Jinhui Zhou1, Yuebin Lv1, Chen Mao2, Jun Duan3, Xiang Gao4, Jiaonan Wang5, Zhaoxue Yin6, Wanying Shi1, Jiesi Luo6, Qi Kang7, Xiaochang Zhang6, Yuan Wei7, Virginia Byers Kraus8, Xiaoming Shi9. 1. National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China. 2. Division of Epidemiology, School of Public Health, Southern Medical University, Guangzhou, Guangdong, China. 3. Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China. 4. Department of Nutritional Sciences, The Pennsylvania State University, University Park, PA. 5. National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China; Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China. 6. Division of Non-Communicable Disease Control and Community Health, Chinese Center for Disease Control and Prevention, Beijing, China. 7. Department of Epidemiology and Biostatistics, School of Public Health, Jilin University, Changchun, Jilin, China. 8. Duke Molecular Physiology Institute and Department of Medicine, Duke University School of Medicine, Durham, NC. 9. National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China; Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China. Electronic address: shixm@chinacdc.cn.
Abstract
OBJECTIVE: Although some people with mild cognitive impairment may not suffer from dementia lifelong, about 5% of them will progress to dementia within 1 year in community settings. However, a general tool for predicting the risk of cognitive impairment was not adequately studied among older adults. DESIGN: Prospective cohort study. SETTING: Community-living, older adults from 22 provinces in China. PARTICIPANTS: We included 10,066 older adults aged 65 years and above (mean age, 83.2 ± 11.1 years), with normal cognition at baseline in the 2002-2008 cohort and 9354 older adults (mean age, 83.5 ± 10.8 years) in the 2008-2014 cohort of the Chinese Longitudinal Healthy Longevity Survey. METHODS: We measured cognitive function using the Chinese version of the Mini-Mental State Examination. Demographic, medical, and lifestyle information was used to develop the nomogram via a Lasso selection procedure using a Cox proportional hazards regression model. We validated the nomogram internally with 2000 bootstrap resamples and externally in a later cohort. The predictive accuracy and discriminative ability of the nomogram were measured by area-under-the-curves and calibration curves, respectively. RESULTS: Eight factors were identified with which to construct the nomogram: age, baseline of the Mini-Mental State Examination, activities of daily living and instrumental activities of daily living score, chewing ability, visual function, history of stroke, watching TV or listening to the radio, and growing flowers or raising pets. The area-under-the-curves for internal and external validation were 0.891 and 0.867, respectively, for predicting incident cognitive impairment. The calibration curves showed good consistency between nomogram-based predictions and observations. CONCLUSIONS AND IMPLICATIONS: The nomogram-based prediction yielded consistent results in 2 separate large cohorts. This feasible prognostic nomogram constructed using readily ascertained information may assist public health practitioners or physicians to provide preventive interventions of cognitive impairment.
OBJECTIVE: Although some people with mild cognitive impairment may not suffer from dementia lifelong, about 5% of them will progress to dementia within 1 year in community settings. However, a general tool for predicting the risk of cognitive impairment was not adequately studied among older adults. DESIGN: Prospective cohort study. SETTING: Community-living, older adults from 22 provinces in China. PARTICIPANTS: We included 10,066 older adults aged 65 years and above (mean age, 83.2 ± 11.1 years), with normal cognition at baseline in the 2002-2008 cohort and 9354 older adults (mean age, 83.5 ± 10.8 years) in the 2008-2014 cohort of the Chinese Longitudinal Healthy Longevity Survey. METHODS: We measured cognitive function using the Chinese version of the Mini-Mental State Examination. Demographic, medical, and lifestyle information was used to develop the nomogram via a Lasso selection procedure using a Cox proportional hazards regression model. We validated the nomogram internally with 2000 bootstrap resamples and externally in a later cohort. The predictive accuracy and discriminative ability of the nomogram were measured by area-under-the-curves and calibration curves, respectively. RESULTS: Eight factors were identified with which to construct the nomogram: age, baseline of the Mini-Mental State Examination, activities of daily living and instrumental activities of daily living score, chewing ability, visual function, history of stroke, watching TV or listening to the radio, and growing flowers or raising pets. The area-under-the-curves for internal and external validation were 0.891 and 0.867, respectively, for predicting incident cognitive impairment. The calibration curves showed good consistency between nomogram-based predictions and observations. CONCLUSIONS AND IMPLICATIONS: The nomogram-based prediction yielded consistent results in 2 separate large cohorts. This feasible prognostic nomogram constructed using readily ascertained information may assist public health practitioners or physicians to provide preventive interventions of cognitive impairment.
Authors: Frank Jessen; Birgitt Wiese; Horst Bickel; Sandra Eiffländer-Gorfer; Angela Fuchs; Hanna Kaduszkiewicz; Mirjam Köhler; Tobias Luck; Edelgard Mösch; Michael Pentzek; Steffi G Riedel-Heller; Michael Wagner; Siegfried Weyerer; Wolfgang Maier; Hendrik van den Bussche Journal: PLoS One Date: 2011-02-18 Impact factor: 3.240
Authors: Dona E C Locke; Robert J Ivnik; Ruth H Cha; David S Knopman; Eric G Tangalos; Bradley F Boeve; Ronald C Petersen; Glenn E Smith Journal: J Clin Exp Neuropsychol Date: 2008-05-16 Impact factor: 2.475
Authors: Mark A Espeland; Owen Carmichael; Sevil Yasar; Christina Hugenschmidt; William Hazzard; Kathleen M Hayden; Stephen R Rapp; Rebecca Neiberg; Karen C Johnson; Siobhan Hoscheidt; Michelle M Mielke Journal: Alzheimers Dement Date: 2018-07-05 Impact factor: 21.566