Abstract
Objectives
We evaluated the effectiveness of Moms2B, a community-based group pregnancy and parenting program, in an effort to assess whether the program improved pregnancy and infant outcomes.
Methods
We conducted a retrospective matched exposure cohort study comparing women exposed to the Moms2B program during pregnancy (two or more prenatal visits) who delivered a singleton live birth or stillbirth (≥ 20 weeks gestation) from 2011–2017 to a closely matched group of women not exposed to the program. Primary outcomes were preterm birth and low birth weight. Propensity score methods were used to provide strong control for confounders.
Results
The final analytic file comprised 675 exposed pregnancies and a propensity score-matched group of 1336 unexposed pregnancies. Most of the women were non-Hispanic Black. We found evidence of better outcomes among pregnancies exposed to Moms2B versus unexposed pregnancies, particularly for the primary outcome of low birth weight [9.45% versus 12.00%, respectively, risk difference (RD) = −2.55, 95% confidence interval (CI) = (−5.44, 0.34)]. Point estimates for all adverse pregnancy outcomes uniformly favored exposure to Moms2B.
Conclusions for Practice
Our findings suggest that participation in the Moms2B program improves pregnancy and infant outcomes. The program offers an innovative group model of pregnancy and parenting support for women, especially in non-Hispanic Black women with high-risk pregnancies.
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References
Austin, P. C. (2009). Balance diagnostics for comparing the distribution of baseline covariates between treatment groups in propensity-score matched samples. Statistics in Medicine, 28(25), 3083–3107. https://doi.org/10.1002/sim.3697.
Austin, P. C. (2011). Optimal caliper widths for propensity-score matching when estimating differences in means and differences in proportions in observational studies. Pharmaceutical Statistics, 10(2), 150–161. https://doi.org/10.1002/pst.433.
Austin, P. C., & Stuart, E. A. (2015). Moving towards best practice when using inverse probability of treatment weighting (IPTW) using the propensity score to estimate causal treatment effects in observational studies. Statistics in Medicine, 34(28), 3661–3679. https://doi.org/10.1002/sim.6607.
Calin-Jageman, R. J., & Cumming, G. (2019). The new statistics for better science: Ask how much, how uncertain, and what else is known. The American Statistician, 73(sup1), 271–280. https://doi.org/10.1080/00031305.2018.1518266.
Carter, E. B., Temming, L. A., Akin, J., Fowler, S., Macones, G. A., Colditz, G. A., & Tuuli, M. G. (2016). Group porenatal care compared with traditional prenatal care: A systematic review and meta-analysis. Obstetrics and Gynecology, 128(3), 551–561. https://doi.org/10.1097/aog.0000000000001560.
Catling, C. J., Medley, N., Foureur, M., Ryan, C., Leap, N., Teate, A., & Homer, C. S. (2015). Group versus conventional antenatal care for women. Cochrane Database of Systematic Reviews. https://doi.org/10.1002/14651858.CD007622.pub3.
Cunningham, S. D., Lewis, J. B., Shebl, F. M., Boyd, L. M., Robinson, M. A., Grilo, S. A., & Ickovics, J. R. (2019). Group prenatal care reduces risk of preterm birth and low birth weight: A matched cohort study. Journal of Womens Health (Larchmt), 28(1), 17–22. https://doi.org/10.1089/jwh.2017.6817.
D’Agostino, R. B., Jr. (1998). Propensity score methods for bias reduction in the comparison of a treatment to a non-randomized control group. Statistics in Medicine, 17(19), 2265–2281. https://doi.org/10.1002/(sici)1097-0258(19981015)17:19%3c2265::aid-sim918%3e3.0.co;2-b.
Gabbe, P. T., Gabbe, S. G., & Lynch, C. D. (2018). Beyond the traditional models of group prenatal care: The case for moms2B. American Journal of Obstetrics and Gynecology, 218(1), 147–148. https://doi.org/10.1016/j.ajog.2017.08.117.
Gabbe, P. T., Reno, R., Clutter, C., Schottke, T. F., Price, T., Calhoun, K., & Lynch, C. D. (2017). Improving maternal and infant child health outcomes with community-based pregnancy support groups: Outcomes from moms2B Ohio. Maternal and Child Health Journal, 21(5), 1130–1138. https://doi.org/10.1007/s10995-016-2211-x.
Garner, A. S., Shonkoff, J. P., Siegel, B. S., Dobbins, M. I., Earls, M. F., Garner, A. S., & Wood, D. L. (2012). Early childhood adversity, toxic stress, and the role of the pediatrician: Translating developmental science into lifelong health. Pediatrics, 129(1), e224–e231.
Geronimus, A. T. (1996). Black/white differences in the relationship of maternal age to birthweight: A population-based test of the weathering hypothesis. Social Science and Medicine, 42(4), 589–597. https://doi.org/10.1016/0277-9536(95)00159-x.
Geronimus, A. T., Hicken, M., Keene, D., & Bound, J. (2006). “Weathering” and age patterns of allostatic load scores among blacks and whites in the United States. American Journal of Public Health, 96(5), 826–833. https://doi.org/10.2105/ajph.2004.060749.
Grobman, W. A., Parker, C. B., Willinger, M., Wing, D. A., Silver, R. M., Wapner, R. J., & Reddy, U. M. (2018). Racial disparities in adverse pregnancy outcomes and psychosocial stress. Obstetrics and Gynecology, 131(2), 328–335. https://doi.org/10.1097/aog.0000000000002441.
Haas, J. S., Fuentes-Afflick, E., Stewart, A. L., Jackson, R. A., Dean, M. L., Brawarsky, P., & Escobar, G. J. (2005). Prepregnancy health status and the risk of preterm delivery. Archives of Pediatrics and Adolescent Medicine, 159(1), 58–63. https://doi.org/10.1001/archpedi.159.1.58.
Hill, J. (2004). Reducing bias in treatment effect estimation in observational studies suffering from missing data. https://academiccommons.columbia.edu/doi/10.7916/D8B85G11.
Ickovics, J. R., Earnshaw, V., Lewis, J. B., Kershaw, T. S., Magriples, U., Stasko, E., & Tobin, J. N. (2016). Cluster randomized controlled trial of group prenatal care: Perinatal outcomes among adolescents in New York city health centers. American Journal of Public Health, 106(2), 359–365. https://doi.org/10.2105/ajph.2015.302960.
Ickovics, J. R., Kershaw, T. S., Westdahl, C., Magriples, U., Massey, Z., Reynolds, H., & Rising, S. S. (2007). Group prenatal care and perinatal outcomes: A randomized controlled trial. Obstetrics and Gynecology, 110(2 Pt 1), 330–339. https://doi.org/10.1097/01.Aog.0000275284.24298.23.
Ickovics, J. R., Kershaw, T. S., Westdahl, C., Rising, S. S., Klima, C., Reynolds, H., & Magriples, U. (2003). Group prenatal care and preterm birth weight: Results from a matched cohort study at public clinics. Obstetrics and Gynecology, 102(5 Pt 1), 1051–1057. https://doi.org/10.1016/s0029-7844(03)00765-8.
Jacob, J. A. (2016). US infant mortality rate declines but still exceeds other developed countries. JAMA, 315(5), 451–452. https://doi.org/10.1001/jama.2015.18886.
Kenward, M. G., & Carpenter, J. (2007). Multiple imputation: Current perspectives. Statistical Methods in Medical Research, 16(3), 199–218. https://doi.org/10.1177/0962280206075304.
Koh, H. K., Bantham, A., Geller, A. C., Rukavina, M. A., Emmons, K. M., Yatsko, P., & Restuccia, R. (2020). Anchor institutions: Best practices to address social needs and social determinants of health. American Journal of Public Health, 110(3), 309–316. https://doi.org/10.2105/ajph.2019.305472.
Little, R. J., & Wang, Y. (1996). Pattern-mixture models for multivariate incomplete data with covariates. Biometrics, 52(1), 98–111.
Lu, M. C., & Halfon, N. (2003). Racial and ethnic disparities in birth outcomes: A life-course perspective. Maternal and Child Health Journal, 7(1), 13–30.
Lu, M. C., Kotelchuck, M., Hogan, V., Jones, L., Wright, K., & Halfon, N. (2010). Closing the black-white gap in birth outcomes: A life-course approach. Ethnicity and Disease, 20(1 Suppl 2), 62–76.
March of Dimes Peristats (Producer). (2019). Preterm birth by race/ethnicity, 2015–2017. Retrieved December 15, 2019 from https://www.marchofdimes.org/Peristats/ViewSubtopic.aspx?reg=99&top=3&stop=63&lev=1&slev=1&obj=1.
Misra, D. P., Guyer, B., & Allston, A. (2003). Integrated perinatal health framework. A multiple determinants model with a life span approach. American Journal of Preventive Medicine, 25(1), 65–75. https://doi.org/10.1016/s0749-3797(03)00090-4.
Mitra, R., & Reiter, J. P. (2016). A comparison of two methods of estimating propensity scores after multiple imputation. Statistical Methods in Medical Research, 25(1), 188–204. https://doi.org/10.1177/0962280212445945.
Muller, C. J., & MacLehose, R. F. (2014). Estimating predicted probabilities from logistic regression: Different methods correspond to different target populations. International Journal of Epidemiology, 43(3), 962–970. https://doi.org/10.1093/ije/dyu029.
Ohio Department of Health. (2019). 2017 Infant mortality data: General findings. Retrieved December 15, 2019 from https://odh.ohio.gov/wps/portal/gov/odh/know-our-programs/infant-and-fetal-mortality/reports/2017-ohio-infant-mortality-report-final.
Peck, M. G., Sappenfield, W. M., & Skala, J. (2010). Perinatal periods of risk: A community approach for using data to improve women and infants’ health. Maternal and Child Health Journal, 14(6), 864–874. https://doi.org/10.1007/s10995-010-0626-3.
Penning de Vries, B., & Groenwold, R. (2016). Comments on propensity score matching following multiple imputation. Statistical Methods in Medical Research, 25(6), 3066–3068. https://doi.org/10.1177/0962280216674296.
Riddell, C. A., Harper, S., & Kaufman, J. S. (2017). Trends in differences in US mortality rates between black and white infants. JAMA Pediatrics, 171(9), 911–913. https://doi.org/10.1001/jamapediatrics.2017.1365.
Rosenbaum, P. R., & Rubin, D. B. (1983). The central role of the propensity score in observational studies for causal effects. Biometrika, 70, 41–55.
Schempf, A. H., Branum, A. M., Lukacs, S. L., & Schoendorf, K. C. (2007). The contribution of preterm birth to the black-white infant mortality gap, 1990 and 2000. American Journal of Public Health, 97(7), 1255–1260. https://doi.org/10.2105/ajph.2006.093708.
StataCorp. (2017). Stata 15 multiple imputation reference manual. Stata Press
State Infant Mortality Collaborative. (2013). State infant mortality (SIM) toolkit: A standardized approach for examining infant mortality. Retrieved December 15, 2019 from http://www.amchp.org/programsandtopics/data-assessment/InfantMortalityToolkit/Pages/default.aspx.
Stepner, M., & Garland, A. (2017). CALIPMATCH: Stata module for caliper matching without replacement. Retrieved December 15, 2019 from https://EconPapers.repec.org/RePEc:boc:bocode:s458342.
Zou, G. (2004). A modified poisson regression approach to prospective studies with binary data. American Journal of Epidemiology, 159(7), 702–706. https://doi.org/10.1093/aje/kwh090.
Acknowledgements
The authors wish to acknowledge CelebrateOne, the Greater Columbus Infant Mortality reduction initiative, and the following current and former Moms2B staff for their contributions to the program over the last 9 years as well as their assistance in assembling the data for this program evaluation, including: Twinkle F. Schottke, Director Moms2B; Brooke Garafalo; Kathryn Calhoun; Jamie Sager; and Taylor Ollis.
Funding
This work was funded, in part, by a research grant from AMAG Pharmaceuticals and by The Ohio State University Center for Clinical and Translational Science grant support (National Center for Advancing Translational Sciences (NCATS), Grant UL1TR002733).
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Hade, E.M., Lynch, C.D., Benedict, J.A. et al. The Association of Moms2B, a Community-Based Interdisciplinary Intervention Program, and Pregnancy and Infant Outcomes among Women Residing in Neighborhoods with a High Rate of Infant Mortality. Matern Child Health J 26, 923–932 (2022). https://doi.org/10.1007/s10995-020-03109-9
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DOI: https://doi.org/10.1007/s10995-020-03109-9