Dataset Information

Causes and age of neonatal death and associations with maternal and newborn care characteristics in Nepal: a verbal autopsy study.

ABSTRACT:

Background

In Nepal, neonatal mortality fell substantially between 2000 and 2018, decreasing 50% from 40 to 20 deaths per 1,000 live births. Nepal's success has been attributed to a decreasing total fertility rate, improvements in female education, increases in coverage of skilled care at birth, and community-based child survival interventions.

Methods

A verbal autopsy study, led by the Integrated Rural Health Development Training Centre (IRHDTC), conducted interviews for 338 neonatal deaths across six districts in Nepal between April 2012 and April 2013. We conducted a secondary analysis of verbal autopsy data to understand how cause and age of neonatal death are related to health behaviors, care seeking practices, and coverage of essential services in Nepal.

Results

Sepsis was the leading cause of neonatal death (n=159/338, 47.0%), followed by birth asphyxia (n=56/338, 16.6%), preterm birth (n=45/338, 13.3%), and low birth weight (n=17/338, 5.0%). Neonatal deaths occurred primarily on the first day of life (27.2%) and between days 1 and 6 (64.8%) of life. Risk of death due birth asphyxia relative to sepsis was higher among mothers who were nulligravida, had <4 antenatal care visits, and had a multiple birth; risk of death due to prematurity relative to sepsis was lower for women who made ≥1 delivery preparation and higher for women with a multiple birth.

Conclusions

Our findings suggest cause and age of death distributions typically associated with high mortality settings. Increased coverage of preventive antenatal care interventions and counseling are critically needed. Delays in care seeking for newborn illness and quality of care around the time of delivery and for sick newborns are important points of intervention with potential to reduce deaths, particularly for birth asphyxia and sepsis, which remain common in this population.

SUBMITTER: Erchick DJ

PROVIDER: S-EPMC8751254 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BACKGROUND:Monitoring progress with disease and injury reduction in many populations will require widespread use of verbal autopsy (VA). Multiple methods have been developed for assigning cause of death from a VA but their application is restricted by uncertainty about their reliability. METHODS:We investigated the validity of five automated VA methods for assigning cause of death: InterVA-4, Random Forest (RF), Simplified Symptom Pattern (SSP), Tariff method (Tariff), and King-Lu (KL), in addition to physician review of VA forms (PCVA), based on 12,535 cases from diverse populations for which the true cause of death had been reliably established. For adults, children, neonates and stillbirths, performance was assessed separately for individuals using sensitivity, specificity, Kappa, and chance-corrected concordance (CCC) and for populations using cause specific mortality fraction (CSMF) accuracy, with and without additional diagnostic information from prior contact with health services. A total of 500 train-test splits were used to ensure that results are robust to variation in the underlying cause of death distribution. RESULTS:Three automated diagnostic methods, Tariff, SSP, and RF, but not InterVA-4, performed better than physician review in all age groups, study sites, and for the majority of causes of death studied. For adults, CSMF accuracy ranged from 0.764 to 0.770, compared with 0.680 for PCVA and 0.625 for InterVA; CCC varied from 49.2% to 54.1%, compared with 42.2% for PCVA, and 23.8% for InterVA. For children, CSMF accuracy was 0.783 for Tariff, 0.678 for PCVA, and 0.520 for InterVA; CCC was 52.5% for Tariff, 44.5% for PCVA, and 30.3% for InterVA. For neonates, CSMF accuracy was 0.817 for Tariff, 0.719 for PCVA, and 0.629 for InterVA; CCC varied from 47.3% to 50.3% for the three automated methods, 29.3% for PCVA, and 19.4% for InterVA. The method with the highest sensitivity for a specific cause varied by cause. CONCLUSIONS:Physician review of verbal autopsy questionnaires is less accurate than automated methods in determining both individual and population causes of death. Overall, Tariff performs as well or better than other methods and should be widely applied in routine mortality surveillance systems with poor cause of death certification practices.

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Project description:BackgroundVerbal autopsy (VA) has been proposed to determine the cause of death (COD) distributions in settings where most deaths occur without medical attention or certification. We develop performance criteria for VA-based COD systems and apply these to the Registrar General of India's ongoing, nationally-representative Indian Million Death Study (MDS).MethodsPerformance criteria include a low ill-defined proportion of deaths before old age; reproducibility, including consistency of COD distributions with independent resampling; differences in COD distribution of hospital, home, urban or rural deaths; age-, sex- and time-specific plausibility of specific diseases; stability and repeatability of dual physician coding; and the ability of the mortality classification system to capture a wide range of conditions.ResultsThe introduction of the MDS in India reduced the proportion of ill-defined deaths before age 70 years from 13% to 4%. The cause-specific mortality fractions (CSMFs) at ages 5 to 69 years for independently resampled deaths and the MDS were very similar across 19 disease categories. By contrast, CSMFs at these ages differed between hospital and home deaths and between urban and rural deaths. Thus, reliance mostly on urban or hospital data can distort national estimates of CODs. Age-, sex- and time-specific patterns for various diseases were plausible. Initial physician agreement on COD occurred about two-thirds of the time. The MDS COD classification system was able to capture more eligible records than alternative classification systems. By these metrics, the Indian MDS performs well for deaths prior to age 70 years. The key implication for low- and middle-income countries where medical certification of death remains uncommon is to implement COD surveys that randomly sample all deaths, use simple but high-quality field work with built-in resampling, and use electronic rather than paper systems to expedite field work and coding.ConclusionsSimple criteria can evaluate the performance of VA-based COD systems. Despite the misclassification of VA, the MDS demonstrates that national surveys of CODs using VA are an order of magnitude better than the limited COD data previously available.

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