Discussion
deaths, death, DHS, stillbirths
SENSITIVITY
Few studies have compared pregnancy dates and outcomes from the DHS full pregnancy history survey to prospective, population-based data at aggregate or individual levels. Our validity study, conducted in a rural Nepali community, found that a DHS full pregnancy history survey reported a similar number of live births that survived to 28 days but fewer stillbirths and live births followed by neonatal death, compared to prospectively collected trial data. Other studies have similarly reported that births of children who died were less likely to be reported in survey data than in longitudinal estimates generated from regular home visits at Health and Demographic Surveillance Systems (HDSS) sites, although these sites differ from population-based cohort studies like our trial in important ways [The Nepal DHS 2016 neonatal mortality rate estimate of 30 deaths per 1,000 live births for Nepal’s Province 2 is similar to that observed in the prospective trial data over the 2010–2017 follow-up period (31.2). However, the NMR in the study population decreased during this period from 34.7 in 2011 to 27.5 in 2016 [About half of the 122 prospectively observed pregnancy outcomes in our study were matched by date within one month in the pregnancy history survey. The high proportion of unmatched dates could be due in part to the large number of partial dates reported in the pregnancy history survey. This, in turn, could be a result of the long recall times (median 6.2 years, range: 4.4–10.5 years) between the prospective outcome and the pregnancy history survey administration date, which is longer than the average recall in the five years preceding the survey range used by DHS. Due to high missingness of infant names or other identifying data for matching participants between these two data sources, there was no definitive method for differentiating omissions from date displacements. However, visual observation of the pregnancy outcomes in both sources that did not match within ± 30 days (Additional file Among pregnancy outcomes matched by date, live births that survived to 28 days were well classified; however, four of nine stillbirths were misreported as live births followed by neonatal death and one in ten neonatal deaths as stillbirths. This misclassification of stillbirths as neonatal deaths resulted in a neonatal mortality rate higher than the prospective data within the outcomes matched by date. Sensitivity analyses allowing for matching of pregnancy outcome dates within wider date ranges (i.e., ± 60 days, ± 100 days, ± 365 days, and unrestricted), found generally lower, but not markedly different agreement, for pregnancy outcomes in the two data sources as the date ranges widened. Again, it must be noted that a high proportion of mismatched outcomes could be due to the large number of partial dates reported in the pregnancy history survey. Underreporting and misclassification of stillbirths and neonatal deaths have been observed in other settings. A study in Bangladesh comparing HDSS data and a DHS pregnancy history survey from the 1990s found that the completeness of neonatal death reporting was 83% [Examination of participant characteristics provided some insights into the drivers of reporting errors in this population. Women with higher parity in our study were more likely to omit or displace an outcome compared to the prospective data, which was similar to the study in Bangladesh that found higher parity was associated with missed live birth in surveys [Women who delivered at a health facility in our study were more likely to not report an outcome in the pregnancy history survey that matched with the prospective data. A study in this same population in Sarlahi District observed lower recall reliability for receipt of several labor and delivery and immediate newborn care interventions among women who delivered at a health facility compared to those that delivered at home [Age at death was fairly accurate for neonatal deaths with pregnancy outcome dates that were correctly recalled, although due to our small sample, there were few late neonatal deaths that would be more subject to age errors resulting in misclassification as postnatal deaths. Date errors and age under- or over-statements are common causes of age error that can impact neonatal mortality rates. The study in Guinea-Bissau reported a large number of postnatal deaths were transferred to the neonatal period, which could lead to overestimation of the neonatal mortality rate [Our study had limitations—including a small sample size, high number of partial dates in the pregnancy history survey, and a small number of pregnancy outcome date matches, yielding fewer participants for analysis and limiting the precision of our estimates—so our findings should be interpreted with caution. The long recall period, relative to the DHS five years preceding the survey time frame, may have contributed to poor date recall and subsequent failure to match more pregnancy outcome dates. An attempt to match pregnancy outcomes by name and sex in this community was not useful, given how few infants are named at birth, which is common in South Asia and other settings. There were few participants with less common but important demographic and socioeconomic characteristics, for example, higher maternal age, Pahadi ethnicity, or more education, limiting investigations of maternal recall by these factors. Both maternal recall and pregnancy outcome incidence may also differ across by factors that we did not consider in this analysis, such as seasonality of birth [Our findings have implications for fertility and mortality estimation in the Terai region of Nepal and similar settings. Stillbirth and neonatal deaths were underestimated by the full pregnancy history survey, which would potentially misrepresent the burden of mortality in this population. This indicates a need to design and evaluate survey measurement tools and techniques to reduce biases and errors or statistical approaches to adjust for these issues.