Frailty and associated factors among elderly patients in Wolaita Zone public hospitals, south Ethiopia

Frailty and associated factors among elderly patients in Wolaita Zone public hospitals, south Ethiopia | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Frailty and associated factors among elderly patients in Wolaita Zone public hospitals, south Ethiopia Besufikad Yilma Dessalegn, Nefsu Awoke, Melese Melako, Timotiwos Adane This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6943157/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Introduction Frailty is an aging-allied condition that suggests a vulnerable state and decline in physiological reserve that affects older people's independence and quality of life. It has also had a significant impact on elderly patients, by leading to impaired activities of daily living, disability, illness, hospitalization, premature death, and increased unnecessary healthcare costs. The previous studies conducted in Ethiopia as well as in Africa were done at the community and residential care facilities level but this study indicated extent of the problem among hospitalized frail patients effectively and also there are limited study on this area in Ethiopia as well as in Africa. Objective : This study aimed to assess frailty and associated factors among elderly patients in Wolaita Zone public hospitals, south Ethiopia, 2023 Method A hospital-based cross-sectional study design was conducted among 367 elderly patients from August 16 to September 21, 2023. A systematic sampling was used to select the participants. The data was collected through structured interviewer-administered questionnaires. The collected data was entered into Epidata version 4.6 and then exported into SPSS version 26 was used for data analysis. A binary logistic regression model was used. Variables with a p value < 0.05 in the multivariable logistic regression analysis were considered statistically significant Results The overall prevalence of frailty was 47.4%. Old age (75–79) (AOR = 3.2, 95%CI = 1.22–8.5) and ≥ 80 years(AOR = 3.46, 95%CI (1.5–7.7), being female (AOR = 2.17, 95%CI = 1.16-4), Weight(60-69kg) (AOR = 0.29, 95% CI (0.1–0.76), Malnutrition (AOR = 3.7,95%CI = 1.88–7.3), Poor social support (AOR = 3, 95%CI = 1.6–5.7), Depression (AOR = 3.5, 95%CI = 1.7–7.11), Hospitalization (AOR = 2.6, 95%CI = 1.4–4.8) and activity of daily living dependence(AOR = 4.57, 95%CI = 2.4–8.7) were factors associated with frailty. Conclusion The prevalence of frailty among elderly patients was high. Older age, being female, weight, depression, hospitalization over the past year, poor social support, malnutrition, and activity of daily living dependence are factors associated with frailty in Wolaita zone public hospitals. Early assessment and prevention of malnutrition, hospitalization, and lifestyle modification of elderly patients may reduce the development of frailty. Elderly patients Frailty Hospital prevalence Aged Ethiopia Figures Figure 1 Figure 2 Figure 3 Introduction Aging is an inherent aspect of human existence. Today, the aging of the population has become one of the major variables impacting the age distribution of the population in all nations[ 1 ]. A major effect of aging is frailty, which increases the likelihood that patients may have negative health outcomes like disability and mortality[ 2 ]. According to the original definition in the field of geriatrics, frailty is a distinct biological syndrome with a declining physiologic reserve and increased vulnerability to health stressors. It is also a multidimensional dysregulation of one or more physiologic systems, such as the immunological, musculoskeletal, cardiovascular, cerebral, and/or neurological systems [ 3 ]. Globally, an increased number of individuals are experiencing frailty, and it is predicted that 150 million older adults may experience frailty over the next 35 years[ 4 – 7 ]. The prevalence of Frailty among older patients receiving medical care was estimated to be from 50–80% [ 8 ]. According to a recent meta-analysis, the prevalence of frailty and pre-frailty in low- and middle-income countries (LMICs) was 12.3% and 55.3% which was higher than the prevalence in high-income countries with a prevalence of 8.2% and 43.9% respectively[ 9 ]. In Sub-Saharan Africa, by 2030 it's anticipated that its elderly population could reach over 67 million and despite to this Frailty in older individuals in sub-Saharan Africa has not been studied in detail[ 10 , 11 ]. In Ethiopia, the prevalence of frailty among residential care facilities, and older adults living with HIV is 45%, and 9.1% respectively[ 12 , 13 ]. Frailty has a significant impact on people and society since it increases the likelihood of impaired activities of daily living (ADL), impairment, and illness and it also shows different symptoms such as decreased mobility, weakness, decreased muscle mass, poor nutritional status, and impaired cognitive function [ 14 ]. These may affect the quality of life and access to medical resources and due to this frailty and its prevention have started to receive great attention in recent years [ 15 – 18 ]. However, based on previous studies, different factors can contribute to the development of frailty such as advanced age, being female, lower dietary protein intake, lack of daily physical exercise, high body mass index and lower education level, sleeping difficulties, and self-reported diabetes, former alcohol use, vision dysfunction, defecation dysfunction [ 19 – 24 ]. A study found that multimodal therapy for frail old patients, including physical activity, nutritional adjustments, and psychological care, had a positive effect on a variety of clinical outcomes[ 12 ]. This study helps healthcare providers to give targeted interventions to enhance recovery and reduce negative health outcomes and it’s also important to prepare a nursing care plan for the patient to deliver the right quality intervention, through identifying different types of associated factors. The frailty and associated factors have been extensively studied in developed and high-income countries, but in the case of sub-Saharan Africa especially Ethiopia the evidence on frailty remains limited. The previous studies indicated that there is association between frailty and factors such as malnutrition, chronic diseases, and poor social support, but there is scarcity of localized data. Frailty in underdeveloped nations, especially in Ethiopia, received little attention despite its significant negative health impacts. There are some studies to show the extent of this, especially in hospital settings besides the variation of demographic aging and occurrence of different types of communicable and uncommunicable diseases. So, this study helps to quantify the burden of frailty and is used to prioritize the required intervention for susceptible elderly patients. Therefore, this study aimed at assessing frailty and associated factors among elderly patients in Wolaita Zone public hospitals, south Ethiopia, 2023 Materials and Methods Study design, Period, and setting A hospital-based cross-sectional study design was applied to elderly patients in the inpatient and outpatient departments of Wolaita Zone Public Hospitals from August 16 to September 21, 2023. Wolaita Sodo is the political and administrative center and is located about 328 km south of Addis Ababa, the capital city of Ethiopia. In the Wolaita zone, there are 68 health centers, 9 public hospitals, and 5 private hospitals. Population All elderly patients (≥ 65 years) who attend public hospitals in outpatient and inpatient departments of all adult wards in Wolaita zone public hospitals were the source population, and all elderly patients (≥ 65 years) who attend Wolaita zone public hospitals as outpatient and inpatient department in all adult wards during the study period were the study population. Inclusion and Exclusion criteria All elderly patients aged 65 years and older who attended the public hospitals during the study period in all adult wards of outpatients, and inpatient departments in the selected public hospitals were included. Those who were seriously ill or unable to respond and communicate well were excluded from the study. Sample size determination Sample Size Determination for proportion The sample size was determined by using the single population proportion formula with the following assumption: n = Sample size Z = level of significance = 95%CI = 1.96, d margin of error of 0.05, and proportion of frailty of elderly patients from the previous study at Hawassa Hospital (P), 9.1%[ 25 ]. By adding a 10% non-response rate, the sample size for the first objective was 139 . Sample size determination for factors The sample size for the second objective was calculated by using Statcalc of Epi Info statistical software version 7.2.5. with the following assumption: confidence level = 95% Power = 80%, The ratio of unexposed to exposed equivalent to 1, P1 = proportion of outcome in the exposed group and P2 = proportion of outcome in the unexposed group. The maximum sample size calculated was 346 “ Table 1 ” By adding a 10% non-response rate, the final sample size of our study becomes 381. Table 1 Sample size determination for the factors associated with frailty Variable Assumptions Proportion (%) 95%CI Sample size(n) Reference Sex ✓ 95%CI ✓ 80% power ✓ Ratio (exposed to unexposed) = 1:1 P1 = 73% P2 = 58.1% 1.005–3.774 346 [ 8 ] Malnutrition P1 = 94.8% P2 = 66.2% 1.029–83.3 72 Multimorbidity P1 = 95.8% P2 = 83.9% 1.944–10.006 232 Functional dependence P1 = 82.1% P2 = 68.4% 1.029–4.343 340 CI, confidence interval Sampling Technique and Procedure From 9 public hospitals in the Wolaita zone, 4 were selected randomly. The sample size was proportionally divided into each hospital based on the average number of elderly patients attending those hospitals per month, after determining the total number of elderly patients in one year, which is obtained from each hospital's health information management system. The allocated number of elderly patients for each hospital is again proportionally divided into all adult wards (Outpatient department, Emergency outpatient department, medical ward, surgical ward, Orthopedics, Gynecology, ophthalmology ward, Adult ICU, and Oncology) in the hospital based on the number of average numbers of elderly patients in each ward per month. From each ward elderly patients were selected by using Systematic random sampling (SRS) by assigning unique identification numbers to each patient in the ward then samples were selected every 3rd interval in each public hospital based on selection criteria. The numbers of elderly patients who attend per year in each randomly selected public hospital are WSUCSH (11,300), Humbo (1414), Boditi (600), and Bitena PH (1500). “ Fig. 1” Study variables Dependent variable Frailty status (Non-frail, Frail) Independent variables Socio-demographic variables, Geriatric health allied outcomes, Nutritional status, Psycho-social factors, Substance use, activity of daily living dependence Operational definitions Elderly patients According to the WHO definition, those who are aged 65 or above, and require comprehensive care to address their physical, mental, and social needs or problems[ 26 ]. Frail elder patients who have a test above the mean score ≥ 7 on the FRAIL-NH scale[ 27 , 28 ] Non-frail elder patients who have a score a point below the mean score 7 of MNA-SF Depression in elderly patients Depressions in elderly patients were measured by using the PHQ-9 depression assessment tool. Elderly patients who scored 10–27 were taken as depressed[ 30 ]. Social support it is defined as based on the score obtained from measurements, which consists of 3 items that range from 3–14. A score of ≤ 8 on the Oslo social support scale was considered as poor support and a score > 8 was considered as strong support[ 31 ]. ADL dependency Measured by the Katz Index of Independence in activities of daily living an elderly patient with a score of ≤ 5 was taken as ADL dependence[ 32 ]. Data collection tools and procedure Data were collected from both outpatient and inpatient departments in all adult wards where elderly patients were found by using interviewer-administered questionnaires. The questionnaire was prepared by reviewing different literature and by adapting from a previous similar study which is conducted on frailty in Addis Ababa[ 12 ]. Quantitative questionnaires have seven parts: Part I-Socio-demographic characteristics, Part II- substance use behavior, Part III-Frailty assessment, Part IV-psycho-social factors assessment, Part V Geriatric nutritional factors assessment, Part VI- Geriatric health-allied outcomes and Part Ⅶ: Activity of daily living dependence. The data was collected by BSc nurses and MSc holders in the health field who supervised the activity of the data collectors. Frailty measurement In this study, frailty was assessed by using the FRAIL-NH scale. This instrument (tool) contains seven items (fatigue, resistance, ambulation, incontinence, loss of weight, nutrition, and help with dressing). Four of these items (transferring, continence, feeding, and dressing) were obtained from the Katz Activities of Daily Living scale, the two items (weight loss and mobility) from the mini–Nutritional Assessment Short Form, and one item (energy) from the quality of life in Alzheimer’s diseases scale. The seven items were scored as 0, 1, or 2 giving a total score of (0–14) and those elderly patients who scored ≥ 7 were considered frail, and < 7 indicated that non-frail based on the FRAIL- NH scale [ 33 ]. The following two self-reported questions from the Center for Epidemiologic Studies-Depression (CES-D) Scale were used to gauge fatigue[ 34 ], “In the last month, I felt that everything I did was an effort, and I was unable to start. Weight loss was defined as unintended weight loss of more than 5 kg during the previous three months, excluding activity and diet. Incontinence and self-dressing skills were assessed to determine functional decline. Independent variable measurement Nutritional status was assessed by Mini-Nutritional Assessment-Short Form (MNA-SF)[ 35 ]. It comprises six questions that can be completed in less than 5 minutes; a dietary questionnaire and subjective assessment. A total possible MNA-SF score ranges from 0 to 14(each item has 2 points). Depression in elderly patients was measured by using PHQ-9(patient health questionnaire), which is an elderly patients depression assessment tool it contains 9 questions and its response is scored as 0, 1, 2, and 3. Elderly patients who scored 10–27 were taken as depressed[ 30 ]. The comorbidity status of elderly patients was assessed according to the Charlson Comorbidity Index diseases list. This is the occurrence of two or more health conditions in the same patient[ 36 ]. The social support status of elderly patients was assessed by the Oslo Social Support Scale (OSSS-3 scale), which consists of 3 items that range from 3–14[ 31 ]. The Katz index of independence: was used to assess the functional status of elderly patients. The index ranks adequacy of performance in the six functions (bathing, dressing, toileting, transferring, continence, and feeding). Its interpretation of the score is given yes = 1 and no = 0 for independence in each of the six functions of items, and a score of 6/6 indicates the full function, a score of 4/6 indicates moderate impairment, and if it scores of 2/6 or less indicates severe functional impairment and the attainable score were 0 to 6. An individual with a score of ≤ 5 was taken as ADL dependent [ 32 ]. A calibrated digital scale was used to assess weight in ambulatory patients, while a bed scale was used in non-ambulatory patients. Weight was recorded and analyzed as a categorical variable for each participant while they were wearing light garments. Data Quality Assurance The questionnaires were pre-tested on 5%(n = 19) of the sample size at Shone Primary Hospital, which was not part of the main study area. Based on the findings of the pre-test some adjustments and developments of the tool were done. The training was given to data collectors and supervisors on the aim of the study, the subjects of the questionnaire, and maintaining the privacy and confidentiality of the study subjects for three days. Data collectors were instructed to check the completeness of each questionnaire whether every question was completely answered and the supervisor rechecked the completeness of the questionnaire after submission. Data Processing and Analysis Data was coded and then, entered into Epi-data version 4.6 and exported to SPSS statistical software with version 26 for further data management and analysis. The univariate analysis such as the percentage and frequency distribution of different characteristics of the questionnaire was analyzed. The continuous variables were expressed as mean ± standard deviation (SD), and categorical variables were expressed as frequencies and percentages. Bivariate analysis was used to identify the association between each independent variable with the dependent variables and also Crude odds ratio (COR) was calculated in bivariate analysis. The multivariable logistic analysis was performed for variables with p-values < 0.25 in the bivariate analysis. It was performed to identify factors associated with frailty among elderly patients and reported in the adjusted odd ratio (AOR) to measure the association between variables. A 95% confidence interval (CI) was reported, and a p-value < 0.05, was considered statistically significant. The results were presented using text, tables, and figures. The Hosmer- Lemeshow goodness of fit test was conducted to assess model fitness (p-value = 0.5). Multi-collinearity was checked by using variance inflation factor (VIF) and tolerance test for each independent variable. The VIF value for each independent variable in this model ranges from 1.054 to 1.55 and the Tolerance test ranges from 0.65 to 0.95, indicating that there is no multicollinearity. Ethical consideration Ethical clearance and approval were obtained from the Institutional Ethical Review Board (IERB) of the College of Health Sciences and Medicine, Wolaita Sodo University (ERC Project number: CHSM/ERC/04/15). Upon approval, the hospital directors received a formal letter from the Wolaita Sodo University College of Health Science and Medicine's research and community service directorate. Informed consent (both written and verbal) was obtained from all subjects for their participation after the nature of the study was fully explained to them. All study participants were encouraged to participate in the study and at the same time, they were told that they had the right not to participate. At last, data was collected after assuring the confidentiality nature of responses, by avoiding the name and other personal identification of each participant. Result Socio-demographic characteristics of respondents A total of 367 study participants were included in this study with a response rate of 96.33%. About 108(29.4%) of the study participant's age group was between 65–69 years and the mean age was 73 ± 6.3years. The majority of the study participants 201(54.8%) were female. One hundred forty-eight (40.3%) of respondents were married, and 142(38.7%) respondents did not get formal education. About 114(31.1%) respondent’s income statuses were between 1501 and 3500 birrs. Regarding weight, the majority of respondents, 197(53.7%) were within the weight range of 60–70 Kg “Table 2 ” Table 2 Socio-demographic characteristics of elderly patients in Wolaita Zone public hospitals, Ethiopia, 2023(n = 367) Variables Categories Frequency Percentage (%) Age 65–69 108 29.4 70–74 90 24.5 75–79 63 17.2 ≥ 80 106 28.9 Sex Male 166 45.2 Female 201 54.8 Educational Status No formal education 142 38.7 Primary education 111 30.2 Secondary-education 71 19.3 Higher education 43 11.7 Marital status Married 148 40.3 Single 96 26.2 Widowed 84 22.9 Divorced 39 10.6 Weight 50-60kg 127 34.6 60-70kg 197 53.7 ≥ 70kg 43 11.7 Income-status 3500 ETB 77 21 Substance use behavior of participants Concerning substance use behavior, the majority of the respondents, 254(69.2%) were non-smokers and 68(18.5%) were previous smokers. Two hundred sixty-five (72.2%) of respondents were non-chat chewers, one hundred fifty-nine (43.3%) were non-alcohol drinkers, and 141(38.4%) were previous alcohol drinkers “Table 3 ”. Table 3 Substance use behavior of elderly patients in Wolaita Zone public hospitals, Ethiopia, 2023(n = 367) Variables Category Frequency Percentage (%) Smoking habit Previous-smoker 68 18.5 Current -smoker 45 12.26 Non-smoker 254 69.2 Chat-chewing Habit Previous-chewer 62 16.9 Current-chewer 40 10.9 Non-Chewer 265 72.2 Alcohol consumption Previous-drinker 141 38.4 Current-drinker 67 18.25 Non-drinker 159 43.3 Psycho-social factors and other geriatric health-related outcomes of respondents The majority of the respondents, 252(68.7%) were non-depressed. One hundred eighty-one, (49.3%) of respondents were malnourished. Concerning to history of falls, one hundred twenty-two (33.2%) of respondents had a previous history of falls over the past year. One hundred fifty-one (41.1%) of respondents had comorbidity. Regarding to social support status of respondents, one hundred seventy-three (47.1%) had poor social support. The majority of the respondents, 199(54.2%) had a history of hospitalization over the last year. In addition, one hundred seventy-six, (48%) were dependent on their activities of daily living “Table 4 ”. Table 4 Geriatric health-related outcomes and psychosocial factors of elderly patients in Wolaita Zone public hospitals, 2023(n = 367) Variables Category Frequency Percentage (%) Depression Depressed 115 31.3 Non-depressed 252 68.7 Nutritional Status Well-nourished 186 50.7 Malnourished 181 49.3 Falling history Yes 122 33.2 No 245 66.8 Comorbidity Yes 151 41.1 No 216 58.9 Social support Good 194 52.9 Poor 173 47.1 Hospitalization over one year Hospitalized 199 54.2 Non-hospitalized 168 45.8 The activity of daily living dependence Dependent 176 48 Non-dependent 191 52 Prevalence of frailty The prevalence of frailty among 367 elderly patients in Wolaita Zone public hospital by FRAIL-NH scale was 47.4% (95%CI; 42-52.6) “Fig. 2” Frailty status based on sex category About 48(27.6%) males and 126(72.4%) females were frail from the total frail group and 118(61.1%) males and 75(38.9%) females were non-frail from the total non-frail group “Fig. 3 ”. Factors associated with frailty In bivariate analysis, 13 variables were candidates for multivariable logistic regression with p-value ≤ 0.25. In multivariable logistic regression, eight variables (Age, sex, weight gain, malnutrition, poor social support, hospitalization, depression, and activity of daily living dependence) were significantly associated with frailty. Being older age (70-74years), (75–79 years) and (≥ 80years) will increase the odds of being frail by 2.79(AOR = 2.79, 95%CI (1.202, 6.45), 3.2(AOR = 3.2, 95%CI (1.22, 8.5) and 3.46(AOR = 3.46, 95%CI (1.6–7.7) times as compared to those in age (65–69) group respectively. Females were 2.2 times more likely to be frail than males (AOR = 2.17, 95%CI (1.16, 4). Elderly patients who had malnutrition were 3.7 times more likely to be frail than well-nourished patients (AOR = 3.7, 95%CI (1.89, 7.3). Elderly patients who have poor social support were 3 times more likely to be frail than those who had good social support (AOR = 3, 95%CI (1.6, 5.7). Depressed elderly patients were 3.5 times more likely to be frail than non-depressed ones (AOR = 3.5, 95%CI (1.72, 7.11). An elderly patient who was dependent on the activity of daily living was 4.65 times more likely to be frail than non-dependent patients (AOR = 4.65, 95%CI (2.41, 8.9). An elder patient whose weight range between 60–69 kg was 71% times less likely to be frail than those in a weight group of ≥ 70 kg (AOR = 0.29, 95%CI (0.1–0.76). Elderly patients who had a history of hospitalization over the last year were 2.6 times more likely to be frail than non-hospitalized patients (AOR = 2.6, 95%CI (1.4–4.8) “Table 5 ”. Table 5 Bivariate and multivariable analysis of factors associated with frailty among elderly patients in public hospitals of Wolaita Sodo, Sothern Ethiopia, 2023(n = 367) Variable Category Frailty status COR (95%CI) AOR (95%CI) Frail (%) Non-frail (%) Age 65–69 35(32.4) 73(67.6) 1 70–74 44(48.9) 46(51.1) 2(1.1–3.55) 2.79(1.2–6.44) * 75–79 33(52.4) 30(47.6) 2.3(1.21–4.34) 3.2(1.22–8.5) * ≥ 80 62(58.2) 44(41.5) 2.94(1.7–5.14) 3.46(1.56–7.7) * Sex Male 50(29.8) 118(70.2) 1 Female 124(62.3) 75(37.7) 4.13(2.66–6.4) 2.17(1.16-4) * Marital status Single 55(57.3) 41(42.7) 2.2(1.31–3.72) 1.44(0.67–3.1) Married 56(37.8) 92(62.2) 1 Widowed 49(58.3) 35(41.7) 2.3(1.33–3.97) 1.32(0.6–2.9) Divorced 14(35.9) 25(64.1) 0.92(0.44–1.9) 0.5(0.165-1.5) Weight 50-60Kg 85(66.9) 42(33.1) 3.4(1.66-7) 0.74(0.26–2.2) 60-70Kg 73(37.1) 124(62.9) 0.99(0.5-2) 0.29(0.1–0.76) ≥ 70 16(37.2) 27(62.8) 1 Educational Status No formal education 73(51.4) 69(48.3) 2(0.97-4) 1.0(0.29–3.44) Primary-education 52(46.8) 59(53.2) 1.65(0.8–3.4) 0.97(0.29–3.23) Secondary-education 34(47.9) 37(52.1) 1.72(0.78–3.75) 1.5(0.455-5.1) Higher education 15(34.9) 28(65.1) 1 Income status ≤ 1500 92(52.3) 84(47.7) 1.8(1.05–3.135) 1.5(0.55–4.12) 1501–3500 53(46.5) 61(53.5) 1.44(0.8–2.6) 2.2(0.84–5.78) ≥ 3500 29(37.7) 48(62.3) 1 Nutritional status Malnourished 126(69.6) 55(30.4) 6.59(4.2–10.4) 3.73(1.9–7.3) * Well-nourished 48(25.8) 138(74.2) 1 Social support Good 50(25.8) 144(74.2) 1 Poor 124(71.7) 49(28.3) 7.3(4.6–11.6) 3(1.6–5.7) ** Hospitalization history Hospitalized 122(61.3) 77(38.7) 3.53(2.3–5.46) 2.6(1.4–4.8) * Non-hospitalized 52(31) 116(69) 1 Falling history Yes 79(45.4) 43(22.3) 2.9(1.85–4.56) 1.53(0.73–3.2 No 95(54.6) 150(77.7) 1 Depression Status Depressed 85(73.9) 30(26.1) 5.2(3.18–8.47) 3.5(1.7–7.11) ** Non-depressed 89(35.3) 163(64.7) 1 Comorbidity Yes 78(36.1) 138(63.9) 3.1(2-4.76) 1.33(0.66–2.7) No 96(63.6) 55(36.4) 1 The activity of daily living dependence Dependent 125(71) 51(29) 7.1(4.5-11.25) 4.65(2.4–8.9) * Non-dependent 49(25.7) 142(74.3) 1 CI, confidence interval; AOR, adjusted odds ratio; COR, crude odds ratio *P value < 0.05; **P value < 0.001; and 1-reference. Discussion To the best of our understanding, no study on frailty has been conducted in both inpatient and outpatient departments in public hospital settings on elderly patients (≥ 65 years). In this study, hospital-based cross-sectional study, a high prevalence of frailty was observed. This study found that the overall prevalence of frailty was 47.4%, and gave new evidence on frailty in both inpatient and outpatient departments. Our study identified significant associated factors for frailty such as increased age, being female, malnutrition, depression, weight gain, poor social support, hospitalization over one year, and activity of daily living dependence were factors found to be significantly associated with frailty. Our finding is consistent with the study conducted in Brazil 47.2%[ 37 ], USA 48.7%[ 38 ], and Ethiopia 45%[ 12 ], which verified that frailty was highly prevalent. This consistency might be due to similarity in the age of participants, sample size, and frailty identification tool (FRIAL-NH scale) respectively. On the other hand, this prevalence is slightly lower as compared to studies conducted in Egypt (71.1%)[ 39 ] and Nigeria (63.3%)[ 8 ]. In the case of Egypt, the discrepancy might be due to differences in sample size, and socio-demographic characteristics especially the age of participants. In Nigeria, the difference might be due to the frailty method difference, measuring tool, they use the Canadian Study of Health and Aging (CSHA) clinical frailty scale but the FRIAL-NH scale mostly applicable, valid, and reliable tool to assess frailty among hospitalized patients and socio-demographic differences. The observed variations in the prevalence of frailty may potentially have been caused by changes in socioeconomic position, therapeutic factors, population features, variation in health status, and nutritional status of the population. In another way, this study's prevalence is higher than the study conducted in Vietnam 31.9%[ 40 ], Germany 31%[ 41 ], and Ethiopia(9.1%)[ 42 ]. In the case of Vietnam, the discrepancy might be due to differences in the methodology of the study, and frailty identification tools they employ fried frailty criterion to identify frailty. In Germany, the difference might be due to the difference in study population, they use outpatient departments only to conduct the study. In the case of Ethiopia, the discrepancy might be due to the difference in the population of the study especially the age of the participants (they use age ≥ 50 years). The way that frailty was identified also varied throughout studies; most studies employ Fried's frailty criterion as a means of determining the prevalence of frailty[ 43 ]. Concerning to age of patients, this study indicated that being older was more likely to be frail than those aged between 65–69 years. In this study, those elder patients belonging within the age range of 70–74 years, 75–79 years, and ≥ 80 years were significantly associated with frailty. This finding is supported by the study conducted in Ethiopia [ 12 ], South India[ 44 ], Spain[ 45 ], and Bangladesh[ 46 ]. The possible explanation may be besides to aging process, physiological changes in older adults have been noted, including insulin resistance, hormonal imbalances, the activation of specific inflammatory processes, decreased fat-free muscle mass, and changes in body composition. These changes can eventually lead to the development of frailty syndrome[ 47 ]. This finding suggests that the occurrence of frailty is amplified with increasing age. In this study, females were more likely to be frail than males, which is consistent with studies conducted in the USA[ 48 ], Bangladesh[ 49 ], and Ethiopia[ 12 ]. The possible justification may be due to females have an intrinsically higher risk of frailty because they have less lean body mass than males in the same age range; as well as having an extrinsically higher risk of frailty because of poor eating habits which make them more vulnerable to the effects of sarcopenia[ 50 ]. Pathophysiological, emotional, cognitive, and comorbidity variations have been cited as explanations for the gender disparities in frailty[ 51 ]. This result holds implications that females are more at risk of developing frailty than men. On the other hand, this finding contradicts the study conducted in Nigeria[ 8 ], the possible explanatory might be due to differences in methodological variation especially the ages of participants. The disparities in frailty across the sexes may be attributed to variations in pathophysiological causes, mood, cognition, and comorbidity[ 52 ]. Weight is significantly associated with frailty. Those elderly patients within the weight range of 60–70 kg were less likely to be frail than those ≥ 70kg. This study was consistent with the study conducted in the United States, the possible justification may be due to a weight trajectory going more toward the idea of sarcopenic obesity, rather than a rapid gain in weight, which may be a better indicator of health[ 53 ]. A key area emerging from the current finding is having weight dysregulation increases the risk of frailty occurrence. Nutritional status is significantly associated with frailty. This study was consistent with the study conducted in Indonesia[ 54 ], Vietnam[ 55 ], Korea[ 56 ], and Nigeria[ 8 ], where malnourished patients were more likely to be frail than well-nourished patients. This consistency might be due to similarities in nutritional assessment tools (MNA-SF), study population groups, and similarity in age groups. The possible explanation may be the development of frailty is greatly influenced by malnutrition, which is linked to weight loss that causes weakness, weariness, a sluggish gait, and inactivity[ 57 ]. This finding suggested that malnutrition increases the risk of developing frailty. In this study those patients who had poor social support were more likely to be frail than those who had good social support, or an increase in social support was statistically significantly associated with a decrease in the odds of having frailty in older patients, this finding supported by the study conducted in Singapore[ 58 ], China[ 59 ], and Thailand[ 60 ], it demonstrates a bidirectional relationship between the degree of social support and frailty, nevertheless. The possible justification may be that frail patients gradually lose their ability to interact and establish good relationships with others [ 61 ]. This implication holds that having poor social support increases the risk of frailty development in elderly patients. Depressions were significantly associated with frailty in elderly patients, those who were depressed had increased odds to become frail than non-depressed ones. This finding is supported by the study findings in Australia[ 62 ], and Ethiopia[ 12 ]. This correlation, which could be explained by depression, may point to frailty brought on by a decrease in social ties, a slow gait, and a decrease in physical activity. It might be a sign of frailty brought on by an increase in sedentary behavior, a higher risk of falling, weight loss, and malnourishment, all of which can exacerbate depressive symptoms including sorrow, helplessness, and anhedonia[ 63 ]. A key area emerging from the current finding is having depression increases the risk of frailty occurrence. Hospitalization is significantly associated with frailty. This is in line with previous studies conducted in London[ 64 ], and Australia[ 28 ], where being hospitalized is more likely to be frail than non-hospitalized once. This might be due to being hospitalized increases the vulnerability to different types of diseases and psychological stress and hospitalization induces a decrease in muscle strength and health-related quality of life in adults and the elderly [ 65 ]. The results hold implications for hospitalization raising the risk of frailty occurrence. Elderly patients those dependent on activities of daily living were more likely to be frail than non-dependent elderly patients. This is consistent with the study done in Nigeria and West Bengal [ 8 , 66 ]. The possible explanatory might be due to the consequence of the aging process, and older persons who self-impose restrictions on their daily activities because they are afraid of falling tend to use less energy, which leads to the formation of intramuscular fat. Intramuscular adipose tissue contributes to inflammatory conditions involved in the frailty etiopathogenesis by releasing proinflammatory cytokines and by encouraging higher numbers of leukocytes and fibrinogen[ 67 ]. A key area emerging from the current results is being dependent on daily living activities increases the development of frailty among elderly patients. This study tried to assess the factors associated with frailty among hospitalized elderly patients in public hospitals. It adds evidence-based knowledge related to frailty. However, due to the nature of the study design, this study could not establish a cause-effect relationship. Therefore, additional studies will be required to indicate the temporal cause-effect association. We only consider weight as an independent variable, it may be affected by other factors, so future research may consider additional variable such BMI to strength their findings. Conclusion The prevalence of frailty was higher in this study. Older age, being female, weight gain, depression, hospitalization over the past year, poor social support, malnutrition, and activity of daily living dependence are factors associated with frailty in Wolaita zone public hospitals. Therefore, healthcare providers better give awareness and education about social support to frail elderly patients from family, friends, and communities give priority to early identification and management of depression, and provide education and support to elderly patients. Early detection and management of frail is important to improve dietary intake and treat any underlying medical issues that may be causing malnutrition better to be the main goals of treatment. The patient should be instructed about healthy weight through diet modification and lifestyle changes to minimize the risk of frailty development. It’s important to be involved in daily living activities to maintain muscle strength and the ability to delay frailty development. Acronyms AOR, Adjusted Odd Ratio; FRAIL-NH, Frail Nursing Home; ADL, The Activity of Daily Living; LMICs, Low and Middle-Income Countries; MNA-SF, Mini Nutritional Assessment Short Form; OSSS, Oslo Social Support Scale; PA, Physical Activity; PHQ-9, Patient Health Questionnaire; SPSS, Statistical Package for Social Science, ETB; Ethiopian birr. Declarations Acknowledgment First, I would like to thank Wolaita Sodo University, the College of Medicine and Health Sciences, and the School of Nursing for providing me with the opportunity to pursue this master’s program. Moreover, I would like to thank the data collectors, supervisors, and all the study participants for their time and willingness to take part in the study. The study "Frailty and associated factors among elderly patients in Wolaita Zone public hospitals, southern Ethiopia" is our original work, as we, the undersigned authors, officially declare. This study is not currently being considered for publication in any other journal, nor has it been published elsewhere.We confirm that all authors have contributed significantly to the conception, design, data collection, analysis, and interpretation of the study. This study is a cross-sectional observational study but not a clinical trial. Due to this, trial registration was not needed. Ethical approval for this study was obtained from Wolaita Sodo university Ethical Review Board (Ref.No/CRCSD 4/1996/2011 and project number: CHSM/ERC/04/15), and written informed consent was obtained from all participants before data collection. The study was conducted in accordance with ethical principles and guidelines for research involving human subjects. Informed consent was obtained from all the participants. Patients who agreed to participate signed a written consent form. This research project received no specific grant from any funding agency in the public, commercial, not for profit sectors. 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Additional Declarations No competing interests reported. Supplementary Files Table1.tif Table2..tif Table2cont....pptx Table3.tif Table4.tif Table5.tif Table5cont....tif Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6943157","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":497296369,"identity":"707573d6-4fa8-4520-970b-29e45de64294","order_by":0,"name":"Besufikad Yilma 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10:19:55","extension":"tif","order_by":6,"title":"","display":"","copyAsset":false,"role":"supplement","size":208530,"visible":true,"origin":"","legend":"","description":"","filename":"Table5cont....tif","url":"https://assets-eu.researchsquare.com/files/rs-6943157/v1/fc3c48094a81e0a7d70110be.tif"}],"financialInterests":"No competing interests reported.","formattedTitle":"Frailty and associated factors among elderly patients in Wolaita Zone public hospitals, south Ethiopia","fulltext":[{"header":"Introduction","content":"\u003cp\u003eAging is an inherent aspect of human existence. Today, the aging of the population has become one of the major variables impacting the age distribution of the population in all nations[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. A major effect of aging is frailty, which increases the likelihood that patients may have negative health outcomes like disability and mortality[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. According to the original definition in the field of geriatrics, frailty is a distinct biological syndrome with a declining physiologic reserve and increased vulnerability to health stressors. It is also a multidimensional dysregulation of one or more physiologic systems, such as the immunological, musculoskeletal, cardiovascular, cerebral, and/or neurological systems [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eGlobally, an increased number of individuals are experiencing frailty, and it is predicted that 150\u0026nbsp;million older adults may experience frailty over the next 35 years[\u003cspan additionalcitationids=\"CR5 CR6\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. The prevalence of Frailty among older patients receiving medical care was estimated to be from 50\u0026ndash;80% [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. According to a recent meta-analysis, the prevalence of frailty and pre-frailty in low- and middle-income countries (LMICs) was 12.3% and 55.3% which was higher than the prevalence in high-income countries with a prevalence of 8.2% and 43.9% respectively[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eIn Sub-Saharan Africa, by 2030 it's anticipated that its elderly population could reach over 67\u0026nbsp;million and despite to this Frailty in older individuals in sub-Saharan Africa has not been studied in detail[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. In Ethiopia, the prevalence of frailty among residential care facilities, and older adults living with HIV is 45%, and 9.1% respectively[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eFrailty has a significant impact on people and society since it increases the likelihood of impaired activities of daily living (ADL), impairment, and illness and it also shows different symptoms such as decreased mobility, weakness, decreased muscle mass, poor nutritional status, and impaired cognitive function [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. These may affect the quality of life and access to medical resources and due to this frailty and its prevention have started to receive great attention in recent years [\u003cspan additionalcitationids=\"CR16 CR17\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. However, based on previous studies, different factors can contribute to the development of frailty such as advanced age, being female, lower dietary protein intake, lack of daily physical exercise, high body mass index and lower education level, sleeping difficulties, and self-reported diabetes, former alcohol use, vision dysfunction, defecation dysfunction [\u003cspan additionalcitationids=\"CR20 CR21 CR22 CR23\" citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eA study found that multimodal therapy for frail old patients, including physical activity, nutritional adjustments, and psychological care, had a positive effect on a variety of clinical outcomes[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. This study helps healthcare providers to give targeted interventions to enhance recovery and reduce negative health outcomes and it\u0026rsquo;s also important to prepare a nursing care plan for the patient to deliver the right quality intervention, through identifying different types of associated factors.\u003c/p\u003e\u003cp\u003eThe frailty and associated factors have been extensively studied in developed and high-income countries, but in the case of sub-Saharan Africa especially Ethiopia the evidence on frailty remains limited. The previous studies indicated that there is association between frailty and factors such as malnutrition, chronic diseases, and poor social support, but there is scarcity of localized data.\u003c/p\u003e\u003cp\u003eFrailty in underdeveloped nations, especially in Ethiopia, received little attention despite its significant negative health impacts. There are some studies to show the extent of this, especially in hospital settings besides the variation of demographic aging and occurrence of different types of communicable and uncommunicable diseases. So, this study helps to quantify the burden of frailty and is used to prioritize the required intervention for susceptible elderly patients. Therefore, this study aimed at assessing frailty and associated factors among elderly patients in Wolaita Zone public hospitals, south Ethiopia, 2023\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eStudy design, Period, and setting\u003c/h2\u003e\u003cp\u003eA hospital-based cross-sectional study design was applied to elderly patients in the inpatient and outpatient departments of Wolaita Zone Public Hospitals from August 16 to September 21, 2023.\u003c/p\u003e\u003cp\u003eWolaita Sodo is the political and administrative center and is located about 328 km south of Addis Ababa, the capital city of Ethiopia. In the Wolaita zone, there are 68 health centers, 9 public hospitals, and 5 private hospitals.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003ePopulation\u003c/h3\u003e\n\u003cp\u003e\u003c/p\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eAll elderly patients (≥ 65 years) who attend public hospitals in outpatient and inpatient departments of all adult wards in Wolaita zone public hospitals were the source population, and all elderly patients (≥ 65 years) who attend Wolaita zone public hospitals as outpatient and inpatient department in all adult wards during the study period were the study population.\u003c/p\u003e\u003c/div\u003e\u003cp\u003e\u003c/p\u003e\n\u003ch3\u003eInclusion and Exclusion criteria\u003c/h3\u003e\n\u003cp\u003e\u003c/p\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eAll elderly patients aged 65 years and older who attended the public hospitals during the study period in all adult wards of outpatients, and inpatient departments in the selected public hospitals were included. Those who were seriously ill or unable to respond and communicate well were excluded from the study.\u003c/p\u003e\u003c/div\u003e\u003cp\u003e\u003c/p\u003e\n\u003ch3\u003eSample size determination\u003c/h3\u003e\n\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003eSample Size Determination for proportion\u003c/h2\u003e\u003cp\u003e\u003c/p\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eThe sample size was determined by using the single population proportion formula with the following assumption:\u003c/p\u003e\u003cp\u003en = Sample size\u003c/p\u003e\u003cp\u003eZ = level of significance = 95%CI = 1.96, d margin of error of 0.05, and proportion of frailty of elderly patients from the previous study at Hawassa Hospital (P), 9.1%[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e].\u003c/p\u003e\u003cp\u003e\u003cimg 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\" width=\"230\" height=\"194.387\" style=\"width: 230px; height: 194.387px;\"\u003e\u003c/p\u003e\u003cp\u003eBy adding a 10% non-response rate, the sample size for the first objective was \u003cb\u003e139\u003c/b\u003e.\u003c/p\u003e\u003c/div\u003e\u003cp\u003e\u003c/p\u003e\n\u003ch3\u003eSample size determination for factors\u003c/h3\u003e\n\u003cp\u003e\u003c/p\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eThe sample size for the second objective was calculated by using Statcalc of Epi Info statistical software version 7.2.5. with the following assumption: confidence level = 95% Power = 80%, The ratio of unexposed to exposed equivalent to 1, P1 = proportion of outcome in the exposed group and P2 = proportion of outcome in the unexposed group. The maximum sample size calculated was 346 “ Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e”\u003c/p\u003e\u003c/div\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eBy adding a 10% non-response rate, the final sample size of our study becomes \u003cb\u003e381.\u003c/b\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eSample size determination for the factors associated with frailty\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariable\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAssumptions\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eProportion (%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e95%CI\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eSample\u003c/p\u003e\u003cp\u003esize(n)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eReference\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSex\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e✓ 95%CI\u003c/p\u003e\u003cp\u003e✓ 80% power\u003c/p\u003e\u003cp\u003e✓ Ratio (exposed to unexposed) = 1:1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eP1 = 73%\u003c/p\u003e\u003cp\u003eP2 = 58.1%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.005–3.774\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e346\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eMalnutrition\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eP1 = 94.8%\u003c/p\u003e\u003cp\u003eP2 = 66.2%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.029–83.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e72\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eMultimorbidity\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eP1 = 95.8%\u003c/p\u003e\u003cp\u003eP2 = 83.9%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.944–10.006\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e232\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eFunctional dependence\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eP1 = 82.1%\u003c/p\u003e\u003cp\u003eP2 = 68.4%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.029–4.343\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e340\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"6\"\u003eCI, confidence interval\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003cp\u003e\u003c/p\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003eSampling Technique and Procedure\u003c/h2\u003e\u003cp\u003eFrom 9 public hospitals in the Wolaita zone, 4 were selected randomly. The sample size was proportionally divided into each hospital based on the average number of elderly patients attending those hospitals per month, after determining the total number of elderly patients in one year, which is obtained from each hospital's health information management system. The allocated number of elderly patients for each hospital is again proportionally divided into all adult wards (Outpatient department, Emergency outpatient department, medical ward, surgical ward, Orthopedics, Gynecology, ophthalmology ward, Adult ICU, and Oncology) in the hospital based on the number of average numbers of elderly patients in each ward per month. From each ward elderly patients were selected by using Systematic random sampling (SRS) by assigning unique identification numbers to each patient in the ward then samples were selected every 3rd interval in each public hospital based on selection criteria. The numbers of elderly patients who attend per year in each randomly selected public hospital are WSUCSH (11,300), Humbo (1414), Boditi (600), and Bitena PH (1500). “ \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eFig.\u0026nbsp;1”\u003c/span\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003eStudy variables\u003c/h2\u003e\u003cdiv id=\"Sec13\" class=\"Section3\"\u003e\u003ch2\u003eDependent variable\u003c/h2\u003e\u003cp\u003eFrailty status (Non-frail, Frail)\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003eIndependent variables\u003c/h2\u003e\u003cp\u003eSocio-demographic variables, Geriatric health allied outcomes, Nutritional status, Psycho-social factors, Substance use, activity of daily living dependence\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\u003ch2\u003eOperational definitions\u003c/h2\u003e\u003cp\u003e\u003cstrong\u003eElderly patients\u003c/strong\u003e\u003c/p\u003e\u003cp\u003eAccording to the WHO definition, those who are aged 65 or above, and require comprehensive care to address their physical, mental, and social needs or problems[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e].\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eFrail\u003c/strong\u003e\u003c/p\u003e\u003cp\u003eelder patients who have a test above the mean score ≥ 7 on the FRAIL-NH scale[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eNon-frail\u003c/strong\u003e\u003c/p\u003e\u003cp\u003eelder patients who have a score a point below the mean score \u0026lt; 7 of the FRAIL-NH scale\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eMalnourished\u003c/strong\u003e\u003c/p\u003e\u003cp\u003ean elderly patient whose test score is below the mean score ≤ 7 of MNA-SF[\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eNormal nutrition\u003c/strong\u003e\u003c/p\u003e\u003cp\u003eelderly patients who score a point above the mean \u0026gt; 7 of MNA-SF\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eDepression in elderly patients\u003c/strong\u003e\u003c/p\u003e\u003cp\u003eDepressions in elderly patients were measured by using the PHQ-9 depression assessment tool. Elderly patients who scored 10–27 were taken as depressed[\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e].\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eSocial support\u003c/strong\u003e\u003c/p\u003e\u003cp\u003eit is defined as based on the score obtained from measurements, which consists of 3 items that range from 3–14. A score of ≤ 8 on the Oslo social support scale was considered as poor support and a score \u0026gt; 8 was considered as strong support[\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e].\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eADL dependency\u003c/strong\u003e\u003c/p\u003e\u003cp\u003eMeasured by the Katz Index of Independence in activities of daily living an elderly patient with a score of ≤ 5 was taken as ADL dependence[\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e].\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\u003ch2\u003eData collection tools and procedure\u003c/h2\u003e\u003cp\u003eData were collected from both outpatient and inpatient departments in all adult wards where elderly patients were found by using interviewer-administered questionnaires. The questionnaire was prepared by reviewing different literature and by adapting from a previous similar study which is conducted on frailty in Addis Ababa[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Quantitative questionnaires have seven parts: Part I-Socio-demographic characteristics, Part II- substance use behavior, Part III-Frailty assessment, Part IV-psycho-social factors assessment, Part V Geriatric nutritional factors assessment, Part VI- Geriatric health-allied outcomes and Part Ⅶ: Activity of daily living dependence. The data was collected by BSc nurses and MSc holders in the health field who supervised the activity of the data collectors.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\u003ch2\u003eFrailty measurement\u003c/h2\u003e\u003cp\u003eIn this study, frailty was assessed by using the FRAIL-NH scale. This instrument (tool) contains seven items (fatigue, resistance, ambulation, incontinence, loss of weight, nutrition, and help with dressing). Four of these items (transferring, continence, feeding, and dressing) were obtained from the Katz Activities of Daily Living scale, the two items (weight loss and mobility) from the mini–Nutritional Assessment Short Form, and one item (energy) from the quality of life in Alzheimer’s diseases scale. The seven items were scored as 0, 1, or 2 giving a total score of (0–14) and those elderly patients who scored ≥ 7 were considered frail, and \u0026lt; 7 indicated that non-frail based on the FRAIL- NH scale [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. The following two self-reported questions from the Center for Epidemiologic Studies-Depression (CES-D) Scale were used to gauge fatigue[\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e], “In the last month, I felt that everything I did was an effort, and I was unable to start. Weight loss was defined as unintended weight loss of more than 5 kg during the previous three months, excluding activity and diet. Incontinence and self-dressing skills were assessed to determine functional decline.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e\u003ch2\u003eIndependent variable measurement\u003c/h2\u003e\u003cp\u003eNutritional status was assessed by Mini-Nutritional Assessment-Short Form (MNA-SF)[\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. It comprises six questions that can be completed in less than 5 minutes; a dietary questionnaire and subjective assessment. A total possible MNA-SF score ranges from 0 to 14(each item has 2 points). Depression in elderly patients was measured by using PHQ-9(patient health questionnaire), which is an elderly patients depression assessment tool it contains 9 questions and its response is scored as 0, 1, 2, and 3. Elderly patients who scored 10–27 were taken as depressed[\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. The comorbidity status of elderly patients was assessed according to the Charlson Comorbidity Index diseases list. This is the occurrence of two or more health conditions in the same patient[\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. The social support status of elderly patients was assessed by the Oslo Social Support Scale (OSSS-3 scale), which consists of 3 items that range from 3–14[\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. The Katz index of independence: was used to assess the functional status of elderly patients. The index ranks adequacy of performance in the six functions (bathing, dressing, toileting, transferring, continence, and feeding).\u003c/p\u003e\u003cp\u003eIts interpretation of the score is given yes = 1 and no = 0 for independence in each of the six functions of items, and a score of 6/6 indicates the full function, a score of 4/6 indicates moderate impairment, and if it scores of 2/6 or less indicates severe functional impairment and the attainable score were 0 to 6. An individual with a score of ≤ 5 was taken as ADL dependent [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eA calibrated digital scale was used to assess weight in ambulatory patients, while a bed scale was used in non-ambulatory patients. Weight was recorded and analyzed as a categorical variable for each participant while they were wearing light garments.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec19\" class=\"Section2\"\u003e\u003ch2\u003eData Quality Assurance\u003c/h2\u003e\u003cp\u003eThe questionnaires were pre-tested on 5%(n = 19) of the sample size at Shone Primary Hospital, which was not part of the main study area. Based on the findings of the pre-test some adjustments and developments of the tool were done.\u003c/p\u003e\u003cp\u003eThe training was given to data collectors and supervisors on the aim of the study, the subjects of the questionnaire, and maintaining the privacy and confidentiality of the study subjects for three days. Data collectors were instructed to check the completeness of each questionnaire whether every question was completely answered and the supervisor rechecked the completeness of the questionnaire after submission.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec20\" class=\"Section2\"\u003e\u003ch2\u003eData Processing and Analysis\u003c/h2\u003e\u003cp\u003eData was coded and then, entered into Epi-data version 4.6 and exported to SPSS statistical software with version 26 for further data management and analysis. The univariate analysis such as the percentage and frequency distribution of different characteristics of the questionnaire was analyzed. The continuous variables were expressed as mean ± standard deviation (SD), and categorical variables were expressed as frequencies and percentages. Bivariate analysis was used to identify the association between each independent variable with the dependent variables and also Crude odds ratio (COR) was calculated in bivariate analysis. The multivariable logistic analysis was performed for variables with p-values \u0026lt; 0.25 in the bivariate analysis. It was performed to identify factors associated with frailty among elderly patients and reported in the adjusted odd ratio (AOR) to measure the association between variables.\u003c/p\u003e\u003cp\u003eA 95% confidence interval (CI) was reported, and a p-value \u0026lt; 0.05, was considered statistically significant. The results were presented using text, tables, and figures. The Hosmer- Lemeshow goodness of fit test was conducted to assess model fitness (p-value = 0.5).\u003c/p\u003e\u003cp\u003eMulti-collinearity was checked by using variance inflation factor (VIF) and tolerance test for each independent variable. The VIF value for each independent variable in this model ranges from 1.054 to 1.55 and the Tolerance test ranges from 0.65 to 0.95, indicating that there is no multicollinearity.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec21\" class=\"Section2\"\u003e\u003ch2\u003eEthical consideration\u003c/h2\u003e\u003cp\u003e Ethical clearance and approval were obtained from the Institutional Ethical Review Board (IERB) of the College of Health Sciences and Medicine, Wolaita Sodo University (ERC Project number: CHSM/ERC/04/15). Upon approval, the hospital directors received a formal letter from the Wolaita Sodo University College of Health Science and Medicine's research and community service directorate. Informed consent (both written and verbal) was obtained from all subjects for their participation after the nature of the study was fully explained to them. All study participants were encouraged to participate in the study and at the same time, they were told that they had the right not to participate. At last, data was collected after assuring the confidentiality nature of responses, by avoiding the name and other personal identification of each participant.\u003c/p\u003e\u003c/div\u003e"},{"header":"Result","content":"\u003ch2\u003eSocio-demographic characteristics of respondents\u003c/h2\u003e\u003cp\u003eA total of 367 study participants were included in this study with a response rate of 96.33%. About 108(29.4%) of the study participant's age group was between 65–69 years and the mean age was 73 ± 6.3years. The majority of the study participants 201(54.8%) were female. One hundred forty-eight (40.3%) of respondents were married, and 142(38.7%) respondents did not get formal education. About 114(31.1%) respondent’s income statuses were between 1501 and 3500 birrs. Regarding weight, the majority of respondents, 197(53.7%) were within the weight range of 60–70 Kg “Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e2\u003c/span\u003e”\u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eSocio-demographic characteristics of elderly patients in Wolaita Zone public hospitals, Ethiopia, 2023(n = 367)\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariables\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCategories\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eFrequency\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePercentage (%)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e\u003cb\u003eAge\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e65–69\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e108\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e29.4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e70–74\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e90\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e24.5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e75–79\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e63\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e17.2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e≥ 80\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e106\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e28.9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cb\u003eSex\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e166\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e45.2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e201\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e54.8\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e\u003cb\u003eEducational\u003c/b\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eStatus\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo formal education\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e142\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e38.7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePrimary education\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e111\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e30.2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSecondary-education\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e71\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e19.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHigher education\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e43\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e11.7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e\u003cb\u003eMarital status\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMarried\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e148\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e40.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSingle\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e96\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e26.2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eWidowed\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e84\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e22.9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDivorced\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e39\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e10.6\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003eWeight\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e50-60kg\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e127\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e34.6\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e60-70kg\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e197\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e53.7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e≥ 70kg\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e43\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e11.7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e\u003cb\u003eIncome-status\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026lt; 1500 ETB\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e176\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e48\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1500–3500 ETB\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e114\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e31\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026gt; 3500 ETB\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e77\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e21\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e\u003c/div\u003e\u003ch2\u003eSubstance use behavior of participants\u003c/h2\u003e\u003cp\u003eConcerning substance use behavior, the majority of the respondents, 254(69.2%) were non-smokers and 68(18.5%) were previous smokers. Two hundred sixty-five (72.2%) of respondents were non-chat chewers, one hundred fifty-nine (43.3%) were non-alcohol drinkers, and 141(38.4%) were previous alcohol drinkers “Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e3\u003c/span\u003e”.\u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eSubstance use behavior of elderly patients in Wolaita Zone public hospitals, Ethiopia, 2023(n = 367)\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariables\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCategory\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eFrequency\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePercentage (%)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003eSmoking habit\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePrevious-smoker\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e68\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e18.5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCurrent -smoker\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e45\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e12.26\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNon-smoker\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e254\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e69.2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003eChat-chewing\u003c/p\u003e\u003cp\u003eHabit\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePrevious-chewer\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e62\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e16.9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCurrent-chewer\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e10.9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNon-Chewer\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e265\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e72.2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003eAlcohol consumption\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePrevious-drinker\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e141\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e38.4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCurrent-drinker\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e67\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e18.25\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNon-drinker\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e159\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e43.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e\u003c/div\u003e\u003ch2\u003ePsycho-social factors and other geriatric health-related outcomes of respondents\u003c/h2\u003e\u003cp\u003eThe majority of the respondents, 252(68.7%) were non-depressed. One hundred eighty-one, (49.3%) of respondents were malnourished. Concerning to history of falls, one hundred twenty-two (33.2%) of respondents had a previous history of falls over the past year. One hundred fifty-one (41.1%) of respondents had comorbidity. Regarding to social support status of respondents, one hundred seventy-three (47.1%) had poor social support. The majority of the respondents, 199(54.2%) had a history of hospitalization over the last year. In addition, one hundred seventy-six, (48%) were dependent on their activities of daily living “Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e4\u003c/span\u003e\u003cb\u003e”.\u003c/b\u003e\u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eGeriatric health-related outcomes and psychosocial factors of elderly patients in Wolaita Zone public hospitals, 2023(n = 367)\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariables\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCategory\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eFrequency\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePercentage (%)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cb\u003eDepression\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDepressed\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e115\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e31.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNon-depressed\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e252\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e68.7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cb\u003eNutritional\u003c/b\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eStatus\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eWell-nourished\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e186\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e50.7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMalnourished\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e181\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e49.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cb\u003eFalling history\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e122\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e33.2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e245\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e66.8\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cb\u003eComorbidity\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e151\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e41.1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e216\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e58.9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cb\u003eSocial support\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGood\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e194\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e52.9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePoor\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e173\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e47.1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cb\u003eHospitalization over one year\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHospitalized\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e199\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e54.2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNon-hospitalized\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e168\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e45.8\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cb\u003eThe activity of daily living dependence\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDependent\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e176\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e48\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNon-dependent\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e191\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e52\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e\u003c/div\u003e\u003ch2\u003ePrevalence of frailty\u003c/h2\u003e\u003cp\u003eThe prevalence of frailty among 367 elderly patients in Wolaita Zone public hospital by FRAIL-NH scale was 47.4% (95%CI; 42-52.6) \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e“Fig.\u0026nbsp;2”\u003c/span\u003e\u003c/p\u003e\u003ch2\u003eFrailty status based on sex category\u003c/h2\u003e\u003cp\u003eAbout 48(27.6%) males and 126(72.4%) females were frail from the total frail group and 118(61.1%) males and 75(38.9%) females were non-frail from the total non-frail group \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e“Fig.\u0026nbsp;3\u003c/span\u003e ”.\u003c/p\u003e\u003ch2\u003eFactors associated with frailty\u003c/h2\u003e\u003cp\u003eIn bivariate analysis, 13 variables were candidates for multivariable logistic regression with p-value ≤ 0.25. In multivariable logistic regression, eight variables (Age, sex, weight gain, malnutrition, poor social support, hospitalization, depression, and activity of daily living dependence) were significantly associated with frailty.\u003c/p\u003e\u003cp\u003eBeing older age (70-74years), (75–79 years) and (≥ 80years) will increase the odds of being frail by 2.79(AOR = 2.79, 95%CI (1.202, 6.45), 3.2(AOR = 3.2, 95%CI (1.22, 8.5) and 3.46(AOR = 3.46, 95%CI (1.6–7.7) times as compared to those in age (65–69) group respectively. Females were 2.2 times more likely to be frail than males (AOR = 2.17, 95%CI (1.16, 4).\u003c/p\u003e\u003cp\u003eElderly patients who had malnutrition were 3.7 times more likely to be frail than well-nourished patients (AOR = 3.7, 95%CI (1.89, 7.3). Elderly patients who have poor social support were 3 times more likely to be frail than those who had good social support (AOR = 3, 95%CI (1.6, 5.7). Depressed elderly patients were 3.5 times more likely to be frail than non-depressed ones (AOR = 3.5, 95%CI (1.72, 7.11). An elderly patient who was dependent on the activity of daily living was 4.65 times more likely to be frail than non-dependent patients (AOR = 4.65, 95%CI (2.41, 8.9). An elder patient whose weight range between 60–69 kg was 71% times less likely to be frail than those in a weight group of ≥ 70 kg (AOR = 0.29, 95%CI (0.1–0.76). Elderly patients who had a history of hospitalization over the last year were 2.6 times more likely to be frail than non-hospitalized patients (AOR = 2.6, 95%CI (1.4–4.8) “Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e5\u003c/span\u003e”.\u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eBivariate and multivariable analysis of factors associated with frailty among elderly patients in public hospitals of Wolaita Sodo, Sothern Ethiopia, 2023(n = 367)\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eVariable\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eCategory\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003eFrailty status\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eCOR (95%CI)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eAOR (95%CI)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eFrail (%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNon-frail (%)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e\u003cb\u003eAge\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e65–69\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e35(32.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e73(67.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e70–74\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e44(48.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e46(51.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2(1.1–3.55)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e2.79(1.2–6.44) *\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e75–79\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e33(52.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e30(47.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.3(1.21–4.34)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e3.2(1.22–8.5) *\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e≥ 80\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e62(58.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e44(41.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.94(1.7–5.14)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e3.46(1.56–7.7) *\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cb\u003eSex\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e50(29.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e118(70.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e124(62.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e75(37.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e4.13(2.66–6.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e2.17(1.16-4) *\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e\u003cb\u003eMarital status\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSingle\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e55(57.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e41(42.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.2(1.31–3.72)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.44(0.67–3.1)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMarried\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e56(37.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e92(62.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eWidowed\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e49(58.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e35(41.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.3(1.33–3.97)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.32(0.6–2.9)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDivorced\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e14(35.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e25(64.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.92(0.44–1.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.5(0.165-1.5)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e\u003cb\u003eWeight\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e50-60Kg\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e85(66.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e42(33.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3.4(1.66-7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.74(0.26–2.2)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e60-70Kg\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e73(37.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e124(62.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.99(0.5-2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.29(0.1–0.76)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e≥ 70\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e16(37.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e27(62.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e\u003cb\u003eEducational\u003c/b\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eStatus\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo formal education\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e73(51.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e69(48.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2(0.97-4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.0(0.29–3.44)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePrimary-education\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e52(46.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e59(53.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.65(0.8–3.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.97(0.29–3.23)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSecondary-education\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e34(47.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e37(52.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.72(0.78–3.75)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.5(0.455-5.1)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHigher education\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e15(34.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e28(65.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e\u003cb\u003eIncome status\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e≤ 1500\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e92(52.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e84(47.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.8(1.05–3.135)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.5(0.55–4.12)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1501–3500\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e53(46.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e61(53.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.44(0.8–2.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2.2(0.84–5.78)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e≥ 3500\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e29(37.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e48(62.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cb\u003eNutritional status\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMalnourished\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e126(69.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e55(30.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e6.59(4.2–10.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e3.73(1.9–7.3) *\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eWell-nourished\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e48(25.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e138(74.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cb\u003eSocial support\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGood\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e50(25.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e144(74.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePoor\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e124(71.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e49(28.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e7.3(4.6–11.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e3(1.6–5.7) **\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cb\u003eHospitalization history\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHospitalized\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e122(61.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e77(38.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3.53(2.3–5.46)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e2.6(1.4–4.8) *\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNon-hospitalized\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e52(31)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e116(69)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cb\u003eFalling history\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e79(45.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e43(22.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.9(1.85–4.56)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.53(0.73–3.2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e95(54.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e150(77.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cb\u003eDepression Status\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDepressed\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e85(73.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e30(26.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e5.2(3.18–8.47)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e3.5(1.7–7.11) **\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNon-depressed\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e89(35.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e163(64.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cb\u003eComorbidity\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e78(36.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e138(63.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3.1(2-4.76)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.33(0.66–2.7)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e96(63.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e55(36.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cb\u003eThe activity of daily living dependence\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDependent\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e125(71)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e51(29)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e7.1(4.5-11.25)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e4.65(2.4–8.9)\u003c/b\u003e *\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNon-dependent\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e49(25.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e142(74.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e\u003c/div\u003e\u003cp\u003eCI, confidence interval; AOR, adjusted odds ratio; COR, crude odds ratio\u003c/p\u003e\u003cp\u003e*P value \u0026lt; 0.05; **P value \u0026lt; 0.001; and 1-reference.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eTo the best of our understanding, no study on frailty has been conducted in both inpatient and outpatient departments in public hospital settings on elderly patients (\u0026ge;\u0026thinsp;65 years). In this study, hospital-based cross-sectional study, a high prevalence of frailty was observed. This study found that the overall prevalence of frailty was 47.4%, and gave new evidence on frailty in both inpatient and outpatient departments. Our study identified significant associated factors for frailty such as increased age, being female, malnutrition, depression, weight gain, poor social support, hospitalization over one year, and activity of daily living dependence were factors found to be significantly associated with frailty.\u003c/p\u003e\u003cp\u003eOur finding is consistent with the study conducted in Brazil 47.2%[\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e], USA 48.7%[\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e], and Ethiopia 45%[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e], which verified that frailty was highly prevalent. This consistency might be due to similarity in the age of participants, sample size, and frailty identification tool (FRIAL-NH scale) respectively. On the other hand, this prevalence is slightly lower as compared to studies conducted in Egypt (71.1%)[\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e] and Nigeria (63.3%)[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. In the case of Egypt, the discrepancy might be due to differences in sample size, and socio-demographic characteristics especially the age of participants. In Nigeria, the difference might be due to the frailty method difference, measuring tool, they use the Canadian Study of Health and Aging (CSHA) clinical frailty scale but the FRIAL-NH scale mostly applicable, valid, and reliable tool to assess frailty among hospitalized patients and socio-demographic differences. The observed variations in the prevalence of frailty may potentially have been caused by changes in socioeconomic position, therapeutic factors, population features, variation in health status, and nutritional status of the population.\u003c/p\u003e\u003cp\u003eIn another way, this study's prevalence is higher than the study conducted in Vietnam 31.9%[\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e], Germany 31%[\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e], and Ethiopia(9.1%)[\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. In the case of Vietnam, the discrepancy might be due to differences in the methodology of the study, and frailty identification tools they employ fried frailty criterion to identify frailty.\u003c/p\u003e\u003cp\u003eIn Germany, the difference might be due to the difference in study population, they use outpatient departments only to conduct the study. In the case of Ethiopia, the discrepancy might be due to the difference in the population of the study especially the age of the participants (they use age\u0026thinsp;\u0026ge;\u0026thinsp;50 years). The way that frailty was identified also varied throughout studies; most studies employ Fried's frailty criterion as a means of determining the prevalence of frailty[\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eConcerning to age of patients, this study indicated that being older was more likely to be frail than those aged between 65\u0026ndash;69 years. In this study, those elder patients belonging within the age range of 70\u0026ndash;74 years, 75\u0026ndash;79 years, and \u0026ge;\u0026thinsp;80 years were significantly associated with frailty. This finding is supported by the study conducted in Ethiopia [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e], South India[\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e], Spain[\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e], and Bangladesh[\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. The possible explanation may be besides to aging process, physiological changes in older adults have been noted, including insulin resistance, hormonal imbalances, the activation of specific inflammatory processes, decreased fat-free muscle mass, and changes in body composition. These changes can eventually lead to the development of frailty syndrome[\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. This finding suggests that the occurrence of frailty is amplified with increasing age.\u003c/p\u003e\u003cp\u003eIn this study, females were more likely to be frail than males, which is consistent with studies conducted in the USA[\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e], Bangladesh[\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e], and Ethiopia[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. The possible justification may be due to females have an intrinsically higher risk of frailty because they have less lean body mass than males in the same age range; as well as having an extrinsically higher risk of frailty because of poor eating habits which make them more vulnerable to the effects of sarcopenia[\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e]. Pathophysiological, emotional, cognitive, and comorbidity variations have been cited as explanations for the gender disparities in frailty[\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e]. This result holds implications that females are more at risk of developing frailty than men.\u003c/p\u003e\u003cp\u003eOn the other hand, this finding contradicts the study conducted in Nigeria[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e], the possible explanatory might be due to differences in methodological variation especially the ages of participants.\u003c/p\u003e\u003cp\u003eThe disparities in frailty across the sexes may be attributed to variations in pathophysiological causes, mood, cognition, and comorbidity[\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eWeight is significantly associated with frailty. Those elderly patients within the weight range of 60\u0026ndash;70 kg were less likely to be frail than those\u0026thinsp;\u0026ge;\u0026thinsp;70kg. This study was consistent with the study conducted in the United States, the possible justification may be due to a weight trajectory going more toward the idea of sarcopenic obesity, rather than a rapid gain in weight, which may be a better indicator of health[\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e]. A key area emerging from the current finding is having weight dysregulation increases the risk of frailty occurrence.\u003c/p\u003e\u003cp\u003eNutritional status is significantly associated with frailty. This study was consistent with the study conducted in Indonesia[\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e], Vietnam[\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e], Korea[\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e], and Nigeria[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e], where malnourished patients were more likely to be frail than well-nourished patients. This consistency might be due to similarities in nutritional assessment tools (MNA-SF), study population groups, and similarity in age groups. The possible explanation may be the development of frailty is greatly influenced by malnutrition, which is linked to weight loss that causes weakness, weariness, a sluggish gait, and inactivity[\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e]. This finding suggested that malnutrition increases the risk of developing frailty.\u003c/p\u003e\u003cp\u003eIn this study those patients who had poor social support were more likely to be frail than those who had good social support, or an increase in social support was statistically significantly associated with a decrease in the odds of having frailty in older patients, this finding supported by the study conducted in Singapore[\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e], China[\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e], and Thailand[\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e], it demonstrates a bidirectional relationship between the degree of social support and frailty, nevertheless. The possible justification may be that frail patients gradually lose their ability to interact and establish good relationships with others [\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThis implication holds that having poor social support increases the risk of frailty development in elderly patients.\u003c/p\u003e\u003cp\u003eDepressions were significantly associated with frailty in elderly patients, those who were depressed had increased odds to become frail than non-depressed ones. This finding is supported by the study findings in Australia[\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e], and Ethiopia[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. This correlation, which could be explained by depression, may point to frailty brought on by a decrease in social ties, a slow gait, and a decrease in physical activity. It might be a sign of frailty brought on by an increase in sedentary behavior, a higher risk of falling, weight loss, and malnourishment, all of which can exacerbate depressive symptoms including sorrow, helplessness, and anhedonia[\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e]. A key area emerging from the current finding is having depression increases the risk of frailty occurrence.\u003c/p\u003e\u003cp\u003eHospitalization is significantly associated with frailty. This is in line with previous studies conducted in London[\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e], and Australia[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e], where being hospitalized is more likely to be frail than non-hospitalized once. This might be due to being hospitalized increases the vulnerability to different types of diseases and psychological stress and hospitalization induces a decrease in muscle strength and health-related quality of life in adults and the elderly [\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e]. The results hold implications for hospitalization raising the risk of frailty occurrence.\u003c/p\u003e\u003cp\u003eElderly patients those dependent on activities of daily living were more likely to be frail than non-dependent elderly patients. This is consistent with the study done in Nigeria and West Bengal [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e]. The possible explanatory might be due to the consequence of the aging process, and older persons who self-impose restrictions on their daily activities because they are afraid of falling tend to use less energy, which leads to the formation of intramuscular fat. Intramuscular adipose tissue contributes to inflammatory conditions involved in the frailty etiopathogenesis by releasing proinflammatory cytokines and by encouraging higher numbers of leukocytes and fibrinogen[\u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e]. A key area emerging from the current results is being dependent on daily living activities increases the development of frailty among elderly patients.\u003c/p\u003e\u003cp\u003eThis study tried to assess the factors associated with frailty among hospitalized elderly patients in public hospitals. It adds evidence-based knowledge related to frailty. However, due to the nature of the study design, this study could not establish a cause-effect relationship. Therefore, additional studies will be required to indicate the temporal cause-effect association. We only consider weight as an independent variable, it may be affected by other factors, so future research may consider additional variable such BMI to strength their findings.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe prevalence of frailty was higher in this study. Older age, being female, weight gain, depression, hospitalization over the past year, poor social support, malnutrition, and activity of daily living dependence are factors associated with frailty in Wolaita zone public hospitals.\u003c/p\u003e\u003cp\u003eTherefore, healthcare providers better give awareness and education about social support to frail elderly patients from family, friends, and communities give priority to early identification and management of depression, and provide education and support to elderly patients. Early detection and management of frail is important to improve dietary intake and treat any underlying medical issues that may be causing malnutrition better to be the main goals of treatment. The patient should be instructed about healthy weight through diet modification and lifestyle changes to minimize the risk of frailty development. It’s important to be involved in daily living activities to maintain muscle strength and the ability to delay frailty development.\u003c/p\u003e"},{"header":"Acronyms","content":"\u003cp\u003eAOR, Adjusted Odd Ratio; FRAIL-NH, Frail Nursing Home; ADL, The Activity of Daily Living; LMICs, Low and Middle-Income Countries; MNA-SF, Mini Nutritional Assessment Short Form; OSSS, Oslo Social Support Scale; PA, Physical Activity; PHQ-9, Patient Health Questionnaire; SPSS, Statistical Package for Social Science, ETB; Ethiopian birr.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eAcknowledgment\u003c/p\u003e\n\u003cp\u003eFirst, I would like to thank Wolaita Sodo University, the College of Medicine and Health Sciences, and the School of Nursing for providing me with the opportunity to pursue this master\u0026rsquo;s program. Moreover, I would like to thank the data collectors, supervisors, and all the study participants for their time and willingness to take part in the study.\u003c/p\u003e\n\u003cp\u003eThe study \u0026quot;Frailty and associated factors among elderly patients in Wolaita Zone\u0026nbsp;public hospitals, southern Ethiopia\u0026quot; is our original work, as we, the undersigned authors, officially declare. This study is not currently being considered for publication in any other journal, nor has it been published elsewhere.We confirm that all authors have contributed significantly to the conception, design, data collection, analysis, and interpretation of the study.\u003c/p\u003e\n\u003cp\u003eThis study is a cross-sectional observational study but not a clinical trial. Due to this, trial registration was not needed. Ethical approval for this study was obtained from Wolaita Sodo university Ethical Review Board\u0026nbsp;(Ref.No/CRCSD 4/1996/2011 and project number: CHSM/ERC/04/15), and written informed consent was obtained from all participants before data collection. The study was conducted in accordance with ethical principles and guidelines for research involving human subjects.\u0026nbsp;Informed consent was obtained from all the participants. Patients who agreed to participate signed a written consent form.\u003c/p\u003e\n\u003cp\u003eThis research project received no specific grant from any funding agency in the public, commercial, not for profit sectors.\u003c/p\u003e\n\u003cp\u003eThere are no conflicts of interest to disclose, and no funding was received for this study unless stated otherwise in the manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAndrieieva, O., et al., \u003cem\u003eEffects of physical activity on aging processes in elderly persons.\u003c/em\u003e 2019.\u003c/li\u003e\n\u003cli\u003eRohrmann, S., \u003cem\u003eEpidemiology of frailty in older people.\u003c/em\u003e Frailty and cardiovascular diseases: Research into an elderly population, 2020: p. 21-27.\u003c/li\u003e\n\u003cli\u003eTandon P, M.-L.A., Lai JC, Dasarathy S, Merli M. , \u003cem\u003eSarcopenia and frailty in decompensated cirrhosis..\u003c/em\u003e J Hepatol, 2021 Jul(75 Suppl 1(Suppl 1)): p:S147-S162. .\u003c/li\u003e\n\u003cli\u003eAmbagtsheer RC, B.J., Visvanathan R, Dent E, Yu S, Braunack-Mayer AJ. , \u003cem\u003eShould we screen for frailty in primary care settings? 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(55(5): ):p. 539-49.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Elderly patients, Frailty, Hospital, prevalence, Aged, Ethiopia","lastPublishedDoi":"10.21203/rs.3.rs-6943157/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6943157/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eIntroduction\u003c/p\u003e\u003cp\u003eFrailty is an aging-allied condition that suggests a vulnerable state and decline in physiological reserve that affects older people's independence and quality of life. It has also had a significant impact on elderly patients, by leading to impaired activities of daily living, disability, illness, hospitalization, premature death, and increased unnecessary healthcare costs. The previous studies conducted in Ethiopia as well as in Africa were done at the community and residential care facilities level but this study indicated extent of the problem among hospitalized frail patients effectively and also there are limited study on this area in Ethiopia as well as in Africa.\u003c/p\u003e\u003cp\u003e\u003cb\u003eObjective\u003c/b\u003e: This study aimed to assess frailty and associated factors among elderly patients in Wolaita Zone public hospitals, south Ethiopia, 2023\u003c/p\u003e\u003cp\u003eMethod\u003c/p\u003e\u003cp\u003eA hospital-based cross-sectional study design was conducted among 367 elderly patients from August 16 to September 21, 2023. A systematic sampling was used to select the participants. The data was collected through structured interviewer-administered questionnaires. The collected data was entered into Epidata version 4.6 and then exported into SPSS version 26 was used for data analysis. A binary logistic regression model was used. Variables with a p value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 in the multivariable logistic regression analysis were considered statistically significant\u003c/p\u003e\u003cp\u003eResults\u003c/p\u003e\u003cp\u003eThe overall prevalence of frailty was 47.4%. Old age (75\u0026ndash;79) (AOR\u0026thinsp;=\u0026thinsp;3.2, 95%CI\u0026thinsp;=\u0026thinsp;1.22\u0026ndash;8.5) and \u0026ge;\u0026thinsp;80 years(AOR\u0026thinsp;=\u0026thinsp;3.46, 95%CI (1.5\u0026ndash;7.7), being female (AOR\u0026thinsp;=\u0026thinsp;2.17, 95%CI\u0026thinsp;=\u0026thinsp;1.16-4), Weight(60-69kg) (AOR\u0026thinsp;=\u0026thinsp;0.29, 95% CI (0.1\u0026ndash;0.76), Malnutrition (AOR\u0026thinsp;=\u0026thinsp;3.7,95%CI\u0026thinsp;=\u0026thinsp;1.88\u0026ndash;7.3), Poor social support (AOR\u0026thinsp;=\u0026thinsp;3, 95%CI\u0026thinsp;=\u0026thinsp;1.6\u0026ndash;5.7), Depression (AOR\u0026thinsp;=\u0026thinsp;3.5, 95%CI\u0026thinsp;=\u0026thinsp;1.7\u0026ndash;7.11), Hospitalization (AOR\u0026thinsp;=\u0026thinsp;2.6, 95%CI\u0026thinsp;=\u0026thinsp;1.4\u0026ndash;4.8) and activity of daily living dependence(AOR\u0026thinsp;=\u0026thinsp;4.57, 95%CI\u0026thinsp;=\u0026thinsp;2.4\u0026ndash;8.7) were factors associated with frailty.\u003c/p\u003e\u003cp\u003eConclusion\u003c/p\u003e\u003cp\u003eThe prevalence of frailty among elderly patients was high. Older age, being female, weight, depression, hospitalization over the past year, poor social support, malnutrition, and activity of daily living dependence are factors associated with frailty in Wolaita zone public hospitals. Early assessment and prevention of malnutrition, hospitalization, and lifestyle modification of elderly patients may reduce the development of frailty.\u003c/p\u003e","manuscriptTitle":"Frailty and associated factors among elderly patients in Wolaita Zone public hospitals, south Ethiopia","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-08-11 09:55:50","doi":"10.21203/rs.3.rs-6943157/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"1db15213-95d3-44c0-acd9-4423bae3d873","owner":[],"postedDate":"August 11th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-02-20T08:56:28+00:00","versionOfRecord":[],"versionCreatedAt":"2025-08-11 09:55:50","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6943157","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6943157","identity":"rs-6943157","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}