METHODS: A total of 429 respondents diagnosed with urologic cancers (prostate cancer, bladder and renal cancer) from Sarawak General Hospital and Subang Jaya Medical Centre in Malaysia were interviewed using a structured questionnaire. Objective and subjective FT were measured by catastrophic health expenditure (healthcare-cost-to-income ratio greater than 40%) and the Personal Financial Well-being Scale, respectively. HRQoL was measured with the Functional Assessment of Cancer Therapy - General 7 Items scale.
RESULTS: Objective and subjective FT were experienced by 16.1 and 47.3% of the respondents, respectively. Respondents who sought treatment at a private hospital and had out-of-pocket health expenditures were more likely to experience objective FT, after adjustment for covariates. Respondents who were female and had a monthly household income less than MYR 5000 were more likely to experience average to high subjective FT. Greater objective FT (OR = 2.75, 95% CI 1.09-6.95) and subjective FT (OR = 4.68, 95% CI 2.63-8.30) were associated with poor HRQoL.
CONCLUSIONS: The significant association between both objective and subjective FT and HRQoL highlights the importance of reducing FT among urologic cancer patients. Subjective FT was found to have a greater negative impact on HRQoL.
METHODS: Through the Association of Southeast Asian Nations Costs in Oncology study, 1,294 newly diagnosed patients with cancer (Ministry of Health [MOH] hospitals [n = 577], a public university hospital [n = 642], private hospitals [n = 75]) were observed in Malaysia. Cost diaries and questionnaires were used to measure incidence of financial toxicity, encompassing financial catastrophe (FC; out-of-pocket costs ≥ 30% of annual household income), medical impoverishment (decrease in household income from above the national poverty line to below that line after subtraction of cancer-related costs), and economic hardship (inability to make necessary household payments). Predictors of financial toxicity were determined using multivariable analyses.
RESULTS: One fifth of patients had private health insurance. Incidence of FC at 1 year was 51% (MOH hospitals, 33%; public university hospital, 65%; private hospitals, 72%). Thirty-three percent of households were impoverished at 1 year. Economic hardship was reported by 47% of families. Risk of FC attributed to conventional medical care alone was 18% (MOH hospitals, 5%; public university hospital, 24%; private hospitals, 67%). Inclusion of expenditures on nonmedical goods and services inflated the risk of financial toxicity in public hospitals. Low-income status, type of hospital, and lack of health insurance were strong predictors of FC.
CONCLUSION: Patients with cancer may not be fully protected against financial hardships, even in settings with universal health coverage. Nonmedical costs also contribute as important drivers of financial toxicity in these settings.
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 total of 2406 Malaysian children aged 5 to 12 years, who had participated in the South East Asian Nutrition Surveys (SEANUTS), were included in this study. Cognitive performance [non-verbal intelligence quotient (IQ)] was measured using Raven's Progressive Matrices, while socioeconomic characteristics were determined using parent-report questionnaires. Body mass index (BMI) was calculated using measured weight and height, while BMI-for-age Z-score (BAZ) and height-for-age Z-score (HAZ) were determined using WHO 2007 growth reference.
RESULTS: Overall, about a third (35.0%) of the children had above average non-verbal IQ (high average: 110-119; superior: ≥120 and above), while only 12.2% were categorized as having low/borderline IQ ( 3SD), children from very low household income families and children whose parents had only up to primary level education had the highest prevalence of low/borderline non-verbal IQ, compared to their non-obese and higher socioeconomic counterparts. Parental lack of education was associated with low/borderline/below average IQ [paternal, OR = 2.38 (95%CI 1.22, 4.62); maternal, OR = 2.64 (95%CI 1.32, 5.30)]. Children from the lowest income group were twice as likely to have low/borderline/below average IQ [OR = 2.01 (95%CI 1.16, 3.49)]. Children with severe obesity were twice as likely to have poor non-verbal IQ than children with normal BMI [OR = 2.28 (95%CI 1.23, 4.24)].
CONCLUSIONS: Children from disadvantaged backgrounds (that is those from very low income families and those whose parents had primary education or lower) and children with severe obesity are more likely to have poor non-verbal IQ. Further studies to investigate the social and environmental factors linked to cognitive performance will provide deeper insights into the measures that can be taken to improve the cognitive performance of Malaysian children.
DESIGN: Population-based, cross-sectional survey, Nepal Demographic and Health Survey 2011.
SETTING: A nationally representative sample of 11 085 households selected by a two-stage, stratified cluster sampling design to interview eligible men and women.
SUBJECTS: Children (n 2591) aged 0-60 months in a sub-sample of households selected for men's interview.
RESULTS: Prevalence of moderate and severe household food insecurity was 23·2% and 19·0%, respectively, for children aged 0-60 months. Weighted prevalence rates for stunting (height-for-age Z-score (HAZ)
METHODS: A systematic search for studies concerning the perception of financial burden among cancer patients and their families was conducted. Several electronic resources such as Medline, Elsevier (Science Direct), Web of Science, Embase, PubMed, CINAHL and Scopus (SciVerse) were searched. Additionally, manual search through indices citation was also thoroughly utilized. The main outcome of interest was the prevalence of perceived financial hardship among cancer patients and their families. Studies reported only the cost of cancer treatment and qualitative studies were excluded. Our search was limited to articles that were published from 2003 to 2013.
RESULT: Ten studies were included in this review and with a majority originating from high-income countries. The prevalence of the financial burden perception was reported between 14.8 and 78.8 %. The most frequent and significant risk factor reported associated with the perception of financial difficulty was the households with low income. Discontinuation of treatment and poverty were conversely the important consequences of financial burden in cancer patients and their families.
CONCLUSION: Evidently, cancer is a long-term illness that requires a high financial cost, and a significant number of cancer patients and families struggle with financial difficulty. Identifying such groups with a high risk of facing financial difficulty is a crucial measure to ensure safety nets are readily available for these targeted population.