We use cookies to distinguish you from other users and to provide you with a better experience on our websites. Close this message to accept cookies or find out how to manage your cookie settings.
To save content items to your account,
please confirm that you agree to abide by our usage policies.
If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account.
Find out more about saving content to .
To save content items to your Kindle, first ensure no-reply@cambridge.org
is added to your Approved Personal Document E-mail List under your Personal Document Settings
on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part
of your Kindle email address below.
Find out more about saving to your Kindle.
Note you can select to save to either the @free.kindle.com or @kindle.com variations.
‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi.
‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.
The origin of malnutrition in older age is multifactorial and risk factors may vary according to health and living situation. The present study aimed to identify setting-specific risk profiles of malnutrition in older adults and to investigate the association of the number of individual risk factors with malnutrition.
Design:
Data of four cross-sectional studies were harmonized and uniformly analysed. Malnutrition was defined as BMI < 20 kg/m2 and/or weight loss of >3 kg in the previous 3–6 months. Associations between factors of six domains (demographics, health, mental function, physical function, dietary intake-related problems, dietary behaviour), the number of individual risk factors and malnutrition were analysed using logistic regression.
Setting:
Community (CD), geriatric day hospital (GDH), home care (HC), nursing home (NH).
Participants:
CD older adults (n 1073), GDH patients (n 180), HC receivers (n 335) and NH residents (n 197), all ≥65 years.
Results:
Malnutrition prevalence was lower in CD (11 %) than in the other settings (16–19 %). In the CD sample, poor appetite, difficulties with eating, respiratory and gastrointestinal diseases were associated with malnutrition; in GDH patients, poor appetite and respiratory diseases; in HC receivers, younger age, poor appetite and nausea; and in NH residents, older age and mobility limitations. In all settings the likelihood of malnutrition increased with the number of potential individual risk factors.
Conclusions:
The study indicates a varying relevance of certain risk factors of malnutrition in different settings. However, the relationship of the number of individual risk factors with malnutrition in all settings implies comprehensive approaches to identify persons at risk of malnutrition early.
Suicide prediction during psychiatric in-patient treatment remains an
unresolved challenge.
Aims
To identify determinants of railway suicides in individuals receiving
in-patient psychiatric treatment.
Method
The study population was drawn from patients admitted to six psychiatric
hospitals in Germany during a 10-year period (1997–2006). Data from 101
railway suicide cases were compared with a control group of 101
discharged patients matched for age, gender and diagnosis.
Results
Predictors of suicide were change of therapist (OR = 22.86,
P = 0.004), suicidal ideation (OR = 7.92,
P<0.001), negative or unchanged therapeutic course
(OR = 7.73, P<0.001), need of polypharmaceutical
treatment (OR = 2.81, P = 0.04) and unemployment (OR =
2.72, P = 0.04). Neither restlessness nor impulsivity
predicted in-patient suicide.
Conclusions
Suicidal ideation, unfavourable clinical course and the use of multiple
psychotropic substances (reflecting the severity of illness) were strong
determinants of railway suicides. The most salient finding was the vital
impact of a change of therapist. These findings deserve integration into
the clinical management of patients with serious mental disease.
The diagnosis of somatisation disorder in DSM-IV was based on ‘medically unexplained’ symptoms, which is unsatisfactory.
Aims
To determine the value of a total somatic symptom score as a predictor of health status and healthcare use after adjustment for anxiety, depression and general medical illness.
Method
Data from nine population-based studies (total n = 28377) were analysed.
Results
In all cross-sectional analyses total somatic symptom score was associated with health status and healthcare use after adjustment for confounders. In two prospective studies total somatic symptom score predicted subsequent health status. This association appeared stronger than that for medically unexplained symptoms.
Conclusions
Total somatic symptom score provides a predictor of health status and healthcare use over and above the effects of anxiety, depression and general medical illnesses.
Recommend this
Email your librarian or administrator to recommend adding this to your organisation's collection.