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Development of a field-friendly automated dietary assessment tool and nutrient database for India.

ABSTRACT: Studies of diet and disease risk in India and among other Asian-Indian populations are hindered by the need for a comprehensive dietary assessment tool to capture data on the wide variety of food and nutrient intakes across different regions and ethnic groups. The nutritional component of the India Health Study, a multicentre pilot cohort study, included 3908 men and women, aged 35-69 years, residing in three regions of India (New Delhi in the north, Mumbai in the west and Trivandrum in the south). We developed a computer-based, interviewer-administered dietary assessment software known as the 'NINA-DISH (New Interactive Nutrition Assistant - Diet in India Study of Health)', which consisted of four sections: (1) a diet history questionnaire with defined questions on frequency and portion size; (2) an open-ended section for each mealtime; (3) a food-preparer questionnaire; (4) a 24 h dietary recall. Using the preferred meal-based approach, frequency of intake and portion size were recorded and linked to a nutrient database that we developed and modified from a set of existing international databases containing data on Indian foods and recipes. The NINA-DISH software was designed to be easily adaptable and was well accepted by the interviewers and participants in the field. A predominant three-meal eating pattern emerged; however, patterns in the number of foods reported and the primary contributors to macro- and micronutrient intakes differed by region and demographic factors. The newly developed NINA-DISH software provides a much-needed tool for measuring diet and nutrient profiles across the diverse populations of India with the potential for application in other South Asian populations living throughout the world.

SUBMITTER: Daniel CR

PROVIDER: S-EPMC5652307 | biostudies-literature | 2014 Jan

REPOSITORIES: biostudies-literature

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Development of a field-friendly automated dietary assessment tool and nutrient database for India.

Daniel Carrie R CR Kapur Kavita K McAdams Mary J MJ Dixit-Joshi Sujata S Devasenapathy Niveditha N Shetty Hemali H Hariharan Sriram S George Preethi S PS Mathew Aleyamma A Sinha Rashmi R

The British journal of nutrition 20140101 1

Studies of diet and disease risk in India and among other Asian-Indian populations are hindered by the need for a comprehensive dietary assessment tool to capture data on the wide variety of food and nutrient intakes across different regions and ethnic groups. The nutritional component of the India Health Study, a multicentre pilot cohort study, included 3908 men and women, aged 35-69 years, residing in three regions of India (New Delhi in the north, Mumbai in the west and Trivandrum in the sout ...[more]

PMID: 23796477

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Project description:BackgroundAutomated dietary assessment tools such as ASA24® are useful for collecting 24-hour recall data in large-scale studies. Modifications made during manual data cleaning may affect nutrient intakes.ObjectivesWe evaluated the effects of modifications made during manual data cleaning on nutrient intakes of interest: energy, carbohydrate, total fat, protein, and fiber.MethodsDifferences in mean intake before and after data cleaning modifications for all recalls and average intakes per subject were analyzed by paired t-tests. The Chi-squared test was used to determine whether unsupervised recalls had more open-ended text responses that required modification than supervised recalls. We characterized food types of text response modifications. Correlations between predictive energy requirements, measured total energy expenditure (TEE), and mean energy intake from raw and modified data were examined.ResultsAfter excluding 11 recalls with invalidating technical errors, 1499 valid recalls completed by 393 subjects were included in this analysis. We found significant differences before and after modifications for energy, carbohydrate, total fat, and protein intakes for all recalls (P < 0.05). Limiting to modified recalls, there were significant differences for all nutrients of interest, including fiber (P < 0.02). There was not a significantly greater proportion of text responses requiring modification for home compared with supervised recalls (P = 0.271). Predicted energy requirements correlated highly with TEE. There was no significant difference in correlation of mean energy intake with TEE for modified compared with raw data. Mean intake for individual subjects was significantly different for energy, protein, and fat intakes following cleaning modifications (P < 0.001).ConclusionsManual modifications can change mean nutrient intakes for an entire cohort and individuals. However, modifications did not significantly affect the correlation of energy intake with predictive requirements and measured expenditure. Investigators can consider their research question and nutrients of interest when deciding to make cleaning modifications.

Project description:Dietary interventions and existing health behaviour theories are centred on individuals; therefore, none of the available tools are applicable to households for changing dietary behaviour. The objective of this pilot study was to develop a practical tool that could be administered by community volunteers to stage households in rural Kerala based on readiness to change dietary behaviour. Such a staging tool, comprising a questionnaire and its algorithm, focusing five dietary components (fruits, vegetables, salt, sugar and oil) and households (rather than individuals), was finalised through three consecutive pilot validation sessions, conducted over a four-month period. Each revised version was tested with a total of 80 households (n = 30, 35 and 15 respectively in the three sessions). The tool and its comparator, Motivational Interviewing (MI), assessed the stage-of-change for a household pertaining to their: 1) fruit and vegetable consumption behaviour; 2) salt, sugar and oil consumption behaviour; 3) overall readiness to change. The level of agreement between the two was tested using Kappa statistics to assess concurrent validity. A value of 0.7 or above was considered as good agreement. The final version was found to have good face and content validity, and also a high level of agreement with MI (87%; weighted kappa statistic: 0.85). Internal consistency testing was performed using Cronbach's Alpha, with a value between 0.80 and 0.90 considered to be good. The instrument had good correlation between the items in each section (Cronbach's Alpha: 0.84 (fruit and vegetables), 0.85 (salt, sugar and oil) and 0.83 (Overall)). Pre-contemplation was the most difficult stage to identify; for which efficacy and perceived cooperation at the household level were important. To the best of our knowledge, this is the first staging tool for households. This tool represents a new concept in community-based dietary interventions. The tool can be easily administered by lay community workers and can therefore be used in large population-based studies. A more robust validation process with a larger sample is needed before it can be widely used.

Dataset Information

Development of a field-friendly automated dietary assessment tool and nutrient database for India.

Publications

Development of a field-friendly automated dietary assessment tool and nutrient database for India.

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