The relationship between supermarket nutrient movements and the mortality rates from fat-associated and non-fat-associated cardiovascular disease: Development of an ecologic method for determining community food patterns

Supermarket nutrient movement, a community food consumption measure, aggregated 1,023 high-fat foods, representing 100% of visible fats and approximately 44% of hidden fats in the food supply (FAO, 1980). Fatty acid and cholesterol content of foods shipped from the warehouse to 47 supermarkets located in the Houston area were calculated over a 6 month period. These stores were located in census tracts with over 50% of a given ethnicity: Hispanic, black non-Hispanic, or white non-Hispanic. Categorizing the supermarket census tracts by predominant ethnicity, significant differences were found by ANOVA in the proportion of specific fatty acids and cholesterol content of the foods examined. Using ecological regression, ethnicity, income, and median age predicted supermarket lipid movements while residential stability did not. No associations were found between lipid movements and cardiovascular disease mortality, making further validation necessary for epidemiological application of this method. However, it has been shown to be a non-reactive and cost-effective method appropriate for tracking target foods in populations of groups, and for assessing the impact of mass media nutrition education, legislation, and fortification on community food and nutrient purchase patterns. ^

Selection of body fat distribution indices in adults and associations with plasma lipid metabolism variables

Body fat distribution is a cardiovascular health risk factor in adults. Body fat distribution can be measured through various methods including anthropometry. It is not clear which anthropometric index is suitable for epidemiologic studies of fat distribution and cardiovascular disease. The purpose of the present study was to select a measure of body fat distribution from among a series of indices (those traditionally used in the literature and others constructed from the analysis) that is most highly correlated with lipid-related variables and is independent of overall fatness. Subjects were Mexican-American men and women (N = 1004) from a study of gallbladder disease in Starr County, Texas. Multivariate associations were sought between lipid profile measures (lipids, lipoproteins, and apolipoproteins) and two sets of anthropometric variables (4 circumferences and 6 skinfolds). This was done to assess the association between lipid-related measures and the two sets of anthropometric variables and guide the construction of indices.^ Two indices emerged from the analysis that seemed to be highly correlated with lipid profile measures independent of obesity. These indices are: 2*arm circumference-thigh skinfold in pre- and post-menopausal women and arm/thigh circumference ratio in men. Next, using the sum of all skinfolds to represent obesity and the selected body fat distribution indices, the following hypotheses were tested: (1) state of obesity and centrally/upper distributed body fat are equally predictive of lipids, lipoproteins and apolipoproteins, and (2) the correlation among the lipid-related measures is not altered by obesity and body fat distribution.^ With respect to the first hypothesis, the present study found that most lipids, lipoproteins and apolipoproteins were significantly associated with both overall fatness and anatomical location of body fat in both sex and menopausal groups. However, within men and post-menopausal women, certain lipid profile measures (triglyceride and HDLT among post-menopausal women and apos C-II, CIII, and E among men) had substantially higher correlation with body fat distribution as compared with overall fatness.^ With respect to the second hypothesis, both obesity and body fat distribution were found to alter the association among plasma lipid variables in men and women. There was a suggestion from the data that the pattern of correlations among men and post-menopausal women are more comparable. Among men correlations involving apo A-I, HDLT, and HDL$\sb2$ seemed greatly influenced by obesity, and A-II by fat distribution; among post-menopausal women correlations involving apos A-I and A-II were highly affected by the location of body fat.^ Thus, these data point out that not only can obesity and fat distribution affect levels of single measures, they also can markedly influence the pattern of relationship among measures. The fact that such changes are seen for both obesity and fat distribution is significant, since the indices employed were chosen because they were independent of one another. ^

Growth and development of body fat distribution from skinfold measurements: Longitudinal principal components

Longitudinal principal components analyses on a combination of four subcutaneous skinfolds (biceps, triceps, subscapular and suprailiac) were performed using data from the London Longitudinal Growth Study. The main objectives were to discover at what age during growth sex differences in body fat distribution occur and to see if there is continuity in body fatness and body fat distribution from childhood into the adult status (18 years). The analyses were done for four age sectors (3mon-3yrs, 3yrs-8yrs, 8yrs-18yrs and 3yrs-18yrs). Longitudinal principal component one (LPC1) for each age interval in both sexes represents the population mean fat curve. Component two (LPC2) is a velocity of fatness component. Component three (LPC3) in the 3mon-3yrs age sector represents infant fat wave in both sexes. In the next two age sectors component three in males represents peaks and shifts in fat growth (change in velocity), while in females it represents body fat distribution. Component four (LPC4) in the same two age sectors is a reversal in the sexes of the patterns seen for component three, i.e., in males it is body fat distribution and in females velocity shifts. Components five and above represent more complicated patterns of change (multiple increases and decreases across the age interval). In both sexes there is strong tracking in fatness from middle childhood to adolescence. In males only there is also a low to moderate tracking of infant fat with middle to late childhood fat. These data are strongly supported in the literature. Several factors are known to predict adult fatness among the most important being previous levels of fatness (at earlier ages) and the age at rebound. In addition we found that the velocity of fat change in middle childhood was highly predictive of later fatness (r $\approx -$0.7), even more so than age at rebound (r $\approx -$0.5). In contrast to fatness (LPC1), body fat distribution (LPC3-LPC4) did not track well even though significant components of body fat distribution occur at each age. Tracking of body fat distribution was higher in females than males. Sex differences in body fat distribution are non existent. Some sex differences are evident with the peripheral-to-central ratios after age 14 years. ^

The heart challenge: The effect of regular aerobic exercise on body fat distribution in third and fourth grade school children: A randomized clinical trial

The pattern of body fat distribution known as "centralized", and characterized by a predominance of subcutaneous fat on the trunk and a "pot belly", has been associated with an increased risk of chronic disease. These patterns of fat distribution, as well as the lifestyle habit variables associated with adult fatness and chronic morbidity clearly begin to develop during childhood, indicating the need for intervention and primary prevention of obesity, particularly the centralized form, during childhood or adolescence. The purpose of this study was to determine whether regular aerobic exercise could beneficially alter the distribution of body fat in 8 and 9 year old children. One hundred and eighty-eight participants were randomized into either a regular aerobic exercise treatment group or a standard physical education program control group. A variety of aerobic activities was used for intervention 5 days per week during physical education class for a period of 12 weeks. Fat distribution was measured by a number of the most commonly used indices, including ratios of body circumferences and skinfolds and indices derived from a principal components analysis. Change over time in average pulse rate was used to determine if intervention actually occurred. Approximately 10% of the students were remeasured, allowing the calculation of intra- and interexaminer measurement reliability estimates for all indices.^ This study group was comparable to the U.S. population, though the study children were slightly larger for certain measures. No effect of the exercise intervention was found. The most likely explanation for this was inadequacy of the intervention, as indicated by the lack of any change in average pulse rate with treatment. The results of the measurement reliability analysis are reported and indicate that body circumference ratios are more precise than skinfold ratios, particularly when multiple observers are used. Reliability estimates for the principal component indices were also high.^ It remains unclear whether the distribution of body fat can be altered with exercise. It is likely that this issue will remain undecided until one highly reliable, valid, and sensitive measure of fat distribution can be found. ^

Acceleration of the PanIN Development in Mice Expressing Oncogenic K-Ras Due to a High Fat Diet

Obesity is postulated to be one of the major risk factors for pancreatic cancer, and recently it was indicated that an elevated body mass index (BMI correlates strongly with a decrease in patient survival. Despite the evident relationship, the molecular mechanisms involved are unclear. Oncogenic mutation of K-Ras is found early and is universal in pancreatic cancer. Extensive evidence indicates oncogenic K-Ras is not entirely active and it requires a triggering event to surpass the activity of Ras beyond the threshold necessary for a Ras-inflammation feed-forward loop. We hypothesize that high fat intake induces a persistent low level inflammatory response triggering increased K-Ras activity and that Cox-2 is essential for this inflammatory reaction. To determine this, LSL-K-Ras mice were crossed with Ela-CreER (Acinar-specific) or Pdx-1-Cre (Pancreas-specific) to “knock-in” oncogenic K-Ras. Additionally, these animals were crossed with Cox-2 conditional knockout mice to access the importance of Cox-2 in the inflammatory loop present. The mice were fed isocaloric diets containing 60% energy or 10% energy from fat. We found that a high fat diet increased K-Ras activity, PanIN formation, and fibrotic stroma significantly compared to a control diet. Genetic deletion of Cox-2 prevented high fat diet induced fibrosis and PanIN formation in oncogenic K-Ras expressing mice. Additionally, long term consumption of high fat diet, increased the progression of PanIN lesions leading to invasive cancer and decreased overall survival rate. These findings indicate that a high fat diet can stimulate the activation of oncogenic K-Ras and initiate an inflammatory feed forward loop requiring Cox-2 leading to inflammation, fibrosis, and PanINs. This mechanism could explain the relationship between a high fat diet and elevated risk for pancreatic cancer.

Density of alkyl esters and its mixtures

Biodiesel density is a key parameter in biodiesel simulations and process development. In this work we selected, evaluated and improved two density models, one theoretical (Rackett-Soave) and one empirical (Lapuerta's method) for methanol based biodiesels (FAME) and ethanol based biodiesel (FAEE). For this purpose, biodiesel was produced from vegetable oils (sunflower, rapeseed, soybean, olive, safflower and other two commercial mixtures of vegetable oils) and animal fats (edible and crude pork fat and beef tallow) using both methanol and ethanol for the transesterification reactions, and blended to get 21 FAME and 21 FAEE, reporting their density and detailed composition. Bibliographic data have also been used. The Rackett-Soave method has been improved by the use of a new acentric factor correlation, whereas the parameters of the empirical one are improved by considering a bigger density data bank. Results show that the evaluated models could be used to estimate the biodiesel density with a good grade of accuracy but the performed modifications improve the accuracy of the models: ARD (%) for FAME; 0.33, and FAEE; 0.26, both calculated with the modification of Rackett-Soave method and ARD (%) for FAME; 0.40 calculated with the modification of the Lapuerta's method).