Negative correlation, but positive effect in multilevel regression


I am doing a longitudinal multilevel analyses.

I am researching the impact of certain restricting abortion policies of US states on the number of abortions. Furthermore I control for the characteristics of these states.

One of these characteristics namely poverty rate of a state, has a negative significant correlation with number of abortions. (So a higher poverty rate in a state, correlates with lower rates of abortions)
Yet when introduced as a controlvariable in the multilevel regression together with others like median income, %black etc. the regressioncoefficient is significant and positive, so contradicting my correlation result.

I dont really know what to think of this result, as it contradicts all my other conclusions.
Namely, that poorer states, will have less abortions, as they are more prone to vote Republican, and these administration are more prone to implement restricting abortion policies. So the effect of the abortion policies does not stand on its own, but is embedded in the social structure of the state. (because when controlling for characteristics of a state, the negative effect of restriciting abortion policies on the number of abortions dissapears)

How come?
Tell me if you need more information, I'll add it!

Edit: I think it may be because of suppresion. But am then not sure what output I should follow. Does poverty then have a negative effect on number of abortions, but when controlling for the other factors it has a positive effect?

Thank you!!!
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