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Heat is known to affect many health outcomes, but more evidence is needed on the impact of rising temperatures on crime and/or violence. We conducted a systematic review with meta-analysis regarding the influence of hot temperatures on crime and/or violence. In this systematic review and meta-analysis, we evaluated the relationship between increase in temperature and crime and/or violence for studies across the world and generated overall estimates. We searched MEDLINE and Web of Science for articles from the available database start year (1946 and 1891, respectively) to 6 November 2023 and manually reviewed reference lists of identified articles. Two investigators independently reviewed the abstracts and full-text articles to identify and summarize studies that analyzed the relationship between increasing temperature and crime, violence, or both and met eligibility criteria. PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines were used to extract information from included articles. Some study results were combined using a profile likelihood random-effects model for meta-analysis for a subset of outcomes: violent crime (assault, homicide), property crime (theft, burglary), and sexual crime (sexual assault, rape). This review is registered at PROSPERO, CRD42023417295. We screened 16,634 studies with 83 meeting the inclusion criteria. Higher temperatures were significantly associated with crime, violence, or both. A 10°C (18°F) increase in short-term mean temperature exposure was associated with a 9% [95% confidence interval (CI): 7%, 12%] increase in the risk of violent crime ( ; eight studies). Studies had differing definitions of crime and/or violence, exposure assessment methods, and confounder assessments. Our findings summarize the evidence supporting the association between elevated temperatures, crime, and violence, particularly for violent crimes. Associations for some categories of crime and/or violence, such as property crimes, were inconsistent. Future research should employ larger spatial/temporal scales, consistent crime and violence definitions, advanced modeling strategies, and different populations and locations. https://doi.org/10.1289/EHP14300.

Climate change, the defining environmental crisis of our time, has been shown to impact concentration, distribution, and composition of tropospheric air pollutants, including particulate matter. Economic patterns greatly shape the generation of particulate matter as well as greenhouse gases that enhance climatic changes. Substantial evidence shows that exposure to fine particulates, particulate matter with aerodynamic diameter <2.5 µm (PM2.5), contributes to premature mortality and morbidity. These detrimental health outcomes have been shown to be experienced unequally across population groups, with disparities in the level of exposure and in the magnitude of health response for marginalized populations that have higher vulnerability to air pollution exposure. It is also possible that these health responses are not static, but dynamic over time due to changes in population health and composition of air pollution exposures, warranting deeper investigation into the directionality and shape of these health responses. Modeling potential future energy scenarios by using existing knowledge on health responses to air pollutants allows researchers and policymakers to understand how changes to air pollution can impact population health before policies are implemented. Thus, inclusion of appropriate modelling techniques and analyses of energy policy impacts is essential to understanding health impacts from climate mitigation and adaptation across population groups within the United States. This dissertation contributes to the growing knowledge base on climate mitigation, health co-benefits from air pollution concentration changes and health response changes across time to air pollution exposures. Chapter two presents work investigating whether energy policies that aim to reduce greenhouse gas emissions have a secondary impact of reducing health burden in the United States (U.S.) and if any changes to mortality and hospitalizations differ across subpopulations. I explored four future sector-specific energy policy scenarios (electrification of ports and marine shipping, low long-term natural gas pricing, high electric vehicle uptake, and innovations in building energy efficiency) and a business-as-usual scenario to determine how changes to ambient PM2.5 levels impact health within the continental U.S. by region, race/ethnicity, urbanicity, and income. I also investigated how methodological assumptions impact findings. I found projected avoided premature mortalities from energy transition policies range from 67,011 (95% CI: 45,692, 82,397) to 81,003 (55,286, 99,532) individuals in 2050 and 11,577 (1,332, 19,918) to 13,552 (1,560, 23,303) avoided cardiorespiratory hospitalizations in 2050, showing substantial health co-benefits from greenhouse gas mitigation policy implementation. These benefits vary by region and subpopulation, with Black, suburban, and less wealthy Americans experiencing the highest percent reduction in mortalities across all energy policy scenarios. Analysis into how population assumption specificity (such as using race-specific incidence rates instead of total population rates) influences the results proved that more specific population assumptions can make substantial differences to overall health projections. This research demonstrates the vast health benefits of climate mitigation strategies and how they differ across subpopulations, with some environmental justice populations benefiting more relative to the overall population. In chapter three, I investigated how PM2.5-mortality associations vary over time (2001-2016) in North Carolina and Michigan, while considering how temporality of these associations varies by sociodemographic variables. Results indicate that the direction of PM2.5– mortality health effects varies by location. The odds ratio (OR) for mortality per 10μg/m3 PM2.5 differed across time from 2001-2008 to 2009-2016, increasing by 0.28% in Michigan and decreasing 0.78% in North Carolina. Non-linear models show steadily increasing PM2.5-mortality odds over time for Michigan but an “S” shape for North Carolina. I also found suggestive evidence of widening disparities in PM2.5-mortality odds over time by age, race/ethnicity, urbanicity, sex, and education, although the magnitude of those changes varies across subpopulations and state. This research shows that mortality impacts of PM2.5 are changing over time, with different trends by location and subpopulation, potentially exacerbating environmental justice. This dissertation research underscores the importance of analysis to determine sociodemographic population health disparities when modeling co-benefits of energy and air pollution policies as overall estimates may obscure important differences across subpopulations. Better projections on local health effects on vulnerable communities can enhance equity considerations for climate mitigation actions, as well as provide a more holistic analysis on benefits of cost to implement versus avoided exposure and health costs. Further, this research shows that concentration-response functions may vary temporally and that such trends vary across location. This suggests that applications of historical concentration-response estimates may be obscuring the actual health impact on populations through over- or underestimates of health responses to a certain level of exposure. Improvements in the methodological assumptions of exposure and health response by introducing temporal variation provide researchers with a more accurate representation of the association between air pollution and health, which should be more widely considered in epidemiologic research. These results can inform policymakers and public health professionals in evaluating which communities are at highest risk from particulate exposures in the present day and into the future, especially in relation to temporal trends and projected changes in emissions, particulate composition, and population vulnerability.

Transnational immigration has increased since the 1950s. In countries such as the United States, immigrants now account for of the population. Although differences in health between immigrants and nonimmigrants are well documented, it is unclear how environmental exposures contribute to these disparities. We summarized current knowledge comparing immigrants' and nonimmigrants' exposure to and health effects of environmental exposures. We conducted a title and abstract review on articles identified through PubMed and selected those that assessed environmental exposures or health effects separately for immigrants and nonimmigrants. After a full text review, we extracted the main findings from eligible studies and categorized each article as exposure-focused, health-focused, or both. We also noted each study's exposure of interest, study location, exposure and statistical methods, immigrant and comparison groups, and the intersecting socioeconomic characteristics controlled for. We conducted a title and abstract review on 3,705 articles, a full text review on 84, and extracted findings from 50 studies. There were 43 studies that investigated exposure (e.g., metals, organic compounds, fine particulate matter, hazardous air pollutants) disparities, but only 12 studies that assessed health disparities (e.g., mortality, select morbidities). Multiple studies reported higher exposures in immigrants compared with nonimmigrants. Among immigrants, studies sometimes observed exposure disparities by country of origin and time since immigration. Of the 50 studies, 43 were conducted in North America. The environmental health of immigrants remains an understudied area, especially outside of North America. Although most identified studies explored potential exposure disparities, few investigated subsequent differences in health effects. Future research should investigate environmental health disparities of immigrants, especially outside North America. Additional research gaps include the role of immigrants' country of origin and time since immigration, as well as the combined effects of immigrant status with intersecting socioeconomic characteristics, such as race/ethnicity, income, and education attainment. https://doi.org/10.1289/EHP9855.

Donegal is a geographically removed county on the northwest coast of Ireland. It is known to have high levels of social deprivation¹.Feedback from both hospital and general practice (GP) colleagues indicate that there appears to be a high proportion of men in Donegal with long-term urinary catheters (LTCs). There is a perceived difficulty accessing Urology services for public (GMS) patients in Donegal.A retrospective analysis of Primary Care Reimbursement Service (PCRS) data (2013) was carried out which demonstrated:Total urinary catheter insertions in men over 65 years of age (2013): Donegal 907 ; Kerry 282; Dublin South 33; Dublin West 28; Waterford 1612.This gives a crude 2.55% rate for male GMS patients in Donegal greater than 65 years of age for urinary catheter insertions compared to Dublin South: 0.045% ;Waterford: 0.63 % ; NICE > 75yrs: 0.5%3.For the patients sampled in Donegal, The average duration since 1st urinary catheter insertion was 53 months. 89% of the patients had been referred to Urology. The mean wait for Urology review was 43.75 months. The mean patient age was 80 years. (21%) were based in a nursing home and (79%) were in the community.Differences in LTC rates in the population sampled in Donegal (Rural), Leinster (Urban) and Waterford (Suburban) were significant 1.41% (95% CI 1.0203 – 1.7958) (P < 0.0001) and 1.81% (95% CI 14840 – 2.1549) ( P < 0.0001) respectively.For many reasons Donegal has struggled with service provision particularly in services like Urology. Could this anomaly in LTC rates be a useful parameter to measure the quality and provision of local health services?References:1- Available from: http://census.cso.ie/areaprofiles/areaprofile.aspx?Geog_Type=CTY&Geog_Code=332- Available from: http://www.hse.ie/eng/staff/PCRS/PCRS_Publications/PCRS_Statistical_Analyis_of_Claims_and_Payments_2013.pdf3- Available from: https://www.nice.org.uk/guidance/cg2/documents/infection-control-second-consultation-full-guideline-section-32

[...]a recent report by Cushman & Wakefield (UK Student Accommodation Report) concluded that last year was the strongest on record for rental growth in the PBSA sector across the UK, with student rents in Glasgow rising more quickly than in any other major student hub across the country. A success story There is no shortage of statistics to reinforce the proposition that the PBSA market in Scotland is achieving strong financial results. In the same period, the Edinburgh market saw growth of 11.2% and, even more impressively, Glasgow returned an increase of 19.4%.