Objective: in the past decades, many studies have examined predictors of nursing home placement (NHP) in the elderly. This study provides a systematic review of predictors of NHP in the general population of developed countries. Design: relevant articles were identified by searching the databases MEDLINE, Web of Science, Cochrane Library and PSYNDEXplus. Studies based on population-based samples with prospective study design and identification of predictors by multivariate analyses were included. Quality of studies and evidence of predictors were determined. Results: thirty-six studies were identified; one-third of the studies were of high quality. Predictors with strong evidence were increased age, low self-rated health status, functional and cognitive impairment, dementia, prior NHP and a high number of prescriptions. Predictors with inconsistent results were male gender, low education status, low income, stroke, hypertension, incontinence, depression and prior hospital use. Conclusions: findings suggested that predictors of NHP are mainly based on underlying cognitive and/or functional impairment, and associated lack of support and assistance in daily living. However, the methodical quality of studies needs improvement. More theoretical embedding of risk models of NHP would help to establish more clarity in complex relationships in using nursing homes.
Objectives: Identifying risk factors of depression can provide a better understanding of the disorder in older people. However, to minimize bias due to the influence of confounders and to detect reverse influence, a focus on longitudinal studies using multivariate analysis is required. Design: A systematic literature search was conducted by searching the databases MEDLINE, Cochrane, PsycINFO and Web of Science for all relevant articles published from January 2000 to the end of March 2020. The following inclusion criteria were used: prospective design, nationally or regionally representative sample, published in English or German, analyzed risk factors for depression of individuals 65+ identified by multivariate analysis, and provided validity of diagnostic instrument. All results of multivariate analysis were reported and summarized. Results: Thirty articles were identified. Heterogeneous results were found for education, female gender, self-rated health, cognitive impairment and older age, although significant in several studies. Findings hinted at a protective quality of physical activity. In terms of physical health, chronic disease and difficulty initiating sleep homogeneously increased risk of depression. Mobility impairment resulted as a risk factor in three studies. IADL impairment and vision impairment were mostly identified as significant risk factors. Alcohol consumption and smoking behavior yielded heterogenous results. Psychosocial factors were assessed similarly in multiple studies and yielded heterogenous results. Limitations: Research was limited to articles published in English or German. Length of follow up was not considered for the presentation of results. Adjustments for and inclusion of different variables in the studies may distort results. Conclusion: Our findings demonstrate the necessity of refined, more comparable assessment tools for evaluating potential risk factors.
Background/Aims: In the past decades, a substantial number of studies considered factors influencing institutionalisation of persons with dementia. This study reviews recent work on predictors of actual institutionalisation in dementia. Method: Relevant articles were identified by a systematic search of the literature. Studies were considered which included persons aged 65 and over, and whose results were based on prospective design and on multivariate statistical analyses. Results: Forty-two studies were identified. The rate of institutionalisation increased from 20% in the first year after diagnosis to 50% after 5 years. Median time to institutionalisation was estimated between 30 and 40 months. Predictors of institutionalisation were classified according to a provided conceptual framework in the categories sociodemographic and relationship characteristics of persons with dementia and caregivers, primary stressors, secondary stressors and resources. Conclusion: The overview of research activities in this area showed a lack of methodological strength in a large part of identified studies. Nevertheless, a lot of well-examined and less highlighted predictors could be identified.
Up to this date, prevalence rates of obesity are still rising. Aside from co-morbid diseases, perceived discrimination and stigmatization leads to worsen outcomes in obese individuals. Higher stigmatizing attitudes towards obese individuals may also result in less support of preventive and interventive measures. In light of the immense burden of obesity on health care systems and also on the individuals' quality of life, accepted and subsidized preventive measures are needed. Policy support might be determined by views of the lay public on causes of obesity and resulting weight stigma. This study seeks to answer how representative samples of the lay public perceive people with obesity or overweight status (stigmatizing attitudes); what these samples attribute obesity to (causal attribution) and what types of interventions are supported by the lay public and which factors determine that support (prevention support).