1. Introduction
Macrosomia is defined as a birth weight either greater than 4000 g or over the 90th percentile for gestational age [1] . Its prevalence varies through the world according to racial and ethnic factors, life style and importance of non communicable diseases (maternal obesity, diabetes-gestational and type 2), post-term gestation and multiparity. The variation of prevalence has also been observed in time for the same population [2] [3] [4] [5] . In developed countries, the prevalence of macrosomia, which was between 5% and 20% in 1980 increased by 15% - 25% in 2007 [2] . In Europe, a Danish study reported an increase in macrosomia incidence from 16.7% in 1990 to 20% in 1999 [3] . Figures from North America show that proportion of newborns with a birth weight above 90th percentile increased from 5% - 9% in United States and 24% in Canada between 1985 and 1988 [6] . A Chinese study noted an increase of 6% in 1994, and 7.8% in 2005 [4] . In Africa, macrosomia prevalence varies from 1% to 15% [7] - [13] . In the Democratic Republic of Congo (DRC), previous studies (30 years ago) estimated its prevalence at 2.4% - 2.7 % [13] [14] . Since then, no other study addressed this subject. Our study purpose was to update data on frequency of macrosomia at UCK, regarding variation in maternal anthropometrics (obesity) and socio-demographic factors.
2. Methods
This cross-sectional study conducted at UCK from 1 January 2007 to 31 December 2016 included all women who delivered babies with macrosomia. All records of pregnant women who gave birth to babies with macrosomia at UCK during study period were included. Files containing less than 50% of the variables studied were excluded from this study. A total of 8268 births were recorded during this period and 308 babies were born with macrosoma. Data were collected by review of medical records from delivery room and maternity. Variables collected were maternal age, weight, height, body mass index, parity, gravidity, medical history and pregnancy outcomes (obstetrical pathology, gestational age and mode of delivery). Newborns parameters included weight, APGAR, sex, size, head circumference (HC) and thoracic circumference (TC), type of macrosomia defined by ratio of HC to TC (a ratio of ˂1 defining constitutional macrosomia and that ≥1 defining diabetic macrosomia), congenital malformations and neonatal glycemia. Postpartum adverse outcomes (uterine atony, haemorrhage, endometritis, soft tissue lacerations, puerperal infections) were also recorded.
Statistical analysis
Data were verified, numbered and entered using Microsoft Office Excel software; and then exported to SPSS (Statistical Package for Social Sciences) version 21.0 for appropriate statistical analysis. Quantitative data were summarized as means and standard deviations, and categorical data as frequencies. The study received approval from the ethical board of Department of Obstetrics and Gynecology of UCK.
3. Results
In this study we numbered 308 cases of macrosomia out of a total of 8268 deliveries. The frequency was 3.7%. Only 152 files were eligible for study (containing more than 50% of study variables). Figure 1 shows evolution of annual frequency of macrosomia at UCK since 2007. Trend shows a variation of the frequency over time with lowest frequency (2.1%) in 2012 and highest (5.3%) in 2009.
The mean maternal age was 32.3 ± 5.4 years, the majority of mothers (66.4%) having an age range from 20 to 34 years. The mean parity and gravidity were 3 ± 2. Multipara and multigravida were 80.9% and 88.8%, respectively. Average maternal weight was 84.7 ± 15.1 kg, and 53.3% had less than 90 kg. Mean of Body Mass Index (BMI) was 30.1 ± 5.1 Kg/m2 and 51.3% were obese (Table 1).
As presented in Table 2, risk factors of macrosomia were dominated by BMI > 25 Kg/m2 (80.9%), followed by male fetus (58.6%), maternal overweight (46.7%) and advanced maternal age (33.6%).
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Figure 1. Annual frequency of macrosomia.
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Table 1. General maternal characteristics of the study sample.
BMI: Body mass index, *Only 152 files were eligible for this study.
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Table 2. Risk factors of macrosomia.
BMI: Body Mass Index.
Concerning delivery characteristics, mean gestational age was 39.4 ± 1.6 weeks, mean uterine fundal-height at the admission in the delivery room was 36.7 ± 2.6 cm and 98.7% of deliveries occurred at term and in 60.5% of cases by Caesarean section. Table 3 shows that C-section was performed in 47.8% for fetal macrosomia.
Average APGAR score was 8 ± 2 at birth, and 9 ± 1 at the fifth minute. Table 4 shows that 90.8% of newborns had a good APGAR score at birth and 92.1% at the fifth minute. The means of birth weight, height, head and thoracic circumferences were 4235.2 ± 314.2 g, 51.8 ± 1.9 cm, 36.5 ± 2.1 cm and 35.2 ± 1.7 cm, respectively. Male newborns represented 58.6% of newborns, with a sex ratio of 0.77. In 81.6% of cases, macrosomia was constitutional.
Maternal and perinatal adverse outcomes associated with macrosomia, presented in Table 5, were dominated, on maternal side, by Caesarean section (28.9%) and lacerations of birth canal (23%), and neonatal distress on perinatal side (9.2%).
4. Discussion
In the present study, the frequency of macrosomia at UCK was 3.7%, higher than that (2.7%) reported 30 years ago [13] [14] . This could be owed to changes in maternal BMI [15] . Trend showing a variation of this frequency over time between 5.3% in 2009 and 2.1% in 2012 is difficult to explain. This frequency is slightly lower than 5.6%, 5.7%, 6.6% and 7% as reported in Saudi Arabia [16] , in Lubumbashi (DRC) [17] , in France [18] and in Turkey [19] , respectively. It’s higher than those reported in some other studies in Africa by Badji et al. [20] , in
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Table 3. Indications of cesarean section.
HC: head circumference, TC: Thoracic circumference.
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Table 5. Adverse outcomes of macrosomia.
Senegal, by Thieba et al. [21] , in Burkina-Faso and by Kakudji et al. [12] , in Kinshasa (DRC) and also by Cheng et al. [5] , in China who reported 1.57%, 2.1%, 2.4% and 3.4% respectively. However, our frequency is very lower than those reported by Ananth et al. [6] , in Canada (24%) between 1992 and 1996 and by Jensen et al. [22] in Denmark (28%).
Our results are in accordance with literature data which show variation of incidence according to racial and ethnic differences but also with presence of local factors in different regions [2] . The lower frequency reported by Cheng et al. [23] , could be explained by the difference in birth weight distribution probably due to genetic differences and anthropometric disparities between populations. The lower frequency reported in african studies could principally be explained by nutritional insufficiency and lower socio-economic level.
Macrosomia in our study was mostly observed in mothers with BMI ≥ 25 Kg/m2 (80.9%), with maternal weight ≥ 90 Kg (46.7%). Several studies have reported higher frequencies of macrosomia in obese women [24] [25] [26] , and Henriksen [2] , found BMI as independent factor of macrosomia. The combination of maternal-transmitted fetal hyperglycemia and fetal hyperinsulinism could explain the high rate of macrosomia in newborns of obese non-diabetic mothers [9] .
Concerning newborns gender, 58.6% were male, a finding also reported in Lubumbashi [13] [17] , Rabat [25] , and Brazzaville [27] , where it was reported a frequency of male newborn above 60%. This is in accordance with the role of male hormones.
In our study, 80.9% of mothers were multipara. Studies have shown that multiparity is a factor that increases risk of macrosomia, irrespective of its association with maternal age. Our results corroborate those of most authors [7] [9] [11] [17] [19] [27] . This finding could be the expression of obesity or diabetes whose risk increases with age. Advanced maternal age (≥ 35 years) and multiparity were associated with fetal macrosomia in our series (33.6% and 32.2% respectively).
In this study, pregnant women also had a family history of diabetes type 2 (14.5%) or developed gestational diabetes during pregnancy (19.7%). Das et al. [28] and Saleh et al. [16] reported that diabetes, regardless of its clinical form (type 2 or gestational), is an important factor involved in risk of macrosomia. This is in accordance whith diabetes and obesity as well known risk factors of macrosomia. Our results are consistent with those of several authors [17] [19] [28] [29] [30] . The mechanism, reported in literature, to explain this association is interdependence of metabolism of carbohydrates and lipids, resulting in fetal hyperinsulinism reaction to maternal hyperglycemia. Increased production of insulin, an anabolic hormone, forces carbohydrates into cells, accumulates fatty acids in adipose tissue and proteins in muscles, which is responsible for the onset of macrosomia [17] [31] [32] . Macrosomia was associated with maternal and perinatal adverse outcomes. Higher risks of infant mortality and traumatic injuries during childbirth have also been reported by Zhang et al. [33] , for macrosome neonates with a birth weight greater than 4.500 g. Heiskanen [34] , particularly cited clavicle or humerus fractures, brachial or facial paralysis, and shoulder dystocia. The most common complications of macrosomia in our study were Cesarean section (28.9%) and soft tissue injuries (23%), while for newborn, it was perpartal distress (9.2%). Chauhan et al. [35] and Zhang et al. [33] , also reported maternal adverse outcomes associated with fetal macrosomia, including prolonged labor, cesarean section and postpartum hemorrhage.
Further research must be focused on the recognition of risk factors during the antenatal visit care and its prevention in the aim to reduce its incidence and thus the related complications.
The main limitation of this study could be found in the fact that it concerned only one site (monocentric study), which limits extrapolation of results.
5. Conclusion
Macrosomia remains a constant finding at UCK, and is associated with maternal, fetal and neonatal adverse outcomes. Trend shows a variation of this frequency over time between 2.1% and 5.3%.
Author Contributions
All authors contributed toward data analysis, drafting and revising the paper and agree to be accountable for all aspects of the work.
Disclosure
The authors report no conflict of interest in this work.