Health Study Research Articles

Circulating levels of blood biomarkers and risk of benign prostatic hyperplasia: Results from two large cohorts in Europe and East Asia.

As one of the most prevalent chronic non-communicable diseases affecting aging males, the burden of benign prostatic hyperplasia is growing over the world. Our study aims at investigating the potential relationships between various blood biomarkers and benign prostatic hyperplasia (BPH) in middle-aged and older men in European and East Asian population cohorts. We included 229 022 male adults from the UK Biobank (UKB) and 20 284 male adults from the China Health and Retirement Longitudinal Study (CHARLS) in this study. Forty-four blood biomarkers in UKB cohort and 16 blood biomarkers in the CHARLS cohort were analysed to examine their association with benign prostatic hyperplasia. Cox, logistic analyses and restricted cubic spline models were used to investigate linear and nonlinear longitudinal associations. In our research, elevated high-density lipoprotein cholesterol showed significant associations with a decreased risk of benign prostatic hyperplasia, and these associations remained significant after accounting for potential covariates both in UKB cohort (hazard ratio (HR) = 0.83; 95% CI = 0.79-0.88, P < 0.001) and CHARLS cohort (odds ratio (OR) = 0.992; 95% CI = 0.985-0.999, P = 0.033). Apolipoprotein A was also found to be inversely associated with BPH (HR = 0.76; 95% CI = 0.70-0.81, P < 0.001). L-shaped relationships were discovered between level of high-density lipoprotein cholesterol and apolipoprotein A with incidence of benign prostatic hyperplasia. This large prospective biomarker-based study highlights that high-density lipoprotein (HDL) cholesterol and apolipoprotein A are significant protective factors against the development of BPH, with L-shaped associations suggesting an optimal protective range. In contrast, biomarkers related to glucose metabolism, inflammation, and hormone levels were not found to significantly influence BPH progression. Our findings support the potential involvement of lipid biomarkers in the early stages of BPH development, suggesting that future strategies should prioritise lipid-related pathways in the prevention and management of BPH.

Technical variability across the 450K, EPICv1, and EPICv2 DNA methylation arrays: lessons learned for clinical and longitudinal studies

DNA methylation (DNAm) is the most commonly measured epigenetic mechanism in human populations, with most studies using Illumina arrays to assess DNAm levels. In 2023, Illumina updated their DNAm arrays to the EPIC version 2 (EPICv2), building on prior iterations, namely the EPIC version 1 (EPICv1) and 450K arrays. Whether DNAm measurements are stable across these three generations of arrays has yet not been investigated, limiting the ability of researchers—especially those with longitudinal data—to compare and replicate results across arrays. Here, we present results from a study of 30 child participants (15 male; 15 female) from the Drakenstein Child Health Study, who had DNAm measured on all three of the latest arrays: 450K, EPICv1, and EPICv2. Using these data, we created an annotation of probe quality across arrays, which includes the intraclass correlations, interquartile ranges, correlations, and array bias (i.e., the extent to which DNAm levels were explained by array type) of all CpGs. We also present results from an analysis of sex differences, where we found that CpGs with lower replicability across arrays had higher array-based variance, suggesting this variance metric help guide replication efforts. We also showed that epigenetic age estimates across arrays were more stable when using the principal component versions of epigenetic clocks. Ultimately, this collection of results provides a framework for investigating the replicability and longitudinal stability of epigenetic changes across multiple versions of Illumina DNAm arrays.

Metabolic Signatures of Blood Pressure and Risk of Cardiovascular Diseases.

The underlying biological mechanisms linking blood pressure (BP) and cardiovascular diseases (CVD) are only partly understood. We aimed to identify metabolic signatures associated with systolic and diastolic BP and investigate their subsequent association with risk of CVD. The study included 201 742 UK Biobank participants with measurements on 249 metabolic biomarkers. A multistep adaptive elastic net penalized regression with 10-fold cross-validation was employed to identify metabolic signatures for systolic BP and diastolic BP. External validation was conducted on 848 participants from the EHS (Epirus Health Study). We further assessed the associations between BP metabolic signatures and incident composite CVD (N=6742), myocardial infarction (N=4192), and stroke (N=2757) in the UK Biobank, using multivariable Cox regression models. The metabolic signatures comprised 31 and 25 metabolites, robustly correlated with systolic BP and diastolic BP, respectively, in both the UK Biobank and the EHS. Following adjustments (including BP), the metabolic signature for systolic BP was positively associated with incident myocardial infarction (hazard ratio [HR], 1.11 [95% CI, 1.07-1.15]) and CVD (HR, 1.07 [95% CI, 1.04-1.10]). Similarly, the metabolic signature for diastolic BP was associated with a higher risk of myocardial infarction (HR, 1.16 [95% CI, 1.12-1.20]) and CVD (HR, 1.09 [95% CI, 1.05-1.12]). The associations between the signatures and stroke were not significant. The metabolic signatures partly mediated the total effect of the BP traits on the risk of myocardial infarction and CVD. Our findings may enhance our understanding of the biological mechanisms through which BP affects CVD.

Initiation of Hearing Aids Use and Incident Dementia Among Mid-to-late Life Adults: The Health and Retirement Study 2010-2018.

Hearing aids may reduce the risk of dementia among individuals with hearing loss. However, no evidence is available from randomized controlled trials (RCTs) on the effectiveness of hearing aids use in reducing incident dementia. Using target trial emulation, we leveraged an existing longitudinal cohort study to estimate the association between hearing aids initiation and risk of dementia. The Health and Retirement Study was used to emulate target trials among non-institutionalized participants aged ≥50 years with self-reported hearing loss, without dementia at baseline, and without use of hearing aids in the previous 2 years. Intention-to-treat analysis was conducted to estimate the risk of dementia associated with hearing aids initiation vs controls who did not initiate hearing aids. Pooled logistic regression models with inverse-probability of treatment and censoring weights were applied to estimate risk ratios, and 95% confidence intervals were calculated using 1000 sets of bootstrapping. Among 2314 participants (328 in the intervention group and 1986 in the control group; average age: 72.3 ± 9.7 years, 49% women, and 81% White), after 8 years of follow-up, risk of dementia was significantly lower among individuals who initiated hearing aids (risk difference (RD): -0.05, 95% confidence interval (CI): -0.08, -0.01). A lower risk was observed particularly among adults aged 50-74 years, men, and individuals with cardiovascular disease. Hearing aids use was associated with a significant reduction of incident dementia. Future interventional studies are needed to further assess the effectiveness of hearing aids in preventing dementia.

Applications of geographical information system and spatial analysis in Indian health research: a systematic review

BackgroundHealth is a fundamental right intricately linked to geographical factors, as evidenced in the health geography literature. The application of geographical information systems (GISs) plays a pivotal role in mapping diseases and evaluating healthcare accessibility and is acknowledged by the World Health Organisation as a solution for enhancing health system resilience and achieving universal health coverage. This study focuses on the geographical perspectives to provide insights into the evolving role of GIS in addressing challenges and shaping healthcare strategies in health research within India. The primary objective was to analyse the utilisation of GISs in health studies specifically on three thematic areas: disease surveillance, health risk assessment, and healthcare access.MethodsThe databases were searched using sixteen keywords for peer-reviewed articles published during 2000–2022. A systematic literature survey was conducted, drawing from peer-reviewed literature available in the PubMed, Web of Science and Scopus databases. Out of 162 search results, 58 articles were selected for review after three rounds of eliminations based on the predefined specific criteria. A systematic literature review was conducted following PRISMA guidelines addressing two research questions.ResultsThis review reveals the extensive use of GIS in health studies since its inception, with particular prominence as a decision-making tool in the aftermath of the COVID-19 outbreak. The analysis of scientific articles focused on disease surveillance, risk assessment, and healthcare access in the Indian context demonstrates the effectiveness of GIS in managing and planning healthcare resources and services. GIS has proven to be an indispensable instrument for understanding spatial patterns in disease and optimising health interventions.ConclusionThis systematic review underscores the critical role of GIS in health research, particularly in the Indian context. The versatile applications of GIS in disease surveillance, risk assessment, and healthcare access highlight its effectiveness as a tool for managing and planning healthcare strategies, contributing to a more resilient and accessible healthcare system in India and beyond.

Clinical utility of novel diabetes subgroups in predicting vascular complications and mortality: up to 25 years of follow-up of the HUNT Study

IntroductionCluster analysis has previously revealed five reproducible subgroups of diabetes, differing in risks of diabetic complications. We aimed to examine the clusters’ predictive ability for vascular complications as compared with...

Immigrant Status and Social Ties: An Intersectional Analysis of Older Adults in the United States.

Diverse social ties are critical facilitators of well-being among older adults. Social ties might be especially important for aging immigrants who face multiple social and economic vulnerabilities over the life course. We investigated social ties (e.g., partners, children, other family, and friends) by immigrant status among older adults in the United States (U.S.). Data come from the 2018 Health and Retirement Study (N = 4,006), a national sample of older adults in the U.S. We used multivariable logistic regression to compare social ties (e.g., partners, children, other family, and friends) by immigrant status. We further explored interactions with sex and race/ethnicity. Older immigrants are more likely to report that they can rely a lot on their partners (aOR = 1.84, 95% CI 1.27, 2.68) but less likely to rely on friends (aOR = 0.72, 95% CI, 0.55, 0.94) compared to non-immigrants. Older immigrants are also less likely to meet frequently with friends (aOR = 0.66, 95% CI, 0.51, 0.86) and with other family (aOR = 0.71, 95%, CI, 0.55, 0.91) compared to non-immigrants. Lastly, older immigrant men are significantly less likely to meet with friends compared to non-immigrant men (aOR = 0.48, 95% CI, 0.32, 0.73). As the older population in the U.S. continues to diversify and immigrant older adults navigate their support options, older immigrants-especially men-may be at risk for less variation in their social support options, particularly from extended family members and friends.

Associations between Physical Performance Tests with Cognitive Changes: The Moderating Effect of Cognitive Status.

Age-related cognitive decline has been linked with risk factors, including physical performance. Prior studies investigating such associations were typically conducted in clinical settings within Western populations with a frequent focus on late neurocognitive diagnostic stages (i.e., Alzheimer's disease), reducing their generalizability to the Asian population and early neurocognitive stages. To address these knowledge gaps, our study investigated longitudinal associations between physical performance measures at baseline and cognitive change in global cognition, executive functioning (EF) based and non-executive functioning (non- EF) based cognitive domains within the Singaporean population. The moderating role of early neurocognitive status, namely mild cognitive impairment (MCI) and cognitively normal (CN), was also examined. This paper examined data from 347 participants (CN = 284; MCI = 63) who participated in the Community Health and Intergenerational (CHI) study at baseline and follow-up. Data from a neurocognitive battery and three physical performance tests, namely the timed-up and go (TUG), fast gait speed (FGS) and 30-second chair-stand test (30s-CST), were analysed using multivariate linear regression models. Only one significant association between FGS scores and cognitive change in Semantic Fluency was observed; other associations were not significant. Cognitive status also significantly moderated associations between TUG/30s-CST tasks with several neurocognitive tests. The lack of significant longitudinal associations between baseline physical performance measures and cognitive change differed from findings in the literature. Nevertheless, the moderating role of cognitive status further highlighted the need to account for cognitive status when exploring such associations within a heterogeneous group of older adults without dementia.

Influence of New Internet Usage on Depressive Symptoms Among Older Adults: Does the Effect Vary in People with Different Economic Status?

ABSTRACT This study investigated the longitudinal effect of new internet usage on depressive symptoms and whether economic status modified this association. Data were from the China Health and Retirement Longitudinal Study, involving 5,259 participants who were 60 +, did not use the internet in 2015, and were followed up in 2018. Linear regression with standard errors clustered at the city level was employed. We found that new internet usage was associated with less depressive symptoms, and the association was more profound among the poor participants. It implies that bridging the digital divide requires special attention to those with disadvantaged economic status.

C-reactive protein-triglyceride glucose index predicts stroke incidence in a hypertensive population: a national cohort study

BackgroundBoth the triglyceride-glucose (TyG) index, a predictor of insulin resistance (IR), and inflammation are risk factors for stroke in hypertensive patients. However, only a handful of studies have coupled the TyG index and inflammation indices to predict stroke risk in hypertensive patients. The C-reactive protein-triglyceride-glucose index (CTI) is a novel marker that comprehensively assesses the severity of IR and inflammation. The present study explored the association between CTI and the risk of stroke in patients with hypertension.MethodsA total of 3,834 hypertensive patients without a history of stroke at baseline were recruited from the China Health and Retirement Longitudinal Study (CHARLS). Multivariate Cox regression and restricted cubic spline (RCS) analyses were employed to assess the relationship between CTI and stroke risk in hypertensive patients. Furthermore, the Boruta algorithm was applied to evaluate the importance of CTI and construct prediction models to forecast the incidence of stroke in the study cohort.ResultsAfter 7 years of follow-up, the incidence of stroke in hypertensive patients was 9.6% (368 cases). Multivariate Cox regression analysis revealed a 21% increase in stroke risk with an increase in each CTI unit (hazard ratio (HR) = 1.21, 95% confidence interval (CI) = 1.08–1.37). The top quartile group was 66% more likely to have a stroke than the bottom quartile group (HR = 1.66, 95% CI = 1.23–2.25). RCS analysis confirmed a linear relationship between CTI and stroke risk. The Boruta algorithm validated CTI as a crucial indicator of stroke risk. The Support Vector Machine (SVM) survival model exhibited the best predictive performance for stroke risk in hypertensive patients, with an area under the curve (AUC) of 0.956.ConclusionsAn increase in CTI levels is associated with a higher risk of stroke in hypertensive patients. This study suggests that CTI may emerge as a unique predictive marker for stroke risk.

Tick population dynamics in the city of Košice (Eastern Slovakia): a public health study

Tick population dynamics in the city of Košice (Eastern Slovakia): a public health study

Association of Coagulation Factor XI Level With Cardiovascular Events and Cardiac Function in Community-Dwelling Adults: From ARIC and CHS.

Coagulation factor XI (FXI) inhibitors are a promising and novel class of anticoagulants, but a recent animal study found that FXI inhibition exacerbated diastolic dysfunction and heart failure (HF). In the ARIC study (Atherosclerosis Risk in Communities), we investigated whether plasma FXI level was associated with cardiovascular events and cardiac function. ARIC was our primary analytic cohort. We included 4471 participants (median age, 75 years; 57% female; 17% Black) who attended visit 5 (2011-2013) with Somalogic-quantified plasma FXI levels and echocardiographic cardiac function. Prevalent HF and atrial fibrillation (AF) cases were defined as having HF or AF diagnosed at or before each participant's visit 5 exam date. Incident HF and AF events were ascertained through 2021. Associations were assessed using Cox, logistic, and linear regression models. Primary prospective associations were also validated in the CHS (Cardiovascular Health Study) using an orthogonal FXI assay (enzyme-linked immunosorbent assay). At ARIC visit 5, there were 665 and 419 participants with prevalent HF and AF, respectively. During a median follow-up of 9 years, there were 580 and 788 incident HF and AF events, respectively. Lower FXI level was associated prospectively with higher incidence of HF (hazard ratio [HR], 1.36 [for each 1-unit decrement of log2-transformed FXI level] [95% CI, 1.01-1.83]) but not incident AF, and cross-sectionally with increased odds of AF (odds ratio [OR], 1.96 [95% CI, 1.23-3.07]) but not HF. In age-stratified analyses, decreased FXI was associated with higher incidence of HF in participants ≥75 years of age (HR, 1.57 [95% CI, 1.08-2.28]) but not <75 years of age (HR, 1.11 [95% CI, 0.68-1.79]). The inverse FXI-HF association was validated in CHS (HR, 1.18 [95% CI, 1.02-1.36]). At ARIC visit 5, lower FXI level was also associated with higher prevalence of diastolic dysfunction and worse E/A ratio, left atrial (LA) volume index, LA function, and left ventricular mass index, but not left ventricular ejection fraction or global longitudinal strain. Decreased FXI level is associated with greater incidence of HF, especially in older adults. It is also associated with prevalent AF, worse diastolic function, worse LA function, and greater LA size. More research is needed to assess potential unwanted effects of FXI inhibition on the risk of cardiovascular events and cardiac function.

Proinflammatory Dietary Pattern and Risk of Total and Subtypes of Breast Cancer Among U.S. Women.

Dietary patterns promoting chronic inflammation, including the empirical dietary inflammatory pattern (EDIP), have been associated with certain cancers. Investigating whether this dietary pattern is associated with breast cancer-where the role of inflammation is less well-defined-could provide valuable insights and potentially improve strategies for preventing this cancer. We prospectively followed 76,386 women from Nurses' Health Study (NHS, 1984-2018) and 92,886 women from Nurses' Health Study II (NHSII, 1991-2019). Diet was assessed by food frequency questionnaires (FFQs) every 4 years, starting at baseline. The inflammatory potential of diet was evaluated using the validated EDIP based on plasma CRP, IL-6, and TNFα-R2. Higher scores indicate higher dietary inflammatory potential. Hazard ratios and 95%CIs of overall and subtypes of breast cancer were estimated using multivariable-adjusted Cox regression models. During 4,490,842 person-years of follow-up, we documented 11,026 breast cancer cases. Women in the highest, compared with the lowest, EDIP quintile were at higher breast cancer risk (HRQ5vs.Q1=1.12; 95% CI, 1.05, 1.19; P-trend<0.001). The association was stronger for ER-negative tumors (HRQ5vs.Q1=1.29; 95% CI, 1.09, 1.53; P-trend=0.003). Also, we observed that the association of EDIP with breast cancer risk differed by molecular subtype, with the strongest association observed with basal-like tumors (HRQ5vs.Q1=1.80; 95% CI, 1.20, 2.71; P-trend=0.004). Higher EDIP scores were associated with a modestly increased risk of breast cancer, which was more pronounced for ER-negative and basal-like breast tumors. These results support the hypothesis that diet-related inflammation plays a role in breast cancer etiology, particularly tumors lacking hormone receptors.

Q-Learning in Dynamic Treatment Regimes With Misclassified Binary Outcome.

The study of precision medicine involves dynamic treatment regimes (DTRs), which are sequences of treatment decision rules recommended based on patient-level information. The primary goal of the DTR study is to identify an optimal DTR, a sequence of treatment decision rules that optimizes the clinical outcome across multiple decision points. Statistical methods have been developed in recent years to estimate an optimal DTR, including Q-learning, a regression-based method in the DTR literature. Although there are many studies concerning Q-learning, little attention has been paid in the presence of noisy data, such as misclassified outcomes. In this article, we investigate the effect of outcome misclassification on identifying optimal DTRs using Q-learning and propose a correction method to accommodate the misclassification effect on DTR. Simulation studies are conducted to demonstrate the satisfactory performance of the proposed method. We illustrate the proposed method using two examples from the National Health and Nutrition Examination Survey Data I Epidemiologic Follow-up Study and the Population Assessment of Tobacco and Health Study.

Theoretical perspectives on biostatistics and its multifaceted applications in global health studies

Biostatistics plays a crucial role in global health studies by providing the tools necessary for analyzing complex health data and informing evidence-based public health decisions. This theoretical review explores the foundations of biostatistics and its diverse applications in the context of global health. At its core, biostatistics utilizes mathematical and statistical principles to analyze health data, enabling researchers to identify patterns, determine risk factors, assess interventions, and predict health outcomes across populations. Key theoretical concepts, including probability theory, statistical inference, and regression models, form the backbone of biostatistical analysis and are integral to understanding the dynamic relationships between health determinants and outcomes. The review highlights the various applications of biostatistics in global health, focusing on areas such as disease surveillance, epidemiology, and public health intervention evaluation. Biostatistical techniques are essential for analyzing epidemiological data, monitoring disease trends, and evaluating the effectiveness of health policies and interventions on a global scale. Furthermore, advanced statistical methods, including machine learning and Bayesian approaches, are becoming increasingly important in global health research. These methods allow for the analysis of large-scale data, predictive modeling, and more precise risk assessments, particularly in the context of emerging diseases, genetic research, and environmental health studies. Despite its strengths, biostatistics faces challenges in global health, including issues related to data quality, ethical considerations, and cross-cultural variations in health outcomes. Addressing these challenges is critical for ensuring accurate and equitable health assessments. Looking forward, biostatistics continues to evolve with innovations in data science, big data analytics, and real-time health data collection, making it an indispensable tool for improving global health outcomes and supporting health policies. This review emphasizes the theoretical underpinnings of biostatistics while highlighting its transformative potential in global health research and practice. Keywords: Theoretical Perspectives, Biostatistics, Multifaceted Applications, Global Health Studies.

Higher-order disease interactions in multimorbidity measurement: marginal benefit over additive disease summation.

Current multimorbidity measures often oversimplify complex disease interactions by assuming a merely additive impact of diseases on health outcomes. This oversimplification neglects clinical observations that certain disease combinations can exhibit synergistic effects. Thus, we aimed to incorporate simultaneous higher-order disease interactions into the validated ICD-coded multimorbidity-weighted index (MICD), to assess for model improvement. Health and Retirement Study participants with linked Medicare data contributed ICD-9-CM claims, 1991-2012. Top 20 most prevalent and impactful conditions (based on associations with decline in physical functioning) were assessed through higher order interactions (two-way, three-way). We applied the least absolute shrinkage and selection operator (LASSO) and bootstrapping to identify and retain statistically significant disease interactions. We compared model fit in MICD with and without disease interactions in linear models. We analyzed 73,830 observations from 18,212 participants (training set N=14,570, testing set N=3,642). MICD without interactions produced an overall R2=0.26. Introducing two-way interactions for the top 10 most prevalent and impactful conditions resulted in a R2=0.27, while expanding to top 20 most prevalent and impactful conditions yielded a R2=0.26. When adding three-way interactions, the same top 10 conditions produced a R2=0.26, while expanding to top 20 conditions resulted in a R2=0.24. We present novel insights into simultaneous higher-order disease interactions for potential integration into multimorbidity measurement. Incorporating two-way disease interactions for the top 10 most prevalent and impactful conditions showed a minimal improvement in model fit. A more precise multimorbidity index may incorporate both the main effects of diseases and their significant interactions.

Association of remnant cholesterol with progression and regression of prediabetes in middle-aged and older adults: a nationwide cohort study.

The relationship between remnant cholesterol (RC) and outcome of patients with prediabetes remains unclear. This study aims to explore the association between dynamic changes in RC and progression to diabetes or regression to normal blood glucose in pre-diabetic population through a nationwide cohort study. Based on the China Health and Retirement Longitudinal Study (CHARLS), 2304 participants aged 45 years or older (58.60 ± 8.04 years) who participated in two surveys in 2011 and 2015 were included. Participants were divided into 3 groups according to the tertiles of dynamic changes in RC levels between the two surveys (Q1: ≤ - 1.59, Q2: - 1.59-12.73, Q3: ≥ 12.73, mmol/L). Multivariate Logistic regression models were used to analyze the association of the dynamic changes in RC and the progression and regression of prediabetes. Restricted cubic splines were used to analyze the dose-response relationship between RC and dynamic changes in RC and progression in the prediabetic population. During follow-up, 522 (22.30%) participants developed diabetes, 1283 (54.8%) participants remained prediabetic, and 536 (22.9%) participants regressed to normoglycemia. Further analysis of dynamic changes in RC revealed that reducing RC levels during follow-up reduced the risk of developing diabetes (OR = 0.76, 95% CI: 0.58-0.99, P = 0.04). However, compared with people with increased RC levels, people with prediabetes and stable RC levels are more likely to return to normal blood glucose (OR = 1.45,95% CI: 1.12-1.88, P = 0.005). In the pre-diabetic population, there was non-linear dose-response relationship between the level of RC and dynamic change in RC and the risk of developing diabetes (P nonlinearity < 0.001). Our findings revealed a substantial and non-linear association between dynamic change in RC levels and the outcome of prediabetes. Decreased RC level were associated with reduced risk of progression to diabetes in prediabetes.

Associations between objectively measured nighttime sleep duration, sleep timing, and sleep quality and body composition in toddlers in the Guelph Family Health Study.

The prevalence of child obesity is a worldwide public health concern. Good sleep hygiene is associated with reduced adiposity in older children and adults. More research is needed in younger children to help mitigate risk of obesity. As well, we aimed to address limitations found in previous studies such as relying on subjective measures, or only including one parameter of sleep,using only one body composition parameter, and/or not adjusting for relevant covariates. This cross-sectional study examined baseline data from 48 toddlers aged 1 to <3 years enrolled in the Guelph Family Health Study. Nighttime sleep duration, sleep timing (time child went to sleep, and awoke), and sleep quality were measured using 24-hour accelerometry for seven consecutive days. Height, body weight, and waist circumference were measured, and BMI z-scores and waist-to-height ratios were calculated. Percent fat mass and fat mass index were calculated using bioelectrical impedance analysis. Linear regression models were used to estimate associations between sleep parameters and body composition outcomes, with adjustments for relevant covariates (age, sex, household income, screen time, energy intake, physical activity, household stress). Nighttime sleep onset time was positively associated with waist-to-height ratio (β^=0.004, p=0.04). Sleep offset time was negatively associated with BMI z-score (β^=-0.48, p=0.02). Total sleep time and wake after sleep onset were not associated with any body composition outcome. Building healthy sleep habits may prevent childhood obesity; longitudinal research in a larger sample is warranted. This study was registered on ClinicalTrials.gov (NCT02939261).

Associations between serum mineral concentrations and mortality by renal function in the Ludwigshafen Risk and Cardiovascular Health Study

The association of serum concentrations of minerals and phosphate with overall and cardiovascular mortality based on renal function is poorly understood. 3307 patients (average age 62.7 ± 10.6 years) in the Ludwigshafen Risk and Cardiovascular Health (LURIC) study were grouped by estimated glomerular filtration rate (eGFR) into three categories: < 60, 60–89, and ≥ 90 mL/min per 1.73 m2, per KDIGO 2022 guidelines and were analysed using Cox regression. Low serum sodium and iron concentrations were associated with poor renal function and increased overall mortality risk, whereas higher serum zinc concentrations were associated with reduced overall and cardiovascular mortality risk. Elevated serum copper concentrations were associated with increased mortality risk across all eGFR categories. Comparing low and normal eGFR, we observed a fourfold increase in all-cause mortality risk for eGFR < 60 mL/min per 1.73 m2 and a twofold increase for eGFR 60–89 mL/min per 1.73 m2, accompanied by changes in serum mineral concentrations. The optimal range of mineral and phosphate concentrations in serum was strongly related to renal function. To reduce mortality risk, it’s important to regularly monitor serum mineral and phosphate concentrations as well as renal function, especially in cardiovascular patients with compromised renal function.

Contributions of Fat and Fatty Acids Intake to the Latin American Diet: Results of ELANS Study.

Fats, although essential for the proper functioning of the body, have been linked to an increased risk of developing chronic diseases, especially cardiovascular disease. The aim of this study was to evaluate the intake of total fat and its components (saturated, monounsaturated, polyunsaturated, and trans fats) in men and women aged 15 to 65 years of the urban population in eight Latin American countries. Survey data were collected from the Latin American Study of Nutrition and Health (ELANS, by its acronym in Spanish), an epidemiological study, including 9218 subjects from Argentina, Brazil, Chile, Colombia, Costa Rica, Ecuador, Peru, and Venezuela. In general, 76.2% of the subjects consumed fat within normal ranges (20-35% of the total caloric value (TCV)). When analyzing its components, a majority of the subjects consumed saturated and polyunsaturated fats within the recommended ranges. However, 94.5% of the population does not comply with the recommended maximum intake of monounsaturated fatty acids (MUFA) (10-20%), and only 57.5% comply with the intake recommendation for trans fatty acids (TRANS) (0-2%). Likewise, on average, women had a significantly higher intake of all types of fat compared to men. Finally, the average fat intake by age indicates that regardless of the age range, the consumption of all fats except MUFA and TRANS are within the recommended ranges, with MUFA being slightly below and TRANS above. Even though the fat intake of the population falls within the recommended range, it is necessary to improve the quality by favoring the consumption of MUFA-rich foods regionally accepted, such as avocados, and reducing the consumption of TRANS.