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. 2022 Feb 25;12(3):350.
doi: 10.3390/jpm12030350.

The Association between Bodily Pain and Cognitive Impairment in Community-Dwelling Older Adults

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The Association between Bodily Pain and Cognitive Impairment in Community-Dwelling Older Adults

Chun-Che Huang et al. J Pers Med. .

Abstract

Background: Bodily pain is a common condition in older adults and interferes with individuals' cognitive functioning. We aimed to evaluate the association between bodily pain and related locations and cognitive impairment among community-dwelling older adults in Taiwan.

Method: In this retrospective, cross-sectional study, we enrolled 2022 participants aged 60‒70 years, from the Taiwan Biobank. Mini-Mental State Examination was performed to assess cognitive impairment. Further, logistic regression analyses were performed to identify the relationship between bodily pain and cognitive impairment.

Results: Overall, 161 participants had cognitive impairment. Multivariable analysis showed that older adults who reported bodily pain were more likely than those who did not have cognitive impairment (odds ratio 1.68). Moreover, the occurrence of cognitive impairment correlated with the presence of two or more pain locations and self-reported low back and waist pain or sciatica.

Conclusion: Our study revealed that cognitive impairment was associated with bodily pain in community-dwelling older adults, particularly older adults with low back and waist pain or sciatica and those with two or more pain locations. To maintain the quality of older adults' life, pain and cognitive decline need to be simultaneously assessed with considerably more precise and objective markers.

Keywords: bodily pain; cognitive impairment; pain locations.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Potential causal pathway analysis between bodily pain and the occurrence of cognitive impairment among community-dwelling older adults. Values are expressed as odds ratio and 95% confidence interval. The models were adjusted for gender, marital status, alcohol drinking, smoking, physical activity, body mass index, waist circumference, total cholesterol, triglyceride, HDL cholesterol, LDL cholesterol, and eGFR by using logistic regression analyses. * p < 0.05, ** p < 0.01, *** p < 0.001. * = statistically significant.

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