Exploring the Impact of Unintended Pregnancy on the Anthropometric Indicators of Newborns in Mothers Living in Marginal Neighborhoods of Bandar Abbas: A Prospective Cohort Study With a Causal Approach



Holakouienaieni K^{1, 2} ; Mansournia MA³ ; Nematollahi S⁴ ; Almasi SZ³ ; Azizpour Y³ ; Hosseini SS³ ; Taherpour M³ Show Affiliations
Source: Journal of Mazandaran University of Medical Sciences Published:2024

Abstract

Background and purpose: An unintended pregnancy denotes a conception that occurs without prior planning or intention by the couple involved. The repercussions of such pregnancies can be substantial for both the mother and the child, potentially resulting in inadvertent neglect of fetal health and influencing the quality of caregiving behaviors. These factors may contribute to adverse outcomes, such as low birth weight. This research aims to assess the impact of unintended pregnancy on newborn anthropometric parameters within the marginal neighborhoods of Bandar Abbas. Materials and methods: This study is a component of a prospective cohort project involving pregnant women residing in marginalized areas of Bandar Abbas City in 2015. A total of 1351 participants were enrolled in the cohort project, with 825 individuals included in this investigation. Among these, 132 were categorized into the exposure group representing unintended pregnancies, while 693 comprised the non-exposure (control) group, based on the proportion of unintended pregnancies in the original dataset. Our study delineates the associations between birth weight, height, head circumference, and the primary exposure variable of maternal unintended pregnancy. Data collection on unintended pregnancy and potential confounding factors was conducted through questionnaires and face-to-face interviews during the initial cohort visit, coinciding with the women's pregnancies. Confounding variables pertinent to each outcome were rigorously evaluated utilizing a causal analysis approach, facilitated by the dagitty software, with data management performed using SPSS version 24. Univariate analysis involved the utilization of Pearson's correlation coefficient, independent t-tests, and one-way analysis of variance to explore the relationships between anthropometric indices and individual characteristics. Meanwhile, multivariate analysis entailed the application of multiple linear regression techniques. Results: Among the total of 1351 pregnancies investigated, 219 (16.2%) were identified as unintended. The mean age of mothers experiencing unintended pregnancies was 29.23±6.49 years, compared to 26.98±5.31 years for those with intended pregnancies. For unintended pregnancies, the mean and standard deviation of birth weight, height, and head circumference were calculated as 3059.24±501.11 grams, 48.52±3.11 cm, and 33.80±2.22 cm, respectively. Conversely, for intended pregnancies, these measures were 3080±17.17 grams, 48.63±2.65 cm, and 33.82±1.92 cm, respectively. Statistically significant positive correlations were observed between birth weight and maternal age (P=0.041, r=0.056), paternal age (P=0.008, r=0.073), and maternal BMI (P<0.001, r=0.159). Additionally, Statistically significant positive correlations were noted between maternal BMI and infant height (P=0.022, r=0.062), as well as birth head circumference (P<0.001, r=0.102). Multiple linear regression analysis revealed no evidence of an association between unintended pregnancy and birth weight (95% CI:-91.3 to 58.3, b=-16.5), height (95% CI:-0.47 to 47.0, b= 0.01), or head circumference (95% CI:-0.32 to 0.34, b= 0.01). Conclusion: Our findings suggest a lack of substantial evidence supporting a correlation between unintended pregnancy and covariates including low birth weight, short height, and low head circumference. The outcomes of research in this domain exhibit inconsistencies, potentially attributed to variations in study design, methodologies for confounding variable management, demographic disparities among study populations, and other pertinent factors. © 2024, Mazandaran University of Medical Sciences. All rights reserved.