scholarly journals Drivers of Frailty from Adulthood into Old Age: Results from a 27-Year Longitudinal Population-Based Study in Sweden

2020 ◽  
Vol 75 (10) ◽  
pp. 1943-1950 ◽  
Author(s):  
Emma Raymond ◽  
Chandra A Reynolds ◽  
Anna K Dahl Aslan ◽  
Deborah Finkel ◽  
Malin Ericsson ◽  
...  
Keyword(s):  
Social Support ◽  
Strong Predictor ◽  
Frailty Index ◽  
Overweight And Obesity ◽  
Adverse Outcomes ◽  
Rate Of Change ◽  
Growth Curve Analysis ◽  
Factors Associated ◽  
Age Related ◽  
Time Varying Covariates

Abstract Background Frailty is a strong predictor of adverse outcomes. However, longitudinal drivers of frailty are not well understood. This study aimed at investigating the longitudinal trajectories of a frailty index (FI) from adulthood to late life and identifying the factors associated with the level and rate of change in FI. Methods An age-based latent growth curve analysis was performed in the Swedish Adoption/Twin Study of Aging (N = 1,842; aged 29–102 years) using data from up to 15 measurement waves across 27 years. A 42-item FI was used to measure frailty at each wave. Results A bilinear, two-slope model with a turning point at age 65 best described the age-related change in FI, showing that the increase in frailty was more than twice as fast after age 65. Underweight, obesity, female sex, overweight, being separated from one’s co-twin during childhood, smoking, poor social support, and low physical activity were associated with a higher FI at age 65, with underweight having the largest effect size. When tested as time-varying covariates, underweight and higher social support were associated with a steeper increase in FI before age 65, whereas overweight and obesity were associated with less steep increase in FI after age 65. Conclusions Factors associated with the level and rate of change in frailty are largely actionable and could provide targets for intervention. As deviations from normal weight showed the strongest associations with frailty, future public health programs could benefit from monitoring of individuals with abnormal BMI, especially those who are underweight.

scholarly journals Drivers of Frailty from Adulthood into Old Age: Results from a 27-year Longitudinal Population-Based Study in Sweden

2019 ◽  
Author(s):  
Emma Raymond ◽  
Chandra A. Reynolds ◽  
Anna K. Dahl Aslan ◽  
Deborah Finkel ◽  
Malin Ericsson ◽  
...  
Keyword(s):  
Social Support ◽  
Strong Predictor ◽  
Frailty Index ◽  
Population Based ◽  
Overweight And Obesity ◽  
Rate Of Change ◽  
Growth Curve Analysis ◽  
Age Related ◽  
Rate Of Increase ◽  
Latent Growth Curve Analysis

AbstractBackgroundFrailty is a strong predictor of adverse aging outcomes. However, the longitudinal drivers of frailty are not well understood. This study aimed at investigating the longitudinal trajectories of a frailty index (FI) from adulthood to late life and identifying the predictors of the level and rate of change in FI.MethodsAn age-based latent growth curve analysis was performed in the Swedish Adoption/Twin Study of Aging (N=1,842; aged 29-102 years) using data from up to 15 measurement waves across 27 years. A 42-item FI was used to measure frailty at each wave.ResultsA bilinear, two-slope model with a turning point at age 65 best described the age-related change in FI, showing that the rate of increase in frailty was more than twice as fast after age 65. Underweight, obesity, female sex, overweight, being separated from one’s co-twin during childhood, smoking, poor social support and low physical activity were associated with a higher level of FI at age 65, with underweight having the largest effect size. When tested as time-varying predictors, underweight and higher social support were associated with a steeper increase in FI before age 65, whereas overweight and obesity were associated with less steep increase in FI after age 65.ConclusionsPredictors for the level and rate of change in frailty are largely actionable and could provide targets for intervention. Underweight increased the risk of higher FI trajectory until age 65, whereas being overweight or obese were associated with slower progression of frailty towards the oldest ages.

scholarly journals The prevalence and correlates of pre-diabetes in middle- to older-aged Irish adults using three diagnostic methods

PLoS ONE ◽  
2021 ◽  
Vol 16 (6) ◽  
pp. e0253537
Author(s):  
Kate Junker ◽  
Claire M. Buckley ◽  
Seán R. Millar ◽  
Sinéad Flynn ◽  
Janas M. Harrington ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Strong Predictor ◽  
Multivariable Analysis ◽  
Overweight And Obesity ◽  
Diagnostic Methods ◽  
World Health ◽  
Expert Committee ◽  
Cross Sectional ◽  
Factors Associated

Background and objectives Type 2 diabetes is a leading cause of death and disability worldwide and pre-diabetes is a strong predictor of diabetes development. To date, studies estimating the prevalence of pre-diabetes in the Irish population are sparse and conflicting. Monitoring the prevalence of pre-diabetes and a knowledge of associated factors is required to inform policies and to prevent development of type 2 diabetes. Therefore, this research examined the prevalence and correlates of pre-diabetes in a sample of middle- to older-aged Irish adults using three different methods for diagnosis. Materials and methods The Mitchelstown Cohort Rescreen (2016/17) was a follow-up, cross-sectional study of the Mitchelstown Cohort Study (2010/11). 1,378 participants were recruited from a random sample of patients attending a single primary care centre. Pre-diabetes was defined using three diagnostic criteria: American Diabetes Association (ADA) glycated haemoglobin A1c (HbA1c) cut-offs between 5.7%–6.4% (39–46 mmol/mol), World Health Organization International Expert Committee (WHO-IEC) HbA1c cut-offs between 6.0%–6.4% (42–46 mmol/mol) and ADA fasting plasma glucose (FPG) cut-offs between 5.6–6.9 mmol/l. Univariate and multivariable logistic regression analyses were used to determine factors associated with pre-diabetes. Results The prevalence of pre-diabetes was found to be 43.9% (95% CI: 41.2%─46.5%), 14.5% (95% CI: 12.7%─16.5%) and 15.8% (95% CI: 13.9%─17.8%) according to HbA1c ADA, HbA1c WHO-IEC and FPG ADA definitions, respectively. Depending on diagnostic method, factors associated with pre-diabetes in univariate analyses included sex, age, marital status, health rating, education and poor diet quality. In multivariable analysis, subjects classified by the FPG ADA pre-diabetes criterion displayed the least optimal metabolic profile defined by overweight and obesity (OR = 2.88, 95% CI: 1.53–5.43), hypertension (OR = 2.27, 95% CI: 1.51–3.40) and low high-density lipoprotein cholesterol concentrations (OR = 1.75, 95% CI: 1.07–2.87). Conclusions The discordance between prevalence estimates according to method of diagnosis is concerning. A National Diabetes Prevention Programme is currently being developed in Ireland. Monitoring the prevalence of pre-diabetes over time will be important to assess the effectiveness of this programme. This study will inform national decision-makers on which definition of pre-diabetes to use for monitoring purposes.

14 A Systematic Review of the Prevalence and Implications of Frailty in Diabetes Mellitus

2021 ◽  
Vol 50 (Supplement_1) ◽  
pp. i1-i6
Author(s):  
P Hanlon ◽  
I Faure ◽  
N Corcoran ◽  
E Butterly ◽  
J Lewsey ◽  
...  
Keyword(s):  
Systematic Review ◽  
Frailty Index ◽  
Vascular Complications ◽  
Adverse Outcomes ◽  
Middle Aged ◽  
Frailty Phenotype ◽  
Age Related ◽  
Low Middle Income Countries ◽  
The Impact ◽  
The Relationship

Abstract Background Frailty, an age-related state of vulnerability to adverse health outcomes, is an important factor in the management of diabetes. This systematic review aims to summarise the observational data on prevalence of frailty in diabetes and the association between frailty and generic (e.g. mortality) and diabetes specific (e.g. hypoglycaemia) outcomes. Methods We searched three electronic databases for observational studies assessing frailty in adults (≥18 years) with diabetes (type 1, type 2, or unspecified). Eligible studies quantified the prevalence or incidence of frailty or the association between frailty and clinical outcomes in the context of diabetes. Results 118 studies included, using 18 different frailty measures. Frailty phenotype was the most used (n = 69) followed by frailty index (n = 16) and the FRAIL scale (n = 10). Studies were highly heterogenous in terms of setting (88 community, 18 outpatient, 10 inpatient, 2 residential care), population demographics, and inclusion criteria. The median frailty prevalence in community-based studies using the frailty phenotype was 13% (interquartile range 7-18%). Frailty was identified in “middle-aged” (<65 years) as well as older people with diabetes. Diabetes was consistently associated with incident frailty. Frailty was associated with higher mortality, hospital admission, incident disability. Frailty was associated with hypoglycemic events in 1/1 study. Frailty was also associated cross-sectionally with micro- and macro-vascular complications, lower quality of life, and cognitive impairment. Frailty was not associated with difference in mean HbA1c, however people with frailty were more likely to have high (>9%) or low (<6.5%) HbA1c. Conclusions Frailty in diabetes is common but inconsistently measured. Frailty is associated with a range of adverse outcomes. Research gaps include the relationship between frailty and glycaemia (particularly hypoglycaemia and the relationship between HbA1c and outcomes in the context of frailty), and the impact of frailty in specific groups such as middle-aged people and in low and low-middle income countries.

scholarly journals Management of Frailty and its Challenges in Geriatric Patients on General Abdominal Anesthesia.

2021 ◽  
Vol 5 (1) ◽  
pp. 785-790
Author(s):  
Majlinda Naço ◽  
Haxhire Gani ◽  
Monika Belba ◽  
Suzana Mukaj ◽  
Nertila Kodra ◽  
...  
Keyword(s):  
Geriatric Patients ◽  
Strong Predictor ◽  
Frailty Index ◽  
Early Mobilization ◽  
Adverse Outcomes ◽  
Clinical Frailty Scale ◽  
Operative Morbidity ◽  
Operative Care ◽  
Patient Will ◽  
Organ Specific

Introduction: In that material, we are doing to informed for frailty, how we can measure it, surgical outcome and its management from the anesthesiologist. Frailty is a condition of decreased physiological reserves that often increases with increasing age and decided in adverse outcomes. Frailty in elderly surgical patients may be varied from 25,5 -56.1% and is a strong predictor for surgical outcomes. The anesthetist needs to predict how a geriatric patient will tolerate the stress of surgery and to do what is necessary to protect and save elderly lives. In Albania, there are almost 439 000 elderly people in 2021 and suspect to 626 000 in 2051. According to the WHO, 1 in 25 persons performed surgery, so the number of geriatric patients that done surgery will be very high. According to deficits’ in function, mobility, cognition, chronic diseases, and geriatric syndromes we can use the clinical frailty scale, the Edmonton Frailty Scale, or frailty index for calculation of frailty. We need frailty patients to evaluated preoperative risk-classification, intra-operative care, management of general anesthesia, early immobilization as well as treatment of postoperative delirium because frailty increased intra-operative morbidity, increased postoperative complications especially delirium, extends hospitalization, non – home discharge, and mortality. Anesthesiologists would be always aware to prepare the geriatric patients for surgery, to maintain the intra-operative functional reserve of frailty patients, to manage perfect anesthesia, to realized early mobilization, and discharge back home. Conclusion: Many geriatric patients have multi-organ problems. Frailty is a practical, unifying concept in the care of these older people that directs attention away from organ-specific diagnoses towards a more holistic viewpoint of the patient and their medical medicament. All geriatric patients need to screen for frailty.

scholarly journals Using an electronic frailty index to predict adverse outcomes in geriatric COVID-19 patients: data from the Stockholm GeroCovid study

2021 ◽  
Author(s):  
Jonathan K. L. Mak ◽  
Maria Eriksdotter ◽  
Martin Annetorp ◽  
Ralf Kuja-Halkola ◽  
Laura Kananen ◽  
...  
Keyword(s):  
Length Of Stay ◽  
Hospital Mortality ◽  
Cox Regression ◽  
Predictive Accuracy ◽  
Strong Predictor ◽  
Characteristic Curve ◽  
Frailty Index ◽  
Predictive Ability ◽  
Adverse Outcomes ◽  
Clinical Frailty Scale

ABSTRACTBackgroundThe Clinical Frailty Scale (CFS) is a strong predictor for worse outcomes in geriatric COVID-19 patients, but it is less clear whether an electronic frailty index (eFI) constructed from routinely collected electronic health records (EHRs) provides similar predictive value. This study aimed to investigate the predictive ability of an eFI in comparison to other frailty and comorbidity measures, using mortality, readmission, and the length of stay as outcomes in geriatric COVID-19 patients.MethodsWe conducted a retrospective cohort study using EHRs from nine geriatric clinics in Stockholm, Sweden, comprising 3,405 COVID-19 patients (mean age 81.9 years) between 1/3/2020 and 31/10/2021. Frailty was assessed using a 48-item eFI developed for Swedish geriatric patients, the CFS, and Hospital Frailty Risk Score (HFRS). Comorbidity was measured using the Charlson Comorbidity Index (CCI). We analyzed in-hospital mortality and 30-day readmission using logistic regression and area under receiver operating characteristic curve (AUC). 30-day and 6-month mortality were modelled by Cox regression, and the length of stay by linear regression.ResultsControlling for age and sex, a 10% increase in the eFI was associated with higher risks of in-hospital mortality (odds ratio [OR]=2.84; 95% confidence interval=2.31-3.51), 30-day mortality (hazard ratio [HR]=2.30; 1.99-2.65), 6-month mortality (HR=2.33; 2.07-2.62), 30-day readmission (OR=1.34; 1.06-1.68), and longer length of stay (β=2.28; 1.90-2.66).The CFS, HFRS and CCI similarly predicted these outcomes, but the eFI had the best predictive accuracy for in-hospital mortality (AUC=0.775).ConclusionsAn eFI based on routinely collected EHRs can be applied in identifying high-risk geriatric COVID-19 patients.

scholarly journals Factors associated with professional identity formation within psychiatry residency training: A longitudinal study

2021 ◽  
Author(s):  
Qian Hui Chew ◽  
Yvonne Steinert ◽  
Kang Sim
Keyword(s):  
Professional Identity ◽  
Identity Formation ◽  
Psychiatry Residency ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Developmental Stages ◽  
Rate Of Change ◽  
Psychiatry Residents ◽  
Factors Associated ◽  
Over Time

Abstract Introduction Conceptual frameworks for professional identity (PI) formation highlight the importance of developmental stages and socialization as the learner progresses from legitimate peripheral to full participation. Based on extant literature and clinical impressions, the authors aimed to explore factors associated with PI formation in psychiatry residents over time, and hypothesized that time in training, seniority status, and duration of exposure to psychiatry prior to residency would be associated with PI formation. Methods Eighty out of 96 psychiatry residents (response rate, 83.3%) from the National Psychiatry Residency Program in Singapore participated and rated their PI development using the Professional Self Identity Questionnaire (PSIQ) across four timepoints from January 2016–December 2019. The residents were classified as junior (first 3 years) or senior residents (years 4–5). Linear mixed model analyses were conducted, with time in training, seniority status (junior versus senior residents), duration of psychiatry postings prior to residency, and their interaction as associated factors with PI over time. Results Time in training, seniority, and duration of psychiatry postings before residency (all p < 0.01) were significantly associated with higher PSIQ scores at baseline. Over time, although all residents had increases in PSIQ scores, this rate of change did not differ significantly between junior and senior residents. Discussion Exposure to psychiatry postings before residency, time in learning, and seniority are factors which influence PI development in residents. This has implications for psychiatry residency selection and training, adequate clinical exposure during training rotations, and continual support for new and senior residents to foster PI formation over time.

scholarly journals 103 Periodontal Health and Sarcopenia: Cross-Sectional Evidence From A Cohort of 2040 Twin Volunteers

2021 ◽  
Vol 50 (Supplement_1) ◽  
pp. i12-i42
Author(s):  
M B Zazzara ◽  
P M Wells ◽  
R C E Bowyer ◽  
M N Lochlainn ◽  
E J Thompson ◽  
...  
Keyword(s):  
Mixed Model ◽  
Linear Mixed Model ◽  
Frailty Index ◽  
Muscle Quality ◽  
Low Grade ◽  
Periodontal Health ◽  
Cross Sectional ◽  
Age Related ◽  
European Working ◽  
Generalised Linear Mixed Model

Abstract Introduction Periodontitis is a chronic inflammatory disease affecting the periodontium, ultimately leading to looseness and/or loss of teeth. Sarcopenia refers to age-related reduction in muscle mass and strength. Similar to periodontitis, chronic low-grade inflammation is thought to play a key role in its development. In addition, both increase in prevalence with advancing age. Despite known associations with other diseases involving a dysregulated inflammatory response, for example rheumatoid arthritis,, the relationship between periodontitis and sarcopenia, and whether they could be driven by similar processes, remains uncertain. The aim of this study was to explore the association between periodontitis and sarcopenia. Methods Observational study of 2040 adult volunteers [age 67.18 (12.17)] enrolled in the TwinsUK cohort study. Presence of tooth mobility and number of teeth lost were used to assess periodontal health. A binary variable was created to define periodontitis. Measurements of muscle strength, muscle quality/quantity and physical performance were used to assess sarcopenia. A categorical variable was created according to the European Working Group on Sarcopenia in Older People (EWGSOP2) consensus, to define sarcopenia (1: probable; 2: positive; 3: severe). Generalised linear mixed model analysis used on complete cases and age-matched (n = 1,288) samples to ascertain associations between periodontitis and sarcopenia. Results No significant association was found between periodontitis and sarcopenia in both the complete cases analysis and age-matched analysis. Results were consistent when analysis was adjusted for potential confounders including body mass index, frailty index, Mini Mental State Examination smoking, nutritional status and educational level. Conclusions This study found no significant association between periodontitis and sarcopenia in a cohort of 2040 adults. Although both periodontitis and sarcopenia have been linked to a dysregulated immune response and demonstrate an increase in prevalence with increasing age, our work is inconclusive due to the plethora of possible aetiopathogenetic pathways.

scholarly journals Maternal Factors Associated with Levels of Fatty Acids, Specifically n-3 PUFA during Pregnancy: ECLIPSES Study

Nutrients ◽  
2021 ◽  
Vol 13 (2) ◽  
pp. 317
Author(s):  
Estefania Aparicio ◽  
Carla Martín-Grau ◽  
Cristina Bedmar ◽  
Núria Serrat Orus ◽  
Josep Basora ◽  
...  
Keyword(s):  
Fatty Acids ◽  
Fatty Acid ◽  
Pregnant Women ◽  
Saturated Fatty Acids ◽  
Overweight And Obesity ◽  
Older Age ◽  
High Educational Level ◽  
Seafood Consumption ◽  
Factors Associated ◽  
High Educational

An optimal fatty acid (FA) profile during pregnancy, especially docosahexaenoic acid (DHA) and eicosapentaenoic acid (EPA), is essential for the health of the mother and child. Our aim was to identify the socioeconomic and maternal lifestyle factors associated with serum FA concentration in pregnant women. A longitudinal study was conducted on 479 pregnant women, who were assessed during the first (T1) and third (T3) trimesters of pregnancy. Data on maternal characteristics, food consumption, and lifestyle were collected. Serum FA concentrations were analysed by a gas chromatography–mass spectrometry combination. The multiple linear regression showed that high educational level and older age were significantly associated with higher EPA and DHA concentrations and lower values of n-6/n-3 and arachidonic acid (AA)/EPA in T1 and/or T3. Regarding diet—fish and seafood consumption increased EPA concentration and reduced n-6/n-3 and AA/EPA values in both trimesters, whereas its consumption increased DHA concentration only in T1. Smoking was associated with lower DHA concentration in T1 and higher values of n-6/n-3 ratio in both trimester. Overweight and obesity were associated with higher values of n-6/n-3 ratio and AA/EPA ratio in T1. A statistically non-significant association was observed with saturated fatty acids (SFA) and monounsaturated fatty acids (MUFA). In conclusion, high educational levels, older age, fish, seafood consumption, and/or non-smoking, are factors that influence better omega-3 polyunsaturated fatty acid (n-3 PUFA) profile in both trimesters of pregnancy. Further research is needed to go in-depth into these findings and their health consequences.

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