presentation: the myth of child malnutrition in india

The Myth of Child Malnutrition in India

Arvind Panagariya Columbia University

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Outline

•  The Narrative •  Three Smell Tests •  Measurement Methodology •  A Critique of the Methodology •  Do height Differences Really Vanish? •  Is it Catch-up with a Lag? •  Malnutrition in India IS Declining •  Concluding Remarks

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Child Malnutrition in India: The Narrative

•  “Nearly half of India's small [under-five] children are malnourished: one of the highest rates of underweight children in the world, higher than most countries in sub-Saharan Africa.

•  … Almost as shocking as the prevalence of malnutrition in India is the country's failure to reduce it much, despite rapid growth.” –  The Economist, September 23, 2011

•  “The problem of malnutrition is a matter of national shame.” –  Manmohan Singh, Prime Minister of India

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Smell Test 1: India and Chad

Indicator India ChadChad as %

of IndiaLife Expectancy (2009) 65 48 74Infant Mortality per 1,000 live births (2009) 50 124 248Under-five mortality per 1,000 live births 66 209 317Maternal Mortality per 100,000 live births (2009) 230 1200 522Percent children below 5 stunted (2000-09) 47.9 44.8 94Percent children below 5 underweight (2000-09) 43.5 33.9 78

“Stunting” implies low height for age against some norm “Underweight” refers to low weight for age against some norm

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Smell Test 2: Kerala Compared with Senegal and Mauritania

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Smell Test 3--India vs. SSA (Life Expectancy): Which Population Looks Healthier?

Life Expectancy (2009): Countries in Rising Order of per-capita GDP from L to R

50 49

56

4749

5457

66

5249

60 59

65

48 4852

4952

49

59

4853

6057

48

60 5855

62 60

5054

51

65

0

10

20

30

40

50

60

70

BurundiD

em R

ep Congo

LiberiaM

alawi

Sierra LeoneEthiopiaN

igerEritreaG

uineaM

ozambique

Gam

bia, TheTogoM

adagascarZam

biaC

. African R

epublicU

gandaZim

babwe

Burkina FasoG

uinea-BissauR

wanda

Chad

Mali

KenyaBeninLesothoC

omoros

Mauritania

TanzaniaSenegalG

hanaC

ote d'IvoireN

igeriaC

ameroon

India

Red bar is India; yellow bar an SSA country with superior achievement to India’s and violate bar an SSA country with inferior achievement to India’s.

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Smell Test 3--India vs. SSA (IMR): Which children Look Healthier?


Infant Mortality per 1,000 live births (2009): Rising per-capita GDP from L to R

101

126

80

69

123

6776

39

8896

78

64

40

86

112

79

56

91

115

70

124

101

55

75

61

75 7468

51 47

83 8695

50

0

20

40

60

80

100

120

140

BurundiD

em R

ep Congo

LiberiaM

alawi


igerEritreaG

uineaM

ozambique

Gam

bia, TheTogoM

adagascarZam

biaC

. African R

epublicU

gandaZim

babwe

Burkina FasoG

uinea-BissauR

wanda

Chad

Mali

KenyaBeninLesothoC

omoros

Mauritania

TanzaniaSenegalG

hanaC

ote d'IvoireN

igeriaC

ameroon

India

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Smell Test 3--India vs. SSA (under 5 Mortality): Which children Look Healthier?

Under-five mortality per 1,000 live births (2009): Rising per-capita GDP from L to R

166

199

112110

192

104

160

55

142142

103 98

58

141

171

128

89

166

193

111

209

191

84

118

84

104117

10893

69

118

138154

66

0

50

100

150

200

250

BurundiD

em R

ep Congo

LiberiaM

alawi


igerEritreaG

uineaM

ozambique

Gam

bia, TheTogoM

adagascarZam

biaC

. African R

epublicU

gandaZim

babwe

Burkina FasoG

uinea-BissauR

wanda

Chad

Mali

KenyaBeninLesothoC

omoros

Mauritania

TanzaniaSenegalG

hanaC

ote d'IvoireN

igeriaC

ameroon

India


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Smell Test 3: India vs. SSA (MMR): Which Mothers Look Healthier?

Maternal Mortality per 100,000 live births (2009): Rising per-capita GDP from L to R

970

670

990

510

970

470

820

280

680

550

400350

440470

850

430

790

560

1000

540

1200

830

530

410

530

340

550

790

410350

470

840

600

230

0

200

400

600

800

1000

1200

1400

BurundiD

em R

ep Congo

LiberiaM

alawi


igerEritreaG

uineaM

ozambique

Gam

bia, TheTogoM

adagascarZam

biaC

. African R

epublicU

gandaZim

babwe

Burkina FasoG

uinea-BissauR

wanda

Chad

Mali

KenyaBeninLesothoC

omoros

Mauritania

TanzaniaSenegalG

hanaC

ote d'IvoireN

igeriaC

ameroon

India


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Smell Test 3--India vs. SSA (Underweight): Which Children Look Healthier? Wow!

Percent children below 5 underweight (2000-09): Rising per-capita GDP from L to R

38.9

28.2

20.4

15.5

21.3

34.6

39.9

34.5

20.821.2

15.8

20.5

14.9

21.8

16.414.0

37.4

17.418.0

33.9

27.9

16.4

20.2

16.6

25.0

16.716.714.514.3

16.7

26.7

16.6

43.5

0.0

5.0

10.0

15.0

20.0

25.0

30.0

35.0

40.0

45.0

50.0

BurundiD

em R

ep Congo

LiberiaM

alawi


igerEritreaG

uineaM

ozambique

Gam

bia, TheTogoM

adagascarZam

biaC

. African R

epublicU

gandaZim

babwe

Burkina FasoG

uinea-BissauR

wanda

Chad

Mali

KenyaBeninLesothoC

omoros

Mauritania

TanzaniaSenegalG

hanaC

ote d'IvoireN

igeriaC

ameroon

India


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Smell Test 3--India vs. SSA (Stunting): Which Children Look Healthier? Wow!

Percent children below 5 stunted (2000-09)

63.1

45.8

39.4

53.2

37.4

50.7

54.8

43.740.0

47.0

27.626.9

49.245.844.6

38.735.8

44.547.7

51.7

44.8

38.535.2

44.745.246.9

24.2

44.4

20.1

28.6

40.141.0

36.4

47.9

0.0

10.0

20.0

30.0

40.0

50.0

60.0

70.0

BurundiD

em R

ep Congo

LiberiaM

alawi


igerEritreaG

uineaM

ozambique

Gam

bia, TheTogoM

adagascarZam

biaC

. African R

epublicU

gandaZim

babwe

Burkina FasoG

uinea-BissauR

wanda

Chad

Mali

KenyaBeninLesothoC

omoros

Mauritania

TanzaniaSenegalG

hanaC

ote d'IvoireN

igeriaC

ameroon

India


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Searching for Answers: The Measurement Methodology

•  The Central Assumption: All differences between populations of children of given age and sex with respect to weight and height occur due to differences in nutrition.

•  Implication:We can set a common norm, say, a minimum height for a child of a given age and gender, below which any given child anywhere in the world can be classified as stunted.

Two Different Standards

•  NCHS 1977: The National Center for Health Statistics (NCHS) of the Centers for Disease Control (CDC) first adopted the height and weight norms using longitudinal-data collected in Yellow Springs, Ohio between 1929 and 1975 by the Fels Research Institute. The World Health Organization (WHO) adopted this same standard in the late 1970s..

•  In the 1990s, the CDC concluded that Fels data were quite limited in geographic, cultural, socioeconomic and genetic variability and therefore replaced the NCHS 1977 charts by CDC 2000 charts that were based on a nationally representative sample.

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The Current WHO Standard

•  In the early 2000s, following the lead of the United States, the WHO collected a sample of 8440 healthy breastfed infants and young children from Brazil, Ghana, India, Norway, Oman and the United States that it considered as representing the population of healthy children.

•  Bottom 2.25 percent of the children by height in each sub-group within this sample, identified by gender and age, were classified as stunted. In turn, the height of the child at 2.25 percent from the bottom was defined as the “cutoff” height for stunting.

•  Applying this cutoff height, each country measures the proportion of stunted children in its populations.

•  Underweight children are identified analogously.

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39" 47"44"

100%

% below the height

2.25%

39.3"(Height Norm)

Population of HealthyFive-year Old Boys

39.3"

50%

46"

Population of Five-year Old Boys in India

Hieghtin inches

Sources of Differences Between Populations

•  Differences in diet (nutrition) •  Different potential with respect to ehight and

weight due to genetic, geographical, cultural or environmental differences. If so populations will differ for ever even when given identical diet

•  Different stages of evolution: potential is the same but achieving it takes several generations. So the populations at different stages of evolution differ even if given identical diets.

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The WHO Approach

•  The WHO in effect recognizes only the first source of the difference

•  There is agreement among scholars that the third factor matters but disagreement on how it should be treated in measuring malnutrition

•  While medical literature recognizes the second factor as an important source of the differences in populations, economists uniformly reject it.

•  I argue that this factor is extremely important. 17

Critique of the Methodology

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Height Differences Across Populations Narrow with Nutrition but do not Disappear: Adults

•  First World War: Average American solider was 2 inches taller than average German soldier.

•  In 1955, northern European adults crossed American adults in height and have continued to grow two centimeters per decade on average

•  But the average American adult height has not changed in the last five and a half decades

•  This is true for sub-populations of whites, blacks, highly educated, wealthy etc.

•  Today, the Dutch are significantly taller their American counterparts.

Adult Height Differences Across Rich Countries

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Country Men WomenNetherlands 183.2 169.9Sweden 181.5 166.8Germany 181 168U.S. 177.6 163.2United Kingdom 177.1 164.4Canada 176 163.3Portugal 173.7 163.7Japan 170.7 158

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Evidence from Ethnic South Asians Abroad

•  Nube (2008) studies Bio Mass Index and concludes: “Results from countries that are home to sizeable population segments from different ethnic backgrounds, including people of Asian and African descent, reveal consistently higher prevalence rates of low BMI among people of South Asian descent. These differences cannot be explained on the basis of indicators which relate to access to food, social status of women or overall standard of living. … On the basis of these outcomes it is hypothesized that there exists among adults of South Asian descent an ethnically determined predisposition for low adult BMI. This ethnic predisposition can be based on both genetic and cultural factors.” [Emphasis added.]

Deaton (2007): “Perhaps the major puzzle is why Africans are so tall.”

•  Deaton (2007) studies heights of adults from 43 developing countries and finds that no variables including those relating to nutrition as measured by calorie intake explain the differences across countries.

•  Unable to resolve the puzzle, Deaton (2007, p. 13236) goes so far as to state, “Given that Africans are deprived in almost all dimensions, yet are taller than less-deprived people elsewhere (although not than Europeans or Americans), it is difficult not to speculate about the importance of possible genetic differences in population heights. Africans are tall despite all of the factors that are supposed to explain height.”

•  Nevertheless, Deaton rejects genetic differences as the cause without providing any other explanation, thus, leaving the puzzle unexplained.

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But could it be that Differences Unrelated to Nutrition Emerge in Adolescence or later so that the

Differences in Childhood are Still Related Exclusively to Nutrition?

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Height and Weight Differences: Newborns of Indian, African American and White Mothers •  Evidence from a comparison of newborns of Indian,

African American and White mothers in the United States (Alexander et al. 2007) –  “Compared to AAs [African Americans] or Whites, AIAs [Asian

Indian Americans] have the lowest percentage of births to teen or unmarried mothers and mothers with high parity for age or with low educational attainment. After taking these factors into account, AIA had the highest risk of LBW [low birth weight], small-for-gestational age (SGA) and term SGA births but a risk of infant death only slightly higher than Whites and far less than AAs. Conclusions: The birth outcomes of AIAs do not follow the paradigm that more impoverished minority populations should have greater proportions of low birth weight and preterm births and accordingly greater infant mortality rates.”

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Birth weight and IMR: Indian Newborns in the United States and their Local Counterparts

Alexander et al. (2007)

Indians Whites

African Americans

Comparing the Newborns of the Japanese and American Mothers

•  Mor et al (1995) compare the birth outcomes of United States resident white (born in mainland U.S.) and Japanese-American mothers (born in Hawaii) using 1979–1990 linked live birth and infant death records from the state of Hawaii. They conclude –  “After controlling for maternal sociodemographic and prenatal

care factors with logistic regression, Japanese-American infants had significantly higher risks of low birth weight, preterm and very preterm birth and of being small-for-gestational age.”

•  Surely, the American born Japanese mothers giving birth during 1979-90 could not still be catching up!

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Alexander et al. (2007) Continued

•  “AIAs are similar to Japanese-Americans in having higher LBW and SGA rates than their socio-demographic characteristics would suggest, but still maintaining relatively equivalent infant mortality as Whites [8,17]. Samoans are yet another ethnic group that does not fit conventional thinking due to having relatively lower LBW rates but higher infant mortality rates compared to White infants [17].”

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Alexander et al. (2007) Conclude

•  “The differences between White Europeans and Asian-Indians have been explained in European literature through various theories, including genetic variations and maternal malnutrition [4,7]. A connection between birth weight and maternal size may be attributable to certain genetic factors related to the shortness or smaller size of the mother caused by undernourishment occurring during childhood [7]. Alternatively, the differential patterns of growth observed among Asian-Indian infants may be attributable to a different body habitus among this ethnic group and maybe due to genetic factors, not suboptimal growth [9,14]. The results of this investigation, focusing mainly on socio demographic characteristics, provide no evidence against these theories, leaving them open for further investigation.”

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•  Fredriks et al (2004) in journal Acta Paediatr –  Samples of 2880 children of Moroccan origin and

14,500 children of Dutch origin living in The Netherlands in the age range 0 to 20 years in 1997.

–  “Moroccan young adults were on average 9 cm shorter than their Dutch contemporaries. … Height differences in comparison with Dutch children increase from 2 years onwards.”

•  The authors recommended drawing up separate growth charts for Moroccan and Dutch children.

Evidence on Children Two Years and Older

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Average Height Growth Charts for Moroccan and Dutch Children In the Netherlands

Boys Girls

Age in years Moroccan Dutch Difference Moroccan Dutch Difference

1 76.1 76.7 0.6 75 75 0

2 87.7 88.4 0.7 86.5 87.1 0.6

3 96.8 97.8 1 96 97 1

4 104.5 105.5 1 103.5 104.9 1.4

5 111.4 113.2 1.8 110.2 112.9 2.7

21 177.8 183.8 6 162.8 170.7 7.9

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Continued Height Gaps between Well-fed Indian Children and the WHO Norms

•  Beginning with a sample of several thousand three-year olds in the NFHS-2, Tarozzi (2008) selects 212 elite children –  “from urban areas, where both parents have at least a

high school diploma, live in a house with a flush toilet with a separate room used as kitchen and whose family owns car, color television, telephone, and refrigerator.”

•  Tarozzi finds a solid 20% of these elite children remain stunted by the WHO norms.

•  GOI (2009) finds the same using the NFHS-3 data

But what about the Finding of Tarozzi on the Children of Indians Living in the U.K.?

•  “Overall, these results [shown in Table 6] provide some prima facie evidence in support of the hypothesis that the growth performance of children of Indian ethnicity who live in the UK is comparable to that of the reference population used to construct either the WHO-2006 or the CDC-2000 references.” (Emphasis in the original)

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Several Problem with Tarozzi’s Conclusion

•  Small sample: The sample of children under two years of age born to Indian parents in the dataset is so small that Tarozzi does not even attempt a comparison. For children 2 to 3 years old, his sample has just 19 Indian children and for those between 2 and 5 years, there are 72 children.

•  Even then the proportion of Indian children in 2 to 3 years age group who are stunted by WHO 2006 definition turns out to be 5.3 percent compared with nil among white children. So the differences remain even in this sample.

•  Sample selection problem: Those who chose to migrate may have come from genetically taller part of the population in the first place.

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But What about the Study of the South Delhi Children by Bhandari et al. (2003)?

•  This study reports the incidence of stunting at 3.2 percent. •  But there are several problems with the study

–  It only included children BOVE ONE AND BELOW TWO YEARS OF AGE. Differences other than those due to nutrition differences are harder to catch at this young age.

–  Selection bias: South Delhi is inhabit by the elite who may be drawn disproportionately from the genetically taller part of the country’s population.

–  Possibility of excessive sanitization of the sample –  The 3.2% stunting figure is based on a standard less

demanding than the current WHO standard 34

Catch-up with a Lag or Genetic Differences?

•  Continuing low height and weight among even elite Indian children and the WHO standard are attributable to possible factors’ – Genetic differences – Catch-up with a lag

•  Rejecting the first factor, Deaton and Dreze (2008) contend that it is the catch with lag problem. But are they right?

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Problems with the Catch up with a Lag Explanation

•  Does this make any sense that – Mauritanian children under five die at rates 7.3

times those in Kerala but are farther along in catch-up than the latter?

– Mauritanian mothers die at rates 5.8 times those of Kerala mothers but give birth the better nourished children than the latter?

– Mauritanian infants die at rates 6.2 times those in Kerala but are better nourished than the latter?

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Additional Problems with Catch-up with a Lag Explanation

•  Differences in adult achievements today between India and SSA are inconsistent with Indian adults having suffered with greater malnutrition in their childhood

•  If 50% of children are currently stunted, 100% of those in my generation had to have been stunted. Is this plausible?

Yet More Problems with the Catch up with a Lag Explanation

•  Why would newborns to Indian mothers in the United States show higher incidence of low birth weight and small size than those to African American and White mothers and yet have better or nearly as good chances of survival?

•  Could Japanese children born in Hawaii during 1979-90 to American born mothers still be catching up?

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Malnutrition HAS Fallen in India

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Malnutrition HAS Fallen in India

NFHS-2 (1998-99) NFHS-3 (2005-06)

Measure of nutrition Urban Rural Total Urban Rural Total

Height-for-age (stunted) 41 54 51 37 47 45

Weight-for-age (underweight) 34 45 43 30 44 40

Number of children 5741 18475 24215 6436 20105 26541

Proportion of under-three Indian children who are stunted and underweight by the WHO 2006 Standard.

Average height too has been rising: According to the NNMB, the average increase in height at age three was a little below 2 centimeters per decade between 1975-79 and 2004-05. According to the NFHS, the increase was 2.5 centimeters per decade between 1992-93 and 2005-06.

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A Concluding Remark

•  Once we begin measuring malnutrition correctly, we are likely to find that –  India has about as much to be ashamed of its

child malnutrition levels as of life expectancy, infant mortality, under-five mortality and maternal mortality.

presentation: the myth of child malnutrition in india

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