Lalit Dandona

Background: Little is known about the underreporting of suicide deaths to the police in India. Aim: To document the extent and reasons of underreporting suicide deaths to the police by socio-demography of the deceased in India. Methods: Interviews documented if a suicide death was reported to the police for suicide deaths that occurred between 2019 and 2022 in India, identified as part of a national all-cause mortality survey in nine states. Further interviews in three of these states explored the reasons for underreporting of suicide deaths to the police. Results: The prevalence of underreporting suicide deaths to the police in India was 35.5% (95% CI 30.8, −40.6), 34.1% (95% CI 28.5, −40.2), and 38.6% (95% CI 30.1, −47.9) for both sexes combined, male, and female suicide deaths, respectively. The underreporting was significantly higher in 15–19 years (46.7%; 95% CI 32.7, −61.2) and in 50+ years (42.5%; 95% CI 32.1, −53.6) compared to those in 30–39 years (19.0%; 95% CI 10.8, −31.1). Avoidance of postmortem was the most cited reason for underreporting followed by compromise between the affected parties, with variations in reasons seen by sex of the deceased and state. Concerns related to social stigma, maintaining family reputation, and securing custody of young children were mentioned as reasons more for female than male suicide deaths. Limitations: Underreporting estimates rely on self-report subject to recall and social desirability bias. Reasons for nonreporting were collected postevent and may not reflect real-time family or community decision-making. Conclusion: One in three suicide deaths are not reported to the police in India, with variations in this underreporting by age, urbanicity, and state of the suicide deaths. These findings can allow for developing targeted awareness campaigns and community engagement in high underreporting areas rather than a one-size-fits-all approach, and simplifying the police protocols around postmortem can help to reduce this underreporting.

The 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. Detailed 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. The 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. To 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.

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. 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. 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). 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.

India has scaled-up antiretroviral treatment (ART) in public sector facilities, but data to understand time trends of average cost of ART are limited. Cost and output data were collected at all public sector ART centres in undivided Andhra Pradesh (high-HIV burden state) and Rajasthan (low-HIV burden state) in India from fiscal year 2007–2008 to 2012–2013. Average cost per patient for first-line ART, and its relation with scale of services, were assessed. Using data on scale of services, the average cost was estimated up to 2015–2016. Break-even point was estimated from average and marginal cost functions. Costs were adjusted to 2015 constant price. The average cost per patient alive and on ART in 2015–2016 was US$162 in undivided Andhra Pradesh and US$186 in Rajasthan, which was 51.4% and 35.8% lower than in 2007–2008, respectively. Average ART drug cost declined by 27.2% during this period, and was 70.9% and 61.5% of the total ART cost in the two states in 2015–2016. The average cost other than ART drugs declined by 73.1% and 45.7%, with the number of patients served increasing 7 and 14.2 times, respectively. Average cost other than ART drugs had a significant negative relation with scale (R² = 86.4%-82.8%, p<0.001). Break-even analysis suggested that 47.5% and 58.8% of the ART centres in undivided Andhra Pradesh and Rajasthan, respectively, were functioning below optimal scale in 2015–2016. The estimated total economic cost of first-line ART services provided in the public sector in India in fiscal year 2015–2016 was US$ 151 million; it would be US$ 216.1 million to provide this to all eligible persons in India. The average cost of providing first-line ART has declined in India, and further reduction is possible if the optimal scale of services is achieved. These findings can inform resource requirement for the ART programme in India.