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Determinants of macrosomia among newborns delivered in Jigjiga City, Eastern Ethiopia: a case-control study

Maternal Health, Neonatology and Perinatology volume 10, Article number: 23 (2024) Cite this article

Abstract

Background

Macrosomia is a forgotten health problem that directly or indirectly affects maternal and neonatal health outcomes. There is a lack of evidence on the factors that affect macrosomia in eastern Ethiopia. This study aimed to assess the determinants of macrosomia among newborns delivered in Jigjiga City, Eastern Ethiopia.

Methods

An institutional-based case-control study was conducted among 82 cases and 164 controls in Jigjiga City from June 25 to August 24, 2023. Bivariable and multivariable logistic regression were used to identify the determinants of macrosomia. An adjusted odds ratio (AOR) with a 95% confidence interval was used to report the strength of the association, and the statistical significance was declared at a p-value < 0.05.

Results

This study found that lack of preconception care (AOR = 2.48, 95% CI: 1.29, 4.76); post-term pregnancy (AOR = 2.90, 95% CI: 1.16, 7.28); inadequate physical activity (AOR = 3.52, 95% CI: 1.55, 7.98), having previous macrosomia (AOR = 4.52, 95% CI: 2.18, 9.36), and gestational diabetic mellitus (AOR = 2.58, 95% CI: 1.10, 6.28) were the main risk factors of macrosomia.

Conclusion

This study indicated that failed utilization of preconception care, inadequate physical activity during pregnancy, post-term pregnancy, gestational diabetic mellitus, and having previous macrosomia were the risk factors for fetal macrosomia. Encouraging women to utilize reproductive health services and providing special care for high-risk mothers are essential to reducing and preventing the level of fetal macrosomia and its consequences.

Introduction

Fetal birth weight is essential because it helps estimate the maternal and newborn nutritional status and determines the newborn survival, future health, growth, and development. According to low and middle-income country (LMIC) researches, macrosomia is a birth weight greater than or equal to 4000 g, which increases maternal and neonatal birth complications [1,2,3].

Macrosomia is a forgotten health problem increasing in most developing countries that directly or indirectly contributes to maternal and neonatal morbidity, mortality, and disability. Globally, it affects about 15% of all pregnancies [4], and around 20% in developed countries [1] each year. Macrosomia can increase maternal birth complications such as prolonged labor, obstructed Labour, caesarian section delivery, uterine rupture, postpartum hemorrhage, and genital lacerations. It also increases the risks of newborn complications like fractures, shoulder dystocia, brachial plexus injuries, hypoglycemia, neonatal asphyxia, infection, and perinatal death [5,6,7]. In addition, macrosomia increases the risks of long-term childhood problems such as cardiovascular disorder, obesity, and insulin resistance in adulthood [8,9,10,11].

The burden of macrosomia varies from region to region, which ranges from 5 to 20% in developed countries [12] and 2–9% in developing countries [2, 12]. The prevalence of macrosomia was 8.3% in sub-Saharan Africa (SSA). The studies indicated that the burden of macrosomia ranges from 6 to 19% in Ethiopia [13,14,15].

There are various factors affecting the burden of macrosomia in developing countries. These are sociodemographic factors, parity, gestational age, previous macrosomia, pre-pregnancy body mass index, and pre-existing maternal diabetic mellitus [13, 14, 16].

World Health Organization (WHO) implemented different strategies to reduce maternal and neonatal mortality [17]. However, despite the increasing number of newborns with macrosomia, it still remains unaddressed problem in Ethiopia. The data shows factors increasing macrosomia were limited in Ethiopia generally. Previous studies have assessed the burden of macrosomia rather than determinants, which could not identify the risk factors [14, 16]. In addition, a few previous studies were focused on nonmodifiable risk factors and conducted in one site region of the country [13, 18]. Overall, there is a lack of evidence on the factors that affect macrosomia in eastern Ethiopia. This study aimed to assess determinants of macrosomia among newborns delivered in public hospitals in Jigjiga City, Eastern Ethiopia.

Methods and materials

Study design, area and period

An institutional-based case-control study was conducted among 82 cases and 164 controls in public hospitals in Jigjiga city from June 25 to August 24, 2023. Jigjiga City is the capital of the Somali regional state, located 620 km east of Addis Ababa (the capital city of Ethiopia). Jigjiga City has a total population of 417,688: 202,050 females, 91,892 women in the reproductive age group, 14,494 pregnant women, and 13,450 infant children. According to Jigjiga city health office reports, 18% of women during childbirth were attended by skilled health professionals at the end of 2022. There are three public hospitals, three health centers, and 24 health posts in the city.

Study population

All mothers who delivered newborn babies in public hospitals in Jigjiga city during study period were the study population. Cases were all newborns delivered with birth weights of ≥ 4000 g in public hospitals in Jigjiga city and Controls were those newborns delivered with birth weights between 2500 and 3999 g during the data collection period.

Eligibility criteria

The mothers who gave birth alive child with a birthweight of ≥ 4000 g at public hospitals in Jigjiga city during the study period were included as cases. The mothers who gave birth alive child with a birth weight between 2500 and 3999 g at public Hospitals in Jigjiga city during study period were included as controls. Critically sick mothers who were unable to respond to interviews and those who experienced pregnancy-related complications (placenta abruption, placenta previa, multiple pregnancies, pre-term delivery, pregnancy-induced hypertension, intrauterine growth retardation, and congenital anomalies) for both cases and controls were excluded from the study.

Sample size determination and sampling

A total sample size (n = 246) was determined by Epi-Info version 7.1 using a double population proportion formula considering the following assumptions: a 95% confidence interval (CI), 80% power, 5% margin of error, two-to-one control case ratio, 6.0% proportion of exposed control, an adjusted odds ratio (AOR) of 3.4 [13, 18] and adding 10% of the non-response rate. The final sample size needed for this study was 246 (cases 82 and controls 164) mothers-newborn pairs.

Three public hospitals in Jigjiga city were selected purposefully. The estimated sample size was allocated proportionally to each hospital based on average delivery case flows in the last three months. Accordingly, the delivery case flows over three months were 1050 in Jigjiga University Sheik Hassen Yabare Referral Hospital (JJUSHYRH), 1170 in Karamara General Hospital (KGH), and 430 in Jigjiga Primary Hospital (JPH). First, an eligible case was selected and interviewed, followed by two controls from the same hospital consecutively until the required size was obtained.

Data collection tools and procedure

The data was collected using a structured questionnaire adapted from previously published literature [13, 18, 19]. The questionnaire contains sociodemographic characteristics, reproductive health factors, health facility-related factors, maternal physical activity, and newborn weight. The data was collected from the mothers using face-to-face interviews. However, the sex and weight of the newborn were reviewed from the newborn’s card. Six data collectors collected the data under the supervision of two supervisors after training for one day on the objective and data collection techniques.

Operational definitions

Cases and Controls

Cases: a newborn whose birth weight is greater than or equal to 4000 g. Controls: a newborn whose birth weight is between 2500 g and 3999 g [20].

Physical activities during pregnancy

Were assessed using ten items asking time spent on daily activities, each coded to ‘1’ (when spending greater than or equal to 30 min per day) and to ‘0’ (when spending less than 30 min per day) and then a composite index score was computed from the ten items. The mothers who scored greater than or equal to five index score were considered to have higher physical activity and unless otherwise low physical activity [21].

Preconception care utilization

The mothers considered to have received preconception care if they received at least one type of intervention (advice, treatment, and lifestyle modification care) at least once before the current pregnancy and not received unless otherwise [22].

Dietary diversity of women

It was measured using ten dichotomous (yes/no) items (asking about food groups consumed by pregnant women in the previous 24 h) coded ‘1’ (when consuming a given food group) and ‘0’ (when not consuming a given food group). Then, the composite index score was computed from 10 items (Grain and white roots, tubers and plantains, Pulses, Nuts and seeds, Dairy, Meat and poultry and fishes, Eggs, Dark green leafy vegetables, Other Vitamin-rich fruits and vegetables, other vegetables, other fruits). The level of dietary diversity was considered ‘high’ when the participant has consumed at least five food groups and ‘low’ unless otherwise [23].

Data quality control

The data quality was ensured using questionnaires adapted from pertinent published literature. These questionnaires were first prepared in English and then translated into local languages (Afsomale and Amharic) and back to English by experts who were proficient in both languages. We pretested the adapted questionnaires on 5% of the total sample (four cases and eight controls) at a separate, non-selected facility to verify their validity. Six data collectors collected the data under the supervision of two supervisors. The data collectors and supervisors were trained for one day on the study’s objective and data collection techniques. During data collection, strict supervision of the data collectors and validation of the collected data was carried out by two supervisors and the principal investigator.

Data processing and analysis

After thoroughly reviewing the data for completeness and consistency, we entered the data into EpiData version 3.1 and analyzed it using SPSS version 27. Descriptive statistics, such as frequency, measures of central tendency, and measures of dispersion were used to characterize the cases and controls. Before conducting the analysis, we checked the internal consistency of the items for the composite index score using reliability analysis (Cronbach α). Our results showed high internal consistency for physical activity use items (Cronbach’s α = 0.77) and the dietary diversity of the women’s use items (Cronbach’s α = 0.85). Bivariable and multivariable logistic regression analyses were used to determine the determinants of macrosomia. A variable with a p-value of < 0.2 in bivariable logistic regression was entered into multivariable logistic regression to assess the significant determinants of macrosomia. The overall model fitness was confirmed using the Hosmer and Lemeshow goodness of fit test, which yielded a p-value > 0.05. The strength of the association was reported using adjusted odds ratios (AOR) with 95% confidence intervals (CI), and statistical significance declared at a p-value < 0.05.

Results

Socio demographic characteristics

A total of 82 cases and 164 controls participated in this study, with a 100% response rate. The majority of cases (54.9%) and controls (56.6%) were in the 25–34 years age groups. The means (± SD) age of cases and controls were 30.5 (± 6) and 27.2 (± 7) years, respectively. About 89% of cases and 80% of controls were from urban residences. Ninety (23.2%) of cases and 45 (27.4%) of controls with educational status were unable read and write. The mean (± SD) of the monthly income of cases and controls was 6234 (± 3485) and 6391 (± 3533) Ethiopian Birr (ETB), respectively. Half (50.0%) of cases and almost half (48.2%) of controls monthly incomes were greater than 6,000 ETB (Table 1).

Table 1 Sociodemographic characteristics of mothers who delivered at public health hospitals in Jigjiga city, eastern Ethiopia, 2023 (n = 246)
Full size table

Obstetric and lifestyle related characteristics

The mean (± SD) parity of cases and controls were 4.4 (± 2.1) and 3.4 (± 2.1), respectively, and 7.3% of cases and 23.2% of controls were primiparous with respect to utilization of preconception care, 45.7% of cases and 62.2% of controls did not receive preconception care during the current pregnancy. Twenty-one (25.6%) cases and 32 (19.5%) controls had never attended antenatal care during the last pregnancy. One-fourth (26.8%) of cases and one-tenth (9.1%) of controls had low physical activity during pregnancy, with the median of physical activity and interquartile range (IQR) of cases and controls being 5 (IQR = 5.9; 25th percentile = 4 and 75th percentile = 9) and 6 (IQR = 4; 25th percentile = 6 and 75th percentile = 10), respectively. Thirty-two (39.0%) of cases and 18 (11.0%) of controls had a previous history of macrosomia, and 25.6% of cases and 7.3% of controls had ever-developed gestational diabetes mellitus. The majority of cases (68.3%) and controls (57.9%) consumed low dietary diversity in the last 24 h, with mean (± SD) dietary diversity feeding levels of cases and controls of 4.0 (± 2.7) and 4.7 (± 2.3), respectively (Table 2).

Table 2 Obstetric and lifestyle related characteristics of mothers delivered at public hospitals in Jigjiga, city, eastern Ethiopia, 2023 (n = 246)
Full size table

Determinants of macrosomia

In bivariable logistic regression, the age of the mother, preconception care, gestational age, parity, physical activity, previous macrosomia, GDM, and sex of neonate were factors associated with macrosomia. However, in multivariable logistic regression, preconception care, gestational age, physical activity, previous macrosomia, and GDM were remained the determinants of macrosomia.

The odds of neonate macrosomia among mothers who did not receive preconception care were 2.5 times higher (AOR = 2.48, 95% CI: 1.29, 4.76) than those who received preconception care. The newborns who were delivered at post-term gestational age were 2.9 times more likely to be macrosomic (AOR = 2.90, 95% CI: 1.16, 7.28) compared with those who were delivered at term. The mothers who were not physically active during pregnancy were 3.5 times (AOR = 3.52, 95% CI: 1.55, 7.98) more likely to deliver macrocosmic newborns than those who were physically active. The odds of newborn macrosomia among mothers who had a previous history of macrosomia were 4.5 times higher compared with their counterparts (AOR = 4.52, 95% CI: 2.18, 9.36). The mothers who had GDM were 2.6 times more likely to deliver newborn macrosomia (AOR = 2.58, 95% CI: 1.10, 6.28) compared with those who did not GDM (Table 3).

Table 3 Determinants of macrosomia among newborn delivered at public hospital in Jigjiga City, eastern Ethiopia, 2023 (n = 246)
Full size table

Discussion

This study assessed the determinants of macrosomia among newborns delivered in public hospitals in Jigjiga City, eastern Ethiopia. The finding of this study shows that lack of preconception care, post-term pregnancy, being physically inactive during pregnancy, having previous macrosomia, and having GDM were the main risk factors of macrosomia.

The finding of this study indicated the utilization of preconception care was significantly associated with fetal macrosomia. The newborns who were delivered from mothers who did not utilize preconception care were 2.5 times more likely macrocosmic compared with those who were from mothers who utilized preconception care. Preconception care is a strategic intervention that helps to improve birth outcomes by addressing modifiable risk factors and optimizing maternal and fetal health, which helps to reduce maternal GDM, excessive weight gain, and fetal macrosomia [24].

The newborns delivered during post-term were almost three times more likely to bemacrosomic than those delivered during term gestational age. This finding was supported by the studies conducted in Northwest Ethiopia [13, 19], Southern Ethiopia [16], Tanzania [2], Malesia [25], and Iraq [26]. The possible justification might increase fetal weight gain especially in 3rd trimester may lead to fetal macrosomia [21].

The findings of this study revealed that physical activity was an important determinant of fetal macrosomia. The odds of macrosomia among newborns from mothers with inadequate physical activity during pregnancy were 3.5 times higher than those from mothers with adequate physical activity during pregnancy. This finding is supported by the study conducted in southern Ethiopia, northwest Ethiopia, Morocco, France, and Brazil [14, 18, 19, 27]. It implies that adequate physical activity during pregnancy reduces the level of fetal macrosomia. A lack of physical activity during pregnancy could lead to excessive gestational weight gain due to enhanced maternal fat storage and fetal adiposity [28]. On the other hand, regular physical activity conducted during pregnancy could help to reduce the risks of GDM, which is the primary risk of fetal macrosomia [29]. Therefore, this study suggests that conducting physical activity throughout pregnancy may be a method to help reduce fetal macrosomia without increasing the risks of low birth weight [30].

In addition, the findings of this study indicated that previous history of macrosomia increase the risk of macrosomia by 4.5 times. This finding is supported by the studies conducted in Northwest Ethiopia [13], Northern Ethiopia [14], Southern Ethiopia [16], Lithuania [31], and Iran [32].

Furthermore, the study revealed that newborns who were delivered from mothers who had GDM were 2.6 times more likely to have macrosomia compared to their counterparts. This finding is in agreement with the studies done in Northwest Ethiopia [13], Tanzania [2], Saud Arabia [33], and Malaysia [25]. Diabetic mellitus causes impairment of maternal glycemic control and high blood glucose levels, which leads to hyperglycemia crossing the placenta barrier. Fetal hyperglycemia leads to increased insulin secretion, insulin-like growth factors, growth hormones, and other growth factors that stimulate fetal tissue growth, the deposition of fat, and an increase in glycogen in the fetus, resulting in macrosomia [4].

The strength of this study is that a case-control study design was used to determine multiple determinants of macrosomia. Multiple data collection methods, such as face-to-face interviews, medical record reviews, and measurements, were used to collect the data. The study limitation was that some of the questions about the last normal menstrual period and events 24 h before might introduce recall bias, which can affect the true relations between exposure and disease.

Conclusion

This study identified the determinants of fetal macrosomia. Utilization of preconception care, physical activity during pregnancy, gestational age, GDM, and previous macrosomia were the main determinants of macrosomia. Providing attention to modifiable factors like utilization of preconception care and physical activity during pregnancy is essential to reducing and preventing the risks of fetal macrosomia at a community level. In addition, providing recommended care and follow-up for mothers with high risk for fetal macrosomia through early detection and management of the risks would be needed to reduce and prevent the burden of macrosomia and its consequences.

Data availability

Data that supports the findings is available and will be provided by the correspondence author on a reasonable request.

Abbreviations

AOR:

Adjusted Odds Ratio

COR:

Crude Odds Ratio

ANC:

Antenatal Care

GDM:

Gestational Diabetic Mellitus

LIMIC:

Lower Middle-Income Countries

SSA:

sub-Saharan Africa

WHO:

World Health Organization

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Acknowledgements

We acknowledged the participants and supervisors for their valuable contributions and efforts. The authors thank Haramaya University for providing the opportunity to conduct the study. We also appreciated Jigjiga City health office and their public health facilities for providing the background information of the study setting.

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Authors and Affiliations

  1. School of Public Health, College of Medical and Health Sciences, Jigjiga University, Jigjiga, Ethiopia

    Abdisalan Elmi Farah

  2. School of Public Health, College of Health and Medical Sciences, Haramaya University, Harar, Ethiopia

    Dureti Abdurahman, Hassen Abdi Adem & Saba Hailu

  3. School of Nursing and Midwifery, College of Health and Medical Sciences, Haramaya University, Harar, Ethiopia

    Kassiye Shiferaw, Ahmedin Aliyi Usso & Mohammed Abdurke Kure

  4. School of Medical Laboratory Sciences, College of Health and Medical Sciences, Haramaya University, Harar, Ethiopia

    Beker Feto

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Contributions

AEF, DA, KS, AAU, MAK, BF, HAA, and SH participated in the conception of the idea, development, and amendment of the proposal, data collection, and analysis, and write up the results. AEF, DA, KS, AAU, MAK, BF, HAA, and SH analyzed the data. AAU drafted the manuscript with continuous input from AEF, DA, KS, AAU, MAK, BF, HAA, and SH reviewed the manuscript for intellectual content. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Ahmedin Aliyi Usso.

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Ethical approval

The study was conducted in accordance with the Helsinki Declaration of researches involving human subjects [34]. The study was also approved by the Institutional Health Research Ethical Review Committee of the College of Health and Medical Sciences, Haramaya University, Ethiopia (Ref, no: IHRERC/107/2023). Written informed consent was obtained from all participants after explaining the purpose and benefits of the study.

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The authors declare no competing interests.

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Farah, A.E., Abdurahman, D., Shiferaw, K. et al. Determinants of macrosomia among newborns delivered in Jigjiga City, Eastern Ethiopia: a case-control study. matern health, neonatol and perinatol 10, 23 (2024). https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s40748-024-00194-4

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Keywords

Maternal Health, Neonatology and Perinatology

ISSN: 2054-958X

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