Nancy Presse’s research while affiliated with Université de Sherbrooke and other places

Background The 2019 Canada’s Food Guide provides universal recommendations to individuals aged ≥2 years. However, the extent to which these recommendations are appropriate for older adults is unknown. Although ideal, conducting a large randomized controlled trial is unrealistic in the short term. An alternative is the target trial emulation framework for causal inference, a novel approach to improve the analysis of observational data. Objective This study aims to describe the protocol for a target trial emulation in older adults, with an emphasis on key aspects of a hypothetical sustained diet and physical activity intervention. Methods To emulate the target trial, nonexperimental data from the Quebec Longitudinal Study on Nutrition and Successful Aging (NuAge; N=1753 adults aged ≥67 years) will be used. NuAge includes 4 yearly measurements of dietary intakes, covariates, and outcomes. The per-protocol causal contrast will be the primary causal contrast of interest to account for nonadherence. The sustained intervention strategy will be modeled using the parametric g-formula. In the hypothetical trial, participants will be instructed to meet sex-specific minimal intakes for vegetables and fruits, whole grains, animal- and plant-based protein foods, milk and plant-based beverages, and unsaturated fats. The eligibility criteria, follow-up, intervention, outcomes, and causal contrast in the emulation will closely align with those of the target trial, with only minor modifications. We will attempt to emulate the randomization of treatment by adjusting for baseline covariates and prebaseline dietary habits. Results Data collection for NuAge was completed in June 2008. For this study, the main analysis was started in May 2024. Submission of the manuscript is expected by February 2025. Conclusions Emulating a target trial will provide the first evidence of the adequacy of the 2019 Canada’s Food Guide recommendations for older adults in relation to health outcomes. International Registered Report Identifier (IRRID) DERR1-10.2196/65182

BACKGROUND The 2019 Canada’s Food Guide provides universal recommendations to individuals aged ≥2 years. However, the extent to which these recommendations are appropriate for older adults is unknown. Although ideal, conducting a large randomized controlled trial is unrealistic in the short term. An alternative is the target trial emulation framework for causal inference, a novel approach to improve the analysis of observational data. OBJECTIVE This study aims to describe the protocol for a target trial emulation in older adults, with an emphasis on key aspects of a hypothetical sustained diet and physical activity intervention. METHODS To emulate the target trial, nonexperimental data from the Quebec Longitudinal Study on Nutrition and Successful Aging (NuAge; N=1753 adults aged ≥67 years) will be used. NuAge includes 4 yearly measurements of dietary intakes, covariates, and outcomes. The per-protocol causal contrast will be the primary causal contrast of interest to account for nonadherence. The sustained intervention strategy will be modeled using the parametric g-formula. In the hypothetical trial, participants will be instructed to meet sex-specific minimal intakes for vegetables and fruits, whole grains, animal- and plant-based protein foods, milk and plant-based beverages, and unsaturated fats. The eligibility criteria, follow-up, intervention, outcomes, and causal contrast in the emulation will closely align with those of the target trial, with only minor modifications. We will attempt to emulate the randomization of treatment by adjusting for baseline covariates and prebaseline dietary habits. RESULTS Data collection for NuAge was completed in June 2008. For this study, the main analysis was started in May 2024. Submission of the manuscript is expected by February 2025. CONCLUSIONS Emulating a target trial will provide the first evidence of the adequacy of the 2019 Canada’s Food Guide recommendations for older adults in relation to health outcomes. INTERNATIONAL REGISTERED REPORT DERR1-10.2196/65182

Background The Canada’s Food Guide 2019 (CFG) provides universal recommendations to individuals aged 2 years or older. The extent to which these recommendations are appropriate for older adults is unknown. Although ideal, conducting a large randomized controlled trial is unrealistic in the short term. An alternative is the target trial emulation framework for causal inference using observational data. Objective Our aim is to describe the protocol of a target trial emulation in older adults with emphasis on key aspects of a hypothetical sustained diet and physical activity intervention. Methods To emulate the target trial, non-experimental data from the NuAge prospective study (n=1753, adults aged 67 years or older) will be used. NuAge includes 4 yearly measurements of dietary intakes, covariates and outcomes. The per protocol causal contrast will be the primary causal contrast of interest to account for non-adherence. The sustained intervention strategy will be modelled using the parametric g-formula. In the hypothetical trial, participants would be instructed to meet sex-specific minimal intakes for vegetables and fruits, whole grains, animal- and plant-based protein foods, milk & plant-based beverages and unsaturated fats. Eligibility criteria, follow-up, intervention, outcomes, and causal contrast will be similar in the emulation to the target trial except for minor modifications. We will attempt to emulate randomization of treatment by adjusting for baseline covariates and pre-baseline dietary habits. Conclusion Emulating a target trial will provide the first evidence of the adequacy of CFG 2019 recommendations for older adults in relation to health outcomes.

Background Protein leverage (PL) is the phenomenon of consuming food until absolute intake of protein approaches a ‘target value’, such that total energy intake (TEI) varies passively with the ratio of protein: non-protein energy (fat + carbohydrate) in the diet. The PL hypothesis (PLH) suggests that the dilution of protein in energy-dense foods, particularly those rich in carbohydrates and fats, combines with protein leverage to contribute to the global obesity epidemic. Evidence for PL has been reported in younger adults, children and adolescents. This study aimed to test for PL and the protein leverage hypothesis (PLH) in a cohort of older adults. Methods We conducted a retrospective analysis of dietary intake in a cohort of 1699 community-dwelling older adults aged 67–84 years from the NuAge cohort. We computed TEI and the energy contribution (EC) from each macronutrient. The strength of leverage of macronutrients was assessed through power functions (TEI=μ*ECL${TEI}=\mu * {{EC}}^{L}$). Body mass index (BMI) was calculated, and mixture models were fitted to predict TEI and BMI from macronutrients’ ECs. Results In this cohort of older adults, 53% of individuals had obesity and 1.5% had severe cases. The mean TEI was 7673 kJ and macronutrients’ ECs were 50.4%, 33.2% and 16.4%, respectively for carbohydrates, fat, and protein. There was a strong negative association (L = −0.37; p < 0.001) between the protein EC and TEI. Each percent of energy intake from protein reduced TEI by 77 kJ on average, ceteris paribus. However, BMI was unassociated with TEI in this cohort. Conclusions Findings indicate clear evidence for PL on TEI, but not on BMI, likely because of aging, body composition, sarcopenia, or protein wasting.

Introduction: Cardiovascular disease risk factors (CVRFs) contribute to the development of cognitive impairment and dementia. Methods: This study examined the associations between circulating CVRF biomarkers and cognition in 386 cognitively healthy older adults (mean age = 78 ± 4 years, 53% females) selected from the Quebec Longitudinal Study on Nutrition and Successful Aging (NuAge). Memory, executive function, and processing speed were assessed at baseline and 2-year follow-up. CVRF biomarkers included total cholesterol, high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein-cholesterol (LDL-C), triglycerides, glucose, insulin, high sensitivity C-reactive protein (hs-CRP), homocysteine, protein carbonyls, and cortisol. Linear mixed models were used to determine associations between individual CVRF biomarkers and cognition at both time points. Results: HDL-C was most consistently associated with cognition with higher values related to better performance across several domains. Overall, stronger and more consistent relationships between CVRF biomarkers and cognition were observed in females relative to males. Discussion: Findings suggest that increases in the majority of circulating CVRFs are not associated with worse cognition in cognitively healthy older adults.

BACKGROUND: Protein leverage (PL), the phenomenon of food consuming until absolute intake of protein meets a target value, regardless of shortfall or overconsuming for other nutrients in the diet and total energy intake (TEI). Evidence for PL was observed in humans, recently in a cohort of youth with obesity. This study aimed to test for PL and the protein leverage hypothesis (PLH) in a cohort of older adults. METHODS: We conducted a retrospective analysis of dietary intake in a cohort of 1699 community-dwelling older adults aged 67-84 years from the NuAge cohort. We computed TEI and the energy contribution (EC) from each macronutrient. The strength of leverage of macronutrients was assessed through power functions (TEI= μ*〖EC〗^L). Body mass index (BMI) was calculated, and mixture models were fitted to predict TEI and BMI from macronutrient ECs. RESULTS: The mean TEI was 7,673 kJ and macronutrient ECs were 50.4 %, 33.2 % and 16.4 %, respectively for carbohydrates, fat, and protein. High carbohydrate intake was associated with low fat intake. There was a strong negative association (L = -0.37; p < 0.001) between the protein EC and TEI. Each percent of energy intake from protein reduced TEI by 77 kJ on average, ceteris paribus. BMI was unassociated with TEI in this cohort, so the PLH could not be tested here. CONCLUSIONS: Findings indicate clear evidence for PL on TEI, but not on BMI, likely because TEI and BMI become increasingly uncoupled during aging.

Background Little is known about how normal variation in dietary patterns in humans affects the ageing process. To date, most analyses of the problem have used a unidimensional paradigm, being concerned with the effects of a single nutrient on a single outcome. Perhaps then, our ability to understand the problem has been complicated by the fact that both nutrition and the physiology of ageing are highly complex and multidimensional, involving a high number of functional interactions. Here we apply the multidimensional geometric framework for nutrition to data on biological ageing from 1560 older adults followed over four years to assess on a large-scale how nutrient intake associates with the ageing process. Results Ageing and age-related loss of homeostasis (physiological dysregulation) were quantified via the integration of blood biomarkers. The effects of diet were modelled using the geometric framework for nutrition, applied to macronutrients and 19 micronutrients/nutrient subclasses. We observed four broad patterns: (1) The optimal level of nutrient intake was dependent on the ageing metric used. Elevated protein intake improved/depressed some ageing parameters, whereas elevated carbohydrate levels improved/depressed others; (2) There were non-linearities where intermediate levels of nutrients performed well for many outcomes (i.e. arguing against a simple more/less is better perspective); (3) There is broad tolerance for nutrient intake patterns that don’t deviate too much from norms (‘homeostatic plateaus’). (4) Optimal levels of one nutrient often depend on levels of another (e.g. vitamin E and vitamin C). Simpler linear/univariate analytical approaches are insufficient to capture such associations. We present an interactive tool to explore the results in the high-dimensional nutritional space. Conclusion Using multidimensional modelling techniques to test the effects of nutrient intake on physiological dysregulation in an aged population, we identified key patterns of specific nutrients associated with minimal biological ageing. Our approach presents a roadmap for future studies to explore the full complexity of the nutrition-ageing landscape.

Introduction: Higher dietary protein, alone or in combination with physical activity (PA), may slow the loss of age-related muscle strength in older adults. We investigated the longitudinal relationship between protein intake and grip strength, and the interaction between protein intake and PA, using four longitudinal ageing cohorts. Methods: Individual participant data from 5584 older adults (52% women; median: 75, IQR: 71.6, 79.0 years) with up to 8.5 years (mean: 4.9, SD: 2.3 years) of follow-up from the Health ABC, NuAge, LASA and Newcastle 85+ cohorts were pooled. Baseline protein intake was assessed with food frequency questionnaires and 24h recalls and categorized into <0.8, 0.8-<1.0, 1.0-<1.2 and ≥1.2 g/kg adjusted body weight (aBW)/d. The prospective association between protein intake, its interaction with PA, and grip strength (sex- and cohort-specific) was determined using joint models (hierarchical linear mixed effects and a link function for Cox proportional hazards models). Results: Grip strength declined on average by 0.018 SD (95%CI: -0.026, -0.006) every year. No associations were found between protein intake, measured at baseline, and grip strength, measured prospectively, or rate of decline of grip strength in models adjusted for sociodemographic, anthropometric, lifestyle and health variables (e.g., protein intake ≥1.2 vs <0.8 g/kg aBW/d: β= -0.003, 95%CI: -0.014,0.005 SD per year). There also was no evidence of an interaction between protein intake and PA. Conclusions: We failed to find evidence in this study to support the hypothesis that higher protein intake, alone or in combination with higher PA, slowed the rate of grip strength decline in older adults.