Internalizing problems are associated with oral health-related quality of life in early childhood: Outcomes from an Asian multi-ethnic prospective birth cohort

Abstract

Oral health status ideally warrants for a holistic biopsychosocial approach to health and wellness. Little is known about the impact of behavioral problems on oral health-related quality of life (OHRQoL) in children due to the paucity of studies in early childhood, particularly in Asian multi-ethnic populations. This study evaluated the relationship between early child’s socioemotional factors and OHRQoL, as well as its association with orofacial pain (OFP) and early childhood caries (ECC) in the Asian GUSTO birth cohort. Mother-child dyads were postnatally assessed at 3 time points. The Child Behavior Checklist (CBCL) was used to assess the child’s socioemotional and behavioral problems at age 4–4.5 years together with other validated questionnaires to evaluate maternal anxiety and depression. ECC detection was performed at age 5, and OHRQoL (primary) and OFP (secondary) outcomes were assessed at age 6 from a total of 555 mother-child dyads. After a univariate regression analysis was performed to identify potential predictors and confounders, a multivariate regression model was run with predisposing factors (CBCL internalization and externalization problems, OFP, ECC) and adjusted for confounders (maternal psychosocial states, maternal education) to determine associations with OHRQoL. Results showed an association between CBCL internalization scores and poorer OHRQoL (RR = 1.03, p = 0.033, 95% CI 1.01 to 1.05), although the limited risk ratio may not have a practical applicability in psychosocially healthy children, alike the majority of those evaluated in this cohort. The average OHRQoL overall score among children with OFP was 2.39 times more than those without OFP (OR = 2.39, p < 0.001, 95% CI 2.00 to 2.86). Thus, in early childhood, OFP, and to lesser extent internalizing behaviors, may negatively impact OHRQoL. This study therefore highlights the complex relationship between OHRQoL and its predisposing socioemotional and somatic pain factors, and demands further investigations in clinically relevant populations.

About the Authors:

Ruth Choe

Roles Data curation, Formal analysis, Investigation, Methodology, Validation, Visualization, Writing – original draft, Writing – review & editing

Affiliation: Faculty of Dentistry, National University of Singapore, Singapore, Singapore

Yu Fan Sim

Roles Conceptualization, Formal analysis, Investigation, Methodology, Software, Supervision, Validation, Visualization, Writing – original draft, Writing – review & editing

Affiliation: Faculty of Dentistry, National University of Singapore, Singapore, Singapore

Catherine H. L. Hong

Roles Conceptualization, Methodology, Supervision, Validation, Visualization, Writing – original draft, Writing – review & editing

Affiliation: Faculty of Dentistry, National University of Singapore, Singapore, Singapore

Sameema Mohideen

Roles Data curation, Project administration, Resources, Writing – review & editing

Affiliation: Singapore Institute for Clinical Sciences, A*STAR, Singapore, Singapore

Ranjani Nadarajan

Roles Data curation, Project administration, Resources, Writing – review & editing

Affiliation: Singapore Institute for Clinical Sciences, A*STAR, Singapore, Singapore

Fabian Yap

Roles Funding acquisition, Project administration, Resources, Writing – review & editing

Affiliation: Department of Paediatrics, KK Women’s and Children’s Hospital, Singapore, Singapore

Lynette P.-C. Shek

Roles Funding acquisition, Project administration, Writing – review & editing

Affiliation: Department of Paediatrics, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore

ORCID logo https://orcid.org/0000-0001-9064-8983

Chin-Ying Stephen Hsu

Roles Conceptualization, Funding acquisition, Methodology, Project administration, Resources, Writing – original draft, Writing – review & editing

Affiliation: Faculty of Dentistry, National University of Singapore, Singapore, Singapore

Birit F. P. Broekman

Roles Conceptualization, Methodology, Supervision, Validation, Visualization, Writing – original draft, Writing – review & editing

Affiliations Singapore Institute for Clinical Sciences, A*STAR, Singapore, Singapore, OLVG and Amsterdam UMC, VU University, Amsterdam, The Netherlands

Joao N. Ferreira

Roles Conceptualization, Funding acquisition, Methodology, Project administration, Resources, Supervision, Validation, Visualization, Writing – original draft, Writing – review & editing

* E-mail: [email protected]

Affiliations Faculty of Dentistry, National University of Singapore, Singapore, Singapore, Faculty of Dentistry, Exocrine Gland Biology and Regeneration Research Group, Department of Research Affairs, Chulalongkorn University, Bangkok, Thailand

ORCID logo https://orcid.org/0000-0002-4230-4593

Abstract

Oral health status ideally warrants for a holistic biopsychosocial approach to health and wellness. Little is known about the impact of behavioral problems on oral health-related quality of life (OHRQoL) in children due to the paucity of studies in early childhood, particularly in Asian multi-ethnic populations. This study evaluated the relationship between early child’s socioemotional factors and OHRQoL, as well as its association with orofacial pain (OFP) and early childhood caries (ECC) in the Asian GUSTO birth cohort. Mother-child dyads were postnatally assessed at 3 time points. The Child Behavior Checklist (CBCL) was used to assess the child’s socioemotional and behavioral problems at age 4–4.5 years together with other validated questionnaires to evaluate maternal anxiety and depression. ECC detection was performed at age 5, and OHRQoL (primary) and OFP (secondary) outcomes were assessed at age 6 from a total of 555 mother-child dyads. After a univariate regression analysis was performed to identify potential predictors and confounders, a multivariate regression model was run with predisposing factors (CBCL internalization and externalization problems, OFP, ECC) and adjusted for confounders (maternal psychosocial states, maternal education) to determine associations with OHRQoL. Results showed an association between CBCL internalization scores and poorer OHRQoL (RR = 1.03, p = 0.033, 95% CI 1.01 to 1.05), although the limited risk ratio may not have a practical applicability in psychosocially healthy children, alike the majority of those evaluated in this cohort. The average OHRQoL overall score among children with OFP was 2.39 times more than those without OFP (OR = 2.39, p < 0.001, 95% CI 2.00 to 2.86). Thus, in early childhood, OFP, and to lesser extent internalizing behaviors, may negatively impact OHRQoL. This study therefore highlights the complex relationship between OHRQoL and its predisposing socioemotional and somatic pain factors, and demands further investigations in clinically relevant populations.

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Citation: Choe R, Sim YF, Hong CHL, Mohideen S, Nadarajan R, Yap F, et al. (2021) Internalizing problems are associated with oral health-related quality of life in early childhood: Outcomes from an Asian multi-ethnic prospective birth cohort. PLoS ONE 16(8): e0256163. https://doi.org/10.1371/journal.pone.0256163

Editor: Sompop Bencharit, Virginia Commonwealth University, UNITED STATES

Received: March 30, 2021; Accepted: July 30, 2021; Published: August 12, 2021

Copyright: © 2021 Choe 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: Data are from the GUSTO birth cohort study. The datasets generated and/or analyzed in this work cannot be made publicly available due to an ethical restriction (patient confidentiality) and research data confidentiality requirements of local ethics reviewing boards (National Health Group Domain Specific Review Board and SingHealth Centralized Institutional Review Board). Data request can be put up through Research Manager, Ms Lam Sock Peng [[email protected]], and must be evaluated and approved by the GUSTO Executive Committee.

Funding: Funding: This research is supported by the Singapore National Research Foundation under its Translational and Clinical Research (TCR) Flagship Programme and administered by the Singapore Ministry of Health’s National Medical Research Council (NMRC), Singapore - NMRC/TCR/004-NUS/2008; NMRC/TCR/012-NUHS/2014. Additional funding is provided by the Singapore Institute for Clinical Sciences, Agency for Science Technology and Research (A*STAR), Singapore. J.N. Ferreira was supported by 2015-2018 grants from the Scientific Investigation Committee of the American Equilibration Society, by a Mid-career Research Grant from the National Research Council of Thailand (NRCT) grant number NRCT5-RSA63001-12 and by grant number STF 6202432001-1 from Chulalongkorn University in Thailand. R. Choe was supported by the National University of Singapore Faculty of Dentistry Master’s programme research grant. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing interests: Competing interests statement: I have read the journal’s policy and the authors of this manuscript have the following competing interests: L.P.-C. Shek has consultant arrangements with Mead Johnson and Nestle; has received payment for lectures from Danone and Nestle; and has received research funding from Danone. R. Choe, Y.F. Sim, C.H.L. Hong, S. Mohideen, R. Nadarajan, F. Yap, C.Y.S. Hsu, B.F.P. Broekman, and J.N. Ferreira declare no potential conflicts of interest.This does not alter our adherence to PLOS ONE policies on sharing data and materials.

1. Introduction

In the last decade, broad improvements in oral health have been reported in all World Health Organization (WHO) regions after the implementation of public policies focused on prevention at early life [1–3]. Despite this progress, early childhood caries (ECC) remains a prevalent childhood disease [4]. ECC commonly triggers orofacial pain complaints [5] resulting in chewing difficulties as well as a poor appetite [6] and diet [7] which subsequently impacts the quality of life of both the child and families [8]. Consequently, ECC and its associated orofacial pain and masticatory dysfunction pose a public health burden for oral care services [9–17]. To tackle these concerns within multi-ethnic Singaporean children, the Growing Up in Singapore Towards healthy Outcomes (GUSTO) cohort, a birth and mother-offspring longitudinal study, has comprehensively collected the oral health data and assessed the socioemotional well-being at early childhood [18,19].

For a more holistic reflection of patient and public healthcare needs, a biopsychosocial model for oral health is needed, one that goes beyond oral symptoms and diagnosis such as ECC. As such, the use of oral health-related quality of life (OHRQoL) instruments for the evaluation of oral health outcomes and treatment needs is common in craniofacial and dental research as well as in clinical practice as it holistically assesses subjective symptoms, functional and emotional well-being [20]. Children have to reach 8 years of age to fully understand and comprehend the tasks involved in reporting their health accurately within a 4-week recall period [21]; hence, to measure the OHRQoL before the age of 8, parents or guardians must be used as proxies, and assessment tools such as the Early Childhood Health Impact Scale (ECOHIS) can be utilized [22]. In addition to ECOHIS and OHRQoL dimensions, behavioral problems in children may also contribute to an impaired quality of life [23], with downstream implications on mental health later in life [24].

Child behavioral and socioemotional problems manifest as either internalizing problems, which include symptoms of anxiety/depression, somatization and emotional symptoms, or externalizing problems like attention-seeking problems or aggression [25]. Behavioral problems may considerably interfere with attitudes such as receptiveness to daily preventive measures e.g. toothbrushing or dietary modifications [26] which directly increases susceptibility to ECC, resulting in deterioration of oral health [27]. Child behavioral and socioemotional problems have also been shown to affect behaviors in the dental setting. In a recent cross-sectional study, authors found that children, aged 4 to 12 years old, with both internalizing and externalizing problems behaved more negatively during routine dental treatment [26]. Further, internalization problems have also been associated with higher instances of orofacial pains, abdominal pain [28–31], and other chronic pains elsewhere in the body [32–39]. Together with pain symptoms, internalization problems can predict for an impaired OHRQoL in 8- to 12-year old children [31]. However, the impact of pain somatization and internalizing problems on OHRQoL in pre-school children is not known due to the paucity of studies in early childhood. Thus, investigating the impact of child behaviors and internalizing problems on OHRQoL dimensions and understanding its relation to common pain reports (i.e. orofacial and abdominal) is of utmost importance. We hypothesize that child internalizing problems can have a negative impact on the child and parents OHRQoL.

Hence, this study aims (1) to identify whether child’s emotional and behavioral problems at age 4–4.5 years are associated with OHRQoL at age 6; (2) to determine if OHRQoL is associated with orofacial/abdominal pains at age 6; and (3) to investigate if ECC at age 5 can predispose for a poorer OHRQoL at age 6. This study report is based on the GUSTO cohort which is an ongoing mother-offspring cohort study that collects a comprehensive and wide array of phenotypic data including mental and oral health data from mothers and their offspring from pregnancy onwards [7,18,19].

2. Materials and methods

2.1 The GUSTO cohort and study design

The GUSTO is a multicenter longitudinal birth and mother-offspring cohort study based in the multi-ethic population of Singapore. It is one of the most comprehensive studies investigating the role of developmental and behavioral factors (including phenotypic, genetic and epigenetic factors) in health as well as oral health outcomes [7,18,19,40]. Deep phenotyping and longitudinal assessments of Singaporean mothers and their offspring was initiated in 2009 and is still ongoing, and such were evaluated from pregnancy onwards. Briefly, healthy pregnant women of Chinese, Malay or Indian and of homogeneous parental ethnic background were recruited during their first pregnancy trimester at the KK Women’s and Children’s Hospital (KKH) or National University Hospital (NUH) in Singapore from June 2009 to September 2010 (n = 1247). Ethics approval for the study was granted by the SingHealth Centralized Institutional Review Board (Reference No. 2009/280/D) for KKH and the National Health Care Group Domain Specific Review Board (Reference No. D/09/021) for NUH. Written informed consent was obtained from all women participants upon recruitment, and the study was conducted according to the principles of the Declaration of Helsinki.

2.2 Data collection

In this cohort, mother-child dyads were postnatally assessed at 3 time points with oral examinations and on-site questionnaires at KKH and NUH as per study flowchart in Fig 1. All questionnaires were provided in Chinese, Malay, Tamil or English, after forward and backward translation to English by certified translation services.

[Figure omitted. See PDF.]

Fig 1. Flowchart with the longitudinal design and assessed variables at each postnatal visit of this study cohort.

https://doi.org/10.1371/journal.pone.0256163.g001

2.3 Independent variables and predisposing factors

2.3.1 Demographics.

Demographic data such as ethnicity, gender and maternal education levels was collected at baseline, 4–4.5th- and 6th-year postnatal visits. Highest maternal education was coded as an ordinal variable according to the following categories/levels: below post-secondary, post-secondary and university level and above. These categories have been used in other published GUSTO studies [18,41–43] and served as an indicator of socio-economic status.

2.3.2 Child behavioral and emotional problems.

The Child Behavior Checklist 1.5–5 (CBCL/1.5–5) is a valid and reliable 99-item parent reported instrument used to screen for emotional and behavioral problems in 1.5- to 5-year old children [44,45]. In this study, responses were scored by the mothers on a 3-point Likert scale (0 = Not True, 1 = Somewhat or Sometimes True, 2 = Very True or Often True) at the 4–4.5th-year postnatal visit. A higher score means more symptoms of socioemotional and behavioral problems. This checklist evaluates the child’s internalizing (social withdrawal, emotionally reactive, somatic complaints and anxiety/depression scales) and externalizing problems (attention problems and aggressive behavior scales). Raw scores were converted to age-matched standardized T-scores using the Singapore-based norms [46]. The Cronbach’s alpha was 0.88 and 0.90 for the internalization and externalization problems subgroups respectively [47], indicating excellent internal reliability.

2.4 Covariates and potential confounders

2.4.1 Maternal psychosocial problems.

The self-reported clinical instrument Spielberger State-Trait Inventory (STAI) was used to detect maternal anxiety as previously [48] during the 4–4.5th-year postnatal visits. This instrument consists of 2 scales with 20 items; one scale appraises the current anxiety condition (State-Anxiety scale) while the other appraises the anxious personality traits (Trait-Anxiety scale). Each item of the STAI was scored on a 4-point Likert scale with higher scores signifying greater anxiety. The STAI has been shown to have construct validity [49] and reliability within the GUSTO cohort [50]. Internal consistencies were established within the cohort and the Cronbach’s alpha was 0.91 for both the State-Anxiety and Trait-Anxiety subscales [42].

The 21-item Beck Depression Inventory II (BDI-II) was used to assess the presence and severity of depressive symptoms in the preceding two weeks [51]. Each item of the BDI-II was scored on a 4-point Likert scale and summed as a total score (score range 0–63). Higher scores indicate more severe depressive symptoms. This widely used self-reported questionnaire has been validated to assess the existence and severity of depressive symptoms [51] and has been shown to have acceptable internal consistency in the literature (Cronbach’s alpha 0.73–0.95) [52].

A higher score on both the STAI and BDI-II means more maternal symptoms of anxiety and depression are present.

2.4.2 Early childhood caries.

During the 5th-year postnatal visits, oral examinations were performed by 3 calibrated dentists (intraclass correlation coefficient (ICC): >0.80) using the modified International Caries Detection and Assessment System (ICDAS-II). Early childhood caries (ECC) was assessed by the number of decayed teeth with incipient caries or cavitated lesions corresponding to ICDAS-II codes 2–6 [53]. Children refrained from consuming any foods, drinks or toothbrushing for at least 1 hour before the oral examination. Participants were examined in a supine position on the dental chair. Teeth surfaces were cleaned, dried with sterile gauze and assessed by visual examination using mouth mirrors and torchlights for artificial illumination. Tactile inspection with WHO blunt probes were used to aid the visual examination when necessary. No radiographs were taken.

2.4.3. Orofacial pain and other bodily pains.

At the 6th-year postnatal visit, the presence and frequency of orofacial pain in children was assessed by the question: “How often has your child had pain in the teeth, mouth or jaws?”. The use of this question to measure pain has been widely used in epidemiological orofacial pains studies [54–56] and has been validated as a pain construct in ECC and OHRQoL studies and tools [57]. The presence of parental-reported orofacial pain was derived from the question and dichotomized. Those who answered “never” or “hardly ever” were categorized as children with “no orofacial pain” while the rest of the responses were recorded as having “orofacial pain”.

An interviewer-administered body pain drawing and screener was then used to directly assess the child’s orofacial pain, abdominal pain and other bodily pains in specific anatomical locations within the last month. This screening tool was adopted from the International Network for Orofacial Pain and Related Disorders Methodology and the International Classification of Orofacial Pain [58,59].

2.5 Outcome variables

2.5.1 Oral health-related quality of life.

The ECOHIS was administered to mothers at the 6th-year postnatal visit. Mothers were asked to consider the child’s entire lifespan when answering the questionnaire. The 13-item questionnaire consists of 2 sections: the child (9 items) and family (4 items) impact sections. Response categories were scored on a 5-point Likert scale: 0 = never; 1 = hardly ever; 2 = occasionally; 3 = often; 4 = very often; 5 = don’t know; “don’t know” responses were recorded as missing and excluded from the overall ECOHIS score. The overall ECOHIS score is calculated based on the summation of the response codes for the family and child sections; whereby higher scores indicate poorer OHRQoL. Subjects with more than 2 missing responses in the child section or 1 missing in the family section were excluded [22]. Crohnbach alphas for child and family sections were 0.91 and 0.95 respectively and the ICC was 0.84 [22].

2.6 Data analysis

STATA SE Version 15 (StataCorp LLC, College Station, Texas, USA) was utilized for all analyses and the significance level was set at p < 0.05.

The primary outcome measure, OHRQoL, was analyzed as a quantitative variable, and the scores on CBCL, STAI and BDI-II as well. ECC was measured as a quantitative variable by summation of the number of decayed teeth (dt) with white spots/cavitated lesions (ICDAS-II codes 2–6). We assessed the correlation between CBCL and OHRQoL and performed univariate regression analyses to investigate the relationship between the primary outcome measure, OHRQoL, and independent variables (orofacial pain, abdominal pain and ECC).

Lastly, a multivariate regression model was run with potential predisposing factors or predictors (CBCL internalization and externalization problems) and adjusted for confounders arising from the univariate analysis (e.g., independent variables with a significant association with the primary outcome measure, OHRQoL, exhibiting a p-value < 0.05). As the OHRQoL, a discrete variable that takes only non-negative values, had positively skewed distribution with overdispersion, generalized linear model with negative binomial family distribution was considered. Negative binomial regression analysis with log-linked function and robust variance estimator was used to estimate the association, in terms of risk ratio (RR) with 95% confidence interval (CI), between independent variables and OHRQoL. Negative binomial regression analysis was deemed suitable for the data set examined and fulfilled the assumptions in the analysis.

To account for potential bias from missing data and for comparable purposes with our previous cohort published studies, multiple imputation using chained equations was employed under the assumption that data were missing at random conditional on the observed data. Forty imputed datasets were generated from imputation models containing all potential predisposing factors and confounders included in the regression analysis. Number of imputations were determined at Monte Carlo error was <10% of the standard error of the estimates to achieved convergence of the parameter estimates. Predictive mean matching algorithms, which is robust against misspecification of the imputation model, was used for imputation of values. Regression analysis were conducted on imputed datasets on final sample of n = 555 and estimates were combined following Rubin’s rule into a single estimate which is less biased by differential losses to follow up. In addition to this protocol, a planned sensitivity analyses using complete cases was performed to assess the robustness of the findings from aforesaid regression models.

3. Results

3.1 Sociodemographics

A total of 555 mothers completed all questionnaires in this cohort at the last postnatal visit. Majority of mothers had higher education levels with 38.9% being university degree holders. The children had a male-to-female ratio of 1:1.2 and were predominantly Chinese (53.2%).

The mean OHRQoL scores was 5.51 (Median: 3.00, range: 0–32) (S1 Table). The lifetime prevalence of orofacial pain and abdominal pain in the birth cohort was 23.1%, and 43% respectively (S1 Fig). The mean CBCL total score was 50.62 (SD: ±11.02, range: 0–125). The mean maternal STAI and BDI-II were 70.42 (SD: ±19.42) and 6.60 (SD: ±7.79) respectively (S2 Table).

Sociodemographic characteristics of the primary outcome OHRQoL are presented in Table 1. Maternal education was associated with overall OHRQoL (p = 0.017) and OHRQoL family subscale (p = 0.008), hence maternal education may have a protective role.

[Figure omitted. See PDF.]

Table 1. Sociodemographics and their association with OHRQoL.

OHRQoL overall was calculated from overall sum of ECOHIS scores.

https://doi.org/10.1371/journal.pone.0256163.t001

Thirteen parent-child dyads had missing data on ethnicity and gender, and 119 responses had missing data for maternal education. The CBCL was incomplete in 135 responses. No cases were excluded, and incomplete cases were accounted for in the multiple imputation model.

3.2 OHRQoL relationships with pain and ECC

Relationships between OHRQoL and bodily pains (orofacial and abdominal) and ECC were assessed (Table 2). Children with orofacial pain (OFP) were associated with higher OHRQoL (overall) as well as with child and family impact scores (p < 0.001). Children with ECC were also correlated with higher OHRQoL (p = 0.006) but only had negative impact on the child scores (p = 0.004).

[Figure omitted. See PDF.]

Table 2. Mann-Whitney U test to identify the relationships between orofacial pain, abdominal pain, ECC and OHRQoL (overall and subscales).

https://doi.org/10.1371/journal.pone.0256163.t002

3.3 Regression analysis

With multiple imputation method for missing data, a univariate regression analysis was performed to identify potential predictors and confounders (Table 3). CBCL internalizing, externalizing and total scores were associated with a higher OHRQoL overall score. However, an increase of 1-unit score in the CBCL total score was only linked with an average 2% increase in the OHRQoL overall score and the 95% CI were very narrow (RR = 1.02, p < 0.001, 95% CI 1.01–1.03). This relationship with limited RR was also observed with both the OHRQoL impact scores on the child (RR = 1.01, p < 0.001, 95% CI 1.01–1.02) and family (RR = 1.01, p < 0.001, 95% CI 1.00–1.02) (S3 Table).

[Figure omitted. See PDF.]

Table 3. Univariate regression analysis for variables associated with overall OHRQoL.

https://doi.org/10.1371/journal.pone.0256163.t003

The average OHRQoL overall score in children with OFP was 2.67 times higher than those without OFP (RR = 2.67, p < 0.001, 95% CI 2.27 to 3.14) (Table 3). Moreover, the average OHRQoL overall score in children with ECC was 1.41 times higher than those without ECC (p = 0.006) (Table 3).

In the multivariate regression model (Table 4), predisposing factors (CBCL internalization and externalization) and outcome variables (OHRQoL) were included while adjusting for multiple factors (maternal STAI and education, OFP, ECC), all according to the univariate analysis findings. CBCL total score was removed due to multicollinearity. CBCL internalization scores remained associated with poorer OHRQoL (RR = 1.03, p = 0.033, 95% CI 1.01 to 1.05), but not externalization. CBCL internalization score was also correlated with the ECOHIS child subscale (RR = 1.03, p = 0.002, 95% CI 1.00 to 1.05) and the family subscale (RR = 1.03, p = 0.030, 95% CI 1.00 to 1.06). Though, RR and 95% CI were near 1 for all the above relationships of CBCL with OHRQoL. Moreover, the average ECOHIS overall score in children with OFP was 2.39 times higher than those without OFP (OR 2.39, p < 0.001, 95% CI, 2.00–2.86).

[Figure omitted. See PDF.]

Table 4. Multivariate regression analysis for all relevant variables associated with OHRQoL dimensions by multiple imputation modeling.

https://doi.org/10.1371/journal.pone.0256163.t004

In addition to the multiple imputation analysis, a sensitivity analysis using complete cases was performed as well to confirm the regression models (S4 Table). We found that results from both multiple imputation modelling (Table 4) and sensitivity analysis (S4 Table) were comparable for the main hypotheses that internalizing behaviors, but not externalizing, are associated with poorer OHRQoL. Despite these findings, the RR is near 1 for both the imputation model and sensitivity analysis. Moreover, OHRQoL is also associated with OFP, independent of ECC and other bodily pains. ECC approached significance in its relationship with OHRQoL, however the 95% CI are very wide in both analyses (Tables 4 and S4).

4. Discussion

The role of behavioral and emotional problems on OHRQoL in children is unclear due to the dearth of early childhood studies in dentistry. To our knowledge, this was the first study to examine the effect of the child’s socioemotional and behavioral problems (measured by CBCL) on OHRQoL in the context of bodily pains and early childhood caries (ECC). Herein, we found that higher internalizing CBCL scores in 4-year-old (±5 months) children were negatively associated with the OHRQoL, which in turn (poorer OHRQoL) was associated in children with orofacial pain. From the limited data extrapolated from pediatric temporomandibular disorders (TMD) [60,61], children with symptomatic TMD conditions had worse behavioral problems than those with asymptomatic and non-painful TMD conditions [60–62]. This is also reported in pain studies from the medical literature, whereby internalization problems, in particular, are associated with higher instances of comorbidities such as recurrent abdominal pain (RAP) [63], headaches, musculoskeletal pain and juvenile rheumatoid arthritis [64]. The hypothesis for this observation is that children with internalization phenotypes are often hypervigilant and tend to ruminate about their pain giving rise to greater pain sensitivity and amplified pain responses. This theory was demonstrated in a study comparing children with low-level versus high-level dental anxiety [65]. Children with a higher baseline level of dental anxiety reported more negative thoughts about pain during a dental restoration which reinforced the pain-related rumination [25,65]. In this cohort study, there was an association between CBCL internalization scores and poorer OHRQoL, although an increase of 1-unit score in the CBCL internalization score was only linked with a 3% increase in the ECOHIS overall score. These findings are consistent with literature as, though limited, there is a general observation that socioeconomic and behavioral problems, internalization problems in particular, may hinder the child’s coping mechanism and influence their behaviors and responses (e.g., intensification) to future painful experiences [25,66–72]. As such, dysregulation of pain modulation pathways caused by anxiety or mood disorders could possibly underlie the hypothesized association between internalization problems and development of chronic pain and comorbid conditions [73]. This may therefore serve as a possible explanation for the observed association between only internalization factors, not externalization, and quality of life. Another possible explanation for the lack of association between externalization with quality of life might be because externalization problems in children are hypothesized to be outcomes of an accumulation of predictors such as recurrent parental distress (maternal and paternal depression) [74], child emotional reactivity [75] and family dysfunction [76]. A child’s social and coping skills are heavily influenced by parents through observational learning and modelling [77]. Negative parental responses to pain or stress may unknowingly reinforce maladaptive coping strategies and lead to poorer social competence and adjustment issues in adolescence [74]. While studies in the literature have shown that there is no gold standard for assessment of childhood psychosocial disorders [76], future studies could consider assessment of parental distress and family dysfunction for a more holistic assessment of externalization issues in children and its effect on overall quality of life.

Although a positive correlation between the increase in CBCL internalization scores and poorer OHRQoL was established, it would be overly simplistic to directly extrapolate this data to clinically meaningful data. Established CBCL cut-offs for identifying children with normal/non-clinical (CBCL total scores <60), borderline (CBCL total scores = 60–63) or clinical (CBCL total scores >63) have been reported in clinical studies [44,46]. Our cohort comprised largely of a mentally healthy population with limited pain chronicity, absence of borderline maternal psychological conditions and a relatively restricted number of children falling below the borderline or high scores above the clinical cut-offs, therefore dichotomizing CBCL may result in skewed data analysis and lack of power (mean CBCL total score = 50.63, SD: ±11.02). Nonetheless, our study established that an increase in internalizing behaviors, even within the normal range, are associated with OHRQoL in early childhood, which is relevant to the population at large.

Various instruments are available to evaluate oral health problems in young adult and geriatric populations [78]. As children are constantly in transitional phases of emotional, cognitive, and social development, several considerations arise when reporting OHRQoL in children. In children, the assessment of quality of life is more complex as firstly, the comprehension of the questionnaire is dependent on the proxy’s age and cognitive development [79]. Secondly, the perceptions, expectations and emotional states of parents or caregivers have to be taken into account which may affect the accuracy of the ECOHIS questionnaire. Currently, the ECOHIS [22] is the only validated instrument to measure OHRQoL in children below 8 years of age that require parents or guardians as proxies due to their poor perception of health [21]. While the ECOHIS has been used widely in epidemiological studies, the instrument does not fully account for certain inherent behavioral problems which may confound the child’s reporting of pain and perceptions [80,81]. Out of the 13-items assessed by ECOHIS, only one assesses for the pain dimension [22]. Pain perceptions are shaped by the amalgamation of learned occurrences, memories of past experiences and pain coping approaches as the child grows up and develops neurocognitive skills [82,83]. Child behaviors may vary during their complex neurodevelopmental stages and hence may have an effect on their orofacial pain awareness and report [84,85]. This highlights the complexity and multidimensional experience of psychosocial problems on OHRQoL and orofacial pain which is unique to the individual patient. Hence, an understanding of how internalizing problems may predict the OHRQoL and associations with pain reports provide a more holistic and comprehensive understanding of the psychosocial effects on OHRQoL and pain pathways.

ECC in the primary dentition was found to be associated with poorer OHRQoL but such relationship did not hold in the multivariate regression model. Although the relationship between caries experience and a corresponding decrease in OHRQoL is well documented in the literature [9,12–17], only a few studies have explored the impact of odontogenic pain on OHRQoL in children [8,10,86]. A cross-sectional Brazilian study reported that parents of children with a history of dental pain had an 84-fold chance of reporting a negative impact on the child’s OHRQoL [10]. The study also demonstrated that a history of dental pain was a stronger predictor of OHRQoL than caries. Hence, an evaluation of both objective (e.g. caries) and subjective measures (e.g. pain symptoms) and their interactions is a more holistic management approach to understand the impact of orofacial pain predictors on overall OHRQoL. In this study, ECC was measured using the ICDAS-II which differentiates between enamel (ICDAS 1–3) and dentine lesions (ICDAS ≥ 4) [87]. This indicator is an accurate reflection of caries severity resulting in pain episodes, which arise when carious lesions progress from dentine to pulpal tissue [88,89]. However, and according to previous GUSTO publications, ECC measured with the ICDAS-II index was dichotomized into binary variables: absent (ICDAS 0) or present (ICDAS 2–6) [7]. Thus, it was not possible to retrospectively dichotomize subjects with superficial and deep lesions. Consequently, this may have led to a less clear relationship between ECC and OHRQoL (wide 95% CI), though such relation did approach a significance level (p = 0.066). Moreover, the ICDAS-II does not capture premature tooth loss due to extraction of carious teeth due to infection or dental trauma in the total score which may also be a contributory cause for orofacial pain and poorer OHRQoL [90,91]. Though, dental trauma at 6–7 years of age has low frequency rates in Singapore [92] and this cohort’s oral examinations did not depict any gross dental trauma case. Despite these limitations with ICDAS-II, this index is still the most widely used tool for reporting the dental disease burden in cohort studies [93]. Future studies should consider including clinical variables such as tooth loss due to premature extraction which may possibly contribute to OHRQoL and OFP [8,94].

In large population-based studies, abdominal pain is one of the most common pain complaints during childhood and it is typically associated with other somatic pain symptoms and internalizing disorders (i.e. child and maternal anxiety) [95]. These abdominal pains can be exacerbated by diet, including milk and carbohydrate intolerances [96], and previous GUSTO studies [7] have shown that such dietary patterns are linked with an increase in EEC which detrimental for an optimal oral health. Though, in this cohort, abdominal pain was not associated with OHRQoL at age 6. Further studies should focus on clinical cohorts of pre-school children with high prevalence of persistent or chronic pains to provide a more robust explanation for the relationship between behavioral and emotional problems and OHRQoL and its association with common pain complaints in the orofacial and abdominal regions. A strength of this study is that our findings were based on a longitudinal birth cohort and thus are likely to be representative for children and families in multi-ethnic communities. This study was also able to capture sociodemographic information (gender, ethnicity and socioeconomic status) that are important for the assessment and prediction of psychosocial factors on OHRQoL and its association with orofacial pain. In fact, herein maternal education was indeed a protective factor for OHRQoL, which fits in reported multilevel conceptual models on children’s oral health [97,98]. However, further studies are needed to establish whether the relationship between the child’s psychosocial factors and OHRQoL may be more robust in clinical subjects with chronic orofacial pain and/or comorbid psychosocial conditions such as psychopathology. These may provide more information on potential risk factors on the genesis of pain episodes later in life. Identification of these psychosocial variables will allow the clinicians together with parents to better understand and formulate interventions to help the child develop healthy pain coping behaviors aimed at improving the overall quality of life. Interventions may include the modification of anxious expectations or dysfunctional patterns of responses while facing pain symptoms. The understanding of how internalizing problems may predict the OHRQoL and associations with pain reports provide a more holistic and comprehensive understanding of the psychosocial effects on OHRQoL and pain pathways which may, in turn, prevent downstream implications on mental health later in life.

5. Conclusion

This cohort study identified that internalizing behaviors (i.e., somatization, withdrawn, emotional, anxiety and depression), but not externalizing behaviors in early childhood were associated with poor OHRQoL, where a poorer OHRQoL was associated with children with orofacial pain, independent of caries and common pain complaints from the abdominal regions. As the child’s internalizing problems may vary during different neurodevelopmental stages, this may have an effect on their orofacial pain awareness and reporting. This therefore highlights the complexity and multidimensional experience of internalizing problems on OHRQoL and orofacial pain which is unique to the individual patient.

Supporting information

S1 Fig. Frequency of different self-reported pains outside the orofacial region within the last month in Singaporean children at the 6th year visit (n = 555).

https://doi.org/10.1371/journal.pone.0256163.s001

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S1 Table. Overall and domain specific ECOHIS scores.

https://doi.org/10.1371/journal.pone.0256163.s002

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S2 Table. Child emotional and behavioral problems and maternal psychosocial problems at the completion of primary dentition years.

https://doi.org/10.1371/journal.pone.0256163.s003

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S3 Table. Univariate regression analysis for variables associated with OHRQoL child and family subdomains.

Result by negative binomial regression model. UUnadjusted risk ratio from univariate regression analysis by negative binomial regression model. Abbreviations: CBCL, Child Behavioral Checklist; STAI, State-Trait Anxiety Inventory; BDI-II, Beck Depression Inventory Second Edition; ECC, Early Childhood Caries; ICDAS-II, International Caries Detection and Assessment System-II.

https://doi.org/10.1371/journal.pone.0256163.s004

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S4 Table. Multivariate regression analysis for all relevant variables associated with OHRQoL dimensions using a sensitivity analysis with complete cases.

https://doi.org/10.1371/journal.pone.0256163.s005

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Acknowledgments

Authors would like to give special thanks to these GUSTO subdomain members for their for their valuable contributions and support: Airu Chia, Allan Sheppard, Amutha Chinnadurai, Anna Magdalena Fogel, Anne Eng Neo Goh, Anne Hin Yee Chu, Anne Rifkin-Graboi, Anqi Qiu, Arijit Biswas, Bee Wah Lee, Birit Froukje Philipp Broekman, Bobby Kyungbeom Cheon, Boon Long Quah, Candida Vaz, Chai Kiat Chng, Cheryl Shufen Ngo, Choon Looi Bong, Christiani Jeyakumar Henry, Ciaran Gerard Forde, Claudia Chi, Daniel Yam Thiam Goh, Dawn Xin Ping Koh, Desiree Y. Phua, Doris Ngiuk Lan Loh, E Shyong Tai, Elaine Kwang Hsia Tham, Elaine Phaik Ling Quah, Elizabeth Huiwen Tham, Evelyn Chung Ning Law, Evelyn Xiu Ling Loo, Fabian Kok Peng Yap, Faidon Magkos, Falk Müller-Riemenschneider, George Seow Heong Yeo, Hannah Ee Juen Yong, Helen Yu Chen, Heng Hao Tan, Hong Pan, Hugo P S van Bever, Hui Min Tan, Iliana Magiati, Inez Bik Yun Wong, Ives Yubin Lim, Ivy Yee-Man Lau, Izzuddin Bin Mohd Aris, Jeannie Tay, Jeevesh Kapur, Jenny L. Richmond, Jerry Kok Yen Chan, Jia Xu, Joanna Dawn Holbrook, Joanne Su-Yin Yoong, Joao Nuno Andrade Requicha Ferreira, Johan Gunnar Eriksson, Jonathan Tze Liang Choo, Jonathan Y. Bernard, Jonathan Yinhao Huang, Joshua J. Gooley, Jun Shi Lai, Karen Mei Ling Tan, Keith M. Godfrey, Kenneth Yung Chiang Kwek, Keri McCrickerd, Kok Hian Tan, Kothandaraman Narasimhan, Krishnamoorthy Naiduvaje, Kuan Jin Lee, Leher Singh, Li Chen, Lieng Hsi Ling, Lin Lin Su, Ling-Wei Chen, Lourdes Mary Daniel, Lynette Pei-Chi Shek, Marielle V. Fortier, Mark Hanson, Mary Foong-Fong Chong, Mary Rauff, Mei Chien Chua, Melvin Khee-Shing Leow, Michael J. Meaney, Michelle Zhi Ling Kee, Min Gong, Mya Thway Tint, Navin Michael, Neerja Karnani, Ngee Lek, Oon Hoe Teoh, P. C. Wong, Paulin Tay Straughan, Peter David Gluckman, Pratibha Keshav Agarwal, Priti Mishra, Queenie Ling Jun Li, Rob Martinus van Dam, Salome A. Rebello, Sambasivam Sendhil Velan, Seang Mei Saw, See Ling Loy, Seng Bin Ang, Shang Chee Chong, Sharon Ng, Shiao-Yng Chan, Shirong Cai, Shu-E Soh, Sok Bee Lim, Stella Tsotsi, Stephen Chin-Ying Hsu, Sue-Anne Ee Shiow Toh, Suresh Anand Sadananthan, Swee Chye Quek, Varsha Gupta, Victor Samuel Rajadurai, Walter Stunkel, Wayne Cutfield, Wee Meng Han, Wei Wei Pang, Wen Lun Yuan, Yanan Zhu, Yap Seng Chong, Yin Bun Cheung, Yiong Huak Chan, Yung Seng Lee.

Citation: Choe R, Sim YF, Hong CHL, Mohideen S, Nadarajan R, Yap F, et al. (2021) Internalizing problems are associated with oral health-related quality of life in early childhood: Outcomes from an Asian multi-ethnic prospective birth cohort. PLoS ONE 16(8): e0256163. https://doi.org/10.1371/journal.pone.0256163

References

1. Petersen PE. Global policy for improvement of oral health in the 21st century–implications to oral health research of World Health Assembly 2007, World Health Organization. Community dentistry and oral epidemiology. 2009;37(1):1–8. pmid:19046331

2. Petersen PE. Priorities for research for oral health in the 21st century—the approach of the WHO Global Oral Health Programme. Community Dent Health. 2005;22(2):71–4. pmid:15984131.

3. Petersen PE. World Health Organization global policy for improvement of oral health—World Health Assembly 2007. Int Dent J. 2008;58(3):115–21. pmid:18630105.

4. Kassebaum N, Bernabé E, Dahiya M, Bhandari B, Murray C, Marcenes W. Global burden of untreated caries: a systematic review and metaregression. Journal of dental research. 2015;94(5):650–8. pmid:25740856

5. Boeira GF, Correa MB, Peres KG, Peres MA, Santos IS, Matijasevich A, et al. Caries is the main cause for dental pain in childhood: findings from a birth cohort. Caries Res. 2012;46(5):488–95. pmid:22813889.

6. Feitosa S, Colares V, Pinkham J. The psychosocial effects of severe caries in 4-year-old children in Recife, Pernambuco, Brazil. Cad Saude Publica. 2005;21(5):1550–6. pmid:16158161.

7. Hu S, Sim YF, Toh JY, Saw SM, Godfrey KM, Chong YS, et al. Infant dietary patterns and early childhood caries in a multi-ethnic Asian cohort. Scientific reports. 2019;9(1):852. pmid:30696871.

8. Moura-Leite FR, Ramos-Jorge ML, Bonanato K, Paiva SM, Vale MP, Pordeus IA. Prevalence, intensity and impact of dental pain in 5-year-old preschool children. Oral Health Prev Dent. 2008;6(4):295–301. pmid:19178094.

9. Abanto J, Carvalho TS, Mendes FM, Wanderley MT, Bonecker M, Raggio DP. Impact of oral diseases and disorders on oral health-related quality of life of preschool children. Community Dent Oral Epidemiol. 2011;39(2):105–14. pmid:21029148.

10. Clementino MA, Gomes MC, Pinto-Sarmento TC, Martins CC, Granville-Garcia AF, Paiva SM. Perceived Impact of Dental Pain on the Quality of Life of Preschool Children and Their Families. PloS one. 2015;10(6):e0130602. pmid:26090927.

11. Granville-Garcia AF, Gomes MC, Perazzo MF, Martins CC, Abreu M, Paiva SM. Impact of Caries Severity/Activity and Psychological Aspects of Caregivers on Oral Health-Related Quality of Life among 5-Year-Old Children. Caries Res. 2018;52(6):570–9. pmid:29723865.

12. Kramer PF, Feldens CA, Ferreira SH, Bervian J, Rodrigues PH, Peres MA. Exploring the impact of oral diseases and disorders on quality of life of preschool children. Community Dent Oral Epidemiol. 2013;41(4):327–35. pmid:23330729.

13. Krisdapong S, Somkotra T, Kueakulpipat W. Disparities in early childhood caries and its impact on oral health-related quality of life of preschool children. Asia-Pacific journal of public health. 2014;26(3):285–94. pmid:22426563.

14. Li MY, Zhi QH, Zhou Y, Qiu RM, Lin HC. Impact of early childhood caries on oral health-related quality of life of preschool children. European journal of paediatric dentistry: official journal of European Academy of Paediatric Dentistry. 2015;16(1):65–72. pmid:25793957.

15. Martins-Junior PA, Vieira-Andrade RG, Correa-Faria P, Oliveira-Ferreira F, Marques LS, Ramos-Jorge ML. Impact of early childhood caries on the oral health-related quality of life of preschool children and their parents. Caries Res. 2013;47(3):211–8. pmid:23257929.

16. Scarpelli AC, Paiva SM, Viegas CM, Carvalho AC, Ferreira FM, Pordeus IA. Oral health-related quality of life among Brazilian preschool children. Community Dent Oral Epidemiol. 2013;41(4):336–44. pmid:23253051.

17. Wong HM, McGrath CP, King NM, Lo EC. Oral health-related quality of life in Hong Kong preschool children. Caries Res. 2011;45(4):370–6. pmid:21822015.

18. Un Lam C, Khin LW, Kalhan AC, Yee R, Lee YS, Chong MF, et al. Identification of Caries Risk Determinants in Toddlers: Results of the GUSTO Birth Cohort Study. Caries Res. 2017;51(4):271–82. pmid:28538220.

19. Soh SE, Tint MT, Gluckman PD, Godfrey KM, Rifkin-Graboi A, Chan YH, et al. Cohort profile: Growing Up in Singapore Towards healthy Outcomes (GUSTO) birth cohort study. Int J Epidemiol. 2014;43(5):1401–9. pmid:23912809.

20. Sischo L, Broder HL. Oral health-related quality of life: what, why, how, and future implications. J Dent Res. 2011;90(11):1264–70. pmid:21422477.

21. Rebok G, Riley A, Forrest C, Starfield B, Green B, Robertson J, et al. Elementary school-aged children’s reports of their health: a cognitive interviewing study. Qual Life Res. 2001;10(1):59–70. pmid:11508476.

22. Pahel BT, Rozier RG, Slade GD. Parental perceptions of children’s oral health: the Early Childhood Oral Health Impact Scale (ECOHIS). Health Qual Life Outcomes. 2007;5:6. pmid:17263880.

23. Sawyer MG, Whaites L, Rey JM, Hazell PL, Graetz BW, Baghurst P. Health-related quality of life of children and adolescents with mental disorders. J Am Acad Child Adolesc Psychiatry. 2002;41(5):530–7. pmid:12014785.

24. Soleimani MA, Sharif SP, Bahrami N, Yaghoobzadeh A, Allen KA, Mohammadi S. The relationship between anxiety, depression and risk behaviors in adolescents. International journal of adolescent medicine and health. 2017;31(2). pmid:28493817

25. Zeltzer LK, Bush JP, Chen E, Riveral A. A psychobiologic approach to pediatric pain: Part 1. History, physiology, and assessment strategies. Current problems in pediatrics. 1997;27(6):225–53. pmid:9377897.

26. Cademartori MG, Corrêa MB, Silva RA, Goettems ML. Childhood social, emotional, and behavioural problems and their association with behaviour in the dental setting. International Journal of Paediatric Dentistry. 2019;29(1):43–9. pmid:30381852

27. Klingberg G. Dental fear and behavior management problems in children. A study of measurement, prevalence, concomitant factors, and clinical effects. Swed Dent J Suppl. 1995;103:1–78. pmid:7740439.

28. Walker LS, Garber J, Van Slyke DA, Greene JW. Long-term health outcomes in patients with recurrent abdominal pain. Journal of pediatric psychology. 1995;20(2):233–45. pmid:7760222.

29. Astrada CA, Licamele WL, Walsh TL, Kessler ES. Recurrent abdominal pain in children and associated DSM-III diagnosis. The American journal of psychiatry. 1981;138(5):687–8. pmid:7235071.

30. Ernst AR, Routh DK, Harper DC. Abdominal pain in children and symptoms of somatization disorder. Journal of pediatric psychology. 1984;9(1):77–86. pmid:6726552.

31. Mahrer NE, Montaño Z, Gold JI. Relations Between Anxiety Sensitivity, Somatization, and Health-Related Quality of Life in Children With Chronic Pain. Journal of pediatric psychology. 2012;37(7):808–16. pmid:22493024

32. Malleson PN, al-Matar M, Petty RE. Idiopathic musculoskeletal pain syndromes in children. The Journal of rheumatology. 1992;19(11):1786–9. pmid:1491402.

33. Naish JM, Apley J. "Growing pains": a clinical study of non-arthritic limb pains in children. Archives of disease in childhood. 1951;26(126):134–40. pmid:14830278.

34. Campo JV, Jansen-McWilliams L, Comer DM, Kelleher KJ. Somatization in pediatric primary care: association with psychopathology, functional impairment, and use of services. J Am Acad Child Adolesc Psychiatry. 1999;38(9):1093–101. pmid:10504807.

35. Campo JV, Bridge J, Ehmann M, Altman S, Lucas A, Birmaher B, et al. Recurrent abdominal pain, anxiety, and depression in primary care. Pediatrics. 2004;113(4):817–24. pmid:15060233.

36. Just U, Oelkers R, Bender S, Parzer P, Ebinger F, Weisbrod M, et al. Emotional and behavioural problems in children and adolescents with primary headache. Cephalalgia: an international journal of headache. 2003;23(3):206–13. pmid:12662188.

37. Lavigne JV, Schulein MJ, Hahn YS. Psychological aspects of painful medical conditions in children. II. Personality factors, family characteristics and treatment. Pain. 1986;27(2):147–69. pmid:3540811.

38. Anttila P, Sourander A, Metsahonkala L, Aromaa M, Helenius H, Sillanpaa M. Psychiatric symptoms in children with primary headache. J Am Acad Child Adolesc Psychiatry. 2004;43(4):412–9. pmid:15187801.

39. Alfven G. Understanding the nature of multiple pains in children. The Journal of pediatrics. 2001;138(2):156–8. pmid:11174608.

40. Soh SE, Chong YS, Kwek K, Saw SM, Meaney MJ, Gluckman PD, et al. Insights from the Growing Up in Singapore Towards Healthy Outcomes (GUSTO) cohort study. Ann Nutr Metab. 2014;64(3–4):218–25. pmid:25300263.

41. Jafar NK, Tham EK, Eng DZ, Goh DY, Teoh OH, Lee YS, et al. The association between chronotype and sleep problems in preschool children. Sleep medicine. 2017;30:240–4. pmid:28215256.

42. Chong SC, Broekman BF, Qiu A, Aris IM, Chan YH, Rifkin-Graboi A, et al. Anxiety and depression during pregnancy and temperament in early infancy: findings from a multi-ethnic, asian, prospective birth cohort study. Infant mental health journal. 2016;37(5):584–98. pmid:27548536.

43. Soe NN, Wen DJ, Poh JS, Li Y, Broekman BF, Chen H, et al. Pre- and Post-Natal Maternal Depressive Symptoms in Relation with Infant Frontal Function, Connectivity, and Behaviors. PloS one. 2016;11(4):e0152991. pmid:27073881.

44. Achenbach TM. Manual for the child behavior checklist/4-18 and 1991 profile. Burlington, VT: Dept. of Psychiatry, University of Vermont; 1991.

45. Rescorla LA, Bochicchio L, Achenbach TM, Ivanova MY, Almqvist F, Begovac I, et al. Parent-teacher agreement on children’s problems in 21 societies. J Clin Child Adolesc Psychol. 2014;43(4):627–42. pmid:24787452.

46. Ivanova MY, Achenbach TM, Rescorla LA, Harder VS, Ang RP, Bilenberg N, et al. Preschool psychopathology reported by parents in 23 societies: testing the seven-syndrome model of the child behavior checklist for ages 1.5–5. J Am Acad Child Adolesc Psychiatry. 2010;49(12):1215–24. pmid:21093771.

47. Tsotsi S, Broekman BF, Shek LP, Tan KH, Chong YS, Chen H, et al. Maternal Parenting Stress, Child Exuberance, and Preschoolers’ Behavior Problems. Child development. 2018.

48. Spielberger C, Gorsuch R, Lushene R, Vagg P, Jacobs G. Consulting Psychologists Press; Palo Alto, CA: 1983. Manual for the state-trait anxiety inventory. 1983.

49. Meades R, Ayers S. Anxiety measures validated in perinatal populations: a systematic review. Journal of affective disorders. 2011;133(1–2):1–15. pmid:21078523

50. Qiu A, Rifkin-Graboi A, Chen H, Chong Y, Kwek K, Gluckman P, et al. Maternal anxiety and infants’ hippocampal development: timing matters. Translational psychiatry. 2013;3(9):e306. pmid:24064710

51. Beck AT, Steer RA, Brown GK. Beck depression inventory-II. San Antonio. 1996;78(2):490–8.

52. Dworkin RH, Turk DC, Wyrwich KW, Beaton D, Cleeland CS, Farrar JT, et al. Interpreting the clinical importance of treatment outcomes in chronic pain clinical trials: IMMPACT recommendations. The journal of pain. 2008;9(2):105–21. pmid:18055266

53. Ismail AI, Sohn W, Tellez M, Amaya A, Sen A, Hasson H, et al. The International Caries Detection and Assessment System (ICDAS): an integrated system for measuring dental caries. Community dentistry and oral epidemiology. 2007;35(3):170–8. pmid:17518963

54. Nuttall NM, Steele JG, Evans D, Chadwick B, Morris AJ, Hill K. The reported impact of oral condition on children in the United Kingdom, 2003. British dental journal. 2006;200(10):551–5. pmid:16732242.

55. Tsakos G, Hill K, Chadwick B, Anderson T. Children’s Dental Health Survey 2013 Report 1: Attitudes, Behaviours and Children’s Dental Health England, Wales and Northern Ireland, 2013. Online information available at http://wwwhscicgovuk/catalogue/PUB17137/CDHS2013-Report1-Attitudes-and-Behaviourspdf (accessed September 2015). 2015.

56. Khanh LN, Ivey SL, Sokal-Gutierrez K, Barkan H, Ngo KM, Hoang HT, et al. Early Childhood Caries, Mouth Pain, and Nutritional Threats in Vietnam. American journal of public health. 2015;105(12):2510–7. pmid:26469655.

57. Mathers N, Fox N, Hunn A. Surveys and Questionnaires, The NIHR Research Design Service For Yorkshire and the Humber. National Institute for Health Research, East Midlands, available at: wwwrds-yhnihracuk/wp-content/uploads/2013/05/12_Surveys_and_Questionnaires_Revision_2009pdf (accessed May 2017) [Google Scholar]. 2007.

58. InFORM. International Network for Orofacial Pain and Related Disorders Methodology: TMD Assessment/Diagnosis 2013 [12 December 2020]. Available from: https://ubwp.buffalo.edu/rdc-tmdinternational/tmd-assessmentdiagnosis/dc-tmd/.

59. International Classification of Orofacial Pain, 1st edition (ICOP). Cephalalgia: an international journal of headache. 2020;40:129–221. pmid:32103673

60. Al-Khotani A, Naimi-Akbar A, Albadawi E, Ernberg M, Hedenberg-Magnusson B, Christidis N. Prevalence of diagnosed temporomandibular disorders among Saudi Arabian children and adolescents. The journal of headache and pain. 2016;17:41. pmid:27102118.

61. Al-Khotani A, Naimi-Akbar A, Gjelset M, Albadawi E, Bello L, Hedenberg-Magnusson B, et al. The associations between psychosocial aspects and TMD-pain related aspects in children and adolescents. The journal of headache and pain. 2016;17:30. pmid:27044436.

62. Al-Khotani A, Gjelset M, Naimi-Akbar A, Hedenberg-Magnusson B, Ernberg M, Christidis N. Using the child behavior checklist to determine associations between psychosocial aspects and TMD-related pain in children and adolescents. The journal of headache and pain. 2018;19(1):88. pmid:30242517.

63. Galli F, D’Antuono G, Tarantino S, Viviano F, Borrelli O, Chirumbolo A, et al. Headache and recurrent abdominal pain: a controlled study by the means of the Child Behaviour Checklist (CBCL). Cephalalgia: an international journal of headache. 2007;27(3):211–9. pmid:17381555.

64. Varni JW, Wilcox KT, Hanson V, Brik R. Chronic musculoskeletal pain and functional status in juvenile rheumatoid arthritis: an empirical model. Pain. 1988;32(1):1–7. pmid:3340417.

65. Prins PJ. Self-speech and self-regulation of high- and low-anxious children in the dental situation: an interview study. Behaviour research and therapy. 1985;23(6):641–50. pmid:4074277.

66. Pain terms: a list with definitions and notes on usage. Recommended by the IASP Subcommittee on Taxonomy. Pain. 1979;6(3):249. pmid:460932.

67. Brown JM, O’Keeffe J, Sanders SH, Baker B. Developmental changes in children’s cognition to stressful and painful situations. Journal of pediatric psychology. 1986;11(3):343–57. pmid:3772682.

68. Kuttner L. Management of young children’s acute pain and anxiety during invasive medical procedures. Pediatrician. 1989;16(1–2):39–44. pmid:2657691.

69. Jay SM, Elliott C, Varni JW. Acute and chronic pain in adults and children with cancer. Journal of consulting and clinical psychology. 1986;54(5):601–7. pmid:3534030.

70. Katz ER, Kellerman J, Siegel SE. Behavioral distress in children with cancer undergoing medical procedures: developmental considerations. Journal of consulting and clinical psychology. 1980;48(3):356–65. pmid:7381095.

71. Barsky AJ, Goodson JD, Lane RS, Cleary PD. The amplification of somatic symptoms. Psychosomatic medicine. 1988;50(5):510–9. pmid:3186894.

72. Andrasik F, Schwartz MS. Behavioral Assessment and Treatment of Pediatric Headache. Behavior Modification. 2006;30(1):93–113. pmid:16330521

73. Apkarian AV, Bushnell MC, Treede R-D, Zubieta J-K. Human brain mechanisms of pain perception and regulation in health and disease. European journal of pain. 2005;9(4):463–84. pmid:15979027

74. Korhonen M, Luoma I, Salmelin R, Tamminen T. Maternal depressive symptoms: Associations with adolescents’ internalizing and externalizing problems and social competence. Nordic Journal of Psychiatry. 2014;68(5):323–32. pmid:24070429

75. Koechlin H, Donado C, Berde CB, Kossowsky J. Effects of Childhood Life Events on Adjustment Problems in Adolescence: A Longitudinal Study. J Dev Behav Pediatr. 2018;39(8):629–41. pmid:29944491.

76. Sourander A, Pihlakoski L, Aromaa M, Rautava P, Helenius H, Sillanpää M. Early predictors of parent- and self-reported perceived global psychological difficulties among adolescents. Social Psychiatry and Psychiatric Epidemiology. 2006;41(3):173–82. pmid:16467953

77. Bandura A. Social Cognitive Theory of Mass Communication. Media Psychology. 2001;3(3):265–99.

78. Slade GD, Strauss RP, Atchison KA, Kressin NR, Locker D, Reisine ST. Conference summary: assessing oral health outcomes—measuring health status and quality of life. Community Dent Health. 1998;15(1):3–7. pmid:9791607

79. McGrath PJ, Cunningham SJ, Goodman JT, Unruh A. The clinical measurement of pain in children: a review. The Clinical journal of pain. 1985;1(4):221–8.

80. Cremeens J, Eiser C, Blades M. Factors influencing agreement between child self-report and parent proxy-reports on the Pediatric Quality of Life Inventory 4.0 (PedsQL) generic core scales. Health Qual Life Outcomes. 2006;4:58. pmid:16942613.

81. Versloot J, Veerkamp JS, Hoogstraten J. Dental Discomfort Questionnaire: assessment of dental discomfort and/or pain in very young children. Community Dent Oral Epidemiol. 2006;34(1):47–52. pmid:16423031.

82. Charlton JE. Core curriculum for professional education in pain. 2005.

83. Schuch HS, Correa MB, Torriani DD, Demarco FF, Goettems ML. Perceived dental pain: determinants and impact on brazilian schoolchildren. J Oral Facial Pain Headache. 2015;29(2):168–76. pmid:25905535.

84. Zeltzer LK, Bush JP, Chen E, Riveral A. A psychobiologic approach to pediatric pain: Part II. Prevention and treatment. Current problems in pediatrics. 1997;27(7):264–84. pmid:9339353.

85. McGrath PA. Psychological aspects of pain perception. Archives of Oral Biology. 1994;39:S55–S62. pmid:7702468

86. Freire M, Correa-Faria P, Costa LR. Effect of dental pain and caries on the quality of life of Brazilian preschool children. Revista de saude publica. 2018;52:30. pmid:29641655.

87. Dikmen B. Icdas II criteria (international caries detection and assessment system). Journal of Istanbul University Faculty of Dentistry. 2015;49(3):63–72. pmid:28955548.

88. Carino KM, Shinada K, Kawaguchi Y. Early childhood caries in northern Philippines. Community Dent Oral Epidemiol. 2003;31(2):81–9. pmid:12641587.

89. Pine CM, Harris RV, Burnside G, Merrett MC. An investigation of the relationship between untreated decayed teeth and dental sepsis in 5-year-old children. British dental journal. 2006;200(1):45–7; discussion 29. pmid:16415836.

90. Castro ALS, Vianna MIP, Mendes CMC. Comparison of caries lesion detection methods in epidemiological surveys: CAST, ICDAS and DMF. BMC Oral Health. 2018;18(1):122. pmid:29980199

91. Honkala E, Runnel R, Honkala S, Olak J, Vahlberg T, Saag M, et al. Measuring dental caries in the mixed dentition by ICDAS. International journal of dentistry. 2011;2011. pmid:22114594

92. Sae-Lim V, Hon TH, Wing YK. Traumatic dental injuries at the Accident and Emergency Department of Singapore General Hospital. Endod Dent Traumatol. 1995;11(1):32–6. pmid:7641613.

93. Almerich-Silla J-M, Boronat-Ferrer T, Montiel-Company J-M, Iranzo-Cortés J-E. Caries prevalence in children from Valencia (Spain) using ICDAS II criteria, 2010. Med Oral Patol Oral Cir Bucal. 2014;19(6):e574–e80. pmid:25350591.

94. Slade GD. Epidemiology of dental pain and dental caries among children and adolescents. Community Dent Health. 2001;18(4):219–27. pmid:11789699.

95. Ramchandani PG, Hotopf M, Sandhu B, Stein A; ALSPAC Study Team. The epidemiology of recurrent abdominal pain from 2 to 6 years of age: results of a large, population-based study. Pediatrics. 2005 Jul;116(1):46–50. pmid:15995029.

96. Shulman RJ. Dietary issues in recurrent abdominal pain. J Pediatr Gastroenterol Nutr. 2012 Nov;55 Suppl 2(0 2):S40–2. pmid:23103654.

97. Fisher-Owens SA, Gansky SA, Platt LJ, Weintraub JA, Soobader MJ, Bramlett MD, et al. Influences on children’s oral health: a conceptual model. Pediatrics. 2007 Sep;120(3):e510–20. pmid:17766495.

98. Kim Seow W. Environmental, maternal, and child factors which contribute to early childhood caries: a unifying conceptual model. Int J Paediatr Dent. 2012 May;22(3):157–68. pmid:21972925.