Plasma Elaidic Acid Level as Biomarker of Industrial Trans Fatty Acids and Risk of Weight Change: Report from the EPIC Study

Background: Few epidemiological studies have examined the association between dietary trans fatty acids and weight gain, and the evidence remains inconsistent. The main objective of the study was to investigate the prospective association between biomarker of industrial trans fatty acids and change in weight within the large study European Prospective Investigation into Cancer and Nutrition ( EPIC) cohort. Methods: Baseline plasma fatty acid concentrations were determined in a representative EPIC sample from the 23 participating EPIC centers. A total of 1,945 individuals were followed for a median of 4.9 years to monitor weight change. The association between elaidic acid level and percent change of weight was investigated using a multinomial logistic regression model, adjusted by length of follow- up, age, energy, alcohol, smoking status, physical activity, and region. Results: In women, doubling elaidic acid was associated with a decreased risk of weight loss ( odds ratio ( OR) = 0.69, 95% confidence interval ( CI) = 0.55- 0.88, p = 0.002) and a trend was observed with an increased risk of weight gain during the 5- year follow- up ( OR = 1.23, 95% CI = 0.97- 1.56, p = 0.082) ( p- trend<. 0001). In men, a trend was observed for doubling elaidic acid level and risk of weight loss ( OR = 0.82, 95% CI = 0.66- 1.01, p = 0.062) while no significant association was found with risk of weight gain during the 5- year follow- up ( OR = 1.08, 95% CI = 0.88- 1.33, p = 0.454). No association was found for saturated and cismonounsaturated fatty acids. Conclusions: These data suggest that a high intake of industrial trans fatty acids may decrease the risk of weight loss, particularly in women. Prevention of obesity should consider limiting the consumption of highly processed foods, the main source of industrially- produced trans fatty acids

Ableitung und Validierung deutscher Risikoscores zur Vorhersage starker Gewichts- und Taillenumfangszunahmen

Currently, more than 60 % of German adults are overweight or obese. During the last decade prevalence of overweight stagnated at a high level, while obesity prevalence grew further - especially among young adults. Excessive accumulation of body fat is a well-established risk factor for many chronic health disorders and premature death. Regarding the extent of metabolic risks, accumulation of abdominal (visceral) fat gained paramount scientific interest by exerting unique pathogenic effects. According to recent estimations for Germany, nearly 16.8 billion euros of annual health-care expenditures are attributed to consequences of overweight and obesity; whereby 82 % of direct costs are driven by metabolic disorders. In order to counteract further increase in obesity prevalence and to reduce the numbers of future body fat-associated health disorders, it is important to derive practicable and informative preventive instruments for public health in Germany. Therefore, the present thesis aimed to derive Germany-wide valid risk scores predicting substantial gain in weight and waist circumference (WC) in the course of five years on the basis of easily obtainable information. Derivation of the German risk scores was based on the data of over 31,000 participants from five German cohort studies; these comprised the two German cohorts of the European Prospective Investigation into Cancer and Nutrition (EPIC) study, the Study of Health In Pomerania (SHIP) -cohort, a cohort of the research platform KORA (Kooperative Gesundheitsforschung in der Region Augsburg), and the nationwide cohort of the German National Health Interview and Examination Survey 1998 / National Health Interview and Examination Survey for Adults (BGS98/DEGS). Substantial weight gain (SWG) and substantial WC gain (SWCG) were specified as gaining ≥10 % of baseline weight and ≥2.5 cm of baseline residual waist (WCBMI), respectively, during the follow-up. The predictor candidates comprised information on socio-demographic and anthropometric characteristics, dietary and lifestyle factors, as well as on psychosocial and further health-related conditions. To most precisely predict the five-year risks based on limited information and to avoid over-adaption to a pre-specified derivation sample, a three-step meta-analytical approach was applied: first, the risk scores were derived using maximal available sets of predictor candidates; next, the predictors were restricted to a homogeneous set of predictors across the cohorts; and finally, homogenous predictor sets were further reduced to the most predictive factors by applying the selection procedure of random survival forest (RSF). To assign weights for each predictor, cohort-specific multivariable regression coefficients were pooled using random-effect meta-analyses. Based on the pooled coefficients, the risk scores were calculated as a linear combination of the included predictors. Across the steps, the risk scores were validated by the assessment of discrimination (area under the receiver operating characteristic curve, aROC) and calibration. In the course of the follow-up period, 6,383 individuals gained ≥10 % of their baseline weight and 8,746 individuals increased their baseline WCBMI ≥2.5 cm. Incidence rates (per 10,000 person-years) across the cohorts ranged from 189 to 266 for SWG and from 206 to 356 for SWCG. Depending on cohorts 19 to 22 predictors were available for the maximum models. Of them, 17 were adequately assessed in all cohorts and determined the homogeneous predictor set of the minimum models. After predictor selection by RSF, and by considering the numbers of cases across the cohorts, five and seven predictors were included in the selection models for SWG and SWCG, respectively. Pursuant to the stepwise applied predictor sets for the risk scores predicting SWG, aROCs (95 % CI) slightly decreased from 0.73 (0.71, 0.76) to 0.71 (0.68, 0.75) and 0.70 (0.67, 0.73), while aROCs (95 % CI) for the risk scores predicting SWCG were relatively constant with values of 0.69 (0.66, 0.73), 0.68 (0.65, 0.72), and 0.68 (0.64, 0.71). For SWG and SWCG discriminatory abilities varied between the cohorts. Use of cohort-specific predictor weights left discrimination for SWG unchanged, while for SWCG some improvements of cohort-specific models were observed. Regarding the calibration of the risk scores, similar patterns were observed for SWG across all the cohorts, while more variability existed for SWCG. The findings of this thesis support the generalizability of meta-analytically derived risk scores predicting SWG on the basis of easily obtainable information from the numerically most important German cohort studies. Moreover, discriminatory performance remains remarkable constant even after reduction to few but most important predictors. For SWCG, performances are inferior and appear more cohort-specific. With regard to the broad spectrum of considered factors, however, predictability of gain in body weight and WC based on easily obtainable information seems generally limited.Mehr als 60 % der deutschen Erwachsenen gelten derzeit als übergewichtig oder adipös. Während die Übergewichtsprävalenz in den vergangenen zehn Jahren auf hohem Niveau stagnierte, stieg die Adipositasprävalenz weiter an - insbesondere bei jungen Erwachsenen. Überschüssiges Körperfett ist ein etablierter Risikofaktor für viele chronische Gesundheitsstörungen und vorzeitige Todesfälle. Im Hinblick auf das Ausmaß metabolischer Risiken, hat insbesondere das abdominale (viszerale) Fett durch seine spezifischen pathogenen Effekte wissenschaftliche Aufmerksamkeit erlangt. Aktuellen Zahlen für Deutschland zufolge, sind etwa 16,8 Milliarden Euro der jährlichen Gesundheitsausgaben den Folgen von Übergewicht und Adipositas zuzuschreiben, wobei 82 % der direkten Kosten auf metabolische Erkrankungen zurückzuführen sind. Um einem weiteren Anstieg der Adipositasprävalenz entgegen zu wirken und die Zahl zukünftiger körperfett-assoziierter Gesundheitsstörungen zu senken, ist die Erstellung einfacher und informativer Präventionsinstrumente für die öffentliche Gesundheit in Deutschland von großer Bedeutung. Die vorliegende Dissertation hat sich daher zum Ziel gesetzt, für Deutschland gültige Risikoscores zu erstellen, die starke Zunahmen von Gewicht und Taillenumfang im Laufe von fünf Jahren, auf Basis einfach zu erhebender Informationen, vorhersagen. Die Erstellung der deutschen Risikoscores basierte auf den Daten von über 31.000 Teilnehmern von fünf deutschen Kohortenstudien; diese umfassten die beide deutschen Kohorten der European Prospective Investigation into Cancer and Nutrition (EPIC) -Studie, die SHIP (Study of Health In Pomerania) -Kohorte, eine Kohorte der Forschungsplattform KORA (Kooperative Gesundheitsforschung in der Region Augsburg) und die überregionale Kohorte des Bundes-Gesundheitssurvey 1998 / Deutsche Erwachsenen-Gesundheits-Studie (BGS98/DEGS). Starke Gewichtszunahmen (SGZ) bzw. starke Taillenumfangszunahmen (STUZ) entsprachen Zunahmen von ≥10 % des Körpergewicht bzw. ≥2.5 cm des residualen Taillenumfangs im Laufe der Beobachtungszeit. Die Prädiktoren umfassten soziodemographische und anthropometrische Charakteristika, Ernährungs- und Lebensstilfaktoren sowie psychosoziale und weitere gesundheitsbezogenen Faktoren. Um die Fünf-Jahresrisiken auf Basis von eingeschränkten Informationen möglichst präzise vorherzusagen und um eine Überanpassung an eine vordefinierte Kohorte zu vermeiden, wurde ein dreistufiger meta-analytischer Ansatz verfolgt: zunächst wurden die Risikoscores unter Verwendung der maximal verfügbaren Prädiktorenzahl erstellt; daraufhin wurde die Prädiktorenzahl auf einen unter den Kohorten einheitlichen Prädiktorensatz eingeschränkt; schließlich wurden dieser Prädiktorensatz unter Anwendung des Variablenselektionsverfahrens random survival forest (RSF) auf die prädikativsten Faktoren weiter reduziert. Die Prädiktorengewichtungen basierten jeweils auf der meta-analytischen Zusammenfassung (mittels random-effects meta-analysis) der kohorten-spezifischen Regressionskoeffizienten. Auf Basis der so zusammengefassten Regressionskoeffizienten wurden die Risikoscores durch lineare Kombination der jeweils eingeschlossenen Prädiktoren berechnet. Auf jeder Stufe (bzw. mit jedem Prädiktorensatz) wurden die Risikoscores mittels Diskrimination (area under the receiver operating characteristic curve, aROC) und Kalibrierung validiert. Im Verlauf der Beobachtungszeit nahmen 6.383 Personen ≥10 % ihres Körpergewichts zu und 8.746 Personen steigerten ihren residualen Taillenumfangs ≥2.5 cm. Die Inzidenzraten (pro 10.000 Personenjahre) für SGZ schwankten zwischen den Kohorten von 189 bis 266 und für STUZ von 206 bis 356. Je nach Kohorte standen 19 bis 22 Prädiktoren für die Maximummodelle zur Verfügung; davon wurden 17 in allen Kohorten erhoben und stellten somit den einheitlichen Prädiktorensatz der Minimummodelle dar. Nach der Prädiktorselektion mittels RSF und unter Berücksichtigung der Fallzahlen der Kohorten, wurden fünf und sieben Prädiktoren für die Selektionsmodelle von SGZ und STUZ verwendet. Dem dreistufigen Ansatz folgend, sank die aROC (95 % Konfidenzintervall) der Risikoscores für SGZ von 0.73 (0.71, 0.76) über 0.71 (0.68, 0.75) auf 0.70 (0.67, 0.73), während sie für die Risikoscores für STUZ mit 0.69 (0.66, 0.73), 0.68 (0.65, 0.72), und 0.68 (0.64, 0.71) relativ konstant blieb. Sowohl für SGZ als auch für STUZ schwankten die aROCs zwischen den Kohorten. Die Verwendung kohorten-spezifischer Prädiktorgewichtungen hatte für SGZ keine Auswirkungen, für STUZ konnten jedoch zum Teil Zunahmen der aROC beobachtet werden. Die Kalibrierungsplots der Risikoscores für SGZ zeigten zwischen den Kohorten einen sehr ähnlichen Verlauf, wohingegen die Kalibrierungsplots der Risikoscores für STUZ mehr variierten. Die Ergebnisse der Dissertation stützen die Verallgemeinerbarkeit von meta-analytisch erstellten Risikoscores zur Vorhersage einer SGZ, auf Basis von einfach zu erhebenden Daten der zahlenmäßig bedeutendsten deutschen Kohortenstudien, für die deutsche Bevölkerung. Die Diskriminationsfähigkeit der Risikoscores für SGZ und STUZ bleibt auch nach Einschränkung der Prädiktorenzahl bemerkenswert konstant. Im Hinblick auf das weite Spektrum berücksichtigter Faktoren, scheint die Vorhersagbarkeit starker Zunahmen von Gewicht und Taillenumfang durch einfach zu erhebenden Prädiktoren jedoch generell begrenzt zu sein

Specific Metabolic Markers Are Associated with Future Waist-Gaining Phenotype in Women

Objective: Our study aims to identify metabolic markers associated with either a gain in abdominal (measured by waist circumference) or peripheral (measured by hip circumference) body fat mass. Methods: Data of 4 126 weight-gaining adults (18–75 years) from three population-based, prospective German cohort studies (EPIC, KORA, DEGS) were analysed regarding a waist-gaining (WG) or hip-gaining phenotype (HG). The phenotypes were obtained by calculating the differences of annual changes in waist minus hip circumference. The difference was displayed for all cohorts. The highest 10% of this difference were defined as WG whereas the lowest 10% were defined as HG. A total of 121 concordant metabolite measurements were conducted using Biocrates AbsoluteIDQ® kits in EPIC and KORA. Sex-specific associations with metabolite concentration as independent and phenotype as the dependent variable adjusted for confounders were calculated. The Benjamini-Hochberg method was used to correct for multiple testing. Results: Across studies both sexes gained on average more waist than hip circumference. We could identify 12 metabolites as being associated with the WG (n = 8) or HG (n = 4) in men, but none were significant after correction for multiple testing; 45 metabolites were associated with the WG (n = 41) or HG (n = 4) in women. For WG, n = 21 metabolites remained significant after correction for multiple testing. Respective odds ratios (OR) ranged from 0.66 to 0.73 for tryptophan, the diacyl-phosphatidylcholines (PC) C32:3, C36:0, C38:0, C38:1, C42:2, C42:5, the acyl-alkyl-PCs C32:2, C34:0, C36:0, C36:1, C36:2, C38:0, C38:2, C40:1, C40:2, C40:5, C40:6, 42:2, C42:3 and lyso-PC C17:0. Conclusion: Both weight-gaining men and women showed a clear tendency to gain more abdominal than peripheral fat. Gain of abdominal fat seems to be related to an initial metabolic state reflected by low concentrations of specific metabolites, at least in women. Thus, higher levels of specific PCs may play a protective role in gaining waist circumference

Changes in Waist Circumference among German Adults over Time - Compiling Results of Seven Prospective Cohort Studies

Aim: This study aims to quantify longitudinal changes in waist circumference (WC) among adults aged 45-64 years in Germany. Methods: Data of 15,444 men and 17,207 women from one nationwide and six regional prospective German cohort studies were analyzed. The sex-specific mean change in WC per year of follow-up was assessed for each study separately. Findings from the cohort-by-cohort analysis were combined by applying meta-analytic methods. Progression to central obesity (WC ≥ 102 cm in men and ≥ 88 cm in women) within a standardized period of 10 years was described for each study. Results: The estimated mean change in WC per year of follow-up for all cohorts combined was 0.53 (95% confidence interval 0.29-0.76) cm/year for men and 0.63 (0.48-0.77) cm/year for women, but varied between the included studies. Within 10 years, about 20% of individuals with low WC (Conclusion: The increase in mean WC with aging along with a profound increase of central adiposity is obviously and may have several adverse health effects. Obesity prevention programs should also focus on abdominal obesity

Significant (p< 0.05) meta-analytic combined associations with corresponding confidence limits and p-values for both phenotypes in men.

<p>Significant (p< 0.05) meta-analytic combined associations with corresponding confidence limits and p-values for both phenotypes in men.</p

Participant characteristics of weight-gaining individuals from DEGS, EPIC and KORA ^a.

<p>Participant characteristics of weight-gaining individuals from DEGS, EPIC and KORA <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0157733#t001fn002" target="_blank">^a</a>.</p

Distribution of waist-hip difference in weight-gaining individuals stratified by sex for each study.

<p>DEGS, German Health Interview and Examination Survey for adults; EPIC, European Prospective Investigation into Cancer and Nutrition Potsdam Study; KORA, Cooperative Health Research in the Region of Augsburg Study.</p

Metabolites showing significant associations with WG phenotype in women after correction for multiple testing.

<p>EPIC, European Prospective Investigation into Cancer and Nutrition Potsdam Study; KORA, Cooperative Health Research in the Region of Augsburg Study; PC, phosphatidylcholines; a, acyl; e, alkyl; SM, sphingomyelin.</p

Waist-hip difference by study and their correlation with weight change.

<p>Waist-hip difference by study and their correlation with weight change.</p

Blood Metabolic Signatures of Body Mass Index: A Targeted Metabolomics Study in the EPIC Cohort

Metabolomics is now widely used to characterize metabolic phenotypes associated with lifestyle risk factors such as obesity. The objective of the present study was to explore the associations of body mass index (BMI) with 145 metabolites measured in blood samples in the European Prospective Investigation into Cancer and Nutrition (EPIC) study. Metabolites were measured in blood from 392 men from the Oxford (UK) cohort (EPIC-Oxford) and in 327 control subjects who were part of a nested case-control study on hepatobiliary carcinomas (EPIC-Hepatobiliary). Measured metabolites included amino acids, acylcarnitines, hexoses, biogenic amines, phosphatidylcholines, and sphingomyelins. Linear regression models controlled for potential confounders and multiple testing were run to evaluate the associations of metabolite concentrations with BMI. 40 and 45 individual metabolites showed significant differences according to BMI variations, in the EPIC-Oxford and EPIC-Hepatobiliary subcohorts, respectively. Twenty two individual metabolites (kynurenine, one sphingomyelin, glutamate and 19 phosphatidylcholines) were associated with BMI in both subcohorts. The present findings provide additional knowledge on blood metabolic signatures of BMI in European adults, which may help identify mechanisms mediating the relationship of BMI with obesity-related diseases