title: The neighbourhood method for measuring differences in maternal mortality, infant mortality and other rare demographic events.
abstract: In the absence of reliable systems for registering rare types of vital events large surveys are required to measure changes in their rates. However some events such as maternal deaths are widely known about in the community. This study examined the utility of asking respondents about events in their neighbourhood as an efficient method for measuring relative rates of rare health events such as maternal and infant deaths. A survey was conducted in the health and demographic surveillance system (HDSS) in Matlab, Bangladesh, which includes two areas with different health care regimes. Adult women were asked about any maternal deaths; multiple births; infant deaths, live births and some other events they knew of in a small specified area around their home. Agreement between HDSS records and survey responses was moderate or better (kappa≥0.44) for all the events and greatest for maternal deaths (kappa = 0.77) with 84% being reported. Most events were more likely to be reported if they were recent (p<0.05). Infant mortality rate in one area was 0.56 times that in the other which was well reflected by the ratio of survey results (0.53). Simulations were used to study the ability of the method to detect differences in maternal mortality ratio. These suggested that a sample size around 5000 would give 80% power to detect a 50% decrease from a baseline of 183 which compared well with an estimated sample size around 10 times larger using the direct sisterhood method. The findings suggest that the Neighbourhood Method has potential for monitoring relative differences between areas or changes over time in the rates of rare demographic events, requiring considerably smaller sample sizes than traditional methods. This raises the possibility for interventions to demonstrate real effects on outcomes such as maternal deaths where previously this was only feasible by indirect methods.
authors.affiliation: Centre for Population, Urbanization and Climate Change, ICDDR,B, Dhaka, Bangladesh.
authors.forename: Nurul
authors.initials: N
authors.lastname: Alam
authors.affiliation: Medical Statistics Team, Division of Applied Health Sciences, University of Aberdeen, Aberdeen, United Kingdom.
authors.forename: John
authors.initials: J
authors.lastname: Townend
mesh_terms: D000293:Adolescent; D000328:Adult; D001459:Bangladesh / Q000453:epidemiology; D003198:Computer Simulation; D005260:Female; D006305:Health Status Indicators; D006801:Humans; D007223:Infant; D007226:Infant Mortality; D008428:Maternal Mortality; D008875:Middle Aged; D016017:Odds Ratio; D062486:Public Health Surveillance / Q000379:methods*; D015203:Reproducibility of Results; D011795:Surveys and Questionnaires; D055815:Young Adult