Dara M. Shearer

Maternal Oral Health Predicts Their Children’s Caries Experience in Adulthood

The long-term effects of poor maternal oral health are unknown. We determined whether maternal oral health when children were young was a risk indicator for caries experience in adulthood, using oral examination and interview data from age-5 and age-32 assessments in the Dunedin Study, and maternal self-rated oral health data from the age-5 assessment. The main outcome measure was probands’ caries status at age 32. Analyses involved 835 individuals (82.3% of the surviving cohort) dentally examined at both ages, whose mothers were interviewed at the age-5 assessment. There was a consistent gradient in age-32 caries experience across the categories of maternal self-rated oral health status (from the age-5 assessment): it was greatest among the probands whose mothers rated their oral health as “poor” or who were edentulous, and lowest among those whose mothers rated their oral health as “excellent”. Unfavorable maternal self-rated oral health when children are young should be regarded as a risk indicator for poor oral health among offspring as they reach adulthood.

Intergenerational continuity in oral health: a review

Life course research considers not only the influences on health which act during the lifespan but it is also concerned with factors that act across generations. Rarely are genetics or environment solely responsible for producing individual variation; virtually all characteristics are the result of gene-environment interaction. An increasing interest in life course research and gene-environment interactions is reflected in greater awareness of the role of family history and intergenerational continuity in oral health as a practical, inexpensive approach to categorizing genetic risk for many common, preventable disorders of adulthood (including oral disease). Does the health status of one generation have an effect on that of the next? While researchers in recent years have begun to investigate the inter-generational associations between exposures and disease, little research has been carried out (to date) on the long-term biological, behavioural, psychological, social and environmental mechanisms that link oral health and oral disease risk to exposures acting across generations. This narrative review identifies studies which have contributed to highlighting some of the intergenerational factors influencing oral health. However, there is a need for a wider perspective on intergenerational continuity in oral health, along with a careful evaluation of the factors which contribute to the effect. A comprehensive investigation into the nature and extent of intergenerational transmission of oral health is required.

Reexamining the association between smoking and periodontitis in the dunedin study with an enhanced analytical approach.

BACKGROUND Smoking is a major risk factor for periodontal disease. Conventional oral epidemiology approaches have found strong, consistent associations between chronic smoking and periodontal attachment loss (AL) through ages 26, 32, and 38 years, but those statistical methods disregarded the datas hierarchical structure. This study reexamines the association using hierarchical modeling to: 1) overcome the limitations of an earlier approach (trajectory analysis) to the data and 2) determine the robustness of the earlier inferences. METHODS Periodontal examinations were conducted at ages 26, 32, and 38 years in the Dunedin Multidisciplinary Health and Development Study. The number of participants examined at those three ages were 913, 918, and 913, respectively. A generalized linear mixed model with a quasi-binomial approach was used to examine associations between chronic smoking and periodontal AL. RESULTS At ages 26, 32, and 38, smokers had 3.5%, 12.8%, and 23.2% greater AL than non-smokers. Regular cannabis use was associated with greater AL after age 32, but not at age 26. Males had more AL than females. Participants with high plaque scores had consistently greater AL; those who were of persistently low socioeconomic status had higher AL at ages 32 and 38, but not at age 26. The amount of AL in anterior teeth was less than in premolars and molars. Gingival bleeding was associated with higher AL at ages 26, 32, and 38. CONCLUSION The smoking-periodontitis association is observable with hierarchical modeling, providing strong evidence that chronic smoking is a risk factor for periodontitis.

Experiences and perceptions of oral health and oral health care among a sample of older New Zealanders

BACKGROUND  Most research on older peoples oral health has been quantitative. A need for more in-depth understanding of the oral health of that age group has pointed to a need for more qualitative investigations. OBJECTIVE To explore experiences and perceptions of oral health and oral health care among an ethnically-mixed sample of older New Zealanders. METHODS In-depth interviews were conducted with 24 older people in two communities in New Zealands South Island. Thematic analysis of transcribed data was undertaken. RESULTS Three main themes that emerged were: (1) the processes of negotiating a tension between cost and convenience of access; (2) the experiential constraining of oral health maintenance; and (3) trusting in dental professionals. These serve to organise processes such as normalising, justifying and social comparisons that create an equilibrium or tolerance and acceptance of what might otherwise be considered to be relatively poor oral health. CONCLUSIONS We identified a number of shared experiences which affect older peoples ability to maintain their oral health in the face of material and social barriers to oral health care. Because expectations were generally lower, there was greater concordance between experience and expectation, and people tended to be fairly satisfied with their oral health and the care they had received.

High-risk glycated hemoglobin trajectories established by mid-20s: findings from a birth cohort study

Objective To describe the natural history of glycemia (as measured by glycated hemoglobin (HbA1c)) over 12 years using group-based trajectory modeling (GBTM), and to examine baseline predictors of trajectory. Research design and methods HbA1c data collected at ages 26, 32 and 38 in the long-running, prospective Dunedin Multidisciplinary Health and Development Study were used to assign study members (n=893) to trajectories applying GBTM. A generalization of the model allowed the statistical linking of baseline demographic, smoking and anthropometric characteristics to group membership probability. Results Mean HbA1c increased with age, as did prevalence of prediabetes, diabetes and dysglycemia. The greatest increase occurred between ages 26 and 32. Glycemic health status at age 26 predicted glycemic health status at age 38. 3 HbA1c trajectory groups were identified: ‘low’ (n=98, 11.0%); ‘medium’ (n=482, 54.0%); and ‘high’ (n=313, 35.0%) with mean HbA1c of 29.6, 34.1, and 38.7 mmol/mol, respectively, at age 38. High waist circumference (≥880 mm for women and ≥1020 mm for men), high waist-height ratio (≥0.50), and being a smoker at age 26 predicted membership of the least favorable trajectory over the next 12 years. High body mass index (≥30) at age 26 did not predict of trajectory. Conclusions Trajectories of HbA1c are established relatively early in adulthood. HbA1c levels, waist circumference, waist-height ratio, and smoking status at age 26 are valid clinical predictors for future dysglycemic risk. The identification of HbA1c trajectories and their predictors introduces the possibility of an individualized approach to prevention at an earlier stage than is currently done.

Periodontitis and multiple markers of cardiometabolic risk in the fourth decade: A cohort study

OBJECTIVES To examine associations between periodontitis at ages 32 and 38 and a range of early cardiometabolic risk biomarkers at age 38. METHODS Periodontal probing depth and bleeding on probing data collected during the age-32 and age-38 assessments in the Dunedin Multidisciplinary Health and Development Study were used to quantify periodontal inflammatory load. Retinal microvascular abnormalities, endothelial dysfunction, and metabolic syndrome data were collected during the age-38 assessment. Regression models were used to examine associations between these cardiometabolic risk markers and (1) the inflammatory load at age 38 and (2) the change in inflammatory load between ages 32 and 38. RESULTS Periodontal inflammatory load was recorded for 890 Study members at age 32, 891 at age 38, and 856 at both ages. Retinal vessel data were available for 922, endothelial dysfunction data for 909 and metabolic syndrome data for 905 at age 38. Neither the inflammatory load of periodontitis at 38 nor the changes in inflammatory load 32-38 were found to be associated with any of the three cardiometabolic risk markers. CONCLUSIONS Periodontitis was not associated with markers of cardiometabolic risk at this relatively early stage in the life course. It is possible that any influence of periodontitis on cardiometabolic health develops later in life, or periodontitis is not involved in the putative causal chain comprising systemic inflammation, cardiometabolic risk markers, and subsequent cardiovascular risk.