Karate kid 2 full movie free. If respondents were asked about a month in the past 12 months when they felt more depressed, anxious, or emotionally stressed than they felt during the past 30 days, they were 2014 ap environmental science free response answers section 2 comparable K6 items for that particular month in the past 12 months.">

2014 ap environmental science free response answers section 2

2014 ap environmental science free response answers section 2

Lab Writeup Guidelines. Wait just a minute here In order to access these resources, you will need to sign in or register for the website takes literally 1 minute! Why do they differ? APES A. AP Information.

Study 50 Ch 4 Vocab flashcards from Emma T. NOT biomes. AP Environmental Science is a good option for interested students who have completed two years of high school laboratory science, such as a year of life science e.

Learn vocabulary, terms, and more with flashcards, games, and other study tools. Download it once and read it on your Kindle device, PC, phones or tablets.

AP Environmental Science can be a good class to take for many people. Make at least three visits to each of the two study areas for a total of six visits , staying for at least 20 minutes each time, to observe the living and nonliving parts of the ecosystem.

These PDF notes are incredibly thorough and detailed. If you're willing to spend some cash, these unofficial, paid AP Environmental Science practice test resources are strong contenders to consider. Environmental Science is the interaction of sciences that attempts to explain how life on the Earth is sustained, what leads to environmental problems, how humans are responsible and interact with these elements and how these problems can be solved. Plano, Texas, United States. Textbook Authors: Friedland, Andrew J.

For general help, questions, and suggestions, try our dedicated support forums. Chapter 5 Evolution of Biodiversity. Chapter 3 Notes 4. New knowledge leads to new technology, which leads to a greater impact on individuals on Earth's resources and higher density of human beings. Tragedy of the Commons.

Lab Report Format. Distance from the sun. APES Resources. AP Environmental Science isn't strictly a science class; it also includes recent and current events as well as some law, among other topics. Quizlet Live. Biodiversity - the number and variety of species in a given area The study of biodiversity starts with cataloging all the species that exist on earth- Known species - collected and described scientifically- Unknown species - exist in remote wilderness, deep oceans, cities.

Chapter 18 Reading Guide. For cocaine, heroin, and stimulants, respondents were asked the dependence and abuse questions if they reported past year use in a core drug module or past year use in the noncore special drugs module. Thus, the CAI logic allowed some respondents to be asked the dependence and abuse questions for these drugs even if they did not report past year use in the corresponding core module.

For cocaine, for example, fewer than 1, respondents in were asked the questions about cocaine dependence and abuse because they reported past year use of cocaine or crack in the core section of the interview. Fewer than 20 additional respondents were asked these questions because they reported past year use of cocaine with a needle in the special drugs module despite not having previously reported past year use of cocaine or crack.

In , two new questions were added to the noncore special drugs module about past year methamphetamine use: "Have you ever, even once, used methamphetamine? Which answer is correct? Based on the decisions made during the methamphetamine analysis, 22 respondents who indicated past year methamphetamine use solely from these new special drug use questions i.

Furthermore, if these same respondents were categorized as not having past year dependence or abuse of any other psychotherapeutic drug e. Also, if these respondents were not classified as having dependence or abuse for other substances e. However, analysts can identify respondents who were routed to the stimulant dependence and abuse questions solely because of their reports of past year methamphetamine use from these noncore questions.

If these respondents' answers to the stimulant dependence or abuse questions indicated that they had dependence or abuse, analysts would have the option to classify these cases as having dependence or abuse.

In , questionnaire logic for determining who would be administered the items that establish hallucinogen, stimulant, and sedative dependence or abuse was modified. The revised skip logic used information collected in the noncore special drugs module in addition to that collected in questions from the core drug modules.

Consistent with the previous decision to exclude respondents whose methamphetamine use was based solely on responses to noncore questions from being classified as having stimulant dependence or abuse, respondents who indicated past year use or nonmedical use of hallucinogens, stimulants, or sedatives based solely on these special drug questions were categorized as NOT having past year dependence or abuse of the relevant substance regardless of how they answered the dependence and abuse questions.

Again, however, analysts can identify these cases and could reclassify their dependence or abuse status according to how they answered the questions for dependence or abuse.

Respondents might have provided ambiguous information about past year use of any individual substance, in which case these respondents were not asked the dependence and abuse questions for that substance. For example, respondents could report lifetime use of a substance but not know or refuse to report when they last used it, in which case it is not known whether their lifetime use included use in the past year. Also, respondents could report that they last used a substance "more than 12 months ago" but also report first use of the substance at their current age, which would imply use at some point in the past 12 months.

If respondents were not asked the dependence or abuse questions based on their previous answers in the interview but they were imputed to be past year users, the dependence and abuse data were unknown; thus, these respondents were classified as not having dependence or abuse of the respective substance. However, these respondents never actually were asked the dependence and abuse questions. These changes are summarized as follows:. For the first change, the past year K6 score in was created for each adult aged 18 or older based on responses to items regarding either the past 30 days if an adult said that he or she did not have any other month that was worse or the worst month in the past 12 months.

This change in questionnaire structure was evaluated to determine whether this change may have affected K6 scores and estimates of SPD that were created from the K6 items for the worst month in the past year. The remaining changes to questions between survey years also could have affected how respondents answer questions in subsequent modules i.

A context effect may be said to take place when the response to a question is affected by information that is not part of the question itself.

For example, the content of a preceding question may affect the interpretation of a subsequent question. Or a respondent may answer a subsequent question in a manner that is consistent with responses to a preceding question if the two questions are closely related to each other. Effects of Changes to the Questions for Adults. Significant differences in the mean past year K6 scores were observed between and , thus suggesting a lack of comparability between the 2 years. Across each of the six items forming the past year K6 score, estimates of adults reporting that they had a given problem "none of the time" e.

The estimate of past year SPD was slightly lower from the full sample of adults in than in In turn, lifetime and past year MDE estimates based on the entire sample in were lower than corresponding estimates from However, estimates of lifetime and past year MDE based on the SDS half sample in were not significantly different from the estimates in However, subsequent adjustment procedures were developed for adult MDE from the SDS half sample to allow data from all adult respondents in to be used for estimating MDE among adults.

Administration of the WHODAS or SDS in did not appear to differentially affect responses to the questions for adults about suicidal thoughts and behavior that also were added in Therefore, further investigation was not done to examine the effects on estimates of suicidal thoughts and behavior in due to the removal of the SDS items. Effects of Changes to the Questions for Youths. The changes to the YMHSU module item 3 in could have affected how adolescents answered the items at the beginning of the adolescent depression module i.

In turn, changes in youths' answers to these introductory adolescent depression items could affect estimates of adolescent MDE. All adolescents were asked question YDS21 "Have you ever in your life had a period of time lasting several days or longer when most of the day you felt sad, empty, or depressed? Those who did not answer question YDS21 as "yes" then were asked question YDS22 "Have you ever had a period of time lasting several days or longer when most of the day you felt very discouraged or hopeless about how things were going in your life?

Youths who did not answer either question YDS21 or YDS22 as "yes" then were asked question YDS23 "Have you ever had a period of time lasting several days or longer when you lost interest and became bored with most things you usually enjoy, like work, hobbies, and personal relationships?

This analysis sought to determine whether changes in the YMHSU module affected responses to the first three adolescent depression questions and the lifetime and past year MDE estimates.

To assess whether any differences in estimates between and could be due to more than just true changes in the population, comparisons between consecutive years beginning in also were carried out. For consistency with the data, comparisons were limited to the first 6 months of data from other survey years. The changes to the YMHSU module in did not appear to affect estimates for the variables based on the lead adolescent depression questions or estimates of adolescent MDE between and None of the differences in estimated responses to the three lead adolescent MDE items or estimates of adolescent lifetime and past year MDE between and was statistically significant.

No apparent trend was observed between and for the lifetime and past year MDE estimates or for the variable corresponding to question YDS Therefore, it was determined that the youth depression items could continue to be compared between and prior years. Although it was recognized that the ideal way to estimate SMI in NSDUH would be to administer a clinical diagnostic interview annually to all 45, adult respondents, this approach was not feasible because of constraints on the interview time and the need for trained mental health clinicians to conduct the interviews.

Therefore, the approach recommended by the technical advisory group and adopted by SAMHSA for NSDUH was to utilize short scales in the NSDUH interview that separately measure psychological distress and functional impairment for use in a statistical model that predicts whether a respondent had mental illness.

Models using the short scales for psychological distress and impairment to predict mental illness status were developed from a subsample of adult respondents who had completed the NSDUH interview and were administered a psychological diagnostic interview.

For the clinical interview data, individuals were defined as having SMI if they had a diagnosable mental, behavioral, or emotional disorder in the past 12 months, other than a developmental or substance use disorder, that met DSM-IV criteria APA, and resulted in substantial functional impairment.

Historical Summary of the Model. A randomly selected subsample of approximately 1, adults in who had completed the NSDUH interview was recruited for a follow-up clinical interview consisting of a diagnostic assessment for mental disorders. Weighted logistic regression models that predicted mental illness were developed for each half sample using the data from the subsample of MHSS respondents.

This model that had been developed using the data subsequently referred to as the " model" was used in the through NSDUHs to produce a predicted probability of having SMI for each clinical interview respondent. Based on the accumulated MHSS clinical data that were collected from to , however, SAMHSA determined that the model had some important shortcomings that had not been detected in the original model fitting because of the small number of respondents in the clinical sample.

Specifically, estimates of SMI and AMI among young adults based on the NSDUH main study data and prediction model were higher than the estimates for this age group based on the clinical interview data. In addition, improvements were needed in the weighting procedures for the MHSS clinical data to account better for undercoverage and nonresponse i.

Therefore, using the combined to clinical data, SAMHSA fit a more accurate model for the estimates with revised weights subsequently referred to as the " model". In particular, to reduce bias and improve prediction, additional mental health-related variables and an age variable were added in the model. In addition, to protect against potential coverage and nonresponse error, alternatives for the weights were applied to the clinical sample data for the model development.

To provide consistent data for trend assessment, mental illness estimates for to were revised using the new model. The model was used in and continued to be used for the mental illness estimates. The next subsections describe the instruments and items used to measure the variables employed in the model. Specifically, the instrument used to measure mental illness in the clinical interviews is described, followed by descriptions of the scales and items in the main NSDUH interviews that were used as predictor variables in the model e.

Clinical Measurement of Mental Illness. Past year disorders that were assessed through the SCID included mood disorders e. Substance use disorders also were assessed, although these disorders were not used to produce estimates of mental illness. Respondents were asked about the second time period only if they indicated that there was a month in the past 12 months when they felt more depressed, anxious, or emotionally stressed than they felt during the past 30 days. HOPE30 During the past 30 days, how often did you feel hopeless?

FIDG30 During the past 30 days, how often did you feel restless or fidgety? NOCHR30 During the past 30 days, how often did you feel so sad or depressed that nothing could cheer you up? DOWN30 During the past 30 days, how often did you feel down on yourself, no good or worthless?

Responses of "don't know" and "refused" also were coded as 0. Summing across the transformed responses in these six items resulted in a score with a range from 0 to If respondents were asked about a month in the past 12 months when they felt more depressed, anxious, or emotionally stressed than they felt during the past 30 days, they were asked comparable K6 items for that particular month in the past 12 months. The scoring procedures for these K6 items for the past 12 months were the same as those described previously for the past 30 days.

The higher of the two K6 total scores for the past 30 days or past 12 months was used both for MHSS analysis purposes and in the adult respondents' final data. An alternative K6 total score was created in which K6 scores of less than 8 were recoded as 0.

A score of 8 was recoded as 1, a score of 9 was recorded as 2, and so on, until a score of 24 was recoded as The rationale for creating the alternative past year K6 score was that SMI prevalence typically was extremely low for respondents with past year K6 scores of less than 8, and the prevalence rates started increasing only when scores were 8 or greater.

This alternative K6 score was used in both the and SMI prediction models. That is, a subset of 8 items was found to capture the information represented in the full item scale with no significant loss of information.

These eight WHODAS items that were included in the main NSDUH interview were assessed on a 0 to 3 scale, with responses of "no difficulty," "don't know," and "refused" coded as 0; "mild difficulty" coded as 1; "moderate difficulty" coded as 2; and "severe difficulty" coded as 3. Some items had an additional category for respondents who did not engage in a particular activity e. Respondents who reported that they did not engage in an activity were asked a follow-up question to determine if they did not do so because of emotions, nerves, or mental health.

Those who answered "yes" to this follow-up question were subsequently assigned to the "severe difficulty" category; otherwise i. Summing across these codes for the eight responses resulted in a total score with a range from 0 to The individual alternative item scores then were summed to yield a total alternative score ranging from 0 to 8. Creation of an alternative version of the WHODAS score was based on the assumption that a dichotomous measure dividing respondents into two groups i.

The first two variables were added to the model to decrease the error rate in the predictions i. A recoded age variable reduced the biases in estimates for particular age groups, especially 18 to 25 year olds. For respondents aged 18 to 30, an adjusted age was created by subtracting 18 from the respondent's current age, resulting in values ranging from 0 to For a respondent aged 18, for example, the adjusted age was 0 i. Sampling and Weighting.

The target annual respondent sample sizes for the MHSS clinical interviews were 1, in of which received the WHODAS and were used in developing the model , in and , and 1, in and Respondent sample sizes were roughly equal across quarters.

A stratified Bernoulli selection process was used in which each eligible NSDUH respondent was given an independent probability of selection based on his or her stratum. In the last two quarters in , stratification attempted to minimize the variance of the AMI prevalence estimate rather than the variance of the SMI estimate. This change reduced the probability that a respondent with an extremely large weight would be selected.

This resulted in a more equally allocated clinical sample by age. Special clinical sample analysis weights were created.

The first six weight components were created separately for each year. The model was fit under the assumption that the relationship between SMI and the covariates of the model stayed the same from through The SMI Model. The response variable Y equaled 1 when an SMI diagnosis was positive based on the clinical interview; otherwise, Y was 0.

As with the model, a cut point probability was determined, so that if for a particular respondent, then he or she was predicted to be SMI positive; otherwise, he or she was predicted to be SMI negative. The cut point 0. A second cut point probability 0. The second cut point was chosen so that the weighted numbers of AMI false positives and false negatives were as close to equal as possible. Estimates of low mild mental illness and moderate mental illness were derived by a process of subtraction.

Respondents were classified as belonging to the moderate mental illness category if they belonged to the SMMI category, but they did not belong to the SMI category. Respondents were classified as belonging to the low mild mental illness category if they belonged to the AMI category but not to the SMMI category.

For the clinical interview respondents who had been administered the SDS in the main survey, an alternative SMI model was fit using the complete MHSS dataset of clinical interviews from through Mental illness estimates based on the predicted values for the B sample were compared with the ones based on the A sample using the model described previously.

The model-based estimates from the A and B samples were similar, and the predicted values for the two half samples in were deemed to be comparable. Therefore, the predicted values from the B sample were combined with predicted values from the complete WHODAS sample for A and for through In fitting the alternative model for the SDS half sample, weights for the clinical interview respondents who had been assigned to the SDS were developed separately using the same steps as in other years.

Weights for the other years were scaled as described previously. Standard Errors for Mental Illness Estimates. For this report and the mental health detailed tables, SEs for mental illness estimates SMI, AMI, SMMI, moderate mental illness, and low [mild] mental illness were computed using the NSDUH dichotomous variable values without taking into account any variance introduced through using a model based on the clinical subsample data. These conditional SEs conditional on the model predictions being correct are useful when making comparisons across years and across subpopulations except those involved in modeling within years because the errors due to model fitting are nearly the same across the estimates being compared and consequently roughly cancel each other out.

Beginning in , modules related to MDE were included in the questionnaire. Questions on depression permit estimates to be calculated for the occurrence of MDE in the population and receipt of treatment for MDE. Separate modules were administered to adults aged 18 or older and youths aged 12 to In addition, some revisions, based on cognitive testing, were made to improve comprehension.

Furthermore, even though titles similar to those used in the NCS were used for the NSDUH modules, the results of these items may not be directly comparable. Respondents who have had MDE in their lifetime are asked if, during the past 12 months, they had a period of depression lasting 2 weeks or longer while also having some of the other symptoms mentioned.

Those reporting that they have had MDE in the past year are asked questions from the SDS to measure the level of functional impairment in major life activities reported to be caused by the MDE in the past 12 months Leon et al.

Note that the questions shown are taken from the adult depression module. A few of the questions in the youth module were modified slightly to use wording more appropriate for youths aged 12 to It should be noted that no exclusions were made for MDE caused by medical illness, bereavement, or substance use disorders.

For other uses, see Ape disambiguation. AP Environmental Science Retrieved 7 May Archived from the original on AP Classroom is a new digital tool designed by the College Board that allows your AP teacher to assign homework and practice questions through an online portal. Your AP Environmental Science teacher might also have access to some additional official practice questions that you can use.

Teachers are sometimes able to buy official practice questions which students don't have access to from the College Board. Your teacher might have chosen not to do this, or they might be saving those AP Enviro questions for class exams. But if you're looking for more official practice materials, you might want to take a chance and ask them.

Official practice tests won't come with a seal, but you can be sure they're the highest-quality practice materials out there. One of the single most important parts of your college application is what classes you choose to take in high school in conjunction with how well you do in those classes.

Our team of PrepScholar admissions experts have compiled their knowledge into this single guide to planning out your high school course schedule. You have to be a bit wary when using unofficial practice materials because some of them don't do a very good job of replicating what topics the AP test covers or how they word their questions ; however, there are many that can still be very helpful. For each of the AP resources below, I'll explain what material it includes and how closely it matches the real AP Environmental Science exam.

Varsity Tutors has one complete AP Enviro multiple-choice section questions, though note that the current format only has 80 questions and four answer choices per question. The practice test is timed and automatically graded for you. While it doesn't include any free-response questions, the multiple-choice questions are similar to those you'll see on the AP exam in terms of content.

You can combine these questions with a set of official free-response questions and make a complete APES practice test. If you'd like to practice a specific topic, Varsity Tutors also offers practice quizzes of varying difficulty for AP Environmental Science ; however, the topics are broken down into such specific categories that many quizzes have only one to two questions, which can make it tedious to move from one very short quiz to the next.

The AP quizzes can be helpful for more focused studying, but, in general, the full diagnostic test is the best resource to use from this site. While this quiz is shorter than many other AP practice quizzes and untimed, the questions are generally well written, so it's still a good resource to use. This website includes question quizzes for each of the 25 chapters of the Environmental Science textbook chapters.

To select a quiz, choose a chapter from the left-hand side of the page and then click "Practice Quiz" on the new page. These quizzes are fairly surface-level, but they can help you study specific topics or prepare for in-class exams , even if you don't use Environmental Science as your class textbook. One frustrating point, however, is that you must click on each chapter individually in order to see what areas it covers if you're looking to study a particular topic.

This is a very quick, question multiple-choice quiz. This is quite a short quiz and, strangely, it gives definitions for some keywords you should already know, but it might be helpful if you want a quick study session for AP Enviro. Effect of changes in green spaces on mental health in older adults: a fixed effects analysis. Journal of Epidemiology and Community Health , 74 1 , Biophilic Cities. Social prescribing for stress related disorders and brain health. Community, Mental Health, and Social Work.

Differential cooling effects of landscape parameters in humid-subtropical urban parks. Economic value of protected areas via visitor mental health. Urban Science , 3 4 , Evidence from Beijing. Does nature make us happier? A spatial error model of greenspace types and mental wellbeing. Green spaces and mortality: a systematic review and meta-analysis of cohort studies. The Lancet Planetary Health , 3 11 , ee Natural neighbourhood environments and the emotional health of urban New Zealand adolescents.

Oh, Erik S. Yando, Jingyuan Zhang, Daniel A. Sustainability , 11 22 , Igou, Eric Klinger. Meaning, nature and well-being. Darcy, Marc Jones, Christopher Gidlow. Affective responses to natural environments. The effect of short-term exposure to the natural environment on depressive mood: A systematic review and meta-analysis.

Neighbourhood greenness and mental wellbeing in Guangzhou, China: What are the pathways?. Subtypes of park use and self-reported psychological benefits among older adults: A multilevel latent class analysis approach. Sustainability , 11 20 , Urban greenery and mental wellbeing in adults: Cross-sectional mediation analyses on multiple pathways across different greenery measures. Burton, Kelly S. Fielding, Zoe Murray, Gavin Turrell.

Changes in perceptions of urban green space are related to changes in psychological well-being: Cross-sectional and longitudinal study of mid-aged urban residents. Packman, Daniel R.

Peters, Denise Lopez, David J. McCuskey, Robert I. McDonald, William M. Miller, Sera L. A systematic review of the human health and social well-being outcomes of green infrastructure for stormwater and flood management. Journal of Environmental Management , , Hodson, Heather A. Relationships between vegetation in student environments and academic achievement across the continental U.

Neural correlates of individual differences in affective benefit of real-life urban green space exposure. Nature Neuroscience , 22 9 , Connections with nature for people living with dementia. Working with Older People , 23 3 , Reeves, Andrew T. Knight, Emily A. A spatial analysis of proximate greenspace and mental wellbeing in London. Applied Geography , , Klompmaker, Gerard Hoek, Lizan D. Bloemsma, Alet H. Associations of combined exposures to surrounding green, air pollution and traffic noise on mental health.

Environment International , , Testing the unsolved problems hypothesis: The evolutionary life issues-mitigating function of nature exposure and its relationship with human well-being. Keith, B. Bynum Boley. Sustainability , 11 15 , Stenfors, Stephen C. Van Hedger, Kathryn E. Schertz, Francisco A. Meyer, Karen E. Smith, Greg J. Norman, Stefan C. Bourrier, James T. Urban resilience at eye level: Spatial analysis of empirically defined experiential landscapes. Bratman, Christopher B.

Anderson, Marc G. Gross, Terry Hartig, Peter H. Kahn, Ming Kuo, Joshua J. Lawler, Phillip S. Smith, Matilda van den Bosch, Benedict W. Wheeler, Mathew P. White, Hua Zheng, Gretchen C. Nature and mental health: An ecosystem service perspective. Science Advances , 5 7 , eaax Neighbourhood-level air pollution and greenspace and inflammation in adults. Residential exposure to green space and early childhood neurodevelopment. Sugg, P. Grady Dixon, Jennifer D. Crisis support-seeking behavior and temperature in the United States: Is there an association in young adults and adolescents?.

Fung, C. Microclimatic resilience of subtropical woodlands and urban-forest benefits. Sustainability , 11 12 , Is moving to a greener or less green area followed by changes in physical activity?. The natural environment and birth outcomes: Comparting 3D exposure metrics derived from LiDAR to 2D metrics based on the normalized difference vegetation index. Is urban living good for mental health?. Current Opinion in Psychiatry , 32 3 , Annual Review of Public Health , 40 1 , Residential green space in childhood is associated with lower risk of psychiatric disorders from adolescence into adulthood.

Proceedings of the National Academy of Sciences , 11 , Challenges facing green space: is statute the answer?. Journal of Place Management and Development , 12 1 , Winter, Pamela E. Padgett, Lee-Anne S.

Milburn, Weimin Li. Environmental Management , 63 3 , Green space associations with mental health and cognitive function.

Environmental Epidemiology , 3 1 , e Environmental Health Perspectives , 2 , Embedding social inclusiveness and appropriateness in engineering assessment of green infrastructure to enhance urban resilience.

Urban Water Journal , 16 1 , Alberto, Loyde A. Harbich, Ying Li. Measuring Wellbeing: How and Why?. Public Health Research , 7 2 , An SDG-based framework for assessing urban stormwater management systems.

Blue-Green Systems , 1 1 , Impact of a nature-based intervention on incarcerated women. International Journal of Prisoner Health , 14 4 , Residential green space quantity and quality and symptoms of psychological distress: a year longitudinal study of women in postpartum.

Neighborhood deprivation and biomarkers of health in Britain: the mediating role of the physical environment. Domestic gardens and self-reported health: a national population study. The green soul of the concrete jungle: the urban century, the urban psychological penalty, and the role of nature. Residential green and blue space associated with better mental health: a pilot follow-up study in university students.

Archives of Industrial Hygiene and Toxicology , 69 4 , Population and Environment , 40 2 , Pun, Justin Manjourides, Helen H. Association of neighborhood greenness with self-perceived stress, depression and anxiety symptoms in older U.

S adults. Breed, David Phillips, Philip Weinstein. Cities, biodiversity and health: we need healthy urban microbiome initiatives. Urban forest benefits to the younger population: The case study of the city of Belgrade, Serbia.

Forest Policy and Economics , 96 , Darrel Jenerette. Ecological contributions to human health in cities. Landscape Ecology , 33 10 , More green space is related to less antidepressant prescription rates in the Netherlands: A Bayesian geoadditive quantile regression approach. Journal of Public Mental Health , 17 3 , The relationship between greenspace and the mental wellbeing of adults: A systematic review.

Personal mobility and climate change. Wiley Interdisciplinary Reviews: Climate Change , 9 5 , e Gray space and green space proximity associated with higher anxiety in youth with autism.

Time spent outdoors, activity levels, and chronic disease among American adults. Journal of Behavioral Medicine , 41 4 , The role of water utilities in urban greening: A case study of Melbourne, Australia.

Utilities Policy , 53 , Atmosphere , 9 7 , Changes in the mode of travel to work and the severity of depressive symptoms: a longitudinal analysis of UK Biobank. Preventive Medicine , , Exposure to nature gardens has time-dependent associations with mood improvements for people with mid- and late-stage dementia: Innovative practice.

Dementia , 17 5 , Bundesgesundheitsblatt - Gesundheitsforschung - Gesundheitsschutz , 61 6 , Vegetation diversity protects against childhood asthma: results from a large New Zealand birth cohort. Nature Plants , 4 6 , Glazer, Melissa N. Eliot, Valery A. Danilack, Lynn Carlson, Maureen G. Phipps, Payam Dadvand, David A. Savitz, Gregory A. Residential green space and birth outcomes in a coastal setting. Soares, Ulrika K.

Stigsdotter, Catharine Ward Thompson. The Lancet Planetary Health , 2 4 , ee Are public open space attributes associated with walking and depression?. Cities , 74 , Natural environments and suicide mortality in the Netherlands: a cross-sectional, ecological study.

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