Health Datasets Research Articles

Tackling Algorithmic Bias and Promoting Transparency in Health Datasets: The STANDING Together Consensus Recommendations

Tackling Algorithmic Bias and Promoting Transparency in Health Datasets: The STANDING Together Consensus Recommendations

Association of dietary patterns with chronic respiratory health among U.S. adults

BackgroundRespiratory health is closely related to immune system function, and diet can also influence immune homeostasis. Diet, an important part of a healthy lifestyle, is also linked to respiratory health. We aimed to explore the relationship between different dietary patterns and the risk of chronic respiratory diseases (CRDs), including chronic bronchitis (CB), emphysema, and asthma.MethodA total of 23,042 adults from the United States were selected from the National Health and Nutrition Examination Survey (NHANES) dataset between 2007 and 2018. Diet quality was assessed using 2-day, 24-hour dietary recall data and quantified as the Healthy Eating Index-2020 (HEI-2020), the Dietary Inflammation Index (DII), the Mediterranean Dietary Index (MEDI), and the Dietary Approaches to Stop Hypertension Index (DASHI). Binary logistic regression models, restricted cubic splines (RCS), and the weighted quartile sum (WQS) models were used to assess the relationship between diet quality and the risk of CB, emphysema, and asthma.ResultsIn logistic regression analyses of the four dietary indices with the three chronic respiratory diseases, it was consistently observed that higher dietary quality scores were linked to a reduced risk of respiratory disease. These consistent trends were also evident in the assessments of the dose–response relationship between dietary quality score and the risk of respiratory disease. Furthermore, evaluations of the combined effects of dietary components across different dietary indices in the risk of chronic respiratory disease yielded results consistent with the logistic regression models. Notably, high-quality protein, minerals, and fiber-rich fruits and vegetables emerged as the food groups making the most significant contributions to health across different dietary indices.ConclusionLow-quality diets, lacking in high-quality protein, minerals, and fruits and vegetables rich in dietary fiber, are associated with a higher risk of chronic respiratory disease, regardless of the dietary index used to measure diet quality.

Predictive role of neutrophil percentage-to-albumin ratio, neutrophil-to-lymphocyte ratio, and systemic immune-inflammation index for mortality in patients with MASLD

There are no studies discussing the significance of neutrophil-to-lymphocyte ratio (NLR), neutrophil-percentage-to-albumin ratio (NPAR), and systemic immune-inflammation index (SII) in predicting poor prognosis in patients with metabolic dysfunction associated steatotic liver disease (MASLD); this study aimed to investigate the relationship between these three inflammatory markers and all-cause mortality and cardiovascular disease (CVD) mortality in patients with MASLD. Survival data for 3970 participants were obtained from National Death Index (NDI) records associated with the National Health and Nutrition Examination Survey (NHANES) dataset, the associations of NPAR, NLR, and SII with all-cause and CVD mortality were analyzed using multivariate COX regression modeling, restricted cubic spline (RCS) was used to explore nonlinear relationships and to determine the inflection point, regrouping was done according to the nonlinear inflection point, using multivariate COX regression modeling, subgroup analysis, and the Kaplan-Meier survival curves to evaluate differences in risk of death between the two groups. Time-dependent receiver operating characteristic curve (ROC) analysis was conducted to assess the predictive efficacy of NPAR, NLR, and SII on survival outcomes. Multivariate COX regression and RCS analyses revealed a positive linear correlation between NLR and all-cause and CVD mortality, whereas a nonlinear relationship was found between NPAR and SII and all-cause and CVD mortality. Further reclassified into two groups according to the inflection point, multivariate COX regression analyses showed a significant difference in the risk of death between the two NPAR groups (HR 1.37, 95% CI = (1.01, 1.86) for all-cause mortality and HR 2.03, 95% CI = (1.24, 3.32) for CVD mortality ) and no difference in the risk of death between the two SII groups (HR 1.11, 95% CI = (0.87, 1.42) for all-cause mortality and HR 1.35, 95% CI = (0.86, 2.12) for CVD mortality), and Kaplan-Meier survival curves showed that both all-cause and CVD mortality rates were higher in patients with MASLD above the NPAR inflection point (log-rank P < 0.05). Subgroup analyses showed that the associations between high levels of NPAR and all-cause mortality were generally consistent across populations (P interaction > 0.05). Also, COPD subgroups had a significant effect on the correlation between high levels of NPAR and CVD mortality (P interaction < 0.05). Time-dependent ROC show the predictive value of NPAR, NLR, and SII for all-cause and CVD mortality in MASLD patients. The correlation between NPAR and mortality was nonlinear, and NLR was linearly and positively correlated with mortality, Measuring NPAR and NLR may be useful in assessing risk and predicting prognosis in populations of patients with MASLD.

Serum concentrations of different or multiple vitamins and Sarcopenia risk among US adults: insights from NHANES

BackgroundThe relationship between serum concentrations of different or multiple vitamins and sarcopenia remains underexplored. This investigation evaluates potential links between serum concentrations of different or multiple vitamins and sarcopenia prevalence among adults in the United States.MethodsUtilizing a cross-sectional design, this research draws from the National Health and Nutrition Examination Survey (NHANES) dataset of 2003–2006, encompassing 5,060 participants with comprehensive serum vitamin A, E, B9, B12, C, and D concentrations, alongside sarcopenia and covariate measurements. Participant stratification into distinct vitamin co-exposure clusters was achieved through K-means clustering. Analytical models, including weighted logistic regression, restricted cubic splines (RCS), weighted quantile sum regression (WQS), quantile g-computation (Q-gcomp), and Bayesian kernel machine regression (BKMR), were employed to evaluate the association between serum concentrations of different or multiple vitamins and sarcopenia risk, with an emphasis on nonlinearity.ResultsIn this study, sarcopenia was detected in 681 individuals (13.46%). Logistic regression results did not demonstrate any linear association between individual vitamin levels and sarcopenia risk (PFDR > 0.05). Contrastingly, the RCS model unveiled significant non-linear relationships for vitamins A and D (P_non-linear < 0.05). The K-means clustering results showed that participants in high-level vitamin exposure group had lower sarcopenia risk compared with those in low-level vitamin exposure group (OR (95% CI): 0.582 (0.397, 0.852)). Additionally, higher serum concentrations of different or multiple vitamins correlated inversely with sarcopenia risk (P_trend = 0.002). This inverse association was corroborated by WQS, Q-gcomp, and theBKMR models and remained consistent upon sensitivity analysis.ConclusionsThis study elucidates an inverse correlation between serum concentrations of different or multiple vitamins and sarcopenia risk, emphasizing a non-linear association, particularly with suboptimal vitamin D concentrations. Given the limitations of the NHANES study, further researches are required to clarify the existence of these relationships.

Tackling algorithmic bias and promoting transparency in health datasets: the STANDING Together consensus recommendations

Tackling algorithmic bias and promoting transparency in health datasets: the STANDING Together consensus recommendations

Conceptual framework for data harmonisation in mental health using the International Classification of Functioning, Disability and Health: an example with the R2D2-MH consortium

IntroductionAdvancing research and support for neurologically diverse populations requires novel data harmonisation methods that are capable of aligning with contemporary approaches to understanding health and disability.ObjectivesWe present the International Classification...

Economic Impact of Bariatric Surgery in Australia: 16-Year Results from the 45 and Up Study with Linked Health Data.

Bariatric surgery is the most effective long-term therapy for severe obesity; however, empirical investigation of its economic impacts has been based on limited samples, short-term costs, and a narrow range of cost categories. This study aimed to evaluate the economic impacts of bariatric surgery in a large cohort of Australians aged ≥ 45years. N = 1157 operated (surgery) and 1157 non-operated participants were selected from the 45 and Up Study. Data sources included the baseline and follow-up surveys along with linked state and national administrative health datasets. Linear mixed-effects regression predicted the cost trajectory 8years pre- and post-bariatric surgery, and the difference-in-differences approach evaluated its economic impact. Sensitivity analyses included an approximation of indirect costs and subgroup analysis by surgery type. The matched cohort composed 77% female, had an average age of 58.1 ± 5.8years. Direct healthcare costs increased over time in both groups. Costs for the operated group peaked ($15,884) during the surgery year and became up to 23.8% lower than those for the non-operated group from the second year post-surgery when including indirect costs. Surgery's economic benefits increased over longer horizons, with a maximum annual cost-saving of $3196 per person in the eighth post-surgery year. However, even after accounting for indirect costs, cumulative cost-savings were not achieved. Subgroup analysis revealed sleeve gastrectomy as the least costly surgical option. Higher short-term costs in the surgery year primarily drove inter-group cost differences. The economic value of bariatric surgery lies in the long-term benefits, particularly when considering indirect costs.

Creating an Empirical Dermatology Dataset Through Crowdsourcing With Web Search Advertisements

Health datasets from clinical sources do not reflect the breadth and diversity of disease, impacting research, medical education, and artificial intelligence tool development. Assessments of novel crowdsourcing methods to create health datasets are needed. To evaluate if web search advertisements (ads) are effective at creating a diverse and representative dermatology image dataset. This prospective observational survey study, conducted from March to November 2023, used Google Search ads to invite internet users in the US to contribute images of dermatology conditions with demographic and symptom information to the Skin Condition Image Network (SCIN) open access dataset. Ads were displayed against dermatology-related search queries on mobile devices, inviting contributions from adults after a digital informed consent process. Contributions were filtered for image safety and measures were taken to protect privacy. Data analysis occurred January to February 2024. Dermatologist condition labels as well as estimated Fitzpatrick Skin Type (eFST) and estimated Monk Skin Tone (eMST) labels. The primary metrics of interest were the number, quality, demographic diversity, and distribution of clinical conditions in the crowdsourced contributions. Spearman rank order correlation was used for all correlation analyses, and the χ2 test was used to analyze differences between SCIN contributor demographics and the US census. In total, 5749 submissions were received, with a median of 22 (14-30) per day. Of these, 5631 (97.9%) were genuine images of dermatological conditions. Among contributors with self-reported demographic information, female contributors (1732 of 2596 contributors [66.7%]) and younger contributors (1329 of 2556 contributors [52.0%] aged <40 years) had a higher representation in the dataset compared with the US population. Of 2614 contributors who reported race and ethnicity, 852 (32.6%) reported a racial or ethnic identity other than White. Dermatologist confidence in assigning a differential diagnosis increased with the number of self-reported demographic and skin-condition-related variables (Spearman R = 0.1537; P < .001). Of 4019 contributions reporting duration since onset, 2170 (54.0%) reported onset within less than 7 days of submission. Of the 2835 contributions that could be assigned a dermatological differential diagnosis, 2523 (89.0%) were allergic, infectious, or inflammatory conditions. eFST and eMST distributions reflected the geographical origin of the dataset. The findings of this survey study suggest that search ads are effective at crowdsourcing dermatology images and could therefore be a useful method to create health datasets. The SCIN dataset bridges important gaps in the availability of images of common, short-duration skin conditions.

The incidence and prevalence of immunoglobulin A nephropathy intheUnited States.

Reliable national estimates for the incidence and prevalence of immunoglobulin A nephropathy (IgAN) in the United States (U.S.) are needed. We performed a national survey with pathologists and used insurance claims data to estimate IgAN frequency nationwide. An online survey with pathologists was conducted between November and December 2021 to obtain data on the number and types of biopsies evaluated and the proportion with IgAN confirmed. Biopsy data were extrapolated to two different claims databases to estimate incidence and prevalence. Results were validated against a separate dataset of electronic health records. A total of 43 pathologists from across U.S. regions reported evaluating a mean of 169 kidney biopsies (standard deviation 179.1) in the past 12 months. Of the 7,267 total biopsies evaluated, 632 (8.7%) were IgAN. Based on the respective claims databases, annual incidence rates of 2.1 and 2.2 per 100,000 and prevalence rates of 59.9 and 62.7 per 100,000 were estimated. Results from the validation dataset were similar, with an incidence of 1.9 per 100,000 and prevalence of 54.2 per 100,000. This study estimated incidence and prevalence of IgAN. Extrapolating the findings to the U.S. population for 2021, total prevalence was 198,887 - 208,184 persons.

Association between weight-adjusted waist circumference index and myocardial infarction: results from the national health and nutrition examination survey, 1999-2014.

Weight-adjusted waist circumference index (WWI) is a novel index related to obesity and has been associated with the risk and prognosis of several diseases. The aim of the study was to determine the association between WWI and myocardial infarction. The study analyzed cross-sectional data from 31,535 participants derived from the 1999-2014 National Health and Nutrition Examination Survey (NHANES) dataset. Multiple logistic regression and restricted cubic spline (RCS) analyses were conducted to assess both linear and nonlinear associations between WWI and myocardial infarction. Subgroup analyses and interaction tests were also performed. Among the 31,535 participants analyzed, 1,449 (4.82%) had experienced a myocardial infarction. The fully adjusted models demonstrated a positive association between WWI and myocardial infarction [odds ratio (OR) = 1.34, 95% confidence interval (CI): 1.13-1.58]. Individuals in the highest quartile of WWI were 81% more likely to suffer from a myocardial infarction compared to those in the lowest quartile (OR = 1.81, 95% CI: 1.24-2.63). The analysis employing restricted cubic spline modeling indicated a nonlinear positive correlation between WWI and myocardial infarction. The risk of myocardial infarction was 1.29 times higher when WWI was below 10.97 cm/√kg (OR = 2.29, 95% CI: 1.37-3.84). When WWI exceeded 10.97 cm/√kg, the upward trend in the risk of myocardial infarction significantly slowed with increasing WWI (OR = 1.26, 95%CI:1.03-1.56). A threshold WWI value of greater than 11.15 cm/√kg was identified for predicting myocardial infarction, outperforming waist circumference and body mass index (BMI). Subgroup analyses revealed that the impact of WWI on myocardial infarction varied across different populations. Interaction analyses demonstrated significant interactions between myocardial infarction incidence and WWI with age, hypertension, coronary heart disease, angina pectoris, and stroke (P for interaction <0.05), but not with gender, race, obesity, diabetes, or prediabetes and heart failure (P for interaction >0.05). The findings suggest that there is a positive and non-linear association between WWI and the incidence of myocardial infarction. We recommend incorporating WWI into routine physical examinations and cardiovascular risk screening as an early warning mechanism. This may facilitate early identification of high-risk individuals and promote earlier preventive interventions.

Impact of sleep problems on the cardiometabolic risks: an integrated epidemiological and metabolomics study

BackgroundWe investigated the association between sleep problems and cardiometabolic risks and the potential linking effect of metabolites and metabolic pathways based on multi-layered research, including observational, mendelian randomization (MR), and metabolomics analysis.MethodsA cross-sectional analysis of the 2015–2018 National Health and Nutrition Examination Survey (NHANES) dataset was conducted to identify the association between sleep problems and cardiometabolic risks. A subsequent MR study based on genetic data was performed to explore the causal correlation of significant associations in the NHANES study. The underlying alteration of metabolism was explored by constructing zebrafish models and wide-targeted metabolomics analysis.ResultsThe cross-sectional analysis of the NHANES database revealed a significant association of snoring with obesity [OR = 2.65, 95% confidence intervals (CI): 1.87, 3.74]; sleep apnea with hypertension (OR = 1.68, 95% CI: 1.14, 2.48) and obesity (OR = 1.44, 95% CI: 1.05, 1.96); trouble sleeping with hypertension (OR = 1.84, 95% CI: 1.18, 2.86), obesity (OR = 1.56, 95% CI: 1.07, 2.26), and type 2 diabetes (T2DM) (OR = 1.52, 95% CI: 1.02, 2.25). MR analysis verified the causal relationship between genetically proxied sleep apnea or snoring and obesity. The decreased activity levels and altered expression levels of six circadian genes (bmal1b, cry1aa, cry1ab, clock1a, per1b, per2) were identified in the zebrafish of the sleep disorder group. Multiple metabolites related to disturbed glucose metabolism (e.g., 20-HETE), lipid metabolism (e.g., inosine), and vascular-related metabolites (e.g., riboflavin) were finally identified, indicating the latent effect of metabolism.ConclusionsThis study identified the chain of sleep-circadian rhythm-metabolism-cardiometabolic risks. These findings can promote improved prevention implementation and therapeutic strategies.

Comparison of Outcomes Between ST-Segment Elevation and Non-ST-Segment Elevation Myocardial Infarctions Based on Left Ventricular Ejection Fraction.

Background: This study was conducted to address the lack of reports comparing the clinical outcomes of non-ST-segment elevation myocardial infarction (NSTEMI) and STEMI based on left ventricular ejection fraction (LVEF). Methods: A total of 9854 patients from the Korea Acute Myocardial Infarction Registry-National Institute of Health dataset were classified into three LVEF categories: heart failure (HF) with reduced ejection fraction (EF) (HFrEF, n = 1250), HF with mildly reduced EF (HFmrEF, n = 2383), and HF with preserved EF (HFpEF, n = 6221). Each group was further divided into NSTEMI and STEMI groups. The primary clinical outcome was the incidence of patient-oriented composite outcomes, defined as all-cause death, recurrent myocardial infarction, any repeat coronary revascularization, hospitalization for HF, and stroke. Results: Following adjustment, in-hospital mortality rates were comparable between the NSTEMI and STEMI groups in the HFrEF and HFmrEF groups. However, 3-year mortality rates were higher in the NSTEMI group. In contrast, in the HFpEF group, the STEMI group had higher rates of in-hospital all-cause death (p = 0.001) and cardiac death (p < 0.001) compared to the NSTEMI group, which was associated with increased 3-year all-cause death (p = 0.026) and cardiac death (p < 0.001) in the STEMI group. When in-hospital mortality was excluded, no difference in 3-year mortality rates was observed between the NSTEMI and STEMI groups in the HFpEF group. Conclusions: In-hospital mortality and 3-year outcomes varied across LVEF groups. Therefore, comparing NSTEMI and STEMI based on LVEF provides valuable insights into the differences in patient outcomes.

Equity of access to pathological diagnosis and bronchoscopy for lung cancer in Aotearoa New Zealand.

Māori are less likely to survive their lung cancer once diagnosed, but it remains unclear whether this is partially driven by poorer access to best-practice diagnostic services. We examined all lung cancer registrations in Aotearoa New Zealand between 2007-2019 (n=27,869) linked to national administrative health datasets and further stratified by ethnicity, tumour type and stage of disease. Using descriptive and regression analyses, we compared ethnic groups in terms of the basis of diagnosis (e.g., histology, cytology), receipt of bronchoscopy and travel distance and time to access bronchoscopy. We found no differences in access to a pathological diagnosis between ethnic groups regardless of cancer type or stage. We found that Māori within the cohort were marginally more likely to access bronchoscopy than the majority European group; however, we also found that Māori had lower odds of living close to the location of their bronchoscopy, and correspondingly higher odds of living 100-200km (adjusted odds ratio [adj. OR] 1.46, 95% confidence interval [CI] 1.26-1.69) or more than 200km away (1.36, 95% CI 1.15-1.61) than Europeans. Interventions that aim to further support Māori to overcome the systematic and cumulative disadvantages in access to cancer care should be broadly supported and resourced.

Variation in commercial prices for thyroidectomy and parathyroidectomy at US hospitals

BackgroundThe 2021 Hospital Price Transparency Rule mandated hospitals to publicly disclose their service prices to improve competition and lower healthcare costs. Our aim was to characterize commercial price variation for thyroidectomy and parathyroidectomy. MethodsWe performed a national cross-sectional study of hospital price variation in 2022 and 2023 using the Turquoise Health dataset. Our main outcomes were within- and across-hospital 90th-to-10th percentile commercial price ratios and a high commercial-to-Medicare (1.5) price ratio. We performed logistic regressions to identify hospital factors associated with a high commercial-to-Medicare price ratio. ResultsFor 16,794 unique commercial rates across 564 facilities, within-hospital price ratios ranged from 2.0 to 2.4, and across-hospital price ratios ranged from 2.7 to 4.1. High market concentration and five-star hospital rating were associated with high commercial-to-Medicare price ratios compared to low market concentration and three-star hospital rating, respectively. ConclusionsNotable variation exists within and across hospitals signaling facilities have negotiated different payments from insurance companies for the same service. Quality may be a modifiable factor to increase hospital revenue and improve care for patients.

Association Between Composite Dietary Antioxidant Index and Endometriosis from NHANES 2001-2006: A Cross-Sectional Study.

To evaluate the association between Composite Dietary Antioxidant Index (CDAI) and the risk of endometriosis in American women. The study adopted a cross-sectional design, incorporating 3862 women aged over 20 years, selected from the National Health and Nutrition Examination Survey (NHANES) dataset from 2001 to 2006. Six dietary antioxidants were taken into account in calculating CDAI. Endometriosis was determined based on self-report. To evaluate the association between CDAI and the risk of endometriosis, we employed models with multivariable logistic variables. For subgroup assessment in relation to CDAI, a stratified multivariate logistic regression model was utilized. Among all participants, 273 participants (7.1%) were found to exhibit endometriosis. The preliminary analysis showed a reverse association between CDAI and the likelihood of endometriosis (odds ratio [OR] = 0.95; 95% confidence interval [CI]: 0.92~0.98). Upon full adjustment within the multivariable logistic regression, the ORs (95% CI) for endometriosis prevalence per unit increase in CDAI were estimated to be 0.96 (0.93~1). When the CDAI levels were divided into quartiles, it was found that the ORs for endometriosis with CDAI levels in Q2 (-2.131-0.023), Q3 (0.023-2.650), and Q4 (2.650-42.854) were 0.74 (0.52, 1.05), 0.76 (0.53, 1.1), and 0.53 (0.36, 0.79), respectively, compared to those with CDAI levels in Q1 (-7.151--2.131). We evaluated the association between CDAI and endometriosis using subgroups stratified by age, race/ethnicity, education level, body mass index (BMI), oral contraceptive, and menopausal status, revealing a substantial negative relationship. In this cross-sectional study, increasing CDAI was proportionally associated with a reduced risk of endometriosis among American women, suggesting a diet high in antioxidants may play an important role in reducing the risk of endometriosis. The findings of NHANES data spanning 2001 to 2006 suggest that promoting antioxidant-rich diets could be an important prevention strategy for endometriosis.

Daily and Peak Monitor Independent Movement Summary (MIMS) Values Associated With Metabolic Syndrome: NHANES 2011-12 and 2013-14.

The U.S. National Health and Nutrition Examination Survey (NHANES) physical activity monitor datasets for 2011-12 and 2013-14 were released in late 2020. To date, there has been limited interpretation of these nationally representative wrist-worn accelerometer data (summarized and reported in Monitor Independent Movement Summary [MIMS] units) and their relationships with health-related outcomes. This study examined the associations between free-living DailyMIMS (volume), Peak 1MIMS and Peak 30MIMS (intensity), and risk of Metabolic Syndrome (MetS). Data from adults (N=3787; 18-80+ years) in the 2011-12 and 2013-14 NHANES cycles with health examination and accelerometry data were included. Accelerometer data were processed into Peak 1MIMS and Peak 30MIMS (MIMS/min), and DailyMIMS (MIMS/day). Design-based generalized linear and logistic regressions, and a sample-weighted decision tree, were used to examine associations between MIMS variables and MetS risk factors. Lower Peak 1MIMS, Peak 30MIMS, and DailyMIMS were observed for every one-unit increase in the number of risk factors -3.9 [95% CI: -4.3, -3.4] and -2.3 [-2.6, -2.1] MIMS/min, (-672.1 [-772.7, -571.5] MIMS/day, respectively, all p< 0.001). The Decision Tree classified individuals ≥ 46.5 years with a DailyMIMS ≥ 12 245 MIMS/day and a Peak 30MIMS < 45.1 MIMS/min as having MetS (≥ 3 risk factors). Individuals < 46.5 years with a Peak 1MIMS ≥ 62.9 MIMS/min were classified with 0 risk factors. Higher DailyMIMS and PeakMIMS were associated with an absence of MetS risk factors, with a progressive decline as the number of risk factors increased. These findings may be considered as preliminary benchmarks for DailyMIMS and PeakMIMS associated with cardiometabolic risk.

Developing a prototype for federated analysis to enhance privacy and enable trustworthy access to COVID-19 research data

BackgroundThe use of federated networks can reduce the risk of disclosure for sensitive datasets by removing the requirement to physically transfer data. Federated networks support federated analytics, a type of privacy-enhancing technology, enabling trustworthy data analysis without the movement of source data. ObjectivesTo set out the methodology used by the International COVID-19 Data Alliance (ICODA) and its partners, the Secure Anonymised Information Linkage (SAIL) Databank and Aridhia Informatics in piloting a federated network infrastructure and consequently testing federated analytics using test data provided from an ICODA project, the International Perinatal Outcome in the Pandemic (iPOP) Study. To share the challenges and benefits of using a federated network infrastructure to enable trustworthy analysis of health-related data from multiple countries and sources. ResultsThis project successfully developed a federated network between the SAIL Databank and the ICODA Workbench and piloted the use of federated analysis using aggregate-level model outputs as test data from the iPOP Study, a one-year, multi-country COVID-19 research project. This integration is a first step in implementing the necessary technical, governance and user experiences for future research studies to build upon, including those using individual-level datasets from multiple data nodes. ConclusionsCreating federated networks requires extensive investment from a data governance, technology, training, resources, timing and funding perspective. For future initiatives, the establishment of a federated network should be built into medium to long term plans to provide researchers with a secure and robust data analysis platform to perform joint multi-site collaboration. Federated networks can unlock the enormous potential of national and international health datasets through enabling collaborative research that addresses critical public health challenges, whilst maintaining privacy and trustworthiness by preventing direct access to the source data.

Association between systemic immune-inflammatory index and systemic inflammatory response index with body mass index in children and adolescents: a population-based study based on the National Health and Nutrition Examination Survey 2017-2020.

The Systemic Immune-Inflammatory Index (SII) and Systemic Inflammatory Response Index (SIRI) are novel composite inflammatory markers. Previous studies suggest that obesity in individuals correlates with persistently low levels of chronic inflammation. This study aims to explore the association between SII and SIRI and Body Mass Index (BMI) among children and adolescents. A cross-sectional survey was conducted using the National Health and Nutrition Examination Survey (NHANES) dataset from 2 consecutive cycles from 2017-2020. Multivariate linear regression models were employed to examine the linear relationships between BMI and SII and SIRI. Non-linear associations were explored using smooth curve fitting and threshold effect analysis. A total of 2980 children and adolescents aged 6-19 years were included in this population-based study. In the population description of body mass index categories, we found progressively higher levels of SII and SIRI, notably peaking among obese children (SII mean ± SD: 528.83 ± 285.46; SIRI mean ± SD: 1.12 ± 0.79). Weighted multivariate linear regression confirmed a significant positive association between BMI and both inflammatory indices (P < 0.0001). Subgroup analyses revealed consistent correlations across gender divisions and highlighted a non-linear relationship between BMI and SII. SII and SIRI are positively associated with BMI in children and adolescents, indicating their potential as markers for assessing systemic inflammation in pediatric obesity. Further large-scale prospective studies are required to substantiate these findings.

Association between stroke and relative fat mass: a cross-sectional study based on NHANES

BackgroundThis study was aimed at investigating the correlation between the occurrence of stroke and relative fat mass (RFM), a novel metric for determining total body fat.MethodsThis cross-sectional study employed the National Health and Nutrition Examination Survey (NHANES) dataset, which encompassed the years 2005 to 2018 to assess the independent relationship between RFM and stroke. Moreover, multinomial logistic regression, subgroup analysis, smooth curve fitting, and interaction testing were also used.ResultsThis study included 35,842 participants and 1,267 (3.53%) of them were diagnosed with stroke. Fully adjusted Models showed that RFM was positively associated with stroke (odds ratio [OR] = 1.02; 95% confidence interval [CI] = 1.01–1.03). The odds of having a stroke in quartile 4 were significantly elevated by 44%, compared to quartile 1 (OR = 1.44,95%CI:1.09–1.90). In addition, a subgroup analysis also demonstrated that age and BMI significantly impacted the association between RFM and stroke (P for interaction<0.01).ConclusionsElevated RFM is associated with increased odds of stroke, suggesting that RFM may have potential value in the prevention and management of stroke.

Effect of diabetes mellitus on 3-year outcomes in patients with acute myocardial infarction with nonobstructive coronary arteries.

Diabetes mellitus (DM) is a significant factor in increased mortality rates among patients with acute myocardial infarction (AMI), but research on its impact on the long-term outcomes in patients with MI with nonobstructive coronary arteries (MINOCA) is limited. Thus, a comparison of the 3-year clinical outcomes between the DM and non-DM groups among patients with MINOCA was undertaken. From the Korea AMI Registry-National Institute of Health dataset, 10,774 AMI patients were enrolled. After applying the exclusion criteria, 379 patients with MINOCA were included. The primary clinical outcomes were major adverse cardiac and cerebrovascular events (MACCE), defined as all-cause death, recurrent myocardial infarction (MI), repeat coronary revascularization, and stroke. The secondary outcomes were the individual components of MACCE. The adjusted hazard ratios for 3-year MACCE (2.287, p = 0.010), all-cause death (2.845, p = 0.004), and non-cardiac death (non-CD, 3.914, p = 0.008) were higher in the DM group than in the non-DM group. It is speculated that the higher non-CD rate in the MINOCA group is attributable to a higher proportion of patients with non-ST-segment elevation MI in the total study population. The CD, recurrent MI, revascularization, and stroke rates were similar between the DM and non-DM groups. DM, advanced age, cardiopulmonary resuscitation on admission, and non-use of statin medications were significant predictors of MACCE. In this study involving patients with MINOCA, the DM group exhibited a higher 3-year mortality rate than the non-DM group. Thus, DM demonstrated a hazardous effect even in patients with MINOCA.