- Research article
- Open Access
Dietary saturated fat and low-grade inflammation modified by accelerometer-measured physical activity in adolescence: results from the GINIplus and LISA birth cohorts
BMC Public Health volume 19, Article number: 818 (2019)
Saturated fatty acids (SFA) have been reported to promote inflammation. Nevertheless, evidence linking dietary SFA and low-grade inflammation in adolescents is scarce and inconsistent. The modulatory role of physical activity (PA) on fat metabolism and inflammation may provide a potential explanation. Thus, we assessed the association of dietary SFA with high-sensitivity C-reactive protein (hsCRP), a marker of low-grade inflammation, in 15-year-olds, and evaluated possible interactions between dietary SFA and different levels of PA.
Children participating in the 15-year follow-ups of the GINIplus and LISA German birth cohort studies were included (N = 824). SFA intake was estimated by means of a food frequency questionnaire and PA recorded by accelerometers. Average daily minutes of PA were classified into “sedentary”, “light” and “moderate-to-vigorous” (MVPA), using Freedson’s cut-offs. HsCRP concentrations were measured in serum and categorized into 3 sex-specific levels (below detection limit (I), above 75th percentile (III), in between (II)). Sex-stratified cross-sectional associations between SFA and hsCRP were assessed using multinomial logistic regression, adjusting for potential confounders. Interaction terms were included between SFA and the different PA levels; and if significant interactions were observed, analyses stratified by tertiles of the relevant PA levels were performed. Relative risk ratios (RRR) and 95% confidence intervals (95%CI) were presented for a 1% increase in SFA.
An inverse association was observed between SFA intake and hsCRP (II vs. I) in males (RRR = 0.85 [95%CI = 0.76;0.96], p = 0.008), whereas no significant association was observed in females. A significant interaction was observed with “sedentary” and “light” PA but not with MVPA in both sexes (p < 0.05). Stratified analyses indicated a significant inverse association between SFA and medium hsCRP levels in males in the highest light PA tertile (hsCRP II vs. I: 0.67 [0.517;0.858], p = 0.002).
Our findings do not support a detrimental role of dietary SFA in low-grade inflammation among adolescents. In males, higher dietary SFA was associated with lower hsCRP, although this should be interpreted in the context of possibly correlated nutrients. Children spending the most time in light PA drove the observed inverse association, suggesting a synergistic effect of SFA and lifestyle PA in the resultant inflammatory response.
Chronic, low-grade inflammation precedes the onset of cardiovascular diseases , which continue to be among the leading causes of death and disability worldwide . Ample evidence indicating that cardiovascular disease (CVD) risk can begin as early as childhood and track into adulthood [3, 4] has drawn research interests towards early biomarkers expressed in youth that may be predictive of adult morbidity . The inflammatory marker high-sensitivity C-reactive protein (hsCRP) is used to predict the risk of atherosclerosis and CVD in adults  and has been observed in association with arterial alterations in children . Raised hsCRP levels, even within the low ranges normally observed in children and adolescents , are associated with intermediate risk factors for CVD, including obesity [9, 10], insulin resistance [11, 12], and metabolic syndrome [13, 14]. Furthermore, childhood hsCRP levels have been shown to independently predict adult levels , as well as metabolic syndrome in adulthood . HsCRP measured in adolescents can therefore offer a possible early indication of future CVD risk. Given that poor diet and lack of physical activity (PA) are amongst the primary lifestyle contributors to CVD , the specific roles of both these aspects in low-grade inflammation have become of eminent public health relevance. For decades, a key nutritional guideline has been to limit consumption of saturated fatty acids (SFA) [18, 19]. Yet the underlying evidence for this recommendation has been questioned in a number of studies [20,21,22], fuelling an ongoing debate [23,24,25,26]. Amidst this discussion, SFA have received much attention for their ability to promote inflammatory processes in vitro [27,28,29]. In large observational studies, direct associations between serum or plasma SFA status with markers of low-grade inflammation have been observed in both overweight and lean adults [30,31,32] as well as in children [33, 34]. Further, the upregulation of several genes relating to inflammatory pathways has been reported in a number of clinical trials in humans following the consumption of SFA, as summarised in a recent review . Nevertheless, epidemiological studies observing longer-term dietary SFA in relation to inflammatory markers do not conclusively support a proinflammatory role of the nutrient [32, 36, 37]. Processes following dietary intake, including digestion, absorption, uptake into tissues, and metabolism, all affect the ensuing fatty acid profile , and could partially explain the conflicting findings relative to dietary SFA.
It has been proposed that the interaction with other lifestyle factors might be relevant in determining whether (or to what extent) dietary SFA contributes to chronic low-grade inflammation . PA is frequently discussed for its role in promoting a long-term anti-inflammatory response , the mechanisms of which are not entirely understood . Various studies in children and adolescents have not confirmed a direct association between PA and hsCRP [42,43,44,45], although the benefits on metabolic function and overall health are undeniable . Studies reporting significant associations in adolescents suggest a protective role of PA. In a sample of adolescents aged 13–16 years, vigorous PA was shown to be protective of elevated CRP in boys but not in girls, independent of weight status . Whereas in a study of adolescents from 10 European cities, objectively-measured vigorous PA was suggested to play an indirect beneficial role through improved cardiorespiratory fitness . An indirect role through altered energy metabolism may also be plausible; for example, studies have shown that skeletal muscle activity can influence fat oxidation . This effect can vary based on the intensity and duration of the activity, as well as by sex, as differences in substrate metabolism have been described, with females oxidising fat more readily than males during exercise . Hence, a sex-specific modulatory role of habitual PA in the relationship between dietary SFA and chronic low-grade inflammation is plausible, perhaps through long-term physiological changes at the cellular level . To our knowledge, no study has been carried out addressing the integrated role of SFA and PA in adolescent females and males. Therefore, this study aims to assess the association of dietary SFA with hsCRP in a large population of 15-year-olds, as well as the possible modulatory role of different levels and duration of objectively-measured PA.
The present study used data from the 15-year follow-up assessments of the GINIplus (German Infant Nutritional Intervention plus environmental and genetic influences on allergy development) and LISA (Influence of Life-style related factors on the development of the Immune System and Allergies in East and West Germany) birth cohort studies. Details on the cohorts’ recruitment and follow-up strategies have been described previously and can be found elsewhere [52, 53]. Briefly, healthy full-term new-borns were recruited from selected obstetric clinics in Germany. The GINIplus cohort (n = 5991) was recruited in Munich and Wesel between 1995 and 1998, and consists of two study arms: an observation arm and an intervention arm. New-borns with a family history of allergy were invited for the intervention arm, in which children were randomised to receive one of three hydrolysed formulas or cow’s milk. The aim was to compare the effect of the different formulae vs. cow’s milk on allergy development in a double-blind controlled trial. Participants with a negative family history of allergy, and those who declined to take part in the intervention trial, were included in the observation arm. The LISA cohort (n = 3094 - originally 3097 but three removed consent) is a true population-based cohort, recruited in Munich, Wesel, Leipzig and Bad Honnef, between 1997 and 1999. In both studies, information on selected exposures and health outcomes were obtained by means of questionnaires and medical examinations carried out at various follow-up assessments. Exposures and outcomes relevant to the present analyses are described in detail below. Both cohort studies have been approved by their local ethics committees (Bavarian Board of Physicians, University of Leipzig, Board of Physicians of North-Rhine-Westphalia) and written consent was obtained from all participants’ families.
Habitual dietary intake was assessed at the 15-year follow-up using a self-administered food frequency questionnaire (FFQ). The applied FFQ was designed at the 10-year follow-up for the estimation of food and nutrient intake in school-aged children over the past year. A detailed description of the FFQ development and its validation can be found elsewhere . Briefly, a list of commonly consumed foods contributing to total energy and especially fatty acid intake, was compiled from food intake data obtained by 3-day weighed dietary records of German children from the DONALD (Dortmund Nutritional and Anthropometric Longitudinally Designed) study ; portion sizes and frequency categories were included in the style of the EPIC (European Prospective Investigation into Cancer and Nutrition) FFQ . A pilot study was conducted to evaluate the comprehensibility and applicability of the resulting FFQ, which was then validated against a 24-h dietary recall (at a food group level and at a nutrient level) . The final version of the FFQ was used in the current study, and is available from the corresponding author upon reasonable request. The FFQ was delivered to participants by post and included detailed instructions for its completion. Participants were asked to report their estimated usual frequency (nine categories: ‘never’, ‘once a month’, ‘2-3 times a month’, ‘once a week’, ‘2-3 times a week’, ‘4-6 times a week’, ‘once a day’, ‘2-3 times a day’ and ‘four times a day or more’) and portion sizes (common household measures or coloured photographs of different portion sizes) of the intakes of the 80 listed food items over the past twelve months . Additionally, several questions were included on preferred fat and energy contents, preparation methods, diets and food preferences, buying habits and dietary supplement use. Participants were asked to complete the FFQ themselves with the support of whoever cooked at home, if needed. The study technical assistant could be contacted if any further clarification was required. A quality control procedure was applied based on recommendations by Willett et al.  for data cleaning in nutritional epidemiology described thoroughly in an earlier publication . Total daily energy and nutrient intakes were calculated (in kcal/day) based on the German Food Code and Nutrient Database (BLS) version II.3.1 . The relative contribution of SFA to the overall diet was calculated and expressed as a percentage of total daily energy intake (%EI).
PA was measured at age 15 years using triaxial accelerometers (ActiGraph GT3X, Pensacola, Florida), worn on the dominant hip for seven consecutive days. The accelerometer has been validated for use in adolescents , and it has been shown that measurements on opposing hips are not significantly different from each other [61, 62]. Participants for accelerometry were recruited from the study centers Munich and Wesel. This includes all of the GINIplus cohort and 64% of the LISA cohort taking part in the 15-year follow-up. The accelerometry protocol, data management and quality control have been described previously in detail [63, 64]. Briefly, participants were asked to keep an activity diary during the days the accelerometer was worn, where they recorded all their activities over the course of the day using a detailed schedule. This was done in order to control for non-wear time as well as the plausibility of the recorded accelerometer data. Since the goal was to capture a representative measure of usual daily PA, participants were asked to do the measurement during a “normal” week, i.e. no holidays, travelling, sickness. The activity diary information was also used to exclude recorded days which were not representative of typical routine, as described in Pfitzner et al. . After passing quality control, at least 10 h of recorded time (or 7 if subjects were awake for less than 10 h) were necessary for a recorded day to be considered valid. Subjects were required to have at least 3 valid recorded weekdays and one valid weekend day. Measured accelerations were converted into activity counts and stored at 1 Hz (resampled from 30 Hz). Activity counts were then classified into one of four intensity levels (“sedentary”, “light”, “moderate”, and “vigorous” PA) on a minute-by-minute basis, estimated according to the uniaxial cut-offs published by Freedson et al. . For the current analyses, three levels of PA were evaluated: “sedentary”, “light” (representing lifestyle PA), and “MVPA” (the sum of “moderate” and “vigorous” PA). Average minutes per day spent on the different PA levels were calculated for each individual by dividing total recorded minutes by the number of valid recorded days.
Chronic low-grade inflammation
Serum concentrations of hsCRP were measured in samples collected during the 15-year follow-up medical examinations, using the Roche (Mannheim, Germany) Tina-quant CRP (latex) high-sensitive assay, according to manufacturer instructions. Measured hsCRP concentrations were highly skewed, with many observations below detection limit (hsCRP 0.016 mg/dl). Given this non-normal distribution, data categorisation was required for analyses. The variable was hence categorised into three levels separately for girls and boys, considering all children with available hsCRP measurements: all adolescents with hsCRP levels below the detection limit (hsCRP < 0.016 mg/dl) were grouped in the lowest category (I); amongst those remaining, sex-specific 75th percentiles were determined (0.085 mg/dl in girls; 0.092 mg/dl in boys), and those below the 75th percentile, i.e. girls with hsCRP < 0.085 and boys with hsCRP < 0.092 mg/dl, were assigned to the middle category (II); those above the 75th percentile, i.e. girls with hsCRP ⩾0.085 and boys with hsCRP ⩾0.092 mg/dl, were assigned to the upper category (III). While hsCRP values between 0.3 and 1 mg/dl are usually deemed indicative of elevated low-grade inflammation and of higher risk of CVD in adults , these levels are rarely met in children . Unlike in adults, the cut-offs applied in the present study do not enable the identification of specific values on which to define high CVD risk. Rather, they allow the comparison between different hsCRP levels in young, healthy adolescents, amongst whom disease risk markers may manifest only in subclinical form. This is relevant given that hsCRP has been associated with early CVD risk factors like obesity [9, 10] and insulin resistance [11, 12] in children; also in the present study population, hsCRP was significantly positively associated with body mass index in both sexes (data not shown). This indicates that even young individuals with higher hsCRP levels with respect to their peers may be at greater CVD risk later in life, especially since hsCRP levels track into adulthood . General consensus suggests that hsCRP > 1 mg/dl likely reflects acute infection or trauma . Values > 1 mg/dl were therefore not considered for the present analyses in order to avoid assessing acute inflammation.
Participants from the 15-year follow-up of GINIplus and LISA studies, with complete data on SFA intake, accelerometer-measured physical activity, and hsCRP, were included in the statistical analyses. Since PA was measured only in Munich and Wesel, the study sample was limited to participants from these two study centres. Sex-stratified associations between SFA intake and hsCRP were assessed using multinomial logistic regression, adjusting for potential confounders: study (GINI intervention arm; GINI observation arm; LISA), region (Munich; Wesel), parental education (based on highest level achieved - low: ≤10th grade; high: >10th grade), pubertal stage (based on a self-rating Pubertal Development Scale (PDS), which has been validated in adolescents and includes ratings on body hair growth, voice change and facial hair growth for boys, and body hair growth, breast development and menarche for girls [67, 68]. For each item (except menarche which had a yes/no response) there were four response options ranging from “not yet started” to “seems complete”, which were used to create pubertal stage categories: early-; mid-; late-; post-pubertal), fasted blood sampling (yes; no), exact age at blood sampling (years), body mass index (BMI, in kg/m2 calculated from height and weight measurements obtained during physical examination, unless unavailable (n = 65), in which case obtained from the 15-year follow-up questionnaire), and total daily energy intake (kcal/day).
In three additional models, separate adjustment for the different PA levels (“sedentary”, “light” and “MVPA”) was carried out. Interaction terms were then included between SFA and the different PA levels. Where a significant interaction was observed, additional analyses were performed, stratified by tertiles of the relevant PA level. Here, we corrected for multiple testing using Bonferroni correction: the α-level was divided by three (the number of subgroups assessed for each sex in stratified analyses). This yielded a corrected two-sided α-level of 0.017 (0.05/3 = 0.017). Relative risk ratios (RRR) and 95% confidence intervals (95%CI) are presented for a 1% increase in SFA. The RRR indicates the risk of being in one of the comparison groups relative to the risk of being in the reference group given a 1% change in SFA. All analyses were conducted using R, version 3.3.2 (https://www.R-project.org/) . Multinomial logistic regression was calculated using the “multinom” function in the R package “nnet” .
A total of 824 participants (469 females, 355 males) were included in the analyses (see Additional file 1: Figure S1). Complete data on SFA intake, accelerometer-measured PA, and hsCRP, was available for 1011 children. Participants were excluded who were lacking data for adjustment variables (171 subjects), as well as those who reported an illness affecting diet or inflammatory status (8 subjects, 3 with diabetes, 2 with coeliac disease, 2 with cancer, 1 with Crohn’s disease). Children were also excluded if they presented clear outliers in SFA intakes (none) or in PA levels (2 subjects, 1 female with MVPA = 257 min/day, 1 male with MVPA = 220 min/day), as identified by visual inspection of descriptive plots. Finally, children with hsCRP values > 1 mg/dl (likely reflecting acute inflammation) were further excluded (6 subjects with hsCRP levels ranging from 1.12 mg/dl to 3.86 mg/dl). Basic characteristics of the study population are displayed in Table 1. Girls and boys presented no significant differences in hsCRP levels (mg/dl) or in SFA intakes (%EI). In contrast, girls spent significantly more time in “sedentary” activities than boys, whereas boys spent more time in “light” PA and “MVPA”, and consumed higher amounts of daily calories.
Dietary SFA and hsCRP
Results from the multinomial logistic regression assessing the association between SFA and hsCRP, including individual adjustment for different PA levels, “sedentary”, “light” and “MVPA”, and their interactions, are displayed in Table 2. No statistically significant association was observed between SFA and hsCRP in females, whereas males presented an inverse association (hsCRP II vs I: RRR = 0.873 (95%CI = 0.78; 0.98), p = 0.021), which remained significant following further adjustment for PA variables. A dose-response relationship was however not indicated, as this association was observed at the middle hsCRP (II) level but not the upper (III) level.
Effect modification by PA
While adjustment for PA levels did not influence the association between SFA and hsCRP, significant interactions with time spent “sedentary” and in “light” PA were observed in females and males. Further analyses were hence carried out stratified by both these PA levels. Results from the stratified analyses are displayed in Fig. 1 (exact values can be found in Additional file 2: Table S1). Analyses stratified by tertiles of “sedentary” time indicated no association between SFA and hsCRP in either females or males in any of the tertiles. On the other hand, analyses stratified by tertiles of time spent in “light” PA indicated an inverse association between SFA and hsCRP only for male subjects in the highest “light” PA tertile (hsCRP II vs I: 0.714 (0.57;0.89), p = 0.003).
The present study assessed the association between dietary SFA and low-grade inflammation, measured by the inflammatory marker hsCRP, in 15-year-old German adolescents. Two aspects stand out among the analyses findings: 1) dietary SFA appears to have no association with hsCRP levels in adolescent females and to be inversely associated with hsCRP in males, albeit only for the middle hsCRP level with respect to the lowest, thus showing no clear exposure-response relationship; 2) a significant interaction between SFA intake and “light” PA likely plays a relevant role, given that the inverse association observed in males was only present among those spending the most time in “light” PA, as indicated by stratified analyses. Although average daily minutes of MVPA were comparable to reports in other adolescent populations [71, 72], it should be kept in mind that the majority of adolescents in this study do not meet the WHO recommendation of 60 min of MVPA per day . This is not uncommon for adolescents; according to the WHO, over 80% of 15-year-olds in European populations do not reach PA recommendations . The present findings are therefore relevant to underscore the positive role of “light” PA in modifying potential inflammatory effects of diet in adolescents, who clearly struggle to reach adequate levels of MVPA. Nevertheless, different results might be expected in more active individuals, especially regarding interactions between MVPA and SFA, as levels may be too low in this population to detect significant effects.
Dietary SFA and hsCRP
The results of our analyses in females are in line with a number of studies in adults, in which no significant association has been observed between dietary SFA and hsCRP [32, 36, 75]. Others have reported positive associations, supporting arguments to limit SFA intake in order to reduce cardiovascular risk [76,77,78]. Existing studies addressing children and adolescents are equally inconclusive. In a sample of 79 Swiss children aged 6–14 years, total dietary fat, but not one specific type of fat (mono- or poly-unsaturated fatty acids or SFA), was directly associated with subclinical inflammation . Another study in a random sample of 12–17-year-old girls in the Balearic Islands (n = 219), reported no association between dietary SFA and hsCRP . On the other hand, a population-based study including 602 children aged 5–13 years in a Brazilian city, showed a direct association between dietary SFA and high hsCRP, defined as CRP levels > 0.1 mg/dl ; while a study in 359 urban Asian Indian adolescents and young adults (87% males) observed twice the odds of having raised CRP levels (> 0.3 mg/dl) in subjects with intakes of SFA > 10%EI . The inconsistency among the various study findings might be related to study location, which could influence habitual dietary behaviours and patterns, sources of dietary SFA, or even baseline hsCRP levels. With respect to this last point, the median hsCRP levels in our study population were 0.04 mg/dl in females and 0.03 mg/dl in males. Although no hsCRP reference values are yet available for adolescents, these levels are comparable to pre-pubertal reference values in Europe . Intakes of SFA in our study population (around 13%EI) were also similar to intakes reported in other German adolescent populations . Compared to the study in Asian Indians, who presented higher average CRP values (0.13 mg/dl), our results and those of the Spanish study might suggest that dietary SFA is not significantly relevant in females, within the ranges of hsCRP and SFA here reported. Nevertheless, this was not supported by results from the Brazilian study, which applied a much lower cut-off to define upper hsCRP levels (> 0.1 mg/dl) and still observed a direct association with SFA.
It is also possible that contradicting results in terms of SFA may reflect true differences between SFA intake and status. While the assessment of SFA intake considers the amount of the nutrient consumed, SFA status likely reflects circulating SFA following additional processes such as digestion, absorption, uptake into tissues, and metabolism . In the present analyses, we observed an inverse association between SFA intake and middle hsCRP levels in males. Such an association between dietary SFA and hsCRP was also observed by Fredrikson et al. in adult females , a finding which the authors described as surprising. It has been proposed that the sparing of SFA and endogenous de novo SFA synthesis both contribute to SFA status and are promoted by high-carbohydrate diets . Reduced SFA intakes have been shown to be compensated by a concomitant increase in carbohydrate (CHO) intakes . Indeed, our dietary data presented strong negative correlations between SFA and CHO (r = − 0.76 and r = − 0.80 in females and males, respectively). Due to the strong correlations, adjustment for CHO in our statistical models was not possible as this would have led to problems of multicollinearity. We hence emphasize that these results should be interpreted in the context of other, possibly correlated nutrients. High glycaemic index CHO has been reported to induce inflammation through postprandial hyperglycaemia even in lean, glucose-tolerant subjects , and several intervention studies seem to support this notion . A previous study including a subset of the present study population showed that the highest contribution towards total energy intake at age 15 years came from “refined grains” and “sugar-sweetened foods” . We therefore speculate that increasing SFA intake likely has no direct role in reducing low-grade inflammation per se, but might promote a reduced inflammatory profile indirectly through a simultaneous reduction in CHO intake. This finding would hence support statements advocating that it is not simply the dietary SFA content, but the entire dietary composition, and especially the relative CHO intake, that determines whether SFA intake is ultimately associated with detrimental outcomes .
Effect modification by PA
The inverse association between SFA and the middle category of hsCRP, apparent in male adolescents of the current study, was driven mainly by a specific subgroup with high levels of daily “light” PA. To our knowledge, this is the first study to evaluate the interaction of PA in the association of SFA and low-grade inflammation in adolescents, and hence comparison with other studies is limited. Anti-inflammatory effects of habitual PA in children have been observed , although a study assessing accelerometer-measured PA in 9-year-old children reported no association between PA and hsCRP . None of the different PA levels assessed were significant confounders in our analyses, and therefore did not alter the inverse relationship between SFA and middle category levels of hsCRP when included in the statistical models as covariates. It could be suggested from the current findings that PA exerts part of its anti-inflammatory effects through its modifying role in SFA metabolism, with “light” PA being most relevant in this context. For a 1% increase in energy intake from SFA in males in the highest tertile of “light” PA, the relative risk of being in the middle hsCRP category vs. the lowest was reduced by a factor of 0.714. It is possible that MVPA was too low in our study population to induce significant synergistic effects with diet. In previous analyses of PA in the present birth cohorts, only about 1% of the subjects achieved the WHO recommended 60 min of MVPA per day . On the other hand, it is known that the intensity of PA is the main factor determining the degree of CHO or fat oxidation for fuel, and that low-intensity exercise depends almost entirely on fatty acids . This might explain why only “light” PA presented a significant interaction with SFA in our analyses. It seems plausible, that an increased capacity to metabolize lipids throughout the day (> 4.6 h of “light” PA were undergone on average daily in males in the highest tertile) could reduce the levels of circulating SFA, thereby limiting a possible pro-inflammatory response to higher SFA intakes compared to less active subjects. The inverse association was not significant in children with the highest hsCRP levels, although a near-significant trend was present (p < 0.05). It is possible that due to the smaller sample size and greater variance in the highest hsCRP category, there was insufficient power to detect a significant association. Why the inverse association was only observed in males is unclear, but it is possible that sex-specific physiological factors might play a significant role, leading to differences in fat metabolism and the resulting inflammatory profile. For example, testosterone has been shown to enhance lipid oxidation whereas oestrogen enhances fat storage , aspects which may be relevant in the context of the present study, especially considering that most of the females in the sample were in late- or post-pubertal stages. On the other hand, males were significantly more active than females and it is possible that females were not sufficiently active for a significant anti-inflammatory response with higher SFA intakes in synergy with “light” PA.
Strengths and limitations
The present study benefits from a large, homogeneous study sample, and adds to the limited literature on the association between dietary SFA and low-grade inflammation in adolescents, in a time of heightened discussion concerning SFA and cardiovascular health. Our study includes data from over 800 individuals, greatly exceeding the size of the few observational studies carried out thus far. Our analyses also include the assessment of different levels of accelerometer-measured physical activity, a method not often available in large cohort studies. Accelerometers were worn by participants on the hip, reported to be the best single location to record data for activity detection . Furthermore, to our knowledge, the role of SFA with regards to inflammation has not been previously assessed in the context of different PA levels and their possible interactions. The current analyses hint towards potential synergistic effects of important modifiable lifestyle factors in relation to health aspects, particularly in males. Their interaction may differ substantially from their individual effects and this can be highly relevant when interpreting findings on a topic such as SFA, on which contradicting results are often discussed. This study focusses on a population of healthy adolescents aged 15-years, which is not a high-risk population. Given the low levels of hsCRP being addressed, results are not necessarily indicative of damage nor directly translatable to CVD risk, and hence the clinical relevance of the present findings may seem limited. However, given the increasing evidence for the progression of risk factors from childhood to adulthood, preventive measures might already consider this age group and hence associations observed could provide valuable insight.
A main limitation when assessing dietary intake is the reliance on subjective measures, which are prone to reporting bias. In the present study the FFQ used to measure dietary SFA was designed to estimate fatty acids and antioxidants in school-aged children . Given the thorough quality control of the dietary data (with plausible values observed in terms of total energy intake), misreporting was likely detected and excluded from the analysis. A further drawback is the high inter-correlation amongst different nutrients, which is often come across in nutritional epidemiology, and if ignored could lead to inappropriate conclusions. Adjustment for these nutrients within the statistical models could result in multicollinearity, generating further misleading associations . With this in mind, and considering that the inclusion of an interaction term with PA would further complicate interpretation, we could not adjust for other nutrients and hence the ability to disentangle the individual effects of SFA is somewhat limited. Nonetheless, we are aware of the importance of accounting for possible intercorrelations and have hence considered these in the interpretation of our results. A further limitation in the present study was the underrepresentation of children from lower social-classes. As often occurs in longitudinal cohort studies, this non-random loss-to-follow-up meant that the current findings may not be entirely representative of the study area. The assessment of other inflammatory markers might have been useful to strengthen our conclusions, but unfortunately these were not available for the studied cohorts. Our findings are based on cross-sectional analyses, meaning that the observed associations between dietary SFA and hsCRP do not necessarily infer causality. Furthermore, blood-withdrawal for CRP measurements was carried out at a slightly different time to dietary assessment and accelerometry. Thus, the present analysis is based on the assumption that dietary intake, as well as PA and CRP, are persistent during this interval, which may not be entirely the case. Nevertheless, for PA, activity measured on non-typical days (e.g. including trips or sickness) were excluded to ensure usual activity was recorded, which more likely represents chronic PA. In terms of dietary intake, it was not possible to check if intakes of SFA directly prior to hsCRP measurement were indeed the same as those recorded in the dietary assessment; however, our focus was on chronic SFA intake and the FFQ was designed to estimate intakes over the past 12 months, which includes the time of blood withdrawal for most participants. We assume that any drastic changes in diet between FFQ completion and blood withdrawal are unlikely, although it cannot be entirely excluded. Nevertheless, changes occurring in either lifestyle behaviour would have occurred at the individual level, and hence any bias due to such changes are expected to be random, not affecting the general trend observed. Furthermore, the analyses were adjusted for age, which partially accounts for season, as participants were invited to follow-up assessments 2–4 weeks before their birth month, with the aim of limiting systematic bias.
From the present analyses, it can be concluded that a higher SFA intake during adolescence, within the ranges observed in the current study, is not detrimental in terms of inflammatory processes in adolescents; although we highlight that this may well depend on the nutrient it replaces. Furthermore, the inflammatory role of SFA might be modulated by the amount of daily “light” PA. Adolescent males with higher SFA intakes, who also participated in greater amounts of “light” PA, presented lower levels of hsCRP than their less active peers. We propose that when evaluating the role of SFA in chronic inflammation, it is essential to differentiate between findings involving SFA status (in serum or plasma) and those assessing dietary SFA, as the latter is likely influenced by important modifiable factors such as PA, which may determine whether an inflammatory response arises.
Availability of data and materials
The datasets generated and/or analysed during the current study are not publicly available due to data protection reasons, but are available from the corresponding author on reasonable request, provided it is consistent with the consent given by the study participants. In some cases, ethical approval can be obtained for the release. Lastly, a data transfer agreement must be accepted and the request must be approved by the studies’ steering committees. Requests should be addressed to Marie Standl (firstname.lastname@example.org).
Moderate-to-vigorous physical activity
Saturated fatty acids
Pearson TA, Mensah GA, Alexander RW, Anderson JL, Cannon RO, Criqui M, et al. Markers of inflammation and cardiovascular disease application to clinical and public health practice - a statement for healthcare professionals from the centers for disease control and prevention and the American Heart Association. Circulation. 2003;107.
World Health Organization. Global health estimates 2015: deaths by cause, age, sex, by country and by region, 2000-2015. Geneva: WHO; 2016.
Nicklas TA, von Duvillard SP, Berenson GS. Tracking of serum lipids and lipoproteins from childhood to dyslipidemia in adults: the Bogalusa heart study. Int J Sports Med. 2002;23(Suppl 1):S39–43.
Juhola J, Magnussen CG, Viikari JS, Kahonen M, Hutri-Kahonen N, Jula A, et al. Tracking of serum lipid levels, blood pressure, and body mass index from childhood to adulthood: the cardiovascular risk in Young Finns study. J Pediatr. 2011;159(4):584–90.
Canas JA, Sweeten S, Balagopal PB. Biomarkers for cardiovascular risk in children. Curr Opin Cardiol. 2013;28(2):103–14.
Ridker PM, Cushman M, Stampfer MJ, Tracy RP, Hennekens CH. Inflammation, aspirin, and the risk of cardiovascular disease in apparently healthy men. N Engl J Med. 1997;336(14):973–9.
Jarvisalo MJ, Harmoinen A, Hakanen M, Paakkunainen U, Viikari J, Hartiala J, et al. Elevated serum C-reactive protein levels and early arterial changes in healthy children. Arterioscler Thromb Vasc Biol. 2002;22(8):1323–8.
Schlenz H, Intemann T, Wolters M, Gonzalez-Gil EM, Nappo A, Fraterman A, et al. C-reactive protein reference percentiles among pre-adolescent children in Europe based on the IDEFICS study population. International journal of obesity (2005). 2014;38(Suppl 2):S26–31.
Cook DG, Mendall MA, Whincup PH, Carey IM, Ballam L, Morris JE, et al. C-reactive protein concentration in children: relationship to adiposity and other cardiovascular risk factors. Atherosclerosis. 2000;149(1):139–50.
Nappo A, Iacoviello L, Fraterman A, Gonzalez-Gil EM, Hadjigeorgiou C, Marild S, et al. High-sensitivity C-reactive protein is a predictive factor of adiposity in children: results of the identification and prevention of dietary- and lifestyle-induced health effects in children and infants (IDEFICS) study. J Am Heart Assoc. 2013;2(3):e000101.
Syrenicz A, Garanty-Bogacka B, Syrenicz M, Gebala A, Walczak M. Low-grade systemic inflammation and the risk of type 2 diabetes in obese children and adolescents. Neuro endocrinology letters. 2006;27(4):453–8.
Retnakaran R, Hanley AJ, Connelly PW, Harris SB, Zinman B. Elevated C-reactive protein in native Canadian children: an ominous early complication of childhood obesity. Diabetes Obes Metab. 2006;8(5):483–91.
Ford ES, Ajani UA, Mokdad AH. The metabolic syndrome and concentrations of C-reactive protein among U.S. youth. Diabetes Care. 2005;28(4):878–81.
DeBoer MD, Gurka MJ, Sumner AE. Diagnosis of the metabolic syndrome is associated with disproportionately high levels of high-sensitivity C-reactive protein in non-Hispanic black adolescents: an analysis of NHANES 1999-2008. Diabetes Care. 2011;34(3):734–40.
Juonala M, Viikari JS, Ronnemaa T, Taittonen L, Marniemi J, Raitakari OT. Childhood C-reactive protein in predicting CRP and carotid intima-media thickness in adulthood: the cardiovascular risk in Young Finns study. Arterioscler Thromb Vasc Biol. 2006;26(8):1883–8.
Mattsson N, Rönnemaa T, Juonala M, Viikari JSA, Raitakari OT. Childhood predictors of the metabolic syndrome in adulthood. The cardiovascular risk in Young Finns study. Ann Med. 2008;40(7):542–52.
Daniels SR, Pratt CA, Hayman LL. Reduction of risk for cardiovascular disease in children and adolescents. Circulation. 2011;124(15):1673–86.
Sacks FM, Lichtenstein AH, Wu JHY, Appel LJ, Creager MA, Kris-Etherton PM, et al. Dietary fats and cardiovascular disease: a presidential advisory from the American Heart Association. Circulation. 2017.
US senate select committee on nutrition and human needs. Dietary goals for the United States. 1st ed. Washington: US Govt print off; 1977.
Siri-Tarino PW, Sun Q, Hu FB, Krauss RM. Meta-analysis of prospective cohort studies evaluating the association of saturated fat with cardiovascular disease. Am J Clin Nutr. 2010;91(3):535–46.
Chowdhury R, Warnakula S, Kunutsor S, Crowe F, Ward HA, Johnson L, et al. Association of dietary, circulating, and supplement fatty acids with coronary risk: a systematic review and meta-analysis. Ann Intern Med. 2014;160(6):398–406.
Harcombe Z, Baker JS, Cooper SM, Davies B, Sculthorpe N, DiNicolantonio JJ, et al. Evidence from randomised controlled trials did not support the introduction of dietary fat guidelines in 1977 and 1983: a systematic review and meta-analysis. Open Heart. 2015;2:1.
Ravnskov U, Diamond D, Canan Efendigil Karatay M, Miller DW, Okuyama H. No scientific support for linking dietary saturated fat to CHD. Br J Nutr. 2011;107(3):455–7.
Malhotra A. Saturated fat is not the major issue. BMJ: British Medical Journal. 2013;347.
Pedersen JI, James PT, Brouwer IA, Clarke R, Elmadfa I, Katan MB, et al. The importance of reducing SFA to limit CHD. Br J Nutr. 2011;106(7):961–3.
Bahl R. The evidence base for fat guidelines: a balanced diet. Open Heart. 2015;2:1.
Ajuwon KM, Spurlock ME. Palmitate activates the NF-kappaB transcription factor and induces IL-6 and TNFalpha expression in 3T3-L1 adipocytes. J Nutr. 2005;135(8):1841–6.
Weatherill AR, Lee JY, Zhao L, Lemay DG, Youn HS, Hwang DH. Saturated and polyunsaturated fatty acids reciprocally modulate dendritic cell functions mediated through TLR4. J Immunol. 2005;174(9):5390–7.
Lee JY, Sohn KH, Rhee SH, Hwang D. Saturated fatty acids, but not unsaturated fatty acids, induce the expression of cyclooxygenase-2 mediated through toll-like receptor 4. J Biol Chem. 2001;276(20):16683–9.
Kaikkonen JE, Kresanov P, Ahotupa M, Jula A, Mikkila V, Viikari JS, et al. High serum n6 fatty acid proportion is associated with lowered LDL oxidation and inflammation: the cardiovascular risk in Young Finns study. Free Radic Res. 2014;48(4):420–6.
Fernandez-Real JM, Broch M, Vendrell J, Ricart W. Insulin resistance, inflammation, and serum fatty acid composition. Diabetes Care. 2003;26(5):1362–8.
Santos S, Oliveira A, Lopes C. Systematic review of saturated fatty acids on inflammation and circulating levels of adipokines. Nutr Res. 2013;33(9):687–95.
Harris C, Demmelmair H, von Berg A, Lehmann I, Flexeder C, Koletzko B, et al. Associations between fatty acids and low-grade inflammation in children from the LISAplus birth cohort study. Eur J Clin Nutr. 2017.
Klein-Platat C, Drai J, Oujaa M, Schlienger JL, Simon C. Plasma fatty acid composition is associated with the metabolic syndrome and low-grade inflammation in overweight adolescents. Am J Clin Nutr. 2005;82(6):1178–84.
Rocha DM, Bressan J, Hermsdorff HH. The role of dietary fatty acid intake in inflammatory gene expression: a critical review. Sao Paulo medical journal = Revista paulista de medicina. 2017;135(2):157–68.
Mazidi M, Gao HK, Vatanparast H, Kengne AP. Impact of the dietary fatty acid intake on C-reactive protein levels in US adults. Medicine. 2017;96(7):e5736.
Santos S, Oliveira A, Pinho C, Casal S, Lopes C. Fatty acids derived from a food frequency questionnaire and measured in the erythrocyte membrane in relation to adiponectin and leptin concentrations. Eur J Clin Nutr. 2014;68(5):555–60.
Arab L, Akbar J. Biomarkers and the measurement of fatty acids. Public Health Nutr. 2002;5(6a):865–71.
Ruiz-Nunez B, Pruimboom L, Dijck-Brouwer DA, Muskiet FA. Lifestyle and nutritional imbalances associated with Western diseases: causes and consequences of chronic systemic low-grade inflammation in an evolutionary context. J Nutr Biochem. 2013;24(7):1183–201.
Kasapis C, Thompson PD. The effects of physical activity on serum C-reactive protein and inflammatory markers: a systematic review. J Am Coll Cardiol. 2005;45(10):1563–9.
Gleeson M, Bishop NC, Stensel DJ, Lindley MR, Mastana SS, Nimmo MA. The anti-inflammatory effects of exercise: mechanisms and implications for the prevention and treatment of disease. Nat Rev Immunol. 2011;11(9):607–15.
Loprinzi P, Cardinal B, Crespo C, Brodowicz G, Andersen R, Sullivan E, et al. Objectively measured physical activity and C-reactive protein: National Health and nutrition examination survey 2003–2004. Scand J Med Sci Sports. 2013;23(2):164–70.
Moran A, Steffen LM, Jacobs DR Jr, Steinberger J, Pankow JS, Hong CP, et al. Relation of C-reactive protein to insulin resistance and cardiovascular risk factors in youth. Diabetes Care. 2005;28(7):1763–8.
Ruiz JR, Ortega FB, Warnberg J, Sjostrom M. Associations of low-grade inflammation with physical activity, fitness and fatness in prepubertal children; the European youth heart study. International journal of obesity (2005). 2007;31(10):1545–51.
Martinez-Gomez D, Eisenmann JC, Warnberg J, Gomez-Martinez S, Veses A, Veiga OL, et al. Associations of physical activity, cardiorespiratory fitness and fatness with low-grade inflammation in adolescents: the AFINOS study. International journal of obesity (2005). 2010;34(10):1501–7.
Poitras VJ, Gray CE, Borghese MM, Carson V, Chaput J-P, Janssen I, et al. Systematic review of the relationships between objectively measured physical activity and health indicators in school-aged children and youth. Appl Physiol Nutr Metab. 2016;41(6 (Suppl. 3):S197–239.
Sabiston CM, Castonguay A, Low NC, Barnett T, Mathieu ME, O'Loughlin J, et al. Vigorous physical activity and low-grade systemic inflammation in adolescent boys and girls. Int J Pediatr Obes. 2010;5(6):509–15.
Martinez-Gomez D, Gomez-Martinez S, Ruiz JR, Diaz LE, Ortega FB, Widhalm K, et al. Objectively-measured and self-reported physical activity and fitness in relation to inflammatory markers in European adolescents: the HELENA study. Atherosclerosis. 2012;221(1):260–7.
Frayn KN. Fat as a fuel: emerging understanding of the adipose tissue–skeletal muscle axis. Acta Physiol. 2010;199(4):509–18.
Lundsgaard AM, Kiens B. Gender differences in skeletal muscle substrate metabolism - molecular mechanisms and insulin sensitivity. Front Endocrinol. 2014;5:195.
Teeman CS, Kurti SP, Cull BJ, Emerson SR, Haub MD, Rosenkranz SK. Postprandial lipemic and inflammatory responses to high-fat meals: a review of the roles of acute and chronic exercise. Nutrition & Metabolism. 2016;13.
Berg A, Kramer U, Link E, Bollrath C, Heinrich J, Brockow I, et al. Impact of early feeding on childhood eczema: development after nutritional intervention compared with the natural course - the GINIplus study up to the age of 6 years. Clinical and experimental allergy: journal of the British Society for Allergy and Clinical Immunology. 2010;40(4):627–36.
Heinrich J, Bolte G, Holscher B, Douwes J, Lehmann I, Fahlbusch B, et al. Allergens and endotoxin on mothers’ mattresses and total immunoglobulin E in cord blood of neonates. Eur Respir J. 2002;20.
Stiegler P, Sausenthaler S, Buyken AE, Rzehak P, Czech D, Linseisen J, et al. A new FFQ designed to measure the intake of fatty acids and antioxidants in children. Public Health Nutr. 2010;13(1):38–46.
Kroke A, Manz F, Kersting M, Remer T, Sichert-Hellert W, Alexy U, et al. The DONALD study. History, current status and future perspectives. Eur J Nutr. 2004;43(1):45–54.
Bohlscheid-Thomas S, Hoting I, Boeing H, Wahrendorf J. Reproducibility and relative validity of food group intake in a food frequency questionnaire developed for the German part of the EPIC project. European prospective investigation into Cancer and nutrition. Int J Epidemiol. 1997;26(Suppl 1):S59–70.
Harris C, Flexeder C, Thiering E, Buyken A, Berdel D, Koletzko S, et al. Changes in dietary intake during puberty and their determinants: results from the GINIplus birth cohort study. BMC Public Health. 2015;15:841.
Willett W. Nutritional epidemiology. USA: Oxford University Press; 1998.
Hartmann BM, Bell S, Va’squez-Caiquedo AL. Der Bundeslebensmittelschlüssel. German nutrient DataBase. Karlsruhe: Federal Research Centre for nutrition and food (BfEL). 2005.
Robusto KM, Trost SG. Comparison of three generations of ActiGraph activity monitors in children and adolescents. J Sports Sci. 2012;30(13):1429–35.
Aadland E, Ylvisåker E. Reliability of the Actigraph GT3X+ accelerometer in adults under free-living conditions. PLoS One. 2015;10(8):e0134606.
Jarrett H, Fitzgerald L, Routen AC. Inter-instrument reliability of the actigraph GT3X+ ambulatory activity monitor during free-living conditions in adults. J Phys Act Health. 2015;12(3):382–7.
Smith MP, Berdel D, Nowak D, Heinrich J, Schulz H. Physical activity levels and domains assessed by Accelerometry in German adolescents from GINIplus and LISAplus. PLoS One. 2016;11(3):e0152217.
Pfitzner R, Gorzelniak L, Heinrich J, von Berg A, Klümper C, Bauer CP, et al. Physical activity in German adolescents measured by Accelerometry and activity diary: introducing a comprehensive approach for data management and preliminary results. PLoS One. 2013;8(6):e65192.
Freedson P, Pober D, Janz KF. Calibration of accelerometer output for children. Med Sci Sports Exerc. 2005;37(11 Suppl):S523–30.
Ridker PM. A Test in Context: High-Sensitivity C-Reactive Protein. J Am Coll Cardiol. 2016;67(6):712–23.
Carskadon MA, Acebo C. A self-administered rating scale for pubertal development. J Adolesc Health. 1993;14(3):190–5.
Petersen AC, Crockett L, Richards M, Boxer A. A self-report measure of pubertal status: reliability, validity, and initial norms. Journal of youth and adolescence. 1988;17(2):117–33.
R Core Team. R: A language and environment for statistical computing R Foundation for Statistical Computing, Vienna, Austria 2016.
Venables WN, Ripley BD. Modern Applied Statistics with S. Fourth ed: Springer, New York. IBSN 0-387-95457-0; 2002.
Van Hecke L, Loyen A, Verloigne M, van der Ploeg HP, Lakerveld J, Brug J, et al. Variation in population levels of physical activity in European children and adolescents according to cross-European studies: a systematic literature review within DEDIPAC. The international journal of behavioral nutrition and physical activity, vol. 13; 2016. p. 70.
Riddoch CJ, Mattocks C, Deere K, Saunders J, Kirkby J, Tilling K, et al. Objective measurement of levels and patterns of physical activity. Arch Dis Child. 2007;92(11):963–9.
Global Recommendations on Physical Activity for Health. Geneva. World Health Organization; 2010. Available from: https://www.ncbi.nlm.nih.gov/books/NBK305057/.
Inchley J, Currie D, Young T, Samdal O, Torsheim T, Augustson L, et al. Growing up unequal: gender and socioeconomic differences in young people's health and well-being. Health Behaviour in School-aged Children (HBSC) study: international report from the 2013/2014 survey Copenhagen, WHO Regional Office for Europe: 2016 (Health Policy for Children and Adolescents, No. 7).
Kalogeropoulos N, Panagiotakos DB, Pitsavos C, Chrysohoou C, Rousinou G, Toutouza M, et al. Unsaturated fatty acids are inversely associated and n-6/n-3 ratios are positively related to inflammation and coagulation markers in plasma of apparently healthy adults. Clinica chimica acta; international journal of clinical chemistry. 2010;411(7–8):584–91.
King DE, Egan BM, Geesey ME. Relation of dietary fat and fiber to elevation of C-reactive protein. Am J Cardiol. 2003;92(11):1335–9.
Navarro SL, Kantor ED, Song X, Milne GL, Lampe JW, Kratz M, et al. Factors associated with multiple biomarkers of systemic inflammation. Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology. 2016;25(3):521–31.
Kantor ED, Lampe JW, Kratz M, White E. Lifestyle factors and inflammation: associations by body mass index. PLoS One. 2013;8(7).
Aeberli I, Molinari L, Spinas G, Lehmann R, l'Allemand D, Zimmermann MB. Dietary intakes of fat and antioxidant vitamins are predictors of subclinical inflammation in overweight Swiss children. Am J Clin Nutr. 2006;84.
Del Mar Bibiloni M, Maffeis C, Llompart I, Pons A, Tur JA. Dietary factors associated with subclinical inflammation among girls. Eur J Clin Nutr. 2013;67(12):1264–70.
Boscaini C, Artifon M, Pellanda LC. High sensitivity C - reactive protein levels are associated with high energy intake, processed foods, Total fat and saturated fats intake in children. Open J Pediatr Neonatal Care. 2017;2(1):024–30.
Arya S, Isharwal S, Misra A, Pandey RM, Rastogi K, Vikram NK, et al. C-reactive protein and dietary nutrients in urban Asian Indian adolescents and young adults. Nutrition. 2006;22(9):865–71.
Mensink GBM, Heseker H, Stahl A, Richter A, Vohmann C. Die aktuelle Nährstoffversorgung von Kindern und Jugendlichen in Deutschland. Ergebnisse aus EsKiMo Ernährungsumschau. 2007;11:636–46.
Fredrikson GN, Hedblad B, Nilsson JA, Alm R, Berglund G, Nilsson J. Association between diet, lifestyle, metabolic cardiovascular risk factors, and plasma C-reactive protein levels. Metab Clin Exp. 2004;53(11):1436–42.
Ruiz-Núñez B, Dijck-Brouwer DA, Muskiet FA. The relation of saturated fatty acids with low-grade inflammation and cardiovascular disease. J Nutr Biochem. 2016;36:1–20.
Centers for disease control and prevention. Trends in intake of energy and macronutrients: United States, 1971–2000. Morb Mortal Wkly Rep. 2004;53(4):80–2.
Dickinson S, Hancock DP, Petocz P, Ceriello A, Brand-Miller J. High-glycemic index carbohydrate increases nuclear factor-kappaB activation in mononuclear cells of young, lean healthy subjects. Am J Clin Nutr. 2008;87(5):1188–93.
Buyken AE, Goletzke J, Joslowski G, Felbick A, Cheng G, Herder C, et al. Association between carbohydrate quality and inflammatory markers: systematic review of observational and interventional studies. Am J Clin Nutr. 2014;99(4):813–33.
Ruiz-Núñez B, Kuipers RS, Luxwolda MF, De Graaf DJ, Breeuwsma BB, Dijck-Brouwer DAJ, et al. Saturated fatty acid (SFA) status and SFA intake exhibit different relations with serum total cholesterol and lipoprotein cholesterol: a mechanistic explanation centered around lifestyle-induced low-grade inflammation. J Nutr Biochem. 2014;25(3):304–12.
Wärnberg J, Nova E, Romeo J, Moreno LA, Sjöström M, Marcos A. Lifestyle-related determinants of inflammation in adolescence. Br J Nutr. 2007;98(S1):S116–S20.
Jeukendrup AE, Saris WH, Wagenmakers AJ. Fat metabolism during exercise: a review--part II: regulation of metabolism and the effects of training. Int J Sports Med. 1998;19(5):293–302.
Kelly DM, Jones TH. Testosterone: a metabolic hormone in health and disease. J Endocrinol. 2013;217(3):R25–45.
Cleland I, Kikhia B, Nugent C, Boytsov A, Hallberg J, Synnes K, et al. Optimal placement of accelerometers for the detection of everyday activities. Sensors (Basel, Switzerland). 2013;13(7):9183–200.
Reed D, McGee D, Yano K, Hankin J. Diet, blood pressure, and multicollinearity. Hypertension (Dallas, Tex : 1979). 1985;7(3 Pt 1):405–10.
The authors thank all the families for their participation in the GINIplus and LISA studies. Furthermore, we thank all members of the GINIplus and LISAplus Study Groups for their excellent work. The GINIplus and LISA Study Groups consist of the following: Helmholtz Zentrum München, German Research Center for Environmental Health, Institute of Epidemiology I, Neuherberg (Heinrich J, Brüske I, Schulz H, Flexeder C, Zeller C, Standl M, Schnappinger M, Sußmann M, Lohr W, Thiering E, Tiesler C); Department of Pediatrics, Marien-Hospital, Wesel (Berdel D, von Berg A, Stiers G, Maas B); Helmholtz Centre of Environmental Research UFZ, Department of Environmental Immunology/Core Facility Studies, Leipzig (Lehmann I, Bauer M, Röder S, Schilde M, Nowak M, Herberth G, Müller J, Hain A); Municipal Hospital “St. Georg”, Department of Pediatrics, Leipzig (Borte M, Gnodtke E); Ludwig Maximilians-University of Munich, Dr. von Hauner Children’s Hospital (Koletzko S); Technical University Munich: Clinical Research Group Molecular Dermatology, Department of Dermatology and Allergy (Ollert M), Department of Pediatrics (Hoffmann U, Paschke M, Marra S), Child and Adolescent Medicine, University Hospital rechts der Isar (Bauer CP, Hoffmann U); Pediatric Practice, Bad Honnef (Schaaf B); IUF- Environmental Health Research Institute, Düsseldorf (Schikowski T, Link E, Klümper C).
The 15-year follow-up examination of the GINIplus and LISA studies was supported by the Commission of the European Communities, the 7th Framework Program: MeDALL project. The 15-year follow-up examination of the GINIplus study was additionally supported by the Mead Johnson and Nestlé companies. The aforementioned funding sources had no involvement in the design of the study, collection, analysis and interpretation of data, writing of the report and decision to submit the article for publication.
Ethics approval and consent to participate
For both the GINIplus and LISA studies, approval by the local ethics committees (Bavarian Board of Physicians, University of Leipzig, Board of Physicians of North-Rhine-Westphalia) and written consent from participant’s families were obtained.
Consent for publication
Tamara Schikowski is an Associate Editor for BMC Public Health. None of the other authors have any competing interests.
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Additional file 1:
Figure S1. Study Participants. (PDF 188 kb)
Additional file 2:
Table S1. Associations between SFA and hsCRP categories stratified by tertiles of PA (Sedentary and Light). (PDF 189 kb)
Rights and permissions
Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
About this article
Cite this article
Harris, C.P., von Berg, A., Berdel, D. et al. Dietary saturated fat and low-grade inflammation modified by accelerometer-measured physical activity in adolescence: results from the GINIplus and LISA birth cohorts. BMC Public Health 19, 818 (2019). https://doi.org/10.1186/s12889-019-7113-6
- Dietary intake
- Low-grade inflammation
- Saturated fat
- Physical activity