Variance Estimation Research Articles

A bootstrap-based approach to combine individual-based forest growth models and remotely sensed data

Abstract Combining forest growth models with remotely sensed data is possible under a generalized hierarchical model-based (GHMB) inferential framework. This implies the existence of two submodels: the growth model itself ($\mathcal{M}_{1}$) and a second submodel that links the growth predictions to some remotely sensed variables ($\mathcal{M}_{2}$). Analytical GHMB estimators are available to fit submodel $\mathcal{M}_{2}$ and account for the uncertainty stemming from submodel $\mathcal{M}_{1}$, i.e. the growth model. However, when the growth model is individual based, it is usually too complex to be differentiated with respect to its parameters. As a result, the analytical GHMB estimators cannot be used. In this study, we developed a bootstrap approach for the GHMB inferential framework in order to combine individual-based forest growth models with remotely sensed data. Through simulation studies, we showed that the bootstrap estimators were nearly unbiased when both submodels were linear. The estimator of the parameter estimates remained nearly unbiased when submodel $\mathcal{M}_{1}$ became complex, i.e. non-differentiable, and submodel $\mathcal{M}_{2}$ was nonlinear with heterogeneous variances and correlated error terms. The variance estimator showed some biases but these were relatively small. We further demonstrated through a real-world case study that the predictions of a complex individual-based model could be linked to a Landsat-8 near-infrared spectral band in the boreal forest zone of Quebec, Canada.

Understanding the Consequences of Collinearity for Multilevel Models: The Importance of Disaggregation Across Levels

In multilevel models, disaggregating predictors into level-specific parts (typically accomplished via centering) benefits parameter estimates and their interpretations. However, the importance of level-specificity has been sparsely addressed in multilevel literature concerning collinearity. In this study, we develop novel insights into the interactivity of centering and collinearity in multilevel models. After integrating the broad literatures on centering and collinearity, we review level-specific and conflated correlations in multilevel data. Next, by deriving formal relationships between predictor collinearity and multilevel model estimates, we demonstrate how the consequences of collinearity change across different centering specifications and identify data characteristics that may exacerbate or mitigate those consequences. We show that when all or some level-1 predictors are uncentered, slope estimates can be greatly biased by collinearity. Disaggregation of all predictors eliminates the possibility that fixed effect estimates will be biased due to collinearity alone; however, under some data conditions, collinearity is associated with biased standard errors and random effect (co)variance estimates. Finally, we illustrate the importance of disaggregation for diagnosing collinearity in multilevel data and provide recommendations for the use of level-specific collinearity diagnostics. Overall, the necessity of disaggregation for identifying and managing collinearity’s consequences in multilevel models is clarified in novel ways.

Time variation of high-risk groups for liver function deteriorations within fluctuating long-term liver function after hepatic radiotherapy in patients with hepatocellular carcinoma

PurposeThe purpose of this study is to find essential risk factors associated with liver function (LF) deteriorations within fluctuating long-term LF and their time-varying effects in patients with hepatocellular carcinoma (HCC) receiving hepatic radiotherapy and to identify high-risk groups for adverse LF deteriorations and their changes over time in facilitating the prevention of hepatic decompensation and the improvement of survival.Materials and methodsA total of 133 HCC patients treated by hepatic radiotherapy were enrolled. A study design was conducted to convert posttreatment long-term LF with fluctuating levels over time to recurrent LF events using defined upgrades in a grading scale. The hazard ratios (HR) of pretreatment biochemical, demographic, clinical, and dosimetric factors in developing posttreatment LF events were estimated using the Cox model. Methodologies of the counting process approach, robust variance estimation, goodness-of-fit testing based on the Schoenfeld residuals, and time-dependent covariates in survival analysis were employed to handle the correlation within subjects and evaluate the time-varying effects during long-term follow-up.ResultsBaseline LF score before radiotherapy and gender were significant factors. Initial HR in developing LF events was 1.17 (95% CI 1.11–1.23; P < 0.001) for each increase of baseline LF score and kept almost constant over time (HR, 1.00; 95% CI 1.00–1.01; P = 0.065). However, no difference was observed regarding initial hazards for gender (HR, 1.00; 95% CI 0.64–1.56; P = 0.994), but the hazard for women got higher monthly over time compared with men (HR, 1.04; 95% CI 1.01–1.07; P = 0.006).ConclusionsHigh-risk groups for adverse LF deteriorations after hepatic radiotherapy may change over time. Patients with poor baseline LF are vulnerable from the beginning. Women require prevention strategies and careful monitoring for deteriorations at a later stage.

Rescaling bootstrap variance estimation technique under dual frame surveys with unknown domain sizes

Dual frame (DF) surveys are a special case of multiple frame (MF) surveys considering two frames covering the entire population. Dual frame surveys are applicable in those situations, where, one frame may cover the entire population but is very expensive to sample; so an alternate frame may be available that does not cover the entire population but is easily available. Unbiased variance estimation in dual frame surveys can be difficult and complicated than corresponding estimators under single frame surveys. Again, the variance of dual frame estimator involves population variances of the individual domains which are generally unknown. Due to this reason, obtaining an unbiased estimate of the variance of the dual frame estimator is quite complex in the case of dual frame surveys. In this article, we propose a Post-stratified Rescaling Bootstrap with Unknown Domain size (PstRBUD) method for variance estimation of the dual frame estimator of population total. The proposed rescaled bootstrap method was compared to that of standard bootstrap methods in simulation analysis. The proposed PstRBUD method provides an unbiased estimation of the variance of the dual frame estimator of population total, according to simulation results.

A general class of improved population variance estimators under non-sampling errors using calibrated weights in stratified sampling.

This paper proposes a new calibration estimator for population variance within a stratified two-phase sampling design. It takes into account random non-response and measurement errors, specifically applying this method to estimate the variance in Gas turbine exhaust pressure data. The study integrates additional information from two highly positively correlated auxiliary variables to develop a general class of estimators tailored for the stratified two-phase sampling scheme. The properties of these estimators, in terms of their biases and mean square errors, have been thoroughly examined and extensively analyzed through numerical and simulation studies. Furthermore, the calibrated weights of the strata are derived. The proposed estimators outperform the natural estimator of population variance. Finally, suitable recommendations have been made for survey statisticians intending to apply these findings to real-life problems.

On the failure of the bootstrap for Chatterjee’s rank correlation

Abstract While researchers commonly use the bootstrap to quantify the uncertainty of an estimator, it has been noticed that the standard bootstrap, in general, does not work for Chatterjee’s rank correlation. In this paper, we provide proof of this issue under an additional independence assumption, and complement our theory with simulation evidence for general settings. Chatterjee’s rank correlation thus falls into a category of statistics that are asymptotically normal, but bootstrap inconsistent. Valid inferential methods in this case are Chatterjee’s original proposal for testing independence and the analytic asymptotic variance estimator of Lin &amp; Han (2022) for more general purposes. [Received on 5 April 2023. Editorial decision on 10 January 2024]

Asymptotically constant risk estimator of the time-average variance constant

Summary Estimation of the time-average variance constant is important for statistical analyses involving dependent data. This problem is difficult as it relies on a bandwidth parameter. Specifically, the optimal choices of the bandwidths of all existing estimators depend on the estimand itself and another unknown parameter that is very difficult to estimate. Thus, optimal variance estimation is unachievable. In this paper, we introduce a concept of converging flat-top kernels for constructing variance estimators whose optimal bandwidths are free of unknown parameters asymptotically and hence can be computed easily. We prove that the new estimator has an asymptotically constant risk and is locally asymptotically minimax.

The estimation of additive genetic variance of body size in a wild passerine is sensitive to the method used to estimate relatedness among the individuals.

Assessing additive genetic variance is a crucial step in predicting the evolutionary response of a target trait. However, the estimated genetic variance may be sensitive to the methodology used, e.g., the way relatedness is assessed among the individuals, especially in wild populations where social pedigrees can be inaccurate. To investigate this possibility, we investigated the additive genetic variance in tarsus length, a major proxy of skeletal body size in birds. The model species was the collared flycatcher (Ficedula albicollis), a socially monogamous but genetically polygamous migratory passerine. We used two relatedness matrices to estimate the genetic variance: (1) based solely on social links and (2) a genetic similarity matrix based on a large array of single-nucleotide polymorphisms (SNPs). Depending on the relatedness matrix considered, we found moderate to high additive genetic variance and heritability estimates for tarsus length. In particular, the heritability estimates were higher when obtained with the genetic similarity matrix instead of the social pedigree. Our results confirm the potential for this crucial trait to respond to selection and highlight methodological concerns when calculating additive genetic variance and heritability in phenotypic traits. We conclude that using a social pedigree instead of a genetic similarity matrix to estimate relatedness among individuals in a genetically polygamous wild population may significantly deflate the estimates of additive genetic variation.

Abstract WP242: Acute Ischemic Stroke With Atrial Fibrillation: Relation Between ω3/ω6 Poly Unsaturated Fatty Acids

Background &amp; Aims: Some poly unsaturated fatty acids (PUFA) are said to be associated with the development of atrial fibrillation (AF). Our aim is to elucidate the relation between PUFA and AF in acute ischemic stroke. Methods: Consecutive patients with ischemic stroke admitted between October 2012 and February 2022 were retrospectively screened. The inclusion criteria were as follows: 1) onset to door time within 7 days; and 2) availability of PUFA measurements from the day of the hospital visit or the next day. Plasma levels of PUFA, including eicosapentaenoic acid (ω3: EPA) docosahexaenoic acid (ω3: DHA), dihomo-γ-linolenic acid (ω6: DGLA), and arachidonic acids (ω6: AA), were assayed by gas chromatography. We investigated the association between each of PUFA levels and AF among the acute ischemic stroke patients. Results: We screened 2,122 consecutive ischemic stroke patients. Of them, 1,574 were identified (1,119 [71%] males, median age 69 years). In Poisson regression analysis with a robust variance estimator, factors associated with AF were lower DGLA level (prevalence ration (PR) 0.885, 95% CI 0.811 to 0.966, p = 0.006), lower AA level (PR 0.797, 95% CI 0.649 to 0.978, p = 0.029), and higher EPA/AA ratio (PR 1.353, 95% CI 1.036 to 1.766, p = 0.026). In Poisson regression analysis with a robust variance estimator for AF using PUFA quartile as indicator variables, negative linear trends were observed between the quartile of DGLA (Quartile 1: PR 1.884, Quartile 2: PR 1.530, Quartile 3: PR 1.429, Quartile 4: reference) and AA (Quartile 1: PR 1.499, Quartile 2: PR 1.199, Quartile 3: PR 1.137, Quartile 4: reference), and a positive linear trend between the quartile of EPA/AA ratio (Quartile 1: reference, Quartile 2: PR 1.544, Quartile 3: PR 1.629, Quartile 4: PR 1.781, Figure). Conclusions: In acute ischemic stroke, lower ω6 level and higher ω3/ω6 ratio were associated with the presence of AF. ω3/ω6 PUFA may have contrasting effects on the incidence of AF in acute ischemic stroke.

Abstract TMP72: Impaired Perfusion Predicts Early Recurrence in Symptomatic Intracranial Atherosclerosis

Background: Intracranial Atherosclerosis (ICAS) leads to stroke by perforator disease, artery to artery embolism, and impaired distal flow/perfusion. While medical treatment is likely to stabilize atherosclerotic plaques, it is unlikely to improve distal perfusion in the acute setting. We hypothesize that medically treated patients with symptomatic ICAS with impaired perfusion have a high risk of recurrence. Methods: We included hospitalized patients with acute ischemic stroke due to ICAS involving the intracranial ICA, proximal MCA, intracranial vertebral artery, or basilar artery over a 3 year period. Patients were treated with medical treatment and followed for 30-days post stroke. Patients generally underwent perfusion imaging with MRI. The study outcome is recurrent ischemic stroke. We used univariate and multivariable Cox regression analyses to determine the association between risk factors, treatment strategies, perfusion delay at T max 4 sec and 6 sec thresholds. To account for multiple admissions per patient, we used robust variance estimator clustering on individual patients. Results: Over the study period, we identified 96 hospitalizations for symptomatic ICAD over 3 years. The recurrence risk within 30 days was 17.7% (17/96). In univariate analysis, factors associated with recurrent risk at 30 days were lack of dual antiplatelet therapy (47.1% versus 22.8%, P=0.068), increased Tmax perfusion mismatch volume as 6 sec (10[0-51] versus 0[0-0], P=0.008) and at 4 sec (60[37-170] versus 13.5[0-91], P=0.050). Using Youden’s index, we identified cutoffs of 6.5 ml and 35.5 ml for Tmax 6 sec mismatch and Tmax 4 sec mismatch respectively. In Cox regression analyses, only predictors of recurrence were T max 6 sec perfusion mismatch &gt; 6.5 ml (aHR 6.72 95% CI 2.01-22.45 p=0.002) and T max 4 sec perfusion mismatch &gt; 35.5 ml (aHR 5.78 95% CI 1.53-21.81 p=0.010). Dual antiplatelet therapy was not associated with reduced recurrence risk (p&gt;0.05) in all models. Conclusions: Patient with symptomatic ICAS and impaired distal perfusion are at high risk of early recurrence. Studies testing reperfusion should focus on this subgroup and enroll patients early, when the risk of recurrence in medically treated patients is highest and likely driven by reperfusion.

Abstract WP237: Anticoagulant Utilization and Risk of Thromboembolic Events Following Ischemic Stroke Among Adults With Cancer

Rationale: Ischemic stroke and cancer frequently coexist, but there are limited data from population-based cohorts regarding prevalence, risk of subsequent thromboembolic events, and treatments. Methods: We leveraged large-scale healthcare data to assess recurrent thromboembolic events in the 6 months following discharge for ischemic stroke among a nationally representative U.S. population with active cancer. Landmark analyses were undertaken with anticoagulant exposure status based on dispensations in the week following hospital discharge. Adjusted hazard ratios (aHRs) were estimated using Cox proportional hazard models with robust variance estimators to account for clustering within propensity score-matched pairs. Results: Among 86,365 adults discharged after an ischemic stroke between 10/2020-09/2021, 10.2% had active cancer. Based on eligibility criteria (including removal of those with known atrial fibrillation), 4,819 were assessed [median age 74 years; 48.7% female; common cancer types: 25.3% gastrointestinal, 20.3% prostate, 18.4% lung]. Anticoagulants were dispensed to 14.7% of the cohort in the week following discharge. Incidence of thromboembolic event recurrence was 37.5 per 100 person-years (66.7% ischemic stroke). Initial anticoagulation was associated with an increased risk of thromboembolism recurrence (aHR=1.42, 95% CI: 1.06-1.90). Conclusions: This large-scale real-world study demonstrates an estimated 10% of patients with ischemic stroke had active cancer, and they faced a very high 6-month incidence of recurrent thromboembolism. Anticoagulants were not commonly prescribed after discharge, suggesting that clinicians use them less commonly for stroke than for venous thromboembolism in cancer patients. The higher risk of recurrent events on anticoagulants likely reflects residual confounding by indication. Clinical trials are needed to further assess optimal antithrombotic strategies in this population.

Abstract 98: Direct-Acting Oral Anticoagulants and Antiseizure Medications for Atrial Fibrillation and Epilepsy: Risk of Thromboembolic and Major Bleeding Events

Rationale: Direct-acting oral anticoagulants (DOACs) are commonly prescribed with antiseizure medications (ASMs) due to concurrency and causal links between atrial fibrillation (AF) and epilepsy. However, enzyme-inducing-ASMs (EI-ASMs) may reduce absorption and accelerate metabolism of DOACs, potentially lowering DOAC levels and elevating thromboembolism risk. Methods: We leveraged large-scale healthcare data to conduct an emulated target trial among a nationally representative cohort with AF and epilepsy. Thromboembolic and bleeding event rates were contrasted between adults on DOACs + EI-ASMs versus active comparators on DOACs + non-enzyme inducing ASMs. Data-adaptive high-dimensional propensity score matching was employed to control for observed confounders and proxies for unobserved confounders. Adjusted hazard ratios (aHRs) were estimated using Cox proportional hazard models with robust variance estimators to account for clustering within matched pairs. Results: Among incident ASM + DOAC users, we identified 14,078 and 14,158 episodes that met eligibility criteria for assessment of thromboembolic and bleeding outcomes, respectively. Incidence per 1,000 person-years was 88.5 for thromboembolic events and 68.3 for major bleeding events. Compared with use of non-enzyme inducing ASMs, use of EI-ASMs with DOACs was not associated with a difference in thromboembolic events (aHR=1.10, 95% CI: 0.82-1.46), but was associated with a reduction in major bleeding events (aHR=0.63, 95% CI: 0.44-0.89). Conclusions: EI-ASMs were not associated with alteration in DOAC efficacy. These real-world data are reassuring for the care of adults with epilepsy who require anticoagulation, particularly across a larger global community where EI-ASMs remain mainstays. Further research is needed on the reduction in bleeding risk with EI-ASMs, as this may be suggestive of pharmacokinetic interactions lowering DOAC levels without negating therapeutic effects.

Association between prenatal exposure to indoor residual spraying insecticides and infection rates among South African children participating in the Venda Health Examination of Mothers, Babies and their Environment (VHEMBE)

In 2021, 53 countries conducted indoor residual spraying (IRS), the application of insecticides such as dichlorodiphenyl trichloroethane (DDT) or pyrethroids to the walls of homes to control malaria. Animal studies show that these insecticides can increase susceptibility to infections but only one human study was conducted in a population from an area where IRS is applied. The aim of the present study was thus to investigate whether maternal exposure to DDT, its breakdown product dichlorodiphenyl dichloroethylene (DDE) or pyrethroid insecticides is associated with symptoms of infection among children living in a region of South Africa were IRS is conducted annually. As part of the Venda Health Examination of Mothers, Babies and their Environment (VHEMBE) we measured maternal serum concentrations of DDT and DDE, and urinary concentrations of four pyrethroid metabolites in peripartum samples. Poisson regression models with robust variance estimates were used to investigate associations with the rates of infection symptoms between ages 3.5–5 years among 629 children as assessed based on caregiver interviews. Multiple pyrethroid metabolites were associated with infection symptoms. For instance, cis-DBCA was associated with increased rates of ear infection (Incidence Rate Ratio for a 10-fold increase (IRR10) = 1.4; 95 % Confidence Interval (CI) = 1.0, 2.1) and persistent diarrhea (IRR10 = 2.1; 95 % CI = 1.2, 3.9), trans-DCCA was associated with increased rates of colds in children (IRR10 = 1.3; 95 % CI = 1.0, 1.6) and persistent fever (IRS10 = 1.4; 95 % CI = 1.0, 2.0), and 3-PBA was associated with increased rates of persistent fever (IRR10 = 1.8; 95 % CI = 1.0, 3.0). We found limited evidence of association between maternal DDE and DDT serum concentrations and infection symptoms. Results suggest that prenatal exposure to pyrethroid insecticides may be associated with infections among children from an area where IRS is conducted.

Assessing Physicians' Recommendations for Hepatitis B Virus (HBV) and Hepatitis C Virus (HCV) Testing Among Minority Populations in Greater Philadelphia and New York City.

Deaths from liver cancer are on the rise and disproportionately affect minority racial/ethnic groups. In this study, we examined associations between physicians' recommendations for hepatitis B virus (HBV) and hepatitis C virus (HCV) screening and sociodemographic and lifestyle factors among minority populations in the areas of Greater Philadelphia and New York City. Using Poisson regression with robust variance estimation, we evaluated potential associations for 576 Hispanic American (HA), African American (AA), and Asian Pacific American (APA) adults, using blood tests as an outcome measure, with adjustment for sociodemographic factors We found that APAs (34.2%) were most likely to have a physician recommend HBV and HCV screening tests (34.2% and 27.1%, respectively), while HAs were least likely to receive an HBV recommendation (15.0%) and AAs were least likely to receive an HCV recommendation (15.3%). HAs were significantly likely to have never received a blood test for either HBV or HCV (RR = 1.25, 95% CI: 1.05, 1.49). APAs were significantly more likely to receive a screening recommendation for HBV (RR = 1.10, 95%CI: 1.01, 1.20) and to have a blood test (RR = 1.57, 95% CI: 1.06, 2.33). Our findings show that, among HAs, AAs, and APAs, physician recommendations are strongly associated with patients undergoing blood tests for HBV and HCV and that minority populations should increasingly be recommended to screen for HBV and HCV, especially given their elevated risk.

Asymptotic uncertainty of false discovery proportion.

Multiple testing has been a prominent topic in statistical research. Despite extensive work in this area, controlling false discoveries remains a challenging task, especially when the test statistics exhibit dependence. Various methods have been proposed to estimate the false discovery proportion (FDP) under arbitrary dependencies among the test statistics. One key approach is to transform arbitrary dependence into weak dependence and subsequently establish the strong consistency of FDP and false discovery rate under weak dependence. As a result, FDPs converge to the same asymptotic limit within the framework of weak dependence. However, we have observed that the asymptotic variance of FDP can be significantly influenced by the dependence structure of the test statistics, even when they exhibit only weak dependence. Quantifying this variability is of great practical importance, as it serves as an indicator of the quality of FDP estimation from the data. To the best of our knowledge, there is limited research on this aspect in the literature. In this paper, we aim to fill in this gap by quantifying the variation of FDP, assuming that the test statistics exhibit weak dependence and follow normal distributions. We begin by deriving the asymptotic expansion of the FDP and subsequently investigate how the asymptotic variance of the FDP is influenced by different dependence structures. Based on the insights gained from this study, we recommend that in multiple testing procedures utilizing FDP, reporting both the mean and variance estimates of FDP can provide a more comprehensive assessment of the study's outcomes.

Addressing subject heterogeneity in time-dependent discrimination for biomarker evaluation.

Accurate discrimination has been the central goal in identifying biomarkers for monitoring disease progression and early detection. Acknowledging the fact that discrimination accuracy of biomarkers for a time-to-event outcome often changes over time, local measures such as the time-dependent receiver operating characteristic curve and its area under the curve (AUC) are used to assess time-dependent predictive discrimination. However, such measures do not address subject heterogeneity, although the impact of covariates including demographics, disease-related characteristics, and other clinical information on the discriminatory performance of biomarkers needs to be investigated before their clinical use. We propose the covariate-specific time-dependent AUC, a measure for covariate-adjusted discrimination. We develop a regression model on the covariate-specific time-dependent AUC to understand how and in what magnitude the covariates influence biomarker performance. Then we construct a pseudo partial-likelihood for estimation and inference. This is followed by our establishing the asymptotic properties of the proposed estimators and provide variance estimation. The simulation studies and application to the AIDS Clinical Trials Group 175 data demonstrate that the proposed method offers an informative tool for inferring covariate-specific and time-dependent predictive discrimination.

Estimation of the causal effects of time-varying treatments in nested case-control studies using marginal structural Cox models.

When estimating the causal effects of time-varying treatments on survival in nested case-control (NCC) studies, marginal structural Cox models (Cox-MSMs) with inverse probability weights (IPWs) are a natural approach. However, calculating IPWs from the cases and controls is difficult because they are not random samples from the full cohort, and the number of subjects may be insufficient for calculation. To overcome these difficulties, we propose a method for calculating IPWs to fit Cox-MSMs to NCC sampling data. We estimate the IPWs using a pseudo-likelihood estimation method with an inverse probability of sampling weight using NCC samples, and additional samples of subjects who experience treatment changes and subjects whose follow-up is censored are required to calculate the weights. Our method only requires covariate histories for the samples. The confidence intervals are calculated from the robust variance estimator for the NCC sampling data. We also derive the asymptotic properties of the estimator of Cox-MSM under NCC sampling. The proposed methods will allow researchers to apply several case-control matching methods to improve statistical efficiency. A simulation study was conducted to evaluate the finite sample performance of the proposed method. We also applied our method to a motivating pharmacoepidemiological study examining the effect of statins on the incidence of coronary heart disease. The proposed method may be useful for estimating the causal effects of time-varying treatments in NCC studies.

Investigating academic performance and perceptions of human physiology and exercise physiology courses among undergraduate students of physical education at a Brazilian public university

PurposeTo compare the academic performance of undergraduate students in physical education who studied exercise physiology before and after studying human physiology and investigate students’ perceptions of human physiology and exercise physiology courses.MethodsThis study included 311 undergraduate students pursuing a bachelor’s degree in physical education. Participants were divided into two groups: those who had previously attended and completed the human physiology course (group 1, n = 212, 68.2%) and those who had not previously attended or had attended but failed the human physiology course (group 2, n = 99, 31.8%). The prevalence ratio (PR) and 95% confidence interval (95% CI) were calculated using a Poisson regression model with a robust variance estimator. The second aim comprised 67 students with bachelor’s degrees in physical education who completed an electronic questionnaire about their perceptions of human physiology and exercise physiology curriculum.ResultsCompared with those who attended human physiology and passed, those who had not previously attended or had attended but failed the human physiology course have a higher PR of 2.37 (95% CI, 1.68–3.34) for failing exercise physiology. Regarding the students’ perceptions of human physiology and exercise physiology courses, most students reported that they were challenging (58.2% and 64.2%, respectively), but they also recognized the importance of these courses for professional practice (59.7% and 85.1%, respectively).ConclusionHuman physiology should be considered a prerequisite for an undergraduate course leading to a bachelor’s degree in physical education. Furthermore, students considered human physiology and exercise physiology courses important yet challenging. Therefore, continuous student assessment is vital for improving the teaching–learning process.

Effectiveness of home-based video exercise programmes on physical fitness in older adults – systematic review and meta-analysis

Background: Home-based video exercise programmes might be a suitable alternative to traditional physi¬cal activity in older adults to preserve muscle health. The aim of this systematic review and meta-analysis was to examine the effects of home-based video exercise programmes on physical fitness in older adults. Methods: A systematic review and robust variance estimation meta-analysis with meta-regression were carried out according to the recommendations and criteria outlined in the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement. Results: Thirteen studies involving 1,056 participants were included. Meta-analysis showed statistically significant positive changes in balance (p = 0.023), upper extremity strength (p = 0.049, and strength overall (p = 0.042), there was also statistically significant positive effect based on all the 28 outcomes in eight studies, including 696 participants (p = 0.008). Conclusion: The present systematic review and meta-analysis indicate that home-based video exercise programmes positively affect essential components of physical fitness, such as balance and strength, to prevent falls in older adults. Promoting home-based video exercise in clinical practice and ideally sup¬porting it through supervision is vital to effectively combat the age-related physical decline, especially for those in home isolation.

Prevalence and association of compliance with the Canadian 24-hour movement guidelines with sociodemographic aspects in Brazilian adults: a cross-sectional epidemiological study

BackgroundThe physical inactivity is a global health concern, so that recommendations on sufficient physical activity levels are elaborated worldwide, such as in Brazil. However, the Canadian 24-Hour Movement Guidelines were first in the world to consider time-specific recommendations for physical activity, sedentary behavior and sleep, which is still not developed for Latin-American population. The present study aimed to verify the adherence to Canadian 24-hour guidelines in a Brazilian inner city and to analyze its association with sociodemographic aspects.MethodsA cross-sectional epidemiological study, with a sample composed by 250 adults (140 women), with a median age of 41.0 years. Objective measures of moderate-to-vigorous physical activity (MVPA) and sedentary behavior were collected by accelerometry. Sleep duration and sociodemographic aspects (ethnicity, gender, age, educational attainment and socioeconomic level) were obtained through a face-to-face questionnaire. Canadian 24-hour guidelines considered ≥ 150 min/week of MVPA, <8 h/day of sedentary behavior and daily sleep time between 7 and 9 h, being analyzed separately and in combination. Poisson regression with robust variance estimator was used to analyze the prevalence ratio (PR) of meeting the 24-hour guidelines according to the categories of sociodemographic variables, being performed by the software IBM SPSS version 25.0.ResultsThe complete 24-hour guidelines were met only by 24.4% of sample (n = 61). Sedentary behavior was the most met guideline (88%), followed by MVPA (56.8%) and sleep (53.2%), without significant difference according to sex. When compared to elderly participants, those participants in younger groups (18–39 years and 40–59 years) were more likely to meet MVPA guideline (PR = 2.51 [95%CI = 1.47; 4.28] and PR = 2.60 [95%CI = 1.52; 4.45], respectively), as well as the combination of MVPA and sedentary behavior (PR = 1.98 [95%CI = 1.13; 3.44] and PR = 2.17 [95%CI = 1.25; 3.79], respectively) and MVPA with the sleep guideline (PR = 2.39 [95%CI = 1.09; 5.27] only for 18–39 years group). Men were more likely to meet MVPA guideline than women (PR = 1.29 [95%CI = 1.04; 1.59]).ConclusionYounger aged and male adults were more likely to meet the Canadian 24-hour guidelines in a small Brazilian city. However, further studies with larger and representative samples of sociodemographic stratum are still needed.