Quality of vital event data for infant mortality estimation in prospective, population-based studies: an analysis of secondary data from Asia, Africa, and Latin America

INTRODUCTION

Infant and neonatal mortality estimates are typically derived from retrospective birth histories collected through surveys in countries with unreliable civil registration and vital statistics systems. Yet such data are subject to biases, including under-reporting of deaths and age misreporting, which impact mortality estimates. Prospective population-based cohort studies are an underutilized data source for mortality estimation that may offer strengths that avoid biases.

METHODS

We conducted a secondary analysis of data from the Child Health Epidemiology Reference Group, including 11 population-based pregnancy or birth cohort studies, to evaluate the appropriateness of vital event data for mortality estimation. Analyses were descriptive, summarizing study designs, populations, protocols, and internal checks to assess their impact on data quality. We calculated infant and neonatal morality rates and compared patterns with Demographic and Health Survey (DHS) data.

RESULTS

Studies yielded 71,760 pregnant women and 85,095 live births. Specific field protocols, especially pregnancy enrollment, limited exclusion criteria, and frequent follow-up visits after delivery, led to higher birth outcome ascertainment and fewer missing deaths. Most studies had low follow-up loss in pregnancy and the first month with little evidence of date heaping. Among studies in Asia and Latin America, neonatal mortality rates (NMR) were similar to DHS, while several studies in Sub-Saharan Africa had lower NMRs than DHS. Infant mortality varied by study and region between sources.

CONCLUSIONS

Prospective, population-based cohort studies following rigorous protocols can yield high-quality vital event data to improve characterization of detailed mortality patterns of infants in low- and middle-income countries, especially in the early neonatal period where mortality risk is highest and changes rapidly.

C-reactive protein response to influenza vaccination as a model of mild inflammatory stimulation in the Philippines

BACKGROUND

C-reactive protein (CRP) is increasingly measured as a marker of systemic inflammation that predicts elevated risk for cardiovascular disease. Influenza vaccination is a mild pro-inflammatory stimulus, and the CRP response to vaccination may provide additional information on individual differences in inflammatory response and risk for disease.

AIM

To document the pattern of CRP response to influenza vaccination among a large sample of older women in the Philippines. The Philippines exemplifies current global trends toward increasing rates of overweight/obesity, but also maintains relatively high rates of infectious disease. The secondary aim of the study is to investigate the impact of infectious symptoms on the pattern of response to vaccination.

METHODS

A community-based sample of 934 women (mean age=55.4 years) received the influenza vaccine. CRP was assessed at baseline and 72h post-vaccination. Descriptive, non-parametric, and parametric analyses were implemented to assess the magnitude of CRP response, and to investigate whether responses were associated with baseline CRP or the presence of infectious symptoms prior to vaccination.

RESULTS

Influenza vaccination resulted in a statistically significant CRP response of 0.35mg/L (p<0.001), representing a 30.2% increase from baseline. For individuals with symptoms of infectious disease at baseline, the CRP response was smaller (12.9%) and not statistically significant (p=0.77). Lower CRP at baseline was associated with larger CRP response to vaccination in the entire sample, and among participants without recent symptoms of infection.

CONCLUSIONS

Influenza vaccination produces a mild CRP response in the Philippines. This study extends prior research in US and European populations validating influenza vaccination as an in vivo model for investigating the dynamics of inflammation, but also raises potential complications in settings where rates of infectious disease are elevated.