bottom 40% of the economic spectrum. A total of 95 community members participated in a quantitative phone survey, while 21 respondents participated in a qualitative phone survey, including 12 community members and nine community health volunteers (CHVs).
RESULTS: The movement restriction imposed during the MCO significantly reduced the frequency and duration of respondents' physical activity. At the same time, respondents reported significantly increased consumption of home-cooked meals. More than half of respondents reduced their consumption of packaged snack foods (53.7%), street desserts (54.7%), fast food (50.5%), soft drinks (50.5%), and 3-in-1 or instant drinks (50.5%) due to limited access during the MCO. B40 communities were receptive to potential interventions to encourage healthier eating and physical activity leveraging digital approaches under the 'new normal'. Reported concerns included internet accessibility and affordability, functionality, and digital literacy.
CONCLUSION: The COVID-19 pandemic requires innovation to address diseases and risk factors at the community level. While movement restrictions reduced physical activity, they created opportunities for low-income individuals to have greater control over their diet, enabling them to adopt healthier eating habits. Lifestyle changes experienced by vulnerable populations provide an opportunity for creative and technology-enabled interventions to promote healthy eating and exercise.
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.
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.
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.
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: Data were obtained from the Malaysia Non-Communicable Disease Surveillance-1. Logistic regressions were estimated and odds ratios of exposure variables calculated.
RESULTS: Diabetes awareness was associated with work hours, age, family history of illnesses, and ethnicity. Individuals with diminished hypertension awareness included those who were younger, without family history of illnesses, not obese, working more hours, and not adhering to a healthy diet. Low awareness of hypercholesterolemia was associated with younger age, lower education level, living in rural areas, female gender, no family history of illnesses, non-obesity, and minority ethnic background. Prevalence generally had the same pattern of association with the exposure variables.
CONCLUSIONS: Various sociodemographic and health and lifestyle characteristics were associated with diabetes, hypertension, and hypercholesterolemia awareness in Malaysia, albeit with varying outcomes. Therefore, programs focusing on lifestyle improvements should be targeted at high-risk subgroups, such as individuals working longer hours and young adults, who are less likely to be aware of their health risk factors.