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Diabetes Care 28:2480-2485, 2005
© 2005 by the American Diabetes Association, Inc.

Metabolic Syndrome/Insulin Resistance Syndrome/Pre-Diabetes
Original Article

The Prevalence of the Metabolic Syndrome Did Not Increase in Mexico City Between 1990–1992 and 1997–1999 Despite More Central Obesity

Carlos Lorenzo, MD1, Ken Williams, MS1, Clicerio Gonzalez-Villalpando, MD2 and Steven M. Haffner, MD1

1 Department of Clinical Epidemiology, University of Texas Heath Science Center, San Antonio, Texas
2 Centro de Estudios en Diabetes, Centro de Investigacion en Salud Poblacional, Instituto Nacional de la Salud Publica, Instituto Mexicano del Seguro Social, American British Cowdray Medical Center, Mexico City, Mexico

Address correspondencereprint requests to Carlos Lorenzo, MD, Department of Medicine, Division of Clinical Epidemiology, University of Texas Health Science Center at San Antonio, 7703 Floyd Curl Dr., San Antonio, TX 78284-7873. E-mail: lorenzo{at}uthscsa.edu


   ABSTRACT
TOP
 ABSTRACT
INTRODUCTION
 RESEARCH DESIGN AND METHODS
 RESULTS
 CONCLUSIONS
 References
 
OBJECTIVE—Trends in the metabolic syndrome might follow trends in obesity. We examined this hypothesis in the Mexico City Diabetes Study (MCDS), a study that showed rising trends in obesity, and the effect of the metabolic syndrome on the risk of coronary heart disease (CHD).

RESEARCH DESIGN AND METHODS—Designed as a population-based study, the MCDS enrolled subjects in 1990–1992 (n = 2,282). Follow-up visits were held in 1993–1995 (n = 1,764) and 1997–1999 (n = 1,754). We used the revised metabolic syndrome definition of the National Cholesterol Education Program and the Framingham equations to estimate the 10-year CHD risk.

RESULTS—In men, the age-adjusted prevalence of the metabolic syndrome was 38.9% in 1990–1992, 43.4% in 1993–1995, and 39.9% in 1997–1999; in women, the prevalences were 65.4, 65.7, and 59.9%, respectively. The prevalence did not change in men (P = 0.349) between 1990–1992 and 1997–1999, but decreased in women (P < 0.001). A prevalence increase was demonstrated for elevated waist circumference (men, P < 0.001; women, P < 0.050), elevated fasting glucose value (men and women, P < 0.001), and low HDL cholesterol level (men, P < 0.050; women, P < 0.010); a prevalence decrease was seen for high blood pressure (men and women, P < 0.001) and hypertriglyceridemia (men, P < 0.001; women, P < 0.010). CHD risk decreased marginally in men (P < 0.050) but did not change in women (P = 0.943).

CONCLUSIONS—Neither the prevalence of the metabolic syndrome nor CHD risk has increased in Mexico City. Lower blood pressure and triglyceride values appear to have counteracted increases in central obesity and fasting glucose.

Abbreviations: CHD, coronary heart disease • MCDS, Mexico City Diabetes Study • NHANES, National Health and Nutrition Examination Survey


   INTRODUCTION
TOP
 ABSTRACT
 INTRODUCTION
RESEARCH DESIGN AND METHODS
 RESULTS
 CONCLUSIONS
 References
 
The prevalence of obesity and type 2 diabetes have reached epidemic proportions in developed and developing countries (1,2). Obesity, particularly abdominal obesity, is a central element of the metabolic syndrome (3–5) and a strong predictor of incident metabolic syndrome (3). Therefore, it has been hypothesized that the prevalence of the metabolic syndrome has increased (5,6). However, information regarding secular trends in the metabolic syndrome is largely unavailable (6).

We aim to test this hypothesis in the Mexico City Diabetes Study (MCDS), a population-based study that showed rising trends in obesity (7). We have examined also the relationship between prevalence trends of the metabolic syndrome and individual metabolic disorders and the effect of these trends on the estimates of coronary heart disease (CHD) risk (8).


   RESEARCH DESIGN AND METHODS
TOP
 ABSTRACT
 INTRODUCTION
 RESEARCH DESIGN AND METHODS
RESULTS
 CONCLUSIONS
 References
 
The MCDS is a population-based study of type 2 diabetes and cardiovascular disease. Detailed descriptions of this study have been already published (9). In brief, the MCDS enrolled men and nonpregnant women aged 35–64 years from six low-income neighborhoods (colonias) of Mexico City, each one corresponding to one census tract. A complete household enumeration was performed in each neighborhood between November 1989 and February 1990. A total of 3,326 study-eligible individuals consisting of men and nonpregnant women 35–64 years of age were identified. Of these, 2,813 (84.5%) subjects completed a home interview, and 2,282 (68.5%) completed a medical examination in a clinic between 1990 and 1992. Subjects who attended the clinical examination were similar to those who attended only the home interview in terms of age, sex, and self-reported history of myocardial infarction, diabetes, and smoking. A total of 1,764 (77.6%) participants returned for a first follow-up examination between 1993 and 1995, and 1,754 (76.9%) returned for a second follow-up examination between 1997 and 1999.

Acquisition of data and definition of variables
Survey protocols at baseline and follow-up were identical for the measures examined in this report. Current cigarette smoking and pharmacological treatment for diabetes and hypertension were self-reported. Waist circumference was measured at the level of the umbilicus. Systolic (1st phase) and diastolic (5th phase) blood pressures were recorded to the nearest even digit with a random-zero sphygmomanometer (Hawksley-Gelman, Sussex, U.K.) and the participant in the sitting position. Systolic and diastolic blood pressures were reported as the mean of the second and third blood pressure readings. Blood specimens were obtained after a 12- to 14-h fast. A 75-g oral glucose load (Orangedex; Custom Laboratories, Baltimore, MD) was administered to determine 2-h plasma glucose. Plasma glucose, total and HDL cholesterol levels, and triglyceride levels were measured with an Abbott Bichromatic Analyzer (South Pasadena, CA) in the laboratory of the Division of Clinical Epidemiology in San Antonio. LDL cholesterol was calculated using the Friedewald formula in samples with triglyceride levels <4.5 mmol/l.

We applied the revised National Cholesterol Education Program definition of the metabolic syndrome. Therefore, an individual had the metabolic syndrome if he or she met at least three of the following criteria: elevated waist circumference (>102 cm in men or >88 cm in women), high triglyceride level (≥1.7 mmol/l), low HDL cholesterol level (<1.04 mmol/l in men or <1.29 mmol/l in women), high blood pressure (≥130/85 mmHg or treatment with antihypertensive medications), and elevated fasting glucose value (≥5.6 mmol/l or current treatment with antidiabetic medications) (10). Obesity was defined as BMI ≥30 kg/m2. We assessed diabetes status using the 1999 criteria of the World Health Organization (11) and applied the Framingham risk equations to estimate the 10-year CHD risk (8).

Statistical analysis
All analyses were performed with SAS statistical software (version 8.0; SAS Institute, Cary, NC). GENMOD, a procedure that fits generalized linear models, was used to compare means and prevalence rates with the logit link between periods of examination. GENMOD permitted us to account for the fact that follow-up data represented repeated measures of the same individuals. Age and age-squared were included as covariates to allow for a nonlinear association between age and each variable. All comparisons in Tables 1, 2, and 3 and Fig. 1 were carried out with these adjustments. Logit transformation of Framingham risk estimates was used to compare CHD risk. Logistic regression analysis was used to examine the metabolic syndrome and other baseline characteristics in subjects who returned for follow-up and in those who did not return. All probability values were two-sided.



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  		Figure 1— Prevalence of the metabolic disorders by age, sex, and period of examination. *Comparisons were adjusted for repeated measures of the same individuals and the tendency for subjects to change nonlinearly.

 

   RESULTS
TOP
 ABSTRACT
 INTRODUCTION
 RESEARCH DESIGN AND METHODS
 RESULTS
CONCLUSIONS
 References
 
Variables associated with the metabolic syndrome did not change in the same direction during follow-up (Table 1). Similarly, elevated waist circumference, low HDL cholesterol level, and high fasting glucose value became more prevalent, and hypertriglyceridemia and high blood pressure became less prevalent (Table 2). Additionally, the prevalence of elevated waist circumference increased more than that of obesity among men.


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  		Table 1— Age-adjusted values of variables associated with the metabolic syndrome by sex and period of examination

 

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  		Table 2— Age-adjusted prevalence of obesity and individual metabolic disorders by sex and period of examination

 
In men, the age-adjusted prevalence of the metabolic syndrome did not increase between 1990–1992 and 1997–1999 (P = 0.349); in women, the prevalence decreased (P < 0.001) (Fig. 1 and Table 3). Prevalence changes in the metabolic syndrome were directly related to weight gain (Fig. 2). The prevalence of the metabolic syndrome did not increase in participants who lost weight, even though the effect of age was not taken into account.


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  		Table 3— Selected risk factors, prevalence of the metabolic syndrome, and CHD risk over 10 years by sex and period of examination

 


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  		Figure 2— Change in the prevalence of the metabolic syndrome between 1990–1992 and 1997–1999 by tertiles of BMI change.

 
Total and LDL cholesterol levels, cigarette smoking, and type 2 diabetes were also examined to determine a 10-year probability of CHD using the Framingham risk equations (Table 3). Total cholesterol did not increase in either men or women, but LDL cholesterol increased in both. Smoking rate decreased in men, but diabetes prevalence increased. Neither smoking nor diabetes changed in women. CHD risk over 10 years decreased slightly in men and did not change in women.

Because of the MCDS design (three-point estimates of a single cohort), we were concerned about the possibility of baseline differences between participants who returned to follow-up and those who did not. After accounting for the effect of age, a return for the second follow-up visit was not associated with metabolic syndrome status at baseline (odds ratio in men 1.13 [95% CI 0.82–1.57]; odds ratio in women 0.94 [0.72–1.24]) or with any other baseline characteristic but high blood pressure (0.57, 0.43–0.77) and smoking (0.58, 0.41–0.84) in women. In addition, the age-adjusted prevalence of the metabolic syndrome did not change significantly after restricting the analysis to participants who attended all three examinations. In men, this prevalence was 40.2% (95% CI 36.3–44.3) in 1990–1992, 42.1% (38.2–46.2) in 1993–1995, and 39.6% (35.7–43.7) in 1997–1999. In women, respective prevalences were 66.0% (62.8–69.0), 65.9% (62.6–68.9), and 60.0% (56.5–63.3).


   CONCLUSIONS
TOP
 ABSTRACT
 INTRODUCTION
 RESEARCH DESIGN AND METHODS
 RESULTS
 CONCLUSIONS
References
 
Contrary to the hypothesis, the prevalence of the metabolic syndrome has not increased in Mexico City between 1990 and 1992 and 1997 and 1999, despite increases in the prevalence of elevated waist circumference, low HDL cholesterol level, and elevated fasting glucose value. Significant decreases in the prevalence of high blood pressure and hypertriglyceridemia have occurred during follow-up and may be the explanation for the observed failure of metabolic syndrome prevalence to increase. CHD risk has not changed either. Blood pressure, triglyceride levels, and improvements in smoking status may have counterbalanced worsening HDL and LDL cholesterol levels and increases in diabetes.

It has been suggested that the prevalence of the metabolic syndrome has increased in the U.S. population because of the increasing number of individuals with obesity and/or type 2 diabetes (5,6). However, studies on prevalence trends in the metabolic syndrome are unavailable, except for a recent report from the National Health and Nutrition Examination Survey (NHANES) (6). In this report, Ford et al. described increases in the prevalence of the metabolic syndrome among women and elevated waist circumference in men and women between 1988–1994 and 1999–2000. We have examined the presumed association between trends in obesity and the metabolic syndrome in MCDS, because this is a survey that showed rising trends in obesity (7). Contrary to our expectations, the prevalence of the metabolic syndrome has not increased in Mexico City between 1990–1992 and 1997–1999.

Why is the metabolic syndrome not more prevalent whereas elevated waist circumference is? We do not have a complete answer beyond two observations. First, hypertriglyceridemia and high blood pressure have decreased significantly. Second, low HDL cholesterol levels in men and women and elevated waist circumference in women cannot sustain large prevalence increases because they are already very prevalent at baseline.

The question can be simplified by looking at the opposite trends of low HDL cholesterol levels and hypertriglyceridemia. These disorders share common genetic and environmental determinants (12). Genetic determinants remain constant in MCDS, but central elements of the metabolic syndrome (obesity, physical activity, and diet) do not. Central obesity has increased during follow-up. However, changes in physical activity and diet are missing, because data are available only at baseline (18–19% of total calories from fat and 64–65% from carbohydrates) (13). Rivera et al. (14) presented data indicating that worsening obesity in the Mexican population between 1988 and 1999 is associated with greater inactivity and dietary changes (increase in fat and refined carbohydrate consumption and decrease in overall carbohydrate intake). Epidemiological data also indicate that an increase in fat intake promotes obesity (although it is a controversial subject) (15) and that high-carbohydrate diets induce hypertriglyceridemia (16). Therefore, we suggest that a decrease in the overall carbohydrate consumption could offset the deleterious effect of increases in central obesity, refined carbohydrate intake, and inactivity on the prevalence of hypertriglyceridemia.

The deleterious effect of these lifestyle changes may be responsible for the increase in LDL cholesterol level. Nevertheless, the total cholesterol level has not increased owing to the decreases in triglyceride and HDL cholesterol levels. Despite rising trends in LDL cholesterol levels, CHD risk has not gone up because of the opposite changes in other risk determinants, such as smoking and the metabolic syndrome. The metabolic syndrome is associated with greater risk for both cardiovascular disease and CHD (17,18), although some components carry a greater risk than others. High blood pressure, hypertriglyceridemia, and low HDL cholesterol levels confer a greater cardiovascular risk than the other two components (19). Consequently, CHD risk has not increased in Mexico City. Improvements in blood pressure and triglycerides in men and women and smoking in men may have counterbalanced worsening LDL and HDL cholesterol levels in men and women and type 2 diabetes in men.

The metabolic syndrome is also a good predictor of type 2 diabetes (20,21), but some components have a greater impact on diabetic risk than others. Those that confer the greatest risk, obesity and elevated fasting glucose value (22), have worsened in Mexico City. In addition, waist circumference, the best predictor among the obesity indexes (23,24), has increased more than BMI in men, a finding that has been previously described in men and women from NHANES (2). Therefore, diabetes risk could have worsened despite similar or even lower prevalence of the metabolic syndrome, an inference that is supported by increasing trends for type 2 diabetes in men.

Our study has limitations that derive from its design (three time point estimates of a single cohort). Follow-up data are repeated measures of the same individuals. The cross-sectional relationship between age and each variable may be nonlinear. Nevertheless, bias is unlikely, because those concerns are taken into account by our statistical methods. Another potential problem is the possibility that the cohort gets gradually enriched (or deprived) with participants who have the metabolic syndrome (or individual risk factors) at baseline. However, baseline characteristics of participants who return to follow-up are not different from those of participants who do not return except for high blood pressure and cigarette smoking in women. Moreover, limiting the analysis to participants who have returned to both follow-up visits generates similar results.

In summary, the prevalence of the metabolic syndrome has not increased in Mexico City between 1990–1992 and 1997–1999 despite more central obesity and worsening glucose status. Trends in the metabolic syndrome may have misleading implications for diabetes risk. Diabetes risk could have risen because obesity and glucose status carry a greater risk than the other components. Improvements in blood pressure, triglyceride levels, and smoking status have averted deleterious changes in LDL and HDL cholesterol levels and diabetes on CHD risk.


   Acknowledgments
 
This work was supported by the National Heart, Lung and Blood Institute (RO1HL24799 and R37HL36820) and by the Consejo Nacional de Ciencia y Tecnología (CONACYT) (2092/M9303, F677-M9407, and 3502-M9607).


   Footnotes
 
A table elsewhere in this issue shows conventional and Système International (SI) units and conversion factors for many substances.

Received for publication April 19, 2005. Accepted for publication June 22, 2005.


   References
TOP
 ABSTRACT
 INTRODUCTION
 RESEARCH DESIGN AND METHODS
 RESULTS
 CONCLUSIONS
 References
 

  1. Mokdad AH, Ford ES, Bowman BA, Dietz WH, Vinicor F, Bales VS, Marks JS: Prevalence of obesity, diabetes, and obesity-related health risk factors, 2001. JAMA289:76–79, 2003
  2. Ford ES, Mokdad AH, Giles WH: Trends in waist circumference among US adults. Obes Res 11:1223–1231, 2003[Medline]
  3. Palaniappan L, Carnethon MR, Wang Y, Hanley AJ, Fortmann SP, Haffner SM, Wagenknecht L: Predictors of the incident metabolic syndrome in adults: the Insulin Resistance Atherosclerosis Study. Diabetes Care27:788–793, 2004
  4. Maison P, Byrne CD, Hales CN, Day NE, Wareham NJ: Do different dimensions of the metabolic syndrome change together over time? Evidence supporting obesity as the central feature. Diabetes Care 24:1758–1763, 2001[Abstract/Free Full Text]
  5. Lorenzo C, Serrano-Rios M, Martinez-Larrad MT, Gabriel R, Williams K, Gomez-Gerique JA, Stern MP, Haffner SM: Central adiposity determines prevalence differences of the metabolic syndrome. Obes Res 11:1480–1487, 2003[Medline]
  6. Ford ES, Giles WH, Mokdad AH: Increasing prevalence of the metabolic syndrome among U.S. adults. Diabetes Care 27:2444–2449, 2004[Abstract/Free Full Text]
  7. Williams K, Stern MP, Gonzalez-Villalpando C: Secular trends in obesity in Mexico City and in San Antonio. Nutr Rev 62:S158–S162, 2004[Medline]
  8. Wilson PWF, D’Agostino RB, Levy D, Belanger AM, Silbershatz H, Kannel WB: Prediction of coronary heart disease risk using risk factor categories. Circulation 97:1837–1847, 1998[Medline]
  9. Burke JP, Williams K, Haffner SM, Villalpando CG, Stern MP: Elevated incidence of type 2 diabetes in San Antonio, Texas, compared with that of Mexico City, Mexico. Diabetes Care 24:1573–1578, 2001[Abstract/Free Full Text]
  10. Grundy SM, Brewer HB Jr, Cleeman JI, Smith SC Jr, Lenfant C: Definition of metabolic syndrome: report of the National Heart, Lung, and Blood Institute/American Heart Association conference on scientific issues related to definition. Circulation 109:433–438, 2004[Medline]
  11. World Health Organization Department of Noncommunicable Disease Surveillance: Definition, Diagnosis and Classification of Diabetes Mellitus and Its Complications: Report of a WHO Consultation. Geneva, World Health Org., 1999
  12. Mahaney MC, Blangero J, Comuzzie AG, VandeBerg JL, Stern SP, MacCluer JW: Plasma HDL cholesterol, triglycerides, and adiposity: a quantitative genetic test of the conjoint trait hypothesis in the San Antonio Family Heart Study. Circulation 92:3240–3248, 1995[Medline]
  13. Stern MP, Gonzalez C, Mitchell BD, Villalpando E, Haffner SM, Hazuda HP: Genetic and environmental determinants of type II diabetes in Mexico City and San Antonio. Diabetes 41:484–492, 1992[Abstract]
  14. Rivera JA, Barquera S, Campirano F, Campos I, Safdie M, Tovar V: Epidemiological and nutritional transition in Mexico: rapid increase of non-communicable chronic diseases and obesity. Public Health Nutr 5:113–122, 2002[Medline]
  15. Rissanen A, Hakala P, Lissner L, Mattlar CE, Koskenvuo M, Ronnemaa T: Acquired preference especially for dietary fat and obesity: a study of weight-discordant monozygotic twin pairs. Int J Obes Relat Metab Disord 26:973–977, 2002[Medline]
  16. Coulston AM, Liu GC, Reaven GM: Plasma glucose, insulin, and lipid responses to high-carbohydrate low-fat diets in normal humans. Metabolism 32:52–56, 1983[Medline]
  17. Isomaa B, Almgren P, Tuomi T, Forsen B, Lahti K, Nissen M, Taskinen MR, Groop L: Cardiovascular morbidity and mortality associated with the metabolic syndrome. Diabetes Care 24:683–689, 2001[Abstract/Free Full Text]
  18. Malik S, Wong ND, Franklin SS, Kamath TV, L’Italien GJ, Pio JR, Williams GR: Impact of the metabolic syndrome on mortality from coronary heart disease, cardiovascular disease, and all causes in United States adults. Circulation 110:1245–1250, 2004[Medline]
  19. McNeill AM, Rosamond WD, Girman CJ, Golden SH, Schmidt MI, East HE, Ballantyne CM, Heiss G: The metabolic syndrome and 11-year risk of incident cardiovascular disease in the atherosclerosis risk in communities study. Diabetes Care 28:385–390, 2005[Abstract/Free Full Text]
  20. Laaksonen DE, Lakka HM, Niskanen LK, Kaplan GA, Salonen JT, Lakka TA: Metabolic syndrome and development of diabetes mellitus: application and validation of recently suggested definitions of the metabolic syndrome in a prospective cohort study. Am J Epidemiol 156:1070–1077, 2002[Abstract/Free Full Text]
  21. Lorenzo C, Okoloise M, Williams K, Stern MP, Haffner SM: The metabolic syndrome as predictor of type 2 diabetes: the San Antonio Heart Study. Diabetes Care 26:3153–3159, 2003[Abstract/Free Full Text]
  22. Bonora E, Kiechl S, Willeit J, Oberhollenzer F, Egger G, Meigs JB, Bonadonna RC, Muggeo M: Population-based incidence rates and risk factors for type 2 diabetes in white individuals: the Bruneck study. Diabetes 53:1782–1789, 2004[Abstract/Free Full Text]
  23. Chan JM, Rimm EB, Colditz GA, Stampfer MJ, Willett WC: Obesity, fat distribution, and weight gain as risk factors for clinical diabetes in men. Diabetes Care 17:961–969, 1994[Abstract]
  24. Wei M, Gaskill SP, Haffner SM, Stern MP: Waist circumference as the best predictor of noninsulin dependent diabetes mellitus (NIDDM) compared to body mass index, waist/hip ratio and other anthropometric measurements in Mexican Americans—a 7-year prospective study. Obes Res 5:16–23, 1997[Medline]

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