An interactive dashboard measuring micronutrient intake, dietary diversity, and the prevalence of inadequacy across Indian households — by state, income level, demographic group, and more.
All intake estimates are benchmarked against the ICMR-NIN Recommended Dietary Allowances for a reference adult woman (55 kg, moderately active, non-pregnant and non-lactating). Inadequacy is assessed using the Estimated Average Requirement (EAR) cut-point method.
The Indian Council of Medical Research — National Institute of Nutrition (ICMR-NIN) publishes nutrient requirements for different age-sex-activity groups. The Estimated Average Requirement (EAR) represents the intake level that meets the needs of 50% of the population — individuals consuming below the EAR are classified as having inadequate intake.
The Recommended Dietary Allowance (RDA) is set higher, covering the needs of ~97.5% of the population. While the dashboard reports intake relative to both benchmarks, the prevalence of inadequacy is formally computed using the EAR cut-point method.
The dashboard also tracks intake excluding cereals — because cereals dominate many Indian diets, this metric reveals how much micronutrient intake depends on non-cereal food sources, which is a marker of dietary quality.
Finally, the Shannon Diversity Index measures how evenly a given micronutrient's intake is spread across different food groups. A higher index means more diversified sources — a sign of a more resilient, balanced diet.
| Micronutrient | EAR | RDA | Unit |
|---|---|---|---|
| Calcium | 800 | 1000 | mg |
| Iron | 15 | 29 | mg |
| Zinc | 11 | 13.2 | mg |
| Vitamin B1 | 1.4 | 1.7 | mg |
| Vitamin B2 | 2 | 2.4 | mg |
| Vitamin B3 | 12 | 14 | mg |
| Vitamin B6 | 1.6 | 1.9 | mg |
| Vitamin B9 (Folate) | 180 | 220 | mcg |
| Vitamin C | 55 | 65 | mg |
The dashboard provides three complementary ways to assess micronutrient status.
Mean daily intake of each micronutrient from all food sources combined. Compared against EAR and RDA benchmarks to gauge whether households meet requirements.
Micronutrient intake from non-cereal food sources only. This reveals the quality dimension — how much nutrition comes from diverse foods beyond the staple grain base.
The Shannon Diversity Index applied to each micronutrient's food-group sources. Higher values mean intake is spread across many food groups rather than concentrated in one.
A fully interactive tool for researchers, policymakers, and journalists to investigate micronutrient intake patterns across India.
Toggle between HCES 2011–12 and 2023–24, or use Compare mode to overlay both rounds and track how micronutrient intake has changed over a decade.
Slice data by sector, state, religion, social group, household head, children, and month of survey to reveal nutrient gaps across populations.
Switch between expenditure deciles and continuous MPCE (log scale) on the x-axis to see how intake changes across the income distribution.
All estimates come from a Bayesian model. Toggle 95% credible intervals on or off for both line charts and bar comparisons.
Export charts as PNG or SVG with citation, download the current data view as CSV, or grab the full dataset for your own analysis.
Select multiple groups simultaneously to compare intake patterns side by side — states, religions, castes, or sectors on the same chart.
Select one or more groups within each dimension to compare micronutrient intake patterns side by side.
Rural vs. Urban — how urbanisation shapes micronutrient intake.
All states and union territories, revealing vast geographic variation in nutrient adequacy.
Hindu, Muslim, Christian, Sikh, and other religious groups with distinct food cultures.
Scheduled Tribes, Scheduled Castes, OBCs, and other groups.
Male- vs. female-headed households and their differing nutrient profiles.
Households with and without children — does family composition affect nutrient adequacy?
Seasonal variation in micronutrient intake across the survey year.
Rigorous statistical modelling underpins every number in the dashboard.
Household food consumption quantities from HCES are converted into micronutrient intake using Indian food composition tables, creating nutrient-level estimates from expenditure data.
Generalised additive models with thin-plate regression splines and factor-smooth interactions capture non-linear Engel curves for each micronutrient across demographic groups.
Micronutrient intake is benchmarked against ICMR-NIN EAR values using the cut-point method. The proportion of households falling below EAR yields the prevalence of inadequacy.
For each micronutrient, the share of intake from each food group is computed and Shannon entropy applied — capturing how diversified the nutrient sources are for each household.
Dive into the interactive dashboard to uncover patterns, compare groups, and download data for your own research.
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