Introduction
Materials and methods
Literature search
Study selection
Data extraction and quality assessment
Statistical analysis
Results
Literature search and study characteristics
Authors | Year | Country | Design | Population | Mean age | Female (%) | Cognitive test/Diagnosis | Albuminuria assessment | Adjustment for confounders | Follow-up (years) | NOS |
---|---|---|---|---|---|---|---|---|---|---|---|
Barzilay | 2008 | US | Longitudinal | 2316 | / | 59 | Dementia | ACR ≥ 30 | Age, sex, race, education, history of CHD, stroke, hypertension, diabetes, smoking, serum cholesterol, LDL, CRP, eGFR, APOEε4 | > 5 | 8/9 |
Abbatecola | 2008 | Italy | Cross-sectional | 140 | 78 | / | MMSE | Continuous log ACR | Baseline MMSE, age, education, BMI, smoking status, depression, drug intake, CV-PPG, SBP, IMT | / | 8/10 |
Vupputuri | 2008 | US | Cross-sectional | 2386 | 71 | 66 | DSS score 0–32 | ACR ≥ 30 | Age, ethnicity, gender, education, smoking, diabetes, hypertension, total cholesterol, HDL, CHD, CHF, MI, stroke, anemia, CRP | / | 9/10 |
Chen | 2008 | China | Cross-sectional | 175 | 61 | 51 | MMSE | ACR | Age, education, BG, cholesterol, history of MI, stroke, smoking, BP | 7/10 | |
Weiner | 2009 | US | Cross-sectional | 335 | 73 | 73 | Executive functioning* | Macroalbuminuria ACR > 250 (M) or 350 (F) | Sex, race, diabetes, cardiovascular disease, hypertension, current use of ACEI or ARB, and eGFR | / | 7/10 |
Wang | 2010 | China | Longitudinal | 1351 | 59 | 48 | MMSE | ACR > 25 (F) or 17 (M) | Age, gender and education | 4 | 7/9 |
Barzilay | 2011 | International | Longitudinal | 28,384 | 67 | 29 | MMSE 3-Point or Greater Decrease | Microalbuminuria: ACR: 30–299 | Age, sex, ethnicity, education, history of CVD, DM, hypertension, baseline SBP, smoking, BMI, and eGFR, alcohol use, exercise, depression, and medication use | 5 | 8/9 |
Tamura (a) | 2011 | US | Longitudinal | 19,339 | 64 | 60 | Item S1 | Microalbuminuria: ACR: 30–299 | Age, race, sex, education, region, diabetes, hypertension, CVD, stroke, smoking alcohol use, eGFR | 4 | 8/9 |
Tamura (b) | 2011 | US | Longitudinal | 3591 | 58 | 47 | 3MS | ACR four quartiles | demographics and Vascular Risk Factors | NA | 6/9 |
Helmer | 2011 | France | Longitudinal | 1003 | 74 | 61 | MMSE | ACR > 30 | age, sex, educational, APOE4 genotype, hypertension, CVD, hypercholesterolemia, hypertriglyceridemia, stroke, diabetes, smoking, BMI, and baseline eGFR | 7 | 7/9 |
O’Hare | 2012 | US | Longitudinal | 2968 | 74 | 60 | DSM-IV criteria | Proteinuria (positive, trace, no) | Time-varying indicator variables | 6 | 7/9 |
Barzilay | 2013 | US | Longitudinal | 2957 | 63 | 47 | ≥ 5% decline in DSST | ACR ≥ 30 | Age, sex, race, education, alcohol consumption, BMI, SBP, secondary CVD prevention, LDL, baseline eGFR | 4–6 | 7/9 |
Higuchi | 2015 | US | Longitudinal | 3583 | 78 | / | DSS score 0–33 | Proteinuria (positive, trace, no) | Age, education, APOEε4, stroke, hypertension, SBP, DM, fasting BG, physical activity index, baseline cognitive abilities screening instrument score and time of follow-up | 8 | 7/9 |
Wei | 2016 | US | Cross-sectional | 1982 | 70 | 54 | DSST | Urinary albumin | Age, sex, race/ethnicity, poverty status, education, physical activity, BMI, cigarette smoking, and alcohol consumption | / | 9/10 |
Takae | 2018 | Japan | Longitudinal | 1562 | 71 | 48 | Dementia | ACR ≥ 30 | Age and sex, educational, history of stroke, SBP, antihypertensive agents, DM, total cholesterol, BMI, smoking, alcohol, and exercise, log eGFR | 10 | 7/9 |
Gabin | 2019 | Norway | Longitudinal | 48,508 | 50 | 54 | Dementia | ACR four quartiles | ACR, age, sex, education, GFR, cholesterol, non-fasting BG, serum iron, BMI, pulse, history of MI, DM, angina, stroke, smoking, subjective health status | > 10 | 8/9 |