Low birth weight and its associated risk factors: Health facility-based case-control study

Background Low birth weight is a preventable public health problem. It is an important determinant of child survival and development, as well as long-term consequences like the onset of non-communicable disease in the life course. A large number of mortality and morbidity can be prevented by addressing the factors associated with low birth weight. The main objective of this study was to identify associated risk factors of low birth weight. Methodology A health facility-based unmatched case-control study was carried out from July 2018 to March 2019 among the mothers who delivered in health facilities of Dang district of Nepal from 17th August to 16th November 2018. The total sample size for the study was 369; 123 cases and 246 controls. Cases and controls were randomly selected independent of the exposure status in the ratio of 1:2. Information regarding exposure status was assessed through interviews and medical records. Mothers who delivered outside Dang districts were excluded from the study. Ethical clearance was obtained from the Institutional Review Committee (IRC) of the Institute of Medicine, Tribhuvan University and written consent was taken from each participant after explaining the objectives of the study. Results Multivariate logistic regression found that having the kitchen in the same living house (AOR 2.7, CI: 1.5–4.8), iron intake less than 180 tablets (AOR 3.2, CI: 1.7–5.7), maternal weight gain during second and third trimester less than 6.53 kg (AOR 2.6, CI: 1.5–4.7), co-morbidity during pregnancy (AOR 2.4, CI: 1.3–4.5), preterm birth (AOR 2.9, CI: 1.4–6.1) were the risk factors associated with low birth weight. Conclusion Having the kitchen in the same living house, iron intake less than 180 tablets during pregnancy, maternal weight gain less than 6.53 kg during the second and third trimester, co-morbidity during pregnancy and preterm birth were the risk factors associated with low birth weight.


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World Health Organization defines low birth weight (LBW) as the birth weight less than 37 2500 grams irrespective of gestational age (1). LBW is considered as a valuable public health 38 indicator that reflects maternal health, nutrition, healthcare delivery. LBW babies are at a 39 higher risk of death and illness shortly after birth and non-communicable disease in the life 40 course (2). LBW infants are 20 times more likely to develop complications and die in 41 compare to normal weight babies (3). LBW babies are in the potential risk of cognitive 42 deficits, motor delays, cerebral palsy, and other behavior and psychological problem (4)(5)(6)(7)(8). 43 The pathophysiology of low birth weight is unclear, whereas intrauterine growth retardation 44 (IUGR) and preterm birth considered as the cause of LBW (3). LBW is considered a 45 significant public health problem as it is estimated that 15% to 20% of all birth worldwide are 46 LBW. The prevalence of LBW varies across regions with the highest 28% in South Asia and 47 the lowest 6% in East Asia and the Pacific region (9). The prevalence of LBW in Nepal 48 ranges from 12% to 21.6%, (10-12). A few descriptive and hospital based case-control 49 studies have been done in Nepal. These studies could not represent the scenarios of risk 50 factors of LBW at the community level. Hence this study aims to identify the scenario of 51 associated risk factors of LBW at the community level. 52

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A retrospective unmatched case-control study was used. This study was conducted in Dang 54 District of Nepal. The study population was mothers of children, who delivered their babies 55 in health institutions of Dang from 17 th August to 16 th November 2018. The study population 56 was divided into case and control as per the following definition. 57 4 The sample size was calculated using EpiInfo software version 7. This was calculated by 62 taking power at 80%, confident level as 95%, the percentage of control exposed as 65.40, the 63 odds ratio of 2.06 from the maternal weight against LBW (13) and the ratio of case to control 64 was 1:2. The total sample size was 369 with 123 cases and 246 controls. The eligible 65 numbers of research participants were enlisted from the maternal and neonate health register 66 of 28 birthing centers and 3 hospitals of Dang District. 123 cases were selected from 224 67 cases and 246 controls from 777 controls randomly. Data were collected by scheduled 68 interviews using semi-structured questionnaires, reviewing Antenatal Care (ANC) card and 69 Maternal and newborn register. 70 Data entry was done in Epi data Version 3.1 following coding. Data analysis was done using 71 SPSS software version 21. Bivariate associations between independent variables and low 72 birth weight were tested through the Chi-square test and the association was analyzed by 73 calculating crude odds ratios (OR) at 95% confidence interval through binary logistic 74 regression. Multivariate logistic regression was examined for the relationship between 75 independent variables and low birth weight to address the confounding effect. Hosmer and 76 Lemeshow test was used to test the goodness-of-fit for regression models. The test statistic 77 was 0.69 (p > 0.05) that showed that the model adequately fit the data. 78 Ethical clearance was obtained from the Institutional Review Committee (IRC) of the 79 Institute of Medicine, Tribhuvan University. Permission was taken from the District Public 80 Health Office (DPHO) Dang and respective health facilities. Written consent was taken from 81 each participant after explaining the objectives of the study. After the interview, the mothers 82 were informed about the importance of growth monitoring, exclusive breastfeeding, 83 immunization and appropriate time of weaning. 84

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The mean age of the participants was 23 years (SD 4.4 years). 86 research participants did not face any health problems (comorbidities) during their pregnancy 103 and 14.6% of the babies were born before 37 weeks of gestation. 104  Table 2 shows the bivariate and multivariate analysis of dependent and independent 106 variables. In bivariate analysis; support from husband during pregnancy, what type…cooking 107 material, where…location of kitchen, cigarette smoking by family members, cigarette 108 smoking by mother during pregnancy, what type….food frequency during pregnancy, use of 109 additional food groups in their diet during pregnancy, ANC visit as per protocol, how 110 much…number of iron tablet intake, how much…weight gain during pregnancy, how 111 many..number of children, health problem (comorbidities) during pregnancy and preterm 112 baby are associated with low birth weight. of baby at 95% confidence interval. 113 In multivariate analysis, where…location of the kitchen (AOR 2.7, CI: 1.5-4.8), how 114 much…number of iron intake (AOR 3.2, CI: 1.7-5.7), how much…maternal weight gain 115 during second and third trimester (AOR 2.6, CI: 1.5-4.7), health problem during pregnancy 116 (AOR 2.4, CI: 1.3-4.5) and preterm birth (AOR 2.9, CI: 1.4-6.1) were significantly 117 associated at 95% confidence interval with the low birth weight. of the baby. Similarly, age 118 of mother, support from husband during pregnancy.., what type… cooking material, the 119 smoking habit of the mother, smoking by family member, how much..food frequency per 120 day, which …type of food used, ANC visit as per protocol, how many…number of children 121 was not associated with LBW in this study.low birth weight. 122

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This study examined and analyszed the socio-demographic factors, maternal factors and co-124 morbiditiesy during recent pregnancy against low birth weight during delivery. 125 The maternal age is considered as a key factor for the healthy outcome of pregnancy. This 126 study revealed no statistical association between maternal age and low birth weight which 127 contradicts with the study done in Nepal, that shows a higher risk of delivering low birth 128 weight babies by mother age less than 20 and more than 30 years (14-16). Smoking during 129 pregnancy had a negative effect on the growth and development of the fetus because of 130 chemical substances present in it. In bivariate analysis mother's habit of smoking had a 131 higher risk of low birth weight in reference to the mother who did not smoke a cigarette (OR 132 6.3, 95% CI: 1.2-31.5). This finding is consistent with the findings of similar studies done in 133 Bangladesh and Turkey (17, 18). Though there was a risk, however, there was no significant 134 association between smoking and low birth weight in multivariate analysis. This could be 135 explained probably due to the small number of smokers in the study population. Moreover, it 136 can also be explained by the social desirability bias, induced due to social stigma. 137 This study identified the location of the kitchen in the living house, iron intake less than 180 138 tablets, weight gain less than 6.53 kg during the second and third trimester, comorbidity 139 during pregnancy, and preterm birth as the risk factors for low birth weight. The finding 140 reveals that the cooking stove fules namely firewood and kerosene use had a risk for LBW 141 with reference to LPG and Biogas however, it was not statistically significant.ly different. 142 This finding contradicts to the find of the study done by Kadam YR et al. and Washam C (19,143 20), however this study revealed that location of kitchen in the same house had 2.5 times 144 Commented [SBP23]: You need to change your reference age group for statistical analysis. I already mentioned above in your result section.
higher risk of delivering low birth weight which may be due to, living in the same house had 145 higher risk and duration of exposure to the pollution caused by burning of fuels, though the 146 amount of exposure was not measured quantitatively, leading to the negative impact on 147 growth and development of fetus. 148 This study showed that total iron tablet intake during pregnancy was associated with the birth 149 weight of the child. Mothers who took less than 180 tablets of iron during their pregnancy 150 were three times more likely to deliver low birth weight babies with reference to mothers 151 who took iron equal to or more than 180 tablets during their pregnancy period (AOR 3.2,. This finding is similar to the studies conducted in Nepal (14,21). Low iron tablets 153 intake causes the poor delivery of iron to the fetus thereby impair in proper hormonal and 154 neuronal regulation of pregnancy and poor oxygenation to the fetus leading to the poor 155 growth and development of the fetus (22). However, the iron intake through diet during 156 pregnancy was not measured in both cases and control. 157 The minimum standard weight gain during the second and third trimester is set as 6.53 kg 158 (23). Women who gained weight less than 6.53 kg during the second and third trimester had 3 159 times higher risk of delivering low birth weight baby with reference to women whose weight 160 gain was 6.53 kg or above (AOR 2.8, CI: 1.6-5.0). This finding is similar to the study done in 161 Bangladesh (24) and Mozambique (25). The weight gain during pregnancy is impaired due to 162 ill health, poor sanitation, and inadequate balance diet which at the end hamper the proper 163 growth and development of the baby. 164 Women who had at least one health problem during their pregnancy were at higher risk of 165 delivering low birth weight in comparison to women without any health problem (AOR 2.6,. This finding is consistent with the study done in Nepal (13,16). Likewise this 167 study suggest that mother delivering baby before completion of 37 weeks of gestation had 168 higher risk of delivering low birth weight than the mothers who deliver the term baby (AOR 169 2.6, CI: 1.2-5.5) which is in line with the study done in Nepal (16), Ethiopia (26) and Kenya 170 (27). Biologically it can be explained that preterm birth was less likely to get sufficient time 171 for maturity, growth and nutrient intake which therefore can lead to low birth weight. 172 In this study, the researcher has retrieved maternal information namely gestational weight, 173 iron tablets intake, gestational age, co-morbidity, frequency of ANC visits and birth weight of 174 a baby from ANC card and maternity register to limit the recall bias. The selection of cases 175 and controls were based on the records of maternal and neonatal register therefore, it is less 176 likely that this study has misclassification biases both in the exposure and case-control 177 categories. Controls were selected randomly independent of the exposure status and 178 moreover, as there was no non-responses rate in both the group, it is less likely that this study 179 would suffer from selection biases. 180

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This study concluded that the location of the kitchen in the same living house (proxy of 182 indoor air pollution), iron intake less than 180 tablets during pregnancy, weight gain less than 183 6.35 kg during the second and third trimester, co-morbidity during pregnancy, and preterm 184 delivery were found to be associated risk factors of low birth weight. Thus, identified risk 185 factors can be efficiently prevented through small doable actions that a family can apply and 186 the mother can easily carry out. Maternal health programs can be directed towards motivating 187 and tracking pregnant mothers for complete iron tablets intake during her pregnancy period. 188 Intake of balance diet as per the protocol of the Government of Nepal for healthy growth and 189