OBJECTIVE: This systematic review aimed to assess, in middle- and older-aged people, the relationship between dietary sodium intake and cognitive outcomes including cognitive function, risk of cognitive decline, or dementia.

METHODS: Six databases (PubMed, EMBASE, CINAHL, Psych info, Web of Science, and Cochrane Library) were searched from inception to 1 March 2020. Data extraction included information on study design, population characteristics, sodium reduction strategy (trials) or assessment of dietary sodium intake (observational studies), measurement of cognitive function or dementia, and summary of main results. Risk-of-bias assessments were performed using the National Heart, Lung, and Blood Institute (NHLBI) assessment tool.

RESULTS: Fifteen studies met the inclusion criteria including one clinical trial, six cohorts, and eight cross-sectional studies. Studies reported mixed associations between sodium levels and cognition. Results from the only clinical trial showed that a lower sodium intake was associated with improved cognition over six months. In analysis restricted to only high-quality studies, three out of four studies found that higher sodium intake was associated with impaired cognitive function.

OBJECTIVE: This systematic review aimed to review epidemiological reports to determine the prevalence of MCI and its associated risk factors in LMICs.

METHODS: Medline, Embase, and PsycINFO were searched from inception until November 2019. Eligible articles reported on MCI in population or community-based studies from LMICs and were included as long as MCI was clearly defined.

RESULTS: 5,568 articles were screened, and 78 retained. In total, n = 23 different LMICs were represented; mostly from China (n = 55 studies). Few studies were from countries defined as lower-middle income (n = 14), low income (n = 4), or from population representative samples (n = 4). There was large heterogeneity in how MCI was diagnosed; with Petersen criteria the most commonly applied (n = 26). Prevalence of amnesic MCI (aMCI) (Petersen criteria) ranged from 0.6%to 22.3%. Similar variability existed across studies using the International Working Group Criteria for aMCI (range 4.5%to 18.3%) and all-MCI (range 6.1%to 30.4%). Risk of MCI was associated with demographic (e.g., age), health (e.g., cardio-metabolic disease), and lifestyle (e.g., social isolation, smoking, diet and physical activity) factors.

METHODS: Data were from the 10/66 Study. Individuals aged 65 years or older and without dementia at baseline were selected from China, Cuba, the Dominican Republic, Mexico, Peru, Puerto Rico, and Venezuela. Dementia incidence was assessed over 3-5 years, with diagnosis according to the 10/66 Study diagnostic algorithm. Discrimination and calibration were tested for five models: the Cardiovascular Risk Factors, Aging and Dementia risk score (CAIDE); the Study on Aging, Cognition and Dementia (AgeCoDe) model; the Australian National University Alzheimer's Disease Risk Index (ANU-ADRI); the Brief Dementia Screening Indicator (BDSI); and the Rotterdam Study Basic Dementia Risk Model (BDRM). Models were tested with use of Cox regression. The discriminative accuracy of each model was assessed using Harrell's concordance (c)-statistic, with a value of 0·70 or higher considered to indicate acceptable discriminative ability. Calibration (model fit) was assessed statistically using the Grønnesby and Borgan test.

FINDINGS: 11 143 individuals without baseline dementia and with available follow-up data were included in the analysis. During follow-up (mean 3·8 years [SD 1·3]), 1069 people progressed to dementia across all sites (incidence rate 24·9 cases per 1000 person-years). Performance of the models varied. Across countries, the discriminative ability of the CAIDE (0·52≤c≤0·63) and AgeCoDe (0·57≤c≤0·74) models was poor. By contrast, the ANU-ADRI (0·66≤c≤0·78), BDSI (0·62≤c≤0·78), and BDRM (0·66≤c≤0·78) models showed similar levels of discriminative ability to those of the development cohorts. All models showed good calibration, especially at low and intermediate levels of predicted risk. The models validated best in Peru and poorest in the Dominican Republic and China.

INTERPRETATION: Not all dementia prediction models developed in HICs can be simply extrapolated to LMICs. Further work defining what number and which combination of risk variables works best for predicting risk of dementia in LMICs is needed. However, models that transport well could be used immediately for dementia prevention research and targeted risk reduction in LMICs.

METHODS: We combined individual participant data for 16 cohorts from 15 countries (members of the COSMIC consortium) and used qualitative and quantitative (Item Response Theory/IRT) harmonization techniques to estimate SCD prevalence.

RESULTS: The sample comprised 39,387 cognitively unimpaired individuals above age 60. The prevalence of SCD across studies was around one quarter with both qualitative harmonization/QH (23.8%, 95%CI = 23.3-24.4%) and IRT (25.6%, 95%CI = 25.1-26.1%); however, prevalence estimates varied largely between studies (QH 6.1%, 95%CI = 5.1-7.0%, to 52.7%, 95%CI = 47.4-58.0%; IRT: 7.8%, 95%CI = 6.8-8.9%, to 52.7%, 95%CI = 47.4-58.0%). Across studies, SCD prevalence was higher in men than women, in lower levels of education, in Asian and Black African people compared to White people, in lower- and middle-income countries compared to high-income countries, and in studies conducted in later decades.