OBJECTIVE: To examine the hypothesis that there is sufficient agreement between percentage of households purchasing selected foods using household budget surveys and percentage of individuals consuming these foods as determined in individual-based surveys to allow the former to act as a surrogate for the latter when estimating food chemical intakes using household budget data. DESIGN: Database study. SETTING: Databases from Sweden, The Netherlands. Ireland and the UK. SUBJECTS: 319 foods (Sweden n = 60, The Netherlands n = 80, Ireland n = 90, UK n = 89). RESULTS: Pearson correlations demonstrated a high degree of linear association between % households purchasing and % consumers (r = 0.86). Regression analysis defined a close positive relationship between the two datasets (slope 0.95, intercept +2.74). Across countries, using the regression equation, the % households predicted % consumers to within 5% of the true value for between 33 and 48% of foods and to within 10% for between 53 and 78% of foods. CONCLUSIONS: Values for % households can be used as a crude surrogate for % consumers and can thus play a role in improving estimates of food additive intake.
OBJECTIVE: To examine the hypothesis that there is sufficient agreement between percentage of households purchasing selected foods using household budget surveys and percentage of individuals consuming these foods as determined in individual-based surveys to allow the former to act as a surrogate for the latter when estimating food chemical intakes using household budget data. DESIGN: Database study. SETTING: Databases from Sweden, The Netherlands. Ireland and the UK. SUBJECTS: 319 foods (Sweden n = 60, The Netherlands n = 80, Ireland n = 90, UK n = 89). RESULTS: Pearson correlations demonstrated a high degree of linear association between % households purchasing and % consumers (r = 0.86). Regression analysis defined a close positive relationship between the two datasets (slope 0.95, intercept +2.74). Across countries, using the regression equation, the % households predicted % consumers to within 5% of the true value for between 33 and 48% of foods and to within 10% for between 53 and 78% of foods. CONCLUSIONS: Values for % households can be used as a crude surrogate for % consumers and can thus play a role in improving estimates of food additive intake.