Characterizing functional alterations in instrumental activities of daily living using latent class analysis: a population-based study (NEDICES)

2018 ◽  
Vol 24 (1) ◽  
pp. 41-48 ◽  
Author(s):  
Israel Contador ◽  
Bernardino Fernández-Calvo ◽  
Laura Rueda-Revé ◽  
Javier Olazarán ◽  
Félix Bermejo-Pareja
Viruses ◽  
2021 ◽  
Vol 13 (6) ◽  
pp. 1118
Author(s):  
Ralf Wagner ◽  
David Peterhoff ◽  
Stephanie Beileke ◽  
Felix Günther ◽  
Melanie Berr ◽  
...  

SARS-CoV-2 infection fatality ratios (IFR) remain controversially discussed with implications for political measures. The German county of Tirschenreuth suffered a severe SARS-CoV-2 outbreak in spring 2020, with particularly high case fatality ratio (CFR). To estimate seroprevalence, underreported infections, and IFR for the Tirschenreuth population aged ≥14 years in June/July 2020, we conducted a population-based study including home visits for the elderly, and analyzed 4203 participants for SARS-CoV-2 antibodies via three antibody tests. Latent class analysis yielded 8.6% standardized county-wide seroprevalence, a factor of underreported infections of 5.0, and 2.5% overall IFR. Seroprevalence was two-fold higher among medical workers and one third among current smokers with similar proportions of registered infections. While seroprevalence did not show an age-trend, the factor of underreported infections was 12.2 in the young versus 1.7 for ≥85-year-old. Age-specific IFRs were <0.5% below 60 years of age, 1.0% for age 60–69, and 13.2% for age 70+. Senior care homes accounted for 45% of COVID-19-related deaths, reflected by an IFR of 7.5% among individuals aged 70+ and an overall IFR of 1.4% when excluding senior care home residents from our computation. Our data underscore senior care home infections as key determinant of IFR additionally to age, insufficient targeted testing in the young, and the need for further investigations on behavioral or molecular causes of the fewer infections among current smokers.


Author(s):  
Jing Huang ◽  
Pui Hing Chau ◽  
Edmond Pui Hang Choi ◽  
Bei Wu ◽  
Vivian W Q Lou

Abstract Objectives This study identified the classes (i.e., patterns) of caregivers’ activities, based on their engagements in caregiving activities, and explored the characteristics and the caregiver burden of these classes. Methods This study was a secondary analysis of a cross-sectional survey on the profiles of family caregivers of older adults in Hong Kong. A latent class analysis approach was adopted to classify family caregivers (N = 932) according to their routine involvements in 17 daily caregiving activities: 6 activities of daily living (ADLs) and 8 instrumental activities of daily living activities (IADLs) in addition to emotional support, decision making, and financial support. Multinomial logistic regression and multiple linear regression illuminated the characteristics of the classes and compared their levels of caregiver burden. Results The family caregivers fell into 5 classes: All-Round Care (High Demand, 19.5%), All-Round Care (Moderate Demand, 8.2%), Predominant IADLs Care (High Demand, 23.8%), Predominant IADLs Care (Moderate Demand, 32.5%), and Minimal ADLs and IADLs Care (Low Demand, 16.0%). These classes exhibited different characteristics in terms of care recipients’ cognitive statuses and caregiver backgrounds. The levels of caregiver burden differed across classes; the All-Round Care (High Demand) class experienced the highest levels of caregiver burden. Discussion This study contributes to existing scholarship by turning away from a predefined category of care tasks to explore the patterns of caregiving activities. By identifying caregiving activity patterns and understanding their associated characteristics and caregiver burden, prioritizing and targeting caregiver support interventions better is possible.


2016 ◽  
Vol 33 (12) ◽  
pp. 1178-1187 ◽  
Author(s):  
Hugo Peyre ◽  
Nicolas Hoertel ◽  
Fabrice Rivollier ◽  
Benjamin Landman ◽  
Kibby McMahon ◽  
...  

PLoS ONE ◽  
2021 ◽  
Vol 16 (3) ◽  
pp. e0248992
Author(s):  
Marcus Heise ◽  
Astrid Fink ◽  
Jens Baumert ◽  
Christin Heidemann ◽  
Yong Du ◽  
...  

Objective Few studies on diabetes self-management considered the patterns and relationships of different self-management behaviours (SMB). The aims of the present study are 1) to identify patterns of SMB among persons with diabetes, 2) to identify sociodemographic and disease-related predictors of SMB among persons with diabetes. Research design and methods The present analysis includes data of 1,466 persons (age 18 to 99 years; 44.0% female; 56.0% male) with diabetes (type I and II) from the population-based study German Health Update 2014/2015 (GEDA 2014/2015-EHIS). We used latent class analysis in order to distinguish different patterns of self-management behaviours among persons with diabetes. The assessment of SMB was based on seven self-reported activities by respondents (dietary plan, diabetes-diary, diabetes health pass, self-assessment of blood glucose, self-examination of feet, retinopathy-screenings and assessment of HbA1c). Subsequent multinomial latent variable regressions identified factors that were associated with self-management behaviour. Results Latent class analysis suggested a distinction between three patterns of SMB. Based on modal posterior probabilities 42.8% of respondents showed an adherent pattern of diabetes self-management with above-average frequency in all seven indicators of SMB. 32.1% showed a nonadherent pattern with a below-average commitment in all seven forms of SMB. Another 25.1% were assigned to an ambivalent type, which showed to be adherent with regard to retinopathy screenings, foot examinations, and the assessment of HbA1c, yet nonadherent with regard to all other forms of SMB. In multivariable regression analyses, participation in Diabetes Self-Management Education programs (DSME) was the most important predictor of good self-management behaviour (marginal effect = 51.7 percentage points), followed by attentiveness towards one’s personal health (31.0 percentage points). Respondents with a duration of illness of less than 10 years (19.5 percentage points), employed respondents (7.5 percentage points), as well as respondents with a high socioeconomic status (24.7 percentage points) were more likely to show suboptimal forms of diabetes self-management. Discussion In the present nationwide population-based study, a large proportion of persons with diabetes showed suboptimal self-management behaviour. Participation in a DSME program was the strongest predictor of good self-management. Results underline the need for continual and consistent health education for patients with diabetes.


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