title: Exploring the relationship between population density and maternal health coverage.
abstract: BACKGROUND
  Delivering health services to dense populations is more practical than to dispersed populations, other factors constant. This engenders the hypothesis that population density positively affects coverage rates of health services. This hypothesis has been tested indirectly for some services at a local level, but not at a national level.
  
  
  METHODS
  We use cross-sectional data to conduct cross-country, OLS regressions at the national level to estimate the relationship between population density and maternal health coverage. We separately estimate the effect of two measures of density on three population-level coverage rates (6 tests in total). Our coverage indicators are the fraction of the maternal population completing four antenatal care visits and the utilization rates of both skilled birth attendants and in-facility delivery. The first density metric we use is the percentage of a population living in an urban area. The second metric, which we denote as a density score, is a relative ranking of countries by population density. The score's calculation discounts a nation's uninhabited territory under the assumption those areas are irrelevant to service delivery.
  
  
  RESULTS
  We find significantly positive relationships between our maternal health indicators and density measures. On average, a one-unit increase in our density score is equivalent to a 0.2% increase in coverage rates.
  
  
  CONCLUSIONS
  Countries with dispersed populations face higher burdens to achieve multinational coverage targets such as the United Nations' Millennial Development Goals.
authors.affiliation: Institute for Health Metrics and Evaluation, University of Washington, 2301 5th Avenue, #600, Seattle, WA 98121, USA. hanlonm@uw.edu
authors.forename: Michael
authors.initials: M
authors.lastname: Hanlon
authors.forename: Roy
authors.initials: R
authors.lastname: Burstein
authors.forename: Samuel H
authors.initials: SH
authors.lastname: Masters
authors.forename: Raymond
authors.initials: R
authors.lastname: Zhang
mesh_terms: D000328:Adult; D001723:Birth Rate / Q000639:trends; D003430:Cross-Sectional Studies; D005260:Female; D040362:Geographic Information Systems; D014943:Global Health / Q000706:statistics & numerical data*; D005102:Health Expenditures / Q000706:statistics & numerical data; D006297:Health Services Accessibility / Q000706:statistics & numerical data; D006742:Hospital Bed Capacity; D006801:Humans; D019458:Insurance Coverage / Q000706:statistics & numerical data; D008430:Maternal-Child Health Centers / Q000191:economics* / Q000706:statistics & numerical data*; D011156:Population Density; D011159:Population Surveillance; D011247:Pregnancy; D011295:Prenatal Care / Q000191:economics / Q000706:statistics & numerical data; D012044:Regression Analysis; D012424:Rural Population / Q000706:statistics & numerical data; D014186:Transportation / Q000706:statistics & numerical data; D014505:Urban Population / Q000706:statistics & numerical data; D014600:Utilization Review