Uncovering the Biological Toll of Neighborhood Physical Disorder: Links to Metabolic and Inflammatory Biomarkers in Older Adults

Abstract

Background Neighborhood physical disorder has been linked to adverse health outcomes, yet longitudinal assessments of its relationship with metabolic and inflammatory biomarkers in older adults remain limited. This study examined the association between patterns of neighborhood physical disorder exposure and biomarkers among older adults. Methods We included community-dwelling Medicare beneficiaries with 2017 biomarker data from the National Health and Aging Trends Study (n = 4,558). Neighborhood physical disorder from 2011 to 2016 was assessed using interviewer reports of neighborhood characteristics. Latent class analysis was employed to identify longitudinal patterns of exposure. Inverse probability weighted linear regression models were used to examine associations between physical disorder patterns and five biomarkers, including body mass index (BMI), waist circumference, hemoglobin A1C (HbA1c), high-sensitivity C-reactive protein (hsCRP), and interleukin-6 (IL-6). Results Four classes of neighborhood physical disorder emerged: stable low exposure (85%), increased exposure (4%), decreased exposure (8%), and stable high exposure (3%). Regression findings indicate that residing in neighborhoods with stable high exposure was significantly associated with higher levels of BMI (b = 0.06, p<0.05), HbA1c (b = 0.09, p<0.05), hsCRP (b = 0.21, p < 0.05), and IL-6 (b = 0.22, p < 0.05), compared to those with stable low exposure. Older adults with increased exposure and decreased exposure also exhibited elevated risks in multiple metabolic and inflammation biomarkers. Conclusions Persistent exposure to neighborhood physical disorder is associated with higher levels of metabolic and inflammatory biomarkers, underscoring the need for targeted clinical screening and neighborhood initiatives to promote healthy aging in place.

Competing Interest Statement

The authors have declared no competing interest.

Funding Statement

The preparation of this article was supported in part by the National Institute on Aging of the National Institutes of Health (R01AG077529, P30AG021342) and the University of Minnesota Life Course Center on the Demography and Economics of Aging (P30AG066613), funded through a grant from the National Institute on Aging. The National Health and Aging Trends Study is sponsored by the National Institute on Aging (U01AG032947) and was conducted by Johns Hopkins University and the University of Michigan. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

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I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.

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The study used publicly available data from the National Health and Aging Trends Study. The National Health and Aging Trends Study can be accessed via https://nhats.org/researcher.

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Data Availability

All data produced in the present study are available upon reasonable request to the authors

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