Optifood, An Approach to Improve Nutrition

The study aims to explore ways in which optifood can be developed to create relevant food based recommendation (FBR) and to used for advocacy purposes.

The optifood tool will be pilot tested with relevant organizations and refine FBRs for the target population. Its performance will be assessed in the hands of Government/NGOs in Peru, Thailand and India to provide guidance on incorporating into their advocacy programs. Qualitative and quantitative methods will be used.

Aims and Objectives

The study aims to explore the ways in which Optifood can be developed to create relevant food-based recommendations (FBRs) and be used for advocacy purposes. Specific objectives seek to:

1. To develop a tool with which to formulate/test FBRs and create effective advocacy materials.
2. To assess its performance in the hands of government/NGOs, in Peru, Thailand and India to identify structural changes required and provide guidance on its incorporation into their program planning and advocacy activities.
3. To use the tool to develop locally appropriate FBRs in Peru, Thailand and India.

Study Setting

The study will take place in Switzerland, India, Thailand and Peru. Collaborating partners and specific locations are as follows:

* World Health Organisation - Geneva
* Society for Applied Studies - New Delhi
* Mahidol University - Bangkok
* Instituto de Investigación Nutricional - Peru.

FBRs will be tested in India in Kheri Kalan PHC in Haryana State.

Overall study design

The study aims to pilot test the Optifood tool with relevant organisations, then use the tool to test and refine existing FBRs for the target population. Mixed-methods research is recommended for exploring complex interventions. Accordingly, quantitative and qualitative methods will be used to address the study objectives. The study will use a wide range of respondents to gain a broader understanding of current behaviours, identify key influencers and understand the facilitators and barriers to behaviour change from different perspectives. Sample size will be determined by saturation sampling, that is, continuing investigating until no new information is uncovered.

Design

Key staff from relevant nutrition experts and governmental and non-governmental organisations will be trained to use Optifood, and asked to provide feedback on how it may be adapted to support nutrition programme planning activities. Next, Optifood will be used to evaluate and refine current FBRs for the target population, which will then be tested with mothers of children aged 9-11 months in the study area. This age group has been selected since 9-11 month old infants will likely demonstrate greater nutritional benefit when compared to older children, and they have more established CF intakes than a younger age group (e.g. 6-8 months) that is more likely to be transitioning to eating complementary foods.

Sampling strategy

Organisational staff will be purposefully selected from relevant NGOs and research institutes in Peru, Thailand and India. Relevant global nutrition experts will also be purposefully sampled for the initial pilot test in Geneva. Sampling will be purposive as the research team is aiming for inclusiveness, not representativeness. The characteristics of participants in the FGD will reflect the diversity and breadth of potential Optifood users. Organisations will be selected based on whether they are involved in nutrition programming and would have use for Optifood.

Mothers of children aged 9-11 months (n=60) will be recruited from six catchment areas within the study setting to collect information on food patterns, which is needed to run Optifood.

Mothers of children aged 9-11 months (n=36) will also be randomly selected from six subcentres in Kheri Kalan PHC (i.e. 6 randomly selected mothers from each subcentre) to test FBRs once they have been finalised using Optifood. This number is based on the recommended sample size from the Trials for Improved Practices (TIPs) protocol guidance, and factors in an attrition rate of 10% based on observed in a similar TIPs study in Indonesia.

Health workers (n=3-6 per FGD) will be purposefully selected from each study area to express their impressions of the new FBRs in FGDs. Sampling will be purposive as the research team is aiming for inclusiveness, not representativeness. The number of FGDs will depend on the number required to reach data saturation i.e., repeated and new material or themes do not emerge. Characteristics of Health workers in the FGDs will reflect the diversity and breadth of potential Health workers involved in the promotion of nutrition messages.

Data Analysis

Quantitative data analysis

Quantitative data collection methods in this study include QQs, FFQs, and 24-HRs. All quantitative data will be double-entered and data entry errors will be identified using range and consistency checks. After the data are cleaned, they will be transferred to Stata 11 software for analysis. Dietary data will be analysed in a specific diet program that has been developed using Microsoft Excel. Categories will be generated for continuous variables as needed. Data will be analysed and represented using numerical, graphical and tabular methods. In order to estimate any changes in infant diet when FBRs are tested with mothers, paired t-tests will be used to identify differences in means with 95% CIs for all 24-HRs. Differences will be considered significant at P\< 0.05. Statistics will be used for descriptive purposes, i.e. the study population will be represented as proportions, means, etc. and dietary data will be represented in means and standard deviations.

Qualitative data analysis

The study will rely heavily on FGDs, IDIs and structured observations at various stages for insights into how to refine the Optifood tool. Qualitative analysis will be iterative, thus evolve alongside data collection. NVivo 8 software will be used to store and code all the FGD and IDI transcripts after they have been translated into English. Contents of FGD and IDI transcripts will identify the range of health personnel and mothers' reactions to Optifood and FBRs, respectively. A thematic approach will be used to code FDGs and IDIs, starting with initial free coding with an ultimate aim of categorizing themes into categories. This process will not use a grounded theory approach, in which coding is entirely inductive.8 However, all qualitative data will be coded allowing for emergence of new unanticipated themes.

Triangulation of data is important to establish reliability of data. Accordingly, data from all the FGDs and IDIs will be compared and checked against each other for inconsistencies and completeness. Doing so will help the student ascertain the most "correct" interpretation of data. All conclusions will be presented to key study staff for accuracy to further improve reliability.

Methods

Objective 1- Developing the Optifood tool

Global nutrition experts will be trained to use the Optifood tool in Geneva. Two FGDs will be conducted during and 1-day post-training to assess the performance and potential applications of Optifood. A self-administered QQ will be collected to obtain information on computer literacy, professional experience and socio-demographics.

Will take place with a trained facilitator with fluency in local language(s) and a transcriber. Nutrition experts will answer questions on recommended changes, as well as the feasibility and acceptability of Optifood. Open-ended questions will be asked, and then followed up by specific prompts which relate to the research question. FGDs will be recorded with digital recorders.

Health personnel will answer self-administered QQs on computer literacy, professional experience and sociodemographic information.

Objective 2- Adapting Optifood for local use

Key staff from NGOs and/or research institutes in Lima, Bangkok and New Delhi will be trained to use the Optifood tool. For each organisation, two FGDs will be conducted during and 7-days post-training to assess the performance and potential applications of Optifood. A self-administered QQ will be collected to obtain information on computer literacy, professional experience and socio-demographics.

FGDs will take place with a trained facilitator with fluency in local language(s) and a transcriber. Health personnel will answer questions on recommended changes, as well as the feasibility and acceptability of Optifood. Open-ended questions will be asked, and then followed up by specific prompts which relate to the research question. FGDs will be recorded with digital recorders.

QQs will be translated into local languages as needed. Health personnel will answer self-administered QQs on computer literacy, professional experience and sociodemographic information.

Objective 3 - Using Optifood to develop, test and refine FBRs

Developing FBRs

Optifood will be used to develop population-specific FBRs for the target population. In order to run the model, Optifood requires data on the following parameters:

1. List of foods eaten by the target population
2. Average portion size
3. How many times/week the food could be consumed
4. Whether the food is staple food (Yes/No)
5. Whether the food is a snack (Yes/No)
6. Cost per 100 grams edible portion for each food
7. Information on food patterns by food groups (e.g. legumes, fruit, vegetables, milk, etc.) to be measured in number of servings/week.

   a. This information should also include a lower level (5th percentile), upper level (95th percentile) and average (50th percentile)
8. Food Composition Table
9. Average body weight of population - this can be an estimate.

Most of these data are available through the collaborating partners. However, data on cost of food and food frequency needs to be collected in order to run Optifood.

A food sub-group frequency questionnaire will be used to collect dietary data on the weekly frequency of consumption for each food sub-group usually consumed by children aged 9-11 months. The food groups and sub-groups to include in the FFQ will be finalised in India based on foods reported in the dietary survey data from SAS. This FFQ is based on the FFQ used in the National Nutrition Survey in Colombia. Data will be collected from 30 mothers of infants aged 9-11 months. For each food sub-group, a trained research assistant fluent in local language(s) will ask mothers if any foods from a food sub-group (i.e. cooked vegetables, salads or raw vegetables) are consumed by the child. If the answer is yes, mothers will be asked to estimate the number of times her child consumed foods from this sub-group over the past week.

A market survey will also be done to obtain cost of foods consumed per 100g edible portion. Research assistants will go to 3 local markets and 3 food sellers in each study setting to collect one sample of each frequently consumed food regardless of whether it is cooked or raw. The edible portion will be determined from the grams of food purchased. For cooked foods, raw ingredients will be purchased and cooked to provide a cost per 100g edible portion. This method is based on one used in a similar study in Indonesia.

Once these data have been collected, Optifood will be used to generate FBRs for each target population in each study setting.

Testing FBRs with mothers

An interviewer-administered socio-demographic QQ will be collected to obtain descriptive data on participants testing the FBRs. QQs will be translated into local languages as needed.

Upon development, FBRs will be tested with 36 mothers of infants aged 9-11 months. Evaluation methodology is based on the ProPAN strategy, with one modification of using the Trial of Improved Practices (TIPs) method of testing multiple instead of individual FBRs with each mother. Sample size is based on TIPS guidance and a similar study in Indonesia.

Research assistants will introduce FBRs to mothers in their respective homes. IDIs will be done to assess their impressions of the FBRs and the feasibility of adopting them. Mothers will be given 7 days to implement the FBRs. IDIs will be done at the beginning, middle and end of the 7-day testing period (Day 8) to reinforce messages and to assess feasibility of long-term practice. IDIs will take place with a trained interviewer with fluency in local language(s). Mothers will answer questions on the feasibility and acceptability of FBRs, barriers to their use and potential ways to change them after they have put the FBRs into practice. IDIs at the final visit at the end of the 7-day testing period will be recorded with digital recorders. Based on IDI results, FBRs will be refined for use in this population.

The child's dietary intakes will also be assessed using a modification of the interactive multiple-pass 24-hour recall7 pre- and post-FBR introduction. Trained research assistants with fluency in local language(s) will ask mothers to recall all food and beverages consumed by their child in the past 24 hours, and estimate the amount of each food consumed. The modification that will be made to the original interactive multiple-pass 24 hour recall is that at the end of the interview, mothers will also be asked to estimate the frequency of consumption of each food over the past week. Infant weight will also be measured at the end of the 7-day testing period.

Health workers will also provide additional data on the barriers to nutrition counseling, as well as the feasibility and acceptability of promoting the Optifood-generated FBRs in comparison with those currently being used. Health workers will participate in a FGD to collect data on these FBRs. A trained facilitator with fluency in local language(s) and a transcriber will ask health workers open-ended questions about their impressions of the FBRs, the feasibility of promoting them, and barriers to nutrition counseling in the target area. FGDs will be recorded with digital recorders. A brief socio-demographic QQ will also be administered to health workers to collect descriptive data.

Eligibility Criteria:
Inclusion Criteria:

* Randomly selected children 9 to 11 month of age