Nevin Manimala Statistics

Do health sector measures of violence against women at different levels of severity correlate? Evidence from Brazil

BMC Womens Health. 2022 Jun 13;22(1):226. doi: 10.1186/s12905-022-01813-y.


OBJECTIVE: To evaluate if characteristics of reports of violence against women at different levels of severity are similar and to test if their prevalence is correlated at the municipal level.

METHODS: I use data from women ages 15-49 who were killed by homicide in Brazil’s national death registry (N = 14,373), were hospitalized for aggression (N = 14,701), or were included in the medical mandatory reports of incidents of violence against women (N = 42,134) between 2011 and 2016 in select municipalities. I provide national level descriptive statistics from 2016 contrasting distributions of victims (age, education, and race) and distributions of the characteristics of the incidents (location and time of day). Then, for 63 municipalities with a high number of violent incidents, I calculate the correlation coefficients between measures of violence against women using quarterly data from 2011 to 2016. I use multiple regression of municipal characteristics at baseline to examine which factors (poverty, spending, health, and civic engagement) predict the correlation.

RESULTS: Victim characteristics and incident characteristics are similar across the measures of violence at the national level. Despite these aggregate similarities, correlations at the municipal level are quite varied, ranging from – 0.69 to 0.83. I find no municipal characteristics that consistently predict these correlation coefficients.

CONCLUSIONS: Despite some similarities at an aggregate level, these measures of violence against women do not have consistent patterns of correlation at the municipality level. Measures of severe levels of violence against women are not good proxies for incidence of violence at less severe physical levels. Lack of correlations could be due to differences in reporting, but may also be due to differences in underlying processes that share similar victims and event characteristics.

PMID:35698218 | DOI:10.1186/s12905-022-01813-y

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