| Literature DB >> 26751953 |
Noha Gomaa1,2, Michael Glogauer3, Howard Tenenbaum3, Arjumand Siddiqi4, Carlos Quiñonez1,2.
Abstract
Oral diseases constitute a major worldwide public health problem, with their burden concentrating in socially disadvantaged and less affluent groups of the population, resulting in significant oral health inequalities. Biomedical and behavioural approaches have proven relatively ineffective in reducing these inequalities, and have potentially increased the health gap between social groups. Some suggest this stems from a lack of understanding of how the social and psychosocial contexts in which behavioural and biological changes occur influence oral disease. To unravel the pathways through which social factors affect oral health outcomes, a better understanding is thus needed of how the social 'gets under the skin,' or becomes embodied, to alter the biological. In this paper, we present the current knowledge on the interplay between social and biological factors in oral disease. We first provide an overview of the process of embodiment in chronic disease and then evaluate the evidence on embodiment in oral disease by reviewing published studies in this area. Results show that, in periodontal disease, income, education and perceived stress are correlated with elevated levels of stress hormones, disrupted immune biomarkers and increased allostatic load. Similarly, socioeconomic position and increased financial stress are related to increased stress hormones and cariogenic bacterial counts in dental caries. Based on these results, we propose a dynamic model depicting social-biological interactions that illustrates potential interdependencies between social and biological factors that lead to poor oral health. This work and the proposed model may aid in developing a better understanding of the causes of oral health inequalities and implicate the importance of addressing the social determinants of oral health in innovating public health interventions.Entities:
Mesh:
Year: 2016 PMID: 26751953 PMCID: PMC4709106 DOI: 10.1371/journal.pone.0146218
Source DB: PubMed Journal: PLoS One ISSN: 1932-6203 Impact factor: 3.240
Keywords, MESH terms, inclusion and exclusion criteria.
| Exposure | Social, socioeconomic, psychosocial. Keywords: stress, psychosocial, psychosocial stress, psychological stress, socioeconomic status, income, education |
| Outcome | Oral disease, periodontitis, dental caries, changes in biological markers. Keywords: oral health, oral disease, periodont*, dental caries, tooth loss, immun*, biological markers, oral health inequalities, oral health disparities |
| Study Design | No restrictions on study-designs were applied |
| Inclusion criteria | Empirical studies, English language, human studies Stressor had to be chronic, psychosocial in nature (i.e. not physical stress) Including at least one social factors and one biological marker (e.g. immune marker) |
| Exclusion criteria | Non-empirical studies Studies assessing acute oral conditions, dental trauma, oral cancer |
Summary of key studies exploring the relationship between structural/social, psychosocial and biological factors in oral disease.
| Authors | Study design | Oral health outcome | Population | Structural/social factors | Psychosocial factors | Behavioural factors | Biological marker(s) | Conclusions |
|---|---|---|---|---|---|---|---|---|
| Moss et al. [ | Case-control | Periodontitis (plaque, CAL, BOP, PD) | Participants from Erie County Risk Factor Study (71 cases, 77 controls), U.S.A | − | Daily Strains (job stain, financial strain, spouse strain, strain related to parenting children); psychological distress and coping style. Strain Scale; Brief Symptom Inventory; COPE inventory | Smoking | Antibody titres for periodontal pathogens | Depression as marker for social isolation was associated with elevated levels of antibody titres for periodontal disease at baseline and after 1-year follow-up |
| Giannopoulou et al. [ | Case-control | Gingivitis, AP, EOP (PI, BOP, SUP) | Participants were selected from a private practice limited to periodontics in Athens, Greece (80) | − | Perceived stress, Modified and Perceived Stress Scale (MAPS) | Smoking | IL-1b, IL-4, IL-6 and IL-8 in the GCF | IL-4, IL-6 and IL-8 were significantly correlated with to smoking while stress was associated with IL-1b, IL-6 and IL-8 levels |
| Mengel et al. [ | Case-control | AGP, ALP, CGP (GI, PI, CAL) | Patients from periodontology department, Philips-University, Marburg, Germany (40 cases; 40 controls) | − | Job-related stress, family-related stress, attitude to life. Questionnaire (non-validated) | Smoking | IL-1β, IL-6, cortisol in serum | No correlation between immunological markers, cortisol and the registered stress values. Patients with untreated AGP showed a pessimistic attitude to life and elevated serum IL-6. Sample size was too small for generalizable conclusions. Method of stress assessment was unvalidated and unstandardized |
| Johannsen et al.[ | Case-control | Periodontitis (plaque, GI, CAL, PD); Number of teeth | Women on long-term sick leave for depression (20 cases, 29 controls), Stockholm, Sweden | − | Job-stress related depression (DSM-IV) | Smoking | IL-1β, IL-6, MMP-8, MMP-9 | Women on long-term sick leave for depression had more plaque accumulation and higher concentrations of GCF IL-6 than controls, suggesting relationships between depressive symptoms and immune changes |
| Sabbah et al.[ | Cross-sectional | Periodontitis (CAL, GB) | NHANES III (1988–1994), U.S.A | Socioeconomic position (poverty: income; education) | − | Smoking | Allostatic load | Allostatic load partly explains socioeconomic gradients in periodontal disease and ischaemic heart disease, suggesting a common stress pathway to both conditions. |
| Borrell et al. [ | Cross-sectional | Periodontitis (CAL, PD) | NHANES (1999–2004), United States | Socioeconomic position (annual family income, PIR) | − | Smoking | Allostatic load | Allostatic load increases the probability of periodontitis. This association is explained by race/ethnicity. |
| Boyce et al. [ | Cross-sectional | Dental Caries (dmfs, DMFS) | Kindergarten children from the Peers and Wellness Study (n = 94), East San Francisco Bay Area, California, U.S.A | Socioeconomic status (parent-reported highest household education level) | Family financial stressors (FSS) | − | Basal salivary cortisol, salivary cortisol reactivity, oral cariogenic bacteria | Low SES, higher basal salivary cortisol and larger numbers of cariogenic bacteria were each significantly and independently associated with caries. Higher salivary cortisol reactivity was associated with thinner, softer enamel surfaces in exfoliated teeth. Highest rates of dental pathology were found among children with the combination of elevated salivary cortisol expression and high counts of cariogenic bacteria. |
| Bakri et al. [ | Longitudinal (6 months follow-up) | Periodontitis (PD, BOP) | 45 patients with periodontitis in need of NPT, Sheffield, UK | − | Perceived stress (PSS) | Smoking | Salivary cortisol, ICTP, elastase activity in GCF | Patients under psychosocial stress had increased elastase levels and poorer outcomes following NPT |
| Buchwald et al. [ | Longitudinal (5-year follow-up) | Periodontitis (CAL); Number of teeth | 3300 participants from Study of Health in Pomerania (SHIP), Germany | Socioeconomic status (education, occupation, household income), marital status | − | Smoking, tooth-brushing, last dental visit | BMI, CRP | Accumulation of socioeconomic and behavioural factors augmented periodontal disease progression and systemic levels of CRP |
| Masterson & Sabbah [ | Cross-sectional | Caries in children | 1184 mother-child pairs usingNHANES III | Socioeconomic status (PIR) | − | Maternal care-taking behaviours | Maternal allostatic load | Maternal allostatic load is associated with caries in children and is linked to health-related maternal behaviours |
Quality of studies included using National Institute of Health (NIH) quality assessment tool for observational and cross-sectional studies.
| Criteria | Moss et al. | Giannopoulou et al. | Mengel et al. | Johannsen et al. | Sabbah et al. | Borrell et al. | Boyce et al. | Bakri et al. | Buchwald et al. | Masterson et al. |
|---|---|---|---|---|---|---|---|---|---|---|
| Was the research question or objective in this paper clearly stated and appropriate? | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 |
| Was the study population clearly specified and defined? | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 |
| Did the authors include a sample size justification? | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 0 |
| Were controls selected or recruited from the same or similar population that gave rise to the cases (including the same timeframe)? | 1 | 1 | 1 | 1 | NA | NA | NA | 1 | 1 | NA |
| Were the definitions, inclusion and exclusion criteria, algorithms or processes used to identify or select cases and controls valid, reliable, and implemented consistently across all study participants? | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 |
| Were the cases clearly defined and differentiated from controls? | 1 | 1 | 1 | 1 | NA | NA | NA | 1 | NA | NA |
| If less than 100 percent of eligible cases and/or controls were selected for the study, were the cases and/or controls randomly selected from those eligible? | 0 | 0 | 0 | 0 | NA | NA | NA | 0 | NA | NA |
| Was there use of concurrent controls? | 1 | 1 | 1 | 1 | NA | NA | NA | 1 | NA | NA |
| Were the investigators able to confirm that the exposure/risk occurred prior to the development of the condition or event that defined a participant as a case? | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| Were the measures of exposure/risk clearly defined, valid, reliable, and implemented consistently (including the same time period) across all study participants? | 1 | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 1 |
| Were the assessors of exposure/risk blinded to the case or control status of participants? | 0 | 0 | 0 | 0 | NA | NA | NR | 1 | NA | NA |
| Were key potential confounding variables measured and adjusted statistically in the analyses? If matching was used, did the investigators account for matching during study analysis? | 1 | 0 | 1 | 0 | 1 | 1 | 0 | 1 | 1 | 1 |
| 1 = Yes; 0 = No; NA = not applicable, NR = not reported |
Fig 1Dynamic conceptual model of social-biological interactions.
The model demonstrates the interdependent relationships between different variables involved in oral disease. Blue lines are relationships derived from studies in Table 2. Orange lines represent hypothetical relationships. (R): reinforcing loops; signs (+/-) on arrowheads: polarity of the relationship between variables.