Risk factors for small for gestational age as defined by a birthweight z-score below minus one: A prospective observational study
Main Article Content
Abstract
Objective: To determine the maternal risk factors for small-for-gestational-age newborns as defined by a birthweight z-score (BWZS) < -1.0
Design: A prospective cohort study with recruitment from August 2007 to January 2015.
Setting: Recruitment at a community health centre with assessments at Tygerberg Academic Hospital, Cape Town, South Africa.
Population: A largely homogeneous population in a low socioeconomic residential area in Cape Town.
Methods: This study is a further analysis of the data of the Safe Passage Study which investigated whether exposure to alcohol and tobacco was associated with increased risk of stillbirth and sudden infant death syndrome (SIDS).
Main outcome measures: Birthweight z-score < -1.0
Results: Individual odds ratios (ORs), in descending order, were associated with smoking, drinking, and preeclampsia (2.45), previous stillbirth (1.85), smoking (including smokers only and drinkers who also smoked) (1.55), preeclampsia (1.52), smoking and drinking (does not include smokers only or drinkers only)(1.43), hypertension (1.28), drug use (1.24), drinking during pregnancy (including drinkers only and drinkers who also smoked) (1.18), thoughts of self-harm (1.13), and crowding (1.10). After multiple logistic regression, highly significant ORs were found for previous stillbirth (1.89), cigarette smoking (1.84), hypertension (1.40), education (0.94) and body mass index (BMI) (0.95). Thoughts of self-harm then had an OR of 1.08 (95% confidence interval (CI) 1.00-1.18).
Conclusion: Previous stillbirth, cigarette smoking, hypertension, lesser education, and a lower BMI were associated with the highest risks for low BWZS.
Article Details
How to Cite
ODENDAAL, Hein J et al.
Risk factors for small for gestational age as defined by a birthweight z-score below minus one: A prospective observational study.
Medical Research Archives, [S.l.], v. 12, n. 8, aug. 2024.
ISSN 2375-1924.
Available at: <https://esmed.org/MRA/mra/article/view/5731>. Date accessed: 06 sep. 2024.
doi: https://doi.org/10.18103/mra.v12i8.5731.
Section
Research Articles
The Medical Research Archives grants authors the right to publish and reproduce the unrevised contribution in whole or in part at any time and in any form for any scholarly non-commercial purpose with the condition that all publications of the contribution include a full citation to the journal as published by the Medical Research Archives.
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3. Odendaal H, Dukes K, Elliott A, Willinger M, Sullivan L, Tripp T, et al. Association of prenatal exposure to maternal drinking and smoking with the risk of stillbirth. JAMA Netw Open. 2021;4(8):e2121726. https://doi.org/10.1001/jamanetworkopen.2021.21726
4. Brink LT, Gebhardt GS, Mason D, Groenewald CA, Odendaal HJ. The association between preterm labour, perinatal mortality and infant death (during the first year) in Bishop Lavis, Cape Town, South Africa. S Afr Med J. 2019;109(2):102–6. https://doi.org/10.7196/samj.2019.v109i2.13438
5. Black RE, Victora CG, Walker SP, Bhutta ZA, Christian P, De Onis M, et al. Maternal and child undernutrition and overweight in low-income and middle-income countries. Lancet. 2013;382(9890):427–51. https://doi.org/10.1016/s0140-6736(13)60937-x
6. Christian P, Lee SE, Angel MD, Adair LS, Arifeen SE, Ashorn P, et al. Risk of childhood undernutrition related to small-for-gestational age and preterm birth in low- and middle-income countries. Int J Epidemiol. 2013;42(5):1340–55. https://doi.org/10.1093/ije/dyt109
7. Bola R, Ujoh F, Lett R. Identification and mitigation of high-risk pregnancy with the Community Maternal Danger Score Mobile Application in Gboko, Nigeria. PLoS One. 2022;17(9 September):1–8. https://doi.org/10.1371/journal.pone.0275442
8. Gupta A, Agrawal R, Gupt A, Guleria R, Bajpayee D, Joshi N, et al. System E-approach for women at risk (SEWA) - A digital health solution for detection of high-risk pregnancies. J Fam Med Prim Care [Internet]. 2021;10(10):3712–9. Available from: http://www.jfmpc.com/article.asp?issn=2249-4863;year=2017;volume=6;issue=1;spage=169;epage=170;aulast=Faizi. https://doi.org/10.4103/jfmpc.jfmpc_466_21
9. Majella MG, Sarveswaran G, Krishnamoorthy Y, Sivaranjini K, Arikrishnan K, Ganesh Kumar S. A longitudinal study on high risk pregnancy and its outcome among antenatal women attending rural primary health centre in Puducherry, South India. J Educ Health Promot. 2019;8(January):1–6. https://doi.org/10.4103/jehp.jehp_144_18
10. Rajbanshi S, Norhayati MN, Hazlina NHN. High-risk pregnancies and their association with severe maternal morbidity in Nepal: A prospective cohort study. PLoS One. 2021;15(12 December):1–14. https://doi.org/10.1371/journal.pone.0244072
11. Atif N, Lovell K, Rahman A. Maternal mental health: The missing “m” in the global maternal and child health agenda. Semin Perinatol. 2015;39(5):345–52. https://doi.org/10.1053/j.semperi.2015.06.007
12. WHO. Performance of late pregnancy biometry for gestational age dating in low-income and middle-income countries : a prospective, multicountry, population-based cohort study from the WHO Alliance for Maternal and Newborn Health Improvement (AMANHI) Study Group. Lancet Glob Health. 2020;8:e545-554. https://doi.org/10.1016/s2214-109x(20)30034-6
13. Gurung S, Tong HH, Bryce E, Katz J, Lee AC, Black RE, et al. A systematic review on estimating population attributable fraction for risk factors for small-for-gestational-age births in 81 low and middle-income countries. J Glob Health. 2022;12:1–15. https://doi.org/10.7189/jogh.12.04024
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