The paper included a decade’s worth of data from the Centers of Disease Control and Prevention among Black women ages 25 to 44 across 30 states.

In the U.S., Black adult women are six times more likely to be killed than their white counterparts, troubling new data reveals.

A paper published Thursday in The Lancet medical journal analyzed homicide rates of Black women ages 25 to 44 across 30 states. The data was collected between 1999 and 2020 by the Centers for Disease Control and Prevention’s National Vital Statistics System.

Homicides were classified in this study as death by shooting, piercing, cutting and other forms of violence. Racial disparities varied among states; in Wisconsin, for example, Black women were 20 times more likely to be killed than white women. Black women living in Midwestern and Northeastern states were also more likely to be killed by a firearm, the paper found.

The study was designed to provide more comprehensive data about homicide rates among Black women and fill in the gaps in the existing literature, said Bernadine Waller, the paper’s lead author and a postdoctoral psychiatry research fellow at the Columbia University’s Irving Medical Center.

  • AnneBonny@lemmy.dbzer0.com
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    5 months ago

    The paper included a decade’s worth of data from the Centers of Disease Control and Prevention among Black women ages 25 to 44 across 30 states.

    This seems weirdly specific.

    • PrinceWith999Enemies@lemmy.world
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      5 months ago

      When you do a meta analysis (a study that aggregates and compares the results of existing studies rather than de novo research), you have to work pretty hard to make sure all of the studies you’re using agree with each other on definitions, the ways they aggregate the data, and so on. You have to start out by collecting a large number of papers, and then building around the ones who are most closely aligned with each other on the statistics you’re interested in studying. Some might group ages differently or report causes of death differently in a way that cannot be reconciled in a statistically reliable way.

      I was a contributing author on a couple such papers, and I swore never to do them again. They can be very useful, and hopefully this one will be high impact, but as an author they’re an order of magnitude harder to write than just doing a paper on your own work.