Local Determinants of Malnutrition:  Formative Research and Programmatic              Implications         FOOD FOR THE HU...
Introduction to the LDM: Where & How?                    South Sudan           Ethiopia                       (2011)      ...
Introduction to the LDM: Where & How?                               Goal: to identify a few critical behaviors            ...
Why was the LDM developed?                                  Local Determinants of  Positive Deviance Inquiry              ...
LDM Methodology Population                      Case Control o Ideal population: 12 to 24        o Cases: PD children   ...
LDM Methodology (cont.) Sampling o 45 PD and 45 malnourished caregivers (minimum) o 80% power, 0.05 alpha, 35% proportion...
LDM Tool Development Survey tool includes 4 domainsWorldview & Maternal                                     IncomeDepress...
LDM Analysis  Outcome:                PD/Malnourished                          Dichotomous  Exposure variables:     Indica...
Limitations Based upon a convenience    sampling frame   Quantitative method may miss    nuances of a qualitative study...
Applications of the Results             11
DiscussionGuide•   Results from a 2012    LDM in DRC•   Program overview•   Choose 2    determinants and    complete the  ...
Resources LDM Manual (in development) Associated Costs Estimated timeline for adjusting, conducting and analyzing a LDM...
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Local Determinants of Malnutrition_Wetzel, Cutherell, Borger_10.12.12

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  • Developed in 2003 and used in 7 countries (6 Africa, 1 LA; Moz ‘04, Kenya ‘05, Bolivia ‘07, Ethiopia ‘08, Burundi ‘09, South Sudan ‘11, DRC ‘12)Based on interviews of mothers of PD and malnourished children and compares their responsesThe goal of the tool, like other PD approaches, is to identify a few critical behaviors that could accelerate improvements in nutrition status that are more likely to be affordable, acceptable, and sustainable because some members of the community are already practicing them.Marsh D and Schroeder D, The positive deviance approach to improve healthoutcomes: experience and evidence from the field—Preface. Food and Nutrition Bulletin. Vol 23, no 4. 2002. Available for download from: http://docserver.ingentaconnect.com
  • Developed in 2003 and used in 7 countries (6 Africa, 1 LA; Moz ‘04, Kenya ‘05, Bolivia ‘07, Ethiopia ‘08, Burundi ‘09, South Sudan ‘11, DRC ‘12)Based on interviews of mothers of PD and malnourished children and compares their responsesThe goal of the tool, like other PD approaches, is to identify a few critical behaviors that could accelerate improvements in nutrition status that are more likely to be affordable, acceptable, and sustainable because some members of the community are already practicing them.Marsh D and Schroeder D, The positive deviance approach to improve healthoutcomes: experience and evidence from the field—Preface. Food and Nutrition Bulletin. Vol 23, no 4. 2002. Available for download from: http://docserver.ingentaconnect.com
  • Developed in 2003 and used in 7 countries (6 Africa, 1 LA; Moz ‘04, Kenya ‘05, Bolivia ‘07, Ethiopia ‘08, Burundi ‘09, South Sudan ‘11, DRC ‘12)Based on interviews of mothers of PD and malnourished children and compares their responsesThe goal of the tool, like other PD approaches, is to identify a few critical behaviors that could accelerate improvements in nutrition status that are more likely to be affordable, acceptable, and sustainable because some members of the community are already practicing them.Marsh D and Schroeder D, The positive deviance approach to improve healthoutcomes: experience and evidence from the field—Preface. Food and Nutrition Bulletin. Vol 23, no 4. 2002. Available for download from: http://docserver.ingentaconnect.com
  • Quantitative PDI tool that is easy and affordable to be implement at the field levelChallenges with Qualitative studies in the fieldTable with PDI and LDM comparisonQualitative/ QuantitativeLDM can measure the strength of association and account for confoundingPDI studies are more observational and nuanced
  • PopulationIdeal age is 12- 24m, but with reality/ time limitations LDM age range is usually 12-36mCase ControlDefinition of cases: PD mothers, weight cut-offs are context specific at least >=-1SD for PD children and <=-2 SD WAZ or HAZ for malnourished childrenSampling45 PD /45 Malnourished (80% power, alpha = 0.05, 35% proportion)Random sample of communities, pulled from a weighted convenience sampling frame; with convenience sampling at the community level8-12 communities, with approximately ½ day each community per team and about 12 interviews in each community (6 PD/ 6 Malnourished)
  • PopulationIdeal age is 12- 24m, but with reality/ time limitations LDM age range is usually 12-36mCase ControlDefinition of cases: PD mothers, weight cut-offs are context specific at least >=-1SD for PD children and <=-2 SD WAZ or HAZ for malnourished childrenSampling45 PD /45 Malnourished (80% power, alpha = 0.05, 35% proportion)Random sample of communities, pulled from a weighted convenience sampling frame; with convenience sampling at the community level8-12 communities, with approximately ½ day each community per team and about 12 interviews in each community (6 PD/ 6 Malnourished)
  • Covers 7 areas or domains: 1) household income, mother’s income, and income generating work; 2) child feeding practices; 3) childcare practices (including hygiene practices); 4) care seeking behaviors; 5) feeding practices during pregnancy and breastfeeding; 6) worldview; and 7) maternal depression.Currently 81 questions (1.5 hours), desire to move to <=40 questions (45m) Developed by Tom Davis and Phil Moses based on exhausted literature review to determine (a) determinants, (b) the strength of those determinants, (c) the feasibility of measurement, and (d) ability to change the behavior.
  • At this point analysis is conducted at the HQ levelUsing Epi 3.5.3Determinants are run as dichotomous and/or continuous exposures and tested for confounding
  • Convenience sample frameQuantitative missing nuances of QualitativeWealth/equality variableCounter-intuitive findings
  • Meant to find key issues (same as intro)For example, in Kenya (2005) the LDM found that ‘mothers of malnourished children were away from their child an average of 6.7 hours per day vs. 5.0 hours for mother of PD children.’ As a result, the FH team investigated barriers to spending more time with children using qualitative methods.For example, in DRC (2012) the LDM found that ‘mothers of malnourished children were 4.5 times more likely to have introduced semi-solid/mashed foods late (at 9 months of age or after) than mothers of PD children.’ As a result, the Care Group curriculum about complementary feeding was revised to highlight the importance of introducing thick, nutritious porridge or mashed foods at 6 months.Introduction of the discussion guide
  • Meant to find key issues (same as intro)For example, in Kenya (2005) the LDM found that ‘mothers of malnourished children were away from their child an average of 6.7 hours per day vs. 5.0 hours for mother of PD children.’ As a result, the FH team investigated barriers to spending more time with children using qualitative methods.For example, in DRC (2012) the LDM found that ‘mothers of malnourished children were 4.5 times more likely to have introduced semi-solid/mashed foods late (at 9 months of age or after) than mothers of PD children.’ As a result, the Care Group curriculum about complementary feeding was revised to highlight the importance of introducing thick, nutritious porridge or mashed foods at 6 months.Introduction of the discussion guide
  • Add picture of the discussion guide.Adjust instructions based on program activities and column names
  • We are currently working on a LDM ManualAt the back of the slide printouts there are some additional resources including:Timing of the study during the LOABudget OutlineTimeline for modifying, conducting and analyzing the LDM
  • Local Determinants of Malnutrition_Wetzel, Cutherell, Borger_10.12.12

    1. 1. Local Determinants of Malnutrition: Formative Research and Programmatic Implications FOOD FOR THE HUNGRY Carolyn Wetzel, Director of Health Programs Andrea Cutherell, MCHN Coordinator Sarah Borger, MCH Coordinator October 12, 2012
    2. 2. Introduction to the LDM: Where & How? South Sudan Ethiopia (2011) (2008)   DRC Kenya  (2012)  (2005)  Burundi Bolivia (2009) (2007)   Mozambique (2004) 3
    3. 3. Introduction to the LDM: Where & How? Goal: to identify a few critical behaviors that could accelerate improvements in nutrition status that are more likely to be affordable, acceptable, and sustainable because some members of the community are already practicing them.11. David R. Marsh and Dirk G. Schroeder, The positive deviance approach to improve health Outcomes, Food and Nutrition Bulletin 2002 4
    4. 4. Why was the LDM developed? Local Determinants of Positive Deviance Inquiry Malnutrition (LDM) Qualitative  Quantitative Observational  Measures the strength of Nuanced association  Accounts for confounding
    5. 5. LDM Methodology Population  Case Control o Ideal population: 12 to 24 o Cases: PD children months of age o PD: at least ≥ -1 SD WAZ/HAZ o Actual population: 12 to 36 o Malnourished: at least ≤ -2 SD months of age WAZ/HAZ 6
    6. 6. LDM Methodology (cont.) Sampling o 45 PD and 45 malnourished caregivers (minimum) o 80% power, 0.05 alpha, 35% proportion o Random sample of communities, from a weighted convenience sampling frame with convenience sampling at the community level o 8-12 communities with ~12 interviews in each Project area Convenience sample within 2-3 hour radius of training facility • Training Center 7
    7. 7. LDM Tool Development Survey tool includes 4 domainsWorldview & Maternal IncomeDepressionChildcare & Care Feeding practices (pregnancy,Seeking Behaviors breastfeeding, and child) Currently 81 questions, editing to 40 questions Developed by Tom Davis and Phil Moses based on an exhaustive literature review 8
    8. 8. LDM Analysis Outcome: PD/Malnourished Dichotomous Exposure variables: Indicators within 4 domains Continuous and Dichotomous Analyzed using EpiInfo 3.5.3 Tests for interaction and confounding Data entry at the field level but analyzed by HQ 9
    9. 9. Limitations Based upon a convenience sampling frame Quantitative method may miss nuances of a qualitative study Challenges finding a reliable wealth/equity variable Detection of counter-intuitive findings Ration-dependent environments 10
    10. 10. Applications of the Results 11
    11. 11. DiscussionGuide• Results from a 2012 LDM in DRC• Program overview• Choose 2 determinants and complete the activities and messages
    12. 12. Resources LDM Manual (in development) Associated Costs Estimated timeline for adjusting, conducting and analyzing a LDM study 14
    13. 13. Questions?
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