ABSTRACT
Urban residence is associated with a higher risk of some psychiatric disorders, but the underlying drivers remain unknown. There is increasing evidence that the level of exposure to natural environments impacts mental health, but few large-scale epidemiological studies have assessed the general existence and importance of such associations. Here, we investigate the prospective association between green space and mental health in the Danish population. Green space presence was assessed at the individual level using high-resolution satellite data to calculate the normalized difference vegetation index within a 210 × 210 m square around each person's place of residence (â¼1 million people) from birth to the age of 10. We show that high levels of green space presence during childhood are associated with lower risk of a wide spectrum of psychiatric disorders later in life. Risk for subsequent mental illness for those who lived with the lowest level of green space during childhood was up to 55% higher across various disorders compared with those who lived with the highest level of green space. The association remained even after adjusting for urbanization, socioeconomic factors, parental history of mental illness, and parental age. Stronger association of cumulative green space presence during childhood compared with single-year green space presence suggests that presence throughout childhood is important. Our results show that green space during childhood is associated with better mental health, supporting efforts to better integrate natural environments into urban planning and childhood life.
Subject(s)
Environment , Mental Disorders/epidemiology , Adolescent , Adult , Child , Denmark , Humans , Risk Factors , UrbanizationABSTRACT
Natural environments have been associated with mental health benefits worldwide. However, how different elements and types of natural environments associate with mental health is still largely unknown. In this study, we perform a detailed analysis on a large, nation-wide data set of mental health records (908 553 individuals) for Denmark combined with remotely-sensed land cover and vegetation density data. We explore associations between growing up surrounded by different environments and rates of a spectrum of 18 psychiatric disorders. Childhood land cover exposure for urban, agricultural, near-natural green space, and blue space was determined around the residence of each individual. Vegetation density and air pollution were evaluated as potential pathways. Cox proportional hazards models were used to estimate rates as hazard ratios and then adjusted for potential confounding from other known risk factors. For 12 of 18 disorders, rates were lower for children growing up in environments with more natural elements (near-natural green space, blue space, and agriculture) compared to children growing up in urban environments. High vegetation density was associated with lower rates for most disorders within all the examined environments, whereas mitigation of air pollution by natural environments seemed a less important potential pathway. Rates were not notably changed by adjustment for urbanization, parental and municipal socioeconomic status, family history of mental illness, and parents' age. In conclusion, we found that growing up surrounded by a range of natural environments such as near-natural green space, blue space, and agriculture may lower rates of psychiatric disorders. Our results show the importance of ensuring access to natural environments from as nature-based solutions for improved public health and sustainable, livable cities.
Subject(s)
Air Pollution , Mental Disorders , Child , Cities , Denmark/epidemiology , Environment , Humans , Mental Disorders/epidemiologyABSTRACT
Latitudinal and elevational richness gradients have received much attention from ecologists but there is little consensus on underlying causes. One possible proximate cause is increased levels of species turnover, or ß diversity, in the tropics compared to temperate regions. Here, we leverage a large botanical dataset to map taxonomic and phylogenetic ß diversity, as mean turnover between neighboring 100 × 100 km cells, across the Americas and determine key climatic drivers. We find taxonomic and tip-weighted phylogenetic ß diversity is higher in the tropics, but that basal-weighted phylogenetic ß diversity is highest in temperate regions. Supporting Janzen's 'mountain passes' hypothesis, tropical mountainous regions had higher ß diversity than temperate regions for taxonomic and tip-weighted metrics. The strongest climatic predictors of turnover were average temperature and temperature seasonality. Taken together, these results suggest ß diversity is coupled to latitudinal richness gradients and that temperature is a major driver of plant community composition and change.
Subject(s)
Biodiversity , Plants , Temperature , PhylogenyABSTRACT
Many species assemblages represent a nonrandom subset of a larger species pool. When an assemblage tends to contain close evolutionary relatives or species with similar functional traits, it can be described as phylogenetically or functionally clustered. Clustering is often interpreted as evidence for filtering by some combination of environmental and biotic factors. At sufficiently large spatial extents, however, biogeographic barriers can also lead to strong clustering. Here, we suggest that the breakdown of biogeographic barriers associated with human introductions of exotic species can be used as an unintentional experiment to assess their importance in driving phylogenetic and functional structure. An important role of biogeographic barriers would be revealed by a breakdown in clustering, particularly phylogenetic clustering, following species introductions. On the other hand, a role of filtering can be supported by similar patterns of clustering in the native and exotic assemblages along environmental gradients. We test these predictions using the grasses of California, a diverse group including many introduced species. Native grass assemblages in the state are highly clustered with respect to the global grass species pool, both phylogenetically and functionally. Within the state, variation in the strength of clustering is well explained by climatic variables, suggesting an important role for environmental-biotic filtering. Further, subregions within the state with highly clustered native assemblages also contain highly clustered exotic assemblages. Contrary to expectation, though, the introduction of exotic species led to even more strongly clustered assemblages. We conclude that biogeographic barriers have generally not excluded the major grass lineages (e.g., tribes) from the state and likely act only on finer taxonomic scales (for example, excluding particular genera). Our approach should prove broadly applicable and contribute to improved understanding of broad-scale patterns of assemblage structure.
Subject(s)
Introduced Species , Phylogeny , Poaceae/genetics , Poaceae/physiology , California , Demography , Ecosystem , Reproduction/physiology , TemperatureABSTRACT
The extent to which species' ecological and phylogenetic relatedness shape their co-occurrence patterns at large spatial scales remains poorly understood. By quantifying phylogenetic assemblage structure within geographic ranges of >8000 bird species, we show that global co-occurrence patterns are linked - after accounting for regional effects - to key ecological traits reflecting diet, mobility, body size and climatic preference. We found that co-occurrences of carnivorous, migratory and cold-climate species are phylogenetically clustered, whereas nectarivores, herbivores, frugivores and invertebrate eaters tend to be more phylogenetically overdispersed. Preference for open or forested habitats appeared to be independent from the level of phylogenetic clustering. Our results advocate for an extension of the tropical niche conservatism hypothesis to incorporate ecological and life-history traits beyond the climatic niche. They further offer a novel species-oriented perspective on how biogeographic and evolutionary legacies interact with ecological traits to shape global patterns of species coexistence in birds.
Subject(s)
Birds/classification , Birds/physiology , Models, Biological , Phylogeny , Animals , Climate , Ecosystem , Homing BehaviorABSTRACT
Natural environments have been associated with mental health benefits, but globally access to these benefits is threatened by urban development and densification. However, it remains unclear how natural environments relate to mental health and how consistent the association is across populations. Here we use a life-course approach with a population consisting of 66 194 individuals from the Danish Blood Donor Study (DBDS) to investigate the association between green and blue space (e.g. parks and lakes) and self-evaluated mental well-being. Green and blue space was identified from remotely-sensed images from the Landsat program, while mental well-being was based on the mental component score (MCS) calculated using the 12-item short form health survey. We use multivariate linear regression models and logistic regression models to quantify the associations. We adjust for additional environmental (urbanization, and air pollution) and lifestyle factors (smoking, body mass index, socioeconomic status, and physical activity) and specifically evaluate the role of physical activity and air pollution as possible mediating factors. We found a positive association between the MCS and current and childhood green space, and a non-significant association for current and childhood blue space. Adjusting for environmental and the other factors attenuated the effect sizes indicating that a broad range of factors determine mental well-being. Physical activity and air pollution were both associated with the MCS as possible mediators of green space associations. In addition, the odds for successfully completing tasks', seeing others, and feeling less downhearted increased with higher levels of green space, and the odds of feeling calm increased with higher levels of blue space. In conclusion, we found support for an association between green and, to less degree, blue space and mental well-being throughout different life stages. In addition, we found a positive association with individual indicators of mental well-being such as being productive, feeling less downhearted and calmer, and being social. The healthy blood donor effect and the bias towards urban residency may explain why we found smaller effect sizes between green and blue space and mental well-being for this generally healthy and resourceful cohort compared to previous studies.
Subject(s)
Life Change Events , Mental Health , Blood Donors , Child , Denmark , Environment , HumansABSTRACT
High exposure to green space and natural environments has previously been associated with lower schizophrenia rates possibly through low air pollution and improved psychological restoration. Exposure to natural environments could explain the negative urban-rural gradient of schizophrenia, but it is unclear if all natural environments are associated with schizophrenia rates. We investigated the association between schizophrenia and growing up surrounded by environments classified as mainly urban, agricultural, near-natural green space, and blue space. Vegetation density and air pollution were assessed as potential pathways. We used the Danish population (943â¯027 people) and remotely-sensed environmental data to determine land cover exposure and vegetation density around each individual's residence. Effect sizes were estimated using Cox regression and adjusted for air pollution, socioeconomic status, and urbanization. Our results show that growing up surrounded by non-urban environments is associated with lower schizophrenia rates. Firstly, growing up surrounded by non-built-up areas (agricultural areas, near-natural green and blue space) is associated with lower schizophrenia rates compared to urban areas. Secondly, rates decrease with vegetation density in a dose-response relationship for urban and agricultural areas. Air pollution mitigation more strongly explained the protective association in near-natural green spaces, implying that restorative pathways together with air pollution mitigation may explain lower rates in natural environments. This study suggests that ensuring access to natural environments during childhood may be important for schizophrenia prevention, whilst being the first study to show that natural environments may influence schizophrenia rates through multiple pathways.
Subject(s)
Air Pollution , Schizophrenia , Air Pollution/adverse effects , Environment , Humans , Rural Population , Schizophrenia/epidemiology , UrbanizationABSTRACT
Childhood exposure to green space has previously been associated with lower risk of developing schizophrenia later in life. It is unclear whether this association is mediated by genetic liability or whether the 2 risk factors work additively. Here, we investigate possible gene-environment associations with the hazard ratio (HR) of schizophrenia by combining (1) an estimate of childhood exposure to residential-level green space based on the normalized difference vegetation index (NDVI) from Landsat satellite images, with (2) genetic liability estimates based on polygenic risk scores for 19 746 genotyped individuals from the Danish iPSYCH sample. We used information from the Danish registers of health, residential address, and socioeconomic status to adjust HR estimates for established confounders, ie, parents' socioeconomic status, and family history of mental illness. The adjusted HRs show that growing up surrounded by the highest compared to the lowest decile of NDVI was associated with a 0.52-fold (95% confidence interval [CI]: 0.40 to 0.66) lower schizophrenia risk, and children with the highest polygenic risk score had a 1.24-fold (95% CI: 1.18 to 1.30) higher schizophrenia risk. We found that NDVI explained 1.45% (95% CI: 1.07 to 1.90) of the variance on the liability scale, while polygenic risk score for schizophrenia explained 1.01% (95% CI: 0.77 to 1.46). Together they explained 2.40% (95% CI: 1.99 to 3.07) with no indication of a gene-environment interaction (P = .29). Our results suggest that risk of schizophrenia is associated additively with green space exposure and genetic liability, and provide no support for an environment-gene interaction between NDVI and schizophrenia.
Subject(s)
Parks, Recreational/statistics & numerical data , Registries/statistics & numerical data , Schizophrenia , Denmark/epidemiology , Gene-Environment Interaction , Humans , Incidence , Multifactorial Inheritance , Schizophrenia/epidemiology , Schizophrenia/etiology , Schizophrenia/geneticsABSTRACT
Schizophrenia risk has been linked to urbanization, but the underlying mechanism remains unknown. Green space is hypothesized to positively influence mental health and might mediate risk of schizophrenia by mitigating noise and particle pollution exposure, stress relief, or other unknown mechanisms. The objectives for this study were to determine if green space are associated with schizophrenia risk, and if different measures of green space associate differently with risk. We used satellite data from the Landsat program to quantify green space in a new data set for Denmark at 30×30m resolution for the years 1985-2013. The effect of green space at different ages and within different distances from each person's place of residence on schizophrenia risk was estimated using Cox regression on a very large longitudinal population-based sample of the Danish population (943,027 persons). Living at the lowest amount of green space was associated with a 1.52-fold increased risk of developing schizophrenia compared to persons living at the highest level of green space. This association remained after adjusting for known risk factors for schizophrenia: urbanization, age, sex, and socioeconomic status. The strongest protective association was observed during the earliest childhood years and closest to place of residence. This is the first nationwide population-based study to demonstrate a protective association between green space during childhood and schizophrenia risk; suggesting limited green space as a novel environmental risk factor for schizophrenia. This study supports findings from other studies highlighting positive effects of exposure to natural environments for human health.
Subject(s)
Environment , Psychotic Disorders/epidemiology , Schizophrenia/epidemiology , Age Factors , Child , Child, Preschool , Denmark/epidemiology , Female , Geography, Medical , Humans , Incidence , Infant , Infant, Newborn , Longitudinal Studies , Male , Prospective Studies , Residence Characteristics , Risk Factors , Rural Population , Satellite Imagery , Urban Population , UrbanizationABSTRACT
For many applications in ecology, it is important to examine the phylogenetic relations between two communities of species. More formally, let [Formula: see text] be a phylogenetic tree and let A and B be two samples of its tips, representing the examined communities. We want to compute a value that expresses the phylogenetic diversity between A and B in [Formula: see text]. There exist several measures that can do this; these are the so-called phylogenetic beta diversity (ß-diversity) measures. Two popular measures of this kind are the Community Distance (CD) and the Common Branch Length (CBL). In most applications, it is not sufficient to compute the value of a beta diversity measure for two communities A and B; we also want to know if this value is relatively large or small compared to all possible pairs of communities in [Formula: see text] that have the same size. To decide this, the ideal approach is to compute a standardised index that involves the mean and the standard deviation of this measure among all pairs of species samples that have the same number of elements as A and B. However, no method exists for computing exactly and efficiently this index for CD and CBL. We present analytical expressions for computing the expectation and the standard deviation of CD and CBL. Based on these expressions, we describe efficient algorithms for computing the standardised indices of the two measures. Using standard algorithmic analysis, we provide guarantees on the theoretical efficiency of our algorithms. We implemented our algorithms and measured their efficiency in practice. Our implementations compute the standardised indices of CD and CBL in less than twenty seconds for a hundred pairs of samples on trees with 7 â 10(4) tips. Our implementations are available through the R package PhyloMeasures.
Subject(s)
Algorithms , Biodiversity , Phylogeny , Animals , Eukaryota , HumansABSTRACT
Diseases which are caused by non-tuberculous mycobacteria (NTM) are an increasing problem in the developed countries. In Latvia, one of the most clinically important members of NTM is Mycobacterium avium (M. avium), an opportunistic pathogen which has been isolated from several lung disease patients and tissue samples of slaughter pigs. This study was designed to characterize the genetic diversity of the M. avium isolates in Latvia and to compare the distribution of genotypic patterns among humans and pigs. Eleven (Hall and Salipante, 2010) clinical M. avium samples, isolated from patients of Center of Tuberculosis and Lung Diseases (years 2003-2010), and 32 isolates from pig necrotic mesenterial lymph nodes in different regions (years 2003-2007) were analyzed. The majority (42 of 43) of samples were identified as M. avium subsp. hominissuis; one porcine isolate belonged to M. avium subsp. avium. MIRU-VNTR genotyping revealed 13 distinct genotypes, among which nine genotype patterns, including M. avium subsp. avium isolate, were newly identified. IS1245 RFLP fingerprinting of 25 M. avium subsp. hominissuis samples yielded 17 different IS1245 RFLP patterns, allowing an efficient discrimination of isolates. Clusters of identical RFLP profiles were observed within host species, geographical locations and time frame of several years. Additional in silico analysis on simulated MIRU-VNTR genotype population datasets showed that the MIRU-VNTR pattern similarity could partly arise due to probabilistic increase of acquiring homoplasy among subpopulations, thus the similar MIRU-VNTR profiles of M. avium strains even in close geographical proximity should be interpreted with caution.
Subject(s)
DNA, Bacterial/genetics , Minisatellite Repeats , Mycobacterium avium/classification , Tuberculosis/microbiology , Animals , Computer Simulation , Genetic Variation , Genotype , Humans , Latvia , Mycobacterium avium/genetics , Mycobacterium avium/isolation & purification , Phylogeny , Swine , Swine Diseases/microbiology , Tuberculosis/veterinaryABSTRACT
BACKGROUND: The phylogenetic Mean Pairwise Distance (MPD) is one of the most popular measures for computing the phylogenetic distance between a given group of species. More specifically, for a phylogenetic tree [Formula: see text] and for a set of species R represented by a subset of the leaf nodes of [Formula: see text], the MPD of R is equal to the average cost of all possible simple paths in [Formula: see text] that connect pairs of nodes in R. Among other phylogenetic measures, the MPD is used as a tool for deciding if the species of a given group R are closely related. To do this, it is important to compute not only the value of the MPD for this group but also the expectation, the variance, and the skewness of this metric. Although efficient algorithms have been developed for computing the expectation and the variance the MPD, there has been no approach so far for computing the skewness of this measure. RESULTS: In the present work we describe how to compute the skewness of the MPD on a tree [Formula: see text] optimally, in Θ(n) time; here n is the size of the tree [Formula: see text]. So far this is the first result that leads to an exact, let alone efficient, computation of the skewness for any popular phylogenetic distance measure. Moreover, we show how we can compute in Θ(n) time several interesting quantities in [Formula: see text], that can be possibly used as building blocks for computing efficiently the skewness of other phylogenetic measures. CONCLUSIONS: The optimal computation of the skewness of the MPD that is outlined in this work provides one more tool for studying the phylogenetic relatedness of species in large phylogenetic trees. Until now this has been infeasible, given that traditional techniques for computing the skewness are inefficient and based on inexact resampling.