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BMI and all-cause mortality in older adults: A meta-analysis

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Abstract

Whether the association between body mass index (BMI) and all-cause mortality for older adults is the same as for younger adults is unclear. The objective was to determine the association between BMI and all-cause mortality risk in adults ≥65 y of age. A 2-stage random-effects meta-analysis was performed of studies published from 1990 to 2013 that reported the RRs of all-cause mortality for community-based adults aged ≥65 y. Thirty-two studies met the inclusion criteria; these studies included 197,940 individuals with an average follow-up of 12 y. With the use of a BMI (in kg/m(2)) of 23.0-23.9 as the reference, there was a 12% greater risk of mortality for a BMI range of 21.0-21.9 and a 19% greater risk for a range of 20.0-20.9 [BMI of 21.0-21.9; HR (95% CI): 1.12 (1.10, 1.13); BMI of 20.0-20.9; HR (95% CI): 1.19 (1.17, 1.22)]. Mortality risk began to increase for BMI >33.0 [BMI of 33.0-33.9; HR (95% CI): 1.08 (1.00, 1.15)]. Self-reported anthropometric measurements, adjustment for intermediary factors, and exclusion of early deaths or preexisting disease did not markedly alter the associations, although there was a slight attenuation of the association in never-smokers. For older populations, being overweight was not found to be associated with an increased risk of mortality; however, there was an increased risk for those at the lower end of the recommended BMI range for adults. Because the risk of mortality increased in older people with a BMI <23.0, it would seem appropriate to monitor weight status in this group to address any modifiable causes of weight loss promptly with due consideration of individual comorbidities.

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... kg/m 2 is not necessarily appropriate to indicate healthy weight and an optimal nutritional state in the elderly. Older adults (65 years or older) have a different body composition (such as lowered muscle mass and increased fat mass) than younger adults, and their mortality risk may even increase when BMI decreases under 23 kg/m 2 (Javed et al., 2020;Winter et al., 2014). Finnish Current Care Guidelines recommend a BMI range 23.0-29.9 ...
... Reductions in BMI can be more detrimental for health than increases in BMI among older adults, while remaining at a stable BMI is probably the most optimal, regardless of baseline BMI (Alharbi et al., 2021). Additionally, changes in body composition (such as reductions in lean body mass and increases in fat mass) and in functional capability, together with changes in BMI, become more important while aging (Suominen et al., 2014;Winter et al., 2014). These should also be kept in mind while reflecting on inequalities in BMI trajectories in older age. ...
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Obesity is a major and growing public health problem in Finland and worldwide. The burden of obesity is unequally distributed between socioeconomic groups, however. In Finland, socioeconomic differences in obesity have persisted over decades. To reduce socioeconomic inequalities in obesity, understanding the trajectories behind these differences is crucial. This study aimed to examine the associations of childhood disadvantage (Sub-study I), changes in adult economic circumstances (Sub-study II), and intergenerational social mobility (Sub-study III) with body mass index (BMI) trajectories in a Finnish occupational cohort. I derived the data from the Helsinki Health Study cohort, which consists of four questionnaire surveys. In Phase 1 (2000–2002), the participants were 40–60-year-old employees of the City of Helsinki, Finland (n=8,960, response rate 67%). The follow-up surveys were conducted in 2007 (n=7,332), 2012 (n=6,809), and 2017 (n=6,832) (response rates 83%, 79%, and 82%, correspondingly). Childhood disadvantage comprised the retrospective measures of parental education and seven types of childhood adversity. I measured changes in adult economic circumstances by household income and experienced economic difficulties (Phases 1–4). Intergenerational social mobility was based on parental and participant’s own education. I calculated BMI from self-reported height and weight (Phases 1–4 and at the age of 25) and analysed the BMI trajectories using group-based trajectory modelling and mixed-effects linear regression. I examined changes in economic circumstances within the BMI trajectory groups using sequence analysis. Other statistical methods included multinomial logistic regression and chi-squared tests. For both genders, low parental education increased the odds of belonging to the trajectory groups of developing overweight and obesity. Experiencing peer bullying and accumulation of adversities in childhood among women, and parental alcohol problems among men, increased the odds of belonging to the trajectory groups of developing obesity. Economic disadvantage was constantly more common in the higher BMI trajectory groups (i.e., groups of overweight and obesity) during Phases 1–4. Differences in household income increased over time between the BMI trajectory groups, and changes in experienced economic difficulties were more common in the higher BMI trajectory groups. Intergenerationally stable low socioeconomic position, but also downward social mobility among men, were associated with the highest BMI trajectory levels. However, birth cohort impacted how upward and downward social mobility were associated with the BMI trajectories. The lowest BMI trajectory levels were found for the groups of stable high socioeconomic position among both genders and birth cohorts. The findings of this study indicate that socioeconomic disadvantage both in childhood and adulthood may predispose an individual to unhealthy weight gain over adulthood. Since socioeconomic disadvantage remains intergenerationally inherited in Finland, obesity prevention should be enhanced among people with unfavourable socioeconomic backgrounds. Additionally, targeted workplace interventions might reduce the existing socioeconomic gradient in obesity among employees, given that substantial increases in BMI were observed during working age. Nevertheless, to tackle socioeconomic inequalities in weight gain more broadly, several societal-level and multidisciplinary policies and actions are highly needed.
... While there is extensive evidence that obesity is associated with an increased risk of cardiovascular disease, cancer, and mortality in younger and middle-aged adults [3], the relationship between obesity and mortality in older adults requires further research [2]. A meta-analysis by Flegal et al. [4] found that a body mass index (BMI) in the overweight range (25)(26)(27)(28)(29)(30) kg/m 2 ) was associated with a lower risk of all-cause mortality in older adults compared to those of a healthy weight (BMI between 18.5 kg/m 2 and <25 kg/m 2 ), while grade 1 obesity (BMI between 30 kg/m 2 and ≤35 kg/m 2 ) had a similar mortality risk to those in the healthy BMI category. BMI is a crude measure of body composition, and a BMI of ≥30 kg/m 2 could encompass a wide range of proportions of lean mass to fat mass. ...
... The associations observed in our study between BMI and all-cause mortality in older adults suggest that being overweight (but not obese) compared to a normal weight was associated with a decreased all-cause mortality risk. This aligns with meta-analyses on the BMI-mortality relationship [4,27], which reported reduced risks of allcause mortality in older adults classified as overweight compared to a normal BMI. Additionally, a recent scoping review of observational studies in a communitydwelling population aged 65 years or over reported a reduced risk of mortality for overweight status compared with normal weight status [28]. ...
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Objectives: The objectives of this study were to examine whether weight loss, weight status (based on body mass index [BMI] categories), and abdominal obesity (based on waist circumference [WC]) were associated with a 17-year mortality risk in community-dwelling older adults. Methods: Participants were 2,017 community-dwelling adults aged 65 years or above in the longitudinal Enquête de Santé Psychologique-Risques, Incidence et Traitement study. Self-reported weight loss was collected at baseline during face-to-face interviews. Bodyweight (kg), height (m), and WC (cm) were independently measured at the baseline. BMI was categorized as follows: underweight (BMI <18.5 kg/m2), normal weight (18.5-24.9 kg/m2), overweight (25-29.9 kg/m2), and obese (≥30 kg/m2). Abdominal obesity was defined by a WC of ≥102 cm in men and ≥88 cm in women. Adjusted Cox proportional hazards models were used to examine associations of weight loss, weight status, and abdominal obesity with all-cause mortality. Results: Over 17 years of follow-up (median 15.5 years), 812 participants died. Abdominal obesity compared to nonabdominal obesity was associated with a 49% increased mortality risk (95% confidence interval (CI): 1.22-1.83). However, being overweight (but not obese) was associated with a 20% decreased risk (95% CI: 0.66-0.97) compared to a normal BMI. Gender did not affect these associations. In the whole cohort, self-reported weight loss at baseline was not associated with an increased mortality risk after adjusting for health and lifestyle factors. However, in men, a baseline self-reported recent weight loss of >3 kg was associated with a 52% increase in mortality risk (95% CI: 1.05-2.18) in a fully adjusted model. Conclusion: In community-dwelling adults aged ≥65 years, abdominal obesity was strongly associated with increased mortality risk. Being overweight appeared, however, to be protective against mortality. Modest self-reported weight loss was not associated with all-cause mortality in community-dwelling older adults after adjusting for health and lifestyle factors. However, men reporting recent weight loss of more than 3 kg may be at increased risk. The findings of this study support the use of WC, rather than BMI, as a predictor of mortality risk in older adults.
... 2 Among these factors, nutrition can be modified to improve life expectancy and health, as well as preserve functional ability. 3 Underweight in older adults is associated with higher mortality [4][5][6][7][8][9][10] and is a condition of malnutrition itself. This may be due to age-related factors, such as sensory loss of taste and smell, decreased masticatory capacity, and digestive problems, 11 as well as changes in body composition, with reduced fat and fat-free mass. ...
... 22 However, few studies have evaluated the relationship between low muscle mass from CC and the risk of death in older adults, 21,[23][24][25][26] and studies with noninstitutionalized older adults in Brazil were not identified. In addition, a wide variation in the cutoff points have been adopted to estimate low muscle mass from CC 25,[27][28][29][30][31][32][33] and underweight according to BMI. [4][5][6][7][8][9][10] The hypothesis of the present study is that underweight (measured by BMI) and low muscle mass (measured by CC) are independent predictors of mortality in older adults. The aim was to investigate the association of underweight and low muscle reserve with mortality in older adults, comparing different cutoff points. ...
Article
Background:There is a wide variation in the cutoff points of body mass index (BMI) and calf circumference (CC) , and it is necessary to assess their adequacy in predicting mortality, especially in the older adults in the community. This study aimed to investigate the association of low muscle mass and underweight with mortality in older adults, comparing different cutoff points. Methods: This was a prospective study that included 796 older adults, not institutionalized, from a Brazilian city. Generalized additive models (GAMs) were used to identify cutoff points for CC and BMI, which were compared with values available in the literature. Survival analysis using Cox regression models was used to assess the independent association between these nutrition indicators and mortality. Results: Over the 9 years of follow-up, 197 deaths (24.7%) occurred. Cutoff points established for CC and BMI as predictors of mortality were, respectively, <34.5 cm and <24.5. In the adjusted Cox models, older adults with a BMI <18.5 showed a significant increase in the risk of death (hazard ratio [HR], 2.57; 95% CI, 1.23–5.35). Higher mortality was observed among older adults with CC <34.5 cm (HR, 1.72; 95% CI, 1.27–2.33) and CC <31 cm (HR, 2.11; 95% CI, 1.44–3.10). Conclusion: CC was an independent predictor of mortality, and the cutoff point identified by GAMs was higher than recommended by literature (31 cm). This study suggests a review of cutoff points for CC currently adopted to assess low muscle mass in older adults.
... WHR higher than 0.85 was assumed as an indicator of abdominal obesity in women as well, however, it was not used for men because of cultural and religious issues. Subjects with BMI < 23:5 were underweight and more than 30.9 were overweight/obese [23]. ...
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Background: Musculoskeletal pains (MSP) are the most common cause of long-term severe pain and physical disability among older adults. This study is aimed at determining the relationship between dietary diversity score (DDS) and MSP in Tehran's older adults. Methods: The study was a cross-sectional one that employed 213 participants with and without MSP complaints between May and October 2019 in Tehran, Iran. A 100 mm length visual analog scale questionnaire was used to assess pain along with a validated 147-item food frequency questionnaire for DDS evaluation. Statistical analyses included descriptive analysis and multiple linear regression with a significance level of p < 0.05. Results: 85% of the participants had a range of MSP with a low but insignificant DDS compared to individuals without pain (p = 0.12, 3.24 (±0.86) vs. 3.43 (±0.85), respectively). A significant association was observed among the quartiles of DDS that most of the subjects with MSP were in the lowest quartile relative to the highest one (p = 0.02). Moreover, the association between DDS and MSP remained significant in the adjusted model (OR = 0.28, 95%(CI) = 0.08 - 0.99). Conclusion: A high-quality diet is important. Our study showed that a higher dietary diversity might be associated with lower MSP in older adults. More robust interventional studies are thus warranted to confirm the results.
... Being underweight and having a decline in BMI in latelife have been associated with cognitive impairment and dementia [45]. Moreover, underweight status in older adults has been associated with higher mortality [46]. We hypothesized that in our study, individuals categorized as underweight and without anxio-depressive disorders may have worse physical health status with severe denutrition and cognitive impairment. ...
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Objective To examine the associations between BMI categories and subsequent 3-year cognitive decline among older adults, and to test whether physical activity modifies the associations. Methods Study sample included n = 1028 cognitively unimpaired older adults participating in the Étude sur la Santé des Aînés (ESA)-Services longitudinal study and followed 3 years later. Cognitive decline was defined as a decrease of > 3 points in MMSE scores between baseline and follow-up. BMI categories (normal weight (reference), underweight, overweight, obese) were derived from self-reported weight and height. Moderate to vigorous physical activity of ≥20 min (# of times per week) was self-reported. The presence of chronic disorders was ascertained from administrative and self-reported data. Logistic regression analyses were used to study the risk of cognitive decline associated with BMI categories stratified by weekly physical activity (≥140 min), the presence of metabolic, cardiovascular and anxio-depressive disorders. Results In the overall sample, there was no evidence that underweight, overweight, or obesity, as compared to normal weight, was associated with cognitive decline, after adjusting for sociodemographic, lifestyle factors, and comorbidities. Individuals with overweight reporting high physical activity had lower odds of cognitive decline (OR = 0.25, 95% CI = 0.07–0.89), whereas no association was observed in individuals with overweight reporting low physical activity (OR = 0.85, 95% CI = 0.41–1.75). Among participants with metabolic and cardiovascular disorders, individuals with overweight reporting high physical activity had lower odds of cognitive decline (OR = 0.09, 95% CI = 0.01–0.59 and OR = 0.03, 95% CI = 0.01–0.92 respectively), whereas no association was observed in those with low physical activity. Conclusion Physical activity modifies the association between overweight and cognitive decline in older adults overall, as in those with metabolic and cardiovascular disorders. Results highlight the importance of promoting and encouraging regular physical activity in older adults with overweight as prevention against cognitive decline.
... There was consistent evidence of increased incident CVD, but not cardiovascular or all-cause mortality amongst participants who met lifestyle recommendations or who had no underlying cardiometabolic complications. We suspect the protective effect of overweight in older adults or the impact of medical interventions to manage risk factors may explain why there was an increased risk of incident CVD, but not mortality in this BMI group, as described in previous studies [10]. ...
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Background Contested evidence suggests that obesity confers no risk to health in people who have a healthy lifestyle, particularly if there are no metabolic complications of obesity. The aim was to examine the association between adherence to lifestyle recommendations and the absence of metabolic complications on the incident or fatal cardiovascular disease and all-cause mortality across different categories of body mass index (BMI). Methods This contemporary prospective cohort study included 339,902 adults without cardiovascular disease at baseline, recruited between 2006 and 2010 from the UK Biobank and followed until 2018–2020. The main exposures were four healthy lifestyle behaviours: never smoker, alcohol intake ≤ 112g/ week, 150 min moderate physical activity or 75 min vigorous activity/week, ≥ 5 servings of fruit or vegetables/day, and we assessed these overall and across the BMI groups. Metabolic complications of excess adiposity were hypertension, diabetes and hyperlipidaemia, and we examined whether obesity was associated with increased risk in the absence of these complications. The outcomes were all-cause mortality, death from, and incident cardiovascular disease (CVD). Results Individuals who met four lifestyle recommendations but had excess weight had higher all-cause mortality; for BMI 30–34.9 kg/m ² , the hazard ratio (HR) was 1.42 (95% confidence interval 1.20 to 1.68), and for BMI ≥ 35 kg/m ² , HR was 2.17 (95% CI 1.71 to 2.76). The risk was lower, but still increased for people with no metabolic complications; for all-cause mortality, BMI 30–34.9 kg/m ² had an HR of 1.09 (95% CI 0.99 to 1.21), and BMI ≥ 35 kg/m ² had an HR of 1.44 (95% CI 1.19 to 1.74) for all-cause mortality. Similar patterns were found for incident and fatal CVD. Conclusions Meeting healthy lifestyle recommendations, or the absence of metabolic complications of obesity offsets some, but not all, of the risk of subsequent CVD, and premature mortality in people with overweight or obesity. Offering support to achieve and maintain a healthy weight and to adopt healthy behaviours are likely to be important components in effective preventative healthcare.
... Obesity is one of the most common alterations of nutritional status in older Hispanic people [1] and a disease now considered a global pandemic [2]. In older adult populations, it is associated with physical disability, morbidity, and mortality [3][4][5][6][7]. The pathophysiology of obesity is reflected in body composition [8], which in these cases is defined as an abnormal or excessive accumulation of fat, diagnosed by a body mass index (BMI) ≥ 30 kg/m 2 [9]. ...
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Background Predictive equations are the best option for assessing fat mass in clinical practice due to their low cost and practicality. However, several factors, such as age, excess adiposity, and ethnicity can compromise the accuracy of the equations reported to date in the literature. Objective To develop and validate two predictive equations for estimating fat mass: one based exclusively on anthropometric variables, the other combining anthropometric and bioelectrical impedance variables using the 4C model as the reference method. Subjects/Methods This is a cross-sectional study that included 386 Hispanic subjects aged ≥60 with excess adiposity. Fat mass and fat-free mass were measured by the 4C model as predictive variables. Age, sex, and certain anthropometric and bioelectrical impedance data were considered as potential predictor variables. To develop and to validate the equations, the multiple linear regression analysis, and cross-validation protocol were applied. Results Equation 1 included weight, sex, and BMI as predictor variables, while equation 2 considered sex, weight, height squared/resistance, and resistance as predictor variables. R² and RMSE values were ≥0.79 and ≤3.45, respectively, in both equations. The differences in estimates of fat mass by equations 1 and 2 were 0.34 kg and −0.25 kg, respectively, compared to the 4C model. This bias was not significant (p < 0.05). Conclusions The new predictive equations are reliable for estimating body composition and are interchangeable with the 4C model. Thus, they can be used in epidemiological and clinical studies, as well as in clinical practice, to estimate body composition in older Hispanic adults with excess adiposity.
... [107] Similarly, a more recent large meta-analysis of nearly 200 000 individuals aged 65 or older showed a U-shaped relationship between BMI and mortality, with the lowest risk seen in those with a BMI between 24.0 and 30.0 kg/m 2 and risk only began to increase when BMI exceeded 33 kg/m 2 in severe obesity. [108] A larger elderly cohort study showed the association between mortality and combined measurements of BMI and waist-to-hip ratio, even after adjusting for various factors. They found that central adiposity was associated with mortality, even amongst subjects with a normal BMI, [109] suggesting that the obesity paradox may at least partly result from failing to accurately account for central adiposity in some patients with 'normal BMI'. ...
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Age‐associated obesity and muscle atrophy (sarcopenia) are intimately connected and are reciprocally regulated by adipose tissue and skeletal muscle dysfunction. During ageing, adipose inflammation leads to the redistribution of fat to the intra‐abdominal area (visceral fat) and fatty infiltrations in skeletal muscles, resulting in decreased overall strength and functionality. Lipids and their derivatives accumulate both within and between muscle cells, inducing mitochondrial dysfunction, disturbing β‐oxidation of fatty acids, and enhancing reactive oxygen species (ROS) production, leading to lipotoxicity and insulin resistance, as well as enhanced secretion of some pro‐inflammatory cytokines. In turn, these muscle‐secreted cytokines may exacerbate adipose tissue atrophy, support chronic low‐grade inflammation, and establish a vicious cycle of local hyperlipidaemia, insulin resistance, and inflammation that spreads systemically, thus promoting the development of sarcopenic obesity (SO). We call this the metabaging cycle. Patients with SO show an increased risk of systemic insulin resistance, systemic inflammation, associated chronic diseases, and the subsequent progression to full‐blown sarcopenia and even cachexia. Meanwhile in many cardiometabolic diseases, the ostensibly protective effect of obesity in extremely elderly subjects, also known as the ‘obesity paradox’, could possibly be explained by our theory that many elderly subjects with normal body mass index might actually harbour SO to various degrees, before it progresses to full‐blown severe sarcopenia. Our review outlines current knowledge concerning the possible chain of causation between sarcopenia and obesity, proposes a solution to the obesity paradox, and the role of fat mass in ageing.
... kg·m −2 ). Such cut-offs were informed by a meta-analysis of 32 studies exploring BMI and mortality risk in older adults, which demonstrated that mortality risk increases when BMI was <23 kg·m −2 and above 33 kg·m −2 , compared with "healthyweight" BMI range of 23-33 kg·m −2 [30]. Participants were grouped for FFM as low FFM (<53.2 kg for men, <38.4 kg for women) and healthy FFM (≥53.2 kg for men, ≥38.4 kg for women), using gender-specific cut-off values of the 25th centile for FFM in a sample of 162 men and 183 women aged 65-74 years [31]. ...
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Proposed strategies for preventing protein deficiencies in older patients include increasing protein intake at breakfast. However, protein is highly satiating and the effects of very high protein intakes at breakfast on subsequent appetite and free-living energy intake (EI) in older adults are unclear. This study compared the acute effects of two breakfast drinks varying in protein and energy contents on appetite and free-living EI in healthy older adults using a randomized 2 × 2 crossover design. Participants (n = 48 (20 men, 28 women); mean ± SD age: 69 ± 3 years; BMI: 22.2 ± 2.0 kg·m−2; fat-free mass: 45.5 ± 8.0 kg) consumed two drinks for breakfast (high-protein (30.4 ± 5.3 g), low-energy (211.2 ± 37.1 kcal) content (HPLE) and very high-protein (61.8 ± 9.9 g), fed to energy requirements (428.0 ± 68.9 kcal) (VHPER)) one week apart. Appetite perceptions were assessed for 3 h post-drink and free-living EI was measured for the remainder of the day. Appetite was lower in VHPER than HPLE from 30 min onwards (p < 0.01). Free-living energy and protein intake did not differ between conditions (p = 0.814). However, 24 h EI (breakfast drink intake + free-living intake) was greater in VHPER than HPLE (1937 ± 568 kcal vs. 1705 ± 490 kcal; p = 0.001), as was 24 h protein intake (123.0 ± 26.0 g vs. 88.6 ± 20.9 g; p < 0.001). Consuming a very high-protein breakfast drink acutely suppressed appetite more than a low-energy, high-protein drink in older adults, though free-living EI was unaffected. The long-term effects of adopting such a breakfast strategy in older adults at high risk of energy and protein malnutrition warrants exploration.
... The BMI, calculated with real weight and height, was found to be 27.65 for men and 28 for women: a situation of overweight in both sexes but for older populations, being overweight was not found to be associated with an increased risk of mortality [36]. ...
Article
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WHO recommend to associate a proper dose of movement with healthy and balanced diet, also in elderly. Promoting healthy lifestyles and adopting healthy habits can lead to a successful aging. The Mediterranean diet model is considered the gold standard nutritional treatment in some Non Communicable Diseases and the evaluation of adherence to this diet becomes essential to study the lifestyle of the population in order to prevent the risk of onset of age-related chronic diseases. In order to implement appropriate interventions for successful aging and to prevent functional alterations affecting the people autonomy in Activities of Daily Living, the LIFestyle of the Elderly in Umbria Population Project (LIFEUP) was promoted in 2018, in Italy. 36 subjects were invited to fill out self-report questionnaires used to assess health status and quality of life (EuroQol), physical activity levels (IPAQ) and Mediterranean diet adherence (MED Diet Score). Anthropometric variables (height, BMI), body composition and functional capacities (through Senior Fitness Test battery) were studied. We observed a situation of overweight (average BMI=27.4) with fat mass=30.45% and low total body water 47.64%), with a medium adherence to the Mediterranean diet (Score=7.19). Furthermore, we noted a good health status perceived (71,14/100), and acceptable physical activity levels (36.55 MET/h/week), and good functional capacities (2 minutes steps average=86.73; chair stands average=14.09; 8-foot up and go test average=6.47 sec.), according to international guidelines and standard ranges for this age. This pilot study gave an overview of a small group of the elderly Umbrian population to implement prevention and health promotion plans among the elderly.
... Although we did not find in our study a direct association between BMI and mortality. Interestingly, a recent meta-analysis showed a 4-10% lower risk of mortality for participants in the overweight range, with a 21% increase in the risk of mortality for the obesity range [33]. In addition, low levels of PA represents a risk factor that contributes to many deaths via chronic non-communicable diseases (coronary heart disease, type 2 diabetes and breast and colon cancer) [34]. ...
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Background Research using objectively measured physical activity (PA) in older adults to assess relationship between PA levels and mortality is scarce. Objective To investigate associations between level of physical activity and mortality in older adults over a 4-year period. Methods The population-based cohort study was carried out including 554 older participants (mean age: 76.2 ± 8.05 years) using data from the SABE study (Health, well-being and aging). Levels of physical activity were measured using accelerometers and participants were divided into tertiles and then categorized into two groups: (I) low level of physical activity and (II) intermediate/high level of physical activity. The dependent variable was mortality between 2010 and 2014. Control variables included socio-demographic and clinical factors. Multiple regression analysis was used from a hierarchical model, grouping the variables into two blocks ordered according to the magnitude of their effect. Results Our results showed that mortality rate in participants with low level of physical activity was 20/1000 person/year and for those with intermediate/high levels of physical activity was 14/1000 person/year. In the adjusted model, by sociodemographic and clinical variables, those with low levels of physical activity presented a higher risk for mortality (OR = 2.79, 95%CI = 1.71–4.57) when compared to individuals with intermediate/high levels of physical activity. Conclusion Older adults with low levels of physical activity have a higher chance of mortality as compared to those with intermediate/high levels of physical activity, regardless of sociodemographic and clinical variables.
... BMI was calculated as weight (in kilograms) divided by square of height (in meters). Subjects were divided into different groups according to BMI and all-cause mortality risk [20]. In particular, three different groups were identified: augmented risk of mortality if BMI was <23, reference range if BMI was 23-30, and increased risk of mortality if BMI was >30. ...
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The global population aged over 60 will double by 2050. This pilot cross-sectional study aims at evaluating nutritional and oral health status and the prevalence of sarcopenia in older adults living in an Italian residential aged care facility. Thirty-two adults aged ≥ 65 years were included. Individual sociodemographic data and nutritional and oral health data were collected. For sarcopenia diagnosis, muscle mass, physical performance, muscle strength and anthropometric parameters were recorded. Participants underwent a nutritional screening and a dental examination. Mini Nutritional Assessment and masticatory mixing ability test were performed. The results showed that men recorded a hand strength significantly higher than that of women, 25.5 ± 7.2 Kg vs. 12.8 ± 5.9 Kg (p < 0.01), respectively. Gait speed test showed that only 20.8% of the participants had a speed of more than 0.8 m/s. A strong negative correlation between masticatory performance and the number of missing teeth was detected (r = −0.84, 95% C.I. [−0.92; −0.69], p < 0.01). Overall, a high percentage of institutionalized older adults were diagnosed as being sarcopenic. Poor oral health in older adults is a major general health problem as it may restrict both food selection and nutrient intake, representing a risk factor for sarcopenia, although longitudinal studies are needed to confirm this relationship.
... In able bodied people older than 65 years of age a BMI of ≥25-29.9 kg/m2 has been associated with lower risk of all-cause mortality [27,28]. To our knowledge this perspective has not been discussed in relation to people with SCI. ...
Article
Observational study To describe body mass index (BMI) during rehabilitation in people with a newly sustained spinal cord injury (SCI). Inpatient SCI rehabilitation in Denmark. Inpatients, >18 years, having sustained a SCI within the last 12 months at admission to primary rehabilitation, inclusive of various SCI etiology, neurological level, completeness of the lesion or mobility status. Measures of BMI were obtained at admission and discharge as part of standard care. At one SCI center measures of BMI were sampled at follow up 9.5 months after discharge as well. BMI was described by mean and standard deviation (SD). Paired t-test was used to test difference in BMI between admission and discharge. Repeated measures Analysis of Variance (ANOVA) was used for analyzing BMI deriving from three time points. Overall BMI was stable with no change (25.4 kg/m² at admission and 25.6 kg/m² at discharge) during rehabilitation at the two national centers. In participants with an American Spinal Injury Association (ASIA) Impairment Scale (AIS) D classification, BMI was higher during rehabilitation compared to the other groups and increased significantly (p = 0.008) from discharge to follow up. Overall BMI was stable but higher than recommended in people with SCI undergoing rehabilitation at the two national centers in Denmark. Participants with an AIS D SCI were obese according to SCI adjusted BMI and the World Health Organization (WHO) recommendations during rehabilitation and at follow up.
... A previous large meta-analysis, including individuals aged 65 and older, however, showed that the relationship between BMI and mortality is not linear but U-shaped. The lowest risk was found in subjects with a BMI between 24 and 30 kg/m 2 , while mortality risk increased in subjects with lower BMI as well as in those with BMI exceeding 33 kg/m 2 [3]. This U-shaped relationship between BMI and mortality should be also explored in the patient series included in the Martini et al. paper. ...
... Thus, underweight status seems more prevalent in the insomnia population than in the general Chinese population. Being underweight is associated with increased risk for medical disorders and mortality relative to the normal-weight category, especially when individuals suffer from severe physical illness [35][36][37]. For example, Dobner et al. [38] and Park et al. [39] found that underweight individuals were more vulnerable to infection and cardiovascular diseases. ...
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Previous studies on the association of insomnia with body mass index (BMI) have been controversial. Physiological hyperarousal, the key pathological mechanism of insomnia, may be an important reason for different findings. We explored whether insomnia with physiological hyperarousal measured by the multiple sleep latency test (MSLT) is associated with body-weight differences. A total of 185 normal sleepers and 440 insomniacs were included in this study. Insomnia was defined by standard diagnostic criteria with symptoms lasting ≥6 months. All subjects underwent one night of laboratory polysomnography followed by a standard MSLT. We used the median MSLT value (i.e., ≥14 min) to define physiological hyperarousal. BMI was based on measured height (cm) and weight (kg) during the subjects’ sleep laboratory visit. BMI > 25 kg/m2 was defined as overweight, while BMI < 18.5 kg/m2 was defined as underweight. After controlling for confounders, the odds of lower weight rather than overweight were significantly increased among insomnia patients with increased MSLT: insomnia with MSLT 14–17 min and MSLT > 17 min increased the odds of lower weight by approximately 89% (OR = 1.89, 95% CI 1.00–4.85) and 273% (OR = 3.73, 95% CI 1.51–9.22) compared with normal sleepers, respectively. In contrast, insomnia in patients with MSLT 11–14 min and 8–11 min was not different from normal sleepers in terms of body weight. Insomnia associated with physiological hyperarousal, the most severe phenotype of chronic insomnia, is associated with higher odds of lower weight and underweight compared with normal sleepers. This is a novel finding consistent with previous physiologic data and has significant clinical implications.
... Obesity rates continue to rise with obesity occurring in more than 41.1% of women in the USA in 2016 [1]. While obesity is most typically defined as body mass index (BMI) > 30 kg/m 2 , limitations in the use of BMI have been noted, including variation in associations with health outcomes by race/ancestry, physical activity, and age [2,3], as well as some reports finding no association between higher-risk categories (overweight and middle obesity) with mortality [4,5]. These conflicting reports have motivated several studies to examine whether differential phenotypes of obesity exist and whether examining BMI in isolation of additional metabolic health parameters is a sufficient metric of overall health. ...
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Background: Body mass index (BMI), a well-known risk factor for poor cardiovascular outcomes, is associated with differential DNA methylation (DNAm). Similarly, metabolic health has also been associated with changes in DNAm. It is unclear how overall metabolic health outside of BMI may modify the relationship between BMI and methylation profiles, and what consequences this may have on downstream cardiovascular disease. The purpose of this study was to identify cytosine-phosphate-guanine (CpG) sites at which the association between BMI and DNAm could be modified by overall metabolic health. Results: The discovery study population was derived from three Women's Health Initiative (WHI) ancillary studies (n = 3977) and two Atherosclerosis Risk in Communities (ARIC) ancillary studies (n = 3520). Findings were validated in the Multi-Ethnic Study of Atherosclerosis (MESA) cohort (n = 1200). Generalized linear models regressed methylation β values on the interaction between BMI and metabolic health Z score (BMI × MHZ) adjusted for BMI, MHZ, cell composition, chip number and location, study characteristics, top three ancestry principal components, smoking, age, ethnicity (WHI), and sex (ARIC). Among the 429,566 sites examined, differential associations between BMI × MHZ and DNAm were identified at 22 CpG sites (FDR q < 0.05), with one site replicated in MESA (cg18989722, in the TRAPPC9 gene). Three of the 22 sites were associated with incident coronary heart disease (CHD) in WHI. For each 0.01 unit increase in DNAm β value, the risk of incident CHD increased by 9% in one site and decreased by 6-10% in two sites over 25 years. Conclusions: Differential associations between DNAm and BMI by MHZ were identified at 22 sites, one of which was validated (cg18989722) and three of which were predictive of incident CHD. These sites are located in several genes related to NF-kappa-B signaling, suggesting a potential role for inflammation between DNA methylation and BMI-associated metabolic health.
... Clinical characteristics included obesity (defined as having a body mass index > 30 kg/m 2 ), malnutrition (defined as having a body mass index < 23 kg/m 2 ) [43], smoking status (smoking versus not smoking), alcohol consumption (consuming alcohol versus not consuming), and the number of general medical conditions (e.g., cardiovascular disorders). ...
... These findings are consistent with the literature, where a normal BMI (18.5 -24.9 Kg/ m 2 ) is associated with reduced mortality compared to the BMI values in the overweight and obese spectrum [55][56][57][58]. Alternatively, in unselected older adults, BMI level above normal have been associated with reduced mortality [59][60][61][62]. The optimal BMI for older adults is not known, optimal BMI level between 20 and 29.9 Kg/ m 2 have been described [61]. ...
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Background: To compare the prevalence of healthy aging among adults age 70 and older from 5 European countries recruited for the DO-HEALTH clinical trial. Participants were selected for absence of prior major health events. Methods: Cross-sectional analysis of DO-HEALTH baseline data. All 2,157 participants (mean age 74.9, SD 4.4; 61.7% women) were included and 2,123 had data for all domains of the healthy aging status (HA) definition. HA was assessed based on the Nurses` Health Study (NHS) definition requiring four domains: no major chronic diseases, no disabilities, no cognitive impairment (Montreal Cognitive Assessment, MoCA ≥25), no mental health limitation (GDS-5 <2, and no diagnosis of depression). Association between HA and age, BMI, gender, and physical function (sit-to-stand, gait speed, grip strength) was assessed by multivariate logistic regression analyses adjusting for center. Results: Overall, 41.8% of DO-HEALTH participants were healthy agers with significant variability by country: Austria (Innsbruck) 58.3%, Switzerland (Zurich, Basel, Geneva) 51.2%, Germany (Berlin) 37.6%, France (Toulouse) 36.7% and Portugal (Coimbra) 8.8% (p <0.0001). Differences in prevalence by country persisted after adjustment for age. In the multivariate model, younger age (OR = 0.95, 95% CI 0.93 to 0.98), female gender (OR = 1.36, 95% CI 1.03 to 1.81), lower BMI (OR = 0.94, 95% CI 0.91 to 0.96), faster gait speed (OR = 4.70, 95% CI 2.68 to 8.25) and faster performance in sit-to-stand test (OR = 0.90, 95% CI 0.87 to 0.93) were independently and significantly associated with HA. Conclusions: Despite the same inclusion and exclusion criteria preselecting relatively healthy adults age 70 years and older, HA prevalence in DO-HEALTH varied significantly between countries and was highest in participants from Austria and Switzerland, lowest in participants from Portugal. Independent of country, younger age, female gender, lower BMI and better physical function were associated with HA. Trial registration: DO-HEALTH was registered under the protocol NCT01745263 at the International Trials Registry ( clinicaltrials.gov ), and under the protocol number 2012-001249-41 at the Registration at the European Community Clinical Trial System (EudraCT).
... IBWs are often used when determining protein needs. IBW was calculated by adjusting each participant's actual weight (kg) to the nearest weight that would give the participant a body mass index (BMI) between 22 and 27 kg/m 2 , which is the BMI range associated with lower mortality in older adults [14,15]. The average intake was compared to the current recommended dietary allowance (RDA) of 0.8 g/kg for adults and the optimal protein intake of 1.2 g/kg, which has been proposed in the literature to improve health outcomes in older adults with acute or chronic diseases [16,17]. ...
Article
Persistent malnutrition after COVID-19 infection may worsen outcomes, including delayed recovery and increased risk of rehospitalization. This study aimed to determine dietary intakes and nutrient distribution patterns after acute COVID-19 illness. Findings were also compared to national standards for intake of energy, protein, fruit, and vegetables, as well as protein intake distribution recommendations. Participants (≥18 years old, n = 92) were enrolled after baseline visit at the Post-COVID Recovery Clinic. The broad screening battery included nutritional assessment and 24-h dietary recall. Participants were, on average, 53 years old, 63% female, 69% non-Hispanic White, and 59% obese/morbidly obese. Participants at risk for malnutrition (48%) experienced significantly greater symptoms, such as gastric intestinal issues, loss of smell, loss of taste, or shortness of breath; in addition, they consumed significantly fewer calories. Most participants did not meet recommendations for fruit or vegetables. Less than 39% met the 1.2 g/kg/day proposed optimal protein intake for recovery from illness. Protein distribution throughout the day was skewed; only 3% met the recommendation at all meals, while over 30% never met the threshold at any meal. Our findings highlight the need for nutritional education and support for patients to account for lingering symptoms and optimize recovery after COVID-19 infection.
... On the other hand, evidence is consistent with our finding of lower handgrip strength associated to aging 14 . BMI is a valuable measure to assess all-cause mortality risk in older adults 15 . However, one concern regarding BMI as a predictor of overall mortality is the inability to discriminate among type and distribution of body tissues. ...
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Prostate cancer and its treatment may induce muscle wasting. Body composition and muscle functionality are rarely assessed in patients with prostate cancer from developing countries due to the limited availability of high-quality equipment for routine diagnosis. This cross-sectional study evaluated the association between several simplistic techniques for assessing muscle mass and function with a more complex standard of reference for muscle wasting among Mexican men with prostate cancer. Muscle wasting was highly prevalent, yet it was presumably associated with aging rather than cancer and its treatment itself. The restricted availability of specifc equipment in clinical settings with technological limitations supports using unsophisticated techniques as surrogate measurements for muscle wasting. The left-arm handgrip dynamometry displayed the highest correlation with the standard of reference and exhibited an acceptable predicted probability for muscle estimation. Combining several simplistic techniques may be preferable. We also developed and internally validated a manageable model that helps to identify elderly patients with prostate cancer at risk of muscle depletion and impairment. These fndings promote the early recognition and treatment of muscle wasting alterations occurring among older adults with prostate cancer.
... In addition, 42.1% were classified as overweight and 42.1% as obese. Growing evidence suggests that, in older individuals, a BMI between 25 and 30 that is defined as overweight may be a positive factor because it is associated with a longer life expectancy and especially with a longer disability-free life expectancy [51,52]. However, it should be emphasized that the BMI is a controversial measure as experts do not agree on its usefulness in predicting life expectancy in older adults [53]. ...
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Among older adults living in long-term nursing homes (LTNHs), maintaining an adequate functional status and independence is a challenge. Whilst a poor nutritional status is a potential risk factor for a decreased function in this population, its role is not fully understood. Here, using a transversal multicenter study of 105 older adults living in 13 LTNHs, we analyzed the associations between nutritional status, as measured by the Mini Nutritional Assessment (MNA), and the parameters of functional status, physical performance, physical activity, and frailty as well as comorbidity and body composition. The MNA scores were positively correlated with the Barthel Index, handgrip strength, Short Physical Performance Battery (SPPB) scores, absolute muscle power, and Assessment of Physical Activity in Frail Older People (APAFOP) scores and were negatively correlated with dynamic balance and frailty. In a multiple linear regression model controlling for gender and age, the APAFOP score (β = 0.386), BMI (β = 0.301), and Barthel Index (β = 0.220) explained 31% of the variance in the MNA score. Given the observed close relationship between the MNA score and functional status, physical performance and activity, and frailty, interventions should jointly target improvements in both the nutritional status and functional status of LTNH residents. Strategies designed and implemented by interdisciplinary professional teams may be the most successful in improving these parameters to lead to better health and quality of life.
... Eine Gewichtsabnahme, selbst eine intendierte, birgt in sich die Gefahr, anteilig mehr Muskel-als Fettmasse zu verlieren und somit das Risiko einer altersassoziierten Kraft-und Mobilitätsreduktion zusätzlich zu erhöhen. Insbesondere in der Hochaltrigkeit scheint ein höheres Gewicht im Bereich zwischen 25 und 35 kg/m 2 mit einem verbesserten Überleben verbunden zu sein [24]. ...
Article
In persons beyond age 70 a decrease of muscle mass and an increase of fat mass are regularly observed. These changes of body composition constitute a relevant predisposition for the imminent loss of functionality and autonomy in older age. In this context adequate nutrition and the prevention of malnutrition play an essential role. As the older population is extremely heterogeneous with regard to the velocity and extent of aging processes and also with regard to comorbidities, recommendations for adequate nutrition have to be individualized. Even voluntary loss of weight may be critical as it may accelerate the development of sarcopenia. As a general rule periods of fasting should be avoided. This is especially true with regard to inadequate caloric intake in the course of acute and chronic diseases. Therefore, weight measurements should be performed regularly in older persons, which would allow early diagnosis and treatment of malnutrition. In comparison to younger adults a higher protein intake of 1.0 g/kg bodyweight is recommended for older persons, as this may slow their decline of muscle mass and muscle function. If sarcopenia is already present, the recommended protein intake is raised towards 1.2 g/kg bodyweight. While restrictive diets may be detrimental in older persons, healthy diets like the Mediterranean diet may support the preservation of muscular and cognitive function.
... Obesity prevalence increases year by year and has become the number one lifestyle-related risk factor for premature death (5). Several studies have demonstrated that obesity increases the risk of all-cause mortality (35)(36)(37)(38)(39). ...
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Background To explore the relationship between weight-adjusted-waist index (WWI) and the risk of all-cause mortality in one urban community-dwelling population in China. Methods This is a prospective cohort study with a sample of 1,863 older adults aged 60 years or over in Beijing who completed baseline examinations in 2009–2010 and a 10-year follow-up in 2020. WWI was calculated as waist circumference (cm) divided by the square root of weight (kg). Cox regression analysis was performed to investigate the significance of the association of WWI with all-cause mortality. The area under the receiver operating characteristic (ROC) curves were used to compare the ability of each obesity index to predict mortality. Results During a median follow-up of 10.8 years (1.0 to 11.3 years), 339 deaths occurred. After adjusted for covariates, the hazard ratios (HRs) for all-cause mortality progressively increased across the tertile of WWI. Compared with the lowest WWI category (tertile1 <10.68 cm/√kg), with WWI 10.68 to 11.24cm/√kg, and≥11.25 cm/√kg, the HRs (95% confidence intervals (CIs)) for all-cause mortality were 1.58 (1.12–2.22), and 2.66 (1.80–3.92), respectively. In stratified analyses, the relationship between WWI and the risk of all-cause mortality persisted. The area under ROC for WWI was higher for all-cause mortality than BMI, WHtR, and WC. Conclusion WWI was associated with a higher risk for all-cause mortality, and the association was more robust with the highest WWI category.
... A meta-analysis conducted in older white adults found that the lowest risk of death was at a BMI of 27-27.9 kg/m 2 , which is higher than that in younger people [26]. ...
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Background The effect of baseline hypertension status on the BMI–mortality association is still unclear. We aimed to explore the relationships of body mass index (BMI) and waist circumference (WC) with all-cause mortality among older hypertensive and normotensive Chinese individuals. Methods This retrospective cohort study was conducted in Xinzheng, Henan Province, Central China. The data came from the residents’ electronic health records of the Xinzheng Hospital Information System. A total of 77,295 participants (41,357 hypertensive participants and 35,938 normotensive participants) aged ≥ 60 years were included from January 2011 to November 2019. Cox proportional hazard regression model was used to examine the relationships. Results During a mean follow-up of 5.3 years, 10,755 deaths were identified (6,377 in hypertensive participants and 4,378 in normotensive participants). In adjusted models, compared with a BMI of 18.5–24 kg/m², the hazard ratios (HRs) and corresponding 95% confidence intervals (CIs) of BMI < 18.5, 24–28 and ≥ 28 kg/m² for mortality in hypertensive participants were 1.074 (0.927–1.244), 0.881 (0.834–0.931) and 0.856 (0.790–0.929), respectively, and 1.444 (1.267–1.646), 0.884 (0.822–0.949) and 0.912 (0.792–1.051), respectively, in normotensive participants. Compared with normal waist circumference, the adjusted HRs and 95% CIs of central obesity for mortality were 0.880 (0.832–0.931) in hypertensive participants and 0.918 (0.846–0.996) in normotensive participants. A sensitivity analysis showed similar associations for both hypertensive and normotensive participants. Conclusion Low BMI and WC were associated with a higher risk of all-cause mortality regardless of hypertension status in older Chinese individuals. The lowest risk of death associated with BMI was in the overweight group in normotensive participants and in the obesity group in hypertensive participants.
... kg/m 2 as overweight, and >30.0 kg/m 2 as obese [28]. For subjects ≥ 65 years old, a BMI of <22kg/m 2 was underweight, 22-27 kg/m 2 was normal, and >27 kg/m 2 was overweight [29]. The waist circumference of the subjects, measured at the midpoint between the lowest rib margin and the iliac crest while subjects maintained a standing position using a soft measuring tape, was recorded to the nearest 0.1 cm. ...
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Background: Osteoporosis is an emerging geriatric condition with high morbidity and healthcare cost in developing nations experiencing rapid population ageing. Thus, identifying strategies to prevent osteoporosis is critical in safeguarding skeletal health. This study aimed to evaluate the effects of a bone health screening and education programme on knowledge, beliefs, and practice regarding osteoporosis among Malaysians aged 40 years and above. Methods: A longitudinal study was conducted from April 2018 to August 2019. During the first phase of the study, 400 Malaysians (190 men, 210 women) aged ≥ 40 years were recruited in Klang Valley, Malaysia. Information on subjects' demography, medical history, knowledge, and beliefs regarding osteoporosis, physical activity status, and dietary and lifestyle practices were obtained. Subjects also underwent body anthropometry measurement and bone mineral density scan (hip and lumbar spine) using a dual-energy X-ray absorptiometry device. Six months after the first screening, similar investigations were carried out on the subjects. Results: During the follow-up session, 72 subjects were lost to follow up. Most of them were younger subjects with a lower awareness of healthy practices. A significant increase in knowledge, beliefs (p < 0.05), calcium supplement intake (p < 0.001), and dietary calcium intake (p = 0.036) and a reduction in coffee intake (p < 0.001) were found among subjects who attended the follow-up. In this study, the percentage of successful referrals was 41.86%. Subjects with osteoporosis were mostly prescribed alendronate plus vitamin D3 by medical doctors, and they followed the prescribed treatment accordingly. Conclusions: The bone health screening and education programmes in this study are effective in changing knowledge, beliefs, and practice regarding osteoporosis. The information is pertinent to policymakers in planning strategies to prevent osteoporosis and its associated problems among the middle-aged and elderly population in Malaysia. Nevertheless, a more comprehensive bone health education program that includes long-term monitoring and consultation is needed to halt the progression of bone loss.
... In the correlation analysis, we found that there was no significant relationship between ADI and BMI ( Figure 2C, P > 0.05). At present, there is controversy about the relationship between BMI and patient prognosis (69). Many studies have shown that there is no significant relationship between BMI and prognosis (70)(71)(72); however, some studies have shown that BMI is positively correlated with mortality (4,44). ...
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Research has shown that the lipid microenvironment surrounding colorectal cancer (CRC) is closely associated with the occurrence, development, and metastasis of CRC. According to pathological images from the National Center for Tumor diseases (NCT), the University Medical Center Mannheim (UMM) database and the ImageNet data set, a model called VGG19 was pre-trained. A deep convolutional neural network (CNN), VGG19CRC, was trained by the migration learning method. According to the VGG19CRC model, adipose tissue scores were calculated for TCGA-CRC hematoxylin and eosin (H&E) images and images from patients at Zhujiang Hospital of Southern Medical University and First People's Hospital of Chenzhou. Kaplan-Meier (KM) analysis was used to compare the overall survival (OS) of patients. The XCell and MCP-Counter algorithms were used to evaluate the immune cell scores of the patients. Gene set enrichment analysis (GSEA) and single-sample GSEA (ssGSEA) were used to analyze upregulated and downregulated pathways. In TCGA-CRC, patients with high-adipocytes (high-ADI) CRC had significantly shorter OS times than those with low-ADI CRC. In a validation queue from Zhujiang Hospital of Southern Medical University (Local-CRC1), patients with high-ADI had worse OS than CRC patients with low-ADI. In another validation queue from First People's Hospital of Chenzhou (Local-CRC2), patients with low-ADI CRC had significantly longer OS than patients with high-ADI CRC. We developed a deep convolution network to segment various tissues from pathological H&E images of CRC and automatically quantify ADI. This allowed us to further analyze and predict the survival of CRC patients according to information from their segmented pathological tissue images, such as tissue components and the tumor microenvironment.
... The effective management and intervention of these modifiable prediction factors will be of significance in reducing the risk of mortality among older adults with hypertension. A meta-analysis focused on ≥65 years older adults, found a U-shaped association between BMI and mortality and the lowest risk of mortality in those with BMI from 24 to 30.9 [34]. Older adults with underweight had a higher risk of mortality [35,36], which might be related to malnutrition and chronic diseases in those people [37]. ...
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Background Hypertension-related mortality has been increasing in older adults, resulting in serious burden to society and individual. However, how to identify older adults with hypertension at high-risk mortality remains a great challenge. The purpose of this study is to develop and validate the prediction nomogram for 5-year all-cause mortality in older adults with hypertension. Methods Data were extracted from National Health and Nutrition Examination Survey (NHANES). We recruited 2691 participants aged 65 years and over with hypertension in the NHANES 1999-2006 cycles (training cohort) and 1737 participants in the NHANES 2007-2010 cycles (validation cohort). The cohorts were selected to provide at least 5 years follow-up for evaluating all-cause mortality by linking National Death Index through December 31, 2015. We developed a web-based dynamic nomogram for predicting 5-year risk of all-cause mortality based on a logistic regression model in training cohort. We conducted internal validation by 1000 bootstrapping resamples and external validation in validation cohort. The discrimination and calibration of nomogram were evaluated using concordance index (C-index) and calibration curves. Results The final model included eleven independent predictors: age, sex, diabetes, cardiovascular disease, body mass index, smoking, lipid-lowering drugs, systolic blood pressure, hemoglobin, albumin, and blood urea nitrogen. The C-index of model in training and validation cohort were 0.759 (bootstrap-corrected C-index 0.750) and 0.740, respectively. The calibration curves also indicated that the model had satisfactory consistence in two cohorts. A web-based nomogram was established (https://hrzhang1993.shinyapps.io/dynnomapp). Conclusions The novel developed nomogram is a useful tool to accurately predict 5-year all-cause mortality in older adults with hypertension, and can provide valuable information to make individualized intervention.
... Clinical characteristics comprised alcohol use (consuming alcohol versus not consuming), smoking status (smoking versus not smoking), obesity (defined as having a body mass index (BMI) > 30 kg/m 2 ), malnutrition (defined as having a BMI < 23 kg/m 2 ) [50], number of non-psychiatric medical conditions (e.g., cardiovascular disorders), duration of schizophrenic disorder, inpatient status and long-term institutionalization (defined as living in a dwelling that offers some form of formal supervision, including homes for the aged, nursing homes, chronic care beds, psychiatric institutions and hospital stays longer than 3 months [51]). ...
... Finally, the definitions of underweight and obesity differed among the included studies, which may have affected the reported postoperative mortality rates. Recent studies proposed the optimal geriatric BMI defined as ranging from 23 to 29.9 kg/m 2 in adults ≥ 65 years of age [47,48]. However, the majority of the enrolled studies used the definitions based on the WHO classification: underweight (BMI < 18.5 kg/ m 2 ), average weight (BMI 18.5-24.9 ...
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Background The obesity paradox, which suggests that high body weight is positively associated with survival in some diseases, has not been proven in patients with hip fracture. In this study, meta-analysis of previous studies on the impacts of body weight on postoperative mortality following hip fracture surgery in older adults was conducted. Methods PubMed, Embase, and Cochrane library were searched for studies investigating the correlation between mortality after hip fracture surgery and body weight. The search main items included: (“Body mass index” OR “BMI” or “body weight”) and (“hip fracture” or “hip fractures”). Studies contained data on short-term (≤ 30-day) and long-term (≥ 1 year) mortality after hip fracture and its association with distinct body weight or BMI groups were reported as full-text articles were included in this meta-analysis. Results Eleven separate studies were included. The definitions of underweight and obesity differed among the included studies, but the majority of the enrolled studies used the average body weight definition of a BMI of 18.5 to 24.9 kg/m ² ; underweight referred to a BMI of < 18.5 kg/m ² ; and obesity pertained to a BMI of > 30 kg/m ² . Based on the generalized definitions of body-weight groups from the enrolled studies, the group with obesity had lower long-term (odds ratio [OR]: 0.63, 95% CI: 0.50–0.79, P < 0.00001) and short-term (OR: 0.63, 95% CI: 0.58–0.68, P ≤ 0.00001) mortality rates after hip fracture surgery when compared with patients with average-weight group. However, compared with the average-weight group, the underweight group had higher long-term (OR: 1.51, 95% CI: 1.15-1.98, P =0.003) and short-term (OR: 1.49, 95% CI: 1.29-1.72, P <0.00001) mortality rates after hip fracture surgery. Conclusions Current evidence demonstrates an inverse relation of body weight with long-term and short-term mortality after hip fracture surgery in older adults.
... Moreover, both obesity and multimorbidity are associated with a higher risk of disability, intense healthcare utilization and mortality [3,4]. On the other hand, older adults with overweight show better health status and lower all-cause mortality compared to those with normal or underweight [5]; an observation known as the obesity paradox [6]. This apparent contradiction should be read in light of the bidirectional relationship between body weight and health, and the dynamic body composition changes accompanying aging, which lead to substantial redistributions of fat, muscle and bone mass [7]. ...
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Background & aims Body weight changes reflect and impact several health conditions in older age, but little is known about its relationship with multimorbidity. We aimed to study the association of long-terms trajectories of body mass index (BMI) with contemporaneous changes in multimorbidity −and multimorbidity type− development in a population-based cohort of older adults. Methods Twelve-year BMI trajectories (2001–2013) were identified in subjects aged 60+ years from the Swedish National Study on Aging and Care-Kungsholmen (SNAC-K) using growth mixture models (N = 2189). Information on 60 chronic diseases and multimorbidity was ascertained based on clinical examinations, lab tests, medications, and inpatient and outpatient medical records. Linear mixed models were used to study the association between BMI trajectories and the speed of chronic diseases accumulation, in general and by groups of cardiovascular and neuropsychiatric diseases. Results Eighty percent of the study population was included in what we defined a stable BMI trajectory, 18% in a slow-decline trajectory with an accelerated BMI decline from age 78 onwards, and 2% in a fast-decline trajectory that reached underweight values before age 85. A significantly higher yearly rate of chronic disease accumulation was observed in the fast-decline versus stable trajectories (β = 0.221, 95% CI 0.090–0.352) after adjusting the model for age cohort, sex, education and time to death. Subjects in the slow-decline trajectory showed a significantly higher yearly rate of cardiovascular diseases accumulation (β = 0.016, 95% CI 0.000–0.031); those in the fast-decline trajectory showed a faster accumulation of both cardiovascular (β = 0.020, 95% CI -0.025, 0.064) and neuropsychiatric diseases (β = 0.102, 95% CI 0.064–0.139), even if the former association did not reach statistical significance. Conclusion Our results provide further evidence of the importance of carefully monitoring older adults with sustained weight loss, which is an early indicator of accelerated health deterioration, reflected in our study by a faster accumulation of chronic −especially neuropsychiatric− diseases.
... With age, BMI values usually stabilize or reduce, but visceral fat and intramyocellular fat increase (79,82). As such, the diagnosis of obesity based only on body weight is imperfect, so body composition data should be considered in the diagnosis; this has resulted in different cutoff values for healthy BMI proposed for this age group (83)(84)(85). At the same time, the possibility of concomitant diseases leading to involuntary weight loss increases with age (76,80,86). ...
Article
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Obesity is a chronic disease associated with impaired physical and mental health. A widespread view in the treatment of obesity is that the goal is to normalize the individual's body mass index (BMI). However, a modest weight loss (usually above 5%) is already associated with clinical improvement, while weight losses of 10%-15% bring even further benefits, independent from the final BMI. The percentage of weight reduction is accepted as a treatment goal since a greater decrease in weight is frequently difficult to achieve due to metabolic adaptation along with environmental and lifestyle factors. In this document, the Brazilian Society of Endocrinology and Metabolism (SBEM) and the Brazilian Society for the Study of Obesity and Metabolic Syndrome (ABESO) propose a new obesity classification based on the maximum weight attained in life (MWAL). In this classification, individuals losing a specific proportion of weight are classified as having "reduced" or "controlled" obesity. This simple classification - which is not intended to replace others but to serve as an adjuvant tool - could help disseminate the concept of clinical benefits derived from modest weight loss, allowing individuals with obesity and their health care professionals to focus on strategies for weight maintenance instead of further weight reduction. In future studies, this proposed classification can also be an important tool to evaluate possible differences in therapeutic outcomes between individuals with similar BMIs but different weight trajectories.
... Several multi-country, population-based studies, with research participants of a wide age range between 20 and 80 years, have shown that high BMI increases mortality risk [2][3][4][5]. However, in age-stratified analyses, the BMImortality association among older persons weakened [3][4][5][6], in agreement with other studies of older individuals, which have reported a nonsignificant or even inverse association between high BMI in late-life and mortality [7][8][9][10]. Therefore, the effects of high BMI in late-life on mortality remain unclear. ...
Article
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Background There is robust evidence that in midlife, higher body mass index (BMI) and metabolic syndrome (MetS), which often co-exist, are associated with increased mortality risk. However, late-life findings are inconclusive, and few studies have examined how metabolic health status (MHS) affects the BMI–mortality association in different age categories. We, therefore, aimed to investigate how mid- and late-life BMI and MHS interact to affect the risk of mortality. Methods This cohort study included 12,467 participants from the Swedish Twin Registry, with height, weight, and MHS measures from 1958—2008 and mortality data linked through 2020. We applied Cox proportional hazard regression with age as a timescale to examine how BMI categories (normal weight, overweight, obesity) and MHS (identification of MetS determined by presence/absence of hypertension, hyperglycemia, low HDL, hypertriglyceridemia), independently and in interaction, are associated with the risk of all-cause mortality. Models were adjusted for sex, education, smoking, and cardiovascular disease. Results The midlife group included 6,252 participants with a mean age of 59.6 years (range = 44.9—65.0) and 44.1% women. The late-life group included 6,215 participants with mean age 73.1 years (65.1—95.3) and 46.6% women. In independent effect models, metabolically unhealthy status in midlife increased mortality risks by 31% [hazard ratio 1.31; 95% confidence interval 1.12–1.53] and in late-life, by 18% (1.18;1.10–1.26) relative to metabolically healthy individuals. Midlife obesity increased the mortality risks by 30% (1.30;1.06–1.60) and late-life obesity by 15% (1.15; 1.04–1.27) relative to normal weight. In joint models, the BMI estimates were attenuated while those of MHS were less affected. Models including BMI-MHS categories revealed that, compared to metabolically healthy normal weight, the metabolically unhealthy obesity group had increased mortality risks by 53% (1.53;1.19—1.96) in midlife, and across all BMI categories in late-life (normal weight 1.12; 1.01–1.25, overweight 1.10;1.01–1.21, obesity 1.31;1.15–1.49). Mortality risk was decreased by 9% (0.91; 0.83–0.99) among those with metabolically healthy overweight in late-life. Conclusions MHS strongly influenced the BMI-mortality association, such that individuals who were metabolically healthy with overweight or obesity in mid- or late-life did not carry excess risks of mortality. Being metabolically unhealthy had a higher risk of mortality independent of their BMI.
... Such results provide further evidence that a BMI at the low normal range might be "too low" for older adults, especially in light of the weaker evidence connecting obesity with increased mortality. Other investigators have noted an increase in all-cause mortality risk for older adults with a BMI at the lower end of the normal range, beginning with a BMI of less than 23.0 kg/m 2 [19,[31][32][33]. ...
Article
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Background Obesity may have a protective effect (greater survival) in older adults, a finding known as the “obesity paradox.” This study examined the association between self-reported body mass index (BMI) and active life expectancy (ALE) among older U.S. adults. Methods Using the Medicare Health Outcomes Survey Cohort 15 (2012 baseline, 2014 follow-up), we estimated life expectancy and ALE by participants’ baseline BMI and age using multi-state models. A participant was classified as in an active state if this person reported having no difficulty for any of these six activities of daily living (ADLs). Results Small differences in life expectancy were noted among persons in normal weight (BMI 18.5–24.9 kg/m²), overweight (BMI 25–29.9 kg/m²), and obesity ranges (BMI 30 kg/m² and higher). However, persons with obesity had a significantly lower ALE. ALE at age 65 was 11.1 (11.0–11.2) years for persons with obesity, 1.2 (1.1–1.3) years less than that for the normal weight and overweight persons (12.3 years for both, 12.2–12.4). Persons with class III obesity had a significantly lower life expectancy and ALE than normal weight persons. Although persons with class I or II obesity had a similar life expectancy as normal weight persons, they have a shorter ALE. Conclusions Although older adults with obesity have a similar life expectancy as normal weight persons, they have a significantly shorter ALE. Given the complex relationship of BMI and ALE, a “one size fits all” approach to weight management is not advisable.
... shown that the BMI range traditionally considered overweight in adults would be associated with a lower risk of death in the elderly 29 . However, waist circumference cut-off points for elderly populations have not been frequently questioned, and the classification recommended by the WHO for the elderly does not differ from that applied to adults 9 . ...
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Introduction: Body composition changes related to aging alter the capacity of predicting risk through anthropometric parameters. Objective: To discuss methodological aspects of anthropometry in active elderly based on associations between Body Mass Index (BMI) and other nutritional indicators. Methods: Cross-sectional study with active elderly from Macaé, Rio de Janeiro, Brazil (2014/2015). Nutritional status was described according to the BMI (Nutritional Screening Initiative, 1994). Linear regression analysis was performed: the outcome variable was BMI and the dependent ones were circumferences of waist, hip, neck, calf, arm and waist-to-hip ratio (WHR). Results: We assessed 173 people (55.5% female; median 71 years old). Calf and neck circumferences and WHR presented low R2 value. Among women, hip (R2=0.825) and waist circumferences (R2=0.729) individually explained much of the variation in BMI; and among men, waist (R2=0.759) and arm circumferences (R2=0.741) performed better. The cut-off points for waist circumference corresponding to the critical BMI value (27 kg/m2) were 87.9 and 96.8 cm, respectively for women and men. In multiple analysis, the association of waist, hip and arm circumferences with BMI remained significant. Conclusion: Circumferences traditionally used to assess adults had higher linear association with BMI than specific indicators for elderly people. The body composition of active elderly can be more similar to adults’ than that of elderly with other profiles. The waist circumference cut-off points established for adults may not be suitable for elderly populations. We suggest testing the cut-off points obtained by this study on other groups of active elderly.
Article
Résumé Le surpoids et l’obésité correspondent à des situations hétérogènes. Le risque pour la santé diffère selon de multiples conditions : l’âge, la composition corporelle, la distribution du tissu adipeux, la trajectoire de poids. Certaines situations complexes, telles l’obésité métaboliquement normale ou l’obésité sarcopénique méritent aussi d’être identifiées, car les approches thérapeutiques sont différentes. Enfin, les régimes amaigrissants peuvent exercer des effets délétères. De sorte que maigrir n’est pas toujours nécessaire, ni la solution. Maigrir à tout prix n’a pas de sens médical. Un essai de synthèse selon les principaux traits liés au poids est proposé.
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Background The association between dietary protein intake and the risk of mortality is still controversial. The present study aimed to examine the associations between dietary total, animal and plant protein intake and all-cause and cause-specific mortality. Methods Community-dwelling men aged ≥ 70 years were recruited from local government areas surrounding Concord Hospital in Sydney, New South Wales for the Concord Health and Ageing in Men Project (CHAMP). The research dietitian administered a standardised validated diet history questionnaire to capture baseline dietary intake. In total, 794 men participated in a detailed diet history interview at the third wave. Adequacy of protein intake was assessed by comparing participant intake with the Nutrient Reference Values. Total protein intake was categorised into quintiles. Sources of protein were also captured. Mortality was ascertained through the New South Wales death registry. Cox proportional hazard models were used to assess the association between dietary total, animal and plant protein intake and risk of mortality. Results The mean age of the CHAMP men was 81 years. In total, 162 men died during a median follow-up of 3.7 years. Of these, 54 (33.3%) and 49 (30.2%) men died due to cancer and cardiovascular disease, respectively. There were U-shaped associations between protein intake and all-cause and cancer mortality. In multiple adjusted analysis, the second (hazard ratio [HR] = 0.38; 95% confidence interval [CI] = 0.18–0.82) and third (HR = 0.36; 95% CI = 0.16–0.82) quintiles of protein intakes were significantly associated with reduced risk of all-cause and only second quintile (HR = 0.47; 95% CI = 0.10–0.93) of protein intake was significantly associated with cancer mortality. Each serve increase in animal protein was significantly associated with 12% (HR = 1.12; 95% CI = 1.00–1.26) and 23% (HR = 1.23; 95% CI = 1.02–1.49) increased risk of all-cause mortality and cancer mortality respectively. Conversely, each serve increase in plant protein intake was significantly associated with 25% (HR = 0.75; 95% CI 0.61–0.92) and 28% (HR = 0.72; 95% CI = 0.53–0.97) reduced risk of all-cause and cancer mortality, respectively. No such associations were observed for cardiovascular disease mortality. Conclusions Both second and third quintiles of total protein intake were associated with reduced all-cause and cancer mortality. Plant protein was inversely associated with all-cause and cancer mortality, whereas animal protein intake was positively associated with mortality. Key points • Our findings suggest a U-shaped association between life expectancy and total protein intake, in which lifespan is greatest among people with 93–113 g day–1 total protein intake, a level that might be considered moderate in Australia but high in other countries. • Both second and third quintiles of total protein intake (range between 79.23 and 107.19 g day–1) were associated with reduced risk of all-cause and cancer mortality. • Higher consumption of animal-derived proteins was associated with greater mortality risk, whereas this association was reversed when protein consumption was replaced with plant-derived protein.
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In der vorliegenden Studie wurde der Zusammenhang des depressiven Syndroms mit dem Vitamin D-Spiegel an einer Stichprobe gerontopsychiatrischer Patienten (n = 140) der Neurogerontopsychiatrischen Tagesklinik Würzburg untersucht. Die Depressivität der Patienten zu Beginn und im Verlauf der Behandlung wurde zum einen mittels der ICD-10-Klassifikation, zum anderen mittels des Scores auf der GDS- und Hamilton-Skala zu Beginn und Ende des Aufenthalts in der Tagesklinik sowie bei einer poststationären Kontrolle bestimmt. Der Vitamin D-Spiegel wurde bei Behandlungsbeginn bestimmt und im Falle eines Mangels 1000 IU Vitamin D am Tag oral substituiert. Hierbei zeigte sich kein Zusammenhang zwischen der Ausprägung des depressiven Syndroms und dem Vitamin D-Spiegel zu Beginn der Behandlung. Dagegen stellte sich heraus, dass Patienten mit einem höheren Spiegel eine deutlichere Verbesserung der depressiven Symptome auf der GDS im Verlauf der Behandlung erfuhren. Außerdem bestand eine signifikante negative Korrelation zwischen BMI und Vitamin D-Spiegel sowie eine Abhängigkeit der Spiegelhöhe von der Jahreszeit. Vitamin D könnte nach den Ergebnissen dieser Studie möglicherweise eine wirkungssteigernde und nebenwirkungsarme Komedikation in der antidepressiven Therapie von älteren psychisch erkrankten Menschen darstellen. Es bedarf weiterer ausführlicher Forschung über den neurophysiologischen Zusammenhang zwischen Vitamin D und der Schwere einer depressiven Erkrankung. Besonders hinsichtlich der Verwendung von Vitamin D als Komedikation gilt es, weitere intensive Forschung in Form von gut designten, randomisierten Fall-Kontroll-Studien und prospektiven Interventionsstudien zu betreiben, um die Therapie von depressiven Patienten im höheren Lebensalter weiter zu verbessern.
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Prior research suggests that certain psychiatric symptoms could be associated with increased risk of death. However, it remains unclear whether this association could rely on all or specific symptoms. In this report, we used data from a multicenter 5-year prospective study (N = 641) of older adults with an ICD-10 diagnosis of schizophrenia, bipolar disorder or major depressive disorder, recruited from French community psychiatric departments. We used a latent variable approach to disentangle the effects shared by all psychiatric symptoms (i.e., general psychopathology factor) and those specific to individual psychiatric symptoms, while adjusting for sociodemographic and clinical factors. Psychiatric symptoms were assessed face-to-face by psychiatrists trained to semi-structured interviews using the Brief Psychiatric Rating Scale (BPRS). Among older adults with major psychiatric disorders, we found that all psychiatric symptoms were associated with increased mortality, and that their effect on the 5-year mortality were exerted mostly through a general psychopathology dimension (β = 0.13, SE = 0.05, p < 0.05). No BPRS item or lower order factor had a significant effect on mortality beyond and above the effect of the general psychopathology factor. Greater number of medical conditions, older age, male sex, and being hospitalized or institutionalized at baseline were significantly associated with this risk beyond the effect of the general psychopathology factor. Since psychiatric symptoms may affect mortality mainly through a general psychopathology dimension, biological and psychological mechanisms underlying this dimension should be considered as promising targets for interventions to decrease excess mortality of older individuals with psychiatric disorders.
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Objective Data are scarce regarding the clinical factors associated with utilization of long-term care facilities among older adults with schizophrenia. In this multicenter study, we sought to examine potential clinical differences between older adults with schizophrenia who are living in a long-term care facility and their community-dwelling counterparts. Method We used data from the French Cohort of individuals with Schizophrenia Aged 55-years or more (CSA) study, a large multicenter sample of older adults with schizophrenia (N=353). Results The prevalence of long-term care utilization was 35.1% of older patients with schizophrenia. Living in a long term care facility was significantly and independently associated with higher level of depression (Adjusted odds ratio (AOR) [95%CI]=1.97 [1.06-3.64]), lower cognitive (AOR [95%CI]=0.94 [0.88-0.99]) and global functioning (AOR [95%CI]=0.97 [0.95-0.99]), greater lifetime number of hospitalizations in a psychiatric department (AOR [95%CI]=2.30 [1.18-4.50]), not having consulted a general practitioner in the past year (AOR [95%CI]=0.28 [0.0.14-0.56]), urbanicity (AOR [95%CI]=2.81 [1.37-5.80]), and older age (AOR [95%CI]=1.08 [1.03-1.13]). Discussion Older patients patients with schizophrenia who live in long-term care facilities appear to belong to a distinct group, marked by a more severe course of illness with higher level of depression and more severe cognitive deficits than older patients with schizophrenia living in other settings. Our study highlights the need of early assessment and management of depression and cognitive deficits in this population and the importance of monitoring closely this vulnerable population.
Thesis
Malgré un gain d’espérance de vie de 30 ans au cours du siècle dernier dans les pays développés, atteindre un âge avancé reste associé au développement de pathologies chroniques et/ou invalidantes. Définir les acteurs de vieillissement est donc une priorité pour espérer freiner l’établissement de ces maladies et/ou réduire leur sévérité. L’enzyme DICER possède des fonctions essentielles au maintien de l’homéostasie cellulaire mais son rôle dans le vieillissement reste encore à définir. Afin d’évaluer sa contribution, le suivi longitudinal de souris Dicer1d/d avec une expression réduite de la protéine a été réalisé. Les animaux Dicer1d/d ont une survie réduite et un développement précoce de pathologies liées à l’âge. Le séquençage ARN du tissu adipeux révèle une profonde altération du transcriptome chez les mutants avec l’âge. Nous suggérons que cette signature transcriptomique différencielle soit à l’origine du vieillissement prématuré. Les données établissent Dicer1 comme un acteur clé de la balance altération/réparation conditionnant la vitesse de vieillissement et posent les animaux dicer1d/d comme un nouveau modèle d’étude de ce processus.
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Working memory is developed in one region of the brain called the dorsolateral prefrontal cortex (DLPFC). The dysfunction of this region leads to synaptic neuroplasticity impairment. It has been reported that several biochemical parameters and anthropometric measurements play a vital role in cognition and brain health. This study aimed to investigate the relationships between cognitive function, serum biochemical profile, and anthropometric measurements using DLPFC activation. A cross-sectional study was conducted among 35 older adults (≥60 years) who experienced mild cognitive impairment (MCI). For this purpose, we distributed a comprehensive interview-based questionnaire for collecting sociodemographic information from the participants and conducting cognitive tests. Anthropometric values were measured, and fasting blood specimens were collected. We investigated their brain activation using the task-based functional MRI (fMRI; N-back), specifically in the DLPFC region. Positive relationships were observed between brain-derived neurotrophic factor (BDNF) (β = 0.494, p < 0.01) and Mini-Mental State Examination (MMSE) (β = 0.698, p < 0.01); however, negative relationships were observed between serum triglyceride (β = −0.402, p < 0.05) and serum malondialdehyde (MDA) (β = −0.326, p < 0.05) with right DLPFC activation ( R ² = 0.512) while the participants performed 1-back task after adjustments for age, gender, and years of education. In conclusion, higher serum triglycerides, higher oxidative stress, and lower neurotrophic factor were associated with lower right DLPFC activation among older adults with MCI. A further investigation needs to be carried out to understand the causal-effect mechanisms of the significant parameters and the DLPFC activation so that better intervention strategies can be developed for reducing the risk of irreversible neurodegenerative diseases among older adults with MCI.
Article
Background Malnutrition and dehydration are widespread in older people, and obesity is an increasing problem. In clinical practice, it is often unclear which strategies are suitable and effective in counteracting these key health threats. Aim To provide evidence-based recommendations for clinical nutrition and hydration in older persons in order to prevent and/or treat malnutrition and dehydration. Further, to address whether weight-reducing interventions are appropriate for overweight or obese older persons. Methods This guideline was developed according to the standard operating procedure for ESPEN guidelines and consensus papers. A systematic literature search for systematic reviews and primary studies was performed based on 33 clinical questions in PICO format. Existing evidence was graded according to the SIGN grading system. Recommendations were developed and agreed in a multistage consensus process. Results We provide eighty-two evidence-based recommendations for nutritional care in older persons, covering four main topics: Basic questions and general principles, recommendations for older persons with malnutrition or at risk of malnutrition, recommendations for older patients with specific diseases, and recommendations to prevent, identify and treat dehydration. Overall, we recommend that all older persons shall routinely be screened for malnutrition in order to identify an existing risk early. Oral nutrition can be supported by nursing interventions, education, nutritional counselling, food modification and oral nutritional supplements. Enteral nutrition should be initiated if oral, and parenteral if enteral nutrition is insufficient or impossible and the general prognosis is altogether favorable. Dietary restrictions should generally be avoided, and weight-reducing diets shall only be considered in obese older persons with weight-related health problems and combined with physical exercise. All older persons should be considered to be at risk of low-intake dehydration and encouraged to consume adequate amounts of drinks. Generally, interventions shall be individualized, comprehensive and part of a multimodal and multidisciplinary team approach. Conclusion A range of effective interventions is available to support adequate nutrition and hydration in older persons in order to maintain or improve nutritional status and improve clinical course and quality of life. These interventions should be implemented in clinical practice and routinely used.
Article
Jenseits des 70. Lebensjahrs ist bei älteren Menschen regelhaft eine Abnahme der Muskelmasse sowie eine Zunahme der Fettmasse zu beobachten. Diese Veränderungen der Körperzusammensetzung stellen eine wesentliche Prädisposition für den im Alter drohenden Verlust an Funktionalität und Selbständigkeit dar. In diesem Kontext kommt der richtigen Ernährung sowie insbesondere dem Vermeiden einer Mangelernährung große Relevanz zu. Da die ältere Bevölkerung hinsichtlich der Geschwindigkeit und Ausprägung der Alterungsvorgänge sowie ihrer Komorbiditäten als äußerst heterogen zu betrachten ist, müssen Ernährungsempfehlungen individualisiert erfolgen. Mit Hinblick auf eine potenzielle Gefährdung durch eine Sarkopenie ist selbst eine beabsichtigte Gewichtsabnahme im Alter kritisch zu sehen. Fastenepisoden sollten generell vermieden werden. Dies betrifft insbesondere eine unzureichende Kalorienzufuhr im Kontext von akuten oder chronischen Erkrankungen. Im höheren Lebensalter sollten daher regelmäßige Gewichtskontrollen erfolgen, um das Auftreten einer Mangelernährung frühzeitig zu erkennen und entsprechende Maßnahmen einleiten zu können. Zum Erhalt der Muskelmasse und -funktion sollte eine gegenüber jüngeren Menschen erhöhte Eiweißzufuhr von 1,0 g/kgKG angestrebt werden. Bei älteren Menschen mit Sarkopenie wird dieses Ziel auf 1,2 g/kgKG angehoben. Während sich im Alter restriktive Diäten als nachteilig erweisen können, scheinen gesunde Ernährungsformen wie z. B. die mediterrane Ernährung den Erhalt der muskulären und kognitiven Funktion zu fördern.
Article
Background and objective High-risk surgery on aged patients raises challenging ethical and clinical issues. The aim of this study was to analyze the preoperative factors associated with severe complications and returning home after pancreatic resection among patients aged ⩾ 75 years. Patients and methods Patients aged ⩾ 75 years undergoing pancreatic resection in 2012–2019 were retrospectively searched from the hospital database. Preoperative indices (Clinical Frailty Scale, Skeletal Muscle Index, Geriatric Nutritional Risk Index, Charlson Comorbidity Index, and National Surgical Quality Improvement Program risk for severe complications) were determined. Postoperative outcome was evaluated by incidence of Clavien–Dindo 3b-5 complications, rate of returning home, and 1-year survival. Results A total of 95 patients were included. American Society of Anesthesiologists Class 3–4 covered 50%, Clinical Frailty Scale > 3 22%, Charlson Comorbidity Index > 6 53%, and a sarcopenic Skeletal Muscle Index 51% of these patients. The National Surgical Quality Improvement Program risk for severe complications was higher than average among 21% of patients. Geriatric Nutritional Risk Index showed high risk among 3% of them. In total, 19 patients (20%) experienced a severe (Clavien–Dindo 3b-5) complication. However, 30- and 90-day mortality was 2.1%. Preoperative indices were not associated with severe complications. Most patients (79%) had returned home within 8 weeks of surgery. Not returning home was associated with severe complications ( p = 0.010). Conclusions The short-term outcome after pancreatic resection of fit older patients is similar to that of younger, unselected patient groups. In these selected patients, the commonly used preoperative indexes were not associated with severe complications or returning home.
Article
Objective This umbrella review aimed to summarize the association between modifiable predictive factors and all-cause mortality in the non-hospitalized elderly population, and estimated the credibility and strength of the current evidence. Methods PubMed, Embase, Web of science, and EBSCOhost were searched up to February 28, 2022. Random-effect summary effect sizes and 95% confidence intervals (CIs), heterogeneity, small-study effect, excess significance bias, as well as 95% prediction intervals (PIs) were calculated. Methodological quality was assessed with the Assessment of Multiple Systematic Reviews 2 (AMSTAR-2) tool. The credibility of the included meta-analyses was graded from convincing to weak using established criteria. This umbrella review was registered with PROSPERO, CRD 42021282183. Results In total, 32 predictive factors involving 49 associations extracted from 35 meta-analyses were analyzed. Forty-three of the 49 (87.8%) associations presented nominal significant effects by the random-effect model (P < 0.05), of which 34 had harmful associations and nine had beneficial associations with all-cause mortality. Frailty (FRAIL scale), low short physical performance battery (SPPB) score, and fewer daily steps carried a more than three-fold risk for all-cause mortality. Convincing evidence showed that weight fluctuation, prefrailty and frailty status, sarcopenia, low SPPB score, fewer daily steps, and fatigue increased the risk of all-cause mortality, while daily moderate-to-vigorous physical activity (MVPA) duration and total physical activity participation reduced the risk of death. There were twenty, nine, five, and six associations that yielded highly suggestive, suggestive, weak, and non-significant grades of evidence. Thirty-four (69.4%) of the associations exhibited significant heterogeneity. Twenty-two associations presented 95% PIs excluding the null value, two indicated small-study effects, and three had evidence for excess significance bias, respectively. The methodological quality of most meta-analyses was rated as low (37.1%) or critically low (42.9%). Conclusions A summary of the currently available meta-analyses suggests that a broad range of modifiable predictive factors are significantly associated with all-cause mortality risk in the non-hospitalized elderly population. The most credible evidence indicates that physical function represented by frailty and sarcopenia, as well as physical activity, are significant predictors for all-cause mortality. This umbrella review may provide prognostic information to direct appropriate diagnostic evaluation and treatment goals in the future. More solid evidence is still needed coming from moderate-to-high quality meta-analyses.
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Healthcare professionals may confront ethical issues in practice, particularly when their values conflict with that of their patients or clients. This paper explores an ethical case study in which a dietitian who practices Health at Every Size® has an older adult client who wishes to lose weight. The dietitian believes that losing weight is inappropriate for this client. Using a framework for ethical decision making, this article explores the problem or dilemma, identifies the potential issues involved, discusses the relevant ethical codes, laws, and regulations, and explores possible courses of action and their consequences. By exploring an ethical issue that healthcare professionals may encounter in practice, we can gain a deeper understanding of ethical decision making.
Article
Background and Aims Despite animal studies revealing a causal link between the gut microbiota and skeletal muscle mass, the role of the gut microbiome and its metabolites in humans having low muscle mass remains unclear. Methods Eighty-eight subjects older than 65 years were measured for sarcopenia-related parameters, including body composition, grip strength, gait speed and flexibility. Participants were divided into normal muscle mass group (NM, n = 52) and low muscle mass group (LM, n = 36) and fresh fecal samples were collected for metagenome and short chain fatty acids (SCFAs) analysis. Results The richness and evenness of gut microbiota diversity were significantly decreased in the subjects with low muscle mass, including observed ASVs, Shannon and Chao 1 index. A significant difference of gut microbiota profile was noted between NM group and LM group. The Firmicutes/Bacteroidetes ratio was significantly reduced in the LM group. A significant decrease in the abundance of a SCFA-producer, Marvinbryantia spp., whereas a remarkable enrichment of a flavonoid degrader, Flavonifractor spp., was observed in the LM elders. Comparing with the NM group, the fecal butyrate significantly diminished in the LM group and correlated with skeletal muscle mass index. Conclusions This is the first study that demonstrates the reduced fecal butyrate in elders with low muscle mass and highlights the associated gut microbiome changes. The identified gut microbial features and fecal butyrate level may serve as potential biomarkers for early detection of sarcopenic patients.
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Background: To compare the prevalence of healthy aging among adults age 70 and older from 5 European countries recruited for the DO-HEALTH clinical trial. Participants were selected for absence of prior major health events. Methods: Cross-sectional analysis of DO-HEALTH baseline data. All 2,157 participants (mean age 74.9, SD 4.4; 61.7% women) were included and 2,123 had data for all domains of the healthy aging status (HA) definition. HA was assessed based on the Nurses` Health Study (NHS) definition requiring four domains: no major chronic diseases, no disabilities, no cognitive impairment (Montreal Cognitive Assessment, MoCA ≥25), no mental health limitation (GDS-5 <2, and no diagnosis of depression). Association between HA and age, BMI, gender, and physical function (sit-to-stand, gait speed, grip strength) was assessed by multivariate logistic regression analyses adjusting for center. Results: Overall, 41.8% of DO-HEALTH participants were healthy agers with significant variability by country: Austria (Innsbruck) 58.3%, Switzerland (Zurich, Basel, Geneva) 51.2%, Germany (Berlin) 37.6%, France (Toulouse) 36.7% and Portugal (Coimbra) 8.8% (p <0.0001). Differences in prevalence by country persisted after adjustment for age. In the multivariate model, younger age (OR = 0.95, 95% CI 0.93 to 0.98), female gender (OR = 1.36, 95% CI 1.03 to 1.81), lower BMI (OR = 0.94, 95% CI 0.91 to 0.96), faster gait speed (OR = 4.70, 95% CI 2.68 to 8.25) and faster performance in sit-to-stand test (OR = 0.90, 95% CI 0.87 to 0.93) were independently and significantly associated with HA. Conclusions: Despite the same inclusion and exclusion criteria preselecting relatively healthy adults age 70 years and older, HA prevalence varied significantly between countries and was highest in Austria and Switzerland, lowest in Portugal. Independent of country, younger age, female gender, lower BMI and better physical function were associated with HA. Trial registration: DO-HEALTH was registered under the protocol NCT01745263 at the International Trials Registry (clinicaltrials.gov), and under the protocol number 2012–001249-41 at the Registration at the European Commu-nity Clinical Trial System (EudraCT).
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Background: Guidelines for optimal weight in older persons are limited by uncertainty about the ideal body mass index (BMI) or the usefulness of alternative anthropometric measures. Objective: We investigated the association of BMI (in kg/m²), waist circumference, and waist-hip ratio (WHR) with mortality and cause-specific mortality. Design: Subjects aged ≥75 y (n = 14 833) from 53 family practices in the United Kingdom underwent a health assessment that included measurement of BMI and waist and hip circumferences; they also were followed up for mortality. Results: During a median follow-up of 5.9 y, 6649 subjects died (46% of circulatory causes). In nonsmoking men and women (90% of the cohort), compared with the lowest quintile of BMI (<23 in men and <22.3 in women), adjusted hazard ratios (HRs) for mortality were <1 for all other quintiles of BMI (P for trend = 0.0003 and 0.0001 in men and women, respectively). Increasing WHR was associated with increasing HRs in men and women (P for trend = 0.008 and 0.0002, respectively). BMI was not associated with circulatory mortality in men (P for trend = 0.667) and was negatively associated in women (P for trend = 0.004). WHR was positively related to circulatory mortality in both men and women (P for trend = 0.001 and 0.005, respectively). Waist circumference was not associated with all-cause or circulatory mortality. Conclusions: Current guidelines for BMI-based risk categories overestimate risks due to excess weight in persons aged ≥75 y. Increased mortality risk is more clearly indicated for relative abdominal obesity as measured by high WHR.
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Context The prevalence of obesity and overweight increased in the United States between 1978 and 1991. More recent reports have suggested continued increases but are based on self-reported data.Objective To examine trends and prevalences of overweight (body mass index [BMI] ≥25) and obesity (BMI ≥30), using measured height and weight data.Design, Setting, and Participants Survey of 4115 adult men and women conducted in 1999 and 2000 as part of the National Health and Nutrition Examination Survey (NHANES), a nationally representative sample of the US population.Main Outcome Measure Age-adjusted prevalence of overweight, obesity, and extreme obesity compared with prior surveys, and sex-, age-, and race/ethnicity–specific estimates.Results The age-adjusted prevalence of obesity was 30.5% in 1999-2000 compared with 22.9% in NHANES III (1988-1994; P<.001). The prevalence of overweight also increased during this period from 55.9% to 64.5% (P<.001). Extreme obesity (BMI ≥40) also increased significantly in the population, from 2.9% to 4.7% (P = .002). Although not all changes were statistically significant, increases occurred for both men and women in all age groups and for non-Hispanic whites, non-Hispanic blacks, and Mexican Americans. Racial/ethnic groups did not differ significantly in the prevalence of obesity or overweight for men. Among women, obesity and overweight prevalences were highest among non-Hispanic black women. More than half of non-Hispanic black women aged 40 years or older were obese and more than 80% were overweight.Conclusions The increases in the prevalences of obesity and overweight previously observed continued in 1999-2000. The potential health benefits from reduction in overweight and obesity are of considerable public health importance.
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In this study, we analyzed age variation in the association between obesity status and US adult mortality risk. Previous studies have found that the association between obesity and mortality risk weakens with age. We argue that existing results were derived from biased estimates of the obesity-mortality relationship because models failed to account for confounding influences from respondents' ages at survey and/or cohort membership. We employed a series of Cox regression models in data from 19 cross-sectional, nationally representative waves of the US National Health Interview Survey (1986-2004), linked to the National Death Index through 2006, to examine age patterns in the obesity-mortality association between ages 25 and 100 years. Findings suggest that survey-based estimates of age patterns in the obesity-mortality relationship are significantly confounded by disparate cohort mortality and age-related survey selection bias. When these factors are accounted for in Cox survival models, the obesity-mortality relationship is estimated to grow stronger with age. © 2013 © The Author 2013. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: [email protected] /* */
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Estimates of the relative mortality risks associated with normal weight, overweight, and obesity may help to inform decision making in the clinical setting. To perform a systematic review of reported hazard ratios (HRs) of all-cause mortality for overweight and obesity relative to normal weight in the general population. PubMed and EMBASE electronic databases were searched through September 30, 2012, without language restrictions. Articles that reported HRs for all-cause mortality using standard body mass index (BMI) categories from prospective studies of general populations of adults were selected by consensus among multiple reviewers. Studies were excluded that used nonstandard categories or that were limited to adolescents or to those with specific medical conditions or to those undergoing specific procedures. PubMed searches yielded 7034 articles, of which 141 (2.0%) were eligible. An EMBASE search yielded 2 additional articles. After eliminating overlap, 97 studies were retained for analysis, providing a combined sample size of more than 2.88 million individuals and more than 270,000 deaths. Data were extracted by 1 reviewer and then reviewed by 3 independent reviewers. We selected the most complex model available for the full sample and used a variety of sensitivity analyses to address issues of possible overadjustment (adjusted for factors in causal pathway) or underadjustment (not adjusted for at least age, sex, and smoking). Random-effects summary all-cause mortality HRs for overweight (BMI of 25-<30), obesity (BMI of ≥30), grade 1 obesity (BMI of 30-<35), and grades 2 and 3 obesity (BMI of ≥35) were calculated relative to normal weight (BMI of 18.5-<25). The summary HRs were 0.94 (95% CI, 0.91-0.96) for overweight, 1.18 (95% CI, 1.12-1.25) for obesity (all grades combined), 0.95 (95% CI, 0.88-1.01) for grade 1 obesity, and 1.29 (95% CI, 1.18-1.41) for grades 2 and 3 obesity. These findings persisted when limited to studies with measured weight and height that were considered to be adequately adjusted. The HRs tended to be higher when weight and height were self-reported rather than measured. Relative to normal weight, both obesity (all grades) and grades 2 and 3 obesity were associated with significantly higher all-cause mortality. Grade 1 obesity overall was not associated with higher mortality, and overweight was associated with significantly lower all-cause mortality. The use of predefined standard BMI groupings can facilitate between-study comparisons.
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Objective: Funnel plots (plots of effect estimates against sample size) may be useful to detect bias in meta-analyses that were later contradicted by large trials. We examined whether a simple test of asymmetry of funnel plots predicts discordance of results when meta-analyses are compared to large trials, and we assessed the prevalence of bias in published meta-analyses. Design: Medline search to identify pairs consisting of a meta-analysis and a single large trial (concordance of results was assumed if effects were in the same direction and the meta-analytic estimate was within 30
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Two methods for point and interval estimation of relative risk for log-linear exposure-response relations in meta-analyses of published ordinal categorical exposure-response data have been proposed. The authors compared the results of a meta-analysis of published data using each of the 2 methods with the results that would be obtained if the primary data were available and investigated the circumstances under which the approximations required for valid use of each meta-analytic method break down. They then extended the methods to handle nonlinear exposure-response relations. In the present article, methods are illustrated using studies of the relation between alcohol consumption and colorectal and lung cancer risks from the ongoing Pooling Project of Prospective Studies of Diet and Cancer. In these examples, the differences between the results of a meta-analysis of summarized published data and the pooled analysis of the individual original data were small. However, incorrectly assuming no correlation between relative risk estimates for exposure categories from the same study gave biased confidence intervals for the trend and biased P values for the tests for nonlinearity and between-study heterogeneity when there was strong confounding by other model covariates. The authors illustrate the use of 2 publicly available user-friendly programs (Stata and SAS) to implement meta-analysis for dose-response data.
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To describe the relationship of body mass index and mortality in older adults, examining the influence of sex and cardiovascular morbidity. Sixteen-year cohort of a population sample of 1,008 people aged 65 and over. BMI mortality hazard ratios are estimated controlling for age, sex, education, physical activity, smoking, chronic conditions, and ADL (activities of daily living) disability. At baseline the median BMI is 26.8 (Interquartile range: 24.2-29.7 Kg/m(2)). Findings show that during 16 years there were 672 deaths. The U-shaped curve of the mortality hazard by BMI is wide. The minimum mortality occur at BMI = 30.5 Kg/m(2). Findings show that men had lower mortality risk with increasing BMI and that cardiovascular disease was associated with high mortality in the low-BMI category. Underweight is a risk factor for mortality among elderly people, whereas overweight and mild obesity are associated with the lowest mortality particularly among men and those with cardiovascular morbidity.
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The impact of body mass index (BMI; kg/m(2)) and waist circumference (WC) on mortality in elderly individuals is controversial and previous research has largely focused on obesity. With special attention to the lower BMI categories, associations between BMI and both total and cause-specific mortality were explored in 7604 men and 9107 women aged ≥ 65 years who participated in the Tromsø Study (1994-1995) or the North-Trøndelag Health Study (1995-1997). A Cox proportional hazards model adjusted for age, marital status, education and smoking was used to estimate HRs for mortality in different BMI categories using the BMI range of 25-27.5 as a reference. The impact of each 2.5 kg/m(2) difference in BMI on mortality in individuals with BMI < 25.0 and BMI ≥ 25.0 was also explored. Furthermore, the relations between WC and mortality were assessed. We identified 7474 deaths during a mean follow-up of 9.3 years. The lowest mortality was found in the BMI range 25-29.9 and 25-32.4 in men and women, respectively. Mortality was increased in all BMI categories below 25 and was moderately increased in obese individuals. U-shaped relationships were also found between WC and total mortality. About 40% of the excess mortality in the lower BMI range in men was explained by mortality from respiratory diseases. BMI below 25 in elderly men and women was associated with increased mortality. A modest increase in mortality was found with increasing BMI among obese men and women. Overweight individuals (BMI 25-29.9) had the lowest mortality.
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A high body-mass index (BMI, the weight in kilograms divided by the square of the height in meters) is associated with increased mortality from cardiovascular disease and certain cancers, but the precise relationship between BMI and all-cause mortality remains uncertain. We used Cox regression to estimate hazard ratios and 95% confidence intervals for an association between BMI and all-cause mortality, adjusting for age, study, physical activity, alcohol consumption, education, and marital status in pooled data from 19 prospective studies encompassing 1.46 million white adults, 19 to 84 years of age (median, 58). The median baseline BMI was 26.2. During a median follow-up period of 10 years (range, 5 to 28), 160,087 deaths were identified. Among healthy participants who never smoked, there was a J-shaped relationship between BMI and all-cause mortality. With a BMI of 22.5 to 24.9 as the reference category, hazard ratios among women were 1.47 (95 percent confidence interval [CI], 1.33 to 1.62) for a BMI of 15.0 to 18.4; 1.14 (95% CI, 1.07 to 1.22) for a BMI of 18.5 to 19.9; 1.00 (95% CI, 0.96 to 1.04) for a BMI of 20.0 to 22.4; 1.13 (95% CI, 1.09 to 1.17) for a BMI of 25.0 to 29.9; 1.44 (95% CI, 1.38 to 1.50) for a BMI of 30.0 to 34.9; 1.88 (95% CI, 1.77 to 2.00) for a BMI of 35.0 to 39.9; and 2.51 (95% CI, 2.30 to 2.73) for a BMI of 40.0 to 49.9. In general, the hazard ratios for the men were similar. Hazard ratios for a BMI below 20.0 were attenuated with longer-term follow-up. In white adults, overweight and obesity (and possibly underweight) are associated with increased all-cause mortality. All-cause mortality is generally lowest with a BMI of 20.0 to 24.9.
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To investigate the relationship between mortality and BMI in older people, taking into account other established mortality risk factors. A total of 3,646 French community dwellers aged 65 years and older from PAQUID cohort study were included. Cox proportional-hazards analysis was used to assess association between BMI and mortality. Death occurred in 54.1% of the cohort more than 13 years: 68.99% of the underweight (BMI <19), 52.13% of the obese (BMI >30), 51.66% of the overweight (BMI 25-30), and 51.79% of the reference participants (BMI 22-25) died.The relative risk of death as a function of BMI, adjusted for gender and age, formed a U-shaped pattern, with larger risks associated with lower BMI (<22.0) and for BMI of 25.0 to 30.0 and BMI >/=30. (BMI 22.0-24.9 was the reference.) After adjustment for demographic factors, smoking history, and comorbidity, increased mortality risk persisted in underweight older people, BMI <18.5 and BMI 18.5-22 (respectively, HR = 1.45, 95% CI 1.17-1.78; HR = 1.27, 95% CI 1.12-1.43) compared with reference. Overweight (BMI 25-29.9) and obesity (>/=30) were not associated with increased mortality compared with the reference category (respectively, HR = 0.98, 95% IC 0.88-1.10; HR = 1.06, 95% IC 0.89-1.27). Similar relationships persisted for disabled participant. For nondisabled participant disability did not alter the associations for BMI of 25.0 and higher but for BMI less than 22.0, the risks become insignificantly different from those for the reference group. BMI below 22 kg/ m(2) is a risk factor for 13-year mortality in older people, but our findings suggest that overweight and obesity may not be associated to mortality after adjustment for established mortality risk factors.
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Low body mass index (BMI) and low cardiorespiratory fitness (CRF) are independently associated with increased mortality in the elderly. However, interactions among BMI, CRF, and mortality in older persons have not been adequately explored. Hazard ratios (HRs) were calculated for predetermined strata of BMI and CRF. Independent and joint associations of CRF, BMI, and all-cause mortality were assessed by Cox proportional hazards analyses in a prospective cohort of 981 healthy men aged at least 65 years (mean age [+/-SD], 71 [+/-5] years; range, 65-88 years) referred for exercise testing during 1987-2003. During a mean follow-up of 6.9 +/- 4.4 years, a total of 208 patients died. Multivariate relative risks (95% confidence interval [CI]) of mortality across BMI groups of <20.0, 20.0-25.0, 25.0-29.9, 30.0-34.9, and > or =35.0 were 2.51 (1.26-4.98), 1.0 (reference), 0.66 (0.48-0.90), 0.50 (0.31-0.78), and 0.44 (0.20-0.97), respectively, and across CRF groups of <5.0, 5.0-8.0, and >8.0 metabolic equivalents were 1.0 (reference), 0.56 (0.40-0.78), and 0.39 (0.26-0.58), respectively. In a separate analysis of within-strata CRF according to BMI grouping, the lowest mortality risk was observed in obese men with high fitness (HR [95% CI] 0.26 [0.10-0.69]; p = .007). In this cohort of elderly male veterans, we observed independent and joint inverse relations of BMI and CRF to mortality. This warrants further investigation of fitness, fatness, and mortality interactions in older persons.
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Funnel plots (plots of effect estimates against sample size) may be useful to detect bias in meta-analyses that were later contradicted by large trials. We examined whether a simple test of asymmetry of funnel plots predicts discordance of results when meta-analyses are compared to large trials, and we assessed the prevalence of bias in published meta-analyses. Medline search to identify pairs consisting of a meta-analysis and a single large trial (concordance of results was assumed if effects were in the same direction and the meta-analytic estimate was within 30% of the trial); analysis of funnel plots from 37 meta-analyses identified from a hand search of four leading general medicine journals 1993-6 and 38 meta-analyses from the second 1996 issue of the Cochrane Database of Systematic Reviews. Degree of funnel plot asymmetry as measured by the intercept from regression of standard normal deviates against precision. In the eight pairs of meta-analysis and large trial that were identified (five from cardiovascular medicine, one from diabetic medicine, one from geriatric medicine, one from perinatal medicine) there were four concordant and four discordant pairs. In all cases discordance was due to meta-analyses showing larger effects. Funnel plot asymmetry was present in three out of four discordant pairs but in none of concordant pairs. In 14 (38%) journal meta-analyses and 5 (13%) Cochrane reviews, funnel plot asymmetry indicated that there was bias. A simple analysis of funnel plots provides a useful test for the likely presence of bias in meta-analyses, but as the capacity to detect bias will be limited when meta-analyses are based on a limited number of small trials the results from such analyses should be treated with considerable caution.
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The US Clinical Guidelines on the Identification, Evaluation, and Treatment of Overweight and Obesity in Adults set the body mass index (BMI; weight in kilograms divided by the square of height in meters) of 25 as the upper limit of ideal weight for all adults regardless of age. However, the prognostic importance of overweight and obesity in elderly persons (>/=65 years) is controversial. We sought to analyze the guidelines in the context of currently available evidence that is relevant to older adults. We searched MEDLINE for all English-language studies of the association between BMI and all-cause or cardiovascular mortality or coronary heart disease events from January 1966 through October 1999. Additional pertinent articles were identified through bibliographies of the MEDLINE articles. We selected studies for detailed review if they reported on the association between BMI and mortality for nonhospitalized subjects who were 65 years or older and had been followed up for at least 3 years. We controlled for age, smoking, and baseline health status. Of the 444 screened articles, 13 were selected to assess the guidelines. We extracted information regarding publication year, study design, population, recruitment period, follow-up duration, number of subjects, sex, age range, inclusion and exclusion criteria, and statistical models, including variables and end points. These data do not support the BMI range of 25 to 27 as a risk factor for all-cause and cardiovascular mortality among elderly persons. The results were not substantially different for men and women. Most studies showed a negative or no association between BMI and all-cause mortality. Three studies indicated overweight (BMI >/=27) as a significant prognostic factor for all-cause and cardiovascular mortality among 65- to 74-year-olds, and one study showed a significant positive association between overweight (BMI >/=28) and all-cause mortality among those 75 years or older. Higher BMI values were consistent with a smaller relative mortality risk in elderly persons compared with young and middle-aged populations. Federal guideline standards for ideal weight (BMI 18.7 to <25) may be overly restrictive as they apply to the elderly. Studies do not support overweight, as opposed to obesity, as conferring an excess mortality risk. Future guidelines should consider the evidence for specific age groups when establishing standards for healthy weight.
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To examine the relationship between body mass index (BMI) at age 70, weight change between age 70 and 75, and 15 y mortality. Cohort study of 70-y-olds. Geriatric Medicine Department, Göteborg University, Sweden. A total of 2628 (1225 males and 1403 females) 70-y-olds examined in 1971--1981 in Gothenburg, Sweden. The relative risks (RRs) for 15 y mortality were highest in the lowest BMI quintiles of males 1.20 (95% CI 0.96--1.51) and females 1.49 (95% CI 1.14--1.96). In non-smoking males, no significant differences were observed across the quintiles for 5, 10 and 15 y mortality. In non-smoking females, the highest RR (1.58, 95% CI 1.15--2.16) for 15 y mortality was in the lowest quintile. After exclusion of first 5 y death, no excess risks were found in males for following 5 and 10 y mortality across the quintiles. In females, a U-shaped relation was observed after such exclusions. BMI ranges with lowest 15 y mortality were 27--29 and 25--27 kg/m(2) in non-smoking males and females, respectively. A weight loss of > or = 10% between age 70 and 75 meant a significantly higher risk for subsequent 5 and 10 y mortality in both sexes relative to individuals with 'stable' weights. Low BMI and weight loss are risk factors for mortality in the elderly and smoking habits did not significantly modify that relationship. The BMI ranges with lowest risks for 15 y mortality are relatively higher in elderly. Exclusion of early deaths from the analysis modified the weight-mortality relationship in elderly males but not in females.
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The relation between relative weight and health differs between young and old. In older populations, weight change may cloud the association between a single relative weight and health outcomes. To determine whether weight or weight change is a more important determinant of mortality in a population of older adults, the authors analyzed data from the Systolic Hypertension in the Elderly Program (1984-1990), a randomized clinical trial testing the efficacy of antihypertensive drug treatment to reduce the risk of stroke in older adults (aged 60 years or more) with isolated systolic hypertension. After adjustment for covariates, an average annualized weight loss of at least 1.6 kg/year (odds ratio = 4.9), a weight loss between 1.6 and 0.7 kg/year (odds ratio = 1.7), a weight gain of more than 0.5 kg/year (odds ratio = 2.4), and a baseline body mass index of less than 23.6 (odds ratio = 1.4) all had a significant (p < 0.05) association with all-cause mortality compared with a referent group that was weight stable and of intermediate body mass index (23.6 to <28.0 kg/m(2)) and weight change (-0.7 to <0.5 kg/year). The authors conclude that, in older adults, dynamic measures (e.g., annualized weight change) of weight change predict mortality better than do static weight measures (e.g., baseline body mass index). Even in those with high or low baseline body mass index, weight stability is associated with a lower mortality risk.
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This paper presents a command, glst, for trend estimation across different exposure levels for either single or multiple summarized case-control, incidence-rate, and cumulative incidence data. This approach is based on constructing an approximate covariance estimate for the log relative risks and estimating a corrected linear trend using generalized least squares. For trend analysis of multiple studies, glst can estimate fixed- and random-effects metaregression models. Copyright 2006 by StataCorp LP.
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For the elderly, the association between waist circumference (WC) and mortality considering body mass index (BMI) remains unclear, and thereby also the evidence base for using these anthropometric measures in clinical practice. This meta-analysis examined the association between WC categories and (cause-specific) mortality within BMI categories. Furthermore, the association of continuous WC with lowest and increased mortality risks was examined. Age- and smoking-adjusted relative risks (RRs) of mortality associated with WC-BMI categories and continuous WC (including WC and WC(2)) were calculated by the investigators and pooled by means of random-effects models. During a 5-year-follow-up of 32 678 men and 25 931 women, we ascertained 3318 and 1480 deaths, respectively. A large WC (men: ≥102 cm, women: ≥88 cm) was associated with increased all-cause mortality RRs for those in the 'healthy' weight {1.7 [95% confidence interval (CI): 1.2-2.2], 1.7 (95% CI: 1.3-2.3)}, overweight [1.1(95% CI: 1.0-1.3), 1.4 (95%: 1.1-1.7)] and obese [1.1 (95% CI: 1.0-1.3), 1.6 (95% CI: 1.3-1.9)] BMI category compared with the 'healthy' weight (20-24.9 kg/m(2)) and a small WC (<94 cm, men; <80 cm, women) category. Underweight was associated with highest all-cause mortality RRs in men [2.2 (95% CI: 1.8-2.8)] and women [2.3 (95% CI: 1.8-3.1]. We found a J-shaped association for continuous WC with all-cause, cardiovascular (CVD) and cancer, and a U-shaped association with respiratory disease mortality (P < 0.05). An all-cause (CVD) mortality RR of 2.0 was associated with a WC of 132 cm (123 cm) in men and 116 cm (105 cm) in women. Our results showed increased mortality risks for elderly people with an increased WC-even across BMI categories- and for those who were classified as 'underweight' using BMI. The results provide a solid basis for re-evaluation of WC cut-points in ageing populations.
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A WHO expert consultation addressed the debate about interpretation of recommended body-mass index (BMI) cut-off points for determining overweight and obesity in Asian populations, and considered whether population-specific cut-off points for BMI are necessary. They reviewed scientific evidence that suggests that Asian populations have different associations between BMI, percentage of body fat, and health risks than do European populations. The consultation concluded that the proportion of Asian people with a high risk of type 2 diabetes and cardiovascular disease is substantial at BMIs lower than the existing WHO cut-off point for overweight (greater than or equal to25 kg/m(2)). However, available data do not necessarily indicate a clear BMI cut-off point for all Asians for overweight or obesity. The cut-off point for observed risk varies from 22 kg/m(2) to 25 kg/m(2) in different Asian populations; for high risk it varies from 26 kg/m(2) to 31 kg/m(2). No attempt was made, therefore, to redefine cut-off points for each population separately. The consultation also agreed that the WHO BMI cut-off points should be retained as international classifications. The consultation identified further potential public health action, points (23.0, 27.5, 32.5, and 37.5 kg/m(2)) along the continuum of BMI, and proposed methods by which countries could make decisions about the definitions of increased risk for their population.
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The relation between relative weight and health differs between young and old. In older populations, weight change may cloud the association between a single relative weight and health outcomes. To determine whether weight or weight change is a more important determinant of mortality in a population of older adults, the authors analyzed data from the Systolic Hypertension in the Elderly Program (1984-1990), a randomized clinical trial testing the efficacy of antihypertensive drug treatment to reduce the risk of stroke in older adults (aged 60 years or more) with isolated systolic hypertension. After adjustment for covariates, an average annualized weight loss of at least 1.6 kg/year (odds ratio = 4.9), a weight loss between 1.6 and 0.7 kg/year (odds ratio = 1.7), a weight gain of more than 0.5 kg/year (odds ratio = 2.4), and a baseline body mass index of less than 23.6 (odds ratio = 1.4) all had a significant (p < 0.05) association with all-cause mortality compared with a referent group that was weight stable and of intermediate body mass index (23.6 to <28.0 kg/m 2 ) and weight change (-0.7 to <0.5 kg/year). The authors conclude that, in older adults, dynamic measures (e.g., annualized weight change) of weight change predict mortality better than do static weight measures (e.g., baseline body mass index). Even in those with high or low baseline body mass index, weight stability is associated with a lower mortality risk.
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To examine how body mass index (BMI) and change in BMI are associated with mortality in old (70–79) and very old (≥80) individuals. Pooled data from three multidisciplinary prospective population-based studies: OCTO-twin, Gender, and NONA. Sweden. Eight hundred eighty-two individuals aged 70 to 95. BMI was calculated from measured height and weight as kg/m2. Information about survival status and time of death was obtained from the Swedish Civil Registration System. Mortality hazard was 20% lower for the overweight group than the normal–underweight group (relative risk (RR) = 0.80, P = .011), and the mortality hazard for the obese group did not differ significantly from that of the normal–underweight group (RR = 0.93, P = .603), independent of age, education, and multimorbidity. Furthermore, mortality hazard was 65% higher for the BMI loss group than for the BMI stable group (RR = 1.65, P < .001) and 53% higher for the BMI gain group than for the BMI stable group (RR = 1.53, P = .001). Age moderated the BMI change differences. That is, the higher mortality risks associated with BMI loss and gain were less severe in very old age. Old persons who were overweight had a lower mortality risk than old persons who were of normal weight, even after controlling for weight change and multimorbidity. Persons who increased or decreased in BMI had a greater mortality risk than those who had a stable BMI, particularly those aged 70 to 79. This study lends further support to the belief that the World Health Organization guidelines for BMI are overly restrictive in old age.
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Objectives: To identify predictors and consequences of nutritional risk, as determined by the Mini Nutritional Assessment (MNA), in older recipients of domiciliary care services living at home. Design: Baseline analysis of subject characteristics with low MNA scores (<24) and follow-up of the consequences of these low scores. Setting: South Australia. Participants: Two hundred fifty domiciliary care clients (aged 67-99, 173 women). Measurements: Baseline history and nutritional status were determined. Information about hospitalization was obtained at follow-up 12 months later. Intervention: Letters suggesting nutritional intervention were sent to general practitioners of subjects not well nourished. Results: At baseline, 56.8% were well nourished, 38.4% were at risk of malnutrition, and 4.8% were malnourished (43.2% not well nourished). Independent predictors of low MNA scores (<24) were living alone, and the physical and mental component scales of the 36-item Short Form Health Survey. Follow-up information was obtained for 240 subjects (96%). In the ensuing year not well-nourished subjects were more likely than well-nourished subjects to have been admitted to the hospital (risk ratio (RR) = 1.51, 95% confidence interval (CI) = 1.07-2.14), have two or more emergency hospital admissions (RR = 2.96, 95% CI = 1.15-7.59), spend more than 4 weeks in the hospital (RR = 3.22, 95% CI = 1.29-8.07), fall (RR = 1.65, 95% CI = 1.13-2.41), and report weight loss (RR = 2.63, 95% CI = 1.67-4.15). Conclusion: The MNA identified a large number of subjects with impaired nutrition who did significantly worse than well-nourished subjects during the following year. Studies are needed to determine whether nutritional or other interventions in people with low MNA scores can improve clinical outcomes.
Article
Objective: To determine the excess mortality associated with obesity (defined by body mass index (BMI)) in older people, with and without adjustment for other risk factors associated with mortality and for demographic factors. Design: Retrospective cohort analysis of the Longitudinal Study of Aging (LSOA). Setting: Nationally representative sample of community-dwelling older people. Participants: Seven thousand five hundred and twenty-seven participants age 70 and older in 1984. Measurements: We used Cox regression to calculate proportional hazards ratios for mortality over 96 months. We tested the hypothesis that increased BMI (top 15%) increased mortality rates in older people. Results: Death occurred in 38% of the cohort: 54% of the thin (lowest 10% of the population, BMI <19.4 kg/m(2)), 33% of the obese (highest 15%, BMI> 28.5 kg/m(2)), and 37% of the remaining participants (normal) died. Adjustment for demographic factors, health services utilization, and functional status still demonstrated reduced mortality in obese older people (hazard ratio 0.86, 95% confidence interval (CI) = 0.77-0.97) compared with normal. After adjustment, thin older people remained more likely to die (hazard ratio 1.46, 95% CI = 1.30-1.64) than normal older people. Sensitivity analyses for income, mortality during the first two years of follow-up, and medical comorbidities did not substantively alter the conclusions. Conclusion: Obesity may be protective compared with thinness or normal weight in older community-dwelling Americans.