Reducing Anemia through Food Fortification at Scale

Our proposed project will leverage the existing state-run public distribution system (PDS) to provide fortified rice using a domestically manufactured rice grain (Fortified Rice Kernels, or FRK). FRKs are grains made from rice flour, highly enriched with iron and other micronutrients (such as Vitamin A, B9 and Vitamin B12), and shaped like a conventional grain of rice. It is mixed into conventional rice in specified ratios (1g of FRK 100g of conventional rice) and is almost indistinguishable from conventional rice in appearance and taste.

The Tamil Nadu PDS already provides up to 20 kilograms of rice at no cost to all households in the state, with an additional 15 kilograms to households identified as particularly poor. This is done through a widespread network of Fair Price Shops (FPS). Our proposed project (implementation and accompanying evaluation) will be conducted as a cluster-randomized controlled trial, with baseline and follow-up surveys conducted 12-15 months apart. In the interim, 110 Treatment FPS will be randomly assigned to receive fortified rice, and another 110 randomly assigned Control FPS will continue receiving conventional rice. We plan to conduct the study in one sub-district of Tamil Nadu with a population of about 1/2 million people.

In cluster, we will randomly select 40 households to participate in the baseline and follow-up surveys. These surveys will collect information about dietary patterns and socio-economic status – and importantly, they will also collect objectively measured health indicators (biomarkers), enabling us to test directly for anemia and micronutrient deficiencies.

To implement the intervention we will use the Government pre-existing PDS system. Every household in Tamil Nadu has a card that entitles it monthly to a pre-specified quantity of rice (and other goods) from a specific location that belongs to a network of so called Fair Price Shops (FPS). These FPS in turn receive rice from government-run warehouses (called godowns) where rice is delivered from a central procurement system and then bagged.

Our treatment and control interventions will be implemented as follows:

Arm 1 (Treatment): PDS fortified rice. All households receiving rice from the PDS will receive fortified rice instead of conventional PDS rice. Because a given FPS only receives rice from a single upstream distributor (godown) it should be straightforward to ensure that fortified rice reaches the appropriate treatment FPS and only those FPS.

Arm 2 (Control): Conventional PDS Rice. FPS assigned to this arm will continue receiving conventional (non-fortified) PDS rice. This experimental arm therefore represents the status quo and serves as a control group against which any improvements observed in the treatment group will be gauged.

2018-10-15

2020-01-15

1. Change in hemoglobin level from baseline to endline using Rapid Diagnostic Tests (RDT)
Rapid Diagnostic Tests (RDT), using Hemocue machine, will be used to measure Hemoglobin concentrations in 40 women and 40 children tested in each FPS catchment area (total sample size 17600 women and children). Hemoglobin (Hb) will be tested with the HemoCue analyzer, a portable, accurate system for measuring Hb. Hb measures will be used to calculate prevalence of anemia among the target population of women and young children. The test requires less than 0.5 ml of blood and delivers results in approximately 15 minutes.
[Time Frame: This will be measured at (1) Baseline, (2) Endline]
2. Change in hemoglobin level from baseline to endline using DBS
Hemoglobin (Hb) will also be measured separately in a sub-sample of individuals (10 children and 10 women per FPS) using Dried Blood Spots (DBS) that will be transported to a lab for analysis. It will take up to 15 minutes for each respondent.
[Time Frame: This will be measured at (1) Baseline, (2) Endline]
3. Change in Transferrin Receptor (TfR) level from baseline to endline using DBS
Transferrin Receptor (TfR) will also be measured separately in a sub-sample of individuals (10 children and 10 women per FPS) using Dried Blood Spots (DBS) that will be transported to a lab for analysis. TfR is a good indicator of iron stores in the body, and this marker is expected to improve following food fortification. We will also be measuring C-Reactive Protein (CRP). CRP is useful both to detect the presence of inflammation and to identify cases where measured TfR is likely to give a biased account of iron stores, given that TfR becomes elevated in the presence of acute and sometimes chronic infections; thus, TfR will be corrected for inflammation using CRP. It will take up to 15 minutes for each respondent.
[Time Frame: This will be measured at (1) Baseline, (2) Endline]
4. Change in anemia measured by RDT (Hemocue machine) and DBS from baseline to endline
[Time Frame: This will be measured at (1) Baseline, (2) Endline]

Anemia measured by RDT (Hemocue machine) and DBS: Hb measured from RDT, i.e. Hemocue machine, and DBS will further be categorized to estimate the prevalence of anemia among the study population using established Hb thresholds. Based on the WHO classification, the following thresholds will be considered:
For children aged 6 to 59 months:
• No anemia: Hb >= 11 g/dL
• Mild anemia: 10 < Hb < 10.9 g/dL
• Moderate anemia: 7 < Hb < 9.9 g/dL
• Severe anemia: Hb < 7 g/dL
For non-pregnant women aged 12 years and above:
• No anemia: Hb >= 12 g/dL
• Mild anemia: 11 < Hb < 11.9 g/dL
• Moderate anemia: 8 < Hb < 10.9 g/dL
• Severe anemia: Hb < 8 g/dL
For pregnant women aged 12 years and above:
• No anemia: Hb >= 11 g/dL
• Mild anemia: 10 < Hb < 10.9 g/dL
• Moderate anemia: 7 < Hb < 9.9 g/dL
• Severe anemia: Hb < 7 g/dL

5. Change in height from baseline to endline
Height will be measured for all study participants (children that are 6 months and older, and women between the ages of 12 and 40 years) at baseline and endline. This will take up to 10 minutes.
[Time Frame: This will be measured at (1) Baseline, (2) Endline]
6. Change in weight from baseline to endline
Weight will be measured for all study participants (children that are 6 months and older, and women between the ages of 12 and 40 years) at baseline and endline. This will take up to 10 minutes.
[Time Frame: This will be measured at (1) Baseline, (2) Endline]
7. Change in productivity from baseline to endline Employment status, hours worked, productivity, and earnings will be measured for working age adults at baseline and endline. This will take approximately 10 minutes.
[Time Frame: This will be measured at (1) Baseline, (2) Endline]
8. Change in cognitive outcomes for children from baseline to endline
Cognitive outcomes for children using Development Milestones Checklist and Wechsler Preschool and Primary Scale of Intelligence instruments, as well as school enrollment and attendance data for older children will be measured. This will take approximately 30 minutes to administer.

Experimental: Treatment
110 Fair Price Shops (FPS) in Chidambaram, Tamil Nadu, India will be assigned randomly to receive rice fortified. Rice will be fortified using Fortified Rice Kernels (FRKs) containing iron, zinc, vitamin A and vitamins B1, B3, B6, B9 and B12. All households receiving rice from the PDS will receive fortified rice instead of conventional PDS rice, and members of households sampled for baseline will have blood samples and demographic surveys taken at a baseline visit, and another visit at 12-15 months after the baseline visit. Because a given FPS only receives rice from a single upstream distributor (godown) we will be able to ensure that fortified rice reaches the appropriate treatment FPS and only those FPS.

No Intervention: Control:
The control arm, i.e. FPS not a part of the treatment shops, will continue to receive the regular rice supplied by the Public Distribution System (PDS), and members of households sampled for baseline will have blood samples and demographic surveys taken at a baseline visit, and another visit at 12-15 months after the baseline visit. It therefore represents the status quo and serves as a control group against which any improvements observed in the treatment group will be gauged.

Randomization done in office by a computer

The unit of randomisation is FPS and associated population within the catchment area of FPS, and treatment is then clustered at the FPS level. the treatment is clustered at the Fair Price Shop (FPS) level. Every household in Tamil Nadu has a card that entitles it monthly to a pre-specified quantity of rice (and other goods) from a specific location that belongs to a network of FPS. These FPS in turn receive rice from government-run warehouses (called godowns) where rice is delivered from a central procurement system and then bagged.

Yes

As stated above, the study will follow a randomized cluster design at the Fair Price Shop (FPS) level, that is, Fair Price Shops will be randomly assigned either to the treatment or the control arm. 110 FPS will be assigned to the treatment arm, and 110 FPS will be assigned to the control arm.

In each area of the 220 FPS, we will obtain a list of all households from a census that will be conducted by our survey team. Households with at least one child 6-59 month old or a woman 12-40 will be ordered randomly using a random number generator in Stata, setting first a seed to ensure replicability. We will then conduct interviews following the randomized order until we have reached a total of 40 children and 40 women in each cluster. Interviews with the same households will be sought at endline. We thus expect to test a total of 220*40=8,800 women between ages of 12 and 40 years and 8,800 children between the ages of 6 to 59 months at baseline. Ideally we will select the same numbers at endline although given attrition the actual number of blood tests completed at endline will be lower.

See above

Our calculations of statistical power focus on blood haemoglobin (Hb) concentrations and anemia prevalence as primary outcomes of interest. We will also study impacts on a number of other bio-markers and health indicators (in particular ferritin levels, a key indicator of iron stores), socio-economic outcomes and cognitive outcomes for children, but we base power calculations on Hb concentrations and anemia prevalence because such outcomes are particularly demanding in terms of statistical power. Using data from rural areas surveyed in the 2005-06 round of the NFHS, we find that the intra-village correlations for hemoglobin and anemia range from 0.02 for anemia among men to 0.11 for anemia among children (6-59 month old). Data from the 1998-99 round of the NFHS confirm similar estimates. The survey of randomized evaluations of food fortification with iron reported in Gera et al (2012) finds an average increase in Hb of 0.28 g/dl (95% CI: 0.28-0.56), and an average reduction in the risk of anemia of 41% (95% CI: 0.29-0.52%). Recent data from the 2012-13 District Level Household Survey (DLHS) show wide variation in the prevalence of anemia across districts in Tamil Nadu. In several districts anemia rates are 50% or higher among women of fertility age, and 60% or higher among children and we use these figures to approximate anemia prevalence at baseline. We thus calculate first the effect size (E), defined as the ratio between the minimum difference between groups that the researcher is interested in being able to estimate precisely (in the numerator) and the standard deviation of the outcome at baseline (in the denominator). If we evaluate the power of estimating a relatively small 15% reduction in anemia, the effect size for anemia among women of fertility age is 0.15 (= 0.50*0.15/sqrt(0.5*0.5)), while it is 0.18 (0.60*0.15/sqrt(0.6*0.4)) for children. We also assume conservatively that the intra-village correlation (R) will be 0.10 and that baseline Hb and anemia will explain only 10% of the variation in the outcomes (R2=0.10). Given these numbers, we propose to study 220 clusters (each cluster corresponds the catchment area for a FPS), randomly allocated to either T (n=110) or C (n=110). Using the Optimal Design software, we estimate that with R = 0.10 and R2 = 0.10, we will need 40 tests per cluster to generate a 91% probability of detecting an effect size E = 0.15 using a 95% confidence level. We also did power calculations for different choices of parameters, including 160 control clusters and 60 treatment clusters (with 40 tests per cluster); 150 control clusters and 50 treatment clusters (with 20 tests per cluster); and 120 control clusters and 60 treatment clusters (with 40 tests per cluster). Statistical power remains in the range of 70-90% even when different parameters are varied in the experimental design. Final decisions will be made keeping in mind logistical and budgetary constraints.