Population Mean Research Articles

Selection of Superior Clones of Cedrela odorata L. at Early Age in an Asexual Seed Orchard for Genetic Improvement

The selection of plant age in forest species is crucial in a genetic improvement program, as time is a key factor in decision-making. This study aimed to evaluate the variation in clonal growth of Cedrela odorata L. to identify clones with superior performance at an early age. The orchard was established in September 2014, utilizing a completely randomized block design with a planting distance of 4 x 4 m. The experiment comprised 70 clones (ortets), each with 35 replicates (ramets), totaling 2,450 ramets. Selection was based on four key traits: total height (th), clear stem height (csh), normal diameter (nd), and crown diameter (cd). These variables were used to calculate the percentage gain or loss in performance for each clone relative to the population mean. A principal component analysis, analysis of variance (ANOVA), Tukey test (p≤0.05), and cluster analysis were performed to assess the data. The results identified 16 out of the 70 clones as having superior traits. The superior clones included 53-CoSFcoChan07, 2-CoGua344, 15-CoB191, 19-CoKal126, 22-CoKal142, 41-CoTux558, 35-CoTez642, 56-CoTez539, 45-CoTez549, 49-CoTez540, 50-CoTez540, 59-CoTux555, 62-CoCar5, 30-CoBac02, 48-CoTez544, and 10-CoKal16. The average traits of these superior clones were 8.0±0.4 m for total height, 2.6±0.1 m for clear stem height, 0.13±0.0 m for normal diameter, and 4.1±0.2 m for crown diameter, representing a 15% increase over the population mean.

A DEVICE-BASED (GAITON) SAGITTAL PLANE KINEMATICS ANALYSIS OF LOWER EXTREMITY JOINTS AMONG PATIENTS WITH KNEE OSTEOARTHRITIS – A METHODOLOGICAL APPROACH.

Background: Gait assessment is an effective method for identifying functional limitations associated with knee Osteoarthritis and understanding the relationship between disease symptoms and gait quality. Objective: To evaluate the mean difference in the kinematics of lower extremity joints among patients with knee osteoarthritis. Methods: A total of 20 people living with Knee OA were recruited as of 25th September 2024 in this prospective cross-sectional design study. The eligible participants were conveniently recruited from the SRM physiotherapy OPD based on voluntary participation after signing the informed consent. Adult participants aged 18 years and above, both sexes and able to walk independently without mobility aids were recruited and the joint kinematics were measured using the GaitOn Software, 2-dimensional analysis, and sagittal kinematic parameters of stance phase. Results: The mean age of the patients was 53.6 ± 7.3, and the mean BMI was 29.1±4.6. The one sample t-test demonstrated a statistically significant difference between kinematic angles of the lower extremity joint in sagittal plane of population mean (reference value) and sample mean (measured by GaitOn); Initial contact phase (hip: mean diff -4.06, p<0.01, ankle: mean diff 34.1, p < 0.0001), Loading response (hip: mean diff -5.8. p <0.001, knee: mean diff 9.6, p < 0.001, ankle: mean diff 32.4, p < 0.001). Midstance (hip: mean diff 11.06, p <0.001, ankle: 31.4, p< 0.001). Terminal stance (hip: mean diff 28.3, p< 0.004, ankle: mean diff 31.4, p< 0.001) and Pre-swing (hip: mean diff 16.5, p< 0.001, ankle: mean diff 31.4, p< 0.001). Conclusions: The hip and ankle joints equally share knee kinematic compensations. By acknowledging the complex interactions between the hip, ankle, and knee joints, healthcare providers can develop more comprehensive and effective treatment plans for individuals with knee OA.

A Monte Carlo Investigation of Confidence Intervals for a Nondecreasing Series

We consider the problem of estimating a time series of population means from a series of sample surveys when the means are known to be nondecreasing. We introduce the standard survey estimators of the series of means, which are not guaranteed to be nondecreasing. We employ the Pool Adjacent Violators Algorithm (PAVA) to turn the series of standard survey estimates into a nondecreasing series. We introduce five methods of constructing confidence intervals for the series of non-decreasing means: normal-theory intervals based on the standard survey point estimator of the mean and the Taylor series estimator of its variance; normal-theory intervals based on the nondecreasing PAVA estimator of the mean and a unique jackknife estimator of its variance developed here (jackknife-[Formula: see text]); intervals similar to the aforementioned method but based on Student’s-[Formula: see text] distribution (jackknife-[Formula: see text]); analytical intervals due to Morris; and simultaneous confidence limits due to Korn. We report the results of a Monte Carlo simulation and assess the methods’ performance under various scenarios. Jackknife-[Formula: see text] intervals exhibited coverage probabilities that are near the nominal value. Taylor, jackknife-[Formula: see text], and Korn intervals found coverage below the nominal value while Morris intervals were excessively conservative. Jackknife intervals were much narrower than Taylor intervals.

EFFICIENCY OF LOGARITHMIC RATIO CUM LOGARITHMIC PRODUCT ESTIMATORS IN DOUBLE SAMPLING USING IMPUTATION TECHNIQUES

In literature, there are many estimators of finite population mean, some of which are superior to the others. In practical situations, all the information on sample units may not be available due to non-response in sample surveys. Thus, our objective in this study is to get more precise estimators of the finite population mean of the study variable under two-phase sampling in case of missing data. Three new logarithmic ratio cum logarithmic product type imputation methods and corresponding point estimators have been introduced and observed to be better under two-phase sampling, which adds contribution to the field of imputation techniques. The bias and mean square errors of the proposed estimators are calculated in terms of population parameters. The performance of the proposed estimators is compared theoretically and empirically as well with existing traditional estimators.

Effects of model-overfit on model-assisted forest inventory in boreal forests with remote sensing data

Abstract While remote sensing can be an effective tool in building a forest inventory, field measurements and model fitting can be both expensive and challenging. One strategy to reduce forest inventory costs is to leverage forest inventory models fitted to a different population (external models), although the effectiveness of external models is poorly understood. One concern is that models may predict well to the sample data, but poorly to the population—which is termed ‘overfitting’. The effect of overfit may be especially problematic in attempts to predict for a different population (a forest area not covered by any sample plots). Assessing overfit is difficult and its consequence for estimation are not well understood, especially in the context of prediction using external models. This study assesses how overfitting affects model-assisted forest inventory estimation when using internal and external models. We used field and remotely sensed data (Sentinel-2 images and airborne laser scanning data) from two forest areas in Finland. We evaluated four modeling approaches: ordinary least square regression (OLS), random forest, k-nearest neighbors, and gaussian process regression. Both analytical and bootstrap variance estimators were used to evaluate model-assisted estimation performance. Internal models, especially OLS, were the most affected by model overfitting, leading to bias in the population means and underestimation of variance. Estimates using external models provided unbiased means and realistic intervals except in the case of deliberate excessive overfitting. The bootstrap variance estimator was found to be more robust to overfit than the analytical variance estimator for the internal model, but was not helpful for the external model. Internal models should be parsimonious to generalize well to the population and avoid bias. The bootstrap estimator of variance is recommended for internal models, especially if there is concern about model overfitting.

COVID-19 testing and reporting behaviours in England across different sociodemographic groups: a population-based study using testing data and data from community prevalence surveillance surveys

Understanding underlying mechanisms of heterogeneity in test-seeking and reporting behaviour during an infectious disease outbreak can help to protect vulnerable populations and guide equity-driven interventions. The COVID-19 pandemic probably exerted different stresses on individuals in different sociodemographic groups and ensuring fair access to and usage of COVID-19 tests was a crucial element of England's testing programme. We aimed to investigate the relationship between sociodemographic factors and COVID-19 testing behaviours in England during the COVID-19 pandemic. We did a population-based study of COVID-19 testing behaviours with mass COVID-19 testing data for England and data from community prevalence surveillance surveys (REACT-1 and ONS-CIS) from Oct 1, 2020, to March 30, 2022. We used mass testing data for lateral flow device (LFD; data for approximately 290 million tests performed and reported) and PCR (data for approximately 107 million tests performed and returned from the laboratory) tests made available for the general public and provided by date and self-reported age and ethnicity at the lower tier local authority (LTLA) level. We also used publicly available data on mean population size estimates for individual LTLAs, and data on ethnic groups, age groups, and deprivation indices for LTLAs. We did not have access to REACT-1 or ONS-CIS prevalence data disaggregated by sex or gender. Using a mechanistic causal model to debias the PCR testing data, we obtained estimates of weekly SARS-CoV-2 prevalence by both self-reported ethnic groups and age groups for LTLAs in England. This approach to debiasing the PCR (or LFD) testing data also estimated a testing bias parameter defined as the odds of testing in infected versus not infected individuals, which would be close to zero if the likelihood of test seeking (or seeking and reporting) was the same regardless of infection status. With confirmatory PCR data, we estimated false positivity rates, sensitivity, specificity, and the rate of decline in detection probability subsequent to reporting a positive LFD for PCR tests by sociodemographic groups. We also estimated the daily incidence, allowing us to calculate the fraction of cases captured by the testing programme. From March, 2021 onwards, individuals in the most deprived regions reported approximately half as many LFD tests per capita as individuals in the least deprived areas (median ratio 0·50 [IQR 0·44-0·54]). During the period October, 2020, to June, 2021, PCR testing patterns showed the opposite trend, with individuals in the most deprived areas performing almost double the number of PCR tests per capita than those in the least deprived areas (1·8 [1·7-1·9]). Infection prevalences in Asian or Asian British individuals were considerably higher than those of other ethnic groups during the alpha (B.1.1.7) and omicron (B.1.1.529) BA.1 waves. Our estimates indicate that the England Pillar 2 COVID-19 testing programme detected 26-40% of all cases (including asymptomatic cases) over the study period with no consistent differences by deprivation levels or ethnic groups. Testing biases for PCR were generally higher than those for LFDs, in line with the general policy of symptomatic and asymptomatic use of these tests. Deprivation and age were associated with testing biases on average; however, the uncertainty intervals overlapped across deprivation levels, although the age-specific patterns were more distinct. We also found that ethnic minorities and older individuals were less likely to use confirmatory PCR tests through most of the pandemic and that delays in reporting a positive LFD test were possibly longer in populations self-reporting as "Black; African; Black British or Caribbean". Differences in testing behaviours across sociodemographic groups might be reflective of the higher costs of self-isolation to vulnerable populations, differences in test accessibility, differences in digital literacy, and differing perceptions about the utility of tests and risks posed by infection. This study shows how mass testing data can be used in conjunction with surveillance surveys to identify gaps in the uptake of public health interventions both at fine-scale levels and across sociodemographic groups. It provides a framework for monitoring local interventions and yields valuable lessons for policy makers in ensuring an equitable response to future pandemics. UK Health Security Agency.

The impact of 12 weeks of circuit body weight training on athletes’ physical fitness

The purpose of this study is to find out the impact of 12-week circuit body weight training on athletes’ physical fitness. This study used an experimental design with a control group. This experimental model consists of three stages. Firstly, pre-testing the dependent variable before implementing the treatment. Secondly, experimental participants are given experimental treatment, specifically the circuit body weight approach. Thirdly, provide a post-test to measure the dependent variable after treatment. The experimental sample included 25 athletes from various sports who were separated into two treatment groups. The circuit body weight group consisted of 13 samples, while the remaining 12 were trained using conventional direct teaching methods. The data analysis technique begins with calculating the data’s normality. The homogeneity test determines if two data sets contain homogeneous versions. Finally, the Mann-Whitney test compares two similar population means. Calculations using SPSS IBM 26 on data before treatment in the experimental class resulted in a valid sample size of 25 and a score of 48.40 ± 2,931. The experimental group had a valid sample size of 25, with a score of 49.57 ± 2,979. Pre-test data for the control class showed 25 valid samples with a score of 38.7 ± 6,607. Meanwhile, the control class post-test data obtained a valid sample size of 25 with a score 39.43 ± 6.796. The table shows a sig (2-tailed) value of 0.000 < 0.05, indicating a significant difference in physical fitness scores between the experimental and control groups. Additionally, there is a difference in average Physical Fitness results between the Circuit bodyweight training model and the conventional learning model.

Spatial–Temporal Characteristics, Source Apportionment, and Health Risks of Atmospheric Volatile Organic Compounds in China: A Comprehensive Review

Volatile organic compounds (VOCs) are ubiquitous in the atmosphere, posing significant adverse impacts on air quality and human health. However, current research on atmospheric VOCs mainly focuses on specific regions or industries, without comprehensive national-level analysis. In this study, a total of 99 articles on atmospheric VOCs in China published from 2015 to 2024 were screened, and data on their concentrations, source apportionment, and health risks were extracted and summarized. The results revealed that the annual average concentrations of TVOCs and their groups in China generally increased and then decreased between 2011 and 2022, peaking in 2018–2019. A distinct seasonal pattern was observed, with the highest concentrations occurring in winter, followed by autumn, spring, and summer. TVOC emissions were highly concentrated in northern and eastern China, mainly contributed by alkanes and alkenes. Source apportionment of VOCs indicated that vehicle sources (32.9% ± 14.3%), industrial emissions (18.0% ± 12.8%), and other combustion sources (13.0% ± 13.0%) were the primary sources of VOCs in China. There was a significant positive correlation (p < 0.05) between the annual mean VOC concentration and population size, and a notable negative correlation (p < 0.05) with GDP per capita. Atmospheric VOCs had no non-carcinogenic risk (HI = 0.5) but exhibited a probable carcinogenic risk (7.5 × 10−5), with relatively high values for 1,2-dibromoethane, 1,2-dichloroethane, and naphthalene. The health risk was predominantly driven by halocarbons. These findings are essential for a better understanding of atmospheric VOCs and for developing more targeted VOC control measures.

Epicardial adipose tissue and subclinical alterations in cardiac structure and function in early adulthood

Abstract Background Epicardial adipose tissue (EAT) is the visceral fat depot surrounding the heart and coronary arteries and shares the same microcirculation with myocardium. Under normal physiologic conditions EAT contains important cardioprotective properties such as cushioning the heart against mechanical stress, thermoregulation of the myocardium in hypothermia as well as balancing myocardial fatty acid homeostasis. Higher accumulation of EAT has been reported to independently associate with deleterious alterations in cardiac structure and function. However, majority of previously addressed study results are derived from older study population and in presence of cardiovascular diseases. Data on the associations of EAT and cardiac echocardiograpghically derived structural and functional parameters in a young and middle-aged population without prevalent cardiovascular disease is scarce. Purpose We aimed to address this knowledge gap by investigating the associations of echocardiographically measured EAT thickness and possible adverse subclinical alteration in cardiac structure and function in a population cohort of young and middle-aged adults. Methods This study participants were examined as part of the ongoing multi-centre longitudinal cohort, focusing on cardiovascular risk factors from childhood through adulthood. EAT thickness was measured by manual delineation from parasternal long-axis echocardiograms at end systole. Transthoracic and Doppler echocardiograpghy was performed and data on cardiac structural and functional parameters were derived comprehensively in accordance with EAE/ASE guidelines. Results In this study population (N=1677, men=770, women=897 ; age range 34-49 years) mean EAT thickness was 4.0 mm in whole population. In multivariable regression analysis models adjusted for age, sex, waist circumference and systolic blood pressure, significant independent associations of EAT and left atrial dimension (P<.0001) and various measures of left ventricular (LV) wall thickness such as LV mean wall thickness (P<.001), LV relative wall thickness (P<.001) as well as LV posterior wall thickness (P<.001) were observed. We found no significant associations between EAT thickness and cardiac functional and hemodynamic parameters after covariate adjustments in multivariable analysis models. Conclusion The findings of this study highlight that larger EAT thickness is associated with subclinical alteration in cardiac wall thicknesses in young and middle-aged adults. However, we found no associations between EAT thickness and cardiac functional parameters, which is perhaps due to the high cardiac adaptation properties in our relatively young study population. Therefore, further follow-ups is required to address long-term probable alterations in cardiac hemodynamics when the participants are older.

Sodium and potassium intake in adults: the Italian Health Examination Survey 2023 – CUORE Project

Abstract Background The WHO recommends a 30% relative reduction in mean population intake of salt/sodium within 2025 (baseline 2010) and an adequate potassium intake. To these ends, the Italian Ministry of Health (MoH) has strengthened prevention/health promotion. To update the assessment of the habitual salt and potassium intake in the Italian general adult population, national health examination surveys (HESs), funded by the MoH-CCM, are conducted within the CUORE Project. Methods In 2023 a new HES started including salt and potassium intake assessment by the use of 24h urine collection. Up to now, data from random samples of residents in 7 Regions (of 20 regions) distributed in North, Centre and South of Italy and aged 35-74 years are available (686 men, 702 women). Urinary excretion is assayed by a central lab. Persons with urinary volume < 500 ml and/or a urinary creatinine content referred to body weight outside the range of population mean ± 2 standard deviations are excluded. Results Out of 657 men and 671 women, mean level of salt per day was 9,2 g (95% CI: 9,0-9.5 g) and 7,1 g (6,9-7,3 g) respectively, and mean level of potassium per day was 2,9 g (2,8-3,0 g) and 2,4 g (2,3-2,5 g) respectively. A salt intake level lower than the WHO recommended target of 5g/day was detected in 9,5 % (5,2 -13,9 %) of men and 23,7 % (17,5 -29,9 %) of women and a potassium intake level higher than the WHO recommended target of 3510 mg/day was detected in 22,4 % (16,3 -28,6 %) of men and 9,7 % (5,4 -14,0 %) of women. Conclusions These preliminary data showed that in Italian adults the average salt intake is still higher and the average potassium intake is still lower than recommended. Compared to 2008, the habitual salt intake decreased of about 12% in 2018 and remained stable in 2023; the habitual potassium intake remained stable in 2008, 2018 and 2023.These results justify and encourage the ongoing preventive initiatives of MoH, facilitating the meeting of WHO targets. Key messages • In Italian adults the average salt intake is still higher than recommended and the habitual salt intake decreased compared to 15 years ago. • In Italian adults the average potassium intake is still lower than recommended and remained stable compared to 15 years ago.

Prevalence and prognostic value of thrombocytopenia in aortic valve replacement surgery: bioprosthesis versus mechanical prosthesis

Abstract Background Thrombocytopenia is a frequent complication of valve surgery, and is associated with different postoperative outcomes. Concern has recently arisen about thrombocytopenia following aortic valve replacement (AVR), as some authors have reported increased postoperative thrombocytopenia with certain biological aortic valves. In adittion, it is unclear whether thrombocytopenia predicts mortality in this type of surgery. Purpose The aim of this study was to determine the prevalence and prognostic value of thrombocytopenia in biological and mechanical aortic valve replacement. Methods The study was an observational analysis of patients undergoing AVR with or without associated coronary artery bypass grafting (CABG) at a single center between October 2014 and October 2023. Cardiac Surgery database was computerized and prospectively completed. Preoperative and first 4 days postoperative platelet counts were analyzed. Thrombocytopenia was defined as platelet count < 100 × 10³/mm³. To obtain comparable populations, a propensity score matching analysis was performed. Results A total of 1,197 patients underwent AVR with (n = 494) or without CABG (n = 703). Patients received either a mechanical prosthesis (n = 320), or a biological prosthesis (n = 877). The mean population age was 68 years (SD 6), with the majority being male (68%). Univariate analysis of the baseline characteristics of both groups of patients showed that they were not comparable. A risk-adjusted subanalysis was performed according to a propensity score (n=278). The nadir of bioprostheses was on the third postoperative day with an average of 93.8 × 10³/mm³, while in mechanical prostheses was also on the same day but with an average of 114.7 × 10³/mm³ (p: 0.001). (Figure 1) Bioprosthesis implantation was significantly associated with a higher prevalence of thrombocytopenia (72.7% vs. 45.3%, p<0.001). The presence of postoperative thrombocytopenia has been associated with higher in-hospital mortality (6.7% vs. 0.9%, p=0.019); but not with other postoperative complications. (Figure 2) Conclusions Patients undergoing AVR with bioprostheses had a significantly higher prevalence of thrombocytopenia, and also lower platelet counts than mechanical prothesis within the first 4 postoperative days. Thrombocytopenia was associated with higher in-hospital mortality in a risk score-adjusted population.Platelet counts after AVROutcomes according to platelet count

Nationwide trends in major cardiovascular risk factors in England in the last 2 decades: Health Survey of England 2003-2019

Abstract Cardiovascular disease (CVD) accounts for a quarter of deaths annually in the UK, with more than 7.6 million people living with the disease. Hypertension, diabetes, and obesity are among the most prevalent modifiable risk factors for CVD, and the strategies to reduce the incidence and prevalence of these CV risk factors are deemed the most effective to reduce this immense toll. In the UK, over the last few decades, several health policy decisions and pathways have been developed to reduce this toll. We used data from 11 nationally representative, cross-sectional surveys from the Health Survey of England between 2003 and 2019 to evaluate trends in the prevalence of these CV risk factors and whether there has been any population-wide improvement in them. These surveys have cumulative information on 94,100 adults, and we applied sample weights, accounting for oversampling and nonresponse. We used "period definitions and cut-offs" to define those with diabetes. For example, for undiagnosed diabetes, we used glycated haemoglobin cut-off equivalent of 7% or more for years before 2011 and the current diagnostic threshold of > 6.5% thereafter. This was done to facilitate and compare the trends after accounting for changes in medical practice and understanding across this period. Similarly, hypertension was defined as doctor-diagnosed hypertension or in its absence regular use of antihypertensive medications or blood pressure ≥ 140/90mmHg (period diagnostic threshold remains unchanged during). Python and STATA were used to conduct analyses, and Join Point regression software was used to develop and compare trends. In England, from 2003-2019, mean population BMI consistently increased over this period, rising by 0.8kg/m2 from 27.6 to 28.8 kg/m2. Obesity prevalence (BMI ≥30kg/m2) increased by 5.4% from 22.6% to 28.0%. Concurrently, mean glycated haemoglobin increased by 0.36% from 6.18% to 6.54%, surpassing the current diabetes diagnostic threshold. Diabetes period prevalence surged from 4.2% to 11.6%, a trend consistent when the current diagnostic threshold was alternatively applied across all periods. Conversely, doctor-diagnosed and total hypertension (including those who are unaware) prevalence exhibited a slight decrease (1.4% and 3%, respectively), mirrored by reductions in population-wide mean systolic and diastolic blood pressure by 4.6mmHg and 1.9mmHg. These results suggest that, with the total population in England standing at 56.3 million in 2019, an estimated 15.8 million adults were within the obese BMI range, 6.5 million had diabetes and 17.6 million had hypertension. The obesity epidemic is likely fuelling the increase in diabetes prevalence. These findings underscore the importance of prioritising obesity reduction in public health initiatives, aiming to subsequently curb diabetes prevalence. Hypertension still remains a major CV risk factor, affecting almost one third of the adult population.

Calibration Estimators with Different Types of Distance Measures Under Stratified Sampling in the Presence of Measurement Error

The calibration method is used in stratified random sampling in the presence of measurement error to achieve optimum strata weights for better precision. In this study we attempt to analyze the behaviour of calibration estimators with different types of distance measures in the presence of measurement error for the estimation of population mean under stratified random sampling. The proposed estimators are compared with the estimators in the absence of measurement error. A simulation study has been carried out to evaluate the proposed estimators.

On the efficiency of paired ranked set sampling for estimating the population mean in the presence of non-response

Non-response is a common problem faced by surveyors while conducting surveys; this introduces a potential bias in the estimates of population parameters. One method of dealing with non-response is subsampling of the non-respondents, which increases precision in estimates by increasing the sample size. This study proposes an unbiased mean estimator in the presence of non-response using the Paired Ranked Set Sampling (PRSS) technique. The proposed estimator is based on a suggested strategy for adapting the subsampled units into the initial sample. Variance of the proposed estimator is derived, and conditions are provided for which the proposed estimator performs better than existing estimators. We conduct a simulation study to evaluate the precision of the proposed estimator in comparison with other existing estimators for estimating the population mean. In simulation, we assume populations based on normal distribution, exponential distribution, and real-life data on abalone. Simulation results show that the proposed mean estimator exhibits a higher probability of precisely estimating the finite population mean.

Dietary calcium intake among Iranian adults: Iranian Multicenter Osteoporosis Study (IMOS-2021).

Adequate dietary consumption of calcium is crucial in the preservation of bone health and the prevention of osteoporosis. This study investigated the prevalence of insufficient dietary calcium intake among individuals aged ≥50 years in Iran. We analyzed data from the Iranian Multicenter Osteoporosis Study (IMOS-2021). Participants aged 50 years and older completed a 168-item food frequency questionnaire. Insufficient dietary calcium intake was characterized as a daily calcium intake of <1000 mg for men aged 50-70 years, and <1200 mg for men over 70 years and women over 50 years and older. Stata v17 statistical software facilitated a survey set analysis to estimate the population's mean and median dietary calcium intake and the prevalence of insufficient dietary calcium intake. The study included 1450 participants with a mean age of 60.7±7.9 years. The estimated mean dietary calcium intake in Iran was 1062.7 mg/day (95% CI: 1029.6-1095.8), with a median intake of 943.5 mg/d (95% CI: 910.5-976.4). The prevalence of insufficient dietary calcium intake in Iran was estimated to be 62.9% (95% CI: 60.0%-65.7%). Notably, the prevalence was higher among women at 75.5% (95% CI: 71.9%-78.8%), compared to men at 47.8% (95% CI: 43.4%-52.3%) with a significant difference (P<0.001). In age-related findings, individuals aged 65 years and older had a higher prevalence of insufficient intake, at 69.0% (95% CI: 63.9%-74.0%), versus those under 65 years, at 60.3% (95% CI: 56.9%-63.8%), with this difference being statistically significant (P = 0.007). Furthermore, a significant inverse relationship was identified between both educational years and socioeconomic status and the prevalence of insufficient dietary calcium intake (Ps for trends<0.001). Our findings revealed a significant prevalence of insufficient dietary calcium intake in women and those aged 65 and older. We advocate for targeted public health strategies to ensure sufficient dietary calcium intake across these populations.

Estimating the Confidence Intervals for the Coefficients of Variation Delta-Gamma Distributions

A common application of the coefficient of variation (CV), which is the ratio of the population standard deviation to the population mean, is frequently used to assess quality control and economic processes, among others. The fiducial quantity approach, Bayesian confidence intervals (CIs) using the Jeffreys, uniform, or normal-gamma-beta (NGB) priors, and highest posterior density (HPD) intervals using the Jeffreys, uniform, or NGB priors were used to provide estimators for the CI for the ratio of CV of two delta-gamma distributions. An evaluation of their performance in terms of average length and coverage probability was carried out using Monte Carlo simulations. The results of this study indicate that the HPD using the Jeffreys prior and fiducial quantity methods are the best for estimating the CI for the ratio of the CV of two delta-gamma distributions. Rainfall data from Mae Hong Son province in Thailand was used to illustrate their practicability when analyzing real-life processes.

Comparing Confidence Intervals for the Mean of Symmetric and Skewed Distributions

In context-aware decision analysis, mean can be an important measure, even when the distribution is skewed. Previous comparative studies showed that it is a real challenge to construct a confidence interval that performs well for highly skewed data. In this study, we propose new confidence intervals for the population mean based on Edgeworth expansion that include both skewness and kurtosis corrections. We compared existing and newly proposed confidence intervals for a range of samples from symmetric and skewed distributions of varying levels of kurtosis. Using Monte Carlo simulations, we evaluated the performance of these intervals based on the coverage probability, mean length, and standard deviation of the length. The proposed bootstrap Edgeworth-based confidence interval outperformed other confidence intervals in terms of coverage probability for both symmetric and skewed distributions and can be recommended for general use in practice.

How Much Does Prosthetic Joint Infection and Its Successful Treatment Affect Patient-reported Quality of Life?

Uncomplicated joint replacement improves pain and other patient-reported outcome measures (PROMs) such as joint function scores and quality-of-life measures. However, the overall impact of periprosthetic joint infection (PJI) and its successful treatment on PROMs is poorly defined. In this study, we describe quality-of-life scores using the 12-item Short Form survey, version 2 (SF-12v2), collected as part of a large, prospective, observational study of PJI. (1) Do patients with newly diagnosed PJI have lower quality-of-life scores than the general age-matched population? (2) Are lower quality-of-life scores for patients with PJI sustained for ≥ 12 months? (3) What factors are associated with a good functional outcome at 12 months, defined by achieving a physical component summary (PCS) score of > 50 on the SF-12v2 (that is, above the age-adjusted population mean) or an increase of > 8.9 or more from baseline? The PIANO (Prosthetic joint Infection in Australia and New Zealand, Observational study) cohort was a prospective, longitudinal, multicenter cohort study of 783 patients with newly diagnosed PJI recruited across 27 centers between July 2014 and December 2017. All participants were followed for 2 years. SF-12v2 scores were collected at diagnosis (baseline) and 3, 12, and 24 months after diagnosis. Treatment success was defined as being alive with no clinical or microbiological evidence of infection and no ongoing use of antibiotics for the index joint. After exclusion of 6.6% (52) who had died, 4.2% (33) with PJI of joints other than hips and knees, and those with incomplete data sets (200 [25.5%]), 498 patients had complete SF-12v2 data sets available. At baseline, the median (IQR) PCS score was 37 (30 to 46), which increased to 41 (34 to 49; p < 0.001) at 12 months. Both measures were lower than those for the general age-matched population norm. There was no further improvement in PCS scores between 12 and 24 months. By contrast, the median (IQR) mental component summary score of the SF-12v2 was similar to age-adjusted population norms (48 [37 to 57]) at baseline. Only 40% of patients with PJI achieved a good functional outcome at 12 months. After adjustment for other factors, treatment success of PJI increased the odds of a good functional outcome by 67% (95% CI 11% to 154%; p = 0.02). PJIs have a large effect on the PCS score of the SF-12v2 quality-of-life measure at baseline, which is sustained for at least 2 years. Successful treatment of PJI increases the likelihood of a good functional outcome. These data can be used to set expectations for patients presenting with PJI and can be used to inform future clinical studies in which quality-of-life measures are incorporated into clinical endpoints. Level II, therapeutic study.

Recent Sociocultural Changes Reverse the Long‐Term Trend of Declining Habitat Availability for Large Wild Mammals in Europe

ABSTRACTAimPeople have strongly influenced the biosphere for millennia, but how their increasing activities have shaped wildlife distribution is incompletely understood. We examined how the distribution of European large (&gt;8 kg), wild mammals has changed in association with changing anthropogenic pressures and climate change through the Holocene.LocationEurope.MethodsWe used over 17,000 zooarchaeological records of 20 species spanning 12,000 years to develop time‐calibrated species distribution models, incorporating dynamic data on cropland extent, natural vegetation fragmentation, human population density and climate. We assessed habitat availability and potential species richness across time and within seven biogeographical regions. We also compared anthropogenic pressures at zooarchaeological record sites with present‐day habitats of remaining large mammals to evaluate recent increases in their potential for coexistence with human activities.ResultsWe found a continuous decline in potential large mammal species richness, particularly linked to changes in human population density. Most habitat loss became evident continentally after 1500 AD, but in the Atlantic and Mediterranean bioregions, habitat loss reached 20% during the Iron/Roman Ages (1000 BC–500 AD) due to increasing human population density. Climate change initially boosted species richness (+0.67 species/km2 on average) until the end of the Mesolithic but had negligible effects afterward. Today, large mammals appear to have a higher potential for coexisting with people compared to the past (e.g., herbivores today inhabit areas with a mean human population density of 95 people/km2, compared to an average of 17 people/km2 in the period 1500–2000 AD).Main ConclusionsOur study emphasizes the crucial role of anthropogenic pressures over natural climate change in determining the distribution and diversity of large mammal communities throughout history. Additionally, our results indicate that contemporary anthropogenic trends like land‐use de‐intensification and stronger conservation policies can counteract the impact of past, higher anthropogenic pressures and reverse defaunation.

Unveiling the Spectrum of Glucose Variability: A Novel Perspective on FreeStyle Libre Monitoring Data.

Since the introduction of insulin therapy, it has become apparent that type 1 diabetes (T1D) is accompanied by long-term microvascular and macrovascular complications. In the context of the many benefits of continuous glucose monitoring (CGM), there remain opportunities to study the large amount of data now available in order to maximise its potential in the endeavour to reduce the occurrence of diabetes tissue complications in the longer term. Continuous glucose monitoring values were downloaded for 89 type 1 diabetes mellitus (T1D) individuals for up to 18 months from 2021 to 2023. Data for patient demographics was also taken from the patient record which included Sex, Date of Birth, and Date of Diagnosis. The recorded laboratory glycated haemoglobin (HbA1c) test results were also recorded. The glucose management index (GMI) was calculated from average glucose readings for 18 months using the formula GMI (%) = (0.82-(Average glucose/100)). This was then adjusted to give GMI (mmol/mol) = 10.929 * (GMI (%) - 2.15). Average Glucose Fluctuation (AGF) was calculated by adding up the total absolute change value between all recorded results over 18 months and dividing by the number of results minus one. The % Above Critical Threshold (ACT) was calculated by summing the total number of occurrences for each result value. A cumulative 95% limit was then applied to identify the glucose value that only 5% of results exceeded in the overall population. Using this value, we estimated the percentage of total tests that were above the Critical Threshold (ACT). The mean age of the participants was 42.6years, and the mean duration of T1D was 18.4years. A total of 3.22 million readings were analysed, yielding an average blood glucose level of 10.3mmol/l and a GMI of 57.2mmol/mol. There was a strong correlation between GMI and measured HbA1c (r2 = 0.82). However, there were patients who had an above-critical threshold (ACT) of 4-10% at a GMI of 60mmol/mol or less. The percentage average value at the time of day (%AVTD) was applied to all blood glucose readings at each 15-min interval throughout the day, averaged over 18months. The %AVTD of GMI (overall average 57.2mmol/mol) increased after midday, dipped at 18:00, and peaked at 22:00. The %AVTD of AGF (overall average 0.60mmol/l) showed higher change rates after 09:00 declining at the end of the day. The %AVTD of ACT peaked at 22:00, with those having the highest %ACT showing an additional peak at 15:00. We have shown here that the percentage glucose results above 18mmol/l (top 5% of distribution) increased exponentially above 54mmol/mol HbA1c. The %AVTD is introduced as a useful measure. Our data indicate that over the 24-h period, improvement in metabolic control could be focussed on the afternoon and evening, when there are higher-than-average levels of GMI, a higher-than-average degree of glucose change, and higher-than-average risks of being above the critical threshold. In conclusion, a measure of glycaemic variation based on the amplitude of glucose change to a population mean could be used to provide valuable clinical insights into glucose change over a 24-h period.