The Contribution of Dietary Composition Over 25 Years to Cardiovascular Risk Factors in Childhood and Adulthood: The Princeton Lipid Research Study

Objectives Our goal was to examine the relationship between diet quality, cardiovascular disease risk, and changes in diet quality over time. We hypothesized that diets lacking in nutrients for ideal cardiovascular health would be conserved from childhood to adulthood. This would be reflected as increased rates of hypertension, diabetes, dyslipidemia, and obesity. Methods Diet data was analyzed from the Princeton Lipid Research study (24 hour recall in the 70’s; Block Food Frequency Questionnaire in 1998). Diet quality at each visit was assessed as a ranking of 15 different macro/micronutrients and by a modified Dietary Approaches to Stop Hypertension (DASH) index based on 9 nutrient targets and adapted for children. Outcomes for childhood/adulthood included: glucose intolerance/diabetes, high blood pressure/hypertension (HTN), dyslipidemia/hyperlipidemia (HLD), and obesity. Linear and logistic regression models were performed with adjustment for age, race, sex, body mass index, occupation and education of self or head of household, and marital status. Results Analysis included 221 total individuals in Generation 1 (parents at initial visit; 39% male, mean age 38.9 ± 6.5 followed up at 66.6 ± 6.6 years) and 606 individuals in Generation 2 (45% male, mean age 11.9 ± 3.23 at initial visit and 38.5 ± 3.6 years at follow up). Generation 1 increased in total DASH score from initial visit to follow-up (1.74 ± 0.95 → 2.11 ± 1.33) while Generation 2 decreased (1.91 ± 0.80 → 1.64 ± 1.13). Overall DASH score was not significantly associated with baseline or follow up outcomes in childhood or adulthood. However, in Generation 2 at follow-up, fiber, potassium, iron, niacin, and vitamin A were associated with HTN; fiber, potassium, and sugar with HLD; cholesterol with obesity; and saturated fat with diabetes in Generation 1. Conclusions Overall diet quality was poor in both generations and changed little over time. No relationship was detected between DASH diet accordance and disease outcomes, however certain nutrients are associated with and may contribute to higher cardiovascular disease risk. Funding Sources Supported by the NIH grant for the University of Cincinnati's Medical Student Summer Research Program.

Lipids Composition in Plant Membranes

The paper focuses on the selected plant lipid issues. Classification, nomenclature, and abundance of fatty acids was discussed. Then, classification, composition, role, and organization of lipids were displayed. The involvement of lipids in xantophyll cycle and glycerolipids synthesis (as the most abundant of all lipid classes) were also discussed. Moreover, in order to better understand the biomembranes remodeling, the model (artificial) membranes, mimicking the naturally occurring membranes are employed and the survey on their composition and application in different kind of research was performed. High level of lipids remodeling in the plant membranes under different environmental conditions, e.g., nutrient deficiency, temperature stress, salinity or drought was proved. The key advantage of lipid research was the conclusion that lipids could serve as the markers of plant physiological condition and the detailed knowledge on lipids chemistry will allow to modify their composition for industrial needs.

Lipid Metabolism in Plants

In plants, lipids function in a variety of ways. Lipids are a major component of biological membranes and are used as a compact energy source for seed germination. Fatty acids, the major lipids in plants, are synthesized in plastid and assembled by glycerolipids or triacylglycerols in endoplasmic reticulum. The metabolism of fatty acids and triacylglycerols is well studied in most Arabidopsis model plants by forward and reverse genetics methods. However, research on the diverse functions of lipids in plants, including various crops, has yet to be completed. The papers of this Special Issue cover the core of the field of plant lipid research on the role of galactolipids in the chloroplast biogenesis from etioplasts and the role of acyltransferases and transcription factors involved in fatty acid and triacylglycerol synthesis. This information will contribute to the expansion of plant lipid research.

Adjusting for adherence in randomized trials when adherence is measured as a continuous variable: An application to the Lipid Research Clinics Coronary Primary Prevention Trial

Background: Clinicians and patients may be more interested in per-protocol effect estimates than intention-to-treat effect estimates from randomized trials. However, per-protocol effect estimates may be biased due to insufficient adjustment for prognostic factors that predict adherence. Adjustment for this bias is possible when appropriate methods, such as inverse probability weighting, are used. But, when adherence is measured as a continuous variable, constructing these weights can be challenging. Methods: In the placebo arm of the Lipid Research Clinics Coronary Primary Prevention Trial, we estimated the 7-year cumulative incidence of coronary heart disease under 100% adherence and 0% adherence to placebo. We used dose-response discrete-hazards models with inverse probability weighting to adjust for pre- and post-randomization covariates. We considered several continuous distributions for constructing the inverse probability weights. Results: The risk difference estimate for 100% adherence compared with 0% adherence ranged from −7.7 to −6.1 percentage points without adjustment for baseline and post-baseline covariates, and ranged from −1.8 to 2.2 percentage points with adjustment using inverse probability weights, depending on the dose-response model and inverse probability weight distribution used. Conclusions: Methods which appropriately adjust for time-varying post-randomization variables can explain away much of the bias in the “effect” of adherence to placebo. When considering continuous adherence, investigators should consider several models as estimates may be sensitive to the model chosen.