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close this bookCauses and Consequences of Intrauterine Growth Retardation, Proceedings of an IDECG workshop, November 1996, Baton Rouge, USA, Supplement of the European Journal of Clinical Nutrition (International Dietary Energy Consultative Group - IDECG, 1996, 100 pages)
close this folderLevels and patterns of intrauterine growth retardation in developing countries
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View the documentIntroduction
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(introductory text...)

M de Onis1, M Blössner1 and J Villar2

Correspondence: Dr Mercedes de Onis

1Nutrition Unit, World Health Organization, 20 Avenue Appia, 1211 Geneva 27, Switzerland;2Special Programme of Research, Development and Research Training in Human Reproduction, World Health Organization, 20 Avenue Appia, 1211 Geneva 27, Switzerland

The aim of this paper is to quantify the magnitude and describe the geographical distribution of intrauterine growth retardation (IUGR) in developing countries. We estimate that at least 13.7 million infants are born every year at term with low birth weight (LBW), representing 11% of all newborns in developing countries. This rate is approximately 6 times higher than in developed countries. LBW, defined as < 2500 g, affects 16.4% of all newborns, or about 20.5 million infants each year. IUGR, defined as birth weight below the 10th percentile of the birth-weight-for-gestational-age reference curve, represents 23.8%, or approximately 30 million newborns per year. Overall, nearly 75% of all affected newborns are born in Asia - mainly in South-central Asia - 20% in Africa, and about 5% in Latin America. Although some of these are healthy, small infants who merely represent the lower tail of a fetal growth distribution, in most developing countries a large proportion of newborns suffer from some degree of intrauterine growth retardation. These data demonstrate that many developing countries currently exceed the internationally recommended IUGR (> 20%) and LBW (> 15%) cut-off levels for triggering public health action, and that population-wide interventions aimed at preventing fetal growth retardation are urgently required.

Introduction

Intrauterine growth retardation (IUGR) constitutes a major clinical and public health problem in developing countries. Various criteria have been used to classify an infant as having experienced normal, subnormal, or supranormal growth in utero. Most recently a WHO Expert Committee (WHO, 1995a; de Onis and Habicht, 1996) recommended the 10th percentile of a birth-weight-for-gestational-age, sex-specific, single/twins risk curve (Williams et al, 1982) for the classification of small-for-gestational-age infants (SGA). Strictly speaking, SGA and IUGR are not synonymous (Altman and Hytten, 1989). Some SGA infants (e.g. those born to short mothers) may merely represent the lower tail of the 'normal' fetal growth distribution, while other infants who have been exposed to growth-inhibiting factors may actually meet the criteria for appropriate-for-gestational-age (AGA)(e.g. those born to tall, well nourished cigarette-smokers). In individual cases, however, it is usually very difficult to determine whether or not the observed reduced birth weight is the result of true in utero growth restriction, and classification is therefore based on the established cut-off for SGA. In fact, the higher the SGA rate, the greater the likelihood that SGA is a result of IUGR (WHO, 1995a). In this paper, for the purpose of being consistent with the terminology used in the Workshop, SGA infants will be referred to as IUGR.

Historically, because valid assessment of gestational age is often unavailable in developing countries, the incidence of low birth weight (LBW) has been often used as a proxy to quantify the magnitude of IUGR in these settings. This approach, however, underestimates considerably the overall magnitude of the IUGR problem as it does not take into account those infants whose weight at birth falls below the 10th percentile but who weigh more than 2500 g; many of these infants are likely to also have IUGR. Within these constraints, we make in this paper, for the first time, an attempt to quantify the magnitude and describe the geographical distribution of intrauterine growth retardation in developing countries. We use as the basis for the analysis, the incidence of infants born at term (³ 37 weeks of gestation) with low birth weight (< 2500 g), referred to as IUGR-LBW in this paper.

Methodology

Source of LBW incidence rates

Data on low birth weight (defined as weight at birth < 2500g) were obtained from an updated version (September 1996) of the WHO database on Low Birth Weight compiled by the Maternal Health and Safe Motherhood Programme (WHO, 1992). This database contains information published from 1980 onward. Articles and reports are identified through a search of library databases (Medline, Healthplan, Popline and Lilacs) and by tracing references found in them. In addition, data from country studies (some unpublished) are also included. Reports containing low birth weight data are examined to ensure basic standards in data collection and reporting, before including the information into the database. For each study, the database includes information related to the geographical region, year or time-period in which the data were collected, the nature or source of the data, sample size (only those with at least 100 births are included), and information regarding gestational age at birth if available (WHO, 1992).

The present analysis has been restricted to studies identified in the database as nationally representative and carried out between 1985 and 1995. The selected country data points are based on nine different sources of information: 52 (38%) are derived from monitoring systems (i.e., Government reports for monitoring "Health for All" indicators); 23 (17%) from registration data; 17 (13%) from the Western Pacific region data bank; 13 (10%) are estimates provided by Unicef field offices; 12 (9%) from hospital data; 6 (4%) from Government reports; 4 (3%) from community-based studies; 3 (2%) are estimates (with no specific methodology mentioned); and 6 (4%) are of unknown source (i.e., data extracted from a secondary source such as Unicef reports or others).

Estimates of IUGR-LBW rates

Estimates of IUGR-LBW rates for developing countries were calculated by applying to the total incidence of LBW the linear regression equation proposed by Villar et al. (Villar et al, 1994) in which the dependent variable was IUGR-LBW and the independent variable the total rate of LBW (ß = 0.8528; SE = 0.0282; P = 0.0001; r = 0.96). This regression equation, for which we calculated the 95% confidence bands (Kleinbaum et al, 1988) (Figure 1), was derived using studies from 60 populations (WHO, 1992; Puffer and Serrano, 1987) from developing countries where gestational ages and birth weights were recorded. All 60 studies were conducted from 1965 onward, and were based on prospective research projects and surveys whose major focus was birth weight with valid gestational age assessments (Villar et al, 1994; Villar and Belizán, 1982). For developed countries, the linear relationship between the proportion of IUGR-LBW and the total incidence of LBW was not a good predictor (ß = 0.2951; SE = 0.1759; P = 0.11; r = 0.4092; n = 16) and thus, for the purpose of this analysis, only the regression model for developing countries was used.

It is important to note that the use of the regression equation only provides an estimate of the incidence of IUGR infants that are low birth weight at term (area labeled as A in Figure 2); i.e., it does not include IUGR preterm infants, or IUGR infants with birth weights above 2500 g (areas labeled as B and C, respectively, in Figure 2).

Validation of the IUGR-LBW estimation

We further tested the agreement between the IUGR-LBW estimation from the regression model and the IUGR LBW rate observed in 17 data sets included in the WHO Collaborative Study on Maternal Anthropometry and Pregnancy Outcomes (WHO, 1995b), in which information was available on both birth weight and gestational age estimated from the last menstrual period. None of these data sets had been included in the earlier analysis used to develop the linear regression equation for estimating IUGR-LBW from overall LBW rates in developing countries (Villar et al, 1994).

The agreement between the two estimations is summarized by the mean of the differences, and the precision of the estimation by the 95% confidence interval of this mean. A graphic display of the agreement between the two values is presented by plotting the difference between estimations against their mean (Martin Bland and Altman, 1986). For the purpose of these analyses, it is assumed that the differences follow an approximately normal distribution and that the differences do not vary systematically over the range of the IUGR-LBW rates.


Figure 1. Relationship between total incidence of low birth weight and incidence of low birth weight/IUGR in developing countries (adapted from Villar et al, 1994).


Figure 2. Birth weight percentiles and perinatal mortality rates (per 1000) for single male births (adapted from WHO, 1995a).

Intrauterine Growth retardation (IUGR) = A+ B +C

A = < 2500 g, ³ 37 weeks
B = < 10th centile, < 37 weeks
C = <10th centile, ³ 2500 g

Regional and global estimates of IUGR-LBW

Regional incidences of IUGR-LBW and LBW were estimated for each geographical area by weighting the available national incidences according to the total number of estimated live births in 1995 in each country. The numbers of IUGR-LBW and LBW newborns in each area were obtained by applying incidence estimates to the total number of live births. Global incidences in developing countries were calculated by adding the estimated number of IUGR-LBW newborns in each area and using as the denominator the 1995 total live births of all developing countries. Estimates for IUGR-LBW and LBW were obtained only for those regions where the proportion of live births covered by studies identified in the database as nationally representative was > 80%.

For this analysis, countries have been grouped according to the United Nations classification (UN 1995), dividing the world into six major areas, which are further subdivided into 20 regions. Total live births estimated for 1995 for the countries concerned were obtained from the UN Population Prospects (UN, 1995).

Results

1. Coverage attained by the database

Table 1 shows the population coverage attained by the database relative to studies identified as nationally representative conducted between 1985 and 1995. All data together are representing 90% of the estimated total number of live births in developing countries in 1995. Overall, there are data available for 106 out of 146 developing countries. Although the data refer to the period 1985 to 1995, the majority of the information corresponds to the first half of this period, with only 50 (37%) out of the total 136 data points based on studies from 1990 onward.

Table 1. Population coverage of LBW data identified as nationally representative in the WHO Database on Low Birth Weight (1985-1995)

UN regions

Countries with data available

Total number live births in 1995 (thousanda)

Coverage live births in 1995 (%)

AFRICA

40/53

29632

74.5

Eastern Africa

12/17

10177

66.0

Middle Africa

6/9

3716

89.0

Northern Africa

5/6

4799

63.8

Southern Africa

4/5

1476

14.6

Western Africa

13/16

9464

92.8

ASIA

33/47

84067

95.3

Eastern Asia

4/5

24362

97.7

South-central Asia

8/14

41812

94.9

South-eastern Asia

9/10

12695

98.3

Western Asia

12/18

5198

80.1

LATIN AMERICA AND THE CARIBBEAN

28/33

11922

99.8

Caribbean

9/13

722

97.9

Central America

7/8

3577

99.8

South America

12/12

7623

100.0

OCEANIA

8/16

510

99.7

Australia-New Zealand

2/2

323

100.0

Melanesia

4/4

179

100.0

Micronesia

1/5

1.2

16.0

Polynesia

1/5

6.4

93.8

Developing countries

106/146

124532

90.7

Developed countriesb

30/45

14347

79.3

World total

136/191

138879

89.6

a Total live births in 1995 based on the UN World Population Prospects, 1995.
b Includes Europe, North America, Australia, New Zealand and Japan.

Coverage in Africa

Information is available for 75% of the total live births in that region in 1995, with data for 40 out of 53 countries. Overall the coverage is high for Middle (89%) and Western Africa (93%), but low for Eastern (66%), Northern (64%) and Southern Africa (15%). Data are lacking from Burundi, Kenya, Somalia, Uganda and Zambia (in the east); Chad, Congo and Equatorial Guinea (in the middle); Egypt (in the north); South Africa (in the south); and Cape Verde, Liberia and Mali (in the west).

Coverage in Asia

Although only 33 out of 47 countries in Asia have information on the incidence of LBW between 1985 and 1995, the region is highly represented in the database, covering 95% of the total live births. Data are available for the most populous countries in this region such as Bangladesh, China, India, Indonesia and Pakistan. Looking at the coverage in the subregions, Western Asia has 80%, while Eastern, South-central and South-eastern Asia have a coverage rate of 95% or above. Countries still with no information are mostly in South-central Asia (Bhutan, Kazakstan, Kyrgyzstan, Nepal, Turkmenistan, and Uzbekistan) and Western Asia (Armenia, Azerbaijan, Georgia, Kuwait, Palestinian self-rule areas, and Yemen). Data are also lacking from the Democratic People's Republic of Korea (in Eastern Asia) and Lao People's Democratic Republic (in South-eastern Asia).

Coverage in Latin America

Countries from Latin America are well represented in the database (28 out of 33), reaching a coverage of almost 100% of the total number of live births. Those countries still not included in the database are mostly in the Caribbean (Antigua and Barbuda, Barbados, Grenada, and St Vincent and the Grenadines), but include also Belize in Central America.

Coverage in Oceania

Although only half of the countries in the region (8 out of 16) are represented in the database, the overall coverage for Oceania is very high (~ 100%), as it includes the most populous countries such as Australia, New Zealand, Papua New Guinea and Western Samoa. Micronesia is the only subregion with low coverage (16%). The following countries are still not included in the database: Kiribati, Marshall Islands, Federated States of Micronesia and Nauru (in Micronesia), and Cook Islands, Nine, Tonga and Tuvalu (in Polynesia).

2. Validation regression model to estimate incidence of IUGR-LBW

The IUGR-LBW rate estimated using the predictive equation was compared with the observed values in 17 selected data sets to test the agreement between the observed and the estimated rates. Table 2 presents for each of the 17 data sets the incidence of IUGR-LBW observed in the study compared to that derived from the regression model. Overall, the model underestimates the incidence of IUGR-LBW by a mean difference of -1.46% (95% confidence intervals of this mean difference: - 2.514% to 0.403%). Figure 3 presents a graph of the agreement between the observed and the estimated IUGR-LBW rates by plotting their difference against their mean. In 14 out of the 17 data sets, the regression model estimated a lower incidence of IUGR-LBW. The underestimation could be as low as 2.5% (lower bound of the 95% confidence interval) and seems fairly constant at all levels of the IUGR-LBW, although the distribution is wider at higher LBW rates more likely reflecting small number of observations.

3. Worldwide distribution IUGR-LBW

Figure 4 shows the distribution of developing countries according to the incidence of IUGR-LBW. Rates are grouped into four categories (< 5%, 5-10%, 10-15%, and ³ 15%), referred to as (relatively) low, moderate, high, and very high. Most developing countries in Latin America and the Caribbean show low to moderate prevalences of IUGR-LBW. The only exceptions are Colombia and Honduras with rates between 10 and 15%.

Africa, in turn, shows the greatest variability among countries, with prevalences going from as low as 1% in the Libyan Arab Jamahiriya or 1.5% in Zimbabwe to 18.1% in Zaire and Guinea. Overall, infants born in sub-Saharan countries are more likely to suffer from IUGR-LBW than their counterparts in the northern countries of Africa. Very high rates, i.e. ³ 15%, are found in Zaire, Angola, Guinea, and The Gambia. High prevalences (between 10 and 14%) are apparent in Tanzania, Rwanda, Niger, Nigeria, Togo, and Guinea-Bissau. However, as shown in Table 1, data are still missing for 13 out of the 53 countries in the region.

South-central Asian countries - which include Afghanistan, Bangladesh, India, Iran, Pakistan, Maldives, Sri Lanka and Tajikistan - show the highest rates worldwide. According to our estimates, Bangladesh presents the highest rate of all countries, with an IUGR-LBW incidence rate of 39.4%. In South-eastern Asia, the highest prevalences (in the range of 10-14%) are found in Myanmar and Cambodia. Eastern Asia shows prevalences of IUGR-LBW ranging from 4 to 7%, that is low and moderate levels, whereas in Western Asia the range goes from 1 to 6%. In this subregion the only exception is Bahrain for which a very high rate of IUGR-LBW (above 25%) has been estimated.

4. Global and regional estimates

Table 3 shows the global, regional and subregional estimates for the incidence of IUGR-LBW and LBW, together with the estimated absolute numbers of newborns affected. Estimates have been calculated only for those regions and subregions that are reasonably well covered (> 80%) by the database (see Table 1). Appendix I presents the incidence rates of LBW and the estimated IUGR-LBW rates used in the calculations for the 136 countries with data available on LBW for the period from 1985 to 1995. Information is also included on the year and source of data for each of the country data points.

In developing countries, one in nine live births (more than 13.5 million) IUGR-LBW newborns were born in 1995, accounting for 11% of the total newborn population that year. Regional data show that the incidence of IUGR-LBW is highest in Asia (12.3%), followed by Oceania (9.8%) (excluding Australia and New Zealand), and Latin America and the Caribbean (6.5%).

Although estimates for Africa could not be calculated because of insufficient data coverage, for the two subregions of Africa for which coverage reached > 80% - Middle and Western Africa the incidence of IUGR-LBW was 14.9% and 11.4%, respectively (Table 3). It would thus seem reasonable to assume that the overall IUGR-LBW rate for Africa as a whole probably follows that of Asia. In South-central Asia, the region which accounts for almost a third of the world's births, it is estimated that 21% of the newborns suffer from IUGR-LBW, i.e., more than 8.5 million each year or approximately one in five live newborns.

As previously mentioned, these global and regional levels refer exclusively to the incidence of IUGR infants that are also LBW (area labeled as A in Figure 2). However, the incidence rates of IUGR and IUGR-LBW observed in the 17 data sets included in the WHO Collaborative Study on Maternal Anthropometry and Pregnancy Outcomes (WHO, 1995b) give an estimate of the magnitude of the difference between the two rates. The definition of IUGR was birth weight below the 10th percentile of the birth-weight-for-gestational-age curve recommended for international use (de Onis and Habicht, 1996). Table 2 shows that the incidence rate of IUGR is consistently higher than that of IUGR-LBW in all data sets by a mean difference of 14.5% (95% confidence intervals of this mean difference: 10.9% to 18.1%). The mean IUGR rate is 23.8%, ranging from 9.4 in China to 54.2 in India (WHO, 1995b).

Table 2. Observed IUGR-LBW rate in 17 datasets from developing countries compared to the incidence of IUGR-LBW estimated using the regression model

Country, year, and location

Sample size

Study design

Method of estimation pregnancy duration

LBW (% < 2500g)

IUGR (% < 10th percentile)

IUGR-LBW (Observed)

IUGR-LBW (Estimated*)

D**

Argentina, 1984-86, City of Rosario

5634

Retrospective: clinical records using standardized forms

LMP

6.3

9.7

3.4

2.1

- 1.3

China, 1981-82, 6 subdistricts of Nanshi in Shanghai

4753

Prospective: pregnant women identified and followed to delivery

LMP

4.2

9.4

2.4

0.3

- 2.1

Colombia, 1989, City of Cali

4598

Retrospective: clinical records using standardized forms

LMP

16.1

17.8

6.8

10.5

3.7

Cuba, 1981, mixed urban and rural centres

4779

Retrospective: clinical records using standardized forms

LMP

8.1

14.7

5.0

3.7

- 1.3

Gambia, 1976-84, Keneba village

379

Prospective: longitudinal community supplementation trial

Dubowitz (within 5 days of delivery)

12.1

13.5

5.2

7.1

1.9

Guatemala, 1969-77, four highland rural villages

286

Prospective: longitudinal randomized community

LMP

12.5

25.3

9.8

7.4

- 2.4

India, 1990, Pune

4307

Prospective: pregnant women identified and followed to delivery

LMP

28.2

54.2

24.8

20.8

- 4.0

Indonesia, 1983, Municipality of Bogor and surrounding villages

1647

Prospective study of women throughout pregnancy and one month postpartum

LMP

10.5

19.8

8.0

5.7

- 2.3

Lesotho, 1982, two rural communities

1071

Prospective: pregnant women identified and followed to delivery

LMP

10.3

13.0

8.3

5.5

- 2.8

Malawi, 1986-89, three rural communities

938

Prospective: women identified in baseline study and recaptured during pregnancy

Modified Dubowitz

11.6

26.1

7.9

6.6

- 1.3

Myanmar, 1981-82, communities in urban and rural areas

3542

Prospective: pregnant women identified and followed to delivery

LMP

17.8

30.4

12.7

11.9

- 0.8

Nigeria, 1976-78, urban

15,159

Retrospective: clinical records using standardized forms

LMP

12.4

22.2

5.7

7.3

1.6

Nepal, 1990, rural

-

Prospective: pregnant women identified and followed to delivery

LMP

14.3

36.3

11.8

8.9

- 2.9

Nepal, 1990, urban

3629

Prospective: pregnant women identified and followed to delivery

LMP

22.3

42.7

18.2

15.8

- 2.4

Sri Lanka, 1990, rural

1851

Prospective: pregnant women identified and followed to delivery

LMP

18.4

34.0

15.8

12.4

- 3.4

Thailand, 1979-80, rural and urban centres

4124

Prospective: pregnant women identified and followed to delivery

LMP

9.6

17.0

6.9

4.9

- 2.0

Vietnam, 1982-84, City of Hanoi and one rural district

4428

Prospective: pregnant women identified and followed to delivery

LMP

5.2

18.2

4.2

1.2

- 3.0

* Y = - 3.2452 + 0.852 X (Villar et al, 1994).

** Difference between observed and estimated IUGR-LBW rates [mean difference = - 1.46 (95% CI: - 2.51 to -0.40)].

Source 17 data sets: WHO Collaborative Study on Maternal Anthropometry and Pregnancy Outcomes, 1995 (WHO, 1995b).

LMP = last menstrual period.

Discussion

The data presented confirm the magnitude of intrauterine growth retardation in developing countries. As summarized in Table 4, we estimate that at least 13.7 million babies in developing countries are already malnourished at birth (IUGR-LBW) every year, representing 11% (ranging from 1.9% to 20.9%) of all newborns in these countries. This rate is considerably higher than that estimated for developed countries, which is approximately 2%. Overall, the incidence of IUGR-LBW is about 6 times higher in developing than in developed countries (Villar et al, 1994).

The estimates for IUGR-LBW should be viewed as a conservative estimation of the magnitude of fetal growth retardation; the actual incidence of IUGR could be considerably higher. For example, if the rate of infants below the 10th percentile of the birth-weight-for-gestational-age reference curve is considered, 23.8%, or approximately 30 million newborns per year, would be affected (Table 4). There are nevertheless some healthy infants with birth weights below the 10th percentile, who represent the lower tail of a fetal growth distribution. However, in most developing countries a large proportion of newborns suffers from some degree of IUGR, as illustrated by the overall downward shift of the birth weight distribution. Unfortunately, a methodology to disentangle these two groups is not available.


Figure 3. Difference of observed and estimated IUGR-LBW rates plotted against the mean of the two rates using 17 data sets from developing countries.


Figure 4. Incidence of IUGR-LBW in developing countries, 1985-1995.

The destination employed and the presentation of material on this map do not imply the expression of any opinion whatsoever on the part of the World Health Organization concerning the legal status of any country, territory, city or area or of its authorities, or concerning the delimitation of its frontiers or boundaries. Dotted lines represent approximate border lines for which there may not yet be full agreement.

Table 3. Estimated incidence rate of LBW and IUGR-LBW, and expected number of affected newborns in a year


Incidence LBW

Total incidence IUGR-LBW

United Nations regions and subregions

% (< 2500g)

Total numbers (thousand)

% (< 2500g; ³ 37 weeks)

Total numbers (thousand)

AFRICA

NAb

NAb

NAb

NAb

Eastern Africa

NAb

NAb

NAb

NAb

Middle Africa

21.3

792

14.9

554

Northern Africa

NAb

NAb

NAb

NAb

Southern Africa

NAb

NAb

NAb

NAb

Western Africa

17.2

1628

11.4

1001

ASIA

18.0d

14911d

12.3d

10147d

Eastern Asia

5.8d

1339d

1.9d

463d

South-central Asia

28.3

11833

20.9

8739

South-eastern Asia

10.3

1308

5.6

711

Western Asia

8.3

431

4.5

234

LATIN AMERICA AND THE CARIBBEAN

11.5

1370

6.5

779

Caribbean

11.7

84

6.7

48

Central America

12.3

440

7.2

258

South America

11.1

846

6.2

473

OCEANIA

15.0e

28.2e

9.8e

18.4e

Melanesia

15.4

28

9.9

18

Micronesia

NAb

NAb

NAb

NAb

Polynesia

4.0

0.2

0.2

0.4

DEVELOPING COUNTRIES

16.4

20423

11.0

13699

DEVELOPED COUNTRIESa

6.2

890

NAc

NAc

WORLD TOTAL

15.3

21313

NAc

NAc

a Includes Europe, North America, Australia, New Zealand and Japan.
b Not applicable because coverage of live births < 80%.
c Not applicable because developed status.
d Excludes Japan.
e Excludes Australia and New Zealand.

Table 4. Summary estimates of impaired fetal growth in developing countries

Indicator

Source

Rate (%)

Total number newborns affected per year¹

IUGR-LBW (< 2500g; ³ 37 wks gestation)

Live births weighted average using LBW rates from WHO data bank (WHO, 1992) and regression model (Villar et al, 1994)

11.0 (1.9-20.9)²

13,699,000

LBW (< 2500g; all gestational ages)

Live births weighted average using LBW rates from WHO data bank

16.4 (5.8-28.3)

20,423,000

IUGR (< 10th percentile; all gestational ages)

From WHO Collaborative Study on Maternal Anthropometry and Pregnancy Outcomes (WHO, 1995b)

23.8 (9.4-54.2)

29,639,000

¹ Total live births for 1995 are based on the UN World Population Prospects (UN, 1995).
² Range.

The risk of being born IUGR-LBW is highest in Asia (mainly South-central Asia), followed by Africa (Middle and Western Africa), Oceania (Melanesia), and the Latin American region. However, the number of total live births in each geographical region has the effect of making the geographical distribution even more unequal; nearly 75% of all affected newborns are born in Asia - mainly in South-central Asia-20% in Africa, and about 5% in Latin America. The developing countries of Oceania contribute very little to the absolute number of IUGR-LBW because there were only 187,000 live births reported in this region in 1995.

Major constraints to deriving the above estimates included both the qualitative and quantitative limitations of the available data. Moreover, the assessment of the relative contribution of IUGR to total incidence of LBW is conservative given that we used a regression model that underestimates IUGR-LBW by an average of 1.5% (95% CI: - 2.5 to -0.4). These constraints notwithstanding, we nevertheless consider this to be a valid attempt to quantify the magnitude and geographical distribution of IUGR; not only does it provide an incentive for improving data quality, but it is also a suitable means for identifying those countries where population-wide interventions to prevent and control IUGR are urgently required.

In addition to improving the availability and quality of birth weight data, there is a compelling need for feasible measures to assess gestational age or fetal growth. The World Health Organization has recently recommended that countries implement simplified data collection systems for all deliveries and encourage the systematic collection of population-based data on birth-weight-for-gestational-age (WHO, 1995a). Nevertheless, this recommendation is unlikely to be followed by the majority of the developing countries in the near future given the difficulties inherent in obtaining valid assessments of gestational age. Therefore, at the present time, our estimates of IUGR-LBW represent a good public health approximation for descriptive and epidemiological purposes.

A prevalence of IUGR in excess of 20% has been recommended as the cut-off point for triggering public health action. In the absence of information on gestational age, a prevalence of > 15% of LBW may be used as a proxy cut-off (WHO, 1995a). As shown in Table 4, Figure 4 and Appendix I, many developing countries currently exceed these trigger levels for action and, thus, population-wide interventions are urgently needed in these settings. Unfortunately a systematic review of 126 randomized controlled trials (RCT) evaluating 36 interventions to prevent or treat impaired fetal growth has shown that most of them did not show any significant effect on short-term perinatal outcomes (Gülmezoglu et al, 1997). There were, nevertheless, a few interventions that are likely to be beneficial: smoking cessation, balanced protein/energy supplementation and antimalarial chemoprophylaxis in primi-gravidae. Other interventions such as zinc, folate and magnesium supplementation during gestation merit further research. Appropriate combinations of interventions should also be evaluated since it is more likely that a synergistic approach will reduce a multicausal outcome like IUGR.

In summary, the data presented confirm that intrauterine growth retardation is a major public health problem worldwide. Fetuses who suffer from growth retardation have higher perinatal morbidity and mortality (Williams et al, 1982; Balcazar and Haas, 1991; Villar et al, 1990), and are at an increased risk of sudden infant death syndrome (Øyen et al, 1995). During childhood they are more likely to have poor cognitive development (Paz et al, 1995; Low et al, 1992) and neurologic impairment (Parkinson et al, 1981; Taylor and Howie, 1989; Villar et al, 1984); in adulthood they are at increased risk of cardiovascular disease (Osmond et al, 1993), high blood pressure (Williams et al, 1992), obstructive lung disease (Barker, 1991), diabetes (Hales et al, 1991), high cholesterol concentrations (Barker et al, 1993) and renal damage (Hinchliffe et al, 1992). Moreover, IUGR contributes to closing the intergenerational cycle of poverty, disease and malnutrition. The implications of this vicious cycle are enormous both in terms of human and socioeconomic development of the affected populations. Country-wide interventions aimed at preventing fetal growth retardation are urgently needed. A good start in life will pay off, both in terms of human capital and economic development.

Acknowledgements - We are grateful to Mrs Elisabeth Åhman from the WHO Maternal Health and Safe Motherhood Programme for kindly providing us with the latest version of the WHO Database on Low Birth Weight.

References

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Balcazar H & Haas ID (1991): Retarded fetal growth patterns and early neonatal mortality in a Mexico city population. Bull Pan. Am. Health Organ. 25, 55-63.

Barker DJ, Martyn CN, Osmond C, Hales CN & Fall CH (1993): Growth in utero and serum cholesterol concentrations in adult life. BMJ 307, 1524-1527.

Barker DJP (1991): The intrauterine origins of cardiovascular and obstructive lung disease in adult life: The Mark Daniels lecture 1990. J. Royal Coll Phys. London 25, 129-133.

de Onis M & Habicht JP (1996): Anthropometric reference data for international use: recommendations from a World Health Organization Expert Committee. Am. J. Clin. Nutr. 64, 650-658.

Gülmezoglu M, de Onis M & Villar J (1997): Effectiveness of interventions to prevent or treat impaired fetal growth. Obstet. Gynecol Surv. 52, 139-149.

Hales CN, Barker DJ, Clark PM et al (1991): Fetal and infant growth and impaired glucose tolerance at age 64. BMJ 303, 1019-1022.

Hinchliffe SA, Lynch MR, Sargent PH, Howard CV & Van Velzen D (1992): The effect of intrauterine growth retardation on the development of renal nephrons. Br. J. Obstet Gynaecol 99, 296-301.

Kleinbaum DG, Kupper LL & Muller KE (1988): Applied regression analysis and other multivariable methods. PWS-KENT Publishing Company: Boston. Pp 41-79.

Low J. Handley-Derry M, Burke S et al (1992): Association of intrauterine fetal growth retardation and learning deficits at age 9 to 11 years. Am. J. Obstet Gynecol 167, 1499-1505.

Martin Bland JM & Altman DG (1986): Statistical methods for assessing agreement between two methods of clinical measurement. Lancet i, 307-310.

Osmond C, Barker DJ, Winter PD, Fall CH & Simmonds SJ (1993): Early growth and death from cardiovascular disease in women. BMJ 307, 1519-1524.

Øyen N. (Skjærven R. Little R & Wilcot A (1995): Fetal growth retardation in Sudden Infant Death Syndrome (SIDS) babies and their siblings. Am. J. Epidemiol. 142, 84-90.

Parkinson CE, Wallis S & Harvey DR (1981): School achievement and behaviour of children who are small-for-dates at birth. Dev. Med. Child. Neurol. 23, 41-50.

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Taylor DJ & Howie PW (1989): Fetal growth achievement and neurodevelopmental disability. Br J. Obstet Gynaecol 96, 789-794.

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Villar J & Belizán JM (1982): The relative contribution of prematurity end fetal growth retardation to low birth weight in developing and developed societies. Am. J. Obstet. Gynecol. 143, 793-798.

Villar J, Smeriglio V, Martorell R. Brown CH & Klein RE (1984): Heterogenous growth and mental development of intrauterine growth-retarded infants during the first three years of life. Pediatrics 74, 783-791.

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Discussion

The paper by de Onis et al. is a great achievement in obtaining for the first time global estimates of levels of IUGR in different countries and regions of the world. A problem that could introduce biases is that most of the data that are available from different parts of the world are from babies delivered at clinics, whereas in some regions, for instance in Africa, most babies are born at home, and it is not possible to judge the validity of extrapolations of prevalence and risk data from clinic to home deliveries. There is a need to determine whether data of hospital-born babies in developing countries are indeed representative of the larger proportion born at home.

Like Bakketeig, de Onis draws attention to the fact that while the focus of the workshop is primarily on IUGR infants born at term with a birthweight < 2500 g, there are also IUGR infants born prematurely and infants born with a birthweight ³ 2500 g who nevertheless were not able to attain their full growth potential and are therefore also to be considered IUGR. Figure 2 of the paper by de Onis et al. shows that perinatal mortality rates are highest among babies who are both premature and IUGR. In public health terms it is important to have data on newborns that are associated with the risk of one or more undesirable outcomes at a later stage in life. Birthweight, symmetry at birth, length of gestation, and the different etiologies underlying these parameters are all related to some extent, and at present it is not yet possible to say which of these factors or what combination (degree of IUGR being one of them) would permit to make the best prediction of preventable risk. In practical terms it is easiest to measure birthweight and to assess symmetry at birth using various anthropometric indicators. To get more valid estimates of length of gestation and degree of IUGR, a more frequent and universal use of ultrasonography dating would have to be advocated. Workshop participants agreed that this would not be making good use of scarce resources in developing countries and may even have unintended negative consequences in regions where female fetuses are more likely to be aborted than male ones. It was also emphasized that there is no evidence from randomized controlled trials that early diagnosis and delivery of IUGR babies with routine use of ultrasound has led to significantly improved outcomes in developed countries.

A WHO Expert Committee acknowledged and regretted the discontinuity in classification of growth retardation before and after delivery. The group dealing with fetal growth recommended that future growth curves be developed using the z-score system. It examined all available data sets on fetal growth using different criteria (an important one among these being associated risk data), to select the one of Williams in the US as the one with the fewest shortcomings. Williams' data were collected between 1972 and 1976, and Hoffman expressed the opinion that temporal trends may have rendered them obsolete in the US; nevertheless, WHO's Expert Committee has recommended them for international use as, on the basis of a number of criteria, they represent the best option presently available.

Some people still advocate the development of local growth curves. Several discussants reemphasized the evidence leading them to the conviction that all populations have the same growth potential (see discussion of Bakketeig paper), even though it may take more than one generation to attain it. The group's consensus is that, from a public health perspective (as opposed to case management), an international reference, based on the growth of healthy babies living under optimal conditions, should be used.

Appendix 1. Incidence of LBW and derived estimates of IUGR-LBW by country (1985-1995)

Country

Data source

Year

LBW (% < 2500g)

IUGR-LBW¹ (%)

Afghanistan

Monitoring system

1987

19.0

13.0

Albania

Registration data

1990

6.5

NA

Algeria

Field estimate

1988

9.0

4.4

Angola

Monitoring system

1987

21.4

15.0

Argentina

Registration data

1992

5.9

1.8

Australia

Western Pacific region data bank

1994

6.3

NA

Austria

Registration data

1985

5.8

NA

Bahamas

Monitoring system

1987

8.0

3.6

Bahrain

Registration data

1994

34.0

25.8

Bangladesh

Monitoring system

1987

50.0

39.4

Belarus

Monitoring system

1987

5.1

NA

Belgium

Registration data

1987

6.1

NA

Benin

Field estimate

1988

8.0

3.6

Bolivia

Field estimate

1988

12.0

7.0

Botswana

Field estimate

1988

8.0

3.6

Brazil

Registration data

1989

11.7

6.7

Brunei

Western Pacific region data bank

1994

5.0

1.0

Bulgaria

Monitoring system

1987

6.3

NA

Burkina Faso

Monitoring system

1987

10.8

6.0

Cambodia

Western Pacific region data bank

1994

18.4

12.4

Cameroon

Monitoring system

1987

10.0

5.3

Canada

Monitoring system

1987

5.6

NA

Central African Rep.

Monitoring system

1987

14.5

9.1

Chile

Registration data

1988

7.2

2.9

China

Western Pacific region data bank

1991

6.0

1.9

Colombia

Monitoring system

1987

17.3

11.5

Comoros

Monitoring system

1987

6.8

2.5

Costa Rica

Government report

1989

7.5

3.2

Cote d'Ivoire

Monitoring system

1987

15.0

9.6

Cuba

Registration data

1990

7.6

3.2

Cyprus

Monitoring system

1987

5.0

1.0

Czech Republic

Registration data

1994

5.5

NA

Denmark

Registration data

1991

5.4

NA

Djibouti

Monitoring system

1987

11.0

6.1

Dominica

Monitoring system

1985

10.5

5.7

Dominican Republic

Unknown source

1991

11.0

6.1

Ecuador

Field estimate

1988

11.0

6.1

El Salvador

Community-based data

1993

8.9

4.3

Eritrea

Unknown source

1993

13.0

7.8

Ethiopia

Hospital data

1988-93

8.9

4.3

Fiji

Western Pacific region data bank

1991

18.0

12.1

Finland

Registration data

1985

4.0

NA

Gabon

Monitoring system

1987

7.7

3.3

The Gambia

Unknown source

1989

24.0

17.2

Ghana

Monitoring system

1987

6.0

1.9

Greece

Registration data

1985

6.0

NA

Guatemala

Field estimate

1988

14.0

8.7

Guinea

Field estimate

1988

25.0

18.1

Guinea-Bissau

Hospital data

1987

20.4

14.1

Guyana

Monitoring system

1987

12.0

7.0

Haiti

Monitoring system

1987

15.0

9.6

Honduras

Field estimate

1988

20.0

13.8

Hungary

Government report

1993

9.9

NA

India

Estimate

1991

28.0

20.6

Indonesia

Monitoring system

1987

8.2

3.8

Iran

Government report

1991

8.0

3.6

Iraq

Hospital data

1991

8.0

3.6

Ireland

Registration data

1987

4.4

NA

Israel

Hospital data

1992

6.9

2.6

Jamaica

Monitoring system

1987

12.0

7.0

Japan

Western Pacific region data bank

1994

7.0

NA

Jordan

Monitoring system

1985

10.0

5.3

Lebanon

Monitoring system

1985

10.0

5.3

Lesotho

Monitoring system

1987

10.0

5.3

Libyan A.J.

Monitoring system

1987

5.0

1.0

Lithuania

Registration data

1992

4.4

NA

Luxembourg

Monitoring system

1987

6.2

NA

Madagascar

Estimate

1994

15.0

9.6

Malawi

Monitoring system

1987

10.0

5.3

Malaysia

Western Pacific region data bank

1994

8.3

3.8

Maldives

Government report

1993

20.0

13.8

Malta

Hospital data

1985

4.2

NA

Mauritania

Monitoring system

1985

10.0

5.3

Mauritius

Monitoring system

1987

7.7

3.3

Mexico

Field estimate

1988

12.0

7.0

Mongolia

Community-based data

1992

6.0

1.9

Morocco

Monitoring system

1985

9.0

4.4

Mozambique

Monitoring system

1987

11.3

6.4

Myanmar

Monitoring system

1987

15.9

10.3

Namibia

Hospital data

1990

11.9

6.9

New Zealand

Western Pacific region data bank

1994

5.7

NA

Nicaragua

Hospital data

1987

10.0

5.3

Niger

Monitoring system

1985

20.0

13.8

Nigeria

Field estimate

1988

20.0

13.8

Norway

Monitoring system

1985

4.5

NA

Oman

Hospital data

1992

9.0

4.4

Pakistan

Monitoring system

1987

25.0

18.1

Palau

Western Pacific region data bank

1994

9.6

4.9

Panama

Registration data

1985

9.8

5.1

Papua New Guinea

Western Pacific region data bank

1994

16.0

10.4

Paraguay

Monitoring system

1987

8.0

3.6

Peru

Field estimate

1988

9.0

4.4

Philippines

Western Pacific region data bank

1994

11.0

6.1

Poland

Registration data

1993

8.6

NA

Portugal

Registration data

1985

5.4

NA

Qatar

Monitoring system

1987

5.0

1.0

Rep. of Korea

Western Pacific region data bank

1988

4.3

0.4

Romania

Hospital data

1992

10.1

NA

Russian Federation

Monitoring system

1987

5.1

NA

Rwanda

Unknown source

1985

17.0

11.3

Saint Kitts and Nevis

Monitoring system

1985

9.4

4.8

Saint Lucia

Monitoring system

1985

9.7

5.0

Sao Tome and Principe

Monitoring system

1987

7.0

2.7

Saudi Arabia

Hospital data

1989

8.3

3.8

Senegal

Monitoring system

1985

10.0

5.3

Seychelles

Monitoring system

1987-88

10.1

5.4

Sierra Leone

Monitoring system

1987

13.0

7.8

Singapore

Western Pacific region data bank

1994

7.3

3.0

Slovenia

Government report

1992

6.0

NA

Solomon Islands

Western Pacific region data bank

1994

10.0

5.3

Sri Lanka

Community-based data

1993

18.7

12.7

Sudan

Estimate

1990

12.5

7.4

Suriname

Monitoring system

1987

13.0

7.8

Swaziland

Hospital data

1990

8.0

3.6

Sweden

Registration data

1985

4.2

NA

Switzerland

Registration data

1992-93

5.4

NA

Syrian Arab Republic

Unknown source

1990

11.0

6.1

Tajikistan

Registration data

1992

6.5

2.3

Thailand

Monitoring system

1987

7.7

3.3

Togo

Field estimate

1988

20.0

13.8

Trinidad and Tobago

Monitoring system

1987

13.0

7.8

Tunisia

Unknown source

1989

9.2

4.6

Turkey

Field estimate

1988

7.0

2.7

U. Rep. Tanzania

Community-based data

1992

16.9

11.2

U. Arab Emirates

Hospital data

1992

6.0

1.9

Ukraine

Monitoring system

1987

5.1

NA

United Kingdom

Monitoring system

1985

6.5

NA

United States

Registration data

1992

7.1

NA

Uruguay

Registration data

1992-93

7.6

3.2

Vanuatu

Western Pacific region data bank

1994

7.4

3.1

Venezuela

Monitoring system

1987

9.8

5.1

Viet Nam

Western Pacific region data bank

1994

10.8

6.0

Western Samoa

Western Pacific region data bank

1991

4.0

0.2

Yugoslavia

Monitoring system

1985

6.4

NA

Zaire

Government report

1990-93

25.0

18.1

Zimbabwe

Registration data

1989

5.6

1.5

¹ Derived using regression model Y= - 3.2452+0.852 X [see figure 1].
Data source: WHO Database on Low Birth Weight (update September 1996) (WHO, 1992).
NA = not applicable (developed country)