Author response: Dietary patterns during adulthood and cognitive performance in midlife: The CARDIA study
ClaireMcEvoy, Assistant Professor, Queen's University Belfast
Submitted December 17, 2019
The authors thank Muñoz-Garcia et al. for their comments on our study.1 Our study builds on earlier work showing that improvement of diet quality score over 20 years was associated with better performance in cognitive function tests at mean age 50 years.3 We agree that examining the influence of diet on cognitive decline during aging in this cohort will help determine if dietary interventions modify the risk of cognitive impairment, and we plan to pursue this in future work.
The mean (SD) MoCA score in our sample was 24 (3.9) and may be partly explained by the diversity of the population (45% Black). While MoCA has not been widely studied in minority populations, optimal cut-offs vary by race and ethnicity.4 Mean MoCA score in community-based Caucasians are reported to be lower than 26 but significantly higher than in other racial groups.4,5 Prior studies have reported mean MoCA score of between 19.8 and 22 in Black middle-aged US adults, most of whom had 12 or more years of education.4,5 Clearly, further research is required to explain the variability in MoCA score in diverse populations. For these reasons, we adopted a conservative approach in the analysis by applying 1SD below the population mean MoCA score to identify individuals with clinically relevant poor global cognitive function. Using the suggested MoCA cut-off of 26 meant that 58% of our community-based sample falls in the mild cognitive impairment range, which we feel is misleading. When the models are repeated for MoCA<26, effect estimates were attenuated but the overall pattern of findings are similar to those reported in the main study. Odds ratios (95% confidence interval) in fully adjusted models comparing extreme tertiles of the three dietary scores were 0.63 (0.50-0.80) for MedDiet, 0.58 (0.45-0.76) for APDQS, and 1.05 (0.84-1.31) for DASH.
Disclosure
The author reports no relevant disclosures. Contact journal@neurology.org for full disclosures.
References
McEvoy CT, Hoang T, Sidney S, et al. Dietary patterns during adulthood and cognitive performance in midlife: The CARDIA study. Neurology 2019;92:e1589–e1599.
Zhu N, Jacobs DR, Meyer KA, et al. Cognitive function in a middle aged cohort is related to higher quality dietary pattern 5 and 25 years earlier: the CARDIA study. J Nutr Health Aging 2015;19:33–38.
Milani SA, Marsiske M, Cottler LB, Chen X, Striley CW. Optimal cutoffs for the Montreal Cognitive Assessment vary by race and ethnicity. Alzheimers Dement (Amst). 2018;10:773–781.
Rossetti HC, Lacritz LH, Cullum CM, Weiner MF. Normative data for the Montreal Cognitive Assessment (MoCA) in a population-based sample. Neurology 2011;77:1272–1275.
Sink KM, Craft S, Smith SC, et al. Montreal Cognitive Assessment and Modified Mini Mental State Examination in African Americans. J Aging Res 2015;2015:872018.
Editor’s Note: Dietary patterns during adulthood and cognitive performance in midlife: The CARDIA study
Roy Hamilton, Associate Professor, University of Pennsylvania
The comments below seem accurate and appropriate to discuss in order to more fully understand the data. Having said that, the notion that different populations may have different mean performance on psychometric tests is a delicate subject. Evidence points increasingly to the relevance of racial identity as a socially rather than biologically relevant distinction. Race in this context serves a proxy for a host of influences--for example, institutionalized differences in educational quality (but also many others)--that can impact performance on psychometric measures. A body of evidence indicates that when these factors are accounted for, they explain differences in psychometric performance deemed attributable to racial identity.
The authors thank Muñoz-Garcia et al. for their comments on our study.1 Our study builds on earlier work showing that improvement of diet quality score over 20 years was associated with better performance in cognitive function tests at mean age 50 years.3 We agree that examining the influence of diet on cognitive decline during aging in this cohort will help determine if dietary interventions modify the risk of cognitive impairment, and we plan to pursue this in future work.
The mean (SD) MoCA score in our sample was 24 (3.9) and may be partly explained by the diversity of the population (45% Black). While MoCA has not been widely studied in minority populations, optimal cut-offs vary by race and ethnicity.4 Mean MoCA score in community-based Caucasians are reported to be lower than 26 but significantly higher than in other racial groups.4,5 Prior studies have reported mean MoCA score of between 19.8 and 22 in Black middle-aged US adults, most of whom had 12 or more years of education.4,5 Clearly, further research is required to explain the variability in MoCA score in diverse populations. For these reasons, we adopted a conservative approach in the analysis by applying 1SD below the population mean MoCA score to identify individuals with clinically relevant poor global cognitive function. Using the suggested MoCA cut-off of 26 meant that 58% of our community-based sample falls in the mild cognitive impairment range, which we feel is misleading. When the models are repeated for MoCA<26, effect estimates were attenuated but the overall pattern of findings are similar to those reported in the main study. Odds ratios (95% confidence interval) in fully adjusted models comparing extreme tertiles of the three dietary scores were 0.63 (0.50-0.80) for MedDiet, 0.58 (0.45-0.76) for APDQS, and 1.05 (0.84-1.31) for DASH.
Disclosure
The author reports no relevant disclosures. Contact journal@neurology.org for full disclosures.
References
Editor’s Note: Dietary patterns during adulthood and cognitive performance in midlife: The CARDIA study
The comments below seem accurate and appropriate to discuss in order to more fully understand the data. Having said that, the notion that different populations may have different mean performance on psychometric tests is a delicate subject. Evidence points increasingly to the relevance of racial identity as a socially rather than biologically relevant distinction. Race in this context serves a proxy for a host of influences--for example, institutionalized differences in educational quality (but also many others)--that can impact performance on psychometric measures. A body of evidence indicates that when these factors are accounted for, they explain differences in psychometric performance deemed attributable to racial identity.