The Oslo Health Study: A Dietary Index Estimating Frequent Intake of Soft Drinks and Rare Intake of Fruit and Vegetables Is Negatively Associated with Bone Mineral Density

Background. Since nutritional factors may affect bone mineral density (BMD), we have investigated whether BMD is associated with an index estimating the intake of soft drinks, fruits, and vegetables. Methods. BMD was measured in distal forearm in a subsample of the population-based Oslo Health Study. 2126 subjects had both valid BMD measurements and answered all the questions required for calculating a Dietary Index = the sum of intake estimates of colas and non-cola beverages divided by the sum of intake estimates of fruits and vegetables. We did linear regression analyses to study whether the Dietary Index and the single food items included in the index were associated with BMD. Results. There was a consistent negative association between the Dietary Index and forearm BMD. Among the single index components, colas and non-cola soft drinks were negatively associated with BMD. The negative association between the Dietary Index and BMD prevailed after adjusting for gender, age, and body mass index, length of education, smoking, alcohol intake, and physical activity. Conclusion. An index reflecting frequent intake of soft drinks and rare intake of fruit and vegetables was inversely related to distal forearm bone mineral density

Daily intake of cod or salmon for 2 weeks decreases the 18:1n-9/18:0 ratio and serum triacylglycerols in healthy subjects

Intake of fish and omega-3 (n-3) fatty acids is associated with a reduced concentration of plasma triacylglycerols (TAG) but the mechanisms are not fully clarified. Stearoyl-CoA desaturase-1 (SCD1) activity, governing TAG synthesis, is affected by n-3 fatty acids. Peripheral blood mononuclear cells (PBMC) display expression of genes involved in lipid metabolism. The aim of the present study was to estimate whether intake of lean and fatty fish would influence n-3 fatty acids composition in plasma phospholipids (PL), serum TAG, 18:1n-9/18:0 ratio in plasma PL, as well as PBMC gene expression of SCD1 and fatty acid synthase (FAS). Healthy males and females (n = 30), aged 20–40, consumed either 150 g of cod, salmon, or potato (control) daily for 15 days. During intervention docosahexaenoic acid (DHA, 22:6n-3) increased in the cod group (P\0.05), while TAG concentration decreased (P\0.05). In the salmon group both eicosapentaenoic acid (EPA, 20:5n-3) and DHA increased (P\0.05) whereas TAG concentration and the 18:1n-9/ 18:0 ratio decreased (P\0.05). Reduction of the 18:1n-9/ 18:0 ratio was associated with a corresponding lowering of TAG (P\0.05) and an increase in EPA and DHA (P\0.05). The mRNA levels of SCD1 and FAS in PBMC were not significantly altered after intake of cod or salmon when compared with the control group. In conclusion, both lean and fatty fish may lower TAG, possibly by reducing the 18:1n-9/18:0 ratio related to allosteric inhibition of SCD1 activity, rather than by influencing the synthesis of enzyme protei

The inverse association between relative abundances of oleic acid and arachidonic acid is related to alpha-linolenic acid

Background: Many health effects of oils rich in oleic acid (OA, 18:1 n9) seem to be opposite those of arachidonic acid (AA, 20:4 n6), i.e. concerning cardiovascular risk. In recent studies in humans and in the rat we observed that percentages of OA and AA were inversely related, raising the question of whether the inverse association is a general one, and how it might be explained. In the present work we examine whether percentages of OA and AA are inversely associated in breast muscle lipids of chickens, and whether alpha-linolenic acid (ALA) may be related to the OA/AA ratio. Methods: The study group consisted of 163 chickens. Breast muscle was collected, and the concentration of fatty acids in muscle lipids was determined using gas chromatography. We studied association between fatty acids using bivariate correlations (Pearson) and linear regression. Synthesis of OA from stearic acid (Stear) was estimated using the OA/Stear ratio, and formation of AA from linoleic acid (LA) was estimated by the AA/LA ratio. Results: We found a strong inverse relationship (r = -0.942, p < 0.001; n = 163) between % OA and % AA in breast muscle lipids of the chickens. There was an inverse association (r = -0.887, p < 0.001) between the OA/Stearic acid ratio, estimating Delta9 desaturase, and the AA/LA ratio, estimating desaturases/elongase activities. Furthermore, there was a strong negative association between % AA and the OA/Stearic acid ratio (r = -0.925, p < 0.001), and % OA correlated negatively (r = -0.914, p < 0.001) with the AA/LA ratio. ALA was positively associated (r = 0.956, p < 0.001) with the OA/AA ratio, and this association prevailed when controlling for the other fatty acids. ALA was positively associated (r = 0.857, p < 0.001) with the OA/Stear ratio, but was negatively related (r = -0.827, p < 0.001) to the AA/LA ratio. Conclusions: The relative abundances of OA and AA that are inversely related in muscle lipids of chickens may be explained by a feedback regulation between the synthesis of OA and AA, and related to ALA, which seems to stimulate formation of OA, and inhibit synthesis of AA, but further studies are required to clarify whether this hypothesis is valid

Distribution dependent and cluster regulation of associations between body fatty acid percentages, as observed in chickens

publishedVersio

Intended Ranges and Correlations between Percentages of Variables Like Oleic Acid, Eicosapentaenoic Acid, and Arachidonic Acid

In chicken muscle, we previously showed that ranges of oleic acid (OA), arachidonic acid (AA), and eicosapentaenoic acid (EPA) might explain why %OA was inversely related to %AA, and that %EPA correlated positively with %AA. We here try to clarify further how ranges of the fatty acids could make strong associations between their relative amounts, utilizing published data from chicken muscle and human sera. We generated random number variables (OA’, AA’, EPA’) in lieu of the true variables, and we studied effects of altering their ranges upon scatterplots of %OA’ vs. %AA’ (%EPA’), and %AA’ vs. %EPA’. To explain the results, we first applied the equation OA’ + AA’ + EPA’ = S, i.e., %OA’ + %AA’ + %EPA’ = 100. Next, we considered how the OA’ (AA’, EPA’) fractions of S related to S. Increasing the OA’ range towards higher values improved the positive association between %AA’ and %EPA’. Thus, increased intake of OA could improve the positive correlations between percentages of eicosanoid precursors, raising the question of whether “intended ranges” of some fatty acids represent a case of evolutionary selection to, e.g., achieve balance between eicosanoids

Association between Relative Amounts of White Blood Cell Counts: a Case of Distribution Dependent Correlations

We previously observed a positive association between relative amounts of particular body fatty acids, provided they had low-numbers relative to sum of the remaining ones. Additionally, theoretical considerations and computer experiments suggested that, with two high-number variables relative to one with much lower numbers, we should expect a negative relationship between relative amounts of the high-number variables. Moreover, the correlation outcomes with true values could be well reproduced using random numbers, provided that the numbers had the true ranges (distributions). This finding led to the concept of Distribution Dependent Correlations. Since counts of segmented neutrophil leukocytes (N) and lymphocytes (L) are normally much higher than sum of the remaining (R) white blood cells (WBC), it was suggested that %N might possibly be negatively associated with %L. In the present work, random numbers were sampled in lieu of reported WBC subgroup values, but using the measured mean ± SD values. The results demonstrate that relative amounts of random number “N” and “L” were indeed inversely related in both sexes: Spearman’s rho = -0.9, p <0.001, n = 200, as observed using within-person data, and between-person data as well. Furthermore, an alteration in distributions (variability) of the WBC subgroup changed the correlation outcome, as evaluated by scatterplots and correlation coefficients. Decreasing (increasing) values of %R improved (made poorer) the negative association between %N and %L. Thus, the observed negative association between %N and %L seems to be a case of Distribution Dependent Correlations. Hypothetically, by directing WBC subgroup counts to particular places on the scale, a powerful tool is available to govern the associations between relative amounts of WBC subgroups

Associations between %AA (20:4 n6) and Relative Amounts of Other Body Fatty Acids

Body fatty acids are important in health and disease. Previously, we reported a positive association between % AA (20:4 n6) and relative amounts of EPA (20:5 n3) and of some other fatty acids. We now study positive and negative correlations in general between %AA and percentages of other fatty acids, as observed in chicken breast muscle. Two groups of fatty acids were identified: Group 1) with relative amounts correlating negatively with %AA, and Group 2) with relative amounts correlating positively with %AA. With the positive correlations, but not with the negative ones, we obtained similar scatterplots using true and random numbers. This apparent discrepancy is probably related to differences in skewness of the concentration distribution of some fatty acids. Most of Group 2 fatty acids are eicosanoid or docosanoid precursors. The overall correlation outcome may be largely explained by the particular concentration ranges of the fatty acids. We therefore suggest Distribution Dependent Correlations to be an evolutionary regulatory principle, possibly ensuring balance between various eicosanoids and docosanoids

Distribution dependent and cluster regulation of associations between body fatty acid percentages, as observed in chickens

Body fatty acids are important in health and disease. We previously observed two groups of fatty acids in breast muscle of chickens: Group 1) with relative amounts correlating negatively with %AA (20:4 n6), and Group 2) with relative amounts correlating positively with %AA. Within each of the two groups, we here found positive correlations between fatty acid percentages. Accordingly, Group 1 percentages correlated negatively with those of Group 2. With random numbers in lieu of the true values of Group 2 fatty acids, we were able to reproduce the positive correlations found with true values, if the random numbers were generated with the true ranges. In contrast, with random numbers we did not succeed in reproducing all of the negative correlations between Group 1 and Group 2 fatty acid percentages. We then observed that absolute amounts (g/kg) of fatty acids in Group 1 correlated positively and strongly (r > 0.9), suggesting a coordinated regulation of these fatty acids. Thus, Group 1 fatty acids seemed to be a cluster of fatty acids. Random number cluster percentage showed nice inverse associations with random number Group 2 fatty acid percentages, like the outcome observed with the true values. We suggest that associations between fatty acid percentages are caused by their concentration distributions, and by cluster regulation. Distribution Dependent and Cluster Regulation could be an evolutionary adaptation, where a mathematical rule is utilized to e.g. balance effects of eicosanoids/docosanoids, and possibly other metabolites