Introduction: personal digital assistants (PDAs) coupled with camera

Introduction:

New approaches of dietary assessment methods and instruments have been developed and applied to overcome some of the challenges and limitations in dietary assessment. Particularly the growing prominence of internet- and communication technologies has offered new possibilities to address bias and measurement errors inherent in all self-reported dietary intakes as well as organizational and financial issues in study planning and design.

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An evaluation of the potential of these innovative technologies to replace, improve or complement these commonly used dietary assessment methods may therefore help to better assess their usability and possible ‘added value’ in epidemiological studies.

The objective of this article was inventory of some available innovative technologies for dietary assessment and evaluate their reliability and validity in epidemiological studies. Critical evaluation of the suitability of using new dietary assessment tools among Arabic countries and spot the light on the areas for future development to improve exiting tools.

Method:

A structured searches were performed in MEDLINE/PubMed, websites and Internet search engines (e.g. Google Scholar). The following terms were used, separately or in combination: Food/nutrient/dietary intake, food consumption, assessment, technically new, tools, innovative, Mobile, computer-/web-based and digital. The abstracts of the studies identified through searches were scanned and potentially relevant articles were retrieved and data was extracted from articles.

 

Result:

The search was categorized according to the technology applied and to their focus of research. Validation studies compared the new technology to a reference dietary instrument. In total, utilized personal digital assistants (PDAs) coupled with camera or mobile phone as replacement for written food records. Visual methods, where the dietary measurement mainly based on photographs. Smart card based system or bar code scanner originally used for meal payment in cafeteria or for monitoring of food purchases provided dietary data. Computer-based tools and Web-based self-administered FFQ/DQ or 24 HDR were developed and applied in other.

 

1-    PDA technologies:

 

Personal digital assistant-technologies are Hand-held computers that integrate computing and networking features, using stylus and/or keyboard for input. PDA with specifically designed dietary software program can be used to register and self-monitor dietary intake. After having received some face-to-face training, The participant is asked to record dietary intake right after consumption, by selecting food items from  menu of foods and beverages items. Amount consumed is estimated by portion size estimation aids (i.e.  food photographs, picture books or food models and household measures). In others, subjects are instructed to quantify their amounts using traditional food models. Further variable assessment procedures include the assessment of qualitative information of dietary habits (e.g. meal start time and date), food labels with nutritional information of purchased foods and the provision of personalized feedback.1

To assess a PDA-based food record accuracy, compared this method with a 24 h Recalls and an observed lunch in 39 adults of different ethnic backgrounds. No significant differences were found in measuring macronutrient intake & energy. When comparing the data, Pearson correlations for the 24 h Recalls ranged from 0·5 to 0·8 and those for the observed lunch from 0·4 to 0·8. Incorrect estimation of portion sizes (49 %), incorrect foods (25 %), omitting food (15 %), reporting similar but not identical food (9 %) and nutrient database differences (2 %).2

 

PDA with camera and Mobile phone card:

PDA with camera and mobile phone card can be used to record individual dietary intake by taking photos instead of manually recording foods and beverages before and after consumption.  A well-known variant is the Japanese “Wellnavi” instrument, which instructs the users to take digital photos of their foods and drinks before and after consumption and subsequently send them via a mobile phone card to the study dietitians. The validity of Wellnavi instrument was evaluated by comparing nutrient intakes obtained by 1d weighed food records to obtained by this instrument. Of energy and 32 nutrients, researchers found no significant differences with the exception of dietary fiber, PUFA, SFA,  Zn and vitamin E.  Spearman correlation coefficients for 33 nutrients ranged from 0.21 to 0.86 with a mean correlation coefficient of 0.62.  Study participants reported that the Wellnavie instrument was the least burdensome and least time consuming.3  In a different study on 75 of normal weight and obese adults, Wellnavie was compared with 5d weighed food records and the results showed daily nutrient intakes measured with the Wellnavie instrument were significantly lower than the weighed records but significant Spearman correlations (0·32–0·77; mean 0·47).4

 

2-    Digital foods Photography (DFP)

It is similar to the direct observation of food selection and plate waste, but instead of observers, food selection and plate waste are photographed with a digital camera. Plate waste are determined, weighed and photographed at the same angle of participants trays photos for accurate comparison.  These images are later compared with images of ‘standard’ portions of food using computer software.

 

 

 

 

 

 

 

The validity of DFP was tested by comparing direct visual estimation in a laboratory with this tool. 60 meals with different portion sizes from 6 university cafeteria menus were prepared and weighed. The results supported the validity of direct visual observation as well as DFP. Pearson correlations to direct visual estimation (0·95–0·97) were significantly more than DFP (0·89–0·94). Data obtained by both methods showed small underestimates or overestimates.5

The Technology Assisted Dietary Assessment (TADA):

Automated mobile device food records (mdFR) have been developed that integrate camera, video, voice, text, and sophisticated image processing based on images of foods taken before and after eating to automatically identify foods and portion size. This project is funded by National Institutes of Health (NIH).6  It estimates the diet by asking people to capture images of food selection and leftovers by cell or Smartphone. Participants are trained to label images of foods that are difficult recognizable with a concise description (e.g., fried meat). The images are then sent through a wireless network in near real-time to the Food Photography Application ( e.g. SmartIntake ). The Food Photography Application sends the images to server for analysis to estimate food intake by compared to images of foods with a known portion size.  When food images are captured a black and white reference card, which is the size of a credit card, is included in the image . This card allows the computer application to correct and standardize images for color and perspective, allowing participants to eat food from any size plate. A Smartphone-based application has been developed that facilitates the automatic identification of foods via bar code scanning and PLU (Price Look Up) codes.

 

3-    Smart Card

Smart cards can be engaged in other functions as payment for meals. It has certain monetary value that can be spent in restaurants and cafeterias. When the customer pays for a meal using the smart card, the foods on the plate are directly recorded and sent to a central computer. Information can be collected about food choices, date and time, costs and the smart card number. Then the data are stored on the computer and can be connected to a nutrient database.

In study to tested the accuracy & feasibility of the smart card as a tool to assess the eating behavior of 168 school children boys aged 7–11 years were recorded by the smart card system as well as direct observation by researchers in a 65  children, weighing leftover foods. During 10 d, the foods on trays were recorded and the data obtained by both dietary-assessment methods were compared.  The results showed an accuracy rating of 95·9 %. The major error was caused by the smart card recording no information, while the child had really consumed a school meal. Another error was those data recorded by the researcher and smart card were not similar. Data from smart card system provided accurate information about food choice, but not about nutrient intake. 7

4-Computer and Web-based self-administered:

The measurement of dietary intake relied on self-report instruments: 24-hour Dietary Recall , Food Record, Food Frequency Questionnaire but they have high respondent burden, require costly processing, and the resulting data  have degrees of error. To overcome a number of these limitations, several research teams are developing instruments designed to improve accuracy, reduce respondent and researcher burden, and automate the processing of data. These instruments are at varying stages of development and are part of a growing technological toolbox that includes automated versions of 24-hour dietary recalls (24HR), food records, and food frequency questionnaires(FFQ).

24-hour dietary recalls

The National Cancer Institute’s (NCI) Automated Self-Administered 24-Hour Dietary Assessment Tool (ASA24) is an automated, self-administered web-based software tool for collecting 24HRs. This freely available tool provides a complete system for probing, coding, and calculating dietary intake, including foods and supplement.

ASA24 consists of a Respondent application used by participants to enter recall data and a Researcher application used by researchers to manage study logistics and obtain nutrient and food level data. The format and design of the Respondent application are modeled on USDA’s interviewer-administered Automated Multiple Pass Method (AMPM) 24HR, which uses multi-level food probes to assess food types and amounts.  Respondents report their intakes using a list of foods and beverages from USDA’s most current FNDDS. Multiple images are shown to help respondents estimate portion size. ASA24 allows respondents to: 1) find foods and beverages by browsing or searching, 2) edit a meal or correct double reports, 3) review a final list of the day’s intake, and 4) access help. Resulting data files include food codes, nutrients, and MyPyramid food group equivalents for each day and each food, as well as variables to calculate Healthy Eating Index scores. Additional optional modules querying location of meals, who one ate with, TV/computer use during meals, and supplement intake are available.8

In study to assess the relative validity of the ASA24 in middle aged adults, men (n= 60) and women (n= 108) were recruited and randomly assigned using a cross-over design to complete both the internet-based ASA24 and telephone interviewer-administered NDSR assessments. Participants were either emailed or called on randomly selected, unannounced days to complete 1 weekend and 2 weekdays of intake. Relative validity was assessed by Spearman correlation for energy. The ASA24 yielded higher energy intakes (1966 vs. 1853 kcal) with a correlation of 0.67. This study provides inconclusive evidence of the validity of the ASA24 relative to standard telephone methods with relatively high correlations for some nutrients and food groups and low correlations for others. 9

Food Record

The eButton is a wearable button-like sensor system that includes video, global positioning system (GPS) sensor, accelerometer, ultraviolet sensor, and digital compass to assess diet.10 From the acquired pictures, the food portion size can be calculated semi-automatically with the help of computer software. In study  to evaluate the accuracy of the calculated food portion size (volumes) from eButton, the computer-based method provides more objective and accurate estimates of food volume than the visual estimation method.11

Food Frequency Questionnaire

Automated web-based versions of FFQs are available online and through private companies. These tools are extension of their original machine-readable paper and pencil versions (e.g., NCI’s Diet History Questionnaire).  To assess the validity and the reproducibility of web-FFQ, total of 34 men and 40 women were asked to complete, in random order, the web-FFQ, a validated interviewer-administered FFQ (IA-FFQ) and a 3-day FR. Cross-classification analysis revealed that on average, 77% of subjects were classified in the same or adjacent quartile of nutrient take between the web-FFQ and the 3-day FR. Correlation coefficients for reproducibility of the web-FFQ tested 4-6 weeks apart in the same individuals were all equal or above 0.48. . More than 90% of the subjects were classified in the same or adjent quartile between the two administrations of the web-FFQ, while only 0.8% was misclassified. These data demonstrate that the newly developed web-based FFQ shows to have reasonable validity and good reproducibility for assessing nutrient intakes at the group and individual levels in a population of healthy adults. 12

Discussion:

PDA have advantages as information stored on the PDA can be reviewed at any point in time, uploading data to a computer allows dietitian to analyze dietary intake as often as the client provides them with information.  PDA-based self-monitoring greatly decreases the burden and the time required to analyze of the dietitian by removing the require for data entry. Another advantage avoid fallacious results. Although the advantages of PDA show their potential to improve data quality, there are several limitations. The use of PDA increases the respondent burden compared with paper diaries. Subjects having difficulty using the search function and experienced inability to find certain foods. Furthermore, PDS require participants to be literate. advance development of PDA by using PDA with a camera, dietitians could not always accurately estimate portion sizes as subjects took photos at the wrong angle and digital photo images were inadequate.

The main advantage of digital photography  is the possibility to collect dietary intake data from large groups in both children and adult populations relatively quickly, with minimal disruption and impact on the eating behavior of participants.   The digital photography  method of assessing dietary intake is fast, as it only requires only photographs of the participant’s food tray, less onsite staff and equipment during data collection, and provides a permanent record (photo) that can be re-examined and re-estimated when an estimate seems in errors.13

smart card system can collect long-term data from large groups on individual food behavior. Furthermore, smart cards are inexpensive and fewer researchers are needed since data are stored when the diner uses the smart card to pay for the meal. However, the smart card-based system also has limitations in its usability as a dietary assessment method when children paid for each other’s meal or  exchanged trays. Diners could buy foods and beverage for consumption at a different time. As such, the application of this tool is better indicated to collect information about subjects’ food selection and not their food intake.

Computer and Web-based self-administered tools makes it possible for participants to register  their dietary intake at their own convenience and assess nutrient intake as immediate feedback which saves considerable time and decreases costs. With the application of recorded audio to complete a computerised-dietary questionnaire or recall, literacy problems can be decreased. A disadvantage of Computer and Web-based self-administered assessment is that it requires the user to have a minimum level of knowledge about technology use.

 

 

 

 

 

 

FUTURE WORK:

While the new technology collects more complete data for nutritional studies and generates more objective reports compared to traditional methods, it can be further improved by future work. Possible future directions include audible alarms make it possible to alert the participant at specific times to record food intake. Using the voice search function to find certain foods in PDA tecnology. Improving the quality of the digital photos by using the laser beam that can be more focused. Smaller components can be used in the future to decrease the size in the hardware design. Applying alerts to notify subjects of implausible answers in Computer system decrease the problem of overreporting and reduce the amount of data cleaning by researchers. Technical problems improvement (e.g. internet connection of high quality).

The application of technology in the area of dietary assessment has resulted in the development of an array of tools, which are often specifically designed for a particular country or region. There were no available studies describe the development, validation, and user evaluation of  technology among  Saudi population or other Arabic countries. New tools in diet assessment technology need greater familiarity with Arabic or Saudi  foods. Inclusion Arabic language in mobile apps and websites tools may improve suitability in Arab countries over time.

CONCLUSION:

New technologies are still important considerations related to the possibility of selection bias since these methods cannot be applied to population subgroups who are not familiar with innovative technologies or modern devices. In general, which tool is the most suitable to collect dietary data depends on study objectives and the target group. Before selecting a given tool, it is important to review the advantages and disadvantages of each method.