|Year : 2013 | Volume
| Issue : 2 | Page : 87-92
A longitudinal study of maternal and socioeconomic factors influencing neonatal birth weight in pregnant women attending an urban health center
Saurabh R Shrivastava, Prateek S Shrivastava
Department of Community Medicine, Shri Sathya Sai Medical College and Research Institute, Ammapettai, Kancheepuram, Tamil Nadu, India
|Date of Web Publication||10-Sep-2013|
Saurabh R Shrivastava
Department of Community Medicine, Shri Sathya Sai Medical College and Research Institute, Ammapettai, Kancheepuram, Tamil Nadu
Source of Support: None, Conflict of Interest: None
Background: Having a low birth weight (LBW) baby can cause emotional, social and financial stress for the family. Settings and Design: A longitudinal study of 1 year duration (June 2009-May 2010) was conducted in an urban slum of Mumbai. Universal sampling method was employed and every antenatal women registered at the urban health center from June 2009 to August 2009 were included as study participants. Materials and Methods: Of the 231 pregnant women that registered, 21 were excluded from analysis as - 5 home deliveries, 3 still births, 3 spontaneous abortions, and 10 that could not be traced. Thus for final analysis, sample size was 210. Inclusion and Exclusion criteria were: All antenatal care (ANC) subjects registered at the urban health center within 20 weeks of their gestational age were included as the study subjects. Subjects with only live hospital/institution birth were included. These registered women were then followed-up for next 9 months for monitoring maternal weight gain and neonatal birth weight. Statistical Analysis: Statistical analysis was done using SPSS version 17. Chi-square test was used for testing significance of association at P value of 0.05 and 0.001. Results: Proportion of LBW in the present study is 27.1% with mean birth weight 2.2285 kg with S.D. 0.2281 kg. Factors like maternal age, education, tobacco addiction, hemoglobin levels, gestational age, and interval between pregnancies were significantly associated with birth weight. Conclusions: LBW continues to be a significant public health problem and as multiple factors are associated with it, it requires a more holistic and multipronged approach for its reduction.
Keywords: Anemia, body mass index, low birth weight, pregnancy
|How to cite this article:|
Shrivastava SR, Shrivastava PS. A longitudinal study of maternal and socioeconomic factors influencing neonatal birth weight in pregnant women attending an urban health center. Saudi J Health Sci 2013;2:87-92
|How to cite this URL:|
Shrivastava SR, Shrivastava PS. A longitudinal study of maternal and socioeconomic factors influencing neonatal birth weight in pregnant women attending an urban health center. Saudi J Health Sci [serial online] 2013 [cited 2019 Jul 21];2:87-92. Available from: http://www.saudijhealthsci.org/text.asp?2013/2/2/87/117912
| Introduction|| |
"How much did he/she weigh?'' is often the first question proud parents are asked after they have announced the sex of their newly delivered progeny. Having a low birth weight (LBW) baby can cause emotional, social, and financial stress for the family. In one mother's words "It is difficult to portray in writing the stress and fear felt as a parent when your child comes into this world not as expected".
Birth weight is a reliable index of intrauterine growth retardation (IUGR) and it is a good indicator not only of mother's health and nutritional status but also the newborns chances for survival, growth, long-term health, and psychosocial development. , LBW has a significant impact on the financial status of the family. 
A LBW is any newborn with a birth weight less than 2.5 kg (including and up to 2.499 kg) regardless of its gestational age and it includes two kinds of infants - preterm babies and small for gestational age or small for date babies. 
Of the 19 million newborns weigh less than 2,500 g in the developing world, more than half in South Asia. India alone has more than 7 million low-birth babies. Preterm babies are those born before the end of 37 weeks of gestation (less than 259 days).  In countries where the population of LBW infants is less, short gestational period is the major cause. In countries where the proportion is high (e.g. India), the majority of cases can be attributed to fetal growth retardation. 
Although small for gestation age has no generally accepted standard definition, the following are commonly used: Birth weight less than 10 th percentile for gestational age, birth weight less than 2500 g and gestational age greater than or equal to 37 weeks and birth weight less than two standard deviations below the mean value for gestational age. 
Birth weight, like growth is determined by complex interplay of genetic and environmental factors. The proportional contribution of these influences is unclear. However, birth weight varies within genetically similar populations, suggesting that environmental factors play a significant role. , Studies in India and worldwide have shown that the etiology of LBW is multifactorial. , Studies have been done across the world to assess the association between maternal body mass index (BMI) and obstetric and neonatal outcomes. ,, Other factors that contribute to LBW are chronic health problems and infections in mothers, alcohol, smoking, and babies with birth defects. 
The purpose of the study is to gain an insight into the maternal and socioeconomic factors influencing the birth weight. The prevalence of LBW babies in India has not decreased to a much extent in the last few decades despite of the continuous efforts of the Government to improve maternal and child health care services. The study will also provide information of the various socioeconomic determinants affecting birth weight and thus suggestion of measures to reduce their influence on birth weight.
| Materials and Methods|| |
A longitudinal study of 1-year duration, from June 2009 to May 2010, was conducted in an urban slum of Mumbai. The Universal sampling method was employed and every antenatal women registered at the urban health center from June 2009 to Aug 2009 were included as the study subjects.
Inclusion and Exclusion criteria were: All ANC subjects registered at the urban health center within 20 weeks of their gestational age were included as the study subjects. Those subjects with past history of any congenital malformed child, twins, or with any pre-existing comorbid illness such as diabetes mellitus, hypertension, HIV, bronchial asthma, heart disease, cancer, etc., were excluded from the study. Subjects with minimum two ANC visits including at least one visit in the third trimester were included in the study. Subjects with only live hospital/institution birth were included while subjects with outcome in the form of still births or home delivery or twins or congenitally malformed child were not considered for analysis purpose.
Of the total 231 pregnant women registered, 21 were excluded from the analysis as - 5 had home deliveries, 3 pregnancies terminated into still birth, 3 had spontaneous abortions and for 10 pregnancies outcome could not be recorded as they could not be contacted (lost to follow-up).
Thus for final analysis, sample size was 210.
These registered women were then followed up for 9 months (Sep 2009-May 2010) at each of their antenatal visit till delivery for monitoring the maternal weight gain and finally birth weight of the newborn which was recorded with the help of discharge cards or the hospital register of the maternity hospital/private hospitals.
On pilot basis, 15 women were interviewed to test validity and response. The questionnaire was then suitably modified and used as the tool for data collection.
With the help of the medical social worker rapport was established with study subjects at the time of their registration and after obtaining their informed consent, information on age, religion, education, and occupation of women, information on family income per month, menstrual and obstetrical history was recorded. Information pertaining to personal habits such as tobacco use and smoking among women and their husband was also noted down.
Maternal weight was recorded at each visit and body mass index (BMI) was calculated. Average BMI was calculated in case of more than one visit in any trimester. Thus, BMI was calculated for each trimester. The expected date of delivery was calculated based on the history of last menstrual period of each woman or with the help of abdomen ultrasound report, whichever was available.
Menstrual and obstetrical history was recorded. Information pertaining to personal habits such as tobacco use and smoking among women and their husband was also noted down.
Protein and calorie intake of women was established by 24-hour dietary recall method. This was done by estimating amount specified by simple household measures like cup, wati, and spoon and calculating calorie and protein content. The calorie and protein intake was assessed at the time of first visit in the third trimester by using above method.
Kuppuswamy's method of socioeconomic status was used to determine social class to which women belonged. 
Height of women was measured with women wearing no footwear. They were made to stand against a wall with heels and head touching the wall. The point was marked after holding a hard card on woman's head. Height was measured from the floor till the mark with the help of standard measuring tape.
Weight was measured with the help of a portable standard size circular weighing machine without any footwear. Weight was measured at each of their visit preferably at three points 12 ± 2 weeks, 24 ± 2 weeks, 36 ± 2 weeks of gestation. In case subject had more than one visit in any trimester the BMI and other statistical parameters were calculated taking last visit into the account. To minimize observer's bias measurement was done twice- one by the investigator and other by a trained person and the average of two was taken. BMI was classified using the International Classification of adult weight. 
Blood pressure was checked with mercury column sphygmomanometer with women sitting comfortably. Bad obstetric history was operationally defined as previous unfavorable fetal outcome in terms of two or more consecutive spontaneous abortions, early neonatal deaths, stillbirths, intrauterine fetal deaths, intrauterine growth retardation, and congenital anomalies.
WHO hemoglobin thresholds classification was used to define anemia which states that in pregnant female level of hemoglobin less than 11g% is classified as anemia. Hemoglobin estimation was done by Sahli's method at two points - at the time of registration and at the time of first visit in the third trimester and WHO classification was used to classify anemia in pregnancy.  For finding out the association between subject hemoglobin and birth weight hemoglobin recorded at the time of first visit in the third trimester was used. Subjects were then advised to get registered at any of the maternity hospital as per their preference for delivery purpose as the urban health center where this study was conducted does not have delivery services.
They were followed-up till the birth of the child over telephone. Follow-up was mainly to know the exact/near most possible date of child birth. This was done keeping their last menstrual period date and expected date of delivery as per their history in mind or with the help of abdominal ultrasonography report whichever was available.
The investigator was not present personally at the time of delivery and all birth weight readings were obtained with the help of hospital/maternity home records or home visits or scrutiny of the discharge cards of the study subjects at the time of under-five/well baby clinic or during immunization sessions.
For calculating proportion of LBW the cut-off value in the present study was taken as 2.5 kg.
Ethical considerations: Ethical clearance was obtained from the Institutional Ethics committee prior to the start of the study. Written informed consent was obtained from the study participants before obtaining any information from them. Utmost care was taken to maintain privacy and confidentiality.
Data analysis: Data entry and statistical analysis was done using SPSS version 17. Frequency distributions were calculated for all the variables. Chi-square test was used for testing the significance of association between sociodemographic parameters and neonatal birth weight at P value of 0.05 and 0.001.
| Results|| |
[Table 1] shows the distribution of babies according to the birth weight. The birth weight of <2.5 kg is termed as LBW and the birth weight >2.5 kg is the normal birth weight. Proportion of LBW in the present study is 27.1% with mean birth weight 2.2285 kg with S.D. 0.2281 kg. Normal birth weight babies accounted for 72.9% of the birth outcomes. The mean birth weight in normal birth weight group is 2.7676 with S.D. 0.2251 kg. The mean birth weight of all babies is 2.601 kg with S.D. 0.3365 kg. When the cut off value of LBW was taken as 2 kg instead of 2.5 kg the proportion of LBW was 19 (9%). Out of the total 210 study subjects 165 (78.6%) delivered at a government institute (hospital/maternity home) and remaining 45 (21.4%) at private hospitals.
[Table 2] and [Table 3] show the association among maternal, socioeconomic and demographic factors, and neonatal birth weight. A large fraction of the LBW outcomes 26 (45.6%) were from the age group 15-19 years signifying the impact of early maternal age over birth weight of the child. With the progressive increase in the age the proportion of LBW has decreased.
All the 19 subjects who had only 2 ANC visits were those who got registered themselves in the second trimester and thus their next visit was in the third trimester. As the number of ANC visits has increased it was observed that the proportion of outcome of LBW decreased. Statistically significant association was found between number of ANC visits and outcome of LBW.
Proportion of anemia in the study subjects was found to be 95 (45.2%). Proportion of LBW was found to vary inversely with maternal hemoglobin levels and thus majority 38 (66.7%) of the LBW outcomes were of the study subjects with hemoglobin ≤10.9 g%.
No significant association was observed between neonatal birth weight and age at first pregnancy; religion; type of family; husband education; maternal occupation; father employment status; family income per month; parity; maternal height; maternal weight or BMI in Ist/IInd trimester; dietary pattern; calorie consumption; protein intake; husband smoking; maternal physical activity; maternal consanguinity; previous fetal loss and sex of the baby.
| Discussion|| |
The proportion of LBW among the study subjects was 27.1% in the present study. In a study in rural Ballabgarh, Haryana, incidence of LBW was 8.8% which was much lower than the present study.  Such a low proportion of LBW could be because of good follow-up and no addiction among the subjects. The rate of LBW was found to be 24.6% in a study done in rural Tamil Nadu which was lower than the present study probably because of higher literacy rates in the study subjects. 
A large fraction of the LBW outcomes 26 (45.6%) were from the age group 15-19 years signifying the impact of early maternal age over birth weight in the current study. In a study done in urban slum it was concluded that maternal age (<18 years) to be associated with more incidence of LBW.  In a study done at urban health center in Mumbai involving 172 mothers (63 teenagers and 109 nonteenagers) revealed birth weight of babies of teenage mothers to be significantly lower than those born to mothers aged 21 years and more (P < 0.01).  This could be because women is still in the process of biological growth in adolescence and she may not be physically and emotionally mature enough to understand the importance of child bearing, nutrition, and self-care.
In the present study a statistically significant association was found between maternal education and LBW while in a study done in Mumbai slum, maternal education had a significant effect on the birth weight of the newborn (P < 0.001). The incidence of LBW was as much as 52% in illiterate women. It decreased rapidly in women who were educated up to secondary level (19.1%) and higher.  This could be probably because educated mothers tend to marry later thus delaying child bearing and conceive fewer children over the course of their lives. Opposite findings were observed in a Kerala-based study. 
The present study showed that there was a statistically significant inverse association between family income per month and LBW. Similar findings were observed in an urban slum of Mumbai.  This was because of the poor maternal nutritional intake during pregnancy which was recorded in the lower socioeconomic class study subjects.
The association between LBW and interval between pregnancies was found to be significant in the present study. Short birth interval was found to be significantly associated with LBW (O.R. -3.84) in a Nagpur-based study.  This was probably because most of the study subjects were from the severe or moderate category of anemia.
Attained weight at third trimester was inversely and significantly associated with proportion of LBW in the present study. In another study done in Mumbai it was observed that post-delivery weight of the women is a proxy for prepregnancy weight and maternal weight less than 40 kg contributed significantly to higher rate of LBW (43.6%). 
It was observed in the present study that 141 (67.1%) of the total study women had BMI in the range of 18.5-24.99 in the last trimester, 11 (5.2%) were with BMI less than 18.5 and 58 (27.6%) were with BMI more than 25. The association between BMI in the third trimester and LBW was statistically significant. Similar findings were recorded in the analysis of anthropometric data of Indian population. 
In the current study proportion of LBW was found to vary inversely with maternal hemoglobin levels and thus majority 38 (66.7%) of the LBW outcomes were of the study subjects with hemoglobin ≤10.9 g%. In a case control study involving pregnant Nepali women it was observed that severe maternal anemia (hematocrit = ≤24%) was significantly associated with increased risk of LBW.  This is mainly because iron is one of the predominant nutritive sources for mother (in combating the stress of pregnancy) as well as for the fetus (in growth and development) and thus its deficiency will definitely have an impact on birth weight of child.
Thirty-two (15.2%) of the present study participants were having addiction of tobacco in any form. It also reveals that the proportion of LBW was significantly higher in subjects with tobacco addiction 14 (43.7%) as compared to nonusers of tobacco 43 (24.2%). In an Indian study effect of smokeless tobacco on the outcome of pregnancy was studied where LBW was observed in 61.1% of tobacco users. The results were statistically significant (P < 0.001).  This is because nicotine which is a constituent of tobacco causes vasoconstriction of the maternal blood vessels which are the only single source of nutrition to the foetus and thus leading to an outcome of LBW.
The present study had its limitations in the form that estimation of neonatal birth weight was done using hospital records as the principal investigator was not present at the time of delivery. Dietary intake assessment was measured only by 24-hours recall method and hence accurate estimation of daily caloric intake was not possible. In addition husbands of study subject were not involved in the study so it is a potential limitation. Also assessment of the role of micro nutrients in determination of birth weight was not feasible.
| Conclusions|| |
LBW continues to be a significant public health problem and as multiple factors are associated with it, it requires a more Holistic and Multipronged approach for its reduction. Concept of high-risk approach needs to be implemented which means better health care services to all antenatal subjects with special attention to those who are found to be at high risk. Early registration of pregnancy should be promoted so as to detect presence of any high-risk factors at the earliest. Importance of regular ANC visits should be explained to each of the high-risk women so that any untoward consequences can be averted. Serial monitoring of weight gain must be done in each ANC visit so that subjects identified as underweight can be given attention throughout antenatal period and delivery. Involvement of the community-level workers should be encouraged in the management and follow-up of high-risk cases at regular intervals. Consumption of tobacco in any form should be discouraged among mothers as well as their husband. Strengthening Information-Education-Counseling activities at health centers and in the community would help to a great extent. Such education must address on issues like hazardous effect of tobacco use and harms of early marriage and teenage pregnancy.
| Acknowledgment|| |
Head of the Department of Community Medicine for guiding us throughout the duration of study.
| References|| |
|1.||Ramakutty P, Tikreti RA, Resam KW. A study on birth weight of Iraqi children. J Trop Pediatr 1983;29:5-10. |
|2.||UNICEF. Statistics: End Decade Database: Low birth weight 2000. Available from: http://www.unicef.org [Last accessed on 2012 Aug 12]. |
|3.||Wang CS, Chou P. Risk factors for LBW among first time mothers in Southern Taiwan. J Formos Med Assoc 2001;100:168-72. |
|4.||UNICEF. Multiple Indicator Cluster Surveys (MICS) and Demographic and Health Surveys (DHS) and other national surveys, 2003-2008. Available from: http://www.unicef.org/mozambique/MICS_Summary_English_201009.pdf [Last accessed on 2012 Aug 12]. |
|5.||Park JE, Park K. Text Book of Preventive and Social Medicine. 20 th ed. Jabalpur: Banarsidas Bhanot Publishers; 2011. |
|6.||Kramer MS. Determinants of low birth weight, methodological assessment and Meta analysis Bull World Health Organ 1987;65:663-737. |
|7.||Spencer N, Logan S. Social influences on birth weight. J Epidemiol Community Health 2002;56:326-7. |
|8.||Makhija K, Murthy GV, Kapoor SK, Lobo J. Socio- biological determinants of birth weight. Indian J Paed 1989;56:639-43. |
|9.||Anand K, Garg BS. A study of factors affecting low birth weight. Indian J Community Med 2000;25:57-62. |
|10.||De Groot LC. High maternal body weight and pregnancy outcome. Nutr Rev 1999;57:62-4. |
|11.||Park JH, Lee BE, Park HS, Ha EH, Lee SW, Kim YJ. Association between pre-pregnancy body mass index and socioeconomic status and impact on pregnancy outcomes in Korea. J Obstet Gynaecol Res 2011;37:138-45. |
|12.||Berghella V. Prevention of recurrent fetal growth restriction. Obs Gyn. 2007;110:904-12. |
|13.||Sebastián MG, Angel SH, Irene VZ, López Criado MS, Alicia PL, José LG. Abnormal maternal body mass index and obstetric and neonatal outcome. J Matern Fetal Neonatal Med 2011;25:308-12. |
|14.||Upadhyay S, Biccha RP, Sherpa MT, Shrestha S, Panta PP. Association between maternal body mass index and the birth weight of neonates. Nepal Med Coll J 2011;13:42-5. |
|15.||Park JE, Park K. Text Book of Preventive and Social Medicine. 21 st ed. Jabalpur: Banarsidas Bhanot Publishers; 2011. p. 638-40. |
|16.||World Health Organization - WHO. WHO Global database on Body Mass Index. Available from: http://apps.who.int/bmi/index.jsp?introPage=intro_3.html. [Last accessed on 2012 Sep 22]. |
|17.||Iron deficiency anaemia: Assessment, prevention, and control. A guide for programme managers. Geneva: World Health Organization; 2001. (WHO/NHD/01.3). Available from: http://www.searo.who.int/LinkFiles/Publications_Iron_Deficiency_Anaemia_Assessment_Prevention_and_Control.pdf. [Last accessed on 11 July 2012]. |
|18.||Kapoor SK, Kumar G, Pandav CS, Anand K. Incidence of low birth in rural Ballabgarh, Haryana. Indian Paediatr 2001;38:271-5. |
|19.||Kamaladoss T, Abel R, Sampathkumar V. Epidemiological correlates of LBW in rural TamilNadu. Indian J Paediatr 1992;59:299-04. |
|20.||Raman L, Rao KV, Adinarayana K, Rawal A, Vasumathi N, Parvati CH, et al. Risk care approach to anemia in pregnancy in an urban slum, maternal anthropometry and pregnancy outcome. Bull World Health Organ 1995;73(Suppl):75-6. |
|21.||Aras R, Pai N, Baliga A. Pregnancy at teenage: Risk factor for low birth weight. Indian Paediatr 1990;26:823-5. |
|22.||Joshi S, Pai NP. Effects of the maternal bio-social determinants on the birth weight in a slum area of Greater Mumbai. Indian J Community Med 2000;25:121-3. |
|23.||Radhakrishnan T, Thankappan KR, Vasan RS, Sarma PS. Socioeconomic and demographic factors associated with birth weight: A community based study in Kerala. Indian Paediatr 2000;37:872-6. |
|24.||Deshmukh JS, Motghare DD, Zodpey SP, Wadhva SK. Low birth weight and associated maternal factors in an urban area. Indian Paediatr 1998;35:33-6. |
|25.||Hirve SS, Ganatra BR. Determinants of low birth weight: A community based prospective cohort study. Indian Paediatr 1994;31:1221-5. |
|26.||Naidu AN, Rao NP. Maternal body mass index: A measure of the nutritional status in Indian population. Eur J Clin Nutr 1994;48(Suppl 3):S131-40. |
|27.||Bondevik GT, Lie RT, Ulstein M, Kvåle G. Maternal haematological status and risk of low birth weight and preterm delivery in Nepal. Acta Obstet Gynaecol Scand 2001;80:402-8. |
|28.||Asif R, Sinha SN, Zaheer M. Outcome of pregnancy in women using tobacco. Indian J Community Health 1994;7:17-9. |
[Table 1], [Table 2], [Table 3]