A Causative Approach to Demographic and Socioeconomic Factors Affecting Parental Ratings of Child Oral Health

Abstract

Introduction: Many studies have investigated associations between demographic, socioeconomic status (SES), behavioral, and clinical factors and parental ratings of child oral health. Caries experience, pain, missing teeth, malocclusions, and conditions and treatments likely to negatively affect the child or family in the future have been consistently associated with poorer parental ratings. In contrast, effect sizes for associations between demographic and SES indicators (race/ethnicity, country of birth, family structure, household income, employment status, and parental education levels) and parental ratings vary greatly. Objectives: The primary objectives of this study were to estimate effect sizes for associations between demographic and SES variables and parental ratings of child oral health and then to consider possible causal implications. Methods: This article uses a nationally representative data set from 24,664 Australian children aged 5 to 14 y, regression analyses guided by a directed acyclic graph causal model, and sensitivity analyses to investigate effects of demographic and SES factors on parental ratings of oral health. Results: One in 8 children had oral health rated as fair or poor by a parent. Indigenous children, older boys, young children with a migrant parent, children from single-parent families, low-income households and families where no parent worked full-time, and children whose parents had lower education levels were much more likely to receive a fair or poor parental oral health rating in crude and adjusted models. Conclusion: This cross-sectional study helps to clarify inconsistent findings from previous research and shows many demographic and SES variables to be strong determinants of parental ratings of child oral health, consistent with the effects of these variables on other health outcomes. Sensitivity analyses and consideration of the potential for chance and bias to have affected these findings suggest that many of these associations may be causal. Knowledge Transfer Statement: Based on regression analyses driven by a directed acyclic graph causal model, this research shows a strong impact of demographic and socioeconomic determinants on parental ratings of child oral health, consistent with associations between these variables and other oral and general health outcomes. Many of these associations may be causal. We demonstrate the value of causal models and causal thinking when analyzing complex multilevel observational data.

Health-related quality of life and impact of socioeconomic status among primary and secondary school students after the third COVID-19 wave in Berlin, Germany

“…However, HRQoL differed across time points as well as strata of sex and age, with older girls more frequently reporting low HRQoL compared to boys of both age groups and to younger girls. This observation with respect to age and sex is in line with other studies [ 40 ] and has been reported prior to the COVID-19 pandemic [ 44 ]. Hypotheses about the mechanisms behind these differences include complex interactions of socio-behavioral and societal factors [ 43 , 45 ] and must be investigated further [ 26 ].…”

Water fluoridation, dental caries and parental ratings of child oral health

“…Effect sizes for LEFW on parental ratings for both age groups are generally comparable with or slightly below those seen for demographic and socioeconomic variables, 12 with the effect being stronger for younger children. The observed parental rating PR effect size (1.5) for younger children and primary teeth with no LEFW could only be accounted for by an unmeasured confounder (or set of confounders) associated with LEFW and parental rating variables, each with an E ‐value risk ratio of 2.3 or greater.…”

“…The NCOHS questionnaire asked parents to rate their child's oral health on a five‐point Likert scale. Consistent with most previous research, these parental ratings were dichotomized to excellent, very good or good, and fair or poor 12 . Creation of a binary variable allowed calculation of prevalence ratio (PR) effect sizes using log Poisson regression models with robust error variance to correct for overdispersion of data 24 .…”

“…Consistent with most previous research, these parental ratings were dichotomized to excellent, very good or good, and fair or poor. 12 Creation of a binary variable allowed calculation of prevalence ratio (PR) effect sizes using log Poisson regression models with robust error variance to correct for overdispersion of data. 24 A PR of 1.5 represents a 50% greater likelihood of an outcome than the reference category.…”

“…Previous studies have identified many variables associated with poorer parental ratings of their child's oral health, hereafter 'parental rating/s.' These include, but are not limited to, membership of demographic or socioeconomic groups experiencing greater disadvantage within society, [12][13][14][15] caries prevalence, pain and perceived urgent treatment needs, 10,11,16,17 and poor dental aesthetics and malocclusions. 16,18,19 Caries experience and related lived experiences are likely to be drivers or mediators for the associations between some of these variables and parental ratings.…”