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Trends in obesity, underweight, and wasting among women attending prenatal clinics in urban Tanzania, 1995–2004^1,2,3

¹ From the Departments of Nutrition (EV, PP, DJH, and WWF), Epidemiology (DS, DJH, and WWF), and Biostatistics (DS), Harvard School of Public Health, Boston, MA, and the Departments of Community Health (GM) and Microbiology and Immunology (WU), Muhimbili University College of Health Sciences, Dar es Salaam, Tanzania

² Supported by grants from the National Institutes of Health (NICHD R01 32257, R01 37701, R01 43688, R01 45134, NIAID U01AI048006).

³ Reprints not available. Address correspondence to E Villamor, Department of Nutrition, Harvard School of Public Health, 665 Huntington Avenue, Boston, MA 02115. E-mail: evillamo{at}hsph.harvard.edu.

	ABSTRACT

TOP ABSTRACT INTRODUCTION SUBJECTS AND METHODS RESULTS DISCUSSION REFERENCES

 
Background: Many developing countries are currently burdened by both undernutrition and increasing rates of overweight and obesity. Scarce data are available from population studies on the recent trends and current epidemiology of obesity in African settings.

Objectives: The objectives were to evaluate changes in the prevalence of obesity, underweight, and wasting in women of reproductive age from Dar es Salaam, Tanzania, during the past 10 y and to identify contemporary sociodemographic correlates of these indicators.

Design: We estimated the prevalence of obesity [body mass index (BMI; in kg/m²) 30], underweight (BMI < 18.5), and wasting (midupper arm circumference <22 cm) in 73 689 women aged 14–52 y who attended antenatal care clinics in the city of Dar es Salaam, Tanzania, between 1995 and 2004.

Results: The prevalence of obesity rose steadily and progressively from 3.6% in 1995 to 9.1% in 2004 [adjusted prevalence ratio (PR): 1.97; 95% CI: 1.66, 2.33; P for trend for year < 0.0001]. Underweight showed only a modest decline from 3.3% in 1995 to 2.6% in 2004 (adjusted PR: 0.91; 95% CI: 0.75, 1.10; P for trend for year = 0.003), whereas no change was observed in the prevalence of wasting. In the most recent years (2003 and 2004), obesity was positively associated with age, parity, and socioeconomic status and inversely with HIV infection. Underweight was inversely related to socioeconomic status and positively to HIV status.

Conclusion: The recent, rapid, and large increase in the prevalence of obesity in women represents a new competing public health priority in urban Tanzania, where underweight and wasting have not decreased substantially.

Key Words: Obesity • underweight • wasting • women • pregnancy • Africa • secular trends • nutrition transition

	INTRODUCTION

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Many developing countries are currently affected by high rates of overweight that in some cases surpass underweight as a public health nutrition problem. In the case of urban Africa, recent analyses of national data on body mass index (BMI; in kg/m²) from women showed that the prevalence of BMI 25 exceeded that of BMI < 18.5 in 17 of 19 countries (1). Whether a similar pattern exists with obesity is not known, although, until as recently as 2000, obesity was considered to be of less concern in sub-Saharan Africa than in other regions (2). The most recent population-based surveys in Africa were conducted in the early or mid-1990s, and it is uncertain whether the prevalence of obesity has remained low during the decade after that period. Documenting recent changes in the prevalence of obesity and underweight in countries undergoing the nutrition transition is of vital importance for planning public health nutrition policy.

Also for program planning purposes, it is relevant to identify the subgroups that are most affected by obesity and underweight. This "social mapping" (2) has been done in part through ecological analyses that relate macroeconomic indicators with epidemiologic figures from nationwide representative surveys (1–3). These analyses would be complemented by epidemiologic studies that examine the associations between sociodemographic indicators and obesity or underweight by using data collected at the individual level and by adjusting the comparisons for potential confounding effects. Such studies are lacking, particularly in African countries.

With the use of data collected routinely at antenatal clinics in the city of Dar es Salaam, Tanzania, we examined the trends in the prevalence of obesity, underweight, and wasting between 1995 and 2004. We also studied the associations between these outcomes and the sociodemographic characteristics of women during the most recent period of 2003–2004.

	SUBJECTS AND METHODS

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Study population
Between April 1995 and December 2004, 112 382 pregnant women who attended their first antenatal clinic visit in the 3 health districts of Dar es Salaam, Tanzania, were approached as part of a process to identify women who were eligible to participate in research studies or service activities related to prevention of vertical transmission of HIV and pregnancy outcomes. The first of these studies was conducted between 1995 and 1997. A break occurred in December 1997 when enrollment for this study was completed, until August 2000 when recruitment for new research or service activities resumed. Recruitment has not been interrupted since then and currently comprises 15 antenatal clinics, which capture most pregnancies seen at primary health care facilities in the city.

At all clinics, trained research nurses obtained consent to evaluate eligibility criteria and used a standardized questionnaire to register sociodemographic information about the women, including their age, marital status, level of education, occupation, number of people eating at home, amount of money spent on food at home every day, and date of the last menstrual period. The nurses also measured the women’s height, weight, and left midupper arm circumference (MUAC) by using calibrated instruments and standardized techniques (4). The date of the last menstrual period was used to estimate the week of gestation. Women were offered individual HIV pretest counseling and then voluntary HIV testing if they met basic eligibility criteria (aged 18 y, willingness to screen, and interest in the study or program). The presence of HIV antibodies in consenting women was determined by using the Enzygnost anti-HIV 1 + 2 Plus enzyme-linked immunosorbent assay (Behring, Marburg, Germany), and reactive samples were confirmed by using the Wellcozyme HIV-1 recombinant enzyme-linked immunosorbent assay (Murex, Dartford, England).

During the initial period of 1995–1997 and between August 2000 and May 2001 data were collected only in women who fulfilled the week of gestation criterion for enrollment into the studies and programs at the time, which was <28 wk. After May 2001, data were collected on women who came for prenatal care at any week of gestation, and a question about parity was introduced in the general questionnaire. Anthropometric data were not collected between September 2001 and January 2003. The study was approved by the institutional review boards of the Muhimbili University College of Health Sciences and the Harvard School of Public Health.

Statistical analyses
Of the 112 382 women who attended our program clinics between 1997 and 2004, anthropometric data were available for 73 708. Nineteen women with implausible age data were further excluded from analyses, for a final sample size of 73 689 women. Age, gestation week at first visit, parity, level of education, and HIV prevalence were comparable between the women who had and the women who did not have anthropometric data.

We compared the distributions of BMI and MUAC by year using the Kruskal-Wallis test and obtained adjusted differences from a multivariate linear regression model. A test for linear changes in the distribution of anthropometric characteristics over time was obtained by introducing year as a continuous variable into the model.

The primary outcomes of interest were defined dichotomously from the distributions of BMI and MUAC according to conventional criteria. Obesity and underweight were defined as BMI 30 and BMI < 18.5, respectively, following the recommended cutoffs of the World Health Organization (5). Wasting was defined as MUAC < 22 cm according to the value recommended in women for the screening of malnutrition (6). The main independent predictor was the year of each woman’s first visit to the antenatal clinic. Other predictors and potential confounders included age; week of gestation at first visit; level of education; whether the woman cohabited with a partner; whether she earned any income outside the home; the money spent on food per person per day at home, which was calculated by dividing the total amount of money spent on food by the number of people eating at home every day; height; and HIV status.

We tested linearity of changes in the prevalence of obesity, underweight, and wasting over the years by using the Cochran-Armitage test in univariate analysis and by introducing year as an ordinal continuous variable in multivariate-adjusted binomial regression models (7, 8). Adjusted prevalence ratios (PRs) and 95% CIs for each year were also estimated from binomial models by using 1995 as the reference. Because the prevalence of BMI-based indicators such as obesity and underweight could vary according to the week of gestation when the women attended prenatal care, we always included week of gestation as an adjustment variable in the models. In addition, we repeated the analyses in 9088 women who attended their first visit at or before week 14 of gestation; their weights and BMIs could be considered to be close to their prepregnant status.

We next examined whether changes over time in the prevalence of the nutritional indicators differed according to sociodemographic characteristics, including age, trimester of pregnancy at first visit, level of education, and HIV status. We stratified the prevalence of each endpoint by period (1995–1997, 2000–2001, and 2003–2004) and by levels of each potential sociodemographic modifier. The statistical significance of these potential interactions was assessed by using the likelihood ratio test to compare main effects binomial models against models with cross-product terms between period and each modifier.

Finally, to gain insight into the current epidemiology of obesity, underweight, and wasting in this population, we examined the associations between sociodemographic characteristics and each of these outcomes in the group of women who attended the antenatal clinics in the latest period of 2003–2004. The prevalence of each outcome was compared between levels of the predictors by using multivariate binomial regression.

	RESULTS

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On average, women attended their first visit at week 20 of gestation (median: 20, interquartile range: 16–22). The age range of the women was 14–52 y. Average ages (±SDs) were 23.4 ± 5.2, 23.2 ± 5.1, 23.3 ± 5.1, 24.5 ± 5.5, 24.4 ± 5.3, and 24.6 ± 5.4 y for the years 1995, 1996, 1997, 2000–2001, 2003, and 2004, respectively. Sixty-eight percent of the women had results on HIV testing, with an average prevalence of seropositivity of 11.4% during the 10-y period.

Average BMI increased monotonically with year between 1995 and 2004 (adjusted P for trend < 0.0001) (Table 1). After adjustment for the potential confounding effects of week of gestation at first prenatal visit, age, education, cohabitation with a partner, height, HIV status, and indicators of socioeconomic status (SES), BMI was significantly greater in 2004 than in 1995 by an average of 0.7. A similar increasing trend was observed for MUAC.

Table 2

Table 3

Figure 1

Figure 2

View larger version (31K): [in this window] [in a new window]   FIGURE 1. Trends in the prevalence of obesity [BMI (in kg/m2) 30] in pregnant women from Dar es Salaam, Tanzania, according to age. The increasing trend in the prevalence of obesity was not significantly modified by the women’s age in multivariate analyses.

View larger version (15K): [in this window] [in a new window]   FIGURE 2. Trends in the prevalence of underweight [BMI (in kg/m2) < 18.5] in pregnant women from Dar es Salaam, Tanzania, according to age and HIV status. After adjustment for the potential confounding effect of sociodemographic characteristics, the trend was modified by age (adjusted P for interaction = 0.05) and HIV status (adjusted P for interaction = 0.05). With respect to age, a significant decrease in the prevalence of underweight was apparent only in the 20–24 y (adjusted P for trend = 0.005) and 30–34 y (adjusted P for trend = 0.001) age groups. With respect to HIV status, a significant decrease in underweight was observed in HIV-negative women (adjusted P for trend < 0.0001), but not in those who were HIV positive (adjusted P for trend = 0.29).

Table 4

	DISCUSSION

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We described a large and rapid increase in the prevalence of obesity, from 3.6% to 9.1% during a 10-y period, in women attending antenatal clinics in an African urban setting. This increase does not appear to be matched by a substantial decrease in the prevalence of underweight or wasting; whereas obesity increased >2.5-fold, the decrease in underweight was <10%, and no significant change was observed in the prevalence of wasting. The study population can be considered to be representative of women in urban Tanzania, given the high coverage of antenatal care: 73% of births in urban settings receive medical prenatal care and, in the city of Dar es Salaam, the coverage is 88% (9).

The usefulness of BMI cutoffs as indicators of obesity and underweight may be limited during pregnancy because BMI strongly depends on the week of gestation. However, our main conclusions were not modified after we took this limitation into consideration by adjusting for week of gestation in multivariate models and by restricting the analyses to women who attended prenatal care at early stages of pregnancy. Furthermore, week of gestation did not appear to be a significant predictor of obesity, defined as BMI 30, in the women who attended prenatal care during the period 2003–2004. We deliberately did not include overweight (BMI 25) as a primary endpoint because this lower BMI cutoff was more likely to be influenced by week of gestation than the more extreme BMI 30 cutoff for obesity. For example, a woman of average height and prepregnant weight in this population (155 cm and 57 kg, respectively) with a prepregnant BMI of 23.7 who gains 6 kg during pregnancy would appear as overweight (BMI: 26.2) by the third trimester even when she is not by her week of gestation. Still, when we restricted the analyses to women in early pregnancy, the prevalence of overweight also showed a progressive increase over time.

It is possible that some women may have registered at the program clinics for >1 pregnancy during the 10 y considered and may have been assigned a new unique identifier every time. Given that BMI is positively associated with age and parity, the potential inclusion of women more than once during the period could have spuriously increased the prevalence of obesity. One way to rule out this potential limitation as an important source of bias for our main finding is to examine the changes in the prevalence of obesity in women who belong to birth cohorts that were mutually exclusive at each time period. When we stratified the trends in nutritional indicators by age groups (Figure 1), we found that the increase in obesity between 1995–1997 and 2003–2004 was comparable within 5-y age groups; that is, women who were aged 20–24 y in 2003–2004 had a significantly higher prevalence of obesity than did women who were aged 20–24 in 1995–1997. These women could not have been the same women. This indicates that the potential of including several pregnancies of the same woman in the analyses was not a likely explanation for the observed increase in the prevalence of obesity.

Although trends in the prevalence of obesity are not available from previous population-based studies in this region, data reported from separate cross-sectional surveys appear to support the notion of a recent increase in obesity. In women aged 35–64 y from the cities of Morogoro and Kilimanjaro who participated in the World Health Organization Inter-Health Programme between 1987 and 1989, the prevalence of BMI 30 was 3.6% (10). Later, the Tanzania Demographic and Health Surveys conducted in 1991–1992 and 1996 reported prevalence rates of 4.1% and 6.0%, respectively, for women aged 15–49 y who lived in urban areas (2); by 1999, a survey of 5654 women aged 25–64 y from the city of Dar es Salaam showed a prevalence of 10.0% (11).

The 2.5-fold increase in the prevalence of obesity over one decade in pregnant women from urban Tanzania is comparable to the 2.6-fold increase found between 1988 and 1999 in Mexican women aged 18–49 y (12) and somewhat higher than the increases reported in some developing and developed countries: a 1.2-fold increase in adult Brazilian women from 1989 to 1997 (13), a 2-fold increase in pregnant British women from 1990 to 2002–2004 (14), and a 1.4-fold increase between 1992 and 2001 in the prevalence of overweight and obesity (BMI 25) in Swedish pregnant women (15). The reasons for the rapid increase in the prevalence of obesity in Tanzania are not clear but could be related to recent social and economic changes that result in modifications to patterns of dietary intake and physical activity. Since the mid-1990s, free market policies have favored the irruption of transnational fast-food chains and supermarkets that distribute and commercialize nontraditional foodstuffs (16). Rapid urbanization in Tanzania, from 21.7% in 1990 to 35.4% in 2003 (17), may also be a contributing factor to the increase in the prevalence of obesity. Urban immigrants are often forced to replace traditional foods such as millet with refined rice and maize products and cheap snacks that include doughnuts, cakes, and sugary soft drinks. In black populations of urban South Africa, an average 60% increase in the consumption of fat as percentage of total caloric intake has occurred between the 1950s and the 1990s; this was accompanied by large decreases in fiber intake (18). Although the consumption of sugar, saturated fat, and salt increased, the patterns of physical activity changed from intense work in agricultural fields to more sedentary occupations. Physical inactivity was identified as a strong risk factor for obesity in a survey of black communities from South Africa (19).

Despite the overall increase in the rates of obesity during the past 10 y in urban Tanzania, it is important to note that, from our analyses of the latest 2 y, obesity appears to be a particularly serious problem in women of the higher socioeconomic strata, because it was positively related to the level of education, the amount of money spent on food, and the possibility of earning extra income outside the household. Considering that Tanzania is among the poorest countries in the world, this pattern is consistent with the results from recent across-country analyses that document how low SES is "protective" against obesity in low-income countries, whereas it is a risk factor in upper-middle income developing countries (3). It is also consistent with increases in the prevalence of other related chronic conditions, particularly diabetes and hypertension, which have occurred preferentially in the affluent groups of the urban Tanzanian society: executives, politicians, priests, and persons of Asian descent (20). People from these groups are more likely to have the resources to purchase newly available processed foods and to lead a sedentary lifestyle. Studies are needed in this setting to examine patterns of dietary intake and physical activity that are potential causes of the observed increase in the prevalence of obesity as a first step to identify mitigating interventions.

Our data do not indicate that obesity is necessarily replacing underweight or wasting as a public health problem in this setting. The prevalence of underweight changed little during the 10-y period considered, and that of wasting was unchanged. As opposed to obesity, the prevalence of underweight depended on the week of gestation at first visit and our best estimate for the nonpregnant status, that is, in women at the earliest stage of gestation (<9 wk), suggests that it remains high at 8%. This figure is comparable with the 7% reported for women of Dar es Salaam aged 15–49 y in the Tanzania Demographic and Health Surveys of 1996 (9). Our examination of the correlates of underweight and wasting during the latest period suggests that low SES, as measured by limited income and lack of food-purchasing power, continues to be a strong determinant of protein-energy malnutrition in women from this setting. HIV status is also a significant contributor to the prevalence of wasting, despite a substantial decline in the prevalence of HIV infection in pregnant women in Dar es Salaam, from 14.2% in 1995 to 10.6% in 2003 (21). The adjusted 40% excess prevalence of wasting attributable to HIV in 2003–2004 is slightly higher than the 34% we reported previously for the same population during the period 1995–1997 (22). In addition, in the subset of HIV-infected women, the prevalence of underweight appeared to increase slightly from 1995 to 2004. These findings suggest that wasting is becoming more frequent or more severe as a clinical feature of HIV infection in this population. These women were naive to antiretroviral agents, because the diagnosis of HIV infection was made at the same time the anthropometric measures were obtained. Improvement of socioeconomic conditions and scaling-up of antiretroviral treatment and inexpensive interventions such as multivitamin supplementation (23) could reduce the burden of wasting during pregnancy in HIV-infected women.

In conclusion, although the prevalence of obesity in pregnant women from urban Tanzania doubled during the past 10 y, only modest changes occurred in the prevalence of underweight. Although obesity affected mostly the highest socioeconomic strata, we observed increasing trends over time in all groups. A decrease in the prevalence of HIV infection was not accompanied by reduced rates of wasting. Future studies need to examine the implications of the fast increase in obesity on the incidence of diabetes, hypertension, cardiovascular disease, cancer, and other noncommunicable diseases in this population. Increasing knowledge on the specific causes of obesity in this population, through research on patterns of dietary intake and physical activity, should provide clearer directions for the implementation of culturally tailored public health interventions. It is critical to promote and strengthen surveillance mechanisms to follow trends in the nutritional status of populations in sub-Saharan Africa.

	ACKNOWLEDGMENTS

 
We thank the women who made the study possible through their participation. We thank the clinic coordinators, research assistants, laboratory technicians, nurses, midwives, and administrative staff in the field.

EV carried out data analyses, interpreted the results, and wrote the initial draft of the manuscript. GM, WU, and PP participated in study implementation and supervision in the field. EV, DJH, DS, and WWF contributed to the study design. All authors participated in data interpretation and writing of the final draft. None of the authors had a conflict of interest in relation to this manuscript.

	REFERENCES

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