Dietary Inflammatory Index and Dietary Diversity Score Associated with Sarcopenia and Its Components: Findings from a Nationwide Cross-Sectional Study.

Little is known about the independent and joint effects of the energy-adjusted dietary inflammatory index (E-DII) and dietary diversity score (DDS) on sarcopenia and its components (low muscle mass, low muscle strength, and low physical performance). A total of 155,669 UK Biobank participants with ≥1 (maximum 5) 24 h dietary assessments were included in this cross-sectional analysis. We used logistic regression models to investigate the associations of E-DII and DDS with sarcopenia and its three components. We further examined the joint effects of E-DII and DDS on sarcopenia and its components using additive and multiplicative interaction analyses. We observed that lower E-DII and higher DDS were associated with lower odds of sarcopenia and its components. There were significant joint associations of E-DII and DDS with sarcopenia and low physical performance (p-interaction < 0.05) on the multiplicative interactive scale. Our study suggests that lower dietary inflammatory potential and higher dietary diversity might be important protective factors against sarcopenia and its components. More cases of sarcopenia and low physical performance might be preventable by adherence to a more anti-inflammatory diet combined with a higher dietary diversity.

High Dietary Intake of Iron Might Be Harmful to Atrial Fibrillation and Modified by Genetic Diversity: A Prospective Cohort Study.

Some studies suggest an association between iron overload and cardiovascular diseases (CVDs). However, the relationship between dietary iron intake and atrial fibrillation (AF) remains uncertain, as does the role of genetic loci on this association. The study involved 179,565 participants from UK Biobank, tracking incident atrial fibrillation (AF) cases. Iron intake was categorized into low, moderate, and high groups based on dietary surveys conducted from 2009 to 2012. The Cox regression model was used to estimate the risk of AF in relation to iron intake, assessing the hazard ratio (HR) and 95% confidence interval (95% CI). It also examined the impact of 165 AF-related and 20 iron-related genetic variants on this association. Pathway enrichment analyses were performed using Metascape and FUMA. During a median follow-up period of 11.6 years, 6693 (3.97%) incident AF cases were recorded. A total of 35,874 (20.0%) participants had high iron intake. High iron intake was associated with increased risk of AF [HR: 1.13 (95% CI: 1.05, 1.22)] in a fully adjusted model. Importantly, there were 83 SNPs (11 iron-related SNPs) that could enhance the observed associations. These genes are mainly involved in cardiac development and cell signal transduction pathways. High dietary iron intake increases the risk of atrial fibrillation, especially when iron intake exceeds 16.95 mg. The association was particularly significant among the 83 SNPs associated with AF and iron, the individuals with these risk genes. Gene enrichment analysis revealed that these genes are significantly involved in cardiac development and cell signal transduction processes.

Fostering dialogue: a phenomenological approach to bridging the gap between the "voice of medicine" and the "voice of the lifeworld".

This article adopts Husserl's transcendental phenomenology to explore the complex relationship between patients and physicians. It delves into the coexistence of two distinct voices in the realm of medicine and health: the "voice of medicine" and the "voice of life-world." Divided into three sections, the article emphasizes the importance of shifting from a scientific-medical attitude to a more personalistic approach in physician-patient interactions. This shift aims to prevent depersonalization and desubjectification. Additionally, it highlights the equal and irreducible nature of patients while acknowledging the vital role physicians hold in the realm of illness. The article stresses the need for a balanced and equitable relationship between both parties, rooted in the shared life-world. Moreover, empathy is underscored as a crucial element in fostering meaningful dialogue, wherein understanding diverse perspectives and attitudes towards illness is paramount. The article argues that differences between patients and physicians are necessary for empathy, while shared similarities form its foundation. Ultimately, a harmonious relationship facilitates empathy and enables the constitution of a new sense of life for both patients and physicians.

DJAN: Deep Joint Adaptation Network for Wildlife Image Recognition.

Wildlife recognition is of utmost importance for monitoring and preserving biodiversity. In recent years, deep-learning-based methods for wildlife image recognition have exhibited remarkable performance on specific datasets and are becoming a mainstream research direction. However, wildlife image recognition tasks face the challenge of weak generalization in open environments. In this paper, a Deep Joint Adaptation Network (DJAN) for wildlife image recognition is proposed to deal with the above issue by taking a transfer learning paradigm into consideration. To alleviate the distribution discrepancy between the known dataset and the target task dataset while enhancing the transferability of the model's generated features, we introduce a correlation alignment constraint and a strategy of conditional adversarial training, which enhance the capability of individual domain adaptation modules. In addition, a transformer unit is utilized to capture the long-range relationships between the local and global feature representations, which facilitates better understanding of the overall structure and relationships within the image. The proposed approach is evaluated on a wildlife dataset; a series of experimental results testify that the DJAN model yields state-of-the-art results, and, compared to the best results obtained by the baseline methods, the average accuracy of identifying the eleven wildlife species improves by 3.6 percentage points.

Reframing Anorexia Nervosa: A Phenomenological Exploration of the Self-Other Relationship with Husserl's Intersubjective Theory.

This paper explores the overlooked contributions of Husserl's Phenomenology of intersubjectivity in understanding anorexia nervosa. It highlights the intricate relationship between the self and others, emphasizing their mutual constitution while acknowledging inherent differences. The distorted body image approach often overlooks this perspective, leading to psychopathological issues in individuals with anorexia nervosa. By integrating subjective experience and external observation, a more balanced and equal intersubjective relationship can be established. Utilizing this philosophical framework allows for a deeper understanding of the disorder's dynamics and sheds new light on the subjective experiences of individuals with anorexia nervosa in relation to others.

Ambient air pollution associated with incident asthma, subsequent cardiovascular disease and death: A trajectory analysis of a national cohort.

No previous study has examined the impact of air pollution on the cardiovascular disease (CVD) trajectory, especially among asthmatic subjects. Based on the UK Biobank cohort, we retrieved 292,227 adults free of asthma and CVD aged 37-73 years at recruitment (2006-2010). Annual mean concentrations of particulate matter (PM10 and PM2.5) and nitrogen oxides (NO2 and NOx) were assessed at each individual's addresses. We used multi-state models to estimate the associations of air pollution with the trajectory from healthy to incident asthma, subsequent CVD, and death. During a median follow-up of 11.7 years, a total of 6338 (2.2%) participants developed asthma, among which, 638 (10.1%) subsequently proceeded to CVD. We observed significant impacts of various air pollutants on the CVD dynamic transitions, with a more substantial effect of particulate matter pollutants than gaseous air pollutants. For example, the hazard ratios (95% confidence intervals) for per interquartile range increase in PM2.5 and PM10 were 1.28 (1.13, 1.44) and 1.27 (1.13, 1.43) for transitions from incident asthma to subsequent CVD. In conclusion, long-term air pollution exposure could affect the CVD trajectory. Distinguishing the effect of air pollutants on CVD transition stages has great significance for CVD health management and clinical prevention, especially among asthma patients.

Temporal Trend in Suicide Mortality for Chinese Adolescents, 2008 to 2021.

This study aims to evaluate the temporal trend in suicide mortality for Chinese adolescents aged 10 to 19 years from 2008 to 2021.

Associations of Life's Essential 8 and fine particulate matter pollution with the incidence of atrial fibrillation.

Both unhealthy lifestyle factors and ambient air pollution have been closely linked with the risk of atrial fibrillation (AF). We retrieved 250,898 participants without AF at baseline from UK Biobank. LE8 was determined by 8 metrics, and was characterized as low, moderate and high cardiovascular health (CVH). Exposure to PM2.5 was estimated at the geocoded residential address of each participant. During a median follow-up of 12.46 years, we identified 14,743 (5.9%) incident AF cases. Participants with moderate and high CVH showed a decreased risk of incident AF compared to those with low CVH. Of the LE8 metrics, ideal body mass index (BMI) and blood pressure (BP) were associated with a decrease of 11.57% and 11.46% AF cases. High PM2.5 exposure was associated with an 8% increased risk of AF as compared to low PM2.5 exposure. Compared with those who had low CVH and high PM2.5 exposure, participants with a high CVH and low PM2.5 exposure had the lower AF incidence. Our study found higher CVH is protective, while higher PM2.5 might be one risk factor of AF. Adherence to the LE8 guidelines may help reduce the incidence of AF, especially in those with lower PM2.5 exposure.

Dietary Diversity and Inflammatory Diet Associated with All-Cause Mortality and Incidence and Mortality of Type 2 Diabetes: Two Prospective Cohort Studies.

A higher dietary diversity score (DDS) and a lower energy-adjusted dietary inflammatory index (E-DII) may be associated with lower risks of type 2 diabetes (T2D) and mortality. This cohort study aimed to investigate the associations of DDS and E-DII with all-cause mortality, incidence of T2D, and mortality of T2D, as well as the joint effects of these two dietary factors. A total of 181,360 participants without all types of diabetes at baseline from the UK Biobank and 42,139 participants from the US NHANES were included. Cox proportional hazards models were used to assess the associations of DDS and E-DII with outcomes. In the UK Biobank data, 8338 deaths, 3416 incident T2D cases, and 353 T2D deaths occurred during a median follow-up of 12.5 years. In the US NHANES data, 6803 all-cause deaths and 248 T2D-specific deaths were recorded during a median follow-up of 9.6 years. We observed that higher DDS and lower E-DII were significantly associated with lower risks of total mortality and incident T2D. Compared with low DDS, the hazard ratios (HRs) and 95% confidence intervals (CIs) of high DDS were 0.69 (0.64, 0.74) for all-cause mortality, 0.79 (0.70, 0.88) for incident T2D in the UK Biobank, and 0.69 (0.61, 0.78) for all-cause mortality in the US NHANES. Compared with participants in tertile 3 of E-DII, those in tertile 1 had a lower risk of overall death [HR 0.86 (95% CI: 0.81, 0.91) in UK Biobank; 0.83 (0.77, 0.88) in US NHANES] and incident T2D [0.86 (0.79, 0.94)] in UK Biobank. No evidence was observed of the interactive effects of DDS and E-DII on either all-cause mortality or the incidence and mortality of T2D. There was no significant association found between any exposure and T2D mortality in this study. In conclusion, our results revealed that higher DDS and lower E-DII were associated with both total mortality and incident T2D in UK and US adults.

Relation of Life's Essential 8 to the genetic predisposition for cardiovascular outcomes and all-cause mortality: results from a national prospective cohort.

AIMS: To evaluate the independent, mediating, interactive, and associated effects of Life's Essential 8 (LE8) and genetic predisposition on the risk of cardiovascular outcomes and all-cause mortality. METHODS AND RESULTS: We retrieved a total of 254 783 individuals from the UK Biobank. LE8 was determined by eight metrics (nicotine exposure, physical activity, diet, sleep, body mass index, blood pressure, blood glucose, and blood lipids), and was characterized as low, moderate, and high cardiovascular health (CVH). Genetic predisposition was estimated using the polygenic risk score (PRS). Cox regressions were performed to evaluate the associations between LE8, PRS, and outcomes. During a median follow-up of 12.53 years, all-cause mortality occurred in 10 257 of 197 473 participants, cardiovascular mortality in 2074 of 215 675, and incident cardiovascular disease (CVD) in 71 774 of 215 675. Individuals with moderate or high CVH experienced a lower risk [hazard ratios (HRs) 0.33 to 0.81] of adverse health outcomes compared with their counterparts with low CVH. A substantial proportion (16.1∼69.8%) of health outcomes could be attributable to moderate or high LE8, and up to 51.2% of the associations between PRS and adverse outcomes were mediated by LE8. In high PRS group, individuals with high CVH had lower CVD mortality (HR: 0.26, 95% confidence interval: 0.18, 0.39), compared to those with low CVH. CONCLUSION: Ideal CVH was associated with lower risks of cardiovascular outcomes and all-cause mortality, with a more pronounced association observed in individuals with high PRS for CVD. Improving CVH according to LE8 guidelines should be encouraged, especially for those with PRS that indicate high CVD risk.

In the UK Biobank cohort of over 250 000 people, we found that participants achieved high scores on the Life's Essential 8 (LE8) guidelines had better health outcomes. The study also found that following LE8 guidelines helped reduce the risk of cardiovascular diseases, especially for those with a genetic predisposition to the condition. Thus, adopting a healthy lifestyle, as per the LE8 guidelines, could improve cardiovascular health and reduce the risk of death, even more than genetics alone. Furthermore, the study found that for every increase of one point in the LE8 score, the risk of adverse health outcomes decreased by 2­5%.

A Lightweight Automatic Wildlife Recognition Model Design Method Mitigating Shortcut Learning.

Recognizing wildlife based on camera trap images is challenging due to the complexity of the wild environment. Deep learning is an optional approach to solve this problem. However, the backgrounds of images captured from the same infrared camera trap are rather similar, and shortcut learning of recognition models occurs, resulting in reduced generality and poor recognition model performance. Therefore, this paper proposes a data augmentation strategy that integrates image synthesis (IS) and regional background suppression (RBS) to enrich the background scene and suppress the existing background information. This strategy alleviates the model's focus on the background, guiding it to focus on the wildlife in order to improve the model's generality, resulting in better recognition performance. Furthermore, to offer a lightweight recognition model for deep learning-based real-time wildlife monitoring on edge devices, we develop a model compression strategy that combines adaptive pruning and knowledge distillation. Specifically, a student model is built using a genetic algorithm-based pruning technique and adaptive batch normalization (GA-ABN). A mean square error (MSE) loss-based knowledge distillation method is then used to fine-tune the student model so as to generate a lightweight recognition model. The produced lightweight model can reduce the computational effort of wildlife recognition with only a 4.73% loss in accuracy. Extensive experiments have demonstrated the advantages of our method, which is beneficial for real-time wildlife monitoring with edge intelligence.

Associations of risk factor burden and genetic predisposition with the 10-year risk of atrial fibrillation: observations from a large prospective study of 348,904 participants.

BACKGROUND: Understanding the effects of risk factor burden and genetic predisposition on the long-term risk of atrial fibrillation (AF) is important to improve public health initiatives. However, the 10-year risk of AF considering risk factor burden and genetic predisposition is unknown. METHODS: A total of 348,904 genetically unrelated participants without AF at baseline from the UK were categorized into three groups: index ages 45 years (n = 84,206), 55 years (n=117,520), and 65 years (n=147,178). Optimal, borderline, or elevated risk factor burden was determined by body mass index, blood pressure, diabetes mellitus, alcohol consumption, smoking status, and history of myocardial infarction or heart failure. Genetic predisposition was estimated using the polygenic risk score (PRS), constructed using 165 predefined genetic risk variants. The combined effects of risk factor burden and PRS on the risk of incident AF in 10 years were estimated for each index age. Fine and Gray models were developed to predict the 10-year risk of AF. RESULTS: The overall 10-year risk of AF was 0.67% (95% CI: 0.61-0.73%) for index age 45 years, 2.05% (95% CI: 1.96-2.13%) for index age 55 years, and 6.34% (95% CI: 6.21-6.46%) for index age 65 years, respectively. An optimal risk factor burden was associated with later AF onset regardless of genetic predisposition and sex (P < 0.001). Significant synergistic interactions were observed for risk factor burden with PRS at each index age (P < 0.05). Participants with an elevated risk factor burden and high PRS had the highest 10-year risk of AF in reference to those who had both an optimal risk factor burden and a low PRS. At younger ages, optimal risk burden and high PRS might also lead to later onset of AF, compared to the joint effect of elevated risk burden and low/intermediate PRS. CONCLUSIONS: Risk factor burden together with a genetic predisposition is associated with the 10-year risk of AF. Our results may be helpful in selecting high-risk individuals for primary prevention of AF and facilitating subsequent health interventions.

Association between Family Environment and Adolescents' Sexual Adaptability: Based on the Latent Profile Analysis of Personality Traits.

Sexual adaptation plays an important role in psychosexual health. Our study aimed to investigate the relationship between the family environment and sexual adaptability among adolescents with different personality traits. A cross-sectional study was conducted in Shanghai and Shanxi province. A total of 1106 participants aged 14-19 was surveyed in 2019, including 519 boys and 587 girls. Univariate analyses and mixed regression models were performed to assess the association. Girls had a significantly lower average score of sexual self-adaptation compared to boys (4.01 ± 0.77 vs. 4.32 ± 0.64, p < 0.001). We found that the family environment did not impact boys' sexual adaptation in different personality groups. For girls in a balanced group, expressiveness factors improved their sexual adaptability (p < 0.05), intellectual-cultural orientation and organization promoted social adaptability (p < 0.05) and active-recreational orientation and control decreased their social adaptability (p < 0.05). In the high-neuroticism group, cohesion facilitated sexual control (p < 0.05), while conflict and organization reduced sexual control ability, and active-recreational orientation decreased sexual adaptation (p < 0.05). No factors associated with the family environment were found to influence sexual adaptability in groups with low neuroticism and high ratings in other personality factors. Compared with boys, girls demonstrated lower sexual self-adaptability, and their overall sexual adaptability was more susceptible to the family environment.

Habitual fish oil supplementation and the risk of incident atrial fibrillation: findings from a large prospective longitudinal cohort study.

AIMS: Mixed effects of fish oil supplementation on the risks of atrial fibrillation (AF) were observed in several large-scale randomized controlled trials. Whether this relationship would be modified by genetic AF risk, baseline cardiovascular disease (CVD) status and background oily fish consumption are unknown. METHODS AND RESULTS: We included 468 665 participants without AF at baseline from the UK Biobank cohort. The association between fish oil supplementation and the AF risk was assessed in the study cohort and in several subgroups, including genetic AF predisposition, baseline CVD status, and background oily fish consumption. During a median follow-up of 11.1 years, fish oil users had a higher rate of incident AF (6.2% vs. 5.2%, adjusted hazard ratio of 1.10, and 95% confidence interval of 1.07, 1.13). Compared with non-users, fish oil users had a higher rate of incident AF in the low (3.7% vs. 3.0%, P= 0.02), intermediate (5.8% vs. 4.8%, P < 0.0001), and high (9.8% vs. 8.1%, P < 0.0001) genetic AF risk groups. In participants without CVD at baseline, fish oil users had a higher rate of incident AF (5.3% vs. 4.1%, P < 0.0001), which was not observed in participants with CVD at baseline (11.6% vs. 11.1%, P = 0.56), with significant interaction (P-interaction < 0.0001). The association between fish oil supplementation and the AF risk was not modified by background oily fish consumption (P-interaction = 0.62). CONCLUSION: Habitual fish oil supplementation was associated with the risk of incident AF, regardless of genetic AF predisposition and background oily fish consumption. This association was observed only in individuals without CVD at baseline.

Associations of single and multiple perfluoroalkyl substances exposure with folate among adolescents in NHANES 2007-2010.

BACKGROUND: The accumulation of perfluoroalkyl substances (PFAS) in human body has raised concerns about the potential health impacts on children and adolescents. However, no study has evaluated the associations of PFAS exposure with folate concentrations among adolescents. METHODS: In the present study, we mainly used three statistical approaches, namely multiple linear regression, Bayesian Kernel Machine Regression (BKMR), and quantile-based g-computation (Q-gcomp) models, to evaluate associations of individual PFAS and their mixtures with serum and red blood cell (RBC) folate concentrations in a sample of 721 adolescents from the NHANES 2007-2010. RESULTS: In multiple linear regression models, for per unit increase in ln-transformed perfluorooctane sulfonate (PFOS), perfluorooctanoic acid (PFOA), and perfluorononanoic acid (PFNA), and perfluorodecanoic acid (PFDA) concentrations, RBC folate concentrations decreased by 72.4 (95% confidence interval (CI): -112.7, -32.2), 58.3 (95% CI: -115.0, -1.6), 60.7 (95% CI: -107.5, -13.8), and 76.5 (95% CI: -119.0, -33.9) nmol/L, respectively. A similar significant inverse association was also observed between ln-transformed PFDA and serum folate. BKMR models further confirmed inverse associations of serum PFOS and PFDA with RBC folate, and serum PFDA with serum folate. However, the inverse associations of PFOA and PFNA with RBC folate shown in multiple linear regression model were not observed or less evident in BKMR analyses. We observed interactions of PFOA with PFOS, PFNA, and PFDA on RBC folate in BKMR models, with the negative slopes for PFOS, PFNA, and PFDA increased when PFOA concentration increased from the 10th percentile to the 90th percentile. Both BKMR and Q-gcomp models suggested that the mixtures of five PFAS showed inverse overall associations with RBC folate concentration. CONCLUSIONS: The present study revealed that adolescent exposure to PFAS might affect serum and RBC folate concentrations.

Identifying Animals in Camera Trap Images via Neural Architecture Search.

Wild animals are essential for ecosystem structuring and stability, and thus they are important for ecological research. Since most wild animals have high athletic or concealable abilities or both, it is used to be relatively difficult to acquire evidence of animal appearances before applications of camera traps in ecological researches. However, a single camera trap may produce thousands of animal images in a short period of time and inevitably ends up with millions of images requiring classification. Although there have been many methods developed for classifying camera trap images, almost all of them follow the pattern of a very deep convolutional neural network processing all camera trap images. Consequently, the corresponding surveillance area may need to be delicately controlled to match the network capability, and it may be difficult to expand the area in the future. In this study, we consider a scenario in which camera traps are grouped into independent clusters, and images produced by a cluster are processed by an edge device installed with a customized network. Accordingly, edge devices in this scenario may be highly heterogeneous due to cluster scales. Resultantly, networks popular in the classification of camera trap images may not be deployable for edge devices without modifications requiring the expertise which may be hard to obtain. This motivates us to automatize network design via neural architecture search for edge devices. However, the search may be costly due to the evaluations of candidate networks, and its results may be infeasible without considering the resource limits of edge devices. Accordingly, we propose a search method using regression trees to evaluate candidate networks to lower search costs, and candidate networks are built based on a meta-architecture automatically adjusted regarding to the resource limits. In experiments, the search consumes 6.5 hours to find a network applicable to the edge device Jetson X2. The found network is then trained on camera trap images through a workstation and tested on Jetson X2. The network achieves competitive accuracies compared with the automatically and the manually designed networks.

Domain-Aware Neural Architecture Search for Classifying Animals in Camera Trap Images.

Camera traps provide a feasible way for ecological researchers to observe wildlife, and they often produce millions of images of diverse species requiring classification. This classification can be automated via edge devices installed with convolutional neural networks, but networks may need to be customized per device because edge devices are highly heterogeneous and resource-limited. This can be addressed by a neural architecture search capable of automatically designing networks. However, search methods are usually developed based on benchmark datasets differing widely from camera trap images in many aspects including data distributions and aspect ratios. Therefore, we designed a novel search method conducted directly on camera trap images with lowered resolutions and maintained aspect ratios; the search is guided by a loss function whose hyper parameter is theoretically derived for finding lightweight networks. The search was applied to two datasets and led to lightweight networks tested on an edge device named NVIDIA Jetson X2. The resulting accuracies were competitive in comparison. Conclusively, researchers without knowledge of designing networks can obtain networks optimized for edge devices and thus establish or expand surveillance areas in a cost-effective way.

Construction and Analysis of the lncRNA-miRNA-mRNA Network Based on Competing Endogenous RNA in Atrial Fibrillation.

BACKGROUND: Accumulated studies have revealed that long non-coding RNAs (lncRNAs) play critical roles in human diseases by acting as competing endogenous RNAs (ceRNAs). However, functional roles and regulatory mechanisms of lncRNA-mediated ceRNA in atrial fibrillation (AF) remain unknown. In the present study, we aimed to construct the lncRNA-miRNA-mRNA network based on ceRNA theory in AF by using bioinformatic analyses of public datasets. METHODS: Microarray data sets of GSE115574 and GSE79768 from the Gene Expression Omnibus database were downloaded. Twenty-one AF right atrial appendage (RAA) samples and 22 sinus rhythm (SR) subjects RAA samples were selected for subsequent analyses. After merging all microarray data and adjusting for batch effect, differentially expressed genes were identified. Gene Ontology (GO) categories and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were carried out. A ceRNA network was constructed. RESULT: A total of 8 lncRNAs and 43 mRNAs were significantly differentially expressed with fold change >1.5 (p < 0.05) in RAA samples of AF patients when compared with SR. GO and KEGG pathway analysis showed that cardiac muscle contraction pathway were involved in AF development. The ceRNA was predicted by co-expressing LOC101928304/ LRRC2 from the constructional network analysis, which was competitively combined with miR-490-3p. The expression of LOC101928304 and LRRC were up-regulated in myocardial tissue of patients with AF, while miR-490-3p was down-regulated. CONCLUSION: We constructed the LOC101928304/miR-490-3p/LRRC2 network based on ceRNA theory in AF in the bioinformatic analyses of public datasets. The ceRNA network found from this study may help improve our understanding of lncRNA-mediated ceRNA regulatory mechanisms in the pathogenesis of AF.

Serum zinc concentrations and prediabetes and diabetes in the general population.

The association between serum zinc and diabetes development remains uncertain. We examined the associations between serum zinc and prediabetes and diabetes, and adult participants (≥ 20 years) from the 2011-2016 National Health and Nutrition Examination Survey. Serum zinc concentrations were measured with inductively coupled plasma dynamic reaction cell mass spectrometry. Prediabetes and diabetes were defined through questionnaires and fasting plasma glucose and hemoglobin A1c levels. Weighted logistic regression and restricted cubic splines were adopted to explore the dose-response relationships between serum zinc concentrations and prediabetes and diabetes. Comparing the highest to lowest quartile of serum zinc concentrations, the multivariable-adjusted odds ratio (95% confidence interval) of prediabetes and diabetes was 3.24 (2.33-4.52, Pfor trend < 0.01) and 1.64 (1.27-2.11, Pfor trend < 0.01), respectively. In stratified analysis by sex, the association between serum zinc concentrations and prediabetes was found in both men (3.83 (2.60-5.66), Pfor trend < 0.01) and women (2.41 (1.51-3.87), Pfor trend < 0.01), and the association between serum zinc concentrations and diabetes was also found in both men (2.05 (1.34-3.13), Pfor trend < 0.01) and women (1.65 (1.07-2.56), Pfor trend = 0.15). The association between serum zinc and prediabetes was consistent in stratified analyses by body mass index and hypertension, and the association with diabetes was also found in subjects with hypertension. Restricted cubic splines showed that the relationships between serum zinc concentrations and prediabetes and diabetes were linear, respectively. In conclusion, serum zinc concentrations were positively associated with prediabetes and diabetes in the general population, and the associations were linear. The findings need to be confirmed by prospective cohort studies.