Global latitudinal gradients and the evolution of body size in dinosaurs and mammals.

Global climate patterns fundamentally shape the distribution of species and ecosystems. For example, Bergmann's rule predicts that homeothermic animals, including birds and mammals, inhabiting cooler climates are generally larger than close relatives from warmer climates. The modern world, however, lacks the comparative data needed to evaluate such macroecological rules rigorously. Here, we test for Bergmann's rule in Mesozoic dinosaurs and mammaliaforms that radiated within relatively temperate global climate regimes. We develop a phylogenetic model that accounts for biases in the fossil record and allows for variable evolutionary dispersal rates. Our analysis also includes new fossil data from the extreme high-latitude Late Cretaceous Arctic Prince Creek Formation. We find no evidence for Bergmann's rule in Mesozoic dinosaurs or mammaliaforms, the ancestors of extant homeothermic birds and mammals. When our model is applied to thousands of extant dinosaur (bird) and mammal species, we find that body size evolution remains independent of latitude. A modest temperature effect is found in extant, but not in Mesozoic, birds, suggesting that body size evolution in modern birds was influenced by Bergmann's rule during Cenozoic climatic change. Our study provides a general approach for studying macroecological rules, highlighting the fossil record's power to address longstanding ecological principles.

New insights into grocery store visits among east Los Angeles residents using mobility data.

In this study, we employed spatially aggregated population mobility data, generated from mobile phone locations in 2021, to investigate patterns of grocery store visits among residents east and northeast of Downtown Los Angeles, in which 60% of the census tracts had previously been designated as "food deserts". Further, we examined whether the store visits varied with neighborhood sociodemographics and grocery store accessibility. We found that residents averaged 0.4 trips to grocery stores per week, with only 13% of these visits within home census tracts, and 40% within home and neighboring census tracts. The mean distance from home to grocery stores was 2.2 miles. We found that people visited grocery stores more frequently when they lived in neighborhoods with higher percentages of Hispanics/Latinos, renters and foreign-born residents, and a greater number of grocery stores. This research highlights the utility of mobility data in elucidating grocery store use, and factors that may facilitate or be a barrier to store access. The results point to limitations of using geographically constrained metrics of food access like food deserts.

GPS-derived environmental exposures during pregnancy and early postpartum - Evidence from the madres cohort.

The built and natural environment factors (e.g., greenspace, walkability) are associated with maternal and infant health during and after pregnancy. Most pregnancy studies assess exposures to environmental factors via static methods (i.e., residential location at a single point in time, usually 3rd trimester). These do not capture dynamic exposures encountered in activity spaces (e.g., locations one visits and paths one travels) and their changes over time. In this study, we aimed to compare daily environmental exposure estimates using residential and global positioning systems (GPS)-measured activity space approaches and evaluated potential for exposure measurement error in the former. To do this, we collected four days of continuous geolocation monitoring during the 1st and 3rd trimesters of pregnancy and at 4-6 months postpartum in sixty-two pregnant Hispanic women enrolled in the MADRES cohort. We applied residential and GPS-based methods to assess daily exposures to greenspace, access to parks and transit, and walkability, respectively. We assessed potential for exposure measurement error in residential vs GPS-based estimates using Pearson correlations for each measure overall and by study period. We found residential and GPS-based estimates of daily exposure to total areas of parks and open spaces were weakly positively correlated (r = 0.31, P < .001) across pregnancy and postpartum periods. Residential estimates of %greenspace (r = 0.52, P < .001) and tree cover (r = 0.55, P < .001) along walkable roads were moderately correlated with GPS-based estimates. Residential and GPS-based estimates of public transit proximity, pedestrian-oriented intersection density, and walkability index score were all highly positively correlated (r > 0.70, P < .001). We also found associations between residential and GPS-based estimates decreased among participants with greater daily mobility. Our findings suggest the popular approach that assessing the built and natural environment exposures using residential methods at one time point may introduce exposure measurement error in pregnancy studies. GPS-based methods, to the extent feasible, are recommended for future studies.

Sources of personal PM2.5 exposure during pregnancy in the MADRES cohort.

BACKGROUND: Personal exposure to fine particulate matter (PM2.5) is impacted by different sources each with different chemical composition. Determining these sources is important for reducing personal exposure and its health risks especially during pregnancy. OBJECTIVE: Identify main sources and their contributions to the personal PM2.5 exposure in 213 women in the 3rd trimester of pregnancy in Los Angeles, CA. METHODS: We measured 48-hr integrated personal PM2.5 exposure and analyzed filters for PM2.5 mass, elemental composition, and optical carbon fractions. We used the EPA Positive Matrix Factorization (PMF) model to resolve and quantify the major sources of personal PM2.5 exposure. We then investigated bivariate relationships between sources, time-activity patterns, and environmental exposures in activity spaces and residential neighborhoods to further understand sources. RESULTS: Mean personal PM2.5 mass concentration was 22.3 (SD = 16.6) µg/m3. Twenty-five species and PM2.5 mass were used in PMF with a final R2 of 0.48. We identified six sources (with major species in profiles and % contribution to PM2.5 mass) as follows: secondhand smoking (SHS) (brown carbon, environmental tobacco smoke; 65.3%), fuel oil (nickel, vanadium; 11.7%), crustal (aluminum, calcium, silicon; 11.5%), fresh sea salt (sodium, chlorine; 4.7%), aged sea salt (sodium, magnesium, sulfur; 4.3%), and traffic (black carbon, zinc; 2.6%). SHS was significantly greater in apartments compared to houses. Crustal source was correlated with more occupants in the household. Aged sea salt increased with temperature and outdoor ozone, while fresh sea salt was highest on days with westerly winds from the Pacific Ocean. Traffic was positively correlated with ambient NO2 and traffic-related NOx at residence. Overall, 76.8% of personal PM2.5 mass came from indoor or personal compared to outdoor sources. IMPACT: We conducted source apportionment of personal PM2.5 samples in pregnancy in Los Angeles, CA. Among identified sources, secondhand smoking contributed the most to the personal exposure. In addition, traffic, crustal, fuel oil, fresh and aged sea salt sources were also identified as main sources. Traffic sources contained markers of combustion and non-exhaust wear emissions. Crustal source was correlated with more occupants in the household. Aged sea salt source increased with temperature and outdoor ozone and fresh sea salt source was highest on days with westerly winds from the Pacific Ocean.

Population mobility data provides meaningful indicators of fast food intake and diet-related diseases in diverse populations.

The characteristics of food environments people are exposed to, such as the density of fast food (FF) outlets, can impact their diet and risk for diet-related chronic disease. Previous studies examining the relationship between food environments and nutritional health have produced mixed findings, potentially due to the predominant focus on static food environments around people's homes. As smartphone ownership increases, large-scale data on human mobility (i.e., smartphone geolocations) represents a promising resource for studying dynamic food environments that people have access to and visit as they move throughout their day. This study investigates whether mobility data provides meaningful indicators of diet, measured as FF intake, and diet-related disease, evaluating its usefulness for food environment research. Using a mobility dataset consisting of 14.5 million visits to geolocated food outlets in Los Angeles County (LAC) across a representative sample of 243,644 anonymous and opted-in adult smartphone users in LAC, we construct measures of visits to FF outlets aggregated over users living in neighborhood. We find that the aggregated measures strongly and significantly correspond to self-reported FF intake, obesity, and diabetes in a diverse, representative sample of 8,036 LAC adults included in a population health survey carried out by the LAC Department of Public Health. Visits to FF outlets were a better predictor of individuals' obesity and diabetes than their self-reported FF intake, controlling for other known risks. These findings suggest mobility data represents a valid tool to study people's use of dynamic food environments and links to diet and health.

Ecological risk and protective factors for food insufficiency in Los Angeles County during the COVID-19 pandemic.

OBJECTIVE: The COVID-19 pandemic increased food insufficiency: a severe form of food insecurity. Drawing on an ecological framework, we aimed to understand factors that contributed to changes in food insufficiency from April to December 2020, in a large urban population hard hit by the pandemic. DESIGN: We conducted internet surveys every 2 weeks in April-December 2020, including a subset of items from the Food Insecurity Experience Scale. Longitudinal analysis identified predictors of food insufficiency, using fixed effects models. SETTING: Los Angeles County, which has a diverse population of 10 million residents. PARTICIPANTS: A representative sample of 1535 adults in Los Angeles County who are participants in the Understanding Coronavirus in America tracking survey. RESULTS: Rates of food insufficiency spiked in the first year of the pandemic, especially among participants living in poverty, in middle adulthood and with larger households. Government food assistance from the Supplemental Nutrition Assistance Program was significantly associated with reduced food insufficiency over time, while other forms of assistance such as help from family and friends or stimulus funds were not. CONCLUSIONS: The findings highlight that during a crisis, there is value in rapidly monitoring food insufficiency and investing in government food benefits.

A review of place-related contextual factors in syndemics research.

This review investigates the extent to which a place-based approach has been used to conceptualize context, as well as the place-related contextual factors explored in studies that explicitly invoked a syndemic framework. The literature search focused on 29 peer-reviewed empirical syndemic studies. Only 11 studies used a place-based approach to define and measure contextual factors and the spatial context was denoted using administrative boundaries such as census tracts, counties, and countries. A narrow range of place-related contextual factors were explored and most of them were related to social and economic factors that were used to define a place. Methodological gaps like a paucity of multilevel studies and studies using a place-based approach to measure context were identified. Future syndemics research should leverage multidimensional geospatial approaches to decipher the role of place-related contextual factors in syndemic dynamics.

Measuring Geographic Access to Transgender Hormone Therapy in Texas: A Three-step Floating Catchment Area Analysis.

While the extant literature has established that transgender people face significant barriers to accessing healthcare, no studies to date have offered an explicitly spatial analysis of their access to trans-specific care. This study aims to fill that gap by providing a spatial analysis of access to gender-affirming hormone therapy (GAHT) using Texas as a case study. We used the three-step floating catchment area method, which relies on census tract-level population data and location data for healthcare facilities to quantify spatial access to healthcare within a specific drive-time window, in our case 120 min. For our tract-level population estimates we adapt estimates of the rates of transgender identification from a recent data source, the Household Pulse Survey, and use these in tandem with a spatial database of GAHT providers of the lead author's creation. We then compare results of the 3SFCA with data on urbanicity and rurality, as well as which areas are deemed medically underserved. Finally, we conduct a hot-spot analysis that identifies specific areas where health services could be planned in ways that could improve both access to GAHT for trans people and access to primary care for the general population. Ultimately, we conclude that our results illustrate that patterns of access to trans-specific medical care, like GAHT, do not neatly follow patterns of access to primary care for the general population and that therefore trans communities' access to healthcare warrants specific, further investigation.

SEnDAE: A resource for expanding research into social and environmental determinants of health.

BACKGROUND AND OBJECTIVE: Social and Environmental Determinants of Health (SEDoH) are of increasing interest to researchers in personal and public health. Collecting SEDoH and associating them with patient medical record can be challenging, especially for environmental variables. We announce here the release of SEnDAE, the Social and Environmental Determinants Address Enhancement toolkit, and open-source resource for ingesting a range of environmental variables and measurements from a variety of sources and associated them with arbitrary addresses. METHODS: SEnDAE includes optional components for geocoding addresses, in case an organization does not have independent capabilities in that area, and recipes for extending the OMOP CDM and the ontology of an i2b2 instance to display and compute over the SEnDAE variables within i2b2. RESULTS: On a set of 5000 synthetic addresses, SEnDAE was able to geocode 83%. SEnDAE geocodes addresses to the same Census tract as ESRI 98.1% of the time. CONCLUSION: Development of SEnDAE is ongoing, but we hope that teams will find it useful to increase their usage of environmental variables and increase the field's general understanding of these important determinants of health.

Food Insecurity Is Under-reported in Surveys That Ask About the Past Year.

INTRODUCTION: Food insecurity affects one in ten Americans in a typical year; recent U.S. Department of Agriculture data show that this food insecurity rate was stable from 2019 to 2021. However, data from Los Angeles County and other U.S. regions show that food insecurity spiked during the early months of the COVID-19 pandemic. One reason for this discrepancy may be that food insecurity measures assess experiences over different time frames. This study investigated the discrepancies in food insecurity rates by comparing past-week and past-year food insecurity measures and explored the role of recall bias. METHODS: Data were obtained from a representative survey panel of Los Angeles adults (N=1,135). Participants were surveyed about past-week food insecurity eleven times throughout 2021 and once about past-year food insecurity in December 2021. Data were analyzed in 2022. RESULTS: Of the participants who reported past-week food insecurity at any time in 2021, only two thirds also reported past-year food insecurity in December 2021, suggesting that one third of participants under-reported past-year food insecurity. Logistic regression models indicated that three characteristics were significantly associated with under-reporting of past-year food insecurity: having reported past-week food insecurity at fewer survey waves, not reporting recent past-week food insecurity, and having a relatively high household income. CONCLUSIONS: These results suggest substantial under-reporting of past-year food insecurity, related to recall bias and social factors. Measuring food insecurity at multiple points throughout the year may help to improve the accuracy of reporting and public health surveillance of this issue.

Regular Cannabis Use During the First Year of the Pandemic: Studying Trajectories Rather Than Prevalence.

INTRODUCTION: Cannabis use in the U.S. rose early in the COVID-19 pandemic, but it is unclear whether that rise was temporary or permanent. This study estimated the nature and sociodemographic correlates of U.S. adult subpopulations regularly using cannabis by examining weekly trajectories of use during the first year of the pandemic. METHODS: Data came from the Understanding America Study, a nationally representative panel of U.S. adults (N=8,397; March 10, 2020-March 29, 2021). A growth mixture model was deployed to identify subgroups with similar regular cannabis use. Sociodemographic correlates of subgroups were examined using multinomial logistic regression. RESULTS: Four cannabis-use groups were identified. Most participants did not regularly use cannabis (no regular use; 81.7%). The other groups increased regular use until April 2020 but then diverged. Some (7.1%) decreased thereafter, whereas others (3.4%) maintained their elevated use until October 26, 2020 before decreasing. The last group (7.7%) sustained their elevated use throughout. Individuals aged between 18 and 39 years, unmarried, living in poverty, without a college degree, and with longer unemployment or underemployment spells had higher odds of being in the other groups with more weekly use than in the no-regular-use group. CONCLUSIONS: The analyses revealed population subgroups with prolonged regular cannabis use and a disproportionate concentration of socioeconomically vulnerable members of society in these subgroups. These findings elucidate important heterogeneity in the subpopulations using cannabis, highlighting the urgent need to tailor public health programs for subgroups that may have unique service needs.

Geospatial techniques for monitoring and mitigating climate change and its effects on human health.

This article begins by briefly examining the multitude of ways in which climate and climate change affect human health and wellbeing. It then proceeds to present a quick overview of how geospatial data, methods and tools are playing key roles in the measurement, analysis and modelling of climate change and its effects on human health. Geospatial techniques are proving indispensable for making more accurate assessments and estimates, predicting future trends more reliably, and devising more optimised climate change adaptation and mitigation plans.

American Indian and Alaska Native Accessibility to Comprehensive Cleft Lip and Palate Treatment.

American Indians and Alaska Natives (AI/AN) have the highest incidence of cleft lip and palate (orofacial clefts [OFCs]) when compared to other ethnic groups. We aim to determine the AI/AN populations' proximity and accessibility to American Cleft Palate-Craniofacial Association accredited centers (ACPA centers) for treatment of OFCs. Our hypothesis is an unacceptable proportion of the AI/AN population lacks reasonable accessibility to ACPA centers and comprehensive craniofacial care.A cross-sectional study of ACPA centers and AI/AN populations were analyzed for possible disparities.ACPA centers were mapped using Geographic Information Systems (GIS) and compared with 2018 census population data and 2017 Tribal Census Tract data to visually display possible disparities. Total annual potential pediatric cleft care need for selected high-density AI/AN populated lands were estimated.GIS mapping demonstrates geographical isolation of AI/AN populations from ACPA centers. Two states with high AI/AN populated lands (ND, WY) have no ACPA centers. 47.1% of ACPA centers in high AI/AN populated lands have no craniofacial trained surgeons versus 78.9% craniofacial staffed ACPA centers nationally. The potential unmet cleft and craniofacial care need in selected high-density AI/AN populated lands is 1042 children.AI/AN populations are likely underserved by ACPA centers and by craniofacial fellowship-trained staffed centers. Not addressing OFCs with comprehensive care can lead to worsened outcomes and further marginalization of these children. With future studies, we will be capable of making data-driven, informed decisions to more effectively ensure AI/AN access to comprehensive cleft and craniofacial care.

Divergent responses of cropland soil organic carbon to warming across the Sichuan Basin of China.

Cropland soils are considered to have the potential to sequester carbon (C). Warming can increase soil organic C (SOC) by enhancing primary production, but it can also cause carbon release from soils. However, the role of warming in governing cropland SOC dynamics over broad geographic scales remains poorly understood. Using over 4000 soil samples collected in the 1980s and 2010s across the Sichuan Basin of China, this study assessed the warming-induced cropland SOC change and the correlations with precipitation, cropland type and soil type. Results showed mean SOC content increased from 11.10 to 13.85 g C kg-1. Larger SOC increments were observed under drier conditions (precipitation < 1050 mm, dryland and paddy-dryland rotation cropland), which were 1.67-2.23 times higher than under wetter conditions (precipitation > 1050 mm and paddy fields). Despite the significant associations of SOC increment with crop productivity, precipitation, fertilization, cropland type and soil type, warming also acted as one of major contributors to cropland SOC change. The SOC increment changed parabolically with the rise in temperature increase rate under relatively drier conditions, while temperature increase had no impact on cropland SOC increment under wetter conditions. Meanwhile, the patterns of the parabolical relationship varied with soil types in drylands, where the threshold of temperature increase rate, the point at which the SOC increment switched from increasing to decreasing with warming, was lower for clayey soils (Ali-Perudic Argosols) than for sandy soils (Purpli-Udic Cambosols). These results illustrate divergent responses of cropland SOC to warming under different environments, which were contingent on water conditions and soil types. Our findings emphasize the importance of formulating appropriate field water management for sustainable C sequestration and the necessity of incorporating environment-specific mechanisms in Earth system models for better understanding of the soil C-climate feedback in complex environments.

The impact of GPS-derived activity spaces on personal PM2.5 exposures in the MADRES cohort.

BACKGROUND: In-utero exposure to particulate matter with aerodynamic diameter less than 2.5 µm (PM2.5) is associated with low birth weight and health risks later in life. Pregnant women are mobile and locations they spend time in contribute to their personal PM2.5 exposures. Therefore, it is important to understand how mobility and exposures encountered within activity spaces contribute to personal PM2.5 exposures during pregnancy. METHODS: We collected 48-h integrated personal PM2.5 samples and continuous geolocation (GPS) data for 213 predominantly Hispanic/Latina pregnant women in their 3rd trimester in Los Angeles, CA. We also collected questionnaires and modeled outdoor air pollution and meteorology in their residential neighborhood. We calculated three GPS-derived activity space measures of exposure to road networks, greenness (NDVI), parks, traffic volume, walkability, and outdoor PM2.5 and temperature. We used bivariate analyses to screen variables (GPS-extracted exposures in activity spaces, individual characteristics, and residential neighborhood exposures) based on their relationship with personal, 48-h integrated PM2.5 concentrations. We then built a generalized linear model to explain the variability in personal PM2.5 exposure and identify key contributing factors. RESULTS: Indoor PM2.5 sources, parity, and home ventilation were significantly associated with personal exposure. Activity-space based exposure to roads was associated with significantly higher personal PM2.5 exposure, while greenness was associated with lower personal PM2.5 exposure (ß = -3.09 µg/m3 per SD increase in NDVI, p-value = 0.018). The contribution of outdoor PM2.5 to personal exposure was positive but relatively lower (ß = 2.05 µg/m3 per SD increase, p-value = 0.016) than exposures in activity spaces and the indoor environment. The final model explained 34% of the variability in personal PM2.5 concentrations. CONCLUSIONS: Our findings highlight the importance of activity spaces and the indoor environment on personal PM2.5 exposures of pregnant women living in Los Angeles, CA. This work also showcases the multiple, complex factors that contribute to total personal PM2.5 exposure.

Time-activity and daily mobility patterns during pregnancy and early postpartum - evidence from the MADRES cohort.

INTRODUCTION: Pregnant women's daily time-activity and mobility patterns determine their environmental exposures and subsequently related health effects. Most studies ignore these and assess pregnancy exposures using static residential measures. METHODS: We conducted 4-day continuous geo-location monitoring in 62 pregnant Hispanic women, during pregnancy and early post-partum then derived trips by mode and stays, classified by context (indoor/outdoor, type). Generalized mixed-effect models were used to examine whether these patterns changed over time. RESULTS: Women spent on average 17.3 h/day at home. Commercial and service locations were the most popular non-home destinations, while parks and open spaces were seldom visited. Women made 3.5 daily trips (63.7 min/day and approximately 25% were pedestrian-based). Women were less likely to visit commercial and services locations and make vehicle-based trips postpartum compared to the 3rd trimester. CONCLUSION: Our findings suggest time-activity patterns vary across pregnancy and postpartum, thus assessing exposures at stationary locations might introduce measurement error.

The dynamics of cardiovascular and respiratory deaths attributed to long-term PM2.5 exposures in global megacities.

Exposure to ambient fine particulate matter (PM2.5) air pollution is a significant driver of premature deaths. We estimate the number of cardiovascular and respiratory (CR) premature deaths attributed to long-term exposure to PM2.5 in 33 global megacities based on long-term remotely sensed observations from 2000 to 2019. Our analysis uses high-resolution (0.01 degree) PM2.5 concentration data and cause-specific integrated exposure-response (IER) functions developed for the Global Burden of Disease Project. From 2000 to 2019, PM2.5-related CR death rates per 1000 people increased in 6 of 33 megacities, decreased in 9, and remained constant in 18 megacities. The increase in PM2.5-related CR mortality in 11 megacities located in South and East Asia during the period 2000-2019 can be attributed to the increases in PM2.5 concentrations. All 33 megacities could avoid 30,248 (9 %), 62,989 (20 %), 128,457 (40 %), 198,462 (62 %) and all of the estimated 322,515 CR deaths attributed to PM2.5 pollution in 2019 if they were to attain the World Health Organization's four interim PM2.5 targets (IT-1, IT-2, IT-3, and IT-4) and the new air quality guideline (AQG), respectively. Major improvements in air quality are needed to reduce the number of CR deaths attributed to PM2.5 in South and East Asia, in addition to ny reductions that would likely follow shifts in the population structures of these megacities moving forward.

Alcohol use trajectories among U.S. adults during the first 42 weeks of the COVID-19 pandemic.

BACKGROUND: This study characterized the prevalence, drinking patterns, and sociodemographic characteristics of U.S. adult subpopulations with distinct drinking trajectories during the COVID-19 pandemic's first 42 weeks. METHODS: Adult respondents (n = 8130) in a nationally representative prospective longitudinal study completed 21 biweekly web surveys (March 2020 to January 2021). Past-week alcohol drinking frequency (drinking days [range: 0 to 7]) and intensity (binge drinking on usual past-week drinking day [yes/no]) were assessed at each timepoint. Growth mixture models identified multiple subpopulations with homogenous drinking trajectories based on mean drinking days or binge drinking proportional probabilities across time. RESULTS: Four drinking frequency trajectories were identified: Minimal/stable (72.8% [95% CI = 71.8 to 73.8]) with <1 mean past-week drinking days throughout; Moderate/late decreasing (6.7% [95% CI = 6.2 to 7.3) with 3.13 mean March drinking days and reductions during summer, reaching 2.12 days by January 2021; Moderate/early increasing (12.9% [95% CI = 12.2 to 13.6) with 2.13 mean March drinking days that increased in April and then plateaued, ending with 3.20 mean days in January 2021; and Near daily/early increasing (7.6% [95% CI = 7.0 to 8.2]) with 5.58 mean March drinking days that continued increasing without returning to baseline. Four drinking intensity trajectories were identified: Minimal/stable (85.8% [95% CI = 85.0% to 86.5%]) with <0.01 binge drinking probabilities throughout; Low-to-moderate/fluctuating (7.4% [95% CI = 6.8% to 8%]) with varying binge probabilities across timepoints (range:0.12 to 0.26); Moderate/mid increasing (4.2% [95% CI = 3.7% to 4.6%]) with 0.39 April binge drinking probability rising to 0.65 during August-September without returning to baseline; High/early increasing trajectory (2.7% [95% CI = 2.3% to 3%]) with 0.84 binge drinking probability rising to 0.96 by June without returning to baseline. Males, Whites, middle-aged/older adults, college degree recipients, those consistently working, and those above the poverty limit were overrepresented in various increasing (vs. minimal/stable) frequency trajectories. Males, Whites, nonmarried, those without college degree, 18 to 39-year-olds, and middle aged were overrepresented in increasing (vs. minimal/stable) intensity trajectories. CONCLUSIONS: Several distinct U.S. adult sociodemographic subpopulations appear to have acquired new drinking patterns during the pandemic's first 42 weeks. Frequent alcohol use assessment in the COVID-19 era could improve personalized medicine and population health efforts to reduce drinking.

Evaluating Changes in Mental Workload in Indoor and Outdoor Ultra-Distance Cycling.

Whilst increasing mental workload has been shown to have a detrimental effect on cycling performance and more generally to increase the risk of harm, no studies have measured how mental workload changes as a function of ultra-distance cycling, indoors or outdoors. Our objective was to measure the difference in mental workload, as indicated by changes in EEG theta power, components of HRV and psychomotor vigilance and as reported using the 'NASA Task Load Index questionnaire', before and after a 5 h indoor ride and outdoor ride completed at 65% of functional threshold power. Results of the NASA-TLX indicated the mental demand of outdoor cycling to be significantly less than that of indoor cycling. There were significant differences in the PVT results between the pre and the post outdoor ride average and median response times. The slowest 10% PVT responses were significantly slower pre than post the indoor ride. There were significant differences in HRV between pre and post outdoor and indoor rides, specifically, in the average RR intervals, RMSSD (ms2), LFPower (ms2), NN50. There were modest changes in indicators of mental workload during an ultra-distance cycle ride. As such, mental workload during ultra-distance cycling is unlikely to be a contributory factor to decreases in performance or to an increased likelihood of accident and injury.

Improving surface water quality of the Yellow River Basin due to anthropogenic changes.

Understanding of how changes in diverse human activities and climate contribute to water quality dynamics is crucial for sustainable water environment management especially in the arid and semi-arid regions. This study conducted a comprehensive estimation of the surface water quality change in the Yellow River basin during 2003-2017 and its responses to varied pollution sources and water volumes under socioeconomic and environmental influences. Basin-wide measurements of chemical oxygen demand (COD), ammonium nitrogen (NH+4-N) and dissolved oxygen (DO) concentrations were used in trend detection. Annual anthropogenic (covering six sectors) and natural (sediment-induced, flow-in from the upstream and stored last year) pollution sources and water components (inflow, natural runoff, water consumption, reservoir storage and evaporation) were compiled for each sub-basin. Bottom-up hierarchical analysis was then performed to differentiate individual contributions. Results showed significant decreasing trends in COD and NH+4-N concentrations and increasing trends in DO concentrations. The middle reaches that traverse the Loess Plateau however remained severely polluted with 11.3-39.0% inferior to level III in 2017. The pollutant load played major positive contributions that gradually increased from upper to lower reaches. Declines in urban, rural and industrial pollution discharges following environmental investments and rural depopulation contributed the most: 78-96% for COD and 55-100% for NH+4-N. The total surface water volume had dilution effects in the upper and middle reaches (3-28%) and condensing effects in the lower reaches (2-37%). Precipitation and vegetation dynamics contributed slightly. The primary unfavorable factors were the growing agricultural pollution discharges and water consumption in the upper and middle reaches that also threatened the lower reaches. This study is expected to provide in-depth insights for the systematic response of regional water quality to combined human interventions and references for water quality management in other arid and semi-arid river basins worldwide.