Assessing the impact of antenatal care utilization on low birthweight in India: Analysis of the 2015–2016 National Family Health Survey

Children and Youth Services Review 106 (2019) 104459

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Assessing the impact of antenatal care utilization on low birthweight in India: Analysis of the 2015–2016 National Family Health Survey

T

Pintu Paula, , Ankita Zaverib, Pradip Chouhanb ⁎

a b

Centre for the Study of Regional Development, School of Social Sciences, Jawaharlal Nehru University (JNU), New Delhi 110067, India Department of Geography, University of Gour Banga (UGB), Malda 732103, India

ARTICLE INFO

ABSTRACT

Keywords: Antenatal care (ANC) Low birthweight (LBW) Women Children India

Low birthweight (LBW) is a serious public health problem in lower-middle income countries. Despite several efforts have been made to improve the utilization of maternal health care, universalization of antenatal care (ANC) remains a major challenge in India. This paper aims to examine the association between the use of ANC services and LBW in India. A cross-sectional observational study was carried out using the data from the 2015 to 2016 National Family Health Survey (n = 147,762). We have carried out bivariate and multivariate analyses to fulfil the objective of this study. About 18% of the sample children were born with LBW. Only ¼th last birth women received full ANC services in 2015–2016. The results of binary logistic regression indicate that the likelihood of LBW was significantly lower among those children whose mother have adequate ANC services compared to those mother who did not receive those services even after accounting for important socioeconomic and demographic factors. The findings of this study suggest that providing affordable and quality ANC services could be an effective strategy to reduce the incidence of LBW. Furthermore, targeted invention is needed among socioeconomically vulnerable women to improve the utilization of ANC services, which could combat the incidence of LBW.

1. Introduction Antenatal care (ANC) remains a safe motherhood intervention and essential for basic primary health care during pregnancy. In 2016, World Health Organization (WHO)’s recommendations on ANC increases from minimum four visits to eight ANC contacts during pregnancy to improve pregnancy and perinatal outcomes (WHO, 2016). The utilization of ANC services are associated with maternal and neonatal mortality (Campbell & Graham, 2006; Carroli, Rooney, & Villar, 2001; Chen, Wen, Yang, & Walker, 2007). The ANC service provider works on several aspects of maternity care during pregnancy such as nutritional intervention, maternal and fetal assessment, provides preventive measures to control bacteria and diseases, and advices on common physiological problems for positive pregnancy experience (WHO, 2016). Low birthweight (LBW) is an important public health issue in lowermiddle income countries, associated with a range of both short-term and long-term consequences affecting human capital. It increases the risk of early childhood morbidity and mortality (Lawn, Cousens, & Zupan, 2005; Titaley, Dibley, Agho, Roberts, & Hall, 2008). Globally, an estimated around 2.5 million newborns are died in their first month of life in 2017 (UNIGME, 2018). LBW is associated with inhabited growth

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and cognitive development and chronic morbidities in later part of life (Risnes et al., 2011; UNICEF & WHO, 2004). LBW is defined by WHO as weight at birth below 2500 g (5.5 lb) regardless of gestational age. LBW is further categorized into very low birthweight (< 1500 g) and extremely low birthweight (< 1000 g) (UNICEF & WHO, 2004). It generally occurs either from prematurity (< 37 weeks of gestation) or restricted intra-uterine growth or combinations of both (UNICEF & WHO, 2004). Globally, an estimated 20.5 million newborns were born with LBW in 2015 (UNICEF & WHO, 2019). Southern Asia accounted for nearly half of all LBW babies in the world (UNICEF & WHO, 2019). In India, although the incidence of LBW has declined from 28% to 18% between 2005–06 and 2015–16 (International Institute for Population Sciences [IIPS] & ICF, 2017), it remains a major risk factor of neonatal and perinatal mortality (Rai et al., 2017). The incidence of LBW has determined by several socioeconomic, demographic, and environmental factors (Carlson, 1984; Kramer, 1987; Mahumud, Sultana, & Sarker, 2017; Neggers, Goldenberg, Cliver, & Hauth, 2004; Noureddine & Abdellatif, 2015). Mother requires adequate care during pregnancy for well-growth and development of fetus. Moreover, regular examination of mother's health situation and monitoring fetal growth and neonatal size evaluation can reduce the risk of

Corresponding author at: Centre for the Study of Regional Development, School of Social Sciences, Jawaharlal Nehru University, New Delhi 110067, India. E-mail address: [email protected] (P. Paul).

https://doi.org/10.1016/j.childyouth.2019.104459 Received 21 February 2019; Received in revised form 6 August 2019; Accepted 6 August 2019 Available online 08 August 2019 0190-7409/ © 2019 Elsevier Ltd. All rights reserved.

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LBW (WHO, 2014). Evidence from prior studies has indicated that mother's adequate dietary intake and calorie consumption during pregnancy significantly reduces the incidence of LBW (Abu-Saad & Fraser, 2010; Dharmalingam, Navaneetham, & Krishnakumar, 2010; Imdad & Bhutta, 2012). The government of India has implemented several policies and programmes to combat the incidence of adverse reproductive and birth outcomes and mortality. The National Rural Health Mission (NRHM), 2005 is envisaged to provide free and quality ANC health care. Accredited Social Health Activist (ASHA) is one of the key components of NRHM to improve the coverage of ANC services. ASHA worker mobilizes the community and facilitate them for ANC check-up in the anganwadi centre, sub-centre, and primary health centre. ANC services are also provided by Anganwadi Worker (AWW) and Auxiliary Nurse Midwives (ANM) at the village level (Kapil & Choudhury, 2005; Nagarajan et al. 2015). Although considerable progress has been made in the coverage of ANC services over the last 20 years in India, it remains inaccessible to the socioeconomically backward women (Kumar & Singh, 2017). Therefore, the occurrence of pregnancy-and childbirth-related mortality and adverse birth outcomes remains very high especially among impoverished group of women. Limited access to healthcare, lack of knowledge on ANC, early age at marriage, and high poverty are the leading factors contributed to the lower utilization of ANC services (Assefa, Berhane, & Worku, 2012; Asundep et al., 2013; Efendi, Chen, Kurniati, & Berliana, 2016; Pallikadavath, Foss, & Stones, 2004; Paul & Chouhan, 2019; Rai, Singh, & Singh, 2012; Simkhada, Teijlingen, Porter, & Simkhada, Van Teijlingen, Porter, & Simkhada, 2007; Singh, Rai, & Singh, 2012). The existing literature mainly focused on various socioeconomic, demographic and obstetric determinants of LBW. Despite several efforts has been made to improve the utilization of maternal health care, universalization of ANC services remains a major challenge in India. Recent estimates of National Family Health Survey (NFHS-4) showed that a considerable proportion of women did not seek adequate ANC services which may have significant negative impacts on pregnancy and birth outcomes. Moreover, little attention has been paid regarding the use of ANC services in determining birth outcomes. With this backdrop, this study aimed to assess the association between the utilization of ANC services and the incidence of children's LBW using recent database of nationally representative sample in India.

Fig. 1. Flow chart for study participants, NFHS, 2015–2016.

for this current study is available in public domain and could be assessed upon a request from the data repository of Demographic and Health Survey (DHS) through online (https://dhsprogram.com/data/). Therefore, ethical approval is not required for conducting this study. 2.2. Study participants The 2015–2016 NFHS interviewed 259,627 children born to women aged 15–49 years in the past five years preceding the survey. However, the current study was limited to most recent births in the past five years preceding the survey born to ever-married women aged 15–49 years (n = 190,898) because only last birth women in the past five years were asked about their health seeking behaviour to avoid recall bias. Of 190,898 most recent births, 37,306 were not weighted at birth and 5830 cases were refused to answer or missing. Therefore, the final analytical sample was restricted to 147,762 most recent births in the last five years preceding the survey (Fig. 1).

2. Materials and methods 2.1. Data source We used data from the fourth round of the National Family Health Survey (NFHS), conducted during 2015–2016. It is a nationally representative cross-sectional sample survey of 601,509 households, 699,686 women aged 15–49 years with a response rate of 97%, and 112,122 men aged 15–54 years with a response rate of 92%. The 2015–2016 NFHS was carried out under the aegis of the Ministry of Health and Family Welfare (MoHFW), Govt. of India and International Institute for Population Sciences (IIPS), Mumbai. The sample was selected using a stratified two-stage sampling design comprising of 28,586 clusters; 8397 in urban, 20,059 in rural, and 130 from slums list provided by Municipal Corporation Offices (MCOs). In the first stage, clusters were selected using probability-proportional-to-size sampling. In the second stage, 22 households from each cluster were selected with an equal opportunity systematic selection from the household listing. Detailed description of sampling design and survey procedure is provided in the national report of NFHS-4, 2015–2016 (IIPS & ICF, 2017). The main purpose of this survey was to provide important and reliable data on fertility and family planning, utilization of maternal and child health care services, infant and child mortality, nutrition, women empowerment, domestic violence and knowledge on HIV/AIDS. The data

2.3. Outcome variable LBW is the dependent variable in this study. Birthweight of children variable was dichotomized as birth weight < 2500 g (assigned as ‘1’) and ≥ 2500 g (coded as ‘0’). The data on birthweight of children were collected either from written record or mother's recall. 2.4. Explanatory variables Utilization of maternal health care services has 3 components: (1) ANC (care during pregnancy), (2) Delivery care (care during childbirth), and (3) Postnatal care (care after childbirth). For the purpose of the study, we have considered the utilization of ANC services as the key explanatory factor. Mother's use of ANC services was assessed from the following indicators: (1) 4 or more ANC visits, (2) ANC visit within first 2

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trimester of pregnancy (first 3 months), (3) ANC from a skilled provider (doctor, auxiliary nurse midwife, nurse, midwife, and other lady health visitor), and (4) Full ANC (at least 4 ANC visits, at least one tetanus toxoid injection, and iron folic acid tablets or syrup taken for 100 or more days). Child and maternal demographics and socioeconomic characteristics were included as control variables for the analysis of the study. Child demographics include age of child, sex of child, and birth order. Age of child is categorized into 5 groups: 0–11 months, 12–23 months, 24–35 months, 36–47 months, and 48–59 months. The youngest category (0–11 months) is adopted as the reference category to compare age differentials in LBW. Similarly, sex of the child (male and female) is included to assess the gender differentials in LBW. Birth order of child is divided into 3 groups: 1st order, 2nd order, and 3rd order or more. Maternal demographics include age of the mother (15–24 years, 25–34 years, and 35–49 years), maternal age at marriage (< 18 years [legally defined as child marriage] and ≥ 18 years [adult marriage]), maternal education (no education, primary, secondary, and higher), and maternal body mass index [BMI] (thin, normal, and obese). BMI is a simple index of weight for height, which measures nutritional status among adults. We have used WHO cut-off points to classify the maternal BMI. These cut-off points are < 18.5 kg/m2 (thin), 18.5 to 24.9 kg/m2 (normal), and ≥ 25.0 kg/m2 (obese). Socioeconomic characteristics include place of residence, social groups, religion, region, and household wealth. Place of residence is included to examine the rural-urban difference in the occurrence of LBW. Social groups can also made significant differences in the incidence of LBW. Social groups has been categorized into Scheduled Caste [SC]/Scheduled Tribe [ST], Other Backward Classes [OBC], and other. Similarly, religious affiliation is included as an explanatory variable to examine the religious differences in LBW occurrence. Religion is categorized into three groups: Hindu, Muslim, and other. Furthermore, regional differences in the incidence of LBW may also be found, and, therefore, Indian states and union territories are grouped into six regions based on geographical locations and cultural setting. These regions are north, central, east, northeast, west, and south. Household wealth quintile has been measured from the ownership of household assets including consumer items and dwelling characteristics. A score was generated for each individuals using principal component analysis and categorized into five quintiles, each represents 20% of the respondents, between 1 (poorest) and 5 (richest).

Table 1 Socioeconomic and demographic characteristics of sample, NFHS, 2015–2016 (n = 147,762). Characteristics Age of child in months 0–11 12–23 24–35 36–47 48–59 Sex of Child Male Female Birth order 1 2 ≥3 Age of mother in years 15–24 25–34 35–49 Maternal age at marriage < 18 years ≥18 years Don't know/missing Maternal education No education Primary Secondary Higher Maternal BMI Thin Normal Obese Don't know/missing Place of residence Urban Rural Social groups SC/ST OBC Other Don't know/missing Religion Hindu Muslim Other Region North Central East Northeast West South Wealth quintiles Poorest Poorer Middle Richer Richest Total

2.5. Statistical analyses First, descriptive analyses were carried out to provide information on the distribution of socioeconomic and demographic characteristics as well as distribution of outcome and explanatory variables. Then, bivariate percentage distribution was estimated to assess the differences in the utilization of ANC services and socio-demographic characteristics by LBW. Finally, binary logistic regression models were run to examine the association between ANC utilization and LBW. We have carried out Pearson's chi-square test between outcome variable and explanatory variables prior perform the multivariate model and variables with significance level P < .005 were included in the final model. Sample weight was applied for estimation of percentage distribution. All statistical analyses were conducted using STATA version 12.1 (StataCorp LP, College Station, TX, USA).

Number (n)

Weighted %

39,225 37,510 29,010 23,324 18,693

26 25.4 19.6 16 13.1

80,506 67,256

54.7 45.4

53,876 51,297 42,589

37.3 36.5 26.2

50,479 83,511 13,772

36.4 55.9 7.7

49,449 95,868 2445

35.7 62.9 1.4

32,581 19,485 76,610 19,086

20.8 12.8 52.2 14.2

32,148 89,442 24,274 1898

22.3 58.4 17.4 1.9

41,909 1,05,853

33.2 66.8

53,697 58,309 28,879 6877

30.5 43 21.8 4.7

1,10,994 19,979 16,789

80.2 14.4 5.4

29,149 36,336 29,529 20,398 13,011 19,339

13.7 20.9 23.7 3.7 15.5 22.6

27,844 31,579 31,619 29,594 27,126 1,47,762

17.5 20.2 21.2 21.5 19.6 100

18 years of age. Only 14% of the women were completed higher level of education. More than one-fifth sample women (22%) were undernourished (BMI < 18.5 kg/m2). Majority of the women/children were living in rural areas (67%), belonged to Other Backward Classes (43%), and affiliated to Hindu religion (80%). About one in four women/ children (24%) were from east region, followed by south (23%), and central region (21%). Moreover, a substantial proportion of them were belonged to poorest (23%) and poorer (21%) quintile of household wealth. Table 2 presents percentage distribution of ANC services and children's LBW. More than half the sample women (59%) were received four or more ANC visits. Similarly, 64% of the women reported that

3. Results Table 1 depicts socioeconomic and demographic characteristics of the respondents. More than one in four sample children (26%) were infants. More than half of the children (55%) were male. More than one-fourth of the children (26%) were born in birth order of 3 or more. More than one-third of the women (36%) were young aged 15–24 years. A considerable proportion of women (36%) were married before 3

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Table 2 Percentage distribution of ANC utilization and LBW for sample children, NFHS, 2015–2016 (n = 147,762). Variables Number of ANC visits < 4 visits ≥4 visits Don't know/missing ANC visit within first trimester No Yes Don't know/missing ANC by skilled provider No Yes Full ANC No Yes Birthweight of children < 2500 g ≥2500 g Total

Number (n)

Weighted %

64,950 81,292 1520

40.2 58.9 0.9

52,544 94,864 354

35.5 64.4 0.2

22,510 1,25,252

14.5 85.5

1,14,546 33,216

74.9 25.1

25,030 1,22,732 1,47,762

17.5 82.5 100

Table 3 Percentage distribution of explanatory variables by outcome variable for sample children, NFHS, 2016–2016 (n = 147,762). Explanatory variables

Utilization of ANC services Number of ANC visits < 4 visits ≥4 visits Don't know/missing ANC visit within first trimester No Yes Don't know/missing ANC by skilled worker No Yes Full ANC No Yes Control variables Child age in months 0–11 12–23 24–35 36–47 48–59 Sex of child Male Female Birth order 1 2 ≥3 Age of mother in years 15–24 25–34 35–49 Maternal age at marriage < 18 years ≥18 years Don't know/missing Maternal education No education Primary Secondary Higher Maternal BMI Thin Normal Obese Don't know/missing Place of residence Urban Rural Social groups SC/ST OBC Other Don't know/missing Religion Hindu Muslim Other Region North Central East Northeast West South Wealth quintiles Poorest Poorer Middle Richer

they had ANC visit within first trimester of pregnancy. Majority of them (86%) were received ANC by a skilled health provider; and one in four women (25%) had full ANC. About 18% of sample children were reported as LBW. Prevalence of LBW by the use of ANC services and socioeconomic and demographic characteristics of sample are presented in Table 3. The prevalence of LBW (< 2500 g) was lower among those women who had four or more ANC visits (17%) compared with those who had < 4 ANC visits (19%) (P < .001). Similarly, LBW of births was significantly lower among those women who had ANC visit within first trimester of pregnancy (17%) compared with those who did not receive within first trimester (19%) (P < .001). A lower proportion of women had LBW who received ANC by a skilled provider (17%) than those who did not receive ANC by skilled provider (20%) (P < .001). Similarly, a significantly lower percentage of women had LBW who had full ANC (15%) compared with those who did not had full ANC (19%) (P < .001). Significant differences in LBW were also found by socioeconomic and demographic characteristics of children and women (P < .005). A higher percentage of children with LBW were infants. LBW was significantly higher among the female child (19%) compared to male child (16%). A higher percentage of mothers had LBW child who were < 25 years compared to 35 years or older. A significantly higher percentage of women who were married before 18 years of age had LBW for their recent birth (19%) compared to those women who married at 18 years or older (17%). Similarly, a higher proportion of women who had no education (20%), thin body mass (21%), live in rural areas (18%), belonged to SC/ST social groups (19%), believed in Hindu religion (18%), from north (20%) and central region (20%), and who were from poorest (20%) and poorer (18%) household had LBW for their recent birth born in the last five year preceding the survey compared to other groups. Table 4 presents binary logistic regression models for the association between the utilization of ANC services and LBW. In the first model, we assessed crude association between ANC utilization and children's LBW. Crude association revealed that the odds of LBW were significantly lower among those births whose mother received adequate ANC care during pregnancy. However, after inclusion of relevant sociodemographic variables in the final model slightly reduced the odds of ANC services. The results revealed that the likelihood of LBW was significantly lower among those children whose mother had four or more ANC visits (AOR: 0.92, 95% CI: 0.89–0.95) ANC visit within first trimester of pregnancy (AOR: 0.92, 95% CI: 0.89–0.95), ANC by a skilled provider (AOR: 0.86, 95% CI: 0.83–0.90), and who had full ANC (AOR: 0.82, 95% CI: 0.79–0.86) compared to those mother who did not

Total sample (n)

Birthweight (%)

64,950 81,292 1520

18.8 16.6 19.4

81.2 83.4 80.6

52,544 94,864 354

18.8 16.8 26.3

81.2 83.2 73.7

22,510 1,25,252

19.7 17.1

80.3 82.9

1,14,546 33,216

18.5 14.5

81.5 85.5

39,225 37,510 29,010 23,324 18,693

18.2 17.9 17.8 16.5 16.1

81.8 82.1 82.2 83.5 83.9

80,506 67,256

16.4 18.9

83.6 81.1

53,876 51,297 42,589

18.2 16.6 17.7

81.8 83.4 82.3

50,479 83,511 13,772

19 16.5 17.3

81 83.5 82.7

49,449 95,868 2445

18.6 16.9 18.8

81.4 83.1 81.3

32,581 19,485 76,610 19,086

19.6 19.7 17.3 13.3

80.5 80.3 82.7 86.7

32,148 89,442 24,274 1898

21.3 16.9 14.6 18.6

78.7 83.2 85.4 81.4

41,909 1,05,853

16.7 17.9

83.3 82.1

53,697 58,309 28,879 6877

18.8 17.1 16.2 18.6

81.2 82.9 83.8 81.4

1,10,994 19,979 16,789

17.8 16.6 15.8

82.2 83.4 84.2

29,149 36,336 29,529 20,398 13,011 19,339

20 19.5 15.7 13.9 18.5 16

80.1 80.5 84.3 86.1 81.6 84

27,844 31,579 31,619 29,594

19.6 18.4 17.8 17.7

80.4 81.6 82.2 82.3

P-value

< 2500 g ≥2500 g 0.000

0.000

0.000 0.000

0.000

0.000 0.000

0.000

0.000

0.000

0.000

0.001 0.001

0.000

0.000

0.000

(continued on next page) 4

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utilization on the prevalence of LBW, several socioeconomic and demographic factors significantly contributed to the incidence of LBW. A number of studies have documented that maternal education and economic status of household are the strong predictors of LBW (Assefa et al., 2012; Mahumud et al., 2017; Silvestrin et al., 2013; UNICEF & WHO, 2004). Besides, poor nutritional status of mother (Abu-Saad & Fraser, 2010; Dharmalingam et al., 2010; Imdad & Bhutta, 2012), obstetric complications (Kramer, 1987), teenage pregnancy (Fall et al., 2015) and several other socio-demographic factors significantly influence LBW. Moreover, women who have limited autonomy in their household are less likely to use ANC services (Bloom, Wypij, & Das Gupta, 2001; Mistry, Galal, & Lu, 2009). Therefore, the risk of LBW babies is significantly higher among those women who have lower decision making power in their household. The findings of our current study suggest that effective intervention to improve the use of ANC services, creating awareness regarding adverse impacts of not receiving ANC services during pregnancy, and reducing socioeconomic vulnerability could be effective strategies to reduce the incidence of LBW. Under the scheme of NRHM and Integrated Child Development Scheme (ICDS) pregnant mothers are provided nutritional supplementation and treatment to maintain good health condition for their own as well as for well-growth and development of fetus (Silvestrin et al., 2013). Yet, a considerable proportion of young married women especially rural and poor communities do not have access to ANC services, may be due to lack of information, limited autonomy, social norms which does not allow women to visit health centre–coupled with poverty and social backwardness (Balarajan, Selvaraj, & Subramanian, 2011; Baru, Acharya, Acharya, Kumar, & Nagraj, 2010; Mistry et al., 2009; Navaneetham & Dharmalingam, 2002; Peters et al., 2008). India has a long way to meet the target of Sustainable Development Goals (SDGs) on Reproductive & Child Health (RCH), which requires accelerated improvement in reproductive health care to combat the incidence of LBW and other adverse pregnancy and birth outcomes (United Nations, 2018). Therefore, there is a need for effective policy intervention on maternal health care especially among the impoverished women to reduce the complications during pregnancy, poor nutrition and adverse birth outcomes including LBW, which in turn, could also reduce neonatal and perinatal mortality. The findings of this study should be discussed with some caution. Recall bias is the most serious problem while collecting data on birthweight because half of information on birthweight was collected from mother's recall. Furthermore, there is large number of missing cases in birthweight data. We could not assess the cause-effect relationship between ANC utilization and LBW because of cross-sectional nature of data. Moreover, maternal BMI was measured at the time of interview and ANC usage is based on recall/history of a past pregnancy. Therefore, the current BMI of woman may not have been the preconception BMI. Prospective study is needed to understand the impact of BMI on the use of ANC services. There are several other pregnancy related factors which could have significant influence on LBW. We could not include those factors in the analysis because of limitations of data.

Table 3 (continued) Explanatory variables

Richest Total

Total sample (n)

Birthweight (%)

27,126 1,47,762

14.1 17.5

P-value

< 2500 g ≥2500 g 85.9 82.5

Note: P-value is derived from Pearson's chi-square tests.

Table 4 Crude and adjusted odds ratios from binary logistic regression models assessing the association between ANC utilization and LBW (< 2500 g), NFHS, 2015–2016. Variables

Four or more ANC visits Noa Yes ANC visit within first trimester of pregnancy Noa Yes ANC by skilled provider Noa Yes Full ANC Noa Yes

Model I

Model II

Crude OR

95% CI

Adjusted OR

95% CI

1.00 0.85

0.82–0.87

1.00 0.92

0.89–0.95

1.00 0.88

0.85–0.90

1.00 0.92

0.89–0.95

1.00 0.81

0.78–0.84

1.00 0.86

0.83–0.90

1.00 0.75

0.72–0.78

1.00 0.82

0.79–0.86

OR = Odds Ratio; CI = Confidence Interval. All odds are significant at p < .01. Adjusted models were controlled for age of child, sex of child, birth order, age of mother, maternal age at marriage, maternal education, maternal BMI, place of residence, social groups, religion, region, and wealth status of household. a Reference category.

received those services after controlling for age, sex, birth order, maternal age, maternal age at first marriage, maternal education, maternal BMI, place of residence, social groups, religion, region, and wealth status of household which suggests importance of ANC utilization in reducing LBW. 4. Discussion The present study has examined the association between mother's use of ANC services and LBW of most recent birth in the past five years preceding survey using latest round of NFHS data. In India, about one in six last birth under-five children (18%) are born with LBW in 2015–2016. We have selected four measures of ANC services: four or more ANC visits, ANC visit within first trimester, ANC from skilled provider, and full ANC. Then, we have examined the impact of each indicator of ANC services on the likelihood of LBW by bivariate and multivariate analyses. This study has found that the use of ANC services is significantly associated with lower likelihood of children's LBW even after controlling for relevant demographic and socioeconomic characteristics. The findings of this study are similar to the findings of several other studies conducted in lower-middle income countries (Assefa et al., 2012; Mahumud et al., 2017; Mbuagbaw & Gofin, 2011). Evidence has found that adequate use of maternity care during pregnancy contributes wellgrowth and development of fetus (UNICEF & WHO, 2004; WHO, 2016). Therefore, the chances of LBW among those babies become lower if their mother received adequate ANC services during pregnancy. Although the main purpose of our study is to determine the impact of ANC

5. Conclusion The findings of this study highlighted the importance of ANC services during pregnancy which has a significant impact on the incidence of LBW. The results of our study suggest that providing affordable and quality ANC services among pregnant mother could be an effective path towards combat the incidence of LBW among under-five children. Furthermore, targeted intervention is needed especially among socioeconomically and demographically vulnerable women to improve the utilization of ANC services which could reduce the incidence of LBW babies among those women.

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Funding

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