Mortality patterns in Vietnam, 2006: Findings from a national verbal autopsy survey

<p>Abstract</p> <p>Background</p> <p>Accurate nationally representative statistics on total and cause-specific mortality in Vietnam are lacking due to incomplete capture in government reporting systems. This paper presents total and cause-specific mortality results from a national verbal autopsy survey conducted first time in Vietnam in conjunction with the annual population change survey and discusses methodological and logistical challenges associated with the implementation of a nation-wide assessment of mortality based on surveys.</p> <p>Verbal autopsy interviews, using the WHO standard questionnaire, were conducted with close relatives of the 6798 deaths identified in the 2007 population change survey in Vietnam. Data collectors were health staff recruited from the commune health station who undertook 3-day intensive training on VA interview. The Preston-Coale method assessed the level of completeness of mortality reporting from the population change survey. The number of deaths in each age-sex grouping is inflated according to the estimate of completeness to produce an <it>adjusted </it>number of deaths. Underlying causes of death were aggregated to the International Classification of Diseases Mortality Tabulation List 1. Leading causes of death were tabulated by sex for three broad age groups: 0-14 years; 15-59 years; and 60 years and above.</p> <p>Findings</p> <p>Completeness of mortality reporting was 69% for males and 54% for females with substantial regional variation. The use of VA has resulted in 10% of deaths being classified to ill-defined among males, and 15% among females. More ill-defined deaths were reported among the 60 year or above age group. Incomplete death reporting, wide geographical dispersal of deaths, extensive travel between households, and substantial variation in local responses to VA interviews challenged the implementation of a national mortality and cause of death assessment based on surveys.</p> <p>Conclusions</p> <p>Verbal autopsy can be a viable tool to identify cause of death in Vietnam. However logistical challenges limit its use in conjunction with the national sample survey. Sentinel population clusters for mortality surveillance should be tested to develop an effective and sustainable option for routine mortality and cause of death data collection in Vietnam.</p

Age-sex differences in the global burden of lower respiratory infections and risk factors, 1990-2019: results from the Global Burden of Disease Study 2019

Background The global burden of lower respiratory infections (LRIs) and corresponding risk factors in children older than 5 years and adults has not been studied as comprehensively as it has been in children younger than 5 years. We assessed the burden and trends of LRIs and risk factors across a groups by sex, for 204 countries and territories.Methods In this analysis of data for the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019, we used dinician-diagnosed pneumonia or bronchiolitis as our case definition for LRIs. We included International Classification of Diseases 9th edition codes 079.6, 466-469, 470.0, 480-482.8, 483.0-483.9, 484.1-484.2, 484.6-484.7, and 487-489 and International Classification of Diseases 10th edition codes A48.1, A70, B97.4 B97.6, 109-115.8, J16 J16.9, J20-121.9, J91.0, P23.0 P23.4, and U04 U04.9. We used the Cause of Death Ensemble modelling strategy to analyse 23109 site-years of vital r *stration data, 825 site-years of sample vital registration data, 1766 site-years of verbal autopsy data, and 681 site-years of mortality surveillance data. We used DisMod-MR 2.1, a Bayesian metaregression tool, to analyse age sex-specific incidence and prevalence data identified via systematic reviews of the literature, population-based survey data, and daims and inpatient data. Additio y, we estimated age sex-specific LRI mortality that is attributable to the independent effects of 14 risk factors.Findings Globally, in 2019, we estimated that there were 257 million (95% uncertainty interval [UI] 240-275) LRI incident episodes in males and 232 million (217-248) in females. In the same year, LRIs accounted for 1.30 million (95% UI 1.18-1.42) male deaths and 1.20 million (1.07-1.33) female deaths. Age-standardised incidence and mortality rates were 1.17 times (95% UI 1.16-1.18) and 1.31 times (95% UI 1.23-1.41) greater in males than in fe es in 2019. Between 1990 and 2019, LRI incidence and mortality rates declined at different rates across age groups and an increase in LRI episodes and deaths was estimated among all adult age groups, with males aged 70 years and older having the highest increase in LRI episodes (126.0% [95% UI 121.4-131.1]) and deaths (100.0% [83.4-115.9]). During the same period, LRI episodes and deaths in children younger than 15 years were estimated to have decreased, and the greatest dedine was observed for LRI deaths in males younger than 5 years (-70.7% [-77.2 to 61.8]). The leading risk factors for LRI mortality varied across age groups and sex. More than half of global LRI deaths in children younger than 5 years were attributable to child wasting (population attributable fraction [PAF] 53.0% [95% UI 37.7-61.8] in males and 56.4% [40.7-65.1] in females), and more than a quarter of LRI deaths among those aged 5-14 years were attributable to household air pollution (PAF 26.0% [95% UI 16.6-35.5] for males and PAF 25.8% [16.3-35.4] for females). PAFs of male LRI deaths attributed to smoking were 20.4% (95% UI 15.4-25.2) in those aged 15-49 years, 305% (24.1-36. 9) in those aged 50-69 years, and 21.9% (16. 8-27. 3) in those aged 70 years and older. PAFs of female LRI deaths attributed to household air pollution were 21.1% (95% UI 14.5-27.9) in those aged 15-49 years and 18 " 2% (12.5-24.5) in those aged 50-69 years. For females aged 70 years and older, the leading risk factor, ambient particulate matter, was responsible for 11-7% (95% UI 8.2-15.8) of LRI deaths.Interpretation The patterns and progress in reducing the burden of LRIs and key risk factors for mortality varied across age groups and sexes. The progress seen in children you - than 5 years was dearly a result of targeted interventions, such as vaccination and reduction of exposure to risk factors. Similar interventions for other age groups could contribute to the achievement of multiple Sustainable Development Goals targets, induding promoting wellbeing at all ages and reducing health inequalities. Interventions, including addressing risk factors such as child wasting, smoking, ambient particulate matter pollution, and household air pollution, would prevent deaths and reduce health disparities.Copyright 2022 The Author(s). Published by Elsevier Ltd

Rising rural body-mass index is the main driver of the global obesity epidemic in adults

Body-mass index (BMI) has increased steadily in most countries in parallel with a rise in the proportion of the population who live in cities(.)(1,2) This has led to a widely reported view that urbanization is one of the most important drivers of the global rise in obesity(3-6). Here we use 2,009 population-based studies, with measurements of height and weight in more than 112 million adults, to report national, regional and global trends in mean BMI segregated by place of residence (a rural or urban area) from 1985 to 2017. We show that, contrary to the dominant paradigm, more than 55% of the global rise in mean BMI from 1985 to 2017-and more than 80% in some low- and middle-income regions-was due to increases in BMI in rural areas. This large contribution stems from the fact that, with the exception of women in sub-Saharan Africa, BMI is increasing at the same rate or faster in rural areas than in cities in low- and middle-income regions. These trends have in turn resulted in a closing-and in some countries reversal-of the gap in BMI between urban and rural areas in low- and middle-income countries, especially for women. In high-income and industrialized countries, we noted a persistently higher rural BMI, especially for women. There is an urgent need for an integrated approach to rural nutrition that enhances financial and physical access to healthy foods, to avoid replacing the rural undernutrition disadvantage in poor countries with a more general malnutrition disadvantage that entails excessive consumption of low-quality calories