Dietary patterns and accelerated multimorbidity in older adults

Abstract

Diet could influence disease development and shape multimorbidity trajectories. Here we examined how four dietary patterns relate to 15-year multimorbidity accumulation in 2,473 community-dwelling older adults from the Swedish SNAC-K cohort. Multimorbidity was operationalized as the total number of chronic conditions and grouped into three organ systems. Higher adherence to the Mediterranean-DASH Diet Intervention for Neurodegenerative Delay, the Alternative Healthy Eating Index and the Alternative Mediterranean Diet was inversely associated with the annual rate of total chronic disease accumulation (β coefficient (95% confidence interval) per 1-s.d. increment: -0.049 (-0.065 to -0.032), -0.051 (-0.068 to -0.035) and -0.031 (-0.048 to -0.014), respectively), whereas higher adherence to the Empirical Dietary Inflammatory Index was associated with a faster rate of accumulation (0.053 (0.035-0.071)). Similar associations were observed for cardiovascular and neuropsychiatric diseases but not for musculoskeletal diseases. Some associations varied by sex and age. Our findings support diet quality as a modifiable risk factor for multimorbidity progression in older adults, with possible implications for dietary guidelines, public health strategies and clinical practice.

Fig. 1. Association between the cumulative adherence to dietary patterns and the yearly rate of total chronic disease accumulation during a 15-year follow-up (N = 2,473).

MIND: baseline range: 2–12; 1 s.d. = 1.74. AHEI: baseline range: 29.9–91.7; 1 s.d. = 9.82. AMED: baseline range: 0–9; 1 s.d. = 1.76. EDII: baseline range: −1.36 to 2.70; 1 s.d. = 0.30. Model: linear mixed model with random intercept and slope, adjusted by age (years), sex (male or female), living arrangements (alone or not), previous occupation (manual or non-manual worker), education (elementary, high school or university), tobacco smoking (never, former smoker, current smoker or unknown), physical activity (inadequate, health-enhancing, fitness-enhancing or unknown) and energy intake (kcal d⁻¹). Data are presented as average predicted number of chronic diseases ± 95% CIs (shaded area).

Fig. 2. Association between the cumulative adherence to dietary patterns and the yearly rate of chronic disease accumulation during a 15-year follow-up, stratified by sex (male, n = 931; female, n = 1,512).

MIND: baseline range: 2–12; 1 s.d. = 1.74. AHEI: baseline range: 29.9–91.7; 1 s.d. = 9.82. AMED: baseline range: 0–9; 1 s.d. = 1.76. EDII: baseline range: −1.36 to 2.70; 1 s.d. = 0.30. Model: linear mixed model with random intercept and slope, adjusted by age (years), living arrangements (alone or not), previous occupation (manual or non-manual worker), education (elementary, high school or university), tobacco smoking (never, former smoker, current smoker or unknown), physical activity (inadequate, health-enhancing, fitness-enhancing or unknown) and energy intake (kcal d⁻¹). Models on disease accumulation within a given organ system were adjusted for diseases not belonging to said organ system. Estimates were obtained from models with multiplicative interaction terms among the dietary patterns, time from inception and sex. Two-sided P values for interaction were obtained from Wald tests. ‘?’ indicates not significant when adjusting for multiple comparisons (FDR of 5%). Data are presented as β coefficients for excess annual change in disease accumulation per 1-s.d. increment in cumulative adherence to every dietary pattern ± 95% CIs. int, interaction.

Extended Data Fig. 1

Flow chart of the study participants.

Extended Data Fig. 2. Trajectories of chronic disease accumulation during a 15-year follow-up, adjusted for age and sex (N = 2,473), obtained from group-based trajectory modelling.

Percentages indicate the proportion of participants assigned to a given trajectory of chronic disease accumulation.

Extended Data Fig. 3. Directed acyclic graph describing the potential causal and confounding effects of diet quality on multimorbidity.

Green arrows indicate a causal path between the exposure (green oval; ►) and outcome of interest (final blue oval; ▌). Pink arrows indicate biasing paths (that is, possible confounding factors [pink ovals] modifying the association between the exposure and the outcome of interest). Blue ovals preceding the outcome of interest indicate mediators.

Extended Data Fig. 4. Baseline data distribution of the dietary patterns (N = 2,473).

MIND: Mediterranean-DASH (Dietary Approaches to Stop Hypertension) Diet Intervention for Neurodegenerative Delay. AHEI: Alternative Health Eating Index. AMED: Alternative Mediterranean Diet. EDII: Empirical Dietary Inflammatory Index. Black spikes indicate individual data points. Note that the MIND and AMED are discrete in nature; therefore, individual data points match the bar charts.