Post2015 Nutrition Consultation Session4 Kay Dewey

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  • IYCF Indicators document states:Consumption of any amount of food from each food group is sufficient to “count”, i.e., there is no minimum quantity, except if an item is only used as a condimentThe cut-off of at least 4 of the 7 food groups was selected because it is associated with better quality diets for both BF and non-BF children. Consumption of foods from at least 4 food groups would mean a high likelihood of consuming at least one ASF and at least one F/V that day, in addition to a staple food.Diversity scores for BF and non-BF children should not be directly compared, because breast milk is not “counted” in any of the food groups (because DD is meant to reflect the quality of the CF diet). Thus this indicator may show “better” results for children who are not BF than those who are BF in populations where formula and/or milk are commonly given to non-BF children.For the same reason, DD should not be used to compare populations that differ in prevalence of continued BF.The composite indicator (#7) can be used for comparisons across time and between populations with different rates of continued BF.
  • Moving on to results from the WDDPThis slide is for non-pregnant, non-lactating women and shows results for one of eight indicators we assessed. This shows a strong and quite consistent relationship between a simple indicator of food group diversity yesterday, and micronutrient adequacy yesterday.For this indicator, foods were grouped into 9 categories. Results were similar for more disaggregated indicators with 13 and 21 food groups. A 6-group indicator did not work as well. This 9-group indicator also excluded foods from “counting” if consumed in very small amounts (< 15 g ~=1 TBLSP); in general indicators excluding these small amounts worked better than indicators that allowed any amount to “count” in the score.Note that we have a “high outlier” on this slide. This reflects the impact of seasonality on results and specifically, the high outlier represents women in Mozambique during mango season. In Mozambique, women typically ate very few food groups but a substantial quantity of each group consumed. Most common foods were grains, legumes/nuts, mango, and other vegetables (largely tomato).You can also see that slopes are comparable, even if ranges of the indicators are very different across sites, meaning that micronutrient adequacy improved in roughly similar amount as scores increased Data points representing fewer than 10 observations are not represented
  • Bullets 1, 2: DD is only one dimension of DQ – however it is an important dimension as evidenced by the fact that all food-based…etc.
  • Post2015 Nutrition Consultation Session4 Kay Dewey

    1. 1. Candidate indicators for measuring progress at improving nutrition Kathryn G. Dewey, PhD Program in Community and International Nutrition University of California, Davis February 20, 2013
    2. 2. Anthropometric indicators (children)• Stunting: HAZ < -2 – Reflects long-term linear growth, both prenatal and postnatal – Moderately sensitive to nutrition interventions – % stunted increases with age until ~24 mo, so indicator should be measured on children 24+ mo (or age-adjusted, if includes 0-24 mo?)• Wasting: WHZ < -2 – Reflects acute undernutrition – Sensitive (in short-term) to nutrition interventions, but recidivism is common• Underweight: WAZ < -2 – Reflects combination of stunting and wasting, so is not as informative – Rates decrease as overweight becomes more common, even if stunting not reduced• Overweight: WHZ > +2 – Good indicator of rising rates of child obesity
    3. 3.  Stunting is a non-specific indicator of nutritionalstatus and overall health, including:- Quantity and quality of dietary intake (mother & child)- Pre- and post-natal exposure to infections- Environmental insults (e.g. mycotoxins, household airpollution)- Caregiving Stunting is linked to numerous adverse outcomes:• Increased child mortality• Delayed development and less schooling• Lower wages in adulthood• Increased obstetrical risks (women)
    4. 4. How strong is the link between stunting and child development/schooling?• Attained schooling +0.5 y per 1 Z difference in HAZ at 2 y of age in Brazil, Guatemala, India, Philippines (Victora et al. 2008)• Higher cognitive scores at 5 years among Vietnamese children who were taller at 1 y (+0.20-0.25 SD per 1 Z difference in HAZ) (Young Lives Project 2009)• Jamaican children stunted at 9-24 mo had cognitive deficits that persisted at 17-18 y (Walker et al. 2005)• Difference of 4 points in MDI at 18 mo between stunted vs. non- stunted children in Tanzania (McDonald et al. 2013) Heterogeneity in the strength of the association with stunting Timing of stunting may play a role (e.g. pre- vs. postnatal)
    5. 5. Dietary candidate indicators• Children under two: IYCF indicators• Adults – Household food insecurity – Measures of consumption (energy intake?) – Dietary diversity among women of reproductive age
    6. 6. Recommended core IYCF indicators• Breastfeeding: a) Early initiation of breastfeeding; b) Exclusive breastfeeding under 6 months; c) Continued breastfeeding at 1 year• Introduction of solid, semi-solid or soft foods• Minimum dietary diversity: Proportion of children 6-23 mo who receive foods from 4 or more food groups (out of 7): a) grains, roots, tubers, b) legumes, nuts, c) dairy, d) flesh foods, e) eggs, f) vitamin A-rich fruits & vegs, g) other fruits & vegs• Minimum meal frequency: Proportion of breastfed and non-breastfed children 6-23 mo who receive solid, semi-solid, or soft foods (including milk feeds for non-breastfed children) the minimum number of times or more (BF: 2 times at 6-8 mo, 3 times at 9-23 mo; non-BF: 4 times 6-23 mo)• Minimum acceptable diet: Proportion of children 6-23 mo who receive a minimum acceptable diet – Breastfed children who had at least minimum dietary diversity and minimum meal frequency – Non-breastfed children who received at least 2 milk feedings and had minimum dietary diversity and minimum meal frequency• Consumption of iron-rich or iron-fortified foods
    7. 7. Median prevalence values of IYCF indicators for 46 countries (data range from 2002 to 2008) Lutter C K et al. Pediatrics 2011;128:e1418-e1427©2011 by American Academy of Pediatrics
    8. 8. Women’s dietary diversity & micronutrient adequacy(Arimond et al., Women’s Dietary Diversity Project, J Nutr. 2010) “MPA” is probability of adequacy averages across 11 micronutrients
    9. 9. Dietary diversity as an indicator?• Reflects dietary quality• All food-based national dietary guidelines include this dimension, usually via recommended food groups for daily consumption• DD indicators are robust: Across all studies and all DD indicators, there are moderate to strong associations with nutrient density and/or nutrient intakes• However, DD indicators are imperfect: Indicator performance (sensitivity, specificity, and best cut-offs) vary by context and all indicators result in some misclassification• For children 6-23 mo, “minimum acceptable diet” may be a better indicator because it can be used for comparisons across time and between populations with different rates of continued breastfeeding.
    10. 10. Summary - Anthropometric• Consider stunting as key indicator rather than underweight? • Pros: better indicator of conditions that support health and development; if weight is measured can also track overweight • Con: requires measuring height – technical & resource challenges• Also include adult & child overweight as indicators?
    11. 11. Summary - Dietary• Children (6-24 mo): consider minimum acceptable diet as key indicator? – Pros: raises attention to IYCF, dietary quality; lots of room for improvement – Cons: composite indicator requires several survey questions; validation results better for dietary diversity than for meal frequency• Adults: consider two indicators? – Household food insecurity • Pros: marker of access to food; sensitive to economic trends • Cons: requires several survey questions; are cross- population comparisons valid? – Dietary diversity among women of reproductive age • Pros: reflective of dietary quality; validation data available • Cons: sensitivity, specificity and best cut-off values vary across populations

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