Cause-specific neonatal mortality: analysis of 3772 neonatal deaths in Nepal, Bangladesh, Malawi and India.
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ABSTRACT: Objective
Understanding the causes of death is key to tackling the burden of three million annual neonatal deaths. Resource-poor settings lack effective vital registration systems for births, deaths and causes of death. We set out to describe cause-specific neonatal mortality in rural areas of Malawi, Bangladesh, Nepal and rural and urban India using verbal autopsy (VA) data.Design
We prospectively recorded births, neonatal deaths and stillbirths in seven population surveillance sites. VAs were carried out to ascertain cause of death. We applied descriptive epidemiological techniques and the InterVA method to characterise the burden, timing and causes of neonatal mortality at each site.Results
Analysis included 3772 neonatal deaths and 3256 stillbirths. Between 63% and 82% of neonatal deaths occurred in the first week of life, and males were more likely to die than females. Prematurity, birth asphyxia and infections accounted for most neonatal deaths, but important subnational and regional differences were observed. More than one-third of deaths in urban India were attributed to asphyxia, making it the leading cause of death in this setting.Conclusions
Population-based VA methods can fill information gaps on the burden and causes of neonatal mortality in resource-poor and data-poor settings. Local data should be used to inform and monitor the implementation of interventions to improve newborn health. High rates of home births demand a particular focus on community interventions to improve hygienic delivery and essential newborn care.
SUBMITTER: Fottrell E
PROVIDER: S-EPMC4552925 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundIn poor settings, where many births and neonatal deaths occur at home, prediction models of neonatal mortality in the general population can aid public-health policy-making. No such models are available in the international literature. We developed and validated a prediction model for neonatal mortality in the general population in India, Nepal and Bangladesh.MethodsUsing data (49?632 live births, 1742 neonatal deaths) from rural and urban surveillance sites in South Asia, we developed regression models to predict the risk of neonatal death with characteristics known at (i) the start of pregnancy, (ii) start of delivery and (iii) 5?minutes post partum. We assessed the models' discriminative ability by the area under the receiver operating characteristic curve (AUC), using cross-validation between sites.ResultsAt the start of pregnancy, predictive ability was moderate {AUC 0.59 [95% confidence interval (CI) 0.58-0.61]} and predictors of neonatal death were low maternal education and economic status, short birth interval, primigravida, and young and advanced maternal age. At the start of delivery, predictive ability was considerably better [AUC 0.73 (95% CI 0.70-0.76)] and prematurity and multiple pregnancy were strong predictors of death. At 5?minutes post partum, predictive ability was good [AUC: 0.85 (95% CI 0.80-0.89)]; very strong predictors were multiple birth, prematurity and a poor condition of the infant at 5?minutes.ConclusionsWe developed good performing prediction models for neonatal mortality. Neonatal deaths are highly concentrated in a small group of high-risk infants, even in poor settings in South Asia. Risk assessment, as supported by our models, can be used as a basis for improving community- and facility-based newborn care and prevention strategies in poor settings.
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Project description: Not available
| S-EPMC10510889 | biostudies-literature
Project description:BackgroundIncreasing mortality among men from drugs, alcohol and suicides is a growing public health concern in many countries. Collectively known as "deaths of despair", they are seen to stem from unprecedented economic pressures and a breakdown in social support structures.MethodsWe use high-quality population wide Scottish data to calculate directly age-standardized mortality rates for men aged 15-44 between 1980 and 2018 for 15 leading causes of mortality. Absolute and relative inequalities in mortality by cause are calculated using small-area deprivation and the slope and relative indices of inequality (SII and RIIL) for the years 2001-2018.ResultsSince 1980 there have been only small reductions in mortality among men aged 15-44 in Scotland. In that period drug-related deaths have increased from 1.2 (95% CI 0.7-1.4) to 44.9 (95% CI 42.5-47.4) deaths per 100,000 and are now the leading cause of mortality. Between 2001 and 2018 there have been small reductions in absolute but not in relative inequalities in all-cause mortality. However, absolute inequalities in mortality from drugs have doubled from SII = 66.6 (95% CI 61.5-70.9) in 2001-2003 to SII = 120.0 (95% CI 113.3-126.8) in 2016-2018. Drugs are the main contributor to inequalities in mortality, and together with alcohol harm and suicides make up 65% of absolute inequalities in mortality.ConclusionsContrary to the substantial reductions in mortality across all ages in the past decades, deaths among young men are increasing from preventable causes. Attempts to reduce external causes of mortality have focused on a single cause of death and not been effective in reducing mortality or inequalities in mortality from external causes in the long-run. To reduce deaths of despair, action should be taken to address social determinants of health and reduce socioeconomic inequalities.
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Project description:Bangladesh has achieved remarkable gains in health indicators during the last four decades despite low levels of economic development. However, the persistence of inequities remains disturbing. This success was also accompanied by health and demographic transitions, which in turn brings new challenges for a nation that has yet to come to terms with pre-transition health challenges. It is therefore important to understand the causes of death and their relationship with socioeconomic status (SES).The paper aims to assess the causes of death by SES based on surveillance data from a rural area of Bangladesh, in order to understand the situation and inform policy makers and programme leaders.We analysed population-based mortality data collected from the Chakaria Health and Demographic Surveillance System in Bangladesh. The causes of death were determined by using a Bayesian-based programme for interpreting verbal autopsy findings (InterVA-4). The data included 1,391 deaths in 217,167 person-years of observation between 2010 and 2012. The wealth index constructed using household assets was used to assess the SES, and disease burdens were compared among the wealth quintiles.Analysing cause of death (CoD) revealed that non-communicable diseases (NCDs) were the leading causes of deaths (37%), followed by communicable diseases (CDs) (22%), perinatal and neonatal conditions (11%), and injury and accidents (6%); the cause of remaining 24% of deaths could not be determined. Age-specific mortality showed premature birth, respiratory infections, and drowning were the dominant causes of death for childhood mortality (0-14 years), which was inversely associated with SES (p<0.04). For adult and the elderly (15 years and older), NCDs were the leading cause of death (51%), followed by CDs (23%). For adult and the elderly, NCDs concentrated among the population from higher SES groups (p<0.005), and CDs among the lower SES groups (p<0.001).Epidemiologic transition is taking place with a shift from the dominance of CDs to NCDs. SES inequity in mortality still persists--the poor suffer from CDs in all age groups, whereas those better off suffer more from NCDs than CDs. Policy makers thus need to consider the social distribution of diseases before developing any public health action targeted towards reducing mortality and the extent of disease burden in an equitable manner.
| S-EPMC4220129 | biostudies-literature
Project description:BackgroundResearch from various countries has shown increases in alcohol- and drug-related deaths and suicide, known as 'deaths of despair' over recent decades, particularly among low-educated middle-aged individuals. However, little is known about trends in death-of-despair causes in Spain. Therefore, we aim to descriptively examine this among 25-64-year-olds from 1980 to 2019 and by educational attainment for the years 2017-19.MethodsWe obtained mortality and population data from the National Institute of Statistics to estimate age-standardized mortality rates and assess educational inequalities using the relative index of inequality (RII).ResultsDeaths of despair as a share of total mortality slightly increased from 2000 onwards, particularly among 25-64-year-old men (from 9 to 10%). Only alcohol-related mortality declined relatively more since 1980 compared with all-cause mortality. Regarding educational differences, low-educated men presented higher mortality rates in all death-of-despair causes (alcohol-related: RII 3.54 (95% CI: 2.21-5.66); drug-related: RII 3.49 (95% CI: 1.80-6.77); suicide: RII 1.97 (95% CI: 1.49-2.61)). Women noteworthy differences were only observed for alcohol-related (RII 3.50 (95% CI: 2.13-5.75)).ConclusionsFindings suggest an increasing proportion of deaths of despair among 25-64-year-olds since 2000, particularly among men. Public health policies are needed to reduce and prevent these premature and preventable causes of mortality.
| S-EPMC10687877 | biostudies-literature
Project description:BACKGROUND:Almost all countries without complete vital registration systems have data on deaths collected by hospitals. However, these data have not been widely used to estimate cause of death (COD) patterns in populations because only a non-representative fraction of people in these countries die in health facilities. Methods that can exploit hospital mortality statistics to reliably estimate community COD patterns are required to strengthen the evidence base for disease and injury control programs. We propose a method that weights hospital-certified causes by the probability of death to estimate population cause-specific mortality fractions (CSMFs). METHODS:We used an established verbal autopsy instrument (VAI) to collect data from hospital catchment areas in Chandpur and Comilla Districts, Bangladesh, and Bohol province, the Philippines, between 2011 and 2014, along with demographic covariates for each death. Hospital medical certificates of cause of death (death certificates) were collected and mapped to the corresponding cause categories of the VAI. Tariff 2.0 was used to assign a COD for community deaths. Logistic regression models were created for broad causes in each country to calculate the probability of in-hospital death, given a set of covariate values. The reweighted CSMFs for deaths in the hospital catchment population, represented by each hospital death, were calculated from the corresponding regression models. RESULTS:We collected data on 4228 adult deaths in the Philippines and 3725 deaths in Bangladesh. Short time to hospital and education were consistently associated with in-hospital death in the Philippines and absence of a disability was consistently associated with in-hospital death in Bangladesh. Non-communicable diseases (excluding stroke) and stroke were the leading causes of death in both the Philippines (33.9%, 19.1%) and Bangladesh (46.1%, 21.1%) according to the reweighted method. The reweighted method generally estimated CSMFs that fell between those derived from hospitals and those diagnosed by Tariff 2.0. CONCLUSIONS:Statistical methods can be used to derive estimates of cause-specific probability of death in-hospital for Bangladesh and the Philippines to generate population CSMFs. In regions where hospital death certification is of reasonable quality and routine verbal autopsy is not applied, these estimates could be applied to generate cost-effective and robust CSMFs for the population.
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Project description:BackgroundThe persistence of preventable maternal and newborn deaths highlights the importance of quality of care as an essential element in coverage interventions. Moving beyond the conventional measurement of crude coverage, we estimated effective coverage of facility delivery by adjusting for facility preparedness to provide delivery services in Bangladesh, Haiti, Malawi, Nepal, Senegal, and Tanzania.MethodsThe study uses data from Demographic and Health Surveys (DHS) and Service Provision Assessments (SPA) in Bangladesh (2014 DHS and 2014 SPA), Haiti (2012 DHS and 2013 SPA), Malawi (2015-16 DHS and 2013-14 SPA), Nepal (2016 DHS and 2015 SPA), Senegal (2016 DHS and 2015 SPA), and Tanzania (2015-16 DHS and 2014-15 SPA). We defined effective coverage as the mathematical product of crude coverage and quality of care. The coverage of facility delivery was measured with DHS data and quality of care was measured with facility data from SPA. We estimated effective coverage at both the regional and the national level and accounted for type of facility where delivery care was sought.FindingsThe findings from the six countries indicate the effective coverage ranges from 24% in Haiti to 66% in Malawi, representing substantial reductions (20% to 39%) from crude coverage rates. Although Malawi has achieved almost universal coverage of facility delivery (93%), effective coverage was only 66%.vSuch gaps between the crude coverage and the effective coverage suggest that women delivered in health facility but did not necessarily receive an adequate quality of care. In all countries except Malawi, effective coverage differed substantially among the country's regions of the country, primarily due to regional variability in coverage.InterpretationOur findings reinforce the importance of quality of obstetric and newborn care to achieve further reduction of maternal and newborn mortality. Continued efforts are needed to increase the use of facility delivery service in countries or regions where coverage remains low.
| S-EPMC6559642 | biostudies-literature
Project description:BackgroundDocumentation of the demographic and geographical details of changes in cause-specific neonatal (younger than 1 month) and 1-59-month mortality in India can guide further progress in reduction of child mortality. In this study we report the changes in cause-specific child mortality between 2000 and 2015 in India.MethodsSince 2001, the Registrar General of India has implemented the Million Death Study (MDS) in 1·3 million homes in more than 7000 randomly selected areas of India. About 900 non-medical surveyors do structured verbal autopsies for deaths recorded in these homes. Each field report is assigned randomly to two of 404 trained physicians to classify the cause of death, with a standard process for resolution of disagreements. We combined the proportions of child deaths according to the MDS for 2001-13 with annual UN estimates of national births and deaths (partitioned across India's states and rural or urban areas) for 2000-15. We calculated the annual percentage change in sex-specific and cause-specific mortality between 2000 and 2015 for neonates and 1-59-month-old children.FindingsThe MDS captured 52 252 deaths in neonates and 42 057 deaths at 1-59 months. Examining specific causes, the neonatal mortality rate from infection fell by 66% from 11·9 per 1000 livebirths in 2000 to 4·0 per 1000 livebirths in 2015 and the rate from birth asphyxia or trauma fell by 76% from 9·0 per 1000 livebirths in 2000 to 2·2 per 1000 livebirths in 2015. At 1-59 months, the mortality rate from pneumonia fell by 63% from 11·2 per 1000 livebirths in 2000 to 4·2 per 1000 livebirths in 2015 and the rate from diarrhoea fell by 66% from 9·4 per 1000 livebirths in 2000 to 3·2 per 1000 livebirths in 2015 (with narrowing girl-boy gaps). The neonatal tetanus mortality rate fell from 1·6 per 1000 livebirths in 2000 to less than 0·1 per 1000 livebirths in 2015 and the 1-59-month measles mortality rate fell from 3·3 per 1000 livebirths in 2000 to 0·3 per 1000 livebirths in 2015. By contrast, mortality rates for prematurity or low birthweight rose from 12·3 per 1000 livebirths in 2000 to 14·3 per 1000 livebirths in 2015, driven mostly by increases in term births with low birthweight in poorer states and rural areas. 29 million cumulative child deaths occurred from 2000 to 2015. The average annual decline in mortality rates from 2000 to 2015 was 3·3% for neonates and 5·4% for children aged 1-59 months. Annual declines from 2005 to 2015 (3·4% decline for neonatal mortality and 5·9% decline in 1-59-month mortality) were faster than were annual declines from 2000 to 2005 (3·2% decline for neonatal mortality and 4·5% decline in 1-59-month mortality). These faster declines indicate that India avoided about 1 million child deaths compared with continuation of the 2000-05 declines.InterpretationTo meet the 2030 Sustainable Development Goals for child mortality, India will need to maintain the current trajectory of 1-59-month mortality and accelerate declines in neonatal mortality (to >5% annually) from 2015 onwards. Continued progress in reduction of child mortality due to pneumonia, diarrhoea, malaria, and measles at 1-59 months is feasible. Additional attention to low birthweight is required.FundingNational Institutes of Health, Disease Control Priorities Network, Maternal and Child Epidemiology Estimation Group, and University of Toronto.
| S-EPMC5677556 | biostudies-literature
Project description:BackgroundIn 2018, Pakistan had the world's highest neonatal mortality rate. Within Pakistan, most neonatal deaths occur in rural areas where access to health facilities is limited, and robust vital registration systems are lacking. To improve newborn survival, there is a need to better understand the causes of neonatal death in high burden settings and engage caregivers in the promotion of newborn health.ObjectiveTo describe the causes of neonatal death in a rural area in Pakistan and to estimate the effect of an integrated neonatal care kit (iNCK) on cause-specific neonatal mortality.MethodsWe analyzed data from a community-based, cluster-randomized controlled trial of 5286 neonates in Rahim Yar Khan (RYK), Punjab, Pakistan between April 2014 and August 2015. In intervention clusters, Lady Health Workers (LHW) delivered the iNCK and education on its use to pregnant women while control clusters received the local standard of care. The iNCK included interventions to prevent and identify signs of infection, identify low birthweight (LBW), and identify and manage hypothermia. Verbal autopsies were attempted for all deaths. The primary outcome was cause-specific neonatal mortality.ResultsVerbal autopsies were conducted for 84 (57%) of the 147 reported neonatal deaths. The leading causes of death were infection (44%), intrapartum-related complications (26%) and prematurity/LBW (20%). There were no significant differences in neonatal mortality due to prematurity/LBW (RR 0.43; 95% CI 0.15-1.24), infection (RR 1.10; 95% CI 0.58-2.10) or intrapartum-related complications (RR 1.04; 95% CI 0.0.45-2.41) among neonates who died in the intervention arm compared to those who died in the control arm.ConclusionThe major causes of neonatal deaths in RYK, Pakistan mirror the global landscape of neonatal deaths. The iNCK did not significantly reduce any cause-specific neonatal mortality.
| S-EPMC7480452 | biostudies-literature
Project description:OBJECTIVE:To examine cause-specific mortality beyond cardiovascular diseases (CVDs) in patients with gout compared to the general population. METHODS:We included all residents of Skåne (Sweden) age ?18 years in the year 2002. Using the Skåne Healthcare Register, we identified subjects with a new diagnosis of gout (2003-2013) and matched each person with gout with 10 comparators free of gout, by age and sex. We used information on the underlying cause of death from the Swedish Cause of Death Register (through December 31, 2014) to estimate hazard ratios (HRs, with 95% confidence intervals [95% CIs]) of mortality for specific causes of death in a multi-state Cox model, with adjustment for potential confounders. RESULTS:Among 832,258 persons, 19,497 had a new diagnosis of gout (32% women) and were matched with 194,947 comparators. Subjects with gout had higher prevalence of chronic kidney disease, metabolic disease, and CVD. Gout was associated with 17% increased hazard of all-cause mortality overall (HR 1.17 [95% CI 1.14-1.21]), 23% in women (HR 1.23 [95% CI 1.17-1.30]), and 15% in men (HR 1.15 [95% CI 1.10-1.19]). In terms of cause-specific mortality, the strongest associations were seen in the relationship of gout to the risk of death due to renal disease (HR 1.78 [95% CI 1.34-2.35]), diseases of the digestive system (HR 1.56 [95% 1.34-1.83]), CVD (HR 1.27 [95% CI 1.22-1.33]), infections (HR 1.20 [95% CI 1.06-1.35]), and dementia (HR 0.83 [95% CI 0.72-0.97]). CONCLUSION:Several non-CV causes of mortality are increased in persons with gout, emphasizing the need for improved management of comorbidities.
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