Regional disparities in the intimate partner sexual violence rate against women in Paraná State, Brazil, 2009-2014: an ecological study.

OBJECTIVE: Evaluate disparities in a Brazilian state by conducting an analysis to determine whether socioeconomic status was associated with the reported intimate partner sexual violence (IPSV) rates against women.

DESIGN: A retrospective, ecological study.

SETTINGS: Data retrieved from the Notifiable Diseases Information System database of the Ministry of Health of Brazil.

PARTICIPANTS: All cases of IPSV (n=516) against women aged 15-49 years reported in the Notifiable Diseases Information System between 2009 and 2014.

OUTCOME MEASURES: The data were evaluated through an exploratory analysis of spatial data.

RESULTS: We identified a positive spatial self-correlation in the IPSV rate (0.7105, P≤0.001). Five high-high-type clusters were identified, predominantly in the Metropolitan, West, South Central, Southwest, Southeast and North Central mesoregions, with only one cluster identified in the North Pioneer mesoregion. Our findings also indicated that the associations between the IPSV rate and socioeconomic predictors (women with higher education, civil registry of legal separations, economically active women, demographic density and average female income) were significantly spatially non-stationary; thus, the regression coefficients verified that certain variables in the model were associated with the IPSV rate in some regions of the state. In addition, the geographically weighted regression (GWR) model improved the understanding of the associations between socioeconomic indicators and the IPSV notification rate, showing a better adjustment than the ordinary least square (OLS) model (OLS vs GWR model: R2 : 0.95 vs 0.99; Akaike information criterion: 4117.90 vs 3550.61; Moran's I: 0.0905 vs -0.0273, respectively).

CONCLUSIONS: IPSV against women was heterogeneous in the state of Paraná. The GWR model showed a better fit and enabled the analysis of the distribution of each indicator in the state, which demonstrated the utility of this model for the study of IPSV dynamics and the indication of local determinants of IPSV notification rates.