Andrea Lauren Christman Schneider, Anny Reyes, James A Henegan, Vidyulata Kamath, Lisa Wruck, James Russell Pike, Alden Gross, Keenan Walker, Anna Kucharska-Newton, Josef Coresh, Thomas H Mosley, Rebecca F Gottesman, Michael Griswold
{"title":"评估基于种族认知规范模型的健康社会决定因素替代方案。","authors":"Andrea Lauren Christman Schneider, Anny Reyes, James A Henegan, Vidyulata Kamath, Lisa Wruck, James Russell Pike, Alden Gross, Keenan Walker, Anna Kucharska-Newton, Josef Coresh, Thomas H Mosley, Rebecca F Gottesman, Michael Griswold","doi":"10.1212/WNL.0000000000210030","DOIUrl":null,"url":null,"abstract":"<p><strong>Background and objectives: </strong>Race and ethnicity are proxy measures of sociocultural factors that influence cognitive test performance. Our objective was to compare different regression-based cognitive normative models adjusting for demographics and different combinations of easily accessible/commonly used social determinants of health (SDoH) factors, which may help describe cognitive performance variability historically captured by ethnoracial differences.</p><p><strong>Methods: </strong>We performed cross-sectional analyses on data from Black and White participants without mild cognitive impairment/dementia in the Atherosclerosis Risk in Communities Study who attended visit 5 in 2011-2013. Participants underwent a battery of 11 cognitive tests (3 domains: memory, executive function, language). We fit 6 separate normative models for each cognitive test, all including age and education, with different combinations of race, the Wide Range of Achievement Test (education quality proxy), and area deprivation index (neighborhood deprivation) associated with current residence. We compared model fits and calculated concordances/discordances between models using z-scores derived from each normative model and a z-score <-1.5 threshold for impairment.</p><p><strong>Results: </strong>Participants (n = 2,392) had a mean age of 74.4 years, 60.4% were female, and 17.1% were of self-reported Black race. The \"Full\" model with race alongside demographic and SDoH measures consistently outperformed other nested submodels (likelihood ratios ≥ 100) for all domains/tests except Delayed Word Recall. Models with education quality alone (\"WRAT\") generally outperformed models with neighborhood deprivation (\"ADI\") or race (\"Race\") alone for memory and language tests while \"Race\" models performed better for executive function tests. Adding neighborhood deprivation to education quality (\"WRAT + ADI\") did not improve models vs using \"WRAT\" alone. Across all domains/tests, the concordance compared with the \"Full\" model was lower for \"Education\" and \"ADI\" models than for other nested models. Although numbers were small, there was greater discordance among Black (range = 8.2%-23.2%) compared with White (range = 2.2%-3.4%) participants, particularly for Boston Naming Test and executive function tests.</p><p><strong>Discussion: </strong>Education quality outperformed neighborhood disadvantage as an additional/alternative SDoH measure in normative models and may be useful to collect in cognitive aging studies. While performance varied across cognitive domains and tests, routinely reported SDoH variables (education level, education quality, late-life neighborhood deprivation) did not fully account for observed ethnoracial variability; future work should evaluate SDoH across the lifespan in more ethnoracially diverse populations.</p>","PeriodicalId":19256,"journal":{"name":"Neurology","volume":"103 11","pages":"e210030"},"PeriodicalIF":7.7000,"publicationDate":"2024-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11567649/pdf/","citationCount":"0","resultStr":"{\"title\":\"Evaluating Social Determinants of Health-Based Alternatives to Race-Based Cognitive Normative Models.\",\"authors\":\"Andrea Lauren Christman Schneider, Anny Reyes, James A Henegan, Vidyulata Kamath, Lisa Wruck, James Russell Pike, Alden Gross, Keenan Walker, Anna Kucharska-Newton, Josef Coresh, Thomas H Mosley, Rebecca F Gottesman, Michael Griswold\",\"doi\":\"10.1212/WNL.0000000000210030\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background and objectives: </strong>Race and ethnicity are proxy measures of sociocultural factors that influence cognitive test performance. Our objective was to compare different regression-based cognitive normative models adjusting for demographics and different combinations of easily accessible/commonly used social determinants of health (SDoH) factors, which may help describe cognitive performance variability historically captured by ethnoracial differences.</p><p><strong>Methods: </strong>We performed cross-sectional analyses on data from Black and White participants without mild cognitive impairment/dementia in the Atherosclerosis Risk in Communities Study who attended visit 5 in 2011-2013. Participants underwent a battery of 11 cognitive tests (3 domains: memory, executive function, language). We fit 6 separate normative models for each cognitive test, all including age and education, with different combinations of race, the Wide Range of Achievement Test (education quality proxy), and area deprivation index (neighborhood deprivation) associated with current residence. We compared model fits and calculated concordances/discordances between models using z-scores derived from each normative model and a z-score <-1.5 threshold for impairment.</p><p><strong>Results: </strong>Participants (n = 2,392) had a mean age of 74.4 years, 60.4% were female, and 17.1% were of self-reported Black race. The \\\"Full\\\" model with race alongside demographic and SDoH measures consistently outperformed other nested submodels (likelihood ratios ≥ 100) for all domains/tests except Delayed Word Recall. Models with education quality alone (\\\"WRAT\\\") generally outperformed models with neighborhood deprivation (\\\"ADI\\\") or race (\\\"Race\\\") alone for memory and language tests while \\\"Race\\\" models performed better for executive function tests. Adding neighborhood deprivation to education quality (\\\"WRAT + ADI\\\") did not improve models vs using \\\"WRAT\\\" alone. Across all domains/tests, the concordance compared with the \\\"Full\\\" model was lower for \\\"Education\\\" and \\\"ADI\\\" models than for other nested models. Although numbers were small, there was greater discordance among Black (range = 8.2%-23.2%) compared with White (range = 2.2%-3.4%) participants, particularly for Boston Naming Test and executive function tests.</p><p><strong>Discussion: </strong>Education quality outperformed neighborhood disadvantage as an additional/alternative SDoH measure in normative models and may be useful to collect in cognitive aging studies. While performance varied across cognitive domains and tests, routinely reported SDoH variables (education level, education quality, late-life neighborhood deprivation) did not fully account for observed ethnoracial variability; future work should evaluate SDoH across the lifespan in more ethnoracially diverse populations.</p>\",\"PeriodicalId\":19256,\"journal\":{\"name\":\"Neurology\",\"volume\":\"103 11\",\"pages\":\"e210030\"},\"PeriodicalIF\":7.7000,\"publicationDate\":\"2024-12-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11567649/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Neurology\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1212/WNL.0000000000210030\",\"RegionNum\":1,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2024/11/15 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q1\",\"JCRName\":\"CLINICAL NEUROLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Neurology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1212/WNL.0000000000210030","RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/11/15 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"CLINICAL NEUROLOGY","Score":null,"Total":0}
Evaluating Social Determinants of Health-Based Alternatives to Race-Based Cognitive Normative Models.
Background and objectives: Race and ethnicity are proxy measures of sociocultural factors that influence cognitive test performance. Our objective was to compare different regression-based cognitive normative models adjusting for demographics and different combinations of easily accessible/commonly used social determinants of health (SDoH) factors, which may help describe cognitive performance variability historically captured by ethnoracial differences.
Methods: We performed cross-sectional analyses on data from Black and White participants without mild cognitive impairment/dementia in the Atherosclerosis Risk in Communities Study who attended visit 5 in 2011-2013. Participants underwent a battery of 11 cognitive tests (3 domains: memory, executive function, language). We fit 6 separate normative models for each cognitive test, all including age and education, with different combinations of race, the Wide Range of Achievement Test (education quality proxy), and area deprivation index (neighborhood deprivation) associated with current residence. We compared model fits and calculated concordances/discordances between models using z-scores derived from each normative model and a z-score <-1.5 threshold for impairment.
Results: Participants (n = 2,392) had a mean age of 74.4 years, 60.4% were female, and 17.1% were of self-reported Black race. The "Full" model with race alongside demographic and SDoH measures consistently outperformed other nested submodels (likelihood ratios ≥ 100) for all domains/tests except Delayed Word Recall. Models with education quality alone ("WRAT") generally outperformed models with neighborhood deprivation ("ADI") or race ("Race") alone for memory and language tests while "Race" models performed better for executive function tests. Adding neighborhood deprivation to education quality ("WRAT + ADI") did not improve models vs using "WRAT" alone. Across all domains/tests, the concordance compared with the "Full" model was lower for "Education" and "ADI" models than for other nested models. Although numbers were small, there was greater discordance among Black (range = 8.2%-23.2%) compared with White (range = 2.2%-3.4%) participants, particularly for Boston Naming Test and executive function tests.
Discussion: Education quality outperformed neighborhood disadvantage as an additional/alternative SDoH measure in normative models and may be useful to collect in cognitive aging studies. While performance varied across cognitive domains and tests, routinely reported SDoH variables (education level, education quality, late-life neighborhood deprivation) did not fully account for observed ethnoracial variability; future work should evaluate SDoH across the lifespan in more ethnoracially diverse populations.
期刊介绍:
Neurology, the official journal of the American Academy of Neurology, aspires to be the premier peer-reviewed journal for clinical neurology research. Its mission is to publish exceptional peer-reviewed original research articles, editorials, and reviews to improve patient care, education, clinical research, and professionalism in neurology.
As the leading clinical neurology journal worldwide, Neurology targets physicians specializing in nervous system diseases and conditions. It aims to advance the field by presenting new basic and clinical research that influences neurological practice. The journal is a leading source of cutting-edge, peer-reviewed information for the neurology community worldwide. Editorial content includes Research, Clinical/Scientific Notes, Views, Historical Neurology, NeuroImages, Humanities, Letters, and position papers from the American Academy of Neurology. The online version is considered the definitive version, encompassing all available content.
Neurology is indexed in prestigious databases such as MEDLINE/PubMed, Embase, Scopus, Biological Abstracts®, PsycINFO®, Current Contents®, Web of Science®, CrossRef, and Google Scholar.