Literature DB >> 26519443

Prevalence and Risk Factor of Cognitive Impairment were Different between Urban and Rural Population: A Community-Based Study.

Hui-Dong Tang1, Yi Zhou1, Xiang Gao2, Liang Liang1, Miao-Miao Hou1, Yuan Qiao1, Jian-Fang Ma1, Sheng-Di Chen1.   

Abstract

BACKGROUND: China is facing a continuously rising numbers of people with cognitive impairment (CI).
OBJECTIVES: To investigate the prevalence and risk factors of CI among elderly people living in rural and urban communities.
METHODS: We conducted a face-to-face survey of CI on 7,900 individuals aged 50 years or older meeting inclusion criteria in the Malu (rural community, n = 4,429) and Wuliqiao (urban community, n = 3,471) communities of Shanghai. The Mini-Mental State Examination (MMSE) was used to evaluate the cognitive function. Information on demographic features and potential risk factors for CI was collected during the interview. Multivariate logistic regression was performed to identify risk factors associated with CI.
RESULTS: Based on the education modified MMSE score, we identified 329 CI cases in rural community and 227 in urban community. The prevalence of CI was 7.43% in rural population and 6.54% in urban population (p = 0.13). In the urban population, risk of having CI was associated with age (OR = 1.04; 95% CI: 1.01-1.08), lack of physical activities (OR = 2.25; 95% CI: 1.11-4.57), presence of diabetes mellitus (OR = 1.79; 95% CI: 1.04-3.07), and having three or more children (OR = 2.39; 95% CI: 1.27-4.50). In contrast, factors associated with rural populations included female gender (OR = 2.03; 95% CI: 1.08-3.82), age (OR = 1.06; 95% CI: 1.03-1.08), exposure to pesticides (OR = 4.68; 95% CI: 1.27-17.21), history of encephalitis or meningitis (OR = 6.02; 95% CI: 1.92-18.85) and head trauma (OR = 1.89; 95% CI: 1.10-3.24).
CONCLUSIONS: Urban rural and populations showed different risk factors for CI, suggesting that different preventive strategies in these areas should be performed.

Entities:  

Keywords:  Cognitive impairment; prevalence; risk factors; rural population; urban population

Mesh:

Year:  2016        PMID: 26519443     DOI: 10.3233/JAD-150748

Source DB:  PubMed          Journal:  J Alzheimers Dis        ISSN: 1387-2877            Impact factor:   4.472


  7 in total

1.  Type 2 Diabetes Mellitus Is Associated with the Risk of Cognitive Impairment: a Meta-Analysis.

Authors:  Xiaojun Zhang; Xiaolu Jiang; Sufang Han; Qianqi Liu; Jing Zhou
Journal:  J Mol Neurosci       Date:  2019-04-04       Impact factor: 3.444

2.  Prevalence of mild cognitive impairment is higher in hypertensive population: a cross-sectional study in less developed northwest China.

Authors:  Mulalibieke Heizhati; Lin Wang; Nanfang Li; Mei Li; Fengyu Pan; Zhikang Yang; Zhongrong Wang; Reyila Abudereyimu
Journal:  Medicine (Baltimore)       Date:  2020-05       Impact factor: 1.889

3.  Risk factors for cognitive impairment in older people with diabetes: a community-based study.

Authors:  Shuangling Xiu; Qiuju Liao; Lina Sun; Piu Chan
Journal:  Ther Adv Endocrinol Metab       Date:  2019-04-02       Impact factor: 3.565

4.  Obesity Is Less Frequently Associated with Cognitive Impairment in Elderly Individuals: A Cross-Sectional Study in Yogyakarta, Indonesia.

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Review 5.  Mild Cognitive Impairment in Rural Areas: Research Advances and Implications for Clinical Practice and Healthcare Policy.

Authors:  Vaios Peritogiannis; Aglaia Roganaki; Eleftheria Siarava; Maria Samakouri
Journal:  Healthcare (Basel)       Date:  2022-07-19

6.  The association between cognitive impairment and 30-day mortality among older Chinese inpatients.

Authors:  Xiao-Ming Zhang; Jing Jiao; Na Guo; Chen Zhu; Zhen Li; Dongmei Lv; Hui Wang; Jingfen Jin; Xianxiu Wen; Shengxiu Zhao; Xinjuan Wu; Tao Xu
Journal:  Front Med (Lausanne)       Date:  2022-08-24

7.  The impact of rural-urban community settings on cognitive decline: results from a nationally-representative sample of seniors in China.

Authors:  Yuanxi Xiang; Hossein Zare; Cuiling Guan; Darrell Gaskin
Journal:  BMC Geriatr       Date:  2018-12-29       Impact factor: 3.921

  7 in total

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