Genetic and environmental factors affecting ultrasound measures of longissimus muscle area and backfat thickness in Nelore cattle

The aim of the present study was to evaluate the genetic and environmental factors affecting records of longissimus muscle area (LMA) and back fat thickness (BF) obtained between the 12th and 13th ribs, and rump fat thickness (RF) between the hook and pin bones, measured by real-time ultrasound in Nelore cattle. Also, weight records of 22,778 animals born from 1998 to 2003, in ten farms across six Brazilian states were used. Carcass traits as measured by ultrasound of the live animal were recorded from 2002 to 2004 in 2590 males and females with ages varying from 450 to 599 days. Fixed models including farm, year and season of birth, sex and type of feed effects, and the covariates age of dam (AOD) and age of animal at measurement were used to study the effect of environmental factors on these traits. The genetic parameters for LMA, BF and RF were estimated with two and three-trait animal models with 120-day weights using a restricted maximum likelihood method. All environmental effects significantly affected carcass traits, with the exception of year of birth for BF and RF and AOD for LMA. The heritability estimates for LMA, BF and RF were 0.35, 0.51 and 0.39, respectively. Standard errors obtained in one-trait analyses were from 0.07 to 0.09. Genetic correlation estimates between LMA and the two traits of subcutaneous fat were low (close to zero) and 0.74 between BF and RF, indicating that the selection for LMA should not cause antagonism in the genetic improvement of subcutaneous fat measured by real-time ultrasound. (C) 2007 Elsevier B.V. All fights reserved.

Evaluation of short dietary questions from the 1995 National Nutrition Survey

Six of the short dietary questions used in the 1995 National Nutrition Survey (see box below) were evaluated for relative validity both directly and indirectly and for consistency, by documenting the differences in mean intakes of foods and nutrients as measured on the 24-hour recall, between groups with different responses to the short questions. 1. Including snacks, how many times do you usually have something to eat in a day including evenings? 2. How many days per week do you usually have something to eat for breakfast? 3. In the last 12 months, were there any times that you ran out of food and couldn’t afford to buy more? 4. What type of milk do you usually consume? 5. How many serves of vegetables do you usually eat each day? (a serve = 1/2 cup cooked vegetables or 1 cup of salad vegetables) 6. How many serves of fruit do you usually eat each day? (a serve = 1 medium piece or 2 small pieces of fruit or 1 cup of diced pieces) These comparisons were made for males and females overall and for population sub-groups of interest including: age, socio-economic disadvantage, region of residence, country of birth, and BMI category. Several limitations to this evaluation of the short questions, as discussed in the report, need to be kept in mind including: · The method for comparison available (24-hour recall) was not ideal (gold standard); as it measures yesterday’s intake. This limitation was overcome by examining only mean differences between groups of respondents, since mean intake for a group can provide a reasonable approximation for ‘usual’ intake. · The need to define and identify, post-hoc, from the 24-hour recall the number of eating occasions, and occasions identified by the respondents as breakfast. · Predetermined response categories for some of the questions effectively limited the number of categories available for evaluation. · Other foods and nutrients, not selected for this evaluation, may have an indirect relationship with the question, and might have shown stronger and more consistent responses. · The number of responses in some categories of the short questions eg for food security may have been too small to detect significant differences between population sub-groups. · No information was available to examine the validity of these questions for detecting differences over time (establishing trends) in food habits and indicators of selected nutrient intakes. By contrast, the strength of this evaluation was its very large sample size, (atypical of most validation studies of dietary assessment) and thus, the opportunity to investigate question performance in a range of broad population sub-groups compared with a well-conducted, quantified survey of intakes. The results of the evaluation are summarised below for each of the questions and specific recommendations for future testing, modifications and use provided for each question. The report concludes with some general recommendations for the further development and evaluation of short dietary questions.