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J Am Dent Assoc, Vol 138, No 3, 309-318.
© 2007 American Dental Association |  |
COVER STORY |
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ABSTRACT |
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 TOP ABSTRACT METHODSRESULTSDISCUSSIONCONCLUSIONREFERENCES |
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Methods. Trained researchers interviewed a representative sample of low-income black families (caregivers and children aged 0 through 5 years) in Detroit to assess their dental visit history, dental insurance status and oral health behaviors. Dental examinations were conducted using the International Caries Diagnosis Assessment System (ICDAS). Of the 1,021 families who completed an interview and examination, a subset of the 552 children aged 3 to 5 years (and their primary caregivers) was the focus of this analysis.
Results. Children with private dental insurance had four times higher odds of having visited a dentist compared with those who had no dental insurance, and the odds for children receiving Medicaid were about 1.5 times higher. A child’s age and a caregiver’s educational attainment were positive and significant determinants of child dental visits. Caregivers who visited a dentist for preventive reasons were five times more likely to have taken their children to visit the dentist. Visiting a dentist was associated with an increased mean number of filled or missing tooth surfaces, but it was not significantly associated with the mean number of untreated decayed teeth.
Conclusion. Children’s dental insurance status was a significant determinant of their having visited a dentist. Even after the authors accounted for insurance status and other risk indicators, they found that children of caregivers who reported visiting a dentist for preventive care had a higher number of dental care visits. Determinants of caregivers’ preventive dental visits must be identified and encouraged to improve the percentage of low-income children who visit dentists.
Key Words: Behavioral sciences; dental insurance; dental care utilization; access to care
Abbreviations: DDHP: Detroit Dental Health Project • ICDAS: International Caries Diagnosis Assessment System • SCHIP: State Children’s Health Insurance Program
Disparities in oral health status between high and low socioeconomic groups persist partly because of lack of access to regular dental care.1,2 Children of low-income families tend to receive episodic or emergency dental care, while those from higher-income households visit dentists more often for preventive checkups.3 Dental organizations have focused their efforts to remedy disparities in access to dental care by advocating for increased financing and insurance coverage for underserved population groups. Safety net programs—including Medicaid, Head Start and the State Children’s Health Insurance Program (SCHIP)—provide dental care coverage for low-income children. However, all of these programs have limitations, and in the state of Michigan and the city of Detroit, they are underfunded. Consequently, utilization of these programs has been low and low-income children’s access to dental care has not been improved as expected, although most would agree that some improvement has indeed occurred in contrast to the alternative of no "safety-net programs."4 Another barrier to improving access to dental care is that in the majority of states, the dental safety-net programs provide coverage for children but, unfortunately, not for their parents or caregivers.
Determinants of access to dental care among low-income children are multifactorial. In addition to poverty, low education levels, lack of transportation and the limited number of dental providers within these communities, two important barriers exist.5,6 Owing to the limited number of dentists who are willing to accept low Medicaid fees or deal with the perceived bureaucratic hassles of reimbursement by Medicaid, finding a dentist when dental care is needed is a major challenge for many low-income families.7 Hence, even if the financial barriers are removed, access to dental care may remain limited for many low-income children.8
Given these barriers that limit the access to dental care for low-income Americans, we contend that achieving the Healthy People 2010 Objective9 of increasing regular dental visits among people 2 years and older to 56 percent annually may not be possible for low-income minority populations. There is a need for research on the complex associations between the different determinants of dental visits made by low-income Americans. We conducted a study to investigate determinants of dental visits among African-American children between the ages of 3 and 5 years and the association between the children’s and their parents’ or caregivers’ dental visit behaviors.
Power considerations, and adjustment for anticipated attrition over the four-year study period, indicated that a specified sample size of 1,000 eligible children completing examinations would meet precision requirements for four different projects of the DHHP.
We selected a two-stage area probability sample of households and eligible children from the study census tracts. There were a total of 1,526 blocks in these tracts. We cumulated census 2000 counts of households by block, and we used a probability-proportionate-to-size selection to choose 118 study blocks. For field data collection efficiency, we linked blocks with fewer than 100 households to other blocks to form units of a minimum size of 100 households. This process resulted in 594 blocks linked together to form 118 study sample segments.
Within each selected segment, we listed and chose households with probabilities inversely proportionate to size to obtain an equal chance of selection of households across the 39-tract study area. A team of specially trained community residents listed 14,391 addresses across all 118 segments. The within-segment selection, with probability inversely proportionate to size, subsampled 12,655 of the listed addresses.
Trained interviewers visited each sampled housing unit. A total of 10,695 sample housing units were occupied (84.5 percent occupancy rate). Among the occupied housing units, interviewers contacted and screened 9,781 of them (91.5 percent contact rate). There were 1,386 (14.2 percent) contacted and screened households with one or more eligible black children. When there was more than one eligible child in a household, only one child was randomly selected, with the use of a predetermined random number, to be the "index child." We defined "main caregiver" as a person who makes major decisions such as feeding, bathing and nurturing the "index child" emotionally, mentally and physically. A total of 1,021 eligible children and their caregivers subsequently completed an interview in the household and an examination in a centrally located study office. The combined screening and interviewing response rate was 73.7 percent.
In this analysis, we used data from a subset of these children: those 3 to 5 years old and their caregivers (n = 522).
Data collection.
Trained staff conducted face-to-face interviews with participants during fall 2002 through spring 2003 at the DDHP’s Dental Assessment Center. The staff interviewed only the caregivers, who were questioned about their own dental care and who served as proxies for the children in answering questions about their care and dental health–related behaviors. Staff received training from investigators and survey specialists for one month. We regularly checked the interview quality throughout the 10-month data collection period by reviewing videotapes of the interviews in addition to conducting face-to-face reviews with the interviewers.
Measures.
The interviewers obtained a child’s dental visit history by asking each caregiver, "Have you taken (index child’s name) to see a dentist?" Variables regarding caregivers’ own dental care included the time since the most recent visit and the reason for the most recent visit. We conducted preliminary analyses on these variables and created categorical variables with the following levels:
Interviewers also asked about the caregiver’s perception of the availability of dental services in general (ranked from poor to excellent).
In addition, interviewers also collected data on the dental insurance status of children and their caregivers (coded as private, government-issued or none) and caregivers’ perceptions of their children’s oral health status. The perception was measured using the question, "How would you describe the condition of (index child’s name)’s mouth and teeth?", which was similar to the one used for adults’ and adolescents’ self-perception of oral health in previous studies.10,11 Valid answers included "Excellent," "Very good," "Good," "Fair" and "Poor." (For this analysis, we collapsed the "Fair" and "Poor" categories owing to the small case counts within these groups.) Interviewers also asked caregivers whether their children had any problems with chewing hard food.
Sociodemographic variables included care-giver’s age, sex, educational attainment (grouped as less than high school, high school degree, higher than high school degree), annual household income (categorized as less than $10,000, $10,000–19,999 and $20,000 or higher) and household size, and the child’s age and sex.
Measurement of dental caries.
We measured caries using criteria from the International Caries Detection and Assessment System (ICDAS).12 In DDHP, four dentists who were trained and calibrated with the ICDAS criteria carried out the scoring for dental caries of children and their caregivers. We ran both inter- and intrareliability
Statistical analyses.
Using an interviewer-administered data collection process instead of a self-administered questionnaire limited the amount of missing data within the data set (less than 4 percent for any individual item). All missing data were imputed using Imputation and Variance Estimation software (IVEware). IVE-ware performs multiple imputations using a procedure in which a sequence of regression models are fit and values are drawn from the predictive distributions.15,16
We conducted bivariate analyses and developed multivariable logistic regression models using SAS (Version 9.1, SAS Institute, Cary, N.C.) and SUDAAN software (Release 9.0.0, SAS-Callable, Research Triangle Institute, Research Triangle Park, N.C.) to estimate variances adjusted for design effects.17 Statistical significance was tested at the conventional level of
All analyses used sample weights created to account for nonresponse and disproportionate representation of the respondents relative to the targeted population’s race, sex and age distributions.
METHODS
TOP
ABSTRACT
METHODS
RESULTS
DISCUSSION
CONCLUSION
REFERENCES
Study population.
Data for this analysis were collected by the Detroit Center for Research on Oral Health Disparities, also known as Detroit Dental Health Project (DDHP), which is a research center founded with the aim of reducing oral health disparities, funded by the National Institute of Dental and Craniofacial Research. The participants in this study were black families who lived in 39 census tracts with the lowest income levels and highest proportion of black children in the city of Detroit. We used the 2000 census tract data to find 39 tracts with the largest proportions of households with black children in low-income families. We chose a subset of the 250 census tracts in Detroit as the study area based on the percentage of households below 200 percent of the federal poverty guidelines, the percentage of households with blacks, and the percentage of households with children younger than 6 years. We used the 200 percent poverty guidelines cutoff for census tracts although the inclusion criterion for the study required selection of families at 250 percent of the poverty guidelines, because data for the 250 percent level were not available at the tract level in the 2000 census data. We collected data on poverty level during household screening to identify households meeting the inclusion criteria.
statistics to evaluate the examiners. Interrater statistics ranged from 0.64 to 0.75 while the intrarater statistics ranged from 0.59 to 0.82. We estimated reliability using weighted statistics, which are more appropriate for ordinal scales.13 More details regarding reliability of the dental examiners have been published elsewhere.14 The caries measurements used in this analysis were untreated noncavitated decayed surface; untreated cavitated decayed surface; and a child’s total caries experience: total sum of decayed surfaces (noncavitated and cavitated), filled surface and missing surfaces due to caries (calculated as four surfaces for an anterior tooth and five surfaces for a posterior tooth). 
= .05, and the Wald F test was used to derive P values.
RESULTS
TOP
ABSTRACT
METHODS
RESULTS
DISCUSSION
CONCLUSION
REFERENCES
Of the 522 caregivers of children aged 3 through 5 years, 60.7 percent (n = 309) reported having ever taken the index child to a dentist at least once. Older and female children were significantly more likely to have visited dentists compared with younger and male children, respectively. Caregiver’s educational level had a positive and significant association with child’s dental care visits (Table 1
). Household income, caregiver’s sex and caregiver’s age did not have a significant association with child’s dental visits.
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). While caregivers who rated their children’s oral health more favorably (that is, as "excellent" or "very good") were more likely to have taken their children to see the dentist, this tendency did not show statistical significance at a 5 percent error level (P value = .061). Caregivers who rated their children’s oral health as "fair" or "poor" were even more likely to have taken their children to the dentist than were those who rated their children’s oral health as "good" or "very good." This might be due to the fact that the children in this group had a higher disease level (preliminary results not reported here) that may have required immediate care. Another explanation might be that caregivers’ unfavorable perception of their children’s oral health motivated them to seek dental care for these children.
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Table 3 compares oral health between children who had and had not visited a dentist. Results in this table compare two groups of children who were different in age. Children who had made a dental visit are significantly older than children who had not. The comparison between these two types of children is adjusted for age in a subsequent analysis. For the sake of completeness, however, we include here comparisons that are not adjusted for age.
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Table 4 presents findings that caregivers who themselves reported having visited the dentist for preventive reasons were significantly more likely to take their child to the dentist compared with caregivers who had visited for treatment purposes. There also is a clear association between child’s dental visits and the recency of caregiver’s dental visits; for example, caregivers who reported seeing a dentist more recently were more likely to have taken their children for dental care. Caregiver’s dental insurance status also was positively, but not significantly, associated with child’s dental visits. Child’s dental visits were positively and significantly associated with care-givers’ perception of the availability of dental care. Caregivers who brushed their teeth less than once per day were less likely to take their child to the dentist, but the association was not statistically significant at a 5 percent error level (Table 4).
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, page 316). The initial model was limited to sociodemographic factors, which explained only 10 percent of the variability in children’s having had dental visits. Child’s age, child’s sex and caregiver’s educational attainment level were significant in the model (Model 1 in Table 5). Results were consistent with bivariate results: older and female children, and caregivers with higher educational levels, were associated with a higher probability of having visited a dentist.
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). Children with private dental insurance were approximately five times more likely to have visited the dentist than were those without dental insurance. Also, children with Medicaid or SCHIP dental coverage were approximately two times more likely to have had dental visits than were those without dental insurance, after we controlled for sociodemographic factors and other dental-related factors such as dental caries level (dmfs) and perceived oral health status in the model (Model 2 in Table 5).
When we added to the model factors representing caregivers’ dental access status, there was a substantial increase in the pseudo R2 value; 24 percent of the variability of child’s dental visits was explained by the final model (Model 3 in Table 5). Caregivers who had last visited the dentist for preventive reasons were about five times more likely to have taken their children to see a dentist than were caregivers who had last visited for treatment purposes or had never been to a dentist. Also, caregivers who had last visited a dentist for both prevention and treatment were 1.74 times more likely to have taken their children to see a dentist than were those in the "treatment only" and "never visited" groups, though this coefficient reached only marginal significance. The caregiver’s preventive visit behavior was one of the most significant determinants of child’s dental visit after we accounted for confounding factors such as child’s age, socioeconomic status, child’s dental insurance status and dental caries status. Dental insurance status of the caregivers did not show significant association with child’s dental visit, nor did the recency of the caregiver’s last dental visit. Caregivers’ perception of the availability of dental care had a positive, but weak, association with child’s dental visit (Model 3 in Table 5). We examined some plausible interactions among the predictor variables in the final model, but we found no significant interactions.
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DISCUSSION |
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TOPABSTRACTMETHODSRESULTSDISCUSSIONCONCLUSIONREFERENCES |
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This study confirms previous reports with regard to the important determinants of children’s dental visits, such as child’s dental insurance coverage and socioeconomic factors that include caregivers’ educational level.6,18,19 Also, the importance of child’s dental health coverage on dental visit behavior is in line with the findings of investigations of dental insurance programs.20,21
While child’s insurance status was a significant determinant, caregiver’s dental insurance status was not significantly associated with child’s dental visits. Although several studies have reported a significant association between adults’ dental insurance coverage and adults’ dental visits,22–24 we located only one study that had specifically reported the relationship between adults’ dental insurance coverage and children’s dental visits.25 In this study, the researchers also found that the adult caregiver’s dental insurance status did not influence the child’s dental care utilization.25 This finding, however, should not be interpreted to mean that adults’ insurance status is irrelevant to children’s dental care utilization. Rather, it underscores the importance of understanding that there are huge barriers to dental care access among this low-income population—such as lack of transportation, lack of family support and lack of dental clinics in the neighborhood—and that it takes far more effort than simply providing some type of dental insurance coverage.7,26
A noticeable finding of this study is the significance of caregivers’ prevention-oriented dental visits as related to their children’s dental visits. Even among the low-income inner-city population, caregivers who had had prevention-oriented visits were five times more likely to have taken their children to a dentist than were those who sought dental care only for treatment or not at all. This also provides an explanation of the previous finding that free care is not sufficient to eliminate differences in dental care utilization and oral health among underserved children.8 Self-care preventive behaviors are paramount in combating oral disease and conditions. It takes a personal commitment to preventive orientation by caregivers to improve utilization of dental care among low-income children. This finding, therefore, underscores the importance of promoting caregivers’ preventive behaviors in concert with increasing access to dental care and removing barriers to dental care. This could be achieved by providing innovative behavioral change interventions targeting oral health habits, as well as by facilitating appropriate preventive dental care by various programs and clinics.
This study identified significant determinants of children’s dental visit behaviors that could be modified or promoted to increase children’s dental visits among low-income populations. However, we do not know whether increased dental visit frequency will result in an improvement in oral health over time. The results of this study showed that there were no differences in untreated decay (both noncavitated and cavitated) between the children who had had dental visits and those who had not. This finding may indicate that the children in this low-income neighborhood received restorative treatments or underwent extractions when they visited the dentist, but they did not receive proper therapies to prevent further development of dental caries. Careful evaluation and policy development on the part of Medicaid and SCHIP are crucial to promote regular dental visits for purposes of prevention as well as necessary restoration of teeth with existing dental caries for low-income and high-risk children.
The strengths of this analysis include that it was based on one of the largest representative samples of low-income black populations living in an inner city (Detroit). On the other hand, interpretation of the results requires consideration of the fact that information on frequency and reasons for dental visits was self-reported. While the data were collected through an interview by a trained interviewer rather than a self-administered questionnaire, it is still possible that caregivers did not clearly remember information or responded incorrectly to the interviewers regarding their own (or their children’s) previous dental visits.
The findings from this analysis warrant several future studies. First, more research must be conducted to find the underlying causes of care-givers’ preventive oral health behaviors, including regular dental visits. The low-income caregivers who participated in this study share problems such as lack of access to dental care (for example, shortage of dentists who accept Medicaid) and other barriers (such as lack of transportation and social support). However, on the basis of the results of this study, we speculate that some care-givers possess underlying attitudes or knowledge that promotes their seeking preventive dental care for themselves and their children. If we can isolate these factors, changing the mind-set of other low-income caregivers should be effective in increasing not only adult care but also, and importantly for this research, children’s dental care.
Second, in 2004, Michigan dropped dental care benefits for adults owing to a budget deficit. While this cut was reversed in 2005, it is unfortunate that preventive services were not reinstated. It is important to understand the influences and ramifications of changes in Medicaid benefits for adults and how they affect their children’s dental care visits. This issue could be investigated using longitudinal oral health survey data (such as those from the Detroit Center) in conjunction with dental services claims data (for example, Medicaid).
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CONCLUSION |
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TOPABSTRACTMETHODSRESULTSDISCUSSIONCONCLUSIONREFERENCES |
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FOOTNOTES |
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REFERENCES |
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TOPABSTRACTMETHODSRESULTSDISCUSSIONCONCLUSIONREFERENCES |
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This article has been cited by other articles:
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  D. Grembowski, C. Spiekerman, and P. Milgrom Linking Mother and Child Access to Dental Care Pediatrics, October 1, 2008; 122(4): e805 - e814. [Abstract] [Full Text] [PDF]
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 S. Lim, W. Sohn, B. A. Burt, A. M. Sandretto, J. L. Kolker, T. A. Marshall, and A. I. Ismail Cariogenicity of Soft Drinks, Milk and Fruit Juice in Low-Income African-American Children: A Longitudinal Study J Am Dent Assoc, July 1, 2008; 139(7): 959 - 967. [Abstract] [Full Text] [PDF]
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