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Noxious family environments in relation to adult and childhood caries Michael F. Lorber, Amy M.S. Slep, Richard E. Heyman, Shu Xu, Ananda P. Dasanayake and Mark S. Wolff JADA 2014;145(9):924-930 10.14219/jada.2014.55 The following resources related to this article are available online at jada.ada.org (this information is current as of December 10, 2014): Updated information and services including high-resolution figures, can be found in the online version of this article at: http://jada.ada.org/content/145/9/924
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ORIGINAL CONTRIBUTIONS
ARTICLE 1
COVER STORY
Noxious family environments in relation to adult and childhood caries Michael F. Lorber, PhD; Amy M.S. Slep, PhD; Richard E. Heyman, PhD; Shu Xu, PhD; Ananda P. Dasanayake, DDS; Mark S. Wolff, DDS
D
ental caries is a disease with a broad range of biological, physical, social and behavioral determinants.1 However, social pathways have received less attention than have the others. We conducted a study to determine whether noxious family environments—those marked by high levels of verbal and physical conflict between family members—are associated with increased caries experience and subjectively poorer oral health–related quality of life in adults and children. Aggression is common in American families. For example, 90 percent of families reported parent-tochild aggression, couple aggression or both in Slep and O’Leary’s2 community sample. Moreover, severe interparental and parent-to-child physical aggression (for example, hitting or kicking) was reported by 24 percent and 13 percent of the couples, respectively. At least some form of emotional aggression (for example, insults and verbal threats) is found in nearly all families.3,4 Noxious family environments typically are chronic stressors.5 Evidence suggests that there are consequences for several child and adult physical health outcomes,6,7 but it is unclear whether oral health is among them. Family oral health may suffer because noxious behaviors create an emotional environment that undermines organized routines such as regular toothbrushing, parents’ socialization of children’s toothbrushing and healthy eating. For example, after intense conflict, a parent may be more preoccupied with his or her own emotional state than with enforcing a child’s toothbrushing or preparing a healthy meal. The stress of family hostility also may promote “stress eating,” which may include sugars and other cariogenic foods.8 Noxious family environments also may affect oral health by means of compromising immune function.
abstract Background. The authors tested hypotheses that more noxious family environments are associated with poorer adult and child oral health. Methods. A community sample of married or cohabiting couples (N = 135) and their elementary school–aged children participated. Dental hygienists determined the number of decayed, missing and filled surfaces via oral examination. Subjective oral health impacts were measured by means of questionnaires completed by the parents and children. The parents completed questionnaires about interparental and parent-to-child physical aggression (for example, pushing) and emotional aggression (for example, derision), as well as harsh discipline. Observers rated the couples’ hostile behavior in laboratory interactions. Results. The extent of women’s and men’s caries experience was associated positively with their partners’ levels of overall noxious behavior toward them. The extent of children’s caries experience was associated positively with the level of their mothers’ emotional aggression toward their partners. Conclusions. Noxious family environments may be implicated in compromised oral health. Future research that replicates and extends these findings can provide the foundation to translate them into preventive interventions. Practical Implications. Noxious family environments may help explain the limitations of routine oral health preventive strategies. Interprofessional strategies that also address the family environment ultimately may prove to be more effective than are single modality approaches. Key Words. Caries; aggression; hostility; family environment; child. JADA 2014;145(9):924-930. doi:10.14219/jada.2014.55
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ORIGINAL CONTRIBUTIONS
Evidence suggests that noxious family environments decrease the body’s ability to fight off pathogens9—perhaps oral bacteria—and trigger low-grade systemic inflammation.6 The role of inflammation in periodontal disease is well established.10 The accruing tissue damage associated with environmentally triggered low-grade systemic inflammation is consistent with Repetti and colleagues’7 “allostatic load” hypothesis. In summary, noxious family environments may compromise oral health by increasing the level of fermentable carbohydrates that feed cariogenic bacteria, compromising the body’s ability to fight these bacteria and increasing oral tissue destruction via inflammatory processes, as well as by preventing the behaviors that buffer these threats. Thus, we hypothesized that for adults, partner hostility (that is, physical aggression, emotional aggression and observed verbal hostility) would be associated with increased caries and poorer oral health–related quality of life, and for children, that both interparental hostility and parent-to-child noxious behavior (physical aggression, emotional aggression and harsh or overreactive parental discipline) would be associated with increased caries and poorer oral health–related quality of life. We expected to see evidence of these associations in objectively measured decayed, missing and filled surfaces and in subjective oral health impacts that reflect a combination of decay and periodontal problems. Taken together, the existing body of research suggests the possibility that noxious family environments affect oral health; however, to our knowledge our investigation is the first to the test this hypothesis directly. MethodS
Participants. The institutional review boards at New York University, New York City, and Stony Brook University, The State University of New York, approved the study, as we collected data at the two separate institutions. In 2010 and 2011, 135 heterosexual couples (mean [standard deviation {SD}] male age, 44.25 [4.93] years; mean [SD] female age, 42.81 [4.59] years) and their children (mean [SD] age, 10.01 [1.59] years; 47 percent girls) residing in the New York City suburbs participated. Ninety-nine percent of the couples were married, and the median family income was $100,000 (interquartile range, $75,000-$147,000). Ninety percent of the fathers and 33 percent of the mothers were employed full time. The study children had a median of two siblings. The mothers and fathers, respectively, self-identified as white (96 percent, 94 percent), black (4 percent, 3 percent), Asian (1 percent, 1 percent) or multiracial (0 percent, 2 percent); 5 percent and 2 percent, respectively, were Latino of any race. The children were 94 percent white, 3 percent black, 3 percent multiracial and 1 percent Asian; 6 percent were Latino of any race. In the 2010 U.S. census data for the study participants’ county of residence, median household income was $87,187, and 32.4 percent
of adults had a bachelor’s degree or higher; 80.8 percent described their race as white, 7.4 percent black and 3.4 percent Asian; and 16.5 percent indicated Latino ethnicity.11 The families in our study had been participants in a previous study.12 We recruited them via telephone by using random-digit dialing (with an oversample of telephone numbers in areas with high levels of minorities provided by a sampling firm). Inclusion criteria for that study were being married or cohabitating for at least one year, one or more parent’s being a biological parent of a 4- to 8-year-old child living at home and having the ability to speak and read English. By means of telephone and mail, we invited all 399 families who participated in the original study to participate in our study. The response rate was 33.83 percent. The 135 families who participated did not differ significantly from the 264 who did not on 23 demographic and family functioning measures that were available in both waves of data collection (shown in eTable 1 in the supplemental data to the online version of this article [found at http://jada.ada. org/content/145/9/924/suppl/DC1]). In our study, families (mother, father and child; n = 117) participated in a 2.5-hour laboratory protocol including questionnaires, observed couples’ conflicts and oral examinations. At least one member of the remaining 18 families (18 mothers, 10 fathers and six sons) completed only the study questionnaires via the Internet. We obtained written informed consent by following the institutional review boards’ guidelines. Dental caries examination and variables. Two dental hygienists under the supervision of one of the authors (M.S.W.) assessed the participants’ oral health by conducting clinical examinations. They conducted visual and noncompression examinations and rated caries with lesions exhibiting exposed dentin (International Caries Detection and Assessment System [ICDAS] stages 4, 5 and 613) as “caries.” They were trained and their ratings were calibrated over two days by one of the authors (M.S.W.). Examinations involved nonexplorer examination under magnification, bright lights and air-drying. Calibration included interrater agreement on two independent examinations of a subset of three adult participants (Cohen k = 0.98 for each rater) and intrarater agreement for examiner A (k = 0.97) and examiner B (k = 1.00). k scores were based on agreement for frank cavitation (ICDAS stages 4, 5 and 6). The dental hygienists were masked to each other’s findings as they conducted their examinations independently and conducted ABBREVIATION KEY. COHIP: Child Oral Health Impact Profile. DMFS: Decayed, missing and filled surfaces. FM: Family Maltreatment. ICDAS: International Caries Detection and Assessment System. OHIP-14: Oral Health Impact Profile (14-item version). PS: Parenting Scale. RMICS: Rapid Marital Interaction Coding System.
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ORIGINAL CONTRIBUTIONS
re-examinations at least several hours after examining three adults who were not study participants. We created an overall caries index for each participant by standardizing each surface’s prevalence measure for decayed, missing and filled surfaces (ICDAS stages 4, 5 and 6 as caries) and computing the mean. In children, we calculated the caries index across both the primary and secondary dentition, reflecting our interest in a decay assessment of the whole mouth. Subjective oral health impacts. Adult oral health impacts. Adults completed the 14-item version of the Oral Health Impact Profile (OHIP-1414). The OHIP-14 measures dysfunction, discomfort and disability associated with oral health problems in the preceding 12 months (for example, oral pain). It has been validated against objective and subjective aspects of oral health.14 We averaged the OHIP-14 item scores (range, 0-4) to form subjective oral health impact variables for men and women (Cronbach α = 0.85 for both sexes). Child oral health impacts. We administered the 38item Child Oral Health Impact Profile (COHIP15) to the child participants. The COHIP has acceptable reliability and both convergent and discriminant validity.16 We conducted a factor analysis and identified an internally consistent (α = 0.90) 15-item oral health impacts meas ure (for example, bleeding gingivae). We averaged the 15 COHIP item scores (range, 0-4) to form a subjective oral health impacts variable. Noxious family environment variables. Overreactive discipline. Parents completed a five-item version of the overreactivity subscale from the Parenting Scale (PS17), a self-reported measure of discipline style validated against home observations and via item response theory methods.12 Each item presented a discipline scenario (for example, “When my child misbehaves”) and asked the parent to identify the point that best described their parenting techniques along a seven-point continuum between two anchors. One anchor reflected a highly overreactive response (for example, “I almost always use bad language”; scored 7) and the other anchor a less overreactive response (for example, “I rarely use bad language or curse”; scored 1). For each parent’s score, we computed averages across the five items; higher scores indicated more overreactivity. Internal consistency was acceptable for mothers (α = 0.78) and fathers (α = 0.68). Observed couple hostility. We observed couples engaged in two seven-minute conversations in which they were instructed to discuss the top area of desired change for each partner and try to resolve it) (see the Appendix in the supplemental data to the online version of this article [found at http://jada.ada.org/content/145/9/924/ suppl/DC1]). The raters coded behaviors by means of the Rapid Marital Interaction Coding System (RMICS), which is an event-based system designed to measure frequencies of behavior and behavioral sequences between intimate partners during conflicts. It has demonstrated
discriminative, convergent, predictive and construct validity.18 The raters were masked as to the study hypotheses. A master rater coded 25 percent of the interactions; interrater agreement was good for this complex type of coding (κ = 0.61). For each participant, we calculated the percentage of his or her total turns being the speaker scored as “hostile” (for example, criticism or angry affect). Partner and parent aggression. Couples individually completed the Family Maltreatment (FM19,20) measure. FM is a computerized measure of physical and emotional aggression between intimate partners and from parent to child in the preceding 12 months. The FM measure involves the use of screener questions and follow-up probes on the basis of the respondent’s previous answers, giving it the flexibility and precision of a structured interview, but allowing anonymity. We computed four scores on the basis of the item averages of the intimate partner emotional aggression subscale (nine items) and physical aggression subscale (14 items) and the parentto-child emotional aggression subscale (nine items) and physical aggression subscale (18 items). Each adult rated intimate partner emotional and physical aggression items on a six-point frequency-based scale that ranged from 0 (never) to 5 (more than 10 times). Each adult rated parent-to-child emotional aggression items from 0 (never) to 4 (once a week to once a day). Each adult rated parent-to-child physical aggression items as present (coded as 1) and absent (coded as 0). We calculated partner aggression scores for each person as the maximum of that person’s self-report of perpetration and the partner’s reports of victimization. Noxious behavior composites. We standardized the scores for FM parent-to-child emotional and physical aggression, as well as scores for the PS overreactivity subscale (that is, converted initial scores to z scores), and averaged them for each parent. This process yielded summary mother-to-child and father-to-child noxious behavior scores. We standardized the FM partner emotional and physical aggression scores, as well as RMICS hostility scores and averaged them to yield female-tomale and male-to-female noxiousness total scores. These a priori composites were supported by the results of principal components analyses, which suggested their unidimensionality. The first components of variance explained an average of 62.9 percent of the variance in the composited variables. The association of each variable with its respective component score (component loadings) ranged from 0.65 to 0.88. Analytic approach. We conducted regression analyses by using a statistical software package (Mplus, Muthén and Muthén, Los Angeles). Cases with missing data were accommodated by full information maximum likelihood estimation, using all available cases for each analysis. To handle distributional skewness, we estimated each parameter’s standard error (SE) with robust maximum likelihood (adult models) and the bias-corrected
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ORIGINAL CONTRIBUTIONS
bootstrap method (child models, 10,000 replicates). We also transformed several variables to decrease nonerroneous outliers’ leveraging of statistical associations. We applied a logarithmic transformation to all couples’ physical and emotional aggression scores and noxious behavior composite scores, as well as children’s caries scores. We applied a square-root transformation to the mother-tochild noxious behavior composite scores. We added constants to variables (that is, score + 1) that had negative values to ensure positive values before transforming the scores. We used these transformed variables in all regression analyses. We added family income and age of the participant whose caries was the outcome variable covariates in all regression models to control for nuisance covariance; there were no hypotheses concerning the covariates. The number of study participants afforded more than 0.80 power to detect correlations 0.24 or greater, relative to a two-tailed α of 0.05. Results
TABLE 1
Descriptive statistics for study variables.* VARIABLE
MEAN (STANDARD DEVIATION)
MINIMUM MAXIMUM
PERCENTILE 25th
50th
75th
Noxious Family Environment Level Female-to-male noxious behavior
−0.014 (0.849)
−0.860
4.590
−0.500
−0.261
0.185
Female-to-male observed hostility
6.602 (7.641)
0.000
35.936
0.000
3.659
10.971
Female-to-male physical aggression
0.066 (0.259)
0.000
1.929
0.000
0.000
0.000
Female-to-male emotional aggression
0.295 (0.447)
0.000
2.222
0.000
0.111
0.444
Male-to-female noxious behavior
−0.014 (0.774)
−0.630
3.740
−0.487
−0.311
0.118
Male-to-female observed hostility
4.661 (7.353)
0.000
34.849
0.000
1.429
5.848
Male-to-female physical aggression
0.044 (0.164)
0.000
1.286
0.000
0.000
0.000
Male-to-female emotional aggression
0.232 (0.416)
0.000
2.111
0.000
0.000
0.333
−0.006 (0.794)
−1.110
3.130
−0.580
−0.180
0.294
Mother-to-child overreactive discipline
3.142 (1.124)
1.000
7.000
2.400
3.000
3.800
Mother-to-child physical aggression
0.067 (0.083)
0.000
0.389
0.000
0.056
0.111
Mother-to-child emotional aggression
0.065 (0.104)
0.000
0.375
0.000
0.000
0.125
−0.007 (0.779)
−1.580
3.250
−0.507
−0.140
0.372
Father-to-child overreactive discipline
3.005 (0.889)
1.000
5.600
2.400
3.000
3.800
Father-to-child physical aggression
0.059 (0.081)
0.000
0.389
0.000
0.000
0.111
Father-to-child emotional aggression
0.055 (0.116)
0.000
0.500
0.000
0.000
0.125
Female oral health impacts
0.418 (0.448)
0.000
1.930
0.071
0.286
0.643
Male oral health impacts
0.309 (0.367)
0.000
1.640
0.000
0.214
0.429
Child oral health impacts
1.140 (0.593)
0.000
2.640
0.727
1.091
1.511
Mother-to-child noxious behavior
Father-to-child noxious behavior
Subjective Oral Health Impacts Level
Caries Examination, Count, DMFS† Index
28.888 (19.750) 0.000 94.000 13.000 25.000 43.750 Female DMFS Descriptive statistics. 26.164 (18.759) 0.000 100.000 13.000 20.000 36.000 Male DMFS Means (SDs), minimums 4.595 (6.590) 0.000 37.000 0.000 2.000 6.000 Child DMFS and maximums for all variables are presented in * The variables are shown in their original metrics before transformation. Table 1. Bivariate associa- † DMFS: Decayed, missing and filled surfaces. tions among the primary study variables and covariates are presented for descriprespective partners’ total scores for noxious behavior tive purposes in eTable 2 in the supplemental data to the toward them (Table 2). An exploratory examination of online version of this article (found at http://jada.ada. these findings (which can be found in eTable 3 in the org/content/145/9/924/suppl/DC1). supplemental data to the online version of this article Adult oral health. Both women’s and men’s caries and [found at http://jada.ada.org/content/145/9/924/suppl/ oral health impacts were associated positively with their DC1]), breaking down the noxious behavior scores into
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ORIGINAL CONTRIBUTIONS
TABLE 2
Association of noxious family environments with adult caries and oral health impacts.* OUTCOME/PREDICTOR
WOMEN β†
SEβ‡
MEN Pβ§
β
SEβ
Pβ
NA
NA
Caries Male-to-female noxious behavior
0.183 0.092 .046 NA §¶
noxious behavior. An exploratory breakdown of these findings (which can be found in eTable 4 in the supplemental data to the online version of this article at http:// jada.ada.org/content/145/9/924/suppl/DC1) revealed that caries in children was associated significantly with female-to-male emotional aggression (P = .017); COHIP impacts were associated significantly with female-to-male hostility (P = .009). Discussion
We found broad support for our hypothesis that noxious family environments are associated with poorer adult Oral Health Impact oral health (controlling for family income). Women with Profile Impacts more caries and/or negative subjective oral health imMale-to-female 0.268 0.089 .003 NA NA NA pacts had male partners who were more aggressive and noxious behavior hostile toward them both physically (as in pushing, grabFemale-to-male NA NA NA 0.255 0.085 .003 bing or hitting) and verbally (as in insulting or interronoxious behavior gating). Men with more caries and/or negative subjective * The results of regression models estimated with robust maximum likelihood; adjusted for covariates (adult’s age and family income). oral health impacts also had female partners who were † β: Standardized regression coefficient. more verbally aggressive and hostile to them. ‡ SEβ: Standard error of β. For children, the associations of noxious family envi§ Pβ: P value of β. ¶ NA: Not applicable. ronments and oral health were less consistent, perhaps because it takes more time for the TABLE 3 effects of a chronically noxious family Association of noxious family environments environment to accrue, which is conwith child caries and oral health impacts.* sistent with the allostatic load process.7 We found PREDICTOR OUTCOME only two significant associations. Caries Child Oral Health Impact Children whose parents reported more Profile Impacts female-to-male emotional aggression β† β B‡ SEB § PB¶ PB B SEB had more caries, and those whose Female-to-Male 0.179 2.499 1.474 .090 0.142 2.543 1.506 .091 Noxious Behavior parents reported greater female-toMale-to-Female 0.113 1.695 1.858 .362 0.052 1.002 1.699 .555 male observed hostility had more Noxious Behavior negative oral health impacts. Moreover, Mother-to-Child 0.036 0.136 0.389 .727 0.072 0.347 0.454 .444 parents’ noxious behavior toward their Noxious Behavior children (for example, hitting, insultFather-to-Child 0.049 0.029 0.068 .668 0.120 0.091 0.085 .283 ing or threatening) was not associated Noxious Behavior significantly with children’s oral health. * The results of regression models with bootstrap method standard errors; adjusted for Ours is the second study that has failed covariates (child’s age and family income). † β: Standardized regression coefficient. to find an association of overreactive ‡ B: Unstandardized regression coefficient. discipline and caries in children.21 § SEB: Standard error of B. ¶ PB: P value of B. The significant effects ranged from small to medium, explaining 3.3 to 10.7 their subcomponents, revealed that women’s caries was percent of the variance in oral health outcomes. To illusassociated significantly with only male-to-female obtrate the effect size, on average women had 3.5 and men served hostility [P = .042]; women’s OHIP impacts were had 5.3 additional carious lesions for every 1.0 SD inassociated significantly with male-to-female physical and crease in their partners’ noxious behavior toward them. emotional aggression (P = .002 and .008, respectively). On average, children had 1.9 additional carious lesions Men’s caries and OHIP impacts were associated signififor every 1.0 SD increase in their mothers’ emotional agcantly with only female-to-male emotional aggression gression toward their partners. The effect sizes we report (P = .027 and .001, respectively). are comparable with other well-known psychosocial risk Child oral health. Caries in children and COHIP factors for caries (for example the r = .22 association beimpacts were not associated significantly with any of the tween poverty and early childhood caries in the National total partner or parent noxious behavior scores (Table 3); Health and Nutrition Examination Survey22). however, both variables were marginally (P = .090 and Our foundational findings linking adults’ and chil .091, respectively) associated with greater female-to-male dren’s oral health to noxious family behaviors do not Female-to-male noxious behavior
NA
NA
NA
0.207 0.081
.010
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ORIGINAL CONTRIBUTIONS
clearly suggest that such behavior causes poor oral health. The association of noxious family environments and oral health likely reflects their historical association over a long period, given the stability of noxious family behavior5 and the fact that the oral health variables we studied reflected the participants’ lifetime history of disease; however, causation is ambiguous. This problem is resistant to experimentation, given that families cannot be assigned randomly to noxious family environments. Prospective prediction of oral health problems stemming from family environments would move dentistry one step closer to establishing causality. Such work would be even more informative if investigators addressed the mechanisms linking noxious behavior and oral health. Our findings suggest only that noxious behavior may affect oral health, not how it could do so. We suggested several possible pathways above that may link noxious behavior with compromised oral health. Establishing the empirical validity of these and other pathways will lend greater plausibility to causality. As an additional limitation, generalizability to the general population of two-parent families is not ensured, given the telephone recruiting methods (although such methods result in more representative samples than does advertising23). Moreover, some extremely aggressive people may have declined participation, potentially truncating the high end of the range of noxious family environments. Furthermore, although the subsample in our study did not exhibit any reliable differences from the previous study’s larger sample,12 the low participation rate left open the possibility that there were unmeasured differences that might have limited generalizability. Future studies with larger, more representative samples will be necessary to confirm our findings. Our findings, if they can be replicated, have public health implications. Existing interventions that aim to prevent oral health problems are primarily biological (for example, fluoridation), performed inside the mouth by dental professionals (for example, placing sealants) or focused on dietary and oral health maintenance behaviors (for example, reducing sugar intake or increasing toothbrushing). However, even among interventions that have demonstrable preventive effects (for example, toothbrushing), the limits of efficacy are well known.24,25 Noxious family behavior eventually may become an additional target of interventions that yield incremental benefits in the prevention of oral health problems, as effective interventions already exist.26 conclusions
Our findings suggest that noxious family environments confer on adults a risk of experiencing poor oral health. The findings relating noxious family environments to oral health in childhood are more equivocal. The results of future research that involves larger representative samples, longitudinal methods and tests of pathways linking
noxious family environments to oral health outcomes can provide the foundation for translating these findings into preventive interventions. Noxious family environments may help explain the limitations of routine oral health preventive strategies.27,28 Interprofessional strategies that also address the family environment ultimately may prove to be more effective than do existing strategies. The results of Brotman and colleagues’ 2012 study29 suggest that changing family environmental factors that have no obvious relevance to a given physical health outcome can yield unexpected and long-term physical health benefits. Perhaps noxious family environment–oral health associations can be leveraged to better prevent oral health problems. n Dr. Lorber is a research scientist, Department of Cariology and Comprehensive Care, College of Dentistry, New York University, 345 E. 24th St., New York, N.Y. 10010, e-mail [email protected]. Address correspondence to Dr. Lorber. Dr. Slep is a professor, Department of Cariology and Comprehensive Care, College of Dentistry, New York University, New York City. Dr. Heyman is a professor, Department of Cariology and Comprehensive Care, College of Dentistry, New York University, New York City. Dr. Xu is a research scientist, Department of Cariology and Comprehensive Care, College of Dentistry, New York University, New York City. Dr. Dasanayake is a professor, Department of Epidemiology and Health Promotion, College of Dentistry, New York University, New York City. Dr. Wolff is a professor, Department of Cariology and Comprehensive Care, College of Dentistry, New York University, New York City. Disclosure. None of the authors reported any disclosures. 1. Fisher-Owens SA, Gansky SA, Platt LJ, et al. Influences on children’s oral health: a conceptual model. Pediatrics 2007;120(3):e510-e520. 2. Slep AM, O’Leary SG. Parent and partner violence in families with young children: rates, patterns, and connections. J Consult Clin Psychol 2005;73(3):435-444. 3. Smith Slep AM, O’Leary SG. Multivariate models of mothers’ and fathers’ aggression toward their children. J Consult Clin Psychol 2007;75(5):739-751. 4. O’Leary KD, Smith Slep AM, O’Leary SG. Multivariate models of men’s and women’s partner aggression. J Consult Clin Psychol 2007;75(5):752-764. 5. Lorber MF, O’Leary KD. Stability, change, and informant variance in newlyweds’ physical aggression: individual and dyadic processes. Aggress Behav 2012;38(1):1-15. 6. Kiecolt-Glaser JK, Loving TJ, Stowell JR, et al. Hostile marital interactions, proinflammatory cytokine production, and wound healing. Arch Gen Psychiatry 2005;62(12):1377-1384. 7. Repetti RL, Taylor SE, Seeman TE. Risky families: family social environments and the mental and physical health of offspring. Psychol Bull 2002;128(2):330-366. 8. Dallman MF, Pecoraro NC, la Fleur SE. Chronic stress and comfort foods: self-medication and abdominal obesity. Brain Behav Immun 2005;19(4):275-280. 9. Wyman PA, Moynihan J, Eberly S, et al. Association of family stress with natural killer cell activity and the frequency of illnesses in children. Arch Pediatr Adolesc Med 2007;161(3):228-234. 10. Kornman KS. Mapping the pathogenesis of periodontitis: a new look. J Periodontol 2008;79(8)(suppl):1560-1568. 12. Lorber MF, Xu S, Slep AMS, Bulling LJ, O’Leary SG. A new look at the psychometrics of the parenting scale through the lens of item response theory (published online ahead of print May 14, 2014.). J Clin Child Adolesc Psychol 2014;43(4):613-626. doi:10.1080/15374416.2014.900717. 13. Pitts NB, Ekstrand KR; International Caries Detection and Assessment System Foundation. International Caries Detection and Assessment System (ICDAS) and its International Caries Classification and Management System (ICCMS): methods for staging of the caries process
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ORIGINAL CONTRIBUTIONS and enabling dentists to manage caries. Community Dent Oral Epidemiol 2013;41(1):e41-e52. doi:10.1111/cdoe.12025. 14. Slade GD. Derivation and validation of a short-form oral health impact profile. Community Dent Oral Epidemiol 1997;25(4):284-290. 15. Slade GD, Reisine ST. The child oral health impact profile: current status and future directions. Community Dent Oral Epidemiol 2007;35(suppl 1):50-53. 16. Broder HL, Wilson-Genderson M. Reliability and convergent and discriminant validity of the Child Oral Health Impact Profile (COHIP Child’s version). Community Dent Oral Epidemiol 2007;35(suppl 1):20-31. 17. Arnold DS, O’Leary SG, Wolff LS, Acker MM. The Parenting Scale: a measure of dysfunctional parenting in discipline situations. Psychol Assess 1993;5(2):137-144. 18. Heyman RE. Rapid marital interaction coding system (RMICS). In: Kerig PK, Baucom DH, eds. Couple Observational Coding Systems. Mahwah, N.J.: Lawrence Erlbaum Associates; 2004:67-94. 19. Foran HM, Slep AM, Heyman RE; United States Air Force Family Advocacy Research Program. Prevalences of intimate partner violence in a representative U.S. Air Force sample. J Consult Clin Psychol 2011;79(3):391-397. 20. Slep AM, Heyman RE, Snarr JD, Foster RE, Linkh DJ, Whitworth JD. Child emotional aggression and abuse: definitions and prevalence (published correction appears in Child Abuse Negl 2012;36[3]:268). Child Abuse Negl 2011;35(10):783-796. 21. Seow WK, Clifford H, Battistutta D, Morawska A, Holcombe T. Case-control study of early childhood caries in Australia. Caries Res
2009;43(1):25-35. 22. Vargas CM, Crall JJ, Schneider DA. Sociodemographic distribution of pediatric dental caries: NHANES III, 1988-1994. JADA 1998;129(9):1229-1238. 23. Gottman JM, Krokoff LJ. Marital interaction and satisfaction: a longitudinal view. J Consult Clin Psychol 1989;57(1):47-52. 24. Smiech-Slomkowska G, Jablonska-Zrobek J. The effect of oral health education on dental plaque development and the level of caries-related Streptococcus mutans and Lactobacillus spp. Eur J Orthod 2007;29(2): 157-160. 25. Marinho VC. Evidence-based effectiveness of topical fluorides. Adv Dent Res 2008;20(1):3-7. 26. Petch JF, Halford WK, Creedy DK, Gamble J. A randomized controlled trial of a couple relationship and coparenting program (Couple CARE for Parents) for high- and low-risk new parents. J Consult Clin Psychol 2012;80(4):662-673. 27. Yevlahova D, Satur J. Models for individual oral health promotion and their effectiveness: a systematic review. Aust Dent J 2009;54(3): 190-197. 28. Horowitz HS. The effectiveness of community water fluoridation in the United States. J Public Health Dent 1996;56(5 special number):253-258. 29. Brotman LM, Dawson-McClure S, Huang KY, et al. Early childhood family intervention and long-term obesity prevention among high-risk minority youth. Pediatrics 2012;129(3):e621-e628. doi:10.1542/ peds.2011-1568.
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Noxious family environments in relation to adult and childhood caries Michael F. Lorber, Amy M.S. Slep, Richard E. Heyman, Shu Xu, Ananda P. Dasanayake and Mark S. Wolff JADA 2014;145(9):924-930 10.14219/jada.2014.55 The following resources related to this article are available online at jada.ada.org (this information is current as of December 10, 2014): Updated information and services including high-resolution figures, can be found in the online version of this article at: http://jada.ada.org/content/145/9/924
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ORIGINAL CONTRIBUTIONS
ARTICLE 1
COVER STORY
Noxious family environments in relation to adult and childhood caries Michael F. Lorber, PhD; Amy M.S. Slep, PhD; Richard E. Heyman, PhD; Shu Xu, PhD; Ananda P. Dasanayake, DDS; Mark S. Wolff, DDS
D
ental caries is a disease with a broad range of biological, physical, social and behavioral determinants.1 However, social pathways have received less attention than have the others. We conducted a study to determine whether noxious family environments—those marked by high levels of verbal and physical conflict between family members—are associated with increased caries experience and subjectively poorer oral health–related quality of life in adults and children. Aggression is common in American families. For example, 90 percent of families reported parent-tochild aggression, couple aggression or both in Slep and O’Leary’s2 community sample. Moreover, severe interparental and parent-to-child physical aggression (for example, hitting or kicking) was reported by 24 percent and 13 percent of the couples, respectively. At least some form of emotional aggression (for example, insults and verbal threats) is found in nearly all families.3,4 Noxious family environments typically are chronic stressors.5 Evidence suggests that there are consequences for several child and adult physical health outcomes,6,7 but it is unclear whether oral health is among them. Family oral health may suffer because noxious behaviors create an emotional environment that undermines organized routines such as regular toothbrushing, parents’ socialization of children’s toothbrushing and healthy eating. For example, after intense conflict, a parent may be more preoccupied with his or her own emotional state than with enforcing a child’s toothbrushing or preparing a healthy meal. The stress of family hostility also may promote “stress eating,” which may include sugars and other cariogenic foods.8 Noxious family environments also may affect oral health by means of compromising immune function.
abstract Background. The authors tested hypotheses that more noxious family environments are associated with poorer adult and child oral health. Methods. A community sample of married or cohabiting couples (N = 135) and their elementary school–aged children participated. Dental hygienists determined the number of decayed, missing and filled surfaces via oral examination. Subjective oral health impacts were measured by means of questionnaires completed by the parents and children. The parents completed questionnaires about interparental and parent-to-child physical aggression (for example, pushing) and emotional aggression (for example, derision), as well as harsh discipline. Observers rated the couples’ hostile behavior in laboratory interactions. Results. The extent of women’s and men’s caries experience was associated positively with their partners’ levels of overall noxious behavior toward them. The extent of children’s caries experience was associated positively with the level of their mothers’ emotional aggression toward their partners. Conclusions. Noxious family environments may be implicated in compromised oral health. Future research that replicates and extends these findings can provide the foundation to translate them into preventive interventions. Practical Implications. Noxious family environments may help explain the limitations of routine oral health preventive strategies. Interprofessional strategies that also address the family environment ultimately may prove to be more effective than are single modality approaches. Key Words. Caries; aggression; hostility; family environment; child. JADA 2014;145(9):924-930. doi:10.14219/jada.2014.55
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ORIGINAL CONTRIBUTIONS
Evidence suggests that noxious family environments decrease the body’s ability to fight off pathogens9—perhaps oral bacteria—and trigger low-grade systemic inflammation.6 The role of inflammation in periodontal disease is well established.10 The accruing tissue damage associated with environmentally triggered low-grade systemic inflammation is consistent with Repetti and colleagues’7 “allostatic load” hypothesis. In summary, noxious family environments may compromise oral health by increasing the level of fermentable carbohydrates that feed cariogenic bacteria, compromising the body’s ability to fight these bacteria and increasing oral tissue destruction via inflammatory processes, as well as by preventing the behaviors that buffer these threats. Thus, we hypothesized that for adults, partner hostility (that is, physical aggression, emotional aggression and observed verbal hostility) would be associated with increased caries and poorer oral health–related quality of life, and for children, that both interparental hostility and parent-to-child noxious behavior (physical aggression, emotional aggression and harsh or overreactive parental discipline) would be associated with increased caries and poorer oral health–related quality of life. We expected to see evidence of these associations in objectively measured decayed, missing and filled surfaces and in subjective oral health impacts that reflect a combination of decay and periodontal problems. Taken together, the existing body of research suggests the possibility that noxious family environments affect oral health; however, to our knowledge our investigation is the first to the test this hypothesis directly. MethodS
Participants. The institutional review boards at New York University, New York City, and Stony Brook University, The State University of New York, approved the study, as we collected data at the two separate institutions. In 2010 and 2011, 135 heterosexual couples (mean [standard deviation {SD}] male age, 44.25 [4.93] years; mean [SD] female age, 42.81 [4.59] years) and their children (mean [SD] age, 10.01 [1.59] years; 47 percent girls) residing in the New York City suburbs participated. Ninety-nine percent of the couples were married, and the median family income was $100,000 (interquartile range, $75,000-$147,000). Ninety percent of the fathers and 33 percent of the mothers were employed full time. The study children had a median of two siblings. The mothers and fathers, respectively, self-identified as white (96 percent, 94 percent), black (4 percent, 3 percent), Asian (1 percent, 1 percent) or multiracial (0 percent, 2 percent); 5 percent and 2 percent, respectively, were Latino of any race. The children were 94 percent white, 3 percent black, 3 percent multiracial and 1 percent Asian; 6 percent were Latino of any race. In the 2010 U.S. census data for the study participants’ county of residence, median household income was $87,187, and 32.4 percent
of adults had a bachelor’s degree or higher; 80.8 percent described their race as white, 7.4 percent black and 3.4 percent Asian; and 16.5 percent indicated Latino ethnicity.11 The families in our study had been participants in a previous study.12 We recruited them via telephone by using random-digit dialing (with an oversample of telephone numbers in areas with high levels of minorities provided by a sampling firm). Inclusion criteria for that study were being married or cohabitating for at least one year, one or more parent’s being a biological parent of a 4- to 8-year-old child living at home and having the ability to speak and read English. By means of telephone and mail, we invited all 399 families who participated in the original study to participate in our study. The response rate was 33.83 percent. The 135 families who participated did not differ significantly from the 264 who did not on 23 demographic and family functioning measures that were available in both waves of data collection (shown in eTable 1 in the supplemental data to the online version of this article [found at http://jada.ada. org/content/145/9/924/suppl/DC1]). In our study, families (mother, father and child; n = 117) participated in a 2.5-hour laboratory protocol including questionnaires, observed couples’ conflicts and oral examinations. At least one member of the remaining 18 families (18 mothers, 10 fathers and six sons) completed only the study questionnaires via the Internet. We obtained written informed consent by following the institutional review boards’ guidelines. Dental caries examination and variables. Two dental hygienists under the supervision of one of the authors (M.S.W.) assessed the participants’ oral health by conducting clinical examinations. They conducted visual and noncompression examinations and rated caries with lesions exhibiting exposed dentin (International Caries Detection and Assessment System [ICDAS] stages 4, 5 and 613) as “caries.” They were trained and their ratings were calibrated over two days by one of the authors (M.S.W.). Examinations involved nonexplorer examination under magnification, bright lights and air-drying. Calibration included interrater agreement on two independent examinations of a subset of three adult participants (Cohen k = 0.98 for each rater) and intrarater agreement for examiner A (k = 0.97) and examiner B (k = 1.00). k scores were based on agreement for frank cavitation (ICDAS stages 4, 5 and 6). The dental hygienists were masked to each other’s findings as they conducted their examinations independently and conducted ABBREVIATION KEY. COHIP: Child Oral Health Impact Profile. DMFS: Decayed, missing and filled surfaces. FM: Family Maltreatment. ICDAS: International Caries Detection and Assessment System. OHIP-14: Oral Health Impact Profile (14-item version). PS: Parenting Scale. RMICS: Rapid Marital Interaction Coding System.
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ORIGINAL CONTRIBUTIONS
re-examinations at least several hours after examining three adults who were not study participants. We created an overall caries index for each participant by standardizing each surface’s prevalence measure for decayed, missing and filled surfaces (ICDAS stages 4, 5 and 6 as caries) and computing the mean. In children, we calculated the caries index across both the primary and secondary dentition, reflecting our interest in a decay assessment of the whole mouth. Subjective oral health impacts. Adult oral health impacts. Adults completed the 14-item version of the Oral Health Impact Profile (OHIP-1414). The OHIP-14 measures dysfunction, discomfort and disability associated with oral health problems in the preceding 12 months (for example, oral pain). It has been validated against objective and subjective aspects of oral health.14 We averaged the OHIP-14 item scores (range, 0-4) to form subjective oral health impact variables for men and women (Cronbach α = 0.85 for both sexes). Child oral health impacts. We administered the 38item Child Oral Health Impact Profile (COHIP15) to the child participants. The COHIP has acceptable reliability and both convergent and discriminant validity.16 We conducted a factor analysis and identified an internally consistent (α = 0.90) 15-item oral health impacts meas ure (for example, bleeding gingivae). We averaged the 15 COHIP item scores (range, 0-4) to form a subjective oral health impacts variable. Noxious family environment variables. Overreactive discipline. Parents completed a five-item version of the overreactivity subscale from the Parenting Scale (PS17), a self-reported measure of discipline style validated against home observations and via item response theory methods.12 Each item presented a discipline scenario (for example, “When my child misbehaves”) and asked the parent to identify the point that best described their parenting techniques along a seven-point continuum between two anchors. One anchor reflected a highly overreactive response (for example, “I almost always use bad language”; scored 7) and the other anchor a less overreactive response (for example, “I rarely use bad language or curse”; scored 1). For each parent’s score, we computed averages across the five items; higher scores indicated more overreactivity. Internal consistency was acceptable for mothers (α = 0.78) and fathers (α = 0.68). Observed couple hostility. We observed couples engaged in two seven-minute conversations in which they were instructed to discuss the top area of desired change for each partner and try to resolve it) (see the Appendix in the supplemental data to the online version of this article [found at http://jada.ada.org/content/145/9/924/ suppl/DC1]). The raters coded behaviors by means of the Rapid Marital Interaction Coding System (RMICS), which is an event-based system designed to measure frequencies of behavior and behavioral sequences between intimate partners during conflicts. It has demonstrated
discriminative, convergent, predictive and construct validity.18 The raters were masked as to the study hypotheses. A master rater coded 25 percent of the interactions; interrater agreement was good for this complex type of coding (κ = 0.61). For each participant, we calculated the percentage of his or her total turns being the speaker scored as “hostile” (for example, criticism or angry affect). Partner and parent aggression. Couples individually completed the Family Maltreatment (FM19,20) measure. FM is a computerized measure of physical and emotional aggression between intimate partners and from parent to child in the preceding 12 months. The FM measure involves the use of screener questions and follow-up probes on the basis of the respondent’s previous answers, giving it the flexibility and precision of a structured interview, but allowing anonymity. We computed four scores on the basis of the item averages of the intimate partner emotional aggression subscale (nine items) and physical aggression subscale (14 items) and the parentto-child emotional aggression subscale (nine items) and physical aggression subscale (18 items). Each adult rated intimate partner emotional and physical aggression items on a six-point frequency-based scale that ranged from 0 (never) to 5 (more than 10 times). Each adult rated parent-to-child emotional aggression items from 0 (never) to 4 (once a week to once a day). Each adult rated parent-to-child physical aggression items as present (coded as 1) and absent (coded as 0). We calculated partner aggression scores for each person as the maximum of that person’s self-report of perpetration and the partner’s reports of victimization. Noxious behavior composites. We standardized the scores for FM parent-to-child emotional and physical aggression, as well as scores for the PS overreactivity subscale (that is, converted initial scores to z scores), and averaged them for each parent. This process yielded summary mother-to-child and father-to-child noxious behavior scores. We standardized the FM partner emotional and physical aggression scores, as well as RMICS hostility scores and averaged them to yield female-tomale and male-to-female noxiousness total scores. These a priori composites were supported by the results of principal components analyses, which suggested their unidimensionality. The first components of variance explained an average of 62.9 percent of the variance in the composited variables. The association of each variable with its respective component score (component loadings) ranged from 0.65 to 0.88. Analytic approach. We conducted regression analyses by using a statistical software package (Mplus, Muthén and Muthén, Los Angeles). Cases with missing data were accommodated by full information maximum likelihood estimation, using all available cases for each analysis. To handle distributional skewness, we estimated each parameter’s standard error (SE) with robust maximum likelihood (adult models) and the bias-corrected
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ORIGINAL CONTRIBUTIONS
bootstrap method (child models, 10,000 replicates). We also transformed several variables to decrease nonerroneous outliers’ leveraging of statistical associations. We applied a logarithmic transformation to all couples’ physical and emotional aggression scores and noxious behavior composite scores, as well as children’s caries scores. We applied a square-root transformation to the mother-tochild noxious behavior composite scores. We added constants to variables (that is, score + 1) that had negative values to ensure positive values before transforming the scores. We used these transformed variables in all regression analyses. We added family income and age of the participant whose caries was the outcome variable covariates in all regression models to control for nuisance covariance; there were no hypotheses concerning the covariates. The number of study participants afforded more than 0.80 power to detect correlations 0.24 or greater, relative to a two-tailed α of 0.05. Results
TABLE 1
Descriptive statistics for study variables.* VARIABLE
MEAN (STANDARD DEVIATION)
MINIMUM MAXIMUM
PERCENTILE 25th
50th
75th
Noxious Family Environment Level Female-to-male noxious behavior
−0.014 (0.849)
−0.860
4.590
−0.500
−0.261
0.185
Female-to-male observed hostility
6.602 (7.641)
0.000
35.936
0.000
3.659
10.971
Female-to-male physical aggression
0.066 (0.259)
0.000
1.929
0.000
0.000
0.000
Female-to-male emotional aggression
0.295 (0.447)
0.000
2.222
0.000
0.111
0.444
Male-to-female noxious behavior
−0.014 (0.774)
−0.630
3.740
−0.487
−0.311
0.118
Male-to-female observed hostility
4.661 (7.353)
0.000
34.849
0.000
1.429
5.848
Male-to-female physical aggression
0.044 (0.164)
0.000
1.286
0.000
0.000
0.000
Male-to-female emotional aggression
0.232 (0.416)
0.000
2.111
0.000
0.000
0.333
−0.006 (0.794)
−1.110
3.130
−0.580
−0.180
0.294
Mother-to-child overreactive discipline
3.142 (1.124)
1.000
7.000
2.400
3.000
3.800
Mother-to-child physical aggression
0.067 (0.083)
0.000
0.389
0.000
0.056
0.111
Mother-to-child emotional aggression
0.065 (0.104)
0.000
0.375
0.000
0.000
0.125
−0.007 (0.779)
−1.580
3.250
−0.507
−0.140
0.372
Father-to-child overreactive discipline
3.005 (0.889)
1.000
5.600
2.400
3.000
3.800
Father-to-child physical aggression
0.059 (0.081)
0.000
0.389
0.000
0.000
0.111
Father-to-child emotional aggression
0.055 (0.116)
0.000
0.500
0.000
0.000
0.125
Female oral health impacts
0.418 (0.448)
0.000
1.930
0.071
0.286
0.643
Male oral health impacts
0.309 (0.367)
0.000
1.640
0.000
0.214
0.429
Child oral health impacts
1.140 (0.593)
0.000
2.640
0.727
1.091
1.511
Mother-to-child noxious behavior
Father-to-child noxious behavior
Subjective Oral Health Impacts Level
Caries Examination, Count, DMFS† Index
28.888 (19.750) 0.000 94.000 13.000 25.000 43.750 Female DMFS Descriptive statistics. 26.164 (18.759) 0.000 100.000 13.000 20.000 36.000 Male DMFS Means (SDs), minimums 4.595 (6.590) 0.000 37.000 0.000 2.000 6.000 Child DMFS and maximums for all variables are presented in * The variables are shown in their original metrics before transformation. Table 1. Bivariate associa- † DMFS: Decayed, missing and filled surfaces. tions among the primary study variables and covariates are presented for descriprespective partners’ total scores for noxious behavior tive purposes in eTable 2 in the supplemental data to the toward them (Table 2). An exploratory examination of online version of this article (found at http://jada.ada. these findings (which can be found in eTable 3 in the org/content/145/9/924/suppl/DC1). supplemental data to the online version of this article Adult oral health. Both women’s and men’s caries and [found at http://jada.ada.org/content/145/9/924/suppl/ oral health impacts were associated positively with their DC1]), breaking down the noxious behavior scores into
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ORIGINAL CONTRIBUTIONS
TABLE 2
Association of noxious family environments with adult caries and oral health impacts.* OUTCOME/PREDICTOR
WOMEN β†
SEβ‡
MEN Pβ§
β
SEβ
Pβ
NA
NA
Caries Male-to-female noxious behavior
0.183 0.092 .046 NA §¶
noxious behavior. An exploratory breakdown of these findings (which can be found in eTable 4 in the supplemental data to the online version of this article at http:// jada.ada.org/content/145/9/924/suppl/DC1) revealed that caries in children was associated significantly with female-to-male emotional aggression (P = .017); COHIP impacts were associated significantly with female-to-male hostility (P = .009). Discussion
We found broad support for our hypothesis that noxious family environments are associated with poorer adult Oral Health Impact oral health (controlling for family income). Women with Profile Impacts more caries and/or negative subjective oral health imMale-to-female 0.268 0.089 .003 NA NA NA pacts had male partners who were more aggressive and noxious behavior hostile toward them both physically (as in pushing, grabFemale-to-male NA NA NA 0.255 0.085 .003 bing or hitting) and verbally (as in insulting or interronoxious behavior gating). Men with more caries and/or negative subjective * The results of regression models estimated with robust maximum likelihood; adjusted for covariates (adult’s age and family income). oral health impacts also had female partners who were † β: Standardized regression coefficient. more verbally aggressive and hostile to them. ‡ SEβ: Standard error of β. For children, the associations of noxious family envi§ Pβ: P value of β. ¶ NA: Not applicable. ronments and oral health were less consistent, perhaps because it takes more time for the TABLE 3 effects of a chronically noxious family Association of noxious family environments environment to accrue, which is conwith child caries and oral health impacts.* sistent with the allostatic load process.7 We found PREDICTOR OUTCOME only two significant associations. Caries Child Oral Health Impact Children whose parents reported more Profile Impacts female-to-male emotional aggression β† β B‡ SEB § PB¶ PB B SEB had more caries, and those whose Female-to-Male 0.179 2.499 1.474 .090 0.142 2.543 1.506 .091 Noxious Behavior parents reported greater female-toMale-to-Female 0.113 1.695 1.858 .362 0.052 1.002 1.699 .555 male observed hostility had more Noxious Behavior negative oral health impacts. Moreover, Mother-to-Child 0.036 0.136 0.389 .727 0.072 0.347 0.454 .444 parents’ noxious behavior toward their Noxious Behavior children (for example, hitting, insultFather-to-Child 0.049 0.029 0.068 .668 0.120 0.091 0.085 .283 ing or threatening) was not associated Noxious Behavior significantly with children’s oral health. * The results of regression models with bootstrap method standard errors; adjusted for Ours is the second study that has failed covariates (child’s age and family income). † β: Standardized regression coefficient. to find an association of overreactive ‡ B: Unstandardized regression coefficient. discipline and caries in children.21 § SEB: Standard error of B. ¶ PB: P value of B. The significant effects ranged from small to medium, explaining 3.3 to 10.7 their subcomponents, revealed that women’s caries was percent of the variance in oral health outcomes. To illusassociated significantly with only male-to-female obtrate the effect size, on average women had 3.5 and men served hostility [P = .042]; women’s OHIP impacts were had 5.3 additional carious lesions for every 1.0 SD inassociated significantly with male-to-female physical and crease in their partners’ noxious behavior toward them. emotional aggression (P = .002 and .008, respectively). On average, children had 1.9 additional carious lesions Men’s caries and OHIP impacts were associated signififor every 1.0 SD increase in their mothers’ emotional agcantly with only female-to-male emotional aggression gression toward their partners. The effect sizes we report (P = .027 and .001, respectively). are comparable with other well-known psychosocial risk Child oral health. Caries in children and COHIP factors for caries (for example the r = .22 association beimpacts were not associated significantly with any of the tween poverty and early childhood caries in the National total partner or parent noxious behavior scores (Table 3); Health and Nutrition Examination Survey22). however, both variables were marginally (P = .090 and Our foundational findings linking adults’ and chil .091, respectively) associated with greater female-to-male dren’s oral health to noxious family behaviors do not Female-to-male noxious behavior
NA
NA
NA
0.207 0.081
.010
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ORIGINAL CONTRIBUTIONS
clearly suggest that such behavior causes poor oral health. The association of noxious family environments and oral health likely reflects their historical association over a long period, given the stability of noxious family behavior5 and the fact that the oral health variables we studied reflected the participants’ lifetime history of disease; however, causation is ambiguous. This problem is resistant to experimentation, given that families cannot be assigned randomly to noxious family environments. Prospective prediction of oral health problems stemming from family environments would move dentistry one step closer to establishing causality. Such work would be even more informative if investigators addressed the mechanisms linking noxious behavior and oral health. Our findings suggest only that noxious behavior may affect oral health, not how it could do so. We suggested several possible pathways above that may link noxious behavior with compromised oral health. Establishing the empirical validity of these and other pathways will lend greater plausibility to causality. As an additional limitation, generalizability to the general population of two-parent families is not ensured, given the telephone recruiting methods (although such methods result in more representative samples than does advertising23). Moreover, some extremely aggressive people may have declined participation, potentially truncating the high end of the range of noxious family environments. Furthermore, although the subsample in our study did not exhibit any reliable differences from the previous study’s larger sample,12 the low participation rate left open the possibility that there were unmeasured differences that might have limited generalizability. Future studies with larger, more representative samples will be necessary to confirm our findings. Our findings, if they can be replicated, have public health implications. Existing interventions that aim to prevent oral health problems are primarily biological (for example, fluoridation), performed inside the mouth by dental professionals (for example, placing sealants) or focused on dietary and oral health maintenance behaviors (for example, reducing sugar intake or increasing toothbrushing). However, even among interventions that have demonstrable preventive effects (for example, toothbrushing), the limits of efficacy are well known.24,25 Noxious family behavior eventually may become an additional target of interventions that yield incremental benefits in the prevention of oral health problems, as effective interventions already exist.26 conclusions
Our findings suggest that noxious family environments confer on adults a risk of experiencing poor oral health. The findings relating noxious family environments to oral health in childhood are more equivocal. The results of future research that involves larger representative samples, longitudinal methods and tests of pathways linking
noxious family environments to oral health outcomes can provide the foundation for translating these findings into preventive interventions. Noxious family environments may help explain the limitations of routine oral health preventive strategies.27,28 Interprofessional strategies that also address the family environment ultimately may prove to be more effective than do existing strategies. The results of Brotman and colleagues’ 2012 study29 suggest that changing family environmental factors that have no obvious relevance to a given physical health outcome can yield unexpected and long-term physical health benefits. Perhaps noxious family environment–oral health associations can be leveraged to better prevent oral health problems. n Dr. Lorber is a research scientist, Department of Cariology and Comprehensive Care, College of Dentistry, New York University, 345 E. 24th St., New York, N.Y. 10010, e-mail [email protected]. Address correspondence to Dr. Lorber. Dr. Slep is a professor, Department of Cariology and Comprehensive Care, College of Dentistry, New York University, New York City. Dr. Heyman is a professor, Department of Cariology and Comprehensive Care, College of Dentistry, New York University, New York City. Dr. Xu is a research scientist, Department of Cariology and Comprehensive Care, College of Dentistry, New York University, New York City. Dr. Dasanayake is a professor, Department of Epidemiology and Health Promotion, College of Dentistry, New York University, New York City. Dr. Wolff is a professor, Department of Cariology and Comprehensive Care, College of Dentistry, New York University, New York City. Disclosure. None of the authors reported any disclosures. 1. Fisher-Owens SA, Gansky SA, Platt LJ, et al. Influences on children’s oral health: a conceptual model. Pediatrics 2007;120(3):e510-e520. 2. Slep AM, O’Leary SG. Parent and partner violence in families with young children: rates, patterns, and connections. J Consult Clin Psychol 2005;73(3):435-444. 3. Smith Slep AM, O’Leary SG. Multivariate models of mothers’ and fathers’ aggression toward their children. J Consult Clin Psychol 2007;75(5):739-751. 4. O’Leary KD, Smith Slep AM, O’Leary SG. Multivariate models of men’s and women’s partner aggression. J Consult Clin Psychol 2007;75(5):752-764. 5. Lorber MF, O’Leary KD. Stability, change, and informant variance in newlyweds’ physical aggression: individual and dyadic processes. Aggress Behav 2012;38(1):1-15. 6. Kiecolt-Glaser JK, Loving TJ, Stowell JR, et al. Hostile marital interactions, proinflammatory cytokine production, and wound healing. Arch Gen Psychiatry 2005;62(12):1377-1384. 7. Repetti RL, Taylor SE, Seeman TE. Risky families: family social environments and the mental and physical health of offspring. Psychol Bull 2002;128(2):330-366. 8. Dallman MF, Pecoraro NC, la Fleur SE. Chronic stress and comfort foods: self-medication and abdominal obesity. Brain Behav Immun 2005;19(4):275-280. 9. Wyman PA, Moynihan J, Eberly S, et al. Association of family stress with natural killer cell activity and the frequency of illnesses in children. Arch Pediatr Adolesc Med 2007;161(3):228-234. 10. Kornman KS. Mapping the pathogenesis of periodontitis: a new look. J Periodontol 2008;79(8)(suppl):1560-1568. 12. Lorber MF, Xu S, Slep AMS, Bulling LJ, O’Leary SG. A new look at the psychometrics of the parenting scale through the lens of item response theory (published online ahead of print May 14, 2014.). J Clin Child Adolesc Psychol 2014;43(4):613-626. doi:10.1080/15374416.2014.900717. 13. Pitts NB, Ekstrand KR; International Caries Detection and Assessment System Foundation. International Caries Detection and Assessment System (ICDAS) and its International Caries Classification and Management System (ICCMS): methods for staging of the caries process
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ORIGINAL CONTRIBUTIONS and enabling dentists to manage caries. Community Dent Oral Epidemiol 2013;41(1):e41-e52. doi:10.1111/cdoe.12025. 14. Slade GD. Derivation and validation of a short-form oral health impact profile. Community Dent Oral Epidemiol 1997;25(4):284-290. 15. Slade GD, Reisine ST. The child oral health impact profile: current status and future directions. Community Dent Oral Epidemiol 2007;35(suppl 1):50-53. 16. Broder HL, Wilson-Genderson M. Reliability and convergent and discriminant validity of the Child Oral Health Impact Profile (COHIP Child’s version). Community Dent Oral Epidemiol 2007;35(suppl 1):20-31. 17. Arnold DS, O’Leary SG, Wolff LS, Acker MM. The Parenting Scale: a measure of dysfunctional parenting in discipline situations. Psychol Assess 1993;5(2):137-144. 18. Heyman RE. Rapid marital interaction coding system (RMICS). In: Kerig PK, Baucom DH, eds. Couple Observational Coding Systems. Mahwah, N.J.: Lawrence Erlbaum Associates; 2004:67-94. 19. Foran HM, Slep AM, Heyman RE; United States Air Force Family Advocacy Research Program. Prevalences of intimate partner violence in a representative U.S. Air Force sample. J Consult Clin Psychol 2011;79(3):391-397. 20. Slep AM, Heyman RE, Snarr JD, Foster RE, Linkh DJ, Whitworth JD. Child emotional aggression and abuse: definitions and prevalence (published correction appears in Child Abuse Negl 2012;36[3]:268). Child Abuse Negl 2011;35(10):783-796. 21. Seow WK, Clifford H, Battistutta D, Morawska A, Holcombe T. Case-control study of early childhood caries in Australia. Caries Res
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