Identification of factors associated with stillbirth in the Indian state of Bihar using verbal autopsy: A population-based study.
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ABSTRACT:
SUBMITTER: Dandona R
PROVIDER: S-EPMC5538635 | biostudies-literature | 2017 Aug
REPOSITORIES: biostudies-literature
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Identification of factors associated with stillbirth in the Indian state of Bihar using verbal autopsy: A population-based study.
Dandona Rakhi R Kumar G Anil GA Kumar Amit A Singh Priyanka P George Sibin S Akbar Mohammad M Dandona Lalit L
PLoS medicine 20170801 8
<h4>Background</h4>India was estimated to have the largest numbers of stillbirths globally in 2015, and the Indian government has adopted a target of <10 stillbirths per 1,000 births by 2030 through the India Newborn Action Plan (INAP). The objective of this study was to use verbal autopsy interviews to examine factors associated with stillbirth in the Indian state of Bihar and make recommendations for the INAP to better inform the setting of priorities and actions to reduce stillbirths.<h4>Meth ...[more]
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Project description:BackgroundVerbal Autopsy (VA) is widely viewed as the only immediate strategy for registering cause of death in much of Africa and Asia, where routine physician certification of deaths is not widely practiced. VA involves a lay interview with family or friends after a death, to record essential details of the circumstances. These data can then be processed automatically to arrive at standardized cause of death information.MethodsThe Population Health Metrics Research Consortium (PHMRC) undertook a study at six tertiary hospitals in low- and middle-income countries which documented over 12,000 deaths clinically and subsequently undertook VA interviews. This dataset, now in the public domain, was compared with the WHO 2012 VA standard and the InterVA-4 interpretative model.ResultsThe PHMRC data covered 70% of the WHO 2012 VA input indicators, and categorized cause of death according to PHMRC definitions. After eliminating some problematic or incomplete records, 11,984 VAs were compared. Some of the PHMRC cause definitions, such as 'preterm delivery', differed substantially from the International Classification of Diseases, version 10 equivalent. There were some appreciable inconsistencies between the hospital and VA data, including 20% of the hospital maternal deaths being described as non-pregnant in the VA data. A high proportion of VA cases (66%) reported respiratory symptoms, but only 18% of assigned hospital causes were respiratory-related. Despite these issues, the concordance correlation coefficient between hospital and InterVA-4 cause of death categories was 0.61.ConclusionsThe PHMRC dataset is a valuable reference source for VA methods, but has to be interpreted with care. Inherently inconsistent cases should not be included when using these data to build other VA models. Conversely, models built from these data should be independently evaluated. It is important to distinguish between the internal and external validity of VA models. The effects of using tertiary hospital data, rather than the more usual application of VA to all-community deaths, are hard to evaluate. However, it would still be of value for VA method development to have further studies of population-based post-mortem examinations.
| S-EPMC3912496 | biostudies-literature
Project description:BACKGROUND: A substantial reduction in neonatal deaths is required in India to meet the Millennium Development Goal of a two-thirds reduction in child mortality by 2015. We report neonatal mortality estimates and utilisation of maternal care in the Indian state of Bihar. METHODS: A representative population-based sample of 14,293 women who had a live birth in the last 12 months based on multistage sampling from all 38 districts of Bihar was selected for interview in early 2012. We estimated neonatal mortality rate and its associations using multiple logistic regression, assessed maternal care coverage and its inequality by wealth index, and retention of mothers in the health system for the full sequence of maternal care services. RESULTS: Neonatal mortality rate for Bihar was 32.2 (95% confidence interval [CI] 27.6-36.8) per 1,000 live births. Postnatal care related variables were significantly associated with neonatal deaths - no delayed bathing of new born (odds ratio [OR] 3.45, 95% CI 2.47-4.81) and no kangaroo care immediately after birth (OR 2.20, 95% CI 1.49-3.25). History of maternal complications and delivery in a private sector health facility had nearly twice the odds of neonatal death; the latter was driven by the very high neonatal mortality associated with private facility delivery in the lower two wealth index quartiles. A pattern of mass deprivation was seen for coverage of 4 or more ANC visits, health facility delivery and postnatal care for the same woman, with only 5.2% of women receiving this overall; this coverage was low for the highest wealth index quartile as well at 12.2%. Coverage of 4 or more ANC visits was 7.4% and 27.7% in the lowest and the highest wealth quartiles, respectively. Giving birth in a health facility was reported by 49.5% of women in the lowest wealth index quartile and by 77.7% in the highest quartile. Only 21.2% women reported post-natal care within 2 weeks of delivery in the lowest wealth index quartile, and 42.2% in the highest quartile. CONCLUSIONS: Neonatal mortality continues to be relatively high in Bihar, and the utilization of maternal care very low and inequitable. Interventions need to address these deficiencies.
| S-EPMC4287469 | biostudies-literature
Project description:IntroductionEach year, more than 10 million children younger than five years of age die. The large majority of these deaths occur in the developing world. The verbal autopsy (VA) is a tool designed to ascertain cause of death in such settings. While VA has been validated against hospital diagnosed cause of death, there has been no research conducted to better understand the factors that may influence individual physicians in determining cause of death from VA.Methodology/principal findingsThis study uses data from over 27,000 neonatal and childhood deaths from The Million Death Study in which 6.3 million people in India were monitored for vital status between 1998 and 2003. The main outcome variable was physician agreement or disagreement of category of death and the variables were assessed for association using the kappa statistic, univariate and multivariate logistic regression using a conceptual hierarchical model, and a sensitivity and specificity analysis using the final VA category of mortality as the gold standard. The main variables found to be significantly associated with increased physician agreement included older ages and male gender of the deceased. When taking into account confounding factors in the multivariate analysis, we did not find consistent significant differences in physician agreement based on the death being in a rural or urban area, at home or in a health care facility, registered or not, or the respondent's gender, religion, relationship to the deceased, or whether or not the respondent lived with the deceased.Conclusions/significanceFactors influencing physician agreement/disagreement to the greatest degree are the gender and age of the deceased; specifically, physicians tend to be less likely to agree on a common category of death in female children and in younger ages, particularly neonates. Additional training of physician reviewers and continued adaptation of the VA itself, with a focus on gender and age of the deceased, may be useful in increasing rates of physician agreement in these groups.
| S-EPMC2833201 | biostudies-literature
Project description:Introduction98% of the 2.6 million stillbirths per annum occur in low and middle income countries. However, understanding of risk factors for stillbirth in these settings is incomplete, hampering efforts to develop effective strategies to prevent deaths.MethodsA cross-sectional study of eligible women on the postnatal ward at Mpilo Hospital, Zimbabwe was undertaken between 01/08/2018 and 31/03/2019 (n = 1779). Data were collected from birth records for maternal characteristics, obstetric and past medical history, antenatal care and pregnancy outcome. A directed acyclic graph was constructed with multivariable logistic regression performed to fit the corresponding model specification to data comprising singleton pregnancies, excluding neonatal deaths (n = 1734), using multiple imputation for missing data. Where possible, findings were validated against all women with births recorded in the hospital birth register (n = 1847).ResultsRisk factors for stillbirth included: previous stillbirth (29/1691 (2%) of livebirths and 39/43 (91%) of stillbirths, adjusted Odds Ratio (aOR) 2628.9, 95% CI 342.8 to 20,163.0), antenatal care (aOR 44.49 no antenatal care vs. > 4 antenatal care visits, 95% CI 6.80 to 291.19), maternal medical complications (aOR 7.33, 95% CI 1.99 to 26.92) and season of birth (Cold season vs. Mild aOR 14.29, 95% CI 3.09 to 66.08; Hot season vs. Mild aOR 3.39, 95% CI 0.86 to 13.27). Women who had recurrent stillbirth had a lower educational and health status (18.2% had no education vs. 10.0%) and were less likely to receive antenatal care (20.5% had no antenatal care vs. 6.6%) than women without recurrent stillbirth.ConclusionThe increased risk in women who have a history of stillbirth is a novel finding in Low and Middle Income Countries (LMICs) and is in agreement with findings from High Income Countries (HICs), although the estimated effect size is much greater (OR in HICs ~ 5). Developing antenatal care for this group of women offers an important opportunity for stillbirth prevention.
| S-EPMC8482658 | biostudies-literature
Project description:BACKGROUND:The India Newborn Action Plan (INAP) aims for < 10 stillbirths per 1000 births by 2030. A population-based understanding of risk factors for stillbirths compared with live births that could assist with reduction of stillbirths is not readily available for the Indian population. METHODS:Detailed interviews were conducted in a representative sample of all births between January and December 2016 from 182,486 households (96.2% participation) in 1657 clusters in the Indian state of Bihar. A stillbirth was defined as foetal death with gestation period of ≥ 7 months wherein the foetus did not show any sign of life. The association of stillbirth was investigated with a variety of risk factors among all births using a hierarchical logistic regression model approach. RESULTS:A total of 23,940 births including 338 stillbirths were identified giving the state stillbirth rate (SBR) of 15.4 (95% CI 13.2-17.9) per 1000 births, with no difference in SBR by sex. Antepartum and intrapartum SBR was 5.6 (95% CI 4.3-7.2) and 4.5 (95% CI 3.3-6.1) per 1000 births, respectively. Detailed interview was available for 20,152 (84.2% participation) births including 275 stillbirths (81.4% participation). In the final regression model, significantly higher odds of stillbirth were documented for deliveries with gestation period of ≤ 8 months (OR 11.36, 95% CI 8.13-15.88), for first born (OR 5.79, 95% CI 4.06-8.26), deferred deliveries wherein a woman was sent back home and asked to come later for delivery by a health provider (OR 5.51, 95% CI 2.81-10.78), and in those with forceful push/pull during the delivery by the health provider (OR 4.85, 95% CI 3.39-6.95). The other significant risk factors were maternal age ≥ 30 years (OR 3.20, 95% CI 1.52-6.74), pregnancies with multiple foetuses (OR 2.82, 95% CI 1.49-5.33), breech presentation of the baby (OR 2.70, 95% CI 1.75-4.18), and births in private facilities (OR 1.75, 95% CI 1.19-2.56) and home (OR 2.60, 95% CI 1.87-3.62). Varied risk factors were associated with antepartum and intrapartum stillbirths. Birth weight was available only for 40 (14.5%) stillborns. Among the facility deliveries, the women who were referred from one facility to another for delivery had significantly high odds of stillbirth (OR 3.32, 95% CI 2.03-5.43). CONCLUSIONS:We found an increased risk of stillbirths in deferred and referred deliveries in addition to demographic and clinical risk factors for antepartum and intrapartum stillbirths, highlighting aspects of health care that need attention in addition to improving skills of health providers to reduce stillbirths. The INAP could utilise these findings to further strengthen its approach to meet the stillbirth reduction target by 2030.
| S-EPMC6366028 | biostudies-literature
Project description:BackgroundIn a range of setting, detecting and generate empirical information on the cause of infant death and contributing risk factors at population level is basically utmost essential to take evidence-based measures in reducing infant morbidity and mortality. An electronic verbal autopsy is suitable tool and best alternative solution to determine individuals' cause of death in a setting where the majority of deaths occur at home and civil registration systems do not exist. The present study was undertaken to find out cause of infant death, applying computer-based probabilistic model (InterVA-4) and analyze the patterns of association factors of mother's and the deceased infant's characteristics to the leading cause-specific infant mortality in Eastern Ethiopia.MethodsThe study employed a community-based prospective longitudinal survey, which was conducted with routinely enumeration of reported infant deaths for a period of two years (from September 2016 to August 2018) in Eastern part of Ethiopia. Using the two-stage cluster sampling technique, the study was undertaken in four randomly selected districts of West Hararghe zone and two districts of zone 3 in Oromia and Afar regional state, respectively. The study included a total of 362 infants who were deceased during the study period. Data was collected by trained enumerators by interviewing the mothers or guardians of the deceased infant using a 2014 standardize World Health Organization (WHO) Verbal Autopsy questionnaire. InterVA-4 model were used for processing and interpreting verbal autopsy data in order to arrive at the most likely causes of infant death. SPSS version 23 was also used for statistical analysis of frequency distribution and logistic regression for the association between covariates and outcomes.FindingsOf the overall (362) deceased infants' during the study period, 53.0% of deaths occurred during neonatal time while 47.0% died in the post-neonatal period. Acute respiratory infection including neonatal and post-neonatal pneumonia (38.4%), birth asphyxia (16.4%), diarrheal diseases (16.3%), prematurity (7.4%) and malaria (4.3%) were found to be the leading causes of infant mortality in the study area. The independent factors strongly associated with probable ARI, including pneumonia related mortality as compared to all-causes of death were infants with maternal age lower than 20 years old (p = 0.001, AOR: 4.82, 95% CI: 1.88, 12.3) and infant being died outside of heath facilities (P = 0.007, AOR: 2.85, 95% CI: 1.33, 6.12). The post-neonatal period (P = 0.000, AOR: 15.5, 95% CI: 6.35, 37.8) and infant died in the wet season (P = 0.006, AOR: 2.38, 95% CI: 1.28, 4.44) had strong relationship with dying from diarrhea-related death than those infants died from all non-diarrhea. The death due to malaria robustly associated with infants whose mothers age between 20-35 years old (P = 0.024, AOR: 4.44, 95% CI: 1.22, 16.2) and infant who was dwelled in the districts of Afar region (P = 0.013, AOR: 4.08, 95% CI: 1.35, 12.4).ConclusionThe highest cause of infant mortality was associated with disease of respiratory system, particularly acute respiratory infection, including both neonates and post-neonatal pneumonia. Most of the infant deaths existed are as a result of diseases and conditions that are readily preventable or treatable cause, similar to those reported in worldwide, which have needs of further attention. The patterns of significant associated factors across cause-specific mortality against all-cause of death were dissimilar. Therefore, strengthen maternal and child health program with effective preventive interventions emphasizing on the most common cause of infant deaths and those factors contributing in raising mortality risk are required.
| S-EPMC9352103 | biostudies-literature
Project description:ObjectiveTo estimate and evaluate the cause-of-death structure and disease-specific mortality rates in a rural area of The Gambia as determined using the InterVA-4 model.DesignDeaths and person-years of observation were determined by age group for the population of the Farafenni Health and Demographic Surveillance area from January 1998 to December 2007. Causes of death were determined by verbal autopsy (VA) using the InterVA-4 model and ICD-10 disease classification. Assigned causes of death were classified into six broad groups: infectious and parasitic diseases; cancers; other non-communicable diseases; neonatal; maternal; and external causes. Poisson regression was used to estimate age and disease-specific mortality rates, and likelihood ratio tests were used to determine statistical significance.ResultsA total of 3,203 deaths were recorded and VA administered for 2,275 (71%). All-age mortality declined from 15 per 1,000 person-years in 1998-2001 to 8 per 1,000 person-years in 2005-2007. Children aged 1-4 years registered the most marked (74%) decline from 27 to 7 per 1,000 person-years. Communicable diseases accounted for half (49.9%) of the deaths in all age groups, dominated by acute respiratory infections (ARI) (13.7%), malaria (12.9%) and pulmonary tuberculosis (10.2%). The leading causes of death among infants were ARI (5.59 per 1,000 person-years [95% CI: 4.38-7.15]) and malaria (4.11 per 1,000 person-years [95% CI: 3.09-5.47]). Mortality rates in children aged 1-4 years were 3.06 per 1,000 person-years (95% CI: 2.58-3.63) for malaria, and 1.05 per 1,000 person-years (95% CI: 0.79-1.41) for ARI. The HIV-related mortality rate in this age group was 1.17 per 1,000 person-years (95% CI: 0.89-1.54). Pulmonary tuberculosis and communicable diseases other than malaria, HIV/AIDS and ARI were the main killers of adults aged 15 years and over. Stroke-related mortality increased to become the leading cause of death among the elderly aged 60 years or more in 2005-2007.ConclusionsMortality in the Farafenni HDSS area was dominated by communicable diseases. Malaria and ARI were the leading causes of death in the general population. In addition to these, diarrhoeal disease was a particularly important cause of death among children under 5 years of age, as was pulmonary tuberculosis among adults aged 15 years and above.
| S-EPMC4220164 | biostudies-literature
Project description:BackgroundThe objectives of this study were to understand the differences in mortality rate, risk factors for mortality, and cause of death distribution in three neonatal age sub-groups (0-2, 3-7, and 8-27 days) and assess the change in mortality rate with previous assessments to inform programmatic decision-making in the Indian state of Bihar, a large state with a high burden of newborn deaths.MethodsDetailed interviews were conducted in a representative sample of 23,602 live births between January and December 2016 (96.2% participation) in Bihar state. We estimated the neonatal mortality rate (NMR) for the three age sub-groups and explored the association of these deaths with a variety of risk factors using a hierarchical logistic regression model approach. Verbal autopsies were conducted using the PHMRC questionnaire and the cause of death assigned using the SmartVA automated algorithm. Change in NMR from 2011 to 2016 was estimated by comparing it with a previous assessment.ResultsThe NMR 0-2-day, 3-7-day, and 8-27-day mortality estimates in 2016 were 24.7 (95% CI 21.8-28.0), 13.2 (11.1 to 15.7), 5.8 (4.4 to 7.5), and 5.8 (4.5 to 7.5) per 1000 live births, respectively. A statistically significant reduction of 23.3% (95% CI 9.2% to 37.3) was seen in NMR from 2011 to 2016, driven by a reduction of 35.3% (95% CI 18.4% to 52.2) in 0-2-day mortality. In the final regression model, the highest odds for mortality in 0-2 days were related to the gestation period of ≤ 8 months (OR 16.5, 95% CI 11.9-22.9) followed by obstetric complications, no antiseptic cord care, and delivery at a private health facility or home. The 3-7- and 8-27-day mortality was driven by illness in the neonatal period (OR 10.33, 95% CI 6.31-16.90, and OR 4.88, 95% CI 3.13-7.61, respectively) and pregnancy with multiple foetuses (OR 5.15, 95% CI 2.39-11.10, and OR 11.77, 95% CI 6.43-21.53, respectively). Birth asphyxia (61.1%) and preterm delivery (22.1%) accounted for most of 0-2-day deaths; pneumonia (34.5%), preterm delivery (33.7%), and meningitis/sepsis (20.1%) accounted for the majority of 3-7-day deaths; meningitis/sepsis (30.6%), pneumonia (29.1%), and preterm delivery (26.2%) were the leading causes of death at 8-27 days.ConclusionsTo our knowledge, this is the first study to report a detailed neonatal epidemiology by age sub-groups for a major Indian state, which has highlighted the distinctly different mortality rate, risk factors, and causes of death at 0-2 days versus the rest of the neonatal period. Monitoring mortality at 0-2 and 3-7 days separately in the traditional early neonatal period of 0-7 days would enable more effective programming to reduce neonatal mortality.
| S-EPMC6639919 | biostudies-literature
Project description:BackgroundHousehold surveys remain important sources of maternal and child health data, but until now, standard surveys such as Demographic and Health Surveys (DHS) have not collected information on maternity care for women who have experienced a stillbirth. Thus, nationally representative data are lacking to inform programmes to address the millions of stillbirths which occur annually.MethodsThe EN-INDEPTH population-based survey of women of reproductive age was undertaken in five Health and Demographic Surveillance System sites in Bangladesh, Ethiopia, Ghana, Guinea-Bissau and Uganda (2017-2018). All women answered a full birth history with additional questions on pregnancy losses (FBH+) or full pregnancy history (FPH). A sub-sample, including all women reporting a recent stillbirth or neonatal death, was asked additional maternity care questions. These were evaluated using descriptive measures. Associations between stillbirth and maternal socio-demographic characteristics, babies' characteristics and maternity care use were assessed using a weighted logistic regression model for women in the FBH+ group.ResultsA total of 15,591 women reporting a birth since 1 January 2012 answered maternity care questions. Completeness was very high (> 99%), with similar proportions of responses for both live and stillbirths. Amongst the 14,991 births in the FBH+ group, poorer wealth status, higher parity, large perceived baby size-at-birth, preterm or post-term birth, birth in a government hospital compared to other locations and vaginal birth were associated with increased risk of stillbirth after adjusting for potential confounding factors. Regarding association with reported postnatal care, women with a stillbirth were more likely to report hospital stays of > 1 day. However, women with a stillbirth were less likely to report having received a postnatal check compared to those with a live birth.ConclusionsWomen who had experienced stillbirth were able to respond to questions about pregnancy and birth, and we found no reason to omit questions to these women in household surveys. Our analysis identified several potentially modifiable factors associated with stillbirth, adding to the evidence-base for policy and action in low- and middle-income contexts. Including these questions in DHS-8 would lead to increased availability of population-level data to inform action to end preventable stillbirths.
| S-EPMC7869205 | biostudies-literature
Project description:BackgroundThe most common method for determining cause of death is certification by physicians based either on available medical records, or where such data are not available, through verbal autopsy (VA). The physician-certification approach is costly and inconvenient; however, recent work shows the potential of a computer-based probabilistic model (InterVA) to interpret verbal autopsy data in a more convenient, consistent, and rapid way. In this study we validate separately both physician-certified verbal autopsy (PCVA) and the InterVA probabilistic model against hospital cause of death (HCOD) in adults dying in a district hospital on the coast of Kenya.MethodsBetween March 2007 and June 2010, VA interviews were conducted for 145 adult deaths that occurred at Kilifi District Hospital. The VA data were reviewed by a physician and the cause of death established. A range of indicators (including age, gender, physical signs and symptoms, pregnancy status, medical history, and the circumstances of death) from the VA forms were included in the InterVA for interpretation. Cause-specific mortality fractions (CSMF), Cohen's kappa (κ) statistic, receiver operating characteristic (ROC) curves, sensitivity, specificity, and positive predictive values were applied to compare agreement between PCVA, InterVA, and HCOD.ResultsHCOD, InterVA, and PCVA yielded the same top five underlying causes of adult deaths. The InterVA overestimated tuberculosis as a cause of death compared to the HCOD. On the other hand, PCVA overestimated diabetes. Overall, CSMF for the five major cause groups by the InterVA, PCVA, and HCOD were 70%, 65%, and 60%, respectively. PCVA versus HCOD yielded a higher kappa value (κ = 0.52, 95% confidence interval [CI]: 0.48, 0.54) than the InterVA versus HCOD which yielded a kappa (κ) value of 0.32 (95% CI: 0.30, 0.38). Overall, (κ) agreement across the three methods was 0.41 (95% CI: 0.37, 0.48). The areas under the ROC curves were 0.82 for InterVA and 0.88 for PCVA. The observed sensitivities and specificities across the five major causes of death varied from 43% to 100% and 87% to 99%, respectively, for the InterVA/PCVA against the HCOD.ConclusionBoth the InterVA and PCVA compared well with the HCOD at a population level and determined the top five underlying causes of death in the rural community of Kilifi. We hope that our study, albeit small, provides new and useful data that will stimulate further definitive work on methods of interpreting VA data.
| S-EPMC3160942 | biostudies-literature