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.

Introduction

World Health Organization defines low birth weight (LBW) as the birth weight less than 2500 grams irrespective of gestational age [1]. LBW is a valuable public health indicator of maternal health, nutrition, healthcare delivery, and poverty as LBW babies are at a higher risk of death and illness shortly after birth and non-communicable disease in the life course [2]. LBW infants are 20 times more likely to develop complications and die in comparison to normal weight babies [3]. LBW babies are in the potential risk of cognitive deficits, motor delays, cerebral palsy, and other behavior and psychological problem [4-8]. The household cost, as well as health system costs, could be saved by reducing the burden of LBW [9]. The pathophysiology of low birth weight is unclear, whereas intrauterine growth retardation (IUGR) and preterm birth considered as the cause of LBW. IUGR is the outcome of insufficient uterine–placental perfusion and fetal nutrition affecting the overall anthropometric parameter of the fetus. IUGR newborn has typical features of malnutrition. Extra-uterine infection, trauma, illness, IUGR, fetal infection, and anomalies are the contributing factors for preterm birth, resulting in growth retardation which ultimately results in LBW [3, 10, 11]. LBW is considered a significant public health problem as it is estimated that 15% to 20% of all birth worldwide are LBW. The prevalence of LBW varies across regions with the highest 28% in South Asia and the lowest 6% in East Asia and the Pacific region [12]. The prevalence of LBW in Nepal ranges from 12% to 21.6%, [13-15]. A few descriptive and hospital-based case-control studies have been done in Nepal [14-19]. These descriptive and hospital-based studies could not represent the risk factors of LBW at the community level as these studies had taken participants from hospitals only. Hence this study aims to identify the associated risk factors of LBW at the community level by including the participants from the community level health facilities.

Methodology

An unmatched case-control study was used. This study was conducted in Dang district of Nepal. This study was approved by the Institutional Review Committee (IRC) of Institute of Medicine (IOM) Tribhuvan University on August 19, 2018. The study population was mothers, who delivered their babies in the governmental health institutions (28 birthing centers and 3 hospitals) of Dang from 17th August to 16th November 2018. The study population was divided into case and control as per the following definition.

Case

Mother delivering singleton live-born baby with birth weight less than 2500 grams without any congenital anomalies and were originally from Dang district.

Control

Mother delivering singleton live-born baby with birth weight more or equal to 2500 grams without any congenital anomalies and were from the same Dang district.

The sample size was calculated using EpiInfo software version 7. This was calculated by taking power at 80%, confidence level as 95%, the percentage of control exposed as 65.40, the odds ratio of 2.06 from the maternal weight against LBW [20], and the ratio of case to control was 1:2. The total sample size was 369 with 123 cases and 246 controls. The eligible numbers of participants were enlisted from the maternal and neonate health register of 28 birthing centers and 3 hospitals of Dang District. One hundred and twenty-three cases were selected from the list of 224 cases and 246 controls from the list of 777 controls randomly independent of exposure status by generating random numbers. The 123 cases and 246 controls with the highest random number were visited with the help of FCHV, local leaders, teachers for the data collection. Face to face interview was done with the participants for the collection of data using a semi-structured questionnaire. Information regarding weight gain, age, ANC visit, birth weight, comorbidity, gestational age etc was taken through reviewing Antenatal Care (ANC) card and Maternal and newborn register to avoid possible recall bias. The tool was adapted from the previous studies done in Nepal [16–18, 20, 21]. The tool was translated into the Nepali language and pretested in Dhulikhel municipality; of Kavrepalanchok district among 10 percent of sample size i.e. 12 cases and 24 controls.

Data entry was done in Epi data Version 3.1 following coding. Data analysis was done using SPSS software version 21. Bivariate associations between independent variables and low birth weight were tested through the Chi-square test and the association was analyzed by calculating crude odds ratios (OR) at 95% confidence interval through binary logistic regression. Multivariate logistic regression was examined for the relationship between independent variables and low birth weight to address the confounding effect. Hosmer and Lemeshow test was used to test the goodness-of-fit for regression models. The test statistic was 0.69 (p > 0.05) that showed that the model adequately fit the data.

Ethical clearance was obtained from the Institutional Review Committee (IRC) of the Institute of Medicine, Tribhuvan University. Permission was taken from the District Public Health Office (DPHO) Dang and respective health facilities. Written consent was taken from each participant after explaining the objectives of the study. After the interview, the mothers were informed about the importance of growth monitoring, exclusive breastfeeding, immunization, and appropriate time of weaning.

Results

Table 1 depicts that the mean age of the participants was 23 years (SD 4.4 years). Getting support from their husbands in day to day activities during pregnancy was quite common. The major (66.4%) fuel used during cooking was firewood and kerosene. The majority (53.1%) of the household did not have a separate kitchen. Majority (55.3%) of participants' family members did not smoke any form of cigarette. A small portion (2.2%) of participants had the habit of smoking cigarettes during pregnancy. Two-third (67%) of participants had their meal thrice a day and 64.2% had included additional food groups in their meal at the time of pregnancy. Majority (78%) of participants had attended ANC visit as per the protocol of the government of Nepal. Similarly, 73% of participants had taken 180 or more iron tablets during pregnancy. More than half of the participants had gained weight less than 6.53 kg during the second and third trimester. Fifty-four percentages of participants had one child. Majority (59.3% among cases and 86.2% among controls) of the research participants did not face any health problems (co-morbidities) during their pregnancy and 14.6% of the babies were born before 37 weeks of gestation.

Table 1

Distribution of participants according to socio-demographic, maternal factors and co-morbidity during pregnancy.

Variables	Case (123)	Control (246)	Total (369)
	n (%)	n (%)
Age of mother
<20 Years	35 (28.5%)	55 (22.4%)	90 (24.4%)
20–30 Years	79 (64.2%)	178 (72.4%)	257 (69.6%)
>30 years	9 (7.3%)	13 (5.3%)	22 (6.0%)
Support from husband in day to day activities
Yes	102 (82.9%)	222 (90.2%)	324 (87.8%)
No	21 (17.1%)	24 (9.8%)	45 (12.2%)
Cooking material
Fire wood and Kerosene	87 (70.7%)	158 (64.2%)	245 (66.4%)
LPG and Bio Gas	36 (29.3%)	88 (35.8%)	124 (33.6%)
Location of kitchen
Same house	86 (69.9%)	110 (44.7%)	196 (53.1%)
Separate house and outside	37 (30.1%)	136 (55.3%)	173 (46.9%)
Smoking by family member
Yes	65 (52.8%)	100 (40.7%)	165 (44.7%)
No	58 (47.2%)	146 (59.3%)	204 (55.3%)
Smoking habit
Yes	6 (4.9%)	2 (.8%)	8 (2.2%)
No	117 (95.1%)	244 (99.2%)	361 (97.8%)
Food frequency per day
Twice	30 (24.4%)	44 (17.9%)	74 (20.1%)
Thrice	81 (65.9%)	166 (67.5%)	247 (67%)
More	12 (9.6%)	36 (14.6%)	48 (13.0%)
Type of food use
As usual	56 (45.5%)	76 (30.9%)	132 (35.8%)
Addition food (Any group)	67 (54.5%)	170 (69.1%)	237 (64.2%)
ANC visit as per protocol
Yes	80 (65.0%)	208 (84.6%)	288 (78.0%)
No	43 (35.0%)	38 (15.4%)	81 (22.0%)
Number of iron tablets used
<180	60 (48.8%)	40 (16.3%)	100 (27.1%)
180 and more	63 (51.1%)	206 (83.7%)	269 (72.9%)
Weight gain between second and third trimester
<6.53 kilogram (kg)	91 (74.0%)	120 (48.8%)	211 (57.2%)
6.53 kg and above	32 (26.0%)	126 (51.2%)	158 (42.8%)
Number of children
1 (Primiparity)	79 (64.2%)	121 (49.2%)	200 (54.2%)
2	32 (26.0%)	93 (37.8%)	125 (33.9%)
3	8 (6.5%)	26 (10.6%)	34 (9.2%)
4 and above	4 (3.3%)	6 (2.4%)	10 (2.7%)
Health problem
Yes	50 (40.7%)	34 (13.8%)	84 (22.8%)
No	73 (59.3%)	212 (86.2%)	285 (77.2%)
Preterm birth
Yes	33 (26.8%)	21 (8.5%)	54 (14.6%)
No	90 (73.2%)	225 (91.5%)	315 (85.4%)

Table 2 shows the bivariate and multivariate analysis of dependent and independent variables. In bivariate analysis; support from husband during pregnancy, use of firewood and kerosene during cooking, having kitchen in the same living house, cigarette smoking by family members, cigarette smoking by mother during pregnancy, use of additional food groups in their diet during pregnancy, four ANC visit as per protocol of Government of Nepal, iron tablets intake less than 180 tablets during pregnancy, weight gain during pregnancy less than 6.53 kg in-between second and third trimester, mother delivering her first baby, health problem during pregnancy and preterm baby were associated with low birth weight.

Table 2

Bivariate and Multivariate analysis of independent variables against low birth weight.

Variables	p-value	Crude OR	CI (95%)	Adjusted OR	CI (95%)
Age of mother
<20 Years	0.4	1.4	0.9 to 2.4	0.8	0.4 to 1.6
>30 years		1.6	0.6 to 3.8	1.5	0.4 to 5.3
20–30 Years		Ref		Ref
Support from husband in day to day activities
No	0.04	1.9	1.0 to 3.6	1.5	0.7 to 3.3
Yes		Ref		Ref
Cooking material
Fire wood and Kerosene	0.2	1.4	0.8 to 2.2	1.4	0.7 to 2.6
LPG and Bio Gas		Ref		Ref
Location of kitchen (Proxy of indoor air pollution)
Same house	<0.0001	2.9	1.8 to 4.6	2.7	1.5 to 4.8
Separate house and outside		Ref		Ref
Smoking by family member
Yes	0.026	1.6	1.1 to 2.5	1.4	0.8 to 2.5
No		Ref		Ref
Smoking habit
Yes	0.032	6.3	1.2 to 31.5	5.3	0.7 to 42.7
No		Ref		Ref
Food frequency per day
Twice	0.19	2	0.9 to 4.6	1.3	0.5 to 3.6
Thrice		1.5	0.7 to 3	1.5	0.7 to 3.5
More		Ref		Ref
Type of food use
As usual	0.006	1.9	1.2 to 2.9	0.9	0.5 to 1.6
Addition food (Any group)		Ref		Ref
ANC visit as per the protocol of Nepal Government
No	<0.0001	2.9	1.8 to 4.9	1.7	0.9 to 3.2
Yes		Ref		Ref
Number of iron tablets used
<180	<0.0001	4.8	3.0 to 7.9	3.2	1.7 to 5.7
180 and more		Ref		Ref
Weight gain
Less than 6.53 kg	< 0.0001	3	1.9 to 4.8	2.6	1.5 to 4.7
6.53 kg and above		Ref		Ref
Number of children
1 (Primiparity)	0.03	1.9	1.2 to 3.1	1.8	0.9 to 3.6
3		0.9	0.4 to 2.2	0.4	0.1 to 1.2
4 and above		1.9	0.5 to 7.3	0.6	0.1 to 3.8
2		Ref		Ref
Health problem (Co-morbidity)
Yes	<0.0001	4.3	2.6 to 7.1	2.4	1.3 to 4.5
No		Ref		Ref
Preterm birth
Yes	<0.0001	3.9	2.2 to 7.2	2.9	1.4 to 6.1
No		Ref		Ref

In multivariate analysis, having 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 less than 6.53 kg during second and third trimester (AOR 2.6, CI: 1.5–4.7), co-morbidities during pregnancy (AOR 2.4, CI: 1.3–4.5) and preterm birth (AOR 2.9, CI: 1.4–6.1) were significantly associated at 95% confidence interval with the low birth weight. Similarly, age of mother, support from husband during pregnancy, use of firewood and kerosene during cooking, smoking habit of the mother, smoking by family member, food frequency less than three per day, use of any additional food group during pregnancy, four ANC visit as per protocol, first children was not associated with LBW in this study.

Discussion

This study analyzed the socio-demographic factors, maternal factors, and co-morbidities during recent pregnancy against low birth weight during delivery.

The maternal age is considered as a key factor for the healthy outcome of pregnancy. This study revealed no statistical association between maternal age and low birth weight which contradicts with the study done in Nepal, that shows a higher risk of delivering low birth weight babies by mother age less than 20 and more than 30 years [16, 17, 18]. Smoking during pregnancy had a negative effect on the growth and development of the fetus because of chemical substances present in it. Nicotine present in the cigarette cause vasoconstriction resulting in the low oxygen flow to the fetus and Carbon-monoxide forms carboxyhemoglobin which inhibits the oxygen release to fetal tissues [22] In bivariate analysis mother habit of smoking had a higher risk of low birth weight in reference to the mother who did not smoke a cigarette (OR 6.3, 95% CI: 1.2–31.5). This finding is consistent with the findings of similar studies done in Bangladesh and Turkey [23, 24]. Though there was a risk, however, there was no significant association between smoking and low birth weight in multivariate analysis. This could be explained probably due to the small number of smokers in the study population. Moreover, it can also be explained by the social desirability bias, induced due to social stigma.

This study identified the location of the kitchen in the living house, iron intake less than 180 tablets, weight gain less than 6.53 kg during the second and third trimester, comorbidity during pregnancy, and preterm birth as the risk factors for low birth weight. The finding reveals that the cooking fuels namely firewood and kerosene use had a risk for LBW with reference to LPG and Biogas however, it was not statistically significant. This finding contradicts to the find of the study done by Kadam YR et al. and Washam C [25, 26], however, this study revealed that having a kitchen in the same living house (proxy of indoor air pollution) had 2.5 times higher risk of delivering low birth weight which may be due to, living in the same house had higher risk and duration of exposure to the pollutants like PM2.5, PM10, NO2, SO2, CO caused by burning of fuels, leading to the impaired supply of oxygen, nutrition to the fetus resulting in the negative impact on the growth and development of fetus [27, 28]. The amount of exposure was not measured quantitatively in this study.

This study showed that total iron tablet intake during pregnancy was associated with the birth weight of the child. Mothers who took less than 180 tablets of iron during their pregnancy were three times more likely to deliver low birth weight babies with reference to mothers who took iron equal to or more than 180 tablets during their pregnancy period (AOR 3.2, CI: 1.7–5.8). This finding is similar to the studies conducted in Nepal [16, 29]. Low iron tablets intake causes the poor delivery of iron to the fetus thereby impair in proper hormonal and neuronal regulation of pregnancy and poor oxygenation to the fetus leading to the poor growth and development of the fetus [30]. However, the iron intake through diet during pregnancy was not measured in both cases and control.

The minimum standard weight gain during the second and third trimester is set as 6.53 kg [31]. Women who gained weight less than 6.53 kg during the second and third trimester had 3 times higher risk of delivering low birth weight baby with reference to women whose weight gain was 6.53 kg or above (AOR 2.8, CI: 1.6–5.0). This finding is similar to the study done in Bangladesh [32] and Mozambique [33]. The weight gain during pregnancy is impaired due to ill health, poor sanitation, and inadequate balance diet which at the end hamper the proper growth and development of the baby.

Women who had at least one health problem during their pregnancy were at higher risk of delivering low birth weight in comparison to women without any health problem (AOR 2.6, CI: 1.4–4.8). This finding is consistent with the study done in Nepal [17, 20]. Likewise, this study suggests that mother delivering baby before completion of 37 weeks of gestation had higher risk of delivering low birth weight than the mothers who deliver the term baby (AOR 2.6, CI: 1.2–5.5) which is in line with the study done in Nepal [17], Ethiopia [34] and Kenya [35]. Biologically it can be explained that preterm birth was less likely to get sufficient time for maturity, growth, and nutrient intake which therefore can lead to low birth weight [36].

In this study, the researcher has retrieved maternal information namely gestational weight, iron tablets intake, gestational age, co-morbidity, frequency of ANC visits, and birth weight of a baby from ANC card and maternity register to limit the recall bias. The selection of cases and controls were based on the records of maternal and neonatal register therefore, it is less likely that this study has misclassification biases both in the exposure and case-control categories. Controls were selected randomly independent of the exposure status and as there was no non-response in both the group, it is less likely that this study would suffer from selection biases. However, the study had some limitations. The findings might be influenced by social desirability bias. The findings could not be generalized as the study was confined in the health institutions of one district. The details of comorbidity during pregnancy, the micro-nutritional status of the mother, and the quality of ANC visit were not evaluated which may affect the outcome of this study.

Conclusion and recommendation

This study concluded that the having the kitchen in the same living house (proxy of indoor air pollution), iron intake less than 180 tablets during pregnancy, weight gain less than 6.35 kg during the second and third trimester, co-morbidity during pregnancy, and preterm delivery were found to be associated risk factors of low birth weight. Thus, identified risk factors can be efficiently prevented through small doable actions that a family can apply and the mother can easily carry out. Maternal health programs can be directed towards motivating and tracking pregnant mothers for complete iron tablets intake during her pregnancy period. Intake of balance diet as per the protocol of the Government of Nepal for healthy growth and development of the child inside the uterus is of paramount importance. Family should help the mother for adequate rest, nutrition and healthy behavior to prevent risk factors identified in this study.

(SAV)

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29 Jan 2020

PONE-D-19-31435

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

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Reviewer #1: 1. Introduction part needs more extensive literature review and rewrite your lines. eg-44-45

2. Identify the risk factors of LBW from literature, and see the factors associated in your context. If you are trying to establish the association in your local settings, then it should fulfil the various criteria, it cannot be be just a random association.

3. You have tried to establish association in diverse area of risk factors, which is inconclusive. Needs more improvement in the technicality of hte subject matter

3. Methodology: Need more explanation on the tool you have used and its validity. Any specific reason to select only those variables in your study. Its not clear how you addressed your confounders.

4. Result: Some of your finding to do not meet the principle of Biological Plausibility

Reviewer #2: Note: Please find all the comments in the attached reviewed manuscript file in track change format.

Title of research: Clear

Abstract:

Organised well.

Line 28 and 29: Variables are not clear. This needs to be more specific like other variables. Suggestion: Not having a kitchen in the same living room.

Line 33-35: In conclusion_This seems recommendations. Please mention your conclusion based on your objective of this research only.

Introduction:

I would suggest adding few literatures from Nepal as well.

Methodology:

Line 54: I think this word (retrospective) is not required here.

Line 56: Better to include health institutions.

Line 67: Start from word…not from number.

Line 68: Not clear….How did you select? Please be specific.

Results:

Line 88: Table 1: Rectify the included variables and better to concise the writing.

It means the kitchen is within the sleeping room in a house. What is the rationale of this category?

Line 90-104: Add the clear component of variables

Line 105: Table 2: Is the p-value same for both bivariate and multivariate analysis? (As you can see there is a change in Confidence Interval in bivariate and multivariate analysis.)

In the age of mothers, 20-30 years category as a reference is more scientific.

Other variable needs to be more specific. (Suggested in track change attached manuscript file.)

Line 106: Here you said both bivariate and multivariate analysis shown in the table but in your title of the table only multivariate included. I think you need to format the table.

Discussion:

Line 126-129: You need to change your reference age group for statistical analysis. I already mentioned above in your result section.

Line 131: Better to add in text citation

Line 147; Mention supporting evidence with in text citation.

Line 166: Is this only clinical assessment?

Line 172: Better to mention in-text citation.

Line 178: How randomly? Need a better explanation.

Conclusion:

Line 191-193: But how?? You need more justification.

References:

Better to add doi and PMID numbers if available.

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Reviewer #1: No

Reviewer #2: Yes: Dr. Surya Bahadur Parajuli

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14 Mar 2020

Reviewer #1:

1. Introduction part needs more extensive literature review and rewrite your lines. eg-44-45

Revised: LBW is a valuable public health indicator of maternal health, nutrition, healthcare delivery, and poverty as LBW babies are at a higher risk of death and illness shortly after birth and non-communicable disease in the life course.

Added: The household cost, as well as health system costs, could be saved by reducing the burden of LBW.

Added: IUGR is the outcome of insufficient uterine–placental perfusion and fetal nutrition affecting the overall anthropometric parameter of the fetus. IUGR newborn has typical features of malnutrition. Extra-uterine infection, trauma, illness, IUGR, fetal infection, and anomalies are the contributing factors for preterm birth, resulting in growth retardation which ultimately results in LBW.

2. Identify the risk factors of LBW from literature, and see the factors associated in your context. If you are trying to establish the association in your local settings, then it should fulfill the various criteria, it cannot be just a random association

Yes, variables were selected based on studies done in Nepali and outside in a similar setting and consultation with experts and try to identify the possible risk factors in the local setting so, this is not just random association and possible explanation was done in the discussion section.

3. Methodology: Need more explanation on the tool you have used and its validity. Any specific reason to select only those variables in your study. Its not clear how you addressed your confounders

Revised: The tool was adapted from the previous study by Sharma SR et al. and other similar studies done in Nepal. The tool was translated into the Nepali language and pretested in Dhulikhel municipality; of Kavrepalanchok District among 10 percent of sample size i.e. 12 cases and 24 controls.

Response: Possible confounders were addressed by randomization and multivariate analysis.

4. Result: Some of your finding to do not meet the principle of Biological Plausibility

Response: The Biological plausibility of each finding from the multivariate analysis was explained in the discussion section.

Reviewer #2:

Note: Please find all the comments in the attached reviewed manuscript file in track change format.

Response: All the comments in the track change format are addressed individually.

Title of research: Clear

Abstract:

Organised well.

Line 28 and 29: Variables are not clear. This needs to be more specific like other variables. Suggestion: Not having a kitchen in the same living room.

Response: the variable location of kitchen wants to know about the kitchen in the same living house or separate from the living house. So it has been explained as having a kitchen in the same living house.

Line 33-35: In conclusion This seems recommendations. Please mention your conclusion based on your objective of this research only.

Revised: 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.

Introduction:

I would suggest adding few literatures from Nepal as well.

Intext citation was added to highlight the literature that was reviewed from Nepal.

Methodology:

Line 54: I think this word (retrospective) is not required here.

Removed: An unmatched case-control study was used.

Line 56: Better to include health institutions.

Response: The data were taken from 31 health institutions of Dang district so it difficult to include the name of the health institution.

Revised: The study population was mothers, who delivered their babies in the governmental health institutions (28 birthing centers and 3 hospitals) of Dang from 17th August to 16th November 2018.

Line 67: Start from word…not from number.

Revised: One hundred and twenty-three

Line 68: Not clear….How did you select? Please be specific.

Added: One hundred and twenty-three cases were selected from the list of 224 cases and 246 controls from the list of 777 controls randomly independent of exposure status by generating random numbers The 123 cases and 246 controls with the highest random number were visited with the help of FCHV, local leaders, teachers for the data collection.

Results:

Line 88: Table 1: Rectify the included variables and better to concise the writing.

It means the kitchen is within the sleeping room in a house. What is the rationale of this category?

The variable wants to know whether the participants had a separate kitchen or not.

The rationale behind 6.53 Kg is, in our context it is difficult to know the exact weight gain during the pregnancy, however the weight gain in each ANC visit was recorded in both ANC card and maternity and newborn register. As per the study done in Low and middle-income county by Diane Coffey in 2015, concluded that the weight gain between the second and third trimester was 6.53Kg and this information can be easily accessible from ANC cards as well as maternity register.

Line 90-104: Add the clear component of variables

Added: Added as per comments.

Line 105: Table 2: Is the p-value same for both bivariate and multivariate analysis? (As you can see there is a change in Confidence Interval in bivariate and multivariate analysis.)

The P-value is of the chi-square test.

In the age of mothers, 20-30 years category as a reference is more scientific.

The reference category changed to 20-30 years and analysis did accordingly.

Other variable needs to be more specific. (Suggested in track change attached manuscript file.)

The location of the kitchen is the proxy indicator of Indoor air pollution.

Smoking by a family member is the proxy indicator of second-hand smoking.

Smoking habit indicates the habit of smoking any form of tobacco; Ciggrate, hukka and other traditional forms of smoking like rolling of tobacco in green leaf and smoke.

Food frequency per day: It is recommended that pregnant women should take one additional meal during their pregnancy for healthy growth and development of a fetus. Based on this line, we can assume that when she had taken an adequate diet or not, however, we cannot say it is balanced or not. It reveals the quantitative prospect of diet than qualitative.

Line 106: Here you said both bivariate and multivariate analysis shown in the table but in your title of the table only multivariate included. I think you need to format the table

The table has been formatted.

Discussion:

Line 126-129: You need to change your reference age group for statistical analysis. I already mentioned above in your result section.

Revised: The reference age group has been changed and statistical analysis was done accordingly.

Line 131: Better to add in-text citation

Added

Line 147; Mention supporting evidence with in-text citation.

Intext citation with supporting evidence has been added.

Line 166: Is this only clinical assessment?

It was based on the diagnosis made by health workers (any level) by reviewing cards.

Line 172: Better to mention in-text citation.

Mentioned

Line 178: How randomly? Need a better explanation.

Explained in the methodological section

Conclusion:

Line 191-193: But how?? You need more justification.

The recommendation was rearranged.

References:

Better to add doi and PMID numbers if available.

Added where possible.

Submitted filename: Response to Reviewers.docx

Click here for additional data file.

28 Apr 2020

PONE-D-19-31435R1

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

PLOS ONE

Dear Mr. K C,

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PLOS ONE

Additional Editor Comments (if provided):

Kindly address the comments provided by Reviewer 1. The rationale for the study needs better justification as to how it better represents the community rather than hospital based studies done in the past (keeping in mind that the few of the study sites for this study were hospitals as well). Authors also need to highlight upon the limitations of the study. Authors need to revisit the grammatical errors and sentence structuring.

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Reviewers' comments:

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Reviewer #1: (No Response)

Reviewer #2: All comments have been addressed

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Reviewer #2: Yes

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Submitted filename: PONE-D-19-31435_R1_reviewer.pdf

Click here for additional data file.

1 Jun 2020

Reviewer #1:

1. Reviewer 1. The rationale for the study needs better justification as to how it better represents the community rather than hospital based studies done in the past (keeping in mind that the few of the study sites for this study were hospitals as well). Authors also need to highlight upon the limitations of the study. Authors need to revisit the grammatical errors and sentence structuring.

Response: This study had taken research participants from 28 birthing centers and 3 hospitals so that it could better represent the community (Birthing center will represent the participants from rural areas and hospitals from both rural (referred case) and urban). So that it better represents the community. The limitation of the study was explained in the discussion section. Grammatical errors and sentence structuring were revisited and edited where necessary.

Added: However, the study had some limitations. The findings might be influenced by social desirability bias. The findings could not be generalized as the study was confined in the health institutions of one district. The details of comorbidity during pregnancy, the micro-nutritional status of the mother, and the quality of ANC visit were not evaluated which may affect the outcome of this study.

Line 48-49: Please go through more literature and published articles on cause of LBW

Response: The literature regarding the cause of LBW, which were reviewed were cited.

Line 59: Do you want to present the scenario, identify the scenario of associated risk factors or provide the evidence of risk factors through its association?? Be clear on your research objectives and rationale.

Response: The objective was to identify the risk factor of low birth weight. The sentence was rewritten as per the objective by removing the words “scenario of”.

Line 63-68: Its better to put this paragraph below. First highlight the details of the methodology placed below this paragraph

Response: Paragraph was placed as per comment below the detail of the methodology.

Line 89: There should be good linkage between your study variables and questionnaire, please look into your conceptual framework, questionnaire and results, So that you could establish your association in your result section. select appropriate variables

Response: The questionnaire was developed according to the conceptual framework and the result was generated based upon the data collected from the questionnaire. The whole steps were closely supervised by experts from the Institute of Medicine, Maharajgunj Medical Campus.

Line 92: Please put this in Citation in the reference??

Response: Updated as per comment.

Line 108-109: You have kept this finding at first, is it that you find this result highly significant in your study???

Response: It is not like that, I had mentioned the age of the mother above the table. I had re-arranged the findings in order of the variables on the table.

Line 124-126: aren't these factors all related to smoke??? Biomass fuel/cigarette??

Yes, these factors are related to smoke, however, the rate of exposure, chemical constituents, and the effects from them are different.

Line 215: Spelling???

Response: Spelling is changed

Submitted filename: Response to Reviewers.docx

Click here for additional data file.

5 Jun 2020

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

PONE-D-19-31435R2

Dear Dr. K C,

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Kind regards,

Pranil Man Singh Pradhan

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

10 Jun 2020

PONE-D-19-31435R2

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

Dear Dr. K C:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

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on behalf of

Dr. Pranil Man Singh Pradhan

Academic Editor

PLOS ONE