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Background: Little is known about the impact of environmental exposures on mortality risk after a myocardial infarction (MI)., Objective: The goal of this study was to evaluate associations of long-term temperature, air pollution and greenness exposures with mortality among survivors of an MI., Methods: We used data from the US-based Nurses' Health Study to construct an open cohort of survivors of a nonfatal MI 1990-2017. Participants entered the cohort when they had a nonfatal MI, and were followed until death, loss to follow-up, end of follow-up, or they reached 80 years old, whichever came earliest. We assessed residential 12-month moving average fine particulate matter (PM 2.5 ) and nitrogen dioxide (NO 2 ), satellite-based annual average greenness (in a circular 1230 m buffer), summer average temperature and winter average temperature. We used Cox proportional hazard models adjusted for potential confounders to assess hazard ratios (HR and 95% confidence intervals). We also assessed potential effect modification., Results: Among 2262 survivors of a nonfatal MI, we observed 892 deaths during 19,216 person years of follow-up. In single-exposure models, we observed a HR (95%CI) of 1.20 (1.04, 1.37) per 10 ppb NO 2 increase and suggestive positive associations were observed for PM 2.5 , lower greenness, warmer summer average temperature and colder winter average temperature. In multi-exposure models, associations of summer and winter average temperature remained stable, while associations of NO 2 , PM 2.5 and greenness attenuated. The strength of some associations was modified by other exposures. For example, associations of greenness (HR = 0.88 (0.78, 0.98) per 0.1) were more pronounced for participants in areas with a lower winter average temperature., Conclusion: We observed associations of air pollution, greenness and temperature with mortality among MI survivors. Some associations were confounded or modified by other exposures, indicating that it is important to explore the combined impact of environmental exposures., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Background: Fine particulate matter (PM 2.5 ) is a well-recognized risk factor for premature death. However, evidence on which PM 2.5 components are most relevant is unclear., Methods: We evaluated the associations between mortality and long-term exposure to eight PM 2.5 elemental components [copper (Cu), iron (Fe), zinc (Zn), sulfur (S), nickel (Ni), vanadium (V), silicon (Si), and potassium (K)]. Studied outcomes included death from diabetes, chronic kidney disease (CKD), dementia, and psychiatric disorders as well as all-natural causes, cardiovascular disease (CVD), respiratory diseases (RD), and lung cancer. We followed all residents in Denmark (aged ≥30 years) from January 1, 2000 to December 31, 2017. We used European-wide land-use regression models at a 100 × 100 m scale to estimate the residential annual mean levels of exposure to PM 2.5 components. The models were developed with supervised linear regression (SLR) and random forest (RF). The associations were evaluated by Cox proportional hazard models adjusting for individual- and area-level socioeconomic factors and total PM 2.5 mass., Results: Of 3,081,244 individuals, we observed 803,373 death from natural causes during follow-up. We found significant positive associations between all-natural mortality with Si and K from both exposure modeling approaches (hazard ratios; 95% confidence intervals per interquartile range increase): SLR-Si (1.04; 1.03-1.05), RF-Si (1.01; 1.00-1.02), SLR-K (1.03; 1.02-1.04), and RF-K (1.06; 1.05-1.07). Strong associations of K and Si were detected with most causes of mortality except CKD and K, and diabetes and Si (the strongest associations for psychiatric disorders mortality). In addition, Fe was relevant for mortality from RD, lung cancer, CKD, and psychiatric disorders; Zn with mortality from CKD, RD, and lung cancer, and; Ni and V with lung cancer mortality., Conclusions: We present novel results of the relevance of different PM 2.5 components for different causes of death, with K and Si seeming to be most consistently associated with mortality in Denmark., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023. Published by Elsevier Inc.)

Background: Long-term exposure to ambient air pollution has been associated with premature mortality, but associations at concentrations lower than current annual limit values are uncertain. We analysed associations between low-level air pollution and mortality within the multicentre study Effects of Low-Level Air Pollution: A Study in Europe (ELAPSE)., Methods: In this multicentre longitudinal study, we analysed seven population-based cohorts of adults (age ≥30 years) within ELAPSE, from Belgium, Denmark, England, the Netherlands, Norway, Rome (Italy), and Switzerland (enrolled in 2000-11; follow-up until 2011-17). Mortality registries were used to extract the underlying cause of death for deceased individuals. Annual average concentrations of fine particulate matter (PM 2·5 ), nitrogen dioxide (NO 2 ), black carbon, and tropospheric warm-season ozone (O 3 ) from Europe-wide land use regression models at 100 m spatial resolution were assigned to baseline residential addresses. We applied cohort-specific Cox proportional hazard models with adjustment for area-level and individual-level covariates to evaluate associations with non-accidental mortality, as the main outcome, and with cardiovascular, non-malignant respiratory, and lung cancer mortality. Subset analyses of participants living at low pollutant concentrations (as per predefined values) and natural splines were used to investigate the concentration-response function. Cohort-specific effect estimates were pooled in a random-effects meta-analysis., Findings: We analysed 28 153 138 participants contributing 257 859 621 person-years of observation, during which 3 593 741 deaths from non-accidental causes occurred. We found significant positive associations between non-accidental mortality and PM 2·5 , NO 2 , and black carbon, with a hazard ratio (HR) of 1·053 (95% CI 1·021-1·085) per 5 μg/m 3 increment in PM 2·5 , 1·044 (1·019-1·069) per 10 μg/m 3 NO 2 , and 1·039 (1·018-1·059) per 0·5 × 10 -5 /m black carbon. Associations with PM 2·5 , NO 2 , and black carbon were slightly weaker for cardiovascular mortality, similar for non-malignant respiratory mortality, and stronger for lung cancer mortality. Warm-season O 3 was negatively associated with both non-accidental and cause-specific mortality. Associations were stronger at low concentrations: HRs for non-accidental mortality at concentrations lower than the WHO 2005 air quality guideline values for PM 2·5 (10 μg/m 3 ) and NO 2 (40 μg/m 3 ) were 1·078 (1·046-1·111) per 5 μg/m 3 PM 2·5 and 1·049 (1·024-1·075) per 10 μg/m 3 NO 2 . Similarly, the association between black carbon and non-accidental mortality was highest at low concentrations, with a HR of 1·061 (1·032-1·092) for exposure lower than 1·5× 10 -5 /m, and 1·081 (0·966-1·210) for exposure lower than 1·0× 10 -5 /m., Interpretation: Long-term exposure to concentrations of PM 2·5 and NO 2 lower than current annual limit values was associated with non-accidental, cardiovascular, non-malignant respiratory, and lung cancer mortality in seven large European cohorts. Continuing research on the effects of low concentrations of air pollutants is expected to further inform the process of setting air quality standards in Europe and other global regions., Funding: Health Effects Institute., Competing Interests: Declaration of interests We declare no competing interests., (Copyright © 2022 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY-NC-ND 4.0 license. Published by Elsevier Ltd.. All rights reserved.)

Particulate matter air pollution and diesel engine exhaust have been classified as carcinogenic for lung cancer, yet few studies have explored associations with liver cancer. We used six European adult cohorts which were recruited between 1985 and 2005, pooled within the "Effects of low-level air pollution: A study in Europe" (ELAPSE) project, and followed for the incidence of liver cancer until 2011 to 2015. The annual average exposure to nitrogen dioxide (NO 2 ), particulate matter with diameter <2.5 μm (PM 2.5 ), black carbon (BC), warm-season ozone (O 3 ), and eight elemental components of PM 2.5 (copper, iron, zinc, sulfur, nickel, vanadium, silicon, and potassium) were estimated by European-wide hybrid land-use regression models at participants' residential addresses. We analyzed the association between air pollution and liver cancer incidence by Cox proportional hazards models adjusting for potential confounders. Of 330 064 cancer-free adults at baseline, 512 developed liver cancer during a mean follow-up of 18.1 years. We observed positive linear associations between NO 2 (hazard ratio, 95% confidence interval: 1.17, 1.02-1.35 per 10 μg/m 3 ), PM 2.5 (1.12, 0.92-1.36 per 5 μg/m 3 ), and BC (1.15, 1.00-1.33 per 0.5 10 -5 /m) and liver cancer incidence. Associations with NO 2 and BC persisted in two-pollutant models with PM 2.5 . Most components of PM 2.5 were associated with the risk of liver cancer, with the strongest associations for sulfur and vanadium, which were robust to adjustment for PM 2.5 or NO 2 . Our study suggests that ambient air pollution may increase the risk of liver cancer, even at concentrations below current EU standards., (© 2021 The Authors. International Journal of Cancer published by John Wiley & Sons Ltd on behalf of UICC.)

Background: Everyday people are exposed to multiple environmental factors, such as surrounding green, air pollution and traffic noise. These exposures are generally spatially correlated. Hence, when estimating associations of surrounding green, air pollution or traffic noise with health outcomes, the other exposures should be taken into account. The aim of this study was to evaluate associations of long-term residential exposure to surrounding green, air pollution and traffic noise with mortality., Methods: We followed approximately 10.5 million adults (aged ≥ 30 years) living in the Netherlands from 1 January 2013 until 31 December 2018. We used Cox proportional hazard models to evaluate associations of residential surrounding green (including the average Normalized Difference Vegetation Index (NDVI) in buffers of 300 and 1000 m), annual average ambient air pollutant concentrations [including particulate matter (PM 2.5 ), nitrogen dioxide (NO 2 )] and traffic noise with non-accidental and cause-specific mortality, adjusting for potential confounders., Results: In single-exposure models, surrounding green was negatively associated with all mortality outcomes, while air pollution was positively associated with all outcomes. In two-exposure models, associations of surrounding green and air pollution attenuated but remained. For respiratory mortality, in a two-exposure model with NO 2 and NDVI 300 m, the HR of NO 2 was 1.040 (95%CI: 1.022, 1.059) per IQR increase (8.3 µg/m 3 ) and the HR of NDVI 300 m was 0.964 (95%CI: 0.952, 0.976) per IQR increase (0.14). Road-traffic noise was positively associated with lung cancer mortality only, also after adjustment for air pollution or surrounding green., Conclusions: Lower surrounding green and higher air pollution were associated with a higher risk of non-accidental and cause-specific mortality. Studies including only one of these correlated exposures may overestimate the associations with mortality of that exposure., (© 2021. The Author(s).)

Background: Most previous studies that investigated associations of surrounding green, air pollution or traffic noise with mortality focused on single exposures., Objectives: The aim of this study was to evaluate combined associations of long-term residential exposure to surrounding green, air pollution and traffic noise with total non-accidental and cause-specific mortality., Methods: We linked a national health survey (Public Health Monitor, PHM) conducted in 2012 to the Dutch longitudinal mortality database. Subjects of the survey who were 30 years or older on 1 January 2013 (n = 339,633) were followed from 1 January 2013 till 31 December 2017. We used Cox proportional hazard models to evaluate associations of residential surrounding green (including the average Normalized Difference Vegetation Index (NDVI) in buffers of 300 m and 1000 m), annual average air pollutant concentrations (including particulate matter (PM 10 , PM 2.5 ), nitrogen dioxide (NO 2 )) and traffic noise with non-accidental, circulatory disease, respiratory disease, lung cancer and neurodegenerative disease mortality., Results: We observed 26,886 non-accidental deaths over 1.627.365 person-years of follow-up. Surrounding green, air pollution and traffic noise exposure were not significantly associated with non-accidental or cause-specific mortality. For non-accidental mortality, we found a hazard ratio (HR) of 0.99 (0.98, 1.01) per IQR increase in NDVI 300 m, a HR of 0.99 (95% CI: 0.97, 1.01) per IQR increase in NO 2 , a HR of 0.98 (0.97, 1.00) per IQR increase in PM 2.5 and a HR of 0.99 (95% CI: 0.97, 1.01) per IQR increase in road-traffic noise. Analyses restricted to non-movers or excluding subjects aged 85+ years did not change the findings., Conclusion: We found no evidence for associations of long-term residential exposures to surrounding green, air pollution and traffic noise with non-accidental or cause-specific mortality in a large population based survey in the Netherlands, possibly related to the relatively short follow-up period., (Copyright © 2019 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Self-perceived general health (SGH) is one of the most inclusive and widely used measures of health status and a powerful predictor of mortality. However, only a limited number of studies evaluated associations of combined environmental exposures on SGH. Our aim was to evaluate associations of combined residential exposure to surrounding green, air pollution and traffic noise with poor SGH in the Netherlands. We linked data on long-term residential exposure to surrounding green based on the Normalized Difference Vegetation Index (NDVI) and a land-use database (TOP10NL), air pollutant concentrations (including particulate matter (PM 10 , PM 2.5 ), and nitrogen dioxide (NO 2 )) and road- and rail-traffic noise with a Dutch national health survey, resulting in a study population of 354,827 adults. We analyzed associations of single and combined exposures with poor SGH. In single-exposure models, NDVI within 300 m was inversely associated with poor SGH [odds ratio (OR) = 0.91, 95% CI: 0.89, 0.94 per IQR increase], while NO 2 was positively associated with poor SGH (OR = 1.07, 95% CI: 1.04, 1.11 per IQR increase). In multi-exposure models, associations with surrounding green and air pollution generally remained, but attenuated. Joint odds ratios (JOR) of combined exposure to air pollution, rail-traffic noise and decreased surrounding green were higher than the odds ratios of single-exposure models. Studies including only one of these correlated exposures may overestimate the risk of poor SGH attributed to the studied exposure, while underestimating the risk of combined exposures., (Copyright © 2019 The Authors. Published by Elsevier Inc. All rights reserved.)

Background: Evidence is emerging that poor mental health is associated with the environmental exposures of surrounding green, air pollution and traffic noise. Most studies have evaluated only associations of single exposures with poor mental health., Objectives: To evaluate associations of combined exposure to surrounding green, air pollution and traffic noise with poor mental health., Methods: In this cross-sectional study, we linked data from a Dutch national health survey among 387,195 adults including questions about psychological distress, based on the Kessler 10 scale, to an external database on registered prescriptions of anxiolytics, hypnotics & sedatives and antidepressants. We added data on residential surrounding green in a 300 m and a 1000 m buffer based on the Normalized Difference Vegetation Index (NDVI) and a land-use database (TOP10NL), modeled annual average air pollutant concentrations (including particulate matter (PM 10 , PM 2.5 ), and nitrogen dioxide (NO 2 )) and modeled road- and rail-traffic noise (Lden and Lnight) to the survey. We used logistic regression to analyze associations of surrounding green, air pollution and traffic noise exposure with poor mental health., Results: In single exposure models, surrounding green was inversely associated with poor mental health. Air pollution was positively associated with poor mental health. Road-traffic noise was only positively associated with prescription of anxiolytics, while rail-traffic noise was only positively associated with psychological distress. For prescription of anxiolytics, we found an odds ratio [OR] of 0.88 (95% CI: 0.85, 0.92) per interquartile range [IQR] increase in NDVI within 300 m, an OR of 1.14 (95% CI: 1.10, 1.19) per IQR increase in NO 2 and an OR of 1.07 (95% CI: 1.03, 1.11) per IQR increase in road-traffic noise. In multi exposure analyses, associations with surrounding green and air pollution generally remained but attenuated. Joint odds ratios [JOR], based on the Cumulative Risk Index (CRI) method, of combined exposure to air pollution, traffic noise and decreased surrounding green were higher than the ORs of single exposure models. Associations of environmental exposures with poor mental health differed somewhat by age., Conclusions: Studies including only one of these three correlated exposures may overestimate the influence of poor mental health attributed to the studied exposure, while underestimating the influence of combined environmental exposures., (Copyright © 2019 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Background: Air pollution, traffic noise and absence of green space may contribute to the development of overweight in children., Objectives: To investigate the combined associations of air pollution, traffic noise and green space with overweight throughout childhood., Methods: We used data for 3680 participants of the Dutch PIAMA birth cohort. We estimated exposure to air pollution, traffic noise and green space (i.e. the average Normalized Difference Vegetation Index (NDVI) and percentages of green space in circular buffers of 300 m and 3000 m) at the children's home addresses at the time of parental reported weight and height measurements. Associations of these exposures with overweight from age 3 to 17 years were analyzed by generalized linear mixed models, adjusting for potential confounders. Odds ratios (OR's) are presented for an interquartile range increase in exposure., Results: odds of being overweight increased with increasing exposure to NO 2 (adjusted OR 1.40 [95% confidence interval (CI) 1.12-1.74] per 8.90 µg/m 3 ) and tended to decrease with increasing exposure to green space in a 3000 m buffer (adjusted OR 0.86 [95% CI 0.71-1.04] per 0.13 increase in the NDVI; adjusted OR 0.86 [95% CI 0.71-1.03] per 29.5% increase in the total percentage of green space). After adjustment for NO 2 , the associations with green space in a 3000 m buffer weakened. No associations of traffic noise with overweight throughout childhood were found. In children living in an urban area, living further away from a park was associated with a lower odds of being overweight (adjusted OR 0.67 [95% CI 0.52-0.85] per 359.6 m)., Conclusions: Exposure to traffic-related air pollution, but not traffic noise or green space, may contribute to childhood overweight. Future studies examining the associations of green space with childhood overweight should account for air pollution exposure., (Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.)

Individual-level studies with adjustment for important COVID-19 risk factors suggest positive associations of long-term air pollution exposure (particulate matter and nitrogen dioxide) with COVID-19 infection, hospitalisations and mortality. The evidence, however, remains limited and mechanisms unclear. We aimed to investigate these associations within UK Biobank, and to examine the role of underlying chronic disease as a potential mechanism. UK Biobank COVID-19 positive laboratory test results were ascertained via Public Health England and general practitioner record linkage, COVID-19 hospitalisations via Hospital Episode Statistics, and COVID-19 mortality via Office for National Statistics mortality records from March-December 2020. We used annual average outdoor air pollution modelled at 2010 residential addresses of UK Biobank participants who resided in England (n = 424,721). We obtained important COVID-19 risk factors from baseline UK Biobank questionnaire responses (2006-2010) and general practitioner record linkage. We used logistic regression models to assess associations of air pollution with COVID-19 outcomes, adjusted for relevant confounders, and conducted sensitivity analyses. We found positive associations of fine particulate matter (PM2.5) and nitrogen dioxide (NO2) with COVID-19 positive test result after adjustment for confounders and COVID-19 risk factors, with odds ratios of 1.05 (95% confidence intervals (CI) = 1.02, 1.08), and 1.05 (95% CI = 1.01, 1.08), respectively. PM 2.5 and NO 2 were positively associated with COVID-19 hospitalisations and deaths in minimally adjusted models, but not in fully adjusted models. No associations for PM10 were found. In analyses with additional adjustment for pre-existing chronic disease, effect estimates were not substantially attenuated, indicating that underlying chronic disease may not fully explain associations. We found some evidence that long-term exposure to PM2.5 and NO2 was associated with a COVID-19 positive test result in UK Biobank, though not with COVID-19 hospitalisations or deaths.

BACKGROUND: Studies have observed associations between long-term air pollution and cardiovascular disease hospitalization. Little is known, however, about effect modification of these associations by greenness, temperature and humidity. METHODS: We constructed an open cohort consisting of all fee-for-service Medicare beneficiaries, aged ≥ 65, living in the contiguous US from 2000 through 2016 (~63 million individuals). We assigned annual average PM2.5, NO2 and ozone zip code concentrations. Cox-equivalent Poisson models were used to estimate associations with first cardiovascular disease (CVD), coronary heart disease (CHD) and cerebrovascular disease (CBV) hospitalization. RESULTS: PM2.5 and NO2 were both positively associated with CVD, CHD and CBV hospitalization, after adjustment for potential confounders. Associations were substantially stronger at the lower end of the exposure distributions. For CVD hospitalization, the hazard ratio (HR) of PM2.5 was 1.041 (1.038, 1.045) per IQR increase (4.0 µg/m3) in the full study population and 1.327 (1.305, 1.350) per IQR increase for a subgroup with annual exposures always below 10 µg/m3 PM2.5. Ozone was only positively associated with CVD, CHD and CBV hospitalization for the low-exposure subgroup (

BACKGROUND: Studies across the globe generally reported increased mortality risks associated with particulate matter with aerodynamic diameter ≤2.5 μm (PM2.5) exposure with large heterogeneity in the magnitude of reported associations and the shape of concentration-response functions (CRFs). We aimed to evaluate the impact of key study design factors (including confounders, applied exposure model, population age, and outcome definition) on PM2.5 effect estimates by harmonizing analyses on three previously published large studies in Canada [Mortality-Air Pollution Associations in Low Exposure Environments (MAPLE), 1991-2016], the United States (Medicare, 2000-2016), and Europe [Effects of Low-Level Air Pollution: A Study in Europe (ELAPSE), 2000-2016] as much as possible. METHODS: We harmonized the study populations to individuals 65+ years of age, applied the same satellite-derived PM2.5 exposure estimates, and selected the same sets of potential confounders and the same outcome. We evaluated whether differences in previously published effect estimates across cohorts were reduced after harmonization among these factors. Additional analyses were conducted to assess the influence of key design features on estimated risks, including adjusted covariates and exposure assessment method. A combined CRF was assessed with meta-analysis based on the extended shape-constrained health impact function (eSCHIF). RESULTS: More than 81 million participants were included, contributing 692 million person-years of follow-up. Hazard ratios and 95% confidence intervals (CIs) for all-cause mortality associated with a 5-μg/m³ increase in PM2.5 were 1.039 (1.032, 1.046) in MAPLE, 1.025 (1.021, 1.029) in Medicare, and 1.041 (1.014, 1.069) in ELAPSE. Applying a harmonized analytical approach marginally reduced difference in the observed associations across the three studies. Magnitude of the association was affected by the adjusted covariates, exposure assessment methodology, age of the population, and marginally by outcome definition. Shape of the CRFs differed across cohorts but generally showed associations down to the lowest observed PM2.5 levels. A common CRF suggested a monotonically increased risk down to the lowest exposure level. [ABSTRACT FROM AUTHOR]

BACKGROUND: Surrounding green, air pollution, and noise have been associated with cardiometabolic diseases, but most studies have assessed only one of these correlated exposures. OBJECTIVES: We aimed to evaluate associations of combined exposures to green, air pollution, and road traffic noise with cardiometabolic diseases. METHODS: In this cross-sectional study, we studied associations between self-reported physician-diagnosed diabetes, hypertension, heart attack, and stroke from a Dutch national health survey of 387,195 adults and residential surrounding green, annual average air pollutant concentrations [including particulate matter with aerodynamic diameter ≤10 lm (PM10), PM with aerodynamic diameter ≤2:5 lm (PM2:5), nitrogen dioxide (NO2), and oxidative potential (OP) with the dithiothreitol (DTT) assay (OPDTT)] and road traffic noise. Logistic regression models were used to analyze confounding and interaction of surrounding green, air pollution, and noise exposure. RESULTS: In single-exposure models, surrounding green was inversely associated with diabetes, while air pollutants (NO2, OPDTT) and road traffic noise were positively associated with diabetes. In two-exposure analyses, associations with green and air pollution were attenuated but remained. The association between road traffic noise and diabetes was reduced to unity when adjusted for surrounding green or air pollution. Air pollution and surrounding green, but not road traffic noise, were associated with hypertension in single-exposure models. The weak inverse association of surrounding green with hypertension attenuated and lost significance when adjusted for air pollution. Only PM2:5 was associated with stroke and heart attack. CONCLUSIONS: Studies including only one of the correlated exposures surrounding green, air pollution, and road traffic noise may overestimate the association of diabetes and hypertension attributed to the studied exposure. [ABSTRACT FROM AUTHOR]

Introduction In epidemiological studies, exposure to green space is inconsistently associated with being overweight and physical activity, possibly because studies differ widely in their definition of green space exposure, inclusion of important confounders, study population and data analysis. Objectives We evaluated whether the association of green space with being overweight and physical activity depended upon definition of greenspace. Methods We conducted a cross-sectional study using data from a Dutch national health survey of 387,195 adults. Distance to the nearest park entrance and surrounding green space, based on the Normalized Difference Vegetation Index (NDVI) or a detailed Dutch land-use database (TOP10NL), was calculated for each residential address. We used logistic regression analyses to study the association of green space exposure with being overweight and being moderately or vigorously physically active outdoors at least 150 min/week (self-reported). To study the shape of the association, we specified natural splines and quintiles. Results The distance to the nearest park entrance was not associated with being overweight or outdoor physical activity. Associations of surrounding green space with being overweight or outdoor physical activity were highly non-linear. For NDVI surrounding greenness, we observed significantly decreased odds of being overweight [300 m buffer, odds ratio (OR) = 0.88; 95% CI: 0.86, 0.91] and increased odds for outdoor physical activity [300 m buffer, OR = 1.14; 95% CI: 1.10, 1.17] in the highest quintile compared to the lowest quintile. For TOP10NL surrounding green space, associations were mostly non-significant. Associations were generally stronger for subjects living in less urban areas and for the smaller buffers. Conclusion Associations of green space with being overweight and outdoor physical activity differed considerably between different green space definitions. Associations were strongest for NDVI surrounding greenness. [ABSTRACT FROM AUTHOR]