A review of spline function procedures in R

Gene regulatory network analysis identifies MYL1, MDH2, GLS, and TRIM28 as the principal proteins in the response of mesenchymal stem cells to Mg2+ ions

Magnesium (Mg)-based implants have emerged as a promising alternative for orthopedic applications, owing to their bioactive properties and biodegradability. As the implants degrade, Mg2+ ions are released, influencing all surrounding cell types, especially mesenchymal stem cells (MSCs). MSCs are vital for bone tissue regeneration, therefore, it is essential to understand their molecular response to Mg2+ ions in order to maximize the potential of Mg-based biomaterials. In this study, we conducted a gene regulatory network (GRN) analysis to examine the molecular responses of MSCs to Mg2+ ions. We used time-series proteomics data collected at 11 time points across a 21-day period for the GRN construction. We studied the impact of Mg2+ ions on the resulting networks and identified the key proteins and protein interactions affected by the application of Mg2+ ions. Our analysis highlights MYL1, MDH2, GLS, and TRIM28 as the primary targets of Mg2+ ions in the response of MSCs during 1-21 days phase. Our results also identify MDH2-MYL1, MDH2-RPS26, TRIM28-AK1, TRIM28-SOD2, and GLS-AK1 as the critical protein relationships affected by Mg2+ ions. By offering a comprehensive understanding of the regulatory role of Mg2+ ions on MSCs, our study contributes valuable insights into the molecular response of MSCs to Mg-based materials, thereby facilitating the development of innovative therapeutic strategies for orthopedic applications.

Sonomorphologic Changes in Colorectal Deep Endometriosis: The Long-Term Impact of Age and Hormonal Treatment

PURPOSE

The progression of deep endometriosis (DE) in women of reproductive age is highly variable. This study aimed to analyze the sonomorphological changes of rectal endometriosis over long periods of time and the influence of hormonal treatment.

METHODS

This retrospective study included premenopausal women with rectal DE treated conservatively between 2002 and 2021. The lesion length and thickness of the nodule were evaluated at regular intervals over time. We created statistical models with mixed effects to identify potential factors influencing lesion progression and regression.

RESULTS

38 patients were monitored over a mean period of 7.2 (± 4.2) years with a mean of 3.1 (± 2.1) check-ups within the observation period. We detected a significant increase in lesion length until the end of the fourth decade of life. In addition, we found a substantial decrease in the length and thickness of the nodule depending on the length of hormonal treatment.

CONCLUSION

In conservatively managed patients with rectal endometriosis, without hormonal therapy, lesion size can exhibit a moderate increase up to the end of the fourth decade of life, after which it appears to stabilize. This increase does not follow a linear pattern. Hormonal therapy is crucial in impeding further progression, resulting in either a cessation or a regression of lesion growth.

The impact of major depressive disorder on glycaemic control in type 2 diabetes: a longitudinal cohort study using UK Biobank primary care records

BACKGROUND

This study evaluates longitudinal associations between glycaemic control, measured by mean and within-patient variability of glycated haemaglobin (HbA1c) levels, and major depressive disorder (MDD) in individuals with type 2 diabetes (T2D), focusing on the timings of these diagnoses.

METHODS

In UK Biobank, T2D was defined using self-report and linked health outcome data, then validated using polygenic scores. Repeated HbA1c measurements (mmol/mol) over the 10 years following T2D diagnosis were outcomes in mixed effects models, with disease duration included using restricted cubic splines. Four MDD exposures were considered: MDD diagnosis prior to T2D diagnosis (pre-T2D MDD), time between pre-T2D MDD diagnosis and T2D, new MDD diagnosis during follow-up (post-T2D MDD) and time since post-T2D MDD diagnosis. Models with and without covariate adjustment were considered.

RESULTS

T2D diagnostic criteria were robustly associated with T2D polygenic scores. In 11,837 T2D cases (6.9 years median follow-up), pre-T2D MDD was associated with a 0.92 increase in HbA1c (95% CI: [0.00, 1.84]), but earlier pre-T2D MDD diagnosis correlated with lower HbA1c. These pre-T2D MDD effects became non-significant after covariate adjustment. Post-T2D MDD individuals demonstrated increasing HbA1c with years since MDD diagnosis ( β = 0.51 , 95% CI: [0.17, 0.86]). Retrospectively, across study follow-up, within-patient variability in HbA1c was 1.16 (95% CI: 1.13-1.19) times higher in post-T2D MDD individuals.

CONCLUSIONS

The timing of MDD diagnosis is important for understanding glycaemic control in T2D. Poorer control was observed in MDD diagnosed post-T2D, highlighting the importance of depression screening in T2D, and closer monitoring for individuals who develop MDD after T2D.

A flexible time-varying coefficient rate model for panel count data

Panel count regression is often required in recurrent event studies, where the interest is to model the event rate. Existing rate models are unable to handle time-varying covariate effects due to theoretical and computational difficulties. Mean models provide a viable alternative but are subject to the constraints of the monotonicity assumption, which tends to be violated when covariates fluctuate over time. In this paper, we present a new semiparametric rate model for panel count data along with related theoretical results. For model fitting, we present an efficient EM algorithm with three different methods for variance estimation. The algorithm allows us to sidestep the challenges of numerical integration and difficulties with the iterative convex minorant algorithm. We showed that the estimators are consistent and asymptotically normally distributed. Simulation studies confirmed an excellent finite sample performance. To illustrate, we analyzed data from a real clinical study of behavioral risk factors for sexually transmitted infections.

Augmenting complex and dynamic performance through mindfulness-based cognitive training: An evaluation of training adherence, trait mindfulness, personality and resting-state EEG

Human performance applications of mindfulness-based training have demonstrated its utility in enhancing cognitive functioning. Previous studies have illustrated how these interventions can improve performance on traditional cognitive tests, however, little investigation has explored the extent to which mindfulness-based training can optimise performance in more dynamic and complex contexts. Further, from a neuroscientific perspective, the underlying mechanisms responsible for performance enhancements remain largely undescribed. With this in mind, the following study aimed to investigate how a short-term mindfulness intervention (one week) augments performance on a dynamic and complex task (target motion analyst task; TMA) in young, healthy adults (n = 40, age range = 18-38). Linear mixed effect modelling revealed that increased adherence to the web-based mindfulness-based training regime (ranging from 0-21 sessions) was associated with improved performance in the second testing session of the TMA task, controlling for baseline performance. Analyses of resting-state electroencephalographic (EEG) metrics demonstrated no change across testing sessions. Investigations of additional individual factors demonstrated that enhancements associated with training adherence remained relatively consistent across varying levels of participants' resting-state EEG metrics, personality measures (i.e., trait mindfulness, neuroticism, conscientiousness), self-reported enjoyment and timing of intervention adherence. Our results thus indicate that mindfulness-based cognitive training leads to performance enhancements in distantly related tasks, irrespective of several individual differences. We also revealed nuances in the magnitude of cognitive enhancements contingent on the timing of adherence, regardless of total volume of training. Overall, our findings suggest that mindfulness-based training could be used in a myriad of settings to elicit transferable performance enhancements.

Determination of speed and assessment of conditioning in horses submitted to a lactate minimum test-alternative approaches

The maximal lactate steady state (MLSS) is a well-known gold standard method for determining the aerobic capacity of athletic horses. Owing to its high cost and complex execution, there is a search for standardized exercise tests that can predict this value in a single session. One of the methods described for this purpose is the lactate minimum test (LMT), which could be more accurate despite being adequate to predict MLSS. This study aimed to examine the impact of training on the speed corresponding to lactate minimum speed (LMS) and to apply new mathematical methods to evaluate the fitness level of horses based on the curve obtained by the LMT. Ten Arabian horses underwent a 6-week training program based on LMS calculated by second-degree polynomial regression (LMSP). In addition, the LMS was also determined by visual inspection (LMSV), bi-segmented linear regression (LMSBI) and spline regression (LMSS). From the curve obtained during the LMT, it was possible to calculate angles α, β and ω, as well as the total area under the curve (AUCTOTAL) before (AUCPRELMS) and after (AUCPOSLMS) the LMS. The methods for determining the LMS were evaluated by ANOVA, intraclass correlation coefficient (ICC) and effect size (ES) by Cohen's d test. The Pearson correlation coefficient (r) between the proposed LMS determination methods and other mathematical methods was also calculated. Despite showing a good correlation (ICC >0.7), the LMS determination methods differed from each other (p < 0.05), albeit without a significant difference resulting from conditioning. There were reductions in α:β ratio, angle α, and AUCPOSTLMS, with the latter indicating lower lactate accumulation in the incremental phase of LMT after conditioning, in addition to an improvement in the animals' aerobic capacity. Considering that the most common methods for determining the LMS are applicable yet with low sensitivity for conditioning assessment, the approaches proposed herein can aid in analyzing the aerobic capacity of horses subjected to LMT. The mathematical models presented in this paper have the potential to be applied in human lactate-guided training program trials with a comparable study basis.

Raspberry leaf (Rubus idaeus) use in pregnancy: a prospective observational study

BACKGROUND

Raspberry leaf use during pregnancy in Australia is widespread. There has been little research exploring the potential beneficial or harmful effects of raspberry leaf on pregnancy, labour, and birth. More research is needed to appropriately inform childbearing women and maternity healthcare professionals on the effects of raspberry leaf so that women can make informed choices.

METHODS

This study aimed to determine associations between raspberry leaf use in pregnancy and augmentation of labour and other secondary outcomes. Data was derived from questionnaires which captured demographic information and herbal use in pregnancy. Clinical outcomes were accessed from the maternity services' clinical database. Data analysis was conducted in R via package 'brms' an implementation for Bayesian regression models.

RESULTS

A total of 91 completed records were obtained, 44 exposed to raspberry leaf and 47, not exposed. A smaller proportion of women in the raspberry leaf cohort had augmentation of labour, epidural anaesthesia, instrumental births, caesarean section, and postpartum haemorrhage. A larger proportion had vaginal birth and length of all phases of labour were shorter. Under these conditions the use of raspberry leaf was strongly predictive of women not having their labours medically augmented.

CONCLUSIONS

While our study demonstrated that raspberry leaf was strongly predictive of women not having their labours medically augmented, the results cannot be relied on or generalised to the wider population of pregnant women. While there were no safety concerns observed in our study, this should not be taken as evidence that raspberry leaf is safe. A randomised controlled trial is urgently needed to provide women and healthcare providers with robust evidence on which to base practice.

Tumour Size and Overall Survival in a Cohort of Patients with Unifocal Glioblastoma: A Uni- and Multivariable Prognostic Modelling and Resampling Study

Published models inconsistently associate glioblastoma size with overall survival (OS). This study aimed to investigate the prognostic effect of tumour size in a large cohort of patients diagnosed with GBM and interrogate how sample size and non-linear transformations may impact on the likelihood of finding a prognostic effect. In total, 279 patients with a IDH-wildtype unifocal WHO grade 4 GBM between 2014 and 2020 from a retrospective cohort were included. Uni-/multivariable association between core volume, whole volume (CV and WV), and diameter with OS was assessed with (1) Cox proportional hazard models +/- log transformation and (2) resampling with 1,000,000 repetitions and varying sample size to identify the percentage of models, which showed a significant effect of tumour size. Models adjusted for operation type and a diameter model adjusted for all clinical variables remained significant (p = 0.03). Multivariable resampling increased the significant effects (p < 0.05) of all size variables as sample size increased. Log transformation also had a large effect on the chances of a prognostic effect of WV. For models adjusted for operation type, 19.5% of WV vs. 26.3% log-WV (n = 50) and 69.9% WV and 89.9% log-WV (n = 279) were significant. In this large well-curated cohort, multivariable modelling and resampling suggest tumour volume is prognostic at larger sample sizes and with log transformation for WV.

Rethinking the effects of adjuvant beam radiation therapy on overall survival in atypical meningioma patients: age considerations

Background

This study aimed to investigate the effects of adjuvant beam radiation therapy (ABRT) on overall survival (OS) in patients with primary single intracranial atypical meningioma (AM), with a focus on age-related outcomes.

Methods

We conducted a retrospective study using data from SEER database. Our cohort consisted of patients diagnosed with a primary single intracranial AM tumor and had undergone surgery. The primary endpoint was OS. For survival analysis, univariable and multivariable Cox regression analysis were performed. A multivariable additive Cox model was used to assess the functional relationship between age and OS in patients with or without ABRT.

Results

Of the 2,759 patients included, 1,650 underwent gross total resection and 833 received ABRT. Multivariable Cox analysis indicated that ABRT did not significantly influence OS across the entire cohort. According to the multivariable generalized additive Cox model, the relative risk of all-cause mortality increased with advancing age in both ABRT-yes and ABRT-no group. ABRT-yes had a lower relative risk than ABRT-no when age ≤ 55 years old while a higher relative risk when age > 55 years old. Subsequent multivariable Cox analysis showed that ABRT was associated with a significant lower risk for all-cause mortality in patients with age ≤ 55 years old while a significant higher risk in patients with age > 55 years old.

Conclusion

Our study found that ABRT enhanced OS in younger primary single intracranial AM patients. But we also revealed a negative correlation between OS and ABRT in older patients.

Age at natural or surgical menopause, all-cause mortality, and lifespan among postmenopausal women in the United States

OBJECTIVE

This study investigated the association of age at natural menopause with or without undergoing hysterectomy and/or bilateral oophorectomy after menopause and age at surgical menopause with all-cause mortality and lifespan in postmenopausal women.

METHODS

The data stemmed from the National Health and Nutrition Examination Survey (NHANES) (1999-2018) and NHANES III (1988-1994), including 14,161 postmenopausal women over 40. Cox proportional hazard models were used to estimate unadjusted and adjusted hazard ratios (HRs) (95% confidence intervals [CIs]). We also used Cox proportional hazard models with penalized splines to depict the association between continuous age at menopause and all-cause mortality and nonparametric regression with smoothing splines to illustrate the association between age at menopause and lifespan in deceased participants.

RESULTS

The adjusted HRs (95% CIs) for age at natural menopause of <40, 40 to 44, and 55+ years in women without undergoing hysterectomy or bilateral oophorectomy after menopause were 1.48 (1.15-1.91), 1.16 (1.00-1.35), and 0.91 (0.77-1.07) compared with age at natural menopause of 45 to 54, respectively. The respective HRs (95% CIs) for age at surgical menopause were 1.39 (1.11-1.75), 1.09 (0.86-1.38), and 0.83 (0.53-1.32). However, no significant association was found between age at natural menopause and all-cause mortality among women undergoing hysterectomy and/or bilateral oophorectomy after menopause. When treated as continuous variables, age at natural menopause without undergoing hysterectomy or bilateral oophorectomy after menopause presented inverse and nonlinear associations with all-cause mortality, whereas age at surgical menopause was linearly inversely associated with all-cause mortality. The association between age at menopause and lifespan was linearly positive regardless of menopausal type.

CONCLUSION

Young age at menopause was associated with increased risks of all-cause mortality. The later menopause age was related to a longer lifespan.

A hypoxia biomarker does not predict benefit from giving chemotherapy with radiotherapy in the BC2001 randomised controlled trial

BACKGROUND

BC2001 showed combining chemotherapy (5-FU + mitomycin-C) with radiotherapy improves loco-regional disease-free survival in patients with muscle-invasive bladder cancer (MIBC). We previously showed a 24-gene hypoxia-associated signature predicted benefit from hypoxia-modifying radiosensitisation in BCON and hypothesised that only patients with low hypoxia scores (HSs) would benefit from chemotherapy in BC2001. BC2001 allowed conventional (64Gy/32 fractions) or hypofractionated (55Gy/20 fractions) radiotherapy. An exploratory analysis tested an additional hypothesis that hypofractionation reduces reoxygenation and would be detrimental for patients with hypoxic tumours.

METHODS

RNA was extracted from pre-treatment biopsies (298 BC2001 patients), transcriptomic data generated (Affymetrix Clariom-S arrays), HSs calculated (median expression of 24-signature genes) and patients stratified as hypoxia-high or -low (cut-off: cohort median).

PRIMARY ENDPOINT

invasive loco-regional control (ILRC); secondary overall survival.

FINDINGS

Hypoxia affected overall survival (HR = 1.30; 95% CI 0.99-1.70; p = 0.062): more uncertainty for ILRC (HR = 1.29; 95% CI 0.82-2.03; p = 0.264). Benefit from chemotherapy was similar for patients with high or low HSs, with no interaction between HS and treatment arm. High HS associated with poor ILRC following hypofractionated (n = 90, HR 1.69; 95% CI 0.99-2.89 p = 0.057) but not conventional (n = 207, HR 0.70; 95% CI 0.28-1.80, p = 0.461) radiotherapy. The finding was confirmed in an independent cohort (BCON) where hypoxia associated with a poor prognosis for patients receiving hypofractionated (n = 51; HR 14.2; 95% CI 1.7-119; p = 0.015) but not conventional (n = 24, HR 1.04; 95% CI 0.07-15.5, p = 0.978) radiotherapy.

INTERPRETATION

Tumour hypoxia status does not affect benefit from BC2001 chemotherapy. Hypoxia appears to affect fractionation sensitivity. Use of HSs to personalise treatment needs testing in a biomarker-stratified trial.

FUNDING

Cancer Research UK, NIHR, MRC.

Does a local Alcohol Health Champion programme have a measurable impact on health and crime outcomes? A natural experiment evaluation of Communities in Charge of Alcohol (CICA) based on triangulation of methods

BACKGROUND AND AIM

Drinking alcohol may cause harm to an individual's health and social relationships, while a drinking culture may harm societies as it may increase crime rates and make an area feel less safe. Local councils in Greater Manchester, UK, developed the Communities in Charge of Alcohol (CICA) intervention, in which volunteers were trained to give alcohol-related advice to the public and taught how to influence policies to restrict when, where and how alcohol is sold. As part of a larger study, the aim of the current project is to measure the impact of CICA on health and crime outcomes at the lower super output (LSOA) geographical aggregation.

DESIGN

Quantitative evaluation using four time series analytic methods (stepped-wedge design, and comparisons to local controls, national controls and synthetic controls) with findings triangulated across these methods. A cost-benefit analysis was carried out alongside the effectiveness analysis.

SETTING AND PARTICIPANTS

The general public in Greater Manchester, UK, between 2010 and 2020.

MEASUREMENTS

The primary outcome of interest was alcohol-related hospital admissions. Secondary outcomes were accident and emergency (A&E) attendances, ambulance callouts, recorded crimes and anti-social behaviour incidents.

FINDINGS

Triangulation of the results did not indicate any consistent effect on area-level alcohol-related hospital admissions, A&E attendances, ambulance callouts, reported crimes or anti-social behaviour associated with the implementation of CICA. The primary stepped-wedge analysis indicated an increase in alcohol-related hospital admissions following the implementation of CICA of 13.4% (95% confidence interval -3.3%, +30.1%), which was consistent with analyses based on other methods with point estimates ranging from +3.4% to 16.4%.

CONCLUSION

There is no evidence of a measurable impact of the Communities in Charge of Alcohol (CICA) programme on area-level health and crime outcomes in Greater Manchester, UK, within 3 years of the programme start. The increase in alcohol-related hospital admissions was likely the result of other temporal trends rather than the CICA programme. Possible explanations include insufficient follow-up time, too few volunteers trained, volunteers being unwilling to get involved in licensing decisions or that the intervention has no direct impact on the selected outcomes.

Modeling multiple correlated end-organ disease trajectories: A tutorial for multistate and joint models with applications in diabetes complications

State-of-the-art biostatistics methods allow for the simultaneous modeling of several correlated non-fatal disease processes over time, but there is no clear guidance on the optimal analysis in most settings. An example occurs in diabetes, where it is not known with certainty how microvascular complications of the eyes, kidneys, and nerves co-develop over time. In this article, we propose and contrast two general model frameworks for studying complications (sequential state and parallel trajectory frameworks) and review multivariate methods for their analysis, focusing on multistate and joint modeling. We illustrate these methods in a tutorial format using the long-term follow-up from the Diabetes Control and Complications Trial and Epidemiology of Diabetes Interventions and Complications study public data repository. A formal comparison of prediction error and discrimination is included. Multistate models are particularly advantageous for determining the order and timing of complications, but require discretization of the longitudinal outcomes and possibly a very complex state space process. Intermittent observation of the states must be accounted for, and discretization is a probable disadvantage in this setting. In contrast, joint models can account for variations of continuous biomarkers over time and are particularly designed for modeling complex association structures between the complications and for performing dynamic predictions of an outcome of interest to inform clinical decisions (eg, a late-stage complication). We found that both models have helpful features that can better-inform our understanding of the complex trajectories that complications may take and can therefore help with decision making for patients presenting with diabetes complications.

Association of sugar intake from different sources with cardiovascular disease incidence in the prospective cohort of UK Biobank participants

BACKGROUND

The relation between incident cardiovascular disease (CVD) and sugar might not only depend on the quantity consumed but also on its source. This study aims to assess the association between various sources of dietary sugars and CVD incidence in the prospective population-based UK Biobank cohort.

METHODS

A total of 176,352 participants from the UK Biobank with at least one web-based dietary questionnaire (Oxford WebQ) for assessment of sugar intake were included in this study. Mean follow-up lasted 10.9 years (standard deviation 2.0), with 12,355 incident cases of CVD. To determine the association of free sugar (FS) and intrinsic sugar intake with incident CVD, hazard ratios (HR) were calculated using Cox proportional hazard regression models. FS intake from beverages and beverage subtypes, i.e., soda/fruit drinks, juice, milk-based drinks, and tea/coffee, as well as from solid foods and solids subtypes, i.e., treats, cereals, toppings, and sauces, was included as penalised cubic splines.

RESULTS

FS intake showed a J-shaped relationship with CVD risk, reaching the lowest HR (HR-nadir) at 9 %E, while intrinsic sugars displayed a non-linear descending association, with the HR-nadir at 14 %E. FS in beverages demonstrated a significant linear relationship with CVD with the HR-nadir at 3 %E, while FS in solids exhibited a significant non-linear U-shaped relationship with the HR-nadir at 7 %E. Within the beverage subtypes, soda/fruit drinks displayed a linear relationship, as did to a lesser extent FS in milk-based drinks and tea/coffee. Juice, however, showed a significant U-shaped relationship with CVD risk. Among solid foods subtypes, FS in treats had a J-shaped relation with the HR-nadir at 5 %E, and FS in cereals showed a linear association. In comparison, FS in toppings and sauces exhibited a U-shaped pattern with HR-nadir at 3 %E and 0.5 %E, respectively. All major results remained similar in various sensitivity analyses and were more robust for ischemic heart disease compared to stroke.

CONCLUSIONS

Only some sources of FS exhibit a robust positive association with CVD incidence. Public health efforts aiming at the reduction of CVD risk should prioritise the reduction of sugary beverages with an emphasis on soda/fruit drinks.

WASH interventions and child diarrhea at the interface of climate and socioeconomic position in Bangladesh

Many diarrhea-causing pathogens are climate-sensitive, and populations with the lowest socioeconomic position (SEP) are often most vulnerable to climate-related transmission. Household Water, Sanitation, and Handwashing (WASH) interventions constitute one potential effective strategy to reduce child diarrhea, especially among low-income households. Capitalizing on a cluster randomized trial population (360 clusters, 4941 children with 8440 measurements) in rural Bangladesh, one of the world's most climate-sensitive regions, we show that improved WASH substantially reduces diarrhea risk with largest benefits among children with lowest SEP and during the monsoon season. We extrapolated trial results to rural Bangladesh regions using high-resolution geospatial layers to identify areas most likely to benefit. Scaling up a similar intervention could prevent an estimated 734 (95% CI 385, 1085) cases per 1000 children per month during the seasonal monsoon, with marked regional heterogeneities. Here, we show how to extend large-scale trials to inform WASH strategies among climate-sensitive and low-income populations.

Fusing trial data for treatment comparisons: Single vs multi-span bridging

While randomized controlled trials (RCTs) are critical for establishing the efficacy of new therapies, there are limitations regarding what comparisons can be made directly from trial data. RCTs are limited to a small number of comparator arms and often compare a new therapeutic to a standard of care which has already proven efficacious. It is sometimes of interest to estimate the efficacy of the new therapy relative to a treatment that was not evaluated in the same trial, such as a placebo or an alternative therapy that was evaluated in a different trial. Such dual-study comparisons are challenging because of potential differences between trial populations that can affect the outcome. In this article, two bridging estimators are considered that allow for comparisons of treatments evaluated in different trials, accounting for measured differences in trial populations. A "multi-span" estimator leverages a shared arm between two trials, while a "single-span" estimator does not require a shared arm. A diagnostic statistic that compares the outcome in the standardized shared arms is provided. The two estimators are compared in simulations, where both estimators demonstrate minimal empirical bias and nominal confidence interval coverage when the identification assumptions are met. The estimators are applied to data from the AIDS Clinical Trials Group 320 and 388 to compare the efficacy of two-drug vs four-drug antiretroviral therapy on CD4 cell counts among persons with advanced HIV. The single-span approach requires weaker identification assumptions and was more efficient in simulations and the application.

A Bayesian phase II proof-of-concept design for clinical trials with longitudinal endpoints

Existing phase II clinical trial designs focus on a single scalar endpoint, such as a binary, continuous, or survival endpoint. In some clinical trials, such as pain management studies, the efficacy endpoint of interest is measured longitudinally. We propose a Bayesian phase II design for such clinical trials. We model the longitudinal measurement process using Bayesian hierarchical model, where subject-specific trajectory shrinks toward the population trajectory to borrow information across subjects. The Bayesian penalized spline is used to model subject-specific and population trajectories without making strong parametric assumption on their shapes. We use the area under the curve of the trajectory as the summary of the treatment effect over time. The design takes a group sequential approach and takes into account both statistical significance and clinical relevance. Bayesian criteria is proposed to make interim and final decisions based on the evidence of statistical significance and clinical relevance. The proposed design is highly flexible and can accommodate trials with one or multiple longitudinal endpoints, as well as a longitudinal primary endpoint with a secondary endpoint. Simulation study shows that the proposed design is robust with desirable operating characteristics.

Regularized parametric survival modeling to improve risk prediction models

We propose to combine the benefits of flexible parametric survival modeling and regularization to improve risk prediction modeling in the context of time-to-event data. Thereto, we introduce ridge, lasso, elastic net, and group lasso penalties for both log hazard and log cumulative hazard models. The log (cumulative) hazard in these models is represented by a flexible function of time that may depend on the covariates (i.e., covariate effects may be time-varying). We show that the optimization problem for the proposed models can be formulated as a convex optimization problem and provide a user-friendly R implementation for model fitting and penalty parameter selection based on cross-validation. Simulation study results show the advantage of regularization in terms of increased out-of-sample prediction accuracy and improved calibration and discrimination of predicted survival probabilities, especially when sample size was relatively small with respect to model complexity. An applied example illustrates the proposed methods. In summary, our work provides both a foundation for and an easily accessible implementation of regularized parametric survival modeling and suggests that it improves out-of-sample prediction performance.

Diffuse traumatic brain injury substantially alters plasma growth hormone in the juvenile rat

Traumatic brain injury (TBI) can damage the hypothalamus and cause improper activation of the growth hormone (GH) axis, leading to growth hormone deficiency (GHD). GHD is one of the most prevalent endocrinopathies following TBI in adults; however, the extent to which GHD affects juveniles remains understudied. We used postnatal day 17 rats (n = 83), which model the late infantile/toddler period, and assessed body weights, GH levels, and number of hypothalamic somatostatin neurons at acute (1, 7 days post injury (DPI)) and chronic (18, 25, 43 DPI) time points. We hypothesized that diffuse TBI would alter circulating GH levels because of damage to the hypothalamus, specifically somatostatin neurons. Data were analyzed with generalized linear and mixed effects models with fixed effects interactions between the injury and time. Despite similar growth rates over time with age, TBI rats weighed less than shams at 18 DPI (postnatal day 35; P = 0.03, standardized effect size [d] = 1.24), which is around the onset of puberty. Compared to shams, GH levels were lower in the TBI group during the acute period (P = 0.196; d = 12.3) but higher in the TBI group during the chronic period (P = 0.10; d = 52.1). Although not statistically significant, TBI-induced differences in GH had large standardized effect sizes, indicating biological significance. The mean number of hypothalamic somatostatin neurons (an inhibitor of GH) positively predicted GH levels in the hypothalamus but did not predict GH levels in the somatosensory cortex. Understanding TBI-induced alterations in the GH axis may identify therapeutic targets to improve the quality of life of pediatric survivors of TBI.

Recent Secular Trends of Body Mass Index in Individuals With Bipolar Disorders and in the General Population

OBJECTIVE

The aims of this study were to investigate secular trends and distribution of body mass index (BMI) among individuals with bipolar disorders and the general population between 2008 and 2019.

METHODS

Data were from the Swedish National Quality Register for Bipolar Disorder, where 24,423 adults with bipolar disorders were identified, and from the national Swedish Living Conditions Surveys, where 77,485 adults from the general population were identified. Quantile regression was used to compare the 15th, 50th, and 85th percentiles of BMI across age and study years.

RESULTS

The study sample included 22,127 individuals with bipolar disorders (mean age, 48 years; 63% women) and 71,894 individuals from the general population (mean age, 52 years; 51% women). BMI percentiles were higher among individuals with bipolar disorders. At the 50th percentile, the BMI group differences were 1.1 (95% CI=0.8-1.14) for men and 1.8 (95% CI=1.5-2.1) for women. The gap was widest at the 85th BMI percentile: men, 2.3 (95% CI=1.8-2.8); women, 4.1 (95% CI=3.7-4.6). BMI increased over time in both study groups, but more in the group with bipolar disorders. The changes per decade in mean BMI were 0.4 (95% CI=0.3-0.5) among men in the general population, 1.1 (95% CI=0.7-1.4) among men with bipolar disorders, 0.6 (95% CI=0.5-0.7) among women in the general population, and 1.4 (95% CI=1.1-1.7) among women with bipolar disorders. Women with bipolar disorders had the highest prevalence and the greatest rate of increase of obesity. In 2019, the obesity prevalence was 33% among women and 29% among men with bipolar disorders, compared with 13% and 15%, respectively, among women and men in the general population.

CONCLUSIONS

Adults with bipolar disorders had a higher BMI and a higher prevalence of obesity than the general population, indicating a higher cardiometabolic risk. Annually, BMI increased more in the group with bipolar disorders than in the general population, particularly among women and among those with high BMI.

Greedy knot selection algorithm for restricted cubic spline regression

Non-linear regression modeling is common in epidemiology for prediction purposes or estimating relationships between predictor and response variables. Restricted cubic spline (RCS) regression is one such method, for example, highly relevant to Cox proportional hazard regression model analysis. RCS regression uses third-order polynomials joined at knot points to model non-linear relationships. The standard approach is to place knots by a regular sequence of quantiles between the outer boundaries. A regression curve can easily be fitted to the sample using a relatively high number of knots. The problem is then overfitting, where a regression model has a good fit to the given sample but does not generalize well to other samples. A low knot count is thus preferred. However, the standard knot selection process can lead to underperformance in the sparser regions of the predictor variable, especially when using a low number of knots. It can also lead to overfitting in the denser regions. We present a simple greedy search algorithm using a backward method for knot selection that shows reduced prediction error and Bayesian information criterion scores compared to the standard knot selection process in simulation experiments. We have implemented the algorithm as part of an open-source R-package, knutar.

Time series analysis in environmental epidemiology: challenges and considerations

In environmental epidemiology, time series analyses represent a widely used statistical tool. However, though being commonly used, there is soften confusion regarding the specific requirements, such as which link function might be most appropriate, when or how to control for seasonality or how to account for lags. The present overview draws from experiences in other disciplines and discusses the proper execution of time series analyses based on considerations that are relevant in environmental epidemiology. Time series analysis in environmental epidemiology focuses on acute events caused by short-term changes in exposure. These exposures should be fairly wide-spread affecting a large number of persons, usually all inhabitants of a political entity. Pollutants in air or drinking water as well as meteorological factors serve as typical examples. Despite the many time series analyses performed world-wide, some health effects that would lend themselves to that approach are still under-explored. This would include also some neurological and psychiatric endpoints. Int J Occup Med Environ Health. 2023;36(6):704-16.

Antiphospholipid antibodies are enriched post-acute COVID-19 but do not modulate the thrombotic risk

BACKGROUND AND OBJECTIVES

COVID-19-associated coagulopathy, shown to increase the risk for the occurrence of thromboses and microthromboses, displays phenotypic features of the antiphospholipid syndrome (APS), a prototype antibody-mediated autoimmune disease. Several groups have reported elevated levels of criteria and non-criteria antiphospholipid antibodies (aPL), assumed to cause APS, during acute or post-acute COVID-19. However, disease heterogeneity of COVID-19 is accompanied by heterogeneity in molecular signatures, including aberrant cytokine profiles and an increased occurrence of autoantibodies. Moreover, little is known about the association between autoantibodies and the clinical events. Here, we first aim to characterise the antiphospholipid antibody, anti-SARS-CoV-2 antibody, and the cytokine profiles in a diverse collective of COVID-19 patients (disease severity: asymptomatic to intensive care), using vaccinated individuals and influenza patients as comparisons. We then aim to assess whether the presence of aPL in COVID-19 is associated with an increased incidence of thrombotic events in COVID-19.

METHODS AND RESULTS

We conducted anti-SARS-CoV-2 IgG and IgA microELISA and IgG, IgA, and IgM antiphospholipid line immunoassay (LIA) against 10 criteria and non-criteria antigens in 155 plasma samples of 124 individuals, and we measured 16 cytokines and chemokines in 112 plasma samples. We additionally employed clinical and demographic parameters to conduct multivariable regression analyses within multiple paradigms. In line with recent results, we find that IgM autoantibodies against annexin V (AnV), β2-glycoprotein I (β2GPI), and prothrombin (PT) are enriched upon infection with SARS-CoV-2. There was no evidence for seroconversion from IgM to IgG or IgA. PT, β2GPI, and AnV IgM as well as cardiolipin (CL) IgG antiphospholipid levels were significantly elevated in the COVID-19 but not in the influenza or control groups. They were associated predominantly with the strength of the anti-SARS-CoV-2 antibody titres and the major correlate for thromboses was SARS-CoV-2 disease severity.

CONCLUSION

While we have recapitulated previous findings, we conclude that the presence of the aPL, most notably PT, β2GPI, AnV IgM, and CL IgG in COVID-19 are not associated with a higher incidence of thrombotic events.

Comparison of Olympic-Style Weightlifting Performances of Elite Athletes: Scaling Models Account for Body Mass

PURPOSE

We developed a scale for comparison of performances by weightlifters of different body mass and compare this scaling formula to current systems.

METHODS

Data from Olympics and World and Continental Championships from 2017 to 2021 were obtained; results from athletes with doping violations were excluded, resulting in performances from 1900 athletes from 150 countries for use in analysis. Functional relationships between performance and body mass were explored by testing various transformations of body mass in the form of fractional polynomials that include a wide range of nonlinear relationships. These transformations were evaluated in quantile regression models to determine the best fit, examine sex differences, and distinguish fits for different performance levels (90th, 75th, and 50th percentiles).

RESULTS

The resulting model used a transformation of body mass with powers -2 and 2 for males and females and was used to specify a scaling formula. The small percentage deviations between modeled and actual performances confirm the high accuracy of the model. In the subset of medalists, scaled performances were comparable across different body masses, whereas both Sinclair and Robi scalings, currently used in competitions, were more variable. The curves had similar shapes for the 90th and 75th percentile levels but were less steep for the 50th percentile.

CONCLUSIONS

The scaling formula we derived to compare weightlifting performances across a range of body mass can easily be implemented in the competition software to determine the overall best lifters. This is an improvement over current methods that do not accurately account for differences in body mass and result in bias or yield large variations even with small differences in body mass despite identical performances.

Forecasting the future burden of primary total shoulder replacement in Australia

OBJECTIVE

To forecast the number of primary total shoulder replacements (TSR) in Australia to the year 2035, and associated costs.

METHODS

De-identified TSR data for 2009-2019 were obtained from the Australian Orthopaedic Association National Joint Replacement Registry. Population data, including population projections to 2035, were obtained from the Australian Bureau of Statistics. Three forecasting scenarios were used: constant TSR rates from 2019 onwards (Scenario 1, conservative); continued growth in TSR rates using negative binomial regression (Scenario 2, exponential); and continued growth using negative binomial regression with monotone B-splines (Scenario 3, moderate). Healthcare costs were estimated using TSR projections and average procedure costs, inflated to 2035 Australian dollars.

RESULTS

The use of TSR increased by 242% in Australia from 2009 to 2019 (from 1983 to 6789 procedures for people ≥40 years). Under Scenario 1, the incidence of TSR is conservatively projected to rise to 9676 procedures by 2035 (43% increase from 2019), at a cost of $AUD 312.6 million to the health system. Under Scenario 2, TSR incidence would increase to 45,295 procedures by 2035 (567% increase), costing $AUD 1.46 billion. Under Scenario 3, 28,257 TSR procedures are forecast in 2035 (316% increase) at a cost of $913 million.

CONCLUSIONS

Recent growth in TSR likely relates to prosthesis improvements, greater surgeon proficiency, and expanded clinical indications. Under moderate and exponential scenarios that consider rising TSR rates and population projections, Australia would face three- to five-fold growth in procedures by 2035. This would have profound implications for the healthcare budget, clinical workforce, and infrastructure.

The association between weight-adjusted-waist index and self-reported infertility among women of reproductive age in the United States

AIM

This study aimed to determine whether the weight-adjusted-waist index (WWI) affected infertility in women of childbearing age in the United States.

METHODS

In this study, a database from the 2013 to 2018 National Health and Nutrition Examination Survey (NHANES) was used. We analyzed 3374 participants' data cross-sectionally. The survey used WWI and fertility status as independent and dependent variables. To determine the effect of WWI, an analysis of the independent relationship between WWI and infertility was conducted using weighted multivariable logistic regression and a generalized additive mode (GAM). A smooth curve fitting test was used to calculate whether there was a linear association between WWI and the incidence rate of infertility, as well as subgroup analyses and interaction tests.

RESULTS

The prevalence of infertility was 10.19% among 3374 participants. Higher WWI quartiles were associated with higher infertility rates. Based on a fully adjusted model, the effects of WWI on fertility were positive (odds ratio = 1.39, 95% confidence interval: 1.17-1.66). As a result of smooth curve fitting, the association was linear across the entire WWI. Different characteristics were associated with different risks of infertility in subgroup analysis.

CONCLUSION

Among women of reproductive age in the United States, WWI levels were positively associated with infertility. This relationship needs to be confirmed by further studies.

Particulate Air Pollution and Blood Pressure: Signaling by the Arachidonate Metabolism

BACKGROUND

Short-term exposure to ambient particulate matter (PM) can raise blood pressure, but the underlying mechanisms are unclear. We explored whether arachidonate metabolites serve as biological intermediates in PM-associated prohypertensive changes.

METHODS

This panel study recruited 110 adults aged 50 to 65 years living in Beijing, China. The participants' blood pressure, arterial stiffness, and cardiac and endothelial function were measured up to 7 times. The serum concentrations of arachidonate metabolites were quantified by targeted lipidomics. Ambient concentrations of fine PM (PM2.5), black carbon, and accumulation mode particles were continuously monitored at a station and their associations with the health indicators were evaluated.

RESULTS

Interquartile range increases in 25 to 96-hour-lag exposure to PM2.5, black carbon, and accumulation mode particles were associated with significant increases in systolic blood pressure (brachial: 0.8-3.2 mm Hg; central: 0.7-2.8 mm Hg) and diastolic blood pressure (brachial, 0.5-1.5 mm Hg; central, 0.5-1.6 mm Hg). At least 1 pollutant was associated with increases in augmentation pressure and heart rate and decreases in reactive hyperemia index and ejection time. The serum concentrations of arachidonate were significantly increased by 3.3% to 14.6% in association with PM exposure, which mediated 9% of the PM-associated increases in blood pressure. The levels of eicosanoids from the cytochrome P450, cyclooxygenase, and lipoxygenase pathways changed with PM exposure, and those from the cytochrome pathway significantly mediated the association between PM exposure and blood pressure.

CONCLUSIONS

Short-term exposure to particulate air pollution was associated with a prohypertensive change in adults, which was in part mediated by alteration of arachidonate metabolism.

Blood cell differential count discretisation modelling to predict survival in adults reporting to the emergency room: a retrospective cohort study

OBJECTIVES

To assess the survival predictivity of baseline blood cell differential count (BCDC), discretised according to two different methods, in adults visiting an emergency room (ER) for illness or trauma over 1 year.

DESIGN

Retrospective cohort study of hospital records.

SETTING

Tertiary care public hospital in northern Italy.

PARTICIPANTS

11 052 patients aged >18 years, consecutively admitted to the ER in 1 year, and for whom BCDC collection was indicated by ER medical staff at first presentation.

PRIMARY OUTCOME

Survival was the referral outcome for explorative model development. Automated BCDC analysis at baseline assessed haemoglobin, mean cell volume (MCV), red cell distribution width (RDW), platelet distribution width (PDW), platelet haematocrit (PCT), absolute red blood cells, white blood cells, neutrophils, lymphocytes, monocytes, eosinophils, basophils and platelets. Discretisation cut-offs were defined by benchmark and tailored methods. Benchmark cut-offs were stated based on laboratory reference values (Clinical and Laboratory Standards Institute). Tailored cut-offs for linear, sigmoid-shaped and U-shaped distributed variables were discretised by maximally selected rank statistics and by optimal-equal HR, respectively. Explanatory variables (age, gender, ER admission during SARS-CoV2 surges and in-hospital admission) were analysed using Cox multivariable regression. Receiver operating curves were drawn by summing the Cox-significant variables for each method.

RESULTS

Of 11 052 patients (median age 67 years, IQR 51-81, 48% female), 59% (n=6489) were discharged and 41% (n=4563) were admitted to the hospital. After a 306-day median follow-up (IQR 208-417 days), 9455 (86%) patients were alive and 1597 (14%) deceased. Increased HRs were associated with age >73 years (HR=4.6, 95% CI=4.0 to 5.2), in-hospital admission (HR=2.2, 95% CI=1.9 to 2.4), ER admission during SARS-CoV2 surges (Wave I: HR=1.7, 95% CI=1.5 to 1.9; Wave II: HR=1.2, 95% CI=1.0 to 1.3). Gender, haemoglobin, MCV, RDW, PDW, neutrophils, lymphocytes and eosinophil counts were significant overall. Benchmark-BCDC model included basophils and platelet count (area under the ROC (AUROC) 0.74). Tailored-BCDC model included monocyte counts and PCT (AUROC 0.79).

CONCLUSIONS

Baseline discretised BCDC provides meaningful insight regarding ER patients' survival.

Attention-deficit/hyperactivity disorder symptoms and subsequent cardiometabolic disorders in adults: investigating underlying mechanisms using a longitudinal twin study

BACKGROUND

Emerging research suggests that attention-deficit/hyperactivity disorder (ADHD) increases the risk for cardiovascular (CVDs) and metabolic disorders (i.e., cardiometabolic disorders) in adulthood. Yet, available studies are scarce and have mainly been focused on individuals receiving clinical ADHD diagnoses. We aimed to investigate the prospective associations of ADHD symptoms in young and mid-adulthood with subsequent cardiometabolic disorders and the underlying mechanisms.

METHODS

We studied 10,394 twins from the Swedish Twin Registry (STR), born between 1958 and 1985 without previous medical history of cardiometabolic disorders. They provided self-assessment of ADHD symptoms (score range 0-36) via a validated, DSM-IV-based scale in a web-based questionnaire/telephone interview within the Study of Twin Adults: Genes and Environment (STAGE), in 2005-2006 (aged 19-47 years), and were followed until the end of 2018 (33-59 years) to identify incident clinical diagnoses/medication prescriptions for cardiometabolic disorders acquired from Swedish national registers. We used Cox regression models to investigate the associations between ADHD symptoms score and cardiometabolic outcomes, with and without adjustment for relevant covariates, and a co-twin control design to study familial confounding.

RESULTS

A one-unit increase in the level of ADHD symptoms was associated with a 2% increase in the rate of CVDs (hazard ratio [HR] = 1.02, 95% confidence interval 1.01-1.04) and a 3% increase in the rate of metabolic disorders (HR = 1.03, 1.02-1.05), after adjusting for birth year and sex. The associations were no longer significant after adjusting for educational attainment, lifestyle factors, and comorbid psychiatric disorders. The associations remained significant after adjusting for familial factors shared by dizygotic twin pairs but became nonsignificant after adjusting for factors shared by monozygotic twin pairs. However, the strength of the associations attenuated significantly in monozygotic twins compared to dizygotic twins for CVDs only, suggesting genetic confounding.

CONCLUSIONS

ADHD symptom score is associated with a higher risk for cardiometabolic disorders, which may be explained by lower educational attainment, adverse lifestyle factors, and psychiatric comorbidities. Moreover, the associations appear to be partly confounded by shared genetic factors, especially for CVDs. Further research is needed to investigate the identified associations at the level of individual cardiometabolic disorders and to follow-up participants until a more advanced older age.

Increasing ambient temperatures trigger shifts in activity patterns and temporal partitioning in a large carnivore guild

Shifts in species' interactions are implicated as an important proximate cause underpinning climate-change-related extinction. However, there is little empirical evidence on the pathways through which climate conditions, such as ambient temperature, impact community dynamics. The timing of activities is a widespread behavioural adaptation to environmental variability, and temporal partitioning is a key mechanism that facilitates coexistence, especially within large carnivore communities. We investigated temperature impacts on community dynamics through its influence on the diel activity of, and temporal partitioning amongst, four sympatric species of African large carnivores: lions (Panthera leo), leopards (Panthera pardus), cheetahs (Acinonyx jubatus) and African wild dogs (Lycaon pictus). Activity of all species was shaped by a combination of light availability and temperature, with most species becoming more nocturnal and decreasing activity levels with increasing temperatures. A nocturnal shift was most pronounced in cheetahs, the most diurnal species during median temperatures. This shift increased temporal overlap between cheetahs and other carnivore species by up to 15.92%, highlighting the importance of considering the responses of interacting sympatric species when inferring climate impacts on ecosystems. Our study provides evidence that temperature can significantly affect temporal partitioning within a carnivore guild by generating asymmetrical behavioural responses amongst functionally similar species.

Patient and Treatment Characteristics Associated With Receipt of Core Patient-Reported Outcome Measures in VA Mental Health

OBJECTIVE

Measurement-based care (MBC) has been implemented in Veterans Affairs since 2016 and is increasingly used in other mental health care organizations. Little quantitative research exists that assesses patient-level barriers and facilitators of MBC. This study examines correlates of receiving patient-reported outcome measures (PROMs) among veterans receiving both psychotherapy and pharmacotherapy (Both), psychotherapy only (Psychotherapy), and pharmacotherapy only (Pharmacotherapy).

METHODS

Data on PROM administration were obtained for a 12-month period for 1,726,578 veterans who initiated outpatient mental health care during fiscal year 2019. Clinical, treatment, and PROM data were extracted from the electronic health record. Logistic regression was used to model the association between veteran and treatment characteristics and PROM administration.

RESULTS

Thirty-two percent of veterans in Both, 26.0% in Psychotherapy, and 8.8% in Pharmacotherapy received at least one PROM. The probability of PROM administration was positively associated with the number of treatment encounters during the fiscal year 2019. Major depressive, generalized anxiety, and other depressive disorders were associated with an increased probability of PROM administration. Psychotic disorders, personality disorders, older age, dementia, and electronic health record suicide risk flag were associated with decreased odds of PROM administration across treatment types.

CONCLUSIONS

Rates of PROM administration differ depending on the type of treatment received. The probability of PROM administration is influenced by the frequency of encounters and, to a lesser extent, having a diagnosis congruent with symptoms assessed in the set of PROMs considered. Consistent with hypotheses from the MBC implementation literature, potential indicators of clinical severity and cognitive impairment decrease the likelihood of PROM utilization.

Sickness Absence and Disability Pension Among Patients With Chronic Pain in Interdisciplinary Treatment or Unspecified Interventions

Interdisciplinary treatment is a widely implemented strategy for the rehabilitation of patients with chronic pain. A primary treatment objective is to decrease the load on the social insurance system; however, it is questionable whether interdisciplinary treatment reduces sickness absence and disability pension (SA/DP). This register-based observational study compared SA and DP between patients in interdisciplinary treatment and unspecified interventions. With data from 7,752 Swedish specialist health care patients in their prime working age, we analyzed total net SA/DP days over 3 years from the first visit to a pain rehabilitation center. A zero-one-inflated beta model, adjusted for theoretically substantiated confounders, was used to estimate the mean differences in total days and the proportions of patients with both zero and maximum days. Compared with unspecified interventions, interdisciplinary treatment resulted in a mean (95% confidence interval) absolute increase of 50 (37, 62) total days, a 13.0% (11.3%, 14.6%) decrease in patients with zero days, and a 1.5% (.2%, 2.8%) decrease in patients with the maximum days. These findings support that interdisciplinary treatment increases SA/DP compared to less intensive interventions but reduces the risk of maximum days, implying that it is advantageous for patients with the highest absence. This highlights the need for improved patient selection procedures and the adaptation of interdisciplinary treatment programs to more adequately target SA/DP reduction. PERSPECTIVES: This study provides an accessible overview of SA/DP among working-age patients with chronic pain in Swedish specialist health care. It also shows that interdisciplinary treatment does not decrease SA/DP more than alternative treatments in most patients but is advantageous for the patients with the longest absence.

Systemic inflammation and subsequent risk of amyotrophic lateral sclerosis: Prospective cohort study

BACKGROUND

While systemic inflammation has been implicated in the etiology of selected neurodegenerative disorders, its role in the development of amyotrophic lateral sclerosis (ALS), a condition with high case-fatality, is untested. Accordingly, we quantified the relationship of C-reactive protein (CRP), an acute-phase reactant and marker of systemic inflammation, with subsequent ALS occurrence.

METHODS

We used data from UK Biobank, a prospective cohort study of 502,649 participants who were aged 37 to 73 years when examined at research centers between 2006 and 2010. Venous blood was collected at baseline in the full cohort and assayed for CRP, and repeat measurement was made 3-7 years later in a representative subgroup (N = 14,514) enabling correction for regression dilution. ALS was ascertained via national hospitalization and mortality registries until 2021. We computed multivariable hazard ratios with accompanying 95% confidence intervals for log-transformed CRP expressed as standard deviation and tertiles.

RESULTS

In an analytical sample of 400,884 initially ALS-free individuals (218,203 women), a mean follow-up of 12 years gave rise to 231 hospitalizations and 223 deaths ascribed to ALS. After adjustment for covariates which included health behaviors, comorbidity, and socio-economic status, a one standard deviation higher log-CRP was associated with elevated rates of both ALS mortality (hazard ratios; 95% confidence intervals: 1.32; 1.13, 1.53) and hospitalizations (1.20; 1.00, 1.39). There was evidence of dose-response effects across tertiles of CRP for both outcomes (p for trend ≤ 0.05). Correction for regression dilution led to a strengthening of the relationship with CRP for both mortality (1.62; 1.27, 2.08) and hospitalizations (1.37; 1.05, 1.76).

CONCLUSIONS

Higher levels of CRP, a blood-based biomarker widely captured in clinical practice, is associated with moderately increased future risk of amyotrophic lateral sclerosis.

B-Spline Modeling of Inertial Measurements for Evaluating Stroke Rehabilitation Effectiveness

Patients who experience upper-limb paralysis after stroke require continual rehabilitation. Rehabilitation must be evaluated for appropriate treatment adjustment; such evaluation can be performed using inertial measurement units (IMUs) instead of standard scales or subjective evaluations. However, IMUs produce large quantities of discretized data, and using these data directly is challenging. In this study, B-splines were used to estimate IMU trajectory data for objective evaluations of hand function and stability by using machine learning classifiers and mathematical indices. IMU trajectory data from a 2018 study on upper-limb rehabilitation were used to validate the proposed method. Features extracted from B -spline trajectories could be used to classify individuals in the 2018 study with high accuracy, and the proposed indices revealed differences between these groups. Compared with conventional rehabilitation evaluation methods, the proposed method is more objective and effective.

The Hitchhiker's guide to longitudinal models: A primer on model selection for repeated-measures methods

Longitudinal data are becoming increasingly available in developmental neuroimaging. To maximize the promise of this wealth of information on how biology, behavior, and cognition change over time, there is a need to incorporate broad and rigorous training in longitudinal methods into the repertoire of developmental neuroscientists. Fortunately, these models have an incredibly rich tradition in the broader developmental sciences that we can draw from. Here, we provide a primer on longitudinal models, written in a beginner-friendly (and slightly irreverent) manner, with a particular focus on selecting among different modeling frameworks (e.g., multilevel versus latent curve models) to build the theoretical model of development a researcher wishes to test. Our aims are three-fold: (1) lay out a heuristic framework for longitudinal model selection, (2) build a repository of references that ground each model in its tradition of methodological development and practical implementation with a focus on connecting researchers to resources outside traditional neuroimaging journals, and (3) provide practical resources in the form of a codebook companion demonstrating how to fit these models. These resources together aim to enhance training for the next generation of developmental neuroscientists by providing a solid foundation for future forays into advanced modeling applications.

Smoothing spline assessment of the accuracy of enteric hydrogen and methane production measurements from dairy cattle using various sampling schemes

Estimating daily enteric hydrogen (H2) and methane (CH4) emitted from dairy cattle using spot sampling techniques requires accurate sampling schemes. These sampling schemes determine the number of daily samplings and their intervals. This simulation study assessed the accuracy of daily H2 and CH4 emissions from dairy cattle using various sampling schemes for gas collection. Gas emission data were available from a crossover experiment with 28 cows fed twice daily at 80% to 95% of the ad libitum intake, and an experiment that used a repeated randomized block design with 16 cows twice daily fed ad libitum. Gases were sampled every 12 to 15 min for 3 consecutive days in climate respiration chambers. Feed was fed in 2 equal portions per day in both experiments. Per individual cow-period combination, generalized additive models were fitted to all diurnal H2 and CH4 emission profiles. Per profile, the models were fitted using the generalized cross-validation, REML, REML while assuming correlated residuals, and REML while assuming heteroscedastic residuals. The areas under the curve (AUC) of these 4 fits were numerically integrated over 24 h to compute the daily production and compared with the mean of all data points, which was considered the reference. Next, the best of the 4 fits was used to evaluate 9 different sampling schemes. This evaluation determined the average predicted values sampled at 0.5, 1, and 2 h intervals starting at 0 h from morning feeding, at 1 and 2 h intervals starting at 0.5 h from morning feeding, at 6 and 8 h intervals starting at 2 h from morning feeding, and at 2 unequally spaced intervals with 2 or 3 samples per day. Sampling every 0.5 h was needed to obtain daily H2 productions not different from the selected AUC for the restricted feeding experiment, whereas less frequent sampling had predictions varying from 47% to 233% of the AUC. For the ad libitum feeding experiment, sampling schemes had H2 productions from 85% to 155% of the corresponding AUC. For the restricted feeding experiment, daily CH4 production needed samplings every 2 h or shorter, or 1 h or shorter, depending on sampling time after feeding, whereas sampling scheme did not affect CH4 production for the twice daily ad libitum feeding experiment. In conclusion, sampling scheme had a major impact on predicted daily H2 production, particularly with restricted feeding, whereas daily CH4 production was less severely affected by sampling scheme.

Body mass index and migraine in adolescence: A nationwide study

BACKGROUND

The association between body mass index (BMI) and migraine in adults has been well established. However, studies in children and adolescents are inconclusive. We aimed to study the association between BMI and migraine using a national dataset that comprises the electronic medical records of more than two million adolescents.

METHODS

This study included all Israeli adolescents (57.7% males, 42.3% females; mean age 17 years) who were medically assessed before mandatory military service during 1990-2020. As part of the pre-recruitment medical assessment, all the adolescents were screened for migraine and their height and weight were measured. Diagnoses of migraine were confirmed by board-certified neurologists. Prevalences and odds ratios (ORs) for migraine were computed across BMI subgroups. Spline models were applied.

RESULTS

A total of 2,094,862 adolescents were included, of whom 57,385 (2.8%) had active migraine. Among males, the adjusted ORs for migraine were 1.11 (95% confidence interval, 1.06-1.16), 1.13 (1.08-1.17), and 1.24 (1.19-1.30), for the underweight, overweight, and obesity subgroups, respectively, compared to the reference group of low-normal BMI (5th-49th percentile). Among females, the respective adjusted ORs were 1.12 (1.05-1.19), 1.23 (1.19-1.28), and 1.38 (1.31-1.46). Results persisted in sensitivity analyses accounting for other medical and psychiatric comorbidities and parental history of migraine. Spline models demonstrated a J-shaped relation between BMI and migraine.

CONCLUSIONS

Both adolescent obesity and underweight were associated with migraine in a sex-dependent manner. This association peaked in female adolescents with overweight and obesity.

Prior elicitation for Gaussian spatial process: An application to TMS brain mapping

The power and commensurate prior distributions are informative prior distributions that incorporate historical data as prior knowledge in Bayesian analysis to improve inference about a phenomenon under study. Although these distributions have been developed for analyzing non-spatial data, little or no attention has been given to spatial geostatistical data. In this study, we extend these informative prior distributions to a Gaussian spatial process, which enables the elicitation of prior knowledge from historical geostatistical data for Bayesian analysis. Three informative prior distributions were developed for spatial modeling, and an efficient Markov Chain Monte Carlo algorithm was developed for performing Bayesian analysis. Simulation studies were used to assess the adequacy of the informative prior distributions. Hierarchical models combined with the developed informative prior distributions were applied to analyze transcranial magnetic stimulation (TMS) brain mapping data to gain insights into the spatial pattern of a patient's response to motor cortex stimulation. The study quantified the uncertainty in motor response and found that the primary motor cortex of the hand is responsible for most of the movement of the right first dorsal interosseous muscle. The findings provide a deeper understanding of the neural mechanisms underlying motor function and ultimately aid the improvement of treatment options for individuals with health issues.

Association between dietary folate intake and bone mineral density in a diverse population: a cross-sectional study

BACKGROUND

Osteoporosis is a major public health problem, yet the association between dietary folate intake and bone health has been rarely studied. This study aimed to investigate the relationship between dietary folate intake and bone mineral density (BMD) in the general population of the USA.

METHODS

Utilizing data from the National Health and Nutrition Examination Survey, dietary folate intake was gauged through 24-h dietary recall and BMD was determined via dual-energy X-ray absorptiometry. Multivariate linear regression models and generalized additive models were employed for correlation analysis.

RESULTS

The study incorporated 9839 participants (48.88% males, aged 20-85 years, mean age: 47.62 ± 16.22). The average dietary folate intake stood at 401.1 ± 207.9 μg/day. And the average total femur, femoral neck, trochanter, intertrochanter, and lumbar BMD were 0.98 ± 0.16 g/cm2, 0.84 ± 0.15 g/cm2, 0.73 ± 0.13 g/cm2, 1.16 ± 0.19 g/cm2, and 1.03 ± 0.15 g/cm2, respectively. The higher quartiles of dietary folate intake directly correlated with increased total femoral, femoral neck, intertrochanteric, and lumbar BMD (P for trend = 0.003, 0.016, < 0.001, and 0.033, respectively). A consistent positive association between folate intake and BMD across age groups was observed, with significant findings for individuals over 80 years and non-Hispanic whites. Physical activity level and serum 25-hydroxyvitamin D levels influenced the association, with an optimal daily folate intake of 528-569 µg recommended for postmenopausal women.

CONCLUSION

In summary, our study reveals a significant positive association between dietary folate intake and BMD, across different age groups and particularly among individuals over 80 years old. Non-Hispanic whites benefit the most from increased folate intake. Physical activity level and serum 25-hydroxyvitamin D levels interact with this association. Screening and early intervention for osteoporosis may be essential for individuals with low dietary folate intake.

Human immune phenotyping reveals accelerated aging in type 1 diabetes

The proportions and phenotypes of immune cell subsets in peripheral blood undergo continual and dramatic remodeling throughout the human life span, which complicates efforts to identify disease-associated immune signatures in type 1 diabetes (T1D). We conducted cross-sectional flow cytometric immune profiling on peripheral blood from 826 individuals (stage 3 T1D, their first-degree relatives, those with ≥2 islet autoantibodies, and autoantibody-negative unaffected controls). We constructed an immune age predictive model in unaffected participants and observed accelerated immune aging in T1D. We used generalized additive models for location, shape, and scale to obtain age-corrected data for flow cytometry and complete blood count readouts, which can be visualized in our interactive portal (ImmScape); 46 parameters were significantly associated with age only, 25 with T1D only, and 23 with both age and T1D. Phenotypes associated with accelerated immunological aging in T1D included increased CXCR3+ and programmed cell death 1-positive (PD-1+) frequencies in naive and memory T cell subsets, despite reduced PD-1 expression levels on memory T cells. Phenotypes associated with T1D after age correction were predictive of T1D status. Our findings demonstrate advanced immune aging in T1D and highlight disease-associated phenotypes for biomarker monitoring and therapeutic interventions.

Visualizing the (Causal) Effect of a Continuous Variable on a Time-To-Event Outcome

Visualization is a key aspect of communicating the results of any study aiming to estimate causal effects. In studies with time-to-event outcomes, the most popular visualization approach is depicting survival curves stratified by the variable of interest. This approach cannot be used when the variable of interest is continuous. Simple workarounds, such as categorizing the continuous covariate and plotting survival curves for each category, can result in misleading depictions of the main effects. Instead, we propose a new graphic, the survival area plot, to directly depict the survival probability over time and as a function of a continuous covariate simultaneously. This plot utilizes g-computation based on a suitable time-to-event model to obtain the relevant estimates. Through the use of g-computation, those estimates can be adjusted for confounding without additional effort, allowing a causal interpretation under the standard causal identifiability assumptions. If those assumptions are not met, the proposed plot may still be used to depict noncausal associations. We illustrate and compare the proposed graphics to simpler alternatives using data from a large German observational study investigating the effect of the Ankle-Brachial Index on survival. To facilitate the usage of these plots, we additionally developed the contsurvplot R-package, which includes all methods discussed in this paper.

Premature Menopause and All-Cause Mortality and Life Span Among Women Older Than 40 Years in the NHANES I Epidemiologic Follow-Up Study: Propensity Score Matching Analysis

Objective: Findings from studies of the long-term effect of premature menopause on risks of all-cause mortality in women are equivocal. We used the approach of propensity score matching to examine the causal association of premature menopause with all-cause mortality and life span among women older than 40 years. Methods: The data were from the National Health and Nutrition Examination Survey I Epidemiologic Follow-up Study. We calculated the propensity score of premature menopause using a logistic regression model, then matched premature menopause with nonpremature menopause according to the score and the ratio of 1:1. We estimated mortality hazard ratios (HRs) and 95% confidence intervals (CIs) using Cox proportional hazard models. We also analyzed and plotted the relationship between age at menopause and reproductive life span with all-cause mortality and life span. Results: The mean age of 1,210 women was 55.4 ± 10.8 years at baseline. The unadjusted and adjusted HRs of all-cause mortality for women with premature menopause were 1.46 (95% CI: 1.08-1.96) and 1.53 (95% CI: 1.13-2.08), respectively, compared to nonpremature menopause. Nonlinear associations were found between age at menopause, reproductive life span, all-cause mortality, and life span. Menopausal age <37.5 years of age or reproductive life span <24 years increased the risk of all-cause mortality. Women with menopausal age <39 years of age or reproductive life span <24 years had a lower mean life span than the overall average of 76 years. Conclusions: Premature menopause significantly increased all-cause mortality risk and shortened life span in women. As women's age at menopause or reproductive life span increases, their overall life span also tends to increase.

Evaluation of Temporal Trends of Lead Exposure in Korean Workers Using Workplace Monitoring Data

BACKGROUND

Lead, which is widely used in various industrial settings, is a major health hazard for manufacturing workers. Therefore, control of lead exposure has been implemented in an effort to prevent lead-related health problems. In this study, our aim was to evaluate temporal trends in occupational lead exposure in Korean lead workers using data from monitoring of workplace exposure.

METHODS

A nationwide work environment monitoring database, data from a work environment monitoring institution, and data extracted from a review paper were utilized. Different versions of standard industrial classification codes were aligned with the 10th Korean Standard Industrial Classification, which is generally consistent with the 4th revision of the International Standard Industrial Classification. The multiple data sources were combined and temporal trends over the period from 1994-2021 were estimated. In addition, separate estimation of temporal trends in the storage battery manufacturing industry over the period from 1987-2021 was also performed.

RESULTS

A total of 444,296 personal airborne lead measurements were used for the estimation process. The temporal trends in occupational exposure to lead declined by -6% annually over the study period. In particular, levels of lead exposure in the storage battery manufacturing industry showed a steeper decline of -12% annually.

CONCLUSIONS

Findings of our study showed that occupational exposure to lead declined over the period from 1994 to 2021 in Korea. However, adverse effects of exposure to lead on health should be regarded with caution. The results will be useful in conduct of epidemiological studies examining lead-related effects on health.

Temminck pangolins relax the precision of body temperature regulation when resources are scarce in a semi-arid environment

Climate change is impacting mammals both directly (for example, through increased heat) and indirectly (for example, through altered food resources). Understanding the physiological and behavioural responses of mammals in already hot and dry environments to fluctuations in the climate and food availability allows for a better understanding of how they will cope with a rapidly changing climate. We measured the body temperature of seven Temminck's pangolins (Smutsia temminckii) in the semi-arid Kalahari for periods of between 4 months and 2 years. Pangolins regulated body temperature within a narrow range (34-36°C) over the 24-h cycle when food (and hence water, obtained from their prey) was abundant. When food resources were scarce, body temperature was regulated less precisely, 24-h minimum body temperatures were lower and the pangolins became more diurnally active, particularly during winter when prey was least available. The shift toward diurnal activity exposed pangolins to higher environmental heat loads, resulting in higher 24-h maximum body temperatures. Biologging of body temperature to detect heterothermy, or estimating food abundance (using pitfall trapping to monitor ant and termite availability), therefore provide tools to assess the welfare of this elusive but threatened mammal. Although the physiological and behavioural responses of pangolins buffered them against food scarcity during our study, whether this flexibility will be sufficient to allow them to cope with further reductions in food availability likely with climate change is unknown.

Short-term association of CO and NO2 with hospital visits for glomerulonephritis in Hefei, China: a time series study

Objective

Recent studies suggest air pollution as an underlying factor to kidney disease. However, there is still limited knowledge about the short-term correlation between glomerulonephritis (GN) and air pollution. Thus, we aim to fill this research gap by investigating the short-term correlation between GN clinical visits and air pollution exposure.

Methods

Between 2015 and 2019, daily GN visit data from two grade A tertiary hospitals in Hefei City were collected, along with corresponding air pollution and meteorological data. A generalized linear model integrated with a distributed lag nonlinear model was employed to analyze the relationship between GN visits and air pollutants. Moreover, we incorporated a dual pollutant model to account for the combined effects of multiple pollutants. Furthermore, subgroup analyses were performed to identify vulnerable populations based on gender, age, and season.

Results

The association between 23,475 GN visits and air pollutants was assessed, and significant positive associations were found between CO and NO2 exposure and GN visit risk. The single-day lagged effect model for CO showed increased risks for GN visits from lag0 (RR: 1.129, 95% CI: 1.031-1.236) to lag2 (RR: 1.034, 95% CI: 1.011-1.022), with the highest risk at lag0. In contrast, NO2 displayed a more persistent impact (lag1-lag4) on GN visit risk, peaking at lag2 (RR: 1.017, 95% CI: 1.011-1.022). Within the dual-pollutant model, the significance persisted for both CO and NO2 after adjusting for each other. Subgroup analyses showed that the cumulative harm of CO was greater in the cold-season and older adult groups. Meanwhile, the female group was more vulnerable to the harmful effects of cumulative exposure to NO2.

Conclusion

Our study indicated that CO and NO2 exposure can raise the risk of GN visits, and female and older adult populations exhibited greater susceptibility.

Neighborhood violence and socioeconomic deprivation influence associations between acute air pollution and temperature on childhood asthma in New York city

Ambient air pollution, temperature, and social stressor exposures are linked with asthma risk, with potential synergistic effects. We examined associations for acute pollution and temperature exposures, with modification by neighborhood violent crime and socioeconomic deprivation, on asthma morbidity among children aged 5-17 years year-round in New York City. Using conditional logistic regression in a time-stratified, case-crossover design, we quantified percent excess risk of asthma event per 10-unit increase in daily, residence-specific exposures to PM2.5, NO2, SO2, O3, and minimum daily temperature (Tmin). Data on 145,834 asthma cases presenting to NYC emergency departments from 2005 to 2011 were obtained from the New York Statewide Planning and Research Cooperative System (SPARCS). Residence- and day-specific spatiotemporal exposures were assigned using the NYC Community Air Survey (NYCCAS) spatial data and daily EPA pollution and NOAA weather data. Point-level NYPD violent crime data for 2009 (study midpoint) was aggregated, and Socioeconomic Deprivation Index (SDI) scores assigned, by census tract. Separate models were fit for each pollutant or temperature exposure for lag days 0-6, controlling for co-exposures and humidity, and mutually-adjusted interactions (modification) by quintile of violent crime and SDI were assessed. We observed stronger main effects for PM2.5 and SO2 in the cold season on lag day 1 [4.90% (95% CI: 3.77-6.04) and 8.57% (5.99-11.21), respectively]; Tmin in the cold season on lag day 0 [2.26% (1.25-3.28)]; and NO2 and O3 in the warm season on lag days 1 [7.86% (6.66-9.07)] and 2 [4.75% (3.53-5.97)], respectively. Violence and SDI modified the main effects in a non-linear manner; contrary to hypotheses, we found stronger associations in lower-violence and -deprivation quintiles. At very high stressor exposures, although asthma exacerbations were highly prevalent, pollution effects were less apparent-suggesting potential saturation effects in socio-environmental synergism.

Associations of sleep duration, daytime napping, and snoring with depression in rural China: a cross-sectional study

BACKGROUND

Most adult patients with depression complain about sleep symptoms, including insufficient and excessive sleep. However, previous studies investigating the impact of sleep duration on depression have yielded conflicting results. Therefore, this study aimed to analyse the link between depression and sleep duration, daytime napping, and snoring among rural Chinese adults.

METHODS

A cross-sectional study was conducted with 9104 individuals. Interviews were conducted with the participants regarding their sleep patterns and their daytime napping routines. The individuals were then assessed for depression using the Patient Health Questionnaire-9. The risk of depression was assessed using a multifactor binary logistic regression analysis. A generalized additive model was used to evaluate the nonlinear relationship between depression and sleep duration/nap time. Additionally, subgroup analysis was conducted to investigate the correlation between sleep duration, daytime napping, snoring, and depression.

RESULTS

Less than 6 h or more than 8 h of nighttime sleep, daytime napping for more than 1 h, and snoring were all significantly associated with an increased risk of depression. A U-shaped relationship was found between the duration of nighttime sleep and depression. In addition, we found that the nighttime duration of sleep, daytime naps, and snoring had a significant combined effect on the risk of depression. The subgroup analysis further revealed that lack of sleep at night significantly increased the risk of depression in all subgroups. However, snoring and excessive nighttime sleep and napping were only associated with the risk of depression in some subgroups.

CONCLUSIONS

Lack of nighttime sleep (short sleep duration), excessive sleep, and napping for more than one hour during the day were associated with a high risk of depression and had a combined effect with snoring.

Development of a prototype for high-frequency mental health surveillance in Germany: data infrastructure and statistical methods

In the course of the COVID-19 pandemic and the implementation of associated non-pharmaceutical containment measures, the need for continuous monitoring of the mental health of populations became apparent. When the pandemic hit Germany, a nationwide Mental Health Surveillance (MHS) was in conceptual development at Germany's governmental public health institute, the Robert Koch Institute. To meet the need for high-frequency reporting on population mental health we developed a prototype that provides monthly estimates of several mental health indicators with smoothing splines. We used data from the telephone surveys German Health Update (GEDA) and COVID-19 vaccination rate monitoring in Germany (COVIMO). This paper provides a description of the highly automated data pipeline that produces time series data for graphical representations, including details on data collection, data preparation, calculation of estimates, and output creation. Furthermore, statistical methods used in the weighting algorithm, model estimations for moving three-month predictions as well as smoothing techniques are described and discussed. Generalized additive modelling with smoothing splines best meets the desired criteria with regard to identifying general time trends. We show that the prototype is suitable for a population-based high-frequency mental health surveillance that is fast, flexible, and able to identify variation in the data over time. The automated and standardized data pipeline can also easily be applied to other health topics or other surveys and survey types. It is highly suitable as a data processing tool for the efficient continuous health surveillance required in fast-moving times of crisis such as the Covid-19 pandemic.

Happiness and Socio-Demographic Factors in an Italian Sample: A Propensity-Matched Study

Happiness is receiving more and more interest both as a determinant of health and a measure of outcome in biomedical and psychological sciences. The main objective of this study was to assess how the levels of happiness vary in a large sample of Italian adults and to identify the socio-demographic conditions which impair happiness domains the most. The participants of this survey consisted of 1695 Italian adults (85.9% women; 14.1% men) who completed the Measure of Happiness (MH) questionnaire online. In this study, the differences between groups in total and single domain (life perspective, psychophysical status, socio-relational sphere, relational private sphere, and financial status) happiness levels were examined through a propensity score matching analysis with respect to socio-demographic conditions, including gender, age, annual income, relationship status, having children, and education level. The results show that low income has a negative impact on happiness levels, whereas being in a relationship has a positive effect. Having children appears to have a negative impact on male happiness. Males appear to be happier than females, especially with regard to the psychophysics status. This evidence emphasizes the urgency for Italian policymakers to take actions on removing obstacles to people's happiness, especially with regard to financial distress, parenthood, and gender gaps.

Associations between lumbar bone mineral density, serum 25-hydroxyvitamin D and history of kidney stones in adults aged 30-69 years in the USA (NHANES 2011-2018)

OBJECTIVES

Most kidney stones contain calcium, which is closely associated with human bone health. Therefore, we aimed to determine the relationship between the history of kidney stones and human bone health. This study examined the associations between lumbar bone mineral density (BMD), serum 25-hydroxyvitamin D (25-OHD) and a history of kidney stones in individuals aged between 30 years and 69 years.

DESIGN AND DATA ANALYSIS

A multivariate logistic regression model was used to estimate the relationship between lumbar BMD, serum 25-OHD levels and kidney stones in this cross-sectional study. All models incorporated survey sample weights and were adjusted for covariates.

SETTING

National Health and Nutrition Examination Survey (NHANES) 2011-2018. The exposure and outcomes of this study included the lumbar BMD and presence of kidney stones.

PARTICIPANTS

All the 7500 participants for this cross-sectional survey were selected from the NHANES between 2011 and 2018.

MAIN OUTCOME MEASURES

The main outcome of this study was the presence of kidney stones. The interviewers asked the questions on kidney stones while the respondents were at home, using a computer-assisted personal interview system.

RESULTS

Lumbar BMD was negatively correlated with a history of kidney stones in all three multivariate linear regression models; the negative association existed in all genders after adjusting for all confounding factors. In the multiple regression analysis, there was an interaction between serum 25-OHD and lumbar BMD (p<0.05) regarding the influence on kidney stones; the negative association between lumbar BMD and kidney stones was more obvious in the higher 25-OHD group (≥50 nmol/L).

CONCLUSION

The study results suggest that maintaining a high lumbar BMD may reduce the incidence of kidney stone formation. Simultaneously, maintaining a high serum 25-OHD level may be more beneficial in preventing the occurrence or recurrence of stones while ensuring a high lumbar BMD.