The Southern Medical Journal (SMJ) is the official, peer-reviewed journal of the Southern Medical Association. It has a multidisciplinary and inter-professional focus that covers a broad range of topics relevant to physicians and other healthcare specialists.
SMJ // Article
Acknowledgment
Joint Effect of Paternal and Maternal Age on the Prevalence of Low Birth Weight in the United States
Abstract
Objective: Prior studies of the effect of father's age on the risk of low birth weight (LBW, infant weight < 2500 g) have been inconclusive. In addition, previous investigators have not conducted a detailed analysis to determine whether paternal age (PA) interacts with maternal age (MA) on the outcome of LBW. We aimed to quantify the joint effect of PA and MA on the prevalence of LBW.Methods: Cross-sectional prevalence data from the National Survey of Family Growth 2017-2019 (female pregnancy file) were analyzed using SAS 9.4 software. The exposure of interest was the PA group. Six PA groups were created based on the mother's and father's age at the time of conception. Weighted frequencies and weighted percent estimates of selected characteristics were calculated. Odds ratios (ORs) and 95% confidence intervals (CIs) for the binary outcome of LBW were calculated from logistic regression models. A causal diagram (ie, directed acyclic graph) identified maternal race-ethnicity as a variable that needed to be controlled for to reduce confounding bias when estimating the association under study. Preterm birth, according to our directed acyclic graph, was a collider on some pathways between parental age and LBW (and an intermediate on other pathways) and hence was not controlled for. All of the analyses accounted for the complex survey sample design.
Results: A total of 1977 subjects were included in our sample. The largest PA group was MA 20 to 34 years (PA < 35 y). Within this group, 26.5% (95% CI 20.1%-32.9%) of the mothers were of Hispanic ethnicity. The weighted prevalence of preterm birth was 10.6% (95% CI 8.5%-12.7%), and the weighted percentage of LBW was 8.0% (95% CI 5.8%-10.2%) within the largest PA group. The unadjusted OR for LBW comparing MA < 20, PA < 35 with MA 20 to 34, PA < 35 was 2.12 (95% CI 0.94-4.80, P = 0.07). After adjusting for maternal race-ethnicity, the MA < 20, PA < 35 versus MA 20 to 34, PA < 35 OR was 2.13 (95% CI 0.92-4.93, P = 0.08).
Conclusions: We did not detect a joint effect of maternal and PA on the prevalence of LBW in a national US sample.
Posted in: Obstetrics and Gynecology97 Pregnancy38
This content is limited to qualifying members.
Existing members, please login first
If you have an existing account please login now to access this article or view purchase options.
Purchase only this article ($25)
Create a free account, then purchase this article to download or access it online for 24 hours.
Purchase an SMJ online subscription ($75)
Create a free account, then purchase a subscription to get complete access to all articles for a full year.
Purchase a membership plan (fees vary)
Premium members can access all articles plus recieve many more benefits. View all membership plans and benefit packages.
References
1. World Health Organization. Low birth weight. https://www.who.int/data/nutrition/nlis/info/low-birth-weight. Accessed January 6, 2026.2. Cutland CL, Lackritz EM, Mallett-Moore T, et al. Low birth weight: case definition & guidelines for data collection, analysis, and presentation of maternal immunization safety data. Vaccine 2017;35(48 Pt A):6492-6500.
3. Cortese M, Moster D, Wilcox AJ. Term birth weight and neurodevelopmentaloutcomes. Epidemiology 2021;32:583-590.
4. Ratiu D, Sauter F, Gilman E, et al. Impact of advanced maternal age on maternal and neonatal outcomes. In Vivo 2023;37:1694-1702.
5. Khoshnood B, Wall S, Lee K. Risk of low birth weight associated with advanced maternal age among four ethnic groups in the United States. Matern Child Health J 2005;9:3-9.
6. Chung YH, Hwang IS, Jung G, et al. Advanced parental age is an independent risk factor for term low birth weight and macrosomia. Medicine (Baltimore) 2022;101:e29846.
7. Reichman NE, Teitler JO. Paternal age as a risk factor for low birthweight. Am J Public Health 2006;96:862-866.
8. Tough SC, Faber AJ, Svenson LW, et al. Is paternal age associated with an increased risk of low birthweight, preterm delivery, and multiple birth? Can J Public Health 2003;94:88-92.
9. Khandwala YS, Baker VL, Shaw GM, et al. Association of paternal age with perinatal outcomes between 2007 and 2016 in the United States: population-based cohort study. BMJ 2018;363:k4372.
10. Li J, Qiu J, Lv L, et al. Paternal factors and adverse birth outcomes in Lanzhou, China. BMC Pregnancy Childbirth 2021;21:19.
11. Sabas RR, Nyange NN, Mayala AM, et al. Paternal characteristics associated with low birth weight among singleton births: a hospital-based birth cohort study in northern Tanzania. Pan Afr Med J 2021;40:179.
12. Goisis A, Remes H, Barclay K, et al. Paternal age and the risk of low birth weight and preterm delivery: a Finnish register-based study. J Epidemiol Community Health 2018;72:1104-1109.
13. Mao Y, Zhang C, Wang Y, et al. Association between paternal age and birth weight in preterm and full-term birth: a retrospective study. Front Endocrinol (Lausanne) 2021;12:706369.
14. Centers for Disease Control and Prevention, National Center for Health Statistics. National Survey of Family Growth. About the National Survey of Family Growth. https://www.cdc.gov/nchs/nsfg/about_nsfg.htm. Accessed March 22, 2024.
15. National Center for Health Statistics. 2017-2019 National Survey of Family Growth Public-Use Data and Documentation User’ Guide. Hyattsville, MD:CDC National Center for Health Statistics;2020;12.
16. Rothman KJ. Epidemiology: An Introduction, 2nd ed. New York:Oxford University Press;2012;209:226.
17. Bandoli G, Palmsten K, Flores KF, et al. Constructing causal diagrams for common perinatal outcomes: benefits, limitations, and motivating examples with maternal antidepressant use in pregnancy. Paediatr Perinat Epidemiol 2016;30:521-528.
18. Luque-Fernandez MA, Schomaker M, Redondo-Sanchez D, et al. Educational note. Paradoxical collider effect in the analysis of non-communicable disease epidemiological data: a reproducible illustration and web application. Int J Epidemiol 2019;48:640-653.
19. VanderWeele TJ, Mumford SL, Schisterman EF. Conditioning on intermediates in perinatal epidemiology. Epidemiology 2012;23:1-9.
20. Ananth CV, Schisterman EF. Confounding, causality, and confusion: the role of intermediate variables in interpreting observational studies in obstetrics. Am J Obstet Gynecol 2017;217:167-175.
21. Elwert F. Graphical causal models. Morgan SL. Handbook of Causal Analysis for Social Research. New York:Springer;2013;:245-273.
