Malnutrition in the OIC Member
Countries: A Trap for Poverty
COMCEC
Stunting Wasting Overweight Anaemia
Wealth quintile: Middle 35.2 7.8 1.9 32.4
Wealth quintile: Fourth 34.5 8. 1 1. 8 30.2
Wealth quintile: Highest 29.1 9 2.4 26.7
Region: North Sumatra 39.7 9.2 1. 8 2 1 . 6
Region: West Sumatra 31.6 6 1.2 13.5
Region: South Sumatra 36.1 10. 2 0.4 35.6
Region: Lampung 31.1 11.9 2. 2 24.2
Region: DKI Jakarta 31.7 7.7 1.9 33.3
Region: West Java 32.9 6.2 1.5 30.8
Region: Central Java 30.7 10.5 2.5 33.9
Region: DI Yogyakarta 26.7 8. 1 3.8 34.8
Region: East Java 33.0 7 2 . 8 26.7
Region: Bali West Nusa 29.9 3.9 1.4 30.3
Region: Tenggara 48.8 10.5 1.0 53.7
Region: South Kalimantan 45.6 7.8 1.9 34.4
Region: South Sulawesi 38.2 10 . 1 1.5 41.6
Mean 35.3 8.5 1.9 31.1
Source: authors' calculations based on the IFLS (2014). Wealth index created by the authors with a factors
analysis.
Trends in Malnutrition
hows that trends in malnutrition are very different between types of malnutrition.
Indonesia has managed to reduce chronic malnutrition in a steady manner since 1995. The
prevalence of stunting has decreased from 48.1% in 1995 to 36.4% in 2013, which
corresponds to a decline of 0.65 percentage point per year. The pace of stunting reduction has
been remarkably constant over the entire period if we ignore the year 2004 which displays a
much lower, and hardly credible, stunting rate of 28.6%.14 Anaemia prevalence has likewise
decreased steadily over the period, from 51.3% in 1995 to 32.8% in 2010 (and 31% in 2014].
The pace of anaemia prevalence reduction has been sustained, at 1.2 percentage point per
year.
In contrast, acute malnutrition (wasting] has not gone down much from its 1995 level.
Prevalence of wasting had initially decreased from 14.9% in 1995 to 5.4% in 2001, but has
since then increased until 2013 to reach the level of 13.5%. Overweight has followed a similar
pattern: prevalence first decreased between 1995 and 2001 (from 6.5% to 1.5%) but has since
steadily increased to reach 12.3% in 2010 and 11.2% in 2013.
14The dataset used in that particular year is different the ones used in the other years, and has a much
lower sample size.
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