What the data is, where it comes from, and how the numbers are made
The badge in the top bar shows “Sample data” (amber) until the real survey numbers are loaded. In that mode the values you see are approximate placeholders generated only so the interface works and can be demonstrated — they are not real BDHS results and must not be quoted. Every placeholder is marked with a grey/red reliability dot for the same reason.
The badge turns green “Live data” automatically once real, survey-weighted estimates are
loaded into data/master.json. There are two honest ways to produce those real numbers,
and neither one invents or predicts anything:
scripts/convert_dta.py on the original
BDHS Stata .dta files. It applies the official sampling weights and computes each
indicator directly from the raw survey responses. No Python on your PC? Run it free in
Google Colab (see the README) and upload the resulting master.json to Hostinger.FR386.pdf) are the official weighted estimates; those can be entered directly.Until then, treat the dashboard as a working demo, not a source of numbers.
The atlas draws on the Bangladesh Demographic and Health Surveys (BDHS) — large, nationally representative household surveys implemented by the National Institute of Population Research and Training (NIPORT) with technical support from The DHS Program (ICF) and funding from USAID. Bangladesh has run BDHS rounds in 1993-94, 1996-97, 1999-2000, 2004, 2007, 2011, 2014, 2017-18 and 2022. This project uses the rounds you supplied, from 1996-97 through 2022.
Each round interviews tens of thousands of households and eligible women (and, in some rounds, men), collecting fertility, family-planning, maternal and child-health, nutrition, anaemia, mortality and household-environment information using standardised questionnaires that are comparable across countries and over time.
| Round | Folder | Main topics added / notes |
|---|---|---|
| 1996-97 | BD_1996-97_DHS… | Core fertility, FP, child health |
| 1999-00 | BD_1999-00_DHS… | + nutrition/anthropometry expansion |
| 2004 | BD_2004_DHS… | + HIV/AIDS knowledge, wider health |
| 2007 | BD_2007_DHS… | Maternal & newborn care detail |
| 2011 | BD_2011_DHS… | + biomarkers (anaemia, BP) |
| 2014 | BD_2014_DHS… | Rangpur reported as a division |
| 2017-18 | BD_2017-18_DHS… | Mymensingh added; biomarkers |
| 2022 | BD_2022_DHS… | Largest round; first designed for some district-level estimates |
Exact sample sizes and the indicators available differ by round — always confirm against the corresponding final report before quoting a figure.
DHS distributes each round as several standardised “recode” Stata files. Each file is a
different unit of analysis. Inside every round folder you supplied you will see codes like
BDIR…, BDKR… etc.:
| Code | Recode | One row = | Used here for |
|---|---|---|---|
| IR | Individual / Women | a woman 15–49 | Contraception, ANC, skilled birth, fertility, child marriage, women's anaemia/BMI, education |
| MR | Men | a man 15–54/59 | Men's knowledge/behaviour (optional) |
| KR | Children (Kids) | a living child < 5 | Immunisation, diarrhoea/ARI treatment, breastfeeding, child anthropometry |
| BR | Births | a birth in the birth history | Infant & under-5 mortality rates |
| HR | Household | a household | Water, sanitation, electricity, wealth quintile |
| PR | Household members (Persons) | a person in the household | Anthropometry & anaemia rosters, education, residence |
| CR | Couples | a matched couple | Couple-level FP analysis (optional) |
| HW / WI | Height-Weight / Wealth Index | child / household | Older-round nutrition & wealth |
| GC | Geographic Covariates | a survey cluster | Cluster context (see the PDF descriptions in each GC folder) |
scripts/convert_dta.py opens the correct recode for each indicator, applies the
weight, groups by division/district, and writes the results the dashboard reads.
The atlas computes 24 indicators across four themes. Each is a survey-weighted proportion (or a rate/mean) using the standard DHS variable shown:
| Theme | Indicators (DHS variable) |
|---|---|
| Child health & mortality | Stunting (hw70<−2SD), wasting (hw72), underweight (hw71), under-5 & infant mortality (birth history), Penta-3 (h7), measles (h9), full immunisation, ORS for diarrhoea (h13) |
| Maternal & reproductive | Modern contraception (v313=3), unmet need (v624), ANC 4+ (m14), skilled birth attendance (m3), facility delivery (m15), total fertility rate, married before 18 (v511) |
| Nutrition & anaemia | Child anaemia, women's anaemia (v457), exclusive breastfeeding, women thin BMI<18.5 (v445) |
| Household, WASH & wealth | Improved water (hv201), improved sanitation (hv205), electricity (hv206), women with secondary+ education (v106) |
Full definitions appear in the tooltip on each indicator button and in
data/indicators.json.
BDHS uses a stratified, two-stage cluster sample, so every record carries a sampling weight
(v005/hv005, divided by 1,000,000). All estimates here are weighted
so they represent the population, not just the sample.
The DHS wealth index (v190/hv270) is built from household assets and
housing characteristics and split into five equal groups — poorest to richest — used by the
Wealth filter.
BDHS is designed to be statistically representative at the division level for every round, and at the district level only for the 2022 round (and partially 2017-18). It is not representative at the upazila level in any round. The atlas therefore attaches a reliability flag to every value:
| Flag | Meaning |
|---|---|
| Reliable | Adequate sample (n ≥ 200) — usually division cells |
| Indicative | Small sample (50–199) — read with caution |
| Not representative | Very small sample (< 50) |
| Modelled / sample | Placeholder or estimated from the parent area (e.g. all upazilas, and everything while in “Sample data” mode) |
Upazila colours are shown for visual exploration only — do not use them for official reporting.
scripts/convert_dta.py on the BDHS .dta files — locally or in
free Google Colab (no install). It outputs a real master.json.public_html/data/master.json with it.Alternatively the official figures in the BDHS 2022 report
(FR386.pdf) can be transcribed directly for the 2022 round.
Source: Bangladesh Demographic and Health Surveys — NIPORT, Ministry of Health & Family Welfare, and The DHS Program (ICF). This atlas is an independent visualisation.