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Oral health-related quality of life and early childhood caries among preschool children in Trinidad

Oral health-related quality of life and early childhood caries among preschool children in Trinidad Background: Early childhood caries (ECC) is a public health problem in developed and developing countries. The purpose of this study was to describe the relationship between oral health-related quality of life (OHRQoL) and ECC among preschool children in a Caribbean population. Method: Parents/primary caregivers of children attending nine, randomly selected preschools in central Trinidad were invited to complete an oral health questionnaire and have their child undertake an oral examination. The questionnaire included the Early Childhood Oral Health Impact Scale (ECOHIS). Visible caries experience was assessed using WHO criteria. Logistic regression models were used to determine the factors associated with OHRQoL and ECC. Results: Three hundred nine parents/caregivers participated in the study (age-range 25–44 years) and 251 children (mean age 3.7 years) completed oral examinations. Adjusting for other factors, the odds for a child aged 4 years of having dental caries were greater than the odds for a child aged 3 years (OR 3.61; 95% CI (1.76, 6.83). The odds for children having difficulty drinking hot or cold drinks were greater for those with dental caries than the odds for children who have no such difficulty. Similarly, the odds for children who had difficulty eating were greater for those with dental caries than the odds ratios for children who had no difficulty eating (OR 8.29; 95% CI (2.00, 43.49). Adjusting for the effects of other factors, the odds of parents/caregivers feeling guilty were greater if their child had experienced dental caries in comparison to parents/caregivers whose child did not have dental caries (OR 3.50; 95% CI (1.32, 9.60). Adjusting for other factors, the odds of parents/primary caregivers having poor quality of life was increased when they had a child with a dmft in the range 1–3 (OR 2.68; 95% CI (1.30, 5.64) dmft > 4 (OR 8.58; 95%CI (3.71, 22.45), in comparison to those whose child had a dmft = 0. Conclusion: In this sample of preschool children OHRQoL was associated with ECC. More negative impacts were found in children with a greater severity of visible caries experience. This suggests the need for strategies to prevent and manage ECC in this Caribbean population. Keywords: Early childhood caries, Quality of life, Preschool children, Caribbean Background any sign of smooth-surface caries is indicative of severe Early Childhood Caries (ECC) has been defined by the early childhood caries (S-ECC) [1]. American Academy of Pediatric Dentistry as ‘the presence Beyond the immediate distress caused by toothache, of one or more decayed, missing due to caries, or filled early childhood caries (ECC) can also have longer term tooth surfaces in any primary teeth in children under 6 negative, health outcomes [2, 3]. Untreated decay in years of age [1]. In children younger than 3 years of age, infancy and early childhood is believed to affect weight gain and overall growth and development [4]. Along with these patho-physiological effects, ECC can impact * Correspondence: [email protected] on oral health related quality of life (OHRQoL) [2, 3]. As School of Dentistry, The University of the West Indies, Saint Augustine, parents and caregivers have the main responsibility for Trinidad and Tobago Full list of author information is available at the end of the article © The Author(s). 2016 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. Naidu et al. BMC Oral Health (2016) 16:128 Page 2 of 9 their preschool-aged children, ECC can also affect them preschools of similar sizes and enable data collection by indirectly, for example, work-loss and financial impact a single examiner. Stratification was not employed. duetohavingtostayathometotake careof the Ethical approval for the study was obtained from The child [5]. ECC is therefore recognized as a public University of the West Indies, Faculty of Medical health problem due to its high prevalence in some Sciences Research Ethics Committee. Permission for the populations and the potential for negative health im- selected preschool’s inclusion in the study was obtained pacts if left untreated [6, 7]. from individual head teachers and written positive The few studies that have been undertaken in the consent was requested from parents and caregivers for English-speaking Caribbean suggest that caries preva- the oral examinations. Self-administered oral health ques- lence among infants and preschool children in the tionnaires were provided to participating preschools. region is high [8, 9]. In central Trinidad, the prevalence These questionnaires were then given to all parents and of ECC among 251 preschool children was reported as caregivers by the school administration, along with a 29.1% with the majority of this being untreated, decayed consent form. teeth and 12% of children were in need of urgent care or OHRQoL was measured using the Early Childhood referral [10]. Affordability and access to dental care for Oral Health Impact Scale (ECOHIS) [3], included as people from lower socioeconomic groups and those part of the oral health questionnaire. The ECOHIS is living in rural locations is a challenge in Trinidad and a short, condition-specific tool, to be completed by Tobago as most of the county’s registered dentists work the child’s parent or primary caregiver. It has been in private practices, generally clustered in urban centers. validated in the English language and translated Although there are international reports on OHRQoL versions are reported to have good psychometric of preschool children [11–16], nothing is known about properties [3]. The ECOHIS consists of questions re- the effect of ECC on OHRQoL among preschool children lating to quality of life domains for both the child in the Caribbean. and the family. These domains include: symptoms, Understanding the impact of dental caries in young function, psychological effects, self-image, parent children and their families can guide the development of distress and family function [3]. Responses are based treatment and preventive protocols as part of dental on the scale: Never, Hardly ever, Occasionally, Often, Very service planning. often, Don’t know. Scores for the instrument are calculated The aim of this study was to describe the relationship from the sum of responses for the child (0–36) and family between OHRQoL and ECC among preschool children sections (0–16) and reported as mean impacts per item/ in Trinidad. section (maximum overall score of 52). Higher mean ECOHIS score represents worse OHRQoL. Method The ECOHIS instrument was piloted among 30 par- A cross-sectional oral health survey of preschool children ents and caregivers of young children attending a dental was undertaken in the Caroni region of central Trinidad. hospital clinic in Trinidad. The instrument was found to The accessible population were children aged 3 to 5 years have acceptable face and content validity and thus did of age, attending preschools in the Caroni Education not require any modification. The ‘don’tknow’ response District. Based on the list of registered preschools, there were treated as ‘missing’ for the analyses. were 27 government/government-assisted and 57 non- Dental examinations were undertaken by a single, government preschools in the district at the time of the trained and calibrated dentist (RN) using WHO criteria survey, with an enrolled population of approximately 2000 [17]. Training and calibration was achieved by use of children. Previous data from Anguilla [9] (which estimated clinical slides on CD ROM, representing all categories of prevalence at 30%) was used to determine that 340 caries to be assessed and recorded. This was done under children were required to assess caries prevalence within the supervision of a dental epidemiologist (JN). Exami- the preschool population in the district. This figure nations took place in classrooms using natural light, accounted for 6% precision and 20% non-response rate. with the child in a seated position on a small chair/ Sampling consisted of cluster sampling within the bench with the examiner positioned behind. Teeth were Caroni Education District. A total of ten schools were assessed visually with the use of a disposable mouth selected by systematic random sampling from the school mirror, with the examiner wearing disposable gloves and lists (three government/assisted schools and seven non- facemask. New gloves and a mouth mirror were used for government preschools). Each cluster consisted of all each child. Teeth were not air dried but soft debris on registered children within the preschool. Each preschool tooth surfaces was removed with a cotton roll or gauze was assumed to have an average of 30 registered chil- square. dren. Very small schools (<15) and very large schools Examiner reliability was assessed by re-examination of (>60) were excluded, in order to enable inclusion of children at one preschool (25 children). These re- Naidu et al. BMC Oral Health (2016) 16:128 Page 3 of 9 examinations took place on the same day as data collec- Results tion. The Kappa statistic for intra-examiner reliability From an enrolment of 340 children, 314 parents gave was 0.9. Data collection was undertaken over a three- consent for the oral examination (91% response rate). Of month period. these children, 36 (11.5%) were absent on the day and In the field, oral examination data were entered onto a 27 (8.6%) refused examination. Three hundred and nine record sheet by a research assistant. This information parents completed the questionnaire (Table 1). The was subsequently transferred to a computer database mean age of the parents and primary caregivers was not (SPSS v 16) for storage and processing. Data were determined as the questionnaire only recorded respondent cleaned and checked for transcription errors before age-range. Among these 309 respondents, 90% of parents/ processing using SPSS version 16 for Windows and primary caregivers were in the age range 25–44 years. STATA version 10. Parent/primary caregiver ethnicity was 74.4% Indian, Statistical analysis Logistic regression models were adopted to determine Table 1 Socio-demographic information for all parents and the family and child related factors associated with dmft caregivers (N = 309) and ECOHIS. Specifically, models examining factors re- n Percent lating to dmft were used to examine the odds of children Age group having a dmft > 0 compared to the odds of children with 18–24 17 5.5 a dmft = 0. Similarly, the odds of a parent/primary care- 25–34 183 59.2 giver having an ECOHIS score >0 was compared to the 35–44 95 30.7 odds of parents/primary caregivers with an ECOHIS score = 0, taking sociodemographic factors into account. 45–54 8 2.6 Child and/or parent-primary caregiver characteristics 55–64 2 0.7 were included as fixed effects in the models and a 65+ 1 0.3 random intercept was included to account for cluster Missing 3 1.0 variation (i.e. variation within preschools). Akaike’sin- Ethnic group formation criteria and likelihood ratio tests were used African 35 11.3 to evaluate goodness of fit. In addition to variables retained in the final model, all models were adjusted Indian 230 74.4 for age and sex. Model sensitivity and specificity were Mixed 41 13.3 examined using receiver operating characteristic White 1 0.3 curves and area under the curve (AUC). If a model Other 2 0.7 achieves perfect sensitivity and specificity, then the Occupation AUC would have a value of 1. If the AUC has a value Professional 11 3.6 of 0.5 then the model achieves poor sensitivity and specificity. Despite estimation of AUC, the models de- Managerial/lower professional 48 15.5 veloped for this research are for descriptive purposes, Non-manual 44 14.2 they are not intended for prediction. Generalised Manual -skilled 107 34.6 variance inflation factors (GVIF) and adjusted GVIF Manual- semi-skilled 6 1.9 were used to determine the presence of multicolli- Manual –unskilled 43 13.9 nearity. Model results are displayed in terms of odds Housewife/unemployed 15 4.9 ratios (ORs) and corresponding 95% confidence inter- val (CI). ORs have a range from 0 to infinity. An OR Retired/old-age pensioner 7 2.3 equal to one, denotes that there is no difference in Missing 28 9.1 odds whereas an OR greater than 1 indicates, for in- Education stance, that the ratio of those with a dmft > 0 versus None 1 0.3 a dmft = 0 in the selected group is greater than the Primary 29 9.4 baseline group. If there is no evidence to suggest that Secondary 255 50.2 the ratio of those with dmft > 0 (versus dmft = 0) for the selected group are different from the baseline Technical college 54 17.5 group, then the 95% CI for the OR will contain 1 in University 49 15.9 the interval. Other 15 4.9 Statistical analysis was performed using statistical Missing 6 1.9 software R (version 3.2.3) [18]. Naidu et al. BMC Oral Health (2016) 16:128 Page 4 of 9 Table 2 Socio-demographic information for parents/caregivers whose child completed the oral health assessment (N = 251) ECOHIS = 0 ECOHIS > 0 dmft = 0 dmft > 0 Count % Count % Count % Count % Parent/primary caregiver characteristics Age < 25 years 8 3.19 7 2.79 12 4.78 3 1.20 25–34 83 33.07 64 25.50 102 40.64 45 17.93 35–44 46 18.33 32 12.75 54 21.51 24 9.56 45+ 7 2.79 2 0.80 8 3.19 1 0.40 Unknown 2 0.80 0 0.00 2 0.80 0 0.00 Sex Male 16 6.37 14 5.58 24 9.56 6 2.39 Female 130 51.79 91 36.25 154 61.35 67 26.69 Education Primary or lower 13 5.18 11 4.38 15 5.98 9 3.59 Secondary 47 18.73 38 15.14 85 33.86 40 15.94 Third level 74 29.48 51 20.32 64 25.50 21 8.37 Other 9 3.59 4 1.59 11 4.38 2 0.80 Unknown 3 1.20 1 0.40 3 1.20 1 0.40 Visits to the dentist Never 27 10.76 19 7.57 30 11.95 16 6.37 1–2 per year 82 32.67 55 21.91 101 40.24 36 14.34 Only when in pain 23 9.16 14 5.58 25 9.96 12 4.78 Other 14 5.58 16 6.37 22 8.76 8 3.19 Unknown 0 0.00 1 0.40 0 0.00 1 0.40 Child characteristics Age (years) 3 56 22.31 29 11.55 71 28.29 14 5.58 4 74 29.48 64 25.50 87 34.66 51 20.32 5 16 6.37 12 4.78 20 7.97 8 3.19 Sex Male 70 27.89 56 22.31 89 35.46 37 14.74 Female 76 30.28 49 19.52 89 35.46 36 14.34 DMFT 0 122 48.61 56 22.31 1–3 16 6.37 20 7.97 > 4 8 3.19 29 11.55 11.3% African, 13.3% mixed and 1% white or other Examination of responses relating to the child’s quality (Table 1). of life indicated that approximately 10.4% (32/309) The ECOHIS showed good internal consistency with a reported that their child experienced pain in the teeth, Cronbach alpha reliability coefficient of 0.94. For the mouth or jaw. child and family sections Cronbach alpha was 0.92 and Approximately 5.2% (16/309) and 4.2% (13/309) re- 0.85, respectively. ported that their child experienced difficulty eating some Overall, quality of life impacts were low, with median foods or difficulty drinking hot or cold drinks. score being 0. Mean impacts scores for the whole instru- Examination of responses relating to family function ment were 2.29 (sd 5.52) and for the child and family indicated that approximately 10% (31/309) of parents/ sections 1.09 (sd 3.62) and 0.80 (sd 2.16), respectively. primary caregivers reported that they felt guilty, 5.2% Naidu et al. BMC Oral Health (2016) 16:128 Page 5 of 9 (16/309) had been upset and 4.9% (15/309) reported that had a value <0.0001. In the principle of parsimony, they had taken time off work due to their child’s oral models with lowest AIC were utilised. With reference to health problems. the model examining family perspectives associated with Despite 309 parent/primary caregivers completing the dmft > 0, the AIC for the model, including random ef- questionnaire, approximately 18% (58/309) of children fects, was 284.14 and was 283.69 for the simplified did not complete the oral examination, thus a total of model. Similarly, the model examining child related 251 children completed the oral examination. Of these factors associated with dmft > 0, the AIC for the model children, 50.2% were male, with an age range of 3 to including random effects was 274.87 and was 273.09 for 5 years-old and mean age of 3.7 years (sd 0.67). Full the less complex model. Examining factors associated with results for visible caries experience have been reported ECOHIS > 0 resulted in the model including random ef- previously [10]. Socio-demographic characteristic for fect having an AIC of 318.19 and the simplified model parents/primary caregivers, together with information having an AIC of 316.19. The factors included in all on ECOHIS and dmft for those children who completed models were free from multicollinearity as all adjusted the oral health assessment, are shown in Table 2. GVIF values had values less than 2. Factors that could not Table 3 shows the frequency of oral health impacts for be included for statistical analysis were ‘child avoided talk- children with some caries experience (dmft > 0) and for ing’ and ‘child being irritable or frustrated’, as these factors those with no caries experience (dmft = 0) for the child had excessively high adjusted GVIF values. The factor and family levels, respectively. ‘child smiling’ was also omitted from the analysis due to Regression analysis was performed on the complete zero observations for this factor with dmft = 0. Crude and dataset excluding all missing and unknown observations. adjusted ORs for children with dmft > 0 compared to As previously stated, initially, there were 340 children to those with dmft = 0 can be seen in Tables 4 and 5. be involved in the study. The final sample was reduced Table 6 shows the crude and adjusted ORs for to 245 (after excluding 7.6% (26/340) of those who did parents/primary caregivers with ECOHIS > 0 compared not give consent and missing observations (69/340). This to those with ECOHIS = 0. Model evaluations indicate accounted for approximately 28% (95/340) not being that the three models are adequate in terms of sensitiv- available for statistical analysis. Thus as a result of this ity, with AUC being estimated as 0.68, 0.64 and 0.74, reduced data set, a number of categories had low respectively. However, as previously stated, these models numbers. Logistic models without a random effect were were not developed for predictive purposes and caution adequate in all three models as the estimated standard must be exercised in model interpretation due to wide deviation for unexplained variation within each cluster confidence intervals. Table 3 Oral health impacts for children with no visible caries dmft = 0 and some visible caries dmft > 0 Never/hardly ever Occasionally/often/very often Don’t know/NA dmft = 0 dmft > 0 dmft = 0 dmft > 0 dmft = 0 dmft > 0 n% n % n % n % n % n % Child impacts Pain in the teeth, mouth or jaw 170 76.9 51 23.1 6 22.2 21 77.8 2 66.6 1 33.3 Difficulty drink hot or cold drinks 174 73.7 62 26.3 2 18.2 9 81.8 2 50.0 2 50.0 Difficulty eating some foods 175 74.5 60 25.5 3 20.0 12 80.0 0 0 1 100 Difficulty pronouncing some words 175 72.6 66 27.4 3 42.9 4 57.1 0 0 3 100 Missed preschool 176 72.1 68 27.9 1 20.0 4 80.0 1 50.0 1 50.0 Trouble sleeping 175 72.9 65 26.4 2 22.2 7 77.8 1 50.0 1 50.0 Been irritable or frustrated 177 74.7 60 25.3 1 8.3 11 91.7 0 0 2 100 Avoided smiling or laughing 176 73.3 64 26.7 1 14.3 6 85.7 1 25.0 3 75.0 Avoided talking 176 72.1 68 27.9 1 20.0 4 80.0 1 50.0 1 50.0 Family impacts Felt upset 173 73.3 63 26.7 4 30.8 9 69.2 1 50.0 1 50.0 Felt guilty 169 75.1 56 24.9 8 33.3 16 66.7 1 50.0 1 50.0 Taken time off work 175 74.5 60 25.5 3 21.4 11 78.6 0 0 1 100 Had a financial impact on your family 177 72.8 66 27.8 1 14.3 6 85.7 0 0 1 100 309 parents/caregiver observations were recorded, of whom 187 had children with dmft = 0, 73 dmft > 0 and 58 unknown dmft Naidu et al. BMC Oral Health (2016) 16:128 Page 6 of 9 Table 4 Child factors associated with DMFT >0 Table 5 Family factors associated with child’s DMFT > 0 Crude OR 95% CI Adjusted OR 95% CI Crude OR 95% CI Adjusted OR 95% CI Child’s age Parent/primary caregiver age 3 1.0 1.0 < 25 years 0.61 (0.13, 2.16) 0.35 (0.05, 1.53) 4 3.08 (1.59, 6.34) 3.61 (1.76, 7.95) 25–34 1.12 (0.61, 2.07) 1.06 (0.56, 2.04) 5 2.12 (0.74, 5.79) 2.26 (0.71, 6.83) 35–44 1.0 1.0 Child’s sex 45+ 0.31 (0.02, 1.81) 0.40 (0.02, 2.40) Male 1.0 1.0 Parent/guardian sex Female 0.89 (0.51, 1.54) 1.04 (0.57, 1.91) Male 1.0 Pain in the teeth, mouth or jaw Female 1.66 (0.68, 4.67) 1.34 (0.53, 3.85) No 1.0 —— Parent/primary caregiver highest level of education Yes 0.76 (0.31, 1.71) Primary or below 1.92 (0.71, 5.07) Difficulty drinking hot or cold drinks Secondary 1.38 (0.74, 2.60) No 1.0 1.0 Third level 1.0 —— Yes 12.55 (3.13, 83.85) 7.14 (1.36, 55.13) Other/unknown 0.54 (0.08, 2.25) Difficulty eating some foods Parent/guardian visits to dentist No 1.0 1.0 Never 1.49 (0.70, 3.07) Yes 10.51 (3.16, 47.63) 8.29 (2.00, 43.49) 1–2 per year 1.0 —— Difficulty pronouncing some words Only when in pain 1.33 (0.59, 2.89) No 1.0 —— Other 1.11 (0.43, 2.67) Yes 3.42 (0.74, 17.76) Felt upset Missed preschool No 1.0 —— No 1.0 —— Yes 6.13 (1.92, 23.30) Yes 10.38 (1.5, 205.20) Felt guilty Trouble sleeping No 1.0 1.0 No 1.0 —— Yes 5.52 (2.28, 14.38) 3.50 (1.32, 9.60) Yes 9.76 (2.21, 64.62) Taken time off work Note: ‘Yes’ denotes occasionally/often/very often; ‘No’ denotes never/hardly ever No 1.0 1.0 Model adjusted for other factors in the model Yes 9.29 (2.74, 42.45) 7.27 (1.76, 41.11) As confidence intervals are large, caution must be exercised when interpreting results Had a financial impact on your family No 1.0 —— In Model 1: child related factors associated with Yes 13.03 (2.05, 252.15) dmft > 0, statistically significant factors include child’s Type of pre-school age, difficulty drinking hot or cold drinks, difficulty eat- Private school 1.0 —— ing some foods, missing preschool and trouble sleeping Government 0.98 (0.54, 1.78) (Table 4). Adjusting for the effects of other factors the school odds for a child aged 4 years were greater for having Note: ‘Yes’ denotes occasionally/often/very often; ‘No’ denotes never/hardly ever dmft > 0 (in comparison to dmft = 0) than the odds for a Model adjusted for other factors in the model As confidence intervals are large, caution must be exercised when interpreting child aged 3 years (OR 3.61; 95% CI (1.76, 6.83)). The results odds for children who had difficulty drinking hot or cold drinks were greater for those with dmft > 0 than the odds for children who had no such difficulty (OR 7.14; time off work (Table 5). Adjusting for the effects of other 95% CI (1.36, 55.13)). Similarly, the odds of a dmft >0 factors, the odds of parents/primary caregivers who felt were increased for children who have difficulty eating guilty were greater for those with a child with a dmft > 0 than the odds for children who have no difficulty eating in comparison to parents/primary caregivers who did (OR 8.29; 95% CI (2.00, 43.49)). not feel guilty (OR 3.50; 95% CI (1.32, 9.60)). Similarly, In Model 2: family perspectives associated with child’s the odds of parents/primary caregivers who had to take dmft > 0, statistically significant factors include parent/ time off work were greater with a child with dmft > 0, in primary caregiver feeling upset, guilty and having to take comparison to parents/primary caregivers who did not Naidu et al. BMC Oral Health (2016) 16:128 Page 7 of 9 Table 6 Factors associated with ECOHIS > 0 reported from the US [3]. As the majority of respon- dents had no impacts this may have resulted in a high Crude OR 95% CI Adjusted OR 95% CI ‘floor effect’. This can reduce the ability of the instru- Parent/guardian age ment to measure the interaction between the items in < 25 years 1.27 (0.43, 1.08) 1.59 (0.46, 5.44) the child and family domains and OHRQoL. Unlike 25–44 1.12 (0.41, 3.90) 1.11 (0.60, 2.07) several other instruments, for the ECHOHIS the parent 45–64 1.0 1.0 is asked to consider lifetime experience rather than the 65+ 0.41 (0.05, 1.85) 0.55 (0.23, 1.28) previous three months, to take account of lower disease Parent/guardian sex levels in some populations. The most frequent child impacts in this sample were Male 1.0 1.0 similar to ECOHIS data from Australia, Canada, Iran, Female 0.75 (0.35, 1.66) 0.55 (0.23, 1.28) Hong Kong, Brazil and Turkey, which included English Parent/guardian highest level of education and non-English-speaking populations in developed and Primary or below 1.11 (0.44, 2.81) developing countries [11–16]. These main impacts were: Secondary 0.82 (0.47, 1.43) pain in the mouth, teeth or jaw, difficulty with eating Third level 1.0 —— some foods, drinking hot or cold beverages and being irritable or frustrated. This suggests that OHRQoL Other/unknown 0.54 (0.14, 1.79) impacts due to ECC are consistent across developed and Parent/guardian visits to dentist developing countries. In a multiethnic population in a Never 0.68 (0.48, 0.95) developing country, Malaysia, the main impacts were 1–2 per year 1.0 —— again similar, however, the prevalence of these impacts Only when in pain 0.90 (0.42, 1.88) was much higher than in the present study [19]. This Other 1.70 (0.75, 3.89) may have been due to the slightly older age groups (4–6 years) and differences in social/cultural backgrounds. Child’s age These main impacts are consistent with symptoms from 3 1.0 1.0 untreated dental caries in children and confirms the 4 1.63 (0.93, 2.88) 1.30 (0.70, 2.43) negative effect on quality of life that ECC can have in 5 1.37 (0.55, 3.35) 1.04 (0.38, 2.76) preschool children. Findings in the family section were Child’s sex also consistent with several other countries, where ECO- Male 1.0 1.0 HIS has been used, with feeling guilty or upset being the most common impacts (4,11,12,14,15,16). Interestingly, Female 0.79 (0.47, 1.31) 0.83 (0.48, 1.47) data from a Turkish study [16] differed from the present Child’s DMFT study findings, with most frequent family impacts being 0 1.0 1.0 financial and having to take time off work, although this 1–3 2.68 (1.30, 5.64) 2.55 (1.19, 5.50) study was among a sample of older children with a > 4 8.58 (3.71, 22.45) 8.70 (3.54, 23.13) higher severity of caries experience. Model adjusted for other factors in the model The issue of feelings of guilt about the oral health of their preschool aged child was explored by Carvalho have to take time off work (OR 7.27; 95% CI (1.76, et al. who defined guilt as “a feeling that occurs when 41.11)). one assesses one’sspecificactionasafailureorwhen In Model 3: factors associated with ECOHIS > 0, a the particular action has led to failure” [20]. The authors child’s dmft value were found to be statistically signifi- suggest that these feelings may be due to some parents cantly related (Table 6). Adjusting for parental age/sex having knowledge about prevention and dental care but and child’s age and sex, model results indicate that the are unable to act on it, effectively, with respect to their odds of parents/primary caregivers having ECOHIS >0 child. (in comparison to ECOHIS = 0), was increased when a In the present study the odds of having negative OHR- child’s dmft was in the range 1–3 (OR 2.68; 95% CI QoL impacts for both the child and family were signifi- (1.30, 5.64) or dmft > 4 (OR 8.58; 95% CI (3.71, 22.45)) cantly associated with having visible caries experience. compared with those whose child had a dmft = 0. These odds increased with greater caries severity, indi- cating that families of children with untreated dental Discussion caries suffer the majority of the disease burden and Overall, the frequency of oral health impacts for this should be prioritized for treatment and preventive care. Trinidadian sample was low for both Child and Family These findings highlight the need to develop oral sections of the instrument, which is similar to data health promotion strategies that support parents and Naidu et al. BMC Oral Health (2016) 16:128 Page 8 of 9 caregivers and that go beyond merely increasing oral information from dental health professionals, family health knowledge. Changing behavior requires approaches physicians, pediatricians, community nurses, and pre- that impart practical advice and enhance motivation, as school staff. well as developing coping skills, enabling families to over- Abbreviations come barriers to preventive dental care. In this regard, AAPD: American Academy of Paediatric Dentistry; ECC: Early childhood caries; patient-centered counselling approaches and brief coun- ECOHIS: Early Childhood Oral Health Impact Scale; OHRQoL: Oral health related quality of life selling techniques such as motivational interviewing (MI) have shown promise in relation to improving preschool Acknowledgements children’s oral health [21, 22] and found to be an accept- The authors would like to acknowledge the late Dr. Alan Kelly (Trinity College Dublin), Dr. Donald Simeon and Miss Shelly Hunte for statistical advice. able as part of health promotion for families of preschool children in Trinidad [23]. Funding This research was supported by a grant from the University of the West Indies Campus Research and Publication Fund. Limitations of the study Availability of data and materials 1. This was a cross-sectional study from one education Data used in this study were part of a doctoral thesis submission and not available for public sharing. district and therefore limits the generalizability of the findings to the rest of Trinidad. However, the Authors’ contributions Caroni district does have a mixed of urban and rural RN and JN contributed to the design and conduct of this research. EDS contributed to the data analyses. All authors contributed to the writing of population and a varied SES profile, similar to the the manuscript. All authors read and approved the final manuscript. national demographic profile. 2. Sampling was not stratified, which may have Competing interests The authors declare that they have no competing interests. influenced the findings and masked differences by SES. Also, not all children under 5-years of age Consent for publication attend preschool and some of those children are Not applicable. likely to have had worse oral health than those in Ethics approval and consent to participate the sampling frame. Ethical approval for this research was obtained from the University of the 3. The findings for OHRQoL of preschool children are West Indies Campus Research Ethics Committee. Written positive consent was requested from parents and caregivers for the oral examinations. limited due to the use of proxy reports. Proxy reports on children’s oral health may underestimate Author details the severity of oral health impacts. School of Dentistry, The University of the West Indies, Saint Augustine, Trinidad and Tobago. School of Dental Sciences, Trinity College Dublin, 4. Re-examination of children for intra examiner Dublin 2, Ireland. reliability took place on the same day, however, to avoid the bias due to memory of the initial Received: 8 July 2016 Accepted: 30 November 2016 examination, ideally, these should have been done on a return visit to the preschools. References 5. Exclusion of very large preschools may have limited 1. American Academy of Pediatric Dentistry and American Academy of Pediatrics. Policy on early childhood caries (ECC): classifications, consequences and the representativeness of the sample. preventive strategies. Reference Manual. (Revised 2014): http://www.aapd.org/ media/policies_guidelines/p_eccclassifications.pdf. Accessed Sept 2016. Conclusion 2. Abanto J, Carvalho TS, Mendes FM, Wanderley MT, Bonecker M, Raggio DP. Impact of oral disease and disorders on oral health-related quality of life of Although overall oral health impacts were low in this preschool children. Community Dent Oral Epidemiol. 2011;139:105–14. sample of preschool children, OHRQoL was found to be 3. Pahel BT, Rozier RG, Slade GD. Parental perceptions of children’s oral health: related to ECC. More impacts were found in children The Early Childhood Oral Health Impact Scale (ECOHIS). Health Qual Life Outcomes. 2007;5:6. http://www.hqlo.com/content/pdf/1477-7525-5-6.pdf. with greater severity of visible caries experience. The 4. Sheiham A. Dental caries affects body weight, growth and quality of life in burden of dental disease and its impacts appears preschool children. Br Dent J. 2006;20:625–6. concentrated in a minority of young children, suggesting 5. Gift H, Reisine S, Larch D. The social impact of dental problems and visits. Am J Public Health. 1992;82:1163–8. the need for strategies to address oral health in early 6. O’ Mullane D, Parnell C. Early childhood caries: a complex problem requiring childhood in Trinidad. Measuring the effect on OHR- a complex solution. Community Dent Health. 2011;28:254. QoL in families with young children may enable 7. Seow W. Environmental, maternal and child factors which contribute to early childhood caries: a unifying conceptual model. Int J Paediatr Dent. prioritization and evaluation of interventions. Such in- 2012;2:157–68. terventions should support families in implementing 8. Vignarajah S, Williams GA. Prevalence of dental caries and enamel defects in positive dental care practices for their young children the primary dentition of Antiguan preschool children aged 3–4 years including an assessment of their habits. Community Dent Health. and include caries risk assessment, early establishment 1992;9:349–60. of the dental home and access to regular fluoride therapy 9. Adewakun A, Beltran-Aguilar ED. Early childhood caries in Anguilla, British for children at high risk for ECC, along with consistent West Indies. Am J Gen Dent. 2003;5:42–7. Naidu et al. BMC Oral Health (2016) 16:128 Page 9 of 9 10. Naidu R, Nunn J, Kelly A. Socio-behavioral factors and early childhood caries: a cross-sectional study of preschool children in central Trinidad. BMC Oral Health. 2013;13:30. http://www.biomedcentral.com/1472-6831/13/30. 11. Arrow P, Klobas E. Evaluation of the Early Childhood Oral Health Impact Scale in an Australian preschool population. Aust Dent J. 2015;60:375–81. 12. Li S, Veronneau J, Allison PJ. Validation of a French language version of the early childhood oral health impact scale (ECOHIS). Health Qual Life Outcomes. 2014;6:9. http://www.hqlo.com/content/pdf/1477-7525-6-9.pdf. 13. Jabbarifar S, Ahmady N, Sahafian SA, Samei F, Soheillipour S. Association of parental stress and early childhood caries. Dent Res J. 2009;6:65–70. 14. Wong H, McGrath CPJ, King NM, Lo ECM. Oral health-related quality of life in Hong Kong preschool children. Caries Res. 2011;45:370–6. 15. Scarpelli A, Oliveira BH, Tesch FC, Leao AT, Pordeus Paiva SM. Psychometric properties of the Brazilian version of the Early Childhood Oral Health Impact Scale (B-ECOHIS). BMC Oral Health. 2011;11:19. http://www.biomedcentral. com/content/pdf/1472-6831-11-19.pdf. 16. Peker K, Uysal O, Bermek G. Cross-cultural adaptation and preliminary validation of the Turkish version of the Early Childhood Oral Health Impact Scale among 5–6 year-old children. Health Qual Life Outcomes. 2011;9:118. http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3310831/pdf/1477-7525-9- 118.pdf. 17. World Health Organisation. Oral health surveys. Basic methods. Geneva: WHO; 1997. 18. R software. https://cran.r-project.org/. Accessed Sept 2016. 19. Hashim AN, Tuysof ZY, Esa R. The Malay version of the Oral Health Impact Scale (Malay-ECOHIS) assessing validity and reliability. Health Qual Life Outcomes. 2015;13:190. http://www.ncbi.nlm.nih.gov/pmc/articles/ PMC4660630/pdf/12955_2015_Article_386.pdf. 20. Carvalho TS, Abanto J, Mendes FM, Raggio DP, Bonecker M. 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Oral health-related quality of life and early childhood caries among preschool children in Trinidad

Naidu, Rahul; Nunn, June; Donnelly-Swift, Erica
BMC Oral Health , Volume 16 (1) – Dec 7, 2016
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Springer Journals
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Copyright © 2016 by The Author(s).
Subject
Dentistry; Dentistry; Oral and Maxillofacial Surgery
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1472-6831
DOI
10.1186/s12903-016-0324-7
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27923355
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Abstract

Background: Early childhood caries (ECC) is a public health problem in developed and developing countries. The purpose of this study was to describe the relationship between oral health-related quality of life (OHRQoL) and ECC among preschool children in a Caribbean population. Method: Parents/primary caregivers of children attending nine, randomly selected preschools in central Trinidad were invited to complete an oral health questionnaire and have their child undertake an oral examination. The questionnaire included the Early Childhood Oral Health Impact Scale (ECOHIS). Visible caries experience was assessed using WHO criteria. Logistic regression models were used to determine the factors associated with OHRQoL and ECC. Results: Three hundred nine parents/caregivers participated in the study (age-range 25–44 years) and 251 children (mean age 3.7 years) completed oral examinations. Adjusting for other factors, the odds for a child aged 4 years of having dental caries were greater than the odds for a child aged 3 years (OR 3.61; 95% CI (1.76, 6.83). The odds for children having difficulty drinking hot or cold drinks were greater for those with dental caries than the odds for children who have no such difficulty. Similarly, the odds for children who had difficulty eating were greater for those with dental caries than the odds ratios for children who had no difficulty eating (OR 8.29; 95% CI (2.00, 43.49). Adjusting for the effects of other factors, the odds of parents/caregivers feeling guilty were greater if their child had experienced dental caries in comparison to parents/caregivers whose child did not have dental caries (OR 3.50; 95% CI (1.32, 9.60). Adjusting for other factors, the odds of parents/primary caregivers having poor quality of life was increased when they had a child with a dmft in the range 1–3 (OR 2.68; 95% CI (1.30, 5.64) dmft > 4 (OR 8.58; 95%CI (3.71, 22.45), in comparison to those whose child had a dmft = 0. Conclusion: In this sample of preschool children OHRQoL was associated with ECC. More negative impacts were found in children with a greater severity of visible caries experience. This suggests the need for strategies to prevent and manage ECC in this Caribbean population. Keywords: Early childhood caries, Quality of life, Preschool children, Caribbean Background any sign of smooth-surface caries is indicative of severe Early Childhood Caries (ECC) has been defined by the early childhood caries (S-ECC) [1]. American Academy of Pediatric Dentistry as ‘the presence Beyond the immediate distress caused by toothache, of one or more decayed, missing due to caries, or filled early childhood caries (ECC) can also have longer term tooth surfaces in any primary teeth in children under 6 negative, health outcomes [2, 3]. Untreated decay in years of age [1]. In children younger than 3 years of age, infancy and early childhood is believed to affect weight gain and overall growth and development [4]. Along with these patho-physiological effects, ECC can impact * Correspondence: [email protected] on oral health related quality of life (OHRQoL) [2, 3]. As School of Dentistry, The University of the West Indies, Saint Augustine, parents and caregivers have the main responsibility for Trinidad and Tobago Full list of author information is available at the end of the article © The Author(s). 2016 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. Naidu et al. BMC Oral Health (2016) 16:128 Page 2 of 9 their preschool-aged children, ECC can also affect them preschools of similar sizes and enable data collection by indirectly, for example, work-loss and financial impact a single examiner. Stratification was not employed. duetohavingtostayathometotake careof the Ethical approval for the study was obtained from The child [5]. ECC is therefore recognized as a public University of the West Indies, Faculty of Medical health problem due to its high prevalence in some Sciences Research Ethics Committee. Permission for the populations and the potential for negative health im- selected preschool’s inclusion in the study was obtained pacts if left untreated [6, 7]. from individual head teachers and written positive The few studies that have been undertaken in the consent was requested from parents and caregivers for English-speaking Caribbean suggest that caries preva- the oral examinations. Self-administered oral health ques- lence among infants and preschool children in the tionnaires were provided to participating preschools. region is high [8, 9]. In central Trinidad, the prevalence These questionnaires were then given to all parents and of ECC among 251 preschool children was reported as caregivers by the school administration, along with a 29.1% with the majority of this being untreated, decayed consent form. teeth and 12% of children were in need of urgent care or OHRQoL was measured using the Early Childhood referral [10]. Affordability and access to dental care for Oral Health Impact Scale (ECOHIS) [3], included as people from lower socioeconomic groups and those part of the oral health questionnaire. The ECOHIS is living in rural locations is a challenge in Trinidad and a short, condition-specific tool, to be completed by Tobago as most of the county’s registered dentists work the child’s parent or primary caregiver. It has been in private practices, generally clustered in urban centers. validated in the English language and translated Although there are international reports on OHRQoL versions are reported to have good psychometric of preschool children [11–16], nothing is known about properties [3]. The ECOHIS consists of questions re- the effect of ECC on OHRQoL among preschool children lating to quality of life domains for both the child in the Caribbean. and the family. These domains include: symptoms, Understanding the impact of dental caries in young function, psychological effects, self-image, parent children and their families can guide the development of distress and family function [3]. Responses are based treatment and preventive protocols as part of dental on the scale: Never, Hardly ever, Occasionally, Often, Very service planning. often, Don’t know. Scores for the instrument are calculated The aim of this study was to describe the relationship from the sum of responses for the child (0–36) and family between OHRQoL and ECC among preschool children sections (0–16) and reported as mean impacts per item/ in Trinidad. section (maximum overall score of 52). Higher mean ECOHIS score represents worse OHRQoL. Method The ECOHIS instrument was piloted among 30 par- A cross-sectional oral health survey of preschool children ents and caregivers of young children attending a dental was undertaken in the Caroni region of central Trinidad. hospital clinic in Trinidad. The instrument was found to The accessible population were children aged 3 to 5 years have acceptable face and content validity and thus did of age, attending preschools in the Caroni Education not require any modification. The ‘don’tknow’ response District. Based on the list of registered preschools, there were treated as ‘missing’ for the analyses. were 27 government/government-assisted and 57 non- Dental examinations were undertaken by a single, government preschools in the district at the time of the trained and calibrated dentist (RN) using WHO criteria survey, with an enrolled population of approximately 2000 [17]. Training and calibration was achieved by use of children. Previous data from Anguilla [9] (which estimated clinical slides on CD ROM, representing all categories of prevalence at 30%) was used to determine that 340 caries to be assessed and recorded. This was done under children were required to assess caries prevalence within the supervision of a dental epidemiologist (JN). Exami- the preschool population in the district. This figure nations took place in classrooms using natural light, accounted for 6% precision and 20% non-response rate. with the child in a seated position on a small chair/ Sampling consisted of cluster sampling within the bench with the examiner positioned behind. Teeth were Caroni Education District. A total of ten schools were assessed visually with the use of a disposable mouth selected by systematic random sampling from the school mirror, with the examiner wearing disposable gloves and lists (three government/assisted schools and seven non- facemask. New gloves and a mouth mirror were used for government preschools). Each cluster consisted of all each child. Teeth were not air dried but soft debris on registered children within the preschool. Each preschool tooth surfaces was removed with a cotton roll or gauze was assumed to have an average of 30 registered chil- square. dren. Very small schools (<15) and very large schools Examiner reliability was assessed by re-examination of (>60) were excluded, in order to enable inclusion of children at one preschool (25 children). These re- Naidu et al. BMC Oral Health (2016) 16:128 Page 3 of 9 examinations took place on the same day as data collec- Results tion. The Kappa statistic for intra-examiner reliability From an enrolment of 340 children, 314 parents gave was 0.9. Data collection was undertaken over a three- consent for the oral examination (91% response rate). Of month period. these children, 36 (11.5%) were absent on the day and In the field, oral examination data were entered onto a 27 (8.6%) refused examination. Three hundred and nine record sheet by a research assistant. This information parents completed the questionnaire (Table 1). The was subsequently transferred to a computer database mean age of the parents and primary caregivers was not (SPSS v 16) for storage and processing. Data were determined as the questionnaire only recorded respondent cleaned and checked for transcription errors before age-range. Among these 309 respondents, 90% of parents/ processing using SPSS version 16 for Windows and primary caregivers were in the age range 25–44 years. STATA version 10. Parent/primary caregiver ethnicity was 74.4% Indian, Statistical analysis Logistic regression models were adopted to determine Table 1 Socio-demographic information for all parents and the family and child related factors associated with dmft caregivers (N = 309) and ECOHIS. Specifically, models examining factors re- n Percent lating to dmft were used to examine the odds of children Age group having a dmft > 0 compared to the odds of children with 18–24 17 5.5 a dmft = 0. Similarly, the odds of a parent/primary care- 25–34 183 59.2 giver having an ECOHIS score >0 was compared to the 35–44 95 30.7 odds of parents/primary caregivers with an ECOHIS score = 0, taking sociodemographic factors into account. 45–54 8 2.6 Child and/or parent-primary caregiver characteristics 55–64 2 0.7 were included as fixed effects in the models and a 65+ 1 0.3 random intercept was included to account for cluster Missing 3 1.0 variation (i.e. variation within preschools). Akaike’sin- Ethnic group formation criteria and likelihood ratio tests were used African 35 11.3 to evaluate goodness of fit. In addition to variables retained in the final model, all models were adjusted Indian 230 74.4 for age and sex. Model sensitivity and specificity were Mixed 41 13.3 examined using receiver operating characteristic White 1 0.3 curves and area under the curve (AUC). If a model Other 2 0.7 achieves perfect sensitivity and specificity, then the Occupation AUC would have a value of 1. If the AUC has a value Professional 11 3.6 of 0.5 then the model achieves poor sensitivity and specificity. Despite estimation of AUC, the models de- Managerial/lower professional 48 15.5 veloped for this research are for descriptive purposes, Non-manual 44 14.2 they are not intended for prediction. Generalised Manual -skilled 107 34.6 variance inflation factors (GVIF) and adjusted GVIF Manual- semi-skilled 6 1.9 were used to determine the presence of multicolli- Manual –unskilled 43 13.9 nearity. Model results are displayed in terms of odds Housewife/unemployed 15 4.9 ratios (ORs) and corresponding 95% confidence inter- val (CI). ORs have a range from 0 to infinity. An OR Retired/old-age pensioner 7 2.3 equal to one, denotes that there is no difference in Missing 28 9.1 odds whereas an OR greater than 1 indicates, for in- Education stance, that the ratio of those with a dmft > 0 versus None 1 0.3 a dmft = 0 in the selected group is greater than the Primary 29 9.4 baseline group. If there is no evidence to suggest that Secondary 255 50.2 the ratio of those with dmft > 0 (versus dmft = 0) for the selected group are different from the baseline Technical college 54 17.5 group, then the 95% CI for the OR will contain 1 in University 49 15.9 the interval. Other 15 4.9 Statistical analysis was performed using statistical Missing 6 1.9 software R (version 3.2.3) [18]. Naidu et al. BMC Oral Health (2016) 16:128 Page 4 of 9 Table 2 Socio-demographic information for parents/caregivers whose child completed the oral health assessment (N = 251) ECOHIS = 0 ECOHIS > 0 dmft = 0 dmft > 0 Count % Count % Count % Count % Parent/primary caregiver characteristics Age < 25 years 8 3.19 7 2.79 12 4.78 3 1.20 25–34 83 33.07 64 25.50 102 40.64 45 17.93 35–44 46 18.33 32 12.75 54 21.51 24 9.56 45+ 7 2.79 2 0.80 8 3.19 1 0.40 Unknown 2 0.80 0 0.00 2 0.80 0 0.00 Sex Male 16 6.37 14 5.58 24 9.56 6 2.39 Female 130 51.79 91 36.25 154 61.35 67 26.69 Education Primary or lower 13 5.18 11 4.38 15 5.98 9 3.59 Secondary 47 18.73 38 15.14 85 33.86 40 15.94 Third level 74 29.48 51 20.32 64 25.50 21 8.37 Other 9 3.59 4 1.59 11 4.38 2 0.80 Unknown 3 1.20 1 0.40 3 1.20 1 0.40 Visits to the dentist Never 27 10.76 19 7.57 30 11.95 16 6.37 1–2 per year 82 32.67 55 21.91 101 40.24 36 14.34 Only when in pain 23 9.16 14 5.58 25 9.96 12 4.78 Other 14 5.58 16 6.37 22 8.76 8 3.19 Unknown 0 0.00 1 0.40 0 0.00 1 0.40 Child characteristics Age (years) 3 56 22.31 29 11.55 71 28.29 14 5.58 4 74 29.48 64 25.50 87 34.66 51 20.32 5 16 6.37 12 4.78 20 7.97 8 3.19 Sex Male 70 27.89 56 22.31 89 35.46 37 14.74 Female 76 30.28 49 19.52 89 35.46 36 14.34 DMFT 0 122 48.61 56 22.31 1–3 16 6.37 20 7.97 > 4 8 3.19 29 11.55 11.3% African, 13.3% mixed and 1% white or other Examination of responses relating to the child’s quality (Table 1). of life indicated that approximately 10.4% (32/309) The ECOHIS showed good internal consistency with a reported that their child experienced pain in the teeth, Cronbach alpha reliability coefficient of 0.94. For the mouth or jaw. child and family sections Cronbach alpha was 0.92 and Approximately 5.2% (16/309) and 4.2% (13/309) re- 0.85, respectively. ported that their child experienced difficulty eating some Overall, quality of life impacts were low, with median foods or difficulty drinking hot or cold drinks. score being 0. Mean impacts scores for the whole instru- Examination of responses relating to family function ment were 2.29 (sd 5.52) and for the child and family indicated that approximately 10% (31/309) of parents/ sections 1.09 (sd 3.62) and 0.80 (sd 2.16), respectively. primary caregivers reported that they felt guilty, 5.2% Naidu et al. BMC Oral Health (2016) 16:128 Page 5 of 9 (16/309) had been upset and 4.9% (15/309) reported that had a value <0.0001. In the principle of parsimony, they had taken time off work due to their child’s oral models with lowest AIC were utilised. With reference to health problems. the model examining family perspectives associated with Despite 309 parent/primary caregivers completing the dmft > 0, the AIC for the model, including random ef- questionnaire, approximately 18% (58/309) of children fects, was 284.14 and was 283.69 for the simplified did not complete the oral examination, thus a total of model. Similarly, the model examining child related 251 children completed the oral examination. Of these factors associated with dmft > 0, the AIC for the model children, 50.2% were male, with an age range of 3 to including random effects was 274.87 and was 273.09 for 5 years-old and mean age of 3.7 years (sd 0.67). Full the less complex model. Examining factors associated with results for visible caries experience have been reported ECOHIS > 0 resulted in the model including random ef- previously [10]. Socio-demographic characteristic for fect having an AIC of 318.19 and the simplified model parents/primary caregivers, together with information having an AIC of 316.19. The factors included in all on ECOHIS and dmft for those children who completed models were free from multicollinearity as all adjusted the oral health assessment, are shown in Table 2. GVIF values had values less than 2. Factors that could not Table 3 shows the frequency of oral health impacts for be included for statistical analysis were ‘child avoided talk- children with some caries experience (dmft > 0) and for ing’ and ‘child being irritable or frustrated’, as these factors those with no caries experience (dmft = 0) for the child had excessively high adjusted GVIF values. The factor and family levels, respectively. ‘child smiling’ was also omitted from the analysis due to Regression analysis was performed on the complete zero observations for this factor with dmft = 0. Crude and dataset excluding all missing and unknown observations. adjusted ORs for children with dmft > 0 compared to As previously stated, initially, there were 340 children to those with dmft = 0 can be seen in Tables 4 and 5. be involved in the study. The final sample was reduced Table 6 shows the crude and adjusted ORs for to 245 (after excluding 7.6% (26/340) of those who did parents/primary caregivers with ECOHIS > 0 compared not give consent and missing observations (69/340). This to those with ECOHIS = 0. Model evaluations indicate accounted for approximately 28% (95/340) not being that the three models are adequate in terms of sensitiv- available for statistical analysis. Thus as a result of this ity, with AUC being estimated as 0.68, 0.64 and 0.74, reduced data set, a number of categories had low respectively. However, as previously stated, these models numbers. Logistic models without a random effect were were not developed for predictive purposes and caution adequate in all three models as the estimated standard must be exercised in model interpretation due to wide deviation for unexplained variation within each cluster confidence intervals. Table 3 Oral health impacts for children with no visible caries dmft = 0 and some visible caries dmft > 0 Never/hardly ever Occasionally/often/very often Don’t know/NA dmft = 0 dmft > 0 dmft = 0 dmft > 0 dmft = 0 dmft > 0 n% n % n % n % n % n % Child impacts Pain in the teeth, mouth or jaw 170 76.9 51 23.1 6 22.2 21 77.8 2 66.6 1 33.3 Difficulty drink hot or cold drinks 174 73.7 62 26.3 2 18.2 9 81.8 2 50.0 2 50.0 Difficulty eating some foods 175 74.5 60 25.5 3 20.0 12 80.0 0 0 1 100 Difficulty pronouncing some words 175 72.6 66 27.4 3 42.9 4 57.1 0 0 3 100 Missed preschool 176 72.1 68 27.9 1 20.0 4 80.0 1 50.0 1 50.0 Trouble sleeping 175 72.9 65 26.4 2 22.2 7 77.8 1 50.0 1 50.0 Been irritable or frustrated 177 74.7 60 25.3 1 8.3 11 91.7 0 0 2 100 Avoided smiling or laughing 176 73.3 64 26.7 1 14.3 6 85.7 1 25.0 3 75.0 Avoided talking 176 72.1 68 27.9 1 20.0 4 80.0 1 50.0 1 50.0 Family impacts Felt upset 173 73.3 63 26.7 4 30.8 9 69.2 1 50.0 1 50.0 Felt guilty 169 75.1 56 24.9 8 33.3 16 66.7 1 50.0 1 50.0 Taken time off work 175 74.5 60 25.5 3 21.4 11 78.6 0 0 1 100 Had a financial impact on your family 177 72.8 66 27.8 1 14.3 6 85.7 0 0 1 100 309 parents/caregiver observations were recorded, of whom 187 had children with dmft = 0, 73 dmft > 0 and 58 unknown dmft Naidu et al. BMC Oral Health (2016) 16:128 Page 6 of 9 Table 4 Child factors associated with DMFT >0 Table 5 Family factors associated with child’s DMFT > 0 Crude OR 95% CI Adjusted OR 95% CI Crude OR 95% CI Adjusted OR 95% CI Child’s age Parent/primary caregiver age 3 1.0 1.0 < 25 years 0.61 (0.13, 2.16) 0.35 (0.05, 1.53) 4 3.08 (1.59, 6.34) 3.61 (1.76, 7.95) 25–34 1.12 (0.61, 2.07) 1.06 (0.56, 2.04) 5 2.12 (0.74, 5.79) 2.26 (0.71, 6.83) 35–44 1.0 1.0 Child’s sex 45+ 0.31 (0.02, 1.81) 0.40 (0.02, 2.40) Male 1.0 1.0 Parent/guardian sex Female 0.89 (0.51, 1.54) 1.04 (0.57, 1.91) Male 1.0 Pain in the teeth, mouth or jaw Female 1.66 (0.68, 4.67) 1.34 (0.53, 3.85) No 1.0 —— Parent/primary caregiver highest level of education Yes 0.76 (0.31, 1.71) Primary or below 1.92 (0.71, 5.07) Difficulty drinking hot or cold drinks Secondary 1.38 (0.74, 2.60) No 1.0 1.0 Third level 1.0 —— Yes 12.55 (3.13, 83.85) 7.14 (1.36, 55.13) Other/unknown 0.54 (0.08, 2.25) Difficulty eating some foods Parent/guardian visits to dentist No 1.0 1.0 Never 1.49 (0.70, 3.07) Yes 10.51 (3.16, 47.63) 8.29 (2.00, 43.49) 1–2 per year 1.0 —— Difficulty pronouncing some words Only when in pain 1.33 (0.59, 2.89) No 1.0 —— Other 1.11 (0.43, 2.67) Yes 3.42 (0.74, 17.76) Felt upset Missed preschool No 1.0 —— No 1.0 —— Yes 6.13 (1.92, 23.30) Yes 10.38 (1.5, 205.20) Felt guilty Trouble sleeping No 1.0 1.0 No 1.0 —— Yes 5.52 (2.28, 14.38) 3.50 (1.32, 9.60) Yes 9.76 (2.21, 64.62) Taken time off work Note: ‘Yes’ denotes occasionally/often/very often; ‘No’ denotes never/hardly ever No 1.0 1.0 Model adjusted for other factors in the model Yes 9.29 (2.74, 42.45) 7.27 (1.76, 41.11) As confidence intervals are large, caution must be exercised when interpreting results Had a financial impact on your family No 1.0 —— In Model 1: child related factors associated with Yes 13.03 (2.05, 252.15) dmft > 0, statistically significant factors include child’s Type of pre-school age, difficulty drinking hot or cold drinks, difficulty eat- Private school 1.0 —— ing some foods, missing preschool and trouble sleeping Government 0.98 (0.54, 1.78) (Table 4). Adjusting for the effects of other factors the school odds for a child aged 4 years were greater for having Note: ‘Yes’ denotes occasionally/often/very often; ‘No’ denotes never/hardly ever dmft > 0 (in comparison to dmft = 0) than the odds for a Model adjusted for other factors in the model As confidence intervals are large, caution must be exercised when interpreting child aged 3 years (OR 3.61; 95% CI (1.76, 6.83)). The results odds for children who had difficulty drinking hot or cold drinks were greater for those with dmft > 0 than the odds for children who had no such difficulty (OR 7.14; time off work (Table 5). Adjusting for the effects of other 95% CI (1.36, 55.13)). Similarly, the odds of a dmft >0 factors, the odds of parents/primary caregivers who felt were increased for children who have difficulty eating guilty were greater for those with a child with a dmft > 0 than the odds for children who have no difficulty eating in comparison to parents/primary caregivers who did (OR 8.29; 95% CI (2.00, 43.49)). not feel guilty (OR 3.50; 95% CI (1.32, 9.60)). Similarly, In Model 2: family perspectives associated with child’s the odds of parents/primary caregivers who had to take dmft > 0, statistically significant factors include parent/ time off work were greater with a child with dmft > 0, in primary caregiver feeling upset, guilty and having to take comparison to parents/primary caregivers who did not Naidu et al. BMC Oral Health (2016) 16:128 Page 7 of 9 Table 6 Factors associated with ECOHIS > 0 reported from the US [3]. As the majority of respon- dents had no impacts this may have resulted in a high Crude OR 95% CI Adjusted OR 95% CI ‘floor effect’. This can reduce the ability of the instru- Parent/guardian age ment to measure the interaction between the items in < 25 years 1.27 (0.43, 1.08) 1.59 (0.46, 5.44) the child and family domains and OHRQoL. Unlike 25–44 1.12 (0.41, 3.90) 1.11 (0.60, 2.07) several other instruments, for the ECHOHIS the parent 45–64 1.0 1.0 is asked to consider lifetime experience rather than the 65+ 0.41 (0.05, 1.85) 0.55 (0.23, 1.28) previous three months, to take account of lower disease Parent/guardian sex levels in some populations. The most frequent child impacts in this sample were Male 1.0 1.0 similar to ECOHIS data from Australia, Canada, Iran, Female 0.75 (0.35, 1.66) 0.55 (0.23, 1.28) Hong Kong, Brazil and Turkey, which included English Parent/guardian highest level of education and non-English-speaking populations in developed and Primary or below 1.11 (0.44, 2.81) developing countries [11–16]. These main impacts were: Secondary 0.82 (0.47, 1.43) pain in the mouth, teeth or jaw, difficulty with eating Third level 1.0 —— some foods, drinking hot or cold beverages and being irritable or frustrated. This suggests that OHRQoL Other/unknown 0.54 (0.14, 1.79) impacts due to ECC are consistent across developed and Parent/guardian visits to dentist developing countries. In a multiethnic population in a Never 0.68 (0.48, 0.95) developing country, Malaysia, the main impacts were 1–2 per year 1.0 —— again similar, however, the prevalence of these impacts Only when in pain 0.90 (0.42, 1.88) was much higher than in the present study [19]. This Other 1.70 (0.75, 3.89) may have been due to the slightly older age groups (4–6 years) and differences in social/cultural backgrounds. Child’s age These main impacts are consistent with symptoms from 3 1.0 1.0 untreated dental caries in children and confirms the 4 1.63 (0.93, 2.88) 1.30 (0.70, 2.43) negative effect on quality of life that ECC can have in 5 1.37 (0.55, 3.35) 1.04 (0.38, 2.76) preschool children. Findings in the family section were Child’s sex also consistent with several other countries, where ECO- Male 1.0 1.0 HIS has been used, with feeling guilty or upset being the most common impacts (4,11,12,14,15,16). Interestingly, Female 0.79 (0.47, 1.31) 0.83 (0.48, 1.47) data from a Turkish study [16] differed from the present Child’s DMFT study findings, with most frequent family impacts being 0 1.0 1.0 financial and having to take time off work, although this 1–3 2.68 (1.30, 5.64) 2.55 (1.19, 5.50) study was among a sample of older children with a > 4 8.58 (3.71, 22.45) 8.70 (3.54, 23.13) higher severity of caries experience. Model adjusted for other factors in the model The issue of feelings of guilt about the oral health of their preschool aged child was explored by Carvalho have to take time off work (OR 7.27; 95% CI (1.76, et al. who defined guilt as “a feeling that occurs when 41.11)). one assesses one’sspecificactionasafailureorwhen In Model 3: factors associated with ECOHIS > 0, a the particular action has led to failure” [20]. The authors child’s dmft value were found to be statistically signifi- suggest that these feelings may be due to some parents cantly related (Table 6). Adjusting for parental age/sex having knowledge about prevention and dental care but and child’s age and sex, model results indicate that the are unable to act on it, effectively, with respect to their odds of parents/primary caregivers having ECOHIS >0 child. (in comparison to ECOHIS = 0), was increased when a In the present study the odds of having negative OHR- child’s dmft was in the range 1–3 (OR 2.68; 95% CI QoL impacts for both the child and family were signifi- (1.30, 5.64) or dmft > 4 (OR 8.58; 95% CI (3.71, 22.45)) cantly associated with having visible caries experience. compared with those whose child had a dmft = 0. These odds increased with greater caries severity, indi- cating that families of children with untreated dental Discussion caries suffer the majority of the disease burden and Overall, the frequency of oral health impacts for this should be prioritized for treatment and preventive care. Trinidadian sample was low for both Child and Family These findings highlight the need to develop oral sections of the instrument, which is similar to data health promotion strategies that support parents and Naidu et al. BMC Oral Health (2016) 16:128 Page 8 of 9 caregivers and that go beyond merely increasing oral information from dental health professionals, family health knowledge. Changing behavior requires approaches physicians, pediatricians, community nurses, and pre- that impart practical advice and enhance motivation, as school staff. well as developing coping skills, enabling families to over- Abbreviations come barriers to preventive dental care. In this regard, AAPD: American Academy of Paediatric Dentistry; ECC: Early childhood caries; patient-centered counselling approaches and brief coun- ECOHIS: Early Childhood Oral Health Impact Scale; OHRQoL: Oral health related quality of life selling techniques such as motivational interviewing (MI) have shown promise in relation to improving preschool Acknowledgements children’s oral health [21, 22] and found to be an accept- The authors would like to acknowledge the late Dr. Alan Kelly (Trinity College Dublin), Dr. Donald Simeon and Miss Shelly Hunte for statistical advice. able as part of health promotion for families of preschool children in Trinidad [23]. Funding This research was supported by a grant from the University of the West Indies Campus Research and Publication Fund. Limitations of the study Availability of data and materials 1. This was a cross-sectional study from one education Data used in this study were part of a doctoral thesis submission and not available for public sharing. district and therefore limits the generalizability of the findings to the rest of Trinidad. However, the Authors’ contributions Caroni district does have a mixed of urban and rural RN and JN contributed to the design and conduct of this research. EDS contributed to the data analyses. All authors contributed to the writing of population and a varied SES profile, similar to the the manuscript. All authors read and approved the final manuscript. national demographic profile. 2. Sampling was not stratified, which may have Competing interests The authors declare that they have no competing interests. influenced the findings and masked differences by SES. Also, not all children under 5-years of age Consent for publication attend preschool and some of those children are Not applicable. likely to have had worse oral health than those in Ethics approval and consent to participate the sampling frame. Ethical approval for this research was obtained from the University of the 3. The findings for OHRQoL of preschool children are West Indies Campus Research Ethics Committee. Written positive consent was requested from parents and caregivers for the oral examinations. limited due to the use of proxy reports. Proxy reports on children’s oral health may underestimate Author details the severity of oral health impacts. School of Dentistry, The University of the West Indies, Saint Augustine, Trinidad and Tobago. School of Dental Sciences, Trinity College Dublin, 4. 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BMC Oral Health – Springer Journals

Published: Dec 7, 2016

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