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. 2021 Feb 9;16(2):e0246694. doi: 10.1371/journal.pone.0246694

Birth weight, growth, nutritional status and mortality of infants from Lambaréné and Fougamou in Gabon in their first year of life

Rella Zoleko-Manego 1,2,3, Johannes Mischlinger 3, Jean Claude Dejon-Agobé 1,2,4, Arti Basra 1, J Rodolphe Mackanga 1, Daisy Akerey Diop 1, Ayola Akim Adegnika 1,2,5,6, Selidji T Agnandji 1,2, Bertrand Lell 1,7, Peter G Kremsner 1,2,5,6, Pierre Blaise Matsiegui 8, Raquel González 9,10,11, Clara Menendez 9,10, Michael Ramharter 1,3, Ghyslain Mombo-Ngoma 1,2,3,*
Editor: Samson Gebremedhin12
PMCID: PMC7872243  PMID: 33561169

Abstract

Background

Malnutrition and low birth weight (LBW) are two common causes of morbidity and mortality among children in sub-Saharan Africa. Both malnutrition and LBW affect early childhood development with long term consequences that may vary in their degree depending on the geographical setting. This study evaluates growth, nutritional status and mortality of infants from Lambaréné and Fougamou in Gabon from a birth cohort of a malaria in pregnancy clinical trial (NCT00811421).

Method

A prospective longitudinal birth cohort conducted between 2009 and 2012, included infants that were followed up from birth until their first-year anniversary. The exposure of interest was low birth weight and the outcomes explored were growth represented by weight gain, the nutritional status including stunting, wasting and underweight, and the mortality. Scheduled follow-up visits were at one, nine and 12 months of age. Logistic regression was used to assess the association between low birth weight and growth and nutritional outcomes, and cox regression was used for mortality.

Result

A total of 907 live-born infants were included in the analysis. The prevalence of LBW was 13% (115). At one month of life, out of 743 infants 10% and 4% presented with stunting and underweight, respectively, while these proportions increased at 12 months of life to 17% and 21%, respectively, out of 530 infants. The proportion of infants with wasting remained constant at 7% throughout the follow-up period. Stunting and underweight were associated with LBW, adjusted odds ratio (aOR): 2.6, 95% confidence interval (95%CI): 1.4–4.9 and aOR: 4.5, 95%CI: 2.5–8.1, respectively. Preterm birth was associated with stunting, aOR: 2.7, 95%CI: 1.2–6.3 and underweight, aOR: 5.4, 95%CI: 1.7–16.1 at one month of life. Infants with LBW were at higher hazard of death during the first year of life, adjusted hazard ratio 4.6, 95%CI: 1.2–17.0.

Conclusion

Low birthweight infants in Gabon are at higher risks of growth and nutritional deficits and mortality during the first year of life. Tailored interventions aiming at preventing adverse pregnancy outcomes including LBW, early detection and appropriate management of growth, and nutritional deficits in infants are necessary in Gabon.

Introduction

Malnutrition is a public health concern particularly in economically disadvantaged regions of the word. According to the 2017 Food and Agriculture Organization’s report, about 821 million people suffer from various forms of malnutrition in the world [1]. Asia and Africa harbor the highest numbers of individuals suffering from malnutrition with children being the most affected [2]. In this particular population, malnutrition is reported as one of the most common causes of morbidity and mortality, mostly affecting early childhood development. Long term consequences of malnutrition include increased risk of diet-related non-communicable diseases such as diabetes and hypertension [3–5]. However, the impact of malnutrition may vary depending—amongst many factors—on the socioeconomic and geographical settings, the burden of infectious diseases, and the availability and capacity of the health care system in respective regions [6–9].

Stunting, wasting and underweight are three established indicators for the nutritional status of infants and children, indicating their overall health and well-being [10, 11]. Stunting, expressed in height-for-age, is reported to be a strong marker of unhealthy growth [12]. It is the most prevalent form of child malnutrition. It is a slow, cumulative process developing over a long period, it is the primary manifestation of malnutrition in early childhood. Once established, stunting and its effects typically become permanent [13]. Stunting is an appropriate indicator for chronic malnutrition. Wasting, using weight-for-height and underweight, using weight-for-age are valuable indicators for acute malnutrition with potential for reversal. Underweight is most commonly used as a nutritional indicator due to difficulties in measuring height in health programs implemented in low- and middle-income countries [14]. In this context and despite its limitation, weight alone appears to be the indicator most often used by parents and primary health care personnel to quickly estimate the growth in infancy [15].

While stunting, wasting and underweight clearly refer to malnutrition during childhood, low birth weight (LBW) may be regarded as an indicator for malnutrition during pregnancy. LBW is defined as birth weight less than 2500 g and is recognized as an indicator of preterm birth or intrauterine growth retardation. Children born with LBW remain at risk of malnutrition [16, 17] and are therefore of special interest for growth monitoring. Furthermore, the association between LBW and malnutrition and the subsequent increased mortality constitute the reason for monitoring child growth during the first 1000 days of life [18, 19]. Compared to those born with normal weight, the World Health Organization (WHO) estimates an increase of 2-to-8 fold the death rate among children born with LBW during their first year of life [20]. The impact of LBW on nutritional indices and survival may however vary according to the setting in which the child lives [18, 21, 22].

There is a lack of data on infant and child growth for many countries in Africa, particularly for the Central African region where the prevalence of LBW is high [23]. Most of the previous studies have focused on the determinants of LBW with the aim to identify modifiable factors while the outcome of infants after birth was rarely investigated. Moreover, there is a lack of prospective studies in Africa focusing on the nutritional status of infants in general and infants born with LBW in particular. Taking advantage of a clinical trial conducted in Gabon on pregnant women and their offspring, this analysis evaluates the nutritional status, growth and mortality of infants in a prospective birth cohort during their first year of life based on their birth weight. This study therefore provides important information about the impact of LBW on nutritional deficits in the first year of life and survival of infants in a semi-urban region of central Gabon.

Methods

Study site and population

This study was conducted in Lambaréné and Fougamou, two semi-urban areas located in the central region of Gabon, central Africa. Study participants were infants born from HIV-negative pregnant women included in a clinical trial assessing intermittent preventive treatment of malaria during pregnancy (Malaria in Pregnancy Preventive Alternative Drugs [MiPPAD]; clinical trials identifier: NCT00811421 [24]). Live-born infants from singleton pregnancies with weight reported at birth were included in this analysis.

Study design

This is a birth cohort study of infants born in the MiPPAD trial. Details of recruitment and data collection procedures have been described elsewhere [24]. Briefly, HIV-uninfected pregnant women were recruited before their third trimester. Eligible pregnant women were randomly allocated to receive two doses one month apart of intermittent preventive treatment during pregnancy (IPTp) with either sulfadoxine/pyrimethamine or mefloquine. Enrolled pregnant women were then followed up until one month after delivery. At birth, demographic data and anthropometric parameters of the newborn were recorded and a physical examination was performed. Infants were followed up until their first anniversary with scheduled visits at one, nine and 12 months of age at which anthropometric measures were recorded including weight and height. When the visits at the health facility were missed, home visits were organized whenever possible.

Study procedures and variables

The study was conducted from September 2009 to April 2012. Mother’s baseline characteristics were recorded at recruitment including maternal age and literacy. Maternal age was calculated from the date of birth recorded in a health booklet or by self-reported date of birth. Maternal age was categorized as following: adolescent, aged < 20 years; young adults, aged 20–35 years and older adults, aged > 35 years. Literacy of the mother was defined as the ability to read or write. Newborn delivery characteristics recorded included place of birth, gestational age, weight, height, infant sex and congenital abnormalities. For each included newborn, weight was captured within a few hours after birth using a weekly re-calibrated electronic pediatric weight scale. For those with no weight available at birth but in the first week of life in case of home deliveries weight was estimated using a linear regression model [24]. The height of the infant was measured in centimeters using a calibrated gauge with a fixed headrest and a movable footrest perpendicular to the surface of the table placed in contact with the infant’s feet for measurement in lying position. Gestational age was calculated using modified Ballard score at birth [25]. Prematurity was defined as a gestational age at birth less than 37 weeks. Z-score for Weight-for-age, weight-for-height and height-for-age were calculated using standard formula [26]. Height-for-age Z-score (HAZ, <-2 standard deviations below an international reference mean), weight-for-age Z-score (WAZ <-2 SD), and weight-for-height Z-score (WHZ <-2 SD) were used to define respectively stunting, underweight and wasting.

Statistical methods

Data were collected using a paper case report form and digitalized using OpenClinica software. Double-entry of data was performed to ensure the reliability of data. The clean database was extracted for statistical analysis. Stata IC/V.13.1 for Windows (StataCorpLp, College Station, Texas, USA) was used to perform the statistical analysis. Because a high proportion of infants were dropped from the subsequent visits at month 9 and month 12, a sensitivity analysis was performed that consisted on comparing baseline characteristics of infants attending each visit to explore whether any differences existed that could be associated with loss to follow up. The main exposure variable was LBW defined as weight less than 2500 g at birth. Weight was used to characterize an infant’s growth during a one-year period. During the analysis, two study groups were considered, LBW and normal birth weight (NBW) groups and the results presented accordingly. Categorical variables were summarized as counts and proportions and were compared using the chi square test while continuous variables were summarized by means and standard deviation (SD) and compared using the Z-test. Weight gain ratio was presented as the ratio of the weight of infants at the actual visit divided by the weight of the infants at the previous visit. Malnutrition determinants were assessed at different study time points considering birth weight categories (LBW vs NBW). Assessment of malnutrition at month 9 and month 12 were done only for participants present at the month 1 visit. The main study was designed as a randomized clinical trial with the assumption that the confounders will be distributed between the treatment arms and therefore not systematically recorded. Variables such as parity, trimester of first antenatal clinic visit, BMI and MUAC, and infectious diseases were collected from the mother and they have been controlled for in the analyses of the determinants of LBW. For the current analysis of the effect of LBW on growth, nutrition and mortality, the maternal variables retained to be controlled for are age and literacy as they are considered to potentially affect the way mothers provide care and follow nutrition instructions for their infants. The infant’s sex has been taken as a forced variable as sex and age are common confounding factors. Several variables including mother’s age and literacy, infant’s sex and prematurity are recognized as risk factors for malnutrition and infant death [10, 27]. Logistic regression was used for multivariate analysis of risk factors associated with malnutrition. Mortality was calculated as the number of deaths per 1000 live births. Time-to-event analysis was conducted using a Kaplan-Meier survival analysis with ‘death’ defined as an event of interest. Plots were created to visualize survival curves stratified by birth weight. Log rank test was used to compare the survival functions between participants born with LBW and those born with normal weight. Lost to follow-up participants were included in the analysis and censored at their last contact. Hazard of death was assessed by Cox proportional hazards model. Crude and adjusted hazard ratios and associated 95% confidence interval (95%CI) were generated. For each statistical analysis, the level of statistical significance was set at p-value less than 0.05.

Ethical consideration

The clinical trial was approved by the Comité d’Ethique Régional Indépendant de Lambaréné (CERIL) and the Ministry of Health in Gabon and was conducted in line with the Good Clinical Practice (GCP) principles of the International Conference on Harmonization and the Declaration of Helsinki.

Results

Study population characteristics

As depicted in Fig 1, a total of 983 live delivered newborns from the MIPPAD trial in Gabon were recorded. Thirty multiple gestations and 46 newborns with missing birth weight records were excluded from this analysis, giving a total of 907 infants included. Their characteristics are described in Table 1. Of the 907 live births, the prevalence of LBW was 12.7% (115). There were 50 (5.5%) preterm newborns and they endured the highest prevalence of LBW of 38% (19/50). There were more LBW infants from adolescent mothers 17.4% (50/287) than from mature adult mothers, 7.0% (5/71). The mean gestational age at birth was 40 weeks (SD: 2.0). During the follow-up, 765 (84.3%) attended the 1-month visit, 575 (63.4%) attended the 9-month visit, and 576 (63.5%) attended the 12-month visit including 64 infants that missed the 9-month visit (Fig 1). Taking into account the participants’ drop out, there were significantly more dropouts in the LBW group at the 9-month visit and at 12-month visit there were significantly more dropouts from the literate mothers group and from the younger mothers groups (S1 Table).

Fig 1. Flow of children in the study from birth until 12 months of age.

Fig 1

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Table 1. Distribution of Low birth weight according to maternal and newborn characteristics at delivery.

N Low Birth Weight Normal Birth Weight p-value
n (%) n (%)
Place of birth
Maternity 827 105 (12.7) 722 (87.3) 0.9
Home 80 10 (12.5) 70 (87.5)
Preterm birth*
Yes 50 19 (38.0) 31 (62) <0.001
No 832 89 (10.7) 743 (89.3)
Infant Sex*
Male 454 53 (11.7) 401 (88.3) 0.3
Female 442 60 (13.6) 382 (86.4)
Mother Literacy
Literacy 745 92 (12.4) 653 (87.6) 0.5
Illiteracy 162 23 (14.2) 139 (85.8)
Maternal age (year)
<20 287 50 (17.4) 237 (82.6) 0.009
20–35 549 60 (10.9) 489 (89.1)
>35 71 5 (7.0) 66 (93)
Congenital Abnormalities*
Present 22 2 (9.1) 20 (90.9) 0.6
Absent 879 110 (12.5) 769 (87.5)
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N: number, (): % percentage,

*missing data.

Growth or weight gain during the 12 months follow-up

As described in Table 2, the mean weight was 2994 g, 4272 g, 8276 g, and 9003 g at birth, 1, 9 and 12 months of age, respectively. The mean birth weight was significantly lower in the LBW group and the difference in mean weight remained as such during the entire follow-up period (Table 2). However, the weight gain ratios were similar in both groups, 1.4 versus 1.6 at one month, 1.9 versus 2.2 at nine months, and 1.1 versus 1.1 at 12 months for the normal birth weight group and the LBW group, respectively (Fig 2).

Table 2. Mean of weight at birth, 1, 9 and 12 month visits according to birth weight.

Normal birth weight Low birth weight Total P value
n Mean SD n Mean SD N Mean SD
Birth 792 3113 366 115 2172 353 907 2994 480 <0.0001
Month 1 674 4369 619 91 3550 934 765 4272 719 <0.0001
Month 9 515 8328 1105 60 7828 1008 575 8276 1106 0.0004
Month 12 509 9058 1181 67 8587 1321 576 9003 1207 0.001
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SD: standard deviation, n: population.

Fig 2. Mean (SE) changes in weight at birth, 1, 9 and 12 months by birth weight.

Fig 2

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Abbreviations: M1: month one; M9: month nine; M12: month twelve, LBW: Low Birth Weight; NBW: Normal Birth Weight.

Malnutrition status at follow-up visits and impact of low birth weight

The prevalence of stunting was 9.7% (72/743; 95%CI: 8–12), 9.5% (50/524; 95%CI: 7–12) and 16.8% (89/530; 95%CI: 14–20) at 1, 9 and 12 months of age, respectively. As presented in Table 3, stunting was significantly more prevalent in infants with LBW from month 1 to month 12 compared to their normal birth weight counterpart. Preterm birth was found to be a factor associated with stunting at month 1 while being a female was associated with a significantly lower risks of stunting at 9 and 12 months of age (Table 3). The prevalence of wasting was 5.8% (43/743; 95%CI: 4–8), 8.2% (43/524; 95%CI: 6–11) and 7.0% (37/530; 95%CI: 5–10) at month 1, 9, and 12, respectively, and none of the preterm born infants was reported with wasting. Mother’s illiteracy was found to be associated with wasting at months 9 and 12. The prevalence of underweight was 4.0% (30/743; 95%CI: 3–6), 14.5% (76/524; 95%CI: 12–19) and 20.7% (110/530; 95%CI: 7–24) from months 1, 9 to 12, respectively. There was significantly more underweight observed among infants born small compared to their normal birth weight counterparts. Mother’s illiteracy was found to be a factor significantly associated with underweight at months 9 and 12, respectively, while male gender of infants was also an associated factor but at month 12 only (Table 3).

Table 3. Prevalence of stunting, wasting and underweight and univariate analysis of the risk factors.

N Stunting Wasting Underweight
n (%) p-value* n (%) p-value* n (%) p-value*
Month 1
LBW <0.0001 0.1 <0.001
NO 658 39 (5.9) 35 (5.3) 7 (1.0)
YES 85 33 (38.8) 8 (9.4) 23 (27.1)
Preterm birth ** 0.001 0.3 <0.001
NO 702 64 (9.1) 43 (6.1) 24 (3.4)
YES 40 10 (25.0) 0 8 (20.0)
Infant Sex 0.1 0.4 0.8
Male 380 43 (11.3) 20 (5.3) 16 (4.2)
Female 363 29 (8.1) 23 (6.3) 14 (3.9)
Maternal Illiteracy 0.4 0.2 0.8
NO 607 61 (10.1) 32 (5.3) 25 (4.1)
YES 136 11 (8.1) 11 (8.1) 5 (3.7)
Maternal age (year) 0.06 0.6 0.5
<20 240 32 (13.3) 16 (6.7) 11 (4.6)
20–35 442 36 (8.1) 26 (5.9) 18 (4.1)
>35 61 4 (6.6) 2 (3.2) 1 (1.6)
Month 9
LBW 0.06 0.004 0.01
NO 469 41 (8.7) 33 (7.0) 72 (13.2)
YES 55 9 (16.4) 10 (18.2) 14 (25.5)
Preterm birth 0.3 0.1 0.1
NO 497 46 (9.3) 42 (8.5) 75 (3.7)
YES 27 4 (14.8) 0 1 (3.7)
Infant sex 0.001 0.6 0.08
Male 262 36 (13.7) 20 (7.6) 45 (17.1)
Female 262 14 (5.3) 23 (8.8) 31 (11.8)
Maternal Illiteracy 0.6 0.006 0.04
NO 424 39 (9.2) 28 (6.6) 55 (13.0)
YES 100 11 (11.0) 15 (15.0) 21 (21.0)
Maternal age (year) 0.3 0.4 0.1
<20 156 19 (12.2) 9 (5.8) 24 (15.4)
20–35 316 28 (8.9) 29 (9.2) 49 (15.5)
>35 52 3 (5.8) 5 (9.6) 3 (5.8)
Month 12
LBW 0.004 0.1 0.001
NO 470 71 (15.1) 30 (6.4) 82 (17.5)
YES 60 18 (30.8) 7 (11.7) 28 (46.7)
Preterm birth 0.5 0.1 0.4
NO 498 85 (17.1) 37 (7.4) 105 (21.1)
YES 32 4 (12.5) 0 5 (15.6)
Infant Sex** <0.001 0.8 0.002
Male 266 67 (25.2) 17 (6.7) 70 (26.3)
Female 263 22 (8.4) 19 (7.2) 41 (15.6)
Maternal Illiteracy** 0.1 0.02 0.01
NO 421 66 (15.7) 24 (5.7) 78 (18.5)
YES 108 23 (21.3) 13 (12.0) 32 (30.5)
Maternal age (year) ** 0.6 0.5 0.5
<20 158 30 (19.0) 14 (8.7) 32 (20.2)
20–35 318 51 (16.0) 20 (6.3) 70 (22.3)
>35 53 8 (15.1) 3 (5.7) 8 (15.1)
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SD: standard deviation, N/n:total population, LBW: Low Birth Weight.

* chi square test.

** 1 missing data.

After adjusting for preterm birth, infant sex, maternal age and literacy, LBW remained an independent risk factor associated with higher odds of stunting and underweight with strong statistical evidence at month 1 and month 12 (adjusted OR (aOR) 10.3, 95%CI:5.9–17.9; aOR 33.1, 95%CI:12.2–83.2 and aOR 2.6, 95%CI:1.4–4.9; aOR 4.5, 95%CI:2.5–7.2; Table 4). Preterm birth was associated with stunting and underweight at month 1 (aOR 2.7, 95%CI:1.2–6.3; aOR 5.4, 95%CI:1.7–16.1).

Table 4. Assessment of the impact of birth weight and term of birth on stunting, wasting and underweight in infancy.

Stunting Wasting Underweight
OR [95%CI] aOR[95%CI] OR [95%CI] aOR[95%CI] OR [95%CI] aOR[95%CI]
Month 1
LBW
No 1 1 1 1 1 1
Yes 10.4 [5.6–17.8] 10.3 [5.9–17.9] 2.1 [0.9–4.5] 2.2 [0.9–4.7] 34.5 [14.2–83.6] 33.1 [12.2–83.2]
Preterm birth
No 1 1 1 1 1 1
Yes 3.6 [1.7–7.5] 2.7 [1.2–6.3] 0.4 [0.5–2.8] 0.3 [0.0–2.3] 7.0 [3.0–17.0] 5.3 [1.4–16.0]
Month 9
LBW
No 1 1 - 1 1
Yes 2.0 [0.9–4.5] 1.9 [0.9–4.3] - 2.2 [1.2–4.3] 2.2 [1.1–4.4]
Preterm birth
No 1 1 - 1 1
Yes 1.7 [0.6–5.1] 1.8 [0.6–5.7] - 0.2 [0.0–1.5] 0.2 [0.0–1.4]
Month 12
LBW
No 1 1 - 1 1
Yes 2.4 [1.3–4.4] 2.6 [1.4–4.9] - 4.1 [2.3–7.2] 4.5 [2.5–7.2]
Preterm birth
No 1 1 - 1 1
Yes 0.7 [0.2–2.0] 0.6 [0.2–2.2] - 0.7 [0.3–1.8] 0.5 [0.1–1.5]
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OR: Odds Ratio, aOR: adjusted Odds Ratio; 95%CI: 95% confidence interval, LBW: Low Birth Weight.

Adjusted for infant sex, maternal age and maternal literacy; there was no wasting at 9 and 12 months among preterm infants, so no estimates of OR could be made for these timepoints for wasting.

Evolution of stunting among study population

The overall HAZ means observed in the study population were -0.60 (95%CI: -0.7 to -0.5), -0.61 (95%CI: -0.5 to -0.4) and -0.87 (95%CI: -0.9 to -0.8) at months 1, 9 and 12, respectively. As shown in Fig 3, the mean HAZ remained negative in both groups over their first year of life. Among infants born with LBW, we observed an increase in HAZ from -1.68 (95%CI: -1.9 to -1.4) at month 1 to -0.97 (95%CI: -1.2 to -0.7) at month 9, followed by a decrease from month 9 of age to -1.29 (95%CI: -1.6 to -1.0) at 12 months of age. Among their counterpart born with normal weight, a slow decrease of the HAZ curve was observed from month 1 of life from -0.46 (95%CI: -0.5 to -0.4) to -0.57 (95%CI: -0.7 to -0.5) at 9 months and to -0.81 (95%CI: -0.9 to -0.7) at 12 months.

Fig 3. Mean (SE) height-for-age Z-score evolution from 1 to 12 months by birth weight.

Fig 3

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Abbreviations: M1: month one, M9: month nine; M12: month twelve; LBW: low birth weight; NBW: normal birth weight.

Mortality during the first year of life

A total of 25 deaths were recorded among the 907 infants included in the study, giving an infant mortality rate of 28 deaths per 1000 live births (95% CI: 17–30). With regards to the study groups, the infant mortality in the first year of life was 18 deaths per 1000 (95% CI: 8.8–27) live births (14 deaths) for infants with NBW and 96 deaths per 1000 (95% CI: 91.3–100.7) for infant with LBW, respectively. The survival curve of infants with LBW compared with those born with NBW demonstrates a statically significant higher number of deaths over the whole observation period (p<0.002) (Fig 4).

Fig 4. Comparison of survival stratified by birth weight.

Fig 4

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Moreover, comparing both study groups, the crude hazard ratio shows a 6.4 (95% CI: 1.95–20.98) increased hazard of death among children with LBW compared to those with NBW. Adjusted for preterm birth, infant sex and mother age and literacy, infants with LBW had a 4.5-fold higher hazard to die than infants with NBW (Table 5).

Table 5. Effect of low birth weight on infant mortality.

Univariable model Multivariable model**
Hazard ratio (95% CI) p-value* Hazard ratio (95% CI) p-value*
NBW 1 1
LBW 6.46 (1.97–21.18) 0,002 4.55 (1.19–17.30) 0.026
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N = 813 for both the univariable and the multivariable models; LBW: low Birth Weight, NBW: Normal Birth Weight.

* Wald test.

**Adjusted for preterm birth, infant sex, maternal age and maternal literacy.

Discussion

Our findings show a high prevalence of low birth weight in the study area in Gabon with 13% babies born too small. There was a significant weight gain in the LBW infants but that was not enough to reach the mean weight of infants born with normal weight. Malnutrition indicators that were stunting, wasting and underweight were significantly more frequent in the LBW infants’ group, and so was the mortality.

Low birthweight is known to be associated with poor postnatal growth, particularly during the first year of life [18, 28]. However, the impact of LBW varies between respective settings, which makes it important to obtain local data. The impact of LBW on nutritional deficits and survival was never assessed in Gabon and few data exist for the Central African region. Weight, nutritional status, and mortality are among the best indicators to assess an infant’s wellness in his first year of life.

The observed higher weight gain among LBW infants during the first year of life is in line with a previous report indicating a difference in mean weight gain up to 8 months of age [29]. Sridhar et al. [30] and Borah et al. [31] also reported higher weight gains in LBW infants compared to their normal birth weight counterpart. This can potentially be explained by the particular attention that mothers and health caregivers may be providing to infants born too small. Indeed, in the maternal and infant health services there is a screening of malnutrition and nutritional advice and practical exercises are provided to mothers with too small infants. Nonetheless, it was observed that despite that particular attention and the observed significant weight gain among LBW infants, there remains a difference in mean weight with the normal weight born infants. This finding corroborates with the results from a study in Burkina Faso in which WAZ was used as an indicator of malnutrition during the first year of life, and it was also observed that LBW children’s growth curve remained below that of normal birthweight children [29].

The results show strong evidence that LBW was an independent risk factor for stunting, wasting and underweight while that was not the case for preterm birth. This suggests that the small for gestational age component of LBW which is in utero growth restriction may be more important in explaining the observed postnatal growth retardation rather than the being born too soon component in our study population. Actually, in the absence of congenital malformations or chromosomal abnormalities foetal size could be the consequence of two distinct processes: constitutional smallness or pathological growth restriction and distinguishing one process from the other is challenging [32]. In our study, infants have been categorized according to their birth weight without checking if a growth restriction really occurred. It is known that growth restricted foetuses are small because of some underlying pathological conditions including uteroplacental dysfunction, hypertensive disorders or illicit and toxic substances during pregnancy such as smoking. The observed important weight gain in the LBW infants’ group may suggest that the constitutional smallness process may be negligible in this population. The implication of the LBW mechanism involved in these infants’ adverse growth and nutrition outcomes would therefore be more explicit if more variables reflecting the potential underlying pathological conditions but also the socioeconomic status of the parents and family size, infant breastfeeding and other nutritional interventions addressed to infants were recorded and controlled for.

The observed overall mortality rate of 28 deaths per 1000 live births was significantly below the 81 deaths per 1000 live births reported by UNICEF in 2016 for the Central African region [2]. This could be explained by the clinical trial context as the MIPPAD study that recruited the participants was a funded clinical trial providing basic health care, and HIV-positive pregnant women were systematically excluded. Most deaths occurred before the second month of life and that is similar to what was reported by previous studies from Burkina Faso and Ghana [20, 29]. There was a strong evidence of an association between LBW and infant mortality in our study, in line with reports from other settings [33, 34].

There were a lot of infants from baseline and month 1 that missed the months 9 and 12 visits and this could be a huge limitation. The high loss to follow-up here can be due to the high mobility of the population in Gabon and it can be interpreted that around the age when infants start sitting and crawling, they are taken into trips with other family members. That was addressed by conducting sensitivity analyses that showed that at 9-month visit there were more infants from the LBW group missing compared to the normal birth weight group. That suggests that the observed effect was certainly misclassified and underestimated.

Among the strengths of this study are the prospective design, the high-quality standardized data collection and follow-up guaranteed by the clinical trial context as well as the high coverage of standard antenatal and postnatal care financially supported that could limit the accessibility and availability of care barriers frequently described in resource-limited settings. The systematic exclusion of HIV positive pregnant women is limiting the generalization of the results of this study and residual confounding may not be completely ruled out as the randomization in the MiPPAD trial was based on the intervention which was not taken into account in this analysis. The fixed time points for assessment that were at months 1, 9 and 12 and the relatively short period of follow-up on one year could also be limiting as important outcomes particularly later in life are not captured. It may therefore be advised for future studies to have monthly visits and a longer follow-up period to account for time-dependent variations of the outcomes.

Conclusion

Our findings that LBW is highly frequent among babies born from HIV-negative pregnant women from our study area in Gabon and its association with infants’ restricted growth, nutritional deficits and mortality, advocate for the strengthening of health interventions targeting the prevention of low birth weight in women. It may be too late to prevent the adverse nutrition and mortality outcomes after birth in the babies born too small but an emphasis on nutritional interventions must be provided for them. Studies designed to distinguish the small for age and intrauterine growth restriction components of LBW are recommended to further understand the mechanisms involved and develop interventions accordingly.

Supporting information

S1 Table. Sensitivity analysis.

(DOCX)

Click here for additional data file. (22.8KB, docx)

Acknowledgments

We are thankful to the MiPPAD Consortium and the staff at CERMEL, at the Centre Médical de Fougamou and at the Centre de Recherches Médicales de la Ngounié in Fougamou, at the Albert Schweitzer hospital and at the Centre Hospitalier Régional Georges Rawiri in Lambaréné. We are also grateful to the women and families that participated in the MiPPAD study in the different study sites in Gabon.

Data Availability

The data are available at DOI: 10.5281/zenodo.4244987.

Funding Statement

The main (MIPPAD) study was funded by the European Developing Countries Clinical Trials Partnership (EDCTP; IP.2007.31080.002). The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

References

  • 1.fao.org. SOFI 2018—The State of Food Security and Nutrition in the World [Internet]. www.fao.org. [cited 20 May 2019]. http://www.fao.org/state-of-food-security-nutrition/en/
  • 2.Levels and Trends in Child Mortality 2017 [Internet]. UNICEF DATA. 2017 [cited 14 Sept 2018]. https://data.unicef.org/resources/levels-trends-child-mortality/
  • 3.WHO’s Africa Nutrition Report highlights an increase in malnutrition in Africa. [Internet]. WHO | Regional Office for Africa. [cited 13 Sept 2018]. https://afro.who.int/news/whos-africa-nutrition-report-highlights-increase-malnutrition-africa
  • 4.Abera L, Dejene T, Laelago T. Prevalence of malnutrition and associated factors in children aged 6–59 months among rural dwellers of damot gale district, south Ethiopia: community based cross sectional study. Int J Equity Health. 26 2017;16(1):111 10.1186/s12939-017-0608-9 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 5.Akombi BJ, Agho KE, Merom D, Renzaho AM, Hall JJ. Child malnutrition in sub-Saharan Africa: A meta-analysis of demographic and health surveys (2006–2016). PloS One. 2017;12(5):e0177338 10.1371/journal.pone.0177338 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 6.Müller O, Krawinkel M. Malnutrition and health in developing countries. CMAJ Can Med Assoc J. 2 Août 2005;173(3):279–86. 10.1503/cmaj.050342 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 7.Galgamuwa LS, Iddawela D, Dharmaratne SD, Galgamuwa GLS. Nutritional status and correlated socio-economic factors among preschool and school children in plantation communities, Sri Lanka. BMC Public Health. 02 2017;17(1):377 10.1186/s12889-017-4311-y [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 8.UNICEF. Children, food and nutrition: growing well in a changing world. 2020.
  • 9.Perez-Escamilla R, Bermudez O, Buccini GS, Kumanyika S, Lutter CK, Monsivais P, et al. Nutrition disparities and the global burden of malnutrition. BMJ. 13 Juin 2018;361:k2252 10.1136/bmj.k2252 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 10.Maleta K, Virtanen SM, Espo M, Kulmala T, Ashorn P. Childhood malnutrition and its predictors in rural Malawi. Paediatr Perinat Epidemiol. October 2003;17(4):384–90. 10.1046/j.1365-3016.2003.00519.x [DOI] [PubMed] [Google Scholar]
  • 11.Motta MEFA, da Silva GAP, Araújo OC, Lira PI, Lima MC. [Does birth weight affect nutritional status at the end of first year of life?]. J Pediatr (Rio J). October 2005;81(5):377–82. 10.2223/JPED.1388 [DOI] [PubMed] [Google Scholar]
  • 12.WHO. Stunting in a nutshell [Internet]. WHO. [cited 8 May 2019]. http://www.who.int/nutrition/healthygrowthproj_stunted_videos/en/
  • 13.Dewey KG, Begum K. Long-term consequences of stunting in early life. Matern Child Nutr. 2011;7(s3):5–18. 10.1111/j.1740-8709.2011.00349.x [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 14.Prendergast AJ, Humphrey JH. The stunting syndrome in developing countries. Paediatr Int Child Health. Avr 2014;34(4):250–65. 10.1179/2046905514Y.0000000158 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 15.de Onis M, Branca F. Childhood stunting: a global perspective. Matern Child Nutr. Mai 2016;12(Suppl Suppl 1):12–26. 10.1111/mcn.12231 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 16.Rahman MS, Howlader T, Masud MS, Rahman ML. Association of Low-Birth Weight with Malnutrition in Children under Five Years in Bangladesh: Do Mother’s Education, Socio-Economic Status, and Birth Interval Matter? PloS One. 2016;11(6):e0157814 10.1371/journal.pone.0157814 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 17.Ntenda PAM. Association of low birth weight with undernutrition in preschool-aged children in Malawi. Nutr J. 2 September 2019;18(1):51 10.1186/s12937-019-0477-8 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 18.UNICEF. Low birthweight [Internet]. UNICEF DATA. [cited 7 May 2017]. //data.unicef.org/topic/nutrition/low-birthweight/
  • 19.Malnutrition in Children [Internet]. UNICEF DATA. [cited 9 Jun 2020]. https://data.unicef.org/topic/nutrition/malnutrition
  • 20.O’Leary M, Edmond K, Floyd S, Newton S, Thomas G, Thomas SL. A cohort study of low birth weight and health outcomes in the first year of life, Ghana. Bull World Health Organ. 1 Août 2017;95(8):574–83. 10.2471/BLT.16.180273 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 21.Guidelines on Optimal Feeding of Low Birth-Weight Infants in Low- and Middle-Income Countries [Internet]. World Health Organization; 2011 [cited 9 Jun 2020]. https://www.ncbi.nlm.nih.gov/books/NBK298973/ [PubMed]
  • 22.Oluwayemi IO, Ogundare EO, Olatunya OS. Care of the Newborn in Developing Countries. April 2014; J Neonatal Biol 2014, 3:5 [Google Scholar]
  • 23.WHO. A cohort study of low birth weight and health outcomes in the first year of life, Ghana [Internet]. WHO. [cited 21 May 2019]. http://www.who.int/bulletin/volumes/95/8/16-180273/en/ [DOI] [PMC free article] [PubMed]
  • 24.González R, Mombo-Ngoma G, Ouédraogo S, Kakolwa MA, Abdulla S, Accrombessi M, et al. Intermittent preventive treatment of malaria in pregnancy with mefloquine in HIV-negative women: a multicentre randomized controlled trial. PLoS Med. 23 September 2014;11(9):e1001733–e1001733. 10.1371/journal.pmed.1001733 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 25.Ballard JL, Khoury JC, Wedig K, Wang L, Eilers-Walsman BL, Lipp R. New Ballard Score, expanded to include extremely premature infants. J Pediatr. sept 1991;119(3):417–23. 10.1016/s0022-3476(05)82056-6 [DOI] [PubMed] [Google Scholar]
  • 26.Rupérez M, González R, Mombo-Ngoma G, Kabanywanyi AM, Sevene E, Ouédraogo S, et al. Mortality, Morbidity, and Developmental Outcomes in Infants Born to Women Who Received Either Mefloquine or Sulfadoxine-Pyrimethamine as Intermittent Preventive Treatment of Malaria in Pregnancy: A Cohort Study. PLoS Med. Févr 2016;13(2):e1001964 10.1371/journal.pmed.1001964 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 27.Rahman MS, Howlader T, Masud MS, Rahman ML. Association of Low-Birth Weight with Malnutrition in Children under Five Years in Bangladesh: Do Mother’s Education, Socio-Economic Status, and Birth Interval Matter? PLoS One. 2016; 11(6): e0157814 10.1371/journal.pone.0157814 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 28.WHO. Standard formula for low-birth-weight infants following hospital discharge [Internet]. WHO. [cited 28 May 2019]. http://www.who.int/elena/titles/formula_infants/en/
  • 29.Kabore P, Potvliege C, Sanou H, Bawhere P, Dramaix M. [Growth velocity and survival of full-term low birth weight infants in an African rural area (Burkina Faso)]. Arch Pediatr Organe Off Soc Francaise Pediatr. Juill 2004;11(7):807–14. [DOI] [PubMed] [Google Scholar]
  • 30.Sridhar K, Bhat BV, Srinivasan S. Growth pattern of low birth weight babies in the first year of life. Indian J Pediatr. June 2002;69(6):485–8. 10.1007/BF02722649 [DOI] [PubMed] [Google Scholar]
  • 31.Borah M, Baruah R Physical Growth of Low Birth Weight Babies in First Six Months of Life: a Longi-tudinal Study in a Rural Block of Assam. Natl J Community Med 2014: 5(4);397–400. [Google Scholar]
  • 32.Barone G, Maggio L, Saracino A, Perri A, Romagnoli C, Zecca E. How to feed small for gestational age newborns. Ital J Pediatr. 10 Mai 2013;39(1):28 10.1186/1824-7288-39-28 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 33.Mwangome M, Ngari M, Bwahere P, Kabore P, McGrath M, Kerac M, et al. Anthropometry at birth and at age of routine vaccination to predict mortality in the first year of life: A birth cohort study in BukinaFaso. PLOS ONE. 28 Mars 2019;14(3):e0213523 10.1371/journal.pone.0213523 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 34.Padonou G, Le Port A, Cottrell G, Guerra J, Choudat I, Rachas A, et al. Factors associated with growth patterns from birth to 18 months in a Beninese cohort of children. Acta Trop. Juill 2014;135:1–9. [DOI] [PubMed] [Google Scholar]

Decision Letter 0

Samson Gebremedhin

17 Sep 2020

PONE-D-20-19873

Birth weight, growth, nutritional status and mortality of infants from Lambaréné and Fougamou in Gabon in their first year of life

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Reviewer #1: This manuscript is on an important topic, but the writing is somewhat confusing and needs a close grammar proofread; not all of the numbers in the text match the tables; and I have certain concerns about the data and analyses as presented.

Major concerns:

My 2 major concerns are about the amount of missing data and the selected confounders. The most concerning issue for me is that loss to follow up is a huge limitation. The study lost either 25 or about 45% of the sample, depending on how you choose the denominator (one month vs. baseline). This issue is not addressed anywhere in the limitations or in the manuscript. I think the authors need to present some sensitivity analyses and say something about how they differed than the study participants who were retained, and how those differences might influence the study's findings. It's also not clear which children are in the KM and hazard analyses--have the authors censored the LTFs at last seen date, or just ignored them in that analysis?

My other major concern is that the authors have some specific confounders they controlled for, but why these specific ones were chosen are mysterious. There are other factors also possibly relevant--breast feeding history, complementary feeding history, family wealth, number of other kids in household, availability of & use of antenatal care--so what was the rationale for including these specific confounders and nothing else?

Minor concerns

Line 68-71: this sentence is hard to understand. I'd break it into 2 because you seem to have 2 concepts here.

Line 80: "Once established, stunting and its effects typically become permanent. Stunting is an appropriate indicator for chronic malnutrition"...There's some controversy about this. Some studies have shown trajectories in which children recover and others in which they don't. Early intervention is believed to help with this. You need some citations for your contention here.

Line 82:"Underweight is most commonly used as nutritional indicator due to difficulties..." This statement again needs some citation. DHS,. MICS, and a lot of other national programs use stunting and wasting. Saying that underweight is most commonly used needs to be backed up with some evidence.

Line 133: "For those with no weight available at birth but in the first week of life in case of home deliveries weight was estimated using a regression model". This needs some explanation. How do you estimate weight with regression?

Table 1: Preterm birth totals don't add to 907 or 115. I suggest that the authors present "n"s when they don't match the stated denominator.

Line 189: Authors haven't defined a weight gain ratio.

Line 200: if the authors are presenting decimal places in the table, it makes sense to match that in the text.

Line 208: "There were more significantly observed underweight LBW infants compared to their normal weight counterpart". I did not understand the sentence. what does it mean to be significantly observed underweight?

Lines 200-212: I found it challenging to read and follow this paragraph. Maybe the authors could restructure this so that they talk about each endpoint separately? So, first stunting, and what's associated. Then wasting, and what's associated with that, etc.

Lines 221-222: These numbers should all match what is in table 4. I found this paragraph also very confusing. LBW was associated with higher stunting at months 1 AND month 12, but not in between . These are all one model, correct? So preterm birth is associated with stunting independent of LBW ?

Discussion: the English here needs some boosting also.

Lines 263-265: I didn't understand what it means to have a nutritional gain if the prevalence of stunting and underweight increased and prevalence of wasting stayed the same. Perhaps reword this? Do you mean that mean weight increased for all children?

Lines 272-274: "We hypothesize that this catching up in weight gain is at least in part due to the particular attention caused by mothers and the health care system allowing children born with LBW to acquire a normal weight" What is this extra attention? Can you be more specific about Gabon's practices in the health care system to address these nutritional challenges in LBW children?

Lines 293-296: I don;t understand this paragraph. LBW is an independently associated with stunting at 12 months in this setting--but what does that have to do with weight deficit since birth? These 2 things are probably true, but the authors haven't really connected them coherently here.

Lines 303-304: "This indicates that 302 health interventions need to focus primarily on the two first months of life, particularly for newborns with LBW." I'm not sure this is a reasonable suggestion. What do the authors mean by "primarily"? Even among those who survive, a high proportion have poor nutrition outcomes. So I'm not sure it makes sense to say that that health care programs should put most focus on the first 2 months. Obviously something needs to be done but the children who survive also need health care support. Also, the authors don;t mention what proportion of deaths occur as neonates. Health interventions often don't help to move the needle on neonatal death. What might help with these early deaths is antenatal care, facility delivery in a well-stocked facility, etc. Other health service interventions may be of more benefit in children after the first few weeks of life.

Reviewer #2: The manuscript presented an interesting data on the significance of LWB for survival and nutritional status of infants in Gabon. While the findings of the analysis are not new, they may help to consolidate the existing knowledge on the topic. In general, the manuscript is also well written.

I recommend the authors accommodate the following comments.

Exhaustive list of potential confounders along with approach used for selecting the variables for multivariable adjustment should be provided. For example, it is not clear how the authors decided to adjust the multivariable models for infant sex, maternal age and maternal literacy.

The adequacy of the sample size for comparing mortality between LBW and normal birthweight infants should be evaluated through post-hoc power calculation.

The possibility of loss to follow up bias should be explored by comparing the characteristics of the study participants retained and dropped out of the study.

The basic characteristics of exposed and non-exposed subjects should be described and statistically compared at the beginning of the Results section.

**********

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PLoS One. 2021 Feb 9;16(2):e0246694. doi: 10.1371/journal.pone.0246694.r002

Author response to Decision Letter 0

8 Nov 2020

Reviewer #1:

This manuscript is on an important topic, but the writing is somewhat confusing and needs a close grammar proofread; not all of the numbers in the text match the tables; and I have certain concerns about the data and analyses as presented.

Reply: We thank the reviewer for the thorough assessment of our manuscript and the queries raised. This has tremendously been helpful in improving the quality of the manuscript. Please, we have performed a grammar proofread and corrected the mismatches in the tables.

Major concerns:

My 2 major concerns are about the amount of missing data and the selected confounders. The most concerning issue for me is that loss to follow up is a huge limitation. The study lost either 25 or about 45% of the sample, depending on how you choose the denominator (one month vs. baseline). This issue is not addressed anywhere in the limitations or in the manuscript. I think the authors need to present some sensitivity analyses and say something about how they differed than the study participants who were retained, and how those differences might influence the study's findings.

Reply: This is correct that there were a lot of losses to follow-up from 9 months that can be explained by the high mobility of the population in Gabon. This limitation has been addressed by conducting sensitivity analyses as advised by the reviewer. The findings of the sensitivity analyses are shown in the supplementary table added. Mention of the sensitivity analyses have been added in the methods, results and discussion sections.

It's also not clear which children are in the KM and hazard analyses--have the authors censored the LTFs at last seen date, or just ignored them in that analysis?

Reply: 907 infants were included in the KM hazard analysis. LTFs were included in the analysis and censored at the last contact date.

My other major concern is that the authors have some specific confounders they controlled for, but why these specific ones were chosen are mysterious. There are other factors also possibly relevant--breast feeding history, complementary feeding history, family wealth, number of other kids in household, availability of & use of antenatal care--so what was the rationale for including these specific confounders and nothing else?

Reply: Some factors including mother’s age and literacy, infant’s sex and prematurity, breast feeding history, complementary feeding history, family wealth, number of other kids in household, availability of & use of antenatal care are recognised as risk factors for malnutrition. The main study was conducted to evaluate intermittent preventive treatment of malaria during pregnancy, for which some of those variables were recorded and used in our analysis. The main study was designed as a randomized clinical trial with the assumption that confounders would be evenly distributed between the treatment arms, they were therefore not systematically recorded. We have mentioned that limitation in the manuscript (line 306-307). It can be believed that the socioeconomic factors have minimal effect as in the context of the clinical trial as standard care was provided to all participants and their offspring.

Minor concerns

Line 68-71: this sentence is hard to understand. I'd break it into 2 because you seem to have 2 concepts here.

Reply: Sentence was broken into two sentences as advised

Line 80: "Once established, stunting and its effects typically become permanent. Stunting is an appropriate indicator for chronic malnutrition"...There's some controversy about this. Some studies have shown trajectories in which children recover and others in which they don't. Early intervention is believed to help with this. You need some citations for your contention here.

Reply: Thank you for this suggestion. We added a citation (Dewey and Begum, 2011) to support the statement

Line 82:"Underweight is most commonly used as nutritional indicator due to difficulties..." This statement again needs some citation. DHS, MICS, and a lot of other national programs use stunting and wasting. Saying that underweight is most commonly used needs to be backed up with some evidence.

Reply: We added citation (Prendergast and Humphrey, 2014) to support the statement.

Line 133: "For those with no weight available at birth but in the first week of life in case of home deliveries weight was estimated using a regression model". This needs some explanation. How do you estimate weight with regression?

Action: There is a linear regression model described by Greenwood and colleagues (1992) adjusting the birthweight measured after the day of birth. On average, infants’ weight 6.3 grams less each day after birth. In the analysis the weight at birth was estimated using this coefficient for those children weighed after day 0. The fitted values by the linear model are very similar to the values estimated by Lowess regression.

Below, the estimations from the main trial as published in Plos Medicine (Gonzales et al. 2014)

Table 1: Preterm birth totals don't add to 907 or 115. I suggest that the authors present "n"s when they don't match the stated denominator.

Reply: The reviewer is correct on that point, we have corrected the table with “n”s for each variable and since the total population at baseline was 907, we have indicated with “*” the variables with missing data.

Line 189: Authors haven't defined a weight gain ratio.

Reply: This is correct, it has now been defined in the text. Weight gain ratio is the ratio of the weight of infants at the visit divided by the weight of the infants at the previous visit. It has been added in the manuscript line 155-157.

Line 200: if the authors are presenting decimal places in the table, it makes sense to match that in the text.

Reply: We rounded in order to make the result easier to read but reviewer’s comment is relevant so we have shown the decimal places in the text as well.

Line 208: "There were more significantly observed underweight LBW infants compared to their normal weight counterpart". I did not understand the sentence. what does it mean to be significantly observed underweight?

Reply: The sentence was reformulated. “There were significantly more underweight observed among infants born with low weight compared to their normal birth weight counterpart” (line 217-219)

Lines 200-212: I found it challenging to read and follow this paragraph. Maybe the authors could restructure this so that they talk about each endpoint separately? So, first stunting, and what's associated. Then wasting, and what's associated with that, etc.

Reply: Text was restructured

Lines 221-222: These numbers should all match what is in table 4. I found this paragraph also very confusing. LBW was associated with higher stunting at months 1 AND month 12, but not in between. These are all one model, correct? So preterm birth is associated with stunting independent of LBW?

Reply: Numbers were corrected in the text to match what is in table 4. That’s the same model, and it showed actually stronger evidence of an association of LBW and stunting at month 1 and month 12. For month 9, there was obviously a trend of an association too as the estimates of OR was 2.0, however the 96%CI crossed 0. That weak evidence at 9 months is not yet fully understood but we think that it reflects what is shown in Figure 3 as there is an important weight gain before 9 months.

Discussion: the English here needs some boosting also.

Reply: The English was reviewed and the section was rewritten to address the language issue

Lines 263-265: I didn't understand what it means to have a nutritional gain if the prevalence of stunting and underweight increased and prevalence of wasting stayed the same. Perhaps reword this? Do you mean that mean weight increased for all children?

Reply: This was actually a mistake that has been corrected, thank you. We meant weight gain instead.

Lines 272-274: "We hypothesize that this catching up in weight gain is at least in part due to the particular attention caused by mothers and the health care system allowing children born with LBW to acquire a normal weight" What is this extra attention? Can you be more specific about Gabon's practices in the health care system to address these nutritional challenges in LBW children?

Reply: We mean that the important weight gain observed in the LBW infants’ group may be explained by the particular attention given to that group and the subsequent restoration of growth that restricted in utero.

Lines 293-296: I don’t understand this paragraph. LBW is an independently associated with stunting at 12 months in this setting--but what does that have to do with weight deficit since birth? These 2 things are probably true, but the authors haven't really connected them coherently here.

Reply: The sentence was rephrased to highlight the potential mechanisms of LBW involved, see action above.

Lines 303-304: "This indicates that 302 health interventions need to focus primarily on the two first months of life, particularly for newborns with LBW." I'm not sure this is a reasonable suggestion. What do the authors mean by "primarily"? Even among those who survive, a high proportion have poor nutrition outcomes. So, I'm not sure it makes sense to say that that health care programs should put most focus on the first 2 months. Obviously, something needs to be done but the children who survive also need health care support. Also, the authors don’t mention what proportion of deaths occur as neonates. Health interventions often don't help to move the needle on neonatal death. What might help with these early deaths is antenatal care, facility delivery in a well-stocked facility, etc. Other health service interventions may be of more benefit in children after the first few weeks of life.

Reply: We have reformulated our recommendations and it is indeed better to promote interventions targeting pregnant women to prevent babies to be born too small.

Reviewer #2:

The manuscript presented an interesting data on the significance of LWB for survival and nutritional status of infants in Gabon. While the findings of the analysis are not new, they may help to consolidate the existing knowledge on the topic. In general, the manuscript is also well written. I recommend the authors accommodate the following comments:

-Exhaustive list of potential confounders along with approach used for selecting the variables for multivariable adjustment should be provided. For example, it is not clear how the authors decided to adjust the multivariable models for infant sex, maternal age and maternal literacy.

Reply: Some factors including mother’s age and literacy, infant’s sex and prematurity, breast feeding history, complementary feeding history, family wealth, number of other kids in household, availability of & use of antenatal care are recognised as risk factors for malnutrition. The main study was conducted to evaluate intermittent preventive treatment of malaria during pregnancy, for which some of those variables were recorded and used in our analysis. The main study was designed as a randomized clinical trial with the assumption that confounders would be evenly distributed between the treatment arms, they were therefore not systematically recorded. We have mentioned that limitation in the manuscript (line 306-307). It can be believed that the socioeconomic factors have minimal effect as in the context of the clinical trial as standard care was provided to all participants and their offspring.

-The adequacy of the sample size for comparing mortality between LBW and normal birthweight infants should be evaluated through post-hoc power calculation.

Reply: we calculated post-hoc power for the comparison of mortality between LBW and normal birth weight and we obtained 95 %.

-The possibility of loss to follow up bias should be explored by comparing the characteristics of the study participants retained and dropped out of the study.

Reply: This is correct, we have now addressed that limitation by conducting sensitivity analyses that showed that the baseline characteristics of the retained participants were similar to that of the whole population including the lost to follow up. This is reported in the supplementary table.

-The basic characteristics of exposed and non-exposed subjects should be described and statistically compared at the beginning of the Results section.

Reply: We included exposed and non-exposed subjects in baseline characteristics table.

Attachment

Submitted filename: Response to Reviewers-final.docx

Click here for additional data file. (265.2KB, docx)

Decision Letter 1

Samson Gebremedhin

7 Dec 2020

PONE-D-20-19873R1

Birth weight, growth, nutritional status and mortality of infants from Lambaréné and Fougamou in Gabon in their first year of life

PLOS ONE

Dear Dr. Mombo-Ngoma,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process. Specially I recommend you to address issues raised on the sensitivity analysis and the approach used for selecting variables for the statistical adjustment. 

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Academic Editor

PLOS ONE

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: (No Response)

Reviewer #2: (No Response)

**********

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Reviewer #1: Partly

Reviewer #2: Yes

**********

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Reviewer #1: No

Reviewer #2: Yes

**********

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Reviewer #1: Yes

Reviewer #2: (No Response)

**********

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Reviewer #1: Yes

Reviewer #2: Yes

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6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: I thank the authors for their efforts to address the comments that the other reviewer and I made. I appreciate their time. However, I still have one large concern and a few minor changes and suggestions.

MAIN large reservation:

I don’t think that the authors entirely understood my request to do a sensitivity analysis of those who were lost to follow up, or if they did, it’s not reflected in the supplemental table. In lines 317-323 “sensitivity analyses that demonstrated that the baseline characteristics of the retained children were not different from the entire population at baseline [**assuming that those dropped out were similar to those retained with regard to these characteristics**].” I have bracketed the concerning portion because in my view, that assumption renders the authors’ sensitivity analysis invalid.

What I am thinking of here is a sensitivity analysis in its simplest form as follows: those who were LTFU are one category and those who were never LTFU or missing are another. Then compare those 2 categories on things like LBW, malnutrition, preterm birth, infant sex, etc., What I see in the Supplementary table are descriptions of those who were retained at different time points, with no p values or comparisons. Just based on the numbers I see in the table, at 9 mo, the authors have 60/115 LBW kids (~52%) vs 515/792 normal birthweight kids (~65%). Which could very well be a statistically significant difference, but we don't know. The mean birthweight in your LBW children at 12 months was somewhat higher than in the LBW children at baseline. My point is that the children that were lost may be different in meaningful ways than the ones who were retained. My suggestion is to figure out whether there were differences, present p values in the supplement table to reassure the readers, and if there are differences, mention in the discussion whether you think they’d impact the results and how. It may be that you suspect that if everyone were there, you’d get even stronger associations.

Minor comments and proofreading:

Line 35, don’t need comma after “both”

Line 40 : included between 2009 and 2012 makes it sound like these are “n”s . Suggest you move the word “included” to after 2012.

Line 48: It could be the same number of infants that were LBW, it’s just that you’ve lost more during follow up. What are the actual ns? Is it same kids?

Line 55: ratio, not ration.

Body:

line 77 “”stunting is reported to be a strong marker of healthy growth”. It’s more like unhealthy growth, no?

line 86” While stunting wasting and underweight…low birth weight…” maybe make that the first sentence of the LBW paragraph

line 139: “like describe elsewhere”. This is not great grammar and not especially useful. I’d suggest you say something like “calculated using standard formula” and cite maybe DHS statistics or WHO web page that talks about how to calculate,

line 139

Height-for-age Z-score (HAZ), weight-for-age Z-score (WAZ) and weight-for-height Z-score (WHZ) were used to define respectively stunting, underweight and wasting. HAZ <-2 standard deviations (SD), WAZ <-2 141SD and WHZ <-2 SD.

Suggest you reword to make complete sentences:

Ex: Height-for-age Z-score (HAZ, <-2 standard deviations below an international reference mean), weight-for-age Z-score (WAZ <-2 SD), and weight-for-height Z-score (WHZ <-2 SD) were used to define respectively stunting, underweight and wasting.

144: data”were” . Data is a plural

Line 148: on comparing baseline characteristics of infants attending each visit to explore whether there was any alteration that could be imputed to the lost to follow-up.

Sentence is confusing. try instead “to explore whether any differences existed that could be associated with loss to follow up”

Table 4: I’ve forgotten why Wasting is only assessed at month 1. I’d suggest the authors add a footnote to the table about that, because the authors obviously calculated prevalence of wasting at all times.

Reviewer #2: Most of my concerns have been addressed. However, it remains vague how the variables infant sex, maternal age and maternal literacy were selected for adjustments. What possible control variables did the authors considered at the beginning of the analysis? How did the end up in the three variables? This must be clearly described in the manuscript.

**********

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Reviewer #2: No

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PLoS One. 2021 Feb 9;16(2):e0246694. doi: 10.1371/journal.pone.0246694.r004

Author response to Decision Letter 1

21 Jan 2021

Rebuttal point-by-point response tot he reviewers

Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: I thank the authors for their efforts to address the comments that the other reviewer and I made. I appreciate their time. However, I still have one large concern and a few minor changes and suggestions.

MAIN large reservation:

I don’t think that the authors entirely understood my request to do a sensitivity analysis of those who were lost to follow up, or if they did, it’s not reflected in the supplemental table. In lines 317-323 “sensitivity analyses that demonstrated that the baseline characteristics of the retained children were not different from the entire population at baseline [**assuming that those dropped out were similar to those retained with regard to these characteristics**].” I have bracketed the concerning portion because in my view, that assumption renders the authors’ sensitivity analysis invalid.

What I am thinking of here is a sensitivity analysis in its simplest form as follows: those who were LTFU are one category and those who were never LTFU or missing are another. Then compare those 2 categories on things like LBW, malnutrition, preterm birth, infant sex, etc., What I see in the Supplementary table are descriptions of those who were retained at different time points, with no p values or comparisons. Just based on the numbers I see in the table, at 9 mo, the authors have 60/115 LBW kids (~52%) vs 515/792 normal birthweight kids (~65%). Which could very well be a statistically significant difference, but we don't know. The mean birthweight in your LBW children at 12 months was somewhat higher than in the LBW children at baseline. My point is that the children that were lost may be different in meaningful ways than the ones who were retained. My suggestion is to figure out whether there were differences, present p values in the supplement table to reassure the readers, and if there are differences, mention in the discussion whether you think they’d impact the results and how. It may be that you suspect that if everyone were there, you’d get even stronger associations.

Reply: We thank the reviewer for the very relevant comment and we agree with the concerns and we also believe that it is an added information that better helps interpret the findings. We have added some more details in the supplementary table like the percentages per line of those present at any specific time point compared to baseline. a statistical test was performed and the P values obtained have been added in the table. At 9 months, there are significantly more infants from the LBW group that did not attend that visit compared to the NBW group.

Minor comments and proofreading:

Line 35, don’t need comma after “both”

Reply: correction made, thanks.

Line 40 : included between 2009 and 2012 makes it sound like these are “n”s . Suggest you move the word “included” to after 2012.

Reply: the suggestion has been taken into account and the move made. the sentence now reads: “...conducted between 2009 and 2012, included infants…”

Line 48: It could be the same number of infants that were LBW, it’s just that you’ve lost more during follow up. What are the actual ns? Is it same kids?

Reply: Following the sensitive analysis, it appears that a significant number of LBW kids was missing at 9 months visit compared to the other group. The proportions remain similar at all the other time-points between LBW group and NBW group. This is now mentioned in the discussion.

Line 55: ratio, not ration.

Reply: typo was corrected

Body:

line 77 “”stunting is reported to be a strong marker of healthy growth”. It’s more like unhealthy growth, no?

Reply: that is true, typo was corrected

line 86” While stunting wasting and underweight…low birth weight…” maybe make that the first sentence of the LBW paragraph

Reply: Done

line 139: “like describe elsewhere”. This is not great grammar and not especially useful. I’d suggest you say something like “calculated using standard formula” and cite maybe DHS statistics or WHO web page that talks about how to calculate,

Reply: Sentence was reworded

line 139

Height-for-age Z-score (HAZ), weight-for-age Z-score (WAZ) and weight-for-height Z-score (WHZ) were used to define respectively stunting, underweight and wasting. HAZ <-2 standard deviations (SD), WAZ <-2 141SD and WHZ <-2 SD.

Suggest you reword to make complete sentences:

Ex: Height-for-age Z-score (HAZ, <-2 standard deviations below an international reference mean), weight-for-age Z-score (WAZ <-2 SD), and weight-for-height Z-score (WHZ <-2 SD) were used to define respectively stunting, underweight and wasting.

Reply: Sentence was reworded

144: data”were” . Data is a plural

Reply: word was corrected

Line 148: on comparing baseline characteristics of infants attending each visit to explore whether there was any alteration that could be imputed to the lost to follow-up.

Sentence is confusing. try instead “to explore whether any differences existed that could be associated with loss to follow up”

Reply: Sentence was reworded, thank you

Table 4: I’ve forgotten why Wasting is only assessed at month 1. I’d suggest the authors add a footnote to the table about that, because the authors obviously calculated prevalence of wasting at all times.

Reply: there were no preterm infants with wasting at 9 and 12 months, that ist he reason why point estimates are not shown at these time-points.

Reviewer #2: Most of my concerns have been addressed. However, it remains vague how the variables infant sex, maternal age and maternal literacy were selected for adjustments. What possible control variables did the authors considered at the beginning of the analysis? How did the end up in the three variables? This must be clearly described in the manuscript.

Reply: This is a good and relevant point raised by the reviewer. Actually, more variables were measured for the mothers during their pregnancies, these included parity, trimester of first antenatal clinic visit, BMI and MUAC and infectious status. These parameters have been controlled in the analyses of the determinants of LBW.

For the current analysis of the effect of LBW on growth, nutrition and mortality, the maternal variables age and literacy were considered to potentially affect the way mothers provide care to their infants and therefore any differences in these parameters could be confounding the potential effect of LBW only. The infant sex has been taken as a forced variable as sex and age are mostly considered as counfounding factors.

A clarifying sentence has been added in the methods section.

Attachment

Submitted filename: Rebuttal point-by-point response to the reviewers.docx

Click here for additional data file. (17.6KB, docx)

Decision Letter 2

Samson Gebremedhin

25 Jan 2021

Birth weight, growth, nutritional status and mortality of infants from Lambaréné and Fougamou in Gabon in their first year of life

PONE-D-20-19873R2

Dear Dr. Mombo-Ngoma,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

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Kind regards,

Samson Gebremedhin, PhD

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

Acceptance letter

Samson Gebremedhin

27 Jan 2021

PONE-D-20-19873R2

Birth weight, growth, nutritional status and mortality of infants from Lambaréné and Fougamou in Gabon in their first year of life

Dear Dr. Mombo-Ngoma:

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.

If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

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on behalf of

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Academic Editor

PLOS ONE

Associated Data

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    S1 Table. Sensitivity analysis.

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    Data Availability Statement

    The data are available at DOI: 10.5281/zenodo.4244987.

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