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Poverty and Undernutrition$

Peter Svedberg

Print publication date: 2000

Print ISBN-13: 9780198292685

Published to Oxford Scholarship Online: November 2003

DOI: 10.1093/0198292686.001.0001

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Anthropometric Indicators of Undernutrition: Measurements and Evidence

Anthropometric Indicators of Undernutrition: Measurements and Evidence

Chapter:
(p.153) 11 Anthropometric Indicators of Undernutrition: Measurements and Evidence
Source:
Poverty and Undernutrition
Author(s):

Peter Svedberg (Contributor Webpage)

Publisher:
Oxford University Press
DOI:10.1093/0198292686.003.0011

Abstract and Keywords

This chapter sets out by assessing the uniform height and weight norms established by the WHO, which are conventionally used to gauge the anthropometric status of people of different age and sex, worldwide. The available estimates of the prevalence of undernutrition in sub‐Saharan Africa and South Asia are compared to estimates from other regions. Most observations are for young children and, to a lesser extent, for females of reproductive age. The anthropometric status of these population groups in the various countries, along age and gender lines and also the rural/urban divide, are mapped. A puzzling finding is that the prevalence of undernutrition, when measured by anthropometrics—both in young children and adult women—is by far the highest in South Asia, while the (FAO) food‐supply‐based estimates find the incidence to be the highest in sub‐Saharan Africa (also see Ch. 18).

Keywords:   Africa, anthropometric status, Asia, FAO, gender, rural, undernutrition, urban, WHO, young children

11.1. Introduction

There are two main sets of estimates of the prevalence of undernutrition in the world that are claimed to allow comparison over time and space. One set of such estimates are provided by the FAO on the basis of the aggregate method that was scrutinized in the previous six chapters. The other set of estimates are based on anthropometric measures. Until quite recently, this type of estimate was derived using a large variety of methods and measurements, and therefore they were not generally comparable across countries and over time. Since the early 1990s, however, estimates for almost 90 developing countries have come forth, based on more uniform measures and methods. This has improved the possibility of making international comparisons and, less frequently, of monitoring changes over time. Most of the new data sets have been compiled by the WHO and are used extensively by UNICEF, the ACC/SCN, and the FAO/ESN.1

The anthropometric indicators allow us to derive POU estimates in an alternative way, which makes possible comparisons with the estimates obtained by the FAO with its aggregate method. The anthropometric method also permits estimates of differences in nutritional status between rural and urban areas, for children of different age and sex and between children and adults. In combination with ‘social’ and economic observations, anthropometric indicators can also be helpful in identifying reasons for nutritional inadequacy. The anthropometric measures thus have a broader application potential than the aggregate POU estimates which we scrutinized earlier.

The overall aim of this and the subsequent two chapters is to assess the anthropometric measures as indicators of undernutrition. In this chapter we present the anthropometric measurements in use and a brief overview of the available empirical estimates. In Chapter 12, measurement and selection errors and biases in the estimates are identified. Chapter 13 addresses the more conceptual question of to what extent the conventional anthropometric indicators capture different aspects of what are considered symptoms of undernutrition.

(p.154) The rest of the present chapter is organized as follows. In section 11.2, the anthropometric measures most commonly used are presented. Section 11.3 contains a summary review of the evidence on the anthropometric status of children in the SSA countries. In section 11.4, these estimates are subjected to international comparison. In section 11.5, the meagre evidence on the anthropometric status of adults is presented. The anthropometric status of adults and children are compared in section 11.6. Finally, a short summary of the main findings is offered in section 11.7.

11.2. Measurements, Data, and norms

The anthropometric approach rests on the presumption that people's physical appearance reflects their nutrition (and health) status, i.e. if energy intake and expenditure balance at a level that is too low, this will show up in body constitution. This means that neither the energy intake nor the energy expenditure has to be measured. The anthropometric approach is therefore more simple and—above all—less reliant on the collection of inherently difficult‐to‐estimate data than the aggregate calorie‐intake/requirement approach. (As we shall see in the two subsequent chapters, this is not to say that the anthropometric method is devoid of problems.)

11.2.1. Child Measurements

In setting up an anthropometric norm for children, the first question is what ‘outcomes’, or body‐composition abnormalities, are the most reliable indicators of nutritional inadequacy. Many measures have been used in the literature. Since the early 1980s, it seems that nutritionists have found height and weight to be the most relevant ones (Waterlow 1984, Payne 1992). The bulk of the recent anthropometric evidence from Africa (and elsewhere) is thus based on height and weight measures. In earlier times, head and arm circumference, triceps skinfold, and a few other measures were frequently used. Following the Waterlow (1972, 1976) classification scheme, the more specific indicators used to assess children are: height for age (stunting), weight for height (wasting), and weight for age (underweight). The three different indicators are intended to capture different aspects of child undernutrition that have partly different aetiologies and time dimensions (to be further elaborated in Chapter 13).

The height‐for‐age indicator is mainly used for monitoring permanent, or chronic, undernutrition in children. The underlying theory is that chronic undernutrition in childhood retards growth in stature, although there is no consensus on the relative importance of nutrition, on the one hand, and disease and unfavourable socio‐economic environment, on the other (Eveleth and Tanner 1990, Waterlow 1992), discussed in more detail in Chapter 14. (p.155) The weight‐for‐height indicator is used to monitor wasting, which is taken to reflect short‐term, or temporary, undernutrition. The weight‐for‐age indicator is intended to capture both long‐term (stunting) and short‐term (wasting) undernutrition. It has been the indicator used most frequently by WHO, UNICEF, and other international organizations concerned with the health status of children, and most of the available empirical evidence is in this dimension.

11.2.2. The Height and Weight Norms

The second step in setting up an anthropometric norm is to decide what are the ‘normal’ height and weight in a population. The norms in use are almost without exception obtained from a Western population. The average child's height in such a population is taken to represent the genetic growth‐potential for the average child worldwide. The average weight of the children in the reference population is not necessarily assumed to represent a genetic potential for weight, but a weight which imposes no hazards for health or mental and physical capabilities. The most commonly applied norm nowadays is from the US National Center for Health Statistics (NCHS), which UNICEF, WHO, and the FAO agreed to use in 1981; before that, the proliferation of norms was bewildering (WHO 1986).

The use of the same height‐for‐age norm (from the US) as the benchmark for what is normal (nutritionally unconstrained) stature in children in all parts of the world implies an assumption that all races and ethnic groups in the world have the same genetic potential for growth in the early age. (The empirical support for this assumption is discussed in Chapter 12.)

11.2.3. Acceptable Deviation from the Norms (The Cut‐Off Points)

The third step in deriving estimates of undernutrition with the anthropometric method is to find the unacceptable downward deviations from the height and weight norms (the cut‐off points). In principle, there are two ways of establishing cut‐off points.

One takes its starting point in what is statistically abnormal in the reference (Western) population. In populations in which nutritional inadequacy is absent (or very small), there is a distribution of heights and weights (for age): some children are short and/or light‐weighted for genetic reasons, others are tall and/or heavy. The cut‐off points used to delineate undernourished children in Third World populations are derived from the lower ends of the height and weight distributions in the reference population. This method is used by WHO, UNICEF, other international organizations engaged in monitoring the status of children in the world, and also by most independent researchers collecting and using anthropometric indicators.

In earlier times, there was no consensus on what precise ‘statistical deviation’ should be used to delineate the undernourished. Regarding height for (p.156) age, for instance, some authors set the cut‐off at 10 per cent below the median reference height; others at 2 standard deviations (SD) below; still others below the third (or fifth) decile in the reference population. (As demonstrated by Mora (1984), the estimated POU can be highly sensitive to which particular measure of deviation is used.)2 However, since the early 1980s, the international organizations have agreed to use the 2 SD measure to delineate undernutrition in all child populations in order to accomplish comparability across countries and over time. This measure has also been accepted by most independent collectors and users of anthropometric indicators.

The second method for establishing cut‐off points is to estimate at what downward deviations from ‘normal’ height and weight there are measurable statistically significant increased risks of health impairments and other dysfunctions in children. This method has a better theoretical foundation in the Adjustment and Adaptation paradigm of undernutrition (cf. Chapter 2). In practice, however, this method is seldom used for assessing children, while it is for adults (for reasons to be elaborated in Chapter 14 below).

11.3. The Anthropometric Status of Children in SSA

This section presents evidence on the anthropometric status of children under the age of five in the SSA countries. Most of the original data are from WHO and used by UNICEF, the ACC/SCN, and the FAO/ESN. The data allow for comparisons across African countries, developments over time, and comparisons with other parts of the so‐called Third World. This data base also allows us to estimate differences by age, sex, and rural/urban location.

11.3.1. Height and Weight Failure of Children in SSA

Estimates of the incidence of undernourished children in 33 SSA countries (for one particular year in the 1985–94 period) are summarized in Table 11.1.3 The table suggests the highest incidence of undernutrition with the height‐for‐age indicator; almost 40 per cent of the children in SSA are stunted. A somewhat smaller share, about 30 per cent, are underweight, i.e. have a weight‐for‐age below the cut‐off point. About 8 per cent of the children have a weight‐for‐height below the norm.

There are wide differences across the African countries. The estimated prevalence of underweight children ranges from below 6 per cent to almost half the child population. Ethiopia, Mauritania, and Madagascar are at the top the list, but the estimated incidence of the underweight is considerably above the average also in Burundi, Niger, Tanzania, and Nigeria. The lowest figures are reported for the Seychelles and Swaziland. In almost all the SSA countries, stunting is somewhat more prevalent than being underweight.

(p.157)

Table 11.1. Prevalence Estimates for Three Anthropometric Indicators, Latest Year (Percentage Below −2 SD of NCHS Reference Median for 0–59 Month‐Olds)

Country by region

Year(s)

Underweight (weight for age)

Stunting (height for age)

Wasting (weight for height)

Eastern and Southern Africa

Botswana

1987

15

44

Burundi

1987

38

48

6

Ethiopia

1992

48

64

8

Kenya

1993

22

33

6

Lesotho

1992

15

33

2

Madagascar

1992

39

51

5

Malawi

1981

27

49

5

Mauritius

1985

24

22

16

Namibia

1992

26

28

4

Rwanda

1992

29

48

3

Seychelles

1988

6

5

2

Swaziland

1983–4

10

30

1

Tanzania

1992

29

43

6

Uganda

1988

23

45

2

Zambia

1992

25

40

5

Zimbabwe

1988

12

29

1

West and Central Africa

Burkina Faso

1993

30

29

13

Cameroon

1991

13

24

3

Cape Verde

1985

19

26

3

Congo

1987

24

27

5

Côte d'Ivoire

1986

12

17

9

Ghana

1994

27

26

11

Guinea–Bissau

1978–80

23

Liberia

1976

20

37

3

Mali

1987

31

24

11

Mauretania

1991

48

56

16

Niger

1992

36

32

16

Nigeria

1990

36

43

9

Sao Tomé & Principe

1986

17

26

5

Senegal

1993

20

22

9

Sierra Leone

1990

29

35

9

Togo

1988

24

30

5

Zaïre

1975

28

43

5

SSA (average)

31

39

8

India

1992

61

62

19

Bangladesh

1990

66

65

16

Sources: UNICEF 1993b and WHO Global Database, cited in FAOa 1996: appendix 2, table 8.

(p.158) It is notable that undernutritition as indicated by wasting (weight‐for‐height) is considerably lower than for the other two indicators, ‘only’ 8 per cent in SSA as a whole. The only SSA countries in which estimated wasting is considerably higher are Niger, Mauritania, and, perhaps surprisingly, high‐income Mauritius. In about half the countries, the prevalence of wasted children is in the 1–5 per cent range, which is about the same as in the reference populations. In Africa as a whole, more than 90 per cent of the children thus have an ‘acceptable’ weight for their height, while only 60 per cent have an ‘acceptable’ height for their age. This means that it is extremely important to make clear what is the most serious threat to child health and well‐being: height or weight failure. If modest height failure poses no serious problem, while being underweight does, undernutrition among children in Africa is rather modest. If, however, height failure is the main problem, the situation is considerably worse. (This question is assessed in Chapter 14.)

11.3.2. Change Over Time

Measures of anthropometric performance of children below the age of five, conducted with methods that permit inter‐temporal comparison according to the ACC/SCN, are available for 11 SSA countries (Fig. 11.1). In three of these, Kenya, Tanzania, and Zimbabwe, the estimated trend in the incidence of underweight children (the only indicator for which changes over time are reported) is downwards; in the other eight countries, it is upwards. According to the Statistics and Monitoring Section of UNICEF (1993a: fig. 7), inter‐temporally comparable data (on the incidence of underweight children) are

                      Anthropometric Indicators of Undernutrition: Measurements and Evidence

Fig. 11.1. Estimated Trends In the Percentage Of Children Who Are Underweight In Selected SSA Countries

Source: ACC/SCN 1994: p. 2.

(p.159) available for three SSA (partly different) countries only. In two of these, Togo and Cape Verde, the trend is downwards; in Zambia it is upwards. At the continental level, the ACC/SCN finds that the estimated incidence of underweight children in the SSA has remained more or less unaltered between 1975 and 1995 (Fig. 11.2).

11.3.3. Anthropometric Status by Rural/Urban Area and Regions

Within each and every country in SSA, the incidence of undernutrition is higher in rural than in urban areas and most of the differences are statistically significant (Table 11.2). In half the countries, rural undernutrition is nearly twice that in urban areas. This is by the weight‐for‐age indicator; similar evidence is not available for other indicators.4

                      Anthropometric Indicators of Undernutrition: Measurements and Evidence

Fig. 11.2. Estimated Trends In the Percentage Of Children Who Are Underweight, By Major Geographical Regions, 1975–95

Sources: ACC/SCN 1992: table 1.2 (1975–90); ACC/SCN 1997a: table on p. 9 (1990–95).

(p.160)

Table 11.2. Prevalence of Underweight Children, by Gender and Rural/Urban Location, in Selected Countries, 1980s

Country

Year

Gender

Location

Male

Female

M/F ratio

Rural

Urban

R/U ratio

Africa

Burundi

1987

38

39

0.96

39

20

1.93

Cape Verde

1985

20

18

1.09

Congo

1987

25

23

1.08

Côte d'Ivoire

1986

14

11

1.21

14

10

1.33

Djibouti

1990

30

20

1.50

Ghana

1987–8

27

27

0.98

31

23

1.38

Lesotho

1981

16

15

1.04

Madagascar

1983–4

40

34

1.20

37

28

1.30

Malawi

1981

Mali

1987

30

32

0.93

34

26

1.32

Mauritius

1985

27

20

1.32

Namibia

1990

Niger

1985

52

27

1.90

Nigeria

1990

36

36

1.00

39

36

1.46

Rwanda

1982–3

29

41

0.70

33

27

1.26

Senegal

1986

23

21

1.09

25

15

1.66

Seychelles

1987–8

5

6

0.92

Sierra Leone

1978

32

24

1.33

Tanzania

1988

Togo

1988

25

24

1.05

28

16

1.75

Uganda

1988

23

23

0.99

24

13

1.90

Zambia

1990

25

24

1.04

Zimbabwe

1988

11

12

0.95

14

5

2.62

Asia

Bangladesh

1989–90

65

68

0.96

67

63

1.06

India

1988–90

62

60

1.03

Pakistan

1990–1

41

40

1.02

45

33

1.37

Sri Lanka

1987

38

39

0.97

39

28

1.40

Source: UNICEF 1993b: table 2.

There is also large variance across different districts/regions within the countries for which disaggregated data are available (most of this information is contained in the FAO/ESN country profiles). In Table 11.3, the estimated prevalence of anthropometric failure in 5–38 districts/regions in a dozen SSA countries is presented. Large intra‐country differences are found in Zimbabwe, Nigeria, Mali, Congo, and Botswana. Considerably less intra‐country differences are observed in Benin, Cameroon, Malawi, and Kenya. Nevertheless, in most of the countries, the intra‐country differences are as (p.161)

Table 11.3. Incidence of Anthropometric Failure of Children, by District in Selected Countries

Country (year) (age group)

Anthropometric indicator

Number of districts

Prevalence of anthropometric failure

lowest

highest

Zimbabwe (1988)

Wt/Age

10

3

16

(3–60 months)

Ht/Age

10

11

37

Wt/Ht

10

0

2

Nigeria (1983–4)

Wt/Ht

38

3

36

(0–60 months)

Nigeria (1987)

Wt/Age

5

25

40

(0–60 months)

Ht/Age

5

24

37

Wt/Ht

5

0

21

Sudan (1986–7)

Wt/Ht

12

9

36

(0–60 months)

Benin (1987–8)

Wt/Ht

6

13

17

(0–60 months)

Wt/Age

7

29

39

Congo (1987)

Wt/Age

9

17

42

(0–60 months)

Ht/Age

9

19

58

Wt/Ht

9

2

9

Burkina Faso (1987)

Wt/Ht

8

11

26

(12–48 months)

Niger (1985)

Wt/Age

7

44

59

(0–60 months)

Ht/Wt

7

7

16

Botswana (1990)

Wt/Age

17

7

26

(0–60 months)

Zambia (1987)

Wt/Age

9

12

35

(0–59 months)

Mali (1975)

Wt/Age

7

3

27

(0–59 months)

Malawi (1982)

Wt/Age

8

32

37

(0–60 months)

Ht/Age

8

47

65

Wt/Ht

8

0

3

Kenya (1982)

Ht/Age

6

22

39

(1–4 years)

Cameroon (1978)

Wt/Age

8

13

27

(3–59 months)

Ht/Age

8

14

31

Ht/Wt

8

1

1

Pakistan (1987)

Ht/Age

5

34

57

(0–60 months)

Wt/Ht

5

9

12

Peru (1984)

Wt/Age

7

3

25

(0–60 months)

Ht/Age

7

16

63

Wt/Ht

7

0

1

Brazil (1989)

Wt/Age

9

17

40

(0–59 months)

Source: FAO/ESN Nutrition Country Profiles, various issues.

(p.162) large as the inter‐country differences in Africa. This is an indication that nutritional inadequacy to a large extent is a problem of uneven access to food, health facilities, and other resources which affect child anthropometric performance within the SSA countries.

11.3.4. Anthropometric Status by Age

The estimated incidence of children with low birth weight (LBW), i.e. less than 2.5 kg, is about 13 per cent on average (unweighted) in the 17 SSA countries for which the IBRD judges the statistical base to be reasonably reliable. The range is from a low of about 5 per cent in Ghana and Zimbabwe, to a high of 32 per cent in Togo (IBRDa 1995: table 27). According to UNICEF, the average incidence of LBW in SSA was about 16 per cent in the early 1990s (Fig. 11.3).

The estimated prevalence of the underweight by age cohorts (1–5 year‐olds) are available for 23 SSA countries. The average for these countries is shown in Fig. 11.4. During the first year, there is a sharp increase in the incidence of those who are underweight, from about 13–16 per cent LBW to almost 30 per cent underweight between the ages of 1 and 2. After that, it tapers off slightly to reach a little above 20 per cent by the age of between 4 and 5. Although the levels differ considerably across the SSA countries, this sharp increase in the early years, and the subsequent slight drop, is found in almost all the countries for which age‐specific estimates of underweight are available (UNICEF 1993a: table 3).5

                      Anthropometric Indicators of Undernutrition: Measurements and Evidence

Fig. 11.3. Estimated Trends In Prevalence Of Low Birth Weight (<2.5 kg) 1980–90, By Major Geographical Regions

Source: ACC/SCN 1992: p. 55.

(p.163)
                      Anthropometric Indicators of Undernutrition: Measurements and Evidence

Fig. 11.4. Estimated Percentage Of Children Who Are Underweight In Different Age Cohorts, By Major Geographical Regions

Source: UNICEFa 1993: p. 14.

11.3.5. Anthropometric Status by Gender

In Table 11.2, estimates of anthropometric failure in the underweight dimension are presented for two dozen SSA countries. In most of the countries there is no (statistically significant) difference between male and female children. There is, however, much more extensive evidence on differences in anthropometric status along gender lines in Africa.

In Table 11.4, summary statistics are reported from four surveys of evidence on the anthropometric status of children by sex in the SSA countries. Altogether 160, what is claimed to be nationally representative, sets of anthropometric data from almost every country in the region have been examined in the four surveys, not only in the underweight dimension, but also for stunting and wasting. In about two‐thirds of the samples there is no

Table 11.4. Summary of Evidence on Gender Differentials in Anthropometric Status of Children Aged 0–59 Months in SSA Countries

Study

Number of samples showing

Total

Anti‐male biasa

Anti‐female biasa

No bias

Svedberg (1990)

5

0

4

9

Klasen (1996)

21

3

45

69

Carlson and Wardlaw (1990)

11

1

11

23

Svedberg (1996)

16

0

43

59

Total

53

4

103

160

(a) Statistically significant (χ2‐test).

Sources: Svedberg (1990), Carlson and Wardlaw (1990), Klasen (1996), Svedberg (1996).

(p.164) statistically significant difference in anthropometric status between male and female children. In about one‐third of the samples, however, the incidence of anthropometric failure is significantly higher for male children than for female children. Only in four samples is there a statistically significant female disadvantage (for more detail and discussion, see Svedberg 1990, 1996 and Klasen 1996).

11.4. Sub‐Saharan Africa in International Comparison

11.4.1. Levels and Change Over Time

Levels On average, the estimated incidence of child undernutrition is lower in the SSA countries than in the Third World as a whole; this is so by all three anthropometric indicators (Table 11.5). The main reason is that the prevalence of anthropometric failure is almost twice as high in populous South Asia as compared to SSA by all three indicators. However, also in East Asia and the Pacific, the incidence of undernutrition by the weight‐for‐age and the weight‐for‐height indicators is higher than in SSA. It is also notable that no African country has a higher estimated share of undernourished children than found in India and Bangladesh by any of the indicators. In the Americas, the prevalence of undernutrition by the height‐for‐age indicator in Bolivia, Haiti, Honduras, Peru, and Guatemala is on a par with, or above, the average for the SSA countries. In the first two countries, the weight‐for‐age indicator also suggests a higher incidence of undernutrition than in Africa.

Changes Over Time Fig. 11.2 suggests that no long‐term improvement in the anthropometric status of children (with the underweight indicator) has taken place in SSA between 1975 and 1990. On comparing SSA with other major geographical regions in the World, we see that in South and South‐East

Table 11.5. Prevalence of Anthropometrically Failed Children Under 5 Years of Age, by Major Geographical Regions (Per Cent)

Region

Underweight (weight‐for‐age)

Stunting (height‐for‐age)

Wasting (weight‐for‐height)

SSA

31

39

8

Middle East and North Africa

23

33

7

South Asia

60

63

12

East Asia and Pacific

37

38

8

China

21

32

4

Americas

11

21

3

Total (developing countries)

36

42

8

Source: UNICEF 1993b.

(p.165) Asia there has been a significant decline over the entire 1975–90 period. In the other regions, there was a decline during 1975–85, but in China and Middle America/the Caribbean, there was a slight increase between 1985 and 1990. Revised estimates for the 1985–95 period appear in Fig. 11.2.6 According to these (highly preliminary) estimates, the prevalence of underweight children in SSA dropped by one percentage point between 1990 and 1995. The most notable message brought out by the recent estimates, however, is that the previous rather marked decline in most other regions seems to have slowed down considerably in the 1990s. (Whether this is a statistical artefact rather than a real phenomenon is discussed in the next chapter.)

11.4.2. Rural/Urban Differences

In Table 11.2 above, estimates of the prevalence of the underweight among small children are presented, showing the situation to be considerably worse in rural than in urban areas in the African countries. Although data are only reported for a few non‐African (Asian) countries in that table, the rural disadvantage in this respect is a global phenomenon, although the rural ‘bias’ seems to be more pronounced in Africa than elsewhere (UNICEF 1993a: table 2). Also, the large intra‐country differences reported in Table 11.3 are not unique for the SSA countries. Millman (1992) reports the estimated prevalence of the underweight in 10 Indian states, which ranged from 27 to 48 per cent. (The average for India in that sample is considerably lower than in the UNICEF estimates, mainly because another (lower) weight‐for‐age norm is used in the former.)

11.4.3. Differences by Age and Gender

According to the IBRDa (1995: table 27), except for Togo, there is no country in Africa which has an incidence of LBW as high as that in Bangladesh, Pakistan, or Sri Lanka (no data for India are presented). Notable is that Sri Lanka has an estimated incidence of LBW (22 per cent) that is almost twice as high as the African average (13 per cent).

The WHO/UNICEF (ACC/SCN 1992) have provided (admittedly rough) estimates of the prevalence of LBW on a regional basis for the 1980s (Fig. 11.3).7 These estimates reveal the same picture as the more selective IBRD data. The LBW share is by far the highest in South Asia (above 30 per cent). It is the second highest in SSA, but the difference between SSA and the other five regions is not that dramatic. (It is notable that the prevalence of LBW is as high as 6–7 per cent in the developed countries, the same as in Ghana and Zimbabwe.) The main difference between SSA and the rest of the world is that the estimated LBW share has not declined here during the 1980s.

When it comes to gender differentials in anthropometric status in young children, the SSA countries seem to be different than most other places. In (p.166) the SSA countries, it is quite common that boys have a statistically significant inferior anthropometric status vis‐à‐vis girls, but almost never the other way around (Table 11.4). In the rest of the developing world, the pattern is more varied. In some Asian and American countries, female children are at a disadvantage in terms of anthropometric status, in others vice versa. The notion that female children worldwide are at a nutritional disadvantage vis‐à‐vis male children has no support in the anthropometric evidence now available.

11.5. Anthropometric Status of Adults

The use of anthropometric measurements to assess the nutritional (and health) status of adults (as well as children above the age of five) is a rather recent phenomenon. There are few well‐established anthropometric measures for adults, and the available empirical evidence is scant when compared to that concerning children. Moreover, since adults and small children are assessed with different anthropometric methods, and because cut‐off points are derived from different principles, there are only limited possibilities for assessing their relative status in a given country (see next section).

11.5.1. Measurements and Norms

There are two main types of anthropometric indicators for adults that seem to have gained reasonably wide recognition. The first is similar to those used to assess small children. This is the estimated share of the adults in a population who fall below some height or weight norm. Only for weight is there a relatively well‐established norm: weights below those corresponding to a BMI of 18.5. (This number also underlies the CCOPs estimated by the FAO; cf. Chapter 9 above.) The ACC/SCN (1992: Chapter 4) has also used the share of women with a weight below 45 kg on the indication of increased obstetric risks. The same organization also estimates the share of women with a height below 145 cm, again on the basis of perceived increased health risks. Finally, the share of adult women with an arm circumference below 22.5 cm is estimated.

The second type of anthropometric measure in use is the average height of adults in the Third‐World populations related to average height in a reference population. The reference population is usually one in which there is no reason to expect nutritional (i.e. energy) inadequacy to have prevailed for a few generations. The Northern European populations have the de facto highest stature in the world and are used below as a reference norm. Notable is that the stature of an adult tells us nothing about his or her current nutritional situation; it is only used as an indicator of the ‘historical’ nutritional (and health) record during childhood and adolescence. Moreover, the average height of people in a population tells us nothing about the incidence of stunting; it can (p.167) be used only to compare averages for different populations. This is usually done on the presumption that all races and ethnic groups (with some reservations) have the same average genetic potential for final growth in stature (to be discussed in Chapter 12).

11.5.2. Evidence on Adult Anthropometric Failure

Incidence of Stunting andWasting The main evidence available is for women of reproductive age (15–49 years) collected by the ACC/SCN (1992). The base data were compiled from 340 studies from all around the world, carried out since the late 1970s. The data for women are acknowledged to be less ‘secure’ than the corresponding data for children, but claimed to ‘give a reasonable estimate of the extent of the problem’ (ACC/SCN 1992: pp.53, 73–4). The lack of similar data for males defies direct gender comparisons, but in combination with data on average height, something can still be said on gender differentials for adults (see below).

The principal findings are contained in Fig. 11.5. By most of the four indicators, women in SSA come out relatively favourably in international comparison. The share of stunted women is found to be very small in comparison with all other regions except China. In fact, by the height indicator, the incidence of failure in South Asia and South‐East Asia is about five times higher than in SSA. Also, the two weight indicators, as well as the arm circumference measure, suggest that women in SSA have a considerably better anthropometric status than women in Asia, and are roughly on a par with women in Latin America.

Adult Average Height In Table 11.6, estimates of the average height of male and female adults in ten different geographical Third‐World regions are presented, as well as the height of the fifth centile (the five per cent shortest). Estimates for Northern Europe have been included in the table to facilitate comparisons of relative anthropometric failure across regions. SSA, together with East Asia (China) and South‐East Asia, is found somewhere in the middle; the average height of both males and females is the smallest in Southern India and in Latin American Indian populations. It is the highest in the North African, Near Eastern and Latin American populations of European and African origin.

Males are on the average 5 to 10 per cent taller than females in the various regions, according to Table 11.6. The smallest difference is found in North Africa, the Near East and North Asia, and the largest in West Africa, South China, and the Indian populations in Latin America. West and South/East Africa have figures close to those in Northern Europe, which is also the case with populations in Northern India and Latin America of European and African decent.

It is of further note that the male:female ratio of the fifth centile is not very different from the 50th centile in most of the regions. This is an indication (p.168)

                      Anthropometric Indicators of Undernutrition: Measurements and Evidence

Fig. 11.5. Estimated Anthropometric Failure In Women Aged 15–49 Years, By Major Geographical Regions, 1980s

Source: ACC/SCN 1992: p. 53.

that in the most deprived segment of the population, female nutritional status relative to that of males is roughly on a par with that in the population at large; the main exception is South China. (The reliability and representativeness of these data are discussed in the next chapter.)

11.6. Comparing Children With Adults

The weight norms (cut‐off points) for adults have been derived from body weights that have been estimated to correlate with increases in health risks. The weight norms for small children have been derived from what is ‘statistically abnormal’ in Western populations. This means that we cannot compare the prevalence of the underweight among children and adults, respectively, within a country or region in a meaningful way.

However, the available estimates of incidence of anthropometric failure in children and adult women allow some interesting comparisons along age lines of relative anthropometric status across main geographical regions. In Fig. 11.6, the estimated prevalence of stunting and the underweight in (p.169)

Table 11.6. Average Height of Adults, by Major Geographical Regions, 1980s

Centile

Height in cm

Male/female ratio

Height in per cent of North European

Males

Females

Males

Females

5

50

5

50

5

50

5

50

5

50

West Africa

156

167

144

153

1.08

1.09

91

92

91

91

S.E. Africa

159

168

148

157

1.07

1.07

93

93

94

93

North Africa

158

169

150

161

1.05

1.05

92

93

95

95

Near East

162

171

154

161

1.05

1.06

95

95

97

95

North India

158

167

145

154

1.09

1.08

92

92

92

91

South India

153

162

139

150

1.10

1.08

89

90

88

89

North Asia

156

169

150

159

1.04

1.06

91

93

95

94

South China

161

166

143

152

1.13

1.09

94

92

91

90

S.E. Asia

153

163

144

153

1.06

1.07

89

90

91

91

Latin America

Indian pop.

152

162

139

148

1.09

1.10

89

90

88

88

Other pop.

165

175

152

162

1.09

1.08

97

97

96

96

North Europe

171

181

158

169

1.08

1.07

100

100

100

100

Source: Base data from Jürgens et al. 1990: section 6.

children (aged 0–5) and adult women (aged 15–49) are plotted for six main geographical regions (no data for women are available for North Africa and Near East). When it comes to the prevalence of underweight people, there is a high correlation between children and women across regions. The prevalence of the underweight among both children and women is by far the highest in South Asia (about 60 per cent for both groups) and the lowest in South America (about 10 per cent). The two ‘outliers’ are South‐East Asia and SSA. In both regions, about 30 per cent of the children are stunted, but the estimated incidence of stunting among women is more than twice as high in South‐East Asia as it is in SSA (43 and 20 per cent, respectively).

The picture is slightly different when it comes to the relative prevalence of stunting. There is a weaker ‘correlation’ between the observations, reflecting that the incidence of stunting in women relative to that in children (according to the measures used) is more varied across the regions. Also in this dimension, the overall situation is worst in South Asia. And as in the case of prevalence of the underweight, South‐East Asia and SSA are the main ‘outliers’, falling above and below the ‘implicit’ regression line, respectively.

The main observation emerging from Fig. 11.6 is that children are relatively far worse off in relation to adult women in SSA compared with all the other regions, and that the opposite holds in South‐East Asia. There are three main possible lines of explanations for these observations. One is that there are biases of different kinds in the measurements. The second is that the norms used are different and not comparable. The third is that there are (p.170)

                      Anthropometric Indicators of Undernutrition: Measurements and Evidence

Fig. 11.6. Estimated Prevalence Of Underweight and Stunted Womena (15–49 Years) and Young Childrenb (0–5 Years), By Major Geographical Regions,c 1980s

Sources: ACC/SCN 1992; UNICEFa 1993.

(a) Percentage of women with weight below 45 kg; height below 145 cm

(b) Percentage of children with weight below –2 SD of the NCHS median norm

(c) SA = South Asia; SEA = South‐East Asia; SSA = Sub‐Saharan Africa; SAm = South America; MAm = Middle America and the Caribbean

(d) Am = Americas (no separate data for South and Middle America are available).

‘factual reasons’. It could be, for instance, that children in SSA are more discriminated against in the intra‐household distribution of food and health facilities than in other regions. But it could also be that children are more frequently ill in Africa for other reasons and that this explains the relatively high incidence of anthropometric failure and high mortality (the latter is well above that in South Asia). (This hypothesis will be tested in Chapter 12.)

11.7. Summary and Conclusions

The bulk of the evidence on anthropometric failure in the world is focused on children below the age of five and refers to height and weight. With the standard cut‐off points, almost 40 per cent of the children in the SSA countries are stunted (low height for age), about 30 per cent are underweight (low weight for age), and less than 8 per cent are wasted (low weight for height). (p.171) The incidence of anthropometric failure by all three indicators is almost twice as high in India and Bangladesh, and no single SSA country is comparable with the South Asian countries.

There are large variations across the African countries and also within them. The incidence of anthropometric failure in rural areas is almost twice that in urban areas, and there are large differences across districts. Comparing different age groups, one finds a drastic increase in the incidence of anthropometric failure from birth up to the age between 1 and 2 years, and, subsequently, a slight decline. A comparison of children of the two sexes, reveals that male children are found to be at a disadvantage much more frequently than female children in the SSA countries, while the opposite is common in Asia and America.

When it comes to the anthropometric status of adults, there are few commonly accepted norms and the available empirical evidence is relatively scant. It suggests that, with the exception of China, the incidence of stunting among women in SSA is much lower than anywhere else in the Third World. The incidence of underweight people (by two indicators) is also lower in SSA than in South Asia and South‐East Asia, and comparable to that in Latin America. The average adult in SSA is taller than in South India, South‐East Asia, and Indian populations in Latin America, but smaller than in North Africa, the Near East, and Latin America.

The average heights of adult males and females in the SSA countries in relation to the average heights of males and females in Northern Europe are about the same, indicating that there is no large gender differential. This is the case also in most other regions; the main exception is in the Indian population in Latin America, where males have a relatively better anthropometric status in the final height dimension.

In this chapter, the most widely used anthropometric indicators of nutritional status, along with a brief summary of the available evidence for Africa in international comparison, have been presented without much comment. In subsequent chapters, a critical assessment of this evidence will be undertaken. In Chapter 12, errors and measurement biases in the data are identified and analysed. In Chapter 13, the more conceptual question of how well anthropometric measurements indicate nutritional status is addressed.

Notes

Notes:

(1.) The ACC/SCN, the Administrative Committee on Co‐ordination/Subcommittee on Nutrition, is a UN agency coordinating work on nutrition by WHO, UNICEF and the FAO. The ESN is a division of the FAO which has responsibility for the Nutrition Planning, Assessment and Evaluation Service. Its main publications are the Nutrition Country Profiles, which contain data not only on the anthropometric status of children, but also a large number of other indicators of the food and nutrition situation in individual countries.

(p.172)

(2.) Mora (1984) estimated the prevalence of undernutrition in a given child population with three different statistical cut‐off points. The difference between the highest and lowest estimates was more than 10 percentage points in some instances.

(3.) There are more anthropometric observations of pre‐school children in SSA from the 1960s and the 1970s. (For collections of such data, see Eveleth and Tanner 1976, 1990; Schofield 1979, Benefice et al. 1981, Dillon and Lajoie 1981, Keller and Fillmore 1983, Haaga et al. 1985, ACC/SCN 1987, 1988, 1989, Kumar 1987, Svedberg 1991a, Test et al. 1987, UNICEF 1985b, Gorstein and Akre 1988). The samples covered in these studies were, however, based on such a variety of methods, norms and cut‐off points that no meaningful comparisons across countries or over time could be undertaken.

(4.) It is of some interest to note that this result is contrary to what has been found in historical data from the now developed countries. In eighteenth‐and nineteenth‐century Britain, ‘military records show clearly that birth and residence in the urban areas, in particular London, was associated with shorter height’ (Floud 1992: p. 237). Additional evidence in the same vain and discussions are presented by Komlos (1990) and Steckel (1995: pp. 1921–2).

(5.) The only exceptions are The Seychelles and Mauritania, where it increases monotonically with age.

(6.) The estimates for the period 1975–90 are not strictly comparable with the estimates for the period 1985–95. The largest discrepancy is for the South Asian countries, due to the introduction of a revised estimation method in India. The revised estimate for India in 1990 is 53 per cent underweight, whereas with the previous method, it was 61 per cent (ACC/SCN 1997a).

(7.) These data are from WHO and UNICEF; the Bank claims that ‘UNICEF sources are not strictly comparable across countries because they are compiled from a combination of surveys and administrative records that may not have national coverage’ (IBRDa 1995: p. 240).