Columbia University Analysis for the Scaling Up Nutrition (SUN) Secretariat Simulating Potential of Nutrition Sensitive Investments Slide Deck to Accompany the Technical Report January 2014
Feb 22, 2016
Columbia University Analysis for the Scaling Up Nutrition (SUN) Secretariat
Simulating Potential of Nutrition Sensitive Investments
Slide Deck to Accompany the Technical Report
January 2014
The Lives Saved Tool (LiST) Visualizer Five outcome areas, intermediary to stunting, served as key starting point for
our study
Source: http://list.cherg.org/
FAMILY PLANNING
MATERNAL NUTRITION
Lancet, 2013
Health
Environment and Water
Social Protection
Agriculture
Maternal Nutrition
[low birth weight and dietary patterns]
Family Planning
[Contraceptive use]
Exclusive Breastfeeding
[EBF for 0-6 months}
Complementary Feeding
[minimum acceptable diet]
1.Selected outcomes delivered through nutrition sensitive channels for literature search.
2.Used data available at the national level to model associations of outcomes with contextual factors.
3.Used data available at the national level and in the literature review to model associations of interventions with outcomes.
Strong or Weak
Associations for decision
making
Nutrition Sensitive Sector
Literature Review And
Modeling
Outcome Areas Predictors
Diarrhea incidence[diarrhea rate]
Education
Theoretical Framework
Public Health Model: Theoretical Framework
Public Health
Maternal Nutrition
[Low-birth weight]
Strong or Weak
Associations for
decision making
Nutrition Sensitive
Sector
Interventions/Delivery Channels
Outcome Areas
Predictors
Peer counseling Commercial packets Facility based education
Maternal education Health professional training Supplement provision
Community Health WorkersSchool promotion Media campaign
Iron/ Folic Acid Supplementation Multiple Micronutrient Supp Calcium Supplementation Balanced Energy Protein Supp
ContextualFactors
Done by LIST:
GNI per capita
Adult literacy rate
Adolescent birth rate
Female labor participation
Sec. School Enrollment
Maternity leave
Family Planning
[Contraceptive use]
Exclusive Breastfeeding
[EBF for 0-6 months}
Complementary Feeding
[minimum acceptable diet]
Environment Model: Theoretical Framework
Environment and Water
Strong or Weak
Associations for
decision making
Nutrition Sensitive
Sector
Interventions/Delivery Channels
OutcomeAreas
Predictors
Reduced diarrhea
[diarrhea rate]
Promotion of access to water and sanitation
Safety of complementary foods
ContextualFactors
% Rural Population
Adult Literacy Rates
Vaccination Rates
Agriculture Model: Theoretical framework
Agriculture
Complementary feeding (minimum
acceptable diet)
Maternal nutrition
[low birth weight; dietary patterns:
% energy from non staples, calories
per capita, micronutrient availability]
Strong or Weak
Associations for
decision making
Nutrition Sensitive
Sector
Agricultural InvestmentsOutcome areas
Predictors
Inputs• Ag biodiversity• Fertilizer • Land available for
agriculture• Water available for
agriculture• MechanizationRural Infrastructure• Irrigation• Crop storage facilities• Road infrastructure• Port infrastructure• Mobile networkInstitutions and governance• Access to finance • Policy and legal
framework• Accountability and
transparancy• Allocation of pub
resourcesMarkets• Ag imports and exports• Ag import tarifsResearch• Ag R&D
Contextual factors
Economic setting and agricultural role in society• GNI per capita• GINI index• % rural
population• % Ag value
added• % Ag
employmentHealth setting• Life expectancy• # physicians
per 1000Gender• Girls/boys ratio
in secondary school
Education• Literacy
We investigate the estimated effect of interventions in these two sectors on the following key outcomes: exclusive breastfeeding, complementary feeding, maternal diet and family planning (public health sector), and promotion of access to improved water and sanitation (environment and water sector).
Contextual models- we used country level data from The State of World Children (SOWC) 2013 report, and most recent
data available from International Labor Organization, World Bank or other sources . The available data ranges from period 2006-2010 for adolescent birth rate to year 2011 for vaccination data.
- we ran cross country multiple regression analysis with 1000 simulations to investigate the predictors of the outcome measures. We estimated the 95% confidence interval
Intervention models: Interventions in these two sectors were assessed via meta-analysis, as following: - we conducted an extensive literature review on intervention impacts on the following outcome
measures: exclusive breastfeeding, minimum acceptable diet, contraceptive use, percent of low births and diarrhea rate.
- we selected relevant studies and formatted the results as needed for meta regressions- we estimated the pooled relative risks (RR) and their respective confidence intervals (CI) using a
restricted maximum likelihood estimator (REML) on a random effect model. The pooled estimates were calculated using the natural logarithms of the RRs and their standard errors from the individual studies.
- we explored sources of heterogeneity using sub-group analysis. The sub-groups (moderators) were identified based on participant or study characteristics. For moderators that were not systematically available at the study level, we used country level data that was matched to the country of the study. Significant moderator were identified using contextual models – described below.
Public Health and Environment: Methodology
Agriculture model: Methodology
We focused on two intermediary outcome areas for the agriculture model including: maternal nutrition and complementary feeding. For both outcome areas, we developed a national-level contextual model that allows us to identify associations rather than causal relationships between agricultural and nutrition variables.
Quantitative model: - National level data from seven publicly available databases were collated and
organized to populate the model integrating agriculture (FAO, IFAD, EIU), socio-economic (World Bank), human nutrition and health (WHO NILS, WHO IYCF) data using the country as the unit
- we first identified model indicators for maternal nutrition and complementary feeding that are significantly related to stunting, while controlling for income level
- Starting from these results we fit the agricultural factors into multivariate regressions against each of these indicators while taking into account a set of contextual factors
Additional literature review:- Starting from the results of the quantitative model, we revisited the literature to
identify specific programs/ interventions and delivery channels that contribute to the implementation of the agricultural investments that were identified as significantly related to nutrition specific indicators.
Exclusive Breastfeeding
[EBF for 0-6 months}
Complementary Feeding
[Minimum acceptable diet]
Family Planning
[Contraceptive use]
Maternal Nutrition
[Low-birth weight]
GNI per
capita
0.01***[0.0001, 1.84]
8.60***[0.022,3295]
Adolescent birth rate
-0.10 [-0.21,0.03]
0.28***[0.07,0.71]
Female to male labor
participation *
maternity leave
-6.13** [-10.79,-1.60] Female
to male labor
participation
-64.31***[-95.5,-35.0]
Adult literacy: females as a % of males
0.24*[0.004, 0.48]
Ethnicity
African -17.90*[-32.16, -3.39]Asian -14.41* [-28.89, 1.09]
Asian 19.10*, [0.64, 37.66]Mixed24.59*[4.98, 44.50]
% urban
-0.56**[-0.90,-0.19]
-0.18*[0.02,0.33]
Secondary school
enrollment
female/male ratio
0.47*** [0.26,0.69]
Latino/Hispanic 12.46* ,95% CI [1.48, 23.75]
Access to
improved rural sanitati
on
0.21**[0.09,0.34]
Public Health Model: ResultsContextual model
Exclusive Breastfeeding
[EBF for 0-6 months}
Peer counseling
Contextual factors influencing the intervention effect
RR 2.46***
Public Health Model: ResultsIntervention model EBF
Non provision of commercial packets
RR 1.55***
Facility based education
RR 1.33***
Duration of BF
Adult literacy rate
% rural population
Female
labor participation
Maternity
leave
Adolescent birth rate
For interpretation: Relative Risk (RR) = 1 indicates that the outcome in intervention and control groups are equally likely to occur; RR<1 outcome in intervention is less likely to occur compared with control; RR>1 outcome in intervention is more likely to occur compared with RR>control. E.g. RR 0.6 is usually interpreted in the following way (exp for RR=0.6). (1-0.6)*100=40%, the outcome in intervention is 40% less likely to occur. If RR is 1.5, the outcome is 1.5 times more likely to occur in the intervention compared with control (or 50% increased risk.
Results of meta-regressions for the effect of peer counseling on exclusive breastfeeding in randomized controlled trials and quasi-
experimental studies Covariate
No. of observations* RR (95% CI) p-value
Duration of breastfeeding (study)3 months or less 36 1.84 (1.44 to 2.35) <0.00014 to 6 months 26 3.82 (2.80 to 5.22) <0.0001Adult literacy rate, female as % of male (country)<80 13 3.09 (1.94 to 4.92) <0.0001>=80 36 2.61 (1.96 to 3.48) <0.0001Rural population, % (country)<=30 41 2.24 (1.72 to 2.92) <0.0001>30 21 2.89 (2.04 to 4.10) <0.0001Maternity leave, # of weeks (country)<=12 19 2.79 (1.93 to 4.02) <0.000113 to 20 34 2.63 (2.00 to 3.47) <0.0001>20 9 1.38 (0.80 to 2.38) 0.2462Female labor participation rate (%) (country)<40 16 3.99 (2.63 to 6.03) <0.0001>=40 46 2.11 (1.69 to 2.64) <0.0001Adolescent birth rate (%)<=60 53 2.61 (2.07 to 3.29) <0.0001>60 9 1.81 (1.06 to 3.07) 0.0286
Results of meta-regressions for the effect of facility based education on exclusive breastfeeding in randomized controlled trials and quasi-
experimental studies Covariate No. of
observations*RR (95% CI) p-value
Duration of breastfeeding (study)3 months or less 10 1.60 (1.28 to 2.01) <0.0001
4 to 6 months 9 1.56 (1.20 to 2.04) 0.001Adult literacy rate, female as % ofmale (country)<80 4 1.98 (1.33 to 2.95) 0.0008
>=80 7 2.09 (1.58 to 2.77) <0.0001Rural population, % (country)<=30 13 1.33 (1.11 to 1.59) 0.0016
>30 7 2.05 (1.60 to 2.63) <0.0001Maternity leave, # of weeks (country)<=12 10 1.27 (1.05 to 1.54) 0.013613 to 20 9 2.07 (1.66 to 2.58) <0.0001
>20 1 1.12 (0.63 to 2.00) 0.6974Female labor participation rate (%)(country)<40 5 2.24 (1.63 to 3.08) <0.0001
>=40 15 1.39 (1.16 to 1.65) 0.0002Adolescent birth rate (%)<=60 14 1.43 (1.19 to 1.71) <0.0001
>60 6 1.89 (1.42 to 2.51) <0.0001
Public Health Model: ResultsIntervention model Family planning
Family Planning
[Contraceptive use]
School promotion, media campaign, community-based education
RR 1.15*
Environment model: ResultsContextual model
Diarrhea treatment
[% treatment with ORS]
Adult literacy
rate: females as % of males
Vaccination rate
0.31* [0.07, 0.56]
0.34* [0.03, 0.68]
Environment Model: ResultsIntervention model
Diarrhea incidence
[Diarrhea rate]
Hand washing
RR 0.76***
Water treatment
Contextual factors controlled for
Adult literac
y
% rural population
Vaccination rate
GNI per
capita
RR 0.71**
Agriculture ModelIdentification of model indicators for nutrition-related
intermediary outcomes
Stunting
Dietary patterns (proxy for maternal nutrition)
% Energy from non staples in
supply(-4.75***)
Calories per capita(-6.86***)
Fe availabilit
y from animal-products(-4.15*)
Low-birth weight(proxy for maternal nutrition)
% Low-birth
weight(2.82***)
Complementary feeding
% Minimum acceptabl
e diet(-6.51***)
CONTEXT- SPECIFICITYLog GNI per capita
Adj R2 0.84 Adj R2 0.73 Adj R2 0.32
Adj R2 0.43% energy from non staples in national food supply significantly related to % low birth weight (-1.91**)
Adj R2 0.63Fe availability from animal based products significantly related to % minimum acceptable diet (9.93*)
Agriculture ModelAgricultural investments related to dietary patterns
Dietary patterns (proxy for maternal nutrition)
% Energy from non staples in supply
Calories per capita
Fe availabilit
y from animal-products
Contextual factors influencing outcomes
6.88*** to -1.81 dependent on income level
% Energy from non staples in production
-0.39 ***
Access to finance for farmers
0.14**
# tractors per land unit
-0.34 **
Road infrastructure
Exports as % of GDP
Log GNI per capita
Fertilizer use per land unit
0.48**
% land for agriculture
0.15**
Ag R&D as % of GDP
Ag import tariffs
0.47** -0.48 **
Agriculture ModelSupply diversity as a function of production diversity
The relationship between food supply diversity and food production diversity depends on the income level of a country. For low-income countries the diversity of agricultural goods produced by a country is a strong predictor for food supply diversity; for middle- and high-income countries national income and trade are better predictors.
Agriculture ModelAgricultural investments related to complementary feeding
Complementary feeding
% Minimum acceptabl
e diet Fe availabilit
y from animal-products
Contextual factors influencing outcomes
9.02*
% Energy from non staples in production
-4.85*
Exports as % of GDP
Log GNI per capita
% land for agriculture
9.93*
Ag R&D as % of GDP
Ag import tariffs
0.47** -0.48 **
Summary Table of Model Results
Intervention Outcome Impact
Peer counselling EBF The likelihood of EBF is 2.46 higher for mothers who received peer counseling than for mothers who weren’t counseled (95% CI: 1.99 to 3.04, p<0.001).
Facility based promotion EBF The likelihood of EBF is 1.55 times higher for mothers receiving the facility based intervention than for mothers who didn’t (95% CI: 1.31 to 1.84, p<0.001).
Commercial packets of infant formula
EBF The likelihood of EBF for mothers who were not given commercial packets is 1.34 higher than for mothers who received the packets (95% CI: 1.12 to 1.59, p=0.0011).
Combined health interventions (minus mass media campaigns which was assessed qualitatively)
EBF The results show that the likelihood of exclusive breastfeeding for mothers that received the public health interventions is 2.02 higher than mothers who did not (95% CI: 1.74 to 2.34, p<0.001)
Summary Table of Model Results
Intervention Outcome Impact
Family Planning Promotion
Contraceptive Use Contraceptive use for participants who were exposed to school promotions, media campaigns and community based education is 1.16 higher than for the control groups (95% CI: 1.01 to 1.35, p<0.0425).
Hand washing Diarrhea rates The likelihood of diarrhea for those who were exposed to hand washing interventions is 24% less likely than for those in the control group (RR= 0.76% CI: 0.62 to 0.93, p=0.0074)
Water treatment Diarrhea rates The likelihood of diarrhea those who were exposed to water treatment intervention is 29% less likely than for those in control group (RR= 0.7073% CI: 0.56 to 0.90, p=0.0043).
Summary Table of Model Results
Investment
Examples specific interventions
Outcome Association
Agricultural diversification
Promotion of animal-based products, homegardens, irrigation, legume intercropping, agro-forestry
Dietary patternsComplementary feeding
Increased food supply diversity in low-income countriesPotential trade-off with calories available per capitaIncreased % of children meeting minimum acceptable diet
Agricultural intensification
Increased fertilizer use per land unit (e.g. subsidy program)Increased number of tractors per land unit
Dietary patterns Increased amount of calories available per capitaPotential trade-off with food supply diversity
Agricultural extensification
Increased % land for agriculture
Dietary patternsComplementary feeding
Increased amount of calories available per capitaPotential trade-off with % children meeting minimum acceptable diet
Rural development
Increased access to finance for farmers (e.g. microcredits)Road infrastructure
Dietary patterns Increased food supply diversity
Trade policies/ strategies
Ag import tariffsExport crops
Dietary patterns Potential trade-off with food supply diversity and micronutrient availability
Ag R&D e.g. biofortification, livestock health programs
Dietary patternsComplementary feeding
Increased micronutrient availability
Implications
• With limited evidence, the evidence at hand suggests that public health, environment and agriculture investments could support nutrition specific interventions that address undernutrition.
• A country’s contextual factors (relating to income, social, education and governance) are important to consider in their impact on nutrition outcomes with nutrition sensitive approaches.
• Examining agriculture through large scale investments, rather than nutrition interventions, can provide insight for MoA on impact for nutrition, indirectly.
• Alternative delivery channels for public health and environment, through marketing, commercialization, food safety, and social protection, are less clear in their evidence of impact.
• Evidence published in the literature remains scant and varied for nutrition sensitive interventions, and more implementation science should be published.
• Using a quantitative statistical simulation model can only go so far as with the current literature and data. This has resulted in some interesting insights but unfortunately it is not a tool that is user friendly for countries looking to scale up nutrition.
• Costing tools and perhaps game tools could provide an entry point for decision making in which this quantitative modeling could be used as a first step resource.
Implications
Maternal Nutrition
Complementary
feeding
Diarrhea incidence
Family planning
Exclusive breastfeedi
ngPUBLIC HEALTH
Peer counselingFacility-based educationNon provision of commercial packagesMaternal counselingHealth worker trainingSchool promotionMedia campaignsCommunity-based education
AGRICULTURE
Agriculture diversification - Animal products- Homegardens- Legumes- Agroforestry- Small scale
irrigationAccess to FinanceFertilizer useAgriculture research and development- BiofortificationRural infrastructureWomen empowerment
ENVIRONMENT AND WATER
Water treatment, HandwashingFood safety measures
SOCIAL PROTECTION
Conditional cash transfers
CONTEXT- SPECIFICITYIncome, Education, Urbanization, Geographic Location, Employment Policy,
Schematic Summary of Findings
(LiST results)