Understanding Women’s Awareness and Access to Preconception Health Care in a Rural Population: A Cross Sectional Study
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Despite evidence of the benefits of preconception health care (PCHC), little is known about awareness and access to PCHC for rural, reproductive-aged women. This study aimed to assess the prevalence of PCHC conversations between rural reproductive-age women and health care providers, PCHC interventions received in the past year, and ascertain predictors of PCHC conversations and interventions. Women (n = 868; 18–45 years) completed a questionnaire including reproductive history, health care services utilization, and interest in PCHC. The prevalence of health care providers’ PCHC conversations was 53.9 %, and the mean number of interventions reported was 2.6 ± 2.7 (±SD). Significant predictors of PCHC conversation based on adjusted odds ratios from logistic regression were race (Native American 76 % greater than White), health care provider type (non-physician 63 % greater than physician), visits to a health care provider (3+ times 32 % greater than 1–2 times), and pregnancy planning (considering in next 1–5 years 51 % greater than no plans). Significant predictors of PCHC interventions received in the past 12 months based on adjusted risk ratios from negative binomial regression were race (Native American 22 % greater than White), PCHC conversation with a health care provider (yes 52 % lower than no), reporting PCHC as beneficial (yes 32 % greater than don’t know), and visits to a health care provider in the past year (3+ times 90 % greater than 1–2 times). Increasing conversations about PCHC between health care providers and their reproductive-aged patients can improve awareness and increase their likelihood of receiving all of the recommended interventions.
KeywordsPreconception health care PCHC Awareness Access Rural population
The authors wish to thank Taylor Mertz, APRN, CNM, for her work on data entry and preparation for analysis.
The study was supported by a grant from SDSU Office of Research, Grants and Sponsored Programs—Li-U-Funded Research-10-11.
Compliance with Ethical Standards
Conflict of Interest
The authors declare that they have no conflicts of interest.
Informed consent was obtained from each study participant using methods prescribed by the South Dakota Institutional Review Board.
Research Involving Human Participants
The South Dakota State University Institutional Review Board approved the study before collecting data.
- 1.World Health Organization. (2013). Meeting to develop a global consensus on preconception care to reduce maternal and childhood mortality and morbidity, February 2012. [meeting report]. Geneva: World Health Organization. Retrieved from http://apps.who.int/iris/bitstream/10665/78067/1/9789241505000_eng.pdf.
- 2.Centers for Disease Control and Prevention. (2012). Preconception health and health care: Information for health professionals. Retrieved from http://www.cdc.gov/preconception/hcp/index.html.
- 4.Centers for Disease Control and Prevention. (2006). Recommendations to improve preconception health and health care—United States: A report on the CDC/ATSDR Preconception Care Workgroup and the Select Panel on Preconception Care. Morbidity and Mortality Weekly Report, 55, 1–23. Retrieved from http://www.cdc.gov/mmwr/pdf/rr/rr5506.pdf.
- 9.Floyd, R. L., Johnson, K. A., Owens, J. R., Verbiest, S., Moore, C. A., & Boyle, C. (2013). A national action plan for promoting preconception health and health care in the United States (2012–2014). Journal of Women’s Health, 22(10), 797–802. doi:10.1089/jwh.2013.4505.CrossRefPubMedPubMedCentralGoogle Scholar
- 10.American College of Obstetrics and Gynecology. (2015). Good health before pregnancy: Preconception care. Retrieved from http://www.acog.org/Patients/FAQs/Good-Health-Before-Pregnancy-Preconception-Care.
- 11.Murphy, S.L., Kochanek, K.D., Xu, J.Q., & Arias, E. (2015). Mortality in the United States, 2014. NCHS data brief, no. 229. Hyattsville, MD: National Center for Health Statistics. Retrieved from http://www.cdc.gov/nchs/data/databriefs/db229.pdf.
- 13.Tough, S., Clarke, M., Hicks, M., & Cook, J. (2006). Pre-conception practices among family physicians and obstetrician-gynecologists: Results form a national survey. Journal of Obstetrics and Gynaecological Cancer, 28(9), 780–788.Google Scholar
- 18.Zhangbin, Y., Shuping, H., Jingai, Z., Xiaofan, S., Chenbo, J., & Xirong, G. (2013). Pre-pregnancy body mass index in relation to infant birth weight and offspring overweight/obesity: A systematic review and meta-analysis. PLoS One, 8(4), e61627. doi:10.1371/journal.pone.0061627.CrossRefGoogle Scholar
- 20.Patra, J., Bakker, R., Irving, H., Jadobe, V. W., Malini, S., & Rehm, J. (2011). Dose-response relationship between alcohol consumption before and during pregnancy and the risks of low birth weight, preterm birth, and small for gestational age: A systematic review and meta-analysis. BJOG: An International Journal of Obstetrics and Gynecology, 118(12), 1411–1421. doi:10.1111/j.1471-0528.2011.03050.x.CrossRefGoogle Scholar
- 23.De-Regil, L. M., Peña-Rosas, J. P., Fernández-Gaxiola, A. C., & Rayco-Solon, P. (2015). Effects and safety of periconceptional oral folate supplementation for preventing birth defects. Cochrane Database of Systematic Reviews, 12. doi:10.1002/14651858.CD007950.pub3.
- 25.Wahabi, H. A., Alzeidan, R. A., Bawazeer, G. A., Alansari, L. A., & Esmaeil, S. A. (2010). Preconception care for diabetic women for improving maternal and infant health: A systematic review and meta-analysis. BMC Pregnancy and Childbirth, 10, 63. doi:10.1186/1471-2393-10-63.CrossRefPubMedPubMedCentralGoogle Scholar
- 27.Xu, F., Town, M., Balluz, S., et al. (2013). Surveillance for certain health behaviors among states and selected local areas—United States, 2010. MMWR: Morbidity and Mortality Weekly Report, 62(ss01), 1–247.Google Scholar
- 28.Robbins, C. L., Zapata, L. B., Farr, S. L., et al. (2014). Core state preconception health indicators—pregnancy risk assessment monitoring system and behavioral risk factor surveillance system, 2009. MMWR: Morbidity and Mortality Weekly Reports, 63(3), 1–62. Retrieved from: https://www.cdc.gov/mmwr/preview/mmwrhtml/ss6303a1.htm.
- 29.United States Department of Health and Human Services, Health Resources and Services Administration, Maternal and Child Health Bureau. (2013). Child Health USA 2012. Rockville, MD: United States Department of Health and Human Services. Retrieved from http://mchb.hrsa.gov/chusa12/more/downloads/pdf/chusa12.pdf.
- 32.Economic Research Service. (2013). 2013 Urban influence codes. United States Department of Agriculture. Retrieved from http://www.ers.usda.gov/data-products/urban-influence-codes.aspx.
- 35.United States Department of Health and Human Services, Health Resources and Services Administration. (2013). Women’s Health USA 2013. Rockville, MD: United States Department of Health and Human Services, Health Resources and Services Administration. Retrieved from http://mchb.hrsa.gov/whusa13/dl/pdf/whusa13.pdf.
- 37.United States Census Bureau. (2010). South Dakota quick facts statistics, 2015. Retrieved from http://www.census.gov/quickfacts/table/PST045215/46.
- 38.Weisman, C. S., Hillemeier, M. M., Chase, G. A., et al. (2008). Women’s perceived control of their birth outcomes in the Central Pennsylvania Women’s Health Study: Implications for the use of preconception care. Women’s Health Issues, 18(1), 17–25. doi:10.1016/j.whi.2007.08.001.CrossRefPubMedGoogle Scholar