PANEL 6.2 HOW DID BANGLADESH REDUCE STUNTING SO RAPIDLY? DEREK HEADEY
B
etween 1997 and 2011 the percentage of stunting in Bangladeshi children under age five dropped from 59 to 40 percent, nearly 1.4 percentage points a year. This represents an average annual rate of reduction of 2.7 percent (it would take a rate of 3.3 percent for Bangladesh to meet the WHA target for stunting). Among infants 0–6 months old, the decline in stunting was even faster: 28 to 16 percent. In fact, Bangladesh’s decrease in stunting among children under age five was almost twice as fast as India’s over a simi- lar time period.1 decline?
What drove this sustained
A recent analysis uses repeated rounds of the Bangladesh Demographic and Health Surveys (DHSs from 1997, 2000, 2004, 2007, and 2011) to explain about 55 percent of the changes in child stunting rates (Headey et
al. 2014). The analysis shows that the drivers of stunting declines are multidimensional: improvements in household assets, parental education, sanitation coverage, health care use, and demographic factors all make import- ant contributions.
Increases in household assets are asso- ciated with nearly a quarter of the explained changes in children’s stunting. Increases in mothers’ and fathers’ education are respon- sible for another quarter. So changes in basic and underlying determinants are important. But so too are more immediate determinants, such as declines in open defecation rates (which contribute 12 percent) and nutrition- related interventions in the health sector such as prenatal care and birth in a medical facility (which together account for 18 percent of the decline). Finally, declines in fertility are
important but often overlooked drivers (longer birth interval and lower birth order together account for 12 percent). The Bangladesh experience shows that low-income countries can rapidly reduce stunting—at a pace approaching that required to meet the WHA 2025 target— through a multidimensional approach. All sec- tors, levels, and actors need to pull together. The Bangladesh experience also shows the value of regular data collection. Large-scale, multi-topic, population-based surveys such as the DHS every three to four years enable anal- yses that can help people hold governments to account, identify the key drivers of under- nutrition reduction, and shape future invest- ments to sustain and accelerate the pace of stunting reduction.
To explore countries’ vulnerabilities on underlying deter- minants, we classified countries on each of the following: prevalence of undernourishment, access to improved drinking water, access to improved sanitation, female secondary educa- tion enrollment, and the population density rates of physicians. Countries were classified as vulnerable if they fell below the 25th percentile across all 100 countries with data on all five variables, a relatively low threshold. This means that the vulnera- bilities are relative, not absolute.
We found that 43 countries were not vulnerable on any of the five underlying determinant indicators (Table 6.1). Thirteen countries were classified as vulnerable on all five indicators. This
result indicates a real need to get the balance right, at the coun- try level, between investments in nutrition-specific and nutrition-sensitive interventions and the general underlying driv- ers of undernutrition. Many countries are likely to need invest- ments in all three areas to reduce undernutrition more rapidly.
For the 59 countries with at least one vulnerability, Table 6.2 suggests which underlying drivers are most important. For ex- ample, the analysis suggests that for India, sanitation is the indi- cator for which it has the lowest rank among the 100 countries, whereas for Nigeria it is improved drinking water coverage. This kind of analysis can help identify key constraints to improved nutrition status in each country.
TABLE 6.2 COUNTRIES THAT ARE MOST VULNERABLE BY EACH UNDERLYING DETERMINANT
Most relatively vulnerable (lowest country rank of the five indicators) On undernourishment
On improved sanitation coverage On improved drinking water coverage
On female secondary education enrollment rates On physician population density Total
Number of countries Total population (millions) 13 12 9
83
12 13
57 (59)a Source: Data on undernourishment: FAO (2014a); water and sanitation: WHO and UNICEF (2014); school enrollment: UNESCO Institute for Statistics (2014); health work-
ers: WHO (2014k). Population data are from United Nations (2013b). a
Malawi has the lowest rank in both sanitation and physician density and is therefore counted twice. Burkina Faso has the lowest rank in both female secondary educa- tion enrollment rates and physician density and is therefore counted twice.
ACTIONS & ACCOUNTABILITY TO ACCELERATE THE WORLD’S PROGRESS ON NUTRITION 43
1,379 317 539 383
Largest three countries in each category
Bolivia, Guatemala, Zimbabwe Ghana, India, Nepal
Kenya, Mozambique, Nigeria Bangladesh, Ethiopia, Pakistan
Cameroon, Indonesia, United Rep. of Tanzania
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