Literature DB >> 35358251

Prepregnancy BMI, gestational weight gain and offspring caries experience: Avon longitudinal study of parents and children.

Aderonke A Akinkugbe1,2, Tegwyn H Brickhouse1,2, Dipankar Bandyopadhyay3, Marcelle M Nascimento4, Gary D Slade5.   

Abstract

Pre-existing maternal overweight/obesity and pregnancy weight gain are associated with adverse birth outcomes such as low birth weight and prematurity, which may increase the risk of developmental tooth defects and early childhood caries. We sought to investigate the association between prepregnancy BMI, gestational weight gain (GWG) and the risk of early childhood caries. Data from 1,429 mother-offspring participants of the 1991/1992 Avon Longitudinal Study of Parents and Children were analyzed. The exposures were prepregnancy BMI (under/normal weight vs. overweight/obese), and gestational weight gain (GWG) based on the Institute of Medicine's recommended levels. The main outcome measured was offspring caries experience determined by clinical oral examinations at three time points. Log binomial regression estimated risk ratios and 95% confidence intervals. Seventy six percent (76%) of the mothers were under/normal weight prepregnancy, 39% and 26% respectively gained less and more than the recommended weight for their prepregnancy BMI during pregnancy. Being overweight/obese prepregnancy was associated with unadjusted RR (95% CI) of offspring caries of 1.16 (0.90, 1.51) at 31-months, 1.20 (0.96, 1.49) at 43-months and 1.09 (0.91, 1.30) at 61-months. GWG less than recommended was associated with higher unadjusted offspring caries experience of 1.13 (0.86, 1.48), 1.17 (0.92, 1.48) and 1.04 (0.87, 1.25) at 31-months, 43-months and 61-months respectively. There was insufficient evidence to indicate an association between prepregnancy BMI and gestational weight gain on offspring caries experience risk.

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Year:  2022        PMID: 35358251      PMCID: PMC8970488          DOI: 10.1371/journal.pone.0266247

Source DB:  PubMed          Journal:  PLoS One        ISSN: 1932-6203            Impact factor:   3.752


Introduction

The prevalence of overweight and obesity are on the rise in the U.S. and around the world [1]. The 2004–2005 pregnancy risk assessment and monitoring system indicate that 23% of pregnant U.S. women were overweight and 19% were obese [2]. More recent data from 2014 birth certificate records found that 26% and 25% of pregnant U.S. women were overweight and obese respectively [3], thus making pre-gravid overweight and obesity frequent high-risk obstetrics clinical conditions [4]. Pregnancy weight is reported to be associated with preterm birth and childhood obesity in the offspring, with prenatal care costs for overweight women about 5.4–16.2 times those of normal weight women [5]. The prenatal period is critical to the developmental origins of health and diseases [6]. Indeed, exposures occurring in the prenatal period are increasingly recognized as having significant impacts on later health outcomes [7]. Thus, the sensitivity of the developing fetus to maternal environment is not a new concept as demonstrated by the well-established impacts of smoking on adverse pregnancy outcomes [8-10] and pregnancy BMI on adverse offspring general health outcomes [11, 12]. Overweight/obesity alters the gut microbiome [13] and induces low grade inflammation [14]. Prenatal smoking promotes local oral inflammation [15], and likewise alters the oral microbiome [13] and induces low-grade systemic inflammation [16]. Thus, prenatal smoking and pregnancy adiposity likely share common biochemical and cellular mechanisms that promote an intrauterine environment conducive to adverse health outcomes (including dental caries) in the offspring. Maternal overweight and obesity during pregnancy are associated with adverse birth outcomes and have been reported in at least one study to exceed smoking as a risk factor with the greatest risk of adverse pregnancy outcomes [17]. Moreover, maternal pregnancy adiposity [12] is associated with low-birth weight and prematurity, conditions that have been reported to increase the risk of developmental enamel defects [18, 19], that are more susceptible to cariogenic bacteria [20, 21] and consequently the occurrence of dental caries. Early childhood caries is the most prevalent chronic childhood disease and it negatively affects the oral health-related quality of life of children and their families at all socioeconomic levels but especially in low socioeconomic levels [22]. Furthermore, poor oral health early in childhood is a risk factor for continued poor oral health throughout the lifecourse [23]. A registry-based study previously reported associations between pregnancy BMI in the first trimester and subsequent caries experience in the teenage offspring [24]. Maternal health and lifestyle habits, such as diet, physical activity, weight, and cigarette smoking, can affect the child’s oral health behaviors [25] and subsequent oral health status. Knowledge on associations between maternal health prepregnancy and in the prenatal period on dental caries occurrence in preschool age children are limited. Thus, this study aims to investigate the association between prepregnancy BMI, gestational weight gain and the risk of early childhood caries.

Materials and methods

Data source and study population

The Avon Longitudinal Study of Parents and Children (ALSPAC), is a prospective population-based birth cohort study originally aimed at studying environmental, and genetic factors affecting the health and development of children. ALSPAC recruited pregnant women residents of Avon, UK, with expected date of delivery between April 1991 and December 1992. Of 14,541 pregnancies enrolled, 13,761 mothers with singleton live births participated in the study [26-28]. A random 10% sample of children born in the last 6 months (June-December 1992) of the study were invited to participate in a sub-study called the “children in focus” (CIF) study. The CIF sample attended research clinics at approximate 6-month intervals during the first 5 years of life and at ages 31, 43 and 61 months, they underwent dental examination [26, 29] performed by dentists and health examiners. Trainings for the health examiners took place in six tutorial sessions totaling 16 hours of training, accompanied by an hour-long session of mock examination and replication on 30 children. Reported kappa statistics for these health examiners was 0.63 [29]. The current study was restricted to the CIF sample because of available data on clinically determined dental caries status. Written informed consent was obtained at the time of data collection following the recommendations of the ALSPAC Ethics and Law Committee. The current study was approved by the Institutional Review Board at Virginia Commonwealth University as exempt (#:HM20011742) and reporting adhered to the Strengthening the Reporting of Observational studies in Epidemiology (STROBE) guidelines.

Exposures

Gestational weight gain

Trained research midwives abstracted every measurement of weight entered into obstetric medical records and the corresponding gestational age and date. There was no between-midwife variation in mean values of abstracted data, and repeat data entry checks demonstrated error rates consistently lower than 1%. Absolute weight gain was calculated as the difference between the first and the last weight measurements in pregnancy [11]. For this investigation, the gestational weight gain (GWG) categories adopted of less than recommended, recommended and more than recommended, were based on the Institute of Medicine’s (IOM) [30] recommended levels of GWG according to prepregnancy BMI categories. The recommended weight gain levels based on prepregnancy BMI are as follows: underweight—12.5 to 18kg; normal weight—11.5 to 16kg; overweight—7–11.5kg; obese—5-9kg (S1 Table in S1 File).

Pre-pregnancy BMI

Measures of prepregnancy weight in the parent ALSPAC cohort were predicted from abstracted pregnancy weight measurements using multilevel models as described by Fraser A et al., [11] while maternal height was self-reported. We calculated BMI according to the WHO specification and modeled it as continuous for descriptive purposes and categorized into underweight (<18.5kg/m2), normal (18.5–24.9kg/m2), overweight (25–29.9kg/m2) and obese (≥30kg/m2) in regression modeling.

Outcome

Offspring dental caries

Using the World Health Organization criteria [29, 31] to assess the number of decayed, missing and filled teeth (dmft), dentists and health examiners conducted oral examinations at three time points: 31mo., 43 mo. and 5 years old. The outcome of caries experience for the current study was analyzed as dmft ≥1 (yes vs. no) at 31 months, 43 months and 61 months old. Given this binary specification and to minimize outcome misclassification, we manually assigned missing dmft (yes vs. no) at each time point when clinically plausible. For instance, if dmft at a previous time point (say 31 mo.) classified a child as diseased (dmft ≥1 i.e. ‘yes’), we assigned the child as diseased at subsequent time points even if the child did not attend subsequent clinics or attended the clinic but was not examined. However, we did not assign subsequent case status to children lost to follow-up whose initial examination status indicated no disease since we could not determine if the child truly remained disease free or progressed to a diseased status. In instances where a later time point (say 61 mo.) indicated no disease (dmft = 0 i.e. ‘no’), the corresponding prior time points (i.e. 31 mo. and 43 mo.) were manually assigned a non-disease status. In instances where a later time point indicated disease, previous time points were left as missing, since we could not determine when disease occurred. This manual dmft assignment described herein assumes that there were no errors in dental examinations. We multiply imputed missing dmfts that we could not manually assign a value to using chained equations [32] as described under the multiple imputation section.

Covariates

Maternal specific factors

Were self-reported or abstracted from the medical records [27], and included maternal age at birth- modeled as continuous; education (≤O level, A-level, and college degree); maternal race (white vs. non-white); and breastfeeding duration (never, <6 months, ≥6months). Other variables include family structure (number of moves in the last 5 years); gestational age; mode of delivery (spontaneous vs. other) and prenatal smoking (never, any smoking during pregnancy).

Child specific factors

Were based on maternal report on mailed-in child specific questionnaires or determined during clinical evaluation of the CIF sample [26, 28]. These include child gender (male, female), history of childhood/perinatal illness (chicken pox, measles, or rubella), tooth brushing frequency (< 2 times daily vs. ≥2 times daily) and past year dental visit (yes vs. no) at 38 or 54 months. Other child specific factors included total sugar intake at 18, 43 and 61 months based on estimates calculated by the parent ALSPAC study from a series of 3-day food diaries for the CIF sample kept by their mothers. Based on our hypothesized causal diagram (S1 Fig in S1 File), these child-specific factors represent risk factors for caries experience in the offspring and to avoid over fitting our regression models, not all were included in our list of adjustment covariates. The ALSPAC website contains detail of all available data through a fully searchable data dictionary and variable search tool that can be accessed at: http://www.bristol.ac.uk/alspac/researchers/our-data/.

Statistical analysis

Data analysis was restricted to singleton births (97%) who were alive at age 1 year. Data analysis began by summarizing the distribution of the exposures and baseline covariates for the CIF sample, reporting means and SDs for continuous variables and frequencies and relative frequencies for categorical variables. Using the Dagitty software (http://www.dagitty.net/) we identified a sufficient adjustment set of covariates (confounders) from a directed acyclic graph (DAG) [Akinkugbe et al., 2016] drawn apriori with knowledge from existing literature of causal relationships among variables presented on the DAG. Log-binomial regression estimated the 31-month, 43-month and 5- year risks of objectively determined offspring dental caries experience (i.e. dmft ≥1) and the corresponding risk ratios (RR) and 95% confidence intervals (C.I). The log-binomial model independently assessed the association between prepregnancy BMI groups and GWG categories on offspring caries experience at 31 months, 43 months and 61 months old. Analysis of prepregnancy BMI as the main exposure did not adjust for GWG because GWG lie on a causal pathway between prepregnancy BMI and offspring caries experience. Analysis of GWG as the main exposure adjusted for prepregnancy BMI as it represents a confounder of GWG and offspring caries experience.

Multiple imputation

Missing data were multiply imputed using chained equations (MICE) [White et al., 2011]. When there are several variables with missing data points, MICE is a practical approach to generate imputations based on a set of imputation models, one for each variable with missing values. Variables included in the imputation model were variables included in the final outcome models and predictors of missing data and loss to follow-up. The following variables with missing observations were imputed: the number of decayed, missing and filled teeth at 31, 43 and 61 months; covariates with missing observations, as well as the exposures (prepregnancy weight, height and absolute weight gain). Eighteen percent of the IOM recommended gestational weight gain variable was missing. This variable is a composite of total weight gain during pregnancy and prepregnancy BMI. Since we independently imputed weight gain during pregnancy, we re-estimated the IOM gestational weight gain categories after multiple imputation. Refer to S2 Table in S1 File for the proportion of missing covariates that we imputed. We imputed a total of 40 datasets using 500 between imputation iterations. Multiple imputation was done with PROC MI and MIANALYZE procedures in SAS that assumes data are missing at random (MAR). We summarized the results from each imputed dataset using Rubin’s rule [Rubin, 1987] into an overall estimate that accounts for both within and between imputation variances and conducted all analyses in SAS v.9.4 (SAS Institute, Cary NC).

Results

A total of 1,429 mother-child pairs were included in this study. Significant differences were noted in the distribution of certain maternal characteristics among the children in focus (CIF) mothers and the not in CIF mothers. Specifically, the CIF mothers were less likely to smoke during pregnancy (22% vs. 30%; p <0.0001), slightly older (29 vs. 28 years; p = 0.002), and more likely to have advanced degrees (40% vs. 35%; p = 0.001) than the not in CIF mothers. There were no significant differences with respect to race (p = 0.4), the number of moves in the past 5 years (p = 0.6) and absolute weight gain during pregnancy (p = 0.3) or in the proportion with chronic health conditions such as gestational diabetes (p = 0.6) and pre-eclampsia (p = 0.4). CIF mothers were less likely to be of normal prepregnancy BMI (71% vs. 75%) and more likely to be overweight (16% vs. 15%) and obese (7% vs. 5%) than the not in CIF mothers (p = 0.05). The CIF were more likely to be male (54% vs. 51%; p = 0.02) and white (96% vs. 95%; p = 0.01) than their counterparts not included in the CIF. However, there was no difference in gestational age at delivery between these groups (p = 0.2) Table 1. Three percent of the CIF had dmft ≥1 at 31 months, 16% at 43-months and 31% had dmft ≥1 at 61 months.
Table 1

Distribution of selected covariates between children selected and those not selected for the Children-in-focus (CIF) sub-study: Avon longitudinal study of parents and children.

CIF sample (n = 1,429)Not in CIF sample (n = 13,449)p-value
Maternal characteristics
Prenatal Smoking305 (22)3,300 (30)<0.0001
Missing512,562
Age at delivery, mean (IQR)29 (26, 32)28 (25, 31)0.002
Age at delivery (yrs.)<0.0001
    15–24240 (17)3,098 (25)
    25–351,072 (75)8,588 (69)
    36–44116 (8)851 (7)
    Missing1912
Education0.001
    O-level or less819 (60)7,201 (65)
    A-level344 (25)2,443 (22)
    College degree199 (15)1,400 (13)
    Missing672,405
Race0.4
    White1,333 (98)10,662 (97)
    Non-white31 (2)292 (3)
    Missing642,495
Moves in the last 5 years0.6
    none341 (25)2,741 (24)
    1–2729 (53)6,064 (54)
    ≥3297 (22)2,581 (23)
    missing622,063
Prepregnancy BMI mean (SD)23 (4.1)23 (3.8)0.003
    Underweight67 (5)514 (5)0.05
    Normal909 (71)7,672 (75)
    Overweight209 (16)1,524 (15)
    Obese87 (7)558 (5)
    Missing1573,181
Absolute weight gain during pregnancy mean (SD)12.4 (4.8)12.5 (4.8)0.3
Method of delivery0.4
    Spontaneous1067 (75)9,185 (76)
    Other356 (25)2,901 (24)
    missing61,363
Pre-eclampsia0.4
    Yes92 (7)858 (7)
    No1,332 (93)11,178 (93)
    missing51,413
Gestational diabetes0.6
    Yes10 (1)100 (1)
    No1,418 (99)12,199 (99)
    Missing11,150
Gestational weight gain0.7
    <recommended459 (39)3,529 (39)
    Recommended403 (34)3,050 (34)
    >Recommended259 (26)2,490 (27)
    missing2594,380
Gestational weight gain >40lbs0.5
    No1,203 (90)9,792 (89)
    Yes140 (10)1,219 (11)
    missing862,438
Child Characteristics
Gender0.02
    Male772 (54)6,828 (51)
    Female657 (46)6,621 (49)
Race
    White1,293 (96)10,169 (95)0.01
    Non-white47 (4)562 (5)
    Missing892,718
Gestational age at delivery mean (SD)39 (1.7)39 (1.9)0.2

CIF- Children in Focus; absolute weight gain-difference between last and first weight measurement

Estimates are N (%) unless otherwise noted

CIF- Children in Focus; absolute weight gain-difference between last and first weight measurement Estimates are N (%) unless otherwise noted Among the CIF mothers, the mean (SD) prepregnancy BMI was 23 (4.1) kg/m2, with 5% being underweight, 71% were of normal weight, 16% and 7% respectively were overweight and obese. The majority gave birth spontaneously (75%), and 34% had gestational weight gain within the IOM recommended level for their prepregnancy BMI category, 39% had less than the recommended GWG level and 26% more than the recommended level (Table 1). Being overweight/obese prepregnancy was associated with greater unadjusted offspring caries experience risk at 31-months, 43-months and 61-months. Specifically, the caries experience risk for offspring of mothers who were overweight/obese prepregnancy was 21% at 31-months, 27% at 43-months and 36% at 61-months as compared to 18%, 23% and 33% for their underweight/normal weight counterparts at 31-months, 43-months and 61-months respectively. Similarly, caries experience risk was higher for mothers with less and more than the IOM recommended GWG levels as compared to those in the recommended weight gain category. For instance, the offspring caries experience risk was 18% at 31-months for those in the recommended GWG group as compared to 20% in the recommended GWG group (Table 2).
Table 2

Risks and relative risks of the associations between pre-pregnancy BMI, gestational weight gain and offspring caries experience: Avon longitudinal study of parents and children (= 1,429).

31 monthsUnadjusted43 monthsUnadjusted61 monthsUnadjusted
Total NN casesRis*RR (95% CI)*N casesRisk*RR (95% CI)***N casesRisk*RR (95% CI)***
Pre-pregnancy BMI
Underweight/ ≤Normal1,0911990.182Ref.2490.228Ref.3590.329Ref.
Overweight/Obese338720.2131.16 (0.90, 1.51)920.271.20 (0.96, 1.49)1210.3581.09 (0.91, 1.30)
GWG (IOM)
<recommended4941000.2031.13 (0.86, 1.48)1250.2531.17 (0.92, 1.48)1650.3331.04 (0.87, 1.25)
recommended545980.179Ref.1180.216Ref.1740.320Ref.
>recommended390730.1871.04 (0.78, 1.40)980.2521.14 (0.91, 1.50)1410.3611.13 (0.93, 1.36)
GWG (>40lbs)
No1,2792460.192Ref.3090.241Ref.4260.333Ref.
Yes150250.1670.90 (0.61, 1.33)320.2160.89 (0.64, 1.25)550.3631.09 (0.86, 1.38)

*unadjusted risks

All estimates were averages from 40 rounds of multiple imputation combined using Rubin’s rule and the variance a function of the within and between completed dataset variances.

*unadjusted risks All estimates were averages from 40 rounds of multiple imputation combined using Rubin’s rule and the variance a function of the within and between completed dataset variances. While our unadjusted and adjusted findings indicated greater 31-month, 43-month and 61-month caries experience risk among offspring of mothers that were overweight/obese prepregnancy, and offspring of mothers who gained less or more than the recommended weight during pregnancy, none of the associations were statistically significant. Furthermore, the associations were strongest for caries experience at 43-months than either of the other two time points, with the adjusted estimates at 61-months being null. For instance, being overweight/obese prepregnancy was associated with unadjusted RR (95% CI) of offspring caries at 31-months of 1.16 (0.90, 1.51), 1.20 (0.96, 1.49) at 43-months and 1.09 (0.91, 1.30) at 61-months (Table 2). The corresponding adjusted estimates were attenuated towards the null and remained statistically non-significant. For instance, prepregnancy overweight/ obesity was associated with the following adjusted offspring caries experience risk: 1.11 (0.85, 1.45) at 31-months, 1.12 (0.90, 1.39) at 43-months and 1.01 (0.85, 1.21) at 61-months (Table 3).
Table 3

Adjusted associations between pre-pregnancy BMI, gestational weight gain and offspring caries experience: Avon longitudinal study of parents and children (N = 1,429).

31 months43 months61 months
Adjusted RR (95% CI)*Adjusted RR (95% CI)***Adjusted RR (95% CI)***
Pre-pregnancy BMI
Underweight/normalRef.Ref.Ref.
Overweight/obese1.11 (0.85, 1.45)1.12 (0.90, 1.39)1.01 (0.85, 1.21)
GWG (IOM)
<recommended1.10 (0.84, 1.42)1.13 (0.90, 1.42)1.02 (0.85, 1.22)
= recommendedRef.Ref.Ref.
>recommended1.01 (0.76, 1.35)1.12 (0.87, 1.44)1.02 (0.92, 1.33)
GWG (>40lbs)
NoRef.Ref.Ref.
Yes0.90 (0.61, 1.33)0.94 (0.67, 1.32)1.13 (0.90, 1.41)

Adjusted for maternal age, education, child gender, Tooth brushing frequency, method of delivery, hypertension, diabetes, race, prenatal smoking, and number of moves in the last 5 years

All estimates were averages from 40 rounds of multiple imputation combined using Rubin’s rule and the variance a function of the within and between completed dataset variances

Adjusted for maternal age, education, child gender, Tooth brushing frequency, method of delivery, hypertension, diabetes, race, prenatal smoking, and number of moves in the last 5 years All estimates were averages from 40 rounds of multiple imputation combined using Rubin’s rule and the variance a function of the within and between completed dataset variances Children of mothers with GWG less than recommended had higher unadjusted caries experience at the three time points studied than children of mothers in the recommended GWG category. The RR (95% CI) for caries experience at 31-months was 1.13 (0.86, 1.48), 1.17 (0.92, 1.48) at 43-months and 1.04 (0.87, 1.25) at 61-months (Table 2). The corresponding estimates for children of mothers with GWG more than recommended were respectively 1.04 (0.78, 1.40), 1.14 (0.91, 1.50) and 1.13 (0.93, 1.36). The adjusted estimates were likewise attenuated towards the null and remained statistically non-significant (Table 3).

Discussion

The current study found insufficient evidence to indicate an association between prepregnancy BMI and gestational weight gain on the risk of offspring caries experience. Our study focused on prepregnancy BMI and gestational weight gain as opposed to prenatal BMI as done by other studies that found an association. Indeed, Julihn et al., reported caries increment among teenagers of mothers who were overweight during pregnancy [24] and a higher caries experience risk in 3 and 7 year old Swedish children exposed to prenatal obesity [33]. Likewise Wigen et al., reported maternal overweight and obesity to be a risk indicator for caries experience among 5 year old Norwegian children [25]. A study of 6 year old, mono and dizygotic twins [34] likewise reported positive associations between maternal obesity and cavitated carious lesions and with concordance between monozygotic and dizygotic twins, indicating that shared and non-shared environmental factors predominate over genetic factors in determining variation in caries risk in children. On the contrary, Un Lam C et al., in a study of prenatal, perinatal and postnatal predictors of early childhood caries failed to identify maternal BMI during the prenatal period as a risk factor for ECC of 2-year-old children [35]. Of note many of the studies that reported significant associations did not adjust for caries risk factors such as sugar intake, tooth brushing frequency, method of delivery (that have the potential to affect the oral microbiome composition and subsequent caries risk), breast feeding duration except for Silva MJ et al., [34] and Un Lam C et al., [35]. The relationship between maternal BMI and offspring dental caries is complex because it is difficult to determine if caries risk is due to biological influences on the child or developing fetus, or a transfer of dietary habits, or perhaps confounding by social, environmental and other unknown factors. Furthermore, the intrauterine environment of maternal obesity may lead to epigenetic changes that result in fetal programming that could result in future susceptibility to dental caries [36]. Pregnancy is an ideal time to focus on health promoting activities before the onset of disease given that most women have regular interactions with health care professionals [7]. High maternal prepregnancy BMI increases the risk of offspring obesity [11, 37], which is a risk factor for caries experience in the offspring [35, 38, 39]. The weak association we found for prepregnancy BMI and offspring caries may thus, be a reflection of prepregnancy BMI being a more distal risk factor in comparison to obesity in the offspring. Of note, our study assessed weight gain during pregnancy according to levels recommended by the IOM for different prepregnancy BMI groups. We found gestational weight gain less and more that recommended was associated with greater offspring caries experience risk, although not statistically significant. Presumably, an underweight woman may gain more than the recommended levels for her prepregnancy BMI group to put her into a normal BMI group or perhaps an overweight BMI group during pregnancy. Given that the BMI group a woman might fall into is likely to vary, this may also partly explain the inconclusive and sometimes null findings that we found that contradicts findings from previous studies that reported a positive association between prenatal BMI and offspring caries experience. Prepregnancy obesity and excessive gestational weight gain are risk factors for fetal macrosomia, cesarean delivery, hyperinsulinemia in infancy, and metabolic syndrome in childhood [13]. Maternal weight exceeding 200 pounds and gestational weight gain of more than 40 pounds have each been found to be associated with increased risk of autism and other developmental disabilities in the child [40]. Thus, we also conducted additional analysis of gestational weight gain in excess of 40 pounds on the risk of ECC and the results were similarly inconclusive as the main analysis suggests (Table 2). While the predictors of ECC by Un Lam C et al., [35], found biological factors such as maternal age, and education more so than psychobehavioral factors, such as tooth brushing frequency as strong predictors of ECC, the current study adjusted for toothbrushing frequency and sugar intake as behavioral factors as well as maternal age, race, and education as adjustment covariates because they represent confounders of the association between prepregnancy BMI, gestational weight gain and offspring caries. Thus, their respective independent associations on the risk on ECC will require adjustments for different sets of covariates as potential confounders [41] and that was not the purpose of this study. Given that our study was not predictive in nature, we focused on reporting the findings of our main exposures, prepregnancy BMI, gestational weight gain associations on the risk of ECC.

Limitations and strengths

Oral examination data was available only on a fraction of the children and the methodology used (i.e., dmft index) measured cavitated lesions and therefore likely to underestimate dental caries that are still in the incipient phase (white spot lesions) of development. Thus, if we had data on incipient caries lesions, the prevalence of ECC might have been higher and the reported association stronger. The non-diverse study population may limit statistical inference to other population subgroups but not necessarily the scientific inference of our findings [42]. Our sample size of 1,429 might not have been sufficiently large enough for us to detect meaningful effects especially given that prepregnancy BMI and gestational weight gain are more distal factors on the causal pathway to ECC and thus will have small effects that our small sample prevented us from detecting. Study strengths include the longitudinal nature and the ability to minimize temporal ambiguity. Contemporaneous determination of weight during pregnancy allowed for the estimation of gestational weight gain. Furthermore, the availability of objectively assessed oral examination data at three time points represents another of this study’s strengths. Lastly, we had access to several covariates on the mother and child that allowed us control for relevant confounding factors as well as risk factors for ECC in an attempt to minimize bias. (DOCX) Click here for additional data file. 13 Dec 2021
PONE-D-21-29637
Prepregnancy BMI, gestational weight gain and offspring caries experience: Avon Longitudinal Study of Parents and Children.
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Please remove any funding-related text from the manuscript and let us know how you would like to update your Funding Statement. Currently, your Funding Statement reads as follows: “This work was supported by the National Institutes of Health/National Institute of Dental and Craniofacial Research (Grant No.: R03DE028403 and L40DE028120) to A.A.  https://www.nidcr.nih.gov/ The views expressed are solely the authors and does not represent the official views of the NIH/NIDCR.  The funding source was not involved in the design, analysis, interpretation or decision to submit this article for publication.” Please include your amended statements within your cover letter; we will change the online submission form on your behalf. 4. We note that you have indicated that data from this study are available upon request. PLOS only allows data to be available upon request if there are legal or ethical restrictions on sharing data publicly. For more information on unacceptable data access restrictions, please see http://journals.plos.org/plosone/s/data-availability#loc-unacceptable-data-access-restrictions. In your revised cover letter, please address the following prompts: a) If there are ethical or legal restrictions on sharing a de-identified data set, please explain them in detail (e.g., data contain potentially sensitive information, data are owned by a third-party organization, etc.) and who has imposed them (e.g., an ethics committee). Please also provide contact information for a data access committee, ethics committee, or other institutional body to which data requests may be sent. b) If there are no restrictions, please upload the minimal anonymized data set necessary to replicate your study findings as either Supporting Information files or to a stable, public repository and provide us with the relevant URLs, DOIs, or accession numbers. For a list of acceptable repositories, please see http://journals.plos.org/plosone/s/data-availability#loc-recommended-repositories. We will update your Data Availability statement on your behalf to reflect the information you provide. 5. We note you have included a table to which you do not refer in the text of your manuscript. Please ensure that you refer to Table 3 in your text; if accepted, production will need this reference to link the reader to the Table. Reviewers' comments: Reviewer's Responses to Questions Comments to the Author 1. Is the manuscript technically sound, and do the data support the conclusions? The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented. Reviewer #1: Partly Reviewer #2: Yes ********** 2. Has the statistical analysis been performed appropriately and rigorously? Reviewer #1: Yes Reviewer #2: Yes ********** 3. Have the authors made all data underlying the findings in their manuscript fully available? The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified. Reviewer #1: Yes Reviewer #2: Yes ********** 4. Is the manuscript presented in an intelligible fashion and written in standard English? PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here. Reviewer #1: Yes Reviewer #2: Yes ********** 5. 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: The authors have to be commented for looking into the ALSPAC data from a different perspective. However, I do have some concerns in regards to the correlations made without taking into consideration important co-founding factors. Below are my comments for improvement of the manuscript if it is selected for publication. Introduction: 1. Generally in the manuscript many times the authors combine information in the same sentence on different topics. Editing of the manuscript, using shorter sentences and more references. For example, the last sentence of the first paragraph "Pregnancy weight....normal weight women" presents the effect of pregnancy weight on birth and childhood obesity and combines this information with treatment cost which is irrelevant. I think that many of the sentences need further development to conclude to the need for this study. 2. Many times the authors make speculations ex. maternal adiposity leads to prematurity that is associated with developmental defects which are more susceptible to cariogenic bacteria, meaning higher caries. The literature data does not suggest any of this. The authors should be more careful in their wording and present this as a speculation that will be investigated through this study. 3. The main findings from the literature that can state the argument for the aim of the study in the fourth paragraph are not developed. 4. The last paragraph should be omitted or should be placed higher in the introduction to help the argument for the need of this study. Materials & Method (is not in a title in the manuscript) 1. I am concerned about the time that these data were collected (1991/1992). There have been many changes in the diet and caries risk of children, as well as to the level of obesity of pregnant women ever since and I think that these data is outdated. 2. Many times in the manuscript the age of collection data is presented in months and some times in months and years. There must be some consistency for the reader. 3. Dental caries is recorded as yes or no. White spot lesions are considered important for caries risk in preschool children. Thus, dental caries prevalence using yes or no is not sufficient for this age group. 4. Maternal caries is a very important factor in caries prevalence of preschool children and it was not recorded. In general, caries is a multifactorial disease if all these factors (maternal caries, dietary habits, toothbrushing, breastfeeding habits) are not put in the model I am not sure the results can be accurate. The authors report that toothbrushing, diet and breastfeeding were recorded but these data are not described in the results. Results I don't see why the data from the non-CIF should be presented in the manuscript since the aim is to correlate caries and nonCIF pairs did not have any caries data. Discussion 1. Many of the factors were not discussed in the manuscript, as well as the many limitations of the study. The discussion is very limited and insufficient to support the findings of the study. 2. One of the main findings were the fact that less than recommended GWG was associated with higher caries. How do the authors explain this finding? Reviewer #2: This study is one that analyzed the association between mother’s prepregnancy BMI and gestational weight gain, and children’s dental caries. Overall, this study is well organized. The viewpoint of authors is of interest. However, there are some points to improve. Results Data of caries status of subjects (dmf and rate of having caries) is not seen in this study. Discussion The influence of difference in mother’s characteristics between CIF sample and non-CIF sample should be discussed. For example, lower smoking and higher education might lower dental caries overall. The date available in this study is old (expected date of delivery between 1991 and 1992). Authors must explain that this old data is still applicable to current state. ********** 6. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files. If you choose “no”, your identity will remain anonymous but your review may still be made public. Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy. Reviewer #1: No Reviewer #2: No [NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.] While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step. 22 Jan 2022 The authors thank the reviewers for the time and effort spent reviewing our manuscript: “PONE-D-21-29637, Prepregnancy BMI, gestational weight gain and offspring caries experience: Avon Longitudinal Study of Parents and Children”. Our response to reviewers’ comments appears below and in track changes in the actual manuscript draft. We have also reformatted our manuscript to adhere to the journal formatting requirements, updated the cover letter with funding information and data access policy. Reviewers' comments: Reviewer's Responses to Questions Comments to the Author 1. Is the manuscript technically sound, and do the data support the conclusions? The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented. Reviewer #1: Partly Reviewer #2: Yes 2. Has the statistical analysis been performed appropriately and rigorously? Reviewer #1: Yes Reviewer #2: Yes 3. Have the authors made all data underlying the findings in their manuscript fully available? The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified. Reviewer #1: Yes Reviewer #2: Yes 4. Is the manuscript presented in an intelligible fashion and written in standard English? PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here. Reviewer #1: Yes Reviewer #2: Yes 5. 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: The authors have to be commented for looking into the ALSPAC data from a different perspective. However, I do have some concerns in regards to the correlations made without taking into consideration important co-founding factors. Below are my comments for improvement of the manuscript if it is selected for publication. Introduction: 1. Generally in the manuscript many times the authors combine information in the same sentence on different topics. Editing of the manuscript, using shorter sentences and more references. For example, the last sentence of the first paragraph "Pregnancy weight....normal weight women" presents the effect of pregnancy weight on birth and childhood obesity and combines this information with treatment cost which is irrelevant. I think that many of the sentences need further development to conclude to the need for this study. Response: Thank you for your comment. The first paragraph the reviewer referred described the prevalence of overweight and obesity in pregnancy, the consequence of this on the offspring including the impact in terms of costs on the health care system. All of these point to or highlight the significance of studying this condition in pregnancy. 2. Many times the authors make speculations ex. maternal adiposity leads to prematurity that is associated with developmental defects which are more susceptible to cariogenic bacteria, meaning higher caries. The literature data does not suggest any of this. The authors should be more careful in their wording and present this as a speculation that will be investigated through this study. Response: Thank you for your comments. We made no speculations at all. The sentence the reviewer referred to is properly cited for the interested reader. 3. The main findings from the literature that can state the argument for the aim of the study in the fourth paragraph are not developed. Response: Thank you for your comment. There is not a lot of literature out there to the authors knowledge that has investigated this topic. Based on the limited literature we are aware of and based on findings from a previous study on teenagers, we are conducting this study. The significance of the pregnancy weight and offspring dental caries are described in earlier paragraphs of the introduction section. 4. The last paragraph should be omitted or should be placed higher in the introduction to help the argument for the need of this study. Response: We have added this paragraph to an earlier section of the introduction Materials & Method (is not in a title in the manuscript) 1. I am concerned about the time that these data were collected (1991/1992). There have been many changes in the diet and caries risk of children, as well as to the level of obesity of pregnant women ever since and I think that these data is outdated. Response: We agree that the data is dated. Nevertheless, the prevalence of dental caries as well as overweight and obesity in this dataset are comparable to contemporary US benchmarks. Please note that the purpose of this study is to determine to the extent possible and within the limitations of this data if overweight and obesity in pregnancy affects dental caries occurrence in the offspring. The is an etiological question that has nothing to do with the prevalence of these conditions. 2. Many times in the manuscript the age of collection data is presented in months and some times in months and years. There must be some consistency for the reader. Response: Age at dental caries assessment has been updated throughout the manuscript to age in months 3. Dental caries is recorded as yes or no. White spot lesions are considered important for caries risk in preschool children. Thus, dental caries prevalence using yes or no is not sufficient for this age group. We agree and we stated this in the limitations section. As a matter of fact, it is likely that dental caries is underestimated since the dmft index only measures cavitated lesions. The ALSPAC study has only measured dental cavitated lesions and not white spot lesion/incipient caries. 4. Maternal caries is a very important factor in caries prevalence of preschool children and it was not recorded. In general, caries is a multifactorial disease if all these factors (maternal caries, dietary habits, toothbrushing, breastfeeding habits) are not put in the model I am not sure the results can be accurate. The authors report that toothbrushing, diet and breastfeeding were recorded but these data are not described in the results. Response: We agree that these are important variables, which we described in Table 1 and noted on our causal diagram S1 Fig. Based on our causal diagram in S1 Fig and the analysis of this causal diagram for potential confounders to adjust for, we adjusted for a sufficient covariate subset to block all confounding pathways and leave open all causal pathways. To avoid committing “Table 2 fallacy” we cannot independently report the findings of the variables the reviewers pointed out on dental caries since they were not the primary predictors. Please refer to Weistrech et al 2010 for more information on this fallacy Results I don't see why the data from the non-CIF should be presented in the manuscript since the aim is to correlate caries and nonCIF pairs did not have any caries data. Response: This is to determine if the CIF and non-CIF mothers and children differ in any of their baseline covariates. i.e., to see if there are systematic differences between these groups. The data of the non-CIF were not utilized beyond what was described in Table 1. Discussion 1. Many of the factors were not discussed in the manuscript, as well as the many limitations of the study. The discussion is very limited and insufficient to support the findings of the study. Response: We discussed the findings of our analysis of whether pre-pregnancy BMI, and pregnancy weight are associated with offspring caries experience. Again, there is not a lot of literature out there to the authors knowledge to compare and contrast our findings with and we avoided making speculations beyond what an epidemiological study can tell us. 2. One of the main findings were the fact that less than recommended GWG was associated with higher caries. How do the authors explain this finding? Response: Yes, the magnitude of the effect was small and not statistically significant Reviewer #2: This study is one that analyzed the association between mother’s prepregnancy BMI and gestational weight gain, and children’s dental caries. Overall, this study is well organized. The viewpoint of authors is of interest. However, there are some points to improve. Results Data of caries status of subjects (dmf and rate of having caries) is not seen in this study. Response: We reported this information in the results section as : Three percent of the CIF had dmft ≥1 at 31 months, 16% at 43-months and 31% had dmft ≥1 at 61 months. Discussion The influence of difference in mother’s characteristics between CIF sample and non-CIF sample should be discussed. For example, lower smoking and higher education might lower dental caries overall. The date available in this study is old (expected date of delivery between 1991 and 1992). Authors must explain that this old data is still applicable to current state. Response: While the prevalence of prenatal smoking (22%) in the ALSPAC cohort [Macdonald-Wallis et al., 2011] was higher than contemporary U.S. benchmarks of 9-14% [Kurti et al., 2017, Berlin and Oncken, 2018], 25% of 5 year-olds in the ALSPAC study experienced caries [Kay et al., 2010], as have similarly aged contemporary U.S. children [Dye et al., 2015]. Oral examination data was available only on a fraction of the children and the methodology used (i.e. dmft index) measured cavitated lesions. This is in contrast to contemporary methods like the international caries detection and assessment system (ICDAS) that records dental caries on a continuum that includes incipient lesions. In spite of this, the underlying biologic mechanism for the proposed association is undated and applicable even today. 6. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files. If you choose “no”, your identity will remain anonymous but your review may still be made public. Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy. Reviewer #1: No Reviewer #2: No Submitted filename: Response to Reviewers.docx Click here for additional data file. 18 Feb 2022
PONE-D-21-29637R1
Prepregnancy BMI, gestational weight gain and offspring caries experience: Avon Longitudinal Study of Parents and Children.
PLOS ONE Dear Dr. Akinkugbe, 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. Please submit your revised manuscript by Apr 04 2022 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file. Please include the following items when submitting your revised manuscript:
A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'. A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'. An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'. If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter. If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: https://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols. Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols. We look forward to receiving your revised manuscript. Kind regards, Angela Lupattelli, PhD Academic Editor PLOS ONE Additional Editor Comments (if provided): Dear authors, multiple comments received in the first review round have not been addressed, eg amendment of the Discussion section and expansion on the Limitations of the study (Reviewer 1, comment 10). Please respond to these comments and make appropriate changes to the Discussion section, as recommended. 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) ********** 2. Is the manuscript technically sound, and do the data support the conclusions? The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented. Reviewer #1: No ********** 3. Has the statistical analysis been performed appropriately and rigorously? Reviewer #1: Yes ********** 4. Have the authors made all data underlying the findings in their manuscript fully available? The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified. Reviewer #1: Yes ********** 5. Is the manuscript presented in an intelligible fashion and written in standard English? PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here. Reviewer #1: Yes ********** 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: Some corrections were made, however the authors did not response to the major limitations in the methodology and for this reason I do not think it is suitable for publication. ********** 7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files. If you choose “no”, your identity will remain anonymous but your review may still be made public. Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy. Reviewer #1: No [NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.] While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step. 15 Mar 2022 The authors thank the reviewers for the second round of review of our manuscript: “PONE-D-21-29637R1, Prepregnancy BMI, gestational weight gain and offspring caries experience: Avon Longitudinal Study of Parents and Children”. Our response to reviewers’ comments appears below and in track changes in the actual manuscript draft. Please note that the latest iteration of track changes is only for the reviewers remaining concerns and does not include track changes from the previous submission which has been disabled. Comments to the Author Additional Editor Comments (if provided): Dear authors, multiple comments received in the first review round have not been addressed, eg amendment of the Discussion section and expansion on the Limitations of the study (Reviewer 1, comment 10). Please respond to these comments and make appropriate changes to the Discussion section, as recommended. Authors’ response: Pasted below are the specific comments related to the discussion section from the previous review and our response to those comments Discussion 1. Many of the factors were not discussed in the manuscript, as well as the many limitations of the study. The discussion is very limited and insufficient to support the findings of the study. Response: We discussed the findings of our analysis of whether pre-pregnancy BMI, and pregnancy weight are associated with offspring caries experience. Again, there is not a lot of literature out there to the authors knowledge to compare and contrast our findings with and we avoided making speculations beyond what an epidemiological study can tell us. Updated response: Please note that the association between adjustment covariates and the outcome of ECC was not the primary purpose of this study. Because we have not accounted for the confounding structure between those adjustment covariates and ECC, discussing their individual association from a model of pre-pregnancy BMI, and pregnancy weight and ECC is fallacious (please refer to the paper by Westreich and Greenland 2013 for detail of this fallacy) 2. One of the main findings were the fact that less than recommended GWG was associated with higher caries. How do the authors explain this finding? Response: Yes, the magnitude of the effect was small and not statistically significant Updated response: The following text has been added to the discussion “The weak association we found for prepregnancy BMI and offspring caries may thus, be a reflection of prepregnancy BMI being a more distal risk factor in comparison to obesity in the offspring.” “Of note, our study assessed weight gain during pregnancy according to levels recommended by the IOM for different prepregnancy BMI groups. We found gestational weight gain less and more that recommended was associated with greater offspring caries experience risk, although not statistically significant.” 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) ________________________________________ 2. Is the manuscript technically sound, and do the data support the conclusions? The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented. Reviewer #1: No ________________________________________ 3. Has the statistical analysis been performed appropriately and rigorously? Reviewer #1: Yes ________________________________________ 4. Have the authors made all data underlying the findings in their manuscript fully available? The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified. Reviewer #1: Yes ________________________________________ 5. Is the manuscript presented in an intelligible fashion and written in standard English? PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here. Reviewer #1: Yes ________________________________________ 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: Some corrections were made, however the authors did not response to the major limitations in the methodology and for this reason I do not think it is suitable for publication. Response: The authors do not understand the specific concern that the reviewer has with our manuscript or the limitations with the methodology that we have not addressed. Nevertheless, we have expanded the discussion section and the limitation section in the revised manuscript. We also want to point that the association between adjustment covariates and the outcome of ECC was not the primary purpose of this study. Because we have not accounted for the confounding structure between those adjustment covariates and ECC, discussing their individual association from a model of pre-pregnancy BMI, and pregnancy weight and ECC is fallacious (please refer to the paper by Westreich and Greenland 2013 for detail of this fallacy) Furthermore, the following text has been added to the discussion “The weak association we found for prepregnancy BMI and offspring caries may thus, be a reflection of prepregnancy BMI being a more distal risk factor in comparison to obesity in the offspring.” “Of note, our study assessed weight gain during pregnancy according to levels recommended by the IOM for different prepregnancy BMI groups. We found gestational weight gain less and more that recommended was associated with greater offspring caries experience risk, although not statistically significant.” ________________________________________ 7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files. If you choose “no”, your identity will remain anonymous but your review may still be made public. Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy. Reviewer #1: No Submitted filename: Response to Reviewers2.docx Click here for additional data file. 17 Mar 2022 Prepregnancy BMI, gestational weight gain and offspring caries experience: Avon Longitudinal Study of Parents and Children. PONE-D-21-29637R2 Dear Dr. Akinkugbe, 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. An invoice for payment will follow shortly after the formal acceptance. To ensure an efficient process, please log into Editorial Manager at http://www.editorialmanager.com/pone/, click the 'Update My Information' link at the top of the page, and double check that your user information is up-to-date. If you have any billing related questions, please contact our Author Billing department directly at authorbilling@plos.org. If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. 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. Kind regards, Angela Lupattelli, PhD Academic Editor PLOS ONE 23 Mar 2022 PONE-D-21-29637R2 Prepregnancy BMI, Gestational Weight Gain And Offspring Caries Experience: Avon Longitudinal Study Of Parents And Children. Dear Dr. Akinkugbe: 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. If we can help with anything else, please email us at plosone@plos.org. Thank you for submitting your work to PLOS ONE and supporting open access. Kind regards, PLOS ONE Editorial Office Staff on behalf of Dr. Angela Lupattelli Academic Editor PLOS ONE
  40 in total

1.  The role of prenatal, obstetric and neonatal factors in the development of autism.

Authors:  Linda Dodds; Deshayne B Fell; Sarah Shea; B Anthony Armson; Alexander C Allen; Susan Bryson
Journal:  J Autism Dev Disord       Date:  2011-07

2.  Contribution of overweight and obesity to the occurrence of adverse pregnancy outcomes in a multi-ethnic cohort: population attributive fractions for Amsterdam.

Authors:  A A A M J Djelantik; A E Kunst; M F van der Wal; H A Smit; T G M Vrijkotte
Journal:  BJOG       Date:  2011-12-13       Impact factor: 6.531

3.  Why representativeness should be avoided.

Authors:  Kenneth J Rothman; John E J Gallacher; Elizabeth E Hatch
Journal:  Int J Epidemiol       Date:  2013-08       Impact factor: 7.196

4.  Prepregnancy Body Mass Index by Maternal Characteristics and State: Data From the Birth Certificate, 2014.

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Journal:  Natl Vital Stat Rep       Date:  2016-08

5.  Maternal health and lifestyle, and caries experience in preschool children. A longitudinal study from pregnancy to age 5 yr.

Authors:  Tove I Wigen; Nina J Wang
Journal:  Eur J Oral Sci       Date:  2011-09-27       Impact factor: 2.612

6.  Prevalence of obesity and trends in the distribution of body mass index among US adults, 1999-2010.

Authors:  Katherine M Flegal; Margaret D Carroll; Brian K Kit; Cynthia L Ogden
Journal:  JAMA       Date:  2012-01-17       Impact factor: 56.272

7.  Multiple imputation using chained equations: Issues and guidance for practice.

Authors:  Ian R White; Patrick Royston; Angela M Wood
Journal:  Stat Med       Date:  2010-11-30       Impact factor: 2.373

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Authors:  Debbie A Lawlor; Caroline Relton; Naveed Sattar; Scott M Nelson
Journal:  Nat Rev Endocrinol       Date:  2012-09-25       Impact factor: 43.330

9.  Smoking cessation increases gingival blood flow and gingival crevicular fluid.

Authors:  Toshiya Morozumi; Takehiko Kubota; Tadashi Sato; Kazuhiro Okuda; Hiromasa Yoshie
Journal:  J Clin Periodontol       Date:  2004-04       Impact factor: 8.728

10.  Cohort Profile: the 'children of the 90s'--the index offspring of the Avon Longitudinal Study of Parents and Children.

Authors:  Andy Boyd; Jean Golding; John Macleod; Debbie A Lawlor; Abigail Fraser; John Henderson; Lynn Molloy; Andy Ness; Susan Ring; George Davey Smith
Journal:  Int J Epidemiol       Date:  2012-04-16       Impact factor: 7.196

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