A novel system for collecting longitudinal self-reported dietary consumption information: the internet data logger (iDL)

A systematic review of dietary data collection methodologies for diet diversity indicators

The purpose of the current study was to critically assess the gaps in the existing methodologies of dietary data collection for diet diversity indicators. The study proposed the importance of smartphone application to overcome the drawbacks. The review paper identified and assessed the conventional methodologies used in diet diversity indicators including Minimum Dietary Diversity for Women (MDD-W), Minimum Dietary Diversity of Infant and Young Child Feeding Practices (IYCF-MDD), and Household Dietary Diversity Score (HDDS). The 80 research studies from 38 countries were critically assessed on the basis of their research aim, study design, target audience, dietary data collection methodology, sample size, dietary data type, dietary data collection frequency, and location point of dietary data collection. Results indicated that most studies employed interviewer-administered 24-h recall assessing the dietary diversity. The review paper concluded that smartphone application had potential to overcome the identified limitations of conventional methodologies including recall bias, social-desirability bias, interviewer training, and cost-time constraints.

Design and Development of 'Diet DQ Tracker': A Smartphone Application for Augmenting Dietary Assessment

The purpose of the current study was to describe the design, development, and validation of the 'Diet DQ Tracker'. The 'Diet DQ Tracker' is the first self-administered smartphone app designed to collect dietary data for diet diversity indicators. The main objective of the app was to replace the traditional methods of dietary data collection, such as in-person or telephone 24 h recall via pen and paper questionnaire or tablets. The real-time meal recording, extensive food database, and automatic score calculations and visualizations for MDD-W, IYCF-MDD, and HDDS have the potential to overcome the drawbacks of 24 h recalls. Recall depends on respondent memory, food expertise, and time consumption and demands skilled interviewers. Further, SAIN, LIM recommendations in the app prompt users to diversify diets with healthy foods. The pilot study determined the acceptability, feasibility, and relative validity of the 'Diet DQ Tracker' with a 24 h dietary recall. The results demonstrated minimal differences in dietary scores by both methodologies. The app, being convenient, easy to use, less time-consuming, and enjoyable, was preferred by the entire study sample over 24 h recall. The app will be continually updated with foods from different cultures for validating in large-scale studies. The future studies will help to improve the subsequent versions of the app.

Comparison of a web-based food record tool and a food-frequency questionnaire and objective validation using the doubly labelled water technique in a Swedish middle-aged population

Two web-based dietary assessment tools have been developed for use in large-scale studies: the Riksmaten method (4-d food record) and MiniMeal-Q (food-frequency method). The aim of the present study was to examine the ability of these methods to capture energy intake against objectively measured total energy expenditure (TEE) with the doubly labelled water technique (TEEDLW), and to compare reported energy and macronutrient intake. This study was conducted within the pilot study of the Swedish CArdioPulmonary bioImage Study (SCAPIS), which included 1111 randomly selected men and women aged 50-64 years from the Gothenburg general population. Of these, 200 were enrolled in the SCAPIS diet substudy. TEEDLW was measured in a subsample (n 40). Compared with TEEDLW, both methods underestimated energy intake: -2·5 (sd  2·9) MJ with the Riksmaten method; -2·3 (sd 3·6) MJ with MiniMeal-Q. Mean reporting accuracy was 80 and 82 %, respectively. The correlation between reported energy intake and TEEDLW was r 0·4 for the Riksmaten method (P < 0·05) and r 0·28 (non-significant) for MiniMeal-Q. Women reported similar average intake of energy and macronutrients in both methods whereas men reported higher intakes with the Riksmaten method. Energy-adjusted correlations ranged from 0·14 (polyunsaturated fat) to 0·77 (alcohol). Bland-Altman plots showed acceptable agreement for energy and energy-adjusted protein and carbohydrate intake, whereas the agreement for fat intake was poorer. According to energy intake data, both methods displayed similar precision on energy intake reporting. However, MiniMeal-Q was less successful in ranking individuals than the Riksmaten method. The development of methods to achieve limited under-reporting is a major challenge for future research.

Development of a web-based survey for monitoring daily health and its application in an epidemiological survey

BACKGROUND

Early detection of symptoms arising from exposure to pathogens, harmful substances, or environmental changes is required for timely intervention. The administration of Web-based questionnaires is a potential method for collecting information from a sample population.

OBJECTIVE

The objective of our study was to develop a Web-based daily questionnaire for health (WDQH) for symptomatic surveillance.

METHODS

We adopted two different survey methods to develop the WDQH: an Internet panel survey, which included participants already registered with an Internet survey company, and the Tokyo Consumers' Co-operative Union (TCCU) Internet survey, in cooperation with the Japanese Consumers' Co-operative Union, which recruited participants by website advertising. The Internet panel survey participants were given a fee every day for providing answers, and the survey was repeated twice with modified surveys and collection methods: Internet Panel Survey I was conducted every day, and Internet Panel Survey II was conducted every 3 days to reduce costs. We examined whether the survey remained valid by reporting health conditions on day 1 over a 3-day period, and whether the response rate would vary among groups with different incentives. In the TCCU survey, participants were given a fee only for initially registering, and health information was provided in return for survey completion. The WDQH included the demographic details of participants and prompted them to answer questions about the presence of various symptoms by email. Health information collected by the WDQH was then used for the syndromic surveillance of infection.

RESULTS

Response rates averaged 47.3% for Internet Panel Survey I, 42.7% for Internet Panel Survey II, and 40.1% for the TCCU survey. During a seasonal influenza epidemic, the WDQH detected a rapid increase in the number of participants with fever through the early aberration reporting system.

CONCLUSIONS

We developed a health observation method based on self-reporting by participants via the Internet. We validated the usefulness of the WDQH by its practical use in syndromic surveillance.

Dietary patterns among the Metro Atlanta Cohort: implications for population-based longitudinal dietary pesticide exposure and risk assessment

Characterizing dietary consumption patterns is critical to dietary pesticide exposure assessment. We compared consumption patterns between adults (age 18-60) in the Metro Atlanta Cohort (MAC), a longitudinal study of pesticide exposure among Atlanta residents, and US National Health and Nutrition Examination Survey (NHANES) adults. We focused on foods commonly eaten by US adults and foods likely to contain certain pesticide residues. MAC participants provided consumption data for 6 days per month for 1 year using a web-based data collection tool. We defined "percent eaters" as the percent of participants who reported eating a particular food in 24 h. We computed the NHANES weighted percent eaters and 95% confidence limits (CLs) using the 24-h dietary recall data. We calculated the MAC percent eaters for each sampling day and the percent of days this number fell below, within, or above the NHANES 95% CLs. We also re-sampled the MAC percent eaters across sampling days to find whether the resulting distribution resembled the NHANES estimate, and used the Kruskal-Wallis test to evaluate whether season affected the number of MAC eaters of a particular food on a given sampling day. In general, across all sampling days, a greater proportion of MAC participants reported eating banana, broccoli, cream, grapes, lettuce, onion, peach, pear, peas, strawberries, string beans, and tomatoes than the national estimate, whereas the proportion of apple, spinach, ketchup and white bread/roll eaters was similar, and the proportion of milk drinkers was lower. Season predicted the number of MAC peach and strawberry eaters but not other foods. The data show how a higher proportion of Atlanta adults may eat certain foods (e.g., peaches in summer or strawberries in spring) than the national average depending on season or other factors. An exposure assessment that ignored this difference could underestimate dietary pesticide intakes.

Comparison between an interactive web-based self-administered 24 h dietary record and an interview by a dietitian for large-scale epidemiological studies

Online self-administered data collection, by reducing the logistic burden and cost, could advantageously replace classical methods based on dietitian's interviews when assessing dietary intake in large epidemiological studies. Studies comparing such new instruments with traditional methods are necessary. Our objective was to compare one NutriNet-Santé web-based self-administered 24 h dietary record with one 24 h recall carried out by a dietitian. Subjects completed the web-based record, which was followed the next day by a dietitian-conducted 24 h recall by telephone (corresponding to the same day and using the same computerised interface for data entry). The subjects were 147 volunteers aged 48–75 years (women 59·2 %). The study was conducted in February 2009 in France. Agreement was assessed by intraclass correlation coefficients (ICC) for foods and energy-adjusted Pearson's correlations for nutrients. Agreement between the two methods was high, although it may have been overestimated because the two assessments were consecutive to one another. Among consumers only, the median of ICC for foods was 0·8 in men and 0·7 in women (range 0·5–0·9). The median of energy-adjusted Pearson's correlations for nutrients was 0·8 in both sexes (range 0·6–0·9). The mean Pearson correlation was higher in subjects ≤ 60 years (P = 0·02) and in those who declared being ‘experienced/expert’ with computers (P = 0·0003), but no difference was observed according to educational level (P = 0·12). The mean completion time was similar between the two methods (median for both methods: 25 min). The web-based method was preferred by 66·1 % of users. Our web-based dietary assessment, permitting considerable logistic simplification and cost savings, may be highly advantageous for large population-based surveys.

Comparison of food consumption frequencies among NHANES and CPES children: implications for dietary pesticide exposure and risk assessment

Characterizing food consumption patterns among children is critical to dietary pesticide exposure assessment. We have used public release data from the US National Health and Nutrition Examination Survey (NHANES) and the longitudinal Children's Pesticide Exposure Study (CPES) to illustrate the magnitude of potential error introduced by using national-scale, cross-sectional data to estimate the consumption frequencies for smaller cohorts. We focused on foods commonly consumed by children in the target CPES age and income group (3-11 years; annual household income >$75,000) and foods likely to contain organophosphorus or pyrethroid pesticide residues. We defined "percent eaters" as the percentage of study participants who reported eating a particular food in a 24-h period. We computed the weighted percent eaters and 95% confidence limits (CL) for the target age/income group using the NHANES 24-h dietary recall data and compared these with the CPES percent eaters by sampling day and season. For certain foods, particularly the seasonally available produce (for example, apples, peaches/nectarines, melon, grapes, pears, strawberries), soy milk, and peanut butter, the CPES percent eaters fell outside the NHANES 95% CLs on many sampling days. For other foods (for example, orange juice and cow's milk), differences were not readily apparent. Although the differences we observed for certain foods may be, in part, because of measurement error, they also likely reflect seasonal and geographic patterns among the CPES data that the public release NHANES data do not capture. Using NHANES data to estimate pesticide intakes from strawberries, for example, may underestimate the exposure of the CPES children, as significantly more CPES than NHANES children ate strawberries on many sampling days. For other sampling days or other foods, overestimation is also possible.