1 Department of Family Medicine and Clinical Epidemiology, School of Medicine, University of Pittsburgh, Pittsburgh, PA.
2 Department of Medicine, University of Vermont, Burlington, VT.
3 Department of Cardiology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH.
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ABSTRACT |
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basal metabolism; contraceptive agents, female; energy metabolism; ethnic groups; menstrual cycle; obesity; smoking; women
Abbreviations: DXA, dual-energy x-ray absorptiometry; NGHS, National Heart, Lung, and Blood Institute Growth and Health Study; REE, resting energy expenditure; SE, standard error
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INTRODUCTION |
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Studies of REE in children have yielded conflicting results, although the majority of published reports do not show significant racial differences in very young children (1319
). Available data suggest that racial differences in REE may evolve sometime during the transition from childhood to adulthood, which is also when racial differences in adiposity and obesity first become manifest (20
). At present, no known information is available on racial differences in REE in young women during this potentially critical time, when the racial disparity in obesity development takes place.
A variety of biologic and environmental factors, such as menstrual cycle, cigarette smoking, and use of contraceptive agents, are presumed to affect REE (2130
). Data on the impact of menstrual cycles on REE conflict with some studies showing a difference of as much as 10 percent between follicular and luteal phases (21
25
), while other studies have failed to show differences in REE between menstrual phases (8
, 26
). Although several studies indicate that cigarette smoking increases REE, its metabolic effects generally are assumed to be acute and transient (27
29
). In addition, estimates of its effect are not consistent (28
). Use of contraceptive medications is also purported to be associated with elevated REE levels, but three studies that examined this association (8
, 24
, 30
) reported no significant relation between use of contraceptive agents and REE.
The purpose of this 19961997 study in Cincinnati, Ohio, was to assess racial differences in REE in a biracial cohort of free-living, healthy adolescent women. It also examined the effects of cigarette smoking, use of contraceptive medications, and menstrual cycles on REE.
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MATERIALS AND METHODS |
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Since the initial NGHS recruitment was school-based, participants were recruited during the fall and spring semesters of the school calendar year to accommodate potential seasonal variation. Race-specific random lists of women from the NGHS roster of names available in the fall and spring time frames were generated for this REE study. Almost equal numbers of women by race were recruited from the spring (28 Black and 27 White) and fall (49 Black and 48 White) sampling frames. Eligibility criteria included availability of a complete 3-day food record and physical activity diary at year 8 of the NGHS (when the women were aged 1617 years) and not permanently living out of town even though they might be attending college outside of Cincinnati. Exclusion criteria included absence of weight gain or loss during the prior month, any change in lifestyle during the past 2 weeks, a chronic illness, and childbirth within the past 4 months. There were no racial differences in the proportion of ineligible womenthose who refused or could not be contacted. Written informed consent was obtained from each participant, and the study was approved by the respective institutional review boards at Cincinnati Children's Hospital Medical Center, the University of Vermont (Burlington, Vermont), and the University of Pittsburgh (Pittsburgh, Pennsylvania).
Of the 152 women recruited, 5 were excluded from data analysis because they currently used medications that could affect heart rate or energy metabolism. The final sample size for this study was 147 women (76 Black and 71 White). There were no dropouts between the two overnight hospital admissions.
Measurement of REE
REE was measured under controlled conditions by using indirect calorimetry with the DeltaTrac Metabolic Monitor II (Sensormetics, Yorba Linda, California). All study subjects were admitted for an overnight stay at the Clinical Research Center of the Cincinnati Children's Hospital. Subjects were served dinner from the regular hospital menu and underwent a mock REE test to become accustomed to the procedure. They were also instructed to refrain from smoking cigarettes for at least 12 hours before the test. After an overnight fast, with the room temperature set at approximately 71°F (21.7°C), subjects were measured in a supine position in bed between 6 a.m. and 7 a.m. while they were still drowsy. A plastic hood that permitted a flow of ambient air equal to five times the subject's normal ventilatory rate was placed over the subject's head. After 15 minutes of adaptation, data were collected for 45 minutes. Energy expenditure was calculated by using the Weir equation (32). A second measurement was performed approximately 11 days later, following the same protocol as the one for the first measurement. Analysis of test-retest conditions yielded a coefficient of variation of 5 percent.
Clinical measurements
At each Clinical Research Center admission, subjects were administered a questionnaire to collect information on their current menstrual status, recent changes in body weight, changes in diet and physical activity, medication use including contraceptive agents, and smoking history. Current smoking status was ascertained by a yes or no response. At the time of the first REE determination, body composition was assessed with a Hologic (Hologic, Inc., Bedford, Massachusetts) QDR-1000/w dual-energy x-ray absorptiometer (DXA) by using total body software in the pencil beam mode. Estimates of fat mass, total fat-free mass (tissue fat-free mass + bone mineral content), tissue fat-free mass, percentage of body fat, and bone mineral content were derived from the DXA measures.
Statistical analysis
The Wilk-Shapiro test was used to judge whether the sampling distribution of the dependent and independent variables approximated a normal distribution (33). Descriptive summary statistics were then generated by using the appropriate test statistic (independent t tests,
2 tests, or median tests for two samples) for racial comparisons. Because of the known higher bone mass in African Americans (34
37
), REE was adjusted for total fat-free mass (which included both tissue fat-free mass and bone mineral content) and fat mass by using the DXA two-compartment model as well as the three-compartment model approach (tissue fat-free mass, fat mass, and bone mineral content).
Generalized estimating equations were used to examine whether differing menstrual cycle phase (luteal vs. follicular) had an impact on the two nonindependent measures of REE (38). The percentage difference in REE levels between the two measurements was 0.4 percent for Black subjects and 2.3 percent for White subjects, well below the intraindividual (test-retest) coefficient of variation of 5 percent for this machine. Because there was no statistically significant difference in REE levels by menstrual phase, the average of two REE readings was used for data analysis.
Multiple linear regression analysis was used to examine potential predictors of REE. The effects of smoking and contraceptive medication use were initially examined separately in the model, which also included race, total fat-free mass, and fat mass. Whenever the term for race was found to be statistically significant, interactions between race and the selected predictors (e.g., race and total fat-free mass, race and fat mass, race and smoking, race and use of contraceptive agents) were also examined. If a race interaction with any of the predictor variables was statistically significant, race-specific models were generated.
Multiple linear regression analysis was also used to examine the relation between adiposity and REE. For this analysis, fat mass was the outcome variable and REE, race, total fat-free mass, cigarette smoking, and use of contraceptive medications were independent variables. The race interaction with REE on fat mass and with the other predictor variables on fat mass was also examined, and, when appropriate, race-specific models were generated. A dependent t test was used to compare the ß coefficients between fat mass and total fat-free mass. Distributional assumptions were rechecked by analyzing the distribution of the residuals from the final model analysis (39). Descriptive statistics and linear regression models were generated by using SAS version 6.12 software (40).
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RESULTS |
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No significant racial difference was found in the unadjusted REE values (figure 1). However, when REE was adjusted for total fat-free mass and fat mass, REE values for Black women were significantly (p < 0.001) lower by 77.5 kcal/day (324 kJ/day) than those for White women (figure 1). The mean (standard error (SE)) REE for Black women, adjusted for body composition, was 1,420 (SE, 16) kcal/day (5,944 (SE, 67) kJ/day) and 1,497 (SE, 17) kcal/day (6,266 (SE, 71) kJ/day) for White women. When REE was adjusted for bone mineral content in addition to tissue fat-free mass and fat mass, REE values were significantly (p = 0.007) lower by 68.6 kcal/day (287 kJ/day) for Blacks than for Whites. However, there was no significant independent effect of bone mineral content on REE (p = 0.54).
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The effect of race interaction on REE was also examined, with total fat-free mass, fat mass, smoking, and contraceptive use as predictor variables. None of the race interaction terms was found to be significant: p = 0.74 for total fat-free mass, p = 0.74 for fat mass, p = 0.84 for smoking, and p = 0.42 for use of contraceptive agents. Thus, the final multiple regression model for REE levels was constructed for the whole group but included race in addition to total fat-free mass, fat mass, smoking, and contraceptive medication use (table 2). Race, total fat-free mass, fat mass, and smoking were all significantly associated with REE, but use of contraceptive agents was not, although a trend was found: p = 0.07. The racial difference of 71 kcal/day (297 kJ/day) in REE still remained (p = 0.004), even after adjustment for body composition, cigarette smoking, and contraceptive use. Total fat-free mass, fat mass, and smoking also were all significantly associated with higher REE values. Total fat-free mass had a far greater impact on REE than did fat mass: 19.8 kcal/day (83 kJ/day) versus 6.2 kcal/day (26 kJ/day), p < 0.001 for the difference between these two ß coefficients. Compared with nonsmokers, cigarette smokers, on average, had a REE that was 67.6 kcal/day (283 kJ/day) higher (p = 0.03).
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DISCUSSION |
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Our study has several methodological strengths. The population was a random sample of a large cohort of healthy young women among whom adiposity and socioeconomic status varied widely for both racial groups. In contrast, many of the studies that examined racial differences in REE were confined to smaller, highly selected samples and included a wider range of ages. The majority of the study populations also consisted of predominantly obese subjects whose metabolic rate may already have been altered or have deviated from that of normal-weight persons. The age range of our study population was narrow, and the mean age was identical for the two racial groups, thus enhancing validity of the racial comparisons. The absence of a significant effect of menstrual cycles on REE enabled us to use the average of two determinations of REE for data analysis, thereby enhancing statistical power by diminishing variability of the outcome measure. In this study, the conditions under which REE was determined were controlled and standardized, and they included overnight admission to a Clinical Research Center. Finally, our sample size of 147 is one of the largest studies of REE, particularly for racial comparisons in healthy premenopausal women whose adiposity varies widely.
Our relatively large sample size and extensive available clinical information permitted the examination of some frequently practiced behavioral traits (i.e., smoking and contraceptive medication use) and racial differences in the effect of these factors on REE. Most published studies excluded smokers and users of contraceptive agents, and a few studies failed to mention smoking status. Thus, our analytical approach provided estimates of the quantitative effects of smoking and contraceptive medication use on REE. Of particular interest was the somewhat surprisingly large effect size of smoking on REE; that is, compared with nonsmokers, smokers had REE values that were on average 68 kcal/day (285 kJ/day) higher, even after adjustment for other potential confounding factors such as adiposity, race, and contraceptive medication use. Although other studies have examined the relation between cigarette smoking and REE, to our knowledge ours is the first that provides an estimate of the quantitative effect of chronic cigarette smoking on energy metabolism in free-living women. Our study demonstrates that young women who smoke cigarettes have a higher REE, even after control for differences in body size. Some women may initiate cigarette smoking in part to control their weight. Although the variety of health risks associated with cigarette smoking substantially outweighs any benefit smoking may confer on REE, this finding could further our current understanding of the pharmacokinetics of nicotine and tobacco products on energy metabolism and could potentially aid in the development of agents to combat weight gain after smoking cessation.
At present, there is an absence of information on racial differences in REE during the transition between adolescence and adulthood. The age range of our study population fills this gap, which is of particular interest because the racial difference in adiposity is established during this age span (20). In general, prepubescent Black girls are not heavier or fatter than comparably aged White girls (41
, 42
) although, by early adulthood, Black women usually are significantly heavier than White women (43
, 44
). The longitudinal findings from the NGHS demonstrated that the racial divergence in adiposity became established by age 12 years, which corresponded to the age of menarche for the majority of Black girls (20
). Although the time of the racial divergence in REE during the life cycle has yet to be determined, our findings show that the level of REE is significantly lower in Black women by age 19 years, even though it has not been clearly established whether this racial difference is present before the onset of pubertal maturation. Hence, one may surmise that the lower REE becomes manifest in Black women sometime during pubertal maturation, which suggests a temporal association between establishment of lower REE and greater accretion of body fat in adolescent Black girls.
Although frequently debated, available research findings have not yet been able to definitively attribute the racial disparity in obesity prevalence to differential caloric intake or physical activity. Under similar environmental conditions, we demonstrated that young Black women had a more parsimonious metabolic rate than their similarly aged White counterparts after we adjusted for body composition and other environmental factors. The significant race interaction with REE on fat mass indicated that the effect on fat mass was 0.016 kg greater for each kcal/day of REE in Black women than in White women. This racial difference in the relation between adiposity and REE may yet be another indication of a racial difference in energy metabolism that may underlie the high vulnerability of Black women to obesity. These two findings from our studylower REE in Black women and the race interaction with REE on adiposityraise anew the "thrifty" gene hypothesis. This hypothesis postulates an adaptive selection over the millennia of those persons who could better store surplus energy as body fat in times of abundant food availability and who also could use energy more efficiently from foodstuffs in times of food shortage, such as famines (45). These persons or population groups with such a gene (a "thrifty" gene) are conjectured to be at increased risk for obesity and type II diabetes when exposed to an environment of abundant food supply and physical inactivity. Pima Indians have been conjectured to have this genetic predisposition, and familial aggregation of lower REE has been observed in Pima Indians who are particularly susceptible to severe obesity (46
, 47
). Osei, in a recent review of the metabolic consequences of the West-African diaspora, speculates that the primary lesion underlying the metabolic abnormalities in people of West-African ancestry may be an enhanced genetic conservation of energy (48
).
Because of the cross-sectional nature of this study, a causal association between lower REE in Black women and obesity cannot be inferred. Nevertheless, the consistent racial difference in REE that fosters greater energy conservation in Black women may be another manifestation of their increased susceptibility to obesity. Although seemingly small, the observed racial difference in REE of 71 kcal/day (297 kJ/day) in this study has a potentially large long-term impact on energy balance. For instance, this incremental difference alone could lead to an extra 3.3 kg of weight gain per year for Black women. In other words, after adjustment for the same caloric intake and physical activity, African-American women are still at a disadvantage compared with White women. The dramatic increase in the prevalence of obesity in African-American females in recent years may be the result of a contemporary sedentary lifestyle in the face of a caloric intake that is in excess of their metabolic needs. The public health implications are clear. It is critical to emphasize the importance of energy homeostasis in young African-American women who seem to have an efficient system of energy metabolism that has evolved over the millennia. While teleologically adaptive in the remote past, this system has now become "maladaptive" in the midst of the abundant availability of food energy and diminished energy expenditure.
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ACKNOWLEDGMENTS |
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NOTES |
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REFERENCES |
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