ObjectiveOlder people in rural areas are possibly more frail due to the limited medical resources and lower socioeconomic status. Given the negative healthy outcomes caused by frailty, knowing the epidemiology of frailty in rural areas is of great importance. We tried to synthesise the existing evidences for the prevalence and risk factors of frailty in rural areas.DesignA systematic review and meta-analysis.Data sourcesPubMed, Embase, MEDLINE, Cochrane Library, Web of Science and Scopus were used to identify the articles from inception to 30 April 2019.Eligibility criteriaObservational studies providing cross-sectional data on the prevalence of frailty in rural elderly were extracted.Data extraction and synthesisTwo independent investigators selected studies, extracted data and assessed the methodological quality of included studies. The pool prevalence of frailty was calculated by the random effects model and the OR and 95% CI were used to calculate the risk factors.ResultsThe literature search yielded 2219 articles, of which 23 met the study criteria and were included in this analysis. The pooled prevalence of frailty and pre-frailty were 18% (95% CI 15% to 21%, I2=98.5%, p<0.001) and 50% (95% CI 45% to 56%, I2=98.4%, p<0.001), respectively. The pooled frailty prevalence was 15% for the Fried Phenotype, 18% for the Frailty Index and 23% for other criteria. The pooled prevalence of frailty was 17% for males and 26% for females. The pooled prevalence of frailty was 17% in developing countries and 23% in developed countries. Age, cognitive impairment, depressive symptom, risk of malnutrition, activity of daily living (ADL) disability and poor self-perception of health were associated with frailty. There was no publication bias.ConclusionsFrailty influences almost one in five older people in rural areas, and increasing age, cognitive impairment, depressive symptom, risk of malnutrition, ADL disability and poor self-perception of health were all risk factors for frailty. We should be cautious about the research results due to the heterogeneity between studies.

The purpose of this study was to explore the relationship among unmet care needs, social support, and anxiety in patients with lung transplantation. We conducted a cross-sectional study; 173 lung transplant patients who met the inclusion criteria completed questionnaires including the Organ Transplant Recipient Care Needs Scale, the Perceived Social Support Scale, and the Anxiety Self-Rating Inventory. Pearson’s correlations and multiple linear regression analyses were used to test the relationship between the selected variables. The results showed a moderate level of unmet care needs at home for lung transplant patients. Education level, transplant-related complications, perceived social support, and anxiety were significantly correlated with unmet care needs of lung transplant patients at home ( p < .05), explaining 23.8% of the total variance for unmet care needs. Further research is required to explore interventions to reduce the level of unmet care needs of lung transplant patients.