Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Longitudinal Research02:20

Longitudinal Research

12.0K
Sometimes we want to see how people change over time, as in studies of human development and lifespan. When we test the same group of individuals repeatedly over an extended period of time, we are conducting longitudinal research. Longitudinal research is a research design in which data-gathering is administered repeatedly over an extended period of time. For example, we may survey a group of individuals about their dietary habits at age 20, retest them a decade later at age 30, and then again...
12.0K
Introduction to Stress and Lifestyle01:27

Introduction to Stress and Lifestyle

109
Stress is a multifaceted response to events perceived as challenging or threatening, highlighting physical, emotional, cognitive, and behavioral reactions. Physically, stress can lead to fatigue, sleep disruptions, and various health issues such as frequent colds, chest pains, and nausea. Emotionally, it can manifest as anxiety, depression, irritability, and anger triggered by both minor and major life events. Cognitively, it may result in difficulty in concentration, memory, and...
109
Correlations02:20

Correlations

32.8K
Correlation means that there is a relationship between two or more variables (such as ice cream consumption and crime), but this relationship does not necessarily imply cause and effect. When two variables are correlated, it simply means that as one variable changes, so does the other. We can measure correlation by calculating a statistic known as a correlation coefficient. A correlation coefficient is a number from -1 to +1 that indicates the strength and direction of the relationship between...
32.8K
Background and Environment Affect Phenotype02:27

Background and Environment Affect Phenotype

6.5K
Although the genetic makeup of an organism plays a major role in determining the phenotype, there are also several environmental factors, such as temperature, oxygen availability, presence of mutagens, that can alter an organism’s phenotype.
An example of how genetic background affects phenotype can be seen in horses. The Extension gene in horses is responsible for their coat color. A wild-type gene (EE) produces black pigment in the coat, while a mutant gene (ee) produces red pigment. A...
6.5K
  1. Home
  3. Association Between Residential Greenness And Allostatic Load: A Cohort Study.
  1. Home
  3. Association Between Residential Greenness And Allostatic Load: A Cohort Study.

Related Experiment Video

Measuring Biophysical and Psychological Stress Levels Following Visitation to Three Locations with Differing Levels of Nature
05:33

Measuring Biophysical and Psychological Stress Levels Following Visitation to Three Locations with Differing Levels of Nature

Published on: June 19, 2019

8.5K

Association between Residential Greenness and Allostatic Load: A Cohort Study.

Ka Yan Lai1,2, Sarika Kumari1, John Gallacher3

  • 1Healthy High Density Cities Lab, HKUrbanLab, The University of Hong Kong, Pokfulam, Hong Kong Special Administrative Region, China.

Environmental Science & Technology
|March 4, 2024

View abstract on PubMed

Summary
This summary is machine-generated.

Living in greener areas is linked to lower allostatic load (AL), a measure of the body's wear and tear. This study highlights the protective health benefits of residential greenness for overall well-being.

Keywords:
UK Biobankallostatic loadphysical activityresidential greenness

More Related Videos

An Application for Pairing with Wearable Devices to Monitor Personal Health Status
06:58

An Application for Pairing with Wearable Devices to Monitor Personal Health Status

Published on: February 3, 2022

2.8K
Protocol for Assessing the Relative Effects of Environment and Genetics on Antler and Body Growth for a Long-lived Cervid
09:09

Protocol for Assessing the Relative Effects of Environment and Genetics on Antler and Body Growth for a Long-lived Cervid

Published on: August 8, 2017

7.4K

Related Experiment Videos

Measuring Biophysical and Psychological Stress Levels Following Visitation to Three Locations with Differing Levels of Nature
05:33

Measuring Biophysical and Psychological Stress Levels Following Visitation to Three Locations with Differing Levels of Nature

Published on: June 19, 2019

8.5K
An Application for Pairing with Wearable Devices to Monitor Personal Health Status
06:58

An Application for Pairing with Wearable Devices to Monitor Personal Health Status

Published on: February 3, 2022

2.8K
Protocol for Assessing the Relative Effects of Environment and Genetics on Antler and Body Growth for a Long-lived Cervid
09:09

Protocol for Assessing the Relative Effects of Environment and Genetics on Antler and Body Growth for a Long-lived Cervid

Published on: August 8, 2017

7.4K

Area of Science:

  • Environmental Health
  • Public Health
  • Biostatistics

Background:

  • Allostatic load (AL) represents physiological burden and predicts chronic disease, but its link to residential greenness is understudied.
  • Understanding environmental determinants of AL is crucial for public health strategies.
  • Previous research has not extensively explored the quantitative association between neighborhood vegetation and physiological stress markers.

Purpose of the Study:

  • To investigate the association between residential greenness and allostatic load (AL) in a large UK population.
  • To quantify the relationship between Normalized Difference Vegetation Index (NDVI) and composite measures of physiological burden.
  • To explore potential mediators, such as physical activity, in the greenness-AL relationship.

Main Methods:

  • Utilized UK Biobank data from 212,600 participants (2007-2010).
  • Modeled residential greenness using high-resolution NDVI within a 0.5 km radial catchment.
  • Calculated AL from 13 biomarkers across metabolic, cardiovascular, inflammatory, liver, and kidney systems.
  • Employed multilevel mixed-effects generalized linear models to analyze the association.

Main Results:

  • Each interquartile range (IQR) increase in NDVI greenness was associated with a significant reduction in AL (β = -0.28, 95% CI = -0.55, -0.01).
  • Participants in the highest quintile of greenness showed substantially lower AL compared to the lowest quintile (β = -0.64, 95% CI = -1.02, -0.26).
  • Physical activity mediated a small proportion (3.2%) of the association between greenness and AL.

Conclusions:

  • Residential greenness demonstrates a protective association with allostatic load.
  • Increased exposure to neighborhood vegetation may contribute to reduced physiological wear and tear.
  • Findings support the integration of green space considerations into urban planning and public health initiatives for improved population health.