Hierarchical Mixed Models Research Articles

A sensor-based study on the environmental determinants of sleep in older adults.

The residential environment is hypothesized to influence sleep quality within urban settings. Factors associated with the residential environment include air and noise pollution, area socioeconomic status, green and blue spaces, and other neighborhood features. This study seeks to quantify the association of selected environmental factors with sleep quality in the daily lives of 211 older adults residing in the Paris metropolitan area with sensor-based methods. Participants' sleep and physical activity were monitored over a 7-day period using 2 accelerometers. Ecological momentary assessment (EMA) surveys were administered 4 times a day to assess depressive and anxiety symptoms. Environmental factors surrounding participants' residential addresses, including noise and air pollution, walkability, green and blue space availability, median income, and population density, were computed using geoprocessing methods. Hierarchical mixed models with a random intercept at the individual level were fitted to estimate the adjusted association between residential environmental factors and sleep outcomes [total sleep time (TST), sleep efficiency (SE), and wake after sleep onset (WASO)]. Potential effect modification of or mediation by physical activity and depression and anxiety levels were explored in the analyses. We observed an effect size of 1.4 more minutes of sleep for each increase of one thousand euro in neighborhood median income (Confidence Intervals: 0.35, 2.45). The average adjusted difference in total sleep time between the 10th and 90th percentiles of neighborhood median income was 23.6 minutes of sleep. Other environmental factors and depression and anxiety levels did not exhibit correlations with sleep outcomes. The results reveal a positive association between median income at the residential level and TST, while no associations were identified for SE and WASO. In conclusion, these findings underscore the impact of neighborhood socioeconomic status on total sleep time within the context of urban living, highlighting the need for further research.

Unlocking Cognitive Analysis Potential in Alzheimer's Disease Clinical Trials: Investigating Hierarchical Linear Models for Analyzing Novel Measurement Burst Design Data.

Measurement burst designs typically administer brief cognitive tests four times per day for 1 week, resulting in a maximum of 28 data points per week per test for every 6 months. In Alzheimer's disease clinical trials, utilizing measurement burst designs holds great promise for boosting statistical power by collecting huge amount of data. However, appropriate methods for analyzing these complex datasets are not well investigated. Furthermore, the large amount of burst design data also poses tremendous challenges for traditional computational procedures such as SAS mixed or Nlmixed. We propose to analyze burst design data using novel hierarchical linear mixed effects models or hierarchical mixed models for repeated measures. Through simulations and real-world data applications using the novel SAS procedure Hpmixed, we demonstrate these hierarchical models' efficiency over traditional models. Our sample simulation and analysis code can serve as a catalyst to facilitate the methodology development for burst design data.

Abstract 4129075: Racial and Ethnic Differences in Semaglutide Prescriptions in the Veterans Affairs Healthcare System

Introduction: Recent advances in obesity treatment added incretin-based injectables like semaglutide to treatments ranging from lifestyle modification to bariatric surgery. While the burden of obesity in the United States is high and disproportionately affects minoritized individuals, obesity interventions may not be equitably distributed. Insurance coverage is often cited as a barrier to accessing novel treatments. Research Question: Do inequities in semaglutide use among patients with obesity persist without insurance barriers to care? Goals: Characterize the role of race and ethnicity in the receipt of semaglutide among Veterans with obesity. Methods: Among VA patients with BMI ≥27 from 2018-2023, we used a hierarchical multivariable mixed effects logistic regression model to evaluate the association between race and ethnicity (White, Non-Hispanic Black, Hispanic, Asian/Native Hawaiian/Pacific Islander, American Indian/Alaska Native) and receipt of semaglutide prescriptions. We adjusted for age, gender, diabetes status, Charlson Comorbidity Index, education, and urbanicity, with a random effect for diagnosis year. Results: Among Veterans with BMI ≥27 (n=2,423,070), 38.8% had Class I obesity (BMI 30-34.9), 18.2% had Class II obesity (BMI 35-39.9), and 9.8% had Class III obesity (BMI>40), with differences by race and ethnicity (p<0.01). Across the cohort, 184,690 (7.6%) received at least one prescription for semaglutide during the study period. Higher severity of obesity was associated with odds of semaglutide prescription (Figure). Compared to White Non-Hispanic patients, Black and Hispanic/Latino Veterans were less likely to receive a semaglutide prescription, with adjusted odds ratios (AOR) of 0.63 (95% confidence interval [CI]): 0.60-0.68) and 0.81 (95% CI: 0.74-0.90), respectively. Receipt of a semaglutide prescription was also highly associated with diabetes status, with an AOR of 35.2 (95% CI 32.5-38.0) for those with a diagnosis of diabetes compared to those without. Conclusions: Racial and ethnic minority Veterans with obesity are less likely to receive prescriptions for semaglutide in VA, suggesting that challenges to equitable obesity care are more complex than financial coverage alone.

Mediterranean Diet, ultra-processed food consumption and semen quality in healthy young men

Abstract Background Diet quality can have beneficial effects on male reproductive health, although studies are still limited, and little is known on the potential impact of ultra-processed foods (UPFs) on semen quality parameters. Methods A cross-sectional analysis was run on 126 participants (mean age 20.0 ± 1.2 y) from the FAST randomized controlled trial in 2018-2019. Food intake was assessed through a FFQ. UPF was defined following the Nova classification and calculated as the ratio (weight ratio) between UPF (g/d) and total food (g/d). Adherence to the Mediterranean Diet (MD) was ascertained by the Mediterranean Diet Score (MDS). The semen analyses were performed using a microscope for optical evaluation with a Makler counting chamber and two automated semen analysers. The primary outcomes were sperm volume, concentration, motility and morphology. A hierarchical mixed model approach was utilized to accommodate the within-subject correlation arising from the triple temporal repetition of measurements. Results Highest UPF consumption (Q4), compared to lowest (Q1), was associated with lower sperm concentration (β=-54.1×106 spz./ml; 95%CI: -92.9 to -15.4; p-trend=0.002 across quarters), and progressive motility (β=-14.2%; 95%CI: -28.2 to -0.09; p-trend=0.036). The percentage of cells with normal morphology tended to be reduced in young men consuming more UPF compared to lowest intake (β=-2.93%; 95%CI: -6.22 to 0.37; p-trend=0.071). The MDS was not associated with any of the parameters under study. Conclusions A larger dietary share of UPF was inversely associated with sperm concentration and progressive motility in young men of reproductive age. MD adherence was not associated with semen quality parameters, and this is possibly due to the low variability of MD adherence in this sample. Dietary recommendations for improving sperm health should prioritize limiting UPF in the diet. Key messages • Ultra-processed food (UPF) intake was unfavourably associated with semen quality parameters amongst young men. • Dietary recommendations for improving sperm health should recommend limiting UPF.

Association of social support and health status outcomes in peripheral artery disease

ObjectiveA critical goal in the care of patients with peripheral artery disease (PAD) is to optimize their health status; that is, their symptoms, function, and quality of life. Social support has been proposed to be a predictor of disease-specific health status in patients with PAD. However, the prevalence of low perceived social support, the association with health status outcomes, and the interaction with other biopsychosocial variables, is unknown. Our aim was to assess the association of baseline perceived social support with health status at 12 months in patients with PAD. MethodsThe Patient-Centered Outcomes Related Treatment Practices in Peripheral Arterial Disease: Investigating Trajectories (PORTRAIT) registry, which enrolled patients with PAD in the United States, the Netherlands, and Australia from 2011 to 2015, was used. Perceived social support was assessed at baseline with the Enhancing Recovery in Coronary Heart Disease Patients (ENRICHD) Social Support Inventory (ESSI), and disease-specific (Peripheral Artery Disease Questionnaire [PAQ]) and generic health status (Euro-Quality of Life Visual Analog Scale [VAS] and EQ-5D-3L Index) questionnaires were assessed at baseline and 12 months. Low social support was defined as a score of ≤3 on two items and an ESSI score of ≤18. A hierarchical mixed level linear regression model adjusting for biopsychosocial variables was used to assess the association between low perceived social support and the ESSI score with health status at 12 months. ResultsA total of 949 patients were included (mean age, 67.64 ± 9.32 years; 37.9% female), with low social support being present in 18.2%. Patients with low social support were more likely to not be married or to be living alone (50.0% vs 77.5%; P < .001); have more financial constraints; have more depressive, stress, and anxiety symptoms; and have lower disease-specific and generic health status at baseline and at 12 months. In the unadjusted model, low social support was associated with a −7.02 (95% confidence interval [CI], −10.97 to −3.07) point reduction in the PAQ, −7.43 (95% CI, −10.33 to −4.54) in the VAS, and −0.06 (95% CI, −0.09 to −0.03) in the EQ-5D-3L Index. Adjusting for biopsychosocial factors minimally attenuated these associations (PAQ: −6.52; 95% CI, −10.55 to −2.49; P = .002; VAS: −5.39; 95% CI, 8.36 to −2.42; P < .001; EQ-5D-3L Index: −0.04; 95% CI, −0.07 to 0.01; P = .022). The ESSI per-point score was associated with a decrease of 0.51 (95% CI, 0.18-0.85; P = .003) in PAQ and 0.46 (95% CI, 0.12-0.61; P = .004) in the VAS. ConclusionsAmong patients with PAD, low social support was frequent and associated with a lower health status at 1 year independent of other biopsychosocial variables. Improving social support could improve health status and outcomes in PAD.

Perioperative Transfusion Practices in Adults Having Noncardiac Surgery

Surgical patients are often transfused to manage bleeding and anemia. Best practices for red blood cell (RBC) transfusion administration in patient having noncardiac surgery remains controversial and a robust evaluation and description of perioperative transfusion practices is lacking. We characterized perioperative hemoglobin concentrations and transfusion practices from the prospective VISION cohort which included 39,222 patients aged ≥45 years who had inpatient noncardiac surgery. Variations in transfusion practices were analyzed using hierarchical mixed models, and associations with mortality and complications were evaluated using a nested frailty survival model. Within the cohort, 16.1% (n = 6296) were given perioperative RBC transfusions, with the fraction declining from 20% to 13% over the 6-year study period. The proportion of patients transfused varied by surgery type from 6.4% for low-risk operations (i.e., minor surgery) to 31.5% for orthopedic surgeries. Variations were largely associated with patient hemoglobin concentrations, but also with center (range: 3.7%-27.3%) and country (0.4%-25.3%). Even after adjusting for baseline hemoglobin, comorbidities and type of surgery, both center and country were significant sources of variation in transfusion practices. Among transfused participants, 60.4% (n = 3728/6170) had at least 1 hemoglobin concentration ≤80g/L and 86.0% (n = 5305/6170) had at least 1 hemoglobin concentration ≤90g/L, suggesting that relatively restrictive transfusion strategies were used in most. The proportion of patients receiving at least 1 RBC transfusion declined from 20% to 13% over 6 years. However, there was considerable unexplained variation in transfusion practices.

Alcohol home delivery usage and its relationship to alcohol consumption in New South Wales during COVID-19

Background: Rapid growth in the use of alcohol home delivery services, combined with increases in home drinking during COVID-19, raises potential concerns around increased consumption. This paper aims to assess the relationship between alcohol home delivery use and consumption across levels of COVID-19 restrictions in New South Wales (NSW), Australia. Methods: A 5-wave longitudinal survey of 586 NSW residents (Mage = 35; 65.3% female) conveniently sampled across 2020. Home delivery usage and the number of daily standard drinks consumed during a typical week were assessed with a survey. Logistic regression models were estimated within each wave to identify predictors of home delivery usage, and hierarchical logistic mixed effects models were estimated to predict purchase source (home delivery vs other) at the occasion level. Results: From baseline, alcohol home delivery use rose significantly during lockdown (20% to 34%), with respondents using home delivery during lockdown and the partial re-opening wave consuming significantly more than those who were not. Use of home delivery was significantly higher during lockdown and the partial re-opening amongst people who drank more heavily, with respondents aged 36 or older more likely to use delivery services in all waves except lockdown. Conclusions: Alcohol home delivery usage increased during lockdown suggesting restrictions impeding on-premise consumption coincided with an increase in home delivery. Associations between persons who drink more heavily and use of home delivery during lockdown and the partial re-opening suggest a subset of the population that may be at increased risk of harmful consumption when accessing alcohol delivery services.

Predictors of Psychological Well-Being and Quality of Life in Patients with Hypertension: A Longitudinal Study.

Previous research has highlighted the positive impact of greater health-related quality of life (Hr-QoL) and subjective well-being (SWB) on chronic diseases' severity and progression. There is a paucity of studies investigating the long-term trajectories of these variables among hypertensive patients. The present study aims to investigate the relationships between psychological variables (Type A and D personality, locus of control-LoC, self-esteem, and trait anxiety) with SWB and Hr-QoL in patients with hypertension and comorbid metabolic syndrome. A total of 185 volunteer patients (130 males, 70.3%; mean age 54 ± 10.93) were enrolled. Patients filled out measures of Hr-QoL and SWB, LoC, and self-esteem at three time points-Type A and D behaviors and anxiety measures only at baseline. Analyses were run through two-level hierarchical mixed models with repeated measures (Level 1) nested within participants (Level 2), controlling for sociodemographic and clinical confounders. Neither Hr-QoL nor SWB changed over time. Patients with greater self-esteem and internal LoC (and lower external LoC) increased their SWB and Hr-QoL up to 1-year follow-up. A greater Type A behavior and trait anxiety at baseline predicted a longitudinal increase in most of the dependent variables. Results suggest that it could be useful to tailor interventions targeting specific variables to increase Hr-QoL and SWB among hypertensive patients.

Urban environment influences on stress, autonomic reactivity and circadian rhythm: protocol for an ambulatory study of mental health and sleep.

Converging evidence suggests that urban living is associated with an increased likelihood of developing mental health and sleep problems. Although these aspects have been investigated in separate streams of research, stress, autonomic reactivity and circadian misalignment can be hypothesized to play a prominent role in the causal pathways underlining the complex relationship between the urban environment and these two health dimensions. This study aims at quantifying the momentary impact of environmental stressors on increased autonomic reactivity and circadian rhythm, and thereby on mood and anxiety symptoms and sleep quality in the context of everyday urban living. The present article reports the protocol for a feasibility study that aims at assessing the daily environmental and mobility exposures of 40 participants from the urban area of Jerusalem over 7 days. Every participant will carry a set of wearable sensors while being tracked through space and time with GPS receivers. Skin conductance and heart rate variability will be tracked to monitor participants' stress responses and autonomic reactivity, whereas electroencephalographic signal will be used for sleep quality tracking. Light exposure, actigraphy and skin temperature will be used for ambulatory circadian monitoring. Geographically explicit ecological momentary assessment (GEMA) will be used to assess participants' perception of the environment, mood and anxiety symptoms, sleep quality and vitality. For each outcome variable (sleep quality and mental health), hierarchical mixed models including random effects at the individual level will be used. In a separate analysis, to control for potential unobserved individual-level confounders, a fixed effect at the individual level will be specified for case-crossover analyses (comparing each participant to oneself). Recent developments in wearable sensing methods, as employed in our study or with even more advanced methods reviewed in the Discussion, make it possible to gather information on the functioning of neuro-endocrine and circadian systems in a real-world context as a way to investigate the complex interactions between environmental exposures, behavior and health. Our work aims to provide evidence on the health effects of urban stressors and circadian disruptors to inspire potential interventions, municipal policies and urban planning schemes aimed at addressing those factors.

The prevalence of gestational syphilis in Malawi between 2014 and 2022: spatiotemporal modeling of population-level factors.

Mother-to-child transmission of syphilis remains high especially in the WHO AFRO region with a prevalence of 1.62%, resulting in a congenital syphilis rate of 1,119 per 100,000 live births. Elimination efforts can be supported by an understanding of the spatial and temporal changes in disease over time, which can identify priority areas for targeted interventions aimed at reducing transmission. We collated routine surveillance data from health facilities and covariate data from demographic and health surveys conducted in Malawi between 2014 and 2022. We fitted a Bayesian hierarchical mixed model with spatial and temporally structured random effects to model the district-level monthly counts of maternal syphilis notifications as a function of individual- and district-level predictors. We then generated district-level spatiotemporally explicit risk profiles to estimate the effect of individual- and district-level covariates on maternal syphilis notifications and to identify hotspot areas. Overall, the national prevalence of maternal syphilis increased from 0.28% (95% CI: 0.27-0.29%) in 2014 to peaking in 2021 at 1.92% (95% CI: 1.89-1.96%). Between 2020 and 2022, there was a decline in prevalence, with the most significant decline seen in Zomba District (1.40, 95% CI: 1.12-1.66%). In regression models, a one percentage point increase in district-level antenatal HIV prevalence was associated with increased maternal syphilis (prevalence ratio [PR]: 1.15, 95% credible interval [CrI]: 1.10-1.21). There was also an increased prevalence of maternal syphilis associated with an increased district-level mean number of sex partners (PR: 1.05, 95% CrI: 0.80-1.37). The number of districts with a high prevalence of maternal syphilis also increased between 2014 and 2022, especially in the southern region, where most had a high probability (approaching 100%) of having high maternal syphilis (defined as relative risk >1 compared to the standard population of women aged 15-49 years) in 2022. Maternal syphilis prevalence in Malawi shows an increasing upward trend, with an estimated six times relative increase between 2014 and 2022 (0.28% to 1.73%) and strong associations with higher district-level HIV prevalence. Controlling syphilis depends on reaching vulnerable populations at the sub-national level, which may be disproportionately affected. Our findings support the move to integrate the elimination of mother-to-child transmission (EMTCT) of syphilis programs with existing prevention of mother-to-child transmission (PMTCT) of HIV programs.

Effect of an 18-Month Walking Intervention on the Rest-Activity Rhythm of Older Adults With Mild-Moderate Dementia.

The objective of this 18-month walking intervention was to evaluate the effect on rest-activity rhythm (RAR) for older adults with mild-to-moderate dementia (65.8% female; aged M = 82.4 [SD = 6.5]). The intervention group (n = 44) was intended to walk 30min, five times per week for 18months. The control group (n = 35) received sedentary activities or usual care. RAR was measured at baseline to after 18 months and five times in between actigraphy outcome variables (interdaily stability, intradaily variability, relative amplitude, activity 10 most active hours, and activity 5 least active hours). Hierarchical mixed model analyses revealed no significant intervention effects (with or without baseline confounders as covariate) on RAR. However, participants in the intervention group were able to significantly increase their daily life activity (activity 10 most active hours) from the onset of the preceding measurement, b = 0.10, t(239.32) = 2.36, p = .019. More research is warranted to study the effect of regular walks on older persons with dementia whose RAR is worst at baseline.

Farm forests, seasonal hunger, and biomass poverty: Evidence of induced intensification from panel data in the Ethiopian Highlands

Seasonal hunger is the most common food insecurity experience for millions of small dryland farmers. This study tests the relationships between food insecurity, farm forests, and biomass poverty using a longitudinal dataset from the Amhara region of Ethiopia. These data form part of the Ethiopia Socioeconomic Survey, which collected panel data over three survey rounds from 530 households between 2011 and 2016. This dataset represents a collection of unique socioeconomic, wellbeing, and micro-land use measures, including farm forests. Hierarchical mixed effect regression models assessed the relationship between food insecurity and farm forests as well as the conditional effects of biomass poverty among the poorest farmers and women-headed households. Over a six-year study period, farmers reported increased stress from smaller land holdings, higher prices, and climate-related shocks. A clear trend towards spontaneous dispersed afforestation is observed by both researchers and satellite remote sensing. Model results indicate, dedicating approximately 10% of farm area to forest reduces months of food insecurity by half. The greatest reductions in food insecurity from farm forests are reported by ultra-poor and crop residue-burning households, suggesting that biomass poverty may be a major constraint to resilient food security on these farms. This research provides novel quantitative evidence of induced intensification and food security impacts of farm management preserving and building stores of biomass value as green assets. The results reported here have important implications for nature-based solutions as a major strategy to achieve sustainable development in some contexts.

Unraveling the relationship between heart rate and agitation in people with dementia

AbstractBackgroundAgitation is a critical behavioral and psychological symptom of dementia, leading alone to increased caregiver burden, more frequent hospitalization, and earlier institutionalization. The results presented here provide preliminary insights into one facet of multimodal agitation detection, specifically analyzing the relationship between heart rate and agitation.MethodTo date, 26 people with dementia have been included in our study to detect agitation using a multimodal approach1. In this analysis, heart rate is derived from the wristwatch wearable measuring photoplethysmography (PPG). Data points were included in subsequent analysis if the signal quality index of the original PPG signal was &gt; = 0.8 (on a scale from 0‐1). For each complete survey, the mean heart rate (HR) was extracted from 1‐minute intervals in a 6‐minute window centered on the survey timestamp (± 3 minutes). For each mean HR per minute, the presence or absence of agitation was derived from the Pittsburgh Agitation Scale integrated into the survey. The data was centered within‐patient. Due to the nested structure of the data, hierarchical mixed models were used to predict presence of agitation as a binary response variable.ResultThe resulting dataset of high‐quality HR data consists of 1286 data points, from 21 patients (Age mean: 81 (8.3), nfemale: 8) The 3‐parameter model built included mean heart rate as an explanatory fixed effect, and two random intercepts: day and patient. In the model, increased HR compared to a participant’s average HR over a week, was significantly associated with an increase in odds of agitation (p&lt; 0.001). Every 1 beat increase in mean HR over a minute, from the participants’ mean heart rate, increased the odds of that 1‐minute interval indicating agitation by 7.68% (CI: 5.43‐10.1).ConclusionThese results provide insight into the relationship between heart rate and agitation, possibly indicating activation of the autonomic nervous system, due to the association of increased HR with increased odds of agitation. Analyses like these provide the basis for future agitation detection algorithms that account for a multi‐faceted patient response.1. Davidoff, et al, 2022, Innovation in Aging, Volume 6, Issue 7, 2022, igac064, https://doi.org/10.1093/geroni/igac064

Quantifying climatic and socioeconomic drivers of urban malaria in Surat, India: a statistical spatiotemporal modelling study

Cities are becoming increasingly important habitats for mosquito vectors of disease. The pronounced heterogeneity of urban landscapes challenges our understanding of the effects of climate and socioeconomic factors on mosquito-borne disease dynamics at different spatiotemporal scales. Here, we quantify the impact of climatic and socioeconomic factors on urban malaria risk, using an extensive dataset in both space and time for reported Plasmodium falciparum cases in the city of Surat, northwest India. We analysed 10 years of monthly P falciparum cases resolved at three nested spatial resolutions (seven zones, 32 units, and 478 worker units) with a Bayesian hierarchical mixed model that incorporates the effects of population density, poverty, relative humidity, and temperature, in addition to random effects (structured and unstructured). To reduce dimensionality and avoid correlation of covariates, socioeconomic variables from survey data were summarised into main axes of variation using principal component analysis. With model selection, we identified the main drivers of spatiotemporal variation in malaria incidence rates at each of the three spatial resolutions. We also compared observations to model-fitted cases by quantifying the percentage of predictions within five discrete levels of malaria risk. The spatial variation of urban malaria cases was stationary over time, whereby locations with high and low yearly cases remained largely consistent across years. Local socioeconomic variation could be summarised with three principal components accounting for approximately 80% of the variance. The model that incorporated local temperature and relative humidity together with two of these principal components, largely representing population density and poverty, best explained monthly malaria patterns in models formulated at the three different spatial scales. As model resolution increased, the effect size of humidity decreased, whereas those of temperature and the principal component associated with population density increased. Model predictions accurately captured aggregated total monthly cases for the city; in space-time, they more closely matched observations at the intermediate scale, with around 57% of units estimated to fall in the observed category on average across years. The mean absolute error was lower at the intermediate level, showing that this is the best aggregation level to predict the space-time dynamics of malaria incidence rates across the city with the selected model. This statistical modelling framework provides a basis for development of a climate-driven early warning system for urban malaria for the units of Surat, including spatially explicit prediction of malaria risk several weeks to months in advance. Results indicate environmental and socioeconomic covariates for which further measurement at high resolution should lead to model improvement. Advanced warning combined with local surveillance and knowledge of disease hotspots within the city could inform targeted intervention as part of urban malaria elimination efforts. US National Institutes of Health.

Preferences for Living Arrangements in Dementia: A Discrete Choice Experiment.

Dementia affects about 55 million people worldwide. Demographic change and shifting lifestyles challenge the organization of dementia care. A discrete choice experiment (DCE) was conducted to elicit preferences for living arrangements in dementia in urban and rural regions of Germany. Preliminary work included review of previous literature and focus groups. The DCE consists of seven attributes (group size, staff qualifications, organization of care, activities offered, support of religious practice, access to garden, consideration of food preferences) with three levels each. Individuals from the general population between the ages of 50 and 65years were identified through population registration offices in three rural municipalities and one urban area, and 4390 individuals were approached via postal survey. A hierarchical Bayesian mixed logit model was estimated and interactions with sociodemographic characteristics were investigated. A total of 428 and 412 questionnaires were returned by rural and urban respondents, respectively. Access to a garden was perceived as the most important attribute (average importance 36.0% in the rural sample and 33.4% in the urban sample), followed by consideration of food preferences (15.8%, 17.8%), staff qualification (14.6%, 15.3%), care organization (11.4%, 12.3%), group size (12.2%, 11.1%), and range of activities (8.0%, 10.1%). The attribute relating to religious practice was given the least importance (2.1%, 0%). Preferences vary according to gender, age, religious beliefs, experience as an informal caregiver, and migrant background. Heterogeneous preferences for living arrangements for people with dementia were identified. The expansion of concepts with access to natural environments for persons with dementia might be a viable option for the formal care market in Germany. Further research is needed to meet the challenges of setting up and designing innovative living arrangements for people with dementia. Preferences vary by gender, age, religious beliefs, experience as an informal caregiver, and migrant background.

COVID-19 and Grade Inflation: Analysis of Undergraduate GPAs During the Pandemic

The COVID-19 pandemic required adaptation to a new learning environment creating challenges for students and instructors. A reduction in student-teacher contact and the lack of supervision should have led to a decline in students’ academic performance. Nonetheless, studies report increases in grades during the pandemic. Yet, limited information is available regarding the persistence of this impact. This study utilizes a hierarchical mixed effect model to estimate the impact of the COVID-19 pandemic on university grades. Using unique class-level data containing chronological variables and institutional, instructor, and student characteristics, spanning Fall 2010 to Spring 2021 of 7,852 undergraduate classes, it is shown class average grade point averages (GPAs) in the College of Agriculture at Texas A&amp;M University increased for the three semesters most impacted by COVID-19. Average class GPAs increased by 0.22 points in Spring 2020 because of COVID-19 and then approximately 0.18 points in the subsequent next two semesters. The negative effect of class size decreased during COVID-19, implying online classes have different size effects than traditional classes. Additionally, the positive effect of SAT scores on grades decreased. One implication of this study is that COVID-19 may not only have a direct, significant, impact on GPAs but may also indirectly affect GPAs through altering the effects of variables on GPAs. The causal mechanisms by which the changes occurred are an area for further research. JEL Codes: I21, I29

Forest management, forest vegetation, and climate influence nesting ecology of a focal bird species in the western USA

Landscape-scale forest restoration aims to restore ecological structure and function and provide habitat for wildlife. However, forest management likely has varying impacts across wildlife life stages, with consequences for population persistence. Using 10 years of nest (n = 294) survey data for a focal bird species, white-headed woodpecker (Dryobates albolarvatus), we assessed how forest management (tree removal and prescribed burning) at two spatial scales (stand [2.25 ha] and landscape [314 ha]), forest vegetation variables at three spatial scales (nest tree, local [0.4 ha], and landscape [314 ha]), and climate influenced nest initiation date, egg production, egg survival, and nestling survival. We applied Bayesian hierarchical mixed effects models to these data to identify and compare drivers at each life stage. None of the variables we considered influenced egg production; white-headed woodpeckers laid an average of four eggs. As the extent of the landscape with tree removal increased, nests initiated later. Egg survival was higher in nests with prescribed burning at the stand scale. Nestling survival was higher in sites that had been managed with burning and tree removal at the stand scale, but the relationship with burning switched to negative at the landscape scale. Only nestling survival was shaped by attributes of the nest cavity itself. Egg survival increased with increased variation in forest patch sizes at the landscape scale. Woodpeckers initiated nests earlier under warmer conditions, with previous August and September temperatures being particularly influential. Both egg and nestling survival increased with cumulative precipitation. While increased temperatures decreased egg survival, nestling survival peaked at an optimal maximum temperature (∼32 °C). This study illustrates how forest management, forest vegetation, and climate factors affecting nesting ecology vary throughout the nesting season. Additionally, effects that switch directions (positive versus negative) across spatial scales indicate spatially dependent ecological processes (e.g., nest suitability versus adult foraging). This study provides a model for assessing the effects of forest management on bird population persistence by considering the nesting season as stages with distinct ecological limitations linked to spatially-dependent factors.

Fast Methods for Posterior Inference of Two-Group Normal-Normal Models

We describe a class of algorithms for evaluating posterior moments of certain Bayesian linear regression models with a normal likelihood and a normal prior on the regression coefficients. The proposed methods can be used for hierarchical mixed effects models with partial pooling over one group of predictors, as well as random effects models with partial pooling over two groups of predictors. We demonstrate the performance of the methods on two applications, one involving U.S. opinion polls and one involving the modeling of COVID-19 outbreaks in Israel using survey data. The algorithms involve analytical marginalization of regression coefficients followed by numerical integration of the remaining low-dimensional density. The dominant cost of the algorithms is an eigendecomposition computed once for each value of the outside parameter of integration. Our approach drastically reduces run times compared to state-of-the-art Markov chain Monte Carlo (MCMC) algorithms. The latter, in addition to being computationally expensive, can also be difficult to tune when applied to hierarchical models.

Investigation of commonly used aortic aneurysm growth rate metrics: Comparing their suitability for clinical and research applications.

An aneurysm is a pathological widening of a blood vessel. Aneurysms of the aorta are often asymptomatic until they rupture, killing approximately 10,000 Americans per year. Fortunately, rupture can be prevented through early detection and surgical repair. However, surgical risk outweighs rupture risk for small aortic aneurysms, necessitating a policy of surveillance. Understanding the growth rate of aneurysms is essential for determining appropriate surveillance windows. Further, identifying risk factors for fast growth can help identify potential interventions. However, studies in the literature have applied many different methods for defining the growth rate of abdominal aortic aneurysms. It is unclear which of these methods is most accurate and clinically meaningful, and whether these heterogeneous methodologies may have contributed to the varied results reported in the literature. To help future researchers best plan their studies and to help clinicians interpret existing studies, we compared five different models of aneurysmal growth rate. We examined their noise tolerance, temporal bias, predictive accuracy, and statistical power to detect risk factors. We found that hierarchical mixed effects models were more noise tolerant than traditional, unpooled models. We also found that linear models were sensitive to temporal bias, assigning lower growth rates to aneurysms that were detected earlier in their course. Our exponential mixed model was noise-tolerant, resistant to temporal bias, and detected the greatest number of clinical risk factors. We conclude that exponential mixed models may be optimal for large studies. Because our results suggest that choice of method can materially impact a study's findings, we recommend that future studies clearly state the method used and demonstrate its appropriateness.

Haemoglobin diagnostic cut-offs for anaemia in Indian women of reproductive age.

The persistent high prevalence of anaemia among Indian women of reproductive age (WRA) despite aggressive long-term iron supplementation could be related to over-diagnosis from an inappropriately high haemoglobin (Hb) diagnostic cut-off. To develop an appropriate cut-off for Indian WRA, we hypothesized that during iron-folic acid (IFA) supplementation to a mixed (anaemic/non-anaemic) WRA population, the positive slope of the Hb-plasma ferritin (PF) response in anaemic women would inflect into a plateau (zero-response) as a non-anaemic status is reached. The 2.5th percentile of the Hb distribution at this inflection point will be the diagnostic Hb cut-off for iron-responsive anaemia. A hierarchical mixed effects model, with a polynomial mean and variance model to account for intraclass correlation due to repeated measures, was used to estimate the response curve of Hb to PF, or body iron stores, in anaemic and non-anaemic WRA (without inflammation), who were receiving a 90-day IFA supplementation. The Hb response curve at low PF values showed a steep increase, which inflected into a plateau at a PF of 10.1 µg/L and attained a steady state at a PF of 20.6 µg/L. The Hb distribution at the inflection was a normal probability distribution, with a mean of 12.3 g/dL. The 2.5th percentile value of this distribution, or the putative diagnostic Hb cut-off for anaemia, was 10.8 g/dL (~11 g/dL). The derived Hb cut-off is lower than the current adult values of 12 g/dL and could partly explain the persistently high prevalence of anaemia.