Authors
1 Assistant Professor, Head of Geriatric Nursing Department, Mazandaran University of Medical Sciences, Sari, Iran
2 Faculty Member, Department of Community Health Nursing, Mazandaran University of Medical Sciences, Sari, Iran
3 Associate Professor, Department of Statistics, Mazandaran University of Medical Sciences, Sari, Iran
4 MSC Student of Geriatric Nursing, Student Research Committee, Mazandaran University of Medical Sciences, Sari, Iran
Abstract
Background: Oral health has a major role in the health as well as quality of life of older adults.
Objectives: The present study was conducted with the aim to determine the relationship between oral health and cognitive status of the elderly.
Methods: In this descriptive, correlation, cross sectional study, 206 older individuals were selected according to a stratified random sampling method from health centers in Ghaemshahr, Iran between May and October 2016. Data collection tools included cognitive state test (COST), geriatric oral health assessment index (GOHAI), geriatric depression scale, as well as a socio-demographic questionnaire. Dental history and risk factors for cardiovascular diseases were also recorded. Data were analyzed using a logistic regression test.
Results: The mean age was 67.71 ± 7.28 years. Out of all participants, 53% (111 individuals) were women, 81.6% (168 individuals) were married, 50.5% (104 individuals) were overweight, 19.4% (40 individuals) had hypertension, and 30.1% (62 individuals) had concomitant hyper-lipidemia, diabetes, and hypertension. No significant relationship was found between age and oral health; however, the relationship between age and cognitive score was significant (P = 0.002). Tooth loss was the most predictive of the cognitive state. People that lost 5 - 7 teeth were 4.16 times more at risk for cognitive decline. The cognitive score of those with no weight gain was 2.6 times better than those with weight gain. The cognitive state improved by 1.77 times with a higher education level. The cognitive state of participants who better observed oral health was 1.14 times better. Generally, predictive power of the model was 57.2%.
Conclusions: Development of interventions to improve older adults’ oral health seems to be essential.
Keywords
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