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: This study included 224 mothers of under-five children living in urban slums of Udupi Taluk, Karnataka. A total of 17 urban slums were selected randomly using random cluster sampling.
Results: Undernutrition was high among children of illiterate mothers (63.8%), and the children of working mothers were affected by more morbidity (96.6%) as compared with housewives. Morbidity was also found to be high among children belonging to families with low incomes (66.1%) and low socio-economic backgrounds (93.1%). Safe drinking water, water supply, sanitation, hygiene, age of the child, mother's and father's education, mother's occupation and age, number of children in the family, use of mosquito nets, type of household, and family income were significantly associated with child morbidity, nutritional status, immunization status, and personal hygiene of under-five children living in urban slums.
Conclusion: Overall, in our study, family characteristics including parental education, occupation and income were significantly associated with outcomes among under-five children. The availability of safe drinking water and sanitation, and the use of mosquito nets to prevent vector-borne diseases are basic needs that need to be urgently met to improve child health.
Funding: Self-funded.
METHODS: This is an extensive literature review of published articles on IPD in selected developing countries from East Asia, South Asia, Middle East, sub-Saharan Africa, and Latin America. We reviewed all the articles retrieved from the knowledge bases that were published between the years 2000 and 2010.
RESULTS: After applying the inclusion, exclusion, and quality criteria, the comprehensive review of the literature yielded 10 articles with data for pneumococcal meningitis, septicemia/bacteremia, and pneumonia. These selected articles were from 10 developing countries from five different regions. Out of the 10 selected articles, 8 have a detailed discussion on IPD, one of them has s detailed discussion on bacteremia and meningitis, and another one has discussed pneumococcal bacteremia. Out of these 10 articles, only 5 articles discussed the case-fatality ratio (CFR). In our article review, the incidence of IPD ranged from less than 5/100,000 to 416/100,000 population and the CFR ranged from 12.2% to 80% in the developing countries.
CONCLUSIONS: The review demonstrated that the clinical burden of IPD was high in the developing countries. The incidence of IPD and CFR varies from region to region and from country to country. The IPD burden was highest in sub-Saharan African countries followed by South Asian countries. The CFR was low in high-income countries than in low-income countries.
METHODS: Data of 328 eligible housewives who participated in the MyBFF@Home study was used. Intervention group of 169 subjects were provided with an intervention package which includes physical activity (brisk walking, dumbbell exercise, physical activity diary, group exercise) and 159 subjects in control group received various health seminars. Physical activity level was assessed using short-International Physical Activity Questionnaire. The physical activity level was then re-categorized into 4 categories (active intervention, inactive intervention, active control and inactive control). Physical activity, blood glucose and lipid profile were measured at baseline, 3rd month and 6th month of the study. General Linear Model was used to determine the effect of physical activity on glucose and lipid profile.
RESULTS: At the 6th month, there were 99 subjects in the intervention and 79 control group who had complete data for physical activity. There was no difference on the effect of physical activity on the glucose level and lipid profile except for the Triglycerides level. Both intervention and control groups showed reduction of physical activity level over time.
CONCLUSION: The effect of physical activity on blood glucose and lipid profile could not be demonstrated possibly due to physical activity in both intervention and control groups showed decreasing trend over time.