| Literature DB >> 35795585 |
Yuhan Zhou1, Jieyuan Wang2, Limin Cao3, Mengyuan Shi1, Huiyuan Liu1, Yuhong Zhao1, Yang Xia1.
Abstract
Objectives: The aim of this meta-analysis was to assess the quantitative associations between fruit and vegetable intake and cognitive disorders in older adults. Design: A meta-analysis. Setting and Participants: We used the PubMed, Web of Science and Scopus databases for a literature search to 12 April 2022. We preliminarily retrieved 11,759 studies, 16 of which met the inclusion criteria including six cross-sectional studies, nine cohort studies and one case-control study, incorporating 64,348 participants and 9,879 cases.Entities:
Keywords: cognitive disorders; dose-response; fruit; meta-analysis; vegetable
Year: 2022 PMID: 35795585 PMCID: PMC9251442 DOI: 10.3389/fnut.2022.871061
Source DB: PubMed Journal: Front Nutr ISSN: 2296-861X
FIGURE 1Flowchart of study selection about the relationship between fruits and vegetables intake and cognitive disorders.
Characteristics of the included studies in this meta-analysis.
| References | Country | Study design | Sample size | Age | Disease assessment | Number of cases | Disease type | Exposure assessment | OR/HR (95% CI) | Adjusted covariates |
| Dai ( | America | Cohort | 1,836 | ≥65 | NINCDS-ADRDA | 81 | AD | FFQ | Age, education, years of education, dietary intake of vitamins C, E, and β-carotene | |
| Barberger-Gateau ( | France | Cohort | 8,085 | ≥65 | Neurological exam, DSM-IV and NINCDS-ADRDA | 281 | Dementia | FFQ | Age, gender, education, city, income, marital status, ApoE genotype, BMI, and diabetes | |
| Vercambre ( | France | Cohort | 4,809 | 76–82 | Observed Cognitive Deterioration Scale | 598 | Recent cognitive impairment | DHQ | Age, education level, BMI, physical activity, daily energy intake, smoking, supplement of vitamin D and/or Ca, supplement of other vitamins or minerals, use of postmenopausal hormones, history of depression, history of cancer, history of CHD, history of stroke, history of diabetes mellitus, history of hypertension, and history of hypercholesterolaemia | |
| Roberts et al. ( | America | Cross-sectional | 1,233 | 70–89 | CDR | 163 | MCI | FFQ | Age, gender, years of education, total energy intake, ApoE ε4, stroke, coronary heart disease, depressive symptoms | |
| Ritchie ( | France | Cohort study | 1,433 | ≥65 | Standardized interview incorporating cognitive testing | 405 | MCI or Dementia | Nutritional questionnaire | Age and gender | |
| Lee et al. ( | Hong Kong, China | Cross-sectional | 285 | ≥60 | DSM-VI and CDR | 146 | Dementia | MNA | Age, gender, and education | |
| Wu et al. ( | Tai Wan, China | Cross-sectional | 2,119 | ≥65 | MMSE | 472 | Cognitive impairment | Questionnaire for lifestyle | Age, gender, educational level, marital status, social support, hyperlipidemia, stroke, physical function, depressive symptoms, self-rated health, cigarette smoking, physical activity, coffee intake, tea intake, multivitamin intake, and BMI | |
| Chen ( | China | Case-control | 5,691 | ≥65 | MMSE | 1,306 | Cognitive impairment | FFQ | Age, gender, marital status, financial status, residential area, BMI, hypertension, diabetes, smoking, alcohol, tea drinking, and exercise habits | |
| Chan ( | Hong Kong, China | Cross-sectional | 3,670 | ≥65 | CSI-D | 877 | Cognitive impairment | FFQ | Age, BMI, PASE, energy intake, educational level, Hong Kong ladder, community ladder, smoking status, alcohol use, No. of ADLs, GDS y of DM, category, self-reported history hypertension, and CVD/stroke | |
| Pastor-Valero et al. ( | Brazilian | Cross-sectional | 1,849 | ≥65 | CSI-D | 147 | Cognitive impairment | FFQ | Age and gender | |
| Lee ( | China | Cohort | 17,700 | ≥65 | ICD-10 and CDR | 1,620 | Dementia | FFQ | Age, gender, education, major chronic diseases, physical exercise and smoking | |
| Kimura ( | Japan | Cohort | 1,071 | ≥60 | DSM-III-R and NINDS-AIREN | 430 | Dementia and AD | FFQ | age, gender, educational level, history of stroke, diabetes, systolic blood pressure, use of anti-hypertensive agents, electrocardiogram abnormalities, serum total cholesterol, BMI, current drinking, current smoking, regular exercise, and intakes of total energy, protein, fat, and carbohydrate | |
| Fischer ( | Germany | Cohort | 2,622 | ≥75 | DSM-IV, ICD-10 and NINDS-AIREN | 418 | Dementia and AD | “Cognitive health” food intake screener | Age, gender, BMI, education, and APOEε4 status | |
| An ( | China | Cohort | 4,749 | ≥80 | MMSE | 1,958 | Cognitive impairment | Self-reported information on dietary intake | Age, gender, education level, living arrangement, place of residence, body weight, smoking status, alcohol consumption status, exercise status, self-rated health, chronic disease, the Katz activities of daily living limitation | |
| Ngabirano ( | France | Cohort | 5,934 | ≥65 | DSM-VI | 662 | Dementia and AD | FFQ | Inclusion center, gender, marital status, income, level of education, APOE 4, smoking, alcohol consumption, physical activity frequency and energy intake | |
| Xu ( | China | Cross-sectional | 1,262 | ≥65 | MMSE | 315 | MCI | FFQ | Age, gender, education, marital status, smoking, alcohol drinking, energy intake, diabetes mellitus, hypertension, physical activity, MNA-SF and IADL scores |
AD, Alzheimer’s disease; BMI, body mass index; CDR, Clinical Dementia Rating Scale; CI, confidence interval; CHD, coronary heart diseases; CSI-D, Community Screening Instrument for Dementia; DSM-IV, Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition; F, fruit; F + V, fruit and vegetable; FFQ, food frequency questionnaire; HR, hazard ratio; IADL, Instrumental Activities of Daily Living scale; ICD-10, the 10th revision of the International Statistical Classification of Diseases and Related Health Problems; MMSE: Mini-Mental State Examination; MNMA-SF, Mini Nutritional Assessment-Short Form; MoCA, Montreal Cognitive Assessment; NINCDS-ADRDA, National Institute of Neurological and Communicative Diseases and Stroke-Alzheimer’s Disease and Related Disorders Association; NINCDS-AIREN, the National Institute of Neurological and Communicative Disorders and Stroke and the Alzheimer’s Disease and Related Disorders Association; OR, odds ratio; PASE, Physical activity Scale for the Elderly; V, vegetable.
Subgroup analyses of relationship between fruits and vegetables intake and cognitive disorders.
| Subgroup | Number of effects | Effect size (95% CI) | |
|
| |||
| China | 12 | 0.76 (0.72–0.81) | 50.0% |
| Others | 19 | 0.84 (0.79–0.90) | 46.1% |
|
| |||
| Men | 1 | 1.09 (0.72–1.66) | – |
| Women | 1 | 0.73 (0.54–0.99) | – |
| Both | 29 | 0.79 (0.76–0.83) | 36.2% |
|
| |||
| Cognitive impairment | 15 | 0.76 (0.72–0.80) | 42.8% |
| Dementia | 10 | 0.84 (0.78–0.91) | 12.7% |
| Alzheimer’s Disease | 6 | 0.88 (0.76–1.01) | 5.80% |
|
| |||
| Cohort | 21 | 0.83 (0.79–0.87) | 0.00% |
| Cross-sectional | 8 | 0.70 (0.61–0.82) | 49.5% |
| Case-control | 2 | 0.68 (0.61–0.76) | 2.90% |
|
| |||
| FFQ | 23 | 0.79 (0.75–0.83) | 42.9% |
| Others | 8 | 0.80 (0.75–0.86) | 9.4% |
|
| |||
| ≥200 | 26 | 0.80 (0.76–0.83) | 35.7% |
| <200 | 5 | 0.68 (0.53–0.87) | 32.3% |
CI, confidence interval; FFQ, food frequency questionnaire.
FIGURE 2Meta-analysis of the association between fruits and vegetables consumption and the prevalence of cognitive disorders.
FIGURE 3Dose-response relationship between fruits and vegetables intake and prevalence of cognitive disorders.