Is moving to a greener or less green area followed by changes in physical activity?

Neighborhood greenness and participation in specific types of recreational physical activities in the Sister Study

BACKGROUND

Urban green spaces have been consistently shown to have important human health benefits across a range of outcomes. These benefits are thought to be achieved, in part, because urban greenness provides opportunities for participation in recreational activity. However, the findings from studies that have assessed links between exposure to greenness and physical activity have been mixed. To date, few studies have examined association between greenness and specific types of recreational physical activities.

OBJECTIVE

We evaluated associations between measures of greenness and specific types of recreational physical activities. Moreover, we explored the extent to which these associations were modified by socioeconomic conditions, and regionally.

METHODS

We analyzed cross-sectional data from 49,649 women in the Sister Study and assigned three residentially-based measures of greenness based on national land cover data at buffer distances of 250 m and 500 m. Data on participation in up to ten specific recreational physical activities, including time spent in each activity were collected. Logistic regression was used to estimate odds ratios (OR) and their 95% confidence intervals (CI) controlling for confounders.

RESULTS

Compared to those in the lowest tertile of greenness, participants in the upper tertile of greenness within a 500 m buffer, were more likely to garden (OR = 1.46, 95% CI = 1.25,1.69), participate in sports (OR = 1.28, 95% CI = 1.19,1.38), run (OR = 1.15, 95% CI = 1.04,1.27), walk (OR = 1.11, 95% CI = 1.06,1.16), and engage in conditioning exercises (OR = 1.10, 95% CI = 1.05,1.16) at least once a week for at least one month over the past year. These associations were modified by household income and US region.

DISCUSSION

Our findings suggest a beneficial effect of greenness on physical activity and provide additional information to inform planning of green environments that contribute to better health and wellbeing.

Minute level smartphone derived exposure to greenness and consumer wearable derived physical activity in a cohort of US women

BACKGROUND

Inconsistent results have been found in the literature on associations of greenness, or vegetation quantity, and physical activity. However, few studies have assessed associations between mobility-based greenness and physical activity from mobile health data from smartphone and wearable devices with fine spatial and temporal resolution.

METHODS

We assessed mobility-based greenness exposure and wearable accelerometer data from participants in the US-based prospective Nurses' Health Study 3 cohort Mobile Health (mHealth) Substudy (2018-2020). We recruited 500 female participants with instructions to wear devices over four 7-day sampling periods equally spaced throughout the year. After restriction criteria there were 337 participants (mean age 36 years) with n = 639,364 unique observations. Normalized Difference Vegetation Index (NDVI) data were derived from 30 m x 30 m Landsat-8 imagery and spatially joined to GPS points recorded every 10 min. Fitbit proprietary algorithms provided physical activity summarized as mean number of steps per minute, which we averaged during the 10-min period following a GPS-based greenness exposure assessment. We utilized Generalized Additive Mixed Models to examine associations (every 10 min) between greenness and physical activity adjusting for neighborhood and individual socioeconomic status, Census region, season, neighborhood walkability, daily mean temperature and precipitation. We assessed effect modification through stratification and interaction models and conducted sensitivity analyses.

RESULTS

Mean 10-min step count averaged 7.0 steps (SD 14.9) and greenness (NDVI) averaged 0.3 (SD 0.2). Contrary to our hypotheses, higher greenness exposure was associated non-linearly with lower mean steps per minute after adjusting for confounders. We observed statistically significant effect modification by Census region and season.

DISCUSSION

We utilized objective physical activity data at fine temporal and spatial scales to present novel estimates of the association between mobility-based greenness and step count. We found higher levels of greenness were inversely associated with steps per minute.

The influence path of community green exposure index on activity behavior under multi-dimensional spatial perception

The purpose of this research is to reveal the internal relationship among community green space, space perception, and activity behavior response to supplement the lack of research results on the binary relationship between green space and behavior. Nine residential community green spaces and 398 residents were selected as the research objects. Thematic clustering and factor identification were used to determine the spatial dimensions of community green space that residents were concerned about. The analysis of the green exposure index, spatial perception evaluation, and activity behavior survey were combined to determine the influence of the green exposure index on spatial perception and activity behavior and its internal correlation path. According to research data, the community green view index (GVI) and normalized difference vegetation index (NDVI) negatively affected the perception factor, while the perception factor positively affected the activity frequency. The SEM model shows that the green exposure index stimulated activity behavior through the intermediate effect of the internal perception path of perceived landscape quality, perceived workability, and perceived accessibility. Spatial perception as the basis of the instantaneous emotional reaction process may affect people's choices for activities but be unable to extend the duration of the activities. The internal association among community green space, spatial perception, and physical activity behavior develops on the basis of spatial patterns at certain scales. This study provides a theoretical basis for understanding the spatial experience and residents' behavioral needs, evaluating the quality of urban green space scientifically, and promoting the optimization of community green space structure.

Methods in Public Health Environmental Justice Research: a Scoping Review from 2018 to 2021

PURPOSE OF REVIEW

The volume of public health environmental justice (EJ) research produced by academic institutions increased through 2022. However, the methods used for evaluating EJ in exposure science and epidemiologic studies have not been catalogued. Here, we completed a scoping review of EJ studies published in 19 environmental science and epidemiologic journals from 2018 to 2021 to summarize research types, frameworks, and methods.

RECENT FINDINGS

We identified 402 articles that included populations with health disparities as a part of EJ research question and met other inclusion criteria. Most studies (60%) evaluated EJ questions related to socioeconomic status (SES) or race/ethnicity. EJ studies took place in 69 countries, led by the US (n = 246 [61%]). Only 50% of studies explicitly described a theoretical EJ framework in the background, methods, or discussion and just 10% explicitly stated a framework in all three sections. Among exposure studies, the most common area-level exposure was air pollution (40%), whereas chemicals predominated personal exposure studies (35%). Overall, the most common method used for exposure-only EJ analyses was main effect regression modeling (50%); for epidemiologic studies the most common method was effect modification (58%), where an analysis evaluated a health disparity variable as an effect modifier. Based on the results of this scoping review, current methods in public health EJ studies could be bolstered by integrating expertise from other fields (e.g., sociology), conducting community-based participatory research and intervention studies, and using more rigorous, theory-based, and solution-oriented statistical research methods.

Expanding Social, Psychological, and Physical Indicators of Urbanites' Life Satisfaction toward Residential Community: A Structural Equation Modeling Analysis

Attention on, and interest in, life satisfaction has increased worldwide. However, research on life satisfaction focused toward the urban dwellers' residential community is mainly from western countries, and the limited research from China is solely focused on the geriatric population via a narrowly constrained research perspective. This study, therefore, aimed to investigate urbanites' life satisfaction toward their community, combining the psychological (behavioral community engagement, mental state of flow, and cognitive community identity), physical (PREQIs-perceived residential environment quality indicators: e.g., green area), and social perspectives (social capital). The proposed conceptual model was tested on a regionally representative sample of 508 urban community residents in the city of Chengdu, Sichuan province, China. Data were analyzed via a structure equation modelling approach in AMOS software. Findings suggested that all of the psychological, physical and social factors contributed to a prediction of life satisfaction. Specifically, social capital mediated the path from community engagement and flow to life satisfaction, and community identity mediated the path from flow experience and green area to life satisfaction. Additionally, social capital contributed to predict life satisfaction through its influence on community identity. Findings provide suggestions for urban designers and policymakers to focus on creating an urban community equipped with green area, which helps to promote physical activities that are flow-productive, to enhance residents' identification to their residential community and, therefore, increase life satisfaction.

Association between residential greenness and sleep quality in Chinese rural population

BACKGROUND

Epidemiological studies on the association of residential greenness with sleep quality are limited in China.

OBJECTIVE

This study aims to investigate the association of long-term exposure to residential greenness with sleep quality in rural China.

METHODS

In our study, 27,654 rural residents were selected from 4 counties of Henan Province by a multi-stage stratified cluster sampling method. Participants' sleep quality was assessed using the Pittsburgh Sleep Quality Index (PSQI). The Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI), two satellite-derived vegetation indexes, were used to assess the level of residential greenness. Long-term greenness exposure was defined as the averages of NDVI and EVI during the three years prior to the baseline survey. The relationship between sleep quality and greenness was assessed using the mixed-effect linear regression models.

RESULTS

Among 27,654 rural residents, the mean age was 55.89 years (standard deviation, SD = 12.22) and 60.18% of them were female. In the crude model, the PSQI score decreased with per interquartile range (IQR) increase in EVI and NDVI [ΔPSQI score (95% confidence interval, 95%CI): -0.073 (-0.115, -0.030) and -0.047 (-0.089, -0.002)]. After controlling potential confounders, ΔPSQI scores and 95%CIs were -0.055 (-0.095, -0.012) and -0.090 (-0.151, -0.025) associated with per IQR increment in EVI and NDVI. The results of stratified analyses showed the effect of residential greenness on sleep was stronger among males and individuals with higher household income and educational attainment than females and those with lower household income and educational attainment. Moreover, the modification effect of air pollution was observed in the greenness-sleep association.

CONCLUSIONS

Our study indicated that higher residential greenness was significantly associated with better sleep quality in Chinese rural population, which highlights the significant effect of green space on human health.

Urban nature and physical activity: Investigating associations using self-reported and accelerometer data and the role of household income

BACKGROUND

Physical inactivity is a major public health concern. Natural, or semi-natural, environments may encourage physical activity, but the influences of socio-economic factors have been under-researched.

METHODS

We explored the associations between meeting physical activity (PA) guidelines and both neighbourhood green (area coverage) and blue (freshwater coverage and coastal proximity) environments for urban adults using data from the Health Survey for England [HSE] (2008/2012). We considered different domains of self-reported PA: walking (n = 18,391), sports and other exercise (n = 18,438), non-recreational (domestic/gardening/occupational; n = 18,446) and all three domains combined (n = 18,447); as well as accelerometer-derived PA data using a subsample (n = 1,774). Relationships were stratified by equivalised household income as an indicator of socio-economic status.

RESULTS

After adjusting for covariates, living <5 km from the coast was associated with significantly higher odds of meeting UK 2010 guidelines through self-reported total, walking and non-recreational PA (e.g. total PA, <5 km vs. >20 km, adjusted odds ratio (OR_adj) = 1.26; 95% confidence interval (CI) = 1.15-1.39) but unrelated to sports and exercise. Greater neighbourhood greenspace, however, was only associated with significantly higher odds of meeting guidelines through non-recreational PA alone (e.g. 80-100% vs. <20% OR_adj = 1.32; 95% CI = 1.12-1.56). Although associations were most consistent in the lowest income quintile, income-related results were mixed. Relationships were not replicated in the smaller accelerometry subsample.

CONCLUSION

Our self-report findings for the differing domains of PA as a function of neighbourhood green and blue space broadly replicated previous research, yet the reasons for the observed differences between PA domains and environments remain unclear. We did not observe any associations between environmental variables and accelerometer-measured PA; further research with larger samples is needed.

Association Between Residential Greenness, Cardiometabolic Disorders, and Cardiovascular Disease Among Adults in China

IMPORTANCE

Living in areas with more vegetation (referred to as residential greenness) may be associated with cardiovascular disease (CVD), but little data are available from low- and middle-income countries. In addition, it remains unclear whether the presence of cardiometabolic disorders modifies or mediates the association between residential greenness and CVD.

OBJECTIVE

To evaluate the associations between residential greenness, cardiometabolic disorders, and CVD prevalence among adults in China.

DESIGN, SETTING, AND PARTICIPANTS

This analysis was performed as part of the 33 Communities Chinese Health Study, a large population-based cross-sectional study that was conducted in 33 communities (ranging from 0.25-0.64 km2) in 3 cities within the Liaoning province of northeastern China between April 1 and December 31, 2009. Participants included adults aged 18 to 74 years who had resided in the study area for 5 years or more. Greenness levels surrounding each participant's residential community were assessed using the normalized difference vegetation index and the soil-adjusted vegetation index from 2010. Lifetime CVD status (including myocardial infarction, heart failure, coronary heart disease, cerebral thrombosis, cerebral hemorrhage, cerebral embolism, and subarachnoid hemorrhage) was defined as a self-report of a physician diagnosis of CVD at the time of the survey. Cardiometabolic disorders, including hypertension, diabetes, dyslipidemia, and overweight or obese status, were measured and defined clinically. Generalized linear mixed models were used to evaluate the association between residential greenness levels and CVD prevalence. A 3-way decomposition method was used to explore whether the presence of cardiometabolic disorders mediated or modified the association between residential greenness and CVD. Data were analyzed from October 10 to May 30, 2020.

MAIN OUTCOMES AND MEASURES

Lifetime CVD status, the presence of cardiometabolic disorders, and residential greenness level.

RESULTS

Among 24 845 participants, the mean (SD) age was 45.6 (13.3) years, and 12 661 participants (51.0%) were men. A total of 1006 participants (4.1%) reported having a diagnosis of CVD. An interquartile range (1-IQR) increase in the normalized difference vegetation index within 500 m of a community was associated with a 27% lower likelihood (odds ratio [OR], 0.73; 95% CI, 0.65-0.83; P < .001) of CVD prevalence, and an IQR increase in the soil-adjusted vegetation index within 500 m of a community was associated with a 26% lower likelihood (OR, 0.74; 95% CI, 0.66-0.84; P < .001) of CVD prevalence. The presence of cardiometabolic disorders was found to mediate the association between residential greenness and CVD, with mediation effects of 4.5% for hypertension, 4.1% for type 2 diabetes, 3.1% for overweight or obese status, 12.7% for hypercholesterolemia, 8.7% for hypertriglyceridemia, and 11.1% for high low-density lipoprotein cholesterol levels.

CONCLUSIONS AND RELEVANCE

In this cross-sectional study, higher residential greenness levels were associated with lower CVD prevalence, and this association may be partially mediated by the presence of cardiometabolic disorders. Further studies, preferably longitudinal, are warranted to confirm these findings.