The impact of breastfeeding on facial appearance in adolescent children

Seppe Goovaerts; Ahmed M. El Sergani; Myoung Keun Lee; John R. Shaffer; Peter Claes; Seth M. Weinberg

doi:10.1371/journal.pone.0310538

Abstract

Evidence that breastfeeding impacts the facial features of children is conflicting. Most studies to date have focused on dental and skeletal malocclusion. It currently remains unclear whether such effects are of sufficient magnitude to be detectable on outward facial appearance. Here, we evaluate the extent to which maternally reported breastfeeding is associated with 3D facial shape in a large adolescent cohort. After extracting 3D facial surfaces from MR scans in 2275 9- and 10-year-old children and aligning the surfaces in dense correspondence, we analyzed the effect of breastfeeding on shape as a dichotomous (no/yes) and semi-quantitative (to assess duration in months) variable using partial least squares regression. Our results showed no effect (p = 0.532) when breastfeeding was dichotomized. However, when treated as a semi-quantitative variable, breastfeeding duration was associated with statistically significant changes in shape (p = 3.61x 10⁻⁴). The most prominent facial changes included relative retrusion of the central midface, zygomatic arches, and orbital regions along with relative protrusion of forehead, cheek, and mandible. The net effect was that as breastfeeding duration increased, the facial profile in children became flatter (less convex). The observed effects on the face, however, were subtle and likely not conspicuous enough to be noticed by most observers. This was true even when comparing the faces of children breastfed for 19–24 months to children with no reported breastfeeding. Thus, breastfeeding does appear to have detectable effect on outward facial appearance in adolescent children, but its practical impact appears to be minimal.

Citation: Goovaerts S, El Sergani AM, Lee MK, Shaffer JR, Claes P, Weinberg SM (2024) The impact of breastfeeding on facial appearance in adolescent children. PLoS ONE 19(9): e0310538. https://doi.org/10.1371/journal.pone.0310538

Editor: James J. Cray Jr., Ohio State University, UNITED STATES OF AMERICA

Received: March 14, 2024; Accepted: September 3, 2024; Published: September 17, 2024

Copyright: © 2024 Goovaerts et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: The data used in this analysis is from the NIH-funded ABCD Study. All the data including MR scans, breastfeeding variables and all relevant covariates are available through the controlled access NIMH data archive (NDA) (https://nda.nih.gov/abcd/). The ABCD data used in this report came from stable data release 3.0 (February 2020). The dataset was accessed on February 17, 2021.

Funding: Data used in the preparation of this article were obtained from the Adolescent Brain Cognitive Development (ABCD) Study (https://abcdstudy.org), held in the NIMH Data Archive (NDA). This is a multisite, longitudinal study designed to recruit more than 10,000 children age 9–10 and follow them over 10 years into early adulthood. The ABCD Study is supported by the National Institutes of Health and additional federal partners under award numbers U01DA041048, U01DA050989, U01DA051016, U01DA041022, U01DA051018, U01DA051037, U01DA050987, U01DA041174, U01DA041106, U01DA041117, U01DA041028, U01DA041134, U01DA050988, U01DA051039, U01DA041156, U01DA041025, U01DA041120, U01DA051038, U01DA041148, U01DA041093, U01DA041089, U24DA041123, U24DA041147. A full list of supporters is available at https://abcdstudy.org/federal-partners.html. A listing of participating sites and a complete listing of the study investigators can be found at https://abcdstudy.org/consortium_members/. ABCD consortium investigators designed and implemented the study and/or provided data but did not necessarily participate in analysis or writing of this report. This manuscript reflects the views of the authors and may not reflect the opinions or views of the NIH or ABCD consortium investigators. Additional funding was provided by the National Institute for Dental and Craniofacial Research (http://www.nidcr.nih.gov/) through the following grants: R01DE027023 (SMW, JRS, PC). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing interests: The authors have declared that no competing interests exist.

Introduction

Breastfeeding has numerous well-established benefits for both babies and mothers [1], most of which have to do with the nutritional and protective factors contained in breastmilk. Within the field of dentistry, some experts assert that breastfeeding is also beneficial for early facial growth and may even be conceptualized as a form of “early functional jaw orthopedics” [2]. The rationale for the claim is that breast suckling, as opposed to bottle feeding and non-nutritive sucking behaviors, produces forward traction forces and engages masticatory muscles that stimulate the coordinated growth of the midface and mandible [3, 4]. The mechanical forces involved in breastfeeding have been described in detail [5]. However, the evidence base supporting the link between breastfeeding and facial form is less solid.

Many studies have investigated the effects of breastfeeding on orofacial form and growth. These studies generally fall within the orthodontics literature and focus on measures of dental and/or skeletal malocclusion. The results of these studies are highly variable with some finding no relationship [6–8] and others reporting significant and clinically relevant effects. For the studies that do report an association, breastfeeding has been found to reduce the incidence of posterior crossbite and anterior open bite [9–14] and impact maxillofacial form, including palatal arch dimensions [15, 16]. Differences in study design, measurement approaches, and study samples are all factors contributing to these variable outcomes, making it difficult to draw definitive conclusions. Several reviews have tried to make sense of the discrepant findings [17–23]. Of these, two systematic reviews found no or equivocal evidence of a relationship between breastfeeding and malocclusion [18, 19]. In contrast, the two available meta-analyses found some evidence of association. Boronat-Catalá et al. [20] reported that breastfeeding is protective against class II malocclusion and posterior crossbite and that this protective effect increases as breastfeeding duration increases. Likewise, Thomaz et al. [21] reported that breast feeding for at least six months was protective against overjet, open bite, posterior crossbite and this protective effect increased when the breastfeeding extended to 12 months. Thus, the weight of evidence based on these prior studies suggests that breastfeeding likely reduces the risk of several common types of malocclusion.

A key limitation of prior studies is that very few focus on facial soft tissues and the ones that do only consider the face in 2D cephalometric profile, which can only capture a limited amount of facial geometry. Thus, it is unclear to what degree the purported effects translate to outward facial appearance, i.e., what a person sees in the mirror and presents to the world. In this retrospective study, we examine the relationship between breastfeeding during infancy and 3D facial surface shape in a large sample of US adolescent boys and girls. We modeled the effects in two ways: as a simple binary trait (no breastfeeding vs any amount of breastfeeding) and as semi-continuous variable (duration of breastfeeding in months). Based on previously published work, we predict the largest effects would involve the mandible and midface. However, the morphometric methods we employ here cover the full 3D facial surface and may allow us to uncover new and unexpected effects.

Materials and methods

Dataset description

For this retrospective cohort study, we used available, pre-existing data collected as part of the Adolescent Brain and Cognitive Development (ABCD) study, a large 10-year NIH-funded longitudinal study recruiting children starting at nine years of age at 21 US locations [24]. A total of 11,880 nine- and ten-year-old boys and girls have been enrolled, and a wide variety of data have been made available to the research community through the controlled-access NIMH data archive (https://nda.nih.gov/). Among the available data relevant for this study are whole-head magnetic resonance (MR) scans, anthropometric data, health and pregnancy history data (including breastfeeding history), and demographic data. These data were collected between 2016 and 2018. The authors did not have access to data that could lead to the identification of individual participants. The ABCD data used for the analyses is from Data Release 3.0 (February 2020) and was accessed on February 17, 2021.

ABCD data has been approved for broad sharing. Local institutional approval at KU Leuven (Protocol: S60568) and the University of Pittsburgh (Protocol: CR19080051) was granted for access and analysis of ABCD data housed in the NIMH data archive. The parents of children enrolled in the ABCD study provided written informed consent for themselves and their children to participate and have their data shared. In addition, enrolled children also provided their assent to demonstrate their willingness to be a participant in the study.

Extraction and processing of 3D facial surfaces from MR scans

Whole head 3T T1-weighted MR scans were accessed through the NIMH data archive. The files were available in NIFTI format, which is standard file format used for MR brain scans. Details about the MR protocol and harmonization have been described previously [25, 26]. The complete 3D facial surface extraction and QC steps are described in our supplemental materials (S1 Text). Briefly, noise levels in each MR image were reduced by inter-subject non-rigid registration of 300 images from the dataset to each given target image using the Elastix (SimpleITK library [27] in Python) and computing a consensus image based on the median intensity values per voxel. After extracting the isosurface (isosurface in Matlab 2023a) and removal of internal structures, the 3D facial surface was extracted and remapped by non-rigidly registering a facial mesh template (n = 7160 vertices) to each image using the MeshMonk toolbox [28]. Imaging artefacts, mostly due to soft-tissue compression of the cheeks and chin, were detected in a vertex-wise manner based on a statistical shape model built from a set of high quality, manually curated images from the total dataset. Following QC and cleaning processes, 4930 MR-derived 3D facial surface images were available for further analysis.

Breastfeeding variables

The mothers of enrolled children were asked to provide information about their breastfeeding habits. First, mothers were asked “When the child was a baby, did (you/ the biological mother) breastfeed him/her?” Responses were available for 6092 children, of which 1319 answered “No, Formula Only” and 4773 answered “Yes, s/he was breastfed.” Mothers who responded “yes” were then asked about the duration of breastfeeding. Responses were coded as 1 = several days (n = 99), 2 = 1–3 months (n = 815), 3 = 4–6 months (n = 1026), 4 = 7–9 months (n = 600), 5 = 10–12 months (n = 943), 6 = 13–18 months (n = 708), 7 = 19–24 months (n = 301), and 8 = more than 24 months (n = 236). An additional 45 mothers who answered “yes” to the initial question either did not know or did not provide a response to the follow up question on duration.

Final study sample

The only exclusion criteria applied to this study were having an unusable 3D facial surface model and failure to provide breastfeeding data. Among the 4930 children with useable 3D facial surfaces, a total of 2275 unrelated children also had valid breastfeeding data available; this was final sample we used for our analyses. Effects were modeled as a simple binary trait and as a quantitative, semi-continuous variable to investigate duration of breastfeeding. For the initial binary response, the final sample breakdown was 434 (“no, formula only) and 1841 (yes, s/he was breastfed”). For the breastfeeding duration variable, the first category (“several days”) and the last category (“more than 24 months”) were dropped due to small sample size, leaving 2,148 children available for analysis. The final sample sizes for the duration analysis were as follows: 0 months (n = 434), 1–3 months (n = 293), 4–6 months (n = 384), 7–9 months (n = 222), 10–12 months (n = 375), 13–18 months (n = 307), and 19–24 months (n = 133). See S1 Table for additional details.

Morphometric analyses

Remapped 3D facial surfaces were Procrustes aligned and adjusted for age, sex, height, weight, BMI, head size, facial size, genetic ancestry, MRI scanner, MRI software, and MRI pulse sequence parameters. Genetic ancestry was based on principal components derived previously using genome-wide data available for the ABCD cohort [29]. We used a regression-based approach to adjust for covariates; this involved predicting the facial surface from all covariates collectively, followed by subtraction of the predictions from the original coordinates, and adding the obtained residuals to the average facial surface. Because of the high noise levels in the data, we applied principal components analysis (PCA) to the adjusted shape residuals and omitted the higher order components which are known to capture imaging-related noise and idiosyncratic artefacts. Specifically, parallel analysis was used to determine which components had eigenvalues indistinguishable from those of simulated noise, leaving 60 components as a multivariate description of facial shape.

The association between breastfeeding, as a binary or semi-quantitative variable (encoded as the middle value of each duration category), and facial shape (modeled as PCs) was tested using partial least squares regression (PLSR; plsregress in Matlab 2023a). PSLR combines the dimensionality reduction benefits of PCA with multiple regression and is useful for uncovering the relationship between a set of reduced latent variables (like those in multivariate shape data) and an independent variable, set of variables, or another set of reduced latent variables [30]. The latent facial phenotype associated with the breastfeeding variable was obtained from the fitted PLSR shape coefficients. Significance of the effect was determined based on an empirical distribution of R² obtained by testing 10⁷ permutations of the breastfeeding variable. For completeness, PLSR analysis was also repeated without the intermediate PCA step (i.e., directly on the shape coordinates) to confirm that the inclusion of this step did not affect our results or conclusions (S1 Fig).

Results

We observed no significant difference in facial shape when treating breastfeeding as a simple binary yes/no variable (PSLR R² = 4.29x10^-4; p = 0.532). In contrast, when treated as a (semi) quantitative variable, breastfeeding duration in months was associated with changes in shape (PSLR R² = 8.05x10^-4; p = 3.61x 10⁻⁴). Looking at the R² and permutation p-value facial heat maps (Fig 1A and 1B, respectively) the facial regions with the strongest effects included the philtrum, cheeks, zygomatic arch, inner (medial) canthal regions of the eye, and the forehead. The magnitude and direction of effect is discernable in Fig 1C, which shows that increased breastfeeding duration is associated with central midface, zygomatic arch, and orbital retrusion along with concomitant forehead, cheek, and mandibular protrusion. The mandibular effect, however, was not significant. The overall impression is that increased breastfeeding is associated with a less convex facial profile. This tendency can be seen clearly when we exaggerate the effect on the face in the direction of greater or lesser breastfeeding duration (magnified +/- 100x) and then superimpose the resulting warped 3D facial surfaces (Fig 1D). The effect of breastfeeding duration is revealed further in Fig 2, which shows the progressively increasing facial shape changes at different duration thresholds.

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Fig 1. The effect of breastfeeding modeled as a semi-quantitative variable on 3D facial surface shape via PLSR.

A) Heat map showing the effect of breastfeeding on the face expressed as R² values; higher R² values (toward the yellow) show areas where breastfeeding has a larger effect on face shape. B) Heat map showing the permutation-based p-values associated with R². C) Heat map showing the direction and magnitude of the effect of breastfeeding on the face as a shift in surface normals; red shows the face moving outward, blue shows the face moving inward, and silver shows no effect. D) The effect of breastfeeding modeled as a 3D shape deformation resulting two hypothetical morphs which are then superimposed. The blue morph represents the shape in the direction of less breastfeeding, while the pink morph represents that shape in the direction of more breastfeeding. For visualization purposes the effects have been magnified 100x.

https://doi.org/10.1371/journal.pone.0310538.g001

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Fig 2. The effect of breastfeeding duration on face shape.

Heat maps showing the effect of breastfeeding duration at four different thresholds on facial surface shape. Each face shows the 3D surface normal displacement at a given threshold relative to the observed mean face from the non-breastfed group. For example, the >6 month comparison shows the facial effect of breastfeeding for at least 7 months relative to the non-breastfed group. For interpretation, blue indicates that the breastfed group shows inward retrusion relative to the non-breastfed group, while red indicates outward protrusion. The colormap is on the same scale for every comparison.

https://doi.org/10.1371/journal.pone.0310538.g002

All of the aforementioned shape changes were very subtle. In contrast to the exaggerated morphs in Fig 1D, the magnitude of the shape changes was very small when considered within the observed 24-month exposure timeframe. This can be appreciated in Fig 3, which shows the expected face shape from our regression model as a 3D deformation at 6-month intervals. At this scale, differences in facial appearance were not conspicuous, even when children were breastfed for 19–24 months.

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Fig 3. Expected changes in facial shape due to breastfeeding based on our PSLR model.

This figure shows the expected face shape as predicted from our regression model as a 3D deformation at 6-month intervals. Note that even by 19–24 months, the effects on the face are not conspicuous.

https://doi.org/10.1371/journal.pone.0310538.g003

Discussion

We observed a statistically significant association between breastfeeding duration (measured to 24 months) and facial shape. As breastfeeding duration increased, we observed a pattern of retrusion in involving the central midface (most prominent in the philtrum and medial canthal region) and protrusion in the forehead and cheeks. Although there was a tendency toward mandibular protrusion, the effect in this region was not statistically significant. Thus, our initial prediction that breastfeeding would impact the midface and mandible was partially borne out. The combined effect of the aforementioned shape changes was one of decreased facial convexity with increased breastfeeding duration. In contrast, we found no shape differences when we simply dichotomized breastfeeding as a yes/no variable. This could be due to the fact that a large portion of our sample was breastfed for a short duration, which when combined with longer duration individuals into a single group, may have muted the impact of breastfeeding on facial shape.

It is difficult to compare our results to the prior literature because we applied an entirely different morphometric approach and focused exclusively on effects involving the facial soft-tissue surface. We have no ability to assess the underlying bones or teeth. As a result, we cannot evaluate the effects of breastfeeding on occlusion directly; only the extent to which breastfeeding impacts outward facial appearance. With that said, our finding that increased breastfeeding was associated with a suite of changes consistent with decreased facial convexity (relative midfacial retrusion) seems to accord with studies showing less risk of a class II skeletal relationship [20, 31] and reduced palate length [15]. However, given how subtleness of the facial surface changes we observed, our results are potentially also in alignment with studies reporting little or no effect of breastfeeding [6–8].

It is important to note that the morphometric approach and large sample size we used is capable of detecting very subtle shape differences. The real-world impact of these statistical effects may be negligible for all practical purposes. Indeed, our results indicate that breastfeeding had such a small effect on 3D facial surface morphology, that the predicted facial differences between an individual never breastfed and an individual breastfed for 18–24 months was barely noticeable (Fig 3). These results could be interpreted as challenging the conventional wisdom in orthodontics that breastfeeding is an important factor in determining positive facial growth outcomes. However, it must be kept in mind that we are looking at a different set of traits here than in the orthodontics literature. It may be that the types of occlusal changes reported to result from lack of breastfeeding minimally impact outward facial appearance. It is also possible that the effects of breastfeeding on facial surface morphology are more prominent during early childhood. Our sample was composed exclusively of 9- and 10-year-old children, so we are unable to test this hypothesis. What we can say is that by adolescence, the effect on outward facial appearance appears to be negligible. Moreover, the effects of breastfeeding could disappear altogether as the children in this study approach puberty and adulthood.

It is important to appreciate that many factors impact facial morphology, including genetic variation, diet and behavior, trauma and disease, environmental exposures throughout the lifespan, and demographic factors such as age, sex and ancestry [32, 33]. For example, common genetic variants at hundreds of chromosomal regions have now been associated with facial shape, including some with effects on the same facial features impacted by breastfeeding [34]. Together, these genetic and environmental factors collectively form the backdrop against which the effects of breastfeeding on facial morphology must be considered. While some factors (like age, sex and ancestry) can usually be adjusted for in the analysis of facial shape, it is difficult or impossible to account for all sources of variation. As a result, a complete understanding of how breastfeeding influences facial shape is currently not possible.

There are several additional limitations and caveats that must be kept in mind when interpreting these results. First, as a retrospective study using an existing data resource, we were limited to the kinds of information collected from participants. There were no additional follow-up questions about breastfeeding or about other sucking or oral habits. Therefore, we were unable to consider the full range of relevant oral behaviors in study participants. Most importantly, questions about non-nutritive sucking behaviors were not available. This is potentially relevant because such behaviors have been consistently associated with malocclusions [35] and may be more prevalent in cases of early weening [36]. This line of reasoning suggests that it may not be the lack of breastfeeding itself that leads to negative orofacial growth outcomes, but rather the suite of oral behaviors and habits that tend to replace the breastfeeding [31, 37, 38].

Another potentially important caveat in this and other studies of breastfeeding relates to the introduction of noise and/or bias into the data due to maternal reporting. Mothers may not be able to accurately recall the duration of their breastfeeding. There may also be a tendency for mothers to overestimate or mislead about their breastfeeding behaviors due to social stigma associated with not breastfeeding [39].

In summary, we can tentatively conclude that the amount of breastfeeding reported by mothers seems to have a detectable, but very small, effect on outward facial appearance in their children at 9 and 10 years of age. A prospective 3D facial surface study focused breastfeeding and other oral behaviors would help resolve some of the limitations and questions posed by these results, particularly if data on occlusion could be collected at the same time.

Supporting information

S1 Table. Demographic breakdown of final sample used in this analysis.

https://doi.org/10.1371/journal.pone.0310538.s001

(DOCX)

S1 Text. Facial surface extraction and quality control filtering.

https://doi.org/10.1371/journal.pone.0310538.s002

(DOCX)

S1 Fig. The effect of PCA and removal of higher order components on semi-quantitative analysis outcomes.

The top row shows the results as presented throughout the manuscript. To obtain these results, PCA was performed on facial shape and higher-order, noisy components were omitted. The bottom row shows the same semi-quantitative analyses without the intermediate PCA step, i.e., performed directly on the landmarks. In the first and last column, blue indicates that the breastfed group shows inward retrusion relative to the non-breastfed group, while red indicates outward protrusion. The vertex-wise variance explained by the semi-quantitative breastfeeding variable was estimated through PLSR and a corresponding P-value was obtained empirically through permutation testing.

https://doi.org/10.1371/journal.pone.0310538.s003

(TIFF)

References

1. Centers for Disease Control and Prevention. About Breastfeeding: Why it Matters. 2023 July 31 [cited 6 March 2024]. Available from: https://www.cdc.gov/breastfeeding/about-breastfeeding/why-it-matters.html.
2. Page DC. Breastfeeding is early functional jaw orthopedics (an introduction). Funct Orthod. 2001;18:24–27. pmid:11799699
- View Article
- PubMed/NCBI
- Google Scholar
3. Carrascoza KC, Possobon Rde F, Tomita LM, Moraes AB. Consequences of bottle-feeding to the oral facial development of initially breastfed children. J Pediatr. 2006;82:395–397.
- View Article
- Google Scholar
4. Silveira LM, Prade LS, Ruedell AM, Haeffner LS, Weinmann AR. Influence of breastfeeding on children’s oral skills. Rev Saude Publica. 2013;47:37–43. pmid:23703128
- View Article
- PubMed/NCBI
- Google Scholar
5. Elad D, Kozlovsky P, Blum O, Laine AF, Po MJ, Botzer E, et al. Biomechanics of milk extraction during breast-feeding. Proc Natl Acad Sci U S A. 2014;111:5230–5235. pmid:24706845
- View Article
- PubMed/NCBI
- Google Scholar
6. Warren JJ, Bishara SE. Duration of nutritive and nonnutritive sucking behaviors and their effects on the dental arches in the primary dentition. Am J Orthod Dentofacial Orthop. 2002;121:347–356. pmid:11997758
- View Article
- PubMed/NCBI
- Google Scholar
7. Luz CL, Garib DG, Arouca R. Association between breastfeeding duration and mandibular retrusion: a cross-sectional study of children in the mixed dentition. Am J Orthod Dentofacial Orthop. 2006;130:531–534. pmid:17045154
- View Article
- PubMed/NCBI
- Google Scholar
8. Lopes-Freire GM, Cárdenas AB, Suarez de Deza JE, Ustrell-Torrent JM, Oliveira LB, Boj Quesada JR Jr. Exploring the association between feeding habits, non-nutritive sucking habits, and malocclusions in the deciduous dentition. Prog Orthod. 2015;16:43. pmid:26683318
- View Article
- PubMed/NCBI
- Google Scholar
9. Peres KG, Barros AJ, Peres MA, Victora CG. Effects of breastfeeding and sucking habits on malocclusion in a birth cohort study. Rev Saude Publica. 2007;41:343–350. pmid:17515986
- View Article
- PubMed/NCBI
- Google Scholar
10. Peres KG, Cascaes AM, Peres MA, Demarco FF, Santos IS, Matijasevich A, et al. Exclusive breastfeeding and risk of dental malocclusion. Pediatrics. 2015;136:e60–67. pmid:26077480
- View Article
- PubMed/NCBI
- Google Scholar
11. Castelo PM, Gavião MB, Pereira LJ, Bonjardim LR. Maximal bite force, facial morphology and sucking habits in young children with functional posterior crossbite. J Appl Oral Sci. 2010;18:143–148. pmid:20485925
- View Article
- PubMed/NCBI
- Google Scholar
12. Kobayashi HM, Scavone H Jr, Ferreira RI, Garib DG. Relationship between breastfeeding duration and prevalence of posterior crossbite in the deciduous dentition. Am J Orthod Dentofacial Orthop. 2010;137:54–58. pmid:20122431
- View Article
- PubMed/NCBI
- Google Scholar
13. Romero CC, Scavone-Junior H, Garib DG, Cotrim-Ferreira FA, Ferreira RI. Breastfeeding and non-nutritive sucking patterns related to the prevalence of anterior open bite in primary dentition. J Appl Oral Sci. 2011;19:161–168. pmid:21552718
- View Article
- PubMed/NCBI
- Google Scholar
14. Pereira Lopes TS, Branco Lima CC, Cerqueira Silva RN, Almeida de Deus Moura LF, Moura de Lima MD, Pinheiro Lima MCM. Association between duration of breastfeeding and malocclusion in primary dentition in Brazil. J Dent Child. 2019;86:17–23. pmid:30992097
- View Article
- PubMed/NCBI
- Google Scholar
15. Diouf JS, Ngom PI, Badiane A, Cisse B, Ndoye C, Diop-Ba K, et al. Influence of the mode of nutritive and non-nutritive sucking on the dimensions of primary dental arches. Int Orthod. 2010;8:372–385. pmid:21094107
- View Article
- PubMed/NCBI
- Google Scholar
16. Agarwal SS, Nehra K, Sharma M, Jayan B, Poonia A, Bhattal H. Association between breastfeeding duration, non-nutritive sucking habits and dental arch dimensions in deciduous dentition: a cross-sectional study. Prog Orthod. 2014;15:59. pmid:25679374
- View Article
- PubMed/NCBI
- Google Scholar
17. Narbutytė I, Narbutytė A, Linkevičienė L. Relationship between breastfeeding, bottle-feeding and development of malocclusion. Stomatologija. 2013;15:67–72. pmid:24375308
- View Article
- PubMed/NCBI
- Google Scholar
18. Hermont AP, Martins CC, Zina LG, Auad SM, Paiva SM, Pordeus IA. Breastfeeding, bottle feeding practices and malocclusion in the primary dentition: a systematic review of cohort studies. Int J Environ Res Public Health. 2015;12:3133–3151. pmid:25785498
- View Article
- PubMed/NCBI
- Google Scholar
19. Abreu LG, Paiva SM, Pordeus IA, Martins CC. Breastfeeding, bottle feeding and risk of malocclusion in mixed and permanent dentitions: a systematic review. Braz Oral Res. 2016;30:S1806–83242016000100401. pmid:27050935
- View Article
- PubMed/NCBI
- Google Scholar
20. Boronat-Catalá M, Montiel-Company JM, Bellot-Arcís C, Almerich-Silla JM, Catalá-Pizarro M. Association between duration of breastfeeding and malocclusions in primary and mixed dentition: a systematic review and meta-analysis. Sci Rep. 2017;7:5048. pmid:28698555
- View Article
- PubMed/NCBI
- Google Scholar
21. Thomaz EBAF, Alves CMC, Gomes E Silva LF, Ribeiro de Almeida CCC, Soares de Britto E Alves MTS, Hilgert JB, et al. Breastfeeding versus bottle feeding on malocclusion in children: a meta-analysis study. J Hum Lact. 2018;34:768–788. pmid:29596751
- View Article
- PubMed/NCBI
- Google Scholar
22. Abate A, Cavagnetto D, Fama A, Maspero C, Farronato G. Relationship between breastfeeding and malocclusion: a systematic review of the literature. Nutrients. 2020;12:3688. pmid:33265907
- View Article
- PubMed/NCBI
- Google Scholar
23. Almahrul A, Alsulaimani L, Alghamdi F. The impact of breastfeeding and non-nutritive sucking behaviors on skeletal and dental malocclusions of pediatric patients: a narrative review of the literature. Cureus. 2021;13:e19160. pmid:34873503
- View Article
- PubMed/NCBI
- Google Scholar
24. Garavan H, Bartsch H, Conway K, Decastro A, Goldstein RZ, Heeringa S, et al. Recruiting the ABCD sample: design considerations and procedures. Dev Cogn Neurosci. 2018;32:16–22. pmid:29703560
- View Article
- PubMed/NCBI
- Google Scholar
25. Casey BJ, Cannonier T, Conley MI, Cohen AO, Barch DM, Heitzeg MM, et al. The Adolescent Brain Cognitive Development (ABCD) study: Imaging acquisition across 21 sites. Dev Cogn Neurosci. 2018;32:43–54. pmid:29567376
- View Article
- PubMed/NCBI
- Google Scholar
26. Hagler DJ Jr, Hatton S, Cornejo MD, Makowski C, Fair DA, Dick AS, et al. Image processing and analysis methods for the Adolescent Brain Cognitive Development Study. Neuroimage. 2019;202:116091. pmid:31415884
- View Article
- PubMed/NCBI
- Google Scholar
27. Klein S, Staring M, Murphy K, Viergever MA, Pluim JP. Elastix: a toolbox for intensity-based medical image registration. IEEE Trans Med Imaging. 2010;29:196–205. pmid:19923044
- View Article
- PubMed/NCBI
- Google Scholar
28. White JD, Ortega-Castrillón A, Matthews H, Zaidi AA, Ekrami O, Snyders J, et al. MeshMonk: Open-source large-scale intensive 3D phenotyping. Sci Rep. 2019;9:6085. pmid:30988365
- View Article
- PubMed/NCBI
- Google Scholar
29. Goovaerts S, Hoskens H, Eller RJ, Herrick N, Musolf AM, Justice CM, et al. Joint multi-ancestry and admixed GWAS reveals the complex genetics behind human cranial vault shape. Nat Commun. 2023;14:7436. pmid:37973980
- View Article
- PubMed/NCBI
- Google Scholar
30. Kreeger PK. Using partial least squares regression to analyze cellular response data. Sci Signal. 2013;6:tr7. pmid:23592846
- View Article
- PubMed/NCBI
- Google Scholar
31. Thomaz EB, Cangussu MC, Assis AM. Maternal breastfeeding, parafunctional oral habits and malocclusion in adolescents: a multivariate analysis. Int J Pediatr Otorhinolaryngol. 2012;76:500–506. pmid:22310072
- View Article
- PubMed/NCBI
- Google Scholar
32. Richmond S, Wilson-Nagrani C, Zhurov A, Farnell D, Galloway J, Safuan A, et al. Factors influencing facial shape. In: Huang GJ, Richmond S, Vig KWL, editors. Evidence‐Based Orthodontics, Second Edition. Hoboken: John Wiley & Sons, Inc; 2018. pp. 69–81.
33. Hughes TE, Townsend GC, Pinkerton SK, Bockmann MR, Seow WK, Brook AH, et al. The teeth and faces of twins: providing insights into dentofacial development and oral health for practicing oral health professionals. Aust Dent J. 2014;59 Suppl 1:101–116.
- View Article
- Google Scholar
34. White JD, Indencleef K, Naqvi S, Eller RJ, Hoskens H, Roosenboom J, et al. Insights into the genetic architecture of the human face. Nat Genet. 2021;53:45–53. pmid:33288918
- View Article
- PubMed/NCBI
- Google Scholar
35. Doğramacı EJ, Rossi-Fedele G. Establishing the association between nonnutritive sucking behavior and malocclusions: A systematic review and meta-analysis. J Am Dent Assoc. 2016;147:926–934.e6. pmid:27692622
- View Article
- PubMed/NCBI
- Google Scholar
36. Khan EB, Bibi A, Hunny Mottani DA, Kumar S. Relationship of early weaning and non-nutritive sucking habits with facial development. J Pak Med Assoc. 2022;72:1118–1122. pmid:35751320
- View Article
- PubMed/NCBI
- Google Scholar
37. Agarwal SS, Sharma M, Nehra K, Jayan B, Poonia A, Bhattal H. Validation of association between breastfeeding duration, facial profile, occlusion, and spacing: a cross-sectional study. Int J Clin Pediatr Dent. 2016;9:162–166. pmid:27365941
- View Article
- PubMed/NCBI
- Google Scholar
38. Costa CTD, Shqair AQ, Azevedo MS, Goettems ML, Bonow MLM, Romano AR. Pacifier use modifies the association between breastfeeding and malocclusion: a cross-sectional study. Braz Oral Res. 2018;32:e101. pmid:30328893
- View Article
- PubMed/NCBI
- Google Scholar
39. Bresnahan M, Zhuang J, Goldbort J, Bogdan-Lovis E, Park SY, Hitt R. Made to feel like less of a woman: the experience of stigma for mothers who do not breastfeed. Breastfeed Med. 2020;15:35–40. pmid:31859523
- View Article
- PubMed/NCBI
- Google Scholar

[ref1] 1. Centers for Disease Control and Prevention. About Breastfeeding: Why it Matters. 2023 July 31 [cited 6 March 2024]. Available from: https://www.cdc.gov/breastfeeding/about-breastfeeding/why-it-matters.html.

[ref2] 2. Page DC. Breastfeeding is early functional jaw orthopedics (an introduction). Funct Orthod. 2001;18:24–27. pmid:11799699
View Article
PubMed/NCBI
Google Scholar

[3] View Article

[4] PubMed/NCBI

[5] Google Scholar

[ref3] 3. Carrascoza KC, Possobon Rde F, Tomita LM, Moraes AB. Consequences of bottle-feeding to the oral facial development of initially breastfed children. J Pediatr. 2006;82:395–397.
View Article
Google Scholar

[7] View Article

[8] Google Scholar

[ref4] 4. Silveira LM, Prade LS, Ruedell AM, Haeffner LS, Weinmann AR. Influence of breastfeeding on children’s oral skills. Rev Saude Publica. 2013;47:37–43. pmid:23703128
View Article
PubMed/NCBI
Google Scholar

[10] View Article

[11] PubMed/NCBI

[12] Google Scholar

[ref5] 5. Elad D, Kozlovsky P, Blum O, Laine AF, Po MJ, Botzer E, et al. Biomechanics of milk extraction during breast-feeding. Proc Natl Acad Sci U S A. 2014;111:5230–5235. pmid:24706845
View Article
PubMed/NCBI
Google Scholar

[14] View Article

[15] PubMed/NCBI

[16] Google Scholar

[ref6] 6. Warren JJ, Bishara SE. Duration of nutritive and nonnutritive sucking behaviors and their effects on the dental arches in the primary dentition. Am J Orthod Dentofacial Orthop. 2002;121:347–356. pmid:11997758
View Article
PubMed/NCBI
Google Scholar

[18] View Article

[19] PubMed/NCBI

[20] Google Scholar

[ref7] 7. Luz CL, Garib DG, Arouca R. Association between breastfeeding duration and mandibular retrusion: a cross-sectional study of children in the mixed dentition. Am J Orthod Dentofacial Orthop. 2006;130:531–534. pmid:17045154
View Article
PubMed/NCBI
Google Scholar

[22] View Article

[23] PubMed/NCBI

[24] Google Scholar

[ref8] 8. Lopes-Freire GM, Cárdenas AB, Suarez de Deza JE, Ustrell-Torrent JM, Oliveira LB, Boj Quesada JR Jr. Exploring the association between feeding habits, non-nutritive sucking habits, and malocclusions in the deciduous dentition. Prog Orthod. 2015;16:43. pmid:26683318
View Article
PubMed/NCBI
Google Scholar

[26] View Article

[27] PubMed/NCBI

[28] Google Scholar

[ref9] 9. Peres KG, Barros AJ, Peres MA, Victora CG. Effects of breastfeeding and sucking habits on malocclusion in a birth cohort study. Rev Saude Publica. 2007;41:343–350. pmid:17515986
View Article
PubMed/NCBI
Google Scholar

[30] View Article

[31] PubMed/NCBI

[32] Google Scholar

[ref10] 10. Peres KG, Cascaes AM, Peres MA, Demarco FF, Santos IS, Matijasevich A, et al. Exclusive breastfeeding and risk of dental malocclusion. Pediatrics. 2015;136:e60–67. pmid:26077480
View Article
PubMed/NCBI
Google Scholar

[34] View Article

[35] PubMed/NCBI

[36] Google Scholar

[ref11] 11. Castelo PM, Gavião MB, Pereira LJ, Bonjardim LR. Maximal bite force, facial morphology and sucking habits in young children with functional posterior crossbite. J Appl Oral Sci. 2010;18:143–148. pmid:20485925
View Article
PubMed/NCBI
Google Scholar

[38] View Article

[39] PubMed/NCBI

[40] Google Scholar

[ref12] 12. Kobayashi HM, Scavone H Jr, Ferreira RI, Garib DG. Relationship between breastfeeding duration and prevalence of posterior crossbite in the deciduous dentition. Am J Orthod Dentofacial Orthop. 2010;137:54–58. pmid:20122431
View Article
PubMed/NCBI
Google Scholar

[42] View Article

[43] PubMed/NCBI

[44] Google Scholar

[ref13] 13. Romero CC, Scavone-Junior H, Garib DG, Cotrim-Ferreira FA, Ferreira RI. Breastfeeding and non-nutritive sucking patterns related to the prevalence of anterior open bite in primary dentition. J Appl Oral Sci. 2011;19:161–168. pmid:21552718
View Article
PubMed/NCBI
Google Scholar

[46] View Article

[47] PubMed/NCBI

[48] Google Scholar

[ref14] 14. Pereira Lopes TS, Branco Lima CC, Cerqueira Silva RN, Almeida de Deus Moura LF, Moura de Lima MD, Pinheiro Lima MCM. Association between duration of breastfeeding and malocclusion in primary dentition in Brazil. J Dent Child. 2019;86:17–23. pmid:30992097
View Article
PubMed/NCBI
Google Scholar

[50] View Article

[51] PubMed/NCBI

[52] Google Scholar

[ref15] 15. Diouf JS, Ngom PI, Badiane A, Cisse B, Ndoye C, Diop-Ba K, et al. Influence of the mode of nutritive and non-nutritive sucking on the dimensions of primary dental arches. Int Orthod. 2010;8:372–385. pmid:21094107
View Article
PubMed/NCBI
Google Scholar

[54] View Article

[55] PubMed/NCBI

[56] Google Scholar

[ref16] 16. Agarwal SS, Nehra K, Sharma M, Jayan B, Poonia A, Bhattal H. Association between breastfeeding duration, non-nutritive sucking habits and dental arch dimensions in deciduous dentition: a cross-sectional study. Prog Orthod. 2014;15:59. pmid:25679374
View Article
PubMed/NCBI
Google Scholar

[58] View Article

[59] PubMed/NCBI

[60] Google Scholar

[ref17] 17. Narbutytė I, Narbutytė A, Linkevičienė L. Relationship between breastfeeding, bottle-feeding and development of malocclusion. Stomatologija. 2013;15:67–72. pmid:24375308
View Article
PubMed/NCBI
Google Scholar

[62] View Article

[63] PubMed/NCBI

[64] Google Scholar

[ref18] 18. Hermont AP, Martins CC, Zina LG, Auad SM, Paiva SM, Pordeus IA. Breastfeeding, bottle feeding practices and malocclusion in the primary dentition: a systematic review of cohort studies. Int J Environ Res Public Health. 2015;12:3133–3151. pmid:25785498
View Article
PubMed/NCBI
Google Scholar

[66] View Article

[67] PubMed/NCBI

[68] Google Scholar

[ref19] 19. Abreu LG, Paiva SM, Pordeus IA, Martins CC. Breastfeeding, bottle feeding and risk of malocclusion in mixed and permanent dentitions: a systematic review. Braz Oral Res. 2016;30:S1806–83242016000100401. pmid:27050935
View Article
PubMed/NCBI
Google Scholar

[70] View Article

[71] PubMed/NCBI

[72] Google Scholar

[ref20] 20. Boronat-Catalá M, Montiel-Company JM, Bellot-Arcís C, Almerich-Silla JM, Catalá-Pizarro M. Association between duration of breastfeeding and malocclusions in primary and mixed dentition: a systematic review and meta-analysis. Sci Rep. 2017;7:5048. pmid:28698555
View Article
PubMed/NCBI
Google Scholar

[74] View Article

[75] PubMed/NCBI

[76] Google Scholar

[ref21] 21. Thomaz EBAF, Alves CMC, Gomes E Silva LF, Ribeiro de Almeida CCC, Soares de Britto E Alves MTS, Hilgert JB, et al. Breastfeeding versus bottle feeding on malocclusion in children: a meta-analysis study. J Hum Lact. 2018;34:768–788. pmid:29596751
View Article
PubMed/NCBI
Google Scholar

[78] View Article

[79] PubMed/NCBI

[80] Google Scholar

[ref22] 22. Abate A, Cavagnetto D, Fama A, Maspero C, Farronato G. Relationship between breastfeeding and malocclusion: a systematic review of the literature. Nutrients. 2020;12:3688. pmid:33265907
View Article
PubMed/NCBI
Google Scholar

[82] View Article

[83] PubMed/NCBI

[84] Google Scholar

[ref23] 23. Almahrul A, Alsulaimani L, Alghamdi F. The impact of breastfeeding and non-nutritive sucking behaviors on skeletal and dental malocclusions of pediatric patients: a narrative review of the literature. Cureus. 2021;13:e19160. pmid:34873503
View Article
PubMed/NCBI
Google Scholar

[86] View Article

[87] PubMed/NCBI

[88] Google Scholar

[ref24] 24. Garavan H, Bartsch H, Conway K, Decastro A, Goldstein RZ, Heeringa S, et al. Recruiting the ABCD sample: design considerations and procedures. Dev Cogn Neurosci. 2018;32:16–22. pmid:29703560
View Article
PubMed/NCBI
Google Scholar

[90] View Article

[91] PubMed/NCBI

[92] Google Scholar

[ref25] 25. Casey BJ, Cannonier T, Conley MI, Cohen AO, Barch DM, Heitzeg MM, et al. The Adolescent Brain Cognitive Development (ABCD) study: Imaging acquisition across 21 sites. Dev Cogn Neurosci. 2018;32:43–54. pmid:29567376
View Article
PubMed/NCBI
Google Scholar

[94] View Article

[95] PubMed/NCBI

[96] Google Scholar

[ref26] 26. Hagler DJ Jr, Hatton S, Cornejo MD, Makowski C, Fair DA, Dick AS, et al. Image processing and analysis methods for the Adolescent Brain Cognitive Development Study. Neuroimage. 2019;202:116091. pmid:31415884
View Article
PubMed/NCBI
Google Scholar

[98] View Article

[99] PubMed/NCBI

[100] Google Scholar

[ref27] 27. Klein S, Staring M, Murphy K, Viergever MA, Pluim JP. Elastix: a toolbox for intensity-based medical image registration. IEEE Trans Med Imaging. 2010;29:196–205. pmid:19923044
View Article
PubMed/NCBI
Google Scholar

[102] View Article

[103] PubMed/NCBI

[104] Google Scholar

[ref28] 28. White JD, Ortega-Castrillón A, Matthews H, Zaidi AA, Ekrami O, Snyders J, et al. MeshMonk: Open-source large-scale intensive 3D phenotyping. Sci Rep. 2019;9:6085. pmid:30988365
View Article
PubMed/NCBI
Google Scholar

[106] View Article

[107] PubMed/NCBI

[108] Google Scholar

[ref29] 29. Goovaerts S, Hoskens H, Eller RJ, Herrick N, Musolf AM, Justice CM, et al. Joint multi-ancestry and admixed GWAS reveals the complex genetics behind human cranial vault shape. Nat Commun. 2023;14:7436. pmid:37973980
View Article
PubMed/NCBI
Google Scholar

[110] View Article

[111] PubMed/NCBI

[112] Google Scholar

[ref30] 30. Kreeger PK. Using partial least squares regression to analyze cellular response data. Sci Signal. 2013;6:tr7. pmid:23592846
View Article
PubMed/NCBI
Google Scholar

[114] View Article

[115] PubMed/NCBI

[116] Google Scholar

[ref31] 31. Thomaz EB, Cangussu MC, Assis AM. Maternal breastfeeding, parafunctional oral habits and malocclusion in adolescents: a multivariate analysis. Int J Pediatr Otorhinolaryngol. 2012;76:500–506. pmid:22310072
View Article
PubMed/NCBI
Google Scholar

[118] View Article

[119] PubMed/NCBI

[120] Google Scholar

[ref32] 32. Richmond S, Wilson-Nagrani C, Zhurov A, Farnell D, Galloway J, Safuan A, et al. Factors influencing facial shape. In: Huang GJ, Richmond S, Vig KWL, editors. Evidence‐Based Orthodontics, Second Edition. Hoboken: John Wiley & Sons, Inc; 2018. pp. 69–81.

[ref33] 33. Hughes TE, Townsend GC, Pinkerton SK, Bockmann MR, Seow WK, Brook AH, et al. The teeth and faces of twins: providing insights into dentofacial development and oral health for practicing oral health professionals. Aust Dent J. 2014;59 Suppl 1:101–116.
View Article
Google Scholar

[123] View Article

[124] Google Scholar

[ref34] 34. White JD, Indencleef K, Naqvi S, Eller RJ, Hoskens H, Roosenboom J, et al. Insights into the genetic architecture of the human face. Nat Genet. 2021;53:45–53. pmid:33288918
View Article
PubMed/NCBI
Google Scholar

[126] View Article

[127] PubMed/NCBI

[128] Google Scholar

[ref35] 35. Doğramacı EJ, Rossi-Fedele G. Establishing the association between nonnutritive sucking behavior and malocclusions: A systematic review and meta-analysis. J Am Dent Assoc. 2016;147:926–934.e6. pmid:27692622
View Article
PubMed/NCBI
Google Scholar

[130] View Article

[131] PubMed/NCBI

[132] Google Scholar

[ref36] 36. Khan EB, Bibi A, Hunny Mottani DA, Kumar S. Relationship of early weaning and non-nutritive sucking habits with facial development. J Pak Med Assoc. 2022;72:1118–1122. pmid:35751320
View Article
PubMed/NCBI
Google Scholar

[134] View Article

[135] PubMed/NCBI

[136] Google Scholar

[ref37] 37. Agarwal SS, Sharma M, Nehra K, Jayan B, Poonia A, Bhattal H. Validation of association between breastfeeding duration, facial profile, occlusion, and spacing: a cross-sectional study. Int J Clin Pediatr Dent. 2016;9:162–166. pmid:27365941
View Article
PubMed/NCBI
Google Scholar

[138] View Article

[139] PubMed/NCBI

[140] Google Scholar

[ref38] 38. Costa CTD, Shqair AQ, Azevedo MS, Goettems ML, Bonow MLM, Romano AR. Pacifier use modifies the association between breastfeeding and malocclusion: a cross-sectional study. Braz Oral Res. 2018;32:e101. pmid:30328893
View Article
PubMed/NCBI
Google Scholar

[142] View Article

[143] PubMed/NCBI

[144] Google Scholar

[ref39] 39. Bresnahan M, Zhuang J, Goldbort J, Bogdan-Lovis E, Park SY, Hitt R. Made to feel like less of a woman: the experience of stigma for mothers who do not breastfeed. Breastfeed Med. 2020;15:35–40. pmid:31859523
View Article
PubMed/NCBI
Google Scholar

[146] View Article

[147] PubMed/NCBI

[148] Google Scholar

Figures

Abstract

Introduction

Materials and methods

Dataset description

Extraction and processing of 3D facial surfaces from MR scans

Breastfeeding variables

Final study sample

Morphometric analyses

Results

Discussion

Supporting information

S1 Table. Demographic breakdown of final sample used in this analysis.

S1 Text. Facial surface extraction and quality control filtering.

S1 Fig. The effect of PCA and removal of higher order components on semi-quantitative analysis outcomes.

References