This study is unique in that we used a regional analysis of whole-body DXA scans to examine central fat and lean mass, rather than the standard DXA analysis to estimate overall fat and lean mass. Our results indicated that centralized body fat (androidal-to-gynoidal fat mass ratio, androidal fat mass, sagittal abdominal diameter, or waist circumference respectively) was the largest contributor to each circulating appetitive hormone: adiponectin, leptin, insulin, or ghrelin in healthy postmenopausal women. As expected, the relationship of centralized body fat to leptin and insulin was positive, but negative to adiponectin and ghrelin. We confirmed previous findings (21
) of a relationship between measures of central adiposity and adiponectin, leptin, and insulin in healthy post-menopausal women. However, unlike previous studies, we found a strong negative relationship between central adiposity (reflected by waist circumference) and ghrelin in these women. Recent research (29
) has reported a strong negative relationship between waist circumference and ghrelin in younger (< 30 years), but not in mid-life (aged 30–56 years) women. Furthermore, in a study of 79 adult opposite-sex twin pairs, Makovey et al
) found a weak relationship between abdominal fat mass assessed by DXA and ghrelin in women, whereas this relationship in men was strong. Further research is needed to understand the response of ghrelin to central adiposity, particularly in postmenopausal women. We also confirmed the findings of other studies that postmenopausal women with a higher level of adiposity have higher concentrations of both leptin (21
) and insulin (28
), but a lower adiponectin concentration (8
Although lean tissue is typically not considered in central body composition assessment, it is important to assess because it is metabolically active. Limited data comparing pre- versus postmenopausal women suggest a decline in both overall and centralized lean tissue with menopause (2
). However, few studies have examined lean tissue in relation to appetitive hormones. Because a higher body weight requires greater muscle mass for movement, a higher fat mass has been associated with higher lean mass, mainly localized in the legs, but with a decrease in overall lean/fat ratio (32
). We found that leptin and ghrelin were the two appetitive hormones related to lean mass in the regression models, with a significant negative relationship between leptin and whole-body lean mass and positive relationship between ghrelin and hip lean mass. However, we hypothesized that because of the direct relationship between overall fat and lean mass, leptin, ghrelin, and insulin would be directly related to lean mass in the thigh region, whereas adiponectin would be indirectly related. Although the Pearson correlation analysis indicated that leptin was positively related to whole-body lean mass, the direction of the relationship was altered once we took other factors into account. In probing a possible explanation, we found that in the presence of androidal fat mass, the direction of the relationship between whole-body lean mass and leptin may have changed because the simple correlation (positive) between lean mass and leptin was fairly weak (r
= 0.14, P
= 0.028), whereas the correlation (positive) between androidal fat mass and leptin was strong (r
= 0.77, P
≤0.0001). It seemed that androidal fat mass thereby exerted a dominant effect in the regression model. Similar to our findings using correlation analysis, Mahabir et al
) recently found that a higher lean mass was associated with a higher leptin concentration, but they did not take other factors into account. Their participants were older (age range 49.2–78.8 years), tended toward the higher end of adiposity (ranged from underweight to morbidly obese status with BMI range 17.7–42.5 kg/m2
) and were further from menopause (up to 38 years postmenopausal) than the women in our study. Research is needed to examine the relationship between lean mass and appetitive hormones.
Interestingly, our results suggest that white blood cell count was related to adiponectin, ghrelin, and insulin. White blood cell count is typically used as an indicator of infection or inflammation. To our knowledge, none of our women had an infection during baseline testing and no women exhibited an elevated white blood cell count (> 11×109
/l). Research has indicated that white blood cell count is related to body fat in humans (33
), suggesting that adipocytokines may be involved in the adipocyte-induced inflammatory response. Further, Vozarova et al
) found that with a high white blood cell count, insulin sensitivity declined in non-diabetic Pima Indians. Although we did not assess insulin sensitivity, our study found a positive relationship between white blood cell count and circulating insulin in the regression model. Collectively, these studies suggest that white blood cells may reflect an obesity-induced inflammatory state that is also mirrored by the appetitive hormones. The context of our study is important because the majority of these women, except for eight women at UC-Davis whose BMI was ≥30.0, were not considered obese based upon BMI (ranged from 17.8 to 32.7). This suggested that modestly elevated (but still within normal range) white blood cell count, elevated insulin, and low adiponectin is an unfavorable metabolic profile in overweight postmenopausal women. In our study, we had two women who had adiponectin concentrations below the reference range (5.0–30.5 μg/ml) for healthy postmenopausal women (35
) and six women who had a higher insulin concentration than the upper limit of the reference range (5.0–24.0 μU/ml) (3
). However, none of our women were beyond the reference range for white blood cell count.
Our study suggests that age influenced adiponectin and leptin, but not ghrelin or insulin, concentrations in healthy postmenopausal women. Based on the regression models, we noted a positive relationship between age and adiponectin, confirming recently reported results (36
) in similarly aged (45–62 years) subjects. By contrast, but similar to our findings, Ostlund et al
) noted an inverse relationship between age and leptin, attributing this finding to decreased leptin production from adipose tissue and/or increased leptin clearance with increasing age. As expected, fasting glucose was an important (positive) contributor to insulin, second to sagittal abdominal diameter. Interestingly, ω-3 fatty acid concentration was the only dietary factor that emerged as significant in any of the regression models. Lombardo et al
) have suggested that in a rat model, dietary polyunsaturated fatty acids may enhance insulin sensitivity, thereby improving the lipoprotein profile and decreasing CVD risk. Increased CVD risk is related to insulin resistance because it contributes to dyslipidemia (38
). We also noted relationships among the appetitive hormones. Adiponectin was inversely related to leptin, which is consistent with some (11
) but not all studies (26
). A low concentration of adiponectin but a high concentration of leptin has been related to an increased risk of insulin resistance (11
). Likewise, we found that leptin was significantly and positively related to insulin in these non-diabetic healthy postmenopausal women, prior to emergence of disease. Furthermore, similar to Purnell et al
), we confirmed that ghrelin was negatively associated with insulin. The associations among these appetitive hormones are not fully understood, but adiponectin, leptin, and ghrelin may be early indicators of insulin resistance in overweight but healthy postmenopausal women.
Study site was a significant factor in the adiponectin, insulin, and ghrelin models, also evidenced by statistical differences (P≤0.0001) in mean values between study sites, possibly related to the somewhat greater (P = 0.077) variability in whole-body fat mass in the women at UC-Davis (8.05–47.77 kg) compared with those at ISU (8.43–37.01 kg). Our entry criteria was designed to exclude women with a BMI≥30.0, although eight women at UC-Davis did not meet this criterion but had a BMI > 29.9. Despite no difference (P = 0.97) in the mean value for BMI between sites, we noted a lack of homogeneity of variance (P = 0.0030) in BMI with respect to site, likely due to the women at UC-Davis whose BMI ranged from 30 to 32.7. We suspect that this wider range in body size and adiposity at UC-Davis likely contributed to the significant site difference in adiponectin, insulin, and ghrelin in these regression models.
This study was hypothesis generating and could not determine cause and effect because it was cross-sectional. In addition, the participants in this study were healthy postmenopausal women, primarily of Caucasian descent. Thus, our results cannot be generalized to all women across ethnic groups. Since central adiposity in postmenopausal women was related to appetitive hormones, despite the apparent health of these women, minimizing weight gain during the menopausal transition may optimize appetitive hormones, thereby facilitating appetite control and weight maintenance. Additional studies are needed to determine at what level central adiposity should be maintained to optimally affect these appetitive hormones, thus potentially preventing further gain in centralized fat with menopause.