Interdisciplinary and Collaborative Approaches Needed to Determine Impact of COVID-19 on Older Adults and Aging: CAG/ACG and CJA/RCV Joint Statement.

The COVID-19 pandemic and subsequent state of public emergency have significantly affected older adults in Canada and worldwide. It is imperative that the gerontological response be efficient and effective. In this statement, the board members of the Canadian Association on Gerontology/L'Association canadienne de gérontologie (CAG/ACG) and the Canadian Journal on Aging/La revue canadienne du vieillissement (CJA/RCV) acknowledge the contributions of CAG/ACG members and CJA/RCV readers. We also profile the complex ways that COVID-19 is affecting older adults, from individual to population levels, and advocate for the adoption of multidisciplinary collaborative teams to bring together different perspectives, areas of expertise, and methods of evaluation in the COVID-19 response.

Nutrient Patterns and Their Food Sources in Older Persons from France and Quebec: Dietary and Lifestyle Characteristics.

BACKGROUND: Dietary and nutrient patterns have been linked to health outcomes related to aging. Food intake is influenced by environmental and genetic factors. The aim of the present study was to compare nutrient patterns across two elderly populations sharing a common ancestral cultural background, but living in different environments. METHODS: The diet quality, lifestyle and socioeconomic characteristics of participants from the Three-City Study (3C, France, n = 1712) and the Québec Longitudinal Study on Nutrition and Successful Aging (NuAge, Quebec, Canada, n = 1596) were analyzed. Nutrient patterns and their food sources were identified in the two samples using principal component analysis. Diet quality was compared across sample-specific patterns by describing weekly food intake and associations with the Canadian Healthy Eating Index (C-HEI). RESULTS: Three nutrient patterns were retained in each study: a healthy, a Western and a more traditional pattern. These patterns accounted for 50.1% and 53.5% of the total variance in 3C and NuAge, respectively. Higher education and non-physical occupations over lifetime were associated with healthy patterns in both studies. Other characteristics such as living alone, having a body mass index lower than 25 and being an ex-smoker were associated with the healthy pattern in NuAge. No association between these characteristics and the nutrient patterns was noted in 3C. The healthy and Western patterns from each sample also showed an inverse association with C-HEI. CONCLUSION: The two healthy patterns showed important similarities: adequate food variety, consumption of healthy foods and associations with common sociodemographic factors. This work highlights that nutrient patterns derived using a posteriori methods may be useful to compare the nutritional quality of the diet of distinct populations.

Individual and collective factors predicting change in diet quality over 3 years in a subset of older men and women from the NuAge cohort.

PURPOSE: This study examined individual and collective factors as predictors of change in global diet quality (DQ). METHODS: Subjects were 373 older adults (57 % female) aged 68-82 years at recruitment (T1) into the NuAge Cohort Study, and followed for three years. Data were collected by questionnaires, physical performance tests and anthropometric measurements. Diet was assessed at T1 and T4 using three non-consecutive 24-h diet recalls (24HR) and DQ (Canadian Healthy Eating Index), and was computed on the means of the 24HR. DQ change over three years was determined as "DQT4-DQT1". Baseline (T1) measures significantly correlated with DQ at T1 were entered into backward stepwise linear regression analyses along with selected theoretical constructs and controlled for baseline DQ to determine predictors of change in DQ over 3 years. RESULTS: Among men, education (p = .009) and sensations of hunger (p = .01) were positive predictors of DQ change over time, while DQ at T1 (p < .0001), cognition (p = .003) and social network (p = .019) were negative predictors (adjusted R (2) = 30.4 %). Finally, among women, diet knowledge (p = .044) was a positive predictor of DQ change, while DQ at T1 (p < .0001) and social network (p = .033) were negative predictors of DQ change over 3 years (adjusted R (2) = 24.1 %). CONCLUSIONS: These results can inform dietary intervention programmes targeting gender-specific determinants of diet quality in older adults.

Diet quality and cognition among older adults from the NuAge study.

BACKGROUND AND OBJECTIVES: A healthy diet may prevent cognitive decline either directly, or by decreasing risk of nutrition-related chronic diseases associated with cognitive decline. This study examined the relationships between diet quality (DQ) and cognition for over 3 years among 1488 older adults (52.6% female) from the NuAge study, aged 67 to 84 years at recruitment. METHODS: Cognition was assessed at four annual visits using the modified mini-mental status examination (3MS); rate of cognitive decline was computed for each participant over the 3 years of follow-up using mixed model analyses and the individual-specific number of months between 3MS assessments. Dietary data were collected at recruitment using a validated 78-item, semi-quantitative food frequency questionnaire (FFQ). DQ was characterized as the Canadian Healthy Eating Index (C-HEI), a 9-component global DQ index (maximum score=100) computed from the FFQ output. Other variables were collected by questionnaire or direct measurement. Multivariate analyses were carried out to assess the association of DQ controlled for confounders on cognition. RESULTS: Total C-HEI was better in females (78.7±9.1 vs 75.7±9.4, p<.0001) as were C-HEI component subscores. Males, the less educated, smokers, those with poor social engagement, symptoms of depression, a higher waist:hip ratio and who reported financial insecurity had a poor quality diet that could contribute to chronic diseases associated with cognition. Along with functional autonomy, most of these variables emerged as covariates of baseline 3MS and predictors of cognitive decline. While certain C-HEI subscores and total C-HEI were positive univariate correlates of 3MS at recruitment, total DQ was not associated with cognition in multivariate analyses, either at baseline or over 3 years of follow-up. CONCLUSIONS: DQ was not independently associated with cognition. However, the study demonstrates relationships between diet quality and risk factors for chronic diseases associated with cognition. Consequently, older adults might benefit from a healthy diet to decrease risk of nutrition-related chronic diseases established as risk factors for cognitive decline. Further work in diverse older populations, use of dietary data collected earlier in life, finer cognitive measures and longer follow-up are necessary to better elucidate relationships between diet quality, chronic diseases and cognition.