Innovative approaches: B
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Innovative approaches studies at ANH2020

 

Session recording:

ANH2020: Innovative approaches B

 

Speakers and presentations:

  • Session chair: Namukolo Covic, A4NH, IFPRI
    @NamukoloC @IFPRI @A4NH_CGIAR
  • Anna Herforth, Harvard T.H. Chan School of Public Health
    @AnnaWHerforth @HarvardChanSPH
    Development of a low-burden diet quality questionnaire (DQ-Q) for measuring dietary diversity and other indicators of diet quality across countries
    Presentation | Slides

  • Kate Schneider, Tufts University
    @GlFoodPolNut @TuftsNutrition
    Household diet quality and the cost of nutritious diets in Malawi~
    Presentation | Slides

  • Maria Garza, Royal Veterinary College
    @RoyalVetCollege
    Framework for food safety assessment of livestock derived food retailers, in selected low and middle-income areas of Nairobi
    Presentation | Slides

  • Sabri Bromage, Harvard T.H. Chan School of Public Health
    @HarvardChanSPH
    Development of the Global Diet Quality Score
    Presentation | Slides

Abstracts:

Development of a low-burden diet quality questionnaire (DQ-Q) for measuring dietary diversity and other indicators of diet quality across countries 

Anna Herforth1

Euridice Martínez-Steele2Is

abela Sattamini2

Deborah Olarte3

Giovanna Andrade2

Carlos Monteiro2

Andy Rzepa4

Terri Ballard5

1Harvard T.H. Chan School of Public Health, USA

2University of São Paulo, Brazil

3Teachers College, Columbia University, USA

4Gallup

5Independent

Introduction

There is a need for low-burden survey tools to collect information on diet quality. Low-burden methods are fast to administer, do not require subject expertise or probing by enumerators, and require low cognitive burden on respondents. The aim of low-burden survey tools for diet quality is to facilitate and democratize the collection of valid dietary data, for example in large-scale multi-topic surveys, and in nutrition-sensitive projects that are not managed by nutrition experts (such as agriculture project planning, monitoring and evaluation). Few low-burden diet survey methods exist, and they need to be rigorously tested to collect consistent and valid information.  

Methods

A common method for collecting dietary diversity data consists of open-ended food group questions, e.g. "Yesterday, did you eat any porridge, bread, rice, pasta or other foods made from grains?" (FAO and FHI360, 2016). We used this as a starting point for developing a 28-item diet quality questionnaire (DQ-Q), where each yes/no question asks about consumption of a distinct food group in the previous day or night. We conducted 82 cognitive interviews in five languages São Paulo and New York City, in which we tested different ways of introducing and asking the questions, compared responses to closed-ended questions to open-ended questions, and interviewed respondents about their thought processes while answering the questions. Simultaneously, we analyzed nationally representative dietary intake data in two countries (Brazil and the United States) to determine the extent to which a short list of foods (<7 items) for each food group could capture the majority of people consuming each food group. A national pilot test of 1,000 respondents was implemented in Brazil within the Gallup World Poll, a multi-topic survey carried out by non-nutritionist enumerators.

Findings

We found that (1) respondents in both countries sometimes miscategorized foods when asked open-ended questions, and open-ended questions presented an additional cognitive burden; (2) respondents varied in their ability to think of other foods that belonged to a specific named food group; (3) cognitive burden on respondents was generally low, and was reduced by asking closed-ended questions, by questions with relatively short lists of food examples, and by specific design aspects of the questionnaire including a comprehensive introduction and intentionally-placed question stems; and (4) the majority of consumption of each food group could be represented by a few foods in each country setting (sentinel foods). On average, 1-7 sentinel foods captured 96-97% of people who consumed each food group (range 85-100%). These findings provide evidence supporting the approach of asking closed-ended questions using sentinel foods. The DQ-Q requires adaptation to each country context: the food groups are the same across countries, but need to be populated with sentinel food examples that capture consumption of the food group specific to each country. The finalized DQ-Q took 3-5 minutes to administer, had very low training requirements for non-specialist enumerators, and was easy for them to administer.

Conclusion

Collecting valid proxy indicators of diet quality with low-burden methods, such as dietary diversity scores or other indicators of diet quality, requires careful attention to the tool design for valid and comparable results. These results have important implications for large multi-topic surveys that aim to measure diet quality, and the DQ-Q can be used in whole or in part for the measurement of diet quality in the Gallup World Poll, the measurement of MDD-W in the DHS, the measurement of diet quality by other national surveys, and by agriculture projects that aim to collect diet quality information.

References

FAO and FHI 360. (2016). Minimum dietary diversity for women: A guide to measurement. FAO: Rome.

Household diet quality and the cost of nutritious diets in Malawi

Kate Schneider1

Luc Christiaensen2
Patrick Webb1
William A. Masters1

1Tufts University, USA
2The World Bank, USA

Introduction

Nutrition needs differ by age, sex, life stage and activity level, but families eat together from a shared basket of foods. Acknowledging that families eat common meals, household consumption and expenditure surveys can be used to fill the gap in evidence regarding the adequacy of the household diet for all its members and the cost of a nutritious diet for a family. Whether nutritionally adequate diets are affordable is an active area of research. Similarly, much remains to be understood about how well different markets and food systems provide access to affordable and nutritious diets year-round.

Methods

We use household survey panel data from 2010-2017 in rural Malawi matched with new food composition data for Malawi, human nutrient requirements, and monthly food prices in 29 rural markets from 2007-2018. We aggregate nutritional requirements to the household level by defining a diet dense enough per nutrient to meet all needs for all members, assuming each member eats in proportion to their own energy needs. The individual requirements come from the Dietary Reference Intakes and include the estimated average requirement (EAR) where an EAR has been defined, upper limits where relevant, and limit macronutrients to within the acceptable range (AMDR). We estimate household adequacy ratios based on current household consumption relative to household needs. We then incorporate food prices and calculate the least-cost nutritionally adequate diet for each household using linear programming. We compare this diet to current household food spending and total expenditure. Finally, we analyze the shadow costs of individual nutrients by transforming them into elasticities, interpreted as the percentage increase in the total diet cost for a percentage increase in the requirement for each nutrient. We compare the shadow cost to the source of nutrients (market, own production, gift) reported by households and its nutrient adequacy.

Findings

Households in Malawi are meeting only some of their nutrient needs and reported household food consumption meets 75% of all nutrition needs, on average. Our adequacy results demonstrate that fats, protein, and micronutrients found in animal source foods (phosphorus, vitamin B12, riboflavin, zinc) are most likely to be lacking in household diets. With respect to cost, we find a nutritionally adequate diet costs 2.6 times current household food spending and even if households spent all their resources on food, it would still not be enough to secure a nutritionally adequate diet on average; the least-cost diet costs an average 1.6 times current total expenditures. Comparing the percent of household expenditure by food groups to the food group percentage of the adequate diet cost reveals households overspend on cereals and flesh foods and underspend on legumes and vitamin A-rich fruits. We find households are net buyers of nearly half of all nutrients. Several nutrients are cost-limiting to meet minimum requirements from the local market; the least-cost diet total cost rises 352% for a 1% increase in riboflavin requirements, 22% for vitamin B12, 14% for lipids, 22% for vitamin B12, 5.2% for vitamin E, 3.3% for selenium, and 4.1% for niacin.

Conclusion

We show that households in Malawi are not consuming high quality diets and that the cost to do so exceeds current food and total expenditures. Current expenditures by food groups are unbalanced relative to the food group cost percentages in a nutritionally adequate least-cost diet and the shadow cost of several under-consumed nutrients are high. These results could help guide policies and programs aimed at lowering the market cost of certain nutrient-rich foods to improve the affordability of healthier diets and can also guide nutrition education. Our methods contribute to ongoing developments using household surveys for food and nutrition analyses.

References

Bai, Y., Masters, W. A., & Schneider, K. Forthcoming. Calculating the Cost of Nutrient Adequacy (CoNA) food price index using Stata and R.
Beaton, G.H. 1995. Fortification of Foods for Refugee Feeding: Final report to the Canadian International Development Agency.
Beaton, G.H. 1999. Recommended Dietary Intakes: Individuals and Populations. In M. E. Shils, J. A. Olson, M. Shike, and A. C. Ross, eds. Modern Nutrition in Health and Disease. Baltimore: Williams & Wilkins, pp. 1705–1725.
Beaton, G.H. 2006. When is an individual an individual versus a member of a group? An issue in the application of the dietary reference intakes. Nutrition Reviews, 64 (5) 211–225.
Beegle, K., J. De Weerdt, J. Friedman, and J. Gibson. 2012. Methods of household consumption measurement through surveys: Experimental results from Tanzania. Journal of Development Economics, 98 (1) 3–18.
Bermudez, O.I., K. Lividini, M.F. Smitz, and J.L. Fiedler. 2012. Estimating micronutrient intakes from Household Consumption and Expenditures Surveys (HCES): an example from Bangladesh. Food And Nutrition Bulletin, 33 (3 Suppl) S208–S213.
Department of Nutrition HIV and AIDS [Government of Malawi]. (2018a). National Multi-Sector Nutrition Policy 2018-2022. Lilongwe, Malawi: Government of Malawi.
Department of Nutrition HIV and AIDS [Government of Malawi]. (2018b). National Multi-Sector Nutrition Strategic Plan 2018–2022. Lilongwe, Malawi: Government of Malawi.
Fiedler, J.L. 2013. Towards overcoming the food consumption information gap: Strengthening household consumption and expenditures surveys for food and nutrition policymaking. Global Food Security, 2 (1) 56–63.
Fiedler, J.L., K. Lividini, O.I. Bermudez, and M.F. Smitz. 2012b. Household Consumption and Expenditures Surveys (HCES): a primer for food and nutrition analysts in low- and middle-income countries. Food And Nutrition Bulletin, 33 (3 Suppl) S170–S184.
Håkansson, A. 2015. Has it become increasingly expensive to follow a nutritious diet? Insights from a new price index for nutritious diets in Sweden 1980-2012. Food and Nutrition Research, 59 (1) 1–9.
Headey, D., Hirvonen, K., Hoddinott, J., & Stifel, D. (2019). Rural Food Markets and Child Nutrition. American Journal of Agricultural Economics, 101 (5) 1311–1327.
Hirvonen, K., Bai, Y., Headey, D., Masters, W. A. 2019. Affordability of the EAT – Lancet reference diet : a global analysis. The Lancet Global Health, (19) 1–8.
Hirvonen, K., & Hoddinott, J. 2017. Agricultural production and children’s diets: evidence from rural Ethiopia. Agricultural Economics, 48 (4) 469–480.
Hirvonen, K., Hoddinott, J., Minten, B., & Stifel, D. 2017. Children’s Diets, Nutrition Knowledge, and Access to Markets. World Development, 95 303–315.
Institute of Medicine of the National Academies. 2006. Dietary Reference Intakes: the essential guide to nutrient requirements. J. J. Otten, J. P. Hellwig, & L. D. Meyers, Eds.. Washington, DC: National Academies Press.
Institute of Medicine of the National Academies. 2011. Dietary Reference Intakes for Calcium and Vitamin D (Vol. 130). Washington, DC: National Academies Press.
MAFOODS. 2019. Malawian Food Composition Table. A. van Graan, J. Chety, M. Jumat, S. Masangwi, A. Mwangwela, F. P. Phiri, … E. Marino-Costello, Eds.. Lilongwe, Malawi.
Masters, W. A., Bai, Y., Herforth, A., Sarpong, D., Mishili, F., Kinabo, J., & Coates, J. 2018. Measuring the Affordability of Nutritious Diets in Africa: Price Indexes for Diet Diversity and the Cost of Nutrient Adequacy. American Journal of Agricultural Economics, 100 (5) 1285–1301.
National Academies of Sciences Engineering and Medicine. 2019. Dietary Reference Intakes for Sodium and Potassium. V. A. Stallings, M. Harrison, & M. Oria, Eds. Washington, DC: The National Academies Press.
National Statistical Office (NSO) [Malawi]. 2012. Third Integrated Household Survey (IHS3) 2010/11 Basic Information Document. Zomba, Malawi.
National Statistical Office (NSO) [Malawi]. 2014. Malawi Integrated Household Panel Survey (IHPS) 2013: Basic Information Document. Zomba, Malawi.
National Statistical Office (NSO) [Malawi]. 2018. Consumer Price Index. Zomba, Malawi.
Optifood. 2012. Optifood, An Approach to Improve Nutrition.
Schneider, K., & Herforth, A. Forthcoming. Software tools for practical application of human nutrient requirements in food-based social science research.
Stigler, G. J. 1945. The cost of subsistence. Journal of Farm Economics, 27 (2) 303–314.
US Department of Agriculture. 2018. USDA National Nutrient Database for Standard Reference, Legacy (2018) (Vol. May). Beltsville, Maryland: USDA Agricultural Research Service Nutrient Data Laboratory.
Weisell, R., and M.C. Dop. 2012. The adult male equivalent concept and its application to Household Consumption and Expenditures Surveys (HCES). Food And Nutrition Bulletin 33 (3 (supplement)) 157–162.

Framework for food safety assessment of Livestock Derived Food retailers, in selected Low and Middle-income areas of Nairobi

Maria Garza1

Barbara Häsler1

Maurice Karani2

Patrick Muinde2

Eric Fevre2,3

Jonathan Rushton3

Pablo Alarcon1

1Royal Veterinary College

2International Livestock Research Institute

3University of Liverpool

Introduction

Despite the crucial nutritional benefits of animal source foods, foodborne associated diseases accounted for 35% of the total Burden of foodborne diseases (FBD) in 2010 (Li et al. 2019). Demand for these products is steadily growing in rapidly urbanising areas of sub-Saharan Africa (Robinson and Pozzi 2011), while provision and development of structures that warrant food safety is compromised, directly impacting public health. The objectives of this study were to characterise Livestock Derived Food (LDF) retailers in informal settlements and peri-urban areas of Nairobi, and to develop a framework to classify and assess retailers according to main food safety characteristics.      

Methods

A cross-sectional study was carried out with LDF retailers in their commercial establishments, purposefully selected to capture diversity. Data were captured through a questionnaire, which included information about: 1) the characteristics of the products sold, such as seasonality, quantities, prices, storage and management; 2) the previous stages of the value chain; and 3) hygiene and management practices, which included an observation checklist of the establishment and food handlers. The descriptive data was subsequently used as the basis to establish an initial classification of retailers. A food safety framework was then developed for the assessment of their food safety characteristics. This included two dimensions, namely the product and the retailer. The product dimension covered intrinsic characteristics to rate perishability and microbial risk. The retailer dimension aimed to rate, qualitatively, the probability of contamination of the product and the presence of mitigation measures for microbial growth and contamination. This was done by assessing the types of (a) sourcing transactions (b) infrastructure and equipment and (c) the hygiene and food safety management practices used. A food safety scoring process was developed for each element, and a final aggregate score was used to rank retailers based on their food safety risks.

Findings

Twenty-one different groups of retailers were identified from 222 LDF retailers surveyed, based on main products sold, and broad infrastructure and equipment characteristics. These retailers included: High, medium and low class butcheries of ruminant meat, pork butcheries, poultry butcheries, offal butcheries, large and small restaurants, milk bars, kiosks, supermarkets, depots and four different types of road side vendors based on product. The groups presented different profiles of product characteristics and degree of specialisation. Most of the groups sold or handled highly perishable products in raw form (20/21) while only few sold treated (5/21) products. Regarding the sourcing routes, meat products were acquired from few specific types, rated with lower scores due to the higher number of informal actors involved and characteristics of previous locations that increased the probability of contamination. In contrast, retailers selling eggs and milk reported the use of a wider variety of routes with different profiles and risk implications. Several deficiencies relating to equipment and practices of food handlers were found. The application of the framework, using a rating system, illustrated variability within and between groups, and assisted the identification of tailored action points.

Conclusion

This study provides a tool that allows the rapid assessment of LDF retailers and systematic identification of improvement points in hygiene and food control, which can be extended to other peri-urban and urban settings in sub-Saharan African countries. Further, the application of the tool generates evidence on risk profiles to inform the design of risk-based surveillance of foodborne pathogens and food safety interventions.

References

Li, M, Havelaar, A.H., Hoffmann, S., Hald, T., Kirk, M. D., Torgerson, P. R., and Devleesschauwer, B., 2019. “Global Disease Burden of Pathogens in Animal Source Foods, 2010.” PLoS ONE 14 (6). https://doi.org/10.1371/journal.pone.0216545.

Robinson, T. and Pozzi, F., 2011. Mapping Supply and Demand for Animal-Source Foods to 2030. Animal Production and Health Working Paper. No. 2. https://doi.org/10.1287/opre.1080.0628.

Development of the Global Diet Quality Score, a novel food-based metric of diet quality

Sabri Bromage1

Carolina Batis2

Shilpa N. Bhupathiraju1

Wafaie W. Fawzi1

Teresa T. Fung1

Yanping Li1

Megan Deitchler3

Analí Castellanos-Gutiérrez2

Yuna He4

Mika Matsuzaki1

Yiwen Zhang1

Selma Gicevic5

Michelle D. Holmes1

Sheila Isanaka1

Sanjay Kinra6

Meir Stampfer1

Walter C. Willett1

1Harvard T.H. Chan School of Public Health, Boston, MA, USA

2National Institute of Public Health, Cuernavaca, MOR, Mexico

3Intake - Center for Dietary Assessment, FHI Solutions, Washington, DC, USA

4National Institute for Nutrition and Health, Chinese Centers for Disease Control and Prevention, Beijing, China

5London Centre for Integrative Research on Agriculture and Health, London, United Kingdom

6London School of Hygiene and Tropical Disease, London, United Kingdom

Introduction

No global standard metric(s) of overall diet quality exists at present. Reasons include different food consumption patterns among populations (creating a challenge for developing a universally-relevant list of foods to measure), and different burdens of disease between the global north and south (the relative importance of NCDs and nutrient deficiencies suggests different food groups and nutrients as priorities to measure). Consequentially, existing diet quality metrics capture either nutrient adequacy or diet-related NCD risk, but not both, and it is difficult to compare diet quality between populations or track trends within populations.      

Methods

We developed a 25-item Global Diet Quality Score (GDQS), a food-based diet quality metric based on the Prime Diet Quality Score (PDQS), which employs a modestly expanded list of food groups relative to most existing metrics (Fung 2018). We assessed validity of the GDQS in secondary analysis of cross-sectional and cohort data from Africa, China, India, Mexico, and the U.S. by evaluating associations between GDQS scores (using food frequency and 24-hour recall data) and nutrient intakes, anthropometry, and other clinical measurements. Stages of GDQS development: (1) The GDQS was created by modifying PDQS food groups to more broadly represent nutritionally-important foods globally, and assigning point values to each food representing low, moderate, or high daily intake. (2) Validity of the GDQS, and “healthy” and “unhealthy” GDQS submetrics (scored using only 16 positively and 9 negatively scored components, respectively) were compared. (3) Validity of different GDQS scoring schemes for specifically targeting NCD risk or nutrient adequacy were evaluated. (4) Validity of a simplified GDQS, scored using only two daily intake ranges for each food group, was evaluated. (5) GDQS cutoffs for classifying diet quality as low, moderate, or high were derived from observed relationships between the GDQS and outcomes across countries.

Findings

Main findings: (1) Based on observed associations with clinical and anthropometric measurements, including weight change and incident type II diabetes among non-pregnant non-lactating women of reproductive age in the U.S., validity of the 25-item GDQS was generally superior to that of the “healthy” and “unhealthy” GDQS submetrics, and provided adequately (albeit less well than the “healthy” submetric) in predicting nutrient intakes. (2) Validity of a GDQS scoring scheme modified for targeting nutrient adequacy (in which legumes, nuts and seeds, and dark green leafy vegetables are given more positive point values, and high-fat dairy and red meat are given positive scores for moderate consumption and no points for high consumption) was generally superior to the NCD risk scoring scheme in predicting aspects of both nutrient adequacy and NCD risk. (3) The simplified GDQS, while generally displaying lower validity than the GDQS, was nonetheless predictive of nutrient adequacy and NCD risk, indicating its potential usefulness as an alternative metric that would be easier to implement. (3) A “low-risk” cutoff for the GDQS was identified at an inflection point in NCD risk, while a “high-risk” cutoff was selected based on the approximate value of the 10th percentile in GDQS score across datasets.

Conclusion

By including an expanded list of food groups relative to other existing diet quality metrics, the GDQS accounts for foods of nutritional importance across a wide range of diets globally, and is capable of predicting both nutrient adequacy and NCD risk. In assessing NCD risk, validity of the GDQS was optimized by including both healthy and unhealthy foods in scoring, using a scoring system initially developed for assessing nutrient adequacy. Future research is warranted to develop population-specific instruments for collecting the GDQS and the simplified GDQS, and evaluate their validity in primary data collection.

References

Fung T.T., Isanaka S., Hu F.B., Willett W.C., 2018. International diet quality and risk of coronary heart disease in men and women. American Journal of Clinical Nutrition, 107 (5) 120-129.

Speakers:
Ag2Nut Community of Practice, Harvard School of Public Health, Wageningen University & Research
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