METHODS: This was a cross sectional study design. A total of 347 respondents from low household income groups, including persons with disability and Orang Asli were recruited from E-kasih. A semi-guided self-administered questionnaire was used. QOL measured by EQ. 5D utility value and health status measured by visual analogue score (VAS). Descriptive statistic, bivariate Chi-square analysis and binary logistic regression were conducted to determine factors influencing low QOL and poor health status.
RESULTS: Majority of the respondents were Malay, female (61%), 63% were married, 60% were employed and 46% with total household income of less than 1 thousand Ringgit Malaysia. 70% of them were not having any chronic medical problems. Factors that associated with low QOL were male, single, low household income, and present chronic medical illness, while poor health status associated with female, lower education level and present chronic medical illness. Logistic regression analysis has showed that determinants of low QOL was present chronic illness [AOR 4.15 95%CI (2.42, 7.13)], while determinants for poor health status were; female [AOR 1.94 95%CI (1.09,3.44)], lower education [AOR 3.07 95%CI (1.28,7.34)] and present chronic illness [AOR 2.53 95%CI (1.39,4.61)].
CONCLUSION: Low socioeconomic population defined as low total household income in this study. Low QOL of this population determined by present chronic illness, while poor health status determined by gender, education level and chronic medical illness.
METHODS: A prospective cohort study was conducted at baseline (after delivery), 2, 4 and 6 months postpartum. From 638 eligible mothers initially recruited, 420 completed until 6 months. Dependent variable was weight retention, defined as difference between weight at 6 months postpartum and pre-pregnancy weight, and weight retention ≥5kg was considered excessive. Independent variables included socio-demographic, history of pregnancy and delivery, lifestyle, practices and traditional postpartum practices.
RESULTS: Average age was 29.61±4.71years, majority (83.3%) were Malays, 58.8% (low education), 70.0% (employed), 65.2% (middle income family), 33.8% (primiparous) and 66.7% (normal/instrumental delivery). Average gestational weight gain was 12.90±5.18kg. Mean postpartum weight retention was 3.12±4.76kg, 33.8% retaining ≥5kg. Bivariable analysis showed low income, primiparity, gestational weight gain ≥12kg, less active physically, higher energy, protein, carbohydrate and fat intake in diet, never using hot stone compression and not continuing breastfeeding were significantly associated with higher 6 months postpartum weight retention. From multivariable linear regression analysis, less active physically, higher energy intake in diet, gestational weight gain ≥12kg, not continuing breastfeeding 6 months postpartum and never using hot stone compression could explain 55.1% variation in 6 months postpartum weight retention.
CONCLUSION: Women need to control gestational weight gain, remain physically active, reduce energy intake, breastfeed for at least 6 months and use hot stone compression to prevent high postpartum weight retention.
METHODS: This cross-sectional study was conducted in three Malaysian public hospitals namely Hospital Kuala Lumpur, Hospital Canselor Tuanku Muhriz and the National Cancer Institute using a multi-level sampling technique to recruit 630 respondents from February 2020 to February 2021. CHE was defined as incurring a monthly health expenditure of more than 10% of the total monthly household expenditure. A validated questionnaire was used to collect the relevant data.
RESULTS: The CHE level was 54.4%. CHE was higher among patients of Indian ethnicity (P = 0.015), lower level education (P = 0.001), those unemployed (P < 0.001), lower income (P < 0.001), those in poverty (P < 0.001), those staying far from the hospital (P < 0.001), living in rural areas (P = 0.003), small household size (P = 0.029), moderate cancer duration (P = 0.030), received radiotherapy treatment (P < 0.001), had very frequent treatment (P < 0.001), and without a Guarantee Letter (GL) (P < 0.001). The regression analysis identified significant predictors of CHE as lower income aOR 18.63 (CI 5.71-60.78), middle income aOR 4.67 (CI 1.52-14.41), poverty income aOR 4.66 (CI 2.60-8.33), staying far from hospital aOR 2.62 (CI 1.58-4.34), chemotherapy aOR 3.70 (CI 2.01-6.82), radiotherapy aOR 2.99 (CI 1.37-6.57), combination chemo-radiotherapy aOR 4.99 (CI 1.48-16.87), health insurance aOR 3.99 (CI 2.31-6.90), without GL aOR 3.38 (CI 2.06-5.40), and without health financial aids aOR 2.94 (CI 1.24-6.96).
CONCLUSIONS: CHE is related to various sociodemographic, economic, disease, treatment and presence of health insurance, GL and health financial aids variables in Malaysia.
MATERIALS AND METHODS: This cross-sectional study was conducted in three Malaysian public hospitals using a multilevel sampling technique to recruit 630 respondents. A validated self-developed four-domain questionnaire which includes one domain for health insurance was used to collect the relevant data.
RESULTS: Approximately 31.7% of the respondents owned PHI. The PHI usage was significantly higher among male respondents (p=0.035), those aged 18-40 years old (p<0.001), Indian and Chinese ethnicities (p=0.002), with tertiary education level (p<0.001), employed (p<0.001), working in the private sector (p<0.001), high household income (T20) (p<0.001), home near to the hospital (p=0.001) and medium household size (p<0.001). The significant predictive factors were age 18-40 years aOR 3.01 (95% CI: 1.67-5.41), age 41-60 years aOR 2.22 (95% CI 1.41-3.49), medium (M40) income aOR 2.90 (95% CI: 1.92-4.39) and high (T20) income aOR 3.86 (95% CI: 1.68-18.91), home near to the hospital aOR 1.68 (95% CI: 1.10-2.55), medium household size aOR 2.20 (95% CI: 1.30-3.72) and female head of household aOR 1.79 (95% CI: 1.01-3.16). The type of cancer treatment, the location of treatment, prior treatment in private healthcare facilities and existence of financial coping mechanisms also were significant factors in determining PHI usage among cancer patients in this study.
CONCLUSION: Several factors are significantly associated with PHI usage in cancer patients. The outcome of this study can guide policymakers to identify high-risk groups which need supplementary health insurance to bear the cost for their cancer treatment so that a better pre-payment health financing system such as a national health insurance can be formulated to cater for these groups.
MATERIAL AND METHODS: A cross-sectional study using face to face structured questionnaire. All 447 respondents included were low-income earners enrolled in the HLA. Chi-square analysis and multiple logistic regression were used to examine association between the risk factors and healthcare utilization.
RESULTS: The response rate was 93.5%. The healthcare utilization among the respondents during the partial lockdown period was 19.5% and 33.1% during the recovery lockdown period. Enrollment in the PeKa B40 scheme among the 7.6% respondents was not associated with healthcare utilization. After controlling for the variables, those aged 60 years and above [AOR: 1.87; 95% (CI): (1.07; 3.27)], self-rated poor health status [AOR: 2.16; 95% (CI): (1.07; 4.34)], having NCDs [AOR: 4.21; 95% (CI): (2.23; 7.94)], and being hospitalized in the past 12 months [AOR: 3.54; 95% (CI): (1.46; 8.62)], were more likely to utilize healthcare services as compared to their counterparts.
CONCLUSION: The results from this study is valuable for policy recommendations to improve on the coverage of the PeKa B40 scheme and healthcare access for the low-income population especially during the pandemic.
MATERIALS AND METHODS: We plan to conduct a two-phase exploratory sequential mixed method study to determine the factors affecting compliance of Malaysian healthcare workers towards tuberculosis prevention programmes in their workplace based on the guidelines of the Ministry of Health, Malaysia. Phase one is a qualitative study with a focus group discussion and questionnaire development and phase two is a quantitative study where data will be collected among healthcare workers in government clinics and hospitals in Selangor. The data from phase one will be analysed using Atlas.Ti software for thematic analysis and data from phase two will be analysed using SEM AMOS software for structural equation modelling.