Department of Neurology, Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Vagelos College of Physicians and Surgeons, Columbia University, New York, New York, United States of America.
Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht and Utrecht University, Utrecht, The Netherlands.
PLoS One. 2022 Feb 25;17(2):e0264166. doi: 10.1371/journal.pone.0264166. eCollection 2022.
As global populations age, cross-national comparisons of cognitive health and dementia risk are increasingly valuable. It remains unclear, however, whether country-level differences in cognitive function are attributable to population differences or bias due to incommensurate measurement. To demonstrate an effective method for cross-national comparison studies, we aimed to statistically harmonize measures of episodic memory and language function across two population-based cohorts of older adults in the United States (HRS HCAP) and India (LASI-DAD).
Data for 3,496 HRS HCAP (≥65 years) and 3,152 LASI-DAD (≥60 years) participants were statistically harmonized for episodic memory and language performance using confirmatory factor analysis (CFA) methods. Episodic memory and language factor variables were investigated for differential item functioning (DIF) and precision.
CFA models estimating episodic memory and language domains based on a priori adjudication of comparable items fit the data well. DIF analyses revealed that four out of ten episodic memory items and five out of twelve language items measured the underlying construct comparably across samples. DIF-modified episodic memory and language factor scores showed comparable patterns of precision across the range of the latent trait for each sample.
Harmonization of cognitive measures will facilitate future investigation of cross-national differences in cognitive performance and differential effects of risk factors, policies, and treatments, reducing study-level measurement and administrative influences. As international aging studies become more widely available, advanced statistical methods such as those described in this study will become increasingly central to making universal generalizations and drawing valid conclusions about cognitive aging of the global population.
随着全球人口老龄化，跨国比较认知健康和痴呆风险变得越来越有价值。然而，目前尚不清楚认知功能的国家差异是归因于人口差异还是由于测量不一致导致的偏差。为了展示跨国比较研究的有效方法，我们旨在通过统计方法协调美国（HRS HCAP）和印度（LASI-DAD）两个基于人群的老年队列中情景记忆和语言功能的测量。
使用验证性因素分析（CFA）方法，对 3496 名 HRS HCAP（≥65 岁）和 3152 名 LASI-DAD（≥60 岁）参与者的数据进行情景记忆和语言表现的统计协调。研究了情景记忆和语言因子变量的差异项目功能（DIF）和精度。
基于可比项目的预先判断，估计情景记忆和语言领域的 CFA 模型很好地拟合了数据。DIF 分析表明，十个情景记忆项目中有四个和十二个语言项目中有五个在样本之间以可比的方式测量了潜在结构。经过 DIF 修正的情景记忆和语言因子得分在每个样本的潜在特质范围内显示出可比的精度模式。
认知测量的协调将促进未来对认知表现的跨国差异以及风险因素、政策和治疗的差异影响的研究，减少研究水平的测量和管理影响。随着国际老龄化研究的广泛开展，像本研究中描述的这种高级统计方法将越来越成为对全球人口认知老化进行普遍概括和得出有效结论的核心。
