Odilia I. Bermudez, Tufts University School of Medicine with John L. Fiedler and Keith Lividini International Food Policy Research Institute (IFPRI)

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1 Odilia I. Bermudez, Tufts University School of Medicine with John L. Fiedler and Keith Lividini International Food Policy Research Institute (IFPRI)

2 Globally, there is a scarcity of national food consumption data Collected with acceptable periodicity and valid representation from all population groups and regions Collected directly from the food consumers The scarcity of such data is most common and tragic in low- and medium-income countries

3 National food consumption data is needed for several purposes, including: Assessment of food consumption patterns Identification of groups at risk of nutrient deficiencies Identification of food fortification or biofortification vehicles Nutrition surveillance Monitoring evaluating food and nutrition interventions

4 To overcome this scarcity of dietary data, alternative sources of information have to be used. For example, food consumption patterns and apparent intakes of energy and nutrients may be obtained from national household consumption and expenditure surveys (HCES) This type of surveys Collect national and regional representative data Collect data on food acquisition and/or food costs Are conducted periodically

5 To use the Household Consumption and Expenditure Survey (HCES) conducted in Bangladesh in 2010 to: Assess food sources of energy and of Vitamin A, Iron and Zinc Assess risk for inadequate intakes of those micronutrients Identify potential food vehicles for nutrient fortification

6 Data from the 2010 HCES from Bangladesh Demographics, Income and economic data Food and non-food expenditure Food acquisition by origin o Purchased o Produced o Gifted (gifts, donations) o Other (e.g. wage in-kind) Foods consumed at home and away from home

7 Food acquisition data was collected over a 14 days period (at household levels) Converted into daily food amounts Development of a Food Composition Table for foods in the BD-2010 HCES Assessment of data plausibility Per capita energy intake <500 or >6,000 kcal/d Statistical estimations with sample expanded with sample weights

8 Intra-household food and nutrient distribution was estimated with adult consumption equivalents (ACE)* Nutrient Recommendations: Vit A: IoM Estimated Average Requirements (EARs) Iron: DRIs from IoM, adjusted to 5% bioavailability Zinc: Recommendation from the International Zinc Consultative Group with bioavailability based on an unrefined, cereal-based diet * As defined by FAO

9 DEMOGRAPHICS (2010) The average household size was 4.5 members Higher for rural (4.5) than for urban (4.4) households Data source: BD-2010 HCES

10 Data source: BD-2010 HCES

11 Data source: BD-2010 HCES

12 Data source: BD-2010 HCES

13 Data source: BD-2010 HCES

14 Data source: BD-2010 HCES

15 Data source: BD-2010 HCES

16 Data source: BD-2010 HCES

17 Data source: BD-2010 HCES 1 Estimated with the cut-point method 2 Estimated with probability method

18 Apparent intakes of foods and selected micronutrients were successfully estimated with the 2010 HCES of Bangladesh We were able to assess inadequate intakes of specific MNs (vit A, iron and zinc) A particular strength of the data was the inclusion of foods eaten away from home Inadequate MN intakes were more prevalent among those from the rural sector and from the lower poverty status

19 Use of HCES, non-dietary data, for dietary purposes Assumptions for intra-household food distribution based on pre-established factors (e.g. ACE) Potential for over-estimation of consumption due to Over-reporting Wastage Stockpiling

20 Nutrient analyses, such as those reported here, are valuable, particularly in the absence of direct measurements of food consumption The results could guide the identification of vulnerable populations that could be targeted for: micronutrient fortification supplementation programs or, other types of interventions

21 Questions? Comments?