Use of Household Apparent Food Intake Data to Estimate Micronutrient Inadequacy in Comparison to the 24-h Recall Data Among Women of Reproductive Age in Kasungu District, Malawi
Abstract
1. Introduction
2. Methods
2.1. Estimating Apparent Food Consumption Using HCES Data
2.2. Estimating Food Consumption from 24HR Dietary Data
2.3. Pre-Processing and Cleaning of Data
2.3.1. Food Consumption Data from 24HR Dietary Recall
2.3.2. Household Apparent Food Consumption Data from IHS5
2.4. Food Composition Data
2.5. Estimating Nutrient Intakes
2.6. Calculation of Households or Individuals at Risk of Inadequate Intakes
2.7. Fortification Scenarios
2.8. Creating a Comparable Subsample of the HCES
3. Results
3.1. HCES and 24HR Study Populations
3.2. Comparison of Dietary Intake Estimates
3.3. Intake and Percentage of Households/Individuals Reporting Consumption of Fortified Foods
3.4. Large-Scale Food Fortification Contribution
4. Discussion
4.1. Discrepancies in Food and Energy Intakes Between 24HR and HCES Data
4.2. Prevalence of Dietary Micronutrient Inadequacies Using 24HR and HCES Data
4.3. Using 24HR and HCES Modelling Outputs to Inform LSFF Decision-Making
4.4. Limitations of This Study
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
- Gibson, R.S. Principles of Nutritional Assessment, 3rd ed.; Oxford University Press: New York, NY, USA, 2023. [Google Scholar]
- Food and Agriculture Organization (FAO). Dietary Assessment: A Resource Guide to Method Selection and Application in Low-Resource Setting; FAO: Rome, Italy, 2018. [Google Scholar]
- World Health Organization (WHO); United Nation International Children’s Emergency Fund (UNICEF). Indicators for Assessing infant and Young Child Feeding Practices: Definitions and Measurement; WHO: Geneva, Switzerland, 2021. [Google Scholar]
- Pisa, P.T.; Landais, E.; Margetts, B. Inventory on the dietary assessment tools available and needed in Africa: A prerequisite for setting up a common methodological research infrastructure for nutritional surveillance, research, and prevention of diet-related non-communicable diseases. Crit. Rev. Food Sci. Nutr. 2018, 58, 37–61. [Google Scholar] [CrossRef]
- Jariseta, Z.R.; Dary, O.; Fiedler, J.L.; Franklin, N. Comparison of estimates of the nutrient density of the diet of women and children in Uganda by household consumption and expenditures surveys (HCES) and 24-hour recall. Food Nutr. Bull. 2012, 33 (Suppl. S3), S199–S207. [Google Scholar] [CrossRef]
- Serajuddin, U.; Uematsu, H.; Wieser, C. Data Deprivation: Another Deprivation to End; Policy Research Working Paper, no. WPS 7252; The World Bank: Washington, DC, USA, 2015. [Google Scholar]
- Fiedler, J.L.; Yadav, S. How can we better capture food away from home? Lessons from India’s linking person-level meal and household-level food data. Food Policy 2017, 72, 81–93. [Google Scholar] [CrossRef] [PubMed]
- Babu, S.C.; Haggblade, S.; Mkandawire, E.; Hendriks, S. Micronutrient Policy Process in Malawi; International Food Policy Research Institute (IFPRI) Discussion Paper; International Food Policy Research Institute (IFPRI): Washington, DC, USA, 2016. [Google Scholar]
- Dary, O.; Jariseta, Z.R. Validation of dietary applications of household consumption and expenditures surveys (HCES) against a 24-hour recall method in Uganda. Food Nutr. Bull. 2012, 33 (Suppl. S33), S190–S198. [Google Scholar] [CrossRef]
- Tang, K.; Adams, K.P.; Ferguson, E.L.; Woldt, M.; Kalimbira, A.A.; Likoswe, B.; Yourkavitch, J.; Chrisinger, B.; Pedersen, S.; De La Revill, L.S.; et al. Modeling food fortification contributions to micronutrient requirements in Malawi using Household Consumption and Expenditure Surveys. Ann. N. Y. Acad. Sci. 2022, 1508, 105–122. [Google Scholar] [CrossRef] [PubMed]
- Adeyemi, K.D.; Kumwenda, N.C.; Oldewage-Theron, W.; Gichohi-Wainaina, W.N. Household food security status and diet diversity predictors of mother–child dyads from rural smallholders in three agroecological zones of Malawi. J. Hunger. Environ. Nutr. 2025, 20, 497–515. [Google Scholar] [CrossRef]
- National Statistical Office; The World Bank. Fifth Integrated Household Survey of Malawi; NSO: Zomba, Malawi; Rockville, MD, USA, 2020. [Google Scholar]
- Weisell, R.; Dop, M.C. The adult male equivalent concept and its application to Household Consumption and Expenditures Surveys (HCES). Food Nutr. Bull. 2012, 33 (Suppl. S3), S157–S162. [Google Scholar] [CrossRef]
- National Statistical Office (NSO) [Malawi]; ICF Macro. Malawi Demographic and Health Survey 2015-16; NSO: Rockville, MD, USA, 2017. [Google Scholar]
- Price, A.J.; Crampin, A.C.; Amberbir, A.; Kayuni-Chihana, N.; Musicha, C.; Tafatatha, T.; Branson, K.; Lawlor, D.A.; Mwaiyeghele, E.; Nkhwazi, L.; et al. Prevalence of obesity, hypertension, and diabetes, and cascade of care in sub-Saharan Africa: A cross-sectional, population-based study in rural and urban Malawi. Lancet Diabetes Endocrinol. 2018, 6, 208–222. [Google Scholar] [CrossRef] [PubMed]
- FAO/WHO/UNU. Human Energy Requirements. Report of a Joint FAO/WHO/UNU Expert Consultation; Food Nutrition Technical Report Series; Food and Agriculture Organization: Rome, Italy, 2001. [Google Scholar]
- Pratt, M.; Sallis, J.F.; Cain, K.L.; Conway, T.L.; Palacios-Lopez, A.; Zezza, A.; Spoon, C.; Geremia, C.M.; Gaddis, I.; Amankwah, A.; et al. Physical activity and sedentary time in a rural adult population in Malawi compared with an age-matched US urban population. BMJ Open Sport Exerc. Med. 2020, 6, e000812. [Google Scholar] [CrossRef]
- Kominiarek, M.A.; Rajan, P. Nutrition recommendations in pregnancy and lactation. Med. Clin. N. Am. 2016, 100, 1199–1215. [Google Scholar] [CrossRef]
- Joy, E.J.M.; Kalimbira, A.A.; Gashu, D.; Ferguson, E.L.; Sturgess, J.; Dangour, A.D.; Banda, L.; Chiutsi-Phiri, G.; Bailey, E.H.; Langley-Evans, S.C.; et al. Can selenium deficiency in Malawi be alleviated through consumption of agrobiofortified maize flour? Study protocol for a randomised, double-blind, controlled trial. Trials 2019, 20, 795. [Google Scholar] [CrossRef]
- Chiutsi-Phiri, G.; Kalimbira, A.A.; Banda, L.; Nalivata, P.C.; Sanuka, M.; Kalumikiza, Z.; Matandika, L.; Mfutso-Bengo, J.; Allen, E.; Ferguson, E.; et al. Preparing for a community-basedagriculture-to-nutrition trial in rural Malawi:formative research to assess feasibility andinform design and implementationdecisions. Pilot Feasibility Stud. 2021, 7, 141. [Google Scholar] [CrossRef]
- Joy, E.J.M.; Kalimbira, A.A.; Sturgess, J.; Banda, L.; Chiutsi-Phiri, G.; Manase, H.; Gondwe, J.; Ferguson, E.L.; Kalumikiza, K.; Bailey, E.H.; et al. Biofortified maize improves selenium status of women and children in a rural community in Malawi: Results of the addressing hidden hunger with agronomy randomized controlled trial. Front. Nutr. 2022, 8, 788096. [Google Scholar] [CrossRef] [PubMed]
- Burcham, S.; Liu, Y.; Merianos, A.L.; Mendy, A. Outliers in nutrient intake data for U.S. adults: National health and nutrition examination survey 2017–2018. Epidemiol. Methods 2023, 12, 20230018. [Google Scholar] [CrossRef] [PubMed]
- Malawi Food Composition Database (MAFOODS). Malawian Food Composition Table; MAFOODS: Lilongwe, Malawi, 2019. [Google Scholar]
- Food and Agriculture Organization (FAO); Government of Kenya. Kenya Food Composition Tables; FAO: Nairobi, Kenya, 2018.
- Food and Agriculture Organization of the United Nations. Food Composition Table for Western Africa; FAO: Rome, Italy, 2020. [Google Scholar]
- United States Department of Agriculture (USDA). U.S. Food Yields Summarized by Different Stages of Preparation; Agriculture Handbook 102; Agricultural Research Service: Washington, DC, USA, 1975.
- Iowa State University, Department of Statistics. Intake Monitoring, Assessment and Planning Program (IMAPP); Iowa State University: Ames, IA, USA, 2013. [Google Scholar]
- Moltedo, C.C. Computing levels of nutrient inadequacy from household consumption and expenditure surveys: A case study. Stat. J. IAOS 2024, 40, 279–288. [Google Scholar] [CrossRef]
- Allen, L.; Carriquiry, A.L.; Murphy, S.P. Perspective: Proposed harmonized nutrient reference values for populations. Adv. Nutr. 2020, 11, 469–483. [Google Scholar] [CrossRef]
- World Health Organization. Guidelines on Food Fortification with Micronutrients; World Health Organization: Geneva, Switzerland, 2006. [Google Scholar]
- Zimba, C.P.W. Seasonality of food availability influences dietary patterns in two farming districts of Malawi. bioRxiv 2019. [Google Scholar] [CrossRef]
- Adams, K.P.; Luo, H.; Vosti, S.A.; Kagin, J.; Ngnie-Teta, I.; Ndjebayi, A.; Assiene, J.G.; Engle-Stone, R. Comparing estimated cost-effectiveness of micronutrient intervention programs using primary and secondary data: Evidence from Cameroon. Ann. N. Y. Acad Sci. 2022, 1510, 100–120. [Google Scholar] [CrossRef]
- Zezza, J.D. Food counts. Measuring food consumption and expenditures in household consumption and expenditure surveys (HCES). Introduction to the special issue. Food Policy 2017, 72, 1–6. [Google Scholar] [CrossRef]
- Coates, J.; Rogers, B.; Blau, A.; Lauer, J. Filling a dietary data gap? Estimating individual nutrient intakes from household-level data in Ethiopia and Bangladesh. FASEB J. 2016, 30 (Suppl. S1), 669.17. [Google Scholar] [CrossRef]
- Ulimwengu, J.; Tefera, W.; Odjo, S.; Sall, L.M.; Dia, K. Assessment of Food Systems Drivers in Malawi; Donor Committee on Agriculture and Food Security (DCAFS) and Trade, Industry and Private Sector Development Partners (TIPDeP): Lilongwe, Malawi, 2021; Available online: https://docs.dcafs-tipdep-donors-mw.org/dt_docs/DOC20230511025849.pdf (accessed on 17 August 2024).
- Mason, N.M.; Jayne, T.S.; Shiferaw, B. Wheat Consumption in Sub-Saharan Africa: Trends, Drivers, and Policy Implications; International Development Working Paper 127; Michigan State University: East Lansing, MI, USA, 2012. [Google Scholar]
- Mildon, A.; Klaas, N.; O’Leary, M.; Yiannakis, M. Can fortification be implemented in rural African communities where micronutrient deficiencies are greatest? Lessons from projects in Malawi, Tanzania, and Senegal. Food Nutr. Bull. 2015, 36, 3–13. [Google Scholar] [CrossRef] [PubMed]
- Bourassa, M.W.; Atkin, R.; Gorstein, J.; Osendarp, S. Aligning the Epidemiology of Malnutrition with Food Fortification: Grasp Versus Reach. Nutrients 2023, 15, 2021. [Google Scholar] [CrossRef] [PubMed]
- Landais, E.; Pelloquin, R.; d’Hôtel, É.M.; Tuyet, M.T.; Thu, N.H.; Thao, Y.B.T.; Phuong, H.D.T.; Thu, T.T.T.; Somé, J.; Béné, C.; et al. Assessing food consumed away from home in low- and middle-income countries by developing specific modules for household surveys: Experimental evidence from Vietnam and Burkina Faso. PLoS ONE 2024, 19, e0314786. [Google Scholar] [CrossRef]
- Landais, E.; Miotto-Plessis, M.; Béné, C.; d’Hôtel, É.M.; Truong, M.T.; Somé, J.W.; Verger, E.O. Consumption of food away from home in low- and middle-income countries: A systematic scoping review. Nutr. Rev. 2023, 81, 727–754. [Google Scholar] [CrossRef]
Variable | HCES (n = 183) | 24HR (n = 177) |
---|---|---|
Household size, mean (SD) | 4.9 (1.8) | 6.6 (1.9) |
Highest education level of household head (%) | What is the highest educational qualification you have acquired? | What is the highest level of education completed by the adult woman participant? |
Primary/none | 74.9 | 82.2 |
Secondary | 18.6 | 15.6 |
More than secondary | - | 2.2 |
Don’t know | 6.6 | - |
Age groups in years (%) | n = 207 (all adult women in sample households) | |
18–19 | 16.4 | - |
20–29 | 41.5 | 32.2 |
30–39 | 26.1 | 43.3 |
40 and more | 15.9 | 24.4 |
Lactating women (%) | Proportion of households with child <24 months | Proportion of women reporting lactating |
27.3 | 33.3 | |
Age groups for breastfeeding children in months (%) | Proportion of households with child in age range | Proportion of women with child in age range |
0–6 | 24.0 | 18.6 |
7–11 | 18.0 | 25.4 |
12–23 | 58.0 | 49.2 |
≥24 | - | 6.8 |
Age of breastfeeding children, mean (SD) | Age of children <24 months in the household | Age of children (in months) of lactating women |
12.2 (6.8) | 13.0 (6.6) |
Variable | HCES | 24HR 1 | HAR—WRA 2 |
---|---|---|---|
Energy, kcal | 1603 (1145, 2063) | 2537 (2211, 2903) | - |
Iron, mg | 13.2 (8.8, 20.8) | 17.0 (14.3, 20.1) | 22.4 |
Zinc, mg | 5.9 (3.9, 9.1) | 9.1 (8.0, 10.4) | 10.2 |
Vitamin A, μg RAE | 263.7 (111.4, 561.5) | 411.8 (367, 462) | 490 |
Vitamin B1, mg | 1.2 (0.8, 2.0) | 1.6 (1.4, 1.9) | 0.9 |
Vitamin B2, mg | 0.5 (0.3, 0.6) | 0.7 (0.6, 0.7) | 1.3 |
Vitamin B3, mg | 7.8 (5.4, 11.1) | 20.0 (16.6, 23.9) | 11 |
Vitamin B6, mg | 1.2 (0.8, 1.8) | 1.7 (1.6, 1.8) | 1.3 |
Vitamin B9, μg Dietary Folate Equivalent | 246.4 (181.3, 407.4) | 304.6 (264, 349) | 250 |
Vitamin B12, µg | 0.4 (0.1, 1.1) | 0.0 (0.0, 1.4) | 2 |
Food Vehicle | HCES (n = 183) | 24HR (n = 177) | p-Value 1 |
---|---|---|---|
Sugar | |||
Intake (g/day) | 17.9 (5.6, 29.3) | 26.0 (20.1, 36.1) | <0.001 |
Coverage (%) | 42.6 | 27.7 | 0.003 |
Oil | |||
Intake (g/day) | 5.7 (2.6, 10.7) | 21.2 (10.0, 37.7) | <0.001 |
Coverage (%) | 83.6 | 45.2 | <0.001 |
Wheat flour and products | |||
Intake (g/day) | 12.6 (6.8, 18.0) | 57.0 (44.8, 77.1) | <0.001 |
Coverage (%) | 32.2 | 11.9 | <0.001 |
No Fortification | Fortification | |||||
---|---|---|---|---|---|---|
Nutrient | 24HR (%) | HCES Apparent Intake (%) | % Pt. Difference | 24HR (%) | HCES Apparent Intake (%) | % Pt. Difference |
Iron | 90.1 | 85.4 | 4.7 * | 90.0 | 85.3 | 4.7 * |
Zinc | 83.3 | 80.3 | 3.0 * | 82.7 | 79.2 | 3.5 * |
Vitamin A | 95.5 | 71.0 | 24.5 | 44.8 | 48.6 | 3.8 * |
Vitamin B1 | 2.5 | 33.9 | −31.4 | 1.7 | 33.9 | −32.2 |
Vitamin B2 | 100 | 98.9 | 1.1 * | 100 | 98.9 | 1.1 * |
Vitamin B3 | 5.3 | 73.8 | −68.5 | 4.7 | 73.2 | −68.5 |
Vitamin B6 | 19.7 | 55.2 | −35.5 | 19.0 | 54.6 | −35.6 |
Vitamin B9 | 49.3 | 52.5 | −3.2 * | 37.1 | 48.6 | −11.5 * |
Vitamin B12 | 70.4 | 88.0 | −17.6 * | 60.2 | 88.0 | −27.8 |
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. |
© 2025 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Kalimbira, A.A.; Kalumikiza-Chikumbu, Z.; Osman, G.; Mkama, B.; Joy, E.J.M.; Ferguson, E.L.; de la Revilla, L.S.; Ander, L.E.; Pedersen, S.; Dary, O.; et al. Use of Household Apparent Food Intake Data to Estimate Micronutrient Inadequacy in Comparison to the 24-h Recall Data Among Women of Reproductive Age in Kasungu District, Malawi. Nutrients 2025, 17, 2485. https://doi.org/10.3390/nu17152485
Kalimbira AA, Kalumikiza-Chikumbu Z, Osman G, Mkama B, Joy EJM, Ferguson EL, de la Revilla LS, Ander LE, Pedersen S, Dary O, et al. Use of Household Apparent Food Intake Data to Estimate Micronutrient Inadequacy in Comparison to the 24-h Recall Data Among Women of Reproductive Age in Kasungu District, Malawi. Nutrients. 2025; 17(15):2485. https://doi.org/10.3390/nu17152485
Chicago/Turabian StyleKalimbira, Alexander A., Zione Kalumikiza-Chikumbu, Gareth Osman, Bridget Mkama, Edward J. M. Joy, Elaine L. Ferguson, Lucia Segovia de la Revilla, Louise E. Ander, Sarah Pedersen, Omar Dary, and et al. 2025. "Use of Household Apparent Food Intake Data to Estimate Micronutrient Inadequacy in Comparison to the 24-h Recall Data Among Women of Reproductive Age in Kasungu District, Malawi" Nutrients 17, no. 15: 2485. https://doi.org/10.3390/nu17152485
APA StyleKalimbira, A. A., Kalumikiza-Chikumbu, Z., Osman, G., Mkama, B., Joy, E. J. M., Ferguson, E. L., de la Revilla, L. S., Ander, L. E., Pedersen, S., Dary, O., Yourkavitch, J., & Woldt, M. (2025). Use of Household Apparent Food Intake Data to Estimate Micronutrient Inadequacy in Comparison to the 24-h Recall Data Among Women of Reproductive Age in Kasungu District, Malawi. Nutrients, 17(15), 2485. https://doi.org/10.3390/nu17152485