Food sampling strategies for energy intake estimates

Association between Dietary Fat Intake and Odds of Gastro-esophageal Reflux Disorder (GERD) in Iranian Adults

Background

Most information on the association of dietary fat intake and gastro-esophageal reflux disorder (GERD) came from developed countries, where lifestyle and other dietary components might be different from those in developing countries. This cross-sectional study was, therefore, conducted to investigate the association between dietary fat intake and odds of having GERD in a large group of Iranian population.

Study Design

This cross-sectional study was done among 3362 adult population in Isfahan, Iran. Dietary intakes were collected by the use of a validated semi-quantitative food frequency questionnaire.

Methods

Assessment of GERD was done using a validated self-administered questionnaire examining the frequency of heartburn in the last 3 months. Individuals with the presence of heartburn symptoms sometimes, often or always during the last 3 months were defined as having GERD.

Results

Participants in the top category of dietary fat intake had higher daily intakes of energy, macronutrients and micronutrients. Dietary intakes of all food groups were also significantly higher among those in the top quintile as compared with those in the bottom category of dietary fat intake (P < 0.001 for all). There were no significant associations between dietary fat intake and incidence of GERD in general population. Crude and multivariable-adjusted models revealed no significant associations between dietary fat intake and having GERD in either gender.

Conclusions

We found no significant association between dietary fat intake and odds of having GERD in this population. Further studies, in particular of prospective designs, are warranted to clarify this association.

The Validity of US Nutritional Surveillance: USDA's Loss-Adjusted Food Availability Data Series 1971-2010

The purpose of this study was to examine the validity of the 1971-2010 United States Department of Agriculture's (USDA's) loss-adjusted food availability (LAFA) per capita caloric consumption estimates. Estimated total daily energy expenditure (TEE) was calculated for nationally representative samples of US adults, 20-74 years, using the Institute of Medicine's predictive equations with "low-active" (TEE L-ACT) and "sedentary" (TEE SED) physical activity values. TEE estimates were subtracted from LAFA estimates to create disparity values (kcal/d). A validated mathematical model was applied to calculate expected weight change in reference individuals resulting from the disparity. From 1971-2010, the disparity between LAFA and TEE L-ACT varied by 394kcal/d-(P < 0.001), from -205kcal/d (95% CI: -214, -196) to +189kcal/d (95% CI: 168, 209). The disparity between LAFA and TEE SED varied by 412kcal/d (P < 0.001), from -84kcal/d (95% CI: -93, -76) to +328kcal/d (95% CI: 309, 348). Our model suggests that if LAFA estimates were actually consumed, reference individuals would have lost ~1-4kg/y from 1971-1980 (an accumulated loss of ~12 to ~36kg), and gained ~3-7kg/y from 1988-2010 (an accumulated gain of ~42 to ~98kg). These estimates differed from the actual measured increments of 10kg and 9kg in reference men and women, respectively, over the 39-year period. The USDA LAFA data provided inconsistent, divergent estimates of per capita caloric consumption over its 39-year history. The large, variable misestimation suggests that the USDA LAFA per capita caloric intake estimates lack validity and should not be used to inform public policy.

The use of summary statistics for sample size allocation for food composition surveys and an application to the potato group

To give a quantitative guide to sample size allocation for developing sampling designs for a food composition survey, we discuss sampling strategies that consider the importance of each food; namely, consumption or production, variability of composition, and the restrictions within the available resources for sample collection and analysis are considered., Here we consider two strategies: 'proportional' and 'Neyman' are discussed. Both of these incorporate consumed quantity of foods, and we review some available statistics for allocation issues. The Neyman optimal strategy allocates less sample size for starch than proportional, because the former incorporates variability in the composition. Those strategies improved accuracy in dietary nutrient intake more than equal sample size allocation. Those strategies will be useful as we often face sample size allocation problems, wherein we decide whether to sample 'five white potatoes and five taros or nine white and one taros'. Allocating sufficient sample size for important foodstuffs is essential in assuring data quality. Nevertheless, the food composition table should be as comprehensive as possible.

Databases on food phytochemicals and their health-promoting effects

Considerable information on the chemistry and biological properties of dietary phytochemicals has accumulated over the past three decades. The scattering of the data in tens of thousands publications and the diversity of experimental approaches and reporting formats all make the exploitation of this information very difficult. Some of the data have been collected and stored in electronic databases so that they can be automatically updated and retrieved. These databases will be particularly important in the evaluation of the effects on health of phytochemicals and in facilitating the exploitation of nutrigenomic data. The content of over 50 databases on chemical structures, spectra, metabolic pathways in plants, occurrence and concentrations in foods, metabolism in humans and animals, biological properties, and effects on health or surrogate markers of health is reviewed. Limits of these databases are emphasized, and needs and recommendations for future developments are underscored. More investments in the construction of databases on phytochemicals and their effects on health are clearly needed. They should greatly contribute to the success of future research in this field.

Criteria for Optimizing Food Composition Tables in Relation to Studies of Habitual Food Intakes

The purpose of this study is to increase the accuracy, reliability, and precision of food composition data and, in consequence, better approximate nutrient intake estimations and recommendations. To do this it is necessary to specify and taken into account factors that play an important role in the variation of composition in order to avoid excessively broad dispersions and irregularities in data distributions. This implies the presentation of representative and, as consequence, extrapolable data, with nutritionally grounded confidence intervals. This study suggests a methodology that better approaches the accuracy, reliability, and precision of food composition data.

Physical activity and cancer: lessons learned from nutritional epidemiology

Convincing epidemiologic evidence currently exists for an association between physical activity and the prevention of colon and breast cancer Physical activity may also reduce the risk of cancer at several other sites. With increasing research on this topic, it is apparent that studies of physical activity and cancer have numerous methodological similarities with studies of nutrition and cancer Lessons learned from nutritional epidemiology that can be applied to studies of physical activity and cancer prevention and recommendations for future research are discussed in this review.