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J Prev Alzheimers Dis ; 11(3): 710-720, 2024.
Article in English | MEDLINE | ID: mdl-38706287

ABSTRACT

BACKGROUND: The potential for greenness as a novel protective factor for Alzheimer's disease (AD) requires further exploration. OBJECTIVES: This study assesses prospectively and longitudinally the association between precision greenness - greenness measured at the micro-environmental level, defined as the Census block - and AD incidence. DESIGN: Older adults living in consistently high greenness Census blocks across 2011 and 2016 were compared to those living in consistently low greenness blocks on AD incidence during 2012-2016. SETTING: Miami-Dade County, Florida, USA. PARTICIPANTS: 230,738 U.S. Medicare beneficiaries. MEASUREMENTS: U.S. Centers for Medicare and Medicaid Services Chronic Condition Algorithm for AD based on ICD-9 codes, Normalized Difference Vegetation Index, age, sex, race/ethnicity, neighborhood income, and walkability. RESULTS: Older adults living in the consistently high greenness tertile, compared to those in the consistently low greenness tertile, had 16% lower odds of AD incidence (OR=0.84, 95% CI: 0.76-0.94, p=0.0014), adjusting for age, sex, race/ethnicity, and neighborhood income. Age, neighborhood income and walkability moderated greenness' relationship to odds of AD incidence, such that younger ages (65-74), lower-income, and non-car dependent neighborhoods may benefit most from high greenness. CONCLUSIONS: High greenness, compared to low greenness, is associated with lower 5-year AD incidence. Residents who are younger and/or who reside in lower-income, walkable neighborhoods may benefit the most from high greenness. These findings suggest that consistently high greenness at the Census block-level, may be associated with reduced odds of AD incidence at a population level.


Subject(s)
Alzheimer Disease , Humans , Alzheimer Disease/epidemiology , Female , Aged , Male , Florida/epidemiology , Longitudinal Studies , United States/epidemiology , Incidence , Aged, 80 and over , Neighborhood Characteristics , Medicare/statistics & numerical data , Residence Characteristics , Prospective Studies
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