Assessing Dietary Diversity in Pregnant Women: Relative Validity of the List-Based and Open Recall Methods

Phuong Hong Nguyen, Yves Martin-Prevel, Mourad Moursi, Lan Mai Tran, Purnima Menon, Marie T Ruel, Mary Arimond, Phuong Hong Nguyen, Yves Martin-Prevel, Mourad Moursi, Lan Mai Tran, Purnima Menon, Marie T Ruel, Mary Arimond

Abstract

Background: The Minimum Dietary Diversity for Women (MMD-W) was validated as a proxy of micronutrient adequacy for nonpregnant women, with proposed data collection being either a list-based or a qualitative open recall method. Few studies have compared the performance of these 2 methods.

Objectives: We compared performance in predicting micronutrient adequacy of food group indicators (FGIs) measured by the list-based and the quantitative open recall methods using varying quantity cut-offs. We also examined the agreement between list-based and open recall FGIs.

Methods: Data were collected in Bangladesh (n = 600 pregnant women) and India (n = 655). The performance of different indicators to predict micronutrient adequacy was compared using receiver operating characteristic (ROC) analysis. Correlations between list-based and open recall FGIs were calculated using Spearman's rank test; agreement was assessed by the intraclass correlation coefficient (ICC) and kappa statistics. Food groups that were most often misreported by the list-based method were identified.

Results: There were no statistically significant differences in ROC curves between list-based and open recall FGIs in either country. In Bangladesh, correlations between list-based and open recall FGIs varied between 0.6 and 0.8; ICC values were 0.43-0.75; kappa values were 0.51-0.53 when using a cut-off of any quantity or 15 g for open recall, but were lower (k = 0.24) with the cut-off of 1 portion. In India, these values were lower: ∼0.4 for correlation, 0.32-0.37 for ICCs, and 0.17-0.22 for kappas. Food groups most susceptible to misreporting using the list-based method were beans/peas in Bangladesh and other vegetables in India.

Conclusions: Our study provides initial support for the use of list-based questionnaires in assessing food group diversity or prevalence of MDD-W in pregnant women. Additional and context-specific work may be required to understand the potential of simple methodologies to assess consumption of specific food groups. This trial was registered at clinicaltrials.gov as NCT02745249 (Bangladesh) and NCT03378141 (India).

Keywords: Bangladesh; India; Minimum Dietary Diversity for Women; list-based method; open recall method.

Copyright © The Author(s) 2019.

Figures

FIGURE 1
FIGURE 1
Distribution of food group indicator scores by method and country. Bangladesh (A), India (B). FGI, food group indicator.

References

    1. GBD 2017 Risk Factor Collaborators. Global, regional, and national comparative risk assessment of 84 behavioural, environmental and occupational, and metabolic risks or clusters of risks for 195 countries and territories, 1990–2017: a systematic analysis for the Global Burden of Disease Study 2017. Lancet. 2018;392:1923–94.
    1. Arimond M, Daelmans B, Dewey K, Steering Team of the Working Group on Infant Young Child Feeding Indicators. Indicators for feeding practices in children. Lancet. 2008;371:541–2.
    1. Ruel MT, Deitchler M, Arimond M. Developing simple measures of women's diet quality in developing countries: overview. J Nutr. 2010;140:2048S–50S.
    1. Naska A, Lagiou A, Lagiou P. Dietary assessment methods in epidemiological research: current state of the art and future prospects. F1000Res. 2017;6:926.
    1. Development Initiatives. 2018 Global Nutrition Report: shining a light to spur action on nutrition. Bristol (UK): Development Initiatives; 2018.
    1. GLOPAN: Global Panel on Agriculture and Food Systems for Nutrition, 2016. Food systems and diets: facing the challenges of the 21st century. London (UK): 2016.
    1. Martin-Prevel Y, Arimond M, Allemand P, Wiesmann D, Ballard TJ, Deitchler M, Dop MC, Kennedy G, Lartey A, Lee WTK et al. .. Development of a dichotomous population-level indicator for global use in assessment of the dietary diversity of women of reproductive age. Curr Dev Nutr. 2017. [Internet]. [cited 2019 Jun 2]. doi: . Available from: .
    1. FAO, FHI360. Minimum dietary diversity for women: a guide for measurement, FAO, Rome, 2016. [Internet]. [cited 2019 May 10]. Available from: .
    1. Martin-Prevel Y, Becquey E, Arimond M. Food group diversity indicators derived from qualitative list-based questionnaire misreported some foods compared to same indicators derived from quantitative 24-hour recall in urban Burkina Faso. J Nutr. 2010;140:2086S–93S.
    1. Daniels MC, Adair LS, Popkin BM, Truong YK. Dietary diversity scores can be improved through the use of portion requirements: an analysis in young Filipino children. Eur J Clin Nutr. 2009;63:199–208.
    1. Working Group on Infant and Young Child Feeding Indicators. Developing and validating simple Indicators of dietary quality and energy intake of infants and young children in developing countries: summary of findings from analysis of 10 data sets. Washington (DC): Food and Nutrition Technical Assistance Project (FANTA) Project; 2006.
    1. Arimond M, Wiesmann D, Becquey E, Carriquiry A, Daniels MC, Deitchler M, Fanou-Fogny N, Joseph ML, Kennedy G, Martin-Prevel Y et al. .. Simple food group diversity indicators predict micronutrient adequacy of women's diets in 5 diverse, resource-poor settings. J Nutr. 2010;140:2059S–69S.
    1. Gewa CA, Murphy SP, Weiss RE, Neumann CG. Determining minimum food intake amounts for diet diversity scores to maximize associations with nutrient adequacy: an analysis of schoolchildren's diets in rural Kenya. Public Health Nutr. 2014;17:2667–73.
    1. Nguyen PH, Kim SS, Sanghvi T, Mahmud Z, Tran LM, Shabnam S, Aktar B, Haque R, Afsana K, Frongillo EA et al. .. Integrating nutrition interventions into an existing maternal, neonatal, and child health program increased maternal dietary diversity, micronutrient intake, and exclusive breastfeeding practices in Bangladesh: results of a cluster-randomized program evaluation. J Nutr. 2017;147:2326–37.
    1. Nguyen PH, Kachwaha S, Avula R, Young M, Tran LM, Ghosh S, Agrawal R, Escobar-Alegria J, Patil S, Menon P. Maternal nutrition practices in Uttar Pradesh, India: role of key influential demand and supply factors. Matern Child Nutr. 2019;15:e12839.
    1. Gibson R, Ferguson E. An interactive 24-hour recall for assessing the adequacy of iron and zinc intakes in developing countries. HarvestPlus Technical Monograph Series 8. Washington (DC) and Cali: International Food Policy Research Institute (IFPRI) and International Center for Tropical Agriculture (CIAT); 2008.
    1. Nahar Q, Choudhury S, Faruque O, Sultana SSS, Siddiquee MA, Dietary Guidelines for Bangladesh. Dhaka (Bangladesh); 2013.
    1. NIN. Dietary Guidelines for Indians—a manual. Hyderabad (India): National Institute of Nutrition; 2011.
    1. Shaheen N, Rahim ATM, Mohiduzzaman M, Banu CP, Bari ML, Tukun AB, Mannan M, Bhattacharjee L, Stadlmayr B. Food Composition Table for Bangladesh. Dhaka (Bangladesh: ): Institute of Nutrition and Food Science. Centre for Advanced Research in Sciences. University of Dhaka; 2013.
    1. Longvah T, Ananthan R, Bhaskarachary K, Venkaiah K. Indian Food Composition Tables 2017. Hyderabad: National Institute of Nutrition; 2017.
    1. IOM: Institute of Medicine. Dietary Reference Intakes: applications in dietary assessment. Washington (DC): National Academies Press; 2000.
    1. Roman-Vinas B, Serra-Majem L, Ribas-Barba L, Ngo J, Garcia-Alvarez A, Wijnhoven TM, Tabacchi G, Branca F, de Vries J, de Groot LC. Overview of methods used to evaluate the adequacy of nutrient intakes for individuals and populations. Br J Nutr. 2009;101(Suppl 2):S6–11.
    1. Akobeng AK. Understanding diagnostic tests 3: receiver operating characteristic curves. Acta Paediatr. 2007;96:644–7.
    1. Fischer JE, Bachmann LM, Jaeschke R. A readers’ guide to the interpretation of diagnostic test properties: clinical example of sepsis. Intensive Care Med. 2003;29:1043–51.
    1. Bland JM, Altman DG. Measuring agreement in method comparison studies. Stat Methods Med Res. 1999;8:135–60.
    1. Marasini D, Quatto P, Ripamonti E. Assessing the inter-rater agreement for ordinal data through weighted indexes. Stat Methods Med Res. 2016;25:2611–33.
    1. McGraw KO, Wong SP. Forming inferences about some intraclass correlation coefficients. Psychological Methods. 1996;1:30–46.
    1. Shrout PE, Fleiss JL. Intraclass correlations: uses in assessing rater reliability. Psychological Bulletin. 1979;86:420–8.
    1. Landis JR, Koch GG. The measurement of observer agreement for categorical data. Biometrics. 1977;33:159–74.
    1. Dietary Assessment Primer. Choosing an approach for dietary assessment. National Institutes of Health, National Cancer Institute; 2019. [Internet]. Available from: . [Accessed on: 2019 Apr 20].

Source: PubMed

3
Tilaa