The objective of the study was to ascertain the influence of various maternal factors like age, BMI, anthropometry, parity, and so forth on body dimensions of newborn and to discover determinants of neonatal subcutaneous fat distribution pattern. 94 Khatri and Arora new borns along with their biological mothers hailing from upper/middle socioeconomic status families were selected against several criteria: only liveborn, healthy full term babies (37–41 gestational weeks), singletons, born through vaginal delivery and for whom all data were available, for the study. Numerous biometric variables were chosen for this study: weight, stature (for mothers), birth length (for neonates), circumferences (head, chest, abdomen, hip, upper arm, and wrist), and skinfolds at different sites (biceps, triceps, subscapular, suprailiac, chest, thigh anterior, and calf posterior) along with newborn’s birth weight. All LBW infants were found to be significantly associated with maternal nutritional status and age, when controlled for other factors. Chances of having an LBW infant varies with mother’s nutritional status as determined by BMI and MUAC. Fat profiling has genetic implications because fat tracking patterns have shown that, irrespective of maternal nutritional status and age, most neonate skinfolds are guided by mother’s skinfold thicknesses. We conclude that early teenage pregnancies should be discouraged so as to reduce the incidence of LBW and larger ethnic-specific studies should be taken to find determinants of subcutaneous fat pattern in neonates.
Various genetic and environmental factors are known to influence the size of newborns. Numerous studies have shown the significant effects of various maternal factors on the somatometrics characteristics of the newborns [
Maternal body dimensions are first determinants of neonate biometrics, predominantly their birth weight and length, which are closely related to perinatal morbidity and mortality. While among the nonbiometric maternal factor, two factors known to play a decisive role in fetal growth are maternal age and parity [
Therefore, the objective of the study is to ascertain the influence of various maternal factors like age, BMI, anthropometry, parity, and so forth on body dimensions of newborn. Determinants of neonatal subcutaneous fat distribution pattern have also been focused on with special attention to the intricate effects of age, nutritional status, and parity.
This study is based on a cross-sectional sample of neonates (mean age
Mothers’ ages were grouped into two age intervals: <20 years (teenage mothers) with mean age
Informed written consent was obtained from each subject. All the subjects were apparently healthy with no visible deformity.
The power for the sample was calculated using statistical power calculator [
From the numerous biometric variables available in the data set, following variables that were representative of the overall dimensions of the sample population were chosen for this study: weight, stature (for mothers), birth length (for neonates), circumferences in cms, to within 1 mm (head, chest, abdomen, hip, upper arm, and wrist), and skinfolds at different sites (biceps, triceps, subscapular, suprailiac, chest, thigh anterior, and calf posterior) measured by means of Harpenden skinfold caliper with 0.2 mm precision. All measurements were taken by using standard technique of Weiner and Lourie, 1981 [
Analysis of variance (ANOVA) and
Regression models tests, for various maternal variables (age, parity, BMI, MUAC) with BW as dependent variable, were performed. This method helps in the choice of the independent variables that are most useful in explaining or predicting the dependent biometric parameter in the newborn variable. The test revealed effects of maternal nutritional status through maternal BMI [
SPSS 17 has been used for data analysis and full results of these tests are available on request.
For inferential parametric analysis,
Descriptive statistics of newborn characteristics according to BMI categories with
Mean ± SD | ||||
Variables | Underweight (23.4%) | Normal (67.02%) | Overweight (9.57%) | |
Length | 6.47** | |||
Weight | 3.70* | |||
Birth weight | 3.35* | |||
Head circumference | 14.62*** | |||
Chest circumference | 3.14* | |||
Waist circumference | NS | |||
Upper arm circumference | 5.43** | |||
Wrist circumference | 2.68* | |||
Thigh circumference | NS | |||
Ankle circumference | 3.50* | |||
Biceps skinfold thickness | 6.88** | |||
Triceps skinfold thickness | 5.80** | |||
Subscapular skinfold thickness | 5.08** | |||
Suprailiac skinfold thickness | 7.12** | |||
Chest skinfold thickness | 12.57*** | |||
Thigh skinfold thickness | 6.98** | |||
Calf posterior skinfold thickness | NS |
***
Descriptive statistics of newborn characteristics and age of mother with
Age of Mother (AOM) | |||
Variables | <20 years | ≥20 years | |
Mean ± SD | Mean ± SD | ||
Length | −1.99* | ||
Weight | −0.89* | ||
Birth weight | −1.38** | ||
Head circumference | NS | ||
Chest circumference | NS | ||
Waist circumference | NS | ||
Upper arm circumference | NS | ||
Wrist circumference | NS | ||
Thigh circumference | NS | ||
Ankle circumference | NS | ||
Biceps skinfold thickness | −2.55* | ||
Triceps skinfold thickness | −2.30* | ||
Subscapular skinfold thickness | −1.33* | ||
Suprailiac skinfold thickness | −0.50* | ||
Chest skinfold thickness | NS | ||
Thigh skinfold thickness | −1.25* | ||
Calf posterior skinfold thickness | −1.87* |
**
Table
Percentage distribution of babies with respect to their birth weight on the basis of age of mother, mother’s MUAC and maternal BMI.
Birth weight | ||||
Variables and standards | <2.5 kg (LBW) | >2.5 kgs | Chi-square | |
Age of mother | <20 years | 55% | 45% | 3.431* |
≥20 years | 32.4% | 67.6% | ||
MUAC | <22 cm | 53.2% | 46.8% | 3.687* |
≥22 cm | 27.7% | 72.3% | ||
BMI categories | Underweight | 59.3% | 40.7% | |
Normal | 48.3% | 61.7% | 5.88* | |
Overweight/obese | 0 | 100% |
*
Mother’s age, BMI, parity, and MUAC were entered into a multivariate logistic regression model, along with an indicator for infant’s nutritional status (BW) as shown in Table
Regression coefficients of birth weight and its significance in the multivariable model of logistic regression for MUAC (mid-upper arm circumference) of the mother, AOM (age of mother) and maternal body mass index (BMI).
Birth weight | B | Std. error of B | Exp B (95% CI) | Sig. | |
---|---|---|---|---|---|
MUAC | < 22 cm (undernourished) | 0.939 | 0.277 | 2.559 (1.927–4.063) | 0.050 |
≥22 cm (normal) | — | 0.00 (referent) | — | ||
AOM | <20 years (teenage) | 0.669 | 0.201 | 1.951 (1.677–3.621) | 0.016 |
≥20 years | — | 0.00 (referent) | — | ||
BMI | Normal (≥18.5) | −0.204 | 0.129 | 0.816 (0.472–0.908) | 0.044 |
Underweight (≤18.49) | — | 0.00 (referent) | — |
Infant’s variable | (I) BMI of the mother | (J) BMI of the mother | Mean difference (I-J) | Std. error | Sig. | 95% confidence interval | |
Lower bound | Upper bound | ||||||
Length | Overweight | Underweight | 3.75* | 1.09 | 0.00 | 1.58 | 5.92 |
Normal weight | 3.59* | 1.05 | 0.00 | 1.51 | 5.69 | ||
Weight | Overweight | Underweight | 0.54* | 0.21 | 0.01 | 0.13 | .97 |
Normal weight | 0.48* | 0.20 | 0.02 | 0.07 | .87 | ||
Birth weight | Overweight | Underweight | 0.71* | 0.26 | 0.01 | 0.19 | 1.24 |
Normal weight | 0.56* | 0.26 | 0.03 | 0.06 | 1.07 | ||
Head circumference | Overweight | Underweight | 76.41* | 14.64 | 0.00 | 47.33 | 105.49 |
Normal weight | 75.95* | 14.13 | 0.00 | 47.88 | 104.02 | ||
Chest circumference | Overweight | Underweight | 3.03* | 1.26 | 0.02 | 0.52 | 5.54 |
Normal weight | 2.24 | 1.22 | 0.07 | −0.19 | 4.66 | ||
Waist circumference | Overweight | Underweight | 1.18 | 1.28 | 0.36 | −1.37 | 3.73 |
Normal weight | .42 | 1.24 | 0.74 | −2.04 | 2.87 | ||
Waist circumference | Overweight | Underweight | 1.23* | 0.38 | 0.00 | 0.47 | 1.99 |
Normal weight | 1.16* | 0.37 | 0.00 | 0.43 | 1.89 | ||
Upper arm circumference | Overweight | Underweight | 1.23* | 0.38 | 0.00 | 0.47 | 1.99 |
Normal weight | 1.16* | 0.37 | 0.00 | 0.43 | 1.89 | ||
Wrist circumference | Overweight | Underweight | 0.61* | 0.27 | 0.03 | 0.07 | 1.15 |
Normal weight | 0.52* | 0.26 | 0.05 | 0.01 | 1.05 | ||
Thigh circumference | Overweight | Underweight | 1.61* | 0.75 | 0.03 | 0.12 | 3.10 |
Normal weight | 1.61* | 0.72 | 0.02 | 0.23 | 3.10 | ||
Ankle circumference | Overweight | Underweight | 0.81* | 0.33 | 0.01 | 0.16 | 1.46 |
Normal weight | 0.83* | 0.32 | 0.01 | 0.21 | 1.46 | ||
Biceps skinfold thickness | Overweight | Underweight | 1.32* | 0.38 | 0.00 | 0.56 | 2.08 |
Normal weight | 1.37* | 0.37 | 0.00 | 0.64 | 2.10 | ||
Triceps skinfold thickness | Overweight | Underweight | 1.65* | 0.52 | 0.00 | 0.63 | 2.68 |
Normal weight | 1.73* | 0.50 | 0.00 | 0.71 | 2.69 | ||
Subscapular skinfold thickness | Overweight | Underweight | 1.40* | 0.48 | 0.00 | 0.44 | 2.36 |
Normal weight | 1.49* | 0.47 | 0.00 | 0.57 | 2.42 | ||
Suprailiac skinfold thickness | Overweight | Underweight | 1.43* | 0.49 | 0.00 | 0.45 | 2.41 |
Normal weight | 1.72* | 0.48 | 0.00 | 0.77 | 2.67 | ||
Chest skinfold thickness | Overweight | Underweight | 1.86* | 0.39 | 0.00 | 1.07 | 2.64 |
Normal weight | 1.92* | 0.38 | 0.00 | 1.16 | 2.67 | ||
Thigh skinfold thickness | Overweight | Underweight | 2.21* | 0.69 | 0.00 | 0.83 | 3.59 |
Normal weight | 2.49* | 0.67 | 0.00 | 1.16 | 3.82 | ||
Calf posterior skinfold thickness | Overweight | Underweight | 0.74 | 0.52 | 0.16 | −0.29 | 1.78 |
Normal weight | 0.83 | 0.50 | 0.10 | −0.16 | 1.83 |
Fat distribution pattern at different sites for teenage mothers and adult mothers along with their infants has been shown in Figures
Fat distribution pattern at different sites for mothers and babies when AOM < 20 years.
Tracking fat distribution pattern at different sites for mothers and babies when AOM < 20 years.
Fat distribution pattern at different sites for mothers and babies when AOM > 20 years.
Tracking fat distribution pattern at different sites for mothers and babies when AOM ≥ 20 years.
Fat distribution pattern at different sites for mothers and babies when mothers are overweight/obese (BMI).
Tracking fat distribution pattern at different sites for mothers and babies when mothers are normal (BMI).
Fat distribution pattern at different sites for mothers and babies when mothers are underweight (BMI).
Tracking fat distribution pattern at different sites for mothers and babies when mothers are underweight (BMI).
Fat distribution pattern at different sites for mothers and babies when mothers are overweight/obese (BMI).
Tracking fat distribution pattern at different sites for mothers and babies when mothers are overweight/obese (BMI).
Periods of fetal and infant growth are vital predictors of child’s health status which are largely determined by maternal characteristics. Hence, maternal anthropometry and indicators of maternal nutritional status are crucial prognosticators of pregnancy outcomes as they reflect genetic aspects, skeletal maturity and give an account of nutritional conditions.
In the present study, all LBW infants are significantly associated with maternal nutritional status and age, when controlled for other factors as they are not preterm babies. There are strong epidemiological evidences of a relation between maternal nutritional status and birth weight resulting in a number of intervention studies of nutritional supplementation during pregnancy that have been carried out both in developing and developed countries [
Neggers et al. reported maternal prepregnancy weight to be the best predictor of all neonatal size measures except for the neonatal skinfold thicknesses, which were better predicted by the pre-pregnancy BMI [
Adaptation of the mother’s vascular system to the transfer of energy to the foetus is an important determinant for newborn subcutaneous fat storage [
Maternal nutrition is one of the most modifiable characteristics among the major environmental causes of IUGR in the developing world, and if taken care of, a substantial fraction of LBW could possibly be prevented. In turn this might reduce the prevalence of mortality, morbidity, physical and mental development and factors associated with LBW. However, role of other environmental factors may indeed directly affect these outcomes independent of birth weight [
We conclude that early teenage pregnancies should be discouraged so as to reduce the incidence of LBW. There should be apposite health awareness and health promotion policies formulated to spread a word about nutritional well-being of the mother for her progeny. Finally, studies similar to the present one should be undertaken at larger scale and among various other ethnic groups of India to understand the determinants of subcutaneous fat pattern in neonates.
The authors are grateful to all the subjects who volunteered for the study and to the Physiological Anthropology Laboratory, Department of Anthropology, University of Delhi, Delhi, India, for providing the infrastructure. S. Kapoor is grateful to CSIR for providing financial assistance.