Are neighborhood sociocultural factors influencing the spatial pattern of gonorrhea in North Carolina?

Ann Epidemiol. 2011 Apr;21(4):245-52. doi: 10.1016/j.annepidem.2010.11.015.

Abstract

Purpose: To determine if the spatial pattern of gonorrhea observed for North Carolina was influenced by neighborhood-level sociocultural determinants of health, including race/ethnicity.

Methods: A generalized linear mixed model with spatially correlated random effects was fit to measure the influence of socio-cultural factors on the spatial pattern of gonorrhea reported to the North Carolina State Health Department (January 1, 2005 to March 31, 2008).

Results: Neighborhood gonorrhea rates increased as the percent single mothers increased (25th to 75th neighborhood percentile Relative Rate 1.18, 95% CI 1.12, 1.25), and decreased as socioeconomic status increased (Relative Rate 0.89, 95% CI 0.84, 0.95). Increasing numbers of men in neighborhoods with more women than men did not change the gonorrhea rate, but was associated with decreased rates in neighborhoods with more men than women. Living in the mountains was protective for all race/ethnicities. Rurality was associated with decreased rates for Blacks and increased rates for Native Americans outside the mountains.

Purpose: Neighborhood-level sociocultural factors, primarily those indicative of neighborhood deprivation, explained a significant proportion of the spatial pattern of gonorrhea in both urban and rural communities. Race/ethnicity was an important proxy for social and cultural factors not captured by measures of socioeconomic status.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Cluster Analysis
  • Demography / statistics & numerical data
  • Female
  • Geography
  • Gonorrhea / epidemiology*
  • Gonorrhea / ethnology
  • Humans
  • Linear Models
  • Male
  • North Carolina / epidemiology
  • Residence Characteristics / statistics & numerical data*
  • Risk Factors
  • Rural Health / statistics & numerical data
  • Sex Factors
  • Socioeconomic Factors
  • Urban Health / statistics & numerical data