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A latent class analysis of cognitive decline in US adults, BRFSS 2015-2020
Snead, Ryan Dumenci, Levent
Snead, Ryan
Dumenci, Levent
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Journal article
Date
2022-08-16
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Epidemiology and Biostatistics
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http://dx.doi.org/10.1186/s12889-022-14001-2
Abstract
Background: Cognitive decline can be an early indicator for dementia. Using quantitative methods and national representative survey data, we can monitor the potential burden of disease at the population-level. Methods: BRFSS is an annual, nationally representative questionnaire in the United States. The optional cognitive decline module is a six-item self-reported scale pertaining to challenges in daily life due to memory loss and growing confusion over the past twelve months. Respondents are 45+, pooled from 2015-2020. Latent class analysis was used to determine unobserved subgroups of subjective cognitive decline (SCD) based on item response patterns. Multinomial logistic regression predicted latent class membership from socio-demographic covariates. Results: A total of 54,771 reported experiencing SCD. The optimal number of latent classes was three, labeled as Mild, Moderate, and Severe SCD. Thirty-five percent of the sample belonged to the Severe group. Members of this subgroup were significantly less likely to be older (65+ vs. 45-54 OR = 0.29, 95% CI: 0.23-0.35) and more likely to be non-Hispanic Black (OR = 1.80, 95% CI: 1.53-2.11), have not graduated high school (OR = 1.60, 95% CI: 1.34-1.91), or earned <$15K a year (OR = 3.03, 95% CI: 2.43-3.77). Conclusions: This study determined three latent subgroups indicating severity of SCD and identified socio-demographic predictors. Using a single categorical indicator of SCD severity instead of six separate items improves the versatility of population-level surveillance.
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Snead, R., Dumenci, L. & Jones, R.M. A latent class analysis of cognitive decline in US adults, BRFSS 2015-2020. BMC Public Health 22, 1560 (2022). https://doi.org/10.1186/s12889-022-14001-2
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BMC Public Health, Vol. 22
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