Refine
Document Type
- Article (5)
Language
- English (5)
Has Fulltext
- yes (5)
Is part of the Bibliography
- no (5)
Keywords
- Agreement (1)
- Apolipoprotein concentration (1)
- Bland-Altman Plots (1)
- Cardiovascular disease (1)
- Cardiovascular risk factors (1)
- Chronic non-communicable diseases (1)
- Compositional data analysis (1)
- Cytokines (1)
- Dyslipidemia (1)
- Energy mobilization (1)
- Epidemiology (1)
- Gelatinase A (1)
- HDL (1)
- Heart-liver axis (1)
- Immunometabolism (1)
- Inflammation (1)
- Inflammatory biomarkers (1)
- LDL (1)
- Lipid metabolism (1)
- Lipidomics (1)
- Lipolysis (1)
- Lipoprotein particles (1)
- Lipoprotein subclasses (1)
- MMP2 (1)
- Measurement (1)
- Method-comparison studies (1)
- Nuclear magnetic resonance spectroscopy (1)
- Prevention of cardiovascular diseases (1)
- Prevention of metabolic diseases (1)
- Prolonged sitting (1)
- Reliability (1)
- Residual risk (1)
- Sedentary behaviour patterns (1)
- Sedentary breaks (1)
- Sedentary time (1)
- Small dense LDL (1)
- Soluble APRIL (1)
- Soluble BAFF (1)
- TNF (1)
- VLDL (1)
- Validity (1)
Institute
Publisher
- BioMed Central (BMC) (5) (remove)
Background
Multimedia multi-device measurement platforms may make the assessment of prevention-related medical variables with a focus on cardiovascular outcomes more attractive and time-efficient. The aim of the studies was to evaluate the reliability (Study 1) and the measurement agreement with a cohort study (Study 2) of selected measures of such a device, the Preventiometer.
Methods
In Study 1 (N = 75), we conducted repeated measurements in two Preventiometers for four examinations (blood pressure measurement, pulse oximetry, body fat measurement, and spirometry) to analyze their agreement and derive (retest-)reliability estimates. In Study 2 (N = 150), we compared somatometry, blood pressure, pulse oximetry, body fat, and spirometry measurements in the Preventiometer with corresponding measurements used in the population-based Study of Health in Pomerania (SHIP) to evaluate measurement agreement.
Results
Intraclass correlations coefficients (ICCs) ranged from .84 to .99 for all examinations in Study 1. Whereas bias was not an issue for most examinations in Study 2, limits of agreement for most examinations were very large compared to results of similar method comparison studies.
Conclusion
We observed a high retest-reliability of the assessed clinical examinations in the Preventiometer. Some disagreements between Preventiometer and SHIP examinations can be attributed to procedural differences in the examinations. Methodological and technical improvements are recommended before using the Preventiometer in population-based research.
Background and aims
Prevention measures for cardiovascular diseases (CVD) have shifted their focus from lipoproteins to the immune system. However, low-grade inflammation and dyslipidemia are tightly entangled. The objective of this study was to assess the relations between a broad panel of inflammatory biomarkers and lipoprotein subclass parameters.
Methods
We utilized data from the population-based Study of Health in Pomerania (SHIP-TREND, n = 403). Plasma concentrations of 37 inflammatory markers were measured by a bead-based assay. Furthermore, we employed nuclear magnetic resonance spectroscopy to measure total cholesterol, total triglycerides, total phospholipids as well as the fractional concentrations of cholesterol, triglycerides, phospholipids, ApoA1, ApoA2 and ApoB in all major lipoprotein subclasses. Associations between inflammatory biomarkers and lipoprotein subclasses were analyzed by adjusted linear regression models.
Results
APRIL, BAFF, TWEAK, sCD30, Pentraxin-3, sTNFR1, sTNFR2, Osteocalcin, Chitinase 3-like 1, IFN-alpha2, IFN-gamma, IL-11, IL-12p40, IL-29, IL-32, IL-35, TSLP, MMP1 and MMP2 were related with lipoprotein subclass components, forming two distinct clusters. APRIL had inverse relations to HDL-C (total and subclasses) and HDL Apo-A1 and Apo-A2 content. MMP-2 was inversely related to VLDL-C (total and subclasses), IDL-C as well as LDL5/6-C and VLDL-TG, IDL-TG, total triglycerides as well as LDL5/5-TG and HDL4-TG. Additionally, we identified a cluster of cytokines linked to the Th1-immune response, which were associated with an atherogenic lipoprotein profile.
Conclusion
Our findings expand the existing knowledge of inflammation-lipoprotein interactions, many of which are suggested to be involved in the pathogeneses of chronic non-communicable diseases. The results of our study support the use of immunomodulatory substances for the treatment and possibly prevention of CVD.
Background
Long periods of uninterrupted sitting, i.e., sedentary bouts, and their relationship with adverse health outcomes have moved into focus of public health recommendations. However, evidence on associations between sedentary bouts and adiposity markers is limited. Our aim was to investigate associations of the daily number of sedentary bouts with waist circumference (WC) and body mass index (BMI) in a sample of middle-aged to older adults.
Methods
In this cross-sectional study, data were collected from three different studies that took place in the area of Greifswald, Northern Germany, between 2012 and 2018. In total, 460 adults from the general population aged 40 to 75 years and without known cardiovascular disease wore tri-axial accelerometers (ActiGraph Model GT3X+, Pensacola, FL) on the hip for seven consecutive days. A wear time of ≥ 10 h on ≥ 4 days was required for analyses. WC (cm) and BMI (kg m− 2) were measured in a standardized way. Separate multilevel mixed-effects linear regression analyses were used to investigate associations of sedentary bouts (1 to 10 min, >10 to 30 min, and >30 min) with WC and BMI. Models were adjusted for potential confounders including sex, age, school education, employment, current smoking, season of data collection, and composition of accelerometer-based time use.
Results
Participants (66% females) were on average 57.1 (standard deviation, SD 8.5) years old and 36% had a school education >10 years. The mean number of sedentary bouts per day was 95.1 (SD 25.0) for 1-to-10-minute bouts, 13.3 (SD 3.4) for >10-to-30-minute bouts and 3.5 (SD 1.9) for >30-minute bouts. Mean WC was 91.1 cm (SD 12.3) and mean BMI was 26.9 kg m− 2 (SD 3.8). The daily number of 1-to-10-minute bouts was inversely associated with BMI (b = -0.027; p = 0.047) and the daily number of >30-minute bouts was positively associated with WC (b = 0.330; p = 0.001). All other associations were not statistically significant.
Conclusion
The findings provide some evidence on favourable associations of short sedentary bouts as well as unfavourable associations of long sedentary bouts with adiposity markers. Our results may contribute to a growing body of literature that can help to define public health recommendations for interrupting prolonged sedentary periods.
Trial registration
Study 1: German Clinical Trials Register (DRKS00010996); study 2: ClinicalTrials.gov (NCT02990039); study 3: ClinicalTrials.gov (NCT03539237).