Sexually transmitted diseases · 2014
Neighborhoods at risk: estimating risk of higher Neisseria gonorrhoeae incidence among women at the census tract level.
СтатьяМногоцентровое исследованиеВалидационное исследованиеНазвание и аннотация: Перевод в очереди
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Stenger Mark R, Samuel Michael C, Anschuetz Greta L, Pugsley River, Eaglin Margaret, Klingler Ellen, Reed Mary, Schumacher Christina M, Simon Julie, Weinstock Hillard
Аннотация
BACKGROUND: The association between area-based social factors and sexually transmitted diseases has been demonstrated in numerous studies. Such associations have not previously been explored for their potential to quantify likelihood of higher transmission of gonorrhea in small geographic areas.
METHODS: Aggregate census tract-level sociodemographic factors in 4 domains (demographics, educational attainment, household income, and housing characteristics) were merged with female gonorrhea incidence data from 113 counties in 10 US states. Multivariate models were constructed, and a tract-level composite gonorrhea risk index was calculated. This composite risk index was validated against gonorrhea incidence among women from 2 independent states.
RESULTS: Seven tract-level factors were found to be most strongly correlated with female gonorrhea incidence: educational attainment, proportion of female headed households, annual household income below US $20,000, proportion of population non-Hispanic black, proportion of housing units currently vacant, proportion of population reporting moving in last year, and proportion of households that are nonfamily units. Composite index was highly correlated with female gonorrhea in the study area and validated with independent data.
CONCLUSIONS: Social factors predict gonorrhea incidence at the census tract level and identify small areas at risk for higher morbidity. These data may be used by health departments and health care practices to develop geographically based disease prevention and control efforts. This is especially useful because gonorrhea incidence data are not routinely available below the county level in many states.
METHODS: Aggregate census tract-level sociodemographic factors in 4 domains (demographics, educational attainment, household income, and housing characteristics) were merged with female gonorrhea incidence data from 113 counties in 10 US states. Multivariate models were constructed, and a tract-level composite gonorrhea risk index was calculated. This composite risk index was validated against gonorrhea incidence among women from 2 independent states.
RESULTS: Seven tract-level factors were found to be most strongly correlated with female gonorrhea incidence: educational attainment, proportion of female headed households, annual household income below US $20,000, proportion of population non-Hispanic black, proportion of housing units currently vacant, proportion of population reporting moving in last year, and proportion of households that are nonfamily units. Composite index was highly correlated with female gonorrhea in the study area and validated with independent data.
CONCLUSIONS: Social factors predict gonorrhea incidence at the census tract level and identify small areas at risk for higher morbidity. These data may be used by health departments and health care practices to develop geographically based disease prevention and control efforts. This is especially useful because gonorrhea incidence data are not routinely available below the county level in many states.