Longitudinal measurement invariance and explanatory IRT models for adolescents’ oral health-related quality of life

The participants in this study were secondary school students recruited for an observation survey to study the association between dental caries and adiposity status [14]. Baseline data were collected from January to April 2010 and they were followed up after 3 years in January to April 2013. The primary sampling unit was Hong Kong secondary schools and the sampling frame was the list of Hong Kong local secondary schools. 45 local secondary schools (about 10% of local secondary school) were randomly drawn. Within each secondary school, all students from S1 and S2 (equivalent to US grades 6 and 7) who were born in April 1997 and May 1997 were invited to participate in this study. The participants were ensured to be 12 and 15 years old respectively at baseline and follow-up. The study protocol was approved by Institutional Review Board of the University of Hong Kong/ Hospital Authority Hong Kong West Cluster (WU09–435) and written parental consent was obtained.

Participants were asked to complete a questionnaire in Chinese, consisted of both CPQ_11–14 RSF:8 and ISF:8, and questions concerning their global self-health ratings, demographic (place of birth and years of residency in Hong Kong) and oral health behaviors (snacking frequency between meals, brushing frequencies, use of fluoridated toothpaste, and previous participation of the School Dental Care Service (SDCS)). Parents were asked about the families’ social economic status (SES) (parents’ place of birth, employment status, family income, education level and whether they have lived in Hong Kong for 7 years or more). Participants and their parents completed the questionnaires in a self-administered manner.

In each item of CPQ_11–14, participants were asked “In the past 3 months, how often have you … (had/been)…because of your teeth/mouth?”. The five-point scale were: “Never” = 0; “Once/ twice” = 1; “Sometimes” = 2; “Often” = 3; “Every day/ almost every day”=4 [15]. The possible total score ranges of both CPQ_11–14 RSF:8 and ISF:8 is 0–32 (with a lower score indicates better OHRQoL). “Never” = 0 were imputed for the missing responses at baseline and follow-up (1.4% of all responses) because it was presumed that children not answering the items probably have not encountered the situation described. This imputing method was previously used to handle another OHRQoL questionnaire with a “Don’t know” option [3]. Respondents with more than 2 missing items were excluded in order to avoid over imputation.

Anchor items were used to equate the baseline (at age 12) and follow-up (at age 15) questionnaires. Since no prior information on invariant items of CPQ_11–14 have been available, five questions concerning global self-health rating were asked, namely “How do you rate your dental/ oral health condition?” (“Very Good” /“Good” /“Average” /“Bad” /“Very Bad”), “How does your dental/oral health impact your life?” (“Not at all” /“A little” /“Somewhat” /“Greatly” /“Tremendously”), “To what extent have you been bothered by these problems?” (i.e. the problems described in the 8 item short form CPQ_11–14), “To what extent have these problems affected your quality of life?” and “To what extent have these problems affected your life overall?” (“Never” /“Hardly Ever” /“Occasionally” /“Often” /“Very Often”).

Each participant received an oral examination for assessment of dental caries experience and periodontal condition following the World Health Organization’s recommendation [16]. Dental caries experiences were measured by the number of decayed, missing and filled teeth (DMFT). Periodontal conditions were measured by the community periodontal index (CPI) with 3 levels, namely “Healthy gum/ absence of bleeding or calculus”=0, “Bleeding on probing”=1 and “Calculus deposits” = 2 on 6 index teeth (16, 11, 26, 36, 31 and 46). The highest CPI score was used as a summary measure of periodontal health status. All oral examinations were performed by trained and calibrated dentists in the school premises on a portable dental chair. The oral examinations were performed using intra-oral disposable mouth mirrors with LED light and CPI probes by one examiner at baseline and another one in the follow-up study. About 10% of the participants were re-examined to evaluate the intra examiner reliability using Intra-class correlation (ICC) and Kappa Statistics, which indicated the consistency in measuring DMFT and CPI respectively (DMFT: ICC = 0.99 at age 12, ICC = 0.82 at age 15; CPI: Kappa = 0.74 at age 12, Kappa = 0.84 at age 15). Anthropometric assessment was also conducted but the information was not used in this study.

Six hundred sixty eight sets of parental and student questionnaires from 12 years old children were collected; 436 (65.3%) students were followed up successfully after 3 years. At baseline, 19 cases with more than 2 missing items in CPQ were excluded; 649 were used in the analysis. In the 3-year follow-up, 415 cases were used in the analysis (after excluding 21 cases with more than 2 missing items in CPQ). The mean scores for CPQ_11–14 RSF:8 and ISF:8 at baseline were respectively 7.0 (SD = 3.8, range = 0–20) and 7.4 (SD = 3.6, range = 0–21). The mean scores of CPQ_11–14 RSF:8 and ISF:8 at follow-up were respectively 6.2 (SD = 3.7, range = 0–17) and 7.2 (SD = 3.8, range = 0–19). The median class of monthly family income was $10,000–$20,000 at both baseline and follow-up. Regarding the oral health behaviors, more than a quarter of the sample brushed teeth less than twice a day and only less than a quarter did not eat snack between meals. For the oral health status, only about one in ten had healthy gum while majority of them bled on probing or had calculus. The mean DMFT on baseline was 0.55 while that in the follow-up had increased to 1.70. The frequency distributions of other factors considered at both baseline and follow-up are shown in Table 1.

Table 2 shows the estimated median and the 95% credible intervals of the regression coefficients and the difference of each pair of levels within each factor for 12 years old children. Respondents with more frequent tooth brushing, less snacks consumption between meals, and with both parents employed showed a better OHRQoL. However, people with worse gum status were found having a worse OHRQoL. Regarding parental education, it is noted that significantly better OHRQoL was found for those with fathers attained secondary compared to below secondary education while significantly worse OHRQoL for those with mothers attained secondary compared to below secondary education. No significant differences were found among other comparisons for father’s or mother’s education.

A longitudinal GRM model allowing parameter drift was fitted with the 5 global rating anchor items. Results on longitudinal invariance are shown in Table 3. No significant change in discriminatory parameters of RSF:8 or ISF:8 was found. This indicated the absence of non-uniform longitudinal invariance. Two items form CPQ_11–14 RSF:8 and 2 items from ISF:8 had significant threshold parameters drift. In CPQ_11–14 RSF:8, the items were “Argued with other children or your family” and “Teased/ called names by other children”. In CPQ_11–14 ISF:8, these items were “Difficult to drink or eat hot or cold foods” and “Irritable/ frustrated”. For the item “Argued with other children or your family”, children at follow-up were prone to choose “Never” = 0 compared to baseline even their OHRQoL levels have not changed. For the item “Teased/ called names by other children”, children at follow-up were more likely to response to “Never” = 0 or “Once/ twice” = 1. For the item “Difficult to drink or eat hot or cold foods”, children at follow-up were prone to choose “Once/ twice” = 1 or higher response options. For the item “Irritable/ frustrated”, children at follow-up were more likely to choose “Sometimes” = 2, or higher response options. Of the 4 items with longitudinal invariance, 3 items came from the domains of emotional well-being and social well-being while the other one came from the domain of functional limitations.

Tables 4, 5and 6 present the results of the longitudinal models with adjustment for longitudinal invariance by allowing the threshold parameter of the 4 items (with significant parameter drift) to vary. In Model 1, baseline explanatory variables were used to predict the change over 3 years (Table 4). Respondents who consumed more snacks at baseline had significantly more improvement in OHRQoL over 3 years. Table 5 presents the results of a similar longitudinal model. Instead of baseline predictors, the change in demographics variables and the change in oral health behavior/status over the 3 years were used to predict the change in OHRQoL (Model 2). For participants with decreased income, their OHRQoL had worsened over 3 years. Table 6 presents the results of Model 3 that used 12 years old and 15 years old conditions to explain baseline and follow-up OHRQoL respectively, while adjusting for longitudinal invariance. Variables significantly associated with 12-years old OHRQoL were similar to that in cross-sectional analysis. More frequent tooth brushing, a lower mother education level (lower secondary vs. primary) and a higher father education level (lower secondary vs. primary, upper secondary vs. primary) was associated with better OHRQoL. Respondents with both parents employed, less snacks consumption between meals and better gum conditions can predict 12 years old OHRQoL. In 15 years old, no variables were significantly associated with OHRQoL.

Three of the four longitudinally biased items were from the domains of emotional and social well-being, namely “Argue with other children or family”, “Teased/ called names by other children” and “Irritable/frustrated”. In short, children tended to choose a lower response options in items concerning emotional and social well-being in the follow-up study. One way to adjust longitudinal invariance is to remove the problematic item. This may however result in an instrument with questionable content validity. Allowing invariant parameters to be varied provides an alternative adjustment method for longitudinal invariance while preserving the content validity.

The investigation of longitudinal invariance also highlighted the importance of testing longitudinal invariance especially when items concern emotions or perceptions which possibly change over time. Moreover, adjustment for longitudinal invariance also enables the questionnaire to be appropriate even if the participants’ age was one year exceeded the CPQ’s target age range of 11–14 years.

Dental caries experience did not significantly associate with OHRQoL in the present study. This was consistent only to the findings from few countries. Table 7 shows studies concerning dental caries status and OHRQoL in adolescents in different countries. It reveals that most studies concluded the significant association had a higher mean DMFT or prevalence compared to that in present study. Studies found no such significant association had a comparable mean DMFT or prevalence to that in the present study, for instance, a study in Dunedin and a previous study in Hong Kong. Although the hypothesis “Dental caries predict OHRQoL only in higher impact populations.” requires a meta-analysis to conclude, the studies in Table 7 and the present study suggest that a higher disease level may be required for detecting the impact of dental caries on OHRQoL because mild dental caries, even untreated, may not be painful and hardly affect the person. Other studies that found the significant association between oral health status and OHRQoL are often in large sample or diseased group [21].

Many studies have attempted to relate the social economic status to OHRQoL but mixed results have been found. Inconsistent results may be attributed to whether the analysis has been adjusted to confounding factors. Also, different studies have employed different variables as a proxy of SES: parents’ education levels, occupations, parents’ age, parents’ attitude, family income, type of flat, household crowding, number of siblings and so on [22]. In this study, the parents’ education level, family income and whether both parents are working were used to measure the SES. There were significant differences in OHRQoL across some subgroups of parents’ education level. But no clear indication of associations between OHRQoL and higher/ lower education levels was observed.

Socioeconomic status often affects OHRQoL through the limited access of dental utilities due to material deprivation [23]. It is unlikely to be the case in Hong Kong because government’s SDCS provides children from primary school (equivalent to US grade 1 to 6) an annual dental checkup. In our sample, 98% of the school children participated in the scheme or had private dental insurance. Almost all children have received adequate dental care regardless of their family income. This may explain the weak association between income and OHRQoL in Hong Kong. However, SDCS was no longer provided for adolescents after 12 years old. Adolescents with increased family income over the age of 12–15 had only little OHRQoL improvement over these 3 years. This concurs with the hypothesis that the lower economic status leads to inadequate access of dental utilities, and thus OHRQoL. This suggests that a specific scheme taking care of children from low income family is needed rather than general measures like extending SDCS to older ages.

All predictors found predictive in OHRQoL of 12 years old adolescents (oral health behaviors, gum status, some socioeconomic variables) became insignificant in the 15 years old follow-up with adjustment for longitudinal invariance. This may be related to the improvement of the OHRQoL over 3 years. When an already low-impact population has further improved, the OHRQoL becomes better in a homogeneous manner. The baseline characteristics (shown in Table 1) of those children lost to follow up were compared with the rest of respondents. No significant difference were found in all variables, except for daily brushing frequencies (Twice or more: 75.9% in follow-up vs. 65.0% in lost follow-up), CPI (Calculus deposit: 62.2% in follow-up vs. 69.7% in lost follow-up) and DMFT (Mean DMFT: 0.47 in follow-up vs. 0.71 in lost follow-up). It makes detecting effect of factors even harder, subsequently resulting in a failure to identify factor significantly associated to OHRQoL of adolescent in 15-years old.

The weakened association at 15 years old may due to the “regress to the mean” which describes the trend that significant associations tended to become insignificant when the variables are measured in the second time because of the random error [24]. Respondents who consumed more snacks had significantly greater improvement in OHRQoL over 3 years and this appear to be counter-intuitive. This is suspicious to the “regress to the mean” effect especially the snacking frequency is highly susceptible to random error due to the difficulty to recall exactly the snack intake and neglecting the amount and types of snack consumed.

Relying on anchor to establish item longitudinal invariance is sometimes criticized because invariance properties of the anchor itself is doubted. This study address this concern by choosing relatively large number of global self-rating items reflecting their own perception about OHRQoL and its impact on daily life.

Many studies suggested that psychological characteristics played an important role in coping with unfavorable conditions, for instance, poor dental aesthetics [25]. No data about sense of coherence, self-esteem and confidence were collected, which have been proven to be potential predictors of OHRQoL [22, 26, 27]. Moreover, malocclusion status directly related to facial appearance and thus may affect OHRQoL directly. Association of OHRQoL and malocclusion status has been shown in both general population and studies confined to disease specific groups [28]. Unfortunately, malocclusion data was not available to be used in this study.

Being part of a larger scale cohort study “Children of 1997”, it is a representative sample of the general Hong Kong adolescents. It should be noted that this is a study on a low impact population of dental caries and OHRQoL. Also, the lost to follow-up respondents had slightly worse oral health status, this dataset may fail to capture their OHRQoL development which may drive more actionable insight for oral health policies. When generalizing the results, one should aware of the cultural difference and the relevant local dental policies which vary across countries.