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Lakshmi and Rajkumar: Role of maternal Body Mass Index (BMI) in predicting the birth weight of the newborn


Weight gain is a normal sign of pregnancy. It is essential for a pregnant woman to have a healthy, nutritious and balanced diet which will help them gain weight during pregnancy. There has however been no recommended guideline regarding the allowable weight gain during pregnancy. On an average, a woman can gain up to 10 kilograms during the antenatal period for a healthy outcome of delivery.1

The assessment and monitoring of weight gain during pregnancy is best carried out using Body Mass Index. The United States’ Institute of Medicine (IOM) has issued recommendations for BMI monitoring during pregnancy. According to their guidelines, the pre-pregnancy weight is an important criteria used to determine the allowable weight gain. While women who were underweight prior to pregnancy are allowed to gain up to 18 kilograms during pregnancy, obese women are restricted to a maximum gain of 9 kilograms during pregnancy.2

Studies have shown that maternal weight gain has an impact on the pregnancy outcomes. It is a modifiable risk factor for abnormal birth weight in the newborns. A study done by Johansson K emphasized that for every kilogram of weight gain in mothers, there was an increase in the weight of the babies by 26g.3 This has been established as a linear correlation which exists between maternal and fetal weight gain. At a molecular level, an underweight mother is said to have negative energy balance, and with inadequate supply of nutrients, intrauterine growth retardation ensues.4 Similarly, excessive weight gain in the mothers increases the carbohydrate load in the babies, thereby resulting in metabolic disturbances impacting the baby’s size and weight. One of the key problems with excessive weight gain is macrosomia, which complicates the delivery process.

Small for Gestational Age (SGA) and Large for Gestational Age (LGA) are significant problems in two ends of the spectrum. While SGA babies demand physical and nutritional support to gain the appropriate weight for age, LGA babies are at increased risk of various hormonal imbalances, disorders of growth and development and non communicable diseases like Diabetes mellitus. In a study by Verma et al, the prevalence of SGA among underweight mothers was 18.9% while the prevalence of LGA among obese mothers was 23%.5 These babies have higher vulnerability to admission and care in neonatal intensive care units, thereby warranting increased physical, mental and financial strain on the parents and care providers.

Despite several studies on predictors of birth weight have been carried out, there are few longitudinal studies which analyze the predictive effect of maternal BMI. A cause and effect analysis will help in early monitoring of the BMI and also aid in pre-pregnancy counseling regarding the importance of optimal weight gain for a safe and healthy outcome.


This study was carried out to evaluate the role of maternal body mass index in predicting the birth weight of the newborns.


Study setting

This cohort study was carried out in the Obstetrics and Gynecology department of our tertiary care hospital for a period of one years between August 2017 and August 2018.

Study population

All pregnant mothers who visited the hospital in first trimester for registration and initial evaluation during the study period formed the study population. Any pregnant mother diagnosed with systemic diseases during the first visit was excluded from the study. Women with twin/ multiple pregnancies were also excluded.

Sample size and sampling technique

Based on the available literature, the lowest prevalence for SGA/LGA was observed for underweight women, with a prevalence of SGA of 18.9%. At 95% confidence limits, 6% absolute precision, the sample size was calculated as 163.5. Accounting 10% for non response, the sample size was calculated as 179.8 and was rounded off to 185. The participants were selected by convenient sampling.

Ethical approval and informed consent

Approval from the Institutional Ethics Committee was obtained prior to the commencement of the study. Each participant was explained in detail about the study and informed consent was obtained prior to the commencement of data collection.

Data collection

A structured interview schedule was used for data collection. Data regard ing the personal history and obstetric history of the study participants were recorded. Detailed history and clinical examination was done. The height was recorded in metres by a stadiometer and weight was recorded in kilograms by standard weighing machine. Body Mass Index was calculated using the formula

BMI = weight (in kilograms) / height (metre2).

The participants were classified based on WHO National Institute of Health guidelines (Table 1).5 The participants were followed up throughout pregnancy and at delivery, the birth weight of the baby was recorded immediately and classified (Table 2).6

Data analysis

Table 1

WHO-NIH classification of BMI:

S. No Value (kg/m2) Classification
1 ≤19.9 Underweight (Group I)
2 20-24.9 Normal (Group II)
3 25-29.9 Overweight (Group III)
4 30-34.9 Obese (Group IV)
5 ≥35 Morbid obese (Group V)
Table 2

Classification of birth weight

S. No Value (kg) Classification
1 ≤2.5 Low birth weight
2 2.5-3.0 Normal
3 3.0-4.0 Above normal
4 >4.0 Macrosomia

Table 3
S. No Characteristics Frequency (N=185) Percentage (%)
1 Age (in years)
Less than 20 59 31.9
20-24 110 59.5
25 & above 16 8.6
2 Socioeconomic status (Kuppuswamy’s classification
Class I - -
Class II 12 6.5
Class III 24 13.0
Class IV 44 23.8
Class V 105 56.7
3 Parity
1 106 57.3
2 67 36.3
3 11 5.9
Above 3 1 0.5
4 B ody M ass Index
Underweight 90 48.6
Normal 89 48.2
Overweight 6 3.2
Obese - -
Morbid obese - -
5 Anaemia
Mild (Hg : 10 – 10.9) 49 26.5
Moderate (Hg 7 – 10) 83 44.9
Severe (Hg 4 – 7) 7 3.8
Very Severe (Hg < 4) 1 0.5
Nil (Hg > 11) 45 24.3
6 Birth weight
Low B.W. (<2.5 kg) 47 25.4
Normal (2.5 – 3.0 kg) 77 41.6
Above normal (> 3 kg) 53 28.6
Abortion 3 1.7
Pre term 5 2.7

Background characteristics of the study participants

Table 4
Socio economic Status (as per B.G. Prasad Scale) BMI P Value
Under Weight Normal Over Weight Obese Mean S.D.
No. % No. % No. % No. %
1 (-) - - - - - - - - - - 0.1864
2 (12) 5 41.7 6 50 1 8.3 - - 21.19 3.14
3 (24) 14 58.3 9 37.5 1 4.2 - - 19.59 2.87
4 (44) 17 38.6 24 54.5 3 6.8 - - 20.45 3.38
5 (105) 54 51.4 50 47.6 1 1.0 - - 19.45 2.76

Association between socio economic status and maternal BMI

Table 5
S.E. Status (B.G. Prasad Scale) Anaemia Hb% P value
Nil Moderate Severe Very Severe Mean S.D.
No % No % No % No % No %
1 (-) - - - - - - - - - - - - 0.0063*
2 (12) - - 2 16.7 9 75 1 8.3 - - 9.01 1.33
3 (24) 3 12.5 4 16.7 17 70.8 - - - - 9.51 1.07
4 (44) 11 25 15 34.1 17 38.6 1 2.3 - * 10.09 1.4
5 (105) 31 29.5 28 26.7 40 38.1 5 4.8 1 1.0 9.93 1.67

Association between socio economic status and anemaia

[i] *Statistically significant

Table 6
BMI Birth Weight P value
Normal Above Normal Abortion Preterm Mean SD
No % No % % No % No % No %
Under weight (90) 31 34.4 32 35.6 21 23.3 3 3.3 3 3.3 2.65 0.42 0.039*
Normal (89) 16 18.0 42 47.2 30 33.7 - - 1 1.1 2.77 0.37
Over Weight (6) - - 3 50.0 2 33.3 - - 1 16.7 2.82 0.31
Obese (-) - - - - - - - - - - - -

Association between BMI and various risk factor

[i] *Statistically significant


This cohort study was carried out among 185 antenatal women who presented in first trimester. A majority of the participants belong to the age group of 20-24 years (59.5%). About 57.6% of the participants were primi. About 44.9% of the participants were anemic. In the study, (48.6%) of the participants were Underweight and 25.4% of the participants delivered a low birth weight baby. (Table 3).

Majority of the participants who were underweight belonged to Socioeconomic class III (58.3%) while most of the overweight participants belonged to socioeconomic class II (8.3%). The mean BMI was highest in class II compared to class IV and V. However the association was statistically not significant. (Table 4)

The association between socio economic status and anemia was analysed. The mean anemia levels increased with the increase in the socioeconomic status. Majority of the participants with moderate and severe anemia belonged to socioeconomic class II (75%) The observed association was statistically significant (p<0.005). (Table 5)

The association between maternal body mass index and birth weight of the newborns showed that underweight mothers had an increased risk of delivering low birth weight babies (34.4%) while overweight mothers were at increased risk of delivering babies with above normal birth weight (33.3%). The observed association was statistically significant (p<0.05). (Table 6)


Maternal BMI is an indicator of the nutritional status and well being of a pregnant mother. While a lower BMI can impair the nourishment in the newborn, a higher BMI can result in various antenatal, intranatal and postnatal complications. There is an imminent need to evaluate the role of maternal BMI on the impact on the newborn.

In our study, majority of the participants were underweight (48.6%) and very few participants were overweight (3.2%). None of them were obese. However, majority of the participants were moderately anemic (44.9%). Low birth weight was seen in 25.4% of the participants while 28.6% of the newborns weighed over 3 kilograms. A statistically significant association was found between socioeconomic status and maternal anemia (p<0.05). Moreover, maternal BMI was a strong predictor of the birth weight. Our study showed that underweight mothers were at an increased risk of delivering low birth weight babies (34.4%) while overweight mothers were at increased risk of delivering babies with birth weight above 3 kilograms (p<0.05).

Our study was similar to a number of studies published. Verma et al also observed similar findings of increased risk of low birth weight among underweight mothers. Also, risk of LGA babies increased with increase in the maternal BMI5 Yazdani S et al demonstrated similar findings and also emphasized that with increase in the BMI, there is an increase in the predisposition towards caesarean section, thereby accentuating the perinatal and postnatal complications.7 Similar results were seen in a study done by Khashan AS et al.8

Overweight and obesity are associated with oxidative stress and rise in circulating inflammatory markers. The plasma levels of C-Reactive protein is elevated in obese individuals with increase in Tumor Necrosis Factor-α(TNF- α), Interleukin (IL)- 6 and IL-8, which predispose to pre-eclampsia.9 Obesity and overweight therefore predispose to several complications during the antenatal period, making the pregnancy a high risk one. A meta analysis done by Han Z et al reviewed the risk of low birth weight in relation to maternal BMI. Underweight mothers were at increased risk of delivering both low birth weight babies and also preterm babies. This phenomenon could be directly related to the lack of adequate nutritional support resulting in diminished fetal growth. Presence of other significant illnesses in mothers like anemia also had an indirect impact.10


Maternal body weight is a significant and silent predictor of the pregnancy outcome. There is a need to raise awareness among pregnant mothers on the impact of the body mass index during pre-pregnancy counseling. Our study has emphasized on the need to maintain an optimum body weight according to the height in order to have a healthy and well nourished baby. An intense evaluation in the first trimester can help the couples monitor the weight gain during pregnancy and achieve desired outcomes. There is a imminent need to rectify nutritional disorders like anemia prior to the conception in order to facilitate healthy and effective weight gain during pregnancy. Any pregnant woman must be provided with nutritional and lifestyle counseling in her initial visits in order to take informed decisions at the appropriate time.

Conflict of interest




Ethical approval




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