Climate, climate change and the global diversity of human houses.

Globally, human house types are diverse, varying in shape, size, roof type, building materials, arrangement, decoration and many other features. Here we offer the first rigorous, global evaluation of the factors that influence the construction of traditional (vernacular) houses. We apply macroecological approaches to analyse data describing house features from 1900 to 1950 across 1000 societies. Geographic, social and linguistic descriptors for each society were used to test the extent to which key architectural features may be explained by the biophysical environment, social traits, house features of neighbouring societies or cultural history. We find strong evidence that some aspects of the climate shape house architecture, including floor height, wall material and roof shape. Other features, particularly ground plan, appear to also be influenced by social attributes of societies, such as whether a society is nomadic, polygynous or politically complex. Additional variation in all house features was predicted both by the practices of neighouring societies and by a society's language family. Collectively, the findings from our analyses suggest those conditions under which traditional houses offer solutions to architects seeking to reimagine houses in light of warmer, wetter or more variable climates.

IV Diuresis in Alternative Treatment Settings for the Management of Heart Failure: Implications for Mortality, Hospitalizations and Cost.

BACKGROUND: Recent advances in heart failure (HF) care have sought to shift management from inpatient to outpatient and observation settings. We evaluated the association among HF treatment in the (1) inpatient; (2) observation; (3) emergency department (ED); and (4) outpatient settings with 30-day mortality, hospitalizations and cost. METHODS: Using 100% Medicare inpatient, outpatient and Part B files from 2011-2018, 1,534,708 unique patient encounters in which intravenous (IV) diuretics were received for a primary diagnosis of HF were identified. Encounters were sorted into mutually exclusive settings: (1) inpatient; (2) observation; (3) ED; or (4) outpatient IV diuretic clinic. The primary outcome was 30-day all-cause mortality. Secondary outcomes included 30-day hospitalization and total 30-day costs. Multivariable logistic and linear regression were used to examine the association between treatment location and the primary and secondary outcomes. RESULTS: Patients treated in observation and outpatient settings had lower 30-day mortality rates (observation OR 0.67, 95% CI 0.66-0.69; P < 0.001; outpatient OR 0.53, 95% CI 0.51-0.55; P < 0.001) compared to those treated in inpatient settings. Observation and outpatient treatment were also associated with decreased 30-day total cost compared to inpatient treatment. Observation relative cost -$5528.77, 95% CI -$5613.63 to -$5443.92; outpatient relative cost -$7005.95; 95% CI -$7103.94 to -$6907.96). Patients treated in the emergency department and discharged had increased mortality rates (OR 1.15, 95% CI 1.13-1.17; P < 0.001) and increased rates of hospitalization (OR 1.72, 95% CI 1.70-1.73; P < 0.001) compared to patients treated as inpatients. CONCLUSIONS: Medicare beneficiaries who received IV diuresis for acute HF in the outpatient and observation settings had lower mortality rates and decreased costs of care compared to patients treated as inpatients. Outpatient and observation management of acute decompensated HF, when available, is a safe and cost-effective strategy in certain populations of patients with HF.

A Focus on the Right Atrium: Right Atrial Diverticulum and Atrial Flutter.

We report a case of a 70-year-old woman who presented for a cavotricuspid isthmus atrial flutter ablation that was aborted prematurely. On subsequent imaging, she was discovered to have a right atrial diverticulum, which was present on prior imaging but not reported, likely due to unfamiliarity with the entity. (Level of Difficulty: Intermediate.).

Identifying socioeconomic and biophysical factors driving forest loss in protected areas.

Protected areas (PAs) are a commonly used strategy to confront forest conversion and biodiversity loss. Although determining drivers of forest loss is central to conservation success, understanding of them is limited by conventional modeling assumptions. We used random forest regression to evaluate potential drivers of deforestation in PAs in Mexico, while accounting for nonlinear relationships and higher order interactions underlying deforestation processes. Socioeconomic drivers (e.g., road density, human population density) and underlying biophysical conditions (e.g., precipitation, distance to water, elevation, slope) were stronger predictors of forest loss than PA characteristics, such as age, type, and management effectiveness. Within PA characteristics, variables reflecting collaborative and equitable management and PA size were the strongest predictors of forest loss, albeit with less explanatory power than socioeconomic and biophysical variables. In contrast to previously used methods, which typically have been based on the assumption of linear relationships, we found that the associations between most predictors and forest loss are nonlinear. Our results can inform decisions on the allocation of PA resources by strengthening management in PAs with the highest risk of deforestation and help preemptively protect key biodiversity areas that may be vulnerable to deforestation in the future.

Identificación de los factores biofísicos y socioeconómicos que impulsan la pérdida de bosques en las áreas protegidas Resumen Las áreas protegidas son una estrategia de uso común para hacer frente a la conversión forestal y la pérdida de biodiversidad. Aunque determinar los factores que impulsan la pérdida de bosques es fundamental para el éxito de la conservación, su comprensión se ve limitada por los supuestos de modelación convencionales. Utilizamos la regresión de bosques aleatorios para evaluar los posibles impulsores de la deforestación en las áreas protegidas de México, considerando las relaciones no lineales y las interacciones de orden superior que subyacen a los procesos de deforestación. Los impulsores socioeconómicos (densidad de carreteras, densidad de población humana) y las condiciones biofísicas subyacentes (precipitaciones, distancia al agua, elevación, pendiente) fueron predictores más fuertes de la pérdida de bosques que las características de las áreas protegidas, como la edad, el tipo y la efectividad de la gestión. Dentro de las características de las áreas protegidas, las variables que reflejan una gestión colaborativa y equitativa y el tamaño del área protegida fueron los predictores más potentes de la pérdida de bosques, aunque con menor poder explicativo que las variables socioeconómicas y biofísicas. A diferencia de los métodos utilizados anteriormente, que suelen basarse en el supuesto de relaciones lineales, observamos que las asociaciones entre la mayoría de los predictores y la pérdida de bosques no son lineales. Nuestros resultados pueden servir de base para la toma de decisiones sobre la asignación de los recursos para las áreas protegidas, reforzando la gestión en las zonas protegidas con mayor riesgo de deforestación y ayudando a proteger de forma preventiva zonas clave para la biodiversidad que pueden ser vulnerables a la deforestación en el futuro.

Cost-effectiveness of Dapagliflozin for the Treatment of Heart Failure With Reduced Ejection Fraction.

Importance: Heart failure with reduced ejection fraction produces substantial morbidity, mortality, and health care costs. Dapagliflozin is the first sodium-glucose cotransporter 2 inhibitor approved for the treatment of heart failure with reduced ejection fraction. Objective: To examine the cost-effectiveness of adding dapagliflozin to guideline-directed medical therapy for heart failure with reduced ejection fraction in patients with or without diabetes. Design, Setting, and Participants: This economic evaluation developed and used a Markov cohort model that compared dapagliflozin and guideline-directed medical therapy with guideline-directed medical therapy alone in a hypothetical cohort of US adults with similar clinical characteristics as participants of the Dapagliflozin in Patients with Heart Failure and Reduced Ejection Fraction (DAPA-HF) trial. Dapagliflozin was assumed to cost $4192 annually. Nonparametric modeling was used to estimate long-term survival. Deterministic and probabilistic sensitivity analyses examined the impact of parameter uncertainty. Data were analyzed between September 2019 and January 2021. Main Outcomes and Measures: Lifetime incremental cost-effectiveness ratio in 2020 US dollars per quality-adjusted life-year (QALY) gained. Results: The simulated cohort had a starting age of 66 years, and 41.8% had diabetes at baseline. Median (interquartile range) survival in the guideline-directed medical therapy arm was 6.8 (3.5-11.3) years. Dapagliflozin was projected to add 0.63 (95% uncertainty interval [UI], 0.25-1.15) QALYs at an incremental lifetime cost of $42 800 (95% UI, $37 100-$50 300), for an incremental cost-effectiveness ratio of $68 300 per QALY gained (95% UI, $54 600-$117 600 per QALY gained; cost-effective in 94% of probabilistic simulations at a threshold of $100 000 per QALY gained). Findings were similar in individuals with or without diabetes but were sensitive to drug cost. Conclusions and Relevance: In this study, adding dapagliflozin to guideline-directed medical therapy was projected to improve long-term clinical outcomes in patients with heart failure with reduced ejection fraction and be cost-effective at current US prices. Scalable strategies for improving uptake of dapagliflozin may improve long-term outcomes in patients with heart failure with reduced ejection fraction.

Prestige and content biases together shape the cultural transmission of narratives.

Cultural transmission biases such as prestige are thought to have been a primary driver in shaping the dynamics of human cultural evolution. However, few empirical studies have measured the importance of prestige relative to other effects, such as content biases present within the information being transmitted. Here, we report the findings of an experimental transmission study designed to compare the simultaneous effects of a model using a high- or low-prestige regional accent with the presence of narrative content containing social, survival, emotional, moral, rational, or counterintuitive information in the form of a creation story. Results from multimodel inference reveal that prestige is a significant factor in determining the salience and recall of information, but that several content biases, specifically social, survival, negative emotional, and biological counterintuitive information, are significantly more influential. Further, we find evidence that reliance on prestige cues may serve as a conditional learning strategy when no content cues are available. Our results demonstrate that content biases serve a vital and underappreciated role in cultural transmission and cultural evolution. Social media summary: Storyteller and tale are both key to memorability, but some content is more important than the storyteller's prestige.

Pathways to social inequality.

Social inequality is ubiquitous in contemporary human societies, and has deleterious social and ecological impacts. However, the factors that shape the emergence and maintenance of inequality remain widely debated. Here we conduct a global analysis of pathways to inequality by comparing 408 non-industrial societies in the anthropological record (described largely between 1860 and 1960) that vary in degree of inequality. We apply structural equation modelling to open-access environmental and ethnographic data and explore two alternative models varying in the links among factors proposed by prior literature, including environmental conditions, resource intensification, wealth transmission, population size and a well-documented form of inequality: social class hierarchies. We found support for a model in which the probability of social class hierarchies is associated directly with increases in population size, the propensity to use intensive agriculture and domesticated large mammals, unigeniture inheritance of real property and hereditary political succession. We suggest that influence of environmental variables on inequality is mediated by measures of resource intensification, which, in turn, may influence inequality directly or indirectly via effects on wealth transmission variables. Overall, we conclude that in our analysis a complex network of effects are associated with social class hierarchies.

Reframing the Wilderness Concept can Bolster Collaborative Conservation.

Indigenous territories represent ~45% of land categorized as wilderness in the Amazon, but account for <15% of all forest loss on this land. At a time when the Amazon faces unprecedented pressures, overcoming polarization and aligning the goals of wilderness defenders and Indigenous peoples is paramount, to avoid environmental degradation.

The Position-Reputation-Information (PRI) scale of individual prestige.

Prestige is a key concept across the social and behavioral sciences and has been implicated as an important driver in the processes governing human learning and behavior and the evolution of culture. However, existing scales of prestige fail to account for the full breadth of its potential determinants or focus only on collective social institutions rather than the individual-level perceptions that underpin everyday social interactions. Here, we use open, extensible methods to unite diverse theoretical ideas into a common measurement tool for individual prestige. Participants evaluated the perceived prestige of regional variations in accented speech using a pool of candidate scale items generated from free-listing tasks and a review of published scales. Through exploratory and confirmatory factor analyses, we find that our resulting 7-item scale, composed of dimensions we term position, reputation, and information ("PRI"), exhibits good model fit, scale validity, and scale reliability. The PRI scale of individual prestige contributes to the integration of existing lines of theory on the concept of prestige, and the scale's application in Western samples and its extensibility to other cultural contexts serves as a foundation for new theoretical and experimental trajectories across the social and behavioral sciences.

Cultural transmission and ecological opportunity jointly shaped global patterns of reliance on agriculture.

The evolution of agriculture improved food security and enabled significant increases in the size and complexity of human groups. Despite these positive effects, some societies never adopted these practices, became only partially reliant on them, or even reverted to foraging after temporarily adopting them. Given the critical importance of climate and biotic interactions for modern agriculture, it seems likely that ecological conditions could have played a major role in determining the degree to which different societies adopted farming. However, this seemingly simple proposition has been surprisingly difficult to prove and is currently controversial. Here, we investigate how recent agricultural practices relate both to contemporary ecological opportunities and the suitability of local environments for the first species domesticated by humans. Leveraging a globally distributed dataset on 1,291 traditional societies, we show that after accounting for the effects of cultural transmission and more current ecological opportunities, levels of reliance on farming continue to be predicted by the opportunities local ecologies provided to the first human domesticates even after centuries of cultural evolution. Based on the details of our models, we conclude that ecology probably helped shape the geography of agriculture by biasing both human movement and the human-assisted dispersal of domesticates.

Cardiovascular Risk Assessment in Renal and Liver Transplant Candidates: A Multidisciplinary Institutional Standardized Approach.

In the modern era, renal and liver transplant candidates present with a greater medical complexity driven in part by a higher prevalence of cardiovascular conditions, including coronary artery disease, valvular heart disease, and cardiomyopathies. In fact, cardiovascular disease is the most common cause of death after kidney transplantation worldwide. Similarly, an increase in the number of patients being listed with end-stage liver disease from nonalcoholic steatohepatitis and a rising model for end-stage liver disease scores at the time of liver transplant in the United States parallel an increasing cardiovascular disease risk profile for liver transplant candidates. A large degree of variation exists among clinical practice guidelines and transplant center practice patterns regarding patient selection for routine cardiac testing and the choice of testing modalities. Here, we review the clinical practice guidelines established at our center by a multidisciplinary group, including transplant nephrology, hepatology, and surgery, as well as general and interventional cardiology, with the goal of improving patient selection and reducing adverse cardiac events posttransplant.

Stable Ischemic Heart Disease.

Stable ischemic heart disease (SIHD) is a leading cause of death in the United States and many other countries. The defining pathobiology is an imbalance between the metabolic demands of the myocardium and its oxygen supply, which most often results from coronary artery atherosclerosis. The classic presenting symptom of SIHD is angina, but clinical presentation varies greatly among patients. Since the last In the Clinic on SIHD in 2014, several new drugs have been approved to reduce ischemic complications, such as myocardial infarction and congestive heart failure.

Impact of an Outpatient Cardiology-managed Urgent Access and Observation Unit on Hospital Admissions.

INTRODUCTION: Alternatives to the emergency department (ED) for expedient and high-value team-based cardiology care for patients with chest pain, volume overload, palpitations, and other urgent, but not life-threatening cardiac conditions are lacking. Here, we report on the development of the Cardiac Direct Access Unit (CDAc), an ambulatory cardiology unit with exam rooms, observation bays, and an advanced heart failure clinic. METHODS: Patients referred to the CDAc are seen same-day by an attending cardiologist in a space independent from the ED. We performed a retrospective review of 1146 consecutive patients referred to the CDAc in its first year of operation. Among patients who were referred for urgent same-day evaluation, 60.1% were discharged home without observation. RESULTS: Among the patients observed or directly discharged from CDAc, 2.4% were readmitted within 30 days for a related symptom. The highest rate of readmission (7.5%) was for heart failure, which compares favorably with guidelines for readmission benchmarks. CONCLUSION: Our first year of data suggests that a cardiology-directed observation unit may serve as a high-value alternative to the ED for appropriately selected patients.

Drivers of geographical patterns of North American language diversity.

Although many hypotheses have been proposed to explain why humans speak so many languages and why languages are unevenly distributed across the globe, the factors that shape geographical patterns of cultural and linguistic diversity remain poorly understood. Prior research has tended to focus on identifying universal predictors of language diversity, without accounting for how local factors and multiple predictors interact. Here, we use a unique combination of path analysis, mechanistic simulation modelling, and geographically weighted regression to investigate the broadly described, but poorly understood, spatial pattern of language diversity in North America. We show that the ecological drivers of language diversity are not universal or entirely direct. The strongest associations imply a role for previously developed hypothesized drivers such as population density, resource diversity, and carrying capacity with group size limits. The predictive power of this web of factors varies over space from regions where our model predicts approximately 86% of the variation in diversity, to areas where less than 40% is explained.

Understanding the drivers of sensitive behavior using Poisson regression from quantitative randomized response technique data.

Understanding sensitive behaviors-those that are socially unacceptable or non-compliant with rules or regulations-is essential for creating effective interventions. Sensitive behaviors are challenging to study, because participants are unlikely to disclose sensitive behaviors for fear of retribution or due to social undesirability. Methods for studying sensitive behavior include randomized response techniques, which provide anonymity to interviewees who answer sensitive questions. A variation on this approach, the quantitative randomized response technique (QRRT), allows researchers to estimate the frequency or quantity of sensitive behaviors. However, to date no studies have used QRRT to identify potential drivers of non-compliant behavior because regression methodology has not been developed for the nonnegative count data produced by QRRT. We develop a Poisson regression methodology for QRRT data, based on maximum likelihood estimation computed via the expectation-maximization (EM) algorithm. The methodology can be implemented with relatively minor modification of existing software for generalized linear models. We derive the Fisher information matrix in this setting and use it to obtain the asymptotic variance-covariance matrix of the regression parameter estimates. Simulation results demonstrate the quality of the asymptotic approximations. The method is illustrated with a case study examining potential drivers of non-compliance with hunting regulations in Sierra Leone. The new methodology allows assessment of the importance of potential drivers of different quantities of non-compliant behavior, using a likelihood-based, information-theoretic approach. Free, open-source software is provided to support QRRT regression.

Hindcasting global population densities reveals forces enabling the origin of agriculture.

The development and spread of agriculture changed fundamental characteristics of human societies1-3. However, the degree to which environmental and social conditions enabled the origins of agriculture remains contested4-6. We test three hypothesized links between the environment, population density and the origins of plant and animal domestication, a prerequisite for agriculture: (1) domestication arose as environmental conditions improved and population densities increased7 (surplus hypothesis); (2) populations needed domestication to overcome deteriorating environmental conditions (necessity hypothesis)8,9; (3) factors promoting domestication were distinct in each location10 (regional uniqueness hypothesis). We overcome previous data limitations with a statistical model, in which environmental, geographic and cultural variables capture 77% of the variation in population density among 220 foraging societies worldwide. We use this model to hindcast potential population densities across the globe from 21,000 to 4,000 years before present. Despite the timing of domestication varying by thousands of years, we show that improving environmental conditions favoured higher local population densities during periods when domestication arose in every known agricultural origin centre. Our results uncover a common, global factor that facilitated one of humanity's most significant innovations and demonstrate that modelling ancestral demographic changes can illuminate major events deep in human history.

The global geography of human subsistence.

How humans obtain food has dramatically reshaped ecosystems and altered both the trajectory of human history and the characteristics of human societies. Our species' subsistence varies widely, from predominantly foraging strategies, to plant-based agriculture and animal husbandry. The extent to which environmental, social and historical factors have driven such variation is currently unclear. Prior attempts to resolve long-standing debates on this topic have been hampered by an over-reliance on narrative arguments, small and geographically narrow samples, and by contradictory findings. Here we overcome these methodological limitations by applying multi-model inference tools developed in biogeography to a global dataset (818 societies). Although some have argued that unique conditions and events determine each society's particular subsistence strategy, we find strong support for a general global pattern in which a limited set of environmental, social and historical factors predicts an essential characteristic of all human groups: how we obtain our food.