The importance of stroke as a risk factor of cognitive decline in community dwelling older and oldest peoples: the SONIC study

• Main Authors: Werayuth Srithumsuk, Mai Kabayama, Yasuyuki Gondo, Yukie Masui, Yuya Akagi, Nonglak Klinpudtan, Eri Kiyoshige, Kayo Godai, Ken Sugimoto, Hiroshi Akasaka, Yoichi Takami, Yasushi Takeya, Koichi Yamamoto, Kazunori Ikebe, Madoka Ogawa, Hiroki Inagaki, Tatsuro Ishizaki, Yasumichi Arai, Hiromi Rakugi, Kei Kamide
• Format: Article
• Language: English
• Published: BMC 2020-01-01
• Series: BMC Geriatrics
• Subjects: Stroke; Cognitive decline; Older and oldest people
• Online Access: https://doi.org/10.1186/s12877-020-1423-5

Abstract Background Cognitive impairment is a major health concern among older and oldest people. Moreover, stroke is a relevant contributor for cognitive decline and development of dementia. The study of cognitive decline focused on stroke as the important risk factor by recruiting older and oldest is still lagging behind. Therefore, the aim of this study was to investigate the importance of stroke as a risk factor of cognitive decline during 3 years in community dwelling older and oldest people. Methods This study was longitudinal study with a 3-year follow-up in Japan. The participants were 1333 community dwelling older and oldest people (70 years old = 675, 80 years old = 589, and 90 years old = 69). Data collected included basic data (age, sex, and history of stroke), vascular risk factors (hypertension, diabetes mellitus, dyslipidemia, atrial fibrillation, and current smoking), and social factors (educational level, frequency of going outdoors, long-term care (LTC) service used, and residential area). The Japanese version of the Montreal Cognitive Assessment (MoCA-J) was decline of ≥2 points was defined as cognitive decline. Multiple logistic regression analysis was used to investigate the association between stroke and other risk factors with cognitive decline during a 3-year follow-up. Results The fit of the hypothesized model by multiple logistic regression showed that a history of stroke, advanced age, and greater MoCA-J score at the baseline were important risk factors, while the presence of dyslipidemia and a higher educational level were protective factors that were significantly correlated with cognitive decline during the 3-year follow-up. Conclusions The cognitive decline after the 3-year follow-up was influenced by the history of stroke and advanced age, while greater MoCA-J score at the baseline was positively associated with subsequent 3 years cognitive decline. The protective factors were the presence of dyslipidemia and a higher educational level. Therefore, these factors are considered important and should be taken into consideration when searching for creative solutions to prevent cognitive decline after stroke in community dwelling older and oldest people.