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Article

Maternal Factors and Utilization of the Antenatal Care Services during Pregnancy Associated with Low Birth Weight in Rural Nepal: Analyses of the Antenatal Care and Birth Weight Records of the MATRI-SUMAN Trial

1
Department of Preventive Medicine, College of Medicine, Dongguk University, Gyeongju 38066, Korea
2
Department of Community Medicine and Public Health, Janaki Medical College, Tribhuvan University, Janakpur 44618, Nepal
3
Personal Social Services Research Unit, London School of Economics and Political Science, London, WC2A2AE, UK
*
Author to whom correspondence should be addressed.
Int. J. Environ. Res. Public Health 2018, 15(11), 2450; https://doi.org/10.3390/ijerph15112450
Submission received: 9 October 2018 / Revised: 29 October 2018 / Accepted: 31 October 2018 / Published: 3 November 2018
(This article belongs to the Section Children's Health)

Abstract

:
Low birth weight (LBW) remains a major public health problem in developing countries, including Nepal. This study was undertaken to examine the association between LBW and maternal factors and antenatal care service utilization, in rural Nepal, using data obtained for a capacity-building and text-messaging intervention, designed to enhance maternal and child health service utilization among pregnant women, in rural Nepal (“MATRI-SUMAN”). The study used a clustered randomized controlled design and was conducted during 2015–2016. We investigated maternal and antenatal care service utilization determinants of LBW, using a logistic regression model. Of the four hundred and two singleton babies, included in the present study, seventy-eight (19.4%) had an LBW (mean (SD), 2210.64 (212.47)) grams. It was found that Dalit caste/ethnicity, illiteracy, manual labor, a female baby, and having more than four family members were significantly positively associated with LBW. In addition, mothers who did not visit an antenatal care (ANC) unit, visited an ANC < 4 times, did not take iron and folic acid (IFA), de-worming tablets, and mothers that did not consume additional food, during pregnancy, were more likely to have an LBW baby, than their counterparts. The MATRI-SUMAN intervention and availability of a kitchen garden at home, were found to reduce the risk of LBW. Nepalese child survival policies and programs should pay attention to these maternal and antenatal care service utilization factors, while designating preventive strategies to improve child health outcomes.

1. Introduction

Low birth weight (LBW) has been defined as a birth weight <2500 grams [1]. In 2013, an estimated 16 per cent (22 million) of all babies born globally, had LBW and 96% of these babies were born in developing countries [1,2]. In Nepal, a recent study, using the Nepal Demographic and Health Survey 2011 data showed that the prevalence of LBW was 15.4% [3]. It was noted that LBW babies are at a greater risk of dying in the first year of life [4]. LBW can result from either intra-uterine growth restriction, small-for-gestational-age (born before 37 weeks of gestation) or a combination of the two [1,5,6]. The majority of LBW cases in developing countries are due to intra-uterine growth retardation, while pre-term birth is common in the developed countries [7]. In addition to adverse consequences, such as, increased neonatal morbidity and mortality, inhibition of growth and cognitive development, and an increased risk of chronic disease development, later in life, LBW also has substantial cost burdens on health care systems and society [1,8,9,10]. Several recent studies have concluded that LBW increases the risk of non-communicable diseases, such as, diabetes and cardiovascular conditions, later in life [11,12,13]. Moreover, LBW has been reported to be associated with negative effects on long-term cognitive and motor development, and on decision-making [14].
Numerous direct and indirect factors have been associated with LBW [15,16,17]. Socio-demographic and economic characteristics, age, household food security, and the use of maternity services are some of the indirect determinants identified, whereas race, maternal height and pre-pregnancy weight, gestational weight gains, calorie intake during pregnancy, perinatal morbidity, parity, infant’s sex, alcohol and cigarette consumption during pregnancy, and prior history of prematurity, among others, have been reported to be direct determinants [16,17,18,19].
Few community-based studies have assessed the risk factors of LBW in Nepal. In a recent Nepalese study on nationally representative samples, it was reported that 12% of infants had an LBW, and that mothers who did not attend antenatal care units, did not take iron tablets during pregnancy, and resided in the westernmost region of the country were at a significant risk of having an LBW baby [20]. Given that the majority (65%) of births took place at home [21] and no significant change was detected between the percentages of LBW babies observed in the 2011 and the 2016 Demographic and Health Surveys (~12% in both surveys) [22], LBW is now considered an important public health problem. Therefore, further understanding of the risk factors of LBW is required to support the early identification of those at risk and facilitate the implementations of evidence-specific interventions to reduce the long-standing problem of LBW in Nepal. To fulfill the existing evidence gap, we aimed to examine the association between low birth weight and maternal factors and utilization of antenatal care services, in rural Nepal.

2. Materials and Methods

2.1. Study Design, Population, and Sampling

We used data from a capacity-building and text-messaging intervention that was developed to enhance maternal and child health service utilization among pregnant women, in rural Nepal (“MATRI-SUMAN”), which was conducted using a clustered randomized controlled design. Pregnant women aged 15–49 years, in their second trimester (13–28 weeks of gestation), from fifty-two clusters (wards) of six village development committees (VDCs), from the Dhanusha district, were selected for the MATRI-SUMAN trial, using multistage cluster sampling method. During the first stage of the MATRI-SUMAN trial, two healthcare facilities were selected as a primary sampling unit. In the second stage, six of the twelve VDCs, in the catchment areas of these two healthcare facilities, were selected, using a stratified random sampling method. In the intervention group, Female Community Health Volunteers (FCHVs) were trained in capacity development skills through reinforcement training, supervision, and monitoring of maternal and child health care services. Pregnant women received periodic health promotion texts about maternal and child health (MCH) components, via a mobile messaging service, while participants in the control group received the usual care. Details of the study design have been reported in a previously published paper [23].
A total of four hundred and twenty-six pregnant women aged 15–49 participated in the MATRI-SUMAN trial. Of the four hundred and twenty-six participants interviewed at baseline, four hundred and thirteen of them were approached at postnatal follow-up and the remainder were not available for follow-up (of the thirteen missing cases, seven had moved to their parental home and six had a miscarriage). Additionally, we were not able to measure the birth weights, within the stipulated time, for eight cases and three mothers had still births, giving us a sample of four hundred and two mothers with live birth babies. Among the four hundred and two cases, seventy-eight newborn babies had low birth weight and the remaining three hundred and twenty-four babies had normal birth weight. We included four hundred and two live birth cases for the statistical analyses (Figure 1). The criteria we used for data selection were as follows; singleton live birth with birth weight measured within one hour of birth, for institutional delivery, and within forty-eight hours of birth, for home delivery. A pan balance was used to measure birth weights in a health facility (hospital/birthing center) and a color-coded spring balance was used by a local FCHV, for the home deliveries. Three sets of validated questionnaires that were adopted from the Nepal Demographic and Population Health Survey, 2011, were used to collect information [21]. These questionnaires addressed; (i) the socio-demographic and household characteristics of pregnant women, (ii) obstetric history of pregnant women, and iii) newborn information. The study data contained information on maternal factors, newborn weight, and maternal utilization of antenatal care services.

2.2. Definition of Variables

A low birth weight (LBW) was defined as one <2500 grams. Birth weights were classified as LBW (<2500 grams) or (ii) normal (≥2500 grams or more), and birth weight was the dependent variable in the present study. Independent variables examined were chosen, as previously described [24]. Age was classified as: (i) <20 years, (ii) 20–34 years, or (iii) ≥35 years. Ethnicity was classified as, (i) upper caste group—Brahmin, Chhetri, and other relatively-advantaged Terai caste groups (Yadav, Shaha, Thakur), (ii) Adibasi/Janajati– Janajati or indigenous groups, and (iii) Dalit (relatively disadvantaged) [25]. Education was recorded as number of completed years of education and classified as, (i) illiterate—no education, (ii) primary—1 to 5 years of education, and (iii) secondary and above (≥6 years of education) [24]. Occupations were categorized as, (i) business or private/government work or involved in household work; (ii) agricultural work on own farms, and (iii) manual labor. Incomes were classified using monthly family incomes and categorized using terciles, (i) 1st tercile (income <14,333 Nepalese Rupees/month (NRs/month), (ii) 2nd tercile (14334–23666 NRs/month), of (iii) 3rd tercile (>23666 NRs/month). Parity was categorized as primiparous or multiparous. Head of household was included as an indicator of maternal autonomy and classified as, (i) the pregnant women herself or (ii) husband/mother-in-law, father-in-law, or others. Personal dietary habits were recorded as vegetarian or non-vegetarian. Family size was classified as ≤4 or >4. Number of living rooms were classified as, (i) sufficient if there were not >2 family members sleeping per room or (ii) insufficient if >2 family members slept in a room. Reponses regarding the presence of domestic animals in a household and of a home kitchen garden were recorded as “yes” or “no”. Antenatal care (ANC) visits were categorized as, (i) no ANC visit, (ii) <4 ANC visits, and (iii) ≥4 ANC visits. Iron and folic acid (IFA) consumption and tetanus and diphtheria (TD) immunization were recorded as “yes” or “no”. Similarly, other components of antenatal care (like de-worming, adequate rest, and sleep (Eight hours of sleep during night time and two hours during day time), additional food (defined as one extra meal per day as recommended by the government of Nepal) were also coded as “yes” or “no”.

2.3. Statistical Analysis

The Chi-square test (unadjusted) was used to examine the association between the LBW and the categorical independent variables of interest. All factors, significant by the unadjusted analysis, were included in the multiple logistic regression analysis to control for confounding effects. Unadjusted and adjusted odds ratios, with their 95% confidence intervals (CI), were reported. Variables having p-value ≤0.1 were entered in a final multivariate logistic regression model with a backward elimination and the analysis results with a p-value of <0.05 was considered statistically significant. Statistical analysis was performed using the Statistical Package for Social Sciences version 21.0 (SPSS, IBM, Armonk, NY, USA).

2.4. Ethical Considerations

The study protocol was approved by the Nepal Health Research Council (approval no: 101), the Ethics Committee of the Institute of Medical Sciences, Banaras Hindu University, India (approval no: ECR/ 526/Inst/UP/2014 Dt.31.1.14) and District Public Health Office, Dhanusha, Nepal (Ref. 2245). Additional ethical approval for the data analysis was obtained from the Institutional Review Board of Janaki Medical College, Nepal. The study objectives and procedures were explained, and a written informed consent was taken from each participant, before the data collection process began. Personal identifiers were removed before data analysis.

3. Results

3.1. Status of Birth Weight

Figure 2 shows the distribution of average birth weight (with standard deviations) of the newborn babies. The average birth weight for the LBW babies was 2210.64 grams with a standard deviation of 212.47 grams, whereas the mean birth weight for the normal weight babies was 3054 grams with a standard deviation of 424 grams. Mean difference in birth weight between an LBW baby and a normal baby was found to be significant (843.24 gm; p < 0.0001, 95% CI: 745.94–940.55).

3.2. Maternal Factors and Utilization of Antenatal Care Services

Table 1 summarizes the maternal characteristics. 402 mother-child pairs were analyzed and the majority of mothers were 20–34 years old (69.2%), upper caste (61.2%), and had a primary or greater education level (75.2%). Almost a half (49.8%) worked in the service/business/household sectors, the majority (65.6%) had second and third terciles of family income, most maternal in-laws/husbands were family heads (77.6%), slightly more than half (51.5%) were from the MATRI-SUMAN intervention area, the majority were from the Terai origin by birth (71.6%), non-vegetarian (79.6%), multiparous (60.9%), slightly more than half ( 52.5%) gave birth to a female baby and had four or fewer family members (52.7%), just over one-third (39.6%) had domestic animals, and the majority (66.4%) had a kitchen garden. Maternal factors, such as, caste/ethnicity, educational status, occupation, family income, head of the family, area of residence, parity, number of family members in a household, adequacy of living rooms for the family, and use of a kitchen garden were found to be significantly associated with LBW (Table 1).
Regarding ANC service utilization, more than half (59.7%) visited four or more ANCs, 58.5% consumed recommended doses of iron and folic acid tablets, 81.6% were properly immunized for tetanus and diphtheria, 81.3% consumed de-worming tablets, 84.3% got adequate rest and sleep, and about one in four received additional food during pregnancy. Utilization of the antenatal care services during pregnancy (as indicated by the number of antenatal care visits), consumption of recommended doses of iron and folic acid (IFA), immunization for tetanus and diphtheria, consumption of deworming tablets, adequate rest and sleep, and additional food intake during pregnancy, were significantly associated with LBW (Table 2).

3.3. Associations between Low Birth Weight and Maternal Factors and the Utilization of Antenatal Care Services

Table 3 shows the results of multivariate analyses on the determinants of LBW. Statistically significant factors that influenced LBW are listed in Table 1 and Table 2, and these were included in the multiple logistic regression model. Maternal socio-demographic factors, such as caste/ethnicity, educational status, occupation, family size, and other factors, such as sex of child, having access to a kitchen garden, and living in the MATRI-SUMAN intervention area were significantly associated with LBW. Similarly, the utilization of antenatal care services as indicated by number of ANC visits, taking recommended doses of IFA tablets and de-worming tablets, and additional food intake during pregnancy, were significantly associated with LBW.
Mothers from the Dalit caste/ethnicity group were four-times more likely (aOR 4.2; 95% CI (1.7–10.4)) to have an LBW baby than mothers from the Adibasi/Janajati and upper-caste groups. Similarly, illiterate mothers were eight-times more likely (aOR 8.1; 95% CI (2.9–22.4)) to have an LBW baby than literate mothers. Mothers that performed manual work were at greater risk (aOR 5.9; 95% CI (1.6–21.1)) of having an LBW baby than mothers with an agricultural or service/business/household occupation. Female children were twice more likely (aOR 2.0; 95% CI (1.0–4.1)) to be born with an LBW than male children. Mothers who had more than four family members had higher odds of having LBW babies (aOR 5.6; 95% CI (2.3–13.5)) than mothers who had four or fewer number of family members. Mothers in the MATRI-SUMAN intervention area were less likely (aOR 0.37; 95% CI (0.16–0.83)) to have an LBW baby than mothers not in the intervention area. Access to a kitchen garden reduced the risk (aOR 0.15; 95% CI (0.06–0.37)) of having an LBW baby.
Mothers who had not visited ANCs were five-times more likely (aOR 5.1; 95% CI (1.1–22.6)) to have an LBW baby, and mothers who visited an ANC, less than four times, were three-times more likely (aOR 3.4; 95% CI (1.1–10.2)) to have an LBW baby than the mothers who visited four or more times. Not taking IFA tablets during pregnancy increased the risk (aOR 3.0; 95% CI (1.1–8.2)) of an LBW baby. Mothers who did not consume de-worming tablets during pregnancy were three-times more likely (aOR 3.1; 95% CI (1.0–13.8)) to have an LBW baby. Finally, not taking additional food during pregnancy was found to increase the risk (aOR 3.6; 95% CI (1.3–9.4)) of delivering an LBW baby.

4. Discussion

We found a wide range of maternal factors, that is, the Dalit caste/ethnicity, illiteracy, occupation as a manual laborer, having four or more family members, and birth of a female child were significantly positively associated with an LBW, and that those with a kitchen garden and those who resided in the intervention area of the MATRI-SUMAN trial area were less likely to have LBW babies. In addition, lack of utilization of antenatal care services (as indicated by no ANC visit), fewer than four ANC visits, not consuming the recommended doses of IFA and de-worming tablets, and not consuming additional food during pregnancy, increased the risk of an LBW baby.
Our study revealed that babies born to mothers from the Dalit caste/ethnic group were at a greater risk of having an LBW baby than those from the Adibasi/Janajati and upper caste/ethnic group. Several previous studies have also observed relations between ethnicity and LBW [26,27,28]. The Dalit ethnic group in Nepal are one of the most deprived and marginalized, many lack basic amenities, and fail to utilize available maternity care services [25,29]. Results from previous studies have consistently demonstrated that Dalit women are at risk of having LBW babies in Nepal [30,31]. Like many other studies [17,18,32,33], we also found that illiterate mothers were more likely to give birth to LBW babies, which may be due to a lesser use of antenatal care services because of a lack of knowledge and decision-making power [34]. Lower maternal education has been previously reported to be associated with poor utilization of prenatal care services and low nutritious food intake, and thus, to increase the risk of LBW babies [35,36]. Additionally, adolescent marriage and pregnancy is one of the major causes of LBW babies and is prevalent among illiterate women [37]. Increasing girls’ education levels, female empowerment, raising health awareness through mass media, and nutritional counseling during antenatal check-ups, would help a lot to address the long-standing problem of LBW, in Nepal [18,34,38].
In the present study, maternal occupation as a manual laborer, four or more family members in a household, and birth of female child were found to increase the risk of LBW, while access to a kitchen garden or residing in the MATRI-SUMAN intervention area reduced the risk of LBW. Furthermore, we found that physical hard work was found to increase the risk of LBW babies, which concurred with the findings of two Indian studies and one Nepalese studies, which showed hard physical work during pregnancy increased the risk of LBW babies [39,40,41]. In another study, it was suggested that higher energy expenditure might lower maternal nutrients and adversely impact birth weight [42]. Incremental risks of LBW have also been attributed to maternal socioeconomic and demographic factors [17,43], possibly because socioeconomic conditions influence the use of essential maternal and child health services [44], maternal nutrition [45], and maternal decision-making power [46]. Our observation that female babies are more at risk of an LBW is supported by studies conducted in Kenya [47], Ethiopia [48,49], Nepal [20] and Australia [50].
Previous study reported male babies are less likely to have LBW, compared to their female counterparts because the male chromosome confers advantages in the determination of birth weight [51]. Interestingly, having access to a kitchen garden at home provides opportunities to increase dietary diversity and consume green leafy vegetables during pregnancy [52]. This study also revealed that mothers in the intervention area were found to be at a lower risk of having an LBW baby, indicating the beneficial effects of MATRI-SUMAN intervention [23] in lowering LBW cases.
We also found that a lack of utilization of essential prenatal care services was linked to LBW. A number of previous studies are in agreement with our finding of a positive association between LBW and poor utilization of prenatal care services, as indicated by low numbers of ANC visits [18,20,32,33,53], non-consumption of IFA [18,20,32] and de-worming tablets [54,55], and no additional food intake [56,57] during pregnancy. An adequate number of antenatal visits aids the early recognition of pregnancy complications and promotes maternal nutrition and necessary care during pregnancy [58,59]. For example, an adequate consumption of IFA tablets reduces maternal anemia, the risks of pre-term birth and LBW [60], the consumption of de-worming tablets during pregnancy prevents worm infestation, and thereby, the proportion of LBW babies [54,61], and an extra meal taken during pregnancy ensures that the growing demand for calories during pregnancy, is met [62].
Previous studies have reported that mothers employed in the agricultural sector [63] have no maternal autonomy [3,46], are multi-parous [64], reside in a single-room apartment [65], have insufficient rest during pregnancy [66] and are at higher risk of giving birth to LBW babies. The univariate analysis conducted in the present study also demonstrated that mothers working in these sectors had a family income in the second tercile, an in-law/husband as the head of family, were multiparous, had an inadequate number of rooms in their homes, and had inadequate time for rest and sleep, were at higher risk of having an LBW baby. However, these associations disappeared after controlling for potential confounders in the multivariate regression analysis.
The present study was conducted to examine an important child healthcare problem faced by many developing countries and had a high response rate. However, our findings should be understood in the light of its pitfalls. First, data collection was conducted in a cross-sectional manner, which prevented investigation of causal relationships. Second, information on socioeconomic and maternal factors was self-reported, and thus, might be subject to bias. Third, although calibrated instruments were used, the different instruments were used to measure the facility-born and home-born (newborn) babies, and this may have influenced their birth weights. Fourth, this study was conducted in a small rural area of Nepal on a relatively small cohort, so special precautions should be taken to generalize our study findings. Nonetheless, a number of clusters from a rural community of Nepal was enrolled in the study, which we feel has policy implications.

5. Conclusions

Child survival policies and programs in Nepal aimed at improving child health outcomes should pay more attention to maternal and antenatal care service utilization factors. In our opinion bespoke maternal and child health programs, such as MATRI-SUMAN, a capacity-building and text-messaging intervention designed to improve maternal and child health outcomes, should be promoted. We suggest future studies to explore the determinants of small-for-gestational-age and pre-term births, and the economic feasibility of MATRI-SUMAN interventions in Nepal and other south Asian countries.

Author Contributions

D.A. and J.K.S. conceived the study design and performed the statistical analysis. D.A., J.K.S., R.K. wrote the manuscript and S.-J.Y., J.-H.P., and K.L. contributed substantially to the manuscript. All authors subsequently reviewed, revised, and approved the final version of the manuscript.

Funding

This study received partial funding (logistics support) from Janaki Medical College Teaching Hospital (JMCTH) to implement the MATRI-SUMAN trial (Grant Number: RES-11-2072-73). The JMCTH did not contribute to the writing of this manuscript or to the decision to submit the manuscript for publication.

Acknowledgements

We thank Janaki Medical College Teaching Hospital (JMCTH) for the logistical support provided during the implementation of the MATRI-SUMAN trial and for the provision of analytical facilities.

Conflicts of Interest

The authors have no conflict of interest to declare.

References

  1. Wardlaw, T.M. Low Birthweight: Country, Regional and Global Estimates; Unicef: New York, NY, USA, 2004. [Google Scholar]
  2. United Nations Children’s Fund (UNICEF). Low Birhtweight. Available online: https://data.unicef.org/topic/nutrition/low-birthweight/ (accessed on 27 October 2018).
  3. Singh, U.; Ueranantasun, A.; Kuning, M. Factors associated with low birth weight in nepal using multiple imputation. BMC Pregnancy Childbirth 2017, 17, 67. [Google Scholar] [CrossRef] [PubMed]
  4. Lawn, J.E.; Cousens, S.; Zupan, J. 4 million neonatal deaths: When? Where? Why? Lancet 2005, 365, 891–900. [Google Scholar] [CrossRef]
  5. Barros, F.C.; Barros, A.J.; Villar, J.; Matijasevich, A.; Domingues, M.R.; Victora, C.G. How many low birthweight babies in low- and middle-income countries are preterm? Rev. Saude Publica 2011, 45, 607–616. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  6. Kramer, M.S. Intrauterine growth and gestational duration determinants. Pediatrics 1987, 80, 502–511. [Google Scholar] [PubMed]
  7. Qadir, M.; Bhutta, Z.A. Low birth weight in developing countries. In Small for Gestational Age; Karger Publishers: Basel, Switzerland, 2009; Volume 13, pp. 148–162. [Google Scholar]
  8. Alderman, H.; Behrman, J.R. Reducing the incidence of low birth weight in low-income countries has substantial economic benefits. World Bank Res. Obs. 2006, 21, 25–48. [Google Scholar] [CrossRef]
  9. Chen, W.; Srinivasan, S.R.; Yao, L.; Li, S.; Dasmahapatra, P.; Fernandez, C.; Xu, J.; Berenson, G.S. Low birth weight is associated with higher blood pressure variability from childhood to young adulthood: The bogalusa heart study. Am. J. Epidemiol. 2012, 1, S99–S105. [Google Scholar] [CrossRef] [PubMed]
  10. Harding, J.E. The nutritional basis of the fetal origins of adult disease. Int. J. Epidemiol. 2001, 30, 15–23. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  11. Ediriweera, D.S.; Dilina, N.; Perera, U.; Flores, F.; Samita, S. Risk of low birth weight on adulthood hypertension—Evidence from a tertiary care hospital in a south asian country, sri lanka: A retrospective cohort study. BMC Public Health 2017, 17, 358. [Google Scholar] [CrossRef] [PubMed]
  12. Larroque, B.; Bertrais, S.; Czernichow, P.; Leger, J. School difficulties in 20-year-olds who were born small for gestational age at term in a regional cohort study. Pediatrics 2001, 108, 111–115. [Google Scholar] [CrossRef] [PubMed]
  13. Risnes, K.R.; Vatten, L.J.; Baker, J.L.; Jameson, K.; Sovio, U.; Kajantie, E.; Osler, M.; Morley, R.; Jokela, M.; Painter, R.C.; et al. Birthweight and mortality in adulthood: A systematic review and meta-analysis. Int. J. Epidemiol. 2011, 40, 647–661. [Google Scholar] [CrossRef] [PubMed]
  14. Christian, P.; Murray-Kolb, L.E.; Tielsch, J.M.; Katz, J.; LeClerq, S.C.; Khatry, S.K. Associations between preterm birth, small-for-gestational age, and neonatal morbidity and cognitive function among school-age children in nepal. BMC Pediatr. 2014, 14, 58. [Google Scholar] [CrossRef] [PubMed]
  15. Ashish, K.C.; Nelin, V.; Wrammert, J.; Ewald, U.; Vitrakoti, R.; Baral, G.N.; Malqvist, M. Risk factors for antepartum stillbirth: A case-control study in nepal. BMC Pregnancy Childbirth 2015, 15, 146. [Google Scholar]
  16. Kramer, M.S. Determinants of low birth weight: Methodological assessment and meta-analysis. Bull. World Health Organ. 1987, 65, 663–737. [Google Scholar] [PubMed]
  17. Sebayang, S.K.; Dibley, M.J.; Kelly, P.J.; Shankar, A.V.; Shankar, A.H.; Group, S.S. Determinants of low birthweight, small-for-gestational-age and preterm birth in lombok, indonesia: Analyses of the birthweight cohort of the summit trial. Trop. Med. Int. Health 2012, 17, 938–950. [Google Scholar] [CrossRef] [PubMed]
  18. Gizaw, B.; Gebremedhin, S. Factors associated with low birthweight in north shewa zone, central ethiopia: Case-control study. Ital. J. Pediatr. 2018, 44, 76. [Google Scholar] [CrossRef] [PubMed]
  19. Khanal, V.; Sauer, K.; Karkee, R.; Zhao, Y. Factors associated with small size at birth in nepal: Further analysis of nepal demographic and health survey 2011. BMC Pregnancy Childbirth 2014, 14, 32. [Google Scholar] [CrossRef] [PubMed]
  20. Khanal, V.; Zhao, Y.; Sauer, K. Role of antenatal care and iron supplementation during pregnancy in preventing low birth weight in nepal: Comparison of national surveys 2006 and 2011. Arch. Public Health 2014, 72, 2049–3258. [Google Scholar] [CrossRef] [PubMed]
  21. Ministry of Health and Population; New ERA; ICF International. Nepal Demographic and Health Survey 2011; Ministry of Health and Population; New ERA: Kathmandu, Nepal; ICF International: Calverton, MD, USA, 2012.
  22. Ministry of Health and Population; New ERA; ICF International. Nepal Demographic and Health Survey 2016; Ministry of Health and Population; New ERA: Kathmandu, Nepal; ICF International: Calverton, MD, USA, 2017.
  23. Singh, J.K.; Kadel, R.; Acharya, D.; Lombard, D.; Khanal, S.; Singh, S.P. ‘Matri-suman’ a capacity building and text messaging intervention to enhance maternal and child health service utilization among pregnant women from rural nepal: Study protocol for a cluster randomised controlled trial. BMC Health Serv. Res. 2018, 18, 447. [Google Scholar] [CrossRef] [PubMed]
  24. Singh, J.K.; Acharya, D.; Kadel, R.; Adhikari, S.; Lombard, D.; Koirala, S.; Paudel, R. Factors associated with smokeless tobacco use among pregnant women in rural areas of the southern terai, nepal. J. Nepal Health Res. Counc. 2017, 15, 12–19. [Google Scholar] [CrossRef] [PubMed]
  25. Bennett, L.; Dahal, D.R.; Govindasamy, P. Caste ethnic and regional identity in nepal: Further analysis of the 2006 nepal demographic and health survey. Available online: https://dhsprogram.com/pubs/pdf/FA58/FA58.pdf (accessed on 13 August 2018).
  26. Collins, J.W., Jr.; David, R.J. The differential effect of traditional risk factors on infant birthweight among blacks and whites in chicago. Am. J. Public Health 1990, 80, 679–681. [Google Scholar] [CrossRef] [PubMed]
  27. Fang, J.; Madhavan, S.; Alderman, M.H. Low birth weight: Race and maternal nativity—Impact of community income. Pediatrics 1999, 103, e5. [Google Scholar] [CrossRef] [PubMed]
  28. Kleinman, J.C.; Kessel, S.S. Racial differences in low birth weight. Trends and risk factors. N. Engl. J. Med. 1987, 317, 749–753. [Google Scholar] [CrossRef] [PubMed]
  29. Bakewell, J.M.; Stockbauer, J.W.; Schramm, W.F. Factors associated with repetition of low birthweight: Missouri longitudinal study. Paediatr. Perinat. Epidemiol. 1997, 11 (Suppl. 1), 119–129. [Google Scholar] [CrossRef]
  30. Acharya, P.P.; Alpass, F. Birth outcomes across ethnic groups of women in nepal. Health Care Women Int. 2004, 25, 40–54. [Google Scholar] [CrossRef] [PubMed]
  31. Ojha, N. Maternal factors for low birth weight and preterm birth at tertiary care hospital. J. Nepal Med. Assoc. 2015, 53, 250–255. [Google Scholar] [CrossRef]
  32. Habib, M.A.; Greenow, C.R.; Ariff, S.; Soofi, S.; Hussain, A.; Junejo, Q.; Hussain, A.; Shaheen, F.; Black, K.I. Factors associated with low birthweight in term pregnancies: A matched case-control study from rural pakistan. East. Mediterr. Health J. 2018, 23, 754–763. [Google Scholar] [CrossRef] [PubMed]
  33. Tang, W.; Mu, Y.; Li, X.; Wang, Y.; Liu, Z.; Li, Q.; Li, M.; Scherpbier, R.; Guo, S.; Huang, X.; et al. Low birthweight in china: Evidence from 441 health facilities between 2012 and 2014. J. Matern.-Fetal Neonatal Med. 2017, 30, 1997–2002. [Google Scholar] [CrossRef] [PubMed]
  34. Chanda, S.K.; Howlader, M.H.; Nahar, N. Educational status of the married women and their participation at household decision making in rural bangladesh. Int. J. Adv. Res. Technol. 2012, 1, 137–146. [Google Scholar]
  35. Cribb, V.L.; Jones, L.R.; Rogers, I.S.; Ness, A.R.; Emmett, P.M. Is maternal education level associated with diet in 10-year-old children? Public Health Nutr. 2011, 14, 2037–2048. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  36. Dai, L.; Hu, W.; Luo, X.; Shen, Y. Interaction of prenatal care and level of maternal education on the risk of neonatal low birth weight. Zhonghua Liu Xing Bing Xue Za Zhi 2014, 35, 533–536. [Google Scholar] [PubMed]
  37. Bates, L.M.; Maselko, J.; Schuler, S.R. Women’s education and the timing of marriage and childbearing in the next generation: Evidence from rural bangladesh. Stud. Fam. Plan. 2007, 38, 101–112. [Google Scholar] [CrossRef]
  38. Acharya, D.; Khanal, V.; Singh, J.K.; Adhikari, M.; Gautam, S. Impact of mass media on the utilization of antenatal care services among women of rural community in nepal. BMC Res. Notes 2015, 8, 345. [Google Scholar] [CrossRef] [PubMed]
  39. Agarwal, K.; Agarwal, A.; Agrawal, V.; Agrawal, P.; Chaudhary, V. Prevalence and determinants of “low birth weight” among institutional deliveries. Ann. Niger. Med. 2011, 5, 48. [Google Scholar] [CrossRef]
  40. Dickute, J.; Padaiga, Z.; Grabauskas, V.; Gaizauskiene, A.; Basys, V.; Obelenis, V. Do maternal social factors, health behavior and work conditions during pregnancy increase the risk of low birth weight in lithuania? Medicina 2002, 38, 321–332. [Google Scholar] [PubMed]
  41. Sharma, S.R.; Giri, S.; Timalsina, U.; Bhandari, S.S.; Basyal, B.; Wagle, K.; Shrestha, L. Low birth weight at term and its determinants in a tertiary hospital of nepal: A case-control study. PLoS ONE 2015, 10, e0123962. [Google Scholar] [CrossRef] [PubMed]
  42. Jurewicz, J.; Hanke, W.; Makowiec-Dabrowska, T.; Kalinka, J. Heaviness of the work measured by energy expenditure during pregnancy and its effect on birth weight. Ginekol. Pol. 2006, 77, 537–542. [Google Scholar] [PubMed]
  43. Bener, A.; Abdulrazzaq, Y.M.; Dawodu, A. Sociodemographic risk factors associated with low birthweight in united arab emirates. J. Biosoc. Sci. 1996, 28, 339–346. [Google Scholar] [CrossRef] [PubMed]
  44. Celik, Y.; Hotchkiss, D.R. The socio-economic determinants of maternal health care utilization in turkey. Soc. Sci. Med. 2000, 50, 1797–1806. [Google Scholar] [CrossRef]
  45. Ramakrishnan, U. Nutrition and low birth weight: From research to practice. Am. J. Clin. Nutr. 2004, 79, 17–21. [Google Scholar] [CrossRef] [PubMed]
  46. Sharma, A.; Kader, M. Effect of women’s decision-making autonomy on infant’s birth weight in rural bangladesh. ISRN Pediatr. 2013, 12. [Google Scholar] [CrossRef] [PubMed]
  47. Muchemi, O.M.; Echoka, E.; Makokha, A. Factors associated with low birth weight among neonates born at olkalou district hospital, central region, kenya. Pan Afr. Med. J. 2015, 20. [Google Scholar] [CrossRef] [PubMed]
  48. Bugssa, G.; Alemayehu, M.; Dimtsu, B. Socio demographic and maternal determinants of low birth weight at mekelle hospital, northern ethiopia: A cross sectional study. Open J. Adv. Drug Deliv. 2014, 2, 609–618. [Google Scholar]
  49. Asmare, G.; Berhan, N.; Berhanu, M.; Alebel, A. Determinants of low birth weight among neonates born in amhara regional state referral hospitals of ethiopia: Unmatched case control study. BMC Res. Notes 2018, 11, 447. [Google Scholar] [CrossRef] [PubMed]
  50. Herceg, A.; Simpson, J.M.; Thompson, J.F. Risk factors and outcomes associated with low birthweight delivery in the australian capital territory 1989–90. J. Paediatr. Child Health 1994, 30, 331–335. [Google Scholar] [CrossRef] [PubMed]
  51. Fisher, R.A. The evolution of dominance. Biol. Rev. 1931, 6, 345–368. [Google Scholar] [CrossRef]
  52. Birdi, T.J.; Shah, S.U. Implementing perennial kitchen garden model to improve diet diversity in melghat, India. Glob. J. Health Sci. 2016, 8, 10. [Google Scholar] [CrossRef] [PubMed]
  53. Khanal, V.; Scott, J.A.; Lee, A.H.; Karkee, R.; Binns, C.W. Factors associated with early initiation of breastfeeding in western nepal. Int. J. Environ. Res. Public Health 2015, 12, 9562–9574. [Google Scholar] [CrossRef] [PubMed]
  54. Christian, P.; Khatry, S.K.; West, K.P., Jr. Antenatal anthelmintic treatment, birthweight, and infant survival in rural nepal. Lancet 2004, 364, 981–983. [Google Scholar] [CrossRef]
  55. Larocque, R.; Casapia, M.; Gotuzzo, E.; MacLean, J.D.; Soto, J.C.; Rahme, E.; Gyorkos, T.W. A double-blind randomized controlled trial of antenatal mebendazole to reduce low birthweight in a hookworm-endemic area of peru. Trop. Med. Int. Health 2006, 11, 1485–1495. [Google Scholar] [CrossRef] [PubMed]
  56. Wang, J.; Zeng, Y.; Ni, Z.M.; Wang, G.; Liu, S.Y.; Li, C.; Yu, C.L.; Wang, Q.; Nie, S.F. Risk factors for low birth weight and preterm birth: A population-based case-control study in wuhan, china. J. Huazhong Univ. Sci. Technol. Med. Sci. 2017, 37, 286–292. [Google Scholar] [CrossRef] [PubMed]
  57. Shakya, K.L.; Shrestha, N.; Kisiju, P.; Onta, S.R. Association of maternal factors with low birth weight in selected hospitals of nepal. J. Nepal Health Res. Counc. 2015, 13, 121–125. [Google Scholar] [PubMed]
  58. Mohamed Shaker El-Sayed Azzaz, A.; Martinez-Maestre, M.A.; Torrejon-Cardoso, R. Antenatal care visits during pregnancy and their effect on maternal and fetal outcomes in pre-eclamptic patients. J. Obstet. Gynaecol. Res. 2016, 42, 1102–1110. [Google Scholar] [CrossRef] [PubMed]
  59. White, D.E.; Fraser-Lee, N.J.; Tough, S.; Newburn-Cook, C.V. The content of prenatal care and its relationship to preterm birth in alberta, canada. Health Care Women Int. 2006, 27, 777–792. [Google Scholar] [CrossRef] [PubMed]
  60. Cogswell, M.E.; Parvanta, I.; Ickes, L.; Yip, R.; Brittenham, G.M. Iron supplementation during pregnancy, anemia, and birth weight: A randomized controlled trial. Am. J. Clin. Nutr. 2003, 78, 773–781. [Google Scholar] [CrossRef] [PubMed]
  61. Urassa, D.P.; Nystrom, L.; Carlsted, A. Effectiveness of routine antihelminthic treatment on anaemia in pregnancy in rufiji district, tanzania: A cluster randomised controlled trial. East Afr. J. Public Health 2011, 8, 176–184. [Google Scholar] [PubMed]
  62. Lechtig, A.; Habicht, J.P.; Delgado, H.; Klein, R.E.; Yarbrough, C.; Martorell, R. Effect of food supplementation during pregnancy on birthweight. Pediatrics 1975, 56, 508–520. [Google Scholar] [CrossRef] [PubMed]
  63. Lima, M.; Ismail, S.; Ashworth, A.; Morris, S.S. Influence of heavy agricultural work during pregnancy on birthweight in northeast brazil. Int. J. Epidemiol. 1999, 28, 469–474. [Google Scholar] [CrossRef] [PubMed]
  64. Defo, B.K.; Partin, M. Determinants of low birthweight: A comparative study. J. Biosoc. Sci. 1993, 25, 87–100. [Google Scholar] [CrossRef] [PubMed]
  65. Grimmer, I.; Buhrer, C.; Dudenhausen, J.W.; Stroux, A.; Reiher, H.; Halle, H.; Obladen, M. Preconceptional factors associated with very low birthweight delivery in east and west berlin: A case control study. BMC Public Health 2002, 2, 10. [Google Scholar] [CrossRef] [Green Version]
  66. Koirala, A.K.; Bhatta, D.N. Low-birth-weight babies among hospital deliveries in nepal: A hospital-based study. Int. J. Womens Health 2015, 7, 581–585. [Google Scholar] [CrossRef] [PubMed]
Figure 1. Flow chart showing the process of sample selection.
Figure 1. Flow chart showing the process of sample selection.
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Figure 2. Status of birth weights among newborns.
Figure 2. Status of birth weights among newborns.
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Table 1. Association between maternal factors and low birth weight (LBW) *.
Table 1. Association between maternal factors and low birth weight (LBW) *.
Variablesn = 402 (%)Low Birth Weightp-Value
Yes, n = 78 (%)No, n = 324 (%)
Age
<20 year91 (22.6)20 (25.6)71 (21.9)0.674
20-34 year278 (69.2)53 (67.9)225 (69.5)
≥35 years33 (8.2)5 (6.4)28 (8.6)
Caste/ethnicity
Upper caste group246 (61.2)27 (34.6)219 (67.6)<0.0001
Adibasi/Janajati89 (22.1)19 (24.4)70 (21.6)
Dalit67 (16.7)32 (41.0)35 (10.8)
Educational status
Illiterate100 (24.8)46 (59.0)54 (16.7)<0.0001
Primary145 (36.1)21 (26.9)124 (38.3)
Secondary and above157 (39.1)11 (14.1)146 (45.0)
Occupation
Labor75 (18.7)36 (46.2)39 (12.0)<0.0001
Agricultural work127 (31.6)24 (30.8)103 (31.8)
Service/business/HH works200 (49.8)18 (23.0)182 (56.2)
Family income
1st tercile138 (34.3)39 (50.0)99 (30.5)<0.0001
2nd tercile128 (31.8)26 (33.3)102 (31.5)
3rd tercile136 (33.8)13 (16.7)123 (38.0)
Head of family
Herself90 (22.4)10 (12.8)80 (24.7)0.024
Others (In-laws/ Husband)312 (77.6)68 (87.2)244 (75.3)
Resided in MATRI-SUMAN intervention area
Yes207 (51.5)31 (39.7)176 (54.3)0.021
No195 (48.5)47 (60.3)148 (45.7)
Origin of residence
Terai288 (71.6)51 (65.4)237 (73.1)0.172
Hill114 (28.4)27 (34.6)87 (26.9)
Dietary habit
Non-vegetarian320 (79.6)63 (80.8)257 (79.3)0.776
Vegetarian82 (20.4)15 (19.2)67 (20.7)
Parity
Primi157 (39.1)22 (28.2)135 (41.7)0.029
Multi245 (60.9)56 (71.8)189 (58.3)
Sex of Child
Male191 (47.5)28 (35.9)163 (50.3)0.022
Female211 (52.5)50 (64.1)161 (49.7)
Family size
4 and less person212 (52.7)12 (15.4)200 (61.7)<0.0001
>4 persons190 (47.3)66 (84.6)124 (38.3)
Living room in family
Insufficient176 (43.8)57 (73.1)119 (36.7)<0.0001
Sufficient226 (56.2)21 (26.9)205 (63.3)
Domestic animals
Yes159 (39.6)25 (32.1)134 (41.4)0.131
No243 (60.4)53 (67.9)190 (58.6)
Kitchen garden
Yes267 (66.4)19 (24.4)248 (76.5)<0.0001
No135 (33.6)59 (75.6)76 (23.5)
* Chi-square test was applied and p-values < 0.05 were considered statistically significant.
Table 2. Association between the utilization of selected antenatal care services and low birth weight (LBW) *.
Table 2. Association between the utilization of selected antenatal care services and low birth weight (LBW) *.
Variablesn = 402 (%)Low Birth Weightp-Value
Yes, n = 78 (%)No, n = 324 (%)
ANC visit-end
No35 (8.7)14 (17.9)21 (6.5)0.002
<4ANC127 (31.6)29 (37.2)98 (30.2)
4 or More240 (59.7)35 (44.9)205 (63.3)
Consumption of recommended dose of Iron and folic acid (IFA)
Yes235 (58.5)34 (43.6)201 (62.0)0.003
No167 (41.5)44 (56.4)123 (38.0)
Immunized with recommended dose of Tetanus and diphtheria (TD)
Yes328 (81.6)48 (61.6)280 (86.4)<0.0001
No74 (18.4)30 (38.4)44 (13.6)
Consumed de-worming tablet
Yes327 (81.3)47 (60.3)280 (86.4)<0.0001
No75 (18.7)31 (39.7)44 (13.6)
Adequate rest and sleep taken
SYes339 (84.3)59 (75.6)280 (86.4)0.019
No63 (15.7)19 (24.4)44 (13.6)
Additional food intake
Yes99 (24.6)47 (60.3)52 (16.0)<0.0001
No303 (75.4)31 (39.7)272 (84.0)
* Chi-square test was applied and p-values of <0.05 were considered statistically significant.
Table 3. Relations between low birth weight (LBW) and maternal factors and the utilization of antenatal care services during pregnancy, by logistic regression analysis *.
Table 3. Relations between low birth weight (LBW) and maternal factors and the utilization of antenatal care services during pregnancy, by logistic regression analysis *.
Variables OR (95% CI)p-ValueaOR (95% CI)p-Value
Maternal factors
Intervention area
Yes0.55 (0.34–1.0)0.0220.37 (0.16–0.83)0.009
No1.0 (ref.) 1.0 (ref.)
Caste/ethnicity
Dalit7.4 (3.9–13.8)0.00014.2 (1.7–10.4)0.0001
Adibasi/Janajati2.2 (1.1–4.2)0.00011.8 (0.8–5.1)0.216
Upper caste group1.0 (ref.)-1.0 (ref.)-
Educational status
Illiterate11.3 (5.4–23.4)0.00018.1 (2.9–22.4)0.0001
Primary2.2 (1.0–4.8)0.00011.6 (0.9–8.6)0.217
Secondary and above1.0 (ref.)-1.0 (ref.)-
Occupation
Labor9.3 (4.8–18.1)0.0015.9 (1.6–21.1)0.006
Agricultural work2.3 (1.2–4.5)0.0111.7 (0.5–5.3)0.332
Service/ business/ HH works1.0 (ref.)-1.0 (ref.)-
Family income
1st tercile3.7 (1.8–7.3)0.00011.1 (0.5–2.9)0.761
2nd tercile2.4 (1.1–4.9)0.0161.4 (0.3–1.9)0.618
3rd tercile1.0 (ref.)-1.0 (ref.)-
Head of family
Others (In-laws/ Husband)2.2 (1.0–4.5)0.0271.9 (0.6–5.5)0.206
Herself1.0 (ref.)-1.0 (ref.)-
Parity
Multi1.8 (1.0–3.1)0.0301.1 (0.5–2.4)0.758
Primi1.0 (ref.)-1.0 (ref.)-
Sex of child
Female 1.8 (1.0–3.0)0.0232.0 (1.0–4.1)0.047
Male1.0 (ref.)-1.0 (ref.)-
Family size
>4 persons8.8 (4.6–17.0)<0.00015.6 (2.3–13.5)<0.0001
4 and less person1.0 (ref.)-1.0 (ref.)-
Living room in family
Insufficient5.0 (2.9–8.8)<0.00011.2 (0.4–3.5)0.664
Sufficient1.0 (ref.)-1.0 (ref.)-
Kitchen garden
Yes0.09 (0.05–0.17)<0.00010.15 (0.06–0.37)<0.0001
No1.0 (ref.)-1.0 (ref.)-
Utilization of antenatal care services during pregnancy
ANC visit
No3.9 (1.8–8.3)<0.00015.1 (1.1–22.6)0.029
<4ANC1.7 (1.0–3.0)<0.00103.4 (1.1–10.2)0.027
4 and more ANC1.0 (ref.)-1.0 (ref.)-
Consumption of recommended dose of Iron and folic acid (IFA)
No2.1 (1.2–3.4)0.0033.0 (1.1–8.2)0.025
Yes1.0 (ref.)-1.0 (ref.)-
Immunized with recommended dose of Tetanus and diphtheria (TD)
No3.9 (2.2–6.9)0.00012.2 (0.5–10.0)0.295
Yes1.0 (ref.)-1.0 (ref.)-
Consumed de-worming tablet
No4.1 (2.4–7.3)0.00013.1 (1.0–13.8)0.049
Yes1.0 (ref.)-1.0 (ref.)-
Adequate rest and sleep taken
No2.0 (1.1–3.7)0.0201.5 (0.5–4.8)0.412
Yes1.0 (ref.)-1.0 (ref.)-
Additional food intake
No7.9 (4.6–13.6)0.00013.6 (1.3–9.4)0.008
Yes1.0 (ref.)-1.0 (ref.)-
* All variables having p-value ≤ 0.1 were entered in a final multivariate logistic regression model and the statistical significance was considered for p-value < 0.05. Ref.: reference.

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Acharya, D.; Singh, J.K.; Kadel, R.; Yoo, S.-J.; Park, J.-H.; Lee, K. Maternal Factors and Utilization of the Antenatal Care Services during Pregnancy Associated with Low Birth Weight in Rural Nepal: Analyses of the Antenatal Care and Birth Weight Records of the MATRI-SUMAN Trial. Int. J. Environ. Res. Public Health 2018, 15, 2450. https://doi.org/10.3390/ijerph15112450

AMA Style

Acharya D, Singh JK, Kadel R, Yoo S-J, Park J-H, Lee K. Maternal Factors and Utilization of the Antenatal Care Services during Pregnancy Associated with Low Birth Weight in Rural Nepal: Analyses of the Antenatal Care and Birth Weight Records of the MATRI-SUMAN Trial. International Journal of Environmental Research and Public Health. 2018; 15(11):2450. https://doi.org/10.3390/ijerph15112450

Chicago/Turabian Style

Acharya, Dilaram, Jitendra Kumar Singh, Rajendra Kadel, Seok-Ju Yoo, Ji-Hyuk Park, and Kwan Lee. 2018. "Maternal Factors and Utilization of the Antenatal Care Services during Pregnancy Associated with Low Birth Weight in Rural Nepal: Analyses of the Antenatal Care and Birth Weight Records of the MATRI-SUMAN Trial" International Journal of Environmental Research and Public Health 15, no. 11: 2450. https://doi.org/10.3390/ijerph15112450

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