Search Results (724)

Background: The relationship between total cholesterol (TC) levels and mortality in older adults is complex and may differ from younger populations. While hypercholesterolemia is a known midlife risk factor, this association may weaken or reverse with age. Biological differences in cholesterol metabolism—particularly hormonal changes—may contribute to sex-specific mortality risks, but this remains underexplored. We examined the association between TC and all-cause mortality in older adults, assessing sex-specific differences. Methods: We used data from the InCHIANTI study, a longitudinal, population-based study conducted in Tuscany, Italy. From the original cohort (N = 1453), 999 participants ≥65 years with baseline TC and mortality data were included. TC levels were categorized as <200 mg/dL, 200–239 mg/dL, and ≥240 mg/dL. The primary outcome was all-cause mortality over 6-years. Kaplan–Meier curves and Cox proportional hazards models assessed mortality risk across TC categories in the overall population and by sex. Restricted cubic splines explored non-linear associations. Models were adjusted for age, sex (only in overall population), BMI, physical activity, diabetes, COPD, hypertension, eGFR, polypharmacy and frailty. Results: A threshold effect was observed: mortality risk rose sharply below ~200 mg/dL and remained stable above. Compared to the <200 mg/dL group, intermediate and high TC levels were associated with lower mortality risk (HR 0.72; 95% CI: 0.53–0.99 and HR 0.71; 95% CI: 0.49–1.02, respectively). In sex-stratified analyses, this pattern was pronounced in women but weaker and not statistically significant in men. Results held after excluding statin users and were confirmed by spline analysis. Conclusions: In older adults, particularly women, low TC may signal underlying vulnerability, including malnutrition or inflammation. Full article

Background/Objectives: Atopic dermatitis (AD), a chronic inflammatory skin condition, significantly impairs quality of life but remains underdiagnosed in primary care. Blood-cell-count-derived inflammatory indices are emerging as cost-effective biomarkers, but their pathological relevance to AD is limited and requires further discussion. Methods: We developed the Atopic Inflammation Index (AII), a novel blood-cell-based biomarker reflecting AD pathogenesis, and initially assessed its levels in AD patients and healthy controls using clinical samples from Shanghai, China. We then analyzed data from the NHANES (National Health and Nutrition Examination Survey) 2005–2006 cohort (n = 6855) to verify the AII-AD association and compared AII’s diagnostic performance with IgE and eosinophils. Results: Clinical analysis showed a nonlinear association between AII and AD severity. AII effectively distinguished AD patients (including mild cases) from healthy controls (p < 0.001) without elevation in psoriasis or urticaria, unlike eosinophils. In NHANES 2005–2006 (n = 720 AD cases, 10.5%), AII levels were higher in AD compared to non-AD patients (2.33 [1.39–4.09] vs. 2.03 [1.19–3.49], p = 0.007) and remained independently associated after adjustment (OR = 1.03, 95%CI = 1.01–1.04, p = 0.003), while IgE/eosinophils showed non-significant trends. Restricted cubic splines confirmed linear prediction (p = 0.006), and subgroup analyses supported consistency (P-interaction > 0.05). AII outperformed eosinophils (AUC:0.568 vs. 0.546, p = 0.025) with improved detection (sensitivity 0.361→0.614). Sensitivity analysis confirmed robustness after excluding medications, chronic diseases and adult populations. Conclusions: AII is stable and reliable in screening and diagnosing AD, offering a low-cost, practical solution for primary care. This verifies the feasibility of integrating existing detection indicators into new biomarkers, providing valuable inspiration for precision medicine research. Full article

Background and Objectives: This study aimed to evaluate the predictive value of systemic inflammatory response markers—namely, the Systemic Inflammatory Response Index (SIRI), Aggregate Index of Systemic Inflammation (AISI), and Monocyte-to-Lymphocyte Ratio (MLR)—in determining the occurrence of major complications following radical cystectomy. Materials and Methods: A retrospective analysis was conducted on 200 patients who underwent open radical cystectomy with ileal conduit diversion. Demographic, clinical, and laboratory variables, including albumin, creatinine, eGFR, smoking, and ASA score, were collected. SIRI, AISI, and MLR were calculated from preoperative blood counts. Major complications and their subtypes (infectious, wound, cardiopulmonary, thrombotic, and anastomotic) were adjudicated independently. Statistical analyses included multivariable logistic regression, ROC curves, calibration (Hosmer–Lemeshow, intercept, slope, and plots), bootstrap resampling (B = 2000), linearity checks (restricted cubic splines and Box–Tidwell), incremental value metrics (ΔAUC, IDI, and NRI), and decision-curve analysis (DCA). Results: Major complications occurred in 57 patients (28.5%). SIRI values were significantly higher in patients with major complications (median 2.12 vs. 1.63, p = 0.006), whereas AISI and MLR did not differ. SIRI remained an independent predictor in multivariable analysis (OR 1.37, 95% CI 1.01–1.86, p = 0.045). An AUC of 0.624 (95% CI 0.538–0.709) with a negative predictive value of 83.3% was observed for SIRI. The baseline clinical model yielded an AUC of 0.648, and an AUC of 0.672 was obtained when SIRI was added (ΔAUC = +0.024, 95% CI −0.022–0.071, p = 0.16). Calibration was excellent (intercept = 0.07, slope = 1.08), and superior net benefit was demonstrated for the SIRI-augmented model within threshold probabilities of 0.15–0.45 in DCA. A statistically significant improvement in IDI (0.024, p = 0.024) was identified, while NRI was positive but not significant. Subtype analyses indicated that the strongest associations of SIRI were with infectious and wound complications. Conclusions: SIRI was found to be an independent predictor of major complications after open radical cystectomy. Although gains in discrimination were modest, incremental analyses demonstrated improved calibration and net clinical benefit when SIRI was incorporated into a clinical model. External validation is required before translation into clinical practice. Full article

Background: The platelet-to-hemoglobin ratio (PHR) has emerged as a potential prognostic marker in various cardiovascular contexts, but its role in acute coronary syndrome (ACS), particularly among patients with diabetes mellitus (DM), remains unclear. Methods: In this retrospective cohort study, 843 ACS patients admitted to the 2nd Cardiology Department at Hippokration Hospital of Thessaloniki, Greece, between 2017 and 2023 were evaluated. PHR was calculated from admission complete blood counts. The primary endpoint was all-cause mortality during a median follow-up of 25 months. Multivariate logistic and Cox regression analyses, receiver operating characteristic (ROC) curves, Kaplan–Meier survival analyses, and restricted cubic spline (RCS) models were employed, with subgroup analyses by DM status. Results: Higher PHR was independently associated with increased mortality in the overall cohort (adjusted hazard ratio [aHR] 1.35, p < 0.001). This association showed stronger predictive value in DM patients, reflected in both a higher aHR (1.52 vs. 1.36 in non-DM patients, p < 0.001 and p = 0.018, respectively) and superior discriminative performance on ROC analysis (AUC 0.707 vs. 0.600 overall, p = 0.0006). Kaplan–Meier analysis confirmed poorer survival in high-PHR groups, especially in DM patients. RCS analysis revealed a J-shaped relationship, with risk increasing markedly beyond PHR values of 2.2. Conclusions: PHR is an independent predictor of long-term mortality in ACS, with greater prognostic significance in DM patients. Its simplicity, low cost, and availability from routine blood tests make it a promising tool for risk stratification in ACS. Full article

Background: Anaemia remains a widespread global public health concern. According to previous research reports, the prevalence rate of anaemia among Chinese adults is lacking. Additionally, the association between anaemia and four common anthropometric indices remains unclear. This study aimed to estimate the prevalence of anaemia and its association with anthropometric indices. Methods: The data was from a large, cross-sectional, nationally representative survey which was conducted from August 2018 to June 2019. A total of 190,236 individuals aged 18 years or old were invited, and 159,468 participants with complete data were included in this study. Anaemia was defined as the decrease in adjusted haemoglobin concentrations, <120 g/L for non-pregnant females and <130 g/L for males. Crude and weighted prevalence of anaemia in the overall population and different strata of Chinese adults were calculated. Weighted logistic regression and restricted cubic spline (RCS) were used to evaluate the association between anaemia and four anthropometric indices, including body mass index (BMI), waist circumference (WC), waist-to-height ratio (WHtR), and body roundness index (BRI). Results: In China, the weighted anaemia prevalence was 9% (95% CI: 8.5–9.6%), 4.9% (95% CI: 4.4–5.4%), and 13.2% (95% CI: 12.4–13.9%) for the overall population, males, and females, respectively. The weighted prevalence of anaemia was higher among females, rural residents, southwestern residents, and individuals with primary-school-level or lower education than others. The prevalence was highest among young females (14.4%, 95% CI, 13.3–15.5%) and older males (11.8%, 95% CI, 12.4–14.3%). In the fully adjusted logistic regression model, per SD increase in BMI (OR = 0.96, 95% CI: 0.95–0.97), WC (OR = 0.99, 95% CI: 0.98–0.99), WHtR (OR = 0.15, 95% CI: 0.07–0.32), and BRI (OR = 0.90, 95% CI: 0.87–0.94) were associated with a decreased risk of anaemia. Furthermore, the RCS curves depicted L-shaped relationships between the study variables and anaemia (all p for nonlinear <0.05). Conclusions: The prevalence of anaemia among Chinese adults, especially among young females and underweight older adults, remained unexpectedly high. More attention should be paid to these populations. Full article

Background: Inflammatory responses critically impact long-term outcomes in myocardial infarction (MI) survivors, yet few biomarkers comprehensively evaluate systemic immune-inflammatory status. This study assessed the prognostic utility of a novel marker—the pan-immune-inflammation value (PIV)—for predicting all-cause and cardiovascular mortality post-MI. Methods: Using the National Health and Nutrition Examination Survey data (2001–2018), 1559 MI survivors were included. PIV was calculated as (neutrophils × platelets × monocytes)/lymphocytes. Weighted Cox models assessed the association between log-transformed PIV (LnPIV) and mortality. Restricted cubic spline (RCS) models explored non-linear dose–response relationships, and predictive performance was evaluated via time-dependent ROC analysis. Results: Over a median 75-month follow-up, 675 deaths occurred. LnPIV showed significant non-linear associations with all-cause (p < 0.0001) and cardiovascular mortality (p = 0.0471). When LnPIV ≥ 5.59, each unit increase was associated with an 85% (HR = 1.85, 95% CI: 1.49–2.28) higher all-cause mortality risk; for cardiovascular mortality, the risk increased by 77% (HR = 1.77, 95% CI: 1.20–2.63) when LnPIV ≥ 5.68. Time-dependent ROC analysis confirmed strong prediction above these thresholds. Conclusion: PIV demonstrates threshold-dependent mortality risk stratification in MI patients, particularly effective in high-inflammatory subgroups, offering a potential tool for personalized risk stratification. Full article

Background: Sedentary behavior (SB) is a growing public health concern associated with cardiometabolic risk; yet few studies have assessed integrated physiological responses across the muscle–fat–vascular system. Methods: This retrospective cross-sectional analysis used data from 13,637 participants (≥12 years) in the 2011–2018 National Health and Nutrition Examination Survey (NHANES). Sedentary duration (SD) was self-reported via a validated questionnaire. Outcomes included the sarcopenic index (SI), fat distribution index (FDI), and pulse pressure index (PPI). Associations were examined using multivariable linear regression and restricted cubic spline models, adjusting for sociodemographic and lifestyle factors. Subgroup analyses explored effect modification by body mass index (BMI), sex, race/ethnicity, education, and self-rated health. Results: Each additional hour/day of SD was associated with a lower SI (β = −0.004, 95% CI: −0.005 to −0.002), lower FDI (β = −0.009, 95% CI: −0.012 to −0.007), and higher PPI (β = 0.001, 95% CI: 0.000 to 0.002). The SD–SI association was nonlinear, with a threshold at 10.73 h/day: below this point, the SI declined sharply (β = −0.001, p < 0.001), while above it the slope plateaued or reversed. The FDI showed consistent adverse associations across the SD range, particularly in men and individuals with lower education. The PPI was significantly elevated with SD only among non-Hispanic Black participants. Conclusions: SD is differentially associated with muscle mass, fat distribution, and vascular function, with overlapping inflection points indicating a coordinated multisystem response to sedentary stress. These findings support targeting <10.7 h/day sedentary time as a potential intervention threshold. Full article

In marine seismic surveys, the indistinguishability of subsurface boundaries caused by the superimposition of the acoustic signals reflected from it, particularly at specific frequency ranges characterized by strong spectral interference, reduces the resolution of the seismic record. We processed sub-bottom profiler data, acquired using a Bubble Pulser (nominal central frequency: ~400 Hz; effective bandwidth extending to ~1 kHz), (i) by extracting continuous wavelet transform (CWT) coefficients at the dominant energy scale to form the envelope and (ii) by applying Hilbert-based instantaneous frequency analysis to characterize medium-dependent spectral shifts. Envelope accuracy was benchmarked against four conventional filters using the sum of squared error (SSE) relative to a cubic-spline reference. CWT yielded the lowest SSE, outperforming low-pass 1 kHz and band-pass 400–1000 Hz; band-pass 400–650 Hz and low-pass 650 Hz were the least effective. Instantaneous-frequency trends differentiated rock, sand, and mud layers. Thus, compared to fixed-band filters, the scale-adaptive CWT envelope replicates raw energy more faithfully, while frequency attributes improve sediment classification. Low-pass filtering at 1000 Hz provides a more accurate representation of energy distribution than does bandpass filtering, particularly in the 400–650 Hz range. The integrated workflow—a robust, parameter-light alternative for high-resolution stratigraphic interpretation—enhances offshore engineering safety. Full article

To address the multipath delay estimation problem in distributed hydrophone passive localization systems, a global energy minimization-based method is proposed in this paper. In this method, correlation pulses are treated as tracking targets, and their trajectories are estimated from correlograms formed by multiple frames. Specifically, an energy function is designed to jointly encode pulse similarity, motion continuity, trajectory persistence, data fidelity, and regularization, thereby reformulating multipath delay estimation as a global optimization problem. In order to balance the discreteness of observations and the continuity of trajectories, the optimization process is implemented alternating between discrete association (solved via $\alpha$-expansion) and continuous trajectory fitting (using weighted cubic splines). Furthermore, a dynamic hypothesis space expansion strategy based on trajectory merging and splitting is introduced to improve robustness while accelerating convergence. By exploiting both the intrinsic characteristics of correlation pulses in multi-frame processing and the physical properties of motion trajectories, the proposed method achieves higher tracking accuracy without requiring prior knowledge of the number of delay trajectories in a noisy environment. Numerical simulations under various noise conditions and sea trial results validate the superiorities of the proposed multipath delay estimation method. Full article

Background: Serum osmolality (SOSM) is a simple and objective tool for assessing hydration status and has been demonstrated in several studies to hold significant prognostic value in patients with cardiovascular and cerebrovascular diseases. This study aims to evaluate the association between SOSM and clinical outcomes in patients with stroke. Methods: This study evaluated the prognostic relevance of SOSM in stroke patients using data from the MIMIC-IV database. Eligible participants were divided into four quartile groups based on their SOSM: Q1, 277.62–296.30 mOsm/kg H₂O; Q2, 296.31–301.60 mOsm/kg H₂O; Q3, 301.61–307.74 mOsm/kg H₂O; and Q4, 307.75–327.50 mOsm/kg H₂O. This study used Cox proportional hazards regression, subgroup analysis, and restricted cubic spline analysis to examine the association between SOSM and mortality. Results: This study included 6005 stroke patients. The 30-day and 365-day mortality rates were 13.49% and 15.84%, respectively. After adjusting for relevant confounders, multivariate Cox regression analysis showed that higher SOSM was independently associated with an increased risk of 30-day death (HR: 1.83; 95% CI: 1.48–2.27; p < 0.001) and 365-day death (HR: 1.71; 95% CI: 1.41–2.08; p < 0.001). Analyses using restricted cubic splines (RCSs) and threshold effect modeling demonstrated a clear U-shaped relationship between SOSM and both short-term and long-term risk of death in stroke patients. Furthermore, subgroup analyses confirmed the stability of this association across diverse patient profiles. Conclusions: SOSM is independently associated with both 30-day and 365-day mortality in stroke patients. Our findings indicate that SOSM may be an effective indicator for stratifying high-risk patients who might benefit from targeted interventions, ultimately improving prognostic outcomes. Full article

Background: Cadmium (Cd) exposure is linked to cognitive decline in middle-aged and older adults, but the modifying role of essential minerals is unclear. This study aimed to identify key protective minerals and quantify their joint antagonistic effect against Cd neurotoxicity. Methods: Baseline serum minerals and urinary Cd were measured in 6795 adults (≥40 years) from the 2015 China Health and Nutrition Survey. Cognitive function (MMSE) was assessed after 3 years. Associations were analyzed using multiple linear regression and Quantile g-computation (QGC) for joint effects. Combined exposure groups and interaction terms were assessed. Restricted cubic spline (RCS) models explored potential nonlinear dose–response relationships. Results: Participants in the highest urinary Cd quartile had significantly lower MMSE score (β = −0.09, 95% CI: −0.15, −0.02) than the lowest quartile. Serum calcium (Ca), ferrum (Fe), magnesium (Mg), selenium (Se), and phosphorus (P) were positively associated with MMSE. QGC revealed that the joint effect of Cd and the 5-mineral mixture (β = 0.10, 95% CI: 0.05, 0.14) was weaker than the protective effect of the 5-mineral mixture. Any high-mineral group had significantly higher MMSE score compared to the high-Cd/low-mineral group. Conclusions: Essential minerals Ca, Fe, Mg, Se, and P effectively antagonize Cd-associated cognitive decline. Their combined exposure demonstrates significant protective effects, providing key evidence for precision nutrition and environmental health risk management in Cd-exposed populations. Full article

The present investigation set out to examine potential categories regarding depressive symptoms in frail senior individuals in China and to identify the contributing variables associated with each category, with the goal of informing more targeted mental health interventions. Data were drawn from the 2018 China Health and Retirement Longitudinal Survey, commonly called CHARLS, which comprised an overall cohort of 1083 qualifying respondents. A latent profile analysis (LPA) revealed the following four distinct depression profiles: a Low Depression–High Loneliness Group (38.4%), a Moderately Low Depression–High Suicidal Ideation Group (7.5%), a Moderately High Depression–High Negative Emotion Group (33.4%), and a High Depression–High Suicidal Ideation Group (20.7%). Ordered multi-categorical logistic regression and restricted cubic spline analyses revealed that age, gender, body pain, pension insurance, sleep duration, and frailty index were significant predictors of depression classification. These findings suggest that depressive symptoms among frail older individuals in China are markedly heterogeneous, highlighting the need to develop differentiated intervention strategies for distinct depression risk groups to promote their mental health. Full article

Background/Objectives: This study examined how reproductive factors—such as oral contraceptive (OC) use, age at menarche, number of pregnancies, and age at first delivery—are related to the risk of metabolic syndrome (MetS) in Korean women aged 30–69, based on their menopausal status. Methods: Data from the Korea National Health and Nutrition Examination Survey 2010–2023 were analyzed, including 31,178 women with complete data. Survey-weighted logistic regression and restricted cubic spline analyses were conducted, adjusting for sociodemographic, lifestyle, and reproductive covariates. Results: OC use was associated with higher MetS risk in both pre-menopausal (adjusted OR 1.40, 95% CI 1.13–1.72) and post-menopausal women (adjusted OR 1.16, 95% CI 1.03–1.29). This association was observed primarily in relation to elevated blood pressure in both groups and high triglycerides in post-menopausal women. Other reproductive factors, including age at menarche, number of pregnancies, and age at first delivery, showed no significant associations with MetS risk. Conclusions: OC use was associated with higher MetS risk in this cross-sectional study of Korean women. These observational findings suggest a potential relationship that warrants further investigation through longitudinal studies to establish temporal relationships and explore underlying mechanisms. Full article

Objectives: This study aims to examine the relationship between dietary trace elements and Type 2 diabetes mellitus (T2DM), as well as to assess the influence of body mass index (BMI) on this relationship. Methods: A total of 38,384 participants participated in this study. Dietary intakes of iron, copper, zinc, heme iron, and non-heme iron were assessed using validated food frequency questionnaires. The odds ratio (OR) and 95% confidence interval (CI) were calculated using the logistic regression model to evaluate the association of dietary intake of iron, copper, zinc, heme iron, and non-heme iron with T2DM. Restrictive cubic splines (RCS) were used to explore the dose–response relationship. In addition, causal mediation analysis was used to explore the role of BMI. Results: After adjusting for the relevant covariates, the highest quartile (Q4) compared with the lowest quartile (Q1) the odds ratios and 95% confidence intervals of iron, heme iron, non-heme iron, copper, and zinc between T2DM were 0.81 (0.70–0.92), 0.81 (0.70–0.92), 0.79 (0.70–0.90), 0.64 (0.77–0.72), and 0.65 (0.55–0.78), respectively. The RCS results showed that the hazards of copper and heme iron in T2DM decreased with the increase in dose (p_-non < 0.05). The results of the mediation analysis showed that BMI mediated the association between dietary trace elements and T2DM. Furthermore, subgroup analysis showed the same results. Conclusions: This study indicates that moderate intake of dietary trace elements may help reduce the incidence of T2DM in rural areas. BMI can mediate the association between the two. Full article

Sea level is an important variable for studying water cycle and coastal hazards under global warming. Global Navigation Satellite System Interferometric Reflectometry (GNSS-IR) has emerged as a relatively new technique for monitoring sea level variations, leveraging signals from GNSS constellations. However, dynamic height errors, primarily caused by non-stationary sea surfaces, compromise the precision of GNSS-IR sea level retrievals and necessitate robust correction. In this study, we propose a new method to correct the dynamic height error by integrating the commonly used tidal analysis method and the cubic spline fitting method. The proposed method is applied to the GNSS-IR sea level retrievals from multiple systems and multiple frequency bands at two coastal GNSS stations, MAYG and HKQT. At MAYG, the results show that our method significantly reduces the Root Mean Square Error (RMSE) of the GNSS-IR sea level retrievals by 42.1% (11.4 cm) to 15.7 cm, performing better than the single tidal analysis method (16.5 cm) and the cubic spline fitting method (21.4 cm). At HKQT, our method improves the accuracy by 21.5% (3.1 cm) to 10.3 cm, which is still better than that of the tidal analysis method (11.3 cm) and the cubic spline fitting method (12.4 cm). Compared to the tidal analysis method and the cubic spline fitting method, our method maintains high retrieval retention while enhancing precision. The effectiveness of our method is further validated in the two storm surge events caused by Typhoon Hato and Typhoon Mangkhut in Hong Kong. Full article