Demographic models predict end-Pleistocene arrival and rapid expansion of pre-agropastoralist humans in Cyprus

The antiquity of human dispersal into Mediterranean islands and ensuing coastal adaptation have remained largely unexplored due to the prevailing assumption that the sea was a barrier to movement and that islands were hostile environments to early hunter-gatherers [J. F. Cherry, T. P. Leppard, J. Isl. Coast. Archaeol. 13, 191-205 (2018), 10.1080/15564894.2016.1276489]. Using the latest archaeological data, hindcasted climate projections, and age-structured demographic models, we demonstrate evidence for early arrival (14,257 to 13,182 calendar years ago) to Cyprus and predicted that large groups of people (~1,000 to 1,375) arrived in 2 to 3 main events occurring within <100 y to ensure low extinction risk. These results indicate that the postglacial settlement of Cyprus involved only a few large-scale, organized events requiring advanced watercraft technology. Our spatially debiased and Signor-Lipps-corrected estimates indicate rapid settlement of the island within <200 y, and expansion to a median of 4,000 to 5,000 people (0.36 to 0.46 km-2) in <11 human generations (<300 y). Our results do not support the hypothesis of inaccessible and inhospitable islands in the Mediterranean for pre-agropastoralists, agreeing with analogous conclusions for other parts of the world [M. I. Bird et al., Sci. Rep. 9, 8220 (2019), 10.1038/s41598-019-42946-9]. Our results also highlight the need to revisit these questions in the Mediterranean and test their validity with new technologies, field methods, and data. By applying stochastic models to the Mediterranean region, we can place Cyprus and large islands in general as attractive and favorable destinations for paleolithic peoples.

A Lack of Generalizability-Total Knee Demographics in the Active Duty Population

INTRODUCTION

Age and sex are known demographic risk factors for requiring revision surgery following primary total knee arthroplasty (TKA). Military service members are a unique population with barriers to long-term follow up after surgery. This study aims to compare demographic data between active duty military personnel and a nationwide sample to identify differences that may impact clinical and economic outcomes.

METHODS

A retrospective observational analysis was performed using the Military Health System Data Repository (MDR) and the National Surgical Quality Improvement Program (NSQIP). Databases were queried for patients undergoing primary TKA between January 1, 2015 and December 31, 2020. The MDR was queried for demographic data including age, sex, duty status, facility type, geographic region, history of prior military deployment, history of deployment-related health condition, branch of military service, and military rank. National Surgical Quality Improvement Program was queried for age and sex. Median age between populations was compared with the Mann-Whitney U test, and gender was compared with a chi-squared test.

RESULTS

During the study period, 2,094 primary TKA patients were identified from the MDR, and 357,865 TKA patients were identified from the NSQIP database. Military TKA patients were 79.4% male with a median age of 49.0, and NSQIP TKA patients were 38.9% were male, with a median age of 67. Military TKA patients were significantly more likely to be male (P < .001) and younger (P < .001).

CONCLUSION

Patients undergoing TKA in the military are younger and more likely to be male compared to national trends. Current evidence suggests these factors may place them at a significant revision risk in the future. The application of quality metrics based on nationwide demographics may not be applicable to military members within the Military Health System.

Demographic, clinical and laboratory characteristics for differential diagnosis of peripheral lymphadenopathy (LAP) and the etiologic distribution of LAP in adults; a multicenter, nested case-control study including 1401 patients from Turkey

Peripheral lymphadenopathy (LAP) is an important and common abnormal finding of the physical exam in general medical practice. We aimed to reveal the LAP etiology and demographic, clinical and laboratory variables that may be useful in the differential evaluation of LAP. This multicenter, nested case-control study including 1401 patients between 2014 and 2019 was conducted in 19 tertiary teaching and research hospitals from different regions in Turkey. The ratio of infectious, malign and autoimmune/inflammatory diseases was 31.3%, 5% and 0.3%, respectively. In 870 (62%) of patients had nonspecific etiology. Extrapulmonary tuberculosis (n: 235, 16.8%) was the most frequent cause of LAP. The ratio of infective etiology of LAP was significantly lower in patients older than 65 years-old compared to younger patients with the rate of 66.67% and 83.84%, respectively (p 0.016, OR 0.386, 95% Cl 0.186-0.803). The probability of malign etiology was higher both in patients who are older than 45 years-old (p < 0.001, OR 3.23, 95% Cl 1.99-5.26) and older than 65 years-old (p 0.002, OR 3.36, 95% Cl 1.69-6.68). Age, localization and duration of LAP, leukocytosis, anemia, thrombocytopenia, CRP and sedimentation rate were important parameters to differentiate infections. Size of lymph node and splenomegaly in addition to the parameters above were useful parameters for differentiating malign from benign etiology. Despite the improvements in diagnostic tools, reaching a definite differential diagnosis of lymphadenopathy is still challenging. Our results may help clinicians to decide in which cases they need an aggressive workup and set strategies on optimizing the diagnostic approach of adulthood lymphadenopathy.

Analysis of COVID-19 vaccine non-intent by essential vs non-essential worker, demographic, and socioeconomic status among 101,048 US adults

As of May 2021, over 286 million coronavirus 2019 (COVID-19) vaccine doses have been administered across the country. This data is promising, however there are still populations that, despite availability, are declining vaccination. We reviewed vaccine likelihood and receptiveness to recommendation from a doctor or nurse survey responses from 101,048 adults (≥18 years old) presenting to 442 primary care clinics in 8 states and the District of Columbia. Occupation was self-reported and demographic information extracted from the medical record, with 58.3% (n = 58,873) responding they were likely to receive the vaccine, 23.6% (n = 23,845) unlikely, and 18.1% (n = 18,330) uncertain. We found that essential workers were 18% less likely to receive the COVID-19 vaccination. Of those who indicated they were not already “very likely” to receive the vaccine, a recommendation from a nurse or doctor resulted in 16% of respondents becoming more likely to receive the vaccine, although certain occupations were less likely than others to be receptive to recommendations. To our knowledge, this is the first study to look at vaccine intent and receptiveness to recommendations from a doctor or nurse across specific essential worker occupations, and may help inform future early phase, vaccine rollouts and public health measure implementations.

Adverse Childhood Experiences and Subsequent Chronic Diseases Among Middle-aged or Older Adults in China and Associations With Demographic and Socioeconomic Characteristics

IMPORTANCE

Associations between adverse childhood experiences (ACEs) and chronic diseases among middle-aged or older Chinese individuals have not been well documented. In addition, whether demographic and socioeconomic characteristics modify any such associations has been underexplored.

OBJECTIVES

To examine associations between ACEs and subsequent chronic diseases and to assess whether age, sex, educational level, annual per capita household expenditure level, and childhood economic hardship modify these associations.

DESIGN, SETTING, AND PARTICIPANTS

This population-based cross-sectional study used data from the China Health and Retirement Longitudinal Study (CHARLS), a survey of residents aged 45 years or older in 28 provinces across China; specifically, the study used data from the CHARLS life history survey conducted from June 1 to December 31, 2014, and a CHARLS follow-up health survey conducted from July 1 to September 30, 2015. The study population included 11 972 respondents aged 45 years or older who had data on at least 1 of 14 specified chronic diseases and information on all 12 of the ACE indicators included in this study. Data analysis was performed from December 1 to 30, 2020.

EXPOSURES

Any of 12 ACEs (physical abuse, emotional neglect, household substance abuse, household mental illness, domestic violence, incarcerated household member, parental separation or divorce, unsafe neighborhood, bullying, parental death, sibling death, and parental disability), measured by indicators on a questionnaire. The number of ACEs per participant was summed and categorized into 1 of 5 cumulative-score groups: 0, 1, 2, 3, and 4 or more.

MAIN OUTCOMES AND MEASURES

Hypertension, dyslipidemia, diabetes, heart disease, stroke, chronic lung disease, asthma, liver disease, cancer, digestive disease, kidney disease, arthritis, psychiatric disease, and memory-related disease were defined by self-reported physician diagnoses or in combination with health assessment and medication data. Multimorbidity was defined as the presence of 2 or more of these 14 chronic diseases. Logistic regression models were used to assess associations of the 12 ACEs with the 14 chronic diseases and with multimorbidity. Modification of the associations by demographic and socioeconomic characteristics was assessed by stratified analyses and tests for interaction.

RESULTS

Of the 11 972 individuals included (mean [SD] age, 59.85 [9.56] years; 6181 [51.6%] were females), 80.9% had been exposed to at least 1 ACE and 18.0% reported exposure to 4 or more ACEs. Compared with those without ACE exposure, participants who experienced 4 or more ACEs had increased risks of dyslipidemia, chronic lung disease, asthma, liver disease, digestive disease, kidney disease, arthritis, psychiatric disease, memory-related disease, and multimorbidity. The estimated odds ratios (ORs) ranged from 1.27 (95% CI, 1.02-1.59) for dyslipidemia to 2.59 (95% CI, 2.16-3.11) for digestive disease. A dose-response association was also observed between the number of ACEs and the risk of most of the chronic diseases (excluding hypertension, diabetes, and cancer) (eg, chronic lung disease for ≥4 ACEs vs none: OR, 2.01; 95% CI, 1.59-2.55; P < .001 for trend) and of multimorbidity (for individuals among the overall study population with ≥4 ACEs vs none: OR, 2.03; 95% CI, 1.70-2.41; P < .001 for trend). The demographic or socioeconomic characteristics of age, sex, educational level, annual per capita household expenditure level, or childhood economic hardship were not shown to significantly modify the associations between ACEs and multimorbidity.

CONCLUSIONS AND RELEVANCE

In this population-based, cross-sectional study of adults in China, exposure to ACEs was associated with higher risks of chronic diseases regardless of demographic and socioeconomic characteristics during childhood or adulthood. These findings suggest a need to prevent ACEs and a need for a universal life-course public health strategy to reduce potential adverse health outcomes later in life among individuals who experience them.

Demographic, clinical characteristics and treatment outcomes of immune-complex membranoproliferative glomerulonephritis and C3 glomerulonephritis in Japan: A retrospective analysis of data from the Japan Renal Biopsy Registry

The reclassification of membranoproliferative glomerulonephritis (MPGN) into immune-complex MPGN (IC-MPGN) and C3 glomerulopathy (C3G) based on immunofluorescence findings in kidney biopsies has provided insights into these two distinct diseases. C3G is further classified into dense deposit disease and C3 glomerulonephritis (C3GN) based on electron micrographic findings. Although these diseases have poor outcomes, limited Japanese literature confined to small, single-center cohorts exist on these diseases. We retrospectively analyzed 81 patients with MPGN type I and III from 15 hospitals in the Japan Renal Biopsy Registry to compare demographic, clinical characteristics and treatment outcomes of patients with IC-MPGN to those with C3GN. Of the 81 patients reviewed by immunofluorescence findings in kidney biopsies, 67 patients had IC-MPGN and 14 patients had C3GN. Age at diagnosis and systolic and diastolic pressure were higher and proteinuria and impaired renal function were significantly more prevalent in patients with IC-MPGN than those with C3GN. About 80% of the patients in both groups were treated with immunosuppressive therapy. At last follow-up (median 4.8 years), complete remission rate of proteinuria was significantly higher in patients with C3GN (64.3%) than in those with IC-MPGN (29.9%; P = 0.015). The renal survival rate was lower in patients with IC-MPGN when compared to C3GN (73.1% vs. 100%; log-rank, P = 0.031). Systolic blood pressure and renal function at baseline were independent predictors of progression to end-stage kidney disease. The overall prognosis of patients with C3GN is more favorable than for patients with IC-MPGN.

Genetic analyses reveal demographic decline and population differentiation in an endangered social carnivore, Asiatic wild dog

Deforestation and agricultural intensification have resulted in an alarming change in the global land cover over the past 300 years, posing a threat to species conservation. Dhole is a monophyletic, social canid and, being an endangered and highly forest-dependent species, is more prone to the loss of favorable habitat in the Anthropocene. We determined the genetic differentiation and demographic history of dhole across the tiger reserves of Maharashtra using the microsatellite data of 305 individuals. Simulation-based analyses revealed a 77-85% decline in the major dhole sub-populations. Protected areas have provided refuge to the historically declining dhole population resulting in clustering with strong genetic structure in the remnant dhole population. The historical population decline coincides with the extreme events in the landscape over the past 300 years. The study highlights the pattern of genetic differentiation and diversity of a highly forest-dependent species which can be associated with the loss of forest cover outside tiger reserves. It also warrants attention to develop conservation plans for the remnant surviving population of dholes in India.

Prediction of individual COVID-19 diagnosis using baseline demographics and lab data

The global surge in COVID-19 cases underscores the need for fast, scalable, and reliable testing. Current COVID-19 diagnostic tests are limited by turnaround time, limited availability, or occasional false findings. Here, we developed a machine learning-based framework for predicting individual COVID-19 positive diagnosis relying only on readily-available baseline data, including patient demographics, comorbidities, and common lab values. Leveraging a cohort of 31,739 adults within an academic health system, we trained and tested multiple types of machine learning models, achieving an area under the curve of 0.75. Feature importance analyses highlighted serum calcium levels, temperature, age, lymphocyte count, smoking, hemoglobin levels, aspartate aminotransferase levels, and oxygen saturation as key predictors. Additionally, we developed a single decision tree model that provided an operable method for stratifying sub-populations. Overall, this study provides a proof-of-concept that COVID-19 diagnosis prediction models can be developed using only baseline data. The resulting prediction can complement existing tests to enhance screening and pandemic containment workflows.

Spatial pattern of the ecological environment in Yunnan Province

Ecological science focuses on the structure and function of the natural environment. However, the study of ecological environments primarily focuses on single-element research and lacks a comprehensive perspective. To examine ecological environmental trends on different scales, the present paper selected Yunnan Province as the study area. Chemical oxygen demand, rocky desertification, forest coverage, natural disaster data and spatial analysis methods were used to obtain the ecological environmental characteristics of each county and construct a comprehensive evaluation method of the ecological environment. The present paper revealed that the environmental capacity in Yunnan Province was at a moderate level, the ecological environment fragility was remarkable, the significance of the ecological environment was very high, natural disasters occurred frequently, and spatial differentiation between ecological environments was obvious. The province may be divided into three functional areas: the comprehensive-balanced area, the efficiency-dominated area and the environment-dominated area. Central Yunnan was a key development zone and the main area for the manufacturing and service industries, which were built as a modern industrial system in Yunnan Province. The ecological environment in northwestern Yunnan and southern Yunnan is of high significance, and this region was an ecological environment protection area that was important area for the construction of the modern agricultural system in Yunnan Province. To achieve sustainable development of the ecological environment, the spatial characteristics of the ecological environment must be determined at the county scale.

A population estimation study reveals a staggeringly high number of cattle on the streets of urban Raipur in India

Cattle are cosmopolitan in distribution. They are economically and ecologically significant. The cattle menace on the urban streets of developing and underdeveloped countries is challenging. The number of road accidents is increasing rapidly over time, in the urban areas of most of the developing countries, like India. In the present study, we estimated the population of cattle wandering on the streets/roads/highways of Raipur city of India using the direct headcount method and advanced Photographic Capture-Recapture Method (PCRCM). We compared these two methods of population estimation to check their suitability and adequacy. We superimposed 163 grids (1.0 x 1.0 km each) on the map of Raipur city using Quantum Geographic Information System (QGIS) software. We randomly selected 20 grids for the estimation of the street cattle population. We used both line transect and block count sampling techniques under the direct headcount method. The estimates of visibly roaming cattle on the Raipur city streets were 11808.45 and 11198.30 using the former and the latter sampling techniques, respectively. Further, advanced PCRCM indicated an estimated 35149.61 and 34623.20 cattle using the line transect and block counting sampling techniques, respectively. We observed a female-biased sex ratio in both mature and immature cattle. The frequency of mature cattle was significantly higher than that of naive cattle, followed by the calf. Further, we noticed the frequency of cattle in a grid in the following order: cow > bull > heifer > immature male > female calf > male calf. We concluded that the estimated population of street cattle in Raipur city is about 35 thousand. The results of both the techniques, i.e., direct headcount method and PCRCM, are consistent for population estimation. The direct headcount method yields the number of cattle visibly roaming on the street at a particular time. In contrast, advanced PCRCM gives the total population of street cattle in the city. Active surveillance of the urban cattle population might be of critical importance for municipal and city planners. A better understanding of the urban cattle population might help mitigate the cattle menace on the street, eventually preventing cattle-human conflict and minimizing road accidents. The techniques adopted in this study will also help estimate the population of free-ranging dogs and other wildlife animals in any target location.

Past and future potential range changes in one of the last large vertebrates of the Australian continent, the emu Dromaius novaehollandiae

In Australia, significant shifts in species distribution have occurred with the loss of megafauna, changes in indigenous Australian fire regime and land-use changes with European settlement. The emu, one of the last megafaunal species in Australia, has likely undergone substantial distribution changes, particularly near the east coast of Australia where urbanisation is extensive and some populations have declined. We modelled emu distribution across the continental mainland and across the Great Dividing Range region (GDR) of eastern Australia, under historical, present and future climates. We predicted shifts in emu distribution using ensemble modelling, hindcasting and forecasting distribution from current emu occurrence data. Emus have expanded their range northward into central Australia over the 6000 years modelled here. Areas west of the GDR have become more suitable since the mid-Holocene, which was unsuitable then due to high precipitation seasonality. However, the east coast of Australia has become climatically sub-optimal and will remain so for at least 50 years. The north east of NSW encompasses the range of the only listed endangered population, which now occurs at the margins of optimal climatic conditions for emus. Being at the fringe of suitable climatic conditions may put this population at higher risk of further decline from non-climatic anthropogenic disturbances e.g. depredation by introduced foxes and pigs. The limited scientific knowledge about wild emu ecology and biology currently available limits our ability to quantify these risks.

Demographic and socio-economic factors, and healthcare resource indicators associated with the rapid spread of COVID-19 in Northern Italy: An ecological study

BACKGROUND

COVID-19 rapidly escalated into a pandemic, threatening 213 countries, areas, and territories the world over. We aimed to identify potential province-level socioeconomic determinants of the virus's dissemination, and explain between-province differences in the speed of its spread, based on data from 36 provinces of Northern Italy.

METHODS

This is an ecological study. We included all confirmed cases of SARS-CoV-2 reported between February 24th and March 30th, 2020. For each province, we calculated the trend of contagion as the relative increase in the number of individuals infected between two time endpoints, assuming an exponential growth. Pearson's test was used to correlate the trend of contagion with a set of healthcare-associated, economic, and demographic parameters by province. The virus's spread was input as a dependent variable in a stepwise OLS regression model to test the association between rate of spread and province-level indicators.

RESULTS

Multivariate analysis showed that the spread of COVID-19 was correlated negatively with aging index (p-value = 0.003), and positively with public transportation per capita (p-value = 0.012), the % of private long-term care hospital beds and, to a lesser extent (p-value = 0.070), the % of private acute care hospital beds (p-value = 0.006).

CONCLUSION

Demographic and socioeconomic factors, and healthcare organization variables were found associated with a significant difference in the rate of COVID-19 spread in 36 provinces of Northern Italy. An aging population seemed to naturally contain social contacts. The availability of healthcare resources and their coordination could play an important part in spreading infection.

Genetic structure of coast redwood (Sequoia sempervirens [D. Don] Endl.) populations in and outside of the natural distribution range based on nuclear and chloroplast microsatellite markers

Coast redwood (Sequoia sempervirens) naturally growing in southern Oregon and northern California is one of the few conifer tree species that are polyploid. Despite its unique ecological and economic importance, its population genetic structure is still insufficiently studied. To obtain additional data on its population genetic structure we genotyped 317 samples collected from populations in California (data set C) and 144 trees growing in a provenance trial in France (data set F) using 12 nuclear (five random nuclear genomic nSSRs and seven expressed sequence tag EST-SSRs) and six chloroplast (cpSSRs) microsatellite or simple sequence repeat (SSR) markers, respectively. These data sets were also used as reference to infer the origin of 147 coast redwood trees growing in Germany (data set G). Coast redwood was introduced to Europe, including Germany as an ornamental species, decades ago. Due to its fast growth and high timber quality, it could be considered as a potential commercial timber species, especially in perspective to climate warming that makes more regions in Germany suitable for its growing. The well performing trees in colder Germany could be potential frost resistant genotypes, but their genetic properties and origin are mostly unknown. Within the natural range in southern Oregon and northern California, only two relatively weak clusters were identified, one northern and one southern, separated by the San Francisco Bay. High genetic diversity, but low differentiation was found based on the 12 nuclear SSR markers for all three data sets F, C and G. We found that investigated 147 German trees represented only 37 different genotypes. They showed genetic diversity at the level less than diversity observed within the natural range in the northern or southern cluster, but more similar to the diversity observed in the southern cluster. It was difficult to assign German trees to the original single native populations using the six cpSSR markers, but rather to either the northern or southern cluster. The high number of haplotypes found in the data sets based on six cpSSR markers and low genetic differentiation based on 12 nuclear SSRs found in this study helps us study and better understand population genetic structure of this complex polyploid tree and supports the selection of potential genotypes for German forestry.

Finite population distribution function estimation with dual use of auxiliary information under simple and stratified random sampling

The main purpose of this paper is to propose two new estimators for estimating the finite population distribution function under simple and stratified random sampling schemes using supplementary information on the distribution function, mean and ranks of the auxiliary variable. The mathematical expressions for the bias and mean squared error of the proposed estimators are derived under the first order of approximation. The theoretical and empirical studies showed that the proposed estimators uniformly perform better than the existing estimators in terms of the percentage relative efficiency.

Wildlife resistance and protection in a changing New England landscape

Rapid changes in climate and land use threaten the persistence of wildlife species. Understanding where species are likely to occur now and in the future can help identify areas that are resistant to change over time and guide conservation planning. We estimated changes in species distribution patterns and spatial resistance in five future scenarios for the New England region of the northeastern United States. We present scenario-specific distribution change maps for nine harvested wildlife species, identifying regions of increasing, decreasing, or stable habitat suitability within each scenario. Next, we isolated areas where species occurrence probability is high (p > 0.7) and resistant to change across all future scenarios. Resistance was also evaluated relative to current land protection to identify patterns in and out of Protected Areas (PAs). Generally, species distributions declined in area over the 50-year assessment period (2010-2060), with the greatest average declines occurring for moose (-40.9%) and wild turkey (-22.1%). Species resistance varied considerably across the region, with coyote demonstrating the highest average regional resistance (91.81% of the region) and moose demonstrating the lowest (0.76% of the region). At the state level, average focal species resistance was highest in Maine (the largest state) and lowest in Massachusetts. Many of the focal species showed high overlap in resistance and land protection. Coyote, white-tailed deer, and black bear had the highest probability of resistance, given protection, while moose and wild turkey had the highest probability of protection, given resistance. Overall, relatively small portions of New England-ranging between 0.25% and 21.12%-were both protected and resistant for the focal species. Our results provide estimates of resistance that can inform conservation planning for commonly harvested species that are important ecologically, economically, and culturally to the region. Expanding protected area coverage to include resistant areas may provide longer term benefits to these species.

Movement patterns and habitat use of tiger sharks (Galeocerdo cuvier) across ontogeny in the Gulf of Mexico

The tiger shark (Galeocerdo cuvier) is globally distributed with established coastal and open-ocean movement patterns in many portions of its range. While all life stages of tiger sharks are known to occur in the Gulf of Mexico (GoM), variability in habitat use and movement patterns over ontogeny have never been quantified in this large marine ecosystem. To address this data gap we fitted 56 tiger sharks with Smart Position and Temperature transmitting tags between 2010 and 2018 and examined seasonal and spatial distribution patterns across the GoM. Additionally, we analyzed overlap of core habitats (i.e., 50% kernel density estimates) among individuals relative to large benthic features (oil and gas platforms, natural banks, bathymetric breaks). Our analyses revealed significant ontogenetic and seasonal differences in distribution patterns as well as across-shelf (i.e., regional) and sex-linked variability in movement rates. Presumably sub-adult and adult sharks achieved significantly higher movement rates and used off-shelf deeper habitats at greater proportions than juvenile sharks, particularly during the fall and winter seasons. Further, female maximum rate of movement was higher than males when accounting for size. Additionally, we found evidence of core regions encompassing the National Oceanographic and Atmospheric Administration designated Habitat Areas of Particular Concern (i.e., shelf-edge banks) during cooler months, particularly by females, as well as 2,504 oil and gas platforms. These data provide a baseline for future assessments of environmental impacts, such as climate variability or oil spills, on tiger shark movements and distribution in the region. Future research may benefit from combining alternative tracking tools, such as acoustic telemetry and genetic approaches, which can facilitate long-term assessment of the species’ movement dynamics and better elucidate the ecological significance of the core habitats identified here.

Spatial heterogeneity and socioeconomic determinants of opioid prescribing in England between 2015 and 2018

BACKGROUND

Opioid overdoses have had a serious impact on the public health systems and socioeconomic welfare of several countries. Within this broader context, we focus our study on primary care opioid prescribing in England from 2015 to 2018, particularly the patterns of spatial variations at the community level and the socioeconomic and environmental factors that drive consumption.

METHODS

Leveraging open data sources, we combine prescription records with aggregated data on patient provenance and build highly granular maps of Oral Morphine Equivalent (OME) prescribing rates for Lower Layer Super Output Areas (LSOA). We quantify the strength of spatial associations by means of the Empirical Bayes Index (EBI) that accounts for geographical variations in population density. We explore the interplay between socioeconomic and environmental determinants and prescribing rates by implementing a multivariate logistic regression model across different temporal snapshots and spatial scales.

RESULTS

We observe, across time and geographical resolutions, a significant spatial association with the presence of localized hot and cold spots that group neighboring areas with homogeneous prescribing rates (e.g., EBI = 0.727 at LSOA level for 2018). Accounting for spatial dependency effects, we find that LSOA with both higher employment deprivation (OR = 62.6, CI 52.8-74.3) and a higher percentage of ethnically white (OR = 30.1, CI 25.4-35.7) inhabitants correspond to higher prescribing rates. Looking at educational attainment, we find LSOA with the prevalent degree of education being apprenticeship (OR = 2.33, CI 1.96-2.76) a risk factor and those with level 4+ (OR = 0.41, CI 0.35-0.48) a protective factor. Focusing on environmental determinants, housing (OR = 0.18, CI 0.15-0.21) and outdoor environment deprivation (OR = 0.62, CI 0.53-0.72) indices capture the bi-modal behavior observed in the literature concerning rural/urban areas. The results are consistent across time and spatial aggregations.

CONCLUSIONS

Failing to account for local variations in opioid prescribing rates smooths out spatial dependency effects that result in underestimating/overestimating the impact on public health policies at the community level. Our study suggests a novel approach to inform more targeted interventions toward the most vulnerable population strata.

Mapping the status of the North American beaver invasion in the Tierra del Fuego archipelago

Quantifying the presence and environmental impact of invasive species is the starting point for research on management and nature conservation. North American beavers (Castor canadensis) were introduced to Argentina from Canada in 1946, and the species has been identified as a major agent of environmental change in the Tierra del Fuego archipelago in the Anthropocene. We studied the invasion status (distribution and density) of beavers through analyses of the dam densities in the Tierra del Fuego landscapes. We identified beaver dams with a GIS using visual interpretation of high-resolution aerial imagery from Microsoft Bing, Google Earth and HERE and related them to natural environmental gradients. These factors comprised geographic (vegetation zones and distance to streams), climatic (temperature, precipitation, evapotranspiration and net primary productivity) and topographic (elevation and slope) data. The datasets (dams and factors) were combined, and the data from the different zonation classes were subsequently compared using ANOVAs and Tukey's mean comparison tests. Deviations from the mean density (x mean density-x total mean density) were calculated to visualize the deviations for the studied factors. The datasets were also evaluated using principal component analyses (PCA). Our results showed a total of 206,203 beaver dams (100,951 in Argentina and 105,252 in Chile) in the study area (73,000 km2). The main island of Tierra del Fuego presented a greater degree of invasion (73.6% of the total study area) than the rest of the archipelago, especially in areas covered by mixed-evergreen and deciduous forests. The studied geographic, climatic and topographic factors showed positive trends (higher beaver preference) with beaver spread, which were all significant (p <0.05) when compared across the landscape. Although beavers are flexible in their habitat use, our empirical records showed that they had marked preferences and were positively influenced by the most productive forests. Here, we describe a scientific panorama that identified the drivers of species invasion based on satellite data and the available ecological datasets. The identification of such drivers could be useful for developing new tools for management and/or control strategies of the beavers in the Tierra del Fuego archipelago.

Vulnerability and resistance in the spatial heterogeneity of soil microbial communities under resource additions

Spatial heterogeneity in composition and function enables ecosystems to supply diverse services. For soil microbes and the ecosystem functions they catalyze, whether such heterogeneity can be maintained in the face of altered resource inputs is uncertain. In a 50-ha northern California grassland with a mosaic of plant communities generated by different soil types, we tested how spatial variability in microbial composition and function changed in response to nutrient and water addition. Fungal composition lost some of its spatial variability in response to nutrient addition, driven by decreases in mutualistic fungi and increases in antagonistic fungi that were strongest on the least fertile soils, where mutualists were initially most frequent and antagonists initially least frequent. Bacterial and archaeal community composition showed little change in their spatial variability with resource addition. Microbial functions related to nitrogen cycling showed increased spatial variability under nutrient, and sometimes water, additions, driven in part by accelerated nitrification on the initially more-fertile soils. Under anthropogenic changes such as eutrophication and altered rainfall, these findings illustrate the potential for significant changes in ecosystem-level spatial heterogeneity of microbial functions and communities.

Faces Divulge the Origins of Caribbean Prehistoric Inhabitants

The origins of the first peoples to colonize the Caribbean Islands have been the subject of intense debate for over 30 years. Competing hypotheses have identified five separate migrations from the mainland with a separate debate concerning the colonization of The Bahamas. Significant differences in the facial morphology of the pre-Columbian inhabitants of Hispaniola and Cuba led to the present study of Lucayan skulls from The Bahamas. The goal was to determine which group the native Lucayans more closely resembled to resolve this long-standing dispute. The results indicate that they are related to groups from Hispaniola and Jamaica and not to Cuban inhabitants. This study clarified the larger picture of Caribbean migrations and supports evidence for a Carib invasion of the Greater Antilles around AD 800.

Genome Resolved Biogeography of Mamiellales

Among marine phytoplankton, Mamiellales encompass several species from the genera Micromonas, Ostreococcus and Bathycoccus, which are important contributors to primary production. Previous studies based on single gene markers described their wide geographical distribution but led to discussion because of the uneven taxonomic resolution of the method. Here, we leverage genome sequences for six Mamiellales species, two from each genus Micromonas, Ostreococcus and Bathycoccus, to investigate their distribution across 133 stations sampled during the Tara Oceans expedition. Our study confirms the cosmopolitan distribution of Mamiellales and further suggests non-random distribution of species, with two triplets of co-occurring genomes associated with different temperatures: Ostreococcuslucimarinus, Bathycoccusprasinos and Micromonaspusilla were found in colder waters, whereas Ostreococcus spp. RCC809, Bathycoccus spp. TOSAG39-1 and Micromonascommoda were more abundant in warmer conditions. We also report the distribution of the two candidate mating-types of Ostreococcus for which the frequency of sexual reproduction was previously assumed to be very low. Indeed, both mating types were systematically detected together in agreement with either frequent sexual reproduction or the high prevalence of a diploid stage. Altogether, these analyses provide novel insights into Mamiellales' biogeography and raise novel testable hypotheses about their life cycle and ecology.

Biomarkers for demographic research: sperm counts and other male infertility biomarkers

Some male infertility biomarkers are etiologically linked to idiopathic infertility in men, the direct cause of which often cannot be determined with conventional sperm count parameters. Open questions remain regarding the universal and generic infertility definitions that cover and combine the clinical, epidemiological, and demographic perspectives. The main effort in the application of these infertility biomarkers are accounted by more or less strict discrimination criteria. For male infertility, beyond classical sperm count assessments, the DNA fragmentation index (DFI) is an adequate biomarker. DFI strongly correlates with pregnancy rates and even strict discrimination criteria for infertility outcomes. Other common biomarkers are reactive oxygen species (ROS) and antisperm antibodies (ASAs), which can explain some biomedical infertility disorders within major constraints. More frequently applied in demographic research, telomere length component analysis is based on identifying the genetic impact of cellular longevity. Sperm telomere length is becoming established as a potential biomarker in infertility research. The aim of this review is to provide an overview of the current status and limitations to the application of novel biomarkers, including TEX101, for infertility research. The review also discusses potential options for the use of biomarkers in population-based studies.Abbreviations: ASAs: antisperm antibodies; DFI: DNA fragmentation index; DNA: deoxyribonucleic acid; ECM1: extracellular matrix protein 1; FSH: follicle stimulating hormone; HS: hypospermatogenesis: IVF: in vitro fertilization; LDHC: L-lactata dehydrogenase C chain; MA: maturation arrest; microTESE: microdissection testicular sperm extraction; NOA: nonobstructive azoospermia; NP: nonprogressive; OA: obstructive azoospermia; pH: potential Hyrogenii (pH-value); PR: progressive; PTGDS: prostaglandin D synthese; ROS: reactive oxygen species; SA: semen analysis; SCO: sertoli cell only; SCSA: sperm chromatin structure assay (SCSA); TL: telomere length; TESE: testicular sperm extraction; TEX101: a glycoprotein that belongs to Ly6/urokinase type plasminogen activator receptor-like protein (uPAR)(LU) superfamily, to be a germ-cell-specific molecular sperm extraction; TUNEL: terminal deoxnucleotidyl dispersion tranferase dUTP nick-end labeling; WHO: World Health Organization.

Diversity and inclusion for the All of Us research program: A scoping review

The All of Us Research Program (All of Us) is a national effort to accelerate health research by exploring the relationship between lifestyle, environment, and genetics. It is set to become one of the largest research efforts in U.S. history, aiming to build a national resource of data from at least one million participants. All of Us aims to address the need for more diversity in research and set the stage for that diversity to be leveraged in precision medicine research to come. This paper describes how the program assessed demographic characteristics of participants who have enrolled in other U.S. biomedical research cohorts to better understand which groups are traditionally represented or underrepresented in biomedical research. We 1) reviewed the enrollment characteristics of national cohort studies like All of Us, and 2) surveyed the literature, focusing on key diversity categories essential to the program's enrollment aims. Based on these efforts, All of Us emphasizes enrollment of racial and ethnic minorities, and has formally designated the following additional groups as historically underrepresented: individuals-with inadequate access to medical care; under the age of 18 or over 65; with an annual household income at or below 200% of the federal poverty level; who have a cognitive or physical disability; have less than a high school education or equivalent; are intersex; identify as a sexual or gender minority; or live in rural or non-metropolitan areas. Research accounting for wider demographic variability is critical. Only by ensuring diversity and by addressing the very barriers that limit it, can we position All of Us to better understand and tackle health disparities.

Moderation of classic social psychological effects by demographics in the U.S. adult population: New opportunities for theoretical advancement

For decades, social psychologists have collected data primarily from college undergraduates and, recently, from haphazard samples of adults. Yet researchers have routinely presumed that thus observed treatment effects characterize "people" in general. Tests of seven highly cited social psychological phenomena (two involving opinion change resulting from social influence and five involving the use of heuristics in social judgments) using data collected from randomly sampled, representative groups of American adults documented generalizability of the six phenomena that have been replicated previously with undergraduate samples. The 1 phenomenon (a cross-over interaction revealing an ease of retrieval effect) that has not been replicated successfully previously in undergraduate samples was also not observed here. However, the observed effect sizes for the replicated phenomena were notably smaller on average than the meta-analytic effect sizes documented by past studies of college students. Furthermore, the phenomena were strongest among participants with the demographic characteristics of the college students who typically provided data for past published studies, even after correcting for publication bias in past studies using a new method, called the behaviorally-informed file-drawer adjustment. The six successful replications suggest that phenomena identified in traditional laboratory research also appear as expected in representative samples but more weakly, so observed effect sizes should be generalized with caution. The evidence of demographic moderators suggests interesting opportunities for future research to better understand the mechanisms of the effects and their limiting conditions. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

From public health and demographic research to decision making: An intervention study in Giza Governorate-Egypt

The purpose of the current study was to develop an empirical model that shows how various contextual data are analyzed, interpreted and presented as evidence-based information for decision making and action taking. A Pre-test-Posttest intervention study was conducted at the National Population Council (NPC)-Giza governorate (GG) where all data were collected from all governmental organizations on an annual basis at the district level (19 districts), which include 28 indicators. Composite indices and indicators (n = 9) had been ranked and presented as a matrix that assigned districts into three situations: Best (green zone), prospective (yellow zone) and critical (red zone).

INTERVENTION

Presentation of the "Districts' Enactment Matrix" (DEM) for the year 2014 in GG -Regional Council for Population (RCP) quarterly meetings, headed by the governor and attended by representatives of all ministries. The feedback and recommendation for action taking by participants were reported by the researchers. Evaluation of the intervention was done by comparing DEM 2014 and DEM 2016.

RESULTS

At the governorate level, short-term strategies were used to improve the situation. All the districts in red zone 2014 and two districts in the yellow zone had demonstrated positive changes in their 28 indicators.

CONCLUSION

The DEM model is a simple tool that facilitates communication between researchers and decision-makers that could be applied in different public health and population programs.

Baseline Psychosocial and Demographic Factors Associated with Study Attrition and 12-Month Weight Gain in the DIETFITS Trial

OBJECTIVE

The purpose of this study was to examine correlates of failure-trial attrition and weight gain-in a randomized clinical weight-loss trial.

METHODS

The Diet Intervention Examining The Factors Interacting with Treatment Success (DIETFITS) trial included 609 adults (18-50 years; BMI 28-40). Participants were randomized to a 12-month healthy low-fat or healthy low-carbohydrate diet for weight loss. At baseline, participants completed psychosocial, demographic, and anthropometric measures. Stepwise logistic regressions identified baseline factors associated with (1) study attrition and (2) among trial completers, weight gain at 12 months.

RESULTS

Having higher baseline food addiction and self-efficacy was linked to treatment failure. Being younger, not having a college education, having higher outcome expectations and quality of life, and having lower social functioning and self-control increased the odds of trial attrition. Identifying as other than non-Hispanic white; not being married or cohabitating; having higher cognitive restraint and self-control; and having lower amotivation, family encouragement, and physical limitations increased the odds of gaining weight by treatment's end.

CONCLUSIONS

Participants' baseline psychosocial and demographic factors may support or impede successful weight loss. Trialists should attend to these factors when designing treatments in order to promote participants' likelihood of completing the trial and achieving their weight-loss goals.

Demographic Characteristics of Participants in Rheumatoid Arthritis Randomized Clinical Trials: A Systematic Review

IMPORTANCE

Racial/ethnic minority groups, women, and elderly people experience a disproportionate burden of disease in rheumatoid arthritis (RA), making it particularly important to examine drug therapies in these populations. Despite a national health agenda to improve representation of diverse populations in randomized clinical trials (RCTs), there have been few large-scale analyses examining RCT demographic characteristics within rheumatology and none focusing on RA.

OBJECTIVE

To characterize the representation of racial/ethnic minority groups, women, and elderly people through a comprehensive systematic review of RA RCTs.

DATA SOURCES

A literature search of PubMed's MEDLINE database was conducted to identify RA RCTs in adults 19 years and older published in English between January 1, 2008, and January 1, 2018.

STUDY SELECTION

Randomized double-blind RCTs examining any systemic, disease-modifying therapy were included. Secondary analyses of previously published RCTs were excluded. Of 1195 identified records, 240 articles (20.1%) met final selection criteria. The analysis focused on RCTs with at least 1 US-based site.

DATA EXTRACTION AND SYNTHESIS

Data were extracted and synthesized according to the PRISMA guidelines for systematic reviews. Studies were screened for eligibility criteria. Demographic data on the age, sex, and race/ethnicity of RCT participants were extracted. Data analysis was conducted from October 25, 2018, to March 15, 2019.

MAIN OUTCOMES AND MEASURES

Representation of race/ethnicity and sex, defined as the proportion of total participants that belonged to each racial/ethnic group or sex. Trends in proportions over time were examined and compared with US demographic data.

RESULTS

A total of 240 RCTs with 77 071 participants were included. Of 126 RCTs with at least 1 US-based site (52.5%), the enrollment of minority racial/ethnic groups was significantly lower than their representation within the US Census population (16% vs 40%; P < .001), and the enrollment of men was significantly lower than the incidence of RA in men nationally (20.4% vs 28.6%; P < .001). There was no trend toward improved representation of racial/ethnic minority groups or men over time.

CONCLUSIONS AND RELEVANCE

Given the disproportionate burden of RA among racial/ethnic minority groups, it is imperative that policy makers better incentivize the inclusion of racial/ethnic minority groups in RA RCTs.

Development and Implementation of a Hands-on Surgical Pipeline Program for Low-Income High School Students

This qualitative study describes the development and implementation of a hands-on surgical pipeline program for low-income high school students.

Associations of Socio-demographic, Family, and Neighborhood Factors with Physical Activity-Related Parenting Practices Among Hong Kong Preschoolers' Parents

Objectives Regular engagement in physical activity (PA) has numerous health benefits in young children. Young children's parents can influence their children's PA behavior through different PA-related parenting practices. This cross-sectional study examined the independent contributions of socio-demographic, family/home and parent-perceived neighborhood environmental characteristics explaining PA-related parenting practices encouraging or discouraging PA among Hong Kong preschool-aged children (3-5 years-old). Methods Hong Kong Chinese preschoolers' parents were recruited from pre-selected kindergartens and Maternal and Child Health Centers located in areas stratified by residential density and socio-economic status. They self-completed socio-demographic, family/home and perceived neighborhood characteristics and PA-related parenting practices questionnaires. Generalized linear models were used to examine associations of socio-demographic, family/home and neighborhood variables with PA-related parenting practices. Results Socio-demographic and family/home characteristics were significantly correlated with parenting practices encouraging and discouraging PA. Parent-perceived neighborhood characteristics were significantly correlated with parenting practices discouraging PA only. Conclusions for Practice This study identified correlates of PA-related parenting practices among parents of Hong Kong Chinese preschoolers. The findings suggest future PA-promoting interventions among Chinese preschoolers via the promotion of parenting practices encouraging children's PA should consider multiple factors, including family relationships and childcare sharing, promotion of PA and its benefits among parents, and neighborhood social cohesion, traffic safety and safety from crime.

Can water quality indicators and biomarkers be used to estimate real-time population?

The precise population estimation, short-term or real-time, is crucial to social and civil management, such as public resource distribution, education budgets, health care, and public safety. In this paper, we reviewed the methods for estimation of real-time population. For real-time population estimation, especially for a certain wastewater treatment plant catchment, many water quality indicators and biomarkers were selected as potential markers and their stability, consumption coefficient, and uncertainty were assessed. The conventional water quality indicators, such as wastewater discharge volume, chemical oxygen demand, biochemical oxygen demand, ammonia nitrogen, and total phosphorus, were used to calculate the serving population within a WWTP catchment. These parameters are all affected by the behavior, living habits and health conditions of people in different regions. Among them, wastewater discharge volume and ammonia might be more suitable for population estimation than the other parameters which may be influenced by additional industrial discharge. Moreover, acesulfame could be used to estimate the general population, while caffeine, tobacco, and carbamazepine could be applied as biomarkers for a specific population. Furthermore, the per capita loading differ should be considered and measured independently. To reduce the uncertainty of population, comprehensive model with multi-parameters should be developed and applicability should be checked.

Spatial modeling of leprosy in the state of Bahia and its social determinants: a study of health inequities

BACKGROUND

Leprosy is a neglected disease caused by Mycobacterium leprae. Brazil has the second largest number of cases in the world.

OBJECTIVES

To analyze the spatial distribution of leprosy in the state of BAHIA, Brazil, and the association between his occurrence and the synthetic indicators of municipal socioeconomic performance, social vulnerability and income inequality.

METHODS

An ecological study with secondary data obtained from the National System of Notifiable Diseases. Dependent variables: coefficient of detection in the general population and in the population under 15 years old and the rate of grade II of physical disability. Independent variables: Synthetic indicators of socioeconomic performance, social vulnerability and income inequality.

RESULTS

The highest coefficients of detection of new cases in the general population and in children under 15 years old are concentrated in the north-west axis and in the southern region of the state. On the other hand, the highest rates of degree II of physical incapacity are concentrated in the north, northeast and south regions. Only the Index of Social and Economic Performance(IPESE)-Economy and Finance composed the final regression model of the general detection coefficients and in children under 15 years old. The municipalities with the highest indexes had the highest detection coefficients, reflecting the capacity to diagnose new cases.

STUDY LIMITATIONS

The use of synthetic indicators is a limitation of the study.

CONCLUSIONS

Leprosy presents a heterogeneous spatial pattern in the state of BAHIA, and the IPESE-Economics and Finance indicator is the only one with explanatory potential of the disease.

Spatial distribution, source analysis, and health risk assessment of heavy metals contamination in house dust and surface soil from four major cities of Nepal

Raising population, deteriorating environmental conditions and limiting natural resources to handle the key environmental health problems have critically affected human health and the environment. Policy makers and planners in Nepal are more concerned today than at any other time in the past about the deterioration of the environmental condition. Therefore, understanding the connection between pollution and human wellbeing is fundamental endeavors to control pollution exposures and secure human wellbeing. This ability is especially critical for countries like Nepal where the issues of environmental pollution have customarily taken a second place to request for economic development. In this study, spatial distribution and sources of 12 heavy metals (HMs) were investigated in surface soils (n = 24) and house dust (n = 24) from four major urban areas of Nepal in order to mark the pollution level. Additionally, a health risk was estimated to establish the link between HMs pollution and human health. Results showed that the median concentration of Ag, Cd, Co, Cr, Cu, Ni, Pb, Sb, Mn and Zn in soil and dust were 2-13 times greater than the background value. The As, Zn, Cu, Cd, and Pb showed a relatively higher spatial variability in soil and dust. Zn was the most abundant metal measured in dust and soil and accounted for 59% and 55% of ∑₇HMs, respectively. The HMs in soil and dust were poorly correlated with total organic carbon (TOC) and black carbon (BC), suggesting little or no influence on HMs contamination. Source analysis study indicated the distribution of Cr, Ni, Sb, Ag, Pb, Cu, and Zn in soil and dust are mainly affected by anthropogenic sources, particularly traffic emissions, industrial source, and domestic households materials, while Co, Fe, As, Mn and Cd were from natural sources. The estimated carcinogenic risk (CR) of HMs in soil and dust exceeded the acceptable level of human exposure, recommending significant CR to the local population.

Social evolution under demographic stochasticity

How social traits such as altruism and spite evolve remains an open question in evolutionary biology. One factor thought to be potentially important is demographic stochasticity. Here we provide a general theoretical analysis of the role of demographic stochasticity in social evolution. We show that the evolutionary impact of stochasticity depends on how the social action alters the recipient’s life cycle. If the action alters the recipient’s death rate, then demographic stochasticity always favours altruism and disfavours spite. On the other hand, if the action alters the recipient’s birth rate, then stochasticity can either favour or disfavour both altruism and spite depending on the ratio of the rate of population turnover to the population size. Finally, we also show that this ratio is critical to determining if demographic stochasticity can reverse the direction of selection upon social traits. Our analysis thus provides a general understanding of the role of demographic stochasticity in social evolution.

Explaining the evolution of social traits such as altruism and spite remains a key outstanding problem in evolutionary biology. Here we develop a simple theory for the effect of demographic stochasticity (random variation in an individual’s birth and death rates) on the evolution of social traits. Our results provide a clear set of predictions: whether a social trait is favoured or disfavoured is determined by how the social action alters the recipient’s life cycle. If the social action alters the recipient’s death rate, then altruism is favoured and spite disfavoured. If instead the social action alters the recipient’s birth rate, then both altruism and spite can be either favoured or disfavoured—the precise outcome depends upon the ratio of the population turnover rate to the population size.

A simplified approach to measuring national gender inequality

The Global Gender Gap Index is one of the best-known measures of national gender inequality, used by both academics and policy makers. We argue that that this measure has a number of problems and introduce a simpler measure of national levels of gender inequality. Our proposed measure is based on sex differences in the opportunity to lead a long healthy and satisfied life that is grounded on educational opportunities. The measure better captures variation in gender inequality than other measures, with inclusion of outcomes that can be favorable or unfavorable to either sex, not simply unfavorable to women. We focus on some of the most basic measures available for 134 countries from 2012-2016 (i.e., disadvantages in children's basic education, life satisfaction, and healthy life span) and we relate these to various measures, including the United Nations' Human Development Index. We found that low levels of human development are typically associated with disadvantages for girls and women, while medium and high levels of development are typically associated with disadvantages for boys and men. Countries with the highest levels of human development are closest to gender parity, albeit typically with a slight advantage for women. We argue that the disparities, when they are found, are related to the sexual division of labor (i.e., traditional gender roles) in poorly developed countries as well as the underinvestment in preventative health care in more developed nations.

Tracing long-term demographic changes: The issue of spatial scales

This paper deals with the analysis of long-term changes in population densities at the regional and macro-regional scale and in the density of metapopulations. The following issues concerning estimations are addressed: chronological resolution of demographic changes, estimation of the weight of values for population density in order to transform the initial values included in the sample into the values that may be compared with each other at the regional scale, calibration of the transformed values into real population densities, and the estimation of the weight of values for population density at the scales of macro-regions and for the density of metapopulations. The proposed methods are tested on demographic changes in Central Europe, Southern Scandinavia, Southeastern Europe, and the Near East. The obtained results represent major trends in demographic development, while the proposed methodology could also be applied in other wide-scale demographic analyses.

Correlates of nurses' motivation and their demographic characteristics

BACKGROUND

Motivation is a significant concern for workforce management in healthcare organizations as it is linked to many important factors, such as performance, staff retention, and satisfaction.

AIM

To assess motivation level, assess sources of motivation, and identify the difference in motivation level in relation to nurses' characteristics.

SETTING

The study was carried out in one major tertiary hospital in Riyadh, Kingdom of Saudi Arabia.

PARTICIPANTS

A total convenient sample of 550 nurses were recruited. All participants are working under the umbrella of executive nursing administration.

METHODS

Data were collected using a self-administered questionnaire, which consisted of 30 items that focused on assessing a nurse's motivation sources and level.

RESULTS

In general, 346 nurses (62%) fully completed the survey. The average motivation level of nurses is 3.6 ± 0.5. Additionally, internal self-concept motivation was identified as the most predominant source of motivation (4.1 ± 0.6). Instrumental and goal internalization motivations ranked second (3.7 ± 0.6), whereas external self-concept (3.4 ± 0.7) and intrinsic (3 ± 0.7) motivations are the lowest sources of motivation. There is a significant difference in the motivation mean between males and females (P = 0.034). Another significant difference was revealed with different years of experience ( P = 0.021).

CONCLUSION

The high percentage of internal self-concept motivation among nurses signified that nurses needed more than enjoyment of their work atmosphere, social acknowledgment, higher salary, and good rationale to give maximum effort. Although these should be taken into consideration, more attention should be given to practices that improve a nurse's challenge, autonomy, internal value, and competency.

Errors as a primary cause of late-life mortality deceleration and plateaus

Several organisms, including humans, display a deceleration in mortality rates at advanced ages. This mortality deceleration is sufficiently rapid to allow late-life mortality to plateau in old age in several species, causing the apparent cessation of biological ageing. Here, it is shown that late-life mortality deceleration (LLMD) and late-life plateaus are caused by common demographic errors. Age estimation and cohort blending errors introduced at rates below 1 in 10,000 are sufficient to cause LLMD and plateaus. In humans, observed error rates of birth and death registration predict the magnitude of LLMD. Correction for these sources of demographic error using a mixed linear model eliminates LLMD and late-life mortality plateaus (LLMPs) without recourse to biological or evolutionary models. These results suggest models developed to explain LLMD have been fitted to an error distribution, that ageing does not slow or stop during old age in humans, and that there is a finite limit to human longevity.

In diverse species, mortality rates increase with age at a relatively fixed rate within populations. However, recent discoveries have suggested this relationship breaks down in advanced old age, with mortality rate increases slowing and even reaching a plateau. This late-life mortality deceleration has initiated sustained debate on the cause of late-life deceleration and plateaus. Proposed explanations include evolutionary patterns, the exhaustion of selective pressure, population heterogeneity, and even the cessation of the ageing process. Here, I demonstrate that apparent late-life mortality decelerations and plateaus can be generated by low-frequency errors. I then reveal how indicators of demographic data quality predict the magnitude of late-life mortality deceleration and the existence of late-life plateaus in human populations. These findings suggest that human late-life mortality plateaus are largely, if not entirely, artefacts of error processes. As a result, late-life mortality plateaus and decelerations may be explained by error patterns in humans and many other species without invoking complex biological, heterogeneity, or evolutionary models. This finding has immediate consequences for demographic modelling, evolutionary biology, and the projected upper limits of human and nonhuman life.

Geolocator deployment reduces return rate, alters selection, and impacts demography in a small songbird

In the past few years, miniature light-level geolocators have been developed for tracking wild bird species that were previously too small to track during their full annual cycle. Geolocators offer an exciting opportunity to study the full annual cycle for many species. However, the potential detrimental effects of carrying geolocators are still poorly understood, especially for small-bodied birds. Here, we deployed light-level geolocators on common yellowthroat warblers (Geothlypis trichas). Over two years, we monitored return rates and neighborhood demography for 40 warblers carrying a geolocator and 20 reference birds that did not carry a geolocator. We compared the two groups with long-term data from 108 unmanipulated birds breeding at the same location in previous and subsequent years. Overall, we found that individuals carrying a geolocator were less likely to return to the study site in the following year (21% to 33% returned, depending on inclusion criteria) than either contemporaneous controls (55%) or long-term controls (55%). Among birds marked with geolocators, we also detected viability selection for greater wing length, whereas this pattern was not present in control birds. Finally, in each year after geolocator deployment, inexperienced breeders colonized vacant territories and this demographic effect persisted for two years after deployment. Sexual selection and ornamentation are strongly age-dependent in this system, and behavioral data collected after geolocator deployment is likely to differ systematically from natural conditions. Clearly geolocators will continue to be useful tools, but we suggest that future studies should carefully consider the potential for biased returns and the ecological validity of behavioral data collected from geolocator marked populations.

Patient Characteristics from an Emergency Care Center in Rural Western Kenya

BACKGROUND

Emergency care is a neglected area of focus in many low- and middle-income countries. There is a paucity of research on types and frequencies of acute illnesses and injuries in low-resource settings.

OBJECTIVE

The primary objective of this study was to describe the demographic characteristics and emergency conditions of patients that presented to a new emergency care center (ECC) at Sagam Community Hospital in Luanda, Kenya.

METHODS

Patient demographic characteristics, modes of arrival, chief symptoms, triage priorities, self-reported human immunodeficiency virus status, tests performed, interventions, discharge diagnoses, and dispositions were collected for all patients that presented to the Sagam Community Hospital ECC.

RESULTS

Between October 1, 2016 and September 30, 2017, 14,518 patients presented to the ECC. The most common mode of arrival to Sagam Community Hospital was by foot (n = 12,605 [86.8%]). There were 8931 (61.5%) female patients and 5571 (38.4%) male patients. Of the total visits, 12,668 (87.3%) were triaged Priority III (lowest priority), 1239 (8.5%) were Priority II, and 293 (2.0%) were Priority I (highest priority). The most common chief symptoms were headache (n = 3923 [15.2%]), hotness of body or chills (n = 2877 [8.8%]), and cough (n = 1827 [5.5%]). The three most common discharge diagnoses were malaria (n = 3692 [18.9%]), acute upper respiratory infection (n = 1242 [6.3%]), and gastritis/duodenitis (n = 1210 [6.2%]).

CONCLUSIONS

Although opening an ECC in rural Kenya attracted patients in need of care, access was limited primarily to those that could arrive on foot. ECCs in rural sub-Saharan Africa have the potential to provide quality care and support attainment of Sustainable Development Goals.

What demographic attributes do our digital footprints reveal? A systematic review

To what extent does our online activity reveal who we are? Recent research has demonstrated that the digital traces left by individuals as they browse and interact with others online may reveal who they are and what their interests may be. In the present paper we report a systematic review that synthesises current evidence on predicting demographic attributes from online digital traces. Studies were included if they met the following criteria: (i) they reported findings where at least one demographic attribute was predicted/inferred from at least one form of digital footprint, (ii) the method of prediction was automated, and (iii) the traces were either visible (e.g. tweets) or non-visible (e.g. clickstreams). We identified 327 studies published up until October 2018. Across these articles, 14 demographic attributes were successfully inferred from digital traces; the most studied included gender, age, location, and political orientation. For each of the demographic attributes identified, we provide a database containing the platforms and digital traces examined, sample sizes, accuracy measures and the classification methods applied. Finally, we discuss the main research trends/findings, methodological approaches and recommend directions for future research.

Prevalence of beliefs about actual and mythical causes of cancer and their association with socio-demographic and health-related characteristics: Findings from a cross-sectional survey in England

BACKGROUND

Literature on population awareness about actual causes of cancer is growing but comparatively little is known about the prevalence of people's belief concerning mythical causes of cancer. This study aimed to estimate the prevalence of these beliefs and their association with socio-demographic characteristics and health behaviours.

METHODS

A survey containing validated measures of beliefs about actual and mythical cancer causes and health behaviours (smoking, alcohol consumption, physical activity, fruit and vegetable consumption, overweight) was administered to a representative English population sample (N = 1330).

RESULTS

Awareness of actual causes of cancer (52% accurately identified; 95% confidence interval [CI] 51-54) was greater than awareness of mythical cancer causes (36% accurately identified; 95% CI 34-37; P < 0.01). The most commonly endorsed mythical cancer causes were exposure to stress (43%; 95% CI 40-45), food additives (42%; 95% CI 39-44) and non-ionizing electromagnetic frequencies (35%; 95% CI 33-38). In adjusted analysis, greater awareness of actual and mythical cancer causes was independently associated with younger age, higher social grade, being white and having post-16 qualifications. Awareness of actual but not mythical cancer causes was associated with not smoking and eating sufficient fruit and vegetables.

CONCLUSIONS

Awareness of actual and mythical cancer causes is poor in the general population. Only knowledge of established risk factors is associated with adherence to behavioural recommendations for reducing cancer risk.

Temporal and spatial distribution of Microcystis biomass and genotype in bloom areas of Lake Taihu

Cyanobacterial blooms as a global environmental issue are of public health concern. In this study, we investigated the spatial (10 sites) and temporal (June, August and October) variations in: 1) their biomass based on chlorophyll-a (chl-a) concentration, 2) their toxic genotype based on gene copy ratio of mcyJ to cpcBA, and 3) their cpcBA genotype composition of Microcystis during cyanobacterial bloom in Lake Taihu. While spatial-temporal variations were found in chl-a and mcyJ/cpcBA ratio, only spatial variation was observed in cpcBA genotype composition. Samples from northwestern part had a higher chl-a, but mcyJ/cpcBA ratio didn't vary among the sites. High chl-a was observed in August, while mcyJ/cpcBA ratio and genotypic richness increased with time. The spatial variations in chl-a and mcyJ/cpcBA ratio and temporal variation in cpcBA genotype were correlated negatively with dissolved N and positively with dissolved P. Spatial distribution of Microcystis biomass was positively correlated with nitrite and P excluding October, but no correlation was found for spatial distribution of mcyJ/cpcBA ratio and cpcBA genotype. Spatial distribution of toxic and cpcBA genotypes may result from horizontal transport of Microcystis colonies, while spatial variation in Microcystis biomass was probably controlled by both nutrient-mediated growth and horizontal transport of Microcystis. The temporal variation in Microcystis biomass, toxic genotype and cpcBA genotype composition were related to nutrient levels, but cause-and-effect relationships require further study.

On the joint distribution of tree height and tree length under the coalescent

Many statistics that examine genetic variation depend on the underlying shapes of genealogical trees. Under the coalescent model, we investigate the joint distribution of two quantities that describe genealogical tree shape: tree height and tree length. We derive a recursive formula for their exact joint distribution under a demographic model of a constant-sized population. We obtain approximations for the mean and variance of the ratio of tree height to tree length, using them to show that this ratio converges in probability to 0 as the sample size increases. We find that as the sample size increases, the correlation coefficient for tree height and length approaches (π2-6)∕[π2π2-18]≈0.9340. Using simulations, we examine the joint distribution of height and length under demographic models with population growth and population subdivision. We interpret the joint distribution in relation to problems of interest in data analysis, including inference of the time to the most recent common ancestor. The results assist in understanding the influences of demographic histories on two fundamental features of tree shape.

Human demographic history has amplified the effects of background selection across the genome

Natural populations often grow, shrink, and migrate over time. Such demographic processes can affect genome-wide levels of genetic diversity. Additionally, genetic variation in functional regions of the genome can be altered by natural selection, which drives adaptive mutations to higher frequencies or purges deleterious ones. Such selective processes affect not only the sites directly under selection but also nearby neutral variation through genetic linkage via processes referred to as genetic hitchhiking in the context of positive selection and background selection (BGS) in the context of purifying selection. While there is extensive literature examining the consequences of selection at linked sites at demographic equilibrium, less is known about how non-equilibrium demographic processes influence the effects of hitchhiking and BGS. Utilizing a global sample of human whole-genome sequences from the Thousand Genomes Project and extensive simulations, we investigate how non-equilibrium demographic processes magnify and dampen the consequences of selection at linked sites across the human genome. When binning the genome by inferred strength of BGS, we observe that, compared to Africans, non-African populations have experienced larger proportional decreases in neutral genetic diversity in strong BGS regions. We replicate these findings in admixed populations by showing that non-African ancestral components of the genome have also been affected more severely in these regions. We attribute these differences to the strong, sustained/recurrent population bottlenecks that non-Africans experienced as they migrated out of Africa and throughout the globe. Furthermore, we observe a strong correlation between FST and the inferred strength of BGS, suggesting a stronger rate of genetic drift. Forward simulations of human demographic history with a model of BGS support these observations. Our results show that non-equilibrium demography significantly alters the consequences of selection at linked sites and support the need for more work investigating the dynamic process of multiple evolutionary forces operating in concert.

Demographic, clinical, lifestyle-related, and social-cognitive correlates of physical activity in head and neck cancer survivors

PURPOSE

The purpose of the study is to identify demographic, clinical, lifestyle-related, and social-cognitive correlates of physical activity (PA) intention and behavior in head and neck cancer (HNC) survivors using the theory of planned behavior (TPB).

METHODS

Data from two cross-sectional studies on correlates of PA in HNC survivors were pooled. Both studies used self-reports to assess PA and social-cognitive correlates. Potential correlates were collected via self-report or medical records. Univariable and multivariable multilevel linear mixed-effects models were built to identify correlates of PA intention and PA behavior (Z scores). Structural equation model analyses were conducted to study the full TPB model in one analysis, taking into account relevant covariates.

RESULTS

In total, 416 HNC survivors were surveyed. Their mean (SD) age was 66.6 (9.4) years; 64% were men, and 78% were diagnosed with laryngeal cancer. The structural equation model showed that PA intention was significantly higher in HNC survivors with a history of exercising, who had a more positive attitude, subjective norm, and perceived behavioral control. Patients with higher PA intention, higher PBC, a lower age, and without unintentional weight loss or comorbidities had higher PA behavior. The model explained 22.9% of the variance in PA intention and 16.1% of the variance in PA behavior.

CONCLUSIONS

Despite significant pathways of the TPB model, the large proportion variance in PA intention and behavior remaining unexplained suggests the need for better PA behavior (change) models to guide the development of PA promotion programs, particularly for the elderly. Such programs should be tailored to comorbidities and nutritional status.

Generalized lambda distribution for flexibly testing differences beyond the mean in the distribution of a dependent variable such as body mass index

BACKGROUND/OBJECTIVES

Conventional statistical methods often test for group differences in a single parameter of a distribution, usually the conditional mean (for example, differences in mean body mass index (BMI; kg m-2) by education category) under specific distributional assumptions. However, parameters other than the mean may of be interest, and the distributional assumptions of conventional statistical methods may be violated in some situations.

SUBJECTS/METHODS

We describe an application of the generalized lambda distribution (GLD), a flexible distribution that can be used to model continuous outcomes, and simultaneously describe a likelihood ratio test for differences in multiple distribution parameters, including measures of central tendency, dispersion, asymmetry and steepness. We demonstrate the value of our approach by testing for differences in multiple parameters of the BMI distribution by education category using the Health and Retirement Study data set.

RESULTS

Our proposed method indicated that at least one parameter of the BMI distribution differed by education category in both the complete data set (N=13 571) (P<0.001) and a randomly resampled data set (N=300 from each category) to assess the method under circumstances of lesser power (P=0.044). Similar method using normal distribution alternative to GLD indicated the significant difference among the complete data set (P<0.001) but not in the smaller randomly resampled data set (P=0.968). Moreover, the proposed method allowed us to specify which parameters of the BMI distribution significantly differed by education category for both the complete and the random subsample, respectively.

CONCLUSIONS

Our method provides a flexible statistical approach to compare the entire distribution of variables of interest, which can be a supplement to conventional approaches that frequently require unmet assumptions and focus only on a single parameter of distribution.

The DHS Program's Modeled Surfaces Spatial Datasets

Spatially interpolated map surface datasets for key development indicators are being produced and publicly shared using population-based surveys from the USAID-funded Demographic and Health Survey (DHS) Program. Each modeled surface is produced with standardized geostatistical modeling methods. For each indicator, a package is available that includes spatial raster grids of 5 × 5 km pixels for the point estimate surface and an uncertainty surface, along with validation statistics and other model diagnostic data. The maps are publicly available for download on the DHS Program Spatial Data Repository at http://spatialdata.dhsprogram.com/. The modeled surfaces are produced with publicly available geo-referenced data on each indicator as collected by the DHS Program, augmented with other relevant spatial data sources that act as covariates. A Bayesian model-based geostatistical (MBG) approach is used to generate the modeled surfaces. Spatially modeled surfaces can be used to support and improve decision-making at multiple levels within many development programs including health, population, family planning, nutrition, and water and sanitation. The modeled surfaces can be used in their original 5 × 5 km pixel format, operationalized to other geographic areas as relevant for the program, or linked to DHS or other survey data for additional analysis.

Demographic and genetic viability of a medium-sized ground-dwelling mammal in a fire prone, rapidly urbanizing landscape

The rapid and large-scale urbanization of peri-urban areas poses major and complex challenges for wildlife conservation. We used population viability analysis (PVA) to evaluate the influence of urban encroachment, fire, and fauna crossing structures, with and without accounting for inbreeding effects, on the metapopulation viability of a medium-sized ground-dwelling mammal, the southern brown bandicoot (Isoodon obesulus), in the rapidly expanding city of Perth, Australia. We surveyed two metapopulations over one and a half years, and parameterized the PVA models using largely field-collected data. The models revealed that spatial isolation imposed by housing and road encroachment has major impacts on I. obesulus. Although the species is known to persist in small metapopulations at moderate levels of habitat fragmentation, the models indicate that these populations become highly vulnerable to demographic decline, genetic deterioration, and local extinction under increasing habitat connectivity loss. Isolated metapopulations were also predicted to be highly sensitive to fire, with large-scale fires having greater negative impacts on population abundance than small-scale ones. To reduce the risk of decline and local extirpation of I. obesulus and other small- to medium-sized ground-dwelling mammals in urbanizing, fire prone landscapes, we recommend that remnant vegetation and vegetated, structurally-complex corridors between habitat patches be retained. Well-designed road underpasses can be effective to connect habitat patches and reduce the probability of inbreeding and genetic differentiation; however, adjustment of fire management practices to limit the size of unplanned fires and ensure the retention of long unburnt vegetation will also be required to ensure persistence. Our study supports the evidence that in rapidly urbanizing landscapes, a pro-active conservation approach is required that manages species at the metapopulation level and that prioritizes metapopulations and habitat with greater long-term probability of persistence and conservation capacity, respectively. This strategy may help us prevent future declines and local extirpations, and currently relatively common species from becoming rare.

Demographic Analysis from Biometric Data: Achievements, Challenges, and New Frontiers

Biometrics is the technique of automatically recognizing individuals based on their biological or behavioral characteristics. Various biometric traits have been introduced and widely investigated, including fingerprint, iris, face, voice, palmprint, gait and so forth. Apart from identity, biometric data may convey various other personal information, covering affect, age, gender, race, accent, handedness, height, weight, etc. Among these, analysis of demographics (age, gender, and race) has received tremendous attention owing to its wide real-world applications, with significant efforts devoted and great progress achieved. This survey first presents biometric demographic analysis from the standpoint of human perception, then provides a comprehensive overview of state-of-the-art advances in automated estimation from both academia and industry. Despite these advances, a number of challenging issues continue to inhibit its full potential. We second discuss these open problems, and finally provide an outlook into the future of this very active field of research by sharing some promising opportunities.

A parsimonious characterization of change in global age-specific and total fertility rates

This study aims to understand trends in global fertility from 1950-2010 though the analysis of age-specific fertility rates. This approach incorporates both the overall level, as when the total fertility rate is modeled, and different patterns of age-specific fertility to examine the relationship between changes in age-specific fertility and fertility decline. Singular value decomposition is used to capture the variation in age-specific fertility curves while reducing the number of dimensions, allowing curves to be described nearly fully with three parameters. Regional patterns and trends over time are evident in parameter values, suggesting this method provides a useful tool for considering fertility decline globally. The second and third parameters were analyzed using model-based clustering to examine patterns of age-specific fertility over time and place; four clusters were obtained. A country’s demographic transition can be traced through time by membership in the different clusters, and regional patterns in the trajectories through time and with fertility decline are identified.