SETTING: Adults interviewed during house-to-house surveys.
PARTICIPANTS: Women (15-45 years) and men (15-49 years) surveyed in four Nepal Demographic and Health Surveys done in 2001, 2006, 2011 and 2016.
OUTCOME MEASURE: Current tobacco use (in any form).
RESULTS: The prevalence of tobacco use for men declined from 66% in 2001 to 55% in 2016, and declined from 29% to 8.4% among women. Across both education and wealth quintiles for both men and women, the prevalence of tobacco use generally declines with increasing education or wealth. We found persistently larger absolute inequalities by education than by wealth among men. Among women we also found larger educational than wealth-related gradients, but both declined over time. For men, the Slope Index of Inequality (SII) for education was larger than for wealth (44% vs 26% in 2001) and changed very little over time. For women, the SII for both education and wealth were similar in magnitude to men, but decreased substantially between 2001 and 2016 (from 44% to 16% for education; from 37% to 16% for wealth). Women had a larger relative index of inequality than men for both education (6.5 vs 2.0 in 2001) and wealth (4.8 vs 1.5 in 2001), and relative inequality increased between 2001 and 2016 for women (from 6.5 to 16.0 for education; from 4.8 to 12.0 for wealth).
CONCLUSION: Increasing relative inequalities indicates suboptimal reduction in tobacco use among the vulnerable groups suggesting that they should be targeted to improve tobacco control.
METHODS: This is a retrospective analysis of the Malaysian National Cardiovascular Disease Database-Acute Coronary Syndrome registry from year 2006 to 2013 (n = 30,873). On-discharge pharmacotherapies examined were aspirin, ADP-antagonists, statins, ACE-inhibitors, angiotensin-II-receptor blockers, and beta-blockers. Multivariate logistic regression was used to calculate adjusted odds ratio of receiving individual pharmacotherapies according to patients' characteristics in NSTEMI patients (n = 11,390).
RESULTS: Prescribing rates for cardiovascular pharmacotherapies had significantly increased especially for ADP-antagonists (76%) in NSTEMI patients. More than 85% were prescribed statins and antiplatelets but rates remained significantly lower compared to STEMI. Women and those over 65 years old were less likely to be prescribed these pharmacotherapies compared to men and younger NSTEMI patients. Chinese and Indians were more likely to receive selected pharmacotherapies compared to Malays (main ethnicity). Geographical variations were observed; East Malaysian (Malaysian Borneo) patients were less likely to receive these compared to Western region of Malaysian Peninsular. Underprescribing in patients with risk factors such as diabetes were observed with other co-morbidities influencing prescribing selectively.
CONCLUSION: This study uncovers demographic and clinical variations in cardiovascular pharmacotherapies prescribing for NSTEMI. Concerted efforts by policy makers, specialty societies, and physicians are required focusing on elderly, women, Malays, East Malaysians, and high-risk patients.
Methods: A multi-center cross sectional study was conducted for a month in out-patient wards of hospitals in Khobar, Dammam, Makkah, and Madinah, Saudi Arabia. Patients were randomly selected from a registered patient pools at hospitals and the item-subject ratio was kept at 1:20. The tool was assessed for factorial, construct, convergent, known group and predictive validities as well as, reliability and internal consistency of scale were also evaluated. Sensitivity, specificity, and accuracy were also evaluated. Data were analyzed using SPSS v24 and MedCalc v19.2. The study was approved by concerned ethics committees (IRB-129-25/6/1439) and (IRB-2019-05-002).
Results: A total of 282 responses were received. The values for normed fit index (NFI), comparative fit index (CFI), Tucker Lewis index (TLI) and incremental fit index (IFI) were 0.960, 0.979, 0.954 and 0.980. All values were >0.95. The value for root mean square error of approximation (RMSEA) was 0.059, i.e., <0.06. Hence, factorial validity was established. The average factor loading of the scale was 0.725, i.e., >0.7, that established convergent validity. Known group validity was established by obtaining significant p-value <0.05, for the associations based on hypotheses. Cronbach's α was 0.865, i.e., >0.7. Predictive validity was established by evaluating odds ratios (OR) of demographic factors with adherence score using logistic regression. Sensitivity was 78.16%, specificity was 76.85% and, accuracy of the tool was 77.66%, i.e., >70%.
Conclusion: The Arabic version of GMAS achieved all required statistical parameters and was validated in Saudi patients with chronic diseases.
OBJECTIVE: To examine the time trends, socio-economic and regional inequalities of under-five mortality rate (U5MR) in Nepal.
METHODS: We analyzed the data from complete birth histories of four Nepal Demographic and Health Surveys (NDHS) done in the years 1996, 2001, 2006 and 2011. For each livebirth, we computed survival period from birth until either fifth birthday or the survey date. Using direct methods i.e. by constructing life tables, we calculated yearly U5MRs from 1991 to 2010. Projections were made for the years 2011 to 2015. For each NDHS, U5MRs were calculated according to child's sex, mother's education, household wealth index, rural/urban residence, development regions and ecological zones. Inequalities were calculated as rate difference, rate ratio, population attributable risk and hazard ratio.
RESULTS: Yearly U5MR (per 1000 live births) had decreased from 157.3 (95% CIs 178.0-138.9) in 1991 to 43.2 (95% CIs 59.1-31.5) in 2010 i.e. 114.1 reduction in absolute risk. Projected U5MR for the year 2015 was 54.33. U5MRs had decreased in absolute terms in all sub groups but relative inequalities had reduced for gender and rural/urban residence only. Wide inequalities existed by wealth and education and increased between 1996 and 2011. For lowest wealth quintile (as compared to highest quintile) hazard ratio (HR) increased from 1.37 (95% CIs 1.27, 1.49) to 2.54 ( 95% CIs 2.25, 2.86) and for mothers having no education (as compared to higher education) HR increased from 2.55 (95% CIs 1.95, 3.33) to 3.75 (95% CIs 3.17, 4.44). Changes in regional inequities were marginal and irregular.
CONCLUSIONS: Nepal is most likely to achieve MDG-4 but eductional and wealth inequalities may widen further. National health policies should address to reduce inequalities in U5MR through 'inclusive policies'.