|Year : 2014 | Volume
| Issue : 1 | Page : 8-12
Maternal anthropometric characteristics as determinants of birth weight in North-West Nigeria: A prospective study
Emmanuel Ajuluchukwu Ugwa
Department of Obstetrics and Gynaecology, Federal Medical Centre, Birnin Kudu, Jigawa, Nigeria
|Date of Web Publication||7-Apr-2014|
Emmanuel Ajuluchukwu Ugwa
Department of Obstetrics and Gynaecology, Federal Medical Centre, Birnin Kudu, Jigawa
Source of Support: None, Conflict of Interest: None
Background/Aim: Foetal weight cannot be measured directly in utero, but it can be estimated or predicted from foetal and maternal anatomical characteristics. This study was undertaken to examine the relationship between birth weights and certain maternal anthropometric measurements (weight, height and BMI). Context/Setting: This study was done in Aminu Kano Teaching Hospital (AKTH), North-West, Nigeria. Aminu Kano Teaching Hospital is a 500-bed tertiary hospital located in Kano, the most populous state in Nigeria. Materials and Methods: This was a prospective study. Interviewer-administered questionnaires were used to retrieve sociodemographic and obstetrics information. Two-hundred (88.9%) pregnant women responded completely. The weight, height and BMI of the women were measured. Unclothed newborns were weighed immediately after delivery. The data obtained was analysed using SPSS version 16.0 statistical software. The accuracy of maternal weight, height and body mass index in predicting birth weight was compared using Student's t-test, Chi-square test and Pearson's Coefficient of Correlation and P < 0.05 was considered statistically significant. Results: The mean maternal age was 28.2 ± 5.7 years. The mean parity was 3 ± 2. The mean gestational age at delivery was 38.5 ± 2 years. The mean actual birth weight was 3.27 ± 0.53 kg. The mean maternal weight was 72.03 ± 11 kg. Maternal weight showed a strong positive correlation with birth weight ( r = 0.48) and this was statistically significant ( P < 0.001). The mean maternal height was 1.64 ± 0.55 m. The mean maternal BMI was 27.9 ± 4.33. Maternal BMI showed a weak positive correlation with birth weight ( r = 0.28) and this was statistically significant ( P < 0.001). Maternal weight and BMI are better predictors of birth weight than maternal height. Conclusion: Maternal weight and BMI are good predictors of birth weight and can be recommended for use as screening test in poor resource setting.
Keywords: Anthropometric characteristics, birth weight, determinants, maternal, Nigeria, north-west, prospective study
|How to cite this article:|
Ugwa EA. Maternal anthropometric characteristics as determinants of birth weight in North-West Nigeria: A prospective study. Niger J Basic Clin Sci 2014;11:8-12
|How to cite this URL:|
Ugwa EA. Maternal anthropometric characteristics as determinants of birth weight in North-West Nigeria: A prospective study. Niger J Basic Clin Sci [serial online] 2014 [cited 2019 Jul 20];11:8-12. Available from: http://www.njbcs.net/text.asp?2014/11/1/8/130151
| Introduction|| |
Maternal exposure to nutrition during the period from conception to birth may have an impact on foetal growth as well as the child's health. , In particular, maternal nutrition during pregnancy has been regarded as an important determinant for foetal growth.  Infant size, such as birth weight and length, was reported to affect not only infant mortality, but also childhood morbidity. , Severe under nutrition could lead to permanent changes in structure and metabolism in the fetus. It is uncommon in developed countries but this is not the case in developing countries where the imbalance or relative deficiency of nutrients could affect foetal growth. ,
Both foetal macrosomia and intrauterine growth restriction increase the risk of perinatal morbidity and mortality. Therefore, when these conditions are diagnosed in utero an appropriate route of delivery is undertaken to forestall these complications.  Foetal weight cannot be measured directly in utero, but it can be estimated or predicted from foetal and maternal anatomical characteristics. Maternal anthropometric measurements provide a simple, cheap and available means of predicting birth weight with a variable degree of reliability. These have been widely studied in other countries, ,,,,,, but studies are still scanty in the developing world where maternal undernutrition is a predisposing factor to poor obstetrics outcome and perinatal morbidity/mortality. ,
Factors that determine birth weight are maternal height, malnutrition, maternal obesity, maternal pregnancy weight gain, parity, foetal sex, ambient attitude, maternal haemoglobin concentration, paternal height, cigarette smoking and glucose intolerance.  In third-world countries where poverty among women of reproductive age is prevalent, malnutrition is a common factor that can substantially affect the size of neonates at all gestational ages.  Other factors that determine foetal birth weight include maternal factors such as race, stature and genetics. ,, Paternal factors such as paternal height also determines birth weight. , Environmental factors that determine foetal birth weight are attitude, nutrition and physical activities.  Altered glucose metabolism, haemoglobin concentration and microvascular integrity are physiological factors known to affect birth weight. Pathological factors such as hypertension and uterine malformations, and complications of pregnancy such as gestational diabetes mellitus and pre-eclampsia are also important determinants of birth weight. , A systematic review of 36 studies found that in addition to paternal height, paternal age, paternal birth weight, paternal occupational exposure and educational level also determine birth weight of an infant.  Others workers have shown that both maternal and paternal anthropometric measures affect birth weight. , Gestational age at delivery is a significant determinant of newborn weight. , A systematic difference has also been observed in the mean birth weight of babies born to mothers of different races and ethnicities and mean birth weight can differ as much as 141-395 g at term depending on maternal race.  If a single birth weight standard is used, Caucasian women have a significantly higher prevalence of foetal macrosomia compared with that of African-American and Asian women who are more prone to having small-for-age newborns. , Maternal illnesses and complications of pregnancy also affect birth weight. The most common are chronic hypertension and pre-eclampsia both of which cause low birth weight.  Intrauterine infections such as toxoplasmosis, rubella, cytomegalovirus, herpes and syphilis (TORCHES) complex, chromosomal abnormalities and congenital syndromes are all associated with low birth weight. 
Evaluation of maternal nutritional status relies on measures such as pre-pregnancy weight, height, body mass index (BMI) and weight gain at different trimesters, weight gain during pregnancy and skinfold thickness. Maternal weight, height and pregnancy weight gain have all been shown to be significant predictors of birth weight.  Numerous research projects have studied maternal anthropometric characteristics as predictors of birth weight. ,,,, Although there is considerable work done on this topic in other countries, the present work was done among women presenting for delivery at Aminu Kano Teaching Hospital (AKTH), North-West Nigeria where such studies have been lacking.
The aim of this study was to examine the relationship between the birth weights of babies delivered between 1 st September and 31 st December 2011 in AKTH at various gestational ages with certain maternal anthropometric measurements (weight, height and BMI). This can be recommended for use among peripheral health workers for detection of mothers at risk of delivering big or low birth weight babies and the need for in utero transfer to centres where Caesarean section and neonatal care can be offered. The findings of this study will also form a basis for recommending nutritional balance as part of pre-natal care.
| Materials and Methods|| |
This was a prospective cohort study. The study subjects were consecutive pregnant women with singleton pregnancy admitted for either vaginal or planned abdominal delivery between 1 st September and 31 st December 2011. Ethical approval from Aminu Kano Teaching Hospital Ethics Committee and informed consent from subjects were obtained. Sample size was determined by using the formula:
Zα = standard normal deviation corresponding to 95% confidence level = 1.96 from normal distribution table; zβ = power of the study to detect difference, 80% used = 0.64 from normal distribution table; d = difference between means = 0.1kg (from a previous similar study in South-West, Nigeria)  ; s = standard deviation in the clinical estimate group (0.361) obtained from a previous similar study. 
This was rounded up to 225 to increase precision and account for non-response. Two hundred and twenty-five (225) consecutive pregnant women who fulfilled the inclusion criteria were counseled and, after consenting, were included in the study. Inclusion criteria include; singleton pregnancy, admission for planned delivery (both vaginally and abdominally) and gestational age of 28 complete weeks and above by last menstrual period or sonographic dating. Exclusion criteria include; patients refusal, obese patients (weight more than 90 kg), and patients with polyhydramnios, ruptured membranes, multiple pregnancies, oligohydramnios, intrauterine foetal death and pregnancy with uterine or adnexal pathology.
Interviewer administered questionnaires were used to obtain sociodemographic and clinical information. Pre-testing of the questionnaire was done at AKTH where 20 self-administered questionnaires were distributed to participants to comment on the clarity of the questions. The weight and height of all the recruited women were measured during the admission for delivery.
The study subjects were weighed and height was taken using spring balance (adult) weighing scale and free-standing height measure Marsden H 628 model made in United Kingdom made in England; with minimum clothing after correcting zero error. The weight was recorded to the nearest 50 g. The height was measured keeping the women standing on level ground, without footwear, against a wall, by using measuring tape to the nearest 0.5 cm. The maternal weight and height obtained was used to calculate maternal BMI (kg/m 2 ). Similarly, unclothed newborns were weighed immediately after delivery using a standard analogue Salters (England) scale corrected for zero error. The interval between anthropometric measurements and delivery of the babies was within 24 hours.
The data obtained was analysed using SPSS version 16.0 statistical software. Absolute numbers and simple percentages were used to describe categorical variables. Similarly, quantitative variables were described using measures of central tendency (mean, median) and measures of dispersion (range, standard deviation) as appropriate. The accuracy of maternal weight, height and body mass index in predicting birth weight was compared using Students' t-test, Chi-square test and Pearson's Coefficient of Correlation. Statistically significant associations between maternal anthropometric measurements and birth weight was considered when P < 0.05.
| Results|| |
Two-hundred (200) women completed the study and 25 were drop-out. The response rate was 88.9%.
[Table 1] shows that hundred women (50%) were aged, 15-24 years, 96 women (48%) were aged, 25-39 years and only 4 women (2%) were aged, 40-49 years. The mean maternal age was 28.2 ± 5.7 years. One hundred and forty-five women (73%) were unemployed and 55 (27%) were employed. Seventy-six women (38%) were of parities 1-2, 116 (58%) were parities 3-4 and 24 (12%) were of parities ≥ 5. The mean parity was 3 ± 2. One hundred and sixty-four women (82%) were delivered at gestational age of 38-40, while 18 women were delivered at < 38 weeks (9%) and another 18 women at > 40 weeks (9%). The average gestational age at delivery was 38.5 ± 2 years. Ninety-nine women (49.5%) had tertiary education, 84 (42%) had secondary education, 9 (4.5%) had primary education, 4 (2%) had Qua'ranic education and 2 (1%) had no form of education.
|Table 1: Distribution of socio-demographic characteristics of the study group|
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[Table 2] shows that 10 newborns (5%) weighed < 2.5 kg, 176 (88%) weighed 2.5-3.99 kg and 14 (7%) weighed ≥ 4 kg. The mean actual birth weight was 3.27 ± 0.53 kg.
|Table 2: Distribution of actual birth weight of the babies in the study group|
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[Table 3] shows that most of the women 32.5% weighed between 61 and 70 kg and 17.5% weighed 51and 60 kg. The mean weight was 72.03 ± 11. Maternal weighed showed a strong positive correlation with birth weight (r = 0.48) and this was statistically significant (P < 0.001). Forty-seven (47) percent of the women were 1.6-1.69-m tall and only 13% were 1.70-1.79 m. The mean height was 1.64 ± 0.55. Maternal height showed a strong positive correlation with birth weight (r = 0.25) and this was statistically significant (P < 0.001). Most of the women, 62.5% had BMI of 25-34.99 while 5% had BMI in the morbid obesity spectrum of 35-44.99. The mean BMI was 27.9 ± 4.33. Maternal BMI showed a weak positive correlation with birth weight (r = 0.28) and this was statistically significant (P < 0.001).
|Table 3: Distribution of anthropometric characteristics and their correlation with birth weight|
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| Discussion|| |
Studies in other countries , have shown that mothers who are malnourished are more likely to give birth to low-birth-weight babies and vice versa. Furthermore, studies in Nigeria by Kemiki and Akindele,  and also by Fakeye and Adetoro  have shown that birth weight correlated well with maternal weight. This is consistent with the report of the present study where maternal weight and BMI showed positive correlation with birth weight of their infants.
The mean birth weight from this study was 3.27 kg ± 0.53 kg. This was similar to studies in Ile-Ife, Nigeria, where Shittu et al., reported an actual average birth weight of 3.255 ± 0.625 kg and Ayoola et al., who reported mean birth weight of 3.238 ± 0.452 kg.  These reports from developing countries were comparable with those of studies from Great Britain and Singapore that showed that the mean birth weight at 38-42 completed weeks' gestation was 3.201-3.753 g (range, 0.551 g)  and 2.880-3.290 g (range, 0.410 g),  respectively. The mean birth weight is, however, higher than 2.746 ± 0.40 kg reported in India where 17.30% of the newborns had low birth weight compared to 5% in the present study.  The explanation was that poverty, chronic under nutrition and poor living conditions exist among a huge population of Indian mothers.
The present study showed significant positive correlations between maternal weight and birth weight (r = 0.48), maternal height and birth weight (r = 0.25), maternal body mass index and birth weight (r = 0.28). This was comparable to significant positive correlations observed among maternal weight and birth weight (r = 0.38), maternal height and birth weight (r = 0.25), and maternal body mass index (BMI) and birth weight (r = 0.30) reported by Mohanty et al. From the above report maternal weight was the strongest determinant of birth weight. This was also confirmed in regression analyses by Karim and Mascie-Taylor who reported correlation coefficient between maternal weight and birth weight of 0.49.  This study has also shown that the correlation between maternal weight, height and BMI and birth weight was statistically significant but Jananthan et al., did not report any significant influence of height on birth weight. 
In conclusion, as shown by this study, , maternal weight and BMI are good predictors of birth weight and can be recommended for use among peripheral health workers for detection of mothers at risk of delivering big or low birth weight babies in North-west Nigeria and need for in utero transfer to centres where Caesarean section or neonatal care can be offered.
The limitation of this study is that anthropometric measurements such as BMI is more reliable before pregnancy. However, in our environment preconceptional care is an evolving field and women commonly present to health facilities only when they are advanced in pregnancy and there may be no record of their pre-pregnancy weight. A community-based study is recommended during which anthropometric parameters like BMI can be taken before pregnancy and followed up throughout pregnancy.
| References|| |
|1.||Guoyao W, Fuller WB, Timothy AC, Cynthia JM, Thomas ES. Maternal nutrition and fetal development. J Nutr 2004;134:2169-72. |
|2.||Godfrey KM, Barker DJ. Fetal nutrition and adult disease. Am J Clin Nutr 2000;71 Suppl 5:S1344-52. |
|3.||Kramer MS, Morin I, Yang H, Platt RW, Usher R, McNamara H, et al. Why are babies getting bigger? Temporal trends in fetal growth and its determinants. J. Pediatr 2002;141:538-42. |
|4.||Boniface K, Francine V, Saskia L, John B. Low birth weight and fetal anaemia as risk factors for infant morbidity in rural Malawi. Malawi Med J 2009;21:69-74. |
|5.||Tarabeia J, Amitai Y, Green M, Halpern GJ, Blau S, Ifrah A, et al. Differences in infant mortality rates between Jews and Arabs in Israel, 1975-2000. Isr Med Assoc J 2004;6:403-7. |
|6.||Okwu GN, Ukoha AI, Nwachukwu N, Agha NC. Studies on the predisposing factors of protein energy malnutrition among pregnant women in a Nigerian community. Online J Health Allied Scs 2007;3:1. |
|7.||Fall CH, Yajnik CS, Rao S, Davies AA, Brown N, Farrant HJ. Micronutrients and fetal growth. J Nutr 2003;133 (Suppl 2):S1747-56. |
|8.||Shittu AS, Kuti O, Orji EO, Mkinde NO, Ogunniyi SO, Ayoola OO, et al. Clinical versus sonographic estimation of fetal weight in Southwest Nigeria. J Health Popul Nutr 2007;25:14-23. |
|9.||Nelson B. Prematurity and IUGR. 17 th ed. 2004. p. 550. |
|10.||Christan P, Khatry SK, Katz J, Pradhan EK, LeClerq SC, Shrestha SR, et al. Effects of alternative maternal micr onutrient supplements on low birth weight in rural Nepal: Double blind randomised community trial. BMJ 2003;326:571-6. |
|11.||Moore V, Davies M. Nutrition before birth, programming and the perpetuation of social inequalities in health. Asia Pac J Clin Nutr 2002;11 Supp 3:S529-36. |
|12.||Finch BK. Socioeconomic gradients and low birth-weight: Empirical and policy consideration. Health Serv Res 2003;38:1819-41. |
|13.||Lam ET, Black JM, Little KD, Ausherman J, Rafiroiu C. The effects of exercise on birth weight: A meta-analysis. Am J Health Stud 2002;18:38-45. |
|14.||Lindsay MK, Graves W, Klein L. The relationship of one abnormal glucose tolerance test value and pregnancy complications. Obstet Gynecol 1989;73:103-6. |
|15.||Velentgas P, Benga-De E, Williams MA. Chronic hypertension, pregnancy-induced hypertension, and low birth weight. Epidemiology 1994;5:345-8. |
|16.||Shah PS. Knowledge Synthesis Group on determinants of preterm/low birthweight births. Paternal factors and low birth weight, preterm, and small for gestational age births: A systematic review. Am J Obstet Gynecol 2010;202:103-23. |
|17.||Gardosi J, Mongelli M, Wilcox M, Chang A. An adjustable fetal weight standard. Ultrasound Obstet Gynecol 1995;6:168-74. |
|18.||Elshibly EM, Schmalisch G. Correlation between anthropometric measures and birth weight of infants: Value in measuring actual birth weight. Am J Perinatol 2008;25:135-9. |
|19.||Voigt M, Heineck G, Hesse V. The relationship between maternal characteristics, birth weight and pre-term delivery: Evidence from Germany at the end of the 20 th century. Econ Hum Biol 2004;2:265-80. |
|20.||Golditch IM, Kirkman K. The large fetus. Management and outcome. Obstet Gynecol 1978;52:26-30. |
|21.||Langer O, Berkus MD, Huff RW, Samueloff A. Shoulder dystocia: Should the fetus weighing greater than or equal to 4000 grams be delivered by cesarean section? Am J Obstet Gynecol 1991;165 (4 Pt 1):831-7. |
|22.||Nahar S, Mascie-Taylor CG, Housne AB. Maternal anthropometry as a predictor of birth weight. Public Health Nutr 2007;10:965-70. |
|23.||Edilberto L. Maternal nutritional status. DHS Comparative Studies No. 24, Calverton, Maryland, USA: Macro International Inc; 1997 |
|24.||Woldemariam G, Timotiows G. Determinants of nutritional status of women and children in Ethiopia. Report of Ethiopian Health and Nutrition Research Institute, 2002. Retrieved from: http://www.measuredhs.com/pubs/pdf/FA39/02-nutrition.pdf. [Last accessed on 2013 Oct 01]. |
|25.||Kemiki AO, Akindele JA. Influence of maternal biosocial factors on birth weight. Nig J Paediatr 1993;20:6-12. |
|26.||Fakeye OO, Adetoro OO. The effects of sociobiochemical factors on birth weights of nigeria full-size, live-born infants. Nig J Paediatr 1989;16:7-13. |
|27.||Nahum GG, Stanislaw H, Huffaker BJ. Accurate prediction of term birth weight from prospectively measurable maternal characteristics. J Reprod Med 1999;44:705-12. |
|28.||Ayoola OO, Orji EO, Adetiloye VA, Nzeh DA. Accuracy of various ultrasonographic formula in predicting fetal weight in a Nigerian population. J Chin Clin Med 2008;3:1. |
|29.||Amini SB, Catalano PM, Hirsch V, Mann LI. An analysis of birth weight by gestational age using a computerized perinatal data base, 1975-1992. Obstet Gynecol 1994;83:342-52. |
|30.||Wilcox M, Gardosi J, Mongelli M, Ray C, Johnson I. Birth weight from pregnancies dated by ultrasonography in a multicultural British population. BMJ 1993;307:588-91. |
|31.||Cheng MC, Chew PC, Ratnam SS. Birth weight distribution of Singapore Chinese, Malay and Indian infants from 34 weeks to 42 weeks gestation. J Obstet Gynaecol Br Commonw 1972;79:149-53. |
|32.||Sen J, Roy A, Mondal N. Association of maternal nutritional status, body composition and socio-economic variables with low birth weight in India. J Trop Pediatr 2010;56:254-9. |
|33.||Mohanty C, Prasad R, Srikanth Reddy A, Ghosh JK, Singh TB, Das BK. Maternal anthropometry as predictors of low birth weight. J Trop Pediatr 2006;52:24-9. |
|34.||Karim E, Mascie-Taylor CG. The association between birth weight, sociodemographic variables and maternal anthropometry in an urban sample from Dhaka, Bangladesh. Ann Hum Biol 1997;24:387-401. |
|35.||Jananthan R, Wijesinghe DG, Sivananthawerl T. Maternal anthropometry as a predictor of birth weight. Trop Agri Res 2009;21:89-98. |
[Table 1], [Table 2], [Table 3]