| 1. |
- Bouillon, Kim, et al.
(författare)
-
Measures of frailty in population-based studies: An overview
- 2013
-
Ingår i: BMC Geriatrics. - : Springer Science and Business Media LLC. - 1471-2318 .- 1471-2318. ; 13:64
-
Tidskriftsartikel (refereegranskat)abstract
- Background: Although research productivity in the field of frailty has risen exponentially in recent years, there remains a lack of consensus regarding the measurement of this syndrome. This overview offers three services: first, we provide a comprehensive catalogue of current frailty measures; second, we evaluate their reliability and validity; third, we report on their popularity of use.Methods: In order to identify relevant publications, we searched MEDLINE (from its inception in 1948 to May 2011); scrutinized the reference sections of the retrieved articles; and consulted our own files. An indicator of the frequency of use of each frailty instrument was based on the number of times it had been utilized by investigators other than the originators.Results: Of the initially retrieved 2,166 papers, 27 original articles described separate frailty scales. The number (range: 1 to 38) and type of items (range of domains: physical functioning, disability, disease, sensory impairment, cognition, nutrition, mood, and social support) included in the frailty instruments varied widely. Reliability and validity had been examined in only 26% (7/27) of the instruments. The predictive validity of these scales for mortality varied: for instance, hazard ratios/odds ratios (95% confidence interval) for mortality risk for frail relative to non-frail people ranged from 1.21 (0.78; 1.87) to 6.03 (3.00; 12.08) for the Phenotype of Frailty and 1.57 (1.41; 1.74) to 10.53 (7.06; 15.70) for the Frailty Index. Among the 150 papers which we found to have used at least one of the 27 frailty instruments, 69% (n = 104) reported on the Phenotype of Frailty, 12% (n = 18) on the Frailty Index, and 19% (n = 28) on one of the remaining 25 instruments.Conclusions: Although there are numerous frailty scales currently in use, reliability and validity have rarely been examined. The most evaluated and frequently used measure is the Phenotype of Frailty.
|
|
| 2. |
- Chastin, Sebastien, et al.
(författare)
-
Joint association between accelerometry-measured daily combination of time spent in physical activity, sedentary behaviour and sleep and all-cause mortality : A pooled analysis of six prospective cohorts using compositional analysis
- 2021
-
Ingår i: British Journal of Sports Medicine. - : BMJ. - 0306-3674 .- 1473-0480. ; 55:22, s. 1277-1285
-
Tidskriftsartikel (refereegranskat)abstract
- OBJECTIVE: To examine the joint associations of daily time spent in different intensities of physical activity, sedentary behaviour and sleep with all-cause mortality.METHODS: Federated pooled analysis of six prospective cohorts with device-measured time spent in different intensities of physical activity, sedentary behaviour and sleep following a standardised compositional Cox regression analysis.PARTICIPANTS: 130 239 people from general population samples of adults (average age 54 years) from the UK, USA and Sweden.MAIN OUTCOME: All-cause mortality (follow-up 4.3-14.5 years).RESULTS: Studies using wrist and hip accelerometer provided statistically different results (I2=92.2%, Q-test p<0.001). There was no association between duration of sleep and all-cause mortality, HR=0.96 (95% CI 0.67 to 1.12). The proportion of time spent in moderate to vigorous physical activity was significantly associated with lower risk of all-cause mortality (HR=0.63 (95% CI 0.55 to 0.71) wrist; HR=0.93 (95% CI 0.87 to 0.98) hip). A significant association for the ratio of time spent in light physical activity and sedentary time was only found in hip accelerometer-based studies (HR=0.5, 95% CI 0.42 to 0.62). In studies based on hip accelerometer, the association between moderate to vigorous physical activity and mortality was modified by the balance of time spent in light physical activity and sedentary time.CONCLUSION: This federated analysis shows a joint dose-response association between the daily balance of time spent in physical activity of different intensities and sedentary behaviour with all-cause mortality, while sleep duration does not appear to be significant. The strongest association is with time spent in moderate to vigorous physical activity, but it is modified by the balance of time spent in light physical activity relative to sedentary behaviour.
|
|
| 3. |
- Dugravot, Aline, et al.
(författare)
-
Do socioeconomic factors shape weight and obesity trajectories over the transition from midlife to old age? : Results from the French GAZEL cohort study
- 2010
-
Ingår i: American Journal of Clinical Nutrition. - : Elsevier BV. - 0002-9165 .- 1938-3207. ; 92:1, s. 16-23
-
Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: Obesity is a contemporary epidemic that does not affect all age groups and sections of society equally. OBJECTIVE: The objective was to examine socioeconomic differences in trajectories of body mass index (BMI; in kg/m(2)) and obesity between the ages of 45 and 65 y. DESIGN: A total of 13,297 men and 4532 women from the French GAZEL (Gaz de France Electricité de France) cohort study reported their height in 1990 and their weight annually over the subsequent 18 y. Changes in BMI and obesity between ages 45 and 49 y, 50 and 54 y, 55 and 59 y, and 60 and 65 y as a function of education and occupational position (at age 35 y) were modeled by using linear mixed models and generalized estimating equations. RESULTS: BMI and obesity rates increased between the ages of 45 and 65 y. In men, BMI was higher in unskilled workers than in managers at age 45 y; this difference in BMI increased from 0.82 (95% CI: 0.66, 0.99) at 45 y to 1.06 (95% CI: 0.85, 1.27) at 65 y. Men with a primary school education compared with those with a high school degree at age 45 y had a 0.75 (95% CI: 0.51, 1.00) higher BMI, and this difference increased to 1.32 (95% CI: 1.03,1.62) at age 65 y. Obesity rates were 3.35% and 7.68% at age 45 y and 9.52% and 18.10% at age 65 y in managers and unskilled workers, respectively; the difference in obesity increased by 4.25% (95% CI: 1.87, 6.52). A similar trend was observed in women. Conclusions: Weight continues to increase in the transition between midlife and old age; this increase is greater in lower socioeconomic groups.
|
|
| 4. |
|
|
| 5. |
- Fransson, Eleonor, 1971-, et al.
(författare)
-
Job strain as a risk factor for leisure-time physical inactivity : an individual-participant meta-analysis of up to 170,000 men and women
- 2012
-
Ingår i: American Journal of Epidemiology. - Cary : Oxford University Press. - 0002-9262 .- 1476-6256. ; 176:12, s. 1078-1089
-
Forskningsöversikt (refereegranskat)abstract
- Unfavorable work characteristics, such as low job control and too high or too low job demands, have been suggested to increase the likelihood of physical inactivity during leisure time, but this has not been verified in large-scale studies. The authors combined individual-level data from 14 European cohort studies (baseline years from 19851988 to 20062008) to examine the association between unfavorable work characteristics and leisure-time physical inactivity in a total of 170,162 employees (50 women; mean age, 43.5 years). Of these employees, 56,735 were reexamined after 29 years. In cross-sectional analyses, the odds for physical inactivity were 26 higher (odds ratio 1.26, 95 confidence interval: 1.15, 1.38) for employees with high-strain jobs (low control/high demands) and 21 higher (odds ratio 1.21, 95 confidence interval: 1.11, 1.31) for those with passive jobs (low control/low demands) compared with employees in low-strain jobs (high control/low demands). In prospective analyses restricted to physically active participants, the odds of becoming physically inactive during follow-up were 21 and 20 higher for those with high-strain (odds ratio 1.21, 95 confidence interval: 1.11, 1.32) and passive (odds ratio 1.20, 95 confidence interval: 1.11, 1.30) jobs at baseline. These data suggest that unfavorable work characteristics may have a spillover effect on leisure-time physical activity.
|
|
| 6. |
- Hidalgo Migueles, Jairo Hidalgo, et al.
(författare)
-
GRANADA consensus on analytical approaches to assess associations with accelerometer-determined physical behaviours (physical activity, sedentary behaviour and sleep) in epidemiological studies
- 2022
-
Ingår i: British Journal of Sports Medicine. - : BMJ. - 0306-3674 .- 1473-0480. ; 56:7, s. 376-384
-
Tidskriftsartikel (refereegranskat)abstract
- The inter-relationship between physical activity, sedentary behaviour and sleep (collectively defined as physical behaviours) is of interest to researchers from different fields. Each of these physical behaviours has been investigated in epidemiological studies, yet their codependency and interactions need to be further explored and accounted for in data analysis. Modern accelerometers capture continuous movement through the day, which presents the challenge of how to best use the richness of these data. In recent years, analytical approaches first applied in other scientific fields have been applied to physical behaviour epidemiology (eg, isotemporal substitution models, compositional data analysis, multivariate pattern analysis, functional data analysis and machine learning). A comprehensive description, discussion, and consensus on the strengths and limitations of these analytical approaches will help researchers decide which approach to use in different situations. In this context, a scientific workshop and meeting were held in Granada to discuss: (1) analytical approaches currently used in the scientific literature on physical behaviour, highlighting strengths and limitations, providing practical recommendations on their use and including a decision tree for assisting researchers decision-making; and (2) current gaps and future research directions around the analysis and use of accelerometer data. Advances in analytical approaches to accelerometer-determined physical behaviours in epidemiological studies are expected to influence the interpretation of current and future evidence, and ultimately impact on future physical behaviour guidelines.
|
|
| 7. |
- Kivimäki, Mika, et al.
(författare)
-
Association of Alcohol-Induced Loss of Consciousness and Overall Alcohol Consumption With Risk for Dementia
- 2020
-
Ingår i: JAMA Network Open. - : American Medical Association. - 2574-3805. ; 3:9
-
Tidskriftsartikel (refereegranskat)abstract
- Importance: Evidence on alcohol consumption as a risk factor for dementia usually relates to overall consumption. The role of alcohol-induced loss of consciousness is uncertain. Objective: To examine the risk of future dementia associated with overall alcohol consumption and alcohol-induced loss of consciousness in a population of current drinkers. Design, Setting, and Participants: Seven cohort studies from the UK, France, Sweden, and Finland (IPD-Work consortium) including 131 415 participants were examined. At baseline (1986-2012), participants were aged 18 to 77 years, reported alcohol consumption, and were free of diagnosed dementia. Dementia was examined during a mean follow-up of 14.4 years (range, 12.3-30.1). Data analysis was conducted from November 17, 2019, to May 23, 2020. Exposures: Self-reported overall consumption and loss of consciousness due to alcohol consumption were assessed at baseline. Two thresholds were used to define heavy overall consumption: greater than 14 units (U) (UK definition) and greater than 21 U (US definition) per week. Main Outcomes and Measures: Dementia and alcohol-related disorders to 2016 were ascertained from linked electronic health records. Results: Of the 131 415 participants (mean [SD] age, 43.0 [10.4] years; 80 344 [61.1%] women), 1081 individuals (0.8%) developed dementia. After adjustment for potential confounders, the hazard ratio (HR) was 1.16 (95% CI, 0.98-1.37) for consuming greater than 14 vs 1 to 14 U of alcohol per week and 1.22 (95% CI, 1.01-1.48) for greater than 21 vs 1 to 21 U/wk. Of the 96 591 participants with data on loss of consciousness, 10 004 individuals (10.4%) reported having lost consciousness due to alcohol consumption in the past 12 months. The association between loss of consciousness and dementia was observed in men (HR, 2.86; 95% CI, 1.77-4.63) and women (HR, 2.09; 95% CI, 1.34-3.25) during the first 10 years of follow-up (HR, 2.72; 95% CI, 1.78-4.15), after excluding the first 10 years of follow-up (HR, 1.86; 95% CI, 1.16-2.99), and for early-onset (<65 y: HR, 2.21; 95% CI, 1.46-3.34) and late-onset (≥65 y: HR, 2.25; 95% CI, 1.38-3.66) dementia, Alzheimer disease (HR, 1.98; 95% CI, 1.28-3.07), and dementia with features of atherosclerotic cardiovascular disease (HR, 4.18; 95% CI, 1.86-9.37). The association with dementia was not explained by 14 other alcohol-related conditions. With moderate drinkers (1-14 U/wk) who had not lost consciousness as the reference group, the HR for dementia was twice as high in participants who reported having lost consciousness, whether their mean weekly consumption was moderate (HR, 2.19; 95% CI, 1.42-3.37) or heavy (HR, 2.36; 95% CI, 1.57-3.54). Conclusions and Relevance: The findings of this study suggest that alcohol-induced loss of consciousness, irrespective of overall alcohol consumption, is associated with a subsequent increase in the risk of dementia.
|
|
| 8. |
- Kivimäki, Mika, et al.
(författare)
-
Physical inactivity, cardiometabolic disease, and risk of dementia : an individual-participant meta-analysis
- 2019
-
Ingår i: The BMJ. - ENGLAND : BMJ Publishing Group Ltd. - 1756-1833 .- 0959-8138. ; 365
-
Tidskriftsartikel (refereegranskat)abstract
- OBJECTIVE To examine whether physical inactivity is a risk factor for dementia, with attention to the role of cardiometabolic disease in this association and reverse causation bias that arises from changes in physical activity in the preclinical (prodromal) phase of dementia. DESIGN Meta-analysis of 19 prospective observational cohort studies. DATA SOURCES The Individual-Participant-Data Meta-analysis in Working Populations Consortium, the Inter-University Consortium for Political and Social Research, and the UK Data Service, including a total of 19 of a potential 9741 studies. REVIEW METHOD The search strategy was designed to retrieve individual-participant data from prospective cohort studies. Exposure was physical inactivity; primary outcomes were incident all-cause dementia and Alzheimer's disease; and the secondary outcome was incident cardiometabolic disease (that is, diabetes, coronary heart disease, and stroke). Summary estimates were obtained using random effects meta-analysis. RESULTS Study population included 404 840 people (mean age 45.5 years, 57.7% women) who were initially free of dementia, had a measurement of physical inactivity at study entry, and were linked to electronic health records. In 6.0 million person-years at risk, we recorded 2044 incident cases of all-cause dementia. In studies with data on dementia subtype, the number of incident cases of Alzheimer's disease was 1602 in 5.2 million person-years. When measured < 10 years before dementia diagnosis (that is, the preclinical stage of dementia), physical inactivity was associated with increased incidence of all-cause dementia (hazard ratio 1.40, 95% confidence interval 1.23 to 1.71) and Alzheimer's disease (1.36, 1.12 to 1.65). When reverse causation was minimised by assessing physical activity >= 10 years before dementia onset, no difference in dementia risk between physically active and inactive participants was observed (hazard ratios 1.01 (0.89 to 1.14) and 0.96 (0.85 to 1.08) for the two outcomes). Physical inactivity was consistently associated with increased risk of incident diabetes (hazard ratio 1.42, 1.25 to 1.61), coronary heart disease (1.24, 1.13 to 1.36), and stroke (1.16, 1.05 to 1.27). Among people in whom cardiometabolic disease preceded dementia, physical inactivity was non-significantly associated with dementia (hazard ratio for physical activity assessed > 10 before dementia onset 1.30, 0.79 to 2.14). CONCLUSIONS In analyses that addressed bias due to reverse causation, physical inactivity was not associated with all-cause dementia or Alzheimer's disease, although an indication of excess dementia risk was observed in a subgroup of physically inactive individuals who developed cardiometabolic disease.
|
|
| 9. |
- Nyberg, Solja T., et al.
(författare)
-
Association of Healthy Lifestyle With Years Lived Without Major Chronic Diseases
- 2020
-
Ingår i: JAMA Internal Medicine. - : American Medical Association (AMA). - 2168-6106 .- 2168-6114. ; 180:5, s. 760-768
-
Tidskriftsartikel (refereegranskat)abstract
- This cohort study examines disease-free life-years in participants with varying combinations of lifestyle risk factors.Question: Are different combinations of lifestyle factors associated with years lived without chronic diseases?Findings: In a multicohort study of 116 & x202f;043 participants, a statistically significant association between overall healthy lifestyle score and an increased number of disease-free life-years was noted. Of 16 different lifestyle profiles studied, the 4 that were associated with the greatest disease-free life years included body mass index lower than 25 and at least 2 of 3 factors: never smoking, physical activity, and moderate alcohol consumption.Meaning: Various healthy lifestyle profiles appear to be associated with extended gains in life lived without type 2 diabetes, cardiovascular and respiratory diseases, and cancer.Importance: It is well established that selected lifestyle factors are individually associated with lower risk of chronic diseases, but how combinations of these factors are associated with disease-free life-years is unknown.Objective: To estimate the association between healthy lifestyle and the number of disease-free life-years.Design, Setting, and Participants: A prospective multicohort study, including 12 European studies as part of the Individual-Participant-Data Meta-analysis in Working Populations Consortium, was performed. Participants included 116 & x202f;043 people free of major noncommunicable disease at baseline from August 7, 1991, to May 31, 2006. Data analysis was conducted from May 22, 2018, to January 21, 2020.Exposures: Four baseline lifestyle factors (smoking, body mass index, physical activity, and alcohol consumption) were each allocated a score based on risk status: optimal (2 points), intermediate (1 point), or poor (0 points) resulting in an aggregated lifestyle score ranging from 0 (worst) to 8 (best). Sixteen lifestyle profiles were constructed from combinations of these risk factors.Main Outcomes and Measures: The number of years between ages 40 and 75 years without chronic disease, including type 2 diabetes, coronary heart disease, stroke, cancer, asthma, and chronic obstructive pulmonary disease.Results: Of the 116 & x202f;043 people included in the analysis, the mean (SD) age was 43.7 (10.1) years and 70 & x202f;911 were women (61.1%). During 1.45 million person-years at risk (mean follow-up, 12.5 years; range, 4.9-18.6 years), 17 & x202f;383 participants developed at least 1 chronic disease. There was a linear association between overall healthy lifestyle score and the number of disease-free years, such that a 1-point improvement in the score was associated with an increase of 0.96 (95% CI, 0.83-1.08) disease-free years in men and 0.89 (95% CI, 0.75-1.02) years in women. Comparing the best lifestyle score with the worst lifestyle score was associated with 9.9 (95% CI 6.7-13.1) additional years without chronic diseases in men and 9.4 (95% CI 5.4-13.3) additional years in women (P < .001 for dose-response). All of the 4 lifestyle profiles that were associated with the highest number of disease-free years included a body-mass index less than 25 (calculated as weight in kilograms divided by height in meters squared) and at least 2 of the following factors: never smoking, physical activity, and moderate alcohol consumption. Participants with 1 of these lifestyle profiles reached age 70.3 (95% CI, 69.9-70.8) to 71.4 (95% CI, 70.9-72.0) years disease free depending on the profile and sex.Conclusions and Relevance: In this multicohort analysis, various healthy lifestyle profiles appeared to be associated with gains in life-years without major chronic diseases.
|
|
