scholarly journals Patterns of Weight Change in Aging and Dying

2020 ◽  
Vol 4 (Supplement_1) ◽  
pp. 491-491
Author(s):  
Stephen Thielke
Keyword(s):  
Older Adults ◽  
Weight Loss ◽  
Risk Factor ◽  
Weight Change ◽  
Population Level ◽  
Chronological Age ◽  
Average Weight ◽  
Remaining Life ◽  
Entire Cohort ◽  
History Of

Abstract Little research has characterized the natural history of weight change in older adults. Different changes may occur during aging and dying. We analyzed 18 years of weight measures from a cohort of 736,361 Veterans, all of whom had died at age 70 or older. We produced summary measures that accounted for both chronological age and number of years before death. Several clear population-level trends appeared. (1) The average weight of the sample declined across all ages at a rate of about 0.18 BMI points per year. (2) Starting about seven years before death, the amount of loss began to accelerate, reaching a decline of 0.75 BMI points in the year before death. (3) Changes in weight relative to years of remaining life were independent of chronologic age. People who died at age 70 experienced, on average, the same type and duration of terminal decline as did those who died at age 95. (4) The dying process involved a cumulative loss of about 1.3 BMI points. (5) The distribution of weights during advancing age both declined and narrowed. (6) Disproportionate deaths occurred at the lower BMI ranges (below a BMI of 24), and especially below 18, regardless of age. (7) The finding in #5 is explained by the entire cohort losing weight, with death of the thinnest members. These findings argue for examining survival time in studies of weight change. They indicate that weight loss may be a natural part of dying, rather than a risk factor for it.

Weight loss trajectories and related factors in a 16-week mobile obesity intervention: A retrospective observational study (Preprint)

2021 ◽  
Author(s):  
Ho Heon Kim ◽  
Young In Kim ◽  
Andreas Michaelides ◽  
Yu Rang Park
Keyword(s):  
Machine Learning ◽  
Weight Loss ◽  
Effect Size ◽  
Weight Change ◽  
Average Weight ◽  
Learning Approach ◽  
Obesity Management ◽  
Significant Difference ◽  
Machine Learning Approach ◽  
Cluster 2

BACKGROUND In obesity management, whether patients lose 5% or more of their initial weight is a critical factor in their clinical outcome. However, evaluations that only take this approach cannot identify and distinguish between individuals whose weight change varies and those who steadily lose weight. Evaluation of weight loss considering the volatility of weight change through a mobile-based intervention for obesity can facilitate the understanding of individuals’ behavior and weight changes from a longitudinal perspective. OBJECTIVE With machine learning approach, we examined weight loss trajectories and explored the factors related to behavioral and app usage characteristics that induce weight loss. METHODS We used the lifelog data of 19,784 individuals who enrolled in a 16-week obesity management program on the healthcare app Noom in the US during August 8, 2013 to August 8, 2019. We performed K-means clustering with dynamic time warping to cluster the weight loss time series and inspected the quality of clusters with the total sum of distance within the clusters. To identify the usage factors to determine clustering assignment, we longitudinally compared weekly usage statistics with effect size on a weekly basis. RESULTS Initial Body Mass Index (BMI) of participants was 33.9±5.9 kg/m2, and ultimately reached an average BMI of 32.0±5.7 kg/m2. In their weight log, 5 Clusters were identified: Cluster 1 (sharp decrease) showed a high proportion of weight reduction class between 10% and 15%—the highest among the five clusters (n=2,364/12,796, 18.9%)—followed by Cluster 2 (moderate decrease), Cluster 3 (increase), Cluster 4 (yoyo), Cluster 5 (other). In comparison between cluster 2 and cluster 4, although the effect size of difference in the average meal input adherence and average weight input adherence did not show a significant difference in the first week, it increased continuously for 7 weeks (Cohen’s d=0.408; 0.38). CONCLUSIONS With machine learning approach clustering shape-based timeseries similarity, this study identified 5 weight loss trajectories in mobile weight management app. Overall adherence and early adherence related to self-monitoring emerged as a potential predictor of these trajectories.

scholarly journals Effect of Weight Change Following Intentional Weight Loss on Bone Health in Older Adults with Obesity

Obesity ◽  
2019 ◽  
Vol 27 (11) ◽  
pp. 1839-1845 ◽  
Author(s):  
Daniel E. Kammire ◽  
Michael P. Walkup ◽  
Walter T. Ambrosius ◽  
Leon Lenchik ◽  
Sue A. Shapses ◽  
...  
Keyword(s):  
Older Adults ◽  
Weight Loss ◽  
Weight Change ◽  
Bone Health ◽  
Intentional Weight Loss

scholarly journals REPORTED WEIGHT CHANGE IN OLDER ADULTS AND PRESENCE OF FRAILTY

2019 ◽  
pp. 1-8
Author(s):  
R.S. Crow ◽  
C.L. Petersen ◽  
S.B. Cook ◽  
C.J. Stevens ◽  
A.J. Titus ◽  
...  
Keyword(s):  
Older Adults ◽  
Weight Loss ◽  
Weight Gain ◽  
Weight Change ◽  
Primary Outcome ◽  
Weight Changes ◽  
Health And Nutrition ◽  
The Impact ◽  
Current Weight ◽  
Time Point

Objective: A 5% change in weight is a significant predictor for frailty and obesity. We ascertained how self-reported weight change over the lifespan impacts rates of frailty in older adults. Methods: We identified 4,984 subjects ≥60 years with body composition measures from the National Health and Nutrition Examination Survey. An adapted version of Fried’s frailty criteria was used as the primary outcome. Self-reported weight was assessed at time current,1 and 10 years earlier and at age 25. Weight changes between each time point were categorized as ≥ 5%, ≤5% or neutral. Logistic regression assessed the impact of weight change on the outcome of frailty. Results: Among 4,984 participants, 56.5% were female, mean age was 71.1 years, and mean BMI was 28.2kg/m2. A weight loss of ≥ 5% had a higher association with frailty compared to current weight, age 25 (OR 2.94 [1.72,5.02]), 10 years ago (OR 1.68 [1.05,2.69]), and 1 year ago (OR 1.55 [1.02,2.36]). Weight gain in the last year was associated with increased rate of frailty (1.59 [1.09,2.32]). Conclusion: There is an association between frailty and reported weight loss over time while only weight gain in the last year has an association with frailty.

scholarly journals Chronic Health Conditions as a Risk Factor for Falls among the Community-Dwelling US Older Adults: A Zero-Inflated Regression Modeling Approach

2017 ◽  
Vol 2017 ◽  
pp. 1-9 ◽  
Author(s):  
Yoshita Paliwal ◽  
Patricia W. Slattum ◽  
Scott M. Ratliff
Keyword(s):  
Older Adults ◽  
Risk Factor ◽  
Medical History ◽  
Community Dwelling ◽  
Chronic Health Conditions ◽  
Health Conditions ◽  
Health Concern ◽  
Chronic Health ◽  
History Of ◽  
First Time

Falls are an important health concern among older adults due to age-related changes in the body. Having a medical history of chronic health condition may pose even higher risk of falling. Only few studies have assessed a number of chronic health conditions as risk factor for falls over a large nationally representative sample of US older adults. In this study, Behavioral Risk Factor Surveillance System (BRFSS) 2014 participants aged 65 years and older (n = 159,336) were evaluated. It was found that 29.7% (n=44,550) of the sample experienced at least one fall and 16.3% (n=20,444) experienced more than one fall in the past 12 months. According to the study findings, having a medical history of stroke, CKD, arthritis, depression, and diabetes independently predict the risk of first-time falling as well as the risk of recurrent falling in older adult population while controlling for other factors. On the other hand, having a medical history of the heart attack, angina, asthma, and COPD did not predict the risk of first-time falling, but did predict the risk of recurrent falling after experiencing the first fall in this population.

scholarly journals Age-Related Difference in Weight Change and All-Cause Mortality in Middle-Aged and Older Korean Populations: Korean Longitudinal Study of Aging

2021 ◽  
Vol 42 (4) ◽  
pp. 297-302
Author(s):  
Jungki Suh ◽  
Yoon Jeong Cho ◽  
Hyun Ji Kim ◽  
Seong Soo Choi
Keyword(s):  
Older Adults ◽  
Weight Loss ◽  
Weight Gain ◽  
Longitudinal Study ◽  
Weight Change ◽  
Significant Risk ◽  
Middle Aged ◽  
Weight Losses ◽  
Age Related ◽  
All Cause Mortality

Background: Obesity is associated with increased mortality as a significant risk factor for chronic diseases, including cardiovascular diseases and cancer. Several people believe that weight gain is harmful, and weight loss helps maintain health. However, some studies have shown that weight loss, particularly among older adults, is more likely to increase the risk of mortality than weight gain.Methods: We used data for the cohort of the Korean Longitudinal Study of Aging, which is a nationwide stratified multi-stage sample of adults aged 45 years. The all-cause mortality risk was assessed using the survival status and the number of months of survival calculated from 2006 (baseline year) to 2016. Cox proportional hazard regression were used to study the causal link between weight change and all-cause mortality risk.Results: The results showed interactive associations between weight loss and mortality among middle-aged and older adults. The hazard ratio was 1.62 (95% confidence interval [CI], 1.10–2.40) for the participants aged 45–65 years with weight losses greater than 5 kg and 1.56 (95% CI, 1.29–1.89) for those older than 65 years with weight losses greater than 5 kg. The results for the group with weight gain above 5 kg were not significant. Middle-aged and older men showed an increase in all-cause mortality associated with weight loss of more than 5 kg, but only the older women showed significant results.Conclusion: This large-scale cohort study in Korea showed a relationship between weight loss and all-cause mortality in middle-aged and older individuals.

The Effects of Weight Change on the Dexamethasone Suppression Test in Depressed and Anorexic Patients

1986 ◽  
Vol 149 (6) ◽  
pp. 751-755 ◽  
Author(s):  
I. Schweitzer ◽  
K. P. Maguire ◽  
J. W. G. Tiller ◽  
A. H. Gee ◽  
L. C. Harrison ◽  
...  
Keyword(s):  
Weight Loss ◽  
Weight Change ◽  
Ideal Body Weight ◽  
Dexamethasone Suppression Test ◽  
Depressed Patients ◽  
Significant Difference ◽  
History Of ◽  
Suppression Test ◽  
Hpa Axis Functioning ◽  
Dexamethasone Suppression

Prior studies on weight change and hypothalmic-pituitary-adrenal (HPA) axis functioning are reviewed. Data on 58 depressed and eight anorexic patients is presented. No significant difference in the frequency of cortisol non-suppression in the dexamethasone suppression test (DST) was found between depressed patients with a history of weight loss and those without, nor between depressed patients who lost weight during their first week in hospital and those who did not. Mean weight loss of suppressors did not significantly differ from that of non-suppressors. Of 12 patients whose DST normalised during their stay in hospital, only four gained weight. Five anorexics who were non-suppressors were <70% of their ideal body weight (IBW), while three suppressor anorexics were ≧70% IBW. These results indicate that mild to moderate weight change is not a significant influence on DST response in depression.

Anti-prothrombin antibodies as a potential risk factor of recurrent venous thromboembolism

2004 ◽  
Vol 91 (02) ◽  
pp. 255-258 ◽  
Author(s):  
Ezio Zanon ◽  
Graziella Saggiorato ◽  
Roberto Ramon ◽  
Antonio Girolami ◽  
Antonio Pagnan ◽  
...  
Keyword(s):  
Risk Factor ◽  
Venous Thromboembolism ◽  
Antiphospholipid Antibodies ◽  
Potential Role ◽  
Clinical Presentation ◽  
Multivariate Logistic Regression Analysis ◽  
Entire Cohort ◽  
Recurrent Venous Thromboembolism ◽  
History Of

SummaryThe role of antiprothrombin (aPT) antibodies in the development of venous thromboembolism (VTE) is still uncertain. The aim of this study was to evaluate the potential role of aPT antibodies in the development of recurrent thromboembolism. Out of 236 consecutive symptomatic patients with an episode of acute VTE, antiphospholipid antibodies were found in 85 (36.0%), of whom 24 were carriers of aPT antibodies (10.2% of the entire cohort). A history of previous thromboembolism was identified in 56 patients (23.7%). The prevalence of previous thromboembolism was significantly higher in carriers than in non-carriers of antiphospholipid antibodies (OR=2.4; 95% CI, 1.3 to 4.4). Of the 24 patients with aPT antibodies, 12 had a history of previous thromboembolism. In a multivariate logistic regression analysis, in which the other categories of antiphospholipid antibodies were taken into account, as well as the patient’s age, sex, and the modality of clinical presentation, it was found that the presence of aPT antibodies was significantly associated with the prevalence of prior thromboembolism (OR=3.3; 95% CI, 1.3 to 8.6). Since aPT antibodies are more commonly identifiable in patients with multiple thrombotic episodes, they are a likely risk factor for recurrent thromboembolism.

P1871Bodyweight variability and atrial fibrillation development

2019 ◽  
Vol 40 (Supplement_1) ◽  
Author(s):  
H Lee ◽  
E K Choi ◽  
K D Han ◽  
S Oh
Keyword(s):  
Atrial Fibrillation ◽  
Weight Loss ◽  
Risk Factor ◽  
Multivariable Analysis ◽  
Previous History ◽  
Population Based ◽  
Incidence Rates ◽  
Normal Weight ◽  
Increased Risk ◽  
History Of

Abstract Background Bodyweight fluctuation is a risk factor for cardiovascular events and death. We investigated whether bodyweight variability is also a risk factor for atrial fibrillation (AF) development. Methods A nationwide population-based cohort of 8,091,401 adults from the Korean National Health Insurance Service database without previous history of AF and with at least 3 measurements of bodyweight over a 5-year period was followed up for incident AF. Intra-individual bodyweight variability was calculated using variability independent of mean, and high bodyweight variability was defined as the quartile with highest bodyweight variability (Q4) with Q1–3 as reference. Results During median 8.1 years of follow-up, AF was newly diagnosed in 158,347 (2.0%). Increasing bodyweight variability was associated with AF development after adjustment for baseline bodyweight, height, age, sex, lifestyle factors and comorbidities: each increase of 1-SD in bodyweight variability was associated with 5% increased risk of AF development (hazard ratio [HR] 1.05, 95% confidence interval [CI] 1.04–1.05), and subjects with highest bodyweight variability (Q4) showed 14% increased risk of AF development compared to those in the quartile with lowest bodyweight variability (HR 1.14, 95% CI 1.12–1.15). When the cohort was grouped by body mass index (BMI) into underweight, normal weight, overweight, obese (Figure 1A), subjects with high bodyweight variability showed a shallow U-shaped relationship of BMI with AF incidence, with the highest incidence rate of AF in the underweight group. On the other hand, subjects with reference bodyweight variability showed a proportional increase of AF incidence with BMI, with the highest AF incidence in the obese group. High bodyweight variability was significantly associated with AF development in all BMI groups except in the very obese (BMI≥30) in multivariable analysis, and this association was stronger in subjects with lower bodyweight. In underweight subjects, high bodyweight variability was associated with 16% increased risk of AF development (HR 1.16, 95% CI 1.08–1.24). Obese subjects with high bodyweight variability compared to those with reference variability showed lower crude AF incidence rates, but after multivariable analysis, AF risk was increased (obese stage I) or comparable (obese stage II). When the cohort was grouped by total bodyweight change (Figure 1B), subjects with high bodyweight variability showed higher AF incidence and elevated AF risk on multivariable analysis in all weight change groups. Subjects with overall weight loss (≥-5%) and high bodyweight variability showed the highest AF incidence and AF risk (HR 1.12, 95% CI 1.09–1.15). Figure 1 Conclusions Fluctuation in bodyweight was independently associated with higher risk of AF development. The association of high bodyweight variability with AF development was especially stronger in subjects with lower bodyweight, and in subjects with overall weight loss (≥-5%)

scholarly journals Does weight loss reduce the incidence of total knee and hip replacement for osteoarthritis?—A prospective cohort study among middle-aged and older adults with overweight or obesity

2021 ◽  
Author(s):  
Xingzhong Jin ◽  
Alice A. Gibson ◽  
Joanne Gale ◽  
Francisco Schneuer ◽  
Ding Ding ◽  
...  
Keyword(s):  
Older Adults ◽  
Weight Loss ◽  
Weight Gain ◽  
Weight Change ◽  
Hip Replacement ◽  
Baseline Body Mass Index ◽  
Middle Aged ◽  
Increased Risk ◽  
Total Knee ◽  
Overweight Or Obesity

Abstract Objective This study aims to investigate the association between weight change and total knee or hip replacement (TKR or THR) for OA among middle-aged and older adults with overweight or obesity. Method Weight data were collected in 2006–2009 and in 2010 from the 45 and Up Study—a population-based cohort aged ≥45 years in New South Wales, Australia. Participants were included if they had a baseline body mass index (BMI) ≥ 25 kg/m2 and no history of TKR or THR. Weight change was categorised into four groups: >7.5% loss; >5–7.5% loss; stable (≤5% change) and >5% gain. Hospital admission data were linked to identify TKR and THR for OA, and multivariable Cox regression was used to assess risk of TKR and THR. Results Of 23,916 participants, 2139 lost >7.5% weight, 1655 lost 5–7.5% weight, and 4430 gained >5% weight. Over 5.2 years, 1009 (4.2%) underwent TKR and 483 (2.0%) THR. Compared to weight-stable, weight loss of >7.5% was associated with reduced risk of TKR after adjusting for age, sex, BMI, socioeconomic and lifestyle factors (hazard ratio 0.69, 95%CI 0.54–0.87), but had no association with THR. Weight loss of 5–7.5% was not associated with altered risk of either TKR or THR. Weight gain was associated with increased risk of THR after adjusting for confounders, but not TKR. Conclusion This study suggests that a weight loss target >7.5% is required to reduce the risk of TKR in adults with overweight or obesity. Weight gain should be avoided as it increases the risk of THR.

scholarly journals Weight Change and Cardiometabolic Outcomes in Postpartum Women with History of Gestational Diabetes

Nutrients ◽  
2019 ◽  
Vol 11 (4) ◽  
pp. 922 ◽  
Author(s):  
Siew Lim ◽  
Vincent L. Versace ◽  
Sharleen O’Reilly ◽  
Edward Janus ◽  
James Dunbar
Keyword(s):  
Weight Loss ◽  
Weight Gain ◽  
Gestational Diabetes ◽  
Weight Change ◽  
Diabetes Prevention ◽  
Density Lipoprotein ◽  
The Other ◽  
Postpartum Women ◽  
Weight Loss Group ◽  
History Of

Weight gain after childbirth is a significant risk factor for type 2 diabetes (T2DM) development after gestational diabetes mellitus (GDM). The level of weight loss achieved in diabetes prevention programs for women after GDM is often low but its effects on the cardiometabolic risk are not known. In a secondary analysis of a diabetes prevention program in postpartum women with history of gestational diabetes, we evaluated the effect of weight change on the cardiometabolic outcomes at 1-year follow-up. Of the 284 women randomized to the intervention arm, 206 with the final outcome measurements were included in the analyses. Participants were categorized into weight loss (>2 kg, n = 74), weight stable (±2 kg, n = 74) or weight gain (>2 kg, n = 58) groups. The weight loss group had significantly greater decrease in glycated hemoglobin (HbA1c) than the weight gain group (−0.1 + 0.4% vs. 0 + 0.4%, p = 0.049). The weight loss group had significantly greater decrease in total cholesterol and low-density lipoprotein cholesterol cholesterol than the other two groups (p < 0.05). The weight gain group had significantly greater increase in triglyceride and triglyceride:high-density lipoprotein cholesterol ratio compare with the other groups (p < 0.01). Overall, a small amount of weight loss and prevention of further weight gain was beneficial to the cardiometabolic outcomes of postpartum women after GDM.

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