Methods: Cross-sectional data from 62 developing countries were used to run several multivariate linear regressions. R2 was used to compare the powers of MPI with income-poverties (income poverty gaps [IPG] at 1.9 and 3.1 USD) in explaining LE.
Results: Adjusting for controls, both MPI (β =-0.245, P<0.001) and IPG at 3.1 USD (β=-0.135, P=0.044) significantly correlates with LE, but not IPG at 1.9 USD (β=-0.147, P=0.135). MPI explains 12.1% of the variation in LE compared to only 3.2% explained by IPG at 3.1 USD. The effect of MPI on LE is higher on female (β=-0.210, P<0.001) than male (β=-0.177, P<0.001). The relative influence of the deprivation indictors on LE ranks as follows (most to least): Asset ownership, drinking water, cooking fuel, flooring, child school attendance, years of schooling, nutrition, mortality, improved sanitation, and electricity.
Conclusion: Interventions to reduce poverty and improve LE should be guided by MPI, not income poverty indices. Such policies should be female-oriented and prioritized based on the relative influence of the various poverty deprivation indicators on LE.
METHODS: A systematic review and meta-analysis of interventional studies assessing quality improvement processes, interventions, and structure in developing country surgical systems was conducted according to the Preferred Reporting Items of Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Studies were included if they were conducted in an LMIC, occurred in a surgical setting, and measured the effect of an implementation and its impact. The primary outcome was mortality, and secondary outcomes were rates of rates of hospital-acquired infection (HAI) and surgical site infections (SSI). Prospero Registration: CRD42020171542.
RESULT: Of 38,273 search results, 31 studies were included in a qualitative synthesis, and 28 articles were included in a meta-analysis. Implementation of multimodal bundled interventions reduced the incidence of HAI by a relative risk (RR) of 0.39 (95%CI 0.26 to 0.59), the effect of hand hygiene interventions on HAIs showed a non-significant effect of RR of 0.69 (0.46-1.05). The WHO Safe Surgery Checklist reduced mortality by RR 0.68 (0.49 to 0.95) and SSI by RR 0.50 (0.33 to 0.63) and antimicrobial stewardship interventions reduced SSI by RR 0.67 (0.48-0.93).
CONCLUSION: There is evidence that a number of quality improvement processes, interventions and structural changes can improve mortality, HAI and SSI outcomes in the peri-operative setting in LMICs.
METHODS: A cross-sectional study of patients with cancer was conducted in Hospital Kuala Lumpur between September and October 2020. Self-reported data from the patients were collected using face-to-face interviews. Detailed information about cancer-related OOP expenses including direct medical, direct non-medical, and productivity loss in addition to financial coping strategies were collected. Costs data were estimated and reported as average annual total costs per patient.
RESULTS: The mean total cost of cancer was estimated at MYR 7955.39 (US$ 1893.46) per patient per year. The direct non-medical cost was the largest contributor to the annual cost, accounting for 46.1% of the total cost. This was followed by indirect costs and direct medical costs at 36.0% and 17.9% of the total annual costs, respectively. Supplemental food and transportation costs were the major contributors to the total non-medical costs. The most frequently used financial coping strategies were savings and financial support received from relatives and friends.
CONCLUSION: This study showed that estimation of the total cost of cancer from the patient's perspective is feasible. Considering the significant impact of direct non-medical and indirect costs on the total costs, it is vital to conduct further exploration of its cost drivers and variations using a larger sample size.
DESCRIPTION: COVID-19 directly affects pregnant women causing more severe disease and adverse pregnancy outcomes. The indirect effects due to the monumental COVID-19 response are much worse, increasing maternal and neonatal mortality.
ASSESSMENT: Amidst COVID-19, governments must balance effective COVID-19 response measures while continuing delivery of essential health services. Using the World Health Organization's operational guidelines as a base, countries must conduct contextualized analyses to tailor their operations. Evidence based information on different services and comparative cost-benefits will help decisions on trade-offs. Situational analyses identifying extent and reasons for service disruptions and estimates of impacts using modelling techniques will guide prioritization of services. Ensuring adequate supplies, maintaining core interventions, expanding non-physician workforce and deploying telehealth are some adaptive measures to optimize care. Beyond the COVID-19 pandemic, governments must reinvest in maternal and child health by building more resilient maternal health services supported by political commitment and multisectoral engagement, and with assistance from international partners.
CONCLUSIONS: Multi-sectoral investments providing high-quality care that ensures continuity and available to all segments of the population are needed. A robust primary healthcare system linked to specialist care and accessible to all segments of the population including marginalized subgroups is of paramount importance. Systematic approaches to digital health care solutions to bridge gaps in service is imperative. Future pandemic preparedness programs must include action plans for resilient maternal health services.
METHODS: This study used the EuroQol 5-Dimension 5-Level (EQ- 5D-5L) tool during the COVID-19 pandemic to examine relationships between socio-demographics, knowledge, and attitudes towards education and outcomes of health-related quality of life (HRQOL). Between September and October 2020 and January and February 2021, a cross-sectional study using a multi-stage sampling technique was carried out.
RESULTS: A total of 1,997 adults participated, with a mean age of 45.17 (SD 14.113). In total, 74.9% had good knowledge, while 59.8% had a positive attitude towards skill education. In univariate analyses, the EQ-5D-5L score was related to age, income, education level, marital status, employment status, financial strain level, and knowledge and attitude towards skilled education. Generalised linear model analyses demonstrated that lower EQ-5D-5L scores were associated with older age, financial constraints, and a negative attitude towards skills education. However, additional adjustments for knowledge and attitude towards skills education show only an increase in age and financial strain was significant.
CONCLUSION: The findings suggest that appropriate strategies be implemented to increase low-income populations' knowledge and attitude towards skill education. Improving education may improve the quality of life for this vulnerable group. Additionally, a qualitative study can be conducted to determine the barriers to low-income households participating in skilled education to fill in the knowledge gap.
MATERIALS AND METHODS: This cross-sectional study was conducted from May to July 2022 in urban areas in Selangor among children aged less than two years old from B40 households using purposive sampling through both online surveys and face-to-face interviews. There were 112 children aged < 2 years old from B40 households participating in this study. The data obtained on maternal sociodemographic, Household Food Insecurity Scale (HFIAS), and children's anthropometric measurements were analysed by using the WHO Anthro Survey, descriptive analysis, Person's Chisquare test and Fischer's exact test.
RESULTS: The prevalence of food insecurity was more significant than the prevalence of food secured, at 55.4% and 44.6% respectively. The stunting among the children rated at 34.8%, followed by 7.2% of the sample found underweight, 7.8% (BAZ) and 16.1% (BAZ) of them were wasted, and overweight & obese, proportionately. This study discovered that household size was the sole determinant of household food security status. This finding suggested that size of a household influenced the odds of a household being food insecure.
CONCLUSION: The findings of this study provide insights into how the COVID-19 pandemic have an impact on children's nutritional status especially those from low-income and bigger size households. Therefore, more thorough and effective interventions should be designed particularly targeting this urban poor community to enhance their nutritional status and health.
AREAS COVERED: This review covers the epidemiology and burden of COPD in LMICs, and challenges and recommendations related to health-care systems, prevention, diagnosis, and treatment. Main challenges are related to under-resourced health-care systems (such as limited availability of spirometry, rehabilitation, and medicines). Lack of policy and practical local guidelines on COPD diagnosis and management further contribute to the low diagnostic and treatment rates. In the absence of, or limited number of respiratory specialists, primary care practitioners (general practitioners, nurses, pharmacists, physiotherapists, and community health workers) play an even more pivotal role in COPD management in LMICs.
EXPERT OPINION: Raising awareness on COPD, educating health-care workers, patients, and communities on cost-effective preventive measures as well as improving availability, affordability and proper use of diagnostic and pharmacological and non-pharmacologic treatment in primary care are the key interventions needed to improve COPD prevention, diagnosis, and care in LMICs.