scholarly journals Sex Differences in the Effects of Inhaled Corticosteroids on Weight Gain among Patients with Asthma

2012 ◽  
Vol 2012 ◽  
pp. 1-7 ◽  
Author(s):  
Amanda K. Rizk ◽  
Kim L. Lavoie ◽  
Véronique Pepin ◽  
Alicia Wright ◽  
Simon L. Bacon

Background. Studies have shown that asthma and asthma exacerbations are related to body weight and that this relationship might be sex-specific. While oral corticosteroids have been associated with weight gain, little is known about the effect of inhaled corticosteroid (ICS) use on short-term weight gain. The purpose of the present study was to examine whether ICSs would be associated with weight gain among asthmatic patients. Methods. A total of 180 adult patients with physician-diagnosed asthma provided details of their medical history and demographic information, along with height and weight at baseline and at one year. Weight change was defined as follow-up minus baseline weight. General linear models were used to assess the relationship between ICS dose (fluticasone propionate equivalent) and sex. Results. Significant main effects of sex (P=.005) and ICS dose (P=.036) and an interaction effect of sex and ICS dose (P=.003) on weight change were observed. Further analysis of the interaction indicated that women had greater weight gain, while men had decreased weight with increased ICS dose. Conclusions. Findings suggest that ICSs may trigger weight gain in females and highlight the need for studies to confirm this relationship and examine the potential underlying mechanisms.

Circulation ◽  
2014 ◽  
Vol 130 (suppl_2) ◽  
Author(s):  
Beatrice A Golomb ◽  
Hayley J Koslik ◽  
Alexis K Bui

Background and Goal: Sleep problems were significantly increased on simvastatin ( simva ) (but not pravastatin) vs placebo in the UCSD Statin Study. Sleep problems on simva predicted glucose rise. Weight gain has also been reported as a statin side effect. We sought to capitalize on existing data to assess whether sleep problems on simva related to weight gain in men. Method: 442 men without known diabetes or CVD were randomized to simva 20mg or placebo for 6 mon. One hundred eighty and 186 completed single-item self-rating of change in sleep problems vs baseline ( Δslpprob ). Weight (lb) was measured at baseline and 6 mon. Missing 6 mon values were imputed. Analyses: A. Regressions stratified by treatment assessed prediction of weight change by Δslpprob, adjusted for baseline weight. B. Regressions assessed prediction of weight change by the interaction term of simva (vs placebo) x Δslpprob, adjusted for the components of the interaction and baseline weight. Since age-related muscle loss may complicate weight change in elderly; and young adults have low vulnerability to metabolic problems, analyses were repeated excluding these groups. Results: A. Increased sleep problems on simva predicted weight gain (significant), but on placebo predicted weight loss (nonsignificant). B. The Δslpprob x simva interaction term significantly predicted weight gain. When that was parceled out, simva, outside of the sleep relationship, negatively predicted weight change. Exclusion of young adults and elderly strengthened significance of findings (Table). Discussion: Sleep problems, which differentially arise on simva, differentially predict weight gain on simva. This expands the metabolic effects to which sleep problems on simva may contribute and might possibly favor mediation by sleep apnea (a reported complication of simva). Once the sleep problem effect is considered, simva use predicted weight loss . The relative contribution of fat vs muscle loss (vs other) requires exploration.


2018 ◽  
Vol 32 (10) ◽  
pp. 1098-1103 ◽  
Author(s):  
David PJ Osborn ◽  
Irene Petersen ◽  
Nick Beckley ◽  
Kate Walters ◽  
Irwin Nazareth ◽  
...  

Background: Follow-up studies of weight gain related to antipsychotic treatment beyond a year are limited in number. We compared weight change in the three most commonly prescribed antipsychotics in a representative UK General Practice database. Method: We conducted a cohort study in United Kingdom primary care records of people newly prescribed olanzapine, quetiapine or risperidone. The primary outcome was weight in each six month period for two years after treatment initiation. Weight changes were compared using linear regression, adjusted for age, baseline weight and diagnosis. Results: N = 6338 people received olanzapine, 12,984 quetiapine and 6556 risperidone. Baseline weight was lowest for men treated with olanzapine (80.8 kg versus 83.5 kg quetiapine, 82.0 kg risperidone) and women treated with olanzapine (67.7 kg versus 71.5 kg quetiapine 68.4 kg risperidone. Weight gain occurred during treatment with all three drugs. Compared with risperidone mean weight gain was higher with olanzapine (adjusted co-efficient +1.24 kg (95% confidence interval: 0.69–1.79 kg per six months) for men and +0.77 kg (95% confidence interval: 0.29–1.24 kg) for women). Weight gain with quetiapine was lower in unadjusted models compared with risperidone, but this difference was not significant after adjustment. Conclusion: Olanzapine is more commonly prescribed to people with lower weight. However, after accounting for baseline weight, age, sex and diagnosis, olanzapine is still associated with greater weight gain over two years than risperidone or quetiapine. Baseline weight does not ameliorate the risks of weight gain associated with antipsychotic medication. Weight gain should be assertively discussed and managed for people prescribed antipsychotics, especially olanzapine.


2011 ◽  
Vol 26 (S2) ◽  
pp. 250-250
Author(s):  
J. Zhao ◽  
P. Cazorla ◽  
J. Schoemaker ◽  
M. Mackle ◽  
J. Panagides ◽  
...  

IntroductionWeight change and metabolic effects of atypical antipsychotics vary considerably.ObjectiveAssess weight and metabolic effects of asenapine in adults.AimDemonstrate that asenapine marketed doses are well tolerated compared with placebo or olanzapine.MethodsData were from pooled asenapine trials that used placebo (1748 patients; duration: 1−6 wk) and/or olanzapine (3430 patients; duration, 3−>100 wk) controls. Asenapine doses were 5 or 10 mg BID (2–20 mg BID in 2 studies); olanzapine doses were 5–20 mg QD. Post hoc inferential analyses based on ANOVA assessed change from baseline weight, body mass index, and fasting lipid and glucose levels.ResultsTable 1 summarizes the results.[Change From Baseline Weight and Metabolic Paramete]DiscussionThese post hoc pooled analyses support published reports and suggest asenapine was associated with moderate weight gain and increased fasting triglyceride and glucose levels vs placebo, but lower propensity for weight gain or increased serum lipids (ie, triglycerides, low-density lipoprotein, and cholesterol) vs olanzapine.


PeerJ ◽  
2021 ◽  
Vol 9 ◽  
pp. e10764
Author(s):  
Julien Delarocque ◽  
Florian Frers ◽  
Korinna Huber ◽  
Klaus Jung ◽  
Karsten Feige ◽  
...  

Background Insulin dysregulation (ID) is an equine endocrine disorder, which is often accompanied by obesity and various metabolic perturbations. The relationship between weight variations and fluctuations of the insulin response to oral glucose tests (OGT) as well as the metabolic impact of ID have been described previously. The present study seeks to characterize the concomitant metabolic impact of variations in the insulin response and bodyweight during repeated OGTs using a metabolomics approach. Methods Nineteen Icelandic horses were subjected to five OGTs over one year and their bodyweight, insulin and metabolic response were monitored. Analysis of metabolite concentrations depending on time (during the OGT), relative bodyweight (rWeight; defined as the bodyweight at one OGT divided by the mean bodyweight across all OGTs) and relative insulin response (rAUCins; defined accordingly from the area under the insulin curve during OGT) was performed using linear models. Additionally, the pathways significantly associated with time, rWeight and rAUCins were identified by rotation set testing. Results The results suggested that weight gain and worsening of ID activate distinct metabolic pathways. The metabolic profile associated with weight gain indicated an increased activation of arginase, while the pathways associated with time and rAUCins were consistent with the expected effect of glucose and insulin, respectively. Overall, more metabolites were significantly associated with rWeight than with rAUCins.


2014 ◽  
Vol 32 (4_suppl) ◽  
pp. 80-80
Author(s):  
Daniel Martin Seible ◽  
Xiangmei Gu ◽  
Andrew Hyatt ◽  
Clair Beard ◽  
Jason Alexander Efstathiou ◽  
...  

80 Background: Androgen deprivation therapy (ADT) is a mainstay of prostate cancer therapy. Weight gain is among the adverse metabolic changes associated with ADT, and may contribute to cardiovascular comorbidity. A better understanding of the risk factors for weight gain on ADT is important for optimal management of ADT-associated morbidity. Methods: A retrospective review assessed weight change among 118 men with nonmetastatic prostate cancer treated with ADT. The primary endpoint was weight change at one year from ADT initiation, with the secondary aim to stratify risk of weight gain by baseline patient characteristics. Statistical analyses were performed using two-tailed t-tests and linear regression. Results: Men in our cohort exhibited a significant increase in weight (p=0.0005) in the one year following ADT initiation. Three risk factors for weight gain on ADT were identified: younger than age 65 (5.98 pounds gained, p=0.001 vs. 1.63 pounds, p= 0.09 for age 65+), body mass index (BMI) less than 30 (4.36 pounds gained, p=0.00002 vs. 0.22 pounds, p=0.87 for BMI 30+), and non-diabetic status (3.43 pounds gained, p=0.0003 vs. 0.57 pounds, p=0.74 for diabetics). An aggregate risk scoring system was contrived to allow for weight change prediction by total number of risk factors present: scores of 0, 1, 2, and 3 risk factors corresponded to weight changes of -2.42 (p=0.43), +0.9 (p=0.56), +2.9 (p=0.01) and +8.3 pounds (p= 0.0001) respectively. Weight gain increased significantly with increasing risk score (p-trend= 0.0005), decreasing baseline age (p-trend= 0.004) and decreasing baseline BMI (p-trend= 0.01). Conclusions: Younger than age 65, BMI less than 30, and non-diabetic status were each significantly associated with weight gain one year after starting ADT. Increasing weight gain was strongly associated with increasing number of baseline risk factors. Although metabolic consequences were previously considered most significant for patients with preexisting comorbidity, these data suggest younger, slimmer, and non-diabetic patients may be at higher risk for gaining weight on ADT. As these three categories of men generally have higher endogenous testosterone (T) levels prior to ADT compared to older, obese, and diabetic men, the magnitude of T decline following ADT might explain these findings.


Blood ◽  
2015 ◽  
Vol 126 (23) ◽  
pp. 2088-2088
Author(s):  
Daphne Y Xiao ◽  
Katiuscia O'Brian ◽  
Suhong Luo ◽  
Kenneth R Carson

Abstract Introduction Weight loss during chemotherapy has been associated with decreased overall survival (OS) in various solid tumors. While weight loss >10% in the 6 months leading up to diagnosis is a known adverse prognostic factor for non-Hodgkin's lymphoma (one of the B symptoms), the association between weight loss during chemotherapy and survival in follicular lymphoma (FL) patients is not well understood. Few studies have looked at long-term weight change patterns following chemotherapy treatment in this patient population. We investigated short and long-term weight change trends, predictors, and association with OS and disease-specific survival (DSS) in a cohort of FL patients. Methods FL patients diagnosed and treated with CHOP (cyclophosphamide, doxorubicin, vincristine, and prednisone) +/- rituximab, CVP (cyclophosphamide, vincristine, and prednisone) +/- rituximab, or rituximab monotherapy regimens between 1998 and 2010 were identified in the Veterans Health Administration database. Data on weight 1 year prior to treatment, at time of first treatment (baseline), and up to 5 years after treatment initiation was obtained. Additional data on height, age, stage, race, comorbidities, date of diagnosis, LDH, and B-symptoms was obtained. Body Mass Index (BMI) at diagnosis was categorized according to World Health Organization criteria. Weight change during treatment is calculated as difference between baseline weight and 3 months after start of treatment. Long-term weight change is calculated as difference between baseline weight and 24 months after start of treatment. Logistic regression identified factors associated with long-term weight gain. Landmark Cox analysis evaluated prognostic significance of weight loss during treatment among patients who survived at least 6 months after treatment initiation. Results 1022 patients met inclusion criteria out of 2235. Mean and median age at diagnosis was 63.6 and 63.0 years respectively, 95.9% were men, and 72.7% had Stage III/IV disease. The mean Charlson co-morbidity score was 2.3. B symptoms were present in 37.9% and LDH was elevated in 26.8%. Mean and median weight change during treatment was -1.4kg (-1.5%) and -0.4kg (-0.6%), with a majority of patients losing weight (56%) and 23% of patients losing >5% of their baseline weight. In contrast, mean and median weight change at 24 months after treatment initiation was +1.2kg (+1.6%) and +1.3kg (+1.6%), with a majority of patients (57%) gaining weight and 14% of patients gaining >10% of their baseline weight after treatment completion. Logistic regression analysis identified factors associated with increased risk of weight gain >10% at 24 months after treatment initiation. These included: weight loss >5% in the year prior to treatment (Odds Ratio (OR) 6.82, 95% Confidence Interval (CI) 3.09-15.05), weight gain between 0-5% during treatment (OR 2.53, 95% CI 1.21-5.27), and weight gain >5% during treatment (OR 9.43, 95% CI 3.85-23.14). Kaplan-Meier survival analysis showed that weight loss >5% during treatment was associated with decreased OS (p<0.0001) and disease specific survival (DSS) (p=0.0027) compared to weight loss <5% or weight gain. A landmark Cox analysis controlling for age, disease stage, comorbidities, elevated LDH, B symptoms, BMI at diagnosis, and treatment type showed that weight loss >5% during treatment was independently associated with worse OS (Hazard Ratio (HR) 1.71, 95% CI 1.32-2.22) and DSS (HR 1.61, 95% CI 1.11-2.34). Conclusions In patients with FL, weight loss >5% during treatment is independently predictive of worse overall survival and disease-specific survival. Weight loss could be considered in conjunction with other dynamic variables (such as PET positivity and nodal size) to assess prognosis at the end of therapy. 14% of patients experience long-term weight gain >10% of baseline. Patients who gained 5% or more during treatment are at highest risk (OR=9.4) for long-term weight gain-this subset of patients could be targeted for weight loss interventions to prevent future obesity-related comorbidities. Disclosures No relevant conflicts of interest to declare.


Circulation ◽  
2012 ◽  
Vol 125 (suppl_10) ◽  
Author(s):  
Julie Holden ◽  
Damon Swift ◽  
Neil Johannsen ◽  
Conrad Earnest ◽  
Timothy Church

Hypothesis: Weight gained in response to aerobic exercise represents an increase in lean mass. Methods: Participants from the exercise group (n=68) of the Inflammation and Exercise (INFLAME) study had fat mass, lean mass, and weight measured at baseline and at follow-up. Fat mass and lean mass were measured using DXA. Changes in lean mass and fat mass were quantified across tertiles of weight change in the exercise training group and were analyzed using generalized linear models with adjustment for baseline value. Results: are presented as least squares means with 95% confidence intervals. Results: Overall, participants exhibited a mean (range) weight change of –0.73 kg (–9.00, 7.00; n=68) following exercise training. Tertiles of mean (range) weight change were: tertile 1 (most weight loss) –3.40 kg (–9.00,–1.50; n=23), tertile 2 (some weight loss) –0.70 kg (–1.30, –0.10; n=22), and tertile 3 (weight gain) 1.93 kg (0, 7.00; n=23). For those in tertile 3, we observed a significant increase (p<0.0001) in lean mass of 0.91 kg (95% CI, 0.48, 1.34) compared to those who lost weight −0.85 kg (−1.28,−0.42) in tertile 1 and −0.52 kg (−0.97,−0.08) in tertile 2. However, no significant difference in lean mass change was seen between the two weight loss tertiles. We also observed a significant increase in fat mass in participants who gained weight (tertile 3) 1.07 kg (0.41, 1.73) while those who lost the most weight (tertile 1) −2.55 kg (−3.21,−1.89) had a significant decrease in fat mass. Participants who experienced some weight loss (tertile 2) showed no significant change in fat mass, −0.24 kg (−0.91, 0.44). Conclusion: Weight gained with aerobic exercise training cannot be attributed to increased lean mass only. Our findings suggest that adults who gained weight with exercise showed significant increases in both fat and lean mass.


1979 ◽  
Vol 9 (4) ◽  
pp. 703-708 ◽  
Author(s):  
Paul E. Garfinkel ◽  
Harvey Moldofsky ◽  
David M. Garner

SYNOPSISPatients with anorexia nervosa have previously been shown to display disturbances in visual self-perception and interoception. In the present investigation we wished to determine the stability of these disturbances and the effects of weight gain on them. We studied 29 females, 16 patients with primary anorexia nervosa and 13 controls, who had also been studied one year previously. Each subject took part in investigations of body image, using a distorting photograph technique, and interoception, using a satiety aversion to sucrose test. We found that some anorexic subjects tend to overestimate body size and have an absence of aversion to repeated sucrose tastes. Moreover, these disturbances were stable over the year and were not affected by weight change.


Blood ◽  
2013 ◽  
Vol 122 (21) ◽  
pp. 2972-2972
Author(s):  
Arun Ganti ◽  
Katiuscia O'Brian ◽  
Weijian Liu ◽  
Suhong Luo ◽  
Kenneth R. Carson

Abstract Introduction Prior studies have demonstrated weight gain among recipients of chemotherapy for various solid tumors, though there is little evidence describing weight changes during and after treatment in patients with non-Hodgkin lymphoma (NHL). Weight gain during and after treatment can contribute to an increased risk of chronic conditions including: diabetes, coronary disease, and hypertension. This is important for long-term health in patients with diseases that are potentially curable or associated with long-disease free intervals, such as diffuse large B-cell lymphoma (DLBCL) and follicular lymphoma (FL). We investigated the magnitude of weight change during and after treatment in a cohort of DLBCL and FL patients. Methods DLBCL and FL patients diagnosed between 1998 and 2008 and treated with combination chemotherapy +/- rituximab, were identified in the Veterans Health Administration database. Data on weight at time of first treatment (baseline) and at all recorded weight measurements up to 5 years after treatment initiation was obtained. Additional data included: height, age, race, co-morbidities, date of diagnosis, disease stage, LDH at diagnosis, B-symptoms, and treatment details (drugs, dates, and dosages). Only patients treated with CHOP (cyclophosphamide, doxorubicin, vincristine, and prednisone) +/- rituximab or CVP (cyclophosphamide, vincristine, and prednisone) +/- rituximab were included in the study cohort. Patients were categorized as gaining or losing 0-2.5%, 2.5-5%, 5-7.5%, 7.5-10%, or >10% of baseline weight. Weight change during treatment was calculated utilizing baseline and weight measurement at or near 3 months following treatment initiation. B-spline modeling was applied to further evaluate trends in weight change over time within the cohort. Results 2,159 patients met inclusion criteria. Mean age at diagnosis was 63.1 years, 96.6% of patients were men, and 59.5% of patients had stage III/IV disease. Mean Charlson co-morbidity score was 2.2. B-symptoms were noted at diagnosis in 48.4% of patients and LDH was elevated in 47.2% of patients. Mean and median weight change at 3 months after treatment initiation were -1.9 kg and -1.1 kg respectively, or -2.1% and -1.3% of baseline weight. Figure 1 illustrates the distribution of weight change during treatment within the cohort. In B-spline analysis, weight loss was maximal at 4.14 months after first treatment, with subsequent weight gain until reaching a plateau at 22 months (Figure 2). Among patients with 24 months or more of follow-up data, 45.7% had gained weight at 3 months and 60.5% had gained weight at 24 months. Only 4.3% of patients had gained >10% of baseline weight at 3 months, while 23.0% had gained >10% at 24 months. Similarly, 15.4% of patients had gained >5% of baseline weight at 3 months, while 38.5% had gained >5% at 24 months. Of the patients that gained weight at 3 months, 9.3% had gained >10% of baseline weight, while of the patients that gained weight at 24 months, 38.0% had gained >10%. Patients who gained weight in the first 3 months after treatment initiation were more likely to gain >10% baseline weight at 24 months compared to those who lost weight in the first 3 months. Discussion These results suggest that in contrast to other malignancies, most patients with NHL who are treated with multi-agent chemotherapy actually experience weight loss rather than weight gain over the course of treatment. Despite this initial trend, a majority of these patients undergo significant weight gain after the conclusion of therapy and in subsequent months. This poses a long-term health risk, particularly to patients who achieve a complete remission and long-term disease control. The timing of greatest weight gain in the 6-18 months after treatment initiation suggests an opportune time for initiation of a diet or exercise intervention to reduce weight gain shortly after the end of treatment. Disclosures: No relevant conflicts of interest to declare.


2012 ◽  
Vol 2012 ◽  
pp. 1-4 ◽  
Author(s):  
Robert J. Karp ◽  
Tawana Winkfield-Royster ◽  
Jeremy Weedon

Background. While rapid early weight gain are common in children who become obese later in life, so is growth faltering in the first 3 months of life.Objective. We seek to determine what relationship weight gain in the first six months of age, separated into two 3-month periods, have with the BMI of children ages 4 to 6 years in an inner-city community.Subjects. A convenience sample cohort of 154 children attending an inner-city clinic.Methods. Consecutive charts were reviewed retrospectively. Age, gender, birth weight and weight change in the first and second 3 months of life were introduced as fixed factors using mixed linear models with BMI in years 4 to 6 as the dependent variable.Results. Weight change quartile in the first 3 months of life did not predict of BMI in years 4 to 6; however, weight changes quartiles during months 4 to 6 were significant predictors for subsequent overweight.Conclusion. The data presented herein suggest that, for this specific population, weight gain can be promoted when it is most essential. It is necessary, however, to identify intermediary variables that could affect outcomes in this and other communities.


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