Tag: statistics

Med Sci Sports Exerc. 2023 Jan 12. doi: 10.1249/MSS.0000000000003123. Online ahead of print.

ABSTRACT

PURPOSE: Harmonization of assessment methods represents an ongoing challenge in physical activity research. Previous research has demonstrated the utility of calibration approaches to enhance agreement between measures of physical activity. The present study utilizes a calibration methodology to add behavioral context from the Global Physical Activity Questionnaire (GPAQ), an established report-based measure, to enhance interpretations of monitor-based data scored using the novel Monitor Independent Movement Summary (MIMS) methodology.

METHODS: Matching data from the GPAQ and MIMS were obtained from adults (20-80 years of age) assessed in the 2011-2014 National Health and Nutrition Examination Survey (NHANES). After developing percentile curves for self-reported activity, a zero-inflated quantile regression model was developed to link MIMS to estimates of moderate to vigorous physical activity (MVPA) from the GPAQ.

RESULTS: Cross validation of the model showed that it closely approximated the probability of reporting MVPA across age and activity level segments, supporting the accuracy of the zero-inflated model component. Validation of the quantile regression component directly corresponded to the 25%, 50% and 75% values for both males and females, further supporting the model fit.

CONCLUSIONS: This study offers a method of improving activity surveillance by translating accelerometer signals into interpretable behavioral measures using nationally representative data. The model provides accurate estimates of minutes of MVPA at a population level but, due to the bias and error inherent in report-based measures of physical activity, is not suitable for converting or interpreting individual level data. This study provides an important preliminary step in utilizing information from both device- and report-based methods to triangulate activity related outcomes; however additional measurement error modeling is needed to improve precision.

PMID:36633833 | DOI:10.1249/MSS.0000000000003123

Drugs Aging. 2023 Jan 12. doi: 10.1007/s40266-022-00994-3. Online ahead of print.

ABSTRACT

The lifetime risk of symptomatic hand osteoarthritis (OA) is 39.8%, with one in two women and one in four men developing the disease by age 85 years and no disease-modifying drug (DMOAD) available so far. Intra-articular (IA) therapy is one of the options commonly used for symptomatic alleviation of OA disease as it can circumvent systemic exposure and potential side effects of oral medications. The current narrative review focuses on the efficacy and safety profiles of the currently available IA agents in hand OA (thumb-base OA or interphalangeal OA) such as corticosteroids and hyaluronic acid (HA), as well as the efficacy and safety of IA investigational injectates in phase 2/3 clinical trials such as prolotherapy, platelet-rich plasma, stem cells, infliximab, interferon-? and botulinum toxin, based on the published randomized controlled trials on PubMed database. The limited published literature revealed the short-term symptomatic benefits of corticosteroids in interphalangeal OA while long-term data are lacking. Most of the short-term studies showed no significant difference between corticosteroids and hyaluronic acid in thumb-base OA, usually with a faster onset of pain relief in the corticosteroid group and a slower but greater (statistically insignificant) pain improvement in the HA group. The majority of studies in investigational agents were limited by small sample size, short-term follow-up, and presence of serious side effects. In addition, we reported higher accuracy rates of drug administrations under imaging guidance than landmark guidance (blind method), and then briefly describe challenges for the long-term efficacy and prospects of IA therapeutics.

PMID:36633823 | DOI:10.1007/s40266-022-00994-3

Rheumatol Ther. 2023 Jan 12. doi: 10.1007/s40744-022-00522-0. Online ahead of print.

ABSTRACT

INTRODUCTION: Biologic disease-modifying anti-rheumatic drugs (bDMARDs), including certolizumab pegol (CZP), are effective treatment options for the management of non-radiographic spondyloarthritis (nr-axSpA). In the absence of head-to-head comparisons in nr-axSpA, we conducted a systematic literature review (SLR) and indirect treatment comparison (ITC) to better understand the comparative efficacy of CZP vs. other bDMARDs.

METHODS: Literature searches were conducted in October 2020 in MEDLINE, Embase, and the Cochrane Central Register of Controlled Trials to identify randomized controlled trials in patients with nr-axSpA who had failed at least one non-steroidal anti-inflammatory drug and were treated with bDMARDs. Outcomes of interest included the Assessment of Spondyloarthritis international Society (ASAS), Ankylosing Spondylitis Disease Activity Score (ASDAS), Bath Ankylosing Spondylitis Functional Index (BASFI) and Disease Activity Index (BASDAI), and spinal pain score. Comparative efficacy was examined using a series of Bucher ITCs in subgroups matched by prior exposure to bDMARDs, disease duration, baseline C-reactive protein (CRP) levels/magnetic resonance imaging (MRI) status, and timepoints, to ensure comparability between studies.

RESULTS: At 12-16 weeks, treatment with CZP was significantly more likely to achieve ASAS20/40 response and ASDAS-inactive disease status vs. etanercept (ETN), ixekizumab (IXE), and secukinumab (SEC). CZP showed statistically significant improvement in BASDAI, BASFI, and total spine pain score over adalimumab (ADA), ETN, and IXE, and in BASFI over SEC. Among patients with objective signs of inflammation (OSI; elevated CRP levels and/or inflammation on MRI at baseline), CZP had a statistically significant advantage over ETN and SEC (with or without loading dose) in achieving ASAS40, whereas the comparisons with other bDMARDs did not show any statistically significant differences.

CONCLUSION: In the overall matched population, CZP performed significantly better than most comparators in improving the clinical outcomes. Among patients with OSI, CZP was found to be superior to SEC (in the MRI-/CRP + and MRI + /CRP- subgroups) and ETN (in the MRI + /CRP- subgroup) and it was comparable to golimumab and IXE across the different OSI subgroups.

PMID:36633815 | DOI:10.1007/s40744-022-00522-0

Neuropsychol Rev. 2023 Jan 12. doi: 10.1007/s11065-022-09574-z. Online ahead of print.

ABSTRACT

Executive Functions are a set of interrelated, top-down processes essential for adaptive goal-directed behaviour, frequently impaired across different neurodevelopmental disorders with variable degrees of severity. Many executive-function-training studies in children with neurodevelopmental disorders have focused on near effects, investigating post-treatment improvements on directly trained processes, while enhancements of skills not directly trained, defined as far effects, are less considered, albeit these could be extremely relevant for reducing the negative impact of a disorder’s core symptomatology. This systematic review and metanalysis aims to investigate the far effect outcomes after EF training in children with different types of neurodevelopmental disorders. 17 studies met the inclusion criteria for the systematic review, while 15 studies were selected in the metanalysis. An overall statistically significant effect size was found in the majority of far effect outcome measures considered in the studies. In particular, trainings on executive functions determine significant far effects on daily life functioning (0.46, 95% CI: [0.05-0.87]) and clinical symptoms (0.33, 95% CI: [0.15-0.51]). Despite a high variability of the results, intensity, frequency and the laboratory/life contexts dimension seem to be the most influential variables in determining far effects. This systematic review and metanalysis highlights the need to measure far effects of executive function training in neurodevelopmental disorders, selecting treatments not only on directly targeted processes, but also according to far impacts on the functional weakness of the disorder.

PMID:36633797 | DOI:10.1007/s11065-022-09574-z

Odontology. 2023 Jan 12. doi: 10.1007/s10266-023-00784-2. Online ahead of print.

ABSTRACT

The main objective of the present study was to evaluate the effect of the morphology of titanium dioxide nanofillers on the flexural strength and shear bond strength of the dental composite. Spherical and rhombic-shaped nano titanium dioxide fillers were synthesized via solvothermal method and were characterized. Subsequently, these fillers were incorporated into a flowable composite (Filtek^™ Z350 XT Flowable Restorative) at 0.5 wt.% and 1.5 wt.% and the prepared specimens were stored in water for 24 h. The specimens were then evaluated for flexural strength using a universal testing machine. Similarly, the shear bond strength of modified composites to the tooth was evaluated and bond failures were analyzed using stereomicroscope magnification. Incorporation of nanofillers significantly enhanced the flexural strength of flowable composite (p = 0.009) with a significant increase at 0.5wt.% of spherical (p = 0.015) and rhomboidal-shaped fillers (p = 0.010). However, no statistically significant difference in flexural strength was observed among the different shapes of nanofillers. The results of our study did not show a significant effect on the shear bond strength of the composites. Thus the reinforcing ability of titanium dioxide nanofillers on dental composite was confirmed in this study, although the effect of using nanofillers with different morphology was not significant.

PMID:36633793 | DOI:10.1007/s10266-023-00784-2

Biol Trace Elem Res. 2023 Jan 12. doi: 10.1007/s12011-023-03554-x. Online ahead of print.

ABSTRACT

The association between circulating copper and the risk of liver cancer has been investigated by previous studies, while the findings were inconsistent. Thus, we aimed to evaluate the association between circulating copper and liver cancer by using meta-analysis and Mendelian randomization (MR). For meta-analysis, PubMed and Web of Science were searched to identify eligible studies published before April 4, 2022. Standardized mean difference (SMD) with 95% confidence interval (CI) in circulating copper level between liver cancer patients and controls were pooled. Furthermore, we selected genetic instruments for circulating copper from a genome-wide association study (GWAS) to conduct MR analysis. The summary statistics related to liver cancer were obtained from two large independent cohorts, UKBB and FinnGen, respectively. MR analysis was performed mainly by inverse-variance weighted (IVW) approach, followed by maximum-likelihood method as sensitivity analysis. In meta-analysis of eight studies, circulating copper was found to be higher in liver cancer patients (SMD: 1.65; 95% CI: 0.65 to 2.65) with high heterogeneity (I² = 96.40%, P = 0.001). However, inconsistent findings were observed among subgroups with high evidence. In MR analysis, genetically predicted circulating copper was not significantly associated with the risk of liver cancer by IVW in UKBB (OR: 1.38; 95% CI: 0.72 to 2.65) and FinnGen (OR: 1.10; 95% CI: 0.69 to 1.73) separately, and the pooled results produced similar results (OR: 1.18, 95% CI: 0.81 to 1.72). Moreover, non-significant finding was confirmed by using maximum-likelihood method. There is no sufficient evidence to demonstrate that high levels of circulating copper increase the risks of liver cancer.

PMID:36633787 | DOI:10.1007/s12011-023-03554-x

Prev Sci. 2023 Jan 12. doi: 10.1007/s11121-022-01485-y. Online ahead of print.

ABSTRACT

A variety of health and social problems are routinely measured in the form of categorical outcome data (such as presence/absence of a problem behavior or stages of disease progression). Therefore, proper quantitative analysis of categorical data lies at the heart of the empirical work conducted in prevention science. Categorical data analysis constitutes a broad dynamic field of methods research and data analysts in prevention science can benefit from incorporating recent advances and developments in the statistical evaluation of categorical outcomes in their methodological repertoire. The present Special Issue, Advanced Categorical Data Analysis in Prevention Science, highlights recent methods developments and illustrates their application in the context of prevention science. Contributions of the Special Issue cover a wide variety of areas ranging from statistical models for binary as well as multi-categorical data, advances in the statistical evaluation of moderation and mediation effects for categorical data, developments in model evaluation and measurement, as well as methods that integrate variable- and person-oriented categorical data analysis. The articles of this Special issue make methodological advances in these areas accessible to the audience of prevention scientists to maintain rigorous statistical practice and decision making. The current paper provides background and rationale for this Special Issue, an overview of the articles, and a brief discussion of some potential future directions for prevention research involving categorical data analysis.

PMID:36633766 | DOI:10.1007/s11121-022-01485-y

Environ Sci Pollut Res Int. 2023 Jan 12. doi: 10.1007/s11356-022-25051-9. Online ahead of print.

ABSTRACT

Phthalate metabolites have been detected from urine in most of the US population and have become a public health problem. However, the association between phthalate metabolites and hyperuricemia has been scarcely studied so far. We aimed to evaluate if phthalate metabolites were associated with hyperuricemia in US adults. A total of 8816 participants of the National Health and Nutrition Examination Survey (NHANES) from 2005 to 2018 were included in our study. We used multivariable logistic regression models and restricted cubic spline (RCS) models to explore the association between urinary phthalate metabolites and hyperuricemia. Then, stratified analyses were conducted by sex and age. The prevalence of hyperuricemia in the study sample was 20.35%. Compared to the lowest quantile, the odds ratios (ORs) and 95% confidence intervals (CIs) for hyperuricemia were all statistically significant in following phthalate metabolites: 1.34 (1.13-1.58) for the second quartile in Mono-isobutyl phthalate (MiBP), 1.21 (1.01-1.46) for the highest quartile in Mono-(carboxyoctyl) phthalate (MCOP), 0.66 (0.56-0.76) for the second quartile in Mono-(2-ethyl)-hexyl phthalate (MEHP), 1.22 (1.05-1.43) for quartile 2 in Benzyl butyl phthalate (ΣBBP), and 1.43 (1.22-1.66) for the third quartile in high molecular-weight phthalate (ΣHigh MWP), respectively. Our results indicate that several urinary phthalate metabolites are positively associated with the odds of hyperuricemia.

PMID:36633744 | DOI:10.1007/s11356-022-25051-9

Environ Sci Pollut Res Int. 2023 Jan 12. doi: 10.1007/s11356-022-24824-6. Online ahead of print.

ABSTRACT

Epidemiological studies using conventional statistical methods have reported an association between individual metal exposure and hyperuricemia (HUA). There is also evidence that diet may influence HUA development, although the available data are inconsistent. We therefore used an elastic net regression (ENR) model to screen the usefulness of various environmental and dietary factors as predictors of HUA in a large sample cohort. This study included 6217 subjects drawn from the Shenzhen Aging Related Disorder Cohort. We obtained information on the subjects’ dietary habits via face-to-face interviews and used inductively coupled plasma mass spectrometry (ICP-MS) to measure the urinary concentrations of 24 metals to which elderly persons in large urban areas may be exposed. An elastic net regression (ENR) model was generated to screen the utility of the metals and dietary factors as predictors of HUA, and we demonstrated the superiority of the ENR model by comparing it to a traditional logistic regression model. The identified predictors were used to create a clinically usable nomogram for identifying patients at risk of developing HUA. The area under curve (AUC) value of the final model was 0.692 for the training set and 0.706 for the test set. Important predictors of HUA were Zn, As, V, and Fe as well as consumption of wheat, beans, and rice; the corresponding estimated odds ratios and 95% confidence intervals were 1.091 (0.932,1.251), 1.190 (1.093,1.286), 0.924 (0.793,1.055), 0.704 (0.626,0.781), 0.998 (0.996,1.001), 0.993 (0.989,0.998), and 1.001 (0.998,1.002), respectively. In contrast to previous studies, we found that both urinary metal concentrations and dietary habits are important for predicting HUA risk. Exposure to specific metals and consumption of specific foods were identified as important predictors of HUA, indicating that the incidence of this disease could be reduced by reducing exposure to these metals and promoting improved dietary habits.

PMID:36633743 | DOI:10.1007/s11356-022-24824-6

Environ Sci Pollut Res Int. 2023 Jan 12. doi: 10.1007/s11356-023-25169-4. Online ahead of print.

ABSTRACT

Industrial structure low-carbon restructuring is an essential channel to accelerate China’s economic growth and fulfilling carbon emission reduction goals. Whether carbon emission trading pilot policy, as an influential carbon reduction instrument, fosters industrial structure low-carbon restructuring is of major significance to green economic development. This paper empirically investigates the shock of the carbon emission trading pilot policy on industrial structure low-carbon restructuring using the differences-in-differences (DID) and synthetic control method (SCM). Statistics reveal that sectors with low carbon productivity, such as electricity, steam, and hot water production and supply, ferrous metal smelting and pressing, etc., and sectors with high carbon productivity, such as electrical equipment and machinery, electronics and telecommunication equipment, etc. The industrial structure did not develop a stable trend of change before the 12th Five-Year Plan, but a stable trend of low-carbon restructuring emerged after such a period. Carbon emission trading pilot policy significantly facilitates industrial structural low-carbon restructuring. Carbon emission trading pilot policy inhibits energy-intensive industries in the industrial sector significantly, which promotes industrial structure low-carbon restructuring. Therefore, policymakers need to develop a nationwide carbon emission trading market that includes more industries to guide production factors to industrial sectors with high carbon productivity for industrial restructuring and dual carbon goals.

PMID:36633739 | DOI:10.1007/s11356-023-25169-4