Associations of lipoprotein particle profile and objectively measured physical activity and sedentary time in schoolchildren: a prospective cohort study.

BACKGROUND: Our understanding of the mechanisms through which physical activity might benefit lipoprotein metabolism is inadequate. Here we characterise the continuous associations between physical activity of different intensities, sedentary time, and a comprehensive lipoprotein particle profile. METHODS: Our cohort included 762 fifth grade (mean [SD] age = 10.0 [0.3] y) Norwegian schoolchildren (49.6% girls) measured on two separate occasions across one school year. We used targeted proton nuclear magnetic resonance (1H NMR) spectroscopy to produce 57 lipoprotein measures from fasted blood serum samples. The children wore accelerometers for seven consecutive days to record time spent in light-, moderate-, and vigorous-intensity physical activity, and sedentary time. We used separate multivariable linear regression models to analyse associations between the device-measured activity variables-modelled both prospectively (baseline value) and as change scores (follow-up minus baseline value)-and each lipoprotein measure at follow-up. RESULTS: Higher baseline levels of moderate-intensity and vigorous-intensity physical activity were associated with a favourable lipoprotein particle profile at follow-up. The strongest associations were with the larger subclasses of triglyceride-rich lipoproteins. Sedentary time was associated with an unfavourable lipoprotein particle profile, the pattern of associations being the inverse of those in the moderate-intensity and vigorous-intensity physical activity analyses. The associations with light-intensity physical activity were more modest; those of the change models were weak. CONCLUSION: We provide evidence of a prospective association between time spent active or sedentary and lipoprotein metabolism in schoolchildren. Change in activity levels across the school year is of limited influence in our young, healthy cohort. TRIAL REGISTRATION: ClinicalTrials.gov , # NCT02132494 . Registered 7th April 2014.

GRANADA consensus on analytical approaches to assess associations with accelerometer-determined physical behaviours (physical activity, sedentary behaviour and sleep) in epidemiological studies.

The inter-relationship between physical activity, sedentary behaviour and sleep (collectively defined as physical behaviours) is of interest to researchers from different fields. Each of these physical behaviours has been investigated in epidemiological studies, yet their codependency and interactions need to be further explored and accounted for in data analysis. Modern accelerometers capture continuous movement through the day, which presents the challenge of how to best use the richness of these data. In recent years, analytical approaches first applied in other scientific fields have been applied to physical behaviour epidemiology (eg, isotemporal substitution models, compositional data analysis, multivariate pattern analysis, functional data analysis and machine learning). A comprehensive description, discussion, and consensus on the strengths and limitations of these analytical approaches will help researchers decide which approach to use in different situations. In this context, a scientific workshop and meeting were held in Granada to discuss: (1) analytical approaches currently used in the scientific literature on physical behaviour, highlighting strengths and limitations, providing practical recommendations on their use and including a decision tree for assisting researchers' decision-making; and (2) current gaps and future research directions around the analysis and use of accelerometer data. Advances in analytical approaches to accelerometer-determined physical behaviours in epidemiological studies are expected to influence the interpretation of current and future evidence, and ultimately impact on future physical behaviour guidelines.

Influence of adiposity and physical activity on the cardiometabolic association pattern of lipoprotein subclasses to aerobic fitness in prepubertal children.

Aerobic fitness (AF) and lipoprotein subclasses associate to each other and to cardiovascular health. Adiposity and physical activity (PA) influence the association pattern of AF to lipoproteins almost inversely making it difficult to assess their independent and joint influence on the association pattern. This study, including 841 children (50% boys) 10.2 ± 0.3 years old with BMI 18.0 ± 3.0 kg/m2 from rural Western Norway, aimed at examining the association pattern of AF to the lipoprotein subclasses and to estimate the independent and joint influence of PA and adiposity on this pattern. We used multivariate analysis to determine the association pattern of a profile of 26 lipoprotein features to AF with and without adjustment for three measures of adiposity and a high-resolution PA descriptor of 23 intensity intervals derived from accelerometry. For data not adjusted for adiposity or PA, we observed a cardioprotective lipoprotein pattern associating to AF. This pattern withstood adjustment for PA, but the strength of association to AF was reduced by 58%, while adjustment for adiposity weakened the association of AF to the lipoproteins by 85% and with strongest changes in the associations to a cardioprotective high-density lipoprotein subclass pattern. When adjusted for both adiposity and PA, the cardioprotective lipoprotein pattern still associated to AF, but the strength of association was reduced by 90%. Our results imply that the (negative) influence of adiposity on the cardioprotective association pattern of lipoproteins to AF is considerably stronger than the (positive) contribution of PA to this pattern. However, our analysis shows that PA contributes also indirectly through a strong inverse association to adiposity. The trial was registered 7 May, 2014 in clinicaltrials.gov with trial reg. no.: NCT02132494 and the URL is https://clinicaltrials.gov/ct2/results?term=NCT02132494&cntry=NO.

Cardiometabolic Associations between Physical Activity, Adiposity, and Lipoprotein Subclasses in Prepubertal Norwegian Children.

Lipoprotein subclasses possess crucial cardiometabolic information. Due to strong multicollinearity among variables, little is known about the strength of influence of physical activity (PA) and adiposity upon this cardiometabolic pattern. Using a novel approach to adjust for covariates, we aimed at determining the "net" patterns and strength for PA and adiposity to the lipoprotein profile. Principal component and multivariate pattern analysis were used for the analysis of 841 prepubertal children characterized by 26 lipoprotein features determined by proton nuclear magnetic resonance spectroscopy, a high-resolution PA descriptor derived from accelerometry, and three adiposity measures: body mass index, waist circumference to height, and skinfold thickness. Our approach focuses on revealing and validating the underlying predictive association patterns in the metabolic, anthropologic, and PA data to acknowledge the inherent multicollinear nature of such data. PA associates to a favorable cardiometabolic pattern of increased high-density lipoproteins (HDL), very large and large HDL particles, and large size of HDL particles, and decreasedtriglyceride, chylomicrons, very low-density lipoproteins (VLDL), and their subclasses, and to low size of VLDL particles. Although weakened in strength, this pattern resists adjustment for adiposity. Adiposity is inversely associated to this pattern and exhibits unfavorable associations to low-density lipoprotein (LDL) features, including atherogenic small and very small LDL particles. The observed associations are still strong after adjustment for PA. Thus, lipoproteins explain 26.0% in adiposity after adjustment for PA compared to 2.3% in PA after adjustment for adiposity.

Cross-sectional and prospective associations between aerobic fitness and lipoprotein particle profile in a cohort of Norwegian schoolchildren.

BACKGROUND AND AIMS: The associations between aerobic fitness and traditional measures of lipid metabolism in children are uncertain. We investigated whether higher levels of aerobic fitness benefit lipoprotein metabolism by exploring associations with a comprehensive lipoprotein particle profile. METHODS: In our prospective cohort study, we used targeted proton nuclear magnetic resonance (1H NMR) spectroscopy to profile 57 measures of lipoprotein metabolism from fasting serum samples of 858 fifth-grade Norwegian schoolchildren (49.0% girls; mean age 10.0 years). Aerobic fitness was measured using an intermittent shuttle run aerobic fitness test. We used multiple linear regression adjusted for potential confounders to examine cross-sectional and prospective associations between aerobic fitness and lipoprotein particle profile. RESULTS: Higher levels of aerobic fitness were associated with a favourable lipoprotein particle profile in the cross-sectional analysis, which included inverse associations with all measures of very low-density lipoprotein (VLDL) particles (e.g., -0.06 mmol·L-1 or -0.23 SD units; 95% CI = -0.31, -0.16 for VLDL cholesterol concentration). In the prospective analysis, the favourable pattern of associations persisted, though the individual associations tended to be more consistent with those of the cross-sectional analysis for the VLDL subclass measures compared to the low-density lipoproteins and high-density lipoproteins. Adjustment for adiposity attenuated the associations in both cross-sectional and prospective models. Nevertheless, an independent effect of aerobic fitness remained for some measures. CONCLUSIONS: Improving children's aerobic fitness levels should benefit lipoprotein metabolism, though a concomitant reduction in adiposity would likely potentiate this effect.

A comparison of analytical approaches to investigate associations for accelerometry-derived physical activity spectra with health and developmental outcomes in children.

The use of high-resolution physical activity intensity spectra obtained from accelerometry can improve knowledge of associations with health and development beyond the use of traditional summary measures of intensity. The aim of the present study was to compare three different approaches for determining associations for spectrum descriptors of physical activity (the intensity gradient, principal component analysis, and multivariate pattern analysis) with relevant outcomes in children. We used two datasets including physical activity spectrum data (ActiGraph GT3X+) and 1) a cardiometabolic health outcome in 841 schoolchildren and 2) a motor skill outcome in 1081 preschool children. We compared variance explained (R2) and associations with the outcomes for the intensity gradient (slope) across the physical activity spectra, a two-component principal component model describing the physical activity variables, and multivariate pattern analysis using the intensity spectra as the explanatory data matrices. Results were broadly similar for all analytical approaches. Multivariate pattern analysis explained the most variance in both datasets, likely resulting from use of more of the information available from the intensity spectra. Yet, volume and intensity dimensions of physical activity are not easily disentangled and their relative importance may be interpreted differently using different methodology.

The multivariate physical activity signature associated with metabolic health in children and youth: An International Children's Accelerometry Database (ICAD) analysis.

There is solid evidence for an association between physical activity and metabolic health outcomes in children and youth, but for methodological reasons most studies describe the intensity spectrum using only a few summary measures. We aimed to determine the multivariate physical activity intensity signature associated with metabolic health in a large and diverse sample of children and youth, by investigating the association pattern for the entire physical intensity spectrum. We used pooled data from 11 studies and 11,853 participants aged 5.8-18.4 years included in the International Children's Accelerometry Database. We derived 14 accelerometry-derived (ActiGraph) physical activity variables covering the intensity spectrum (from 0-99 to ≥8000 counts per minute). To handle the multicollinearity among these variables, we used multivariate pattern analysis to establish the associations with indices of metabolic health (abdominal fatness, insulin sensitivity, lipid metabolism, blood pressure). A composite metabolic health score was used as the main outcome variable. Associations with the composite metabolic health score were weak for sedentary time and light physical activity, but gradually strengthened with increasing time spent in moderate and vigorous intensities (up to 4000-5000 counts per minute). Association patterns were fairly consistent across sex and age groups, but varied across different metabolic health outcomes. This novel analytic approach suggests that vigorous intensity, rather than less intense activities or sedentary behavior, are related to metabolic health in children and youth.

Interpretation of associations between the accelerometry physical activity spectrum and cardiometabolic health and locomotor skills in two cohorts of children using raw, normalized, log-transformed, or compositional data.

It is discussed whether associations between accelerometer-derived physical activity intensities and outcomes should be analysed as absolute or relative data. The aim of the present study was to compare interpretation of association patterns of spectrum physical activity descriptions with outcome using raw, normalized, log-transformed, or compositional data. We used two datasets including 1) 841 schoolchildren and a cardiometabolic health outcome and 2) 1081 preschool children and a locomotor skill outcome. Accelerometry (ActiGraph GT3X+) data were described using multiple variables across the intensity spectrum. We varied the binning of variables to examine sensitivity of the compositional analyses to changes in the distribution centre. We used multivariate pattern analysis for all analyses and interpretations of data. Analyses of absolute (i.e., non-compositional) data showed weak associations for lower intensities and strongest associations with cardiometabolic health and locomotor skills for vigorous intensities. The same association patterns were partly observed for the compositional data, but association patterns were in some cases conflicting. The binning of variables had a major influence on associations for compositional data, but not for absolute data, meaning that conclusions depend on the operationalization of compositional data. These differences challenge and confuse interpretation of association patterns derived from the different approaches.

Accelerometer epoch setting is decisive for associations between physical activity and metabolic health in children.

When analysing physical activity (PA) levels using accelerometry, the epoch setting is critical to capture intensity-specific PA correctly. The aim of the present study was to investigate the PA intensity signatures related to metabolic health in children using different epoch settings. A sample of 841 Norwegian children (age 10.2 ± 0.3 years; BMI 18.0 ± 3.0; 50% boys) provided data on accelerometry (ActiGraph GT3X+) and several indices of metabolic health (aerobic fitness, abdominal fatness, insulin sensitivity, lipid metabolism, blood pressure) that were used to create a composite metabolic health score. We created intensity spectra from 0-99 to ≥ 10000 counts per minute (cpm) for files aggregated using 1, 10, and 60-second epoch periods and used multivariate pattern analysis to analyse the data. The association patterns with metabolic health differed substantially between epoch settings. The intensity intervals most strongly associated with metabolic health were 7000-8000 cpm for data analysed using 1-second epoch, 5500-6500 cpm for data analysed using 10-second epoch, and 4000-5000 cpm analysed using 60-second epoch. Aggregation of data over different epoch periods has a clear impact on how PA intensities in the moderate and vigorous range are associated with childhood metabolic health.

The Triaxial Physical Activity Signature Associated with Metabolic Health in Children.

PURPOSE: The use of uniaxial summary measures from accelerometry (i.e., counts per minute or minutes spent in moderate-to-vigorous intensity) substantially restricts information about physical activity (PA), and is probably a result of reliance on analytic approaches that cannot handle collinear variables. In the present study, we aimed to determine the multivariate triaxial PA intensity signature related to metabolic health in children, by investigating associations of the whole spectra of PA intensities from all axes using multivariate pattern analysis. METHODS: We included 841 children (age, 10.2 ± 0.3 yr; body mass index, 18.0 ± 3.0; 50% boys) from the Active Smarter Kids study conducted in Norway 2014 to 2015 providing valid data on accelerometry (ActiGraph GT3X+) and several indices of metabolic health (aerobic fitness, abdominal fatness, insulin sensitivity, lipid metabolism, blood pressure) that were used to create a composite metabolic health score. We created intensity spectra from 0 to 100 to ≥10,000 counts per minute for separate axes and used multivariate pattern analysis to analyze the data. RESULTS: The explained variance of metabolic health was 3.2% for counts per minute from the vertical axis, 17.0% for the vertical axis intensity spectrum, and 29.5% for the full model including all axes. Thus, including full triaxial intensity spectra improved the model for metabolic health tenfold compared with using overall PA (counts per minute) from the vertical axis only. The intensity signature associated with metabolic health differed across the axes. CONCLUSIONS: Our findings show that the three different axes carry distinct information about children's PA and the relation of PA to their health and demonstrate a great potential for triaxial accelerometry and a multivariate analytic approach to advance the field of PA epidemiology.

Multicollinear physical activity accelerometry data and associations to cardiometabolic health: challenges, pitfalls, and potential solutions.

BACKGROUND: The analysis of associations between accelerometer-derived physical activity (PA) intensities and cardiometabolic health is a major challenge due to multicollinearity between the explanatory variables. This challenge has facilitated the application of different analytic approaches within the field. The aim of the present study was to compare association patterns of PA intensities with cardiometabolic health in children obtained from multiple linear regression, compositional data analysis, and multivariate pattern analysis. METHODS: A sample of 841 children (age 10.2 ± 0.3 years; BMI 18.0 ± 3.0; 50% boys) provided valid accelerometry and cardiometabolic health data. Accelerometry (ActiGraph GT3X+) data were characterized into traditional (four PA intensity variables) and more detailed categories (23 PA intensity variables covering the intensity spectrum; 0-99 to ≥10,000 counts per minute). Several indices of cardiometabolic health were used to create a composite cardiometabolic health score. Multiple linear regression and multivariate pattern analyses were used to analyze both raw and compositional data. RESULTS: Besides a consistent negative (favorable) association between vigorous PA and the cardiometabolic health measure using the traditional description of PA data, associations between PA intensities and cardiometabolic health differed substantially depending on the analytic approaches used. Multiple linear regression lead to instable and spurious associations, while compositional data analysis showed distorted association patterns. Multivariate pattern analysis appeared to handle the raw PA data correctly, leading to more plausible interpretations of the associations between PA intensities and cardiometabolic health. CONCLUSIONS: Future studies should consider multivariate pattern analysis without any transformation of PA data when examining relationships between PA intensity patterns and health outcomes. TRIAL REGISTRATION: The study was registered in Clinicaltrials.gov 7th of April 2014 with identification number NCT02132494 .

Interpretation of Multivariate Association Patterns between Multicollinear Physical Activity Accelerometry Data and Cardiometabolic Health in Children-A Tutorial.

Associations between multicollinear accelerometry-derived physical activity (PA) data and cardiometabolic health in children needs to be analyzed using an approach that can handle collinearity among the explanatory variables. The aim of this paper is to provide readers a tutorial overview of interpretation of multivariate pattern analysis models using PA accelerometry data that reveals the associations to cardiometabolic health. A total of 841 children (age 10.2 ± 0.3 years) provided valid data on accelerometry (ActiGraph GT3X+) and six indices of cardiometabolic health that were used to create a composite score. We used a high-resolution PA description including 23 intensity variables covering the intensity spectrum (from 0-99 to ≥10000 counts per minute), and multivariate pattern analysis to analyze data. We report different statistical measures of the multivariate associations between PA and cardiometabolic health and use decentile groups of PA as a basis for discussing the meaning and impact of multicollinearity. We show that for high-resolution accelerometry data; considering all explanatory variables is crucial to obtain a correct interpretation of associations to cardiometabolic health; which is otherwise strongly confounded by multicollinearity in the dataset. Thus; multivariate pattern analysis challenges the traditional interpretation of findings from linear regression models assuming independent explanatory variables.

Associations of physical activity and sedentary time with lipoprotein subclasses in Norwegian schoolchildren: The Active Smarter Kids (ASK) study.

BACKGROUND AND AIMS: Physical activity is favourably associated with certain markers of lipid metabolism. The relationship of physical activity with lipoprotein particle profiles in children is not known. Here we examine cross-sectional associations between objectively measured physical activity and sedentary time with serum markers of lipoprotein metabolism. METHODS: Our cohort included 880 children (49.0% girls, mean age 10.2 years). Physical activity intensity and time spent sedentary were measured objectively using accelerometers. 30 measures of lipoprotein metabolism were quantified using nuclear magnetic resonance spectroscopy. Multiple linear regression models adjusted for age, sex, sexual maturity and socioeconomic status were used to determine associations of physical activity and sedentary time with lipoprotein measures. Additional models were adjusted for adiposity. Isotemporal substitution models quantified theoretical associations of replacing 30 min of sedentary time with 30 min of moderate- to vigorous-intensity physical activity (MVPA). RESULTS: Time spent in MVPA was associated with a favourable lipoprotein profile independent of sedentary time. There were inverse associations with a number of lipoprotein measures, including most apolipoprotein B-containing lipoprotein subclasses and triglyceride measures, the ratio of total to high-density lipoprotein (HDL) cholesterol, and non-HDL cholesterol concentration. There were positive associations with larger HDL subclasses, HDL cholesterol concentration and particle size. Reallocating 30 min of sedentary time to MVPA had broadly similar associations. Sedentary time was only partly and weakly associated with an unfavourable lipoprotein profile. CONCLUSIONS: Physical activity of at least moderate-intensity is associated with a favourable lipoprotein profile in schoolchildren, independent of time spent sedentary, adiposity and other confounders.

The multivariate physical activity signature associated with metabolic health in children.

BACKGROUND: Physical activity is a cornerstone for promoting good metabolic health in children, but it is heavily debated which intensities (including sedentary time) are most influential. A fundamental limitation to current evidence for this relationship is the reliance on analytic approaches that cannot handle collinear variables. The aim of the present study was to determine the physical activity signature related to metabolic health in children, by investigating the association pattern for the whole spectrum of physical activity intensities using multivariate pattern analysis. METHODS: We used a sample of 841 children (age 10.2 ± 0.3 years; BMI 18.0 ± 3.0; 50% boys) from the Active Smarter Kids study, who provided valid data on accelerometry (ActiGraph GT3X+) and several indices of metabolic health (aerobic fitness, abdominal fatness, insulin sensitivity, lipid metabolism, blood pressure) that were used to create a composite metabolic health score. We created 16 physical activity variables covering the whole intensity spectrum (from 0-100 to ≥ 8000 counts per minute) and used multivariate pattern analysis to analyze the data. RESULTS: Physical activity intensities in the vigorous range (5000-7000 counts per minute) were most strongly associated with metabolic health. Moderate intensity physical activity was weakly related to health, and sedentary time and light physical activity were not related to health. CONCLUSIONS: This study is the first to determine the multivariate physical activity signature related to metabolic health in children across the whole intensity spectrum. This novel approach shows that vigorous physical activity is strongest related to metabolic health. We recommend future studies adapt a multivariate analytic approach to further develop the field of physical activity epidemiology. TRIAL REGISTRATION: The study was registered in Clinicaltrials.gov (www.clinicaltrials.gov) 7th of April 2014 with identification number NCT02132494 .

Associations of volumes and patterns of physical activity with metabolic health in children: A multivariate pattern analysis approach.

Physical activity (PA) favorably affects metabolic health in children, but it is unclear how total volumes versus patterns (bouts and breaks) of PA relate to health. By means of multivariate pattern analysis that can handle collinear variables, we determined the associations of PA volumes and patterns with children's metabolic health using different epoch settings. A sample of 841 Norwegian children (age 10.2 ±â€¯0.3 years) provided in 2014 data on accelerometry (ActiGraph GT3X+), using epoch settings of 1, 10, and 60 s and several indices of metabolic health used to create a composite metabolic health score. We created 355 PA indices covering the whole intensity and bout duration spectrum, and used multivariate pattern analysis to analyze the data. Findings showed that bouts of PA added information about childhood health beyond total volumes of PA for all epoch settings. Yet, associations of PA patterns with metabolic health were completely dependent on the epoch settings used. Vigorous PA was strongly associated with metabolic health, while associations of light and moderate PA were weak to moderate, and associations of sedentary time with metabolic health was non-existing. Short intermittent bursts of PA were favorably associated with children's metabolic health, whereas associations of prolonged bouts were weak. This study is the first to determine the multivariate physical activity association pattern related to metabolic health in children across the whole PA intensity and bout duration spectrum. The findings challenge our understanding of PA patterns, and are of major importance for the analysis of accelerometry data.

Aerobic fitness and metabolic health in children: A clinical validation of directly measured maximal oxygen consumption versus performance measures as markers of health.

High aerobic fitness is consistently associated with a favorable metabolic health profile in children. However, measurement of oxygen uptake, regarded as the gold standard for evaluating aerobic fitness, is often not feasible. Thus, the aim of the present study was to perform a clinical validation of three measures of aerobic fitness (peak oxygen consumption [VO2peak] and time to exhaustion [TTE] determined from a graded treadmill protocol to exhaustion, and the Andersen intermittent running test) with clustered metabolic health in 10-year-old children. We included 93 children (55 boys and 38 girls) from Norway during 2012-2013 in the study. Associations between aerobic fitness and three different composite metabolic health scores (including lipoprotein subgroup particle concentrations, triglyceride, glucose, systolic blood pressure, and waist-to-height ratio) were determined by regression analyses adjusting for sex. The relationships among the measures of aerobic fitness were r = 0.78 for VO2peak vs. TTE, r = 0.63 for VO2peak vs. the Andersen test, and r = 0.67 for TTE vs. the Andersen test. The Andersen test showed the strongest associations across all markers of metabolic health (r = - 0.45 to - 0.31, p < 0.002), followed by VO2peak (r = - 0.35 to - 0.12, p < 0.256), and TTE (r = - 0.28 to - 0.10, p < 0.334). Our findings indicate that indirect measures of aerobic fitness do not stand back as markers of metabolic health status in children, compared to VO2peak. This is of great importance as good field tests provide opportunities for measuring aerobic fitness in many settings where measuring VO2peak are impossible.

Serum fatty acid and lipoprotein subclass concentrations and their associations in prepubertal healthy Norwegian children.

INTRODUCTION: The lipid metabolism is one of the most important and complex processes in the body. Serum concentrations of 18 fatty acids (FAs) and 24 lipoprotein features, i.e. concentrations of lipoprotein main and subclasses and average particle size in main classes, in 195 ethnic Norwegian children from the rural Fjord region were quantified by chromatography. OBJECTIVES: To assess gender differences in prepubertal children and reveal predictive FA patterns for lipoprotein features. METHODS: Lipoprotein features were modelled from FA profiles using multivariate regression. RESULTS: Contrary to observations for adults from the same region, gender differences in prepubertal children were generally small. However, higher concentrations of C16-C18 FAs for girls compared to boys correlated to higher concentrations of triglycerides (TG) and very low density lipoprotein (VLDL) particles and larger average size of VLDL particles. Concentrations of high density lipoprotein (HDL) and its subclass of medium particle size were higher in boys than in girls. These findings are opposite to observations in adults from the same region, but reflect that prepubertal boys are more physically active than girls. Furthermore, children possessed only half the serum levels of eicosapentaenoic acid and docosahexaenoic acid measured in adults. Since sampling was done after 12 h of fasting, these differences may reflect higher rate of utilization of these crucial FAs in children. CONCLUSION: Good predictive models were obtained for TGs, VLDL and chylomicrons with C14-C18 FAs as major contributors. Weak predictive associations were observed for HDL and Apolipoprotein A1 (ApoA1) with C20-C24 FAs as contributors.

Changes in serum fatty acid and lipoprotein subclass concentrations from prepuberty to adulthood and during aging.

Concentrations in serum were determined for 18 fatty acids (FAs) and 21 lipoprotein main and subclasses by chromatographic analyses and the average size was calculated for very low density (VLDL), low density (LDL) and high density (HDL) particles. 283 ethnic Norwegian children and adults from the rural Fjord region of Western Norway were compared with the objectives to reveal patterns and gender differences during the development from prepuberty to adulthood and during aging in adults. Both genders showed a large increase in eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) from child to adult. Males, but not females, show a significant increase in most C16-C18 FAs from prepuberty to adulthood. These changes in males correlate to a pattern of increased concentrations of triglycerides, VLDL and LDL particles, especially the atherogenic subclasses of small and very small LDL particles. Furthermore, concentrations of medium, large and very large HDL particles decrease, while concentration of very small HDL particles increase leading to reduced average size of HDL particles. Females only showed significant increase in concentrations of small and very small LDL particles, very small HDL particles and apolipoprotein B. While EPA and DHA continued to increase during aging in women, no validated model for connecting age to FA profile was obtained for men. Women showed significant increase in concentrations of all subclasses of LDL particles during aging, while men exhibited a more complex pattern with increase also in apolipoprotein A1 and HDL particles.

Changes in Serum Fatty Acid Levels During the First Year After Bariatric Surgery.

BACKGROUND: We have assessed the effects of laparoscopic sleeve gastrectomy (LSG) and biliopancratic diversion with a duodenal switch (BPDDS) on fatty acid (FA) levels in serum. In particular, we examine the impact of surgery on the ratio of the FAs eicosapentaenoic acid (EPA) to arachidonic acid (AA) which impacts, e.g., cardiovascular health. Our hypothesis is that LSG and BPDDS influence the FA levels but that BPDDS may have a more persistent impact since BPDSS superimposes intestinal malabsorption on gastric restriction. METHODS: Serum samples after overnight fasting were collected 3 months and 1 day before surgery and 3 days, 3 months, and 12 months after surgery from 10 BPDDS patients and 23 LSG patients. The levels of 16 FAs were quantified by gas chromatography. Preoperative and postoperative concentrations of EPA and AA and the ratio of EPA to AA were compared by Wilcoxon signed-rank test corrected for multiple testing using false discovery rate. RESULTS: The ratio of EPA/AA at each of the three postoperative sampling points was lower than at the two preoperative sampling points for BPDDS with p < 0.05 after correcting significance levels for multiple testing. For LSG, the ratio was lower with p < 0.05 at 3 days and at 3 months after surgery, but not after 12 months. CONCLUSION: Both LSG and BPDDS lower the ratio of EPA/AA significantly and below recommended values, but LSG patients resurge toward normal values after approximately 12 months, while BPDDS patients do not.

Predictive associations between serum fatty acids and lipoproteins in healthy non-obese Norwegians: implications for cardiovascular health.

A battery of methods for multivariate data analysis has been used to assess the associations between concentrations of fatty acids (FAs) and lipoprotein subclasses and particle size in serum for a normolipidemic population of ethnic Norwegians living in the rural Fjord region. Significant gender differences were found in the lipoprotein and FA patterns. Predictive FA patterns were revealed for lipoprotein features of importance for cardiovascular (CV) health. Thus, the subclasses of atherogenic small and very small low density lipoprotein (LDL) particles and the same subclasses of high density lipoprotein (HDL) particles were associated with a pattern of saturated FAs and mono-unsaturated C16-C18 FAs. Eicosapentaenoic acid (EPA) and the ratio of EPA to arachidonic acid (AA) had strongest associations to features that promotes CV health: (i) large average size of HDL and LDL particles, and, (ii) small average size of very low density lipoprotein (VLDL) particles. Total concentration of HDL in both genders correlated to EPA, but docosahexaenoic acid (DHA) correlated just as strongly for women. For men, docosapentaenoic acid (DPA) showed stronger association to HDL concentration than EPA. For both genders, concentration of large LDL particles showed associations to levels of EPA, but stronger to DHA and DPA. High values of EPA/AA seem to be the strongest single biomarker for good CV health in both men and women.