Dataset Information

Greater tree cover near residence is associated with reduced allostatic load in residents of central North Carolina.

ABSTRACT:

Background

Among urban residents, increased contacts with nature are associated with reduced morbidity and mortality. The concept of allostatic load, a biomarker-based composite measure of physiological dysregulation, can be applied to study subclinical benefits of exposure, and to elucidate pathways leading to improved health.

Objective

This research explored associations between residential vegetated land cover and an allostatic load index calculated using the statistical distance measure known as Mahalanobis distance.

Methods

This cross-sectional population-based study involved 186 adult residents of the Durham-Chapel Hill, North Carolina metropolitan area. Measures of tree and grass cover within 500 m of residence were derived from the U.S. Environmental Protection Agency's EnviroAtlas land cover database. Fifteen biomarkers of immune, neuroendocrine, and metabolic functions were analyzed in serum samples. Regression analysis was conducted using generalized additive models with thin-plate spline functions of geographic coordinates, adjusting for modelled traffic air pollution from local sources and sociodemographic covariates.

Results

The second and third tertiles of distance-weighted tree cover were associated with 14% (95% Confidence Limits 20%; 8%) and 15% (21%; 8%) reduction in adjusted median allostatic load, respectively, compared to the first tertile. The same tertiles of tree cover were also associated with 0.16 (0.03; 0.76) and 0.04 (0.01; 0.35) adjusted odds ratios of having allostatic load index above the 90th percentile of the sample distribution. Grass cover was inversely correlated with tree cover and was not associated with reduced allostatic load.

Conclusions

Subclinical beneficial health effects of green spaces demonstrated in this study are consistent with reduced susceptibility to acute environmental and social stressors, and reduced risks of morbidity and mortality.

SUBMITTER: Egorov AI

PROVIDER: S-EPMC7584403 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundGreater exposure to urban green spaces has been linked to reduced risks of depression, cardiovascular disease, diabetes and premature death. Alleviation of chronic stress is a hypothesized pathway to improved health. Previous studies linked chronic stress with a biomarker-based composite measure of physiological dysregulation known as allostatic load.ObjectiveThis study's objective was to assess the relationship between vegetated land cover near residences and allostatic load.MethodsThis cross-sectional population-based study involved 206 adult residents of the Durham-Chapel Hill, North Carolina metropolitan area. Exposure was quantified using high-resolution metrics of trees and herbaceous vegetation within 500m of each residence derived from the U.S. Environmental Protection Agency's EnviroAtlas land cover dataset. Eighteen biomarkers of immune, neuroendocrine, and metabolic functions were measured in serum or saliva samples. Allostatic load was defined as a sum of potentially unhealthy biomarker values dichotomized at 10th or 90th percentile of sample distribution. Regression analysis was conducted using generalized additive models with two-dimensional spline smoothing function of geographic coordinates, weighted measures of vegetated land cover allowing decay of effects with distance, and geographic and demographic covariates.ResultsAn inter-quartile range increase in distance-weighted vegetated land cover was associated with 37% (95% Confidence Limits 46%; 27%) reduced allostatic load; significantly reduced adjusted odds of having low level of norepinephrine, dopamine, and dehydroepiandrosterone, and high level of epinephrine, fibrinogen, vascular cell adhesion molecule-1, and interleukin-8 in serum, and α-amylase in saliva; and reduced odds of previously diagnosed depression.ConclusionsThe observed effects of vegetated land cover on allostatic load and individual biomarkers are consistent with prevention of depression, cardiovascular disease and premature mortality.

Project description:Background Prevention of hearing loss via addressing potentially modifiable risk factors may offer means of reducing the global burden of hearing loss. Prior studies reported associations between individual markers of inflammation and risk of hearing impairment. Allostatic load is an index of cumulative physiological stressors, including inflammation, to multiple biological systems. Our aims were to investigate associations between allostatic load and both audiometric and self-reported hearing impairment and examine whether associations are stronger over time due to prolonged high allostatic load. Methods Data were taken from the English Longitudinal Study of Ageing (ELSA), a nationally representative study of people aged 50+ living in England over 3 time points between 2008 and 2014. Allostatic load score was comprised of thirteen different measures available at baseline and 4 years post-baseline (high-density lipoprotein/total cholesterol, triglyceride, fibrinogen, haemoglobin A1c, C-reactive protein, insulin-like growth factor 1 (IGF-1), systolic and diastolic blood pressure, mean arterial pressure, resting pulse rate, peak expiratory flow, BMI and waist circumference), measured using clinical cut-off points for normal biomarker parameters. Hearing acuity was measured with a simple handheld tone-producing device at follow-up 7 years post-baseline, while self-reported hearing impairment was measured at time point. Results We included samples of 4373 and 4430 for the cross-sectional and longitudinal analysis, respectively. In the cross-sectional model high allostatic load was associated both self-reported (OR = 1.08, 95% CI 1.0,1.1; p < 0.01) and objective hearing loss (OR = 1.10, 95% CI 1.1,1.2; p < 0.001) adjusting for age and sex. Cross-sectional associations between allostatic load and hearing were not significant after further adjustment for covariates (qualification, physical activity and smoking). In longitudinal modelling, high allostatic load was associated with both audiometric (Z score OR = 1.11, 95% CI 1.1,1.2; p < 0.001) and self-reported hearing impairment (OR = 1.08, 95% CI 1.0,1.1; p < 0.001) adjusting for age and sex. Allostatic load was no longer associated with self-reported hearing loss but the association with audiometric hearing impairment (OR = 1.08, 95% CI 1.03,1.13; p < 0.001) remained following additional adjustment for baseline self-reported hearing, education, physical activity, and smoking. Conclusions Prolonged high allostatic load was associated with risk of hearing impairment. Reducing allostatic load via healthy lifestyle changes including non-smoking, healthy diet and exercise may offer an opportunity to reduce the risk of hearing impairment in later life. Highlights • Allostatic load captures cumulative physiological stress which has consequence for subsequent hearing function.• Prolonged high allostatic load was associated with risk of objectively measured hearing impairment.• This association is shown in nationally representative longitudinal ageing study.

Project description:Allostatic load is commonly operationalized using a sum-score of high-risk biomarkers. However, this method implies that biomarkers contribute equally to allostatic load, as each is given equal weight. Our goal in this methodological paper is to evaluate this, and complementarily, to identify biomarkers that are most informative and least informative for developing an allostatic load index. Item response theory models provide an alternate approach to calculating the allostatic load score, by treating individual biomarkers (e.g. “items”) as indicators of a latent allostatic load construct. Item response theory scores account for the data-driven discriminating power of each biomarker, and an individual’s pattern of biomarker responses. To demonstrate feasibility of this approach, we used data from the 2015–2016 National Health Examination and Nutrition Survey (NHANES; N = 3751), with twelve allostatic load biomarkers representing immune response, metabolic function and cardiovascular health. Item response theory models revealed that body-mass-index and C-reactive protein were the most informative biomarkers for allostatic load. Both higher allostatic load sum-score and allostatic load item response theory score were associated with lower socio-economic status (p = 0.008; p<0.001, respectively). Further, both formulations of allostatic load were positively associated with a nine-item depression screener (p<0.001 for both), but only the item response theory score was also positively associated with the impact of depressive symptoms on daily life (p = 0.045). Item response theory scores may be more finely tuned to tease out effects, compared to sum-scores, and also provide more flexibility when there are missing biomarker measurements. Supplemental R code for our approach are included. Highlights • Methodological paper to introduce item response theory for calculating allostatic load.• Biomarker data from NHANES 2015–2016 representative of United States adults.• Body-mass-index and C-reactive protein most informative for allostatic load.• Item response theory captures more variability in allostatic load compared to sum-scores.• Future work - item response theory can standardize allostatic load across datasets.