Exploring associations of greenery, air pollution and walkability with cardiometabolic health in people at midlife and beyond

Alison Carver; Richard Beare; Luke D Knibbs; Suzanne Mavoa; Kaya Grocott; Amanda J Wheeler; Velandai Srikanth; Nadine E Andrew

doi:10.1111/ggi.14743

Exploring associations of greenery, air pollution and walkability with cardiometabolic health in people at midlife and beyond

Geriatr Gerontol Int. 2024 Mar:24 Suppl 1:208-214. doi: 10.1111/ggi.14743. Epub 2023 Dec 19.

Authors

Alison Carver^{1

2

3}, Richard Beare^{1

2

3

4}, Luke D Knibbs^{5

6}, Suzanne Mavoa⁷, Kaya Grocott⁸, Amanda J Wheeler⁹, Velandai Srikanth^{1

2

3}, Nadine E Andrew^{1

2

3}

Affiliations

¹ National Centre for Healthy Ageing, Melbourne, Victoria, Australia.
² Peninsula Clinical School, Central Clinical school, Faculty of Medicine, Monash University, Melbourne, Victoria, Australia.
³ Peninsula Health, Melbourne, Victoria, Australia.
⁴ Developmental Imaging, Murdoch Children's Research Institute, Melbourne, Victoria, Australia.
⁵ School of Public Health, The University of Sydney, Sydney, New South Wales, Australia.
⁶ Public Health Research Analytics and Methods for Evidence, Public Health Unit, Sydney Local Health District, Camperdown, New South Wales, Australia.
⁷ Environmental Protection Authority, Melbourne, Victoria, Australia.
⁸ University of Melbourne, Melbourne, Victoria, Australia.
⁹ CSIRO, Aspendale, Victoria, Australia.

PMID: 38115171
DOI: 10.1111/ggi.14743

Abstract

Aim: To examine associations of neighborhood greenery, air pollution and walkability with cardiometabolic disease in adults aged ≥45 years in the Frankston-Mornington Peninsula region, Victoria, Australia.

Methods: A cross-sectional, ecological study design was used. We assessed mean annual neighborhood greenery using the Normalized Difference Vegetation Index; air pollution (fine particulate matter of diameter ≤2.5 μm [PM_2.5] and NO₂) using land-use regression models; and walkability using Walk Score (possible values 0-100). Medically diagnosed diabetes (~95% type-2), heart disease and stroke were self-reported in the Australian Census (2021). Multivariable regression was used to model associations between environmental exposures and area-level (neighborhood) cardiometabolic disease prevalence (age group ≥45 years), with socioeconomic status, age and sex as covariates. Air pollution was examined as a mediator of associations between greenery and disease prevalence.

Results: Our sample comprised 699 neighborhoods with the following mean (SD) values: Normalized Difference Vegetation Index 0.47 (0.09), PM_2.5, 8.5 (0.6) μg/m³ and NO₂, 5.2 (1.6) ppb. Disease prevalences were: heart disease, mean 8.9% (4.5%); diabetes, mean 10.3% (4.7%); and stroke, median 1.2% (range 0-10.9%). Greenery was negatively associated with diabetes (β = -5.85, 95% CI -9.53, -2.17) and stroke prevalence (β = -1.26, 95% CI -2.11, -0.42). PM_2.5 and NO₂ were positively associated with diabetes (β = 1.59, 95% CI 1.00, 2.18; β = 0.42, 95% CI 0.22, 0.62) and stroke prevalence (β = 0.15, 95% CI 0.01, 0.29; β = 0.06, 95% CI 0.01, 0.10). The association between greenery and diabetes was partially mediated by PM_2.5 (mediated effect -5.38, 95% CI -7.84, -3.03).

Conclusions: Greenery and air pollutants were associated with lower and higher prevalence, respectively, of self-reported diabetes and, to a lesser extent, stroke. These ecological findings require further exploration with stronger, longitudinal study designs to inform public health policy and directions. Geriatr Gerontol Int 2024; 24: 208-214.

Keywords: air pollution; cardiometabolic disease; greenery; older adults; walkability.

MeSH terms

Air Pollution* / adverse effects
Air Pollution* / analysis
Cross-Sectional Studies
Diabetes Mellitus* / epidemiology
Heart Diseases*
Humans
Longitudinal Studies
Nitrogen Dioxide / analysis
Particulate Matter / adverse effects
Particulate Matter / analysis
Stroke* / epidemiology
Victoria / epidemiology

Substances

Nitrogen Dioxide
Particulate Matter