Jing Kang1, Bei Wu2, David Bunce3, Mark Ide4, Vishal R Aggarwal5, Sue Pavitt6, Jianhua Wu6,7. 1. Division of Oral Biology, School of Dentistry, University of Leeds, Leeds, UK. 2. Rory Meyers College of Nursing, Hartford Institute of Geriatric Nursing, New York University, New York, USA. 3. School of Psychology, Faculty of Medicine and Health, University of Leeds, Leeds, UK. 4. Dental Institute, Kings College London, London, UK. 5. Division of Oral Medicine, Oral Surgery, Oral Pathology and Radiology, School of Dentistry, University of Leeds, Leeds, UK. 6. Division of Applied Health and Clinical Translation, School of Dentistry, University of Leeds, Leeds, UK. 7. Leeds Institute for Data Analytics, University of Leeds, Leeds, UK.
Abstract
BACKGROUND: evidence suggests a reciprocal relationship between cognitive function (CF) and oral health (OH), but no study has demonstrated this inter-relationship in a longitudinal population. OBJECTIVE: to investigate the bidirectional relationship between CF and OH in an ageing cohort. DESIGN: cohort study. SETTING: general community. SUBJECTS: participants from the English Longitudinal Study of Ageing. METHODS: OH, measured by teeth status, self-reported OH and OH-related quality of life (OHRQoL), and CFs were collected at three time points in 2006/07, 2010/11 and 2014/15. Cross-lagged structural equation models were used to investigate the association between CF and OH, adjusted for potential confounding factors. RESULTS: 5477 individuals (56.4% women) were included (mean age = 63.1 years at 2006/07, 67.2 at 2010/11 and 70.4 at 2014/15, SD = 8.9) in analyses. The average CF score was 46.5(SD = 12.3) at baseline and 41.2 (SD = 13.4) at follow-up. 3350 (61.2%) participants had natural teeth only and 622 (11.2%) were edentulous. In the fully adjusted model, better cognition at baseline was associated with better OH at follow-up (beta coefficient = 0.02, 95% CI: 0.01-0.03); conversely better OH at baseline predicted better cognition (beta coefficient = 0.12, 95% CI: 0.06-0.18). Similar magnitude and direction of the reciprocal association was evident between cognition and OHRQoL. CONCLUSIONS: This is the first longitudinal study to demonstrate the positive reciprocal association between CF and OH. The findings suggest the importance of maintaining both good CF and OH in old age.
BACKGROUND: evidence suggests a reciprocal relationship between cognitive function (CF) and oral health (OH), but no study has demonstrated this inter-relationship in a longitudinal population. OBJECTIVE: to investigate the bidirectional relationship between CF and OH in an ageing cohort. DESIGN: cohort study. SETTING: general community. SUBJECTS:participants from the English Longitudinal Study of Ageing. METHODS: OH, measured by teeth status, self-reported OH and OH-related quality of life (OHRQoL), and CFs were collected at three time points in 2006/07, 2010/11 and 2014/15. Cross-lagged structural equation models were used to investigate the association between CF and OH, adjusted for potential confounding factors. RESULTS: 5477 individuals (56.4% women) were included (mean age = 63.1 years at 2006/07, 67.2 at 2010/11 and 70.4 at 2014/15, SD = 8.9) in analyses. The average CF score was 46.5(SD = 12.3) at baseline and 41.2 (SD = 13.4) at follow-up. 3350 (61.2%) participants had natural teeth only and 622 (11.2%) were edentulous. In the fully adjusted model, better cognition at baseline was associated with better OH at follow-up (beta coefficient = 0.02, 95% CI: 0.01-0.03); conversely better OH at baseline predicted better cognition (beta coefficient = 0.12, 95% CI: 0.06-0.18). Similar magnitude and direction of the reciprocal association was evident between cognition and OHRQoL. CONCLUSIONS: This is the first longitudinal study to demonstrate the positive reciprocal association between CF and OH. The findings suggest the importance of maintaining both good CF and OH in old age.
Keywords:
English longitudinal study of ageing; bidirectional; cognitive function; cross-lagged; older people; oral health; structural equation model; tooth loss
Authors: Huabin Luo; Chenxin Tan; Samrachana Adhikari; Brenda L Plassman; Angela R Kamer; Frank A Sloan; Mark D Schwartz; Xiang Qi; Bei Wu Journal: Curr Alzheimer Res Date: 2021 Impact factor: 3.498