Project description:ObjectiveTo examine whether the adverse effect of obesity on psychological well-being can be explained by weight discrimination.MethodsThe study sample included 5056 older (≥50 y) men and women living in England and participating in the English Longitudinal Study of Ageing. Participants reported experiences of weight discrimination in everyday life and completed measures of quality of life (CASP-19 scale), life satisfaction (Satisfaction With Life Scale), and depressive symptoms (eight-item CES-D scale). Height and weight were objectively measured, with obesity defined as BMI ≥30 kg/m2 . Mediation analyses were used to test the role of perceived weight discrimination in the relationship between obesity and each psychological factor.ResultsObesity, weight discrimination, and psychological well-being were all significantly inter-related. Mediation models revealed significant indirect effects of obesity through perceived weight discrimination on quality of life (β = -0.072, SE = 0.008), life satisfaction (β = -0.038, SE = 0.008), and depressive symptoms (β = 0.057, SE = 0.008), with perceived weight discrimination explaining approximately 40% (range: 39.5-44.1%) of the total association between obesity and psychological well-being.ConclusionsPerceived weight discrimination explains a substantial proportion of the association between obesity and psychological well-being in English older adults. Efforts to reduce weight stigma in society could help to reduce the psychological burden of obesity.
Project description:BackgroundThe body mass index (BMI) is closely related to mortality risk, and energy intake (EI) is essential for maintaining energy balance in weight control. However, self-reported EI has been shown to lead to a systematic underestimation. Total energy expenditure measured using the doubly labelled water (DLW) method is considered an objective biomarker of EI and the gold standard for its estimation in individuals with stable body weight. We aimed to examine the association between DLW-calibrated EI and BMI on overall mortality risk in older adults.MethodsA prospective cohort study was performed using data of 8051 (4267 women and 3784 men) Japanese older adults from the Kyoto-Kameoka Study in Japan. Calibrated EI was calculated from the estimated EI using a food frequency questionnaire and equation developed based on DLW. Participants were classified by quartiles based on their EI stratified by sex. BMI was calculated using self-reported height and body weight. Mortality data were collected between 30 July 2011 and 30 November 2016. Statistical analysis was performed using the multivariable-adjusted Cox proportional hazard model with a restricted cubic spline.ResultsThe 8051 participants' mean (standard deviation) age and BMI were 73.5 (6.1) years and 22.6 (3.0) kg/m2 , respectively. The mean (standard deviation) EI with and without calibration was 1909 (145) kcal/day and 1569 (358) kcal/day in women and 2383 (160) kcal/day and 1980 (515) kcal/day in men, respectively. During the median 4.75 years of follow-up (36 552 person-years), 661 deaths were recorded. In both women (hazard ratio [HR], 0.63; 95% confidence interval [CI] [0.41, 0.98]) and men (HR, 0.62; 95% CI [0.44, 0.87]), after adjusting for confounders, the top quartile as compared with the bottom calibrated EI quartile showed a negative association with risk of all-cause mortality. The lowest HR for all-cause mortality was 1900-2000 kcal/day in women and 2400-2600 kcal/day in men. However, after adjusting for BMI, no significant association was observed between the calibrated EI and the risk of death. These associations could not be confirmed in the uncalibrated EI. The HR for mortality was minimal at a BMI of 23 kg/m2 in both men and women, with or without adjustment for the calibrated EI.ConclusionsCalibrated EI was negatively associated with mortality risk but not uncalibrated EI. This may be mediated by an increase in body weight over time. Caution is required when interpreting the association between EI and mortality risk without adjusting for self-reported measurement errors and outcomes.
Project description:ObjectiveTo estimate the daily dietary energy intake for me to maintain a constant body weight. How hard can it be?DesignVery introspective study.SettingAt home. In lockdown. (Except every Tuesday afternoon and Saturday morning, when I went for a run.) PARTICIPANTS: Me. n=1.Main outcome measuresMy weight, measured each day.ResultsSleeping, I shed about a kilogram each night (1.07 (SD 0.25) kg). Running 5 km, I shed about half a kilogram (0.57 (SD 0.15) kg). My daily equilibrium energy intake is about 10 000 kJ (10 286 (SD 201) kJ). Every kJ above (or below) 10 000 kJ adds (or subtracts) about 40 mg (35.4 (SD 3.2) mg).ConclusionsBody weight data show persistent variability, even when the screws of control are tightened and tightened.
Project description:PurposeThe objective of this investigation is to study how excess body weight influences the energy cost of walking (Cw) and determine whether overweight and obese older adults self-select stride frequency to minimize Cw.MethodsUsing body mass index (BMI), men and women between the ages of 65 and 80 yr were separated into normal weight (NW, BMI ≤24.9 kg·m(-2), n = 13) and overweight-obese groups (OWOB, BMI ≥25.0 kg·m(-2), n = 13). Subjects walked at 0.83 m·s on an instrumented treadmill that recorded gait parameters and completed three 6-min walking trials; at a preferred stride frequency (PSF), at +10% PSF, and at -10% PSF. Cw was determined by indirect calorimetry. Repeated-measures ANOVA was used to compare groups, and associations were tested with Pearson correlations, α = 0.05.ResultsOWOB had 62% greater absolute Cw (301 ± 108 vs 186 ± 104 J·m, P < 0.001) and 20% greater relative Cw(kg) (3.48 ± 0.95 vs 2.91 ± 0.94 J·kg(-1)·m(-1), P = 0.046) than NW. Although PSF was not different between OWOB and NW (P = 0.626), Cw was 8% greater in OWOB at +10% PSF (P < 0.001). At PSF, OWOB spent less time in single-limb support (33.1% ± 1.5% vs. 34.9% ± 1.6 % gait cycle, P = 0.021) and more time in double-limb support (17.5% ± 1.6% vs 15.4% ± 1.4% gait cycle, P = 0.026) than NW. In OWOB, at PSF, Cw was correlated to impulse (r = -0.57, P = 0.027) and stride frequency (r = 0.51, P = 0.046).ConclusionsExcess body weight is associated with greater Cw in older adults, possibly contributing to reduced mobility in overweight and obese older persons.
Project description:This research aimed to replicate a previous UK-based finding that low craving control predicts increased intake of high energy density foods (HED) during the COVID-19 lockdown, and extend this finding to adults living in Victoria, Australia. The study also assessed whether acceptance coping moderates the relationship between craving control and increased HED food intake, and examined the associations between trait disinhibition, perceived stress and changes to HED food intake. An online survey completed by 124 adults living in Victoria, Australia (total eligible n = 147; 38.5 ± 12.9 years) during the COVID-19 lockdown showed that 49% of participants reported increased overall food intake, and 21-29% reported increased intake of HED sweet and savoury foods during the COVID-19 lockdown. Of the eating behaviour traits assessed, low craving control was the only significant predictor of increased HED sweet and savoury food intake (cognitive restraint, disinhibition and emotional eating were non-significant predictors). Perceived stress was associated with reported increases in overall savoury and sweet snack intake, but was not significantly associated with changes to specific HED food groups (sweet and savoury). In this sample, acceptance coping did not significantly moderate the relationship between craving control and increased HED food intake. Based on these replicated findings, further trials should now consider interventions targeting craving control to promote controlled food intake in individuals at-risk of weight gain during the current COVID-19 and future potential lockdowns.
Project description:BackgroundIndividuals with overweight or obesity commonly underreport energy intake (EI), but it is unknown if the tendency to underreport persists in formerly obese individuals who lose significant weight and maintain their weight loss over long periods of time.ObjectiveAssess the accuracy of self-reported EI in successful weight loss maintainers (WLM) compared with controls of normal body weight (NC) and controls with overweight/obesity (OC).MethodsParticipants for this case-controlled study were recruited in 3 groups: WLM [n = 26, BMI (in kg/m2) 24.1 ± 2.3; maintaining ≥13.6 kg weight loss for ≥1 y], NC (n = 33, BMI 22.7 ± 1.9; similar to current BMI of WLM), and OC (n = 32, BMI 34.0 ± 4.6; similar to pre-weight loss BMI of WLM). Total daily energy expenditure (TDEE) was measured over 7 d using the doubly labeled water (DLW) method, and self-reported EI was concurrently measured from 3-d diet diaries. DLW TDEE and self-reported EI were compared to determine accuracy of self-reported EI.ResultsWLM underreported EI (median, interquartile range) (-605, -915 to -314 kcal/d) to a greater degree than NC (-308, -471 to -68 kcal/d; P < 0.01) but not more than OC (-310, -970 to 18 kcal/d; P = 0.21). WLM also showed a greater degree of relative underreporting (-25.3%, -32.9% to -12.5%) compared with NC (-14.3%, -19.6% to -3.1%; P = 0.02) but not OC (-11.2%, -34.1% to -0.7%; P = 0.16). A greater proportion of WLM was classified as underreporters (30.8%) than NC (9.1%; P = 0.05) but not OC (28.1%; P = 1.00).ConclusionsWLM underreported EI in both absolute and relative terms to a greater extent than NC but not OC. These findings call into question the accuracy of self-reported EI in WLM published in previous studies and align with recent data suggesting that WLM rely less on chronic EI restriction and more on high levels of physical activity to maintain weight loss. This trial was registered at clinicaltrials.gov as NCT03422380.
Project description:COVID-19 measures which reduce interpersonal contact may be effective in containing the transmission, but their impacts on peoples' well-being and daily lives overtime remain unclear. Older adults are more vulnerable to both the virus and social isolation. It is therefore imperative to understand how they were affected during this period. Major concerns arising from the pandemic cover the aspects of mental health, healthcare utilisation and individual behavioural changes. Complementing the existing before-and-after analyses, we explore the impacts of easing and re-introducing COVID-19 measures by using a time-series data in England. The data was collected between May and November 2020 from the monthly surveys of the Platform for Research Online to Investigate Genetics and Cognition in Aging (PROTECT). Chi-squared analysis and interrupted time-series analysis were conducted to examine impacts of easing and re-introducing COVID-19 measures. Overall, mental health improves overtime but at a decreasing rate. The use of telephone/video consultations with a doctor or health professional presented a decreasing trend during the pandemic, whilst that of in-person consultation was increasing overtime. We observed significant variations in the time trends of mental health measures, healthcare utilisation and physical activity following the ease but not the re-introduction of COVID-19 measures. Future research is required to understand if these asymmetric impacts were driven by adaption of the people or stringency of the measures.Supplementary informationThe online version contains supplementary material available at 10.1007/s10433-022-00741-y.
Project description:BACKGROUND:Alternate-day fasting (ADF) involves a 'famine day' (25% energy intake) and a 'feast day' (ad libitum intake). This secondary analysis examined changes in beverage intake in relation to energy intake and body weight during 12 months of ADF versus daily calorie restriction (CR). METHODS:Obese subjects (n = 100 enrolled, n = 69 completers) were randomized to one of three groups for 12 months: (a) ADF; (b) CR; or (c) control. RESULTS:At baseline, intakes of diet soda, caffeinated beverages, sugar-sweetened soda, alcohol, juice, and milk were similar between groups. There were no statistically significant changes in the intake of these beverages by month 6 or 12 between ADF (feast or famine day), CR, or control groups. Beverage intake was not related to energy intake or body weight at month 6 or 12 in any group. CONCLUSION:These pilot findings suggest that intermittent fasting does not impact beverage intake in a way that affects energy intake or body weight.
Project description:Both aging and obesity are associated with increased levels of pro-inflammatory metabolites, while weight reduction is associated with improvements in inflammatory status. However, few studies have explored the response of key inflammatory markers to the combined settings of weight reduction in an aging population. There are also few studies that have investigated the potential impact of diet composition on inflammatory marker responses. In the MEASUR-UP trial, we evaluated changes in baseline levels of inflammatory markers with post-study levels for a traditional weight loss control group versus a group with generous, balanced protein intake. In this 6-month randomized controlled trial (RCT), older (≥60 years) adults with obesity (BMI ≥30 kg/m2) and Short Physical Performance Battery (SPPB) score of 4-10 were randomly assigned to either a traditional weight loss regimen, (Control, n = 14) or one with higher protein intake (≥30 g) at each meal (Protein, n = 25). All participants were prescribed a hypo-caloric diet and attended weekly support and education groups and weigh-ins. Protein participants consumed ≥30 g of high-quality protein/meal, including lean and extra lean beef provided to them for two of the three meals per day. Protein intakes were 0.8 and 1.2 g/kg/day for Control and Protein, respectively. Adiponectin, leptin, C-reactive protein (hs-CRP), tumor necrosis factor-α (TNF-α), interleukin-1 (IL-1), IL-6, IL-8, serum amyloid A (SAA), vascular cell adhesion molecule-1 (VCAM-1), intercellular adhesion molecule-1 (ICAM-1), and glycated serum protein (GSP) levels were measured at 0 and 6-month time points. At the 6-month endpoint, there was significant weight loss and decrease in BMI in both the Control (-4.8 ± 8.2 kg; -2.3 ± 2.4 kg/m2; p = 0.05) and Protein (-8.7 ± 7.4 kg; -2.9 ± 2.3 kg/m2; p < 0.0001) groups. SPPB scores improved in both arms, with a superior functional response in Protein (p < 0.05). Body fat (%) at baseline was positively correlated with leptin, hs-CRP, VCAM-1, ICAM-1, and GSP. Several markers of inflammation responded to the Protein group: leptin (p < 0.001), hs-CRP (p < 0.01), and ICAM-1 (p < 0.01) were decreased and adiponectin increased (p < 0.01). There were no significant changes in any inflammatory markers in the Control arm. In the between group comparison, only adiponectin trended towards a group difference (more improvement in Protein; p < 0.07). Our findings in the MEASUR-UP trial show that a weight loss diet with enhanced protein intake is comparable to an adequate protein diet in terms of weight loss success and that it can lead to improvements in inflammatory status, specifically for adiponectin, leptin, hs-CRP, and ICAM-1. These findings are important given current recommendations for higher protein intakes in older adults and justify the additional study of the inflammatory impact of an enhanced protein diet. (ClinicalTrials.gov identifier: NCT01715753).
Project description:The aim of this study was to evaluate the effects of non-nutritive sweeteners (NNS) consumption on energy intake, body weight and postprandial glycemia in healthy and with altered glycemic response rats. Animals on normal diet (ND) or high-fat diet (HFD) were divided to receive NNS (sucralose, aspartame, stevia, rebaudioside A) or nutritive sweeteners (glucose, sucrose) for 8 weeks. The NNS were administered at doses equivalent to the human acceptable daily intake (ADI). A test using rapidly digestible starch was performed before and after treatments to estimate glycemic response. No effects of NNS consumption were observed on energy intake or body weight. Sucrose provoked an increased fluid consumption, however, energy intake, and weight gain were not altered. In ND, no effects of NNS on glycemic response were observed. In HFD, the glycemic response was increased after sucralose and stevia when only the final tolerance test was considered, however, after including the baseline test, these results were no longer significant compared to glucose. These findings provide further evidence suggesting that at the recommended doses, NNS do not alter feeding behavior, body weight or glycemic tolerance in healthy and with altered glycemic rats.