The relationship between body system-based chronic conditions and dental utilization for Medicaid-enrolled children: a retrospective cohort study

  • Donald L Chi1Email author and

    Affiliated with

    • Nicholas A Raklios1

      Affiliated with

      BMC Oral Health201212:28

      DOI: 10.1186/1472-6831-12-28

      Received: 1 August 2011

      Accepted: 11 July 2012

      Published: 7 August 2012

      Abstract

      Background

      Dental care is the most common unmet health care need for children with chronic conditions. However, anecdotal evidence suggests that not all children with chronic conditions encounter difficulties accessing dental care. The goals of this study are to evaluate dental care use for Medicaid-enrolled children with chronic conditions and to identify the subgroups of children with chronic conditions that are the least likely to use dental care services.

      Methods

      This study focused on children with chronic conditions ages 3-14 enrolled in the Iowa Medicaid Program in 2005 and 2006. The independent variables were whether a child had each of the following 10 body system-based chronic conditions (no/yes): hematologic; cardiovascular; craniofacial; diabetes; endocrine; digestive; ear/nose/throat; respiratory; catastrophic neurological; or musculoskeletal. The primary outcome measure was use of any dental care in 2006. Secondary outcomes, also measured in 2006, were use of diagnostic dental care, preventive dental care, routine restorative dental care, and complex restorative dental care. We used Poisson regression models to estimate the relative risk (RR) associated with each of the five outcome measures across the 10 chronic conditions.

      Results

      Across the 10 chronic condition subgroups, unadjusted dental utilization rates ranged from 44.3% (children with catastrophic neurological conditions) to 60.2% (children with musculoskeletal conditions). After adjusting for model covariates, children with catastrophic neurological conditions were significantly less likely to use most types of dental care (RR: 0.48 to 0.73). When there were differences, children with endocrine or craniofacial conditions were less likely to use dental care whereas children with hematologic or digestive conditions were more likely to use dental care. Children with respiratory, musculoskeletal, or ear/nose/throat conditions were more likely to use most types of dental care compared to other children with chronic conditions but without these specific conditions (RR: 1.03 to 1.13; 1.0 to 1.08; 1.02 to 1.12; respectively). There was no difference in use across all types of dental care for children with diabetes or cardiovascular conditions compared to other children with chronic conditions who did not have these particular conditions.

      Conclusions

      Dental utilization is not homogeneous across chronic condition subgroups. Nearly 42% of children in our study did not use any dental care in 2006. These findings support the development of multilevel clinical interventions that target subgroups of Medicaid-enrolled children with chronic conditions that are most likely to have problems accessing dental care.

      Background

      The 2011 Institute of Medicine Report Improving Access to Oral Health Care for Vulnerable and Underserved Populations highlights the problems children with chronic conditions have in accessing dental care [1]. Over 20% of children in the U.S. have chronic conditions [2, 3]. Based on the definition of children with special health care needs developed by the Maternal and Child Health Bureau, chronic conditions are behavioral, intellectual, developmental, or physical ailments expected to last ≥12 months in ≥75% of patients identified with the condition [4]. Examples of common chronic conditions include uncontrolled asthma, attention deficit and hyperactivity disorder, and cerebral palsy.

      Dental caries is the most common disease among all children, including those with chronic conditions [2, 5]. As a group, children with chronic conditions are believed to be at increased risk for caries for the following reasons: (1) use of sugar-containing, acidic, or xerostomic medications; (2) frequent exposure to carbohydrates because of dietary needs or oromuscular problems; (3) behavioral co-morbidities that make it difficult for caregivers to brush the child’s teeth regularly with fluoridated toothpaste; and (4) dentists’ unwillingness to treat children with chronic conditions. A comprehensive strategy to ensure optimal oral health for children with chronic conditions includes regular visits to a dentist for preventive care (e.g., examinations; cleanings; topical fluoride; sealants) as well as restorative care (e.g., fillings; stainless steel crowns; extractions) when needed. However, dental care is the most common unmet health care need among children with chronic conditions [2], which has renewed interests in developing strategies aimed at improving dental utilization for medically vulnerable children.

      Medicaid is the largest public source of dental care funding for children with chronic conditions in the U.S. [6]. State Medicaid programs are required by the federal Early and Periodic Screening, Diagnosis, and Treatment (EPSDT) Program to provide all child enrollees with comprehensive dental care [7]. While Medicaid-enrolled children are more likely to visit a dentist than uninsured children [8, 9], studies have documented disparities in dental care use among subgroups of Medicaid-enrolled children [10, 11]. A recent publication reported that Medicaid-enrolled children with chronic conditions are slightly more likely to use dental care than Medicaid-enrolled children without chronic conditions [12]. Compared to Medicaid-enrolled children with less complex chronic conditions, those with more complex chronic conditions were less likely to use any dental care [12]. In another study, Medicaid-enrolled children with an intellectual or developmental disability (defined as children with a non-acquired cognitive impairment) were equally as likely to use preventive dental care as Medicaid-enrolled children without an intellectual or developmental disability [13]. Collectively, these studies suggest heterogeneity in dental care use across subgroups of Medicaid-enrolled children with chronic conditions. While this is consistent with anecdotal evidence, there are no empirical studies to support this statement. The lack of data demonstrating heterogeneity in dental use may be one reason why current interventions fail to target children with chronic condition at greatest risk for disparities in dental use. Population-based interventions that target all children with chronic conditions are inefficient and may misallocate scare resources, which can lead to suboptimal outcomes.

      In this study, we used 3M Clinical Risk Grouping (CRG) Software, a validated risk adjustment tool [14], to identify Medicaid-enrolled children with chronic conditions. Our goal was to assess dental use across 10 body system-based chronic condition subgroups. This approach is consistent with the specialty-focused medical care system into which most children with chronic conditions are integrated. Based on previous findings that children with chronic conditions have higher levels of unmet dental needs than those without [2], we compared dental care use for children with chronic conditions across each of the following chronic condition subgroups: hematologic; cardiovascular; craniofacial; diabetes; endocrine; digestive; ear/nose/throat; respiratory; catastrophic neurological; and musculoskeletal. The knowledge generated from this study will help us to identify the subgroups of children with chronic conditions who are at greatest risk for disparities in dental care use and to develop future interventions aimed at ensuring that these children have optimal access to dental care.

      Methods

      Study design

      This was a retrospective study based on enrollment and claims data from the Iowa Medicaid Program (2003-2006). We received approvals from the University of Washington and the University of Iowa Institutional Review Boards.

      Conceptual model

      The study was based on a sociocultural oral health disparities model presented by Patrick and colleagues [15]. Model covariates were organized into five domains:

      • Ascribed factors (immutable individual-level determinants);

      • Proximal factors (modifiable individual-level health behaviors);

      • Immediate factors (household-level mediators between proximal and intermediate factors);

      • Intermediate factors (community-level factors); and

      • Distal factors (system-level factors).

      Study subjects

      We focused on children with chronic conditions ages 3-14 years who were enrolled in the Iowa Medicaid Program for ≥11 months in 2005 and in 2006. Children under age 3 were excluded because chronic conditions are typically not diagnosed until the child’s third birthday [16]. We also excluded children ≥15 years of age because the determinants of dental use for older adolescents are different from younger children [17].

      Children with chronic conditions were identified by applying the 3M Clinical Risk Grouping (CRG) Software to each child’s medical claims data from 2003-2005 (Wallingford, CT) [18]. The CRG algorithm uses diagnostic codes (International Classification of Disease–Version Nine–Clinical Modification [ICD-9-CM]) and health service utilization codes (Current Procedural Terminology [CPT]) to classify each child into one of nine mutually exclusive Core Health Status Groups (CHSGs) [4]. We excluded children in CHSGs 1 (healthy children) or 2 (children with an acute condition) and focused on children in CHSGs 3 (minor chronic condition) through 9 (catastrophic chronic condition). The final study population consisted of 25,993 Iowa Medicaid-enrolled children with chronic conditions ages 3-14 years (Figure 1).
      http://static-content.springer.com/image/art%3A10.1186%2F1472-6831-12-28/MediaObjects/12903_2011_215_Fig1_HTML.jpg
      Figure 1

      Flowchart on how final study population was derived.

      Main exposure variables

      The CRG Software also uses ICD-9-CM codes to classify each child into non-mutually exclusive body system-based Medical Diagnostic Categories (MDC). The diagnoses under each MDC correspond to a single organ system and are aligned with the delivery of specialty pediatric medical care [19]. We selected 10 MDCs most relevant for oral health: hematologic (MDC-161); cardiovascular (MDC-51); craniofacial (MDC-32); diabetes (MDC-101); digestive (MDC-61); endocrine (MDC-102); ear/nose/throat (MDC-31); respiratory (MDC-41); catastrophic neurological (MDC-12); and musculoskeletal (MDC-81). Each child with a chronic condition was classified as “no” or “yes” to indicate whether they were classified into each of the 10 MDCs.

      Outcome measure

      The primary outcome measure was use of any dental care in 2006 (no/yes) [20]. Dental services were identified from encounter files using Current Dental Terminology (CDT) codes, which are five-digit alphanumeric codes used for billing. Secondary outcome measures included use of diagnostic care (e.g., examinations; D0110-D0330), preventive care (e.g., cleanings; topical fluoride treatment; sealants; D1110-D1351; D4355), routine restorative care (e.g., fillings; D2110-D2394), or complex restorative care (e.g., pulp therapy; stainless steel crowns; extraction; D1510-D1550; D2930-4342; D7110-D7140; D9420).

      Model covariates

      Based on Patrick’s model [15], we considered the following 10 variables (organized into five domains) for inclusion in our models, measured in 2005.

      Ascribed factors: age (three categories based on the child’s dentition: 3-7 [primary and early mixed dentition]; 8-12 [mixed dentition]; 13-14 [early permanent dentition] years); sex (male/female); race/ethnicity (White, Black, other, missing/unknown); and chronic condition severity (using previously validated methods [14], the seven CHSGs were reorganized into a four-category hierarchical, mutually exclusive variable referred to as modified CHSGs: episodic chronic condition; life-long chronic condition; malignancy; or catastrophic chronic condition).

      Proximal factors: use of preventive medical care in 2005 (no/yes); previous use of any dental care in 2005 (no/yes).

      Immediate factors: whether the child had any Medicaid-enrolled siblings (no/yes) or adults in the household (no/yes).

      Intermediate factor: rurality (a four-category variable [13] based on the 2003 USDA Rural-Urban Continuum Codes and the child’s county of residence: metropolitan; urban adjacent to metropolitan; urban non-adjacent to metropolitan; rural).

      Distal factor: whether the child lived in a dental Health Professional Shortage Area based on the child’s residential zip code (no/yes).

      Statistical analyses

      After generating descriptive statistics, we used the Pearson chi-square test (α = 0.05) to test the bivariate relationships between model covariates and (1) the 10 chronic condition subgroups and (2) the five outcome measures. Next, we assessed for collinearity between the rurality and dental HPSA variables. There was no evidence of collinearity and both variables were included in the models. Then we constructed five Poisson regression models (use of any dental care, diagnostic care, preventive care, routine restorative care, and complex restorative care) for each of the 10 chronic condition subgroups. We reported covariate-adjusted relative risk ratios and estimated 95% confidence intervals using robust general estimating equation estimators of variance [21]. We tested for a statistical interaction between the two immediate factors (whether the child had a Medicaid-enrolled sibling or adult in the household) and included the interaction term in the regression model only if it was statistically significant. To address the problem of high correlation between use of any dental care in 2005 and the outcome measures, we dropped this variable from the final regression models. We analyzed the data using SPSS Version 19.0 for Windows.

      Results

      Descriptive statistics

      The mean age for children in the study was 8.9 ± 3.4 years (data not shown). About 40% of children were female (Table 1). Over 70% were White; 9.1% were Black; 7.5% were another race or ethnicity; and 13.2% had missing/unknown race or ethnicity data. In regards to chronic condition severity 69.3% had episodic chronic conditions; 28.2% had life-long chronic conditions; 0.3% had a malignancy; and 2.2% had catastrophic chronic conditions. Nearly 90% of children utilized preventive medical care in 2005. About 67.1% had a Medicaid-enrolled sibling and 55.5% had an adult in their household enrolled in Medicaid. Most children lived in a metropolitan area (55.2%) and 65.8% lived in a dental HPSA.
      Table 1

      Medicaid-enrolled children (N = 25,993) by chronic condition subgroup

       

      All children with a chronic condition

      N = 25,993

      Respiratory condition subgroup

      Ear/nose/throat condition subgroup

      Digestive condition subgroup

      Musculoskeletal condition subgroup

      Endocrine condition subgroup

        

      No

      Yes

      No

      Yes

      No

      Yes

      No

      Yes

      No

      Yes

        

      n = 4,415

      n = 21,578

      n = 6,965

      n = 19,028

      n = 14,759

      n = 11,234

      n = 14,757

      n = 11,236

      n = 20,429

      n = 5,564

        

      (17.0)

      (83.0)

      (26.8)

      (73.2)

      (56.8)

      (43.2)

      (56.8)

      (43.2)

      (78.6)

      (21.4)

      Ascribed factors

                 

      Age (years)

                 

      3-7

      9,644 (37.1)

      732 (16.6)

      8,912 (41.3)*

      413 (5.9)

      9,231 (48.5)*

      4,655 (31.5)

      4,989 (44.4)*

      6,060 (41.1)

      3,584 (31.9)*

      7,075 (34.6)

      2,569 (46.2)*

      8-12

      11,321 (43.6)

      2,452 (55.5)

      8,869 (41.1)

      4,305 (61.8)

      7,016 (36.9)

      6,982 (47.2)

      4,339 (38.6)

      6,542 (44.3)

      4,779 (42.5)

      9.248 (45.3)

      2,073 (37.3)

      13-14

      5,028 (19.3)

      1,231 (27.9)

      3,797 (17.6)

      2,247 (32.3)

      2,781 (14.6)

      3,122 (21.2)

      1,906 (17.0)

      2,155 (14.6)

      2,873 (25.6)

      4,106 (20.1)

      922 (16.6)

      Sex

                 

      Female

      10,434 (40.1)

      1,461 (33.1)

      8,973 (41.6)*

      2,502 (35.9)

      7,932 (41.7)*

      5,604 (38.0)

      4,830 (43.0)*

      5,627 (38.1)

      4,807 (42.8)*

      8,102 (39.7)

      2,332 (41.9) †

      Race/ethnicity

                 

      White

      18,255 (70.2)

      2,998 (67.9)

      15,257 (70.7)*

      4,892 (70.2)

      13,363 (70.2)*

      10,278 (69.6)

      7,977 (71.0)*

      9,916 (67.2)

      8,336 (74.2)*

      14,373 (70.4)

      3,882 (69.8)*

      Black

      2,372 (9.1)

      428 (9.7)

      1,944 (9.0)

      769 (11.0)

      1,603 (8.4)

      1,438 (9.7)

      934 (8.3)

      1,543 (10.5)

      829 (7.4)

      1,944 (9.5)

      428 (7.7)

      Other

      1,944 (7.5)

      263 (6.0)

      1,681 (7.8)

      411 (5.9)

      1,533 (8.1)

      1,058 (7.2)

      886 (7.9)

      1,203 (8.2)

      741 (6.6)

      1,529 (7.5)

      415 (7.5)

      Missing/Unknown

      3,422 (13.2)

      726 (16.4)

      2,696 (12.5)

      893 (12.8)

      2,529 (13.3)

      1,985 (13.4)

      1,437 (12.8)

      2,092 (14.2)

      1,330 (11.8)

      2,583 (12.6)

      839 (15.1)

      Chronic condition severity

                 

      Episodic

      18,025 (69.3)

      2,936 (66.5)

      15,089 (69.9)*

      4,784 (68.7)

      13,241 (69.6)

      10,891 (73.8)

      7,134 (63.5)*

      10,706 (72.5)

      7,319 (65.1)*

      15,231 (74.6)

      2,794 (50.2)*

      Life-Long

      7,324 (28.2)

      1,352 (30.6)

      5,972 (27.7)

      2,020 (29.0)

      5,304 (27.9)

      3,672 (24.9)

      3,652 (32.5)

      3,881 (26.3)

      3,443 (30.6)

      4,896 (24.0)

      2,428 (43.6)

      Malignancy

      85 (0.3)

      18 (0.4)

      67 (0.3)

      16 (0.2)

      69 (0.4)

      27 (0.2)

      58 (0.5)

      41 (0.3)

      44 (0.4)

      36 (0.2)

      49 (0.9)

      Catastrophic

      559 (2.2)

      109 (2.5)

      450 (2.1)

      145 (2.1)

      414 (2.2)

      169 (1.1)

      390 (3.5)

      129 (0.9)

      430 (3.8)

      266 (1.3)

      293 (5.3)

      Proximal factors

                 

      Child used preventive medical care in 2005

      23,080 (88.8)

      3,317 (75.1)

      19,763 (91.6)*

      5,562 (79.9)

      17,518 (92.1)*

      12,583 (85.3)

      10,497 (93.4)*

      12,722 (86.2)

      10,358 (92.2)*

      17,875 (87.5)

      5,205 (93.5)*

      Child used any dental care in 2005

      15,398 (59.2)

      2,456 (55.6)

      12,942 (60.0)*

      4,039 (58.0)

      11,359 (59.7) ‡

      8,605 (58.3)

      6,793 (60.5)*

      8,449 (57.3)

      6,949 (61.8)*

      12,217 (59.8)

      3,181 (57.2)*

      Immediate factors

                 

      Child had at least one Medicaid- enrolled sibling

      17,449 (67.1)

      2,799 (63.4)

      14,650 (67.9)*

      4,625 (66.4)

      12,824 (67.4)

      10,287 (69.7)

      7,162 (63.8)*

      10,077 (68.3)

      7,372 (65.6)*

      14,286 (69.9)

      3,163 (56.8)*

      Child had at least one Medicaid- enrolled adult

      14,436 (55.5)

      1,841 (41.7)

      12,595 (58.4)*

      3,377 (48.5)

      11,059 (58.1)*

      7,879 (53.4)

      6,557 (58.4)*

      7,999 (54.2)

      6,437 (57.3)*

      11,604 (56.8)

      2,832 (50.9)*

      Immediate factor

                 

      Rurality

                 

      Metropolitan

      14,353 (55.2)

      2,653 (60.1)

      11,700 (54.2)*

      4,071 (58.4)

      10,282 (54.0)*

      8,261 (56.0)

      6,092 (54.2) ‡

      8,391 (56.9)

      5,962 (53.1)*

      11,327 (55.4)

      3,026 (54.4)

      Urban adjacent to metropolitan

      4,978 (19.2)

      812 (18.4)

      4,166 (19.3)

      1,304 (18.7)

      3,674 (19.3)

      2,765 (18.7)

      2,213 (19.7)

      2,716 (18.4)

      2,262 (20.1)

      3,883 (19.0)

      1,095 (19.7)

      Urban non-adjacent to metropolitan

      5,237 (20.1)

      730 (16.5)

      4,507 (20.9)

      1,239 (17.8)

      3,998 (21.0)

      2,917 (19.8)

      2,320 (20.7)

      2,870 (19.4)

      2,367 (21.1)

      4,091 (20.0)

      1,146 (20.6)

      Rural

      1,425 (5.5)

      220 (5.0)

      1,205 (5.6)

      351 (5.0)

      1,074 (5.6)

      816 (5.5)

      609 (5.4)

      780 (5.3)

      645 (5.7)

      1,128 (5.5)

      297 (5.3)

      Distal factor

                 

      Child lived in a dental Health Professional Shortage Area

      17,110 (65.8)

      2,876 (65.1)

      14,234 (66.0)

      4,616 (66.3)

      12,494 (65.7)

      9,753 (66.1)

      7,357 (65.5)

      9,798 (66.4)

      7,312 (65.1) ‡

      13,555 (66.4)

      3,555 (63.9) †

      Pearson Chi Square test to evaluate bivariate relationship between model covariates and each chronic condition.

      * p < .0001.

      † p < .01.

      ‡ p < .05.

      The proportions of children in the non-mutually exclusive chronic condition subgroups, in descending order, are as follows: respiratory (83.0%); ear/nose/throat (73.2%); digestive (43.2%); musculoskeletal (43.2%); endocrine (21.4%); cardiovascular (10.2%); hematologic (6.4%); catastrophic neurological (2.5%); craniofacial (1.8%); and diabetes (1.4%) (Tables 1 and 2).
      Table 2

      Medicaid-enrolled children (N = 25,993) by chronic condition subgroup

       

      Cardiovascular condition subgroup

      Hematologic condition subgroup

      Catastrophic neurological condition subgroup

      Craniofacial condition subgroup

      Diabetes subgroup

       

      No

      Yes

      No

      Yes

      No

      Yes

      No

      Yes

      No

      Yes

       

      n = 23,340

      n = 2,653

      n = 24,325

      n = 1,668

      n = 25,356

      n = 637

      n = 25,517

      n = 476

      n = 25,642

      n = 351

       

      (89.8)

      (10.2)

      (93.6)

      (6.4)

      (97.5)

      (2.5)

      (98.2)

      (1.8)

      (98.6)

      (1.4)

      Ascribed factors

                

      Age (years)

                

      3-7

      8,651 (37.1)

      993 (37.4)*

      8,719 (35.8)

      925 (55.5)*

      9,388 (37.0)

      256 (40.2)

      9,383 (36.8)

      261 (54.8)*

      9.545 (37.2)

      99 (28.2)*

      8-12

      10,262 (44.0)

      1,059 (39.9)

      10,829 (44.5)

      492 (29.5)

      11,069 (43.7)

      252 (39.6)

      11,172 (43.8)

      149 (31.3)

      11,174 (43.6)

      147 (41.9)

      13-14

      4,427 (19.0)

      601 (22.7)

      4,777 (19.6)

      251 (15.0)

      4,899 (19.3)

      129 (20.3)

      4,962 (19.4)

      66 (13.9)

      4,923 (19.2)

      105 (29.9)

      Sex

                

      Female

      9,353 (40.1)

      1,081 (40.7)

      9,757 (40.1)

      677 (40.6)

      10,158 (40.1)

      276 (43.3)

      10,250 (40.2)

      184 (38.7)

      10,264 (40.0)

      170 (48.4)‡

      Race/ethnicity

                

      White

      16,393 (70.2)

      1,862 (70.2)

      17,191 (70.7)

      1,064 (63.8)*

      17,790 (70.2)

      465 (73.0)*

      17,928 (70.3)

      327 (68.7)*

      18,002 (70.2)

      253 (72.1)

      Black

      2,133 (9.1)

      239 (9.0)

      2,181 (9.0)

      191 (11.5)

      2,356 (9.3)

      16 (2.5)

      2,347 (9.2)

      25 (5.3)

      2,338 (9.1)

      34 (9.7)

      Other

      1,724 (7.4)

      220 (8.3)

      1,783 (7.3)

      161 (9.7)

      1,913 (7.5)

      31 (4.9)

      1,913 (7.5)

      31 (6.5)

      1,924 (7.5)

      20 (5.7)

      Missing/Unknown

      3,090 (13.2)

      332 (12.5)

      3,170 (13.0)

      252 (15.1)

      3,297 (13.0)

      125 (19.6)

      3,329 (13.0)

      93 (19.5)

      3,378 (13.2)

      44 (12.5)

      Chronic condition severity

                

      Episodic

      16,720 (71.6)

      1,305 (49.2)*

      17,052 (70.1)

      973 (58.3)*

      17,981 (70.9)

      44 (6.9)*

      17,810 (69.8)

      215 (45.2)*

      17,957 (70.0)

      68 (19.4)*

      Life-Long

      6,124 (26.2)

      1,200 (45.2)

      6,728 (27.7)

      596 (35.7)

      7,180 (28.3)

      144 (22.6)

      7,082 (27.8)

      242 (50.8)

      7,066 (27.6)

      258 (73.5)

      Malignancy

      58 (0.2)

      27 (1.0)

      48 (0.2)

      37 (2.2)

      84 (0.3)

      1 (0.2)

      85 (0.3)

      0 (0.0)

      83 (0.3)

      2 (0.6)

      Catastrophic

      438 (1.9)

      121 (4.6)

      497 (2.0)

      62 (3.7)

      111 (0.4)

      448 (70.3)

      540 (2.1)

      19 (4.0)

      536 (2.1)

      23 (6.6)

      Proximal factors

                

      Child used preventive medical care in 2005

      20,602 (88.3)

      2,478 (93.4)*

      21,480 (88.3)

      1,600 (95.9)*

      22,471 (88.6)

      609 (95.6)*

      22,631 (88.7)

      449 (94.3)*

      22,751 (88.7)

      329 (93.7)‡

      Immediate factors

                

      Child had at least one Medicaid-enrolled sibling

      15,857 (67.9)

      1,592 (60.0)*

      16,401 (67.4)

      1,048 (62.8)*

      17,326 (68.3)

      123 (19.3)*

      17,200 (67.4)

      249 (52.3)*

      17,214 (67.1)

      235 (67.0)

      Child had at least one Medicaid-enrolled adult

      13,016 (55.8)

      1,420 (53.5) ‡

      13,457 (55.3)

      979 (58.7)†

      14,330 (56.5)

      106 (16.6)*

      14,228 (55.8)

      208 (43.7)*

      14,235 (55.5)

      201 (57.3)

      Immediate factor

                

      Rurality

                

      Metropolitan

      12,871 (55.1)

      1,482 (55.9)

      13,431 (55.2)

      922 (55.3)

      13,962 (55.1)

      391 (61.4)‡

      14,095 (55.2)

      258 (54.2)

      14,170 (55.3)

      183 (52.1)

      Urban adjacent to metropolitan

      4,486 (19.2)

      492 (18.5)

      4,673 (19.2)

      305 (18.3)

      4,873 (19.2)

      105 (16.5)

      4,891 (19.2)

      87 (18.3)

      4,898 (19.1)

      80 (22.8)

      Urban non-adjacent to metropolitan

      4,707 (20.2)

      530 (20.0)

      4,901 (20.1)

      336 (20.1)

      5,122 (20.2)

      115 (18.1)

      5,134 (20.1)

      103 (21.6)

      5,171 (20.2)

      66 (18.8)

      Rural

      1,276 (5.5)

      149 (5.6)

      1,320 (5.4)

      105 (6.3)

      1,399 (5.5)

      26 (4.1)

      1,397 (5.5)

      28 (5.9)

      1,403 (5.5)

      22 (6.3)

      Distal factor

                

      Child lived in a dental Health Professional Shortage Area

      15,351 (65.8)

      1,759 (66.3)

      16,023 (65.9)

      1,087 (65.2)

      16,768 (66.1)

      342 (53.7)*

      16,809 (65.9)

      301 (63.2)

      16,879 (65.8)

      231 (65.8)

      Pearson Chi Square test to evaluate bivariate relationship between model covariates and each chronic condition.

      * p < .0001.

      † p < .01.

      ‡ p < .05.

      Bivariate statistics

      The bivariate relationships between model covariates and exposure variables (each of the 10 chronic condition subgroups) are summarized in Tables 1 and 2. Even though most children were male, when there were statistically significant differences, larger proportions of children across the chronic condition subgroups were female. Across every subgroup, significantly larger proportions of children with the chronic condition utilized preventive medical care in 2005 than children without the specific chronic condition. There were no other consistent findings.

      The bivariate relationships between model covariates and the primary outcome variable (any dental care use in 2006) as well as the secondary outcome measures (use of diagnostic, preventive, routine restorative, or complex restorative dental care) are summarized in Table 3. Significantly larger proportions of children who utilized each type of dental care were White. In addition, significantly larger proportions of children who utilized preventive medical care in 2005 subsequently utilized all types of dental care in 2006.
      Table 3

      Relationships between covariates and dental utilization outcome measures

       

      Any dental care use in 2006

      Diagnostic dental care use in 2006

      Preventive dental care use in 2006

      Routine restorative dental care use in 2006

      Complex restorative dental care use in 2006

       

      No

      Yes

      No

      Yes

      No

      Yes

      No

      Yes

      No

      Yes

       

      n = 10,846 (41.7)

       n = 15,147 (58.3)

      n = 11,772 (45.3)

      n = 14,221 (54.7)

      n = 13,119 (50.5)

      n = 12,874 (49.5)

      n = 21,116 (81.2)

      n = 4,877 (18.8)

      n = 23,637 (90.9)

      n = 2,356 (9.1)

      Main predictor variables (chronic condition subgroups)

                

      Respiratory condition

                

       No

      2,017 (18.6)

      2,398 (15.8)*

      2,227 (18.9)

      2,188 (15.4)*

      2,427 (18.5)

      1,988 (15.4)*

      3,656 (17.3)

      759 (15.6)†

      4,078 (17.3)

      337 (14.3)*

       Yes

      8,829 (81.4)

      12,749 (84.2)

      9,545 (81.1)

      12,033 (84.6)

      10,692 (81.5)

      10,886 (84.6)

      17,460 (82.7)

      4,118 (84.4)

      19,559 (82.7)

      2,019 (85.7)

      Ear/nose/throat chronic condition

                

       No

      3,025 (27.9)

      3,940 (26.0)‡

      3,336 (28.3)

      3,629 (25.5)*

      3,751 (28.6)

      3,214 (25.0)*

      5,650 (26.8)

      1,315 (27.0)

      6,433 (27.2)

      532 (22.6)*

       Yes

      7,821 (72.1)

      11,207 (74.0)

      8,436 (71.7)

      10,592 (74.5)

      9,368 (71.4)

      9,660 (75.0)

      15,466 (73.2)

      3,562 (73.0)

      17,204 (72.8)

      1,824 (77.4)

      Digestive condition

                

       No

      6,286 (58.0)

      8,473 (55.9)†

      6,842 (58.1)

      7,917 (55.7)*

      7,555 (57.6)

      7,204 (56.0)‡

      11,937 (56.5)

      2,822 (57.9)

      13,469 (57.0)

      1,290 (54.8)‡

       Yes

      4,560 (42.0)

      6,674 (44.1)

      4,930 (41.9)

      6,304 (44.3)

      5,564 (42.4)

      5,670 (44.0)

      9,179 (43.5)

      2,055 (42.1)

      10,168 (43.0)

      1,066 (45.2)

      Musculoskeletal condition

                

       No

      6,373 (58.8)

      8,384 (55.4)*

      6,891 (58.5)

      7,866 (55.3)*

      7,532 (57.4)

      7,225 (56.1)‡

      12,102 (57.3)

      2,655 (54.4)*

      13,438 (56.9)

      1,319 (56.0)

       Yes

      4,473 (41.2)

      6,763 (44.6)

      4,881 (41.5)

      6,355 (44.7)

      5,587 (42.6)

      5,649 (43.9)

      9,014 (42.7)

      2,222 (45.6)

      10,199 (43.1)

      1,037 (44.0)

      Endocrine condition

                

       No

      8,508 (78.4)

      11,921 (78.7)

      9,249 (78.6)

      11,180 (78.6)

      10,272 (78.3)

      10,157 (78.9)

      16,408 (77.7)

      4,021 (82.4)*

      18,559 (78.5)

      1,870 (79.4)

       Yes

      2,338 (21.6)

      3,226 (21.3)

      2,523 (21.4)

      3,041 (21.4)

      2,847 (21.7)

      2,717 (21.1)

      4,708 (22.3)

      856 (17.6)

      5,078 (21.5)

      486 (20.6)

      Cardiovascular condition

                

       No

      9,743 (89.8)

      13,597 (89.8)

      10,586 (89.9)

      12,754 (89.7)

      11,747 (89.5)

      11,593 (90.0)

      18,938 (89.7)

      4,402 (90.3)

      21,242 (89.9)

      2,098 (89.0)

       Yes

      1,103 (10.2)

      1,550 (10.2)

      1,186 (10.1)

      1,467 (10.3)

      1,372 (10.5)

      1,281 (10.0)

      2,178 (10.3)

      475 (9.7)

      2,395 (10.1)

      258 (11.0)

      Hematologic condition

                

       No

      10,182 (93.9)

      14,143 (93.4)

      11,047 (93.8)

      13,278 (93.4)

      12,307 (93.8)

      12,018 (93.4)

      19,746 (93.5)

      4,579 (93.9)

      22,101 (93.5)

      2,224 (94.4)

       Yes

      664 (6.1)

      1,004 (6.6)

      725 (6.2)

      943 (6.6)

      812 (6.2)

      856 (6.6)

      1,370 (6.5)

      298 (6.1)

      1,536 (6.5)

      132 (5.6)

      Catastrophic neurological condition

                

       No

      10,491 (96.7)

      14,865 (98.1)*

      11,386 (96.7)

      13,970 (98.2)*

      12,721 (97.0)

      12,635 (98.1)*

      20,527 (97.2)

      4,829 (99.0)*

      23,054 (97.5)

      2,302 (97.7)

       Yes

      355 (3.3)

      282 (1.9)

      386 (3.3)

      251 (1.8)

      398 (3.0)

      239 (1.9)

      589 (2.8)

      48 (1.0)

      583 (2.5)

      54 (2.3)

      Craniofacial condition

                

       No

      10,648 (98.2)

      14, 865 (98.1)*

      11,386 (96.7)

      13,964 (98.2)

      12,864 (98.1)

      12,653 (98.3)

      20,703 (98.0)

      4,814 (98.7)‡

      23,198 (98.1)

      2,319 (98.4)

       Yes

      198 (1.8)

      282 (1.9)

      386 (3.3)

      257 (1.8)

      255 (1.9)

      221 (1.7)

      413 (2.0)

      63 (1.3)

      439 (1.9)

      37 (1.6)

      Diabetes

                

       No

      10,690 (98.6)

      14,952 (98.7)

      11,603 (98.6)

      14,039 (98.7)

      12,933 (98.6)

      12,709 (98.7)

      20,822 (98.6)

      4,820 (98.8)

      23,207 (98.6)

      2,335 (99.1)‡

       Yes

      156 (1.4)

      195 (1.3)

      169 (1.4)

      182 (1.3)

      186 (1.4)

      165 (1.3)

      294 (1.4)

      57 (1.2)

      330 (1.4)

      21 (0.9)

      Ascribed factors

                

      Age (years)

                

       3–7

      4,023 (37.1)

      5,621 (37.1)

      4,287 (36.4)

      5,357 (37.7)*

      4,588 (35.0)

      5,056 (39.3)*

      7,969 (37.7)

      1,675 (34.3)*

      8,659 (36.6)

      985 (41.8)*

       8–12

      4,60 2(42.4)

      6,719 (44.4)

      5,042 (42.8)

      6,279 (44.2)

      5,424 (41.3)

      5,897 (45.8)

      9,208 (43.8)

      2,113 (43.3)

      10,218 (43.2)

      1.103(46.8)

       13–14

      2,221 (20.5)

      2,807(18.5)

      2,443 (20.8)

      2,585 (18.12)

      3,107 (23.7)

      1,921 (14.9)

      3,939 (18.7)

      1,089 (22.3)

      4,760 (20.1)

      268 (11.4)

      Sex

                

       Female

      4,178 (38.5)

      6,256 (41.3)*

      4,544 (38.6)

      5,890 (41.4)*

      5,147 (39.2)

      5,287(41.1)^

      8,436 (40.0)

      1,998 (41.0)

      9,483 (40 1)

      951 (40.4)

      Race/ethnicity

                

       White

      7,400(68.2)

      10.855 (71.7)*

      8,069 (68.5)

      10,186 (71.6)*

      9,099 (69.4)

      9,156 (71.1)

      14,696(69.8)

      3,559 (73.0)*

      16,539 (70.0)

      1.716 (72.8)*

       Black

      1,140 (10.5)

      1,232 (8.1)

      1,193 (10.1)

      1,179 (8.3)

      1,303 (9.9)

      1,069 (8.3)

      1,992 (9.4)

      380 (7.8)

      2,220 (9.4)

      152 (6.5)

       Other

      817 (7.5)

      1,127 (7.4)

      883 (7.5)

      1,061 (7.5)*

      948(72)

      996 (7.7)

      1,562(7.4)

      382 (7.8)

      1,751 (7.4)

      193 (8.2)

       Missing Unknown

      1,489 (13.7)

      1,933 (12.8)

      1,627 (13.8)

      1,795 (12.6)

      1,653 (13.5)

      1,653 (12.8)

      2,866 (13.6)

      556 (11.4)

      3,127 (13.2)

      295 (12.5)

      Chronic condition severity

                

       Episodic

      7,504 (69.2)

      10,521 (69.5)*

      8,139 (69.1)

      9,886 (69.5)*

      9,037 (68.9)

      8,988 (69.8)*

      14,488 (68.8)

      3,537 (72.5)

      16,396 (69.4)

      1,629 (69.1)

       Life-Long

      3,019 (27.8)

      4,305 (28.4)

      3,279 (27.9)

      4,045 (28.4)

      3,705 (28.2)

      3,619 (28.1)

      1,992 (9.4)

      1,269 (26.0)

      6,654 (28.2)

      670 (28.4)

       Malignancy

      33 (0.3)

      52 (0.3)

      37 (0.3)

      48 (0.3)

      43 (0.3)

      42 (0.3)

      1,562 (7.4)

      20 (0.4)

      72 (0.3)

      13 (0.6)

       Catastrophic

      290 (2.7)

      269 (1.8)

      317 (2.7)

      242 (1.7)

      334 (2.5)

      225 (1.7)

      2,866 (13.6)

      51 (1.0)

      515 (2.2)

      44 (1.9)

      Proximal factors

                

      Child used preventive medical care in 2005

      9,391 (86.6)

      13,689 (90.4)*

      10,205 (86.7)

      12,875 (90.5)*

      11,437 (87.2)

      11,643 (90.4)*

      18,691 (88.5)

      4,389 (90.0)†

      20,969 (88.7)

      2,111 (89.6)

      Immediate factors

                

      Child had at least one Medicaid- enrolled sibling

      7,200 (66.4)

      10,249 (67.7)‡

      7,816 (66.4)

      9,633 (67.7)‡

      8,677 (66.1)

      8,772 (68.1)†

      13,971 (66.2)

      3,478 (71.3)*

      15,806 (66.9)

      1,643 (69.7)†

      Child had at least one Medicaid- enrolled adult

      6,097 (56.2)

      8,339 (55.1)

      6,528 (55.5)

      7,908 (55.6)

      7,334 (55.9)

      7,102 (55.2)

      11,595 (54.9)

      2,841 (58.3)*

      13,036 (55.2)

      1,400 (59.4)*

      Immediate factor

                

      Rurality

                

       Metropolitan

      5,854 (54.0)

      8,499 (56.1)†

      6,363 (54.1)

      7,990 (56.2)†

      6,958 (53.0)

      7,395 (57.4)*

      11,631 (55.1)

      2,722 (55.8)

      13,007 (55.0)

      1,346 (57.1)

       Urban adjacent to metropolitan

      2,123 (19.6)

      2,855 (18.8)

      2,308 (19.6)

      2,670 (18.8)

      2,607 (19.9)

      2,371 (18.4)

      4,088 (19.4)

      890 (18.2)

      4,545 (19.2)

      433 (18.4)

       Urban non-adjacent to metropolitan

      2,275 (21.0)

      2,962 (19.6)

      2,456 (20.9)

      2,781 (19.6)

      2,802 (21.4)

      2,435 (18.9)

      4,264 (20.2)

      973 (20.0)

      4,783 (20.2)

      454 (19.3)

       Rural

      594 (5.5)

      831 (5.5)

      645 (5.5)

      780 (5.5)

      752 (5.7)

      673 (5.2)

      1,133 (5.4)

      292 (6.0)

      1,302 (5.5)

      123 (5.2)

      Distal factor

                

      Child lived in a dental Health Professional Shortage Area

      7,260 (66.9)

      9,850 (65.0)†

      7,821 (66.4)

      9,289 (65.3)

      8,718 (66.5)

      8,392 (65.2)‡

      13,898 (65.8)

      3,215 (65.9)

      15,566 (65.9)

      1,544 (65.5)

      Pearson Chi Square test to evaluate bivariate relationship between model covariates and each outcome measure.

      * p < .0001.

      † p < .01.

      ‡ p < .05.

      Unadjusted dental utilization in 2006

      About 58.3% of Medicaid-enrolled children with chronic conditions used any dental care in 2006; 54.7% used diagnostic care; 49.5% used preventive care; 18.8% used routine restorative care; and 9.1% used complex restorative care (Table 4).
      Table 4

      Dental utilization rates by chronic condition subgroups and across covariates

      All children with a chronic condition

      N = 25,993

       

      Utilized any dental care in 2006

      Utilized any diagnostic dental care in 2006

      Utilized any preventive dental care in 2006

      Utilized any routine restorative dental care in 2006

      Utilized any complex restorative dental care in 2006

       

      n = 15,147 (58.3)

      n = 14,221 (54.7)

      n = 12,874 (49.6)

      n = 4,877 (18.8)

      n = 2,356 (9.1)

       

      n

      %

      n

      %

      n

      %

      n

      %

      n

      %

      Main predictor variables (chronic condition subgroups)

                

      Respiratory condition

                

       No

      2,398

      54.3*

      2,188

      49.6*

      1,988

      45.0*

      759

      17.2‡

      337

      7.6*

       Yes

      12,749

      59.1

      12,033

      55.8

      10,886

      50.4

      4,118

      19.1

      2,019

      9.4

      Ear/nose/throat chronic condition

                

       No

      3,940

      56.6‡

      3,629

      52.1*

      3,214

      46.1*

      1,315

      18.9

      532

      7.6*

       Yes

      11,207

      58.9

      10,592

      55.7

      9,660

      50.8

      3,562

      18.7

      1,824

      9.6

      Digestive condition

                

       No

      8,473

      57.4‡

      7,917

      53.6*

      7,204

      48.8‡

      2,822

      19.1

      1,290

      8.7‡

       Yes

      6,674

      59.4

      6,304

      56.1

      5,670

      50.5

      2,055

      18.3

      1,066

      9.5

      Musculoskeletal condition

                

       No

      8,384

      56.8*

      7,866

      53.3*

      7,225

      49.0‡

      2,655

      18.0*

      1,319

      8.9

       Yes

      6,763

      60.2

      6,355

      56.6

      5,649

      50.3

      2,222

      19.8

      1,037

      9.2

      Endocrine condition

                

       No

      11,921

      58.4

      11,180

      54.7

      10,157

      49.7

      4,021

      19.7*

      1,870

      9.2

       Yes

      3,226

      58.0

      3,041

      54.7

      2,717

      48.8

      856

      15.4

      486

      8.7

      Cardiovascular condition

                

       No

      13,597

      58.3

      12,754

      54.6

      11,593

      49.7

      4,402

      18.9

      2,098

      9.0

       Yes

      1,550

      58.4

      1,467

      55.3

      1,281

      48.3

      475

      17.9

      258

      9.7

      Hematologic condition

                

       No

      14,143

      58.1

      13,278

      54.6

      12,018

      49.4

      4,579

      18.8

      2,224

      9.1

       Yes

      1,004

      60.1

      943

      56.5

      856

      51.3

      298

      17.9

      132

      7.9

      Catastrophic neurological condition

                

       No

      14,865

      58.6*

      13,970

      55.1*

      12,635

      49.8*

      4,829

      19.0*

      2,303

      9.1

       Yes

      282

      44.3

      251

      39.4

      239

      37.5

      48

      7.5

      54

      8.5

      Cranofacial condition

                

       No

      14,869

      58.3

      13,964

      54.7

      12,635

      49.6

      4,814

      18.9‡

      2,319

      9.1

       Yes

      278

      58.4

      257

      54.0

      239

      46.4

      63

      13.2

      37

      7.8

      Diabetes

                

       No

      14,952

      58.3

      14,039

      54.8

      12,709

      49.6

      4,820

      18.8

      2,335

      9.1‡

       Yes

      195

      55.6

      182

      51.9

      165

      47.0

      57

      16.2

      21

       

      Ascribed factors

                

      Age (years)

                

       3–7

      5,621

      58.3*

      5,357

      55.5*

      5,056

      52.4*

      1,675

      17.4*

      985

      10.2*

       8–12

      6,719

      59.3

      6,279

      55.5

      5,897

      52.1

      2,113

      18.7

      1,103

      9.7

       13–14

      2,807

      55.8

      2,585

      51.4

      1,921

      38.2

      1,089

      21

      268

      5.3

      Sex

                

       Female

      6,256

      60.0*

      5,890

      56.5*

      5,287

      50.7‡

      1,998

      19.1

      951

      9.1

       Male

      8,891

      57.1

      8,331

      53.5

      7,587

      48.8

      2,879

      18.5

      1,405

      9.0

      Race/ethnicity

                

       White

      10,855

      59.5*

      10,186

      55.8*

      9,156

      50.2*

      3,559

      19.5*

      1,716

      9.4*

       Black

      1,232

      51.9

      1,179

      49.7

      1,069

      45.1

      380

      16.0

      152

      6.4

       Other

      1,127

      58.0

      1,061

      54.6

      996

      51.2

      382

      19.7

      193

      9.9

      Missing/Unknown

      1,933

      56.5

      1,795

      52.5

      1,653

      48.3

      556

      16.2

      295

      8.6

      Chronic condition severity

                

       Episodic

      10,521

      58.4*

      9,886

      54.8*

      8,988

      49.9*

      3,537

      19.6*

      1,629

      9.0

       Life-Long

      4,305

      58.8

      4,045

      55.2

      3,619

      49.4

      1,269

      17.3

      670

      9.1

       Malignancy

      52

      61.2

      48

      56.5

      42

      49.4

      20

      23.5

      13

      15.3

       Catastrophic

      269

      48.1

      242

      43.3

      225

      40.3

      51

      9.1

      44

      7.9

      Proximal factors

                

      Child used preventive medical care in 2005

                

       No

      1,458

      50.1*

      1,346

      46.2*

      1,231

      43.3*

      488

      16.8†

      245

      8.4

       Yes

      13,689

      59.3

      12,875

      55.8

      11,643

      50.4

      4,389

      19.0

      2,111

      9.1

      Immediate factors

                

      Child had at least one Medicaid-enrolled sibling

                

       No

      4,898

      57.3‡

      4,588

      53.7‡

      4,102

      48.0‡

      1,399

      16.4*

      713

      8.3†

       Yes

      10,249

      58.7

      9,633

      55.2

      8,772

      50.3

      3,478

      19.9

      1,643

      9.4

      Child had at least one Medicaid-enrolled adult

                

       No

      6,808

      58.9

      6,313

      54.6

      5,772

      49.9

      2,036

      17.6*

      956

      8.3*

       Yes

      8,339

      57.8

      7,908

      54.8

      7,102

      49.2

      2,841

      19.7

      1,400

      9.7

      Immediate factor

                

      Rurality

                

       Metropolitan

      8,499

      59.2†

      7,990

      55.7†

      7,395

      51.5*

      2,722

      19.0

      1,346

      9.4

       Urban adjacent to metropolitan

      2,855

      57.4

      2,670

      53.6

      2,371

      47.6

      890

      17.9

      433

      8.7

       Urban non-adjacent to metropolitan

      2,962

      56.6

      2,781

      53.1

      2,435

      46.5

      973

      18.6

      454

      8.7

       Rural

      831

      58.3

      780

      54.7

      673

      47.2

      292

      20.5

      123

      8.6

      Distal factor

                

      Child lived in a dental Health Professional Shortage Area

                

       No

      5,297

      59.6†

      4,932

      55.5

      4,482

      50.5‡

      1,662

      18.7

      812

      9.1

       Yes

      9,850

      57.6

      9,289

      54.3

      8,392

      49.0

      3,215

      18.8

      1,544

      9.0

      Pearson Chi Square test to evaluate bivariate relationship between each chronic condition and outcome measure.

      * p < .0001.

      † p < .01.

      ‡ p < .05.

      Significantly lower proportions of children with catastrophic neurological conditions used all types of dental care, expect for complex restorative care, for which there was no difference. Larger proportions of children with respiratory, ear/nose/throat, digestive, or musculoskeletal conditions used most types of dental care than did children with chronic conditions without these specific conditions. There was no difference in use across all types of dental care for children with and without diabetes or cardiovascular conditions. Utilization was inconsistent across the different types of dental care for children with hematologic, endocrine, or craniofacial conditions and those children with chronic conditions but without these specific conditions.

      In regards to other variables, significantly larger proportions of children ages 3-7 and 8-12 years utilized all types of dental care, except routine restorative care, than did children ages 13-14 years. Compared to children with the least severe chronic conditions (episodic), larger proportions of children with a malignancy (the second highest severity group) utilized all types of dental care except for preventive dental care whereas children with a catastrophic condition (the most severe chronic condition group) utilized all types of dental care at the lowest rates.

      Larger proportions of children who utilized preventive medical care in 2005 subsequently utilized dental care in 2006. Significantly larger proportions of children with a Medicaid-enrolled sibling utilized all types of dental care, whereas this relationship was statistically significant only for routine and complex restorative dental care for the children with a Medicaid-enrolled adult in the household. Significantly larger proportions of children in metropolitan areas utilized any, preventive, or diagnostic dental care; there were no significant differences by rurality for routine and complex restorative dental care. Finally, children who lived in a dental HPSA were less likely to utilize all types of dental care, though these differences were significant only for any dental care and for preventive dental care.

      Poisson regression models

      The statistical interaction between the two immediate factors, having a Medicaid-enrolled sibling or adult in the household, was statistically significant for routine restorative dental care use across all 10 chronic condition subgroups and for preventive dental care use for some of the chronic condition subgroups. The interaction term was included only in the models in which it was statistically significant. Covariate-adjusted relative risks (RR) corresponding to the 10 chronic condition subgroups are summarized in Table 5. Relative risks for other model covariates are available upon request. Our findings are organized into 4 groupings.
      Table 5

      Covariate-adjusted relative risk (RR) associated with dental use across chronic condition subgroups

       

      Models A

      Model B

      Model C

       

      Utilized any dental care in 2006

      Utilized any diagnostic dental care in 2006

      Utilized any preventive dental care in 2006

      Utilized any routine restorative dental care in 2006

      Utilized any complex restorative dental care in 2006

       

      RR*

      95% CI

      RR

      95% CI

      RR*

      95% CI

      RR†

      95% CI

      RR*

      95% CI

      Main exposure variables (reference group = no)

                

      Respiratory condition

      1.06

      1.03, 1.10

      1.09*

      1.05, 1.13

      1.07

      1.03, 1.11

      1.10

      1.02, 1.19

      1.13

      1.01, 1.26

      Ear/nose/throat condition

      1.02

      0.99, 1.05

      1.04†

      1.01, 1.07

      1.03

      1.01, 1.07

      1.03

      0.97, 1.10

      1.12

      1.01, 1.24

      Digestive condition

      1.03

      1.01, 1.05

      1.03†

      1.01, 1.06

      1.02

      0.99, 1.04

      0.98

      0.93, 1.04

      1.04

      0.96, 1.13

      Musculoskeletal condition

      1.06

      1.04, 1.08

      1.06†

      1.04, 1.09

      1.06

      1.03, 1.08

      1.08

      1.02, 1.13

      1.08

      0.99, 1.17

      Endocrine condition

      0.99

      0.96, 1.02

      0.99†

      0.97, 1.02

      0.97

      0.94, 1.01

      0.83

      0.77, 0.89

      0.92

      0.84, 1.02

      Cardiovascular condition

      1.00

      0.97, 1.04

      1.01†

      0.97, 1.04

      0.98

      0.94, 1.02

      0.98

      0.90, 1.06

      1.09

      0.96, 1.23

      Hematologic condition

      1.04

      0.99, 1.08

      1.03†

      0.99, 1.08

      1.03

      0.98, 1.08

      0.99

      0.89, 1.10

      0.82

      0.70, 0.98

      Catastrophic neurological condition

      0.72

      0.63, 0.81

      0.68*

      0.60, 0.78

      0.73

      0.63, 0.84

      0.48

      0.34, 0.67

      1.11

      0.79, 1.56

      Craniofacial condition

      0.99

      0.92, 1.07

      0.98†

      0.90, 1.06

      0.92

      0.83, 1.01

      0.76

      0.61, 0.96

      0.83

      0.61, 1.13

      Diabetes

      0.95

      0.87, 1.05

      0.95†

      0.86, 1.05

      0.98

      0.87, 1.10

      0.89

      0.71, 1.13

      0.67

      0.44, 1.02

      * Models adjusted for age, sex, race/ethnicity, chronic condition severity, preventive medical care use in 2005, Medicaid-enrolled sibling, Medicaid-enrolled adult, rurality, and living in a dental Health Professional Shortage Area.

      † Models adjusted for age, sex, race/ethnicity, chronic condition severity, preventive medical care use in 2005, Medicaid-enrolled sibling, Medicaid-enrolled adult, statistical interaction between Medicaid-enrolled sibling and Medicaid-enrolled adult, rurality, and living in a dental Health Professional Shortage Area.

      First, children with catastrophic neurological conditions were significantly less likely (RR: 0.48 to 0.73) to use most types of dental care than other children with chronic conditions but without a catastrophic neurological condition. There was no difference in complex restorative dental care use (p = .56). Children with an endocrine condition were slightly less likely to use preventive care and routine restorative dental care than children with chronic conditions but without an endocrine condition (p = .049 and p < .0001; respectively). Children with craniofacial conditions were also less likely to use routine restorative care and children with hematologic conditions were less likely to utilize complex restorative dental care than children with chronic conditions who did not have these particular conditions (p = .02 and p = .03; respectively). In other words, when there were differences, children with catastrophic neurological, endocrine, craniofacial, or hematologic conditions were less likely to utilize dental care than children with chronic conditions but without these specific conditions.

      Second, children with respiratory or musculoskeletal conditions were significantly more likely to use most types of dental care than other children with chronic conditions but without these specific conditions (RR: 1.06 to 1.13 and 1.06 to 1.08; respectively). Among children with chronic conditions, there was no difference in complex restorative dental care use for children with and without musculoskeletal conditions. Children with ear/nose/throat conditions were significantly more likely to use diagnostic, preventive, and complex restorative dental care and there was no difference in use of any or routine restorative dental care. Children with digestive conditions were significantly more likely to use any dental care or diagnostic dental care than other children with chronic conditions without these specific conditions (RR: 1.03 for both types of dental care). There was no difference in use of the other three types of dental care. In other words, when there were differences, children with respiratory, musculoskeletal, ear/nose/throat, or digestive conditions were significantly were more likely to utilize dental care than other children with chronic conditions who did not have these particular chronic conditions.

      Third, there was no significant difference across all five outcome measures for children with diabetes or cardiovascular conditions and children with other types of chronic conditions but without these specific conditions.

      Fourth, in regards to other model covariates there are three sets of findings (data not shown). In the any, diagnostic, and preventive dental care use models (Models A), children in the following subgroups were significantly less likely to use dental care: children ages 13-14 (referent = ages 3-7); males; Blacks (referent = Whites); children with the most severe chronic health conditions; children who did not use preventive medical care in 2005; children without a Medicaid-enrolled sibling; those living in urban areas (referent = metropolitan); and those living in a dental HPSA. In the routine restorative dental care use models (Model B), findings were similar to those from Models A except that children ages 13-14 were more likely to use routine restorative care. There were no significant differences in the risk ratios of routine restorative dental care use across sex and dental HPSA status. For the complex restorative dental care use models (Model C), findings were similar to those from Models A except that there were no significant differences across sex, whether the child used preventive medical care in 2005, whether the child had a Medicaid-enrolled sibling, or whether the child lived in a dental HPSA.

      Discussion

      This is the first known study, to our knowledge, that examined dental care use for Medicaid-enrolled children with chronic conditions with an emphasis on body system-based subgroups. We compared dental care use for Medicaid-enrolled children across 10 chronic condition subgroups. Collectively, our data support two findings that are new to the dental health services literature: (1) dental care use is heterogeneous across chronic condition subgroups; and (2) the determinants of dental care use vary across different types of dental care.

      There were three main findings in regards to specific chronic conditions. The first is that when there were differences children in certain subgroups (e.g., catastrophic neurologic, endocrine, craniofacial, hematologic conditions) were significantly less likely to use dental care than other children with chronic conditions who did not have these particular conditions. Children with these chronic conditions may be at the greatest risk for disparities in dental care use. There are two possible explanations. Many of these children have developmental or acquired cognitive deficits and may have difficulty cooperating during dental visits. Dentists could be less willing to treat these children because of inadequate training [22]. Another explanation is that caregivers may have high levels of stress associated with managing the child’s other systemic health care needs [23], which pushes oral health down on the priority list. It is particularly worrisome that children with catastrophic neurologic conditions were significantly less likely to use preventive dental care. This finding has oral health-related implications especially if the child has a poor diet or behavioral comorbidities that make it difficult for caregivers to brush the child’s teeth regularly with fluoridated toothpaste. These findings appear to conflict with previous work suggesting that Medicaid-enrolled children with intellectual or developmental disabilities are equally as likely to use preventive dental care as those without [13]. A possible explanation for this inconsistency is that children with intellectual or developmental disabilities present with varying degrees of disability. The previous study did not control for this factor while the current study did.

      The second finding is that children with respiratory, musculoskeletal, ear/nose/throat, or digestive conditions were more likely to use most types of dental care compared to children with other types of chronic conditions but without these spe-cific conditions. Children with respiratory conditions (e.g., asthma, cystic fibrosis) may require medications or have enamel defects – factors that increase their risk for dental caries [2426]. Children with musculoskeletal conditions (e.g., arthritis) are also at risk for oral health problems [27]. Children with ear/nose/throat conditions undergo procedures involving the mouth and oral structures, making it plausible that these children receive team-based medical care. These factors may increase caregiver awareness of the importance of dental visits or the likelihood of dental referrals by physicians, though there are no published data to support these hypotheses. Studies from the medical literature report low adherence to inhaler medication for Medicaid-enrolled children with asthma because of caregiver misunderstanding of medications, which makes the former explanation unlikely [28]. We recognize that the risk ratios from our models are small (ranging from 1.02 to 1.13). However, on a population-level, small risk ratios are meaningful, especially when the prevalence of a particular chronic condition is high [29]. The prevalence of respiratory conditions was over 80% and over 40% of children in our study had a musculoskeletal or ear/nose/throat condition. Identifying the mechanisms underlying higher rates of dental use for children with specific types of chronic conditions in future studies may provide insight on how to improve utilization rates for children in other chronic condition subgroups that are not as likely to use dental care.

      The third finding is that there was no difference in dental use for children with diabetes or cardiovascular conditions compared to children with other chronic conditions but without these conditions. Non-significant differences in dental care use may not be a clinically significant problem as long as children are receiving appropriate dental care. However, this is unlikely, especially because these chronic conditions have oral health-related sequelae that make dental visits important. For instance, the link between pediatric diabetes and periodontal disease [30, 31] underscores the importance of regular maintenance and monitoring therapy that might require additional dental visits for children with diabetes. Future studies should investigate whether no differences in dental care use across subgroups actually means that children in these subgroups are receiving appropriate dental care.

      In addition to the findings related to specific chronic conditions, we found that children who used preventive medical care are significantly more likely to use all types of dental care, except for complex restorative care. While there is potential for selection bias [32], this finding reinforces the importance of strengthening the clinical ties between pediatric medicine and dentistry [33]. The mechanisms between use of medical and dental care have not yet been elucidated and require further investigation.

      In term of the research significance of the our study, any dental care use, a standard measure of access to dental care services, may be a more appropriate proxy for use of diagnostic or preventive dental care services rather than routine or complex restorative dental care. When developing oral health intervention and polices, it may be most effective for planners to specify the particular types of dental care the program seeks to improve use of by taking into consideration the differential determinants of dental care. This maximizes the likelihood that children have appropriate access to preventive as well as restorative dental care when needed [34].

      As with all studies, our investigation has strengths and limitations. The primary strength is that we used validated methods, 3M Clinical Risk Groups, to identify children with chronic conditions and to adjust for the severity of those chronic conditions in the models. In addition, we adopted an a priori conceptual model that helped to guide model covariate selection. Finally, we examined use of different types of dental care to obtain a more complete view of dental utilization for children with chronic conditions. The major limitation is the lack of clinical oral health data, which precluded us from determining whether the observed utilization rates were appropriate. This limitation can be addressed with future studies by collecting clinical data and linking these data with dental claims data. Another limitation is that we measured dental use during a single calendar year, which provides a snapshot rather than a longitudinal perspective on dental use. Future studies might examine utilization trends over time across the different chronic condition subgroups. Finally, because this was an observational study, there is potential for residual confounding, which we attempted to minimize by adopting a conceptual model that we used to develop our empirical model. In the future, there is the potential to link claims data with survey data that might be used to collect social and behavioral measures that potentially confound the relationship between chronic conditions and dental use.

      Conclusion

      The goal of pediatric dentistry is to ensure optimal oral health for all children, including children with chronic conditions. An important component of optimal oral health is regular visits to the dentist for preventive dental care and restorative care when needed. Our findings suggest heterogeneous dental utilization patterns for children across different chronic condition subgroups. It is important to note that nearly 42% of children in our study did not utilize any dental care in 2006, which highlights the barriers to dental care that many Medicaid-enrolled children with chronic condition encounter. Some of these barriers may be system-level (e.g., low reimbursement to dentists for treatment) whereas others are environmental/social (e.g., lack of dental offices in areas where Medicaid enrollees live) or behavioral (e.g., dentists’ unwillingness to see Medicaid patients or symptom-driven dental utilization patterns by patients). The next step for researchers is to identify the social and behavioral determinants of particular types of dental care use that exist at these various levels (e.g., ascribed, proximal, immediate, intermediate, distal). This information can then be used to develop and test multilevel clinical interventions aimed at improving dental utilization for specific subgroups of children with chronic conditions who exhibit the greatest disparities in dental care use.

      Declarations

      Acknowledgements

      Thank you to the 3M Corporation for a no-cost Clinical Risk Grouping (CRG) Software license and the Iowa Department of Human Services and the University of Iowa Public Policy Center for access to Iowa Medicaid data. This study was supported in part by NIDCR/NIH Grant Numbers K08DE020856 and TL1RR025016.

      Authors’ Affiliations

      (1)
      Department of Oral Health Sciences, University of Washington School of Dentistry

      References

      1. Institute of Medicine (IOM) and National Research Council (NRC): Improving access to oral health care for vulnerable and underserved populations. The National Academies Press, Washington, DC; 2011.
      2. Newacheck P, McManus M, Fox H, Hung Y, Halfon N: Access to health care for children with special health care needs. Pediatrics 2000, 105:760–766.PubMedView Article
      3. Neff J, Sharp V, Popalisky J, Fitzgibbon T: Using medical billing data to evaluate chronically ill children over time. J Ambul Care Manage 2006, 29:283–290.PubMed
      4. Muldoon J, Neff J, Gay J: Profiling the health service needs of populations using diagnosis-based classification systems. J Ambul Care Manage 1997, 20:1–18.PubMed
      5. Lewis C, Robertson AS, Phelps S: Unmet dental care needs among children with special health care needs: implications for the medical home. Pediatrics 2005, 116:e426-e431.PubMedView Article
      6. Burwell B, Crown W, Drabek J: Children with severe chronic conditions on Medicaid . In . Department of Health and Human Services, Washington, DC: U.S; 1997.
      7. Johnson P: Medicaid: Medicaid: benefits and services—2005. End of Year Issue Brief. Issue Brief Health Policy Track Serv 2005, 31:1–21.
      8. Dubay L, Kenney GM: Health care access and use among low-income children: who fares best? Health Aff (Millwood) 2001, 20:112–121.View Article
      9. Bloom B, Dey AN, Freeman G: Summary health statistics for U.S. children: National Health Interview Survey, 2005. Vital Health Stat 10 2006, 231:1–84.PubMed
      10. Buescher PA, Horton SJ, Devaney BL, Roholt SJ, Lenihan AJ, Whitmire JT, Kotch JB: Differences in use of health services between White and African American children enrolled in Medicaid in North Carolina. Matern Child Health J 2003, 7:45–52.PubMedView Article
      11. Dasanayake AP, Li Y, Chhun N, Bronstein JM, Childers NK: Challenges faced by minority children in obtaining dental care. J Health Care Poor Underserved 2007, 18:779–789.PubMedView Article
      12. Chi DL, Momany ET, Neff J, Jones MP, Warren JJ, Slayton RL, Weber-Gasparoni K, Damiano PC: Impact of chronic condition status and severity on dental utilization for Iowa Medicaid-enrolled children. Med Care 2011, 49:180–192.PubMedView Article
      13. Chi DL, Momany ET, Kuthy RA, Chalmers JM, Damiano PC: Preventive dental utilization for Medicaid-enrolled children in Iowa identified with intellectual and/or developmental disability. J Public Health Dent 2010, 70:35–44.PubMedView Article
      14. Neff J, Clifton H, Park K, Goldenberg C, Popalisky J, Stout JW, Danielson BS: Identifying children with lifelong chronic conditions for care coordination by using hospital discharge data. Acad Pediatr 2010, 10:417–423.PubMedView Article
      15. Patrick DL, Lee RS, Nucci M, Grembowski D, Jolles CZ, Milgrom P: Reducing oral health disparities: a focus on social and cultural determinants. BMC Oral Health 2006, 15:S4.View Article
      16. Pinto-Martin JA, Dunkle M, Earls M, Fliedner D, Landes C: Developmental stages of developmental screening: steps to implementation of a successful program. Am J Public Health 2005, 95:1928–1932.PubMedView Article
      17. Eklund SA, Pittman JL, Clark SJ: Michigan Medicaid's Healthy Kids Dental program: an assessment of the first 12 months. J Am Dent Assoc 2003, 134:1509–1515.PubMed
      18. 3M Health Information Systems: 3M Clinical Risk Grouping Software (for Windows), Version 6.1 . In . 3M Health Information Systems, Wallingford, CT; 2008.
      19. 3M Health Information Systems: All patient refined diagnosis related groups (APR-DRGs), version 20.0, methodology overview . In . 3M Health Information Systems, Wallingford, CT; 2003.
      20. Healthcare Effectiveness Data and Information Set (HEDIS): Technical specifications manual, volume 2. National Committee for Quality Assurance, Washington, DC; 2004.
      21. McNutt LA, Wu C, Xue X, Hafner JP: Estimating the relative risk in cohort studies and clinical trials of common outcomes. Am J Epidemiol 2003, 157:940–943.PubMedView Article
      22. Casamassimo PS, Seale NS, Ruehs K: General dentists' perceptions of educational and treatment issues affecting access to care for children with special health care needs. J Dental Educ 2004, 68:23–28.
      23. Viner-Brown SI, Kim HK: Impact of caring for children with special health care needs on the family: Rhode Island's experience. Matern Child Health J 2005, 9:S59-S66.PubMedView Article
      24. Narang A, Maguire A, Nunn JH, Bush A: Oral health and related factors in cystic fibrosis and other chronic respiratory disorders. Arch Dis Child 2003, 88:702–707.PubMedView Article
      25. Bimstein E, Wilson J, Guelmann M, Primosch RE: The relationship between oral and demographic characteristics of children with asthma. J Clin Pediatr Dent 2006, 31:86–89.PubMed
      26. Widmer RP: Oral health of children with respiratory diseases. Paediatr Respir Rev 2010, 11:226–232.PubMedView Article
      27. Barr T, Carmichael NM, Sándor GK: Juvenile idiopathic arthritis: a chronic pediatric musculoskeletal condition with significant orofacial manifestations. J Can Dent Assoc 2008, 74:813–821.PubMed
      28. Farber HJ, Capra AM, Finkelstein JA, Lozano P, Quesenberry CP, Jensvold NG, Chi FW, Lieu TA: Misunderstanding of asthma controller medications: association with nonadherence. J Asthma 2003, 40:17–25.PubMedView Article
      29. Rutledge T, Loh C: Effect sizes and statistical testing in the determination of clinical significance in behavioral medicine research. Ann Behav Med 2004, 27:138–145.PubMedView Article
      30. Lalla E, Cheng B, Lal S, Tucker S, Greenberg E, Goland R, Lamster IB: Periodontal changes in children and adolescents with diabetes: a case-control study. Diabetes Care 2006, 29:295–299.PubMedView Article
      31. Lalla E, Cheng B, Lal S, Kaplan S, Softness B, Greenberg E, Goland RS, Lamster IB: Diabetes mellitus promotes periodontal destruction in children. J Clin Periodontol 2007, 34:294–298.PubMedView Article
      32. Lee JY, Rozier RG, Norton EC, Vann WF: Addressing selection bias in dental health services research. J Dent Res 2005, 84:942–946.PubMedView Article
      33. Rozier RG, Sutton BK, Bawden JW, Haupt K, Slade GD, King RS: Prevention of early childhood caries in North Carolina medical practices: implications for research and practice. J Dent Educ 2003, 67:876–885.PubMed
      34. Taichman LS, Sohn W, Lim S, Eklund S, Ismail A: Assessing patterns of restorative and preventive care among children enrolled in Medicaid, by type of dental care provider. J Am Dent Assoc 2009, 140:886–889.PubMed
      35. Pre-publication history

        1. The pre-publication history for this paper can be accessed here:http://​www.​biomedcentral.​com/​1472-6831/​12/​28/​prepub

      Copyright

      © Chi and Raklios; licensee BioMed Central Ltd. 2012

      This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://​creativecommons.​org/​licenses/​by/​2.​0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.