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Supplement

Introduction¹

Center for Human Nutrition and Department of International Health, Johns Hopkins School of Public Health, Baltimore, MD 21205

²To whom correspondence and reprint requests should be addressed at Johns Hopkins School of Public Health, Center for Human Nutrition and Department of International Health, 615 North Wolfe Street, Baltimore, MD 21205. E-mail: caballero{at}jhu.edu.

	ABSTRACT

TOP ABSTRACT INTRODUCTION Assessing obesity in populations... Obesity trends in the... BIOLOGICAL FACTORS ECOLOGICAL FACTORS REFERENCES

 
Over the past decade there has been an increasing concern about the impact of chronic, noncommunicable diseases on the health of developing world populations. Traditionally, major causes of illness and death in developing countries have been linked to infectious diseases and undernutrition, and these are still major public health problems in several regions of the world. But recent projections indicate that in 20 y noncommunicable diseases will account for over 60% of the disease burden and mortality in the developing world. Obesity is recognized as an underlying risk factor for many of these chronic conditions. As in developed societies, the risk for obesity in developing countries is also strongly influenced by diet and lifestyle, which are changing dramatically as a result of the economic and nutrition transition. This symposium discusses key aspects of the phenomenon of obesity in the developing world and provides some specific examples from countries facing increasing prevalence of that condition.

KEY WORDS: • obesity • developing countries • nutrition transition • international nutrition

	INTRODUCTION

TOP ABSTRACT INTRODUCTION Assessing obesity in populations... Obesity trends in the... BIOLOGICAL FACTORS ECOLOGICAL FACTORS REFERENCES

 
Although obesity prevalence in less-developed countries (LDC) have not reached the level of many developed countries (DC), there is no question, as the data presented here shows, that there is an alarming upward trend in obesity rates in many LDC. This concern is amplified by the overall rise in noncommunicable diseases in the developing world: it is predicted that by the year 2020 over 60% of the disease burden and mortality in LDC will result from noncommunicable diseases (Murray and Lopez 1996 ). Because several of these chronic conditions are associated with excess body weight, it seems clear that preventing obesity would be a very effective way of reversing that trend.

It is logical to link the increasing obesity rates in developing countries with a progressive introduction of factors associated with obesity in developed societies, such as sedentary lifestyle, high fat and fast foods. But it is also recognized that there are several unique elements to the nutritional conditions of LDC. First, chronic malnutrition is common in LDC, leading to lifetime stunting in significant segments of the population. There is increasing evidence that malnutrition early in life is one additional risk factor for obesity and other chronic diseases in the adult (Barker 1992 , Law et al. 1992 , Phillips et al. 1994 ). In addition, the fact that a large percentage of the population may be of low stature resulting from chronic malnutrition requires careful interpretation of weight–height relationships used for the diagnosis of obesity, particularly in children. Second, contrary to DC, food choices in LDC may remain limited, because of either market limitations or cost (Aguirre 1994 ). Third, low income and limited access to education may pose constraints on people’s ability to seek and secure healthier foods and lifestyle. These biological and environmental factors are summarized in Table 1 .

	Assessing obesity in populations with high prevalence of undernutrition

TOP ABSTRACT INTRODUCTION Assessing obesity in populations... Obesity trends in the... BIOLOGICAL FACTORS ECOLOGICAL FACTORS REFERENCES

Whereas the BMI in children (ages 2–19 in the United States) is based on patterns of normal growth, the acceptable BMI range in the adult is based on mortality and morbidity risks. There is increasing recognition that the BMI–risk correlation, based on U.S. data, may be quite different in different populations in the developing world. First, ethnic factors may result in a different body adiposity distribution, which is itself a major determinant of risk associated with excess body fat (McKeigue et al. 1991 ). Second, since short stature is an independent risk factor for a number of diseases, this element must be considered along with BMI in assessing disease risk in developing country populations.

	Obesity trends in the developing world

TOP ABSTRACT INTRODUCTION Assessing obesity in populations... Obesity trends in the... BIOLOGICAL FACTORS ECOLOGICAL FACTORS REFERENCES

 
Although obesity prevalence figures were previously reported from many LDC (Gurney and Gorstein 1988 , Popkin and Doak 1998 , Martorell et al. 1998 ), the number of nationally representative, reliable longitudinal surveys is still limited. Many of the estimates of obesity prevalence are based on surveys covering only urban areas, or relatively small population samples. Several of the available nationally representative surveys will be discussed in this symposium. A 1988 report from cross-sectional data from 34 countries listed seven countries with > 5% of children 0–5 y of age with weight-for-height above 2 SD (Gurney and Gorstein 1988 ). Of these, six were LDC. In a more recent analysis of Latin American cross-sectional data, Martorell et al. (1998 ) reported percentages of women with BMI of 30 to 39.9, ranging from 2.6 in Haiti to 11.3 in the Dominican Republic. Although these figures are quite below the U.S. prevalence rates, the data also show that a substantial number of Latin American women have BMI between 25 and 30, from 8.9% in Haiti to 35.5% in Peru, with several countries matching or exceeding the U.S. prevalence of 26.5% of women in that BMI range. In another report, Popkin and Doak (1998 ) used data from eight mid- and low income countries that had more than one survey to estimate trends, reporting increases of 2.3 to 19.6% in obesity prevalence over a 10-y period.

Because of the limited availability of longitudinal data, Pelletier and Rahn (1998 ) estimated obesity trends by applying a regression model to cross-sectional data from over 200 cross-sectional studies. A summary of these results is presented in Figure 1 . Although a general trend toward higher BMIs can be observed, the characteristics and implications of those changes may be quite different. For example, in countries like China, gains in BMI move the population away from borderline undernutrition and well into the normal BMI range. In contrast, BMI gains in other countries put some segment of the population, usually the high socioeconomic status group, at risk of obesity.

View larger version (13K): [in this window] [in a new window]   Figure 1. Trends in BMI in the developing world, 1960–1990. Arrows depict changes in BMI in that period for lower (solid arrows) and higher (dotted arrows) quartiles of socioeconomic levels. [Data estimated from cross-sectional surveys using a multiple regression model, by Pelletier and Rahn (1998 ).]

	BIOLOGICAL FACTORS

TOP ABSTRACT INTRODUCTION Assessing obesity in populations... Obesity trends in the... BIOLOGICAL FACTORS ECOLOGICAL FACTORS REFERENCES

Undernutrition in early life was previously proposed as a significant risk factor for several adult chronic diseases, some of them linked to obesity (Barker 1992 , Law et al. 1992 , Phillips et al. 1994 ). The review by Martorell et al. in this symposium discusses this issue, pointing to different results from a number of studies exploring this association. The main descriptive studies supporting a positive correlation between fetal malnutrition and risk of adult diseases such as diabetes, cardiovascular and pulmonary diseases emerged from data in the United Kingdom (Barker 1992 ) and from a study of records of the Dutch famine during WWII (Susser and Stein 1994 ). The impact of postnatal growth retardation on obesity risk in the adult is less clear, and is further discussed in this symposium. Postnatal growth retardation, however, may also be associated with risk of other chronic conditions. In a recent report on a 7-y follow-up of children who were stunted during the first 2 y of life, Gaskin et al. (2000 ) found that children who were stunted at young age had significantly higher systolic blood pressure at age 7–8 y; however, they found no effect of birth weight.

Proponents of the link between early malnutrition and later obesity suggest that energy deficiency triggers a series of metabolic and hormonal changes that put the individual at higher risk of excess body fat accumulation. Some of the endocrine changes associated with protein-energy malnutrition, such as decreased plasma IGF-1 levels, increased plasma cortisol and a relative reduction in plasma insulin concentrations (Torun and Chew 1999 ) are consistent with an inhibitory effect on lipolysis. When more calories become available, particularly from fat, these hormonal changes may impair the individual’s ability to respond by increasing fat oxidation. A recent study from Sao Paulo appears to support this possibility, reporting a significant reduction in fat oxidation (estimated by indirect calorimetry) in stunted vs. nonstunted children (Hoffman et al. 2000 ).

Assessing the association between stunting and later obesity is complicated by the differential responses of weight and height gain to increased caloric intake, as discussed above. Early stunting would facilitate attaining a higher BMI, if recovery in weight with little or no recovery in height occurs later in childhood. This effect could be potentiated by a diet limited in micronutrients shown to affect linear growth, such as zinc (Golden and Golden 1981 ).

Genetic factors

For centuries, human survival depended on body fat accumulation and maximizing energy utilization. Thus, genes favoring minimum energy expenditure, maximum storage of energy in adipose tissue, were preferentially activated. In modern society, when the supply of energy is constant throughout the year and the energy demand of daily work has greatly decreased, that adaptation has become a severe handicap. This is the basis of the "thrifty gene" hypothesis, invoked to explain the remarkable susceptibility to obesity of American Indians (Byers 1992 ). A similar mismatch between atavistic metabolism and modern lifestyle may conceivably play a role in the emergence of obesity in LDC. Genetic polymorphism also determines individual responses to environmental challenges in terms of dietary intake, nutrient levels and energy balance, and there is much to be explored in this area in LDC populations. Similarly, familial clustering of energy expenditure was previously documented among high obesity populations, showing that families whose members tend to have lower resting energy expenditure are at increased risk of excess weight gain in subsequent years (Ravussin et al. 1988 ).

	ECOLOGICAL FACTORS

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Urbanization

Demographic projections for the next 30 y coincide in placing the burden of population growth primarily on the developing world, and most of this growth will be in urban areas. According to United Nations’ estimates, in the next 25 y the rural population in the developing world is expected to increase by 6%, while the urban population will grow by 87% (UN Population Division 1988 ). Several studies have pointed out the positive correlation between urbanization and population BMI and have showed that, as urbanization advances, the BMI distribution curve of the population shifts to the right (INCLEN 1996). Studies comparing growth of children from rural and urban areas also described higher weight-for-age and height-for-age in urban children. Table 2 presents data from Venezuela, comparing weight–age of children from urban and rural areas (Lopez-Blanco et al. 1992 ). It is of note that urban dwelling seems to improve growth patterns, reducing the percentage of children with low weight-for-age. However, urban residence is also associated with a marked increase in the percentage of children with weight-for-age above the 95th percentile. The mechanisms of these changes are not well documented, but it can be suggested that urban children appear to achieve a more positive energy balance than rural children, allowing them to grow at a better rate. One can speculate that this may result from a combination of increased energy intake, decreased energy expenditure and, perhaps, reduced gastrointestinal nutrient losses.

The lack of adequate longitudinal data on patterns of physical activity in the developing world precludes an estimation of trends. Indirect evidence, however, supports the notion of a reduction in daily energy expenditure associated with urban living. Many typical rural survival tasks requiring high energy output, such as hauling wood for cooking and heating over long distances or steep terrain, are reduced or eliminated in the urban setting (Torun 2000 ). Studies in rural Guatemala measuring energy expenditures of agricultural workers reported figures of 2700–3700 kcal/d, (equivalent to 1.8 to 2.35 x BMR), which can be considered from moderately heavy to very heavy (Viteri and Torun 1975 ). In contrast, the predominance of service-type jobs in urban areas may result in lower labor energy demands. The increasing role of service work in LDC was pointed out by Popkin et al. (1999 ). Using a time-series regression model to analyze employment data, they reported that urbanization is associated with an increasing shift of the labor force toward service-type jobs, with a concomitant reduction in agriculture-type jobs. From these results, it can be inferred that work energy expenditure would tend to be lower in the urban than in the rural environment.

Besides labor energy demands, there is also some evidence that a sedentary lifestyle is common among low income urban dwellers. Over 10 y ago, a PAHO report in six Latin American cities (Pan American Health Organization 1986 ) found sedentary lifestyle in 40–70% of men and 65–82% of women. More recently, a survey in Panama City found that 50% of men and 75% of women engaged in little or no regular exercise (Torun 2000 ).

Food availability and dietary intake

The traditional association between per capita income and dietary patterns, described in a global WHO report over 30 y ago, was one in which lower incomes were associated with lower fat, lower animal protein and higher complex carbohydrate intakes, whereas consumption of total and animal fat increased as income level went up (WHO 1990 ). Analyzing food balance data from LDC, Drewnowski and Popkin (1997 ) suggested that the classical correlation between income and dietary patterns has been drastically changed by the globalization of food production and marketing. Even lower income countries appear to consume a higher percentage of calories from fat, a fact attributed to the widespread availability and low cost of vegetable oils (Beare-Rogers et al. 1998 ). Whether an increased dietary energy density results in a higher caloric intake is still unclear, and some reports describe lower rather than higher total dietary energy intake in the urban setting (Alarcon and Adrino 1991 ).

In DC increasing numbers of dietary calories are consumed outside the home (Frazao 1999 ). Some of the apparent reasons for this trend, such as women working outside the home, and ease and lower cost of fast foods, may also apply to LDC in transition. This issue is important because fast foods and low cost restaurant foods tend to have a higher fat content than home-prepared foods (Frazao 1999 ).

The overall impact of these environmental changes on obesity risk has been documented in many situations and cultures. The evolution of obesity among American Indian communities is a case in point. For example, the prevalence of overweight (BMI > 85th percentile) in children 5–12 y of age in the White Mountain Apache reservation increased from 14% in 1974 to 48% in 1992. In that relatively short time span, major economic and social changes occurred in that community, with transition from physical to mechanized transportation, increasing proportion of service jobs and introduction of processed foods, supermarkets, television and other forms of sedentary leisure activities (Owen et al. 1981 , Nelson 1994 ). Exposure to a "Western-style" living environment has a similar effect, as documented in a comparison of Pima Indians living in rural Mexico with Pimas living near Phoenix, a large urban area in Arizona (Ravussin et al. 1994 ). Although from identical genetic pool, Pimas living in Arizona had an average BMI 10 points higher than that of their Mexican counterparts, who live in a more traditional, semirural environment.

There is no question that, for many LDC, gains in average population BMI are desirable and may reflect improved socioeconomic conditions. The economist Robert Fogel documented the centuries-long struggle of humankind to overcome undernutrition and attain a body size that increases productivity and protects from premature death (Fogel 1986 ). Using Whaaler surface plots to correlate stature, BMI and mortality risk, Fogel tracked the secular trends in body size in humans over the past several centuries. Figure 2 presents the evolution of body size in the French population since 1705 (Fogel 1997 ), showing that secular gains in BMI resulted from combined gains in weight and in height. In LDC, the nutrition transition is facilitating rapid gains in body weight in low income and undernourished populations. But unless there is a concurrent reduction in childhood stunting and an improvement in adult stature, normalizing BMIs will not confer the same reduction in mortality risk as that in DC populations. Continuing gains in BMI beyond the normal range will potentiate the risk associated with low stature. Thus, whereas in DC reducing the health risk associated with obesity demands a focus on controlling excess body weight, in LDC that task will also demand a major effort to combat chronic childhood malnutrition, to increase the stature of future generations of adults.

View larger version (32K): [in this window] [in a new window]   Figure 2. Waaler surface plot of weight and height relationships, using population data from Norway and France. Vertical lines connecting weight–height combinations yielding identical BMIs, between 16 and 31, are depicted. Three curves represent weight–height combinations with similar mortality risk are presented for 0.7, 1.0. and 1.3 relative risk. The evolution of body size in the French population from 1705 to 1975 is also shown. The solid arrow describes the hypothetical evolution of body size in developing countries, where low stature is common, and where gains in body weight may not be paralleled by gains in stature. As a result, mortality risk at a given BMI may be higher than that in taller populations from developed countries. [From R. Fogel (1997 ).]

	FOOTNOTES

 
¹ Presented as part of the symposium "Obesity in Developing Countries: Biological and Ecological Factors" given at the Experimental Biology 2000 meeting held in San Diego, CA on April 15–19, 2000. This symposium was sponsored by the American Society for Nutritional Sciences and was supported in part by an educational grant from Monsanto Company. Symposium proceedings are published as a supplement to The Journal of Nutrition. Guest editors for the symposium publication were Benjamin Caballero, Center for Human Nutrition, Johns Hopkins University, Baltimore, MD and Najat Mokhtar, Ibn Tofaïl University, Kenitra, Morocco.

	REFERENCES

TOP ABSTRACT INTRODUCTION Assessing obesity in populations... Obesity trends in the... BIOLOGICAL FACTORS ECOLOGICAL FACTORS REFERENCES

 

1. Aguirre P. How the very poor survive: the impact of hyper-inflationary crisis on low-income urban households in Buenos Aires/Argentina. GeoJournal 1994;34:295-304

2. Alarcon J. A., Adrino F. J. Diferencias urbano-rurales en la ingesta de alimentos de familias pobres de Guatemala. Arch. Latinoam. Nutr. 1991;51:327-335

3. Barker D.J.P. The effects of nutrition of the fetus and neonate on cardiovascular disease in later life. Proc. Nutr. Soc. 1992;51:135-144[Medline]

4. Beare-Rogers J., Ghafoorunissa Korver O., Rocquelin G., Sundram K., Uauy R. Dietary fat in developing countries. Food Nutr. Bull. 1998;19:251-267

5. Byers T. The epidemic of obesity in American Indians. Am. J. Dis. Child. 1992;146:285-286[Abstract/Free Full Text]

6. Drewnowski A., Popkin B. M. The nutrition transition: new trends in the global diet. Nutr. Rev. 1997;55:31-43[Medline]

7. Fogel R. W. Nutrition and the decline in mortality since 1700: some preliminary findings. Engerman S. L. Gallman R. E. eds. Long-Term Factors in American Economic Growth 1986:439-555 University of Chicago Press Chicago, IL.

8. Fogel R. W. The global struggle to escape from chronic malnutrition since 1700. Proceedings of the World Food Programme/United Nations University 1997 Rome, Italy

9. Frazao E. America’s Eating Habits: Changes & Consequences 1999;750 U.S. Department of Agriculture Washington, D.C.

10. Gaskin P. S., Walker S. P., Forrester T. E., Grantham-McGregor S. Early linear growth retardation and later blood pressure. Eur. J. Clin. Nutr. 2000;54:563-567[Medline]

11. Golden M., Golden B. Effect of zinc supplementation on the dietary intake, rate of weight gain, and energy cost of tissue deposition in children recovering from severe malnutrition. Am. J. Clin. Nutr. 1981;34:900-908[Abstract/Free Full Text]

12. Gurney M., Gorstein J. The global prevalence of obesity—an initial overview of available data. World Health Stat. Q. 1988;41:251-254[Medline]

13. Hoffman D. J., Sawaya A. L., Verreschi I., Tucker K. L., Roberts S. B. Why are nutritionally stunted children at increased risk of obesity? Studies of metabolic rate and fat oxidation in shantytown children from Sao Paulo, Brazil.. Am. J. Clin. Nutr. 2000;72:702-707[Abstract/Free Full Text]

14. International Clinical Epidemiology Network (INCLEN) Body mass index and cardiovascular disease risk factors in seven Asian and five Latin American centers: data from the International Clinical Epidemiology Network (INCLEN). Obes. Res. 1996;4:221-228[Medline]

15. Law C. M., Barker D.J.P., Osmond C., Fall C. H. Early growth and abdominal fatness in adult life. J. Epidemiol. Community Health 1992;46:184-186[Abstract/Free Full Text]

16. Lopez-Blanco M., Landaeta Jimenez M., Mendez Castellano H. Urban-rural differences in the growth status of Venezuelan children. Am. J. Hum. Biol. 1992;4:105-113

17. Martorell R., Kettel Khan L., Hughes M. L., Grummer-Strawn L. M. Obesity in Latin American women and children. J. Nutr. 1998;128:1464-1473[Abstract/Free Full Text]

18. McKeigue P. M., Shah B., Marmot M. G. Relation of central obesity and insulin resistance with high diabetes prevalence and cardiovascular risk in South Asians. Lancet 1991;337:382-386[Medline]

19. Murray C.J.L., Lopez A. D. The Global Burden of Disease 1996 Harvard University Press Cambridge, MA

20. Must A., Dallal G. E., Dietz W. H. Reference data for obesity: 85th and 95th percentiles of body mass index (wt/ht²) and triceps skinfold thickness. Am. J. Clin. Nutr. 1991;53:839-846[Abstract/Free Full Text]

21. Nelson D. M. Height and weight changes among White Mountain Apache children. The IHS Provider 1994;:50-55

22. Owen G. M., Garry P. J., Seymoure R. D., Harrison G. G., Acosta P. B. Nutrition studies with White Mountain Apache preschool children in 1976 and 1969. Am. J. Clin. Nutr. 1981;34:266-277[Abstract/Free Full Text]

23. Pan American Health Organization Health Conditions in the Americas 1986 Edition 1986 PAHO Washington, D.C.

24. Pelletier D. L., Rahn M. Trends in body mass index in developing countries. Food Nutr. Bull. 1998;19:223-239

25. Phillips D.I.W., Barker D.J.P., Hales C. N., Hirst S., Osmond C. Thinness at birth and insulin resistance in adult life. Diabetologia 1994;37:150-154[Medline]

26. Popkin B. M. Urbanization, lifestyle changes and the nutrition transition. World Dev 1999;27:1905-1916

27. Popkin B. M., Doak C. M. The obesity epidemic is a worldwide phenomenon. Nutr. Rev. 1998;56:106-114[Medline]

28. Ravussin E., Lillioja S., Knowler W. C., Christin L., Freymond D., Abbott W.G.H., Howard B. V., Bogardus C. Reduced rate of energy expenditure as a risk factor for body-weight gain. N. Engl. J. Med. 1988;318:467-472[Abstract]

29. Ravussin E., Valencia M. E., Esparza J., Bennett P. H., Schulz L. O. Effects of a traditional lifestyle on obesity in Pima Indians. Diabetes Care 1994;17:1067-1074[Abstract]

30. Susser M., Stein Z. Timing in prenatal nutrition: a reprise of the Dutch Famine Study. Nutr. Rev. 1994;52:84-94[Medline]

31. Torun B. Physical activity patterns in Central America. Peña M. Bacallao J. eds. Obesity and Poverty 2000:29-40 Pan American Health Organization Washington, D.C.

32. Torun B., Chew F. Protein-energy malnutrition. Shils M. E. Olson J. A. Shike M. Ross A. C. eds. Modern Nutrition in Health and Disease 1999:963-988 Williams & Wilkins Baltimore, MD.

33. UN Population Division World Urbanization Prospects. United Nations Report 4 1988 New York, NY

34. Viteri F., Torun B. Ingestión calórica y trabajo físico de obreros agrícolas de Guatemala. Bol. Oficina Sanit. Panam. 1975;78:58-74[Medline]

35. World Health Organization (WHO) Diet, Nutrition, and the Prevention of Chronic Diseases 1990 WHO Geneva, Switzerland.

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