Under-reporting of food consumption is a recurrent challenge for nutrition surveys. Past research suggests that under-reporting tends to be most pronounced among overweight and obese people.
Data from 16,190 respondents to the 2004 Canadian Community Health Survey (CCHS 2.2)-Nutrition were used to estimate underreporting of food intake for the population aged 12 or older in the 10 provinces. Multiple linear regression models were used to assess the impact of different characteristics on underreporting.
Average under-reporting of energy intake was estimated at 10%. Under-reporting was greater among people who were overweight or obese, those who were physically active, adults compared with teenagers, and women compared with men.
Under-reporting of energy intake is not random and varies by key health determinants. Awareness of the characteristics associated with under-reporting is important for users of nutrition data from the CCHS 2.2.
Under-reporting is common in nutrition surveys. The identification of plausible respondents is a way of measuring the impact of under-reporting on the relationship between energy intake and body mass index (BMI).
A 24-hour dietary recall from 16,190 respondents aged 12 or older to the Canadian Community Health Survey (CCHS)--Nutrition was used to determine energy and nutrient intake. To identify plausible respondents, a confidence interval was applied to total energy expenditure derived from equations developed by the Institute of Medicine. Estimates of energy and nutrient intake for plausible respondents were compared with estimates for all respondents. Linear regression was used to demonstrate the impact of under-reporting on the relationship between reported energy intake and weight. Logistic regression was used to determine the impact of under-reporting on modelling the characteristics of obese people.
With a confidence interval of 70% to 142% around energy expenditure, 57% of CCHS respondents were identified as "plausible respondents". Nutrient under-reporting varied between 1% and 10%. Analysis based only on plausible respondents re-establishes the theoretical relationship between energy intake and body weight, a relationship that is lost when analysis is based on the full sample.
Identifying plausible respondents is an effective way of measuring the impact of under-reporting food intake. Conclusions based on plausible respondents, rather than on all respondents, are more in line with theoretical expectations, such as a positive association between high energy intake and obesity.