High body mass index (HBMI) is an independent risk factor for stroke. Previous studies on the incremental burden of the rapid growth of stroke attributable to HBMI are incomplete and lag behind. We aim to assess the global burden of stroke attributable to HBMI based on a public database online.Study data were taken from the Global Burden of Disease, Injuries, and Risk Factors Study; deaths, the Disability-Adjusted Life-Years (DALYs), and their age-standardized rates were screened. The join point regression was used, wherein age-standardized rates were referred to as temporal trends in disease burden.the Annual Percentage Change (APC) = 0.30%, p < 0.05]. China, India, Indonesia, the Russian Federation, and the United States of America shared in sequence the rate of leading deaths and DALYs in 2019. The Socio-Demographic Index (SDI) was associated with an increasing trend in age-standardized deaths  and age-standardized DALYs .Deaths from stroke attributable to HBMI worldwide were on the rise during 1990–2019, with an increase of 88.75%. Age-standardized DALYs were on the rise during 1990–2003 but declined during 2003–2013, with a turning point in 2013 and an increasing trend since then [the past three decades. Tremendous efforts worldwide should be in place to control and treat stroke attributable to HBMI, especially in regions with high-middle and middle SDIs and among middle-aged and aged populations.A range of indicators for the global burden of stroke attributable to HBMI have been on the rise for  The estimated total global direct and indirect costs of stroke in 2017 were approximately 1.12% of the global gross domestic product (GDP) , including cardiovascular disease, cancer, chronic respiratory disease, and diabetes . Previous studies showed that HBMI was associated with a variety of cardiovascular outcomes, but the effects of HBMI on the risk of stroke remain varied ; it is also the third-leading cause of death and disability combined in populations of all ages and the second-leading cause of the DALYs in populations aged ≥50 , 2. The ct (GDP) . High Boct (GDP) . Typicalor obese , and theThe Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) provides an opportunity to incorporate newly available datasets, enhance method performance and standardization, and respond to outbreaks of scientific knowledge. Due to various premature deaths and disabilities by human diseases, a series of scientific assessments for the burden of disease progress and adverse patterns need to be conducted. We based this study on the newest data from the GBD 2019 to assess the global burden of stroke attributable to HBMI, including deaths, DALYs, and their age-standardized rates.http://ghdx.healthdata.org/gbd-results-tool” by the Institute for Health Metrics and Evaluation (IHME) at the University of Washington, the World Health Organization  guidelines for reporting health estimates.Study data from 1990 to 2019 were taken from the GBD 2019, a publicly available resource online “Each cause and related states cover the years 1990 to 2019 and were identified with standard case definitions. Stroke was defined by the WHO criteria and was estimated based on the International Statistical Classification of Diseases and Related Health Problems (ICD), the GBD 2019, and the Cause List Mapped to the ICD codes of the I64 in the 10th ICD  disturbance of cerebral function lasting more than 24 h or leading to death and of presumed vascular origin, wherein ischemic attack and subarachnoid hemorrhage were included.2 as HBMIWe clarified the standard BMI in continents for the World Obesity Atlas 2023 taking the BMI ≥ 25 kg/m, which is the acknowledged estimate for global levels of overweight and obesity. HBMI is defined as overweight and obese with a BMI > 25.00 kg/m2. Overweight (or pre-obesity) and obesity are observed in adults with a BMI between 25.00 and 29.99 kg/m2 and ≥ 30.00 kg/m2, respectively , a number (or the weight) of persons (wi) in the same age subgroup i (a reference of the standard population), and a dividend of summing up standard population weight  groups: high, high-middle, middle, low-middle, and low SDIs  for every metric based on the 25th and 975th ordered values of 1000 draws of the posterior distribution. Temporal trends are represented by age-standardized DALYs and age-standardized deaths; their increase (or decrease) and stability are significant (p < 0.05) and insignificant (p ≥ 0.05) for the slope , respectively; temporal trends here were performed in models of the join point regression (the version of 4.9.1.0), wherein the Z Test was used to assess a hypothesis on segmentation points and the p values were two-sided, with a significance level of 0.05. In brief, when H0 (a segmentation point at 0) was first assumed, a traditional linear regression model could be used; H1 represented a segmentation with at least one point. Once H0 was rejected, the significance between 1 segment point and n segment points was assessed. According to a reference for the APC  and DALYs (a growth of 120.54% for men vs a growth of 71.69% for women) in 1990–2019  in 2003–2007 and − 1.24% (p > 0.05) in 2007–2013 (p < 0.05), a significant APC in 2002–2013 , and a turning point in 2013 with an increasing trend since then  was observed ] to 2013 . The APCs worldwide were − 1.84%  in 1990 and 0.27 million (95% UI: 0.12–0.47) in 2019, and with an increase of 245.45% for deaths and 238.18% for the DALYs, respectively; Central Asia had the highest age-standardized deaths  in 2019; Eastern Europe had the highest age-standardized deaths  in 1990. Among 21 regions, Central Asia had the highest age-standardized DALYs in 1990  and in 2019 [1,060.70 per 100,000 persons (95% UI: 735.10–1399.77); High-middle SDI regions shared the highest numbers of deaths and the DALYs before 2011, but these numbers were surpassed by middle SDI regions since then and rapid growth was experienced. Almost two-thirds of the global burdens were borne by high-middle to middle SDI regions  and age-standardized deaths  in 2019.This study showed more than a 1.89-fold increase in deaths and a 1.94-fold increase in DALYs from global stroke attributable to HBMI in 1990–2019 although their age-standardized rates had a slight decline, with 8.90% for age-standardized deaths, and 1.06% for age-standardized DALYs. Our results suggest that the immense financial burden caused by stroke attributable to HBMI worldwide should have deteriorated in recent decades .DALYs showed the percentages to be 17.94% for those populations aged approximately 70, 52.49% for those populations aged 50–69, and 29.57% for those populations aged 15–49; such results revealed that those populations aged 50–69, which is a high incidence age for stroke, shared main contributions to deaths and DALYs of stroke attributable to HBMI. Our results are consistent with the fact that the incidence of stroke worldwide was increasing in contrast to older adults  for stroke attributable to HBMI, a significant increasing trend in the APC but a decreasing trend in age-standardized rates (both deaths and DALYs) occurred in 1990–2003 although this profile has improved since 2003; globally, such previous results highlight an inadequacy in primary preventive efforts worldwide  for lowering obesity occurrence, while medium and advanced middle to high SDI regions have a large population but poor acute healthcare and awareness of stroke, which naturally causes the most deaths and highest DALYs caused by stroke attributable to HBMI. Therefore, inequality services for the prevention and treatment in lower SDI regions have become an immense barrier to lower stroke attributable to HBMI.Trends in deaths and DALYs by stroke attributable to HBMI remained upward across the SDI regions, with a decline in high and high-middle SDI regions, especially with a low level in high SDI regions but an increasing trend in middle and low-middle SDI regions, which reveals that high SDI regions are paying more attention to health problems by HBMI for preventing and controlling stroke. Deaths and DALYs by stroke attributable to HBMI deteriorated in middle and low-middle SDI regions, with fewer means and insufficient payments to prevent and treat this disease on a large scale in fast-increasing and increasingly aging populations ; middle orldwide , 32; conWe also observed dissimilar burdens of the disease in developing and developed countries; hence, we are considering doing some analyses in the future. This study was comprehensive in its global coverage and is the largest stroke epidemiological dataset to date, and it tried, first, to provide systematic estimates of the burden of stroke attributable to HBMI. However, some limitations are included. First, a scarcity of high-quality epidemiological data from different countries limited studies of both high and low methodological qualities from the GBD countries. Second, there was substantial regional heterogeneity in the study data, and different countries might account for some differences noted in the epidemiological characteristics of the disease and disease burden. Nevertheless, we applied standard methodological criteria for the studies across the past 3 decades to avoid marked effects on the estimates by the above limitations; hence, we believe that the quality of data was consistent for the included studies.Body mass index, which is one of the best-known measurements for body size , was assIn this study, we showed that global burdens of stroke attributable to HBMI were continuously on the rise. Therefore, it is necessary to insist on avoiding overweight and obesity throughout the lifespan, which also foreshadows a great challenge worldwide to establish causes of disparities and changes in trends in the burden of stroke attributable to HBMI among countries of different income levels. Findings from this study will also help with the development and monitoring of the effectiveness of stroke prevention and management and rehabilitation strategies in different countries and among different populations.http://ghdx.healthdata.org/gbd-results-tool.Publicly available datasets were analyzed in this study. This data can be found here: Institute for Health Metrics and Evaluation (IHME), Global Health Data Exchange (GHDx), and Global Burden of Disease (GBD) study, XG, JL, XY, and QZ made contributions to the acquisition, interpretation, and analysis of data. FZ and ZZ designed the study. FZ drafted and revised the article. All authors contributed to the article and approved the submitted version.This work was supported by the Guangzhou Municipal Science and Technology Project  and the Guangdong Medical Research Foundation (A2022209). The funders had no role in the study design, data collection or analysis, or preparation of the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Knee osteoarthritis (KOA), one of the most common musculoskeletal diseases in older adults, is associated with a high incidence of falls. Similarly, toe grip strength (TGS) is associated with a history of falls in older adults; however, the relationship between TGS and falls in older adults with KOA who are at risk of falling is not known. Therefore, this study aimed to determine if TGS is associated with a history of falls in older adults with KOA.The study participants, older adults with KOA scheduled to undergo unilateral total knee arthroplasty (TKA), were divided into two groups: non-fall (n = 256) and fall groups (n = 74). Descriptive data, fall-related assessments, modified Fall Efficacy Scale (mFES), radiographic data, pain, and physical function including TGS were evaluated. The assessment was conducted on the day before performing TKA. Mann–Whitney and chi-squared tests were performed to compare the two groups. Multiple logistic regression analysis was performed to determine the association of each outcome with the presence or absence of falls.Mann-Whitney U test revealed that the fall group had statistically significantly lower height, TGS on the affected and unaffected sides, and mFES. Multiple logistic regression analysis revealed that the incidence of fall history is associated with TGS on the affected side; the weaker the affected TGS of the KOA, the more likely the individual is to fall.Our results indicate that TGS on the affected side is related to a history of falls in older adults with KOA. The significance of evaluating TGS among patients with KOA in routine clinical practice was demonstrated. Falls in older adults can lead to injuries, such as bone fractures, and to significant deterioration of physical function. Over 30% of people aged 65 or older experience approximately one fall every year . Knee osAs mentioned, older adults with KOA have a high incidence of falls; however, related risk factors remain undetermined in this population. Knee pain, impaired balance, lower muscle weakness, and decreased walking ability have been reported as risk factors for falls in individuals with KOA , 8. PrevAmong the aforementioned risk factors for falls, particular attention has been paid to TGS. Many studies reported an association between TGS and falls in older adults. With increasing age, TGS in older adults deteriorates –18, resuTo date, no study has investigated the relationship between falls and TGS in older adults with KOA who are at risk of falling owing to lower limb muscle weakness and impaired balance. We hypothesized that the history and frequency of falls in older adults with KOA would be associated with TGS. Therefore, this study aimed to determine whether TGS is associated with a history of falls in older adults with KOA.This study complied with the Declaration of Helsinki and was approved by the Research Ethics Committee of Kashiba Asahigaoka hospital (2019-04-21-007). Details of the study protocol and aim were explained to all participants, both verbally and in writing. All study participants then signed a written consent prior to participating in the study.This study used a descriptive cross-sectional design to identify the association between falls and clinical evaluation factors including TGS. We recruited 407 participants with KOA, scheduled to undergo unilateral TKA at a single hospital in Japan between May 2019 and September 2021. The inclusion criteria were: 1. diagnosis of KOA, 2. ability to ambulate independently or with a T-cane at the time of pre-operative evaluation, 3. individuals who were scheduled for primary TKA, 4. individuals between 60 and 84 years of age, and 5. informed consent to participate in the study was obtained. The exclusion criteria were: 1. diagnosis of rheumatoid arthritis, idiopathic osteonecrosis, or foot and ankle disorders; 2. individuals with bilateral toe flexion problems, neurologic diseases, or other musculoskeletal diseases that significantly impair basic movements, such as walking; and 3. Those with severe depression or dementia, which would hinder evaluation. The number of falls over one-year period was obtained retrospectively within the inclusion time by nurses. The group with one or more falls was defined as the fall group, and the group with no falls was defined as the non-fall group.We assessed the participants one day prior to TKA. Descriptive data, fall-related assessments , radiographs, and physical function data were collected from electronic medical records. Physical function measurements were measured in the rehabilitation room, and were performed by 14 randomly assigned physical therapists for all participants to reduce bias as much as possible. The surgical side was considered as the affected side, whereas the non-surgical side was considered as the unaffected side.A fall was defined as “an event that results in a person coming to rest unintentionally on the ground or other lower level, not as a result of a major intrinsic event of overwhelming hazard” . Falls wA toe grip dynamometer  was used to measure TGS  in a sitDescriptive data, such as gender, age, height, weight, and body mass index were collected by nurses during the evaluation. The patients self-reported whether and how many times they experienced falls in the one past year. The severity of KOA was determined using the Kellgren–Lawrence (K-L) grading system . Four orDescriptive data were presented as the number of cases, mean with standard deviations (SD), and percentages. For all analyses, the significance level was set at 5%. All statistical analyses were performed using SPSS Statistics for Windows, version 26.0 . The sample size was calculated by G-power Post-hoc. The sample sizes for both the fall and non-fall groups were calculated based on effect size = 0.5 and α = 0.05.Before comparing the difference between the two groups, a Kolmogorov–Smirnov test was performed as a homogeneity test. The results confirmed that the p-values for all factors were less than 0.05 for both groups. Therefore, Mann–Whitney- and chi-squared tests were used to test the difference between the two groups. The factors subjected to Mann–Whitney U test were age, height, weight, BMI, TGS on both sides, IKES on both sides, pain at rest on both sides, pain while walking on both sides, TUG, and mFES. Factors subjected to the chi-squared test were sex and K-L grade.Multiple logistic regression was performed to examine the association of each factor to the dependent variable . The independent variables were height, weight, TGS on both sides, and mFES. Hosmer-Lemeshow test was performed to determine whether the analysis result was significantly fitted to the actual data. The significance of the regression equation was confirmed by rate of accurate discrimination. The variance inflation factor (VIF) was calculated to account for the degree of multicollinearity among the related factors.We excluded 77 participants, while 330 met the inclusion criteria . The 330Factors that differed significantly between the fall and non-fall groups were height (p = .014), TGS on the affected side (p = .003), TGS on the unaffected side (p = .007), and mFES (p = .001).2 was significant at p < .01. The result of the Hosmer–Lemeshow test was not significant at p = .56, and the fit of regression equation was good. The rate of accurate discrimination was 77.6%. VIF for mFES and TGS on the affected side were 1.023 in both cases, and no multicollinearity was observed. VIF calculated from the related factors were height: 1.165; weight: 1.059; and TGS on the unaffected side: 2.320.The results of multiple logistic regression analysis are presented in We analyzed a number of factors that potentially contributed to a history of falls in patients with KOA, including TGS, and clarified which of those had an impact. Only a few studies reported the incidence of falls in individuals with KOA in Japan . To the In a study of 5,062 frail older adults in Japan, approximately 30% experienced a fall at least once in a year . CompareA previous study has reported that TGS declines with age , resultiAdults with KOA with more frequent falls may have a more pronounced fear of falling than those with fewer falls. Tinetti et al.  defined This study had three major limitations. First, TGS was the only assessment performed on the foot. The degree of flatfoot and range of motion of the foot, which are common problems in individuals with KOA, were not measured. The abnormal foot posture of KOA has excessive first medial tibiofemoral contact force during walking . As thesIn this study, we investigated the factors leading to falls in older adults with KOA in Japan. Our results indicated that falls in older adults with KOA were related to TGS. In short, falls in older adults with KOA are associated with lower TGS. Physical therapy interventions to enhance TGS could be one solution to help prevent falls in individuals with KOA. In the future, cohort and interventional studies evaluating the relationship between TGS and falls should be performed.S1 Checklist(DOCX)Click here for additional data file.S1 Dataset(XLSX)Click here for additional data file.


The standard care of schizophrenia patients is based on the assessment of their psychotic behavior, using interview-based, subjective scales that measure symptoms severity. We aimed at defining easily accessible and inexpensive blood-derived clinical diagnostic parameters that might serve as objective markers in the prediction of the effects of pharmacological treatment of schizophrenia patients.A total of 40 patients with schizophrenia diagnosis according to ICD 10 during psychotic decompensation were included in the study. Blood-based biochemical parameters, BMI and interview-based medical scales of symptom severity were determined – all at admission and after 12 weeks of standard pharmacological treatment.The drops in scale values were correlated with clinical parameters. All scale changes after treatment were dependent on the value of the given scale at admission, with higher initial values leading to larger drops of the values after treatment. Models based on those correlations were significantly improved when immune and metabolism parameters were included. C4 complement and C-reactive protein (CRP) level at admission were predictive of changes in Positive and Negative Syndrome Scale (PANSS) subscales related to significant disruption of thought processes, reality testing and disorganization. The pharmacological treatment-driven changes in scales representing negative symptoms were correlated with markers of the patients’ thyroid status and metabolism.We show that objective markers can be obtained by testing immune and metabolic parameters from the patients’ blood and may be added at a low cost to the standard care of schizophrenia patients in order to predict the outcome of pharmacological treatment. The immune system has been known to be involved in the pathophysiology of schizophrenia for many years, and it is also known that the immune answer is being modified by antipsychotic therapy , 2. LateIn a study which evaluated the proinflammatory state in the first episode of schizophrenia, IL-6 was recognized as a state marker for acute exacerbations and tumor necrosis factor alpha (TNFα) as a trait marker of schizophrenia . HoweverPro-inflammatory serum cytokines including IL-6 and IL-17 are elevated in patients after with schizophrenia pharmacological treatment , and havHowever, while a link between psychiatric disfunctions and the immune system has been indicated in a growing number of investigations, this does not reflect the existence of a specific direct causal link. Other variables, like neurobiological dysfunctions, may also be involved in the pathophysiology of those diseases . Due to The role of the immune system in the pathomechanism of schizophrenia is therefore well-supported in literature data. There is, however, still a lack of clear indications about how to use this knowledge in the everyday routine.We aimed at assessing the correlations of routinely measured laboratory blood tests at admission with changes in psychological symptoms after unified pharmacological treatment of schizophrenia patients. Those results could enable us to make assumptions about the expected outcome of a patient’s treatment, based on easy-to-obtain and relatively inexpensive diagnostic tests performed at admission.Forty patients were included in the study, who have been diagnosed with paranoid schizophrenia during psychotic decompensation according to the ICD-10 classification. One patient was excluded due to extremely high white blood cell values at admission, which were identified as outliers in all analyses. Among the remaining patients, 18 (46.15%) were female and 21 (53.85%) were male. The median age was 18 years, with the youngest patient aged 15 and the oldest 38 (IQR 17–29 years).Inclusion criteria: Age between 15 and 40 years, psychical state requiring psychiatric hospitalization, medical diagnosis of paranoid schizophrenia, F20, informed consent to participate in the study.Exclusion criteria: Inability to express informed consent, intellectual disability, hospitalization without the patient’s consent, drug or psychoactive substances abuse within 3 months before admission, overuse of alcohol or other substances (other than tobacco), previous head injuries with loss of consciousness, alcohol addiction, mental disability of the parent in the case of minor patients, psychiatric diagnosis of affective disorders (F30–F39), use of drugs  in the last 2 weeks before admission, presence of acute or chronic diseases: autoimmune diseases, acute inflammatory diseases, active or previous oncological diseases, chronic terminal disease, cardiovascular disorders, history of thyroid dysfunction, diabetes, and history of CNS disorders. In addition, the study excluded patients taking drugs that may affect the concentration of thyroid hormones and their precursors: oral contraceptives, estrogens, phenytoin, anti-thyroid drugs , lithium, propranolol, glucocorticoids, mineralocorticoids, anti-epileptic drugs, non-steroidal anti-inflammatory drugs, and other immunomodulation therapies.Demographic and clinical data were collected from each patient; they were also asked to complete questionnaire surveys. Blood samples were collected during routine collection of material in the first week after the admission of the participants, as well as after 12 weeks of pharmacological treatment, each time after overnight fasting of the patients. Routine blood tests included blood count, lipid profile , CRP, complement C3 and C4, ionogram , glucose, creatinine, cortisol, and thyroid panel . Routine laboratory tests were carried out on the day of blood collection at the clinical hospital laboratory in Krakow using the automatic Sysmex XN-2000 analyzer  for blood count and the Cobas 6000 and Cobas 8000 biochemical analyzers  to assess biochemical and hormonal parameters. The BMI was calculated based on the height and weight parameters from 3 sets of values.Pharmacotherapy was prescribed and continued in all patients. Both classical neuroleptics and second-generation neuroleptics were used in accordance with the guidelines of the American Psychiatric Association . Drug doThe study protocol has been approved by the Bioethics Committee of the Jagiellonian University, consent number: 122.6120.23.2016 from the 23rd June 2016 and 1072.6120.152.2019 from the 27th June 2019. Each study participant and their legal caretaker in the case juvenile patients gave their informed consent to become included in the study. Patients were recruited from January 2019 to January 2020.The Positive and Negative Syndrome Scale for Schizophrenia (PANSS)  measuresThe following subscales of the PANSS scale, according to Marder et al. , were anThe commonly used self-report State-Trait Anxiety Inventory (STAI)  in PolisThe Beck Depression Inventory – Second Edition (BDI-II)  in PolisThe Calgary Depression Scale for Schizophrenia (CDSS) , a PolisThe standardized versions of the STAI measure of state anxiety (STAI_state), Beck Depression Inventory (BDI) and the CDSS  were measured for changes after 12 weeks of unified pharmacological treatment.Statistical analyses were performed in Statistica v13 (TIBCO Software Inc.). For analyses of the psychological scales, the drop in the value of each subscale after 12 weeks of pharmacological treatment was investigated. The change of each of the subscales was obtained by subtracting the value of a given subscale after 12 weeks from the value of the same subscale at admission. The obtained values represent the improvement of the patient’s condition on each scale.t-test in case of normal distribution or Mann–Whitney test in case of non-normal distribution of the parameter in each group. For correlation analysis of continuous variables, correlation and regression analyses were performed.The normal distribution was verified using the Shapiro–Wilk test. The comparison of continuous variables between two groups was performed with the Student’s In order to address the question of whether changes in PANSS subscales after 12 weeks of pharmacotherapy were dependent on immunological parameters, stepwise linear regression analyses were performed, for each of the PANSS subscales independently. Other blood-derived parameters were also included in order to correct for clinically important information. As modeled (dependent) parameter, the value of the change in the PANSS subscale of interest was used. Independent parameters included the given PANSS subscale value at admission, medication dose, BMI, number of neutrophils (103/μl), number of lymphocytes (103/μl), CRP serum level (mg/L), complement C3 (g/L), complement C4 (g/L), fT3 (free triiodothyronine) (pmol/L), fT4 (free thyroxin) (pmol/L), natrium (mmol/L), creatinine (μmol/L), glucose (mmol/L), cortisol (μg/dl), HDL (mmol/L), LDL (mmol/L), triglycerides (mmol/L) .The statistical significance cut-off value was α = 0.05. Where appropriate, Bonferroni corrections for multiple comparisons were applied.P = 0.004).C-reactive protein levels have repeatedly been shown to be altered in patients with schizophrenia as compared to healthy individuals , 36–38. After 12 weeks of treatment, none of the changes in scales correlated with CRP, when no other factors were corrected for, which means that an elevated CRP level at admission alone is not indicative of the expected efficacy of treatment.Changes in the subscales noted after 12 weeks of treatment were positively dependent on the value of the given subscale at baseline, i.e., in general, the higher the baseline value, the bigger the observed drop of the scale after treatment, at week 12 .P-values determined by regression analysis were 0.05, 0.75, 0.88, 0.36, and 0.87 for correlations of medication dose and changes in PANSS_pos, PANSS_neg, PANSS_dis, PANSS_exc, and PANSS_emo, respectively, corrected for the appropriate baseline value. This means that higher values at admission were characterized by a greater decrease in values after 12 weeks of pharmacological treatment, independently of the amount of the pharmacological substance the patients received.The change in none of the measures of mental status correlated with drug dose at admission. Corrections for baseline values were taken. R2 value indicates the superiority of this more complex model over the model with only the baseline PANSS_pos value. This means that for PANSS_pos, the simultaneous consideration of baseline PANSS_pos score, C4 level and the implemented pharmacological treatment dose are best predictive for the change in PANSS_pos after 12 weeks of treatment.As seen in R2 value indicating the superiority of this model over the model with baseline PANSS_dis scale values only . The correlation of the STAI_state with CRP was not significant for the change of this value after treatment. The change after treatment of the Calgary scale, which is a measure of depression level in schizophrenia patients, was modeled to be dependent only on the number of neutrophils at admission and not on the value at admission (not shown). However, the low value of the coefficient of determination for this model (adj. R2 = 0.086) indicates a low predictive value of this parameter for the change in the Calgary scale after treatment.The remaining scales did not reveal significant correlations for immunological parameters (and are therefore not shown). The change in STAI_state and BDI were dependent only on their initial values  for PANSS_pos, and CRP level at admission for PANSS_dis. Both subscales represent the significant disruption of thought processes and perception of reality. In contrast, the scales representing negative symptoms like emotional and social withdrawal, depressive mood, hostility etc., did not depend on immune parameters. For both PANSS_pos and PANSS_dis, lower values of immunological parameters corresponded to larger drops in the corresponding scale after 12 weeks of pharmacological treatment. This is in agreement with literature data on other immune parameters. For example, it has been shown that patients having low concentrations of serum IL-2 or IL-8 at baseline showed greater improvement than patients presenting with higher IL-2 or IL-8 concentrations in the serum at baseline . It has In the case of the subscale representing negative symptoms, the free thyroid hormone T3 was significant, together with levels of glucose and creatinine, which are markers of the patients’ metabolism. A correlation of negative symptoms with thyroid status can be found in previous literature. For example, in the study of Barbero et al. anti-thyroid antibodies correlated with a more severe phenotype, which was characterized by increased negative symptoms and poorer functioning in early psychotic patients . In the The correlation of inflammation parameters with positive PANSS scales at admission, as well as of fT3 with PANSS_neg at admission has been shown by our team in a previous work . Here, wMeasurement of mental parameters on subjective scales based on interviews with the patients remains the standard for clinical assessment of patients with mental illness. The clinical phenotype is particularly variable for patients with schizophrenia, who are therefore vulnerable to polypragmasia. The introduction of the suggested changes into the standard clinical care would result in the addition, at a low financial cost, of objective markers of a patient’s chance of improving specific areas of their functioning following pharmacological treatment. The addition of laboratory markers, i.e., CRP, C4, and metabolic parameters, to the standard of psychiatric care during a patient’s admission to a psychiatric ward is a cost of only around €100–160 per patient . This coConcluding, in this study, we provide practical evidence that basic immunological and metabolic markers may be of value in the therapeutics course of patients with schizophrenia. Our results show how easily accessible diagnostic values obtained at patient admission may be used in predicting the outcome of given aspects of the clinical schizophrenia picture. Moreover, we provide a cost-effective research framework and laboratory work for frontline clinicians interested in the relationship of the immune system and metabolism with schizophrenia. Validation of those results on additional patient cohorts may lead to the implementation of such predictors in everyday practice.The original contributions presented in this study are included in the article/The studies involving human participants were reviewed and approved by the Bioethics Committee of the Jagiellonian University, consent number: 122.6120.23.2016 from the 23rd June 2016. Written informed consent to participate in this study was provided by the participants’ legal guardian/next of kin.AS wrote the first draft of the manuscript and counted the results and interpreted them to the constructed statistical model. NŚ, MS, MP, and PD recruited patients and conducted the clinical and biochemical evaluation. WK, TK, and MP provided critical revision of the manuscript and important intellectual contributions. All authors contributed to the article and approved the submitted version.


The COVID-19 pandemic has had a significant impact on physical and mental health, while physical activity and sleep are two important indicators of the impact that have been explored in recent studies. However, the results of studies with different measurement methods and populations with different levels of physical activity have been diverse in that physical activity and sleep are affected by the COVID-19 pandemic in some studies but not in others. Our study aimed to investigate the impact of the COVID-19 pandemic on physical activity and sleep and the role of measurement methods and populations on results.PubMed, Web of Science, and CNKI databases were used to search for related studies systematically. Study characteristics and data on physical activity and sleep were collected and analyzed from each included study. Standardized mean differences (SMDs) with 95% confidence intervals (CIs) were used to estimate pooled effect sizes.p = 0.07) during the lockdown. The “wearables” subgroup had no heterogeneity  in sleep duration, while MVPA time measured by subjective scales was not significantly changed. The “elite athletes” subgroup had lower heterogeneity  in sleep duration than general adults, while the results of sleep quality for population subgroups were significant and there was no heterogeneity within either.A total of 13 articles were included in the systematic review, 11 of which were included in the meta-analysis. We found that moderate-to-vigorous physical activity (MVPA) time was 0.33 (95% CI 0.07 to 0.59) and sleep quality was 0.37 (95% CI 0.21 to 0.53) decreased, while sleep duration was −0.24 (95% CI −0.28 to −0.20) increased during the lockdown; overall physical activity time had no significant difference (The COVID-19 pandemic had a significant impact on MVPA time, sleep duration, and sleep quality, instead of overall physical activity time among healthy adults. The results of MVPA time and sleep duration were greatly influenced by the measurement methods, and sleep behavior differed among populations with varying physical activity levels. Thus, when researching physical activity, especially MVPA time, should consider measurement methods, and more attention should be given to differences in populations when researching sleep behavior. The worldwide COVID-19 pandemic has brought immense distress to all human beings. In the period of early COVID-19, it was estimated that 2.6 billion people  the inclusion of a single population  statement  P, Participants: healthy adults who are not healthcare workers and without any risks of disease; (2) I, Intervention: experience the lockdown of the COVID-19 pandemic; (3) C, Comparison: physical activity and sleep behavior data during the lockdown and un-lockdown periods; (4) O, Outcome: the COVID-19 pandemic affects physical activity and sleep or not; and (5) S, Study design: cohort study or cross-sectional study. Any disagreements in the literature screening process were discussed and resolved by consensus between the two authors (XZ and JG).The two authors (XZ and JG) extracted the necessary data independently, and all disagreements were resolved through discussion until a consensus was reached. Since the variables that we are concerned with were physical activity and sleep behavior, the necessary data we extracted included overall physical activity time, different levels of physical activity time, sleep duration, and sleep quality, where different levels of physical activity time were not available due to insufficient data on sedentary behavior in the included studies, so we instead performed a detailed analysis of MVPA time. Finally, the necessary data extraction was performed using a Microsoft Excel spreadsheet, and the content of the sheet was author, year, study design, population characteristics, research tools used, date of data collection, main findings, and data regarding physical activity and sleep behavior.The quality of eligibility studies was assessed using the Joanna Briggs Institute (JBI) critical appraisal tools, including both cross-sectional and cohort , subgroup analyses were conducted according to different populations and measurement methods which included a measurement by wearables or not, and whether the population was elite athletes or not for further research.The difference between studies in a meta-analysis is heterogeneity. To assess heterogeneity in the quantitative analyses, we calculated the A total of 1,379 records were identified by searching PubMed, Web of Science, and CNKI databases, with two additional records from other sources. After the removal of duplicates (17 records) and studies not meeting the inclusion criteria , 407 studies remained. Ultimately, 13 studies were included in the systematic review according to the PICOs criteria, while 11 studies met the inclusion criteria of the meta-analysis. Details of the search results are shown in A total of 7,096 participants were included in the studies, except one that did not mention the number of female participants, of which 38.06% were female participants. Of these participants, nine studies included general adults, while five studies included elite athletes in badminton, soccer, basketball, kayaking and canoeing, and track and field. The details are described in All the included studies conducted research in both lockdown and un-lockdown contexts, with one study focusing on the lockdown and post-lockdown and the others on the pre-lockdown and lockdown periods. The measurement methods used by the studies are summarized in We identified all 13 studies in our research, including seven cross-sectional studies and six cohort studies , 3. FiveChanges in physical activity and sleep behavior between the lockdown and the un-lockdown periods in individuals are mixed. For overall physical activity time, six studies were included, and two studies presented a decrease during the lockdown period. Four of seven studies assessed MVPA time and showed decreases, while others showed no significant change. For sleep duration, 10 studies were included, and six studies presented an increase during the lockdown period while others were unchanged. Four studies assessed sleep quality, three of four showed a decrease, and one of four showed unchanged.For the quantitative analyses, we included 11 studies that assessed physical activity and sleep behavior, while studies  assessed overall physical activity time, MVPA time, sleep duration, and sleep quality, respectively. The exclusion reason for quantitative analyses is that the necessary data were not available in these two studies , and with high heterogeneity . A subgroup analysis was conducted accordingly.Data from six studies including 3,625 participants were analyzed for overall physical activity time. The random-effect pooled Hedges' g = 0.33; CI = , with high heterogeneity . To further explore the source of heterogeneity, subgroup analyses were conducted.Data were acquired from seven studies which included 5,556 participants. An analysis of the data revealed a significant association between MVPA time and COVID-19 lockdown, as indicated by Hedges' p = 0.39, I2 = 5%), and consequently, a fixed-effect model was employed. The resulting fixed-effect pooled SMD (Hedges' g) was −0.24 , which was statistically significant  with a 95% CI was conducted. For sleep quality, the results showed a statistically significant Hedges' g of 0.37 ; thus, a subgroup analysis was performed.Data from four studies including 1,186 participants were acquired, and a random-effect pooled SMD  and 0.24 (−0.00 to 0.48), respectively, 0.20 (−0.21 to 0.61) and 0.20 (−0.05 to 0.46) for measurement methods, see p = 0.08, I2 = 56%) effect on MVPA time measured by wearables (p < 0.01), while MVPA time measured using subjective scales was unaffected with high heterogeneity . In the subgroups of elite athletes and general adults, there was no association between MVPA time and the COVID-19 pandemic, which is not consistent with the pooled effect result.In the subgroup analyses of measurement methods in MVPA time, the COVID-19 pandemic had a moderate heterogeneity  and consistent with the results of the pooled effect size, while subjective scales were not. When comparing subjective and objective measurement methods of physical activity (Beagle et al., First, there are discrepancies regarding measurement methods on MVPA time and sleep duration, and the wearables subgroup showed a significant advantage in both the subgroup analysis of MVPA time and sleep duration. One of the possible reasons is that wearables are more accurate and reliable. Studies by Schmidt et al.  and HagsSecond, the difference of populations existed in sleep behavior, including sleep duration and sleep quality, of which sleep behavior among general adults was more affected by the pandemic. Physical activity may be the cause of the difference. Our study demonstrated small relative changes in physical activity for the population subgroups. Large differences in absolute values of physical activity between elite athletes and general adults existed, while the former still exhibited higher levels of physical activity than general adults during the lockdown period (Monterrosa Quintero et al., In this study, we did not include enough studies on healthy adults with different levels of physical activity due to the limited availability of relevant studies, especially healthy adults with high physical activity levels, e.g., elite athletes. The results for both elite athletes and general adults in the MVPA time measure were not significant and inconsistent with the pooled effect size results, which may be due to the small sample size. Although the wearables results were more convincing than the subjective scale, it was not possible to further explore the subjective scale mechanisms and confounders, and it could be the motivation for our research on the improvement of measurement methods.We conducted the first systematic review and meta-analysis of physical activity and sleep behavior among healthy adults to assess the impact of the COVID-19 pandemic on both of them during the lockdown period vs. the un-lockdown period. Subgroup analyses were conducted to identify grouping influencing factors. In summary, our results suggest that the COVID-19 pandemic had a significant effect on healthy adults' physical activity and sleep behavior, of which MVPA time and sleep quality decreased, and sleep duration increased. Additionally, measurement methods and populations were found to be valid grouping variables on measures of physical activity and sleep behavior. The results differed between subjective scales and wearables, with wearables being more significantly affected by MVPA time and sleep duration during the COVID-19 pandemic, suggesting that wearables are sensitive and that population subgroups have an impact on sleep duration and sleep quality.These findings may provide a reference for the preparation of mental health and physical health-related countermeasures under a possible future pandemic. In future studies, the sleep behavior of different populations should be a concern, and we should pay more attention to the accuracy and stability of wearables and subjective scales in measurements for more efficient studies.The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author.XZ and JG conducted an assessment of included studies, data collection, analysis, and prepared the article for publication after editing and revisions. XZ wrote the initial draft. DC formulated the aims of this study, designed the methodology, made contributions to the revision, and acquired financial support for this study. All authors prepared the article to be published with critical reviews.


The parent–child correlation in metabolic syndrome (MetS) and elevated transaminases is sparsely researched. We assessed the correlation of parental MetS and elevated transaminase status with these conditions in their children.Data of 4,167 youths aged 10–18 years were analyzed in a population-based survey, and the parental characteristics were stratified by the presence or absence of MetS or alanine aminotransferase (ALT) elevation in their children. The prevalence of these conditions in children was analyzed according to their parents’ status. Logistic regression analyses were performed with MetS and ALT elevation in youth as the dependent variables.The proportions of MetS and ALT elevation were higher in parents of children with MetS and ALT elevation than in those without, even among youths without obesity. In logistic regression analyses, age, body mass index–standard deviation score (BMI–SDS), and ALT elevation were positively associated with MetS, whereas age, male sex, BMI–SDS, protein intake, and MetS were positively associated with ALT elevation. Higher protein intake was related to ALT elevation, whereas metabolic components and nutritional factors were closely related in parents and their children. Odds ratios (OR) of ALT elevation for MetS was 8.96 even after adjusting nutritional factors in the children. The OR was higher for ALT elevation in the children of parents with MetS and ALT elevation compared to those without. ORs for MetS and ALT elevation in the children of parents with MetS were higher than those of children of parents without MetS, even after adjusting for nutritional intake. ORs for ALT elevation were higher in the children of parents with ALT elevation than those without, even after adjusting for nutritional intake and BMI of parents as well as the nutritional intake, age, sex, and BMI–SDS of the children.MetS and elevated liver transaminase statuses in children were associated with those of their parents even after adjusting for nutritional factors, and the relationships were more prominent in the youth without obesity. A syNonalcoholic fatty liver disease (NAFLD) is a chronic liver disease characterized by excessive hepatic fat accumulation in a spectrum that ranges from nonalcoholic steatohepatitis, hepatic fibrosis, to idiopathic cirrhosis, without significant alcohol consumption –9. AmongIn the pathogenesis of MetS and NAFLD, insulin resistance plays a key role –15. FurtIn this population-based study, we aimed to investigate the association of pediatric MetS and elevated liver transaminase levels with these conditions in the parents. The study’s objectives were to investigate: (1) the relationship between MetS and elevated liver transaminases in youths; (2) the risk factors of MetS and elevated liver transaminases in youths; and (3) the association of MetS and elevated liver transaminase levels in parents with these conditions in children.2.2.1.This cross-sectional study analyzed data from the Korea National Health and Nutrition Examination Survey (KNHANES), a national population-based survey conducted by the Korea Centers for Disease Control and Prevention based on the National Health Promotion Act, that were obtained between 2007 and 2019. The KNHANES was conducted in 1998, 2001, 2005, and annually since 2007 using a rolling sampling survey method. The cross-sectional survey includes approximately 10,000 participants each year as a cohort and investigates data on health behaviors and clinical examination, including anthropometric and laboratory analysis-based information, socioeconomic status, nutritional status, the presence of chronic disease, and quality of life. The survey involved a two-step stratified sampling method that used sampling units and households as the primary and secondary sampling units, respectively. In total, 200 and 192 primary sampling units (PSU) per year were drawn from approximately 200,000 geographically defined PSU nationwide in KNHANES 2007–2009 and KNHANES 2010–2019, respectively. On average, a PSU comprises 60 households, and 20 final target households were sampled for each PSU using systematic sampling; individuals who were ≥ 1-year-old were targeted from the selected households.From among children and adolescents as well as their parents who participated in KNHANES 2007–2019, individuals whose anthropometric, blood pressure, fasting glucose and lipid, and alanine aminotransferase (ALT) data were missing were excluded. Finally, data from 4,167 children and adolescents as well as their respective parents were analyzed in this study; details of the participant screening and selection are presented in a flowchart in To ensure accurate representation of the Korean population and minimize selection bias, a multistage-stratified systematic sampling design was used wherein the sample weights were constructed for sample participants by accounting for the complex survey design, survey non-response, and post-stratification. The weights based on the inverse of selection probabilities and response rates were modified by adjusting them to the sex- and age-specific Korean populations .2.2.2). Waist circumference (WC) was measured at the narrowest point between the lower borders of the rib cage and the iliac crest at the end of normal expiration. Height, weight, and BMI were presented as standard deviation scores (SDS) based on the 2017 Korean National Growth Charts , and weight was measured using a calibrated balance beam scale . Body mass index (BMI) was calculated as the weight (kg) divided by the height (in meters) squared , triglycerides, aspartate aminotransferase (AST), and ALT were measured using Labospect 008AS . Low-density lipoprotein cholesterol (LDL-C) was calculated using the Friedewald formula ]). The triglycerides/5 were used for serum samples with triglyceride values ≤400 mg/dL, whereas samples with triglyceride levels >400 mg/dL were considered as missing values in the analysis . “ALT el2.4.t-test for continuous variables and the Rao–Scott chi-square test for categorical variables. To clarify the risk factors for pediatric MetS and ALT elevation, logistic regression analyses were performed with MetS and ALT elevation in youth as the dependent variables. Furthermore, to clarify the association of MetS and ALT elevation between children and their parents, logistic regression analyses were performed with the MetS and ALT elevation of the children and parents as dependent and independent variables, respectively. Linear regression analyses were performed with each component of MetS, liver enzymes, and nutritional intake of parents and children as independent and dependent variables, respectively. A p-value < 0.05 was considered statistically significant.All statistical analyses were performed using SAS  for the complex sampling design, with clustering, stratification, and unequal weighting of the KNHANES sample and considering sampling weights to present data on the representative Korean youth population and to overcome limitations conferred by the sampling survey design. All categorical variables are presented as weighted percentages with standard errors, whereas continuous variables are presented as weighted means with standard errors. Participants were stratified into subgroups based on the presence of MetS and ALT elevation, and the proportion of participants with MetS or ALT elevation and the characteristics of their parents were analyzed. Moreover, the prevalence of MetS and ALT elevation was analyzed in subgroups stratified by BMI and the presence of parental MetS and ALT elevation. Intergroup differences were ascertained using the Student’s 3.3.1.In univariable logistic regression analyses, the odds ratio  for MetS in age, BMI SDS, and ALT elevation were 1.13 (1.02–1.25), 1.52 (0.90–2.55), 4.01 (3.31–4.85), and 8.91 (5.16–15.38), respectively . The OR 3.2.3.3.p = 0.033 for normal BMI and p = 0.017 for overweight; p = 0.021 for normal BMI and p = 0.003 for overweight; Among youth with normal BMI or overweight, the proportion of children with MetS was higher in the progeny of parents with MetS than in those without  for MetS compared to the children of parents without MetS; the OR was highest in the children whose both parents had MetS  . Additio4.Our results demonstrate an association between parental MetS and elevated liver transaminases and offspring’s MetS and elevated liver transaminases. Moreover, parental MetS was associated with ALT elevation as well as MetS in their children. The relationship between mothers and descendant was stronger than that between fathers and their children. In addition, nutritional factors were closely related between parents and descendant. Among the nutritional factors, higher protein intake was related to ALT elevation. Additionally, older age, male sex, and higher BMI were associated with MetS and ALT elevation. The association of parental MetS and ALT elevation with descendant was significant, even after adjusting for nutritional factors. Moreover, parental ALT elevation was positively associated with descendant, even after adjusting for age and BMI. In addition, the relationship between parental MetS and ALT elevation with their children was more prominent in youths with normal BMI or overweight compared than in those with obesity. These findings suggest a genetic link between parents and descendant. Beyond genetics, epigenetic modifications can play a pivotal role by altering gene expression without changing the DNA sequence itself, potentially passing on metabolic risks to the offspring . Additiode novo lipogenesis by activating sterol regulatory element–binding protein 1 and lipid accumulation by inactivating Forkhead box protein A2, a transcription factor that promotes fatty acid oxidation in the liver . The studies were conducted in accordance with the local legislation and institutional requirements. Written informed consent for participation in this study was provided by the participants’ legal guardians/next of kin.KS and HWC had the idea and designed the study, had full access to all the data in the study, take responsibility for the integrity of the data and the accuracy of the data analysis, critically revised the manuscript for important intellectual content, and gave final approval for the version to be published. KS, JY, and HSL drafted the manuscript and did the analysis. JO, SK, ML, JS, AK, and H-SK take the responsibility for double check of the data analysis. All authors agree to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately resolved.


Participating in research studies often involves interactions with healthcare professionals, potentially influencing the participant’s future help-seeking behaviour. We investigated whether participating in the Childhood Health Activity and Motor Performance School Study – Denmark (CHAMPS) (2008–2014), which involved telephone consultations and clinical assessments by healthcare professionals with participants experiencing musculoskeletal complaints, changed frequency of contacts with primary public healthcare services among participants over the subsequent five-years-period, compared to non-participating children.Using Danish health register data from 1998 to 2020, we compared CHAMPS participant’s and two control group’s contacts with private physiotherapists, chiropractors , and general practitioners: a random 10% sample of children from Denmark , and a secondary local control group  during three periods: Before (1998–31.10.2008), during (01.11.2008–20.06.2014), and after (21.06.2014–31.12.2019) the CHAMPS-study. Separate multivariable Poisson regression models were used to assess the differences between groups for the outcome variables: contacts with physiotherapists, chiropractors, and general practitioners, and overall contacts.Compared to National Controls, the CHAMPS-Group had fewer physiotherapy contacts before the study with an estimated mean of 0.01 vs 0.02 per person-year, and after (0.13 vs 0.18 per person-year), corresponding to a crude incidence rate ratio (IRR) of 0.69 : 0.58–0.83) after the study period. However, they had more chiropractor contacts before (0.05 vs 0.03), and after (0.21 vs 0.09) the study, with a crude IRR of 2.29 (95% CI: 1.93–2.71) after the study period. General practice contacts were equal for the CHAMPS-group compared to national controls (5.84 vs 5.84) before the study but reduced during and after (3.21 vs 3.71), with a crude IRR of 0.86 (95% CI: 0.83–0.90) after the study. Comparable patterns of contacts changes from before to after the study were observed between the CHAMPS-group and the Local Controls except for physiotherapy which was equal between the two groups after the study.Our findings suggest that research studies involving systematic engagement with participants experiencing musculoskeletal complaints can influence subsequent healthcare-seeking behaviour. Future research should address the influence of health literacy, health education, and healthcare provider recommendations on healthcare decisions during such research studies.The online version contains supplementary material available at 10.1186/s12875-023-02233-z. Participating in research clinical studies often involves regular interactions with healthcare professionals, but the influence on the participant’s future help-seeking behaviour remains unclear.Primary care providers, such as physiotherapists (PT), chiropractors (DC), and general practitioners (GPs), often treat pain and injuries. However, young people often choose to self-manage their pain and injuries without seeking professional help. Previous studies have shown that 51–60% of adolescents with pain seek help from healthcare professionals .Help-seeking and coping strategies may, to some extent, be learned behaviours , 4, as yIn the period 2008–2014, a longitudinal quasi-experimental trial among school students, “The Childhood Health Activity and Motor Performance School Study – Denmark” (CHAMPS) , was perEvery week during the research period, parents responded if their child had experienced any musculoskeletal complaints during the preceding week. To secure proper treatment and supervision, a telephone consultation was conducted by a clinician within the research team with the parents of the children with musculoskeletal complaints. If deemed necessary, the child was offered an examination within the next 2 weeks . In someThe participants may from their visits to these examinations somewhat have learned to deal with their musculoskeletal complaints and self-manage their pain or increased their dependency on healthcare professionals as a result of the study.Therefore, we hypothesize that these study-specific systematic contacts with participants with musculoskeletal complaints provided by clinicians from the CHAMPS research team might influence the participants´ future healthcare-seeking behaviour.In this study, we aimed to investigate if participating in the school-based study, CHAMPS, was associated with changed frequency of contacts with private physiotherapy (PT) and chiropractor (DC) clinics outside hospitals, and general practitioners (GP) in the following five-year-period compared to non-participating children as controls.In 2007, the Svendborg Municipality Council in Denmark launched an initiative to improve the physical health of primary school students by increasing physical activities in public schools named “The Svendborg Project”. The initiative was scientifically evaluated by researchers from the University of Southern Denmark, leading to the Childhood Health Activity and Motor Performance School Study – Denmark (CHAMPS-study DK) which ran from 2008 to 2014 .The CHAMPS-study Dk was a natural quasi-experimental study. School children were recruited in the municipality of Svendborg (58.600 inhabitants). All 19 primary schools in the municipality of Svendborg were invited to participate. 10 schools participated in this study, with six of these schools agreeing to participate as intervention schools, while four schools served as control schools. Schools were matched by size and socioeconomic distribution to ensure comparable catchment areas between the intervention schools and control schools.The control schools maintained the mandatory two 45-minute physical education lessons per week . The sports schools incorporated an additional four physical education lessons, totalling 270 minutes weekly, for all children from pre-school (age 5) to the sixth grade (age 12). For those in the seventh to ninth grade (age 13–15), the number of additional physical education lessons was reduced to the mandatory two sessions per week , 11.We employed a register-based cohort design, wherein we tracked the healthcare utilisation of three groups of children over a period of 17–21 years. We compared register-based outcomes between the CHAMPS participants born in 1998–2002 (CHAMPS-group) and both a primary and a secondary control group identified by the registry of Statistic Denmark. All CHAMPS participants were included regardless of their school intervention status or their own compliance.As participation in the CHAMPS-study was self-selected at both the school and individual levels, we included both a national (primary) and local (secondary) control group to gain a more comprehensive understanding of the factors that may influence the result of our study.The primary control group, National Controls, consisted of a random 10% sample of Danish children of the same age as the CHAMPS-study children born in 1998–2002 in Denmark (eligible for inclusion in the CHAMPS-Group). The secondary control group, Local Controls, comprised children from the municipality of Svendborg born in 1998–2002 who did not participate in the CHAMPS-study  , which tIn Denmark, public medical assistance is provided free of charge for all Danish residents, and more than 98% of the Danish population is registered with a specific general practice .General Practice play a central role in the healthcare system and acts as the primary entry point for healthcare services, overseeing both disease management and preventive measures. Each resident in Denmark has the privilege of consulting a GP at no cost for any healthcare concern . GPs havAt private clinics outside hospitals, patients can directly access physiotherapy services, which incurs a full-service fee. This fee can be paid by the patient or covered by private health insurance. However, when referred by a GP, patients are eligible for partial reimbursement, typically around 40%, for physiotherapy services provided by licensed providers in Denmark’s regions. The remaining cost is the responsibility of the patient or can be covered by private health insurance. While physiotherapists do not possess official referral rights, they can suggest referrals  through electronic communication with GPs.Chiropractic services can also be directly assessed by patients, with approximately 20% of the cost reimbursed, regardless of a GP referral. Patients are responsible for the remaining cost or can use private health insurance for coverage. Chiropractors have the authority to refer patients for advanced imaging, and the majority have in-house radiography equipment.We included register-based outcomes in three different periods defined based on CHAMPS: before CHAMPS (1998–31.10.2008), during (01.11.2008–20.06.2014), and after (21.06.2014–31.12.2019). The year 1998 was chosen as this was the birth year of the oldest included year-group of children .To assess the differences in healthcare usage between the CHAMPS-Group and the two control groups for the outcome variables , separate multivariable Poisson regression models of incidence rate (IR) were employed. Both crude and adjusted analyses were conducted. Note that the crude model estimates lead to the mean rates described above. The primary exposure variable was defined as group status, specifically, participation in CHAMPS or non-participation in CHAMPS. The risk time was determined based on the three study periods. Participants entered the study at birth and were censored at the study end, death, or emigration.In the adjusted models, we included gender, parental healthcare usage before CHAMPS, and equivalised disposable family income. Regarding parental healthcare usage, due to varying numbers of parents registered for each child (ranging from 1 to 4), we included data from one parent for each child with whom the child lived. Parental healthcare usage was defined as follows: for each outcome during the period before CHAMPS, we included the number of contacts with GPs, DC, and PT  of the child’s parent or guardian who had the highest utilization of these services and lived with the child. Subsequently, we grouped contacts with GPs and total contacts into tertiles of low, middle, and high usage, while contacts with PTs and DCs were categorised into two groups . Equivalised disposable income per period was also grouped into tertiles.Data from 41,907 children and their parents were available for this study  in the after period. For CDs, the mean number contacts per person-year were consistently higher for the CHAMPS-group than National Controls in all periods, with 0.05 vs 0.03 before, and 0.21 vs 0.09 after, corresponding to a crude IRR of 2.29 (95% CI: 1.93–2.71) in the after period. The estimated mean number of contacts per person-year with GPs was equal between the National Controls and the CHAMPS-group before the CHAMPS-study period but changed to fewer during and after with 3.21 vs 3.71 after, corresponding to a crude IRR of 0.86 (95% CI: 0.83–0.90).In all three periods, the children in the CHAMPS-Group had fewer contacts with PTs than the National Controls with an estimated mean of 0.01 contacts per person-year before vs 0.02, and of 0.13 vs 0.18 after, corresponding to a crude incidence rate ratio (IRR) of 0.69 In total, the CHAMPS-Group had slightly more contacts than the National Controls in the before period with an estimated mean of 5.91 contacts per person-year vs 5.89 and fewer during and after with an estimated mean of 3.55 vs 3.99 after, corresponding to a crude IRR of 0.89 (95% CI: 0.86–0.92)  between the CHAMPS-Group and the Local Controls increased from 1.11 0.41–1.11) (before) to 1.30 (1.00–1.69) (during) and 1.15 (0.92–1.45) (after), with statistically nonsignificant results for all periods  with PTs before the study, and 33% fewer contacts after the study. Conversely, their contacts with DCs increased from 54% more contacts before the study to 117% more contacts after study end compared to National Controls, and the number of GP contacts changed from 1% fewer before CHAMPS to 14% fewer after for CHAMPS children as compared to National controls. This pattern was reflected in the overall number of total contacts, with children in the CHAMPS-group having 12% fewer contacts corresponding to half a visit less per child per year after the study.A similar association was observed when comparing the CHAMPS-group to Local Controls, although the differences were less pronounced. These findings suggest that participating in CHAMPS was associated with changes in contacts with the primary public healthcare services among participants. Some CHAMPS participants altered their healthcare-seeking preferences, opting for PTs and DCs over GPs after the end of the CHAMPS-study.While a decrease of half a GP visit per year and an increase of 0.1 DC visit per year may not have significant clinical implications for individual children, the cumulative effect could have a considerable impact on both healthcare providers and the health-care system as a whole.In our study, these changes can be seen as both positive and negative outcomes. In the Danish healthcare system, the roles of different healthcare professions vary significantly with GPs often serving as gatekeepers and diagnosticians, traditionally referring patients with musculoskeletal complaints to PTs and, to a lesser extent, DCs for treatment . It is pTo our knowledge, the potential influence of participating in a research study on patients’ future healthcare seeking behaviour has not been previously investigated. This concept, however, bears some resemblance to the well-described seeding trails´ , which aThe main strength of this study lies in its relatively large sample size and comprehensive nationwide approach, utilising register data that covers the study groups over a period of 22 years. Our data material is robust, encompassing high-quality information on all investigated outcomes both before, during, and after a five-year experimental study, along with key adjustment variables such as income, gender, and parental healthcare utilisation.Our primary outcomes were the numbers of contacts with PTs, DCs, and GPs. As registering contacts is mandatory in Denmark and essential for payment, the overall completeness of these data are high . HoweverAdditionally, our study did not directly measure participants´ access to healthcare services, including the availability of PT, DC, and GP services in their geographic area. Variations in access to these services may have influenced participants´ choices, which we were unable to account for in our analysis.The primary limitation of this study stems from its observational design. Despite having access to comprehensive healthcare utilisation data for children before, during, and after the CHAMPS-study, and employing two control groups, we acknowledge that we probably cannot establish causal relationships. Instead, we can only identify associations followed by hypothetical explanations. However, the study could also be regarded as a real-world or what might be termed a “phase four study”. In such studies, the practical implications of an intervention are assessed in real-world conditions. Randomized studies often exhibit weakness due to their homogenous study populations, causing the effectiveness of a given intervention to diminish in a real-world setting, which tends to be more heterogenous than the typical study population” in a randomized controlled trial.Identifying the optimal control group posed challenges. The CHAMPS-study involved self-selection from the schools, and we lacked data explaining why 9 schools declined to participate. Consequently, we cannot rule out that non-participating children from the municipality of Svendborg might be systematically different from those included in the study. Ideally, an optimal control group should have no awareness of the trial. Hence, we opted to incorporate a national control group consisting of a random 10% sample of Danish children to mitigate this potential bias. However, while all Danish citizens have equal right to healthcare access, it is important to acknowledge that the difference in healthcare service access between Svendborg and the national controls may not be fully accounted for in our analysis. This discrepancy could result in a “Svendborg effect” rather than an effect solely attributed to participation in the CHAMPS-study. Therefore, as an optimal control group was challenged to identify, we chose to include both. Nevertheless, it is worth noting that the most significant change observed was a decrease in GP services, which alone cannot attribute to a shortage of GP clinics, as there are fewer clinics in rural Denmark than in Svendborg. We could have considered including comparable municipalities instead of a random 10% sample as controls, but this would limit the generalizability of our study. In summary, both control groups present advantages and disadvantages, and variations in healthcare service admission may indeed vary locally. However, if Svendborg exhibits a systematic bias in either over- or underutilization of healthcare services, this bias should remain consistent across all three periods, which is not the case.In the Local control group, there was a risk of biased participants because some of the children attended the schools included in CHAMPS and were, therefore, exposed the CHAMPS culture at school. This may explain the smaller difference in healthcare seeking between the CHAMPS-Group and the Local Controls compared to the difference between CHAMPS and the National Controls. Due to the exclusion of children with severe or chronic disease in CHAMPS we had to identify comparable children in both control groups. As we used specific diagnosis to exclude participants, there was a risk of information bias due to variation in coding, but this risk is likely to be minimal, as we only used the diagnosis codes for severe and chronic diseases.The children in CHAMPS had varying numbers of complaints, and consequently, they were exposed to different rates of clinician contacts during the study period. This may lead to an underestimation of the subsequent change in healthcare seeking behaviour, as many of the included children did not report any or only a few musculoskeletal complaints during the five-year CHAMPS period.We observed a skewed proportion of economic status between the children in the CHAMPS-Group and the control groups. Combined with the fact that payment for DC and PT services in Denmark combines user payment and public subsidies, this could contribute to difference in the usage of PT and DC services among the groups. However, we adjusted for economic status in our analyses, as we had register data available.We acknowledge that our study lacked comprehensive information on the controls´ health and lifestyle factors, such as diet, physical activity, and smoking habits. These unmeasured variables could have influenced both participants healthcare-seeking behaviour and their musculoskeletal complaints, hence potentially confounding our results. Furthermore, we did not have data on participants´ quality of life, differences in pain levels, or the extent of patient education they may have received during the CHAMPS-study. This lack of information limits our ability to evaluate whether the children in CHAMPS achieved better health, changed their lifestyle, or changed their preference for seeking the three types of healthcare professionals. If they have achieved better health, this could explain the decrease in contact with the general practitioner after study end. Furthermore, if the CHAMPS-children adopted a more physical active lifestyle, this might potentially lead to more visits to the chiropractors or physiotherapists, due to increased risk of musculoskeletal complaints and injuries. However, it is also possible that they developed a higher ability to navigate the healthcare system.Furthermore, it is essential to acknowledge that our study lack specific data on individual diagnosis and treatment details, making it challenging to directly assess the extent of overdiagnosis and overtreatment. Furthermore, we did not investigate the potential for overtreatment during the CHAMPS-study, where individuals may have received more medical attention than necessary due to their participation in the research study and the fact that they were systematically contacted if they reported any new musculoskeletal complaint.The findings of this study suggest that the impact of participating in a large-scale, municipality-based intervention, similar to the CHAMPS-study, may extend beyond our specific context. It is plausible that other municipalities can achieve comparable changes in health behaviour given the commonalities in the healthcare infrastructure, school settings, and sociodemographic factors that influence children’s lifestyles.Furthermore, the observed changes are not necessarily limited to children with musculoskeletal complaints within the Danish healthcare system. The broader implication is that the effects of interactions with healthcare professionals may extend to all participants in studies that involve assessments and interactions with healthcare professionals according to national healthcare guidelines. It is important that researchers be aware of participating in their study might change the participants´ behaviour way beyond the study period.In conclusion, our findings suggest that children who participated in the CHAMPS-study showed a change in their healthcare-seeking preferences. The utilisation of physiotherapy and chiropractic services increased compared to the National Controls during the post-CHAMPS period while the utilisation of general practitioner services declined, simultaneously. This shift in healthcare-seeking behaviour persisted for at least 5 years after the collection of musculoskeletal complaints data and may be attributed to for example improved health, increased ability to make informed health choices, or the influence of study clinicians.Our findings suggest that research studies involving systematic engagement of healthcare professionals with participants experiencing musculoskeletal complaints may have an impact on the subsequent healthcare-seeking behaviour of those participants. To explore this further, future studies could be designed to study the influence of health literacy, health education, and healthcare provider recommendations on the participant’s healthcare decisions. Often, the unintended influence on participants subsequent health care behaviour is not explicitly addressed during participant inclusion. Our study imply that future studies should include these issues when pursuing the ethical considerations.Additional file 1.


Of the 1228 patients diagnosed with peptic ulcers, 90.6% underwent endoscopy. rebleeding occurred in 12.5% of the patients, and 2.5% of the patients died within 30 days. The Japanese score was the most effective in predicting the need for endoscopic intervention for PUB. Sex, systolic blood pressure, hematemesis, syncope, blood urea nitrogen level, and the American Society of Anesthesiologists score were predictive factors for the probability of endoscopic intervention in patients with PUB. The Japanese score is an effective predictor of the probability of endoscopic intervention in patients with PUB.Acute upper gastrointestinal bleeding (UGIB) is one of the most urgent medical conditions, with peptic ulcer bleeding (PUB) accounting for most gastrointestinal bleeding cases. The Japanese scoring system was developed to predict the probability of intervention in patients with UGIB, and it is more effective than other scoring systems, according to several studies. This study aimed to verify whether the Japanese scoring system is better than other scoring systems in predicting the probability of intervention when limited to PUB in patients with UGIB. We enrolled patients who presented with symptoms of UGIB and were diagnosed with peptic ulcers using endoscopy. The performances of the scoring systems in predicting patient outcomes were validated and compared using the receiver-operating characteristic curve analysis. Additionally, we used the chi-square test, Fisher exact test, and the  It can be divided into 7 variables based on patient medical history (use of antiplatelets), symptoms (syncope and hematemesis), and measured laboratory data . The Japanese score has been evaluated as an effective scoring system in Japan; however, it has not been systematically verified for Koreans. Recently, a few studies have compared the Japanese score with other scoring systems and verified the effectiveness of the Japanese score in patients with UGIB. Choi et al performed a retrospective study that compared the Japanese score with other scoring systems in patients with non-variceal upper gastrointestinal bleeding (NVUGIB) and found that compared to other scoring systems, the Japanese score was more effective in predicting endoscopic intervention but showed no superiority in predicting 30-day mortality or rebleeding. Therefore, this study aimed to determine whether the Japanese score is superior to other validated systems  in predicting clinical outcomes among patients with NUVGIB due to PUB.Acute upper gastrointestinal bleeding (UGIB) is one of the most urgent conditions in the emergency department.Among the patients who visited the emergency room of the Chungnam National University Hospital between May 2012 and March 2022, those who presented with melena, hematemesis, or suspected UGIB due to reduced Hb levels based on laboratory data were included in this study. The exclusion criteria were; Absence of UGIB ; Bleeding after endoscopic treatment, such as endoscopic submucosal dissection or endoscopic mucosal resection; Bleeding from varices; Unknown bleeding sources; and Absence of follow-up within 30 days.We collected patients data from the Clinical Data Warehouse of the Chungnam National University Hospital, and the values of each of the 4 scoring systems  were calculated and compared. Variables such as patient characteristics , initial vital signs (SBP and heart rate), symptoms , laboratory data , endoscopic findings, endoscopic intervention, 30-day mortality, and presence of rebleeding were collected.Ethical approval was obtained for all protocols from the local institutional review board . The requirement for informed consent from the patients was waived owing to the retrospective nature of this study.The primary outcome was to verify which of the 4 scoring systems was superior in predicting the need for endoscopic intervention. Secondary outcomes were the comparison of the scoring system in predicting 30-day mortality, rebleeding, and defining predictive factors for endoscopic intervention. Endoscopic intervention was limited to treatments using argon plasma coagulation (APC), hypertonic saline-epinephrine (HSE), coagrasper hemostatic forceps, or hemoclips, regardless of the successful cessation of bleeding. The 30-day mortality was defined as death from any cause, with or without UGIB. Rebleeding was defined as the need for re-endoscopy owing to unstable vital signs and reduced hemoglobin level of ≥ 2 g/dL for a day.t test, Fisher exact test, and chi-square test, were used. Differences were considered statistically significant at a P value < .05.The receiver-operating characteristic curves of the 4 scoring systems were plotted, and area under the curve (AUC) values were used to compare the ability to predict the need for endoscopic intervention, 30-day death, and rebleeding. To determine the predictive factors of endoscopic interventions, statistical analyses, such as the From May 2012 to March 2022, 1780 patients with suspected UGIB visited the emergency department of Chungnam National University Hospital. We excluded 515 patients from this study based on the exclusion criteria. Overall, 1228 patients were enrolled in this study  were male, with an average age of 67 years. Among the patients who underwent endoscopy, gastric ulcer was the most common type of peptic ulcer , followed by duodenal ulcers  , and 1 case with an unknown cause of death.P < .001), and the values of other scoring systems were.478 (P = .43),.498 (P = .93), and.587 (P = .002) for the ABC score, MAP score, and GBS, respectively. The AUC values of the 4 scoring systems were not significantly different, which suggests that they do not differ in their ability to predict rebleeding. The AUC values were.625 (P < .001) for the Japanese score,.612 (P < .001) for the ABC score,.649 (P < .001) for the MAP score, and.583 (P < .001) for the GBS. The scoring systems, except the Japanese score, were all effective in predicting 30-day mortality, and the ABC score showed the best predictive ability among them. The AUC values were.914 (P < .001) for the ABC score,.847 (P < .001) for the MAP score,.769 (P < .001) for the GBS, and.517 (P = .74) for the Japanese score.Figure Predictive factors for the need for endoscopic intervention were male sex, age > 65 years, SBP < 100 mm Hg, hematemesis, syncope, BUN level ≥ 22.4 mg/dL, use of antiplatelet agents, and the ASA score in the univariate analysis. The multivariate analysis showed that male sex, SBP < 100 mm Hg, hematemesis, syncope, BUN level ≥ 22.4 mg/dL, and ASA score were related  score as a new scoring system for predicting the need for intervention and mortality in patients with UGIB and reported that the GBS predicted the need for endoscopic intervention better than the AIMS65 score and pre-endoscopic Rockall score.PUB is an emergency condition with different prognoses in patients depending on whether endoscopic intervention is performed.,23; therefore, there is a limit to predicting the need for intervention alone. Furthermore, the GBS’ accuracy is poor in predicting endoscopic intervention in patients with low Hb levels.,However, according to recent studies, for patients aged > 65 years, the GBS and AIMS65 score are ineffective for predicting the need for endoscopic intervention in patients with UGIB. The GBS includes predicting the need for blood transfusion treatment in addition to predicting the need for intervention A previous study in South Korea demonstrated the superiority of the Japanese score in predicting the need for endoscopic intervention for patients with UGIB, except in patients with NVUGIB.Therefore, to replace the GBS, a new Japanese scoring system has been introduced in Japan that, unlike the GBS, does not include variables for predicting the need for blood transfusion treatment; thus, its predictability is considered superior. A study of patients with UGIB in Japan has proven the superiority of the Japanese scoring system.P < .001) when compared with other scoring systems, including the GBS . Compared with that observed in Choi study, the AUC value of the Japanese score for predicting the need for endoscopic intervention in patients with PUB was higher than that in patients with NVUGIB . Direct comparison of the 2 values is difficult, and whether the increased AUC value is statistically significant is unknown because the values were not calculated in the same patient group; however, the pathogenesis of peptic ulcers, among other variables contributing to the Japanese score, may be related to the overall increase in the AUC value of the Japanese score when limited to predicting the need for intervention for patients with peptic ulcers.In this study, when the patient group was limited to those with PUB, the Japanese score showed superior predictive ability for the need for endoscopic intervention  was used, whereas the highest rate was observed when a combination of HSE and hemoclips (25%) was used. While some studies have demonstrated the effectiveness of each hemostatic method,Considering the profound relationship between rebleeding and mortality, further studies may be necessary to analyze the hemostatic effects of the different hemostatic methods.Our study had some limitations. First, it was a single-center retrospective study. Second, because it was performed at a higher-level general hospital with high-severity cases, endoscopy was performed in almost all patients presenting with signs of bleeding, indicating the possibility of selection bias. Finally, the endoscopist was not the same for every case, and the therapeutic intervention was determined by the discretion and clinical context of the attending endoscopist.The AUC value of the Japanese score was higher than that of the ABC score, MAP score, and GBS in predicting the need for endoscopic intervention in patients with PUB. However, there were no differences among the scoring systems in predicting the probability of rebleeding, and the Japanese score was less predictive than the other scoring systems regarding the probability of 30-day mortality. Patient variables, including male sex, SBP < 100 mm Hg, hematemesis, syncope, BUN level > 22.4 mg/dL, and ASA score, were found to be predictors of the need for endoscopic intervention. Considering the limitations of this study, further multicenter prospective studies are necessary.Conceptualization: Hee Seok Moon.Data curation: Seong Hoon Kim.Formal analysis: Seong Hoon Kim.Investigation: Seong Hoon Kim.Methodology: Seong Woo Choi.Project administration: Hyun Yong Jeong.Resources: Sun Hyung Kang.Software: Seong Woo Choi.Supervision: Jae Kyu Sung.Validation: Sun Hyung Kang.Visualization: Seong Hoon Kim.Writing – original draft: Seong Hoon Kim.Writing – review & editing: Hee Seok Moon.