METHODS: Data for 91 countries were obtained from United Nations agencies. The response variable was life expectancy, and the determinant factors were demographic events (total fertility rate and adolescent fertility rate), socioeconomic status (mean years of schooling and gross national income per capita), and health factors (physician density and human immunodeficiency virus [HIV] prevalence rate). Path analysis was used to determine the direct, indirect, and total effects of these factors on life expectancy.
RESULTS: All determinant factors were significantly correlated with life expectancy. Mean years of schooling, total fertility rate, and HIV prevalence rate had significant direct and indirect effects on life expectancy. The total effect of higher physician density was to increase life expectancy.
CONCLUSIONS: We identified several direct and indirect pathways that predict life expectancy. The findings suggest that policies should concentrate on improving reproductive decisions, increasing education, and reducing HIV transmission. In addition, special attention should be paid to the emerging need to increase life expectancy by increasing physician density.
METHODS: The authors obtained quantitative data as key indicators of the neurosurgical workforce from each country. Qualitative data analysis was also done to provide a description of the current state of neurosurgical training and education in the region. A strengths, weaknesses, opportunities, and threats (SWOT) analysis was also done to identify strategies for improvement.
RESULTS: The number of neurosurgeons in each country is as follows: 370 in Indonesia, 10,014 in Japan, 152 in Malaysia, 134 in the Philippines, and 639 in Taiwan. With a large neurosurgical workforce, the high-income countries Japan and Taiwan have relatively high neurosurgeon to population ratios of 1 per 13,000 and 1 per 37,000, respectively. In contrast, the low- to middle-income countries Indonesia, Malaysia, and the Philippines have low neurosurgeon to population ratios of 1 per 731,000, 1 per 210,000, and 1 per 807,000, respectively. In terms of the number of training centers, Japan has 857, Taiwan 30, Indonesia 7, Malaysia 5, and the Philippines 10. In terms of the number of neurosurgical residents, Japan has 1000, Taiwan 170, Indonesia 199, Malaysia 53, and the Philippines 51. The average number of yearly additions to the neurosurgical workforce is as follows: Japan 180, Taiwan 27, Indonesia 10, Malaysia 4, and the Philippines 3. The different countries included in this report have many similarities and differences in their models and systems of neurosurgical education. Certain important strategies have been formulated in order for the system to be responsive to the needs of the catchment population: 1) establishment of a robust network of international collaboration for reciprocal certification, skills sharing, and subspecialty training; 2) incorporation of in-service residency and fellowship training within the framework of improving access to neurosurgical care; and 3) strengthening health systems, increasing funding, and developing related policies for infrastructure development.
CONCLUSIONS: The varied situations of neurosurgical education in the East Asian region require strategies that take into account the different contexts in which programs are structured. Improving the education of current and future neurosurgeons becomes an important consideration in addressing the health inequalities in terms of access and quality of care afflicting the growing population in this region of the world.
DESIGN: Cross-sectional observational study.
SETTING: Twenty-three Asian countries and regions, covering 92.1% of the continent's population.
PARTICIPANTS: Ten low-income and lower-middle-income economies, five upper-middle-income economies, and eight high-income economies according to the World Bank classification.
INTERVENTIONS: Data closest to 2017 on critical care beds, including ICU and intermediate care unit beds, were obtained through multiple means, including government sources, national critical care societies, colleges, or registries, personal contacts, and extrapolation of data.
MEASUREMENTS AND MAIN RESULTS: Cumulatively, there were 3.6 critical care beds per 100,000 population. The median number of critical care beds per 100,000 population per country and region was significantly lower in low- and lower-middle-income economies (2.3; interquartile range, 1.4-2.7) than in upper-middle-income economies (4.6; interquartile range, 3.5-15.9) and high-income economies (12.3; interquartile range, 8.1-20.8) (p = 0.001), with a large variation even across countries and regions of the same World Bank income classification. This number was independently predicted by the World Bank income classification on multivariable analysis, and significantly correlated with the number of acute hospital beds per 100,000 population (r = 0.19; p = 0.047), the universal health coverage service coverage index (r = 0.35; p = 0.003), and the Human Development Index (r = 0.40; p = 0.001) on univariable analysis.
CONCLUSIONS: Critical care bed capacity varies widely across Asia and is significantly lower in low- and lower-middle-income than in upper-middle-income and high-income countries and regions.
METHODS: Optimal RTU (oRTU) rates were determined for nine middle-income countries, following the epidemiological evidence-based method. The actual RTU (aRTU) rates were calculated dividing the total number of new notifiable cancer patients treated with radiotherapy in 2012 by the total number of cancer patients diagnosed in the same year in each country. An analysis of the characteristics of patients and treatments in a series of 300 consecutive radiotherapy patients shed light on the particular patient and treatments profile in the participating countries.
RESULTS: The median oRTU rate for the group of nine countries was 52% (47-56%). The median aRTU rate for the nine countries was 28% (9-46%). These results show that the real proportion of cancer patients receiving RT is lower than the optimal RTU with a rate difference between 10-42.7%. The median percent-unmet need was 47% (18-82.3%).
CONCLUSIONS: The optimal RTU rate in middle-income countries did not differ significantly from that previously found in high-income countries. The actual RTU rates were consistently lower than the optimal, in particular in countries with limited resources and a large population.
OBJECTIVES: To determine the a) aetiology, b) factors associated with bacterial pneumonia and c) association between co-infections (bacteria + virus) and severity of disease, in children admitted with severe pneumonia.
METHODS: A prospective cohort study involving children aged 1-month to 5-years admitted with very severe pneumonia, as per the WHO definition, over 2 years. Induced sputum and blood obtained within 24 hrs of admission were examined via PCR, immunofluorescence and culture to detect 17 bacteria/viruses. A designated radiologist read the chest radiographs.
RESULTS: Three hundred patients with a mean (SD) age of 14 (±15) months old were recruited. Significant pathogens were detected in 62% of patients (n = 186). Viruses alone were detected in 23.7% (n = 71) with rhinovirus (31%), human metapneumovirus (HMP) [22.5%] and respiratory syncytial virus (RSV) [16.9%] being the commonest. Bacteria alone was detected in 25% (n = 75) with Haemophilus influenzae (29.3%), Staphylococcus aureus (24%) and Streptococcus pneumoniae (22.7%) being the commonest. Co-infections were seen in 13.3% (n = 40) of patients. Male gender (AdjOR 1.84 [95% CI 1.10, 3.05]) and presence of crepitations (AdjOR 2.27 [95% CI 1.12, 4.60]) were associated with bacterial infection. C-reactive protein (CRP) [p = 0.007]) was significantly higher in patients with co-infections but duration of hospitalization (p = 0.77) and requirement for supplemental respiratory support (p = 0.26) were not associated with co-infection.
CONCLUSIONS: Bacteria remain an important cause of very severe pneumonia in developing countries with one in four children admitted isolating bacteria alone. Male gender and presence of crepitations were significantly associated with bacterial aetiology. Co-infection was associated with a higher CRP but no other parameters of severe clinical illness.
METHODS: Data among former and current adult smokers aged 18 and older came from contemporaneous Global Adult Tobacco Surveys (2008-2011) and the International Tobacco Control Surveys (2009-2013) conducted in eight LMICs (Bangladesh, Brazil, China, India, Mexico, Malaysia, Thailand and Uruguay). Adjusted odds ratios (AORs) of successful quitting in the past year by SES indicators (household income/wealth, education, employment status, and rural-urban residence) were estimated using multivariable logistic regression controlling for socio-demographics and average tobacco product prices. A random effects meta-analysis was used to combine the estimates of AORs pooled across countries and two concurrent surveys for each country.
RESULTS: Estimated quit rates among smokers (both daily and occasional) varied widely across countries. Meta-analysis of pooled AORs across countries and data sources indicated that there was no clear evidence of an association between SES indicators and successful quitting. The only exception was employed smokers, who were less likely to quit than their non-employed counterparts, which included students, homemakers, retirees, and the unemployed (pooled AOR≈0.8, p<0.10).
CONCLUSION: Lack of clear evidence of the impact of lower SES on adult cessation behaviour in LMICs suggests that lower-SES smokers are not less successful in their attempts to quit than their higher-SES counterparts. Specifically, lack of employment, which is indicative of younger age and lower nicotine dependence for students, or lower personal disposable income and lower affordability for the unemployed and the retirees, may be associated with quitting. Raising taxes and prices of tobacco products that lowers affordability of tobacco products might be a key strategy for inducing cessation behaviour among current smokers and reducing overall tobacco consumption. Because low-SES smokers are more sensitive to price increases, tobacco taxation policy can induce disproportionately larger decreases in tobacco consumption among them and help reduce socio-economic disparities in smoking and consequent health outcomes.