[version 1; peer review: 3 approved with reservations]
No competing interests were disclosed.
Antenatal care (ANC) globally is an important health strategy that has been considered as an essential intervention to contribute to the health of newborns and their mothers. This health intervention reduces low birth weight (LBW) which is a foremost public health burden that weakens the development of families and nations due to its harmful effects on quality of life.
Prior studies indicated that maternal and environmental factors are major factors with regard to LBW.
ANC refers to the routine health management of presumed healthy pregnant women without the symptomatology or screening so as to diagnose and detect the diseases or complicating symptoms.
Earlier researchers documented that through ANC services, pregnant women and their newborns develop physiological and psychosocial wellbeing. It also reduces risk to have a LBW newborn. ANC visits contributed to development of healthy behaviors and compromise of the emergency preparedness plan to intensify the maternal awareness, improving the newborn needs and self-care.
Previous studies indicated that there is a substantial influence of ANC on increase of birth weight for the children and their development of a good life characterized by prevention and management of pregnancy-related or concurrent diseases and psychosocial development.
The rationale of this study was to increase the accessibility to ANC services that were documented to be practiced, but there was no scientific evidence that was conducted to indicate its effect on neither LBW nor contributing determinants to the reduction of children and maternal morbidity and deaths in Rwanda. Through the findings from this research, the investigators indicated how pregnant women achieve the third goal of Sustainable Development Goal (SDG-III) related to the reduction of infant and maternal mortality and morbidity by completing four ANC visits and more. Although it is known that ANC visits are an important intervention that contributes to prediction of the newborn birth weight, little has been conducted on effect of ANC visits on birth weight in developing countries, including Rwanda. This research, therefore, aimed to determine the effect of antenatal care visits on the LBW of children in Rwanda using the secondary data analysis of Rwanda Demographic and Health Survey (RDHS) 2014-2015. We hypothesize that ANC visits result in reducing the high incidence of LBW among newborns of Rwanda.
The fifth RDHS 2015 was utilized as a nationally representative sample implemented by the National Institute of Statistics of Rwanda (NISR) and Ministry of Health of Rwanda.
The study design was a secondary analysis of cross-sectional survey data from RDHS 2014/2015 that was retrospectively carried out for investigating the effects of antenatal care visits on birth weight of the newborn in Rwanda. The RDHS data collection fieldwork was conducted from November 9, 2014, to April 8, 2015. The data entry, editing, and cleaning was completed by May 15, 2015, and the final survey report was completed in March 2016. A total of 8,004 pregnant women who were to receive antenatal care interventions before delivery were recruited. The interviewed women were of reproductive age (15–49 years). This study was conducted in Rwanda, a small country located in the Central and Eastern Africa bordered by the Republic Democratic of Congo to the West, Uganda to the North, Tanzania to the East and Burundi to the South. This country lies a few degrees south of the equator and is landlocked. Concerning ANC visits, accessibility to ANC services is increasing due to the improvement of the health system and health financing.
RDHS was a national survey conducted to assess the birth weight of newborns. To collect the data of this household-based survey, mothers who had the youngest children, age five years or less, were interviewed to provide data related to birth weight for their children. The data for this survey were collected using a two-stage sampling strategy for enrolling participants. These stages were cluster sampling design and the sampling frame. The sampling frame was composed of the list of the enumerators’ areas (EAs) that covered the entire country. All residents in selected households were eligible to be interviewed. At the first stage of this study, 492 clusters were randomly selected (113 in urban and 379 in rural areas). At the second stage of this study, the systematic sampling technique that focused on selecting the households was applied. Then, a fixed number of 26 households were selected randomly from each cluster and a total of 12,792 households were selected for the final sample for this study.
Additionally, the proportional sampling technique was used in the survey where the sample for each cluster was equal. The study included women aged 15–49 years who were permanent residents of the households or visitors who stayed in the recruited household the night before the survey. For this epidemiological research, this fifth demographic survey presented that although the weight of the newborns at birth is an important predictor of their probability of surviving, current birth weights were not available for the most children. Instead, the mothers were interviewed about the size of their children at birth because this determinant was found to be a proxy for the weight of the newborn. Therefore, 8,004 mothers with 15–49 years of reproductive age were interviewed for reporting the actual weight in kilograms using the written information about birth weight or recalling the weight at birth for their newborns. It was found that 92% of newborns had a birth weight reported while 8% did not.
RDHS 2014/2015 collected data at the national level using household-based survey data on birth weight retrospectively collected from the mothers. The data collection was completed by trained data collectors who used face-to-face interviews, asking mothers eligible for this study to provide a detailed birth history for children born in the preceding five years. Recruitment included stratified sampling, two stages of cluster sampling designs. The first stage was characterized by selecting the participants from the samples frame constructed from enumeration whereas the second stage involved the systematic sampling of the households. These were listed from each cluster to ensure that an adequate number of the completed individuals were obtained.
Bias refers to any tendency or deviation from the truth in study design, data collection, recruiting participants, data analysis, and results interpretation. Generally, bias may occur at any stage of the research. To manage the bias for the data from RDHS, the authors systematically did data cleaning and removed the missing variables. All authors checked several times the selected variables to include in the analysis for minimizing all possible systematic errors that could occur in the study.
The outcome variable of the current study was birth weight of the newborns. As per World Health Organization (WHO) classification, newborns weighing <2,500 grams were categorized as LBW while newborns weigh >2,500 grams were categorized as not having LBW.
Based on the literature review and the structure of the RDHS 2014/2015 dataset, the independent variables were found. The main explanatory variable was the number of the antenatal care visits for the pregnant women. Pregnant women who attend none or one ANC visit were considered to have inadequate number of visits, those who attended two or three ANC visits were considered to have intermediate, and those who attended four to seven were taken as adequate number of visits. As recommended by WHO, the pregnant women who attended four ANC visits were considered to have obtained extremely adequate healthcare that effectively contributes to the health of the mother and unborn.
Before analysis, the observations with missing data were dropped. Statistical analysis was performed using descriptive (such as frequency, percentage, standard deviation, and mean) and analytical analyses. In the analytical analysis, bivariate logistic regression and multiple logistic regression models were computed to determine the association between LBW and the explanatory variables. The factors that were significantly associated with LBW at 0.05 or 0.01 in bivariate logistic regression were analyzed using multiple logistic regression models for identifying the association between ANC visits and birth weight when controlling for other covariates, presenting adjusted odds ratio, 95% confidence intervals. Therefore, we adjusted sampling based on the RDHS data that were widely used and consistent data for assessing maternal and child health statistics at the national level using STATA software version 13 (RRID:SCR_012763).
Data used were electronically accessed. To get full access, the first registration was completed on the DHS website. The permission to use the 2014/2015 RDHS data was granted by DHS using its website and the prior approval was maintained. In the prior approval, the women of reproductive age who were age 18–49 years provided oral and written informed consent forms to take part in the survey. In the cases on the minor participants (those women aged 15–17 years); the assent form was obtained from them while written informed consent were simultaneously provided by their guardians or parents who were adults.
The results indicated the average birth weight was 3846.1 grams with a standard deviation of 1840.5 grams. The results indicated that the average family size was 5.7 (SD=2). The majority [6012 (76.6%)] weighed 2,500–4,000grams. The majority (61.3%) of pregnant women were aged 35–39 years. For the occupation of the pregnant women, it was found that the majority (86.1%) were involved in agricultural activities (self-employed). About the participants’ religious beliefs, the majority (96.8%) were Christians. Regarding the information about the households, the results indicated that the majority (21.6%) were the poorest. The majority of them (57.9%) were from the families consisting of four to seven family members and 77.3% resided in rural setting. 92% of the pregnant women attended ANC at health centers. Moreover, the prevalence of LBW and macrosomia was 5.8% and 17.6%, respectively, whereas 76.6% of pregnant women delivered newborns who weighed between 2.5 kg and 4 kg. The number of pregnant women who attended four or more ANC visits was 44.1%, those who attended fewer than four ANC was 55.1%, and only 0.8% attended no ANC visits. This indicated that Rwanda did not yet achieve the SDG-III. Besides, the findings showed that during pregnancy, these women are provided different health education and measurement for improving the health of the children including normalizing the birth weight for both mother and their children. Within this period, the results indicated that the majority of the pregnant women (80.5%) were provided at least one tetanus injection before birth, but 19.5% were not. Before pregnancy, the results indicated that the majority was not given any tetanus injection. This means that the tetanus injection is mostly attended by the women when they were pregnant during the ANC visits. The results indicated that more than 70.7% of the pregnant women were provided counseling and education related to nutrients. Indeed, the findings showed that 79.9% of pregnant women were given iron tablet during the pregnant period. The majority (83.4%) of pregnant women were measured blood pressure (
Characteristics
Number
Percentage
15-19
120
4
20-34
2260
74.9
35-49
638
21.1
Mean (SD)
36.8(7.4)
<80 kg
2621
33.4
80-89 kg
2922
37.2
≥90 kg
2305
29.4
Single
324
10.7
Married/cohabiting
2478
82.1
Widowed/separated/divorced
216
7.2
Illiterate
389
12.9
Primary
2139
70.9
Secondary/higher
490
16.2
Christian
2922
96.8
Muslim
666
2.1
Traditional
213
1.1
Yes
63
0.9
No
7319
99.1
Urban
685
22.7
Rural
2333
77.3
Poor
236
51.5
Middle/rich
222
48.5
Less than 4
282
19.3
4 to 7
843
57.9
More than 7
332
22.8
Mean (SD)
5.7(2)
<2,500grams
458
5.8
2,500-4,000grams
6012
76.6
>4000grams
1378
17.6
Mean (SD)
3846.1(1840.5)
1-2
13
2.2
3-4
138
23.5
≥5
436
74.3
No injection
1161
19.5
Yes
4792
80.5
No injection
833
30.4
Yes
1858
67.7
More than 7
52
1.9
No
1198
20.1
Yes
4756
79.9
Male
729
50
Female
728
50
Homes
589
2.0
Provincial/district hospital
2166
7.2
Health center
4836
16.1
Privates and other health facilities
262
74.7
No ANC and less than 4 ANC
3329
55.9
≥4 ANC
2622
44.1
No
53
16.6
Yes
266
83.4
No
9
2.8
Yes
310
97.2
No
908
42
Yes
1251
58
No
893
29.3
Yes
2159
70.7
In the bivariate logistic regression, we indicated how low birth weight is associated with ANC services, socio-demographic characteristics, maternal influences and behaviors. Therefore, we found that LBW is significantly associated with the ANC visits, BMI, maternal height, maternal weight, residence, place of delivery, sex of child, HWI, maternal parity, maternal, anemia for pregnant women, family size, age, maternal education, provision of tetanus injection during the pregnancy, health education about pregnant complications, provision of counseling about nutrients during pregnancy, provision of malaria drugs, use of health card, and attendance of ANC visits at health center (
Characteristics
LBW, n (%)
Odds ratio
95% CI
Urban
75(16.4)
Rural
383(83.6)
1.3
1.1-1.7
0.031*
≤18.5 kg/m
2
367(80.2)
18.5-25.9 kg/m
2
60(13.1)
0.4
0.1-1.1
0.02*
≥25 kg/m
2
31(6.7)
1.9
1.1-3.3
0.0.3*
1-2
49(10.7)
3-4
338(73.8)
1.9
1.1-3.7
0.003*
≥5
71(15.5)
2.8
1.1-7.2
0.031*
Less than 160 cm
187(40.8)
160 cm and more
271(59.2)
2.4
1.3-4.5
0.04*
<80 kg
200(43.7)
80-89 kg
133(29.1)
2.4
1.2-4.8
0.02*
≥90 kg
125(27.2)
2.8
1.3-5.9
0.0009*
Male
203(44.3)
Female
255(55.7)
0.8
0.6-0.9
0.014*
Poor
236(51.5)
Richer/middle
222(48.5)
0.5
0.1-0.7
<0.001**
Single
129(28.2)
Married/cohabited
263(57.4)
0.2
1.7-2.9
<0.001**
Widowed/separated/divorced
66(14.4)
0.1
0.1-0.2
<0.001**
Wanted then
290(63.3)
Wanted later
114(24.9)
1.8
0.8-1.3
0.673
Wanted no more
54(11.8)
1.1
0.8-1.5
0.405
Both want same
279(61)
Husband wants more
49(10.8)
0.8
0.6-1.1
0.211
Husband wants fewer
92(20.1)
1.1
0.8-1.4
0.610
Unaware
37(8.1)
0.99
0.8-1.2
0.956
Household
16(3.5)
Public hospitals
176(38.4)
1.3
0.3-5.8
0.741
Health center
257(56.1)
0.3
0.2-0.6
<0.001**
Privates health facilities
9(2)
0.3
0.2-0.6
<0.001**
15-19
12(2.6)
20-34
342(74.7)
2.7
1.5-4.9
<0.001**
35-49
104(22.7)
14.6
7.9-27.1
<0.001**
Less than 6
297(64.8)
6 members and more
161(35.2)
0.5
0.4-0.6
<0.001**
Yes
14(3)
No
444(97)
0.3
0.1-0.6
0.003*
No
57(12.5)
Yes
401(87.5)
0.3
0.2-0.7
0.003*
Male
351(76.6)
Female
107(23.4)
1.2
0.7-1.02
0.074
Not anemic
387(84.4)
Anemic
71(15.6)
4.7
2.5-9.2
<0.001**
Illiterate
69(15.1)
Post-primary/vocational
335(73.1)
0.5
0.3-1.3
0.105
Secondary and above
54(11.8)
0.3
0.1-0.9
0.036*
≥ 4 ANC visits
158(34.5)
No and less than 4 ANC visit
300(65.5)
1.5
1.2-1.9
<0.001*
No
49(10.7)
Yes
409(89.3)
0.3
0.1-0.2
<0.001*
No
76(16.6)
1
Yes
382(83.4)
0.8
0.6-1.1
0.193
No
198(43.3)
Yes
260(56.7)
0.87
0.1-1.1
0.130
Yes
13(2.8)
No
445(97.2)
1.04
0.5-2.1
0.905
Yes
371(81.1)
No
87(18.9)
1.1
0.8-1.5
0.0054*
No
95(20.8)
Yes
363(79.2)
0.4
.12-1.02
0.001**
No
395(86.3)
Yes
63(13.7)
2
1.4-2.8
<0.001**
No
453(98.8)
Yes
5(1.2)
1.1
0.4-3
0.871
No
449(98.1)
Yes
9(1.9)
4.1
1.7-10.2
0.002*
Yes
252(55)
No
206(45)
6
3.5-10.7
<0.001**
No
14(3.1)
Yes
444(96.9)
0.5
0.3-0.9
0.02*
No
76(16.5)
Yes, no drug taken
382(83.5)
0.5
0.4-0.7
<0.001**
Multiple logistic regression analyses indicated that ANC check-ups are the risk factor of LBW among the pregnant women. Mother attending fewer than four ANC visits are almost three-times more likely to give birth to LBW children [aOR=2.8; 95%CI (1.5–5.4), p=.002] when compared with mothers attending four or more ANC visits. Besides, newborns who were delivered at the health center [aOR=0.3; 95%CI (0.2–0.7), p=.002] and private health institutions [aOR=0.3; 95%CI (0.2–0.6), p<0.001] were less likely to weigh less than 2.5 kg than who were delivered in their households. The findings demonstrated that pregnant women who were not provided Coartem for malaria treatment [aOR=0.6; 95%CI (0.4–0.8), p<0.001] or who received other malaria drugs [aOR=4.1;95CI (1.7–10), p=0.02] were more likely to have LBW newborns. The pregnant women who attended the ANC visits at the health center [aOR=0.5; 95%CI (0.3–0.9), p=0.02] were less likely to have newborns with less than 2.5 kg. For marital status, married and cohabiting pregnant women were 1.86-times at greater risk to have LBW children [aOR=1.9; 95%CI (1.3–2.8), p=0.002] compared with single pregnant women. Mothers who were widowed, divorced and separated from their husbands were more likely to have LBW children compared with the women who were single during pregnancy. The results indicated that the widowed, separated and divorced pregnant women had 1.7-times greater risk of having LBW babies [aOR=1.7; 95%CI (1.1–2.5), p=0.015] than women who were single during pregnancy. Results found that being provided maternal iron and folic acid supplementation during pregnancy [aOR=0.5, 95%CI (0.3–0.9), p=0.015], not being given nutrients during pregnancy [aOR=2.5, 95%CI (2-8.4), p<0.001], being told about maternal complications during pregnancy [aOR=0.7, 95%CI (0.5–1), p=0.05], pregnant women with anemia [aOR=3.5, 95%CI (1.5–9), p<0.001] were positively associated with LBW. Through the number of the pregnant women who smoked during pregnancy, it was found that birth weight is significantly associated with smoking, as pregnant women who did not smoke were less likely [aOR=0.3; 95%CI (0.1–0.6), p=0.002] to deliver LBW babies (
Characteristics
Low birth weight
Adjusted odds ratio
Percent
95% CI
Urban
16.4
Rural
83.6
1.1
0.7-1.6
0.008*
Illiterate
15.1
Primary/vocational
73.1
1.01
0.7-1.5
<0.001**
Secondary/higher
11.8
0.99
0.6-1.8
<0.001**
15-19
2.6
20-34
74.7
0.8
0.4-1.5
0.428
35-49
22.7
0.8
0.4-1.5
0.467
Yes
89.3
No
10.7
1.3
0.8-2.1
0.037*
≤18.5 kg/m
2
80.2
18.5-25.9kg/m
2
13.1
0.9
0.4-2.3
0.008*
≥25kg/m
2
6.7
0.5
0.2-1.1
0.005*
Less than 160cm
40.8
160cm and more
59.2
0.5
0.2-1.2
0.11
Yes
3
No
97
0.3
0.1-0.6
0.002*
<80kg
43.7
80-89kg
29.1
0.4
0.1-1.1
0.003*
≥90kg
27.2
1.7
0.8-3.5
0.03*
4 ANC and more
34.5
No and less than ANC
65.5
2.8
1.5-5.4
0.002*
1-2
10.7
3-4
73.8
0.5
0.2-1.1
0.2
≥5
15.5
0.7
0.4-1.4
0.041
Less than 6
64.8
6 members and more
35.2
1.02
0.8-1.4
0.918
Poor
51.5
Middle/rich
48.5
0.9
0.6-1.4
0.728
Not anemic
84.4
Anemic
15.6
3.5
1.5-8.6
<.001*
Single
15.5
Married/cohabited
75.5
1.9
1.3-2.8
0.002*
Widowed/separated/divorced
9.0
1.6
1.1-2.5
0.015*
No
86.3
Yes
13.7
0.6
0.4-0.8
<0.001*
No
16.5
Yes, no drug taken
83.5
0.3
0.1-0.8
0.018*
Yes
55
No
45
2.5
2-8.4
<0.001*
Household
3.5
Public hospitals
38.4
1.03
0.2-4.8
0.969
Health center
56.1
0.3
0.2-0.7
0.002*
Privates
2
0.3
0.2-0.6
<0.001*
Male
44.3
1
Female
55.7
0.8
0.62-1.16
0.293
No
15.2
Yes
84.8
0.3
0.8-2
0.337
No
3.2
Yes
96.8
1.9
0.9-4.1
0.109
No
79.2
Yes
20.8
0.5
0.3-0.9
0.015*
Yes
81.1
No
18.9
3.3
1.5-6.6
0.003*
No
12.5
Yes
87.5
0.7
0.5-1
0.05*
Male
76.6
1
Female
23.4
1.1
0.8-1.6
0.519
This study revealed that LBW remains a public health burden at the national level and it remains higher in Rwanda. The results found that the prevalence of LBW and macrosomia was 5.8% and 17.6%, respectively; however, the newborns weighing more than 2.5kg were 94.2%. These results were coincided with the previous studies that documented an improvement of ANC services contributing to birth weight of the newborns.
We observed that pregnant women who attended four and more ANC visits had less risk of having LBW children than those who attended fewer than four recommended ANC visits. This finding is consistent with previous data that indicated that the more pregnant women attend ANC visits, especially more than four, the more their children do not have LBW.
Newborns whose mothers were had normal BMI (18.5–24.9 kg/m
2) and mothers who were overweight (or obese;) were less likely to have new-born with LBW when compared to those mothers who were underweight. This result is consistent with the earlier research carried out in Uganda.
Maternal anemia was identified as a risk factor, where we found that pregnant women with anemia had 3.5- times greater odds of delivering a newborn who weighed less than 2.5 kg than those who are not anemic. This result is in line with the prior studies conducted in Nigeria.
The present research has numerous prominent strengths. The first strength is that the RDHS 2014/2015 used the validated and standardized tools for interviewing the eligible participants. Second, the research data about birth weight that we used were obviously verified through records and recall bias was prevented. However, several limitations also warrant discussion. First, it was limited to a study design that did not actually explore for modifiable factors of ANC visits, such as HIV status of pregnant women, maternal gestational age, prenatal depression, receiving the supplementary vitamins (like vitamin A) during the pregnant period, maternal weight gain during pregnancy, eclampsia, gestational diabetes, high blood glucose level during pregnancy, antiretroviral (ART) for HIV-positive women and reducing transmission of HIV from pregnant mother to child. Second, birth weight data was available for only babies whose weight was measured at birth. This limited us for estimating the real prevalence. Third, the selection bias resulted in the underestimation of the association between ANC and birth weight. This was because not all babies’ weight was measured. The other limitation was that the qualitative aspects data from the participants was not included for exploring some factors and to triangulate the findings of the quantitative methods used. Additionally, as the methods used for measuring birth weight were not validated by the survey team, the misclassification could occur in this research. As we do not know the exact timing of the birth weight measurement, this causes misclassification.
In conclusion, this study found several risk factors of LBW in Rwanda that remains a national public health concern. However, ANC services for pregnant women are a fundamental intervention for reducing LBW. This integral part of primary health care, ANC services, is the population-based intervention that reduces the risk to deliver the newborn with LBW. Therefore, there is a need of a multifaceted approach for addressing the factors of LBW through reinforcing ANC coverage and quality of ANC services for pregnant women. Information on anthropometric measurement and increased awareness of the importance of regular ANC visits is also desirable. Attending four or more ANC visits is a step toward improving maternal health by providing maximum required packages and this strategy reduces the risk to LBW. The policy makers and researchers should prioritize maternal education and families with low socio-economic status for preventing LBW in Rwanda.
We recommend further research be conducted on the risk factors of macrosomia in Rwanda. Additionally, further study to explore the barriers to access ANC visits effectively for pregnant women from the rural settings is recommended. In the meantime, pregnant women in Rwanda are required to attend ANC visits appropriately and regularly for benefiting from the required packages that increase the probability to attenuate the LBW among the newborns. We recommend to measure birth weight immediately after birth for reducing the recall bias and misclassification.
Underlying data for ‘Regular antenatal care visits were associated with low risk of low birth weight among newborn in Rwanda: Evidence from the 2014/2015 Rwanda Demographic Health Survey (RDHS) Data was owned by the DHS program that can be obtained from
The electronic data is available from the DHS program under its terms of use. Before downloading the data, the main author of this study registered as DHS user for reasons laid out on the DHS program website and dataset access was only granted for legitimate purpose of this research.
EB conceptualized the study, did study design, formal analysis, wrote the protocol, requested the permission from the DHS website, drafted the manuscript and coordinated the study. SH contributed to data analysis, data curation and methodology. DR substantially contributed to the conceptualization. He also wrote the original draft preparation. He revised and reviewed the manuscript, and searched the relevant journal to which the study is submitted. HE reviewed and edited the study. All investigators approved the final manuscript. They also agreed to take responsibility and be accountable for the content of the manuscript. All of them agreed on all versions of the manuscript before submitting it in the international journal. They also agreed on the final version accepted for publication.
The present study was exempt from searching the ethical approval because the RDHS 2014/15 obtained the ethical approval from the Institutional Review Board (IRB) of the Rwanda National Ethics Committee (RNEC).
We are thankful to DHS program for providing for us the permission to use the dataset. We sincerely acknowledge the substantial help of RDHS for provision of the datasets.
This is an important domain and the paper reiterates the importance of antenatal care. However, this a rather simplistic view of a complex issue. Few points to consider:
The focus of the manuscript is on the number of ANC visits and not on the quality, content, examination, investigations, ultrasound, or respectful care, ability to identify/manage or refer high risk pregnancies, etc. The underlying assumption is that these are optimum at the the ANC sources. In that case, information on the same needs to be provided. Additionally, just the number of ANC visits is not enough, gestational age when the pregnant women was first registered, the timeliness of the ANC visits going by the 4 ANC norm, that is, one in the first trimester, 1 in the second trimester and 2 in the third trimester, are equally important. The ANC standard needs mention, there are women with 7 ANCs. Is the 2016 WHO ANC guideline being implemented at the study site? In that case is the rationale of 4 ANC as a cut-off based on minimum ANC visits? Need clarity. Specific issues: How were the 8004 women selected? It is mentioned that that women who had documented birth weight were interviewed. The sampling method says 2 stage cluster sampling and random selection. In that case the selection of women seems purposive, this needs clarity. This is a retrospective data collection, where women with youngest child less than 5 years were interviewed. It will be important to mention that all records on birth weight, number of ANC visits, measurement of BP, administration of antimalarial drug, height, weight and BMI, etc were available. Recall bias cannot be ruled out unless good documentation was available. At which stage was BMI measured? Pre-pregnancy or early first trimester? This will be important to document. Gestational weight gain is an essential component of ANC, this is not specified. It is not clear why BP measurement and antimalarials are considered as confounders. Tables do not have N (total number, denominators). Table 1 needs explanation. The sample size was 8004 women but in table 1, the numbers do not add up to 8004. it varies with each variable. There is no information on the number of births. It would be informative to know about preterms, SGA, AGA as well. The information on availability of birth weight is a little confusing. 92% reported birth weight, were these documented on discharge reports or verbally reported. Additionally, the low birth weight does not seem to be a major issue, with only 5.8% low birth weight while 18% macrosomia. Some information would be useful to present. 99% women attended ANC clinic but 44% had 4 ANCs. A qualitative component would have been helpful to understand the barriers to low utilization. The discussion section needs strengthening, it is repetition of the previous section. Some of the findings could have been analyzed, for eg., explore further how was home delivery associated with LBW. The places of ANC, pros and cons, etc. have not been discussed. Typographical error, table 2, 7th row, last column. 0.0.3. The authors need to match the numbers in the tables and text.
Is the work clearly and accurately presented and does it cite the current literature?
Yes
If applicable, is the statistical analysis and its interpretation appropriate?
Partly
Are all the source data underlying the results available to ensure full reproducibility?
Yes
Is the study design appropriate and is the work technically sound?
Partly
Are the conclusions drawn adequately supported by the results?
Partly
Are sufficient details of methods and analysis provided to allow replication by others?
Partly
Reviewer Expertise:
Maternal and child health
I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above.
This is an important domain, and the paper reiterates the importance of antenatal care. However, this a rather simplistic view of a complex issue. Few points to consider:
The focus of the manuscript is on the number of ANC visits and not on the quality, content, examination, investigations, ultrasound, or respectful care, ability to identify/manage or refer high risk pregnancies, etc. The underlying assumption is that these are optimum at the ANC sources. In that case, information on the same needs to be provided.
Additionally, just the number of ANC visits is not enough, gestational age when the pregnant women was first registered, the timeliness of the ANC visits going by the 4 ANC norm, that is, one in the first trimester, 1 in the second trimester and 2 in the third trimester, are equally important.
The ANC standard needs mention, there are women with 7 ANCs. Is the 2016 WHO ANC guideline being implemented at the study site? In that case is the rationale of 4 ANC as a cut-off based on minimum ANC visits? Need clarity.
Specific issues: How were the 8004 women selected? It is mentioned that that women who had documented birth weight were interviewed. The sampling method says 2 stage cluster sampling and random selection. In that case the selection of women seems purposive, this needs clarity.
This is a retrospective data collection, where women with youngest child less than 5 years were interviewed. It will be important to mention that all records on birth weight, number of ANC visits, measurement of BP, administration of antimalarial drug, height, weight and BMI, etc were available. Recall bias cannot be ruled out unless good documentation was available.
At which stage was BMI measured? Pre-pregnancy or early first trimester? This will be important to document.
Gestational weight gain is an essential component of ANC, this is not specified.
It is not clear why BP measurement and antimalarials are considered as confounders.
Tables do not have N (total number, denominators). Table 1 needs explanation. The sample size was 8004 women but in table 1, the numbers do not add up to 8004. it varies with each variable. There is no information on the number of births. It would be informative to know about preterms, SGA, AGA as well.
The information on availability of birth weight is a little confusing. 92% reported birth weight, were these documented on discharge reports or verbally reported. Additionally, the low birth weight does not seem to be a major issue, with only 5.8% low birth weight while 18% macrosomia.
Some information would be useful to present. 99% women attended ANC clinic but 44% had 4 ANCs. A qualitative component would have been helpful to understand the barriers to low utilization.
The discussion section needs strengthening, it is repetition of the previous section. Some of the findings could have been analyzed, for e.g., explore further how was home delivery associated with LBW. The places of ANC, pros and cons, etc. have not been discussed.
Typographical error, table 2, 7th row, last column. 0.0.3.
The authors need to match the numbers in the tables and text.
Thank you very much.
The article presents the prevalence of LBW and the risk factors for the same in Rwanda using the RDHS 2014/15 data.
The manuscript needs attention in some sections:
1. Methods
1.1 Macrosomia definitions should be mentioned
2. Results
2.1 The following statements need review and clarification.
"For marital status, married and cohabiting pregnant women were 1.86-times at greater risk to have LBW children [aOR=1.9; 95%CI (1.3–2.8), p=0.002] compared with single pregnant women."
"The results indicated that the widowed, separated and divorced pregnant women had 1.7-times greater risk of having LBW babies [aOR=1.7; 95%CI (1.1–2.5), p=0.015] than women who were single during pregnancy."
The two statements are in conflict. Please check.
2.2. The statement "Results found that being provided maternal iron and folic acid supplementation during pregnancy [aOR=0.5, 95%CI (0.3–0.9), p=0.015], not being given nutrients during pregnancy [aOR=2.5, 95%CI (2-8.4), p<0.001], being told about maternal complications during pregnancy [aOR=0.7...."
How was the nutrient given assessed?
3. Discussion
3.1. Please check the statements and discuss
"They revealed that marital status increased the odds of LBW. It was found that pregnant women who were married or living with the cohabitants were 1.9-times likely to have LBW compared with pregnant women who were single. They also revealed that the pregnant women who divorced or separated had 1.7-greater risks to have new-borns who weigh less than 2.5 kg."
This statement needs to be examined carefully, whether the factor responsible was crowding, low SES and undernutrition or hunger.
4. Limitations
4.1 The limitations should mention the qualitative nature of the risk factors captured in the RDHS, like iron intake and duration, nutrition intake, maternal anemia and malnutrition status, which influence the birth weight.
Is the work clearly and accurately presented and does it cite the current literature?
Yes
If applicable, is the statistical analysis and its interpretation appropriate?
Yes
Are all the source data underlying the results available to ensure full reproducibility?
Partly
Is the study design appropriate and is the work technically sound?
Yes
Are the conclusions drawn adequately supported by the results?
Partly
Are sufficient details of methods and analysis provided to allow replication by others?
Yes
Reviewer Expertise:
Child health, public health
I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above.
Reviewer 2
The article presents the prevalence of LBW and the risk factors for the same in Rwanda using the RDHS 2014/15 data.
The manuscript needs attention in some sections:
1. Methods
1.1 Macrosomia definitions should be mentioned
2. Results
2.1 The following statements need review and clarification.
"For marital status, married and cohabiting pregnant women were 1.86-times at greater risk to have LBW children [aOR=1.9; 95%CI (1.3–2.8), p=0.002] compared with single pregnant women."
"The results indicated that the widowed, separated and divorced pregnant women had 1.7-times greater risk of having LBW babies [aOR=1.7; 95%CI (1.1–2.5), p=0.015] than women who were single during pregnancy."
The two statements are in conflict. Please check.
2.2. The statement "Results found that being provided maternal iron and folic acid supplementation during pregnancy [aOR=0.5, 95%CI (0.3–0.9), p=0.015], not being given nutrients during pregnancy [aOR=2.5, 95%CI (2-8.4), p<0.001], being told about maternal complications during pregnancy [aOR=0.7...."
How was the nutrient given assessed?
3. Discussion
3.1. Please check the statements and discuss
"They revealed that marital status increased the odds of LBW. It was found that pregnant women who were married or living with the cohabitants were 1.9-times likely to have LBW compared with pregnant women who were single. They also revealed that the pregnant women who divorced or separated had 1.7-greater risks to have new-borns who weigh less than 2.5 kg."
This statement needs to be examined carefully, whether the factor responsible was crowding, low SES and undernutrition or hunger.
4. Limitations
4.1 The limitations should mention the qualitative nature of the risk factors captured in the RDHS, like iron intake and duration, nutrition intake, maternal anemia and malnutrition status, which influence the birth weight.
The paper addressed a very important issue of public health. The findings of the paper are likely to contribute in literature of the impact of antenatal care on birth weight. However, I have some observations, which are given below.
In the Introduction section, page 3, the authors stated that WHO recommended four or more ANC visits during pregnancy, which is a dated recommendation. Perhaps, the authors are referencing 2001 WHO recommended schedule of 4 ANC visits (Villar
The authors defined the main explanatory variable (no or less than 4 ANC and ≥ 4 ANC) based on the old schedule of ANC. Considering the low average frequency of ANC visits in Rwanda, I am not claiming that the analysis is wrong, but not mentioning the latest development is a clear oversight. The authors should discuss the compliance of 8 or more ANC visits in Rwanda. Under sampling design, page 4, the authors wrote: ……. “current birth weights were not available for the most children”, which contradicts the last line of the paragraph stating that “It was found that 92% of newborns had a birth weight reported while 8% did not.” The authors should provide clear information about the total number of births considered in the study, of whom birth weights were available for how many or what proportion of births. Among the children with birth weights, what proportion of birth weights was obtained from mothers' recall and what proportion from written information. What was meant by written information? Is it birth certificates or health cards? The most important information which is missing in this study is the total sample size of the study population. In one place, the authors mentioned about 8,004 mothers of reproductive age, but the distribution of the mothers provided in column 2 of Table 1 does not reflect that. What are these numbers in column 2 of Table 1 and why there is a wide variation in number across the variables? In page 6, under the Results section of Multiple logistic regression analysis: There are a lot of mistakes. Most of the aORs and the 95%CIs given within parenthesis do not correspond with the results presented in Table 3. The discussion section has been written very poorly, as it is mostly a repetition of the description of the findings without providing any explanations or possible implications of their findings. To validate their results, the authors just wrote “the results are consistent or similar or corroborate with findings of other study” without providing any numerical evidence how their findings are consistent with other studies. There is a methodological problem in the application of multiple logistic regression analysis to the real data considered in this study. One of the basic assumptions of the regression model is that the explanatory variables are independent. However, in this study, all the selected explanatory variables are not independent. For example, maternal height and weight are linearly dependent, and they are also related to body mass index (BMI) because BMI = weight/height
2. Violation of the assumption of independence creates a serious problem in statistical analysis, which is known as multicollinearity problem, resulting in biased results. While applying regression model, the researchers should be careful about multicollinerity problem. The authors did not provide any information about the goodness of fit of the model and adequacy of the fitted model. The author should redo the multiple regression analysis by removing the suspected inter-correlated variables.
Is the work clearly and accurately presented and does it cite the current literature?
Yes
If applicable, is the statistical analysis and its interpretation appropriate?
Partly
Are all the source data underlying the results available to ensure full reproducibility?
Yes
Is the study design appropriate and is the work technically sound?
Partly
Are the conclusions drawn adequately supported by the results?
Partly
Are sufficient details of methods and analysis provided to allow replication by others?
Yes
Reviewer Expertise:
NA
I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above.
The paper addressed a very important issue of public health. The findings of the paper are likely to contribute in literature of the impact of antenatal care on birth weight. However, I have some observations, which are given below.
In the Introduction section, page 3, the authors stated that WHO recommended four or more ANC visits during pregnancy, which is a dated recommendation. Perhaps, the authors are referencing 2001 WHO recommended schedule of 4 ANC visits (Villar et al., 2001). However, in 2016 WHO revised its recommendation and prescribed 8 or more visit schedules (see WHO (2016). WHO recommendations on antenatal care for a positive pregnancy experience.
The authors defined the main explanatory variable (no or less than 4 ANC and ≥ 4 ANC) based on the old schedule of ANC. Considering the low average frequency of ANC visits in Rwanda, I am not claiming that the analysis is wrong, but not mentioning the latest development is a clear oversight. The authors should discuss the compliance of 8 or more ANC visits in Rwanda.
1. Sserwanja, Q., Nuwabaine, L., Gatasi, G.
2. Rurangirwa, A.A., Mogren, I., Ntaganira, J.
Under sampling design, page 4, the authors wrote: ……. “current birth weights were not available for the most children”, which contradicts the last line of the paragraph stating that “It was found that 92% of newborns had a birth weight reported while 8% did not.”
The authors should provide clear information about the total number of births considered in the study, of whom birth weights were available for how many or what proportion of births. Among the children with birth weights, what proportion of birth weights was obtained from mothers' recall and what proportion from written information. What was meant by written information? Is it birth certificates or health cards?
The most important information, which is missing in this study, is the total sample size of the study population. In one place, the authors mentioned about 8,004 mothers of reproductive age, but the distribution of the mothers provided in column 2 of Table 1 does not reflect that. What are these numbers in column 2 of Table 1 and why there is a wide variation in number across the variables?
Responses: Thank you very much for this observation about mismatching of the totals for the table 1. We included the corrected table. In addition to that, the sample size was 7381 women who provided the weight of their babies. They were recruited from 8004 women who delivered and 30058 individuals for the participants of this dataset in which we used.
In page 6, under the Results section of Multiple logistic regression analysis: There are a lot of mistakes. Most of the aORs and the 95%CIs given within parenthesis do not correspond with the results presented in Table 3.
The discussion section has been written very poorly, as it is mostly a repetition of the description of the findings without providing any explanations or possible implications of their findings. To validate their results, the authors just wrote “the results are consistent or similar or corroborate with findings of other study” without providing any numerical evidence how their findings are consistent with other studies.
There is a methodological problem in the application of multiple logistic regression analysis to the real data considered in this study. One of the basic assumptions of the regression model is that the explanatory variables are independent. However, in this study, all the selected explanatory variables are not independent. For example, maternal height and weight are linearly dependent, and they are also related to body mass index (BMI) because BMI = weight/height2. Violation of the assumption of independence creates a serious problem in statistical analysis, which is known as multicollinearity problem, resulting in biased results. While applying regression model, the researchers should be careful about multicollinerity problem. The authors did not provide any information about the goodness of fit of the model and adequacy of the fitted model. The author should redo the multiple regression analysis by removing the suspected inter-correlated variables.