Figure - available from: GeoHealth
This content is subject to copyright. Terms and conditions apply.
Map showing the case study region of New England, composed of six states in the northeastern United States: Connecticut (CT), Rhode Island (RI), Massachusetts (MA), Vermont (VT), New Hampshire (NH), and Maine (ME). Population data based on 2010 U.S. Census (Centers for Disease Control and Prevention, 2015), highway shapefile provided by Esri®, and background mapping provided by ArcWorld and ArcWorld Supplement from Esri®.
Source publication
Weather and climate have substantial effects on human health. While much is known about how morbidity and mortality are affected by moderate-to-extreme heat, poor air quality, and heavy precipitation individually, less is known about the cumulative occurrence of these climatic hazards, and the extent to which they spatially overlap with community-s...
Similar publications
We hereby present the variability of fine particles (PM1 ≤ 1 micron) that has not yet been investigated under the influence of COVID-19-induced lockdown in three major cities of different climatic zones in India. We unfold the baseline level of PM1, a level to which the population is chronically exposed and extremely critical for epidemiologists fo...
Citations
... According to the literature spatial planning effectiveness on integrating the human and natural aspects of hazards facilitate impacts assessments. (Spangler et al. 2019). An integrative earthquake hazards assessment within the spatial planning system plays a pivotal role in identifying communities that face both frequent hazards and relatively high vulnerability. ...
The 2011 Tohoku Earthquake catapulted seismic vulnerabilities to the forefront of Japan's concerns, sparking a seismic shift in spatial planning and disaster management strategies. Through an exploration of the interplay between seismic realities, legislative responses, and planning frameworks, this study unveils Japan's adept utilization of innovative technologies and legislative adaptations to fortify its preparedness. The research leverages NASA-USGS data collection, Geographic Information System (GIS) technology, kriging interpolation, and relational content analysis to illuminate Japan's trajectory towards heightened resilience. Therefore, a long term satellite data collected based on NASA-USGS data between 2000 and 2023 which is 10 years before and after the Great East Japan Earthquake in Fukushima, 2011 or known as 2011 Tohoku. Japan's intricate seismic landscape, coupled with the profound impact of the 2011 Tohoku Earthquake, necessitated an immediate re-evaluation of its spatial planning and disaster management strategies. To comprehend the aftermath of the profound 2011 Tohoku Earthquake, this study delves into Japan's intricate seismic landscape, which compelled an immediate re-evaluation of disaster management strategies. It strives to unravel the intricate connections among seismic attributes, legislative adjustments, and planning systems that collectively shape Japan's capacity and feasibility to mitigate risks and amplify its resilience. The earthquake's seismic attributes spurred a proactive fusion of targeted risk evaluation and mitigation strategies within the planning fabric. The legislative adaptations and evolving planning drafts demonstrate Japan's commitment to strengthening its resilience against seismic intricacies and environmental hazards, effectively positioning the nation at the vanguard of disaster readiness.
... Average ambient temperature and relative humidity on a 4 km × 4 km scale over the sampling period was calculated at the geocoded residential address at the time of each visit. 41 ...
Introduction
Indoor nitrogen dioxide (NO 2 ) sources include gas heating, cooking, and infiltration from outdoors. Associations with pulmonary function, systemic inflammation, and oxidative stress in patients with chronic obstructive pulmonary disease (COPD) are uncertain.
Methods
We recruited 144 COPD patients at the VA Boston Healthcare System between 2012 and 2017. In-home NO 2 was measured using an Ogawa passive sampling badge for a week seasonally followed by measuring plasma biomarkers of systemic inflammation (C-reactive protein [CRP] and interleukin-6 [IL-6]), urinary oxidative stress biomarkers (8-hydroxy-2'deoxyguanosine [8-OHdG] and malondialdehyde [MDA]), and pre- and postbronchodilator spirometry. Linear mixed effects regression with a random intercept for each subject was used to assess associations with weekly NO 2 . Effect modification by COPD severity and by body mass index (BMI) was examined using multiplicative interaction terms and stratum-specific effect estimates.
Results
Median (25%ile, 75%ile) concentration of indoor NO2 was 6.8 (4.4, 11.2) ppb. There were no associations observed between NO 2 with CRP, 8-OHdG, or MDA. Although the confidence intervals were wide, there was a reduction in prebronchodilator FEV 1 and FVC among participants with more severe COPD (FEV 1 : –17.36 mL; –58.35, 23.60 and FVC: –28.22 mL; –91.49, 35.07) that was greater than in patients with less severe COPD (FEV 1 : –1.64 mL; –24.80, 21.57 and FVC: –6.22 mL; –42.16, 29.71). In participants with a BMI <30, there was a reduction in FEV 1 and FVC.
Conclusions
Low-level indoor NO 2 was not associated with systemic inflammation or oxidative stress. There was a suggestive association with reduced lung function among patients with more severe COPD and among patients with a lower BMI.
... [80][81][82] Moreover, the vulnerability of social and ecological communities displays high spatial variability with certain regions much more threatened by climate change than others. [83][84][85][86] Such high spatiotemporal variability and uncertainty contribute not only to a diverse resilience to climate change but also to different public risk perceptions, 87 and climate negotiation strategies may adjust accordingly. 58 Additionally, demographics, environmental organizations, organized unions, elected officials, green and brown lobbying, and other entities can influence public opinion and the adoption of policies. ...
... Climatic and geographical factors such as temperature, rainfall, relative humidity and altitude are important to define risk, but the ability to differentiate risk levels with these variables is limited in this set-up, as they tend to vary minimally in the context of neighboring geographical areas [55,56]. ...
To better guide dengue prevention and control efforts, the use of routinely collected data to develop risk maps is proposed. For this purpose, dengue experts identified indicators representative of entomological, epidemiological and demographic risks, hereafter called components, by using surveillance data aggregated at the level of Consejos Populares (CPs) in two municipalities of Cuba (Santiago de Cuba and Cienfuegos) in the period of 2010–2015. Two vulnerability models (one with equally weighted components and one with data-derived weights using Principal Component Analysis), and three incidence-based risk models were built to construct risk maps. The correlation between the two vulnerability models was high (tau > 0.89). The single-component and multicomponent incidence-based models were also highly correlated (tau ≥ 0.9). However, the agreement between the vulnerability- and the incidence-based risk maps was below 0.6 in the setting with a prolonged history of dengue transmission. This may suggest that an incidence-based approach does not fully reflect the complexity of vulnerability for future transmission. The small difference between single- and multicomponent incidence maps indicates that in a setting with a narrow availability of data, simpler models can be used. Nevertheless, the generalized linear mixed multicomponent model provides information of covariate-adjusted and spatially smoothed relative risks of disease transmission, which can be important for the prospective evaluation of an intervention strategy. In conclusion, caution is needed when interpreting risk maps, as the results vary depending on the importance given to the components involved in disease transmission. The multicomponent vulnerability mapping needs to be prospectively validated based on an intervention trial targeting high-risk areas.
... Some of these populations are referred to as susceptible, meaning they are biologically predisposed to more severe health outcomes, while others are considered vulnerable, meaning there are societal and structural issues that place them at higher risk (59). While investigations in the heat and health literature identify ways that data source decisions can affect measures of association by changing exposure misclassification rates, results from the present study show that while different data sources may decrease levels of measurement error and minimize the impact of exposure misclassification, these changes do not occur uniformly across strata of many common environmental and community determinants of health such as race, socioeconomic status, and social vulnerability, which vary substantially over space (49,(60)(61)(62). These factors all increase a population's vulnerability to negative health effects of climate change (53,54,60,(63)(64)(65)(66)(67). ...
... While investigations in the heat and health literature identify ways that data source decisions can affect measures of association by changing exposure misclassification rates, results from the present study show that while different data sources may decrease levels of measurement error and minimize the impact of exposure misclassification, these changes do not occur uniformly across strata of many common environmental and community determinants of health such as race, socioeconomic status, and social vulnerability, which vary substantially over space (49,(60)(61)(62). These factors all increase a population's vulnerability to negative health effects of climate change (53,54,60,(63)(64)(65)(66)(67). The results presented here demonstrate that the evaluated data sources and methods vary across commonly identified vulnerability factors, suggesting that different exposure data may limit the ability to detect harmful health effects of climate change in a population at higher risk. ...
Epidemiologic investigations of extreme precipitation events (EPEs) often rely on observations from the nearest weather station to represent individuals' exposures, and due to structural factors that determine the siting of weather stations, levels of measurement error and misclassification bias may differ by race, class, and other measures of social vulnerability. Gridded climate datasets provide higher spatial resolution that may improve measurement error and misclassification bias. However, similarities in the ability to identify EPEs among these types of datasets have not been explored. In this study, we characterize the overall and temporal patterns of agreement among three commonly used meteorological data sources in their identification of EPEs in all census tracts and counties in the conterminous United States over the 1991–2020 U.S. Climate Normals period and evaluate the association between sociodemographic characteristics with agreement in EPE identification. Daily precipitation measurements from weather stations in the Global Historical Climatology Network (GHCN) and gridded precipitation estimates from the Parameter-elevation Relationships on Independent Slopes Model (PRISM) and the North American Land Data Assimilation System (NLDAS) were compared in their ability to identify EPEs defined as the top 1% of precipitation events or daily precipitation >1 inch. Agreement among these datasets is fair to moderate from 1991 to 2020. There are spatial and temporal differences in the levels of agreement between ground stations and gridded climate datasets in their detection of EPEs in the United States from 1991 to 2020. Spatial variation in agreement is most strongly related to a location's proximity to the nearest ground station, with areas furthest from a ground station demonstrating the lowest levels of agreement. These areas have lower socioeconomic status, a higher proportion of Native American population, and higher social vulnerability index scores. The addition of ground stations in these areas may increase agreement, and future studies intending to use these or similar data sources should be aware of the limitations, biases, and potential for differential misclassification of exposure to EPEs. Most importantly, vulnerable populations should be engaged to determine their priorities for enhanced surveillance of climate-based threats so that community-identified needs are met by any future improvements in data quality.
... In additional analyses, we restricted hospitalizations to the warmer months. We chose May through September because a prior study in New England demonstrated that the frequency of days with excessive heat, heavy precipitation, and ozone and fine particulate matter extremes during these months spatially corelated with social vulnerability (36). We examined separate models for inflammatory arthritis (RA, psoriatic arthritis, ankylosing spondylitis, sacroiliitis, palindromic rheumatism, juvenile idiopathic arthritis), connective tissue disease (CTD) (SLE, Sjögren's syndrome, mixed or unspecified CTD, sarcoidosis, inflammatory myositis), vasculitis, crystalline arthritis (gout and pseudogout), and osteoarthritis. ...
Objective
Climate and social vulnerability contribute to morbidity and health care utilization. We examined associations between the neighborhood Social Vulnerability Index (SVI) and the Heat Vulnerability Index (HVI) and recurrent hospitalizations among individuals with rheumatic conditions.
Methods
Using a Massachusetts multihospital centralized clinical data repository, we identified individuals ≥18 years of age with a rheumatic condition who received rheumatology care within 3 years of April 2021. We defined the index date as 2 years before the last encounter and the baseline period as 1 year pre‐index date. Addresses were geocoded and linked by census tract to the SVI and the HVI. We used multilevel, multinomial logistic regression to examine the odds of 1–3 and ≥4 hospitalizations (reference = 0) over 2 years post index date by vulnerability index, adjusting for age, gender, race/ethnicity, insurance, and comorbidities.
Results
Among 14,401 individuals with rheumatic conditions, the mean ± age was 61.9 ± 15.7 years, 70% were female, 79% White, 7% Black, and 2% Hispanic. There were 8,251 hospitalizations; 11,649 individuals (81%) had 0 hospitalizations, 2,063 (14%) had 1–3, and 689 (5%) had ≥4. Adjusting for individual‐level factors, individuals living in the highest versus lowest SVI areas had 1.84 times higher odds (95% confidence interval [95% CI] 1.43–2.36) of ≥4 hospitalizations. Individuals living in the highest versus lowest HVI areas had 1.64 times greater odds (95% CI 1.17–2.31) of ≥4 hospitalizations.
Conclusion
Individuals with rheumatic conditions living in areas with high versus low social and heat vulnerability had significantly greater odds of recurrent hospitalizations. Studies are needed to determine modifiable factors to mitigate risks.
... For example, it has been estimated that the time lag between a CO 2 emission pulse and its maximum impact on average temperature may be of several decades (Ricke and Caldeira, 2014a; Zickfeld and Herrington, 2015;. Moreover, the vulnerability of social and ecological communities displays high spatial variability with certain regions much more threatened by climate change than others (Reid et al., 2009;Flanagan et al., 2011;Field and Barros, 2014;Spangler et al., 2019). Such high spatio-temporal variability and uncertainty contribute not only to a diverse resilience to climate change but also to different public risk perceptions (Leiserowitz, 2006), and climate negotiation strategies may adjust accordingly citebarrett2012climate. ...
Anthropogenic emissions of CO2 must soon approach net-zero to stabilize the global mean temperature. Although several international agreements have advocated for coordinated climate actions, their implementation has remained below expectations. One of the main challenges of international cooperation is the different degrees of socio-political acceptance of decarbonization. Here we interrogate a minimalistic model of the coupled natural-human system representing the impact of such socio-political acceptance on clean energy investments and the path to net-zero emissions. We show that incentives and carbon pricing are essential tools to achieve net-zero before critical CO2 concentrations are reached, and deep international coordination is necessary for a rapid and effective transition. Although a perfect coordination scenario remains unlikely, as investments in clean energy are ultimately limited by myopic economic strategies and a policy system that promotes free-riding, more realistic decentralized cooperation with partial efforts from each actor could still lead to significant emissions cuts.
... While international and national assessments of climate change, such as those produced by the United Nations Intergovernmental Panel on Climate Change (IPCC) and the US Global Change Research Program, are focused on describing broad climate mechanisms, risks, and trends, this information is of limited value to people seeking to understand what climate change could mean for them and their local communities specifically. Just as both local and global actions are needed to appropriately contend with the climate crisis, so too must information about the impacts of climate change be made available on multiple scales (Patz et al. 2005;Spangler et al. 2019). But an advantage of presenting climate change as a local and regional health problem is that such an approach lends itself to the field of applied epidemiology, which relates changes in local and/or regional environmental conditions (e.g., changes in daily minimum and maximum temperatures) to expected changes in the incidence of health problems (e.g., heat stroke) (Limaye et al. 2018). ...
Climate change-driven health impacts are serious, widespread, and costly. Importantly, such damages are largely absent from policy debates around the costs of delay and inaction on this crisis. While climate change is a global problem, its impacts are localized and personal, and there is growing demand for specific information on how climate change affects human health in different places. Existing research indicates that climate-fueled health problems are growing, and that investments in reducing carbon pollution and improving community resilience could help to avoid tens to hundreds of billions of dollars in climate-sensitive health impacts across the USA each year, including those stemming from extreme heat, air pollution, hurricanes, and wildfires. Science that explores the underappreciated local health impacts and health-related costs of climate change can enhance advocacy by demonstrating the need to both address the root causes of climate change and enhance climate resilience in vulnerable communities. The climate crisis has historically been predominantly conceived as a global environmental challenge; examination of climate impacts on public health enables researchers to localize this urgent problem for members of the public and policymakers. In turn, approaches to climate science that focus on health can make dangerous climate impacts and the need for cost-effective solutions more salient and tangible.
... Assess the threat posed by climate change . Explore the association between heat-related outcomes and social vulnerability (Spangler et al. 2019;Lehnert et al. 2020). ...
... As a result, cities are responsible for about 80% of global carbon dioxide emissions including the greenhouse gasses that further impacts climate change (Keivani, 2010). This has led to the recent increase in environmental hazards such as hurricanes, air pollution and floods in major cities of North America, China, England and the Caribbean (Keivani, 2010;Spangler et al., 2019). Tackling the challenges facing urban centres such as waste management, carbon emissions and environmental degradation could be the drive for the achievement of the SDGs (Kawakubo et al., 2018;Parnell, 2016;Sanchez Rodriguez et al., 2018). ...
The 2015 Paris Agreement marked a significant shift in public and scholarly discourse on climate change by laying more emphasis on stakeholder involvement and local level policies in achieving sustainability transitions. Sustainable Development Goal 12 further emphasises the importance of households in achieving sustainable consumption before 2030, especially in urban centres. However, since its adoption in 2015, no study has sought to synthesise the scholarship conducted around the emerging urban household consumption challenges that could inhibit the achievement of Goal 12. Through a systematic selection and in-depth review of relevant literature over the last five years, this paper assesses these sustainability challenges and critically examines the policy implications for achieving sustainable consumption. The review notes that in recent years, researchers have explored a range of issues including energy consumption, sustainable lifestyles, consumption footprints and class relations in urban household consumption through models and social perspectives. The urban household challenges identified include, inter alia: intensifying household consumption; rising commodification of household activities; continued reliance on unsustainable energy sources; low levels of sustainability education; high costs of sustainable lifestyles; and class differences in sustainable consumption patterns. In addressing these problems, the literature suggests strategies such as greening urban infrastructure, involving households in intervention programmes and promoting sustainability education, among others. Furthermore, to achieve Goal 12, future research and policy initiatives should consider the impact of materiality in household consumption, explore the interlinkages of household consumption with wider socio-cultural institutions and be more practice-oriented.
