ASU Scholarship Showcase

Background: While there is ample evidence for health risks associated with heat and other extreme weather events today, little is known about the impact of weather patterns on population health in preindustrial societies.

Objective: To investigate the impact of weather patterns on population health in Sweden before and during industrialization.

Methods: We obtained records of monthly mortality and of monthly mean temperatures and precipitation for Skellefteå parish, northern Sweden, for the period 1800-1950. The associations between monthly total mortality, as well as monthly mortality due to infectious and cardiovascular diseases, and monthly mean temperature and cumulative precipitation were modelled using a time series approach for three separate periods, 1800−1859, 1860-1909, and 1910-1950.

Results: We found higher temperatures and higher amounts of precipitation to be associated with lower mortality both in the medium term (same month and two-months lag) and in the long run (lag of six months up to a year). Similar patterns were found for mortality due to infectious and cardiovascular diseases. Furthermore, the effect of temperature and precipitation decreased over time.

Conclusions: Higher temperature and precipitation amounts were associated with reduced death counts with a lag of up to 12 months. The decreased effect over time may be due to improvements in nutritional status, decreased infant deaths, and other changes in society that occurred in the course of the demographic and epidemiological transition.

Contribution: The study contributes to a better understanding of the complex relationship between weather and mortality and, in particular, historical weather-related mortality.

Background: Extreme heat is a public health challenge. The scarcity of directly comparable studies on the association of heat with morbidity and mortality and the inconsistent identification of threshold temperatures for severe impacts hampers the development of comprehensive strategies aimed at reducing adverse heat-health events.

Objectives: This quantitative study was designed to link temperature with mortality and morbidity events in Maricopa County, Arizona, USA, with a focus on the summer season.
Methods: Using Poisson regression models that controlled for temporal confounders, we assessed daily temperature–health associations for a suite of mortality and morbidity events, diagnoses, and temperature metrics. Minimum risk temperatures, increasing risk temperatures, and excess risk temperatures were statistically identified to represent different “trigger points” at which heat-health intervention measures might be activated.

Results: We found significant and consistent associations of high environmental temperature with all-cause mortality, cardiovascular mortality, heat-related mortality, and mortality resulting from conditions that are consequences of heat and dehydration. Hospitalizations and emergency department visits due to heat-related conditions and conditions associated with consequences of heat and dehydration were also strongly associated with high temperatures, and there were several times more of those events than there were deaths. For each temperature metric, we observed large contrasts in trigger points (up to 22°C) across multiple health events and diagnoses.

Conclusion: Consideration of multiple health events and diagnoses together with a comprehensive approach to identifying threshold temperatures revealed large differences in trigger points for possible interventions related to heat. Providing an array of heat trigger points applicable for different end-users may improve the public health response to a problem that is projected to worsen in the coming decades.

Background: Extreme heat is a leading weather-related cause of mortality in the United States, but little guidance is available regarding how temperature variable selection impacts heat–mortality relationships.
Objectives: We examined how the strength of the relationship between daily heat-related mortality and temperature varies as a function of temperature observation time, lag, and calculation method.
Methods: Long time series of daily mortality counts and hourly temperature for seven U.S. cities with different climates were examined using a generalized additive model. The temperature effect was modeled separately for each hour of the day (with up to 3-day lags) along with different methods of calculating daily maximum, minimum, and mean temperature. We estimated the temperature effect on mortality for each variable by comparing the 99th versus 85th temperature percentiles, as determined from the annual time series.

Results: In three northern cities (Boston, MA; Philadelphia, PA; and Seattle, WA) that appeared to have the greatest sensitivity to heat, hourly estimates were consistent with a diurnal pattern in the heat-mortality response, with strongest associations for afternoon or maximum temperature at lag 0 (day of death) or afternoon and evening of lag 1 (day before death). In warmer, southern cities, stronger associations were found with morning temperatures, but overall the relationships were weaker. The strongest temperature–mortality relationships were associated with maximum temperature, although mean temperature results were comparable.

Conclusions: There were systematic and substantial differences in the association between temperature and mortality based on the time and type of temperature observation. Because the strongest hourly temperature–mortality relationships were not always found at times typically associated with daily maximum temperatures, temperature variables should be selected independently for each study location. In general, heat-mortality was more closely coupled to afternoon and maximum temperatures in most cities we examined, particularly those typically prone to heat-related mortality.

The role of ambiguity tolerance in career decision making was examined in a sample of college students (n = 275). Three hypotheses were proposed regarding the direct prediction of ambiguity tolerance on career indecision, the indirect prediction of ambiguity tolerance on career indecision through environmental and self explorations, and the moderation effect of ambiguity tolerance on the link of environmental and self explorations with career indecision. Results supported the significance of ambiguity tolerance with respect to career indecision, finding that it directly predicted general indecisiveness, dysfunctional beliefs, lack of information, and inconsistent information, and moderated the prediction of environmental exploration on inconsistent information. The implications of this study are discussed and suggestions for future research are provided.

Species turnover or β diversity is a conceptually attractive surrogate for conservation planning. However, there has been only 1 attempt to determine how well sites selected to maximize β diversity represent species, and that test was done at a scale too coarse (2,500 km² sites) to inform most conservation decisions. We used 8 plant datasets, 3 bird datasets, and 1 mammal dataset to evaluate whether sites selected to span β diversity will efficiently represent species at finer scale (sites sizes < 1 ha to 625 km²). We used ordinations to characterize dissimilarity in species assemblages (β diversity) among plots (inventory data) or among grid cells (atlas data). We then selected sites to maximize β diversity and used the Species Accumulation Index, SAI, to evaluate how efficiently the surrogate (selecting sites for maximum β diversity) represented species in the same taxon. Across all 12 datasets, sites selected for maximum β diversity represented species with a median efficiency of 24% (i.e., the surrogate was 24% more effective than random selection of sites), and an interquartile range of 4% to 41% efficiency. β diversity was a better surrogate for bird datasets than for plant datasets, and for atlas datasets with 10-km to 14-km grid cells than for atlas datasets with 25-km grid cells. We conclude that β diversity is more than a mere descriptor of how species are distributed on the landscape; in particular β diversity might be useful to maximize the complementarity of a set of sites. Because we tested only within-taxon surrogacy, our results do not prove that β diversity is useful for conservation planning. But our results do justify further investigation to identify the circumstances in which β diversity performs well, and to evaluate it as a cross-taxon surrogate.

A major challenge for biogeographers and conservation planners is to identify where to best locate or distribute high-priority areas for conservation and to explore whether these areas are well represented by conservation actions such as protected areas (PAs). We aimed to identify high-priority areas for conservation, expressed as hotpots of rarity-weighted richness (HRR)–sites that efficiently represent species–for birds across EU countries, and to explore whether HRR are well represented by the Natura 2000 network. Natura 2000 is an evolving network of PAs that seeks to conserve biodiversity through the persistence of the most patrimonial species and habitats across Europe. This network includes Sites of Community Importance (SCI) and Special Areas of Conservation (SAC), where the latter regulated the designation of Special Protected Areas (SPA). Distribution maps for 416 bird species and complementarity-based approaches were used to map geographical patterns of rarity-weighted richness (RWR) and HRR for birds. We used species accumulation index to evaluate whether RWR was efficient surrogates to identify HRRs for birds. The results of our analysis support the proposition that prioritizing sites in order of RWR is a reliable way to identify sites that efficiently represent birds. HRRs were concentrated in the Mediterranean Basin and alpine and boreal biogeographical regions of northern Europe. The cells with high RWR values did not correspond to cells where Natura 2000 was present. We suggest that patterns of RWR could become a focus for conservation biogeography. Our analysis demonstrates that identifying HRR is a robust approach for prioritizing management actions, and reveals the need for more conservation actions, especially on HRR.

Background: Most excess deaths that occur during extreme hot weather events do not have natural heat recorded as an underlying or contributing cause. This study aims to identify the specific individuals who died because of hot weather using only secondary data. A novel approach was developed in which the expected number of deaths was repeatedly sampled from all deaths that occurred during a hot weather event, and compared with deaths during a control period. The deaths were compared with respect to five factors known to be associated with hot weather mortality. Individuals were ranked by their presence in significant models over 100 trials of 10,000 repetitions. Those with the highest rankings were identified as probable excess deaths. Sensitivity analyses were performed on a range of model combinations. These methods were applied to a 2009 hot weather event in greater Vancouver, Canada.

Results: The excess deaths identified were sensitive to differences in model combinations, particularly between univariate and multivariate approaches. One multivariate and one univariate combination were chosen as the best models for further analyses. The individuals identified by multiple combinations suggest that marginalized populations in greater Vancouver are at higher risk of death during hot weather.

Conclusions: This study proposes novel methods for classifying specific deaths as expected or excess during a hot weather event. Further work is needed to evaluate performance of the methods in simulation studies and against clinically identified cases. If confirmed, these methods could be applied to a wide range of populations and events of interest.

One argument used by detractors of human embryonic stem cell research (hESCR) invokes Kant's formula of humanity, which proscribes treating persons solely as a means to an end, rather than as ends in themselves. According to Fuat S. Oduncu, for example, adhering to this imperative entails that human embryos should not be disaggregated to obtain pluripotent stem cells for hESCR. Given that human embryos are Kantian persons from the time of their conception, killing them to obtain their cells for research fails to treat them as ends in themselves.

This argument assumes two points that are rather contentious given a Kantian framework. First, the argument assumes that when Kant maintains that humanity must be treated as an end in itself, he means to argue that all members of the species Homo sapiens must be treated as ends in themselves; that is, that Kant regards personhood as co-extensive with belonging to the species Homo sapiens. Second, the argument assumes that the event of conception is causally responsible for the genesis of a Kantian person and that, therefore, an embryo is a Kantian person from the time of its conception.

In this paper, I will present challenges against these two assumptions by engaging in an exegetical study of some of Kant's works. First, I will illustrate that Kant did not use the term "humanity" to denote a biological species, but rather the capacity to set ends according to reason. Second, I will illustrate that it is difficult given a Kantian framework to denote conception (indeed any biological event) as causally responsible for the creation of a person. Kant ascribed to a dualistic view of human agency, and personhood, according to him, was derived from the supersensible capacity for reason. To argue that a Kantian person is generated due to the event of conception ignores Kant's insistence in various aspects of his work that it is not possible to understand the generation of a person qua a physical operation. Finally, I will end the paper by drawing from Allen Wood's work in Kantian philosophy in order to generate an argument in favor of hESCR.

The per-capita growth rate of a species is influenced by density-independent, positive and negative density-dependent factors. These factors can lead to nonlinearity with a consequence that species may process multiple nontrivial equilibria in its single state (e.g., Allee effects). This makes the study of permanence of discrete-time multi-species population models very challenging due to the complex boundary dynamics. In this paper, we explore the permanence of a general discrete-time two-species-interaction model with nonlinear per-capita growth rates for the first time. We find a simple sufficient condition for guaranteeing the permanence of the system by applying and extending the ecological concept of the relative nonlinearity to estimate systems' external Lyapunov exponents. Our method allows us to fully characterize the effects of nonlinearities in the per-capita growth functions and implies that the fluctuated populations may devastate the permanence of systems and lead to multiple attractors. These results are illustrated with specific two species competition and predator-prey models with generic nonlinear per-capita growth functions. Finally, we discuss the potential biological implications of our results.

We calculate the electron self-energy in a magnetized QED plasma to the leading perturbative order in the coupling constant and to the linear order in an external magnetic field. We find that the chiral asymmetry of the normal ground state of the system is characterized by two new Dirac structures. One of them is the familiar chiral shift previously discussed in the Nambu-Jona-Lasinio model. The other structure is new. It formally looks like that of the chiral chemical potential but is an odd function of the longitudinal component of the momentum, directed along the magnetic field. The origin of this new parity-even chiral structure is directly connected with the long-range character of the QED interaction. The form of the Fermi surface in the weak magnetic field is determined.