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)
AIMS AND METHODS: Global Youth Tobacco Survey (GYTS)s from Georgia, Iraq, Italy, Latvia, Montenegro, Paraguay, Peru, Qatar, Romania, and San Marino were analyzed. Changes in prevalence of "awareness of e-cigarettes," "ever use" (even tried a few puffs) and "current use" (during last 30 days) of e-cigarettes and cigarette smoking, and "dual use" (both e-cigarette and cigarette smoking) between baseline (2013 and 2014) and most recent (2017-2019) surveys were estimated.
RESULTS: "Awareness of e-cigarettes" and "ever e-cigarette use" significantly increased (p 50% in most countries. During the most recent surveys, "current e-cigarette" use was > 10% in five countries Italy (18.3%) and Latvia (18.5%) being the highest. Cigarette smoking significantly declined in Italy, Latvia, Peru, and San Marino (p
METHODS: We analysed sequential Global Adult Tobacco Survey (GATS) data done at least at five years interval in 10 countries namely India, Bangladesh, China, Mexico, Philippines, Russia, Turkey, Ukraine, Uruguay, and Vietnam. We estimated weighted prevalence rates of smoking behaviors namely current smoking (both daily and non-daily), prevalence of hardcore smoking (HCS) among current smokers (HCSs%) and entire surveyed population (HCSp%), quit ratios (QR), and the number of cigarettes smoked per day (CPD). We calculated absolute and relative (%) change in rates between two surveys in each country. Using aggregate data, we correlated relative change in current smoking prevalence with relative change in HCSs% and HCSp% as well as explored the relationship of MPOWER score with relative change in smoking behaviors using Spearman' rank correlation test.
RESULTS: Overall daily smoking has declined in all ten countries lead by a 23% decline in Russia. In India, Bangladesh, and Philippines HCSs% decreased as the smoking rate decreased while HCSs% increased in Turkey (66%), Vietnam (33%) and Ukraine (15%). In most countries, CPD ranged from 15 to 20 sticks except in Mexico (7.8), and India (10.4) where CPD declined by 18 and 22% respectively. MPOWER scores were moderately correlated with HCSs% in both sexes (r = 0.644, p = 0.044) and HCSp% (r = 0.632, p = 0.05) and among women only HCSs% (r = 0.804, p = 0.005) was significantly correlated with MPOWER score.
CONCLUSION: With declining smoking prevalence, HCS had also decreased and quit rates improved. Ecologically, a positive linear relationship between changes in smoking and HCS is a possible evidence against 'hardening'. Continued monitoring of the changes in quitting and hardcore smoking behaviours is required to plan cessation services.
METHODS: We analysed Demographic and Health Survey data on tobacco use collected from large nationally representative samples of men and women in 54 LMICs. We estimated the weighted prevalence of any current tobacco use (including smokeless tobacco) in each country for 4 educational groups and 4 wealth groups. We calculated absolute and relative measures of inequality, that is, the slope index of inequality (SII) and relative index of inequality (RII), which take into account the distribution of prevalence across all education and wealth groups and account for population size. We also calculated the aggregate SII and RII for low-income (LIC), lower-middle-income (lMIC) and upper-middle-income (uMIC) countries as per World Bank classification.
FINDINGS: Male tobacco use was highest in Bangladesh (70.3%) and lowest in Sao Tome (7.4%), whereas female tobacco use was highest in Madagascar (21%) and lowest in Tajikistan (0.22%). Among men, educational inequalities varied widely between countries, but aggregate RII and SII showed an inverse trend by country wealth groups. RII was 3.61 (95% CI 2.83 to 4.61) in LICs, 1.99 (95% CI 1.66 to 2.38) in lMIC and 1.82 (95% CI 1.24 to 2.67) in uMIC. Wealth inequalities among men varied less between countries, but RII and SII showed an inverse pattern where RII was 2.43 (95% CI 2.05 to 2.88) in LICs, 1.84 (95% CI 1.54 to 2.21) in lMICs and 1.67 (95% CI 1.15 to 2.42) in uMICs. For educational inequalities among women, the RII varied much more than SII varied between the countries, and the aggregate RII was 14.49 (95% CI 8.87 to 23.68) in LICs, 3.05 (95% CI 1.44 to 6.47) in lMIC and 1.58 (95% CI 0.33 to 7.56) in uMIC. Wealth inequalities among women showed a pattern similar to that of men: the RII was 5.88 (95% CI 3.91 to 8.85) in LICs, 1.76 (95% CI 0.80 to 3.85) in lMIC and 0.39 (95% CI 0.09 to 1.64) in uMIC. In contrast to men, among women, the SII was pro-rich (higher smoking among the more advantaged) in 13 of the 52 countries (7 of 23 lMIC and 5 of 7 uMIC).
INTERPRETATION: Our results confirm that socioeconomic inequalities tobacco use exist in LMIC, varied widely between the countries and were much wider in the lowest income countries. These findings are important for better understanding and tackling of socioeconomic inequalities in health in LMIC.
OBJECTIVE: To determine levels and trends in the fatal and nonfatal burden of diseases and injuries among younger children (aged <5 years), older children (aged 5-9 years), and adolescents (aged 10-19 years) between 1990 and 2013 in 188 countries from the Global Burden of Disease (GBD) 2013 study.
EVIDENCE REVIEW: Data from vital registration, verbal autopsy studies, maternal and child death surveillance, and other sources covering 14,244 site-years (ie, years of cause of death data by geography) from 1980 through 2013 were used to estimate cause-specific mortality. Data from 35,620 epidemiological sources were used to estimate the prevalence of the diseases and sequelae in the GBD 2013 study. Cause-specific mortality for most causes was estimated using the Cause of Death Ensemble Model strategy. For some infectious diseases (eg, HIV infection/AIDS, measles, hepatitis B) where the disease process is complex or the cause of death data were insufficient or unavailable, we used natural history models. For most nonfatal health outcomes, DisMod-MR 2.0, a Bayesian metaregression tool, was used to meta-analyze the epidemiological data to generate prevalence estimates.
FINDINGS: Of the 7.7 (95% uncertainty interval [UI], 7.4-8.1) million deaths among children and adolescents globally in 2013, 6.28 million occurred among younger children, 0.48 million among older children, and 0.97 million among adolescents. In 2013, the leading causes of death were lower respiratory tract infections among younger children (905.059 deaths; 95% UI, 810,304-998,125), diarrheal diseases among older children (38,325 deaths; 95% UI, 30,365-47,678), and road injuries among adolescents (115,186 deaths; 95% UI, 105,185-124,870). Iron deficiency anemia was the leading cause of years lived with disability among children and adolescents, affecting 619 (95% UI, 618-621) million in 2013. Large between-country variations exist in mortality from leading causes among children and adolescents. Countries with rapid declines in all-cause mortality between 1990 and 2013 also experienced large declines in most leading causes of death, whereas countries with the slowest declines had stagnant or increasing trends in the leading causes of death. In 2013, Nigeria had a 12% global share of deaths from lower respiratory tract infections and a 38% global share of deaths from malaria. India had 33% of the world's deaths from neonatal encephalopathy. Half of the world's diarrheal deaths among children and adolescents occurred in just 5 countries: India, Democratic Republic of the Congo, Pakistan, Nigeria, and Ethiopia.
CONCLUSIONS AND RELEVANCE: Understanding the levels and trends of the leading causes of death and disability among children and adolescents is critical to guide investment and inform policies. Monitoring these trends over time is also key to understanding where interventions are having an impact. Proven interventions exist to prevent or treat the leading causes of unnecessary death and disability among children and adolescents. The findings presented here show that these are underused and give guidance to policy makers in countries where more attention is needed.
METHODS: To estimate incidence and mortality for HIV, we used the UNAIDS Spectrum model appropriately modified based on a systematic review of available studies of mortality with and without antiretroviral therapy (ART). For concentrated epidemics, we calibrated Spectrum models to fit vital registration data corrected for misclassification of HIV deaths. In generalised epidemics, we minimised a loss function to select epidemic curves most consistent with prevalence data and demographic data for all-cause mortality. We analysed counterfactual scenarios for HIV to assess years of life saved through prevention of mother-to-child transmission (PMTCT) and ART. For tuberculosis, we analysed vital registration and verbal autopsy data to estimate mortality using cause of death ensemble modelling. We analysed data for corrected case-notifications, expert opinions on the case-detection rate, prevalence surveys, and estimated cause-specific mortality using Bayesian meta-regression to generate consistent trends in all parameters. We analysed malaria mortality and incidence using an updated cause of death database, a systematic analysis of verbal autopsy validation studies for malaria, and recent studies (2010-13) of incidence, drug resistance, and coverage of insecticide-treated bednets.
FINDINGS: Globally in 2013, there were 1·8 million new HIV infections (95% uncertainty interval 1·7 million to 2·1 million), 29·2 million prevalent HIV cases (28·1 to 31·7), and 1·3 million HIV deaths (1·3 to 1·5). At the peak of the epidemic in 2005, HIV caused 1·7 million deaths (1·6 million to 1·9 million). Concentrated epidemics in Latin America and eastern Europe are substantially smaller than previously estimated. Through interventions including PMTCT and ART, 19·1 million life-years (16·6 million to 21·5 million) have been saved, 70·3% (65·4 to 76·1) in developing countries. From 2000 to 2011, the ratio of development assistance for health for HIV to years of life saved through intervention was US$4498 in developing countries. Including in HIV-positive individuals, all-form tuberculosis incidence was 7·5 million (7·4 million to 7·7 million), prevalence was 11·9 million (11·6 million to 12·2 million), and number of deaths was 1·4 million (1·3 million to 1·5 million) in 2013. In the same year and in only individuals who were HIV-negative, all-form tuberculosis incidence was 7·1 million (6·9 million to 7·3 million), prevalence was 11·2 million (10·8 million to 11·6 million), and number of deaths was 1·3 million (1·2 million to 1·4 million). Annualised rates of change (ARC) for incidence, prevalence, and death became negative after 2000. Tuberculosis in HIV-negative individuals disproportionately occurs in men and boys (versus women and girls); 64·0% of cases (63·6 to 64·3) and 64·7% of deaths (60·8 to 70·3). Globally, malaria cases and deaths grew rapidly from 1990 reaching a peak of 232 million cases (143 million to 387 million) in 2003 and 1·2 million deaths (1·1 million to 1·4 million) in 2004. Since 2004, child deaths from malaria in sub-Saharan Africa have decreased by 31·5% (15·7 to 44·1). Outside of Africa, malaria mortality has been steadily decreasing since 1990.
INTERPRETATION: Our estimates of the number of people living with HIV are 18·7% smaller than UNAIDS's estimates in 2012. The number of people living with malaria is larger than estimated by WHO. The number of people living with HIV, tuberculosis, or malaria have all decreased since 2000. At the global level, upward trends for malaria and HIV deaths have been reversed and declines in tuberculosis deaths have accelerated. 101 countries (74 of which are developing) still have increasing HIV incidence. Substantial progress since the Millennium Declaration is an encouraging sign of the effect of global action.
FUNDING: Bill & Melinda Gates Foundation.
METHODS: We used robust statistical methods including the Cause of Death Ensemble model (CODEm) to analyse a database of data for 7065 site-years and estimate the number of maternal deaths from all causes in 188 countries between 1990 and 2013. We estimated the number of pregnancy-related deaths caused by HIV on the basis of a systematic review of the relative risk of dying during pregnancy for HIV-positive women compared with HIV-negative women. We also estimated the fraction of these deaths aggravated by pregnancy on the basis of a systematic review. To estimate the numbers of maternal deaths due to nine different causes, we identified 61 sources from a systematic review and 943 site-years of vital registration data. We also did a systematic review of reports about the timing of maternal death, identifying 142 sources to use in our analysis. We developed estimates for each country for 1990-2013 using Bayesian meta-regression. We estimated 95% uncertainty intervals (UIs) for all values.
FINDINGS: 292,982 (95% UI 261,017-327,792) maternal deaths occurred in 2013, compared with 376,034 (343,483-407,574) in 1990. The global annual rate of change in the MMR was -0·3% (-1·1 to 0·6) from 1990 to 2003, and -2·7% (-3·9 to -1·5) from 2003 to 2013, with evidence of continued acceleration. MMRs reduced consistently in south, east, and southeast Asia between 1990 and 2013, but maternal deaths increased in much of sub-Saharan Africa during the 1990s. 2070 (1290-2866) maternal deaths were related to HIV in 2013, 0·4% (0·2-0·6) of the global total. MMR was highest in the oldest age groups in both 1990 and 2013. In 2013, most deaths occurred intrapartum or postpartum. Causes varied by region and between 1990 and 2013. We recorded substantial variation in the MMR by country in 2013, from 956·8 (685·1-1262·8) in South Sudan to 2·4 (1·6-3·6) in Iceland.
INTERPRETATION: Global rates of change suggest that only 16 countries will achieve the MDG 5 target by 2015. Accelerated reductions since the Millennium Declaration in 2000 coincide with increased development assistance for maternal, newborn, and child health. Setting of targets and associated interventions for after 2015 will need careful consideration of regions that are making slow progress, such as west and central Africa.
FUNDING: Bill & Melinda Gates Foundation.
METHODS: Using a self-administered Menopause Quick-6 in the Malay language (MQ6[M]) questionnaire, we surveyed 349 women aged 40-60 years attending primary healthcare clinics in four states in Malaysia for their menopause symptoms. Health-seeking behaviors for menopause symptoms were assessed using questions regarding HCPs consulted and treatments prescribed. Binary logistic regression was employed on factors associated with seeking consultation for menopause symptoms.
RESULTS: Using MQ6(M), we observed that 125 (31.3%) women reported at least one menopause symptom, with joint pains (42.8%), menstrual changes (39.5%), and hot flashes (29.3%) being the most frequent symptoms. Furthermore, 60% of the women were prescribed vitamins, and only 13% were administered Hormone Replacement Therapy (HRT). Medical comorbidities, the presence of at least one gynecological condition, menopause status, and MQ6(M) score were associated with seeking consultation with an HCP. For women with medical conditions, the odds of seeking consultation increased by a factor of 1.34 (adjusted odds ratio [AOR], 1.34; 95% confidence interval [CI], 1.11-1.76) for every additional comorbidity. The odds of seeking consultation from an HCP increased by a factor of 1.26 (AOR, 1.26; 95% CI, 1.04-1.47) with a unit increase in MQ6(M) score.
CONCLUSIONS: Most women had menopause symptoms but favored the use of complementary and alternative medicine over HRT. Screening and awareness of menopause treatments need to be improved at primary healthcare clinics.
PARTICIPANTS AND METHODS: We conducted online in-depth interviews among seven house officers using an interview guide developed based on a literature review. The transcripts were analyzed. Major themes were identified. A 33-item questionnaire was developed, and the main and sub-themes were identified as motivators for specialist career choice. An online survey was done among 185 house officers. Content validation of motivators for specialist choice was done using exploratory factor analysis. First, second and third choices for a specialist career were identified. Multinomial logistic regression analyses were done to determine the socio-demographic factors and motivators associated with the first choice.
RESULTS: HOs perceived that specialist training opportunities provide a wide range of clinical competencies through well-structured, comprehensive training programs under existing specialist training pathways. Main challenges were limited local specialist training opportunities and hurdles for 'on-contract' HO to pursue specialist training. Motivators for first-choice specialty were related to 'work schedule', 'patient care characteristics', 'specialty characteristics', 'personal factors', 'past work experience', 'training factors', and 'career prospects.' House officers' first choices were specialties related to medicine (40.5%), surgery (31.5%), primary care (14.6%), and acute care (13.5%). On multivariate analysis, "younger age", "health professional in the family", "work schedule and personal factors", "career prospects" and "specialty characteristics" were associated with the first choice.
CONCLUSIONS: Medical and surgical disciplines were the most preferred disciplines and their motivators varied by individual discipline. Overall work experiences and career prospects were the most important motivators for the first-choice specialty. The information about motivational factors is helpful to develop policies to encourage more doctors to choose specialties with a shortage of doctors and to provide career specialty guidance.
METHODS: We analyzed 30 Malaysia-based retailer websites using a mixed methods approach. Data were extracted as the frequency of occurrences of marketing claims, presence of regulatory information, product types, and flavors of e-juice as per a predefined codebook based on published literature. We also extracted textual details published on the websites about marketing claims, and slogans.
RESULTS: Most retailer websites provided contact information and physical store addresses (83%) but only half had 'click through' age verification (57%) that seldom needed any identification proof for age (3%). Marketing claims were related to health (47%), smoking cessation (37%), and modernity/trend (37%) and none had health warnings. Promotional strategies were discounts (80%). starter kits (57%) and email subscriptions (53%). Product types displayed were rechargeable (97%) and disposable (87%) devices and e-liquids (90%) of an array of flavors (> 100). Nicotine presence, its concentration, and "nicotine is an addictive chemical" were displayed in 93%, 53%, and 23% of websites respectively.
CONCLUSION: Surveillance of content displayed online on e-cigarette retailer websites and regulation of online marketing and sales should be implemented by the Ministry of Health, Malaysia. Such measures are needed to prevent access to, and initiation of e-cigarette use among the youth and adults who do not smoke.