Ghrelin, Adiponectin, and Leptin Do Not Predict Long-term Changes in Weight and Body Mass Index in Older Adults: Longitudinal Analysis of the Rancho Bernardo Cohort

Claudia Langenberg1,2, Jaclyn Bergstrom1, Gail A. Laughlin1 and Elizabeth Barrett-Connor1

1 Department of Family and Preventive Medicine, School of Medicine, University of California, San Diego, La Jolla, CA
2 Department of Epidemiology and Public Health, University College London Medical School, London, United Kingdom

Correspondence to Dr. Elizabeth Barrett-Connor, Department of Family and Preventive Medicine, School of Medicine, University of California, San Diego, 9500 Gilman Drive, La Jolla, CA 92093-0607 (e-mail: ebarrettconnor{at}ucsd.edu).

Received for publication March 15, 2005. Accepted for publication July 27, 2005.


    ABSTRACT
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 APPENDIX
 References
 
Ghrelin, leptin, and adiponectin are associated with body size in cross-sectional studies; it is unknown whether these hormones predict long-term changes in body size. Multilevel models were used to study associations between fasting serum hormones, measured in 698 men and 619 women (60–91 years) in samples collected at baseline (1984–1987), and changes in weight and body mass index, assessed repeatedly over a follow-up period of up to 18 years (median, 4.7 years). Baseline weight was –1.5 kg lower for a one-standard-deviation increment in ghrelin and –3.3 kg lower for a one-standard-deviation increment in adiponectin, similar in men and women. For leptin, baseline weight was 12.1 kg higher for a one-standard-deviation increment in men, compared with 5.7 kg in women (sex-interaction p ≤ 0.0001). Ghrelin and adiponectin did not affect weight change; their associations with weight were constant over time, indicated by nonsignificant hormone-by-time interactions. The positive association between leptin and weight became slightly weaker over time. Results were similar when investigating repeated measures of body mass index. From this analysis of Rancho Bernardo Study data, the authors conclude that ghrelin, adiponectin, and leptin do not predict weight gain beyond reflecting the influence of attained body size on future changes in weight or body mass index.

adipocytes; body weight changes; leptin; longitudinal studies; obesity; peptide hormones


Abbreviations: CI, confidence interval


    INTRODUCTION
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 APPENDIX
 References
 
The growing obesity epidemic, together with advances in the understanding of the complex physiology that regulates body weight, has led to an increased interest in hormonal signals implicated in weight homeostasis and metabolic disorders. Ghrelin, leptin, and adiponectin have all been associated with different measures of body size in cross-sectional studies; it is unknown whether these hormones influence long-term changes of weight and body mass index.

Ghrelin is produced primarily by the stomach; its function as a short-duration, meal-related hunger signal in humans is supported by evidence of a preprandial increase and postprandial decrease in concentration (1Go–3Go) and the stimulation of appetite and food intake in response to parenteral ghrelin administration (4Go). In contrast, a recent study reported an inverse association between endogenous plasma ghrelin and ad libidum food intake, highlighting that ghrelin's potential as an orexigenic hormone is far from understood (5Go). One small experimental study found no association between baseline plasma ghrelin and 3-month weight change in participants exposed to overfeeding or negative energy balance conditions (6Go). Long-term epidemiologic studies in free-living individuals are required to determine whether ghrelin is involved in the etiology of human obesity.

Leptin is synthesized and secreted by adipose tissue. Although the severe obesity that accompanies rare leptin deficiency is reversible through exogenous leptin administration, studies of the general population have shown a positive correlation between leptin and body size (7Go–9Go). This observation led to the hypothesis that high leptin levels reflect leptin resistance (10Go). Accordingly, one study found that elevated leptin concentrations were significantly associated with 4-year weight gain in men who were overweight, but not in the total population (11Go). While positive associations between leptin and weight change were shown in some studies (12Go–14Go), most reported no or inverse associations (15Go–23Go). Heterogeneity of study populations (normal weight vs. morbidly obese) and designs (experimental vs. observational) may have contributed to their contradictory results; information from population-based studies is scarce.

Adiponectin is produced mainly in fat cells. Contrary to leptin, adiponectin levels are lower in obese individuals (24Go, 25Go). Adiponectin was not associated with 2- to 3-year weight gain in Pima Indians, a population with a high prevalence of obesity (26Go). The authors concluded that low adiponectin concentrations are likely to be the consequence rather than the cause of obesity in Pima Indians. Prospective population-based studies of adiponectin and weight change in nonobese populations have not been reported.

Previous studies of the importance of ghrelin, adiponectin, and leptin for the regulation of body weight have focused on obese populations, experimentally induced weight loss, or observational weight gain in younger cohorts. Changes in body weight and composition differ at older ages; unintentional weight loss and reduced appetite in older people are common and remain incompletely understood (27Go). It remains unclear whether ghrelin, leptin, and adiponectin influence long-term changes of weight and body mass index. Whether hormonal signals that regulate food intake and weight homeostasis contribute to changes in body weight that occur at later stages of life has not been investigated (28Go). The purpose of this study is to report the associations of ghrelin, leptin, and adiponectin with long-term changes in weight and body mass index in community-dwelling older adults. We investigate whether these hormones influence future weight change beyond reflecting current body size and whether any associations differ by previous body size.


    MATERIALS AND METHODS
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 APPENDIX
 References
 
Subjects and measures
The Rancho Bernardo Study is a prospective cohort study that began in 1972–1974 when 82 percent (n = 5,052) of adult residents aged 30–79 years and living in a southern California suburban community were enrolled (29Go). Between 1984 and 1987, 82 percent (1,093 men and 1,396 women) of surviving members attended a follow-up clinic visit when blood samples were obtained for later hormone assays. This visit is considered the "baseline visit" for the purpose of this analysis.

Blood samples were obtained by venipuncture between 7.5 and 11 hours after a requested 12-hour fast in 1984–1987; serum was separated and frozen at –70°C until 2004 when the samples were thawed (for the second time) for measurement of ghrelin, adiponectin, and leptin by radioimmunoassay (Linco Diagnostics Laboratory, St. Louis, Missouri). The sensitivity and the intra- and interassay coefficients of variation, respectively, were 0.8 mg/liter, 6 percent, and 7 percent for adiponectin; 0.5 ng/ml, 4 percent, and 5 percent for leptin; and 95 pg/ml, 8 percent, and 15 percent for ghrelin. Hormone levels for all participants were above the assay sensitivities. The laboratory reports no problem with two freeze-thaw cycles with these assays, and our levels are similar to those reported in the literature using the same assays (25Go, 30Go–33Go). For comparison purposes, all three hormones were converted into internally derived, standard deviation scores (z scores).

Height and weight were measured according to the same standardized protocol at clinic visits in 1972–1974 (prebaseline), 1984–1987 (baseline), 1988–1992, 1992–1996, 1997–1999, and 1999–2002, and body mass index was calculated (kg/m2). Participants provided informed consent, and the institutional review board approved research protocols.

Of the 2,489 participants who attended the 1984–1987 clinic visit, 332 women were excluded for current estrogen use; 860 men and 702 women of the remaining participants had sufficient stored sera for hormone measurement. Of these, 182 men and 50 women were excluded for being less than 60 years of age, and 13 were excluded for missing height and/or weight data. The remaining 698 men and 619 women that were included in this study were slightly older and more likely to be male, but they did not differ in terms of weight or body mass index, compared with those not included. The median follow-up time was 4.7 years (0–18.2 years).

Statistical analysis
The means and confidence intervals of baseline characteristics and weight and body mass index at each clinic visit were calculated for the men and women included in this study. Geometric means and interquartile ranges were calculated for ghrelin, adiponectin, and leptin. The mean and range of follow-up time, baseline weight, and average annual change of weight between baseline and the last available measurement were calculated for the 860 participants who had a minimum of two measures of weight. The change in weight between 1972–1974 and baseline in 1984–1987 was derived, subtracting the earlier from the later weight; differences in log-transformed standardized hormones were then tested across quarters of prebaseline weight change, using F tests and adjusting for age, sex, and earlier weight. Analysis of covariance was used to test whether age- and sex-adjusted levels of weight, ghrelin, adiponectin, and leptin differed by the number of repeated measures available for each individual.

For multilevel analyses, repeated measures of weight and body mass index taken at a maximum of five occasions per participant between baseline in 1984–1987 and the most recent clinic visit in 1999–2002 were used as outcomes in multilevel analyses with PROC-MIXED software (SAS, version 9.0; SAS Institute, Inc., Cary, North Carolina). In these models, weight changes within and between individuals. A time variable, measured in years since baseline (0–18.2 years), indicates when each measurement was taken and represents follow-up time. This allows investigating changes in the influence of any exposure variable (i.e., sex, age, hormones) on the outcome over time, by including "exposure-by-time" interaction terms. The coefficient for the exposure variable then indicates its influence on weight at time 0 (thus, baseline weight or the intercept), while the interaction term indicates the influence of the exposure on weight change per year from baseline (slope). These models account for within-subject correlation between repeated measures and allow for incomplete outcome data as long as a missing-at-random process can be assumed (34Go).

Weight change was modeled with baseline weight in 1984–1987 representing the intercept and repeated measures of weight representing the linear change of weight over time (slope). Time was included as a random effect, allowing the variance of weight to change over the follow-up time (level-1 random variation) and both intercept and slope to vary between individual cohort members (level-2 random variation). Nonlinear changes of weight were also considered but were nonsignificant and therefore omitted (Appendix, equation 1). Baseline age and sex were included as time-independent covariates, and the main effects of age, sex, time, and the potential interactions between them were evaluated (Appendix, equation 1). Only the age-by-time interaction was significant, indicating that the influence of time on weight, that is, weight change, differed according to baseline age. The basic model was therefore reduced to include sex, age, time, and the age-by-time interaction.

Chi-squared tests based on where is the coefficient estimate and "se" is the standard error, were carried out to assess levels of significance for the fixed-effect parameters as suggested by Goldstein (34Go). The model fit was evaluated by inspection of the Akaike Information Criterion. The random effects of time and any interaction term involving time were included in the model based on likelihood ratio tests.

Separate models were created for ghrelin, adiponectin, and leptin. Each hormone was individually added to the basic model as a fixed effect, allowing the intercept to vary according to hormone levels. An interaction term between each hormone and time was added to the model to test whether the influence of the hormone on weight changed over time. We further investigated whether associations between each hormone and weight differed according to the participant's age at baseline by including a hormone-by-age interaction term. Sex differences in associations between each hormone and baseline weight and changes in weight were investigated in models including both, men and women, a variable indicating sex, and also sex-by-hormone and sex-by-hormone-by-time interaction terms, separately for each hormone (Appendix, equations 2 and 3).

To investigate whether the associations between ghrelin, adiponectin, and leptin and weight were confounded by prebaseline weight, we added weight measured in 1972–1974 as a covariate to the model. We further compared associations in those with and without a prebaseline body mass index of 25 or more kg/m2, to test whether hormonal influences on weight gain were stronger in those who were overweight or obese, as suggested by a previous study (11Go). Differences in associations were tested by including hormone-by-prebaseline body mass index interaction terms in each final model; the significance was assessed using likelihood ratio tests.

All analyses were repeated using body mass index instead of weight as the outcome. Sensitivity analyses were performed using log-transformed, sex-specific standardized hormones.


    RESULTS
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 APPENDIX
 References
 
The mean age at baseline was 74.4 years in men and 75.6 years in women (table 1). The median levels of ghrelin, adiponectin, and leptin were 1,416.0 pg/ml, 10.4 µg/ml, and 6.4 ng/ml in men and 1,319.0 pg/ml, 15.8 µg/ml, and 13.9 ng/ml in women, respectively. The number of participants with available measurements of weight and body mass index declined over the follow-up period, from 1,317 at baseline (1984–1987) to 209 at the most recent follow-up in 1999–2002.


View this table:
[in this window]
[in a new window]
 
TABLE 1. Descriptive characteristics of men and women participating in the Rancho Bernardo Study visit in 1984–1987

 
Simple analyses, restricted to the 860 people with a minimum of two measures of weight, showed that the average follow-up was progressively lower with greater baseline age (table 2); the mean follow-up was 11.9 years in the youngest group aged 60–64 years, compared with 6.3 years in those aged 80 years or more. Baseline weight was lower, and the average annual weight loss between baseline and the most recent measurement was greater at higher baseline ages, ranging from an average increase of 0.01 kg/year in the youngest to a loss of 0.47 kg/year in the oldest group.


View this table:
[in this window]
[in a new window]
 
TABLE 2. Average annual weight change between baseline and last available weight, by age group, in 860 men and women of the Rancho Bernardo Study with at least two measures of weight between 1984 and 2002

 
The levels of ghrelin, adiponectin, and leptin differed significantly (p = 0.03, p ≤ 0.0001, and p ≤ 0.0001, respectively) by quarters of weight change before baseline; ghrelin and adiponectin were highest and leptin was lowest in those who experienced the greatest loss of weight, compared with those who had the greatest weight gain, after adjustment for age, sex, and earlier weight (figure 1).



View larger version (15K):
[in this window]
[in a new window]
 
FIGURE 1. Mean z scores of hormone levels (ghrelin (pg/ml), adiponectin (µg/ml), and leptin (ng/ml) standardized to each have a mean of zero and a standard deviation of one) and 95% confidence intervals (vertical bars) according to weight change before study baseline (from 1972–1974 to 1984–1987) in 1,317 men and women in the Rancho Bernardo Study, adjusted for age, sex, and earlier weight.

 
Further analyses confirmed that participants with older baseline age had fewer repeated measures available; no differences were observed with regard to sex, baseline weight, ghrelin, adiponectin, or leptin (table 3).


View this table:
[in this window]
[in a new window]
 
TABLE 3. Means and proportions (95% confidence interval) of baseline variables according to the number of observations available between 1984 and 2002 for participants of the Rancho Bernado Study

 
In multilevel analyses, baseline weight and body mass index differed by sex and age, being lower in women and at higher ages. The average baseline weight of the youngest (aged 60 years) participants in the study was 83.2 kg (body mass index = 26.6 kg/m2) in men and 68.7 kg (body mass index = 25.6 kg/m2) in women (p ≤ 0.0001). Baseline weight was –0.44 kg lower per year increment in seniority at baseline (95 percent confidence interval (CI): –0.53, –0.36; p ≤ 0.0001); this effect did not differ by sex (p = 0.3). Longitudinal changes in weight and body mass index were similar in men and women but differed by age, as indicated by tests for interaction between sex and time (p = 0.8 for weight and body mass index) and between age and time (p ≤ 0.0001 in both cases). Weight increased nonsignificantly by 0.5 kg per decade (95 percent CI: –0.40, 1.32; p = 0.30) in the youngest participants; this rate of increase was –0.25 kg lower per decade for each year increment in seniority at baseline (95 percent CI: –0.31, –0.18; p ≤ 0.0001).

Adiponectin was significantly associated with weight; baseline weight was –3.3 kg lower for a one-standard-deviation increment in adiponectin. This association did not differ by age or sex (pinteraction = 0.86 and 0.54, respectively). Adiponectin did not affect weight change, similar in both sexes (pinteraction = 0.77); the association between adiponectin and weight was constant over time, as indicated by a nonsignificant adiponectin-by-time interaction (table 4). For example, the estimated weight of a participant whose adiponectin levels were one standard deviation higher compared with another participant was –3.3 kg lower at baseline; this difference changed nonsignificantly by 0.03 kg/year of follow-up (p = 0.2), signifying that after 10 years of follow-up weight was –3.0 kg lower for a one-standard-deviation increment in adiponectin at baseline.


View this table:
[in this window]
[in a new window]
 
TABLE 4. Regression coefficients and 95% confidence intervals for the effect of a one-standard-deviation increment of ghrelin, adiponectin, and leptin on weight at baseline (intercept) and on weight change (slope) between 1984 and 2002 from a multilevel model including 3,128 observations from the Rancho Bernardo Study before (model 1) and after (model 2) adjustment for prebaseline weight

 
Similar results were obtained for ghrelin, with weight being –1.5 kg lower for a one-standard-deviation increment in ghrelin, with no significant differences by age or sex (p = 0.58 and p = 0.06, respectively). Again, ghrelin was not associated with weight change; the hormone-by-time interaction was not significant (table 4), and no sex difference was observed in this association (pinteraction = 0.74).

Sex differences were observed for leptin; baseline weight was 12.1 kg higher for men with a one-standard-deviation greater leptin concentration, compared with 5.7 kg in women (pinteraction ≤ 0.0001). The strong positive association between leptin and weight at baseline became slightly weaker over time (0.06 kg/year) (table 4), as indicated by a significant leptin-by-time interaction (p = 0.01).

Adjustment for body weight measured 12 years earlier in 1972–1974 reduced the strength of the estimates for associations between hormones and baseline weight, but the levels of significance remained unchanged (table 4). The estimates for the slopes (weight change) remained unchanged in adjusted analyses.

A total of 587 of all 1,317 participants (44.6 percent) were overweight or obese (body mass index ≥ 25 kg/m2) at the 1972–1974 visit, the mean difference in body mass index between these groups being 5.1 kg/m2. Stratified analyses of our final models indicated that hormonal influences on weight at baseline and weight change were not stronger in participants who were overweight or obese before baseline (data not shown).

Analyses of repeated measures of body mass index yielded results that were similar to those obtained using weight, with the baseline body mass index being –0.53 kg/m2 lower for a one-standard-deviation increase in ghrelin and –1.16 kg/m2 lower for a one-standard-deviation increase in adiponectin. Sex differences were again observed for leptin, with the baseline body mass index 3.79 kg/m2 higher for a one-standard-deviation increase in leptin in men, compared with 2.28 kg/m2 in women (pinteraction ≤ 0.0001) (table 5). Similar to the analyses for weight, the effects of ghrelin, adiponectin, and leptin on body mass index remained constant over time, indicating that their levels did not predict body mass index gain beyond reflecting the influence of attained body size on future changes in body mass index (table 5).


View this table:
[in this window]
[in a new window]
 
TABLE 5. Regression coefficients and 95% confidence intervals for the effect of a one-standard-deviation increment of ghrelin, adiponectin, and leptin on body mass index at baseline (intercept) and on body mass index change (slope) between 1984 and 2002 from a multilevel model including 3,128 observations from the Rancho Bernardo Study before (model 1) and after (model 2) adjustment for prebaseline weight

 
Results of the multilevel models were similar or equal using log-transformed, sex-specific standardized hormones, except for sex differences in the association between leptin and weight, which lost statistical significance.


    DISCUSSION
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 APPENDIX
 References
 
In this prospective population-based study of 1,317 men and women aged 60–91 years, there were strong and significant associations of ghrelin, adiponectin, and leptin with both weight and body mass index at baseline. None of these associations became stronger over a median follow-up of 4.7 years in either men or women. Although weight loss was common in this study of older adults, associations between hormones and weight did not differ by age. The association between leptin and weight became slightly weaker over time. The negative and significant interaction term between leptin and time does not, however, implicate an influence of leptin on weight loss; rather, it reflects a small change in the degree to which leptin predicts weight as the duration of follow-up increases.

Baseline body size is determined by prebaseline weight and changes of weight, which in turn influence the levels of ghrelin, leptin, and adiponectin, as demonstrated by this study and other studies (35Go–37Go). Cross-sectional associations between hormones and body size thus partly reflect the influence of earlier weight and changes in weight on both hormonal levels and weight at baseline. Accordingly, adjustment for prebaseline weight reduced the estimates of associations between hormones and baseline weight; however, the levels of significance remained unchanged. This shows that the strong associations between hormones and body size are a reflection of weight history on the one hand and attained body size on the other. This, together with the lack of an association between hormones and future weight change, suggests that the levels of ghrelin, adiponectin, and leptin follow an individual's weight trajectory or its accompanying metabolic changes rather than govern it. Thus, our findings suggest that any influence of ghrelin, adiponectin, and leptin on future weight is limited to mirroring attained body size and weight trajectory.

Previous studies investigating weight change
An earlier small study reported that, under standardized conditions of either fixed energy excess or deficit, ghrelin levels did not predict short-term changes in body weight in either condition (6Go). We now show that endogenous ghrelin levels are not associated with spontaneous changes in weight and body mass index, assessed prospectively over a follow-up of up to 18 years in men and women from a population-based cohort. Similar results were obtained for adiponectin, confirming the findings of an earlier study in obese Pima Indians (26Go) and extending them to a population of older adults with a low prevalence of obesity. Studies of leptin have been conflicting, and while some have reported an inverse association between leptin and subsequent weight gain (17Go, 18Go), suggesting that relative hypoleptinemia may be associated with an increased susceptibility for weight gain, this has been challenged by later studies finding positive associations (12Go–14Go). The positive results have been interpreted as evidence that high levels of leptin are indicative of leptin resistance in overweight and obese people, a contributing factor to weight gain. This hypothesis was supported by a study reporting a positive association between leptin and weight gain in overweight, but not normal weight, men (11Go). We found no evidence that the effect of leptin is stronger in people who are overweight or obese. Thus, our results are in line with the majority of recent studies and question the importance of leptin for predicting weight change in humans (15Go, 16Go, 19Go–23Go).

Sex differences were observed for the association between leptin and baseline weight and body mass index, and stronger correlations between leptin and body size in men, compared with women, have previously been reported (38Go). These differences reflect the fact that women have both higher levels and a greater range of leptin than do men, and the differences were abolished in analyses using sex-specific z scores of leptin (results not shown).

Strengths and limitations of the study
This is the largest study with the longest follow-up to investigate the roles of ghrelin, adiponectin, and leptin in future weight change; however, it does have some limitations. Participants are adult residents of Rancho Bernardo, California, a predominantly White, upper-middle-class community. Thus, although our results are more generalizable than those of previous studies, often limited by small selected samples or restricted to obese populations, they are largely based on White older men and women in more advantageous socioeconomic positions and with a lower prevalence of overweight and obesity than the general population. However, we found that associations were not stronger in the 45 percent of men and women who were overweight in this study, compared with those who were not, suggesting that the lower levels of body mass index in this study are not responsible for the lack of association between hormones and weight gain.

Multilevel analyses were used to take account of the correlation between repeated measures of weight and body mass index for the same individual. Although missing outcome data can be incorporated in this method of analysis, the missing-at-random assumption might be violated if missing occurs systematically with regard to hormonal levels, body size, or weight gain. The majority of loss to follow-up in the Rancho Bernardo Study is due to mortality; 70 percent of the participants included in this study died between baseline in 1984–1987 and 2002. Consequently, people with greater baseline age were more likely to have fewer repeated measures available. However, loss to follow-up was nondifferential with regard to gender, weight, and levels of ghrelin, leptin, and adiponectin.

Ghrelin, adiponectin, and leptin were measured from the second thawed serum of fasting blood samples taken and stored in 1984–1987. A single morning sample may be subject to measurement error and inadequately reflect levels throughout the day. However, our results confirm previous studies reporting cross-sectional associations between hormones and body size; it seems unlikely that any measurement error differentially attenuated the association with weight gain only. A previous study showed that, although ghrelin levels are highly variable during the day, fasting morning levels accurately reflect daily ghrelin exposure (39Go). Long-term storage and twice freezing and thawing are unlikely to have distorted the levels of ghrelin, adiponectin, and leptin; our levels are similar to those reported in the literature using the same assays (25Go, 30Go–32Go). One previous study found no significant decrease in ghrelin values after repeated freezing and thawing (40Go). This has also been demonstrated in studies of leptin and adiponectin (41Go, 42Go). Many environmental and genetic factors influence body weight and its change, and any investigation of the roles of ghrelin, adiponectin, and leptin in the complex system regulating weight homeostasis has to be simplistic in the context of a long-term, population-based study. Levels of hormones were assessed only at baseline in this study, and we cannot exclude the possibility that changes of ghrelin, adiponectin, and leptin accompanying weight gain or loss may be important for the regulation of body weight. Weight and body mass index at different time points were used as measures of changes in body fat in this study, as no direct repeated measures of body composition or fat mass were available. The same level of weight or body mass index may reflect different proportions of body fat in men and women and at different ages, and changes in body mass index may thus reflect different changes in body fat in subgroups of this population; however, this cannot be investigated in the present study.

Conclusions
With the background of the increasing obesity epidemic, hormonal markers as predictors of weight gain or regain are an appealing concept for targeting interventions and understanding neuroendocrine responses that may counteract the maintenance of intentional weight loss in overweight and obese people. The same applies to potential predictors of unintentional weight loss in older people, associated with increased morbidity and mortality. Many studies have made assumptions about the roles of ghrelin, adiponectin, and leptin in the regulation of body weight based on cross-sectional findings or alterations in hormonal levels as a result of weight change, interpreted as adaptive responses aimed at maintaining a stable weight. The results of this long-term prospective cohort study suggest that the influences of ghrelin, adiponectin, and leptin on weight gain are limited to mirroring attained body size and weight trajectory, and that their physiologic variations have little role in regulating future body weight in older populations with a normal weight distribution. While results from this observational study cannot provide definitive proof, they indicate that caution is required when predicting long-term effects from cross-sectional or short-term studies.


    APPENDIX
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 APPENDIX
 References
 
Parameters of the Basic and Extended Multilevel Models
In the following equations, yij denotes the weight (body mass index) on measurement occasion i (i = 1–5) of subject j (j = 1, ..., N) and timeij, defined as the time in years after baseline (1984–1987) at which each measurement was taken. The fixed parameter ß0 represents the mean intercept, in this example, the overall mean weight (body mass index) in 1984–1987. The fixed parameter ß1 represents the mean slope or equivalently the linear change in weight (body mass index) for each yearly increase in time. ß2 ß4 denote the fixed effects of age, sex, and the interaction term, time by age. The basic multilevel model for repeated measures of weight (body mass index) in 1984–1987, 1988–1992, 1992–1996, 1997–1999, and 1999–2002 is then written as equation 1.

(1)

The parameters u0j and u1j are the random (between-individual) effects that allow each individual to have his/her own intercept and slope, respectively, and indicate the deviation of each individual's intercept and slope from the mean intercept and slope. These "level 2" random effects parameters are assumed to be bivariate normal with a mean of 0 and variance defined by the variance-covariance matrix that has entries given by the variance of the variance of and the covariance between u0j and The within-individual ("level 1") variation was allowed to increase over time and is represented by the terms e0ij and e1ij. These level 1 random effects are assumed to be bivariate normally distributed, with a mean of 0 and variance defined by the variance-covariance matrix that has entries given by the variance of the variance of and the covariance between e0ij and

Note that interactions of time by sex, age by sex, and time by age by sex are not included. These terms were considered in the model selection but were nonsignificant and therefore not included in the basic model. Nonlinear changes of weight over time were also considered but were also nonsignificant and therefore omitted.

The model given in equation 1 was then extended to assess how hormonal levels influenced both the intercept and the change of weight (body mass index) over time.

(2)

The sex-by-hormone term was considered in model selection for each hormone but included only in the leptin model (equation 3), as the sex-by-leptin interaction was statistically significant. Equation 2 is exemplary, written to include ghrelin; the adiponectin model was identical and is therefore not stated separately.

(3)

Sex-by-hormone-by-time and hormone-by-age interaction terms were considered in all models, but they were nonsignificant and therefore omitted. Nonlinear temporal relations between each hormone and weight change were tested by including quadratic and cubic time terms and their interactions with hormones; none of these was statistically significant.


    ACKNOWLEDGMENTS
 
The Rancho Bernardo Study was funded by research grant AG07181 from the National Institute on Aging and grant DK31801 from the National Institute of Diabetes and Digestive and Kidney Diseases. C. L. is supported by a Medical Research Council Research Training Fellowship from the United Kingdom.

Conflict of interest: none declared.


    References
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 APPENDIX
 References
 

  1. Cummings DE, Purnell JQ, Frayo RS, et al. A preprandial rise in plasma ghrelin levels suggests a role in meal initiation in humans. Diabetes 2001;50:1714–19.[Abstract/Free Full Text]
  2. Tschop M, Wawarta R, Riepl RL, et al. Post-prandial decrease of circulating human ghrelin levels. J Endocrinol Invest 2001;24:RC19–21.[ISI][Medline]
  3. Schwartz MW, Morton GJ. Obesity: keeping hunger at bay. Nature 2002;418:595–7.[CrossRef][ISI][Medline]
  4. Wren AM, Seal LJ, Cohen MA, et al. Ghrelin enhances appetite and increases food intake in humans. J Clin Endocrinol Metab 2001;86:5992–5.[Abstract/Free Full Text]
  5. Salbe AD, Tschop MH, DelParigi A, et al. Negative relationship between fasting plasma ghrelin concentrations and ad libitum food intake. J Clin Endocrinol Metab 2004;89:2951–6.[Abstract/Free Full Text]
  6. Ravussin E, Tschop M, Morales S, et al. Plasma ghrelin concentration and energy balance: overfeeding and negative energy balance studies in twins. J Clin Endocrinol Metab 2001;86:4547–51.[Abstract/Free Full Text]
  7. Maffei M, Halaas J, Ravussin E, et al. Leptin levels in human and rodent: measurement of plasma leptin and ob RNA in obese and weight-reduced subjects. Nat Med 1995;1:1155–61.[CrossRef][ISI][Medline]
  8. Considine RV, Sinha MK, Heiman ML, et al. Serum immunoreactive-leptin concentrations in normal-weight and obese humans. N Engl J Med 1996;334:292–5.[Abstract/Free Full Text]
  9. Zimmet P, Hodge A, Nicolson M, et al. Serum leptin concentration, obesity, and insulin resistance in Western Samoans: cross sectional study. BMJ 1996;313:965–9.[Abstract/Free Full Text]
  10. Frederich RC, Hamann A, Anderson S, et al. Leptin levels reflect body lipid content in mice: evidence for diet-induced resistance to leptin action. Nat Med 1995;1:1311–14.[CrossRef][ISI][Medline]
  11. Chu NF, Spiegelman D, Yu J, et al. Plasma leptin concentrations and four-year weight gain among US men. Int J Obes Relat Metab Disord 2001;25:346–53.[CrossRef][Medline]
  12. Chessler SD, Fujimoto WY, Shofer JB, et al. Increased plasma leptin levels are associated with fat accumulation in Japanese Americans. Diabetes 1998;47:239–43.[Abstract]
  13. Savoye M, Dziura J, Castle J, et al. Importance of plasma leptin in predicting future weight gain in obese children: a two-and-a-half-year longitudinal study. Int J Obes Relat Metab Disord 2002;26:942–6.[CrossRef][Medline]
  14. van Rossum CT, Hoebee B, van Baak MA, et al. Genetic variation in the leptin receptor gene, leptin, and weight gain in young Dutch adults. Obes Res 2003;11:377–86.[Abstract/Free Full Text]
  15. Wing RR, Sinha MK, Considine RV, et al. Relationship between weight loss maintenance and changes in serum leptin levels. Horm Metab Res 1996;28:698–703.[ISI][Medline]
  16. Niskanen LK, Haffner S, Karhunen LJ, et al. Serum leptin in obesity is related to gender and body fat topography but does not predict successful weight loss. Eur J Endocrinol 1997;137:61–7.[Abstract/Free Full Text]
  17. Ravussin E, Pratley RE, Maffei M, et al. Relatively low plasma leptin concentrations precede weight gain in Pima Indians. Nat Med 1997;3:238–40.[CrossRef][ISI][Medline]
  18. Lindroos AK, Lissner L, Carlsson B, et al. Familial predisposition for obesity may modify the predictive value of serum leptin concentrations for long-term weight change in obese women. Am J Clin Nutr 1998;67:1119–23.[Abstract/Free Full Text]
  19. Haffner SM, Mykkanen LA, Gonzalez CC, et al. Leptin concentrations do not predict weight gain: the Mexico City Diabetes Study. Int J Obes Relat Metab Disord 1998;22:695–9.[CrossRef][Medline]
  20. Nagy TR, Davies SL, Hunter GR, et al. Serum leptin concentrations and weight gain in postobese, postmenopausal women. Obes Res 1998;6:257–61.[Abstract]
  21. Hodge AM, de Courten MP, Dowse GK, et al. Do leptin levels predict weight gain?—A 5-year follow-up study in Mauritius. Mauritius Non-communicable Disease Study Group. Obes Res 1998;6:319–25.[Abstract]
  22. Torgerson JS, Carlsson B, Stenlof K, et al. A low serum leptin level at baseline and a large early decline in leptin predict a large 1-year weight reduction in energy-restricted obese humans. J Clin Endocrinol Metab 1999;84:4197–203.[Abstract/Free Full Text]
  23. Folsom AR, Jensen MD, Jacobs DR, et al. Serum leptin and weight gain over 8 years in African American and Caucasian young adults. Obes Res 1999;7:1–8.[Abstract]
  24. Cnop M, Havel PJ, Utzschneider KM, et al. Relationship of adiponectin to body fat distribution, insulin sensitivity and plasma lipoproteins: evidence for independent roles of age and sex. Diabetologia 2003;46:459–69.[ISI][Medline]
  25. Gavrila A, Chan JL, Yiannakouris N, et al. Serum adiponectin levels are inversely associated with overall and central fat distribution but are not directly regulated by acute fasting or leptin administration in humans: cross-sectional and interventional studies. J Clin Endocrinol Metab 2003;88:4823–31.[Abstract/Free Full Text]
  26. Vozarova B, Stefan N, Lindsay RS, et al. Low plasma adiponectin concentrations do not predict weight gain in humans. Diabetes 2002;51:2964–7.[Abstract/Free Full Text]
  27. Bales CW, Ritchie CS. Sarcopenia, weight loss, and nutritional frailty in the elderly. Annu Rev Nutr 2002;22:309–23.[CrossRef][ISI][Medline]
  28. Chapman IM. Endocrinology of anorexia of ageing. Best Pract Res Clin Endocrinol Metab 2004;18:437–52.[CrossRef][ISI][Medline]
  29. Criqui MH, Barrett-Connor E, Austin M. Differences between respondents and non-respondents in a population-based cardiovascular disease study. Am J Epidemiol 1978;108:367–72.[Abstract]
  30. Choi KM, Lee J, Lee KW, et al. The associations between plasma adiponectin, ghrelin levels and cardiovascular risk factors. Eur J Endocrinol 2004;150:715–18.[Abstract/Free Full Text]
  31. Ruhl CE, Everhart JE, Ding J, et al. Serum leptin concentrations and body adipose measures in older black and white adults. Am J Clin Nutr 2004;80:576–83.[Abstract/Free Full Text]
  32. Maahs DM, Ogden LG, Kinney GL, et al. Low plasma adiponectin levels predict progression of coronary artery calcification. Circulation 2005;111:747–53.[Abstract/Free Full Text]
  33. Groschl M, Uhr M, Kraus T. Evaluation of the comparability of commercial ghrelin assays. Clin Chem 2004;50:457–8.[Free Full Text]
  34. Goldstein H. Multilevel statistical models. 2nd ed. London, United Kingdom: Edward Arnold, 1995.
  35. Foster-Schubert KE, McTiernan A, Frayo RS, et al. Human plasma ghrelin levels increase during a one-year exercise program. J Clin Endocrinol Metab 2005;90:820–5.[Abstract/Free Full Text]
  36. Hotta K, Funahashi T, Arita Y, et al. Plasma concentrations of a novel, adipose-specific protein, adiponectin, in type 2 diabetic patients. Arterioscler Thromb Vasc Biol 2000;20:1595–9.[Abstract/Free Full Text]
  37. Rosenbaum M, Nicolson M, Hirsch J, et al. Effects of weight change on plasma leptin concentrations and energy expenditure. J Clin Endocrinol Metab 1997;82:3647–54.[Abstract/Free Full Text]
  38. Miller GD, Frost R, Olive J. Relation of plasma leptin concentrations to sex, body fat, dietary intake, and peak oxygen uptake in young adult women and men. Nutrition 2001;17:105–11.[CrossRef][ISI][Medline]
  39. Purnell JQ, Weigle DS, Breen P, et al. Ghrelin levels correlate with insulin levels, insulin resistance, and high-density lipoprotein cholesterol, but not with gender, menopausal status, or cortisol levels in humans. J Clin Endocrinol Metab 2003;88:5747–52.[Abstract/Free Full Text]
  40. Groschl M, Wagner R, Dotsch J, et al. Preanalytical influences on the measurement of ghrelin. Clin Chem 2002;48:1114–16.[Free Full Text]
  41. Flower L, Ahuja RH, Humphries SE, et al. Effects of sample handling on the stability of interleukin 6, tumour necrosis factor-alpha and leptin. Cytokine 2000;12:1712–16.[CrossRef][ISI][Medline]
  42. Meier U, Gressner AM. Endocrine regulation of energy metabolism: review of pathobiochemical and clinical chemical aspects of leptin, ghrelin, adiponectin, and resistin. Clin Chem 2004;50:1511–25.[Abstract/Free Full Text]




This Article
Abstract
Full Text (PDF)
All Versions of this Article:
162/12/1189    most recent
kwi338v1
Alert me when this article is cited
Alert me if a correction is posted
Services
Email this article to a friend
Similar articles in this journal
Similar articles in ISI Web of Science
Similar articles in PubMed
Alert me to new issues of the journal
Add to My Personal Archive
Download to citation manager
Disclaimer
Request Permissions
Google Scholar
Articles by Langenberg, C.
Articles by Barrett-Connor, E.
PubMed
PubMed Citation
Articles by Langenberg, C.
Articles by Barrett-Connor, E.