Linear Spline Regression Research Articles

Systemic immune-inflammation states in US adults with seropositivity to infectious pathogens: A nutrient-wide association study.

Limited understanding exists regarding the association between daily total dietary nutrient intakes and immune-inflammation states in US adults exposed to various pathogens. This study sought to examine the correlation between nutrient intakes and immune-inflammation indicators and to assess their performance in distinguishing immune-inflammation states. This study was derived from the National Health and Nutrition Examination Survey (NHANES), which included 33,804 participants aged 20 years or older between 2005 and 2018. Multivariable linear regression and restricted cubic spline regression were conducted to evaluate the association between nutrient intakes and immune-inflammation indicators. Receiver operating characteristic curve analysis was performed to evaluate the discriminatory performance of identified nutrients for various immune-inflammation states measured by the systemic immune-inflammation index (SII). Ten key nutrients were significantly associated with immune-inflammation responses, including calcium, saturated fatty acid (SFA) 4:0, SFA 6:0, SFA 12:0, SFA 14:0, SFA 16:0, vitamin B2, total SFAs, retinol, and lutein + zeaxanthin, which show potential as dietary indicators. The area under the curve for discriminating various immune-inflammation states was improved by at least 0.03 compared with a model that included only covariates, with all P values <0.05 in the Delong tests, indicating a significant enhancement in model performance. Ten nutrients, including calcium, various SFAs, vitamin B2, retinol, and lutein + zeaxanthin, exhibit significant association with SII and potential as dietary indicators for distinguishing between different immune-inflammation states in US adults with seropositivity to various viruses.

Sea surface temperature differences between in situ and GHRSST (L4) records in a socio-ecological critical area of the northeastern Pacific Ocean May 2015 to July 2016

Using satellite sensor data for studying sea surface temperature (SST) provides advantages over in situ information, such as obtaining data from large areas and remote access regions in short periods. However, differences between the SST values recorded in situ and those by satellite sensors are due to the intrinsic nature of both methods and meteorological factors. The present study aims to search the difference between SST values from in situ and satellite sensor data of 1×1 km resolution (type L4) from the Group of High-Resolution Sea Surface Temperature (GHRSST) for an annual cycle in a socio-ecological critical area known as the Gulf of Ulloa (GU). The linear regression, linear spline regression, and logic models showed an overestimated SST by satellites compared to in situ data, particularly at temperatures below 20°C. The overestimation can be attributed to the oceanic-atmospheric variations, which are consequences of upwelling and the time lag between the data record morning by in situ and night by satellite sensors. This finding may be relevant in decision-making for marine resource management and conservation in the GU. The information may help to seek the sustainability of this social-environmental system.

How Do Quantitative Tissue Imaging Outcomes in Acute Ischemic Stroke Relate to Clinical Outcomes?

Infarct volume and other imaging markers are increasingly used as surrogate measures for clinical outcome in acute ischemic stroke research, but how improvements in these imaging surrogates translate into better clinical outcomes is currently unclear. We investigated how changes in infarct volume at 24 hours alter the probability of achieving good clinical outcome (modified Rankin Scale [mRS] 0-2). Data are from endovascular thrombectomy patients from the randomized controlled ESCAPE-NA1 (Efficacy and Safety of Nerinetide for the Treatment of Acute Ischaemic Stroke) trial. Infarct volume at 24 hours was manually segmented on non-contrast computed tomography or diffusion-weighted magnetic resonance imaging. Probabilities of achieving good outcome based on infarct volume were obtained from a multivariable logistic regression model. The probability of good outcome was plotted against infarct volume using linear spline regression. A total of 1,099 patients were included in the analysis (median final infarct volume 24.9 mL [interquartile range: 6.6-92.2]). The relationship between total infarct volume and good outcome probability was nearly linear for infarct volumes between 0 mL and 250 mL. In this range, a 10% increase in the probability of achieving mRS 0-2 required a decrease in infarct volume of approximately 34.0 mL (95% confidence interval: -32.5 to -35.6). At infarct volumes above 250 mL, the probability of achieving mRS 0-2 probability was near zero. The relationships of tissue-specific infarct volumes and parenchymal hemorrhage volume generally showed similar patterns, although variability was high. There seems to be a near-linear association between total infarct volume and probability of achieving good outcome for infarcts up to 250 mL, whereas patients with infarct volumes greater than 250 mL are highly unlikely to have a favorable outcome.

Relationship between serum uric acid and sarcopenia in geriatric heart failure patients with preserved ejection fraction

BackgroundHeart failure with preserved ejection fraction (HFpEF) presents a serious risk to human health. The increased prevalence of sarcopenia in the HFpEF population has a negative impact on patient prognosis. Uric acid (UA) is the byproduct of purine metabolism and is harmful to the cardiovascular system. This study aims to establish the potential relationship between sarcopenia and serum UA in HFpEF patients. MethodsData were obtained from 180 individuals (aged ≥60 years) with HFpEF admitted to the Geriatric Department of Jiangsu Province Hospital between January 2021 and December 2022. The UA values were grouped into 4 quartiles (Q1-Q4). Logistic generalized linear models and restricted cubic spline (RCS) regression were used to analyze the relationship between sarcopenia and UA. Subgroups based on gender were utilised for further analysis. ResultsAfter adjusting for covariates, odds ratios (ORs) and 95 % confidence intervals (CIs) for sarcopenia prevalence in the 2nd, 3rd, and 4th quartiles were 2.56 (0.57–12.65), 4.94 (1.10–24.49), and 6.95 (1.30–44.25), respectively, unlike the 1st quartile (P for trend = 0.022). The RCS plot demonstrated a positive linear relationship between serum UA levels and sarcopenia (P for non-linearity = 0.190). A sex-based subgroup analysis revealed a statistically significant relationship between UA and sarcopenia in males (P < 0.05). ConclusionsIn summary, the prevalence of sarcopenia is positively related to serum UA levels among the elderly diagnosed with HFpEF. Due to the cross-sectional nature of the study design, additional investigations are necessary to validate our findings and identify the optimal range for UA reduction.

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.

Raman and photoluminescence signal separation in Raman hyperspectral imagery including noise reduction

AbstractRaman hyperspectral imaging (RHSI) is a valuable tool for gaining crucial information about the chemical composition of materials. However, obtaining clear Raman signals is not always a trivial task. Raw Raman signals can be susceptible to photoluminescence interference and noise. Hence, the preprocessing of RHSI is a required step for an effective and reliable chemical analysis. The main challenge is splitting the measured RHSI into separate Raman photoluminescence signals. Since no golden‐standard exists, it is non‐trivial to validate the correctness of the separated signals. While current state‐of‐the‐art preprocessing methods are effective, they require expert knowledge and involve unintuitive hyperparameters. Current approaches also lack generalizability, requiring extensive hyperparameter tuning on a case‐by‐case basis, while even then results are not always as expected. To this end, this work proposes a novel iterative RHSI preprocessing pipeline for splitting raw Raman signals and noise removal based on linear spline and radial basis function regression (IlsaRBF). The proposed method involves hyperparameters based on the physical properties of Raman spectroscopy, making them intuitive to use. This leads to more robust and stable hyperparameters, reducing the necessity for extensive hyperparameter tuning. A thorough evaluation shows that the proposed method outperforms the current state‐of‐the‐art. Additionally, a cosmic ray identification and removal algorithm (CRIR) and dynamic PCA for noise reduction are introduced. A standalone tool containing our proposed methods is provided, making RHSI preprocessing available to a broader audience, aiding further research and advancements in the field of Raman spectroscopy.

Association between circulating antioxidants and sleep disorders: comprehensive results from NHANES 2017-2018.

Background: Oxidative stress plays an important role in the occurrence and pathological process of numerous human diseases. A bidirectional relationship was found between sleep disorders and oxidative stress. However, the association between circulating antioxidant levels and the risk of sleep disorders at the population-scale has yet to be determined. Methods: We used the dataset from the National Health and Nutrition Examination Survey (NHANES) 2017-2018 data release cycle and included 3062 adult participants aged 25-75 years. The circulating antioxidants levels in serum were measured, and the sleep status was assessed by self-reported sleep disorder questionnaire tests. We investigated the association and exposure-response relationship between the 12 main circulating antioxidants and sleep disorders using a generalized additive model (GAM), multiple linear, binary logistic, and restricted cubic spline (RCS) regression models. Multiple sensitivity analyses were conducted to validate the results of our study. Results: Significantly lower serum concentrations of ten antioxidants were observed in the group which had trouble sleeping symptoms compared to the control group. After adjusting for all the covariates, the binary logistic regression models indicated that six of the circulating antioxidants including alpha-carotene, alpha-cryptoxanthin, trans-beta-carotene, beta-cryptoxanthin, lutein and zeaxanthin, and vitamin C, showed a significant association with the risk of overall trouble sleeping symptoms, with odds ratios corresponding to 0.88 (95% CI: 0.80-0.96), 0.74 (95% CI: 0.62-0.87), 0.87 (95% CI: 0.79-0.97), 0.85 (95% CI: 0.75-0.95), 0.72 (95% CI: 0.61-0.84), and 0.83 (95% CI: 0.74-0.93), respectively. The GAM and multiple linear regression revealed similar associations whereas the RCS regression models further confirmed their significant negative exposure-response relationship. Conclusions: The circulating carotenoids and vitamin C levels were negatively correlated with the risk of sleep disorders. Higher circulating antioxidant levels were significantly associated with a lower risk of sleep disorders. The potential health risk of low circulating antioxidants levels was higher in the female population than in the male population.

Analysis of wastewater from 2013 to 2021 detected a recent increase in nicotine use in Queensland, Australia

Previous wastewater-based epidemiology (WBE) studies have reported decreasing trends of nicotine and tobacco use in Australia before 2017, but there is concern that increasing illicit use of nicotine in vaping products and illicit tobacco could reverse this progress. This study aimed to assess temporal trends of nicotine consumption and specifically tobacco consumption via wastewater analysis in a population in Australia between 2013 and 2021. One week of daily wastewater samples were analyzed every two months from February 2013 to December 2021 in a regional city serving ∼100,000 people. A total of 340 daily samples were analyzed for anabasine (tobacco specific biomarker) and nicotine metabolites, cotinine and hydroxycotinine, using direct injection method by liquid chromatography with tandem mass spectrometry. Daily consumption estimates were calculated from daily flow data, population estimates and previously reported excretion factors. Linear spline regression was performed to identify periods when significant change of slopes occurred and to evaluate the temporal trends. Tobacco use monitored using anabasine as a biomarker, showed a decreasing trend over the whole period with a higher rate of decrease during the first two years (2013-2014, 21 % decrease) compared to the later 7 years (2015-2021, 10 % decrease). Nicotine use, monitored using cotinine and hydroxycotinine, showed a downward trend between 2013 and 2018 (2013‐2014: 18 % decrease, p < 0.05; 2015‐2016: 6 % increase, p = 0.48; Feb-Dec 2017: 15 % decrease, p = 0.39) followed by a significant increase from 2018 to 2021 (40 % increase, p < 0.001). This finding suggests the increasing use of non-tobacco nicotine-based products. Additionally, the tobacco use estimate by wastewater analysis was higher than the tobacco sales data, which suggests the use of illicit tobacco in the catchment.

Temperature impact on the economic growth effect: method development and model performance evaluation with subnational data in China

Temperature-economic growth relationships are computed to quantify the impact of climate change on the economy. However, model performance and differences of predictions among research complicate the use of climate econometric estimation. Machine learning methods provide an alternative that might improve the predictive effects. However, time series and extrapolation issues constrain methods such as random forests. We apply a simple thought experiment with national marginal GDP growth by aggregating subnational climate impact to alleviate the shortcomings in random forests. This paper uses random forests, multivariate cubic regression, and linear spline regression to examine the direct impacts of temperature on economic development and conducts a performance comparison of the methods. The model results indicate an optimal temperature of 15°C, 15°C or 21°C for each model. Furthermore, a thought experiment indicates that the marginal predictions of national GDP changes by approximately 1%, −3%, or −6% for models with 1°C warming. The performance comparison suggests that random forests have stable model performance and better prediction performance in bootstrapping. However, the extrapolation problem in random forests causes underestimation of climate impact in 5% of cells under 6°C warming. Overall, our results suggest that temperature should be considered in economic projections under climate change scenarios. We also suggest the use of more machine learning methods in climate impact assessment.

Association between physical activity and depressive symptoms in adolescents: A prospective cohort study

It remains uncertain whether a protective association between physical activity and depression exists among adolescents and what the optimal level of physical activity might be. This study aimed to estimate the associations of physical activity levels with depressive symptoms and new-onset depression, while identifying potential modifying factors influencing the relationships. In this cohort study, we initially enrolled 1957 participants at baseline and followed up with 1738 of them after two years. Our analysis focused on data from 1482 students who provided complete information on both physical activity and depressive symptoms. Generalized linear regression and restricted cubic spline regression models were performed. Our adjusted models revealed that engaging in 4–7 h/week of moderate-to-vigorous physical activity (MVPA) at baseline was negatively associated with subsequent depressive symptoms and new-onset depression compared to the non-MVPA group. However, exceeding 7 h/week of MVPA did not provide substantial benefits. Furthermore, drinking and screen time potentially modified the relationship between MVPA and new-onset depression. Our findings suggest that 4–7 h of MVPA per week may be an appropriate level to reduce depressive symptoms in adolescents. Moreover, individual behaviors (e.g., drinking and screen time) warrant heightened attention in interventions targeting the reduction of depression in this population.

Impact of the COVID-19 pandemic on tuberculosis control in Indonesia: a nationwide longitudinal analysis of programme data

The impact of the COVID-19 pandemic on tuberculosis control in high-burden countries has not been adequately assessed. We aimed to estimate the impact of the COVID-19 pandemic on the national tuberculosis programme in Indonesia, in association with indicators of human development and health-system capacity across all 514 districts in 34 provinces. We did a nationwide longitudinal analysis to compare tuberculosis case notification, treatment coverage, and mortality rates in Indonesia before (2016-19) and during (2020-21) the COVID-19 pandemic. The following outcomes were assessed: the district-level quarterly reported tuberculosis case notification rate (number of all reported tuberculosis cases per 100 000 population), treatment coverage (proportion of tuberculosis patients who started treatment), and all-cause mortality rate in patients with tuberculosis (number of reported deaths per 100 000 population). District-level data on COVID-19 incidence and deaths, health-system capacity, and human development and sociodemographics were also analysed. Multilevel linear spline regression was done to assess quarterly time trends for the three outcomes. During the COVID-19 pandemic, the tuberculosis case notification rate declined by 26% (case notification rate ratio 0·74, 95% CI 0·72-0·77) and treatment coverage declined by 11% (treatment coverage ratio 0·89, 95% CI 0·88-0·90), but there was no significant increase in all-cause mortality (all-cause mortality rate ratio 0·97, 95% CI 0·91-1·04) compared with the pre-pandemic period. In the second year of the pandemic, we observed a partial recovery of the case notification rate from Q1 to Q4 of 2021, a persistent decrease in treatment coverage, and a decrease in the all-cause mortality rate from Q2 of 2020 to Q4 of 2021. The multivariable analysis showed that the reduction in the tuberculosis case notification rate was associated with a higher COVID-19 incidence rate (adjusted odds ratio 3·1, 95% CI 1·1-8·6, for the highest compared with the lowest group) and fewer GeneXpert machines for tuberculosis diagnosis (3·1, 1·0-9·4, for the lowest compared with the highest group) per 100 000 population. The reduction in tuberculosis treatment coverage was associated with higher COVID-19 incidence (adjusted odds ratio 11·7, 95% CI 1·5-93·4, for the highest compared with the lowest group), fewer primary health centres (10·6, 4·1-28·0, for the lowest compared with the middle-high group), and a very low number of doctors (0·3, 0·1-0·9, for the low-middle compared with the lowest group) per 100 000 population. No factors were shown to be significantly associated with all-cause mortality. The COVID-19 pandemic adversely and unevenly affected the national tuberculosis programme across Indonesia, with the greatest impacts observed in districts with the lowest health-system capacity. These disruptions could lead to an escalation in tuberculosis transmission in the coming years, warranting the need for intensified efforts to control tuberculosis and strengthen local health systems. Wellcome Africa Asia Programme Vietnam. For the Bahasa translation of the abstract see Supplementary Materials section.

Human serum albumin-bound selenium (Se-HSA) in serum and its correlation with other selenium species

IntroductionSelenium (Se) is a trace element with different toxicological and nutritional properties according to its chemical forms. Among the wide range of selenium species, human serum albumin-bound selenium (Se-HSA) has still uncertain composition in terms of organic or inorganic selenium species. This study aimed at investigating the relation between Se-HSA levels with total selenium and the specific organic and inorganic selenium species. MethodsWe determined levels of total selenium and selenium species in serum of participants enrolled in two populations of the Emilia-Romagna region, in Northern Italy. Anion exchange chromatography coupled with inductively coupled plasma dynamic reaction cell mass spectrometry was used as quantification method. Correlations between Se-HSA and the other selenium compounds were analyzed using linear regression and restricted cubic spline regression models, adjusted for potential confounders. ResultsThe first cohort comprised 50 participants (men/women: 26/24) with median (interquartile range, IQR) age 50 (55−62) years, while the second was composed of 104 participants (M/W: 50/54), median (IQR) age 48 (44−53) years. Median (IQR) levels of total selenium were 118.5 (109−136) µg/L and 116.5 (106−128) µg/L, respectively, while Se-HSA was 25.5 µg/L (16.2–51.5) and 1.1 (0.03–3.1) µg/L, respectively. In both populations, Se-HSA was positively associated with inorganic selenium species. Conversely, Se-HSA was inversely associated with organic selenium, especially with selenoprotein P-bound-Se (Se-SELENOP) and less strongly with selenomethionine-bound-Se (Se-Met), while the relation was null or even positive with other organic species. Evaluation of non-linear trends showed a substantially positive association with inorganic selenium, particularly selenite, until a concentration of 30 µg/L, above which a plateau was reached. The association with Se-SELENOP was inverse and strong until 100 µg/L, while it was almost null at higher levels. ConclusionsOur findings seem to indicate that Se-HSA incorporates more selenium when circulating levels of inorganic compounds are higher, thus supporting its mainly inorganic nature, particularly at high circulating levels of selenite.

Negative association between triglyceride glucose index and BMI-adjusted skeletal muscle mass index in hypertensive adults

BackgroundThe triglyceride glucose (TyG) index, an indicator of insulin resistance, is often associated with adverse outcomes in various cardiovascular diseases, while hypertension is associated with an increased risk of cardiovascular diseases. As the loss of muscle mass in people with hypertension is poorly understood, the current study aimed to explore the relationship between TyG index and muscle mass in hypertensive population.MethodsWe analyzed data from hypertensive adult participants in the National Health and Nutrition Examination Survey (NHANES) from 2011 to 2018. The TyG index and body mass index (BMI)-adjusted skeletal muscle mass index (SMI) were calculated and the relationship between the two was evaluated using multivariable linear regression and restricted cubic spline (RCS) regression models.ResultsA total of 1633 participants in the dataset were included for the final analysis. In the multivariable regression analysis, the adjusted β of SMI with a 95% confidence interval (CI) for the highest TyG index quartile was − 5.27 (− 9.79 to − 0.75), compared with the lowest quartile. A negative linear relationship between TyG index and SMI was plotted by RCS regression (nonlinear P = 0.128). Stratified models of non-smoking women of different ages also demonstrated that SMI decreased as TyG index increased (all P for trend < 0.05).ConclusionThis linear and negative correlation between TyG index and SMI in hypertensive patients suggests that insulin resistance adversely affects muscle mass.

Birthweight is associated with clinical characteristics in people with recently diagnosed type 2 diabetes

Aims/hypothesisLow birthweight is a risk factor for type 2 diabetes but it is unknown whether low birthweight is associated with distinct clinical characteristics at disease onset. We examined whether a lower or higher birthweight in type 2 diabetes is associated with clinically relevant characteristics at disease onset.MethodsMidwife records were traced for 6866 individuals with type 2 diabetes in the Danish Centre for Strategic Research in Type 2 Diabetes (DD2) cohort. Using a cross-sectional design, we assessed age at diagnosis, anthropomorphic measures, comorbidities, medications, metabolic variables and family history of type 2 diabetes in individuals with the lowest 25% of birthweight (<3000 g) and highest 25% of birthweight (>3700 g), compared with a birthweight of 3000–3700 g as reference, using log-binomial and Poisson regression. Continuous relationships across the entire birthweight spectrum were assessed with linear and restricted cubic spline regression. Weighted polygenic scores (PS) for type 2 diabetes and birthweight were calculated to assess the impact of genetic predispositions.ResultsEach 1000 g decrease in birthweight was associated with a 3.3 year (95% CI 2.9, 3.8) younger age of diabetes onset, 1.5 kg/m2 (95% CI 1.2, 1.7) lower BMI and 3.9 cm (95% CI 3.3, 4.5) smaller waist circumference. Compared with the reference birthweight, a birthweight of <3000 g was associated with more overall comorbidity (prevalence ratio [PR] for Charlson Comorbidity Index Score ≥3 was 1.36 [95% CI 1.07, 1.73]), having a systolic BP ≥155 mmHg (PR 1.26 [95% CI 0.99, 1.59]), lower prevalence of diabetes-associated neurological disease, less likelihood of family history of type 2 diabetes, use of three or more glucose-lowering drugs (PR 1.33 [95% CI 1.06, 1.65]) and use of three or more antihypertensive drugs (PR 1.09 [95% CI 0.99, 1.20]). Clinically defined low birthweight (<2500 g) yielded stronger associations. Most associations between birthweight and clinical characteristics appeared linear, and a higher birthweight was associated with characteristics mirroring lower birthweight in opposite directions. Results were robust to adjustments for PS representing weighted genetic predisposition for type 2 diabetes and birthweight.Conclusion/interpretationDespite younger age at diagnosis, and fewer individuals with obesity and family history of type 2 diabetes, a birthweight <3000 g was associated with more comorbidities, including a higher systolic BP, as well as with greater use of glucose-lowering and antihypertensive medications, in individuals with recently diagnosed type 2 diabetes.Graphical

Association of Serum Concentrations of Copper, Selenium, and Zinc with Grip Strength Based on NHANES 2013-2014.

Increasing evidence has found metals to be strongly associated with muscle strength, but the correlations between serum copper (Cu), selenium (Se), and zinc (Zn) with grip strength in adult populations have not yet been established. We examined the linear and non-linear associations between these three metals and grip strength via multiple linear regression and restricted cubic spline (RCS) regression using data from the National Health and Nutrition Examination Survey (NHANES) 2013-2014. A higher concentration of serum Cu was monotonically linked with lower grip strength [β = - 0.004 m2 (95% CI: - 0.005, - 0.002)], and serum Zn was positively associated with grip strength [β = 0.004 m2 (95% CI: 0.002, 0.006)]. We observed a positive association between serum Se and grip strength in the unadjusted model but not in covariate-adjusted models. Interestingly, the results of RCS regression showed that serum Cu had an L-shaped non-linear association with grip strength in all participants and subgroups. We further found a linear-increased trend between serum Zn and the grip strength in all participants. There were also non-linear associations that varied across different subgroups. Taken together, serum Cu and Zn were significantly associated with grip strength, while Se was not. This study offers new evidence to help formulate a reference concentration range for serum Cu and Zn.

Opioid-limiting legislation and prescribing habits of otolaryngologists among Medicare beneficiaries.

To identify changes in otolaryngologists' opioid prescribing trends for Medicare beneficiaries associated with the enactment of state laws that limit the duration of prescriptions to 3-7 days in the years 2016 and 2017 in the United States. Through the Centers for Medicare and Medicaid Services (CMS) database, we retrieved data on Medicare enrollment and on the total days prescribed and total number of beneficiaries for the drugs codeine/acetaminophen, hydrocodone/acetaminophen, oxycodone HCl, oxycodone/acetaminophen, and tramadol HCl, by each otolaryngologist prescriber in 13 states from January 2013 to December 2019. We modeled trends using linear spline regression models that controlled for Medicare beneficiaries' state-level socio-demographic characteristics' fixed effects. Across the 13 states, the number of days of all five opioids prescribed per beneficiary declined by 8.35 (SD = 12.61). The most commonly prescribed opioid type by otolaryngologists during the 5-year study period was tramadol HCl (28.72 days/beneficiary) followed by oxycodone HCl (19.99 days/beneficiary). All opioids had declines in prescription days over this time window and higher rates of decline in the years following law passage. Four states experienced statistically significant declines in the prescriptions of all opioids after the year of legislation passage (p < .05). Some states that had the greatest inclines in opioid prescriptions in the years prior to law enactment also experienced the greatest reductions in the time after legislation enactment. Opioid prescribing practices of otolaryngologists may have been affected by opioid prescription duration limiting laws passed in 13 states in 2016 and 2017. Level 4.

Association of blood metals with serum sex hormones in adults: A cross-sectional study

Heavy metals such as lead, mercury, and cadmium have been identified to have negative impacts on human health. Although the individual effects of these metals have been extensively researched, the present study aims to explore their combined effects and their association with serum sex hormones among adults. Data for this study were obtained from the general adult population of the 2013-2016 National Health and Nutrition Survey (NHANES) and included five metal (mercury, cadmium, manganese, lead, and selenium) exposures and three sex hormones (total testosterone [TT], estradiol [E2], and sex hormone-binding globulin [SHBG]) levels. The free androgen index (FAI) and TT/E2 ratio were also calculated. The relationships between blood metals and serum sex hormones were analysed using linear regression and restricted cubic spline regression. The effect of blood metal mixtures on sex hormone levels was examined using the quantile g-computation (qgcomp) model. There were 3,499 participants in this study, including 1,940 males and 1,559 females. In males, positive relationships between blood cadmium and serum SHBG (β=0.049 [0.006, 0.093]), lead and SHBG (β=0.040 [0.002, 0.079]), manganese and FAI (β=0.080 [0.016, 0.144]), and selenium and FAI (β=0.278 [0.054, 0.502]) were observed. In contrast, manganese and SHBG (β=-0.137 [-0.237, -0.037]), selenium and SHBG (β=-0.281 [-0.533, -0.028]), and manganese and TT/E2 ratio (β=-0.094 [-0.158, -0.029]) were negative associations. In females, blood cadmium and serum TT (β=0.082 [0.023, 0.141]), manganese and E2 (β=0.282 [0.072, 0.493]), cadmium and SHBG (β=0.146 [0.089, 0.203]), lead and SHBG (β=0.163 [0.095, 0.231]), and lead and TT/E2 ratio (β=0.174 [0.056, 0.292]) were positive relationships, while lead and E2 (β=-0.168 [-0.315, -0.021]) and FAI (β=-0.157 [-0.228, -0.086]) were negative associations. This correlation was stronger among elderly women (>50 years old). The qgcomp analysis revealed that the positive effect of mixed metals on SHBG was mainly driven by cadmium, while the negative effect of mixed metals on FAI was mainly driven by lead. Our findings indicate that exposure to heavy metals may disrupt hormonal homeostasis in adults, particularly in older women.

Health systems and telemedicine adoption for diabetes and hypertension care.

The COVID-19 pandemic accelerated telemedicine use nationally, but differences across health systems are understudied. We examine telemedicine use for adults with diabetes and/or hypertension across 10 health systems and analyze practice and patient characteristics associated with greater use. Encounter-level data from the AMGA Optum Data Warehouse for March 13, 2020, to December 31, 2020, were analyzed, which included 3,016,761 clinical encounters from 764,521 adults with diabetes and/or hypertension attributed to 1 of 1207 practice sites with at least 50 system-attributed patients. Linear spline regression estimated whether practice size and ownership were associated with telemedicine during the adoption (weeks 0-4), de-adoption (weeks 5-12), and maintenance (weeks 13-42) periods, controlling for patient socioeconomic and clinical characteristics. Telemedicine use peaked at 11% to 42% of weekly encounters after 4 weeks. In adjusted analyses, small practices had lower telemedicine use for adults with diabetes during the maintenance period compared with larger practices. Practice ownership was not associated with telemedicine use. Practices with higher proportions of Black patients continued to expand telemedicine use during the de-adoption and maintenance periods. Practice ownership was not associated with telemedicine use during first months of the pandemic. Small practices de-adopted telemedicine to a greater degree than medium and large practices. Technical support for small practices, irrespective of their ownership, could enable telemedicine use for adults with diabetes and/or hypertension.

The effect of total cholesterol/high-density lipoprotein cholesterol ratio on mortality risk in the general population.

The relationship between the total cholesterol/high-density lipoprotein cholesterol (TC/HDL-C) ratio and all-cause and cardiovascular mortality has not been elucidated. Herein, we intend to probe the effect of the TC/HDL-C ratio on all-cause and cardiovascular mortality in the general population. From the 1999-2014 National Health and Nutrition Examination Surveys (NHANES), a total of 32,405 health participants aged ≥18 years were included. The TC/HDL-C levels were divided into five groups: Q1: <2.86, Q2: 2.86-3.46, Q3: 3.46-4.12, Q4: 4.12-5.07, Q5: >5.07. Multivariate Cox regression models were used to explore the relationship between the TC/HDL-C ratio and cardiovascular and all-cause mortality. Two-piecewise linear regression models and restricted cubic spline regression were used to explore nonlinear and irregularly shaped relationships. Kaplan-Meier survival curve and subgroup analyses were conducted. The population comprised 15,675 men and 16,730 women with a mean age of 43 years. During a median follow-up of 98 months (8.1 years), 2,859 mortality cases were recorded. The TC/HDL-C ratio and all-cause mortality showed a nonlinear association after adjusting for confounding variables in the restricted cubic spline analysis. Hazard ratios (HRs) of all-cause mortality were particularly positively related to the level of TC/HDL-C ratio in the higher range >5.07 and in the lower range <2.86 (HR 1.26; 95% CI 1.10, 1.45; HR 1.18; 95% CI 1.00, 1.38, respectively), although the HRs of cardiovascular disease mortality showed no difference among the five groups. In the two-piecewise linear regression model, a TC/HDL-C ratio range of ≥4.22 was positively correlated with cardiovascular mortality (HR 1.13; 95% CI 1.02, 1.25). In the subgroup analysis, a nonlinear association between TC/HDL-C and all-cause mortality was found in those aged <65 years, men, and the no lipid drug treatment population. A nonlinear association between the TC/HDL-C ratio and all-cause mortality was found, indicating that a too-low or too-high TC/HDL-C ratio might increase all-cause mortality. However, for cardiovascular mortality, it does not seem so. The cutoff value was 4.22. The individuals had higher cardiovascular mortality with a TC/HDL-C ratio >4.22.

The Association of Alcohol Consumption with Glaucoma and Related Traits: Findings from the UK Biobank

To examine the associations of alcohol consumption with glaucoma and related traits, to assess whether a genetic predisposition to glaucoma modified these associations, and to perform Mendelian randomization (MR) experiments to probe causal effects. Cross-sectional observational and gene-environment interaction analyses in the UK Biobank. Two-sample MR experiments using summary statistics from large genetic consortia. UK Biobank participants with data on intraocular pressure (IOP) (n=109097), OCT-derived macular inner retinal layer thickness measures (n=46236) and glaucoma status (n=173407). Participants were categorized according to self-reported drinking behaviors. Quantitative estimates of alcohol intake were derived from touchscreen questionnaires and food composition tables. We performed a 2-step analysis, first comparing categories of alcohol consumption (never, infrequent, regular, and former drinkers) before assessing for a dose-response effect in regular drinkers only. Multivariable linear, logistic, and restricted cubic spline regression, adjusted for key sociodemographic, medical, anthropometric, and lifestyle factors, were used to examine associations. We assessed whether any association was modified by a multitrait glaucoma polygenic risk score. The inverse-variance weighted method was used for the main MR analyses. Intraocular pressure, macular retinal nerve fiber layer (mRNFL) thickness, macular ganglion cell-inner plexiform layer (mGCIPL) thickness, and prevalent glaucoma. Compared with infrequent drinkers, regular drinkers had higher IOP (+0.17 mmHg; P<0.001) and thinner mGCIPL (-0.17 μm; P= 0.049), whereas former drinkers had a higher prevalence of glaucoma (odds ratio, 1.53; P= 0.002). In regular drinkers, alcohol intake was adversely associated with all outcomes in a dose-dependent manner (all P<0.001). Restricted cubic spline regression analyses suggested nonlinear associations, with apparent threshold effects at approximately 50 g (∼6 UK or 4 US alcoholic units)/week for mRNFL and mGCIPL thickness. Significantly stronger alcohol-IOP associations were observed in participants at higher genetic susceptibility to glaucoma (Pinteraction < 0.001). Mendelian randomization analyses provided evidence for a causal association with mGCIPL thickness. Alcohol intake was consistently and adversely associated with glaucoma and related traits, and at levels below current United Kingdom (< 112 g/week) and United States (women, < 98 g/week; men, < 196 g/week) guidelines. Although we cannot infer causality definitively, these results will be of interest to people with or at risk of glaucoma and their advising physicians. Proprietary or commercial disclosure may be found after the references.