Performance of a short tool to assess dietary intakes of fruits and vegetables, percentage energy from fat and fibre

Risk Factor Surveillance and Methodology Branch, Applied Research Program, Division of Cancer Control and Population Sciences, National Cancer Institute, EPN 4016, 6130 Executive Blvd, MSC 7344, Bethesda, MD 20892-7344, USA.
Public Health Nutrition (Impact Factor: 2.68). 01/2005; 7(8):1097-105. DOI: 10.1079/PHN2004642
Source: PubMed


We describe the methods used to develop and score a 17-item 'screener' designed to estimate intake of fruit and vegetables, percentage energy from fat and fibre. The ability of this screener and a food-frequency questionnaire (FFQ) to measure these exposures is evaluated.
Using US national food consumption data, stepwise multiple regression was used to identify the foods to be included on the instrument; multiple regression analysis was used to develop scoring algorithms. The performance of the screener was evaluated in three different studies. Estimates of intakes measured by the screener and the FFQ were compared with true usual intake based on a measurement error model.
US adult population.
For development of instrument, n=9323 adults. For testing of instrument, adult men and women in three studies completing multiple 24-hour dietary recalls, FFQ and screeners, n=484, 462 and 416, respectively.
Median recalled intakes for examined exposures were generally estimated closely by the screener. In the various validation studies, the correlations between screener estimates and estimated true intake were 0.5-0.8. In general, the performances of the screener and the full FFQ were similar; estimates of attenuation were lower for screeners than for full FFQs.
When coupled with appropriate reference data, the screener approach described may yield useful estimates of intake, for both surveillance and epidemiological purposes.

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Available from: Frances E Thompson
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    • "The conceptual framework presented in Fig. 2shows the relationship between personal and environmental variables and behavior. Fat intake was assessed using six items from the NCI fat screener developed by Thompson and colleagues[43]. Items included regular fat sausage or bacon; regular fat cheese or cheese spread; French fries or hash browns; regular fat mayonnaise; regular fat salad dressings; and margarine, butter, or oil. Response options ranged from never or less than once per month to five or more times per week. "
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    ABSTRACT: Background: Dietary behaviors are influenced by many individual and environmental factors. This study explores how dietary fat intake in high-risk midlife adults living in the rural south is influenced by three behavior settings, i.e. in the home, at work, and at church. Methods: Self-report data were collected from rural African American or Caucasian adults age 40-70 at three time points at baseline, 6, and 12 months post baseline. Multilevel analyses investigated the impact of determinants of fat intake over time. Results: Home and work environments varied significantly over time in regard to healthy eating while church environments remained stable. Age, gender, and self-efficacy for healthy eating were individual factors associated with fat intake. In the home, presence of more high fat items, a time-varying variable, was significant. In the work environment, having access to healthy foods as well as healthy eating programs has positive impact as did hearing healthy eating messages and availability of healthy foods at church. Conclusions: Understanding stability and variability of dietary fat intake from a social ecologic perspective will aid in identifying targets of change for intervention. Understanding which components of key behavior settings are dynamic and which are relatively stable will help to disentangle the complexity of multi-level determinants of dietary behavior.
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    • "Questionnaire data included demographics, medical history, medication use, and fasting and smoking status. The National Cancer Institute's 18-item Five-Factor Screener was used to assess dietary intake (Thompson et al., 2004). An OMRON HEM-907XL automatic inflation sphygmomanometer, portable stadiometer, Tanita body fat analyzer (Model TBF- 310T), and Cholestech LDX lipid analyzer were used to measure BP, height, weight and body composition, and nonfasting cholesterol and glucose, respectively. "
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    ABSTRACT: The objective of this secondary analysis was to evaluate the utility of several participant adherence indicators for predicting changes in clinical, anthropometric, dietary, fitness, and physical activity (PA) outcomes in a lifestyle intervention, HUB City Steps, conducted in a southern, African American cohort in 2010. HUB City Steps was a 6-month, community-engaged, multicomponent, noncontrolled intervention targeting hypertension risk factors. Descriptive indicators were constructed using two participant adherence measures, education session attendance (ESA) and weekly steps/day pedometer diary submission (PDS), separately and in combination. Analyses, based on data from 269 primarily African American adult participants, included bivariate tests of association and multivariable linear regression to determine significant relationships between seven adherence indicators and health outcome changes, including clinical, anthropometric, dietary, fitness, and PA measures. ESA indicators were significantly correlated with four health outcomes: body mass index (BMI), fat mass, low-density lipoprotein (LDL), and PA (-.29 ≤ r ≤ .23, p < .05). PDS indicators were significantly correlated with PA (r = .27, p < .001). Combination ESA/PDS indicators were significantly correlated with five health outcomes: BMI, percentage body fat (%BF), fat mass, LDL, and PA (r = -.26 to .29, p < .05). Results from the multivariate models indicated that the combination ESA/PDS indicators were the most significant predictors of changes for five outcomes-%BF, fat mass, LDL diastolic blood pressure (DBP), and PA-while ESA performed best for BMI only. For DBP, a one-unit increase in the continuous-categorical ESA/PDS indicator resulted in 0.3 mm Hg decrease. Implications for assessing participant adherence in community-based, multicomponent lifestyle intervention research are discussed.
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    • "Items will be used to assess frequency of food intake in 16 broad categories to estimate intakes of fruits and vegetables, percentage energy from fat, and fiber diets [81]. "
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