Reply to E Archer and SN Blair

Dietary patterns related to zinc and polyunsaturated fatty acids intake are associated with serum linoleic/dihomo-γ-linolenic ratio in NHANES males and females

Identifying dietary patterns that contribute to zinc (Zn) and fatty acids intake and their biomarkers that may have an impact on health of males and females. The present study was designed to (a) extract dietary patterns with foods that explain the variation of Zn and PUFAs intake in adult men and women; and (b) evaluate the association between the extracted dietary patterns with circulating levels of serum dihomo-γ-linolenic fatty acid (DGLA) or serum linoleic/dihomo-γ-linolenic (LA/DGLA) ratio in males and females. We used reduced rank regression (RRR) to extract the dietary patterns separated by sex in the NHANES 2011-2012 data. A dietary pattern with foods rich in Zn (1st quintile = 8.67 mg/day; 5th quintile = 11.11 mg/day) and poor in PUFAs (5th quintile = 15.28 g/day; 1st quintile = 18.03 g/day) was found in females (S-FDP2) and the same pattern, with foods poor in PUFAs (5th quintile = 17.6 g/day; 1st quintile = 20.7 g/day) and rich in Zn (1st quintile = 10.4 mg/day; 5th quintile = 12.9 mg/day) (S-MDP2), was found in males. The dietary patterns with foods rich in Zn and poor in PUFAs were negatively associated with serum LA/DGLA ratio. This is the first study to associate the LA/DGLA ratio with Zn and PUFAs related dietary patterns in males and females.

Obesity does not modulate men's eating behavior after a high intensity interval exercise session: an exercise trial

BACKGROUND

We investigated the impact of obesity on responses to high intensity interval exercise (HIIE) on hunger and energy intake (EI) in young men.

METHODS

Ten men with obesity (OB) (Body Mass Index [BMI]: 34.6±4.4 kg/m²) and 10 with normal weight (CG) (BMI: 23.1±3.9 kg/m²) participated in a HIIE session. The session consisted of 6 rounds performed at 100% of maximum aerobic velocity (MAV) for 30 seconds, followed by 30 seconds of active recovery at 50% MAV and concluded with 4 minutes of passive recovery. This was repeated three times. EI was estimated at baseline and 24 h-post-HIIE. Hunger was measured at baseline, 2 h- and 24 h-post HIIE.

RESULTS

Carbohydrate (CHO) intake increased in both groups (P<0.01). Hunger feelings (19.5 [0-50] mm at baseline to 50 [9-73] mm post-2 h and 60 [8-92] mm in post-24 h [group: P=0.71, time: P<0.01, group × time: P=0.06]) and a desire to eat (34 [1-89] ±36.0 mm at baseline to 63 [11-86] mm post-2 h and 51 [7-84] mm post-24 h [group: P=0.65, time: P<0.01, group × time: P=0.29]) increased in both groups.

CONCLUSIONS

Weight status does not modulate hunger and EI post-HIIE. However, the compensatory increase in CHO intake and hunger feelings is particularly noteworthy for health professionals.

Energy Intake Derived from an Energy Balance Equation, Validated Activity Monitors, and Dual X-Ray Absorptiometry Can Provide Acceptable Caloric Intake Data among Young Adults

Background

Assessments of energy intake (EI) are frequently affected by measurement error. Recently, a simple equation was developed and validated to estimate EI on the basis of the energy balance equation [EI = changed body energy stores + energy expenditure (EE)].

Objective

The purpose of this study was to compare multiple estimates of EI, including 2 calculated from the energy balance equation by using doubly labeled water (DLW) or activity monitors, in free-living adults.

Methods

The body composition of participants (n = 195; mean age: 27.9 y; 46% women) was measured at the beginning and end of a 2-wk assessment period with the use of dual-energy X-ray absorptiometry. Resting metabolic rate (RMR) was calculated through indirect calorimetry. EE was assessed with the use of the DLW technique and an arm-based activity monitor [Sensewear Mini Armband (SWA); BodyMedia, Inc.]. Self-reported EI was calculated by using dietitian-administered 24-h dietary recalls. Two estimates of EI were calculated with the use of a validated equation: quantity of energy stores estimated from the changes in fat mass and fat-free mass occurring over the assessment period plus EE from either DLW or the SWA. To compare estimates of EI, reporting bias (estimated EI/EE from DLW × 100) and Goldberg ratios (estimated EI/RMR) were calculated.

Results

Mean ± SD EEs from DLW and SWA were 2731 ± 494 and 2729 ± 559 kcal/d, respectively. Self-reported EI was 2113 ± 638 kcal/d, EI derived from DLW was 2723 ± 469 kcal/d, and EI derived from the SWA was 2720 ± 730 kcal/d. Reporting biases for self-reported EI, DLW-derived EI, and SWA-derived EI are as follows: -21.5% ± 22.2%, -0.7% ± 18.5%, and 0.2% ± 20.8%, respectively. Goldberg cutoffs for self-reported EI, DLW EI, and SWA EI are as follows: 1.39 ± 0.39, 1.77 ± 0.38, and 1.77 ± 0.38 kcal/d, respectively.

Conclusions

These results indicate that estimates of EI based on the energy balance equation can provide reasonable estimates of group mean EI in young adults. The findings suggest that, when EE derived from DLW is not feasible, an activity monitor that provides a valid estimate of EE can be substituted for EE from DLW.

Dietary assessment methods in epidemiological research: current state of the art and future prospects

Self-reported dietary intake is assessed by methods of real-time recording (food diaries and the duplicate portion method) and methods of recall (dietary histories, food frequency questionnaires, and 24-hour dietary recalls). Being less labor intensive, recall methods are more frequently employed in nutritional epidemiological investigations. However, sources of error, which include the participants’ inability to fully and accurately recall their intakes as well as limitations inherent in the food composition databases applied to convert the reported food consumption to energy and nutrient intakes, may limit the validity of the generated information. The use of dietary biomarkers is often recommended to overcome such errors and better capture intra-individual variability in intake; nevertheless, it has its own challenges. To address measurement error associated with dietary questionnaires, large epidemiological investigations often integrate sub-studies for the validation and calibration of the questionnaires and/or administer a combination of different assessment methods (e.g. administration of different questionnaires and assessment of biomarker levels). Recent advances in the omics field could enrich the list of reliable nutrition biomarkers, whereas new approaches employing web-based and smart phone applications could reduce respondent burden and, possibly, reporting bias. Novel technologies are increasingly integrated with traditional methods, but some sources of error still remain. In the analyses, food and nutrient intakes always need to be adjusted for total daily energy intake to account for errors related to reporting.

Reliability of 24-Hour Dietary Recalls as a Measure of Diet in African-American Youth

BACKGROUND

Although it is a common practice to estimate dietary intake using three random 24-hour dietary recalls, some studies have suggested up to nine may be necessary to reliably estimate usual intake in youth. Given the resulting increase in resources and participant burden, more research is needed to determine whether this method is reliable, particularly in African-American youth at increased risk for obesity and other chronic diseases.

OBJECTIVE

This study estimated the reliability with which 24-hour dietary recalls measure energy, fat, fruit, and vegetable intake in African-American youth and examined how reliability changes as a function of the number of recalls.

DESIGN

This study used cross-sectional data collection across three studies.

PARTICIPANTS/SETTING

Participants were African-American youth (n=456, mean±standard deviation age 13.28±1.86 years, 64% were girls, mean±standard deviation body mass index [calculated as kg/m(2)] 31.45±7.94) who completed random 24-hour dietary recalls (67% completed three) conducted by research assistants using the Automated Self-Administered 24-Hour recall system (n=258) or registered dietitian nutritionists using the Nutrition Data System for Research (n=198).

MAIN OUTCOME MEASURES/STATISTICAL ANALYSES

Estimates provided by multilevel models were used to calculate the proportion of variance accounted for between individuals and the reliability of means within individuals as a function of the number of recalls.

RESULTS

Reliability estimates for assessing dietary outcomes using one to three recalls ranged from 11% to 62%. To achieve 80% reliability, the following number of recalls would need to be conducted: 8 for energy intake, 13 for fat intake, 21 to 32 for fruit intake, and 21 to 25 for vegetable intake.

CONCLUSIONS

The common practice of assessing dietary intake with three recalls does so with low reliability in African-American youth. Until more objective methods for reliably estimating usual intake are developed, researchers who choose to use 24-hour dietary recalls are encouraged to include estimates of the measure's reliability in a priori power calculations for improved decision making regarding the number of observations and/or sample size.

Perspective: Randomized Controlled Trials Are Not a Panacea for Diet-Related Research

Research into the role of diet in health faces a number of methodologic challenges in the choice of study design, measurement methods, and analytic options. Heavier reliance on randomized controlled trial (RCT) designs is suggested as a way to solve these challenges. We present and discuss 7 inherent and practical considerations with special relevance to RCTs designed to study diet: 1) the need for narrow focus; 2) the choice of subjects and exposures; 3) blinding of the intervention; 4) perceived asymmetry of treatment in relation to need; 5) temporal relations between dietary exposures and putative outcomes; 6) strict adherence to the intervention protocol, despite potential clinical counter-indications; and 7) the need to maintain methodologic rigor, including measuring diet carefully and frequently. Alternatives, including observational studies and adaptive intervention designs, are presented and discussed. Given high noise-to-signal ratios interjected by using inaccurate assessment methods in studies with weak or inappropriate study designs (including RCTs), it is conceivable and indeed likely that effects of diet are underestimated. No matter which designs are used, studies will require continued improvement in the assessment of dietary intake. As technology continues to improve, there is potential for enhanced accuracy and reduced user burden of dietary assessments that are applicable to a wide variety of study designs, including RCTs.