Racial and ethnic differences in patterns of long-acting reversible contraceptive use in the United States, 2011-2015.

OBJECTIVE

To investigate whether demographic, socioeconomic, and reproductive health characteristics affect long-acting reversible contraceptive (LARC) use differently by race-ethnicity. Results may inform the dialogue on racial pressure and bias in LARC promotion.

STUDY DESIGN

Data derived from the 2011-2013 and 2013-2015 National Surveys of Family Growth (NSFG). Our study sample included 9321 women aged 15-44. Logistic regression analyses predicted current LARC use (yes vs. no). We tested interaction terms between race-ethnicity (non-Hispanic White, non-Hispanic Black, Hispanic) and covariates (for example, education, parity, poverty level) to explore whether their effects on LARC use vary by race-ethnicity.

RESULTS

In the race-interactions model, data did not show that low income and education predict LARC use more strongly among Black and Hispanic women than among White women. There was just one statistically significant race-interaction: experience of unintended pregnancy (p=.014). Among Whites and Hispanics, women who reported ever experiencing an unintended pregnancy had a higher predicted probability of LARC use than those who did not. On the other hand, among Black women, the experience of unintended pregnancy was not associated with a higher predicted probability of LARC use.

CONCLUSIONS

With the exception of the experience of unintended pregnancy, findings from this large, nationally representative sample of women suggest similar patterns in LARC use by race-ethnicity.

IMPLICATIONS

Results from this analysis of NSFG data do not provide evidence that observed differences in LARC use by race-ethnicity represent socioeconomic disparities, and may assuage some concerns about reproductive coercion among women of color. Nevertheless, it is absolutely critical that providers use patient-centered approaches for contraceptive counseling that promote women's autonomy in their reproductive health care decision-making.