The Dietary Carbohydrate/Fat-Ratio and Cognitive Performance: Panel Analyses in Older Adults at Risk for Dementia

Jakob Norgren, Shireen Sindi, Anna Sandebring-Matton, Tiia Ngandu, Miia Kivipelto, Ingemar Kåreholt, Jakob Norgren, Shireen Sindi, Anna Sandebring-Matton, Tiia Ngandu, Miia Kivipelto, Ingemar Kåreholt

Abstract

Background: Roughly 80% of total energy intake (TEI) in most human diets originates from digestible carbohydrates (eCarb) and fat (eFat), but the impact of their proportions on cognitive performance is poorly understood.

Objectives: Our primary aim was to investigate estimates of global cognition in relation to macronutrient intake, with the log-ratio eCarb/eFat (CFr) as the primary predictor variable of interest. Secondary predictors were protein and the saturated/total fat ratio. Exploratory comparisons of CFr with eCarb and eFat as separate predictors were an additional aim.

Methods: The observations were made on panel data (years 0, 1, 2) from the Finnish Geriatric Intervention Study to Prevent Cognitive Impairment and Disability, n = 1251; age 60-77 y; 47% females; selected by risk factors for dementia. Self-reported diet was assessed by 3-d food records. Global cognition was measured using a modified Neuropsychological Test Battery. A mixed linear regression model was used, adjusted for age, sex, education, body-mass index, cholesterol-lowering drugs, TEI, time, time × intervention/control group, with study site and subject as random factors. Estimates were standardized (mean = 0; SD = 1) with 95% CI.

Results: CFr had a negative estimate to global cognition (β = -0.022, CI: -0.039, -0.005; P = 0.011). The point estimate for protein was β = 0.013 (P = 0.41), and for the saturated/total fat ratio, associations with cognition were nonlinear. CFr correlated highly with eCarb (Pearson's r = 0.92) and eFat (r = -0.94). The point estimate for CFr fell between eCarb (β = -0.026, P < 0.001) and (inversely) eFat (β = 0.017, P = 0.090).

Conclusions: A lower CFr was associated with better global cognition among older adults at risk for dementia. Because this is an important target group for preventive interventions, clinical trials are warranted to further investigate the impact of macronutritional composition on cognitive health. The potential role of CFr as a predictor for cognitive health should be further studied.

Keywords: aged; cognitive decline; compositional data; macronutrients; memory; nutritional epidemiology; target trial.

© 2023 The Author(s).

Figures

FIGURE 1
FIGURE 1
Methodological clarifications. (A) The homogenous distribution of CFr between randomization groups and time points is illustrated (n = 1029, matched between years). (B) Definition of CFr-Stable/unstable, showing that half of the participants differed by ≥1.1 SD between their highest and lowest measure of CFr (independent of order). The correspondence of 1.1 SD in CFr to 6.9 E% exchange between eCarb and eFat was estimated by crude regression reported below. (C) A hypothetical scenario for individual A and B when the between-slope (green/striped, generated from intraindividual mean levels of X and Y) and the within-slope (red/solid, “averaged” from everyone’s within-slope) are coherent in direction. (D) In contrast to panel C, the between and within slopes have opposing directions that might be a warning for unmeasured confounding. This could happen when the true effect of X on Y is detrimental but higher levels of X is typical for “health aware” people, which for other reasons have higher values of Y. CFr, log-ratio carbohydrates/fat; eCarb, carbohydrates by E%; eFat, fat by E%; ICC, intraclass correlation coefficient.
FIGURE 2
FIGURE 2
Visualization of macronutrient parameters. (A) The reciprocal relation between carbohydrates and fat and the distribution of their ratio (CFr) are illustrated. The substantially lower E% ranges of the other macronutrients at baseline are described. The sum of protein + fiber + alcohol is approximated to 20 E% in the figure. The actual distribution for p10, 25, 50, 75, and 90 was 16, 18, 20, 23, and 27 E%. (B) Visual validation of approximately interpreting CFr as “iso-caloric exchange between carbohydrates and fat within their internal pool.” CFr, log-ratio carbohydrates/fat; eCarb, carbohydrates by E%; eFat, fat by E%; p, percentile.
FIGURE 3
FIGURE 3
Distribution of macronutrients within quintiles based on CFr, eCarb, and eFat. (A) The relatively balanced baseline distribution of eProt and SAFr over CFr quintiles is illustrated. In contrast, eCarb (B) and eFat (C) are more confounded by outliers in eAlc and (at least for eCarb) eProt. The variables eCarb and eFat are shown to be proxies for CFr by having (inversely) similar distributions of eCarb and eFat. Boxes indicate percentiles 25, 50, and 75. CFr, log-ratio carbohydrates/fat; eAlc, alcohol (E%); eCarb, carbohydrates by E%; eFat, fat by E%; eFib, fiber by E%; eProt, protein by E%; SAFr, saturated/total fat ratio.
FIGURE 4
FIGURE 4
Primary estimates for diet variables as predictors of global cognition. Models without (blue) and with (orange) adjustment for TEI (standardized by sex). Linear mixed regression adjusted for age, sex, education, BMI, use of statins or other cholesterol-lowering drugs, time, time × group, and clustering on study center and subject (n = 1247; data on diet and cognition from years 0, 1, and 2). CFr, log-ratio carbohydrates/fat; eCarb, carbohydrates by E%; eFat, fat by E%; eProt, protein by E%; TEI, total energy intake. Diet and cognitive variables measured on a z-scale.
FIGURE 5
FIGURE 5
Estimates between diet variables and cognitive subdomains. Linear mixed regression adjusted for age, sex, education, BMI, use of statins or other cholesterol-lowering drugs, TEI (standardized by sex), time, time × group (n = 1247; data on diet and cognition from years 0, 1, and 2). CFr, log-ratio carbohydrates/fat; eCarb, carbohydrates by E%; eFat, fat by E%. Diet and cognitive variables measured on a z-scale.
FIGURE 6
FIGURE 6
Complementary regression analyses between diet variables and global cognition. (A) The log ratio carbohydrates/fat (CFr) and (B) protein by E% (eProt) as predictor variables in regression models adjusted for age, sex, education, BMI, cholesterol-lowering drugs, TEI (standardized by sex), time, time × group, and clustering on study site and subject. Matched samples with complete data (n = 947). Cross-sectional analyses (black) use data from a single year; the other analyses use data from all 3 y. The between-subject slope (green cross) is estimated by collapsing each subjects’ repeated measures per variable to a mean. The within-slope (fixed effects model, red triangles) is based on intraindividual variability in relation to intraindividual means. The model in blue is the primary estimate (mixed effects model), used in Figure 4. Diet-stable/unstable defined by median-split, on the basis of intraindividual difference between highest and lowest value of each diet variable among the repeated measures (see Figure 1B). Those sensitivity analyses (striped) were assumed to restrict the samples to participants where the slopes most reliably represent long-term diet (between) and “true” dietary changes (within), respectively. Diet and cognitive variables measured on a z-scale.
FIGURE 7
FIGURE 7
The saturated/total fat ratio (SAFr) and global cognition. Cross-sectional baseline analysis on the SAFr by quintiles as a predictor of global cognition (n = 1199). Mixed regression adjusted for age, sex, education, BMI, use of cholesterol-lowering drugs, TEI (standardized by sex), and clustering on study site. Mean SAFr (as %) per quintile (Q) is indicated.

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