METHODS: A total of 110 hospitalized geriatric patients aged 60 years and older were selected using convenience sampling method in a cross-sectional study. Sociodemographic data and medical history were obtained from the medical records. Questionnaires were used during the in-person semistructured interviews, which were conducted in the wards. Linear regression analyses were used to determine the predictors of each domain of quality of life.
RESULTS: Multiple regression analysis showed that activities of daily living, depression, and appetite were the determinants of physical health domain of quality of life (R(2)=0.633, F(3, 67)=38.462; P<0.001), whereas depression and instrumental activities of daily living contributed to 55.8% of the variability in psychological domain (R(2)=0.558, F(2, 68)=42.953; P<0.001). Social support and cognitive status were the determinants of social relationship (R(2)=0.539, F(2, 68)=39.763; P<0.001) and also for the environmental domain of the quality of life (R(2)=0.496, F(2, 68)=33.403; P<0.001).
CONCLUSION: The findings indicated different predictors for each domain in the quality of life among hospitalized geriatric patients with diabetes mellitus. Nutritional, functional, and psychological aspects should be incorporated into rehabilitation support programs prior to discharge in order to improve patients' quality of life.
METHODS: A cross-sectional study was conducted in the Kandy district using multistage sampling. A total of 999 older people were recruited, with a female preponderance. Data were collected using interviewer-administered questionnaires on demographic characteristics, depression, and physical activity. Anthropometric measurements including weight, height, mid-upper arm circumference, calf circumference, and HGS were recorded. Complex sample general linear model was used to examine the association between HGS and its associated factors.
RESULTS: The mean highest HGS of the study group was 12.56 kg (95% confidence interval: 11.94-13.19). Male older people had a higher HGS (17.02, 95% confidence interval: 15.55-18.49 kg) than females (10.59, 95% confidence interval: 10.12-11.06 kg). For both men and women, older age was associated with lower HGS, while mid-upper arm circumference was associated with better HGS. Diabetes mellitus, vegetarian diet, and alcohol consumption were associated with HGS for women only.
CONCLUSION: Men had a higher HGS compared with women. Age, mid-upper arm circumference, diabetes mellitus, vegetarian diet, and alcohol consumption were factors associated with HGS among community-dwelling older people in Kandy district, Sri Lanka. HGS can be used as a feasible strategy to improve health status of older people by community health nurses.
OBJECTIVE: The aim of this study was to externally validate the GerontoNet ADR risk score and to assess its validity in specific subpopulations of older inpatients.
METHODS: Data from the prospective CRIteria to assess appropriate Medication use among Elderly complex patients (CRIME) cohort were used. Dose-dependent and predictable ADRs were classified as type A, probable or definite ADRs were defined according to the Naranjo algorithm, and diagnostic accuracy was tested using receiver operating characteristic (ROC) analyses. Sensitivity and specificity were calculated for a cut-off point of 4.
RESULTS: The mean age of the 1075 patients was 81.4 years (standard deviation 7.4) and the median number of drugs was 10 (range 7-13). At least one ADR was observed in 70 patients (6.5%); ADRs were classified as type A in 50 patients (4.7%) and defined as probable or definite in 41 patients (3.8%). Fair diagnostic accuracy to predict both type A and probable or definite ADRs was found in subpopulations aged <70 or ≥80 years with heart failure, diabetes, or a previous ADR. Good accuracy to predict type A ADRs was found in patients with a low body mass index (BMI; >18.5 kg/m2) and a Mini-Mental State Examination (MMSE) score of >24/30 points, as well as in patients with osteoarthritis. The cut-off point of 4 points yielded very good sensitivity but poor specificity results in these subpopulations.
CONCLUSION: This study suggests that the GerontoNet ADR risk score might represent a pragmatic approach to identifying specific subpopulations of older inpatients at increased risk of an ADR with a fair to good diagnostic accuracy.
METHODS: A cross-sectional study was conducted in the Kandy district, Sri Lanka. The nutritional status of older persons was assessed using the Mini Nutritional Assessment -Short Form (MNA-SF). A standardised questionnaire was used to record factors associated with malnutrition: demographic characteristics, financial characteristics, food and appetite, lifestyle, psychological characteristics, physical characteristics, disease and care, oral health, and social factors. Complex sample multinomial logistic regression analysis was performed.
RESULTS: Among the 999 participants included in the study, 748 (69.3%) were females and 251 (25.1%) were males. The mean age was 70.80 years (95% CI: 70.13, 71.47). The prevalence of malnutrition, risk of malnutrition and well-nutrition was 12.5%, 52.4% and 35.1% respectively. In the multivariate model, hypertension (adjusted OR = 1.71; 95% CI: 1.02, 2.89), alcohol consumption (aOR = 4.06; 95% CI: 1.17, 14.07), and increased age (aOR = 1.06; 95% CI: 1.01, 1.11) were positively associated with malnutrition. An increased number of people living with the older person (aOR: 0.91; 95% CI: 0.85, 0.97) was a protective factor among those at risk for malnutrition.
CONCLUSION: Both the prevalence of malnutrition and risk of malnutrition were commonly observed among community-dwelling older persons in Sri Lanka. The associated factors identified in this study might help public health professionals to implement necessary interventions that improve the nutritional status of this population.