Functional Deficit of Sense Organs as a risk factor for Cognitive Functional Disorder in Chinese Community Elderly People

2021 ◽  
Author(s):  
Lan Wang ◽  
Mei Song ◽  
Xiaochuan Zhao ◽  
Qifeng Zhu ◽  
Lulu Yu ◽  
...  
Keyword(s):  
Risk Factor ◽  
Elderly People ◽  
Functional Disorder ◽  
Chinese Community ◽  
Sense Organs ◽  
Functional Deficit

Determination of Dietary Status as a Risk Factor of Cardiovascular Heart Disease in Turkish Elderly People

2015 ◽  
Vol 54 (4) ◽  
pp. 328-341 ◽  
Author(s):  
Alev Keser ◽  
Nurcan Yabanci Ayhan ◽  
Pelin Bilgiç ◽  
Muhittin Tayfur ◽  
Işil ŞImşek
Keyword(s):  
Risk Factor ◽  
Heart Disease ◽  
Elderly People ◽  
Cardiovascular Heart Disease

Fear of imbalance and falling

1998 ◽  
Vol 8 (1) ◽  
pp. 23-29 ◽  
Author(s):  
Lucy Yardley
Keyword(s):  
Risk Factor ◽  
Psychological Distress ◽  
Elderly People ◽  
Fear Of Falling ◽  
Direct Result ◽  
Serious Injury ◽  
Combined Impact ◽  
The Relationship

This review examines the relationship between dysequilibrium, falling and anxiety, and their combined impact on the lives of elderly people. More than one in four people aged over 69 fall each year, and a higher proportion of those over 74. Although only one in ten incurs serious injury as a direct result of the fall, fear of falling can often lead not only to psychological distress but also to restriction of activity and an unnecessary and undesirable loss of independence. Naturally, symptoms of imbalance constitute a key risk factor for falling.

Study Organization in the Canadian Study of Health and Aging

2001 ◽  
Vol 13 (S1) ◽  
pp. 41-48 ◽  
Author(s):  
Ian McDowell ◽  
Barbara Helliwell ◽  
Elizabeth Sykes ◽  
Gerry Hill ◽  
Joan Lindsay
Keyword(s):  
Risk Factor ◽  
Elderly People ◽  
Clinical Examination ◽  
Staff Training ◽  
Neuropsychological Testing ◽  
Canadian Study ◽  
Multicenter Studies ◽  
Blood Samples ◽  
Time Zones ◽  
Screening Interview

The Canadian Study of Health and Aging was a complex undertaking that faced management challenges not encountered by smaller-scale projects. The study followed 10,263 elderly people in 18 study centers spanning six time zones; it was administered in two languages, and over 70 investigators were involved. The data collected from each participant were not fixed, but varied according to the results of earlier testing. The data could include a screening interview, a self-completed risk factor questionnaire, an interview with a relative, a clinical examination, neuropsychological testing, blood samples, and neuroimaging.This report describes the approach taken to organize the study, to track participants, and to monitor adherence to the study protocol. It also describes the human organizational aspects, including systems for staff training, for communicating among study centers, and for coordinating the publication of results. The discussion proposes some guiding principles for administering multicenter studies.

Psychiatric symptoms are not an independent mortality risk factor in community-living elderly people

2014 ◽  
Vol 26 (6) ◽  
pp. 911-920 ◽  
Author(s):  
Sergio Benabarre ◽  
Javier Olivera ◽  
Teófilo Lorente ◽  
Mariano Rodriguez ◽  
Alfonso Barros-Loscertales ◽  
...  
Keyword(s):  
Risk Factor ◽  
Elderly People ◽  
Mortality Risk ◽  
Depressive Symptomatology ◽  
Psychiatric Symptoms ◽  
The Elderly ◽  
Physical Illness ◽  
Research Interest ◽  
Psychiatric Disease ◽  
Prospective Longitudinal

ABSTRACTBackground:Mortality risk factors have attracted great research interest in recent years. Physical illness is strongly associated with mortality risk in elderly people. Furthermore, a relationship between mortality risk and psychiatric disease in the elderly has gained research interest.Methods:This is a prospective longitudinal multicenter study. A sample of 324 participants was selected as a representative sample of community members aged 65 years and older and living in Huesca (Spain). The following information was collected: affiliation data, severity of physical illness, psychosocial, and psychiatric factors. Statistical analyses were completed with a multivariate analysis in order to control possible confounding variables related to mortality.Results:Of the initially selected sample, 293 participants were assessed. Sixty-four participants died (21.8%, 95% CI [16.9%, 26.7%]), 5.3% annual rate, and 46.1% showed symptomatology of mental disorders. Older people have eight times greater risk of mortality. The risk increased 53 times in patients affected by several physical illness. No relationship between cognitive dysfunction and depressive symptomatology was observed. In fact, physical condition was associated with depression, and the percentage of participants with depressive symptoms increased according to the severity of physical illness.Conclusions:Severity of physical illness and age are independently and directly associated with mortality in the elderly people. Therefore, severity of physical illness seems to be a crucial factor in the bi-directional association between mortality and depression, acting as a risk factor independently for both. So the relationship between depression and mortality can be affected by the severity of physical illness.

scholarly journals PO-035 Association between sedentary behavior and diabetes mellitus in the prevalence of middle-aged and elderly people

2018 ◽  
Vol 1 (3) ◽  
Author(s):  
Xinzheng Wang ◽  
Hongbin Luo
Keyword(s):  
Diabetes Mellitus ◽  
Logistic Regression ◽  
Regression Analysis ◽  
Risk Factor ◽  
Sedentary Behavior ◽  
Elderly People ◽  
Independent Risk Factor ◽  
Sedentary Time ◽  
Middle Aged ◽  
The Relationship

Objective This study aims to explore the relationship between sedentary behavior and the diabetes mellitus prevalence of middle-aged and elderly people. Methods  we conduct a questionnaire survey and physical examination for a total of 3,000 middle-aged and elderly people (≥45 years old) ,analysing by he software of  SPSS21.0 and Stata12.0. Results The logistic regression analysis shows that the risk of diabetes is 1.617 (95% CI, 0.762-1.789, P <0.05) at 2-4h, 4-6h, 6-8h, ≥8h, = 0.003), 1.235 (95% CI, 0.818-1.865, P = 0.034), 3.420 (95% CI, 2.241-5.218, P = 0.000), 5.014 (95% CI, 3.049-8.247, P = 0.000). With each additional one-hour sedentariness the risk of diabetes increases by 23% (OR1.23, 95% CI 1.18-1.29, p <0.0001). Conclusions The sedentary behavior is an independent risk factor for diabetes. The prevalence of diabetes is gradually increasing with the increase of sedentary time, which indicates the longer sedentary time, the higher prevalence of diabetes.

scholarly journals A Risk Prediction Model Based on Machine Learning for Cognitive Impairment Among Chinese Community-Dwelling Elderly People With Normal Cognition: Development and Validation Study

10.2196/20298 ◽  
2021 ◽  
Vol 23 (2) ◽  
pp. e20298
Author(s):  
Mingyue Hu ◽  
Xinhui Shu ◽  
Gang Yu ◽  
Xinyin Wu ◽  
Maritta Välimäki ◽  
...  
Keyword(s):  
Machine Learning ◽  
Logistic Regression ◽  
Cognitive Impairment ◽  
Older People ◽  
Prediction Model ◽  
Elderly People ◽  
Community Dwelling ◽  
Chinese Community ◽  
Model Based ◽  
Normal Cognition

Background Identifying cognitive impairment early enough could support timely intervention that may hinder or delay the trajectory of cognitive impairment, thus increasing the chances for successful cognitive aging. Objective We aimed to build a prediction model based on machine learning for cognitive impairment among Chinese community-dwelling elderly people with normal cognition. Methods A prospective cohort of 6718 older people from the Chinese Longitudinal Healthy Longevity Survey (CLHLS) register, followed between 2008 and 2011, was used to develop and validate the prediction model. Participants were included if they were aged 60 years or above, were community-dwelling elderly people, and had a cognitive Mini-Mental State Examination (MMSE) score ≥18. They were excluded if they were diagnosed with a severe disease (eg, cancer and dementia) or were living in institutions. Cognitive impairment was identified using the Chinese version of the MMSE. Several machine learning algorithms (random forest, XGBoost, naïve Bayes, and logistic regression) were used to assess the 3-year risk of developing cognitive impairment. Optimal cutoffs and adjusted parameters were explored in validation data, and the model was further evaluated in test data. A nomogram was established to vividly present the prediction model. Results The mean age of the participants was 80.4 years (SD 10.3 years), and 50.85% (3416/6718) were female. During a 3-year follow-up, 991 (14.8%) participants were identified with cognitive impairment. Among 45 features, the following four features were finally selected to develop the model: age, instrumental activities of daily living, marital status, and baseline cognitive function. The concordance index of the model constructed by logistic regression was 0.814 (95% CI 0.781-0.846). Older people with normal cognitive functioning having a nomogram score of less than 170 were considered to have a low 3-year risk of cognitive impairment, and those with a score of 170 or greater were considered to have a high 3-year risk of cognitive impairment. Conclusions This simple and feasible cognitive impairment prediction model could identify community-dwelling elderly people at the greatest 3-year risk for cognitive impairment, which could help community nurses in the early identification of dementia.

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