Linear Random Effects Research Articles

Statistical modelling of growth curve for longitudinal data on a feeding trial in goat breeds

The growth curve parameters were estimated extending a linear regression to higher degree polynomial with attempts to use also the biologically appealing Gombertz function. The data contained monthly weight records from weaning to the age of 14 months of kids in two Omani goat breeds Sahrawi and Jabbali used in a feeding trial assessing the effect of concentrate supplement (14% crude protein). The growth curve parameters were estimated within the fixed effects breed and feed concentrate level (2 or 3% of live body weight) with an extension to mixed models using animals as random effects. The parameters and model contrasting were performed with ML or REML as appropriate with relative comparison relying on AIC and significance testing of estimated parameters. The mixed model analyses were performed with publicly available R software package programs. The fixed effect cubic regression with linear random effect model fitted into the data. The higher level of concentrates improved the immediate post-weaning growth in the same way in the breeds while the subsequent growth curve differed with more pronounced weight increments in the Jabbali breed.

Physical Activity Behaviour and Motivation During and Following Pulmonary and Cardiac Rehabilitation: A Repeated Measures Study.

Exercise rehabilitation programmes are important for long-term health and wellbeing among people with cardiac and pulmonary diseases. Despite this, many people struggle to maintain their physical activity once rehabilitation ends. This repeated measures study tracked changes in physical activity behaviour and motivation during and after completing a community-based exercise rehabilitation programme. Cardiac and pulmonary exercise rehabilitation patients (N = 31) completed six once-monthly measures of physical activity (MET·min), self-determined motivation, intention, and habit strength for rehabilitation exercise (within rehabilitation sessions) and lifestyle physical activity (outside of rehabilitation sessions). Linear regression and random effects models with estimated marginal means were used to test for associations between physical activity motivation and behaviour and change during and post-rehabilitation. Overall physical activity decreased after rehabilitation (823 MET·min) despite patients becoming more self-determined for lifestyle physical activity during rehabilitation. More self-determined motivation, stronger intentions, and stronger habits were associated with more lifestyle physical activity behaviour. However, none of these motivation variables were significantly associated with rehabilitation exercise behaviour. Among community-based cardiac and pulmonary rehabilitation patients, physical activity levels decreased following exercise rehabilitation programmes. The findings revealed clear distinctions in the motivation of rehabilitation exercise compared to lifestyle physical activity. Exercise rehabilitation programmes might improve the longevity of outcomes by integrating approaches to enhance lifestyle physical activity beyond the clinic.

The Relationship Between Vitamin D Intake and Serum 25-hydroxyvitamin D in Young Children: A Meta-Regression to Inform WHO/FAO Vitamin D Intake Recommendations

BackgroundThis work was commissioned by the World Health Organization and Food and Agriculture Organization to inform their update on the vitamin D requirements for children aged <4 y. ObjectivesThe objective of this work was to undertake multilevel and multivariable dose-response modeling of serum 25-hydroxyvitamin D (25OHD) to total vitamin D intake in children aged <4 y with the goal of deriving updated vitamin D requirements for young children. MethodsSystematically identified randomized controlled trials among healthy children from 2 wk up to 3.9 y of age provided with daily vitamin D supplements or vitamin D-fortified foods were included. Linear and nonlinear random effects multilevel meta-regression models with and without covariates were fitted and compared. Interindividual variability was included by simulating the individual serum 25OHD responses. The percentage of individuals reaching set minimal and maximal serum 25OHD thresholds was calculated and used to derive vitamin D requirements. ResultsA total of 31 trials with 186 data points from North America, Europe, Asia, and Australasia/Oceania, with latitudes ranging from 61°N to 38°S, and with participants of likely mostly light or medium skin pigmentation, were included. In 29 studies the children received vitamin D supplements and in 2 studies the children received vitamin D-fortified milk with or without supplements. The dose-response relationship between vitamin D intake and serum 25OHD was best fitted with the unadjusted quadratic model. Adding additional covariates, such as age, did not significantly improve the model. At a vitamin D intake of 10 μg/d, 97.3% of the individuals were predicted to achieve a minimal serum 25OHD threshold of 28 nmol/L. At a vitamin D intake of 35 μg/d, 1.4% of the individuals predicted to reach a maximal serum 25OHD threshold of 200 nmol/L. ConclusionsIn conclusion, this paper details the methodological steps taken to derive vitamin D requirements in children aged <4 y, including the addition of an interindividual variability component.

How much do conservation cropping practices mitigate runoff and soil erosion under Western European conditions: A focus on conservation tillage, tied ridging and winter cover crops

AbstractConservation farming practices are known for their capacity to mitigate runoff and erosion, but the magnitude of their effectiveness is highly variable across studies. In order to better understand the contribution of environmental and management factors to their effectiveness, up to 37 studies reporting 271 individual trials were collated for a quantitative review regarding 3 common conservation agriculture‐related practices, at the plot scale and in a Western European context. Two different methods suitable for hierarchically structured data sets were used for the meta‐analyses—hierarchical nonparametric bootstrapping and linear random effects models—, yielding nearly identical average outcomes but differing in terms of confidence intervals. We found that, on average, winter cover crops reduce cumulative seasonal (autumn‐winter) runoff by 68% and soil losses by 72% compared with a bare soil. The occurrence and intensity of stubble tillage on the control plot is a key explanatory variable for the mitigation effect of winter cover crops. In potato crops, tied ridging reduces cumulative seasonal (spring–summer) runoff by a mean of 70% and soil erosion by 92%. Conservation (non‐inversion) tillage techniques alleviate cumulative seasonal overland flow by 27% and associated sediments losses by 66%, but strong evidence of publication bias was detected for this farming practice, probably leading to an overestimation of its effectiveness. These mitigation effects are shown to be much greater for spring crops than for winter crops, and to increase with time since ploughing was stopped. The type of conservation tillage scheme strongly affects the ability to attenuate surface flows. Intensive non‐inversion tillage systems relying on repeated use of (powered) tillage operations appear to be the least effective for reducing both water and sediment losses. The best performing scheme against runoff would be a deep (non‐inversion) tillage (−61%), while against erosion it would be a no‐till system (−82%). Although several explanatory factors were identified, there remains a high (unexplained) variability between trials effect sizes, thus not attributable to pure sampling variability. Meanwhile, this review provides farm advisors or policy makers with guidance on the contexts in which implementation of such conservation practices should be supported so as to maximize expected benefits.

Role Of Fintech Adoption on Banking Sector Efficiency: A Survey Based Research Approach

Comparing financial technology businesses during the fourth industrial age to their counterparts, this study investigates the effects of these companies adhering to effective manufacturing practices. The objective is to offer actual proof of the operational effectiveness of FinTech companies and how business efficiency affects market performance. FinTech has to pass through different business models to attain the maturity as a successful pure player actor. This demonstrates that FinTech innovations improve banks' performance using several panel data estimators, including panel-corrected standard errors for linear regression, fixed effects, and random effects. Furthermore, it also show that the proportion of capital that is adequate, earnings capacity, total assets, and yearly GDP growth rate of banks also have a noteworthy beneficial influence on bank performance. By using a balanced scorecard to examine financial points of view, customer perspectives, business internal perspectives, education and growth perspectives, and competitive advantage in services growth and development, monetary advantage, and economic inclusion when implementing FinTech, this study seeks to understand the impact of these factors on banks' performance. A sample of 259 respondents was collected from people working in banking sector. The variables that identify the role of Fintech adoption on banking sector efficiency are Financial Inclusion, Data Analytics and Insights, Cost Reduction, and Improved Customer Experience.

Baseline Frailty and Domain‐specific Cognitive Declines in Healthy and MCI Older Adults

AbstractBackgroundBoth physical frailty and cognitive decline increase with age and each place adults at elevated risk for loss of independence. Inconsistent associations have been found between frailty and risk for cognitive declines across cognitive domains. However, most studies were cross‐sectional and did not include a comprehensive battery of neuropsychological tests. We hypothesized that frail older adults, whether with or without Mild Cognitive Impairment (MCI) at baseline, are at risk for accelerated domain‐specific cognitive declines.MethodThe Ginkgo Evaluation of Memory Study (GEMS) was a prospective study of 3069 dementia‐free older adults aged 72‐96 years, followed for up to 7.5 years or a diagnosis of dementia, 482 of whom were diagnosed with MCI at baseline. A modified physical frailty phenotype was constructed using GEMS baseline data. A Neuropsychological Battery consisted of 13 tests reflecting global cognition, memory, visual‐spatial construction, language, psychomotor speed/attention, and executive function were administered annually. Linear random effects models were used to compare differences in baseline and rate of change in domain scores among individuals with and without baseline frailty.ResultOverall, frail participants showed poorer baseline cognitive function in all domains, and greater declines in all cognitive domains. When stratified by baseline MCI, among non‐MCI participants, those with frailty revealed poorer baseline psychomotor speed/attention and executive function, and greater declines in all cognitive domains. Among MCI participants, those with frailty exhibited lower baseline visual‐spatial construction, and greater declines in all cognitive domains except for visual‐spatial construction and executive function. In all cognitive domains, the estimated effect of frailty on cognitive decline was greater in MCI participants than non‐MCI participants.ConclusionFrailty was predictive of accelerated cognitive declines across domains and more so in those with baseline MCI. The results from this study highlight the importance of assessing frailty as a risk factor for accelerated cognitive declines, particularly among those at elevated preclinical cognitive risk. These individuals may be at the greatest risk of transitioning to dementia.

Adverse Childhood Experiences and Primary Headache Disorders: A Systematic Review, Meta-analysis, and Application of a Biological Theory.

Headache disorders are among the leading causes of disability worldwide. While an association between adverse childhood experiences and primary headaches has been reported, the pooled magnitude across studies and pathways of the association are unknown. Our objectives were (1) to estimate the pooled effect of ≥1 adverse childhood experience (ACE) on primary headache disorders in adulthood and (2) to test the hypothesis that ACEs categorized as "threat" traumas or "deprivation" traumas have distinct effects on primary headaches based on a selected theory from our narrative review of how ACEs affect human development along the life course. PubMed, EMBASE, MEDLINE, Web of Science, Google Scholar, Biological Psychiatry, and gray literature were searched up to March 16, 2023 (PROSPERO, CRD42020223403). Selected articles included (1) observational studies with a comparator group, (2) ACEs that occurred before 18 years of age, and (3) primary headaches occurring at or after 21 years of age. Pooled odds ratios (ORs) were calculated using multilevel linear random-effects modeling. The narrative review included theories that describe how ACEs affect human development and disease across the life course. We selected a theory from our narrative review and tested ACEs categorized according to this theory for any modification of point estimates. Our search identified 32 studies, of which 28 were eligible for meta-analysis (n = 154,739 participants, 19 countries). The occurrence of ≥1 adverse childhood experience(s) was associated with primary headaches (pooled OR = 1.48 [95% CI 1.36-1.61]; high-quality evidence, 134,696 participants). As the number of ACEs increased, the odds of primary headaches increased (range: 1 ACE OR = 1.24 [95% CI 1.14-1.35] to ≥4 ACEs OR = 2.09 [95% CI 1.83-2.38], p for trend <0.0001). From the narrative review, a neurodevelopmental theory that categorizes ACEs into threat or deprivation was tested, and both were independently associated with primary headaches (threat OR = 1.46 [95% CI 1.32-1.60] and deprivation OR = 1.35 [95% CI 1.23-1.49], respectively), accounting for heterogeneity (p = 0.021). This systematic review and meta-analysis confirm that ACEs are important risk factors of primary headache disorders in adulthood. Our findings provide epidemiologic support that ACEs categorized as threat and deprivation may manifest as distinct pathways of early adversity.

Efficacy of Willis covered stent of intracranial pseudoaneurysms in the internal carotid artery: A systematic review and meta-analysis

Objective: To evaluate the efficacy of a novel coated stent in the treatment of intracranial pseudoaneurysm. Methods: MEDLINE, EMBASE, and PubMed databases were searched for literature published between 1990 and April 2022 according to PRISMA guidelines. All studies with ≥10 patients reporting successful implantation of Willis covered stent, therapeutic effect, complications, and postoperative follow-up were included. The combined incidence and corresponding 95% confidence intervals were assessed using a generalized linear mixed method and random effects model. Results: Five studies (116 patients with pseudoaneurysms) were included. The experimental groups in the selected studies showed a combined technical success rate of 81.03% (OR=18.31, 95% CI=9.39-35.69, I 2=79%, P&lt;0.001). Clinical follow-up showed that the complete cure rate was as high as 94.4% after the follow-up (OR=106.81, 95% CI=39.08-291.88, I 2=0%, P=0.71). Conclusions: Willis covered stent is feasible, safe, and effective in the treatment of intracranial pseudoaneurysm.

Allometric model for height estimation of Alnus acuminata Kunth in agroecological zones of the high Andean tropics

The complexity in the management of field tools for recording dasometric information has led to the use of allometric equations that save time, work, and costs allowing the estimation of variables that are difficult to record, such as total height (TH). The objective of this research was to develop an allometric equation for the species Alnus acuminata in order to calculate TH from the diameter at breast height (DBH). At the Obonuco-AGROSAVIA Research Center in Pasto (Nariño), dasometric information was recorded for 75 months for 200 even-aged trees. Four models were evaluated: linear, polynomial, Mixed linear (random effect per tree age), and Mixed linear (random effect per tree). For the selection of the best model, the criteria were used with the lowest values ​​of Akaike (AIC) and Bayesian (BIC). The information was analyzed using the "Nonlinear Mixed-Effects Models" package, R software. The results revealed that A. acuminata had an 81% survival; the TH average was 7.4 ± 1.3 m; and the average DBH was 9.51 ± 2.23cm. The average annual increase of DBH was 1.5 cm year-1, and the TH was 1.18 m∙ per year-1. The mixed linear model confirmed the assumptions of normality, independence, and homogeneity of variances in addition of having good criteria in its predictive performance and efficiency through the equation TH=2.07+0.35*DBH+0.95*Age. This research contributes to the management of native species of the high tropics by designing an equation for the first vegetative growth phases of A. acuminata in high mountain agroecological zones.

A comparative study of different variable selection methods based on numerical simulation and empirical analysis.

This study employs the principles of computer science and statistics to evaluate the efficacy of the linear random effect model, utilizing Lasso variable selection techniques (including Lasso, Elastic-Net, Adaptive-Lasso, and SCAD) through numerical simulation and empirical research. The analysis focuses on the model's consistency in variable selection, prediction accuracy, stability, and efficiency. This study employs a novel approach to assess the consistency of variable selection across models. Specifically, the angle between the actual coefficient vector β and the estimated coefficient vector is computed to determine the degree of consistency. Additionally, the boxplot tool of statistical analysis is utilized to visually represent the distribution of model prediction accuracy data and variable selection consistency. The comparative stability of each model is assessed based on the frequency of outliers. This study conducts comparative experiments of numerical simulation to evaluate a proposed model evaluation method against commonly used analysis methods. The results demonstrate the effectiveness and correctness of the proposed method, highlighting its ability to conveniently analyze the stability and efficiency of each fitting model.

Modeling fuel consumption in various external vehicle conditions for military vehicle using mixed linear models

With the crisis in fuel consumption, it is necessary to save fuel consumption by selecting fuel that is quite efficient. The aim of the research is to examine the fuel consumption patterns of vehicles in an area that experiences various weathers so as to determine the level of efficiency of fuel use. both from the factor of fuel type, distance, speed, temperature, to the weather. testing was carried out using the linear model technique, the Linear Mixed effect model, and the Anova mathematical model. The results of the analysis if the different types of fuel have a very large significant effect in influencing the fuel consumption of a vehicle. With all the approaches analyzed from the linear mix model, analysis of variance and linear mix random effect model, the results show that other independent variables such as average speed, distance traveled and ambient temperature do not have much effect on fuel consumption. Based on modeling results that has been done, it can be identified if fuel consumption is strongly influenced by the type of fuel used by the vehicle. Meanwhile, other variables such as vehicle mileage, average speed, and ambient temperature at the time of data collection did not show any significant effect on fuel consumption.

Seasonal dynamics of herbaceous layer biomass and its contribution to annual net primary production in an oak–hornbeam forest

The role of the herbaceous layer in carbon assimilation and nutrient cycling is still undiscovered and unappreciated. One reason is that simple methods of annual net primary production (ANPP) estimation often underestimate its value, while more accurate methods are too labor-demanding. Moreover, studies on herbaceous layer and litterfall biomass in the same study site are extremely rare and usually conducted during one vegetation season, providing temporally-specific estimates. We hypothesized that (1) the seasonal herb layer biomass dynamics show a two-peak shape and (2) contribution of herbaceous layer biomass production in annual litter production was not more than 5% of tree litterfall. We studied the herb layer and litterfall biomass dynamics in an oak-hornbeam forest in W Poland for three years (January 2013 – October 2015). Samples of the herb layer (ten samples for four sample plots) were collected weekly in March, April and May or every two weeks for the remainder of each year, and litterfall was collected every month. All herb plants were cut at the soil level from circular frames with an area of 0.16 m2. Litterfall was studied with thirty litter traps (height of 15 cm, and catching area of 0.36 m2). We performed Kruskal–Wallis tests with Dunn’s post hoc tests to assess differences in variables among all collection times and linear random effects models to assess variance sources. We observed the highest biomass in 2013 on May 3rd (47.05 g m−2), and the lowest on October 30th in 2015 (4.69 g m−2). The seasonal herb layer biomass dynamic showed a single-peak shape; a very distinct peak occurred in spring and continued in late spring, summer, and early autumn. The spring ephemeralAnemone nemorosahad the highest share of herbaceous layer ANPP with 27% and was responsible for the spring biomass peak every season. The mean contribution of the herb layer biomass in annual litterfall was 9.23%. Our results highlight the underestimation of the herb layer role in biomass production in forest ecosystems in previous studies.

Efficient peer effects estimators with group effects

We study linear peer effect models where peers interact in groups and individual’s outcomes are linear in the group mean outcome and characteristics. We allow for unobserved random group effects as well as observed fixed group effects. The specification is in part motivated by the moment conditions imposed in Graham (2008). We show that these moment conditions can be cast in terms of a linear random group effects model and that they lead to a class of GMM estimators with parameters generally identified as long as there is sufficient variation in group size or group types. We also show that our class of GMM estimators contains a Quasi Maximum Likelihood estimator (QMLE) for the random group effects model, as well as the Wald estimator of Graham (2008) and the within estimator of Lee (2007) as special cases. Our identification results extend insights in Graham (2008) that show how assumptions about random group effects, variation in group size and certain forms of heteroscedasticity can be used to overcome the reflection problem in identifying peer effects. Our QMLE and GMM estimators accommodate additional covariates and are valid in situations with a large but finite number of different group sizes or types. Because our estimators are general moment based procedures, using instruments other than binary group indicators in estimation is straight forward. Our QMLE estimator accommodates group level covariates in the spirit of Mundlak and Chamberlain and offers an alternative to fixed effects specifications. This model feature significantly extends the applicability of Graham’s identification strategy to situations where group assignment may not be random but correlation of group level effects with peer effects can be controlled for with observable group level characteristics. Monte-Carlo simulations show that the bias of the QMLE estimator decreases with the number of groups and the variation in group size, and increases with group size. We also prove the consistency and asymptotic normality of the estimator under reasonable assumptions.

The Associations of Birthweight for Gestational Age Status with Its Differential 0-2 Year Growth Trajectory and Blood Pressure at Two Years of Age in Chinese Boys and Girls.

The first 1000 days of life represents a critical period for lifelong metabolic health. This study prospectively examined the contrasts between the growth trajectories of large, small, and appropriate sizes for gestational age (LGA, SGA, and AGA) term-born infants in their first two years, and their blood pressure at two years. In 2012-2013, 806 Chinese mother-newborn dyads were enrolled in the Shanghai Obesity and Allergy Birth Cohort Study. Repeated anthropometric measures were obtained at age 42 days, and at 3, 6, 9, 12, 18 and 24 months. Systolic and diastolic blood pressure (SBP, DBP) were measured at two years of age. Linear random effect models were employed to evaluate growth trajectory differences between LGA, SGA, and AGA infants. Of the study infants, 12.4% were LGA and 4.0% SGA. Length, weight, and weight-for-length z-score (ZWFL) were all consistently higher in LGA infants and lower in SGA infants than AGA infants. SGA infants had a higher ZWFL (0.11 unit/month; 95% CI: 0.04, 0.19) and a higher BMI (0.19; 95% CI: 0.09, 0.28 kg/m2 per month) growth velocity at age 0-6 months, relative to AGA infants. SGA was associated with 6.4 (0.4-12.4) mmHg higher SBP, and LGA was associated with 2.9 (95% CI -5.2, -0.5) mmHg lower DBP at two years of age in boys, however, not in girls. In conclusion, in this prospective birth cohort with repeated anthropometric measures and BP at two years of age, LGA, SGA, and AGA term-born infants manifested differential patterns of weight growth trajectory and BP, providing new insight into developmental origins of cardiometabolic health.

Associations between air pollutants and blood pressure in an ethnically diverse cohort of adolescents in London, England.

Longitudinal evidence on the association between air pollution and blood pressure (BP) in adolescence is scarce. We explored this association in an ethnically diverse cohort of schoolchildren. Sex-stratified, linear random-effects modelling was used to examine how modelled residential exposure to annual average nitrogen dioxide (NO2), particulate matter (PM2.5, PM10) and ozone (O3), measures in μg/m3, associated with blood pressure. Estimates were based on 3,284 adolescents; 80% from ethnic minority groups, recruited from 51 schools, and followed up from 11-13 to 14-16 years old. Ethnic minorities were exposed to higher modelled annual average concentrations of pollution at residential postcode level than their White UK peers. A two-pollutant model (NO2 & PM2.5), adjusted for ethnicity, age, anthropometry, and pubertal status, highlighted associations with systolic, but not diastolic BP. A μg/m3 increase in NO2 was associated with a 0.30 mmHg (95% CI 0.18 to 0.40) decrease in systolic BP for girls and 0.19 mmHg (95% CI 0.07 to 0.31) decrease in systolic BP for boys. In contrast, a 1 μg/m3 increase in PM2.5 was associated with 1.34 mmHg (95% CI 0.85 to 1.82) increase in systolic BP for girls and 0.57 mmHg (95% CI 0.04 to 1.03) increase in systolic BP for boys. Associations did not vary by ethnicity, body size or socio-economic advantage. Associations were robust to adjustments for noise levels and lung function at 11-13 years. In summary, higher ambient levels of NO2 were associated with lower and PM2.5 with higher systolic BP across adolescence, with stronger associations for girls.

Air pollution and plasma amyloid beta in a cohort of older adults: Evidence from the Ginkgo Evaluation of Memory study

Air pollution has been linked to Alzheimer’s disease and related dementias (ADRD), but the mechanisms connecting air pollution to ADRD have not been firmly established. Air pollution may cause oxidative stress and neuroinflammation and contribute to the deposition of amyloid beta (Aβ) in the brain. We examined the association between fine particulate matter<2.5 μm in diameter (PM2.5), particulate matter<10 μm in diameter (PM10), nitrogen dioxide (NO2), and plasma based measures of Aβ1-40, Aβ1-42 and Aβ1-42/Aβ1-40 using data from 3044 dementia-free participants of the Ginkgo Evaluation of Memory Study (GEMS). Air pollution exposures were estimated at residential addresses that incorporated address histories dating back to 1980, resulting in one-, five-, 10- and 20- year exposure averages. Aβ was measured at baseline (2000–2002) and then again at the end of the study (2007–2008) allowing for linear regression models to assess cross-sectional associations and linear random effects models to evaluate repeated measures. After adjustment for socio-demographic and behavioral covariates, we found small positive associations between each air pollutant and Aβ1-40 but no association with Aβ1-42 or the ratio measures in cross sectional analysis. In repeat measures analysis, we found larger positive associations between each air pollutant and all three outcomes. We observed a 4.43% (95% CI 3.26%, 5.60%) higher Aβ1-40 level, 9.73% (6.20%, 13.38%) higher Aβ1-42 and 1.57% (95% CI: 0.94%, 2.20%) higher Aβ1-42/Aβ1-40 ratio associated with a 2 µg/m3 higher 20-year average PM2.5. Associations with other air pollutants were similar. Our study contributes to the broader evidence base on air pollution and ADRD biomarkers by evaluating longer air pollution exposure averaging periods to better mimic disease progression and provides a modifiable target for ADRD prevention.

Association Between Exposure to Ozone (O3) and the Short-Term Effect on Tuberculosis Outpatient Visits: A Time-Series Study in 16 Cities of Anhui Province, China.

Evidence has shown that air pollutant exposure plays a vital role in the progression of tuberculosis (TB). The aim of this research was to assess the short-term effects of ozone (O3) exposure and TB outpatient visits in 16 prefecture-level cities of Anhui, China, 2015-2020. Distributed lag nonlinear model (DLNM), Poisson generalized linear regression model and random effects model were applied in this study. The effects of different age and gender on TB were investigated by stratified analysis, and then we performed sensitivity analyses to verify the stability of the results. A total of 186,623 active TB cases were registered from January 1, 2015 to December 31,2020 in Anhui. The average concentration of ozone is 92.77 ± 42.95 μg/m3. The maximum lag-specific and cumulative relative risk (RR) of TB outpatient visits was 1.0240 (95% CI: 1.0170-1.0310, lag 28 days) for each 10 µg/m³ increase in O3 in the single-pollutant model. Estimation for 16 prefecture-level cities indicated that the strong association between O3 and the risk of TB outpatient visits was in tongling (RR = 1.0555, 95% CI: 1.0089-1.1042), Suzhou (RR = 1.0475, 95% CI: 1.0268-1.0687), wuhu (RR = 1.0358, 95% CI: 1.0023-1.0704). Stratified analysis showed that the health effects of ozone exposure remained significant in male and older adults, and there was no significant association between exposure to ozone in children and adolescents and the risk of tuberculosis. We found that ozone exposure increases the risk of TB infection in outpatient patients, with males and the elderly being more susceptible, and it is necessary for government departments to develop targeted publicity and prevention measures in response to the local air quality conditions.

Labor and infrastructure factors affecting provincial distribution of foreign direct investment in Vietnam

The study assesses the influence of labor and infrastructure on attracting foreign direct investment (FDI) to the provinces of Vietnam in the period of 2009 - 2020. Research results from linear regression model and random effects estimation method have confirmed the importance of human capital and infrastructure in attracting FDI. The labor-related aspects in this study confirm that tendency of MNEs focusing on labor-intensive industries in Vietnam has not changed. The study also provides policy implications as building and improving the quality of infrastructure with the main goal of reducing inequality in attracting more FDI inflows to Vietnam's provinces in the near future. In addition, the workforce needs to have a plan to prepare themselves with solid knowledge and necessary skills to hone and absorb the know-how transferred from foreign investment companies, to have an ability to contribute to the development of the quality of our country's human resources.

Investigating longitudinal associations of hair cortisol and cortisone with cognitive functioning and dementia

We rigorously investigated potential longitudinal associations of hair cortisol and cortisone with verbal memory, time orientation, and dementia, adjusting for sociodemographic and health confounders. Data from the English Longitudinal Study of Ageing wave 6–9 (6-year follow-up, covering 4399 persons aged 50+) were analysed using linear random effects and cox regression models. In unadjusted models, hair cortisol was associated with worsened verbal memory (β 0.19; SE 0.08), but not with time orientation (β 0.02; SE 0.01), or dementia (β 0.07; SE 0.16). Hair cortisone was associated with worsened verbal memory (β 0.74; SE 0.14) and time orientation (β 0.06; SE 0.02), but not with dementia (β 0.47; SE 0.28). However, in the fully adjusted models, neither hair cortisol nor cortisone was associated with verbal memory, time orientation, or dementia. Consistent with prior studies, we found that more advanced age was associated with worsened verbal memory (β 0.15; SE 0.01), time orientation (β 0.01; SE 0.00), and dementia risk (β 0.11; SE 0.02). Our rigorous analyses did not detect robust associations of neither hair cortisol nor cortisone with cognitive functioning or dementia across 6 years. More detailed insights into potential mechanisms are discussed.

Protocol for a systematic review and meta-analysis of minimal important differences for generic multiattribute utility instruments

IntroductionGeneric multiattribute utility instruments (MAUIs) are efficient tools for determining and enumerating health-related quality of life. MAUIs accomplish this by generating health state utilities (HSUs) via algorithms. Minimal important differences...