Undernutrition and associated factors among older adults living in Bahir Dar City, Northwest Ethiopia.

Undernutrition and associated factors among older adults living in Bahir Dar City, Northwest 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 Undernutrition and associated factors among older adults living in Bahir Dar City, Northwest Ethiopia. Yibeltal Wolelaw Admas, Addisu Yihenew, Belayneh Addis Mekuria, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6084340/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: In any society, older adults are among the vulnerable and high-risk groups in health status. In this age group undernutrition is a major health concern, multifactorial, and has serious negative consequences including decreased resistance to infection, declined functional status, loss of independence, and affected quality of life but it is inadequately recognized and addressed. Despite their growing numbers and nutritional needs, older people in Ethiopia have been given little attention, and there are limited studies done about undernutrition in this population in Northern Ethiopia. Hence, this study aimed to assess the prevalence of undernutrition and its associated factors among older adults living in Bahir Dar City, Northwest Ethiopia, 2024. Methods: A community-based cross-sectional study design was conducted from September 5 to November 25, 2024. A multistage sampling technique was employed to recruit a total of 579 study participants aged 60 and above. The MNA-SF tool was used to assess undernutrition. The data was collected through the Kobo toolbox using face-to-face interviews, entered into Microsoft Excel, and then exported to SPSS version 25 for analysis. Variables having a p < 0.25 at bivariable logistic regression were included in the multivariable logistic regression. Finally, variables with a p-value < 0.05 at a 95% CI and adjusted odds ratio were statistically significant in multivariable logistic regression. Results: Among the 567 participants enrolled, the overall prevalence of undernutrition was 24.5% (95% CI: 21.0–28.3). Being female (AOR = 1.81, CI 1.19-2.76), age 80 years and older (AOR = 1.73, CI 1.03-2.91), being unable to read and write (AOR= 3.06, CI 1.54-6.08), being widowed (AOR = 1.63, CI 1.00-2.63) and smoking (AOR = 1.88, CI 1.19-2.99) were significantly associated with undernutrition. Conclusion and recommendation: This study found that the prevalence of undernutrition among older adults in the study area was high, making it an important public health issue. Being female, age 80 years and older, being widowed, being unable to read and write, and smoking were factors associated with undernutrition. Therefore, we suggest that education focus on very old and female older adults in improving dietary practice, incorporating behavioral supports to assist in the cessation of smoking to ensure healthy aging. Nutrition & Dietetics Undernutrition Older adults Prevalence Bahir Dar Ethiopia Figures Figure 1 Background The global population is increasing in both developed and developing nations, especially with an increase in the number of older people ( 1 ). According to the United Nations, the population of older adults (aged 60 and above) will double by 2050 and triple in 2100 ( 2 ), which accounts for11% of the world population ( 3 ). Although there is a serious shortage of recent data, this aging population in Ethiopia was 5.2 million in 2015, accounting for more than 5% of the total population, and is expected to rise to 6.1% in 2030 and 10.4% in 2050 ( 4 ). Consequently, as the world’s population ages and lifespan rises within the older population, there are numerous public health challenges that require continuous and specialized medical care particularly in developing nations where the healthcare system is underdeveloped and resources are scarce ( 5 ). These include: chronic non-communicable diseases like heart disease, stroke, and others, nutritional problems, especially undernutrition ( 6 ). Undernutrition is a common health issue in older individuals, characterized by a decline in appetite, inadequate food intake, dietary imbalances, deficiencies of specific nutrients, involuntary weight loss ( 7 ), and an inability to meet the requirements of the body to ensure growth, maintenance, and specific functions ( 8 ). It is described as protein-energy deficiency, particularly in vulnerable older adults ( 9 ) and adversely affecting physiological functions and clinical outcomes such as quality of life, infection rates and complications, hospitalization outcomes and mortality rate ( 10 – 12 ). In the aging group undernutrition is an important problem that has been seen in hospitals, residential care and in the community ( 13 ). It is a substantial problem globally among older individuals and is associated with serious negative consequences such as an altered body composition (impaired muscle function, decreased bone mass), delayed recovery from surgery, higher hospital readmission rates, is recognized as an important predictor of morbidity and mortality ( 14 ), leads to increases the risk of falls and fractures ( 13 , 15 ), decrease resistance to infection, slow wound healing ( 16 ). Additionally, without adequate care undernutrition may result in decline functional status ( 9 ) and activities of daily living ( 17 ), reduced cognitive function ( 18 , 19 ), and high healthcare costs ( 20 ), induces or worsens a state of frailty and dependence, and affects quality of life and life expectancy ( 11 , 21 ). According to the literature, undernutrition in older adults may be associated with several individual factors encompassing demographic variables such as age, gender ( 22 ), low monthly income, unable to read and write ( 23 ). In addition, smoking ( 24 ), history of hospitalization, the presence of chronic morbidities like hypertension, cerebrovascular disease, osteoarthritis ( 25 ), depression ( 26 ), and high number of prescription drugs (polypharmacy) ( 27 ) have all been linked to under nutrition. Despite these, the health and nutrition of the older adults are usually ignored; many of the intervention activities are directed towards neonates, children, adolescents, expectant and nursing mothers ( 28 ). More generally, undernutrition in Ethiopia has been given little attention concerning the older adult age group, despite the country's demographic transition toward an aging society, however; most of the studies conducted on undernutrition in Ethiopia focus on mothers and children. Thus, relevant research is needed for the early identification of older people who are at risk and to clearly state the magnitude of undernutrition among those individuals. This helps to develop strategies for preventing vulnerable older adults as early as possible that allows older people to live as long as possible, thereby improving health, which is paramount to ensuring quality of life. Data obtained from this study will also be useful for raising awareness of the nutritional needs of older people and will be a base for policy makers and planners. As far as the authors’ best search, there are limited studies which assess undernutrition and its determinant factors among these segments of the population in Northwest Ethiopia. Therefore, the aim of this study was to determine the prevalence and associated factors of undernutrition among community-dwelling older adults aged 60 years and older living in Bahir Dar city, Amhara regional state, Northwest Ethiopia. Methods and Materials Study design and setting A community-based cross-sectional study was conducted from September 1 to October 30, 2024. The study was conducted in Bahir Dar City, Amhara regional state, Northwest Ethiopia. Bahir Dar is the capital city of Amara, regional state located in Northwestern Ethiopia, 565 kilometers from Addis Ababa, the capital city of Ethiopia. The Ethiopian Central Statistics Agency estimated the city's population to be ~ 455,901 in 2022 ( 29 ). According to the data obtained from the Bahir Dar City administration Bureau of Labor and Social Affairs, the city is divided into six sub-cities and a total of 26 kebeles. The total number of older adults in the age group of 60 years and older who lived in the city was 11,930 (5351 males and 6579 females), and the profile of all older adults living in the city is given by their full addresses: name, age, sex, house number, and their respective kebeles. Source population and study population The source population included all older adults aged 60 years and above who were permanent residents in Bahir Dar City for more than six months. The study population consisted of older adults aged 60 years and older who were officially registered in Bahir Dar City in the selected kebeles during the study period. Inclusion criteria and exclusion criteria All older adults of both genders, aged 60 years and older, who registered in the Social and Labor Office and were available during the data collection period in the selected kebeles, were included in this study. On the other hand, participants who were unable to respond due to a critical illness during the data collection period were excluded from this study. Sample size determination The sample size was determined using a single population proportion formula with the following assumptions: a 21.9% anticipated proportion of undernutrition from a previous study done in Gondar town ( 30 ), a 95% confidence level (Zα/2 = 1.96), a 5% margin of error (d), a 10% none response rate and 2 design effect. n = \(\:\frac{{(Z{\alpha\:}/2)}^{2}\:\:\left(p\right)\:(1-P)}{{\text{d}}^{2}}\) n = 263 After considering the 2 design effect and adding a 10% non-response rate, the required final sample size was 579. Sampling technique and procedure A multistage sampling technique was employed to select the study participants. Bahir Dar city has six sub-cities and 26 kebeles. To obtain an adequate final sample size, a total of 13 kebeles (50 percent of the total kebeles) from each sub-city was selected by a simple random sampling technique. Primarily the total number of households was identified through reviewing records from the social and labor office. Then we considered a proportional allocation of the total sample size to allocate participants for each selected kebeles. All individuals were then framed using their particular code number of the house and their name. Then the study participants were selected by systematic random sampling technique after the Kth interval value was calculated by dividing the total older adults of the selected kebeles into actual sample sizes (k = N/n = 5471/579 ≈ 10 for each selected kebele). Where N = total number of older adults in the selected kebeles and n = the required final sample size. A lottery method was used to get the first sampled individual from 1–10 sampling intervals and another older adult was selected at every tenth sampling interval from the initial older adult. Whenever more than one eligible older adult was found in the same selected household, only one of them was chosen using the lottery method. If no participants in the selected household fulfilled the criteria, the next household was selected. Variables of the study Under-nutrition as dependent variable and gender, age, educational status, marital status, income, history of hospitalization, polypharmacy, comorbidities, depression, smoking, and alcohol consumption were explanatory variables. Operational definitions Nutritional status For this study, nutritional status was determined using the Mini Nutritional Assessment Short-Form (MNA-SF) tool, and participants with a score of > 7 were considered as having normal nutritional status (by merging normal nutrition and risk of undernutrition), while those with a score of ≤ 7 were considered as undernourished ( 31 ). Older adult A person aged 60 years and older referred to as older adult ( 32 ). Depression Was assessed using the Geriatric Depression Scale short form (GDS-15). The 15 items in the GDS-SF were extracted from the original 30-item GDS and consists of yes/no questions, yielding a total score ranging from 0 to 15. Participants with a score of ≥ 5 were considered as having depressive symptoms ( 33 ). Smoker For this study, those who have smoked more than 100 cigarettes in their lifetime and now smoke every day were considered current smokers, whereas those who have smoked more than 100 cigarettes in their lifetime but haven’t smoked in the last 28 days were considered previous smokers ( 34 ). Data collection tool and procedure The data was collected using a structured interview questionnaire adopted from different literature and nutritional status using the MNA-SF screening tool. The MNA-SF tool has a maximum of 14 points, consisting of five questionnaires and one anthropometric measuring tool on food intake, weight loss, mobility, psychological stress or acute disease, presence of dementia and body mass index (BMI) ( 22 ). If height and/or weight could not be assessed, the measurement of the calf circumference was used instead of the BMI as an alternate scoring. The questionnaire had three sections that included sociodemographic variables, nutritional status using the MNA-SF tool, health-related and psychological factors, and lifestyle factors. The questionnaire was first prepared in English and translated into the local language (Amharic) and then back-translated to English to ensure its consistency. An explanation of the purpose and potential benefits of the study was provided for the participants. Written informed consent was obtained from each participant, ensuring that they fully understood their involvement and voluntarily agreed to participate. Older adults who were willing to participate in the study were screened based on inclusion and exclusion criteria. Then, trained data collectors conducted face-to-face interviews with the participants to gather the necessary data for this study. Data quality control To ensure the quality of data, the questionnaires were first prepared in English then translated into the local language (Amharic), and then back to English to keep its consistency. Then, data collectors and supervisors were given a one-day training by the principal investigator before the actual data collection about how to use the Kobo toolbox, the purpose of the study, the details of the data collection tools (questionnaires), how to approach and interview the participants and importance of privacy and ensuring confidentiality of the respondents. Then, the questionnaires were pretested before the actual data collection period to check language clarity and appropriateness of the tool, to estimate time on 10% of the total sample size selected from kebeles that were not included in the study. Daily close supervision during the data collection was done and the collected data were reviewed and checked for completeness by supervisors and investigators to take timely corrective measures. Data processing and analysis Data was collected using the Kobo toolbox, entered into Microsoft Excel, and then exported to SPSS version 25 for analysis, summary presentation, and estimation. Descriptive statistics were done for all the variables in the study using statistical measurements: frequency tables, figures, percentages, means, and standard deviations. Multicollinearity test was performed to check the correlation between independent variables using collinearity statistics (variance inflation factors > 10 was considered suggestive of multicollinearity) and model fitness was checked by the Hosmer-Lemeshow goodness of fit test. All variables were taken into bivariable logistic regression analysis at a P-value < 0.25 and were employed to identify the potential predictors fitted into the multivariable logistic regression analysis to determine statistically significant factors of undernutrition at a P-value < 0.05. Then, the adjusted odds ratio with a 95% confidence interval was used to interpret the findings of the final model. Results Sociodemographic characteristics of the study participants Of the total 579, 567 older adults were participated in this study, yielding a response rate of 97.93%. Among the study participants, more than half, (54.5%, n = 309)), were females, and the age of respondents ranged between 60 and 94 years, with a mean age and standard deviation of 70.89 ± 8.28 years. In addition, the majority of them, (39.7%, n = 225) were married. Likewise, more than one-third of the participants, (36.5%, n = 207) had completed secondary school. Moreover, in terms of monthly income, most (40.6%, n = 230), had monthly income ≥ 3501 ETB. See Table 1 for more details. Table 1 Sociodemographic characteristics of the study participants of older adults who lived in Bahir Dar City, Northwest Ethiopia, 2024 (n = 567) Variables Frequency (n) Percent (%) Gender Male 258 45.5% Female 309 54.5% Age (in years ) 60–69 184 32.5% 70–79 226 39.8% 80 and older 157 27.7% Educational level Unable to read and write 96 16.9% Primary education 162 28.6% Secondary education 207 36.5% College and above 102 18% Monthly income (in ETB) ≤ 1500 168 29.6% 1501–3500 169 29.8% ≥ 3501 230 40.6% Marital status Married 225 39.7% Divorced 138 24.3% Widowed 204 36% Health-related, psychological and lifestyle-related factors of study participants Regarding the health-related characteristics of study participants, 111 (19.6%), had commodities, majority, 378 (66.7%) had no history of visiting any hospital in the past year. In terms of psychological and lifestyle-related factors, 163(28.7%) of the participants had depressed symptoms and 123 (21.7%) were smokers. See table 2 for more details. Prevalence of undernutrition Out of 567 older adults, the overall prevalence of undernutrition among older adults living in Bahir Dar City was found to be 139 (24.5%) (95% CI: 21.0 to 28.3). Among the participants 48 (16.8%) males and 91 (29.4%) females were suffered from undernutrition. Likewise, 56 (33.3%) participants who had monthly income ≤ 1500 ETB and 65(31.9%) widowed individuals were undernourished. Regarding health-related, psychological and lifestyle-related characteristics of study participants 42 (37.8%) had comorbidities, 51(27%) had history of hospitalization in the past one year, 23 (24.2%) participants took 5 or more prescribed drugs and 47(28.8%) with depression symptoms were had undernutrition. Moreover, among smokers and alcohol drinkers, 44(35.8%) and 5(5.4%) were undernourished respectively. Factors associated with undernutrition among older adults Primarily, the independent variables were entered into bivariable logistic regression analysis, and variables with a p-value of less than 0.25 were drawn into multivariable logistic regression analysis together. In bivariable logistic regression gender (being female), age, education (being unable to read and write and primary education), marital status of divorced and widowed, smoking, depression symptoms were positively associated with undernutrition, whereas, being female, age 80 years and older, unable to read and write, widowed and smoking were remained significantly associated with undernutrition on the multivariable logistic regression (p < 0.05). Participants aged 80 years and older had 1.73 times higher odds of developing undernutrition than those older adults who were 60–69 years older (AOR = 1.73, CI 1.03–2.91). The odds of undernutrition were more than 1.81 times higher among female participants compared to male participants (AOR = 1.81, CI 1.19–2.76). Regarding educational status, being unable to read and write increased the odds of undernutrition among the study participants as compared with those who had an educational status of college and above (AOR = 3.06,CI 1.54–6.08). This study also revealed that older adults who were widowed had 1.63 times more likely to be undernourished than those who were married (AOR = 1.63, CI 1.00-2.63). Furthermore, study participants who smoked were 1.88 times more likely to be undernourished compared to those who did not smoke (AOR = 1.88, CI 1.19–2.99). See Table 3 for more details. Table 3 Factors associated with undernutrition in older people living in Bahir Dar City, 2024 (n = 567). Undernutrition OR (95% CI) Variables Yes No COR (95% CI) AOR ( 95% CI) P-Value Gender Male 48 210 1 1 Female 91 218 1.82(1.22–2.71) * 1.81(1.19–2.76) ** 0.006 Age (in years) 60–69 39 145 1 1 70–79 45 181 0.92(0.57–1.49) 0.97(0.59–1.61) 0.93 80 and older 55 102 2.00 (1.23–3.24) * 1.73(1.03–2.91)** 0.037 Educational status Unable to read & Write 34 62 2.39 (1.25–4.59) * 3.06 (1.54–6.08) ** 0.001 Primary education 42 120 1.52 (0.83–2.81) 1.77 (0.93–3.36) 0.077 Secondary education 44 163 1.17 (0.64–2.14) 1.48 (0.78–2.78) 0.222 College and above 19 83 1 1 Marital status Married 41 184 1 1 Divorced 33 105 1.41 (0.84–2.36) 1.25 (0.73–2.16) 0.405 Widowed 65 139 2.09 (1.34–3.28) * 1.63 (1.00-2.63) ** 0.046 Smoking No 95 349 1 1 Yes 44 79 2.04 (1.32–3.15) * 1.88 (1.19–2.99) ** 0.007 Depression No 92 312 1 1 Yes 47 116 1.37 (0.91–2.07) 1.29 (0.83-2.00) 0.242 Note : COR: Crude Odds ratio; AOR: Adjusted Odd ratio; CI: Confidence interval; 1 = Reference category,*: statistically significant at P < 0.25 and **: statistically significant at P < 0.05. Discussion This study aimed to assess the magnitude and associated factors of undernutrition among older adults living in Bahir Dar City. In this study, the overall prevalence of undernutrition among older adults living in the study area was found to be 24.5% (95% CI: 21.0–28.3). This finding indicates that undernutrition is a significant a high public health burden and health problem among community dweller older adults living in Bahir Dar City. The result of the present study revealed that undernutrition among older adults was significantly associated with age 80 years and older, being female, widowed, and unable to read and write and smoking. The prevalence of undernutrition in current study was comparable with the findings from other studies conducted on Nutritional status and associated factors among the older people in Derham City, India (21.8%) ( 35 ), Nepal (24.8%) ( 36 ) and Gondar town (21.9%) ( 30 ). This might be due to the similar study designs and assessment tools used and the comparable mean ages of the study participants. For instance, similar to our study, the study conducted in Nepal and Gondar town were a community-based cross-sectional studies that employed a multistage sampling techniques. Additionally, the mean ages of the study participants in these studies were comparable to those in our study, which could contribute to the consistency in results. Furthermore, the study done in Derham City of India utilized a cross-sectional study design and similar assessment tool. However, the prevalence found in our study was lower compared to what was reported from studies conducted in Sri Lanka (30%) ( 37 ), Barcelona, Spain (34.5%) ( 27 ), Belgium (57.1%) ( 22 ), and Eldoret, Kenya (41%) ( 38 ). This difference could be due to variations in geographic settings, lifestyle characteristics, socioeconomic factors, and health status of the study populations. In addition, these differences could be created by the variation of inclusion or exclusion criteria of the study participants. Our study revealed that age 80 years and older are significantly associated with undernutrition. This was similar to a study done in Belgium ( 22 ) and Gondar town ( 30 ). The possible reason might be as age advances the risk of undernutrition increases. This might be due to the natural aging process, which is accompanied by physiological changes that can have a detrimental impact on nutritional status and lead to inadequate nutrition ( 39 , 40 ). This study revealed a significant difference between females and males. Females were significantly associated with more likely to be undernourished than males. This was supported by studies done in Kolkata, India ( 41 ) and Belgium ( 22 ). The possible implication could be that female older individuals are more vulnerable for undernutrition due to the fact that the older population is predominantly female and tends to live longer than males, and it may also be due to the fact that older females still remain the caretakers of their grandchildren, and they receive less than the care necessary for themselves ( 30 ). Another possible explanation could be that older female adults are often economically dependent and may face gender discrimination, along with reduced health-seeking behavior. These factors can negatively impact their health and nutritional status, leading to undernutrition. According to the findings of our study marital status was one of the factors affecting nutritional status of older people. Individuals who are widowed/widower were more likely to be undernourished compared to married individuals. This finding was supported by study done in Ghana ( 42 ). The reason could be that being alone as a result of the death of one of the mates decrease social relations, exposure to loneliness and economic deficiencies. These changes may cause inadequate nutrition ( 43 ). The loss of one’s mate may also be associated with loss of motivation to prepare and eat food, thereby increases the risk of undernourishment ( 44 ). Regarding educational status, participants who were unable to read and write were more likely to be undernourished compared to those with an educational status of college and above. This is similar to other reported studies in the aging population in Gondar town, Ethiopia ( 30 ). This because education is an essential factor in improving health status; educated individuals develop habits, skills, resources, and the ability to achieve a better life ( 45 ). Additionally, knowledge might encourage individuals to consume diversified foods, and educated people are more likely to have better feeding practices and healthy lifestyles. Furthermore, being a smoker was found to be an independent predictor of undernutrition as compared to their counterparts in this study. This finding is in-line with reports from Northern Ghana ( 42 ). The plausible explanation is related to the fact that smoking might influence appetite ( 46 ), reduce the desire to consume foods, and decrease the need to take vitamin-rich fruits and vegetables, as a result increasing the likelihood of being undernourished. Conclusions and recommendations This community-based study among older adults found the overall prevalence of undernutrition in the study area was high, making it an important public health burden. The findings of this study have shown that being female, age 80 years and older, being widowed, being unable to read and write, and smoking were independent factors significantly associated with undernutrition among older people. To improve the nutritional status of older people, education focusing on very old and female older people need to be initiated in improving dietary practice, including behavioral support interventions to assist in the cessation of smoking, especially targeting vulnerable groups identified in this study. Further studies are needed to create a comprehensive database for effective policymaking and design a national strategy on nutrition targeting the whole population of older adults to promote healthy aging. Additionally, further research including potential unaddressed factors contributing to undernutrition in older adults in the present study, is also recommended. Limitations and the strengths of the study First, since our study was conducted only in one district and included only urban older adults, the finding of the study is not generalizable to the entire rural population. Second, due to the nature of a cross-sectional study, it is difficult to know the exposure and outcome inferences. Despite these drawbacks, to the best of our knowledge, this is the first study of its kind to look at undernutrition in older individuals, conducted in Bahir Dar City, Ethiopia. In addition, because the study was conducted in a community to determine the prevalence and associated factors of undernutrition among older adults, it may address the huge gap of evidence about undernutrition and reflects the actual nature of the issue in the study area. Abbreviations AOR Adjusted Odds Ratio BMI Body Mass Index CI Confidence Interval COR Crude Odds Ratio ETB Ethiopian Birr GDS Geriatric Depression Scale GDS-SF Geriatric Depression Scale Short Form MNA-SF Mini Nutritional Assessment Short Form OR Odds Ratio SPSS Statistical Package for Social Science fiction Declarations Ethical approval and informed consent to participate This study was conducted following the Declaration of Helsinki version-2013 that embraces Ethical Principles for Medical Research involving Human Subjects. Ethical approval was obtained from the institutional ethical review board of the School of Medicine, College of Medicine and Health Sciences, Bahir Dar University, (Ref. 1545/Med/2024). Informed consent was obtained from each study participants after the purpose of the study was explained. Participants were informed that their participation was voluntary and the information obtained from them would be kept confidential, with no individual identifiers linked to their personal information. Consent for publication Not applicable Data availability statement All essential datasets generated and/or analyzed during the current study are not publicly available due to privacy issues but are available from the primary author (Yibeltal Wolelaw Admas). Competing interests All authors declared they have no conflict of interest Funding No funding Authors’ contributions Generally, all authors contributed to several revisions and approved the final version of the manuscript. Yibeltal Wolelaw: Has contributed to develop the research project, coordinate, supervised data collection process and finalized the manuscript. Addisu Yihenew: Has taken part to supervise the data collection and review process. Belayneh Addis: Has participated in data clearing and entry activities. Gebremariam Bekele: He has participated in in the data entry and analysis process. Gebremeskel Birhanie: He has contributed to the methodology designing and sampling procedures. Yesahmbel Ejigu: Has also contributed to initiate the idea of the research project and wrote the introduction part of the manuscript. Awoke Kebede: Contributed in the write up process of the manuscript Berihun Assefa: Has contributed to the overall write up, review and submission process of the manuscript. Acknowledgment We would like to thank Bahir Dar University for approval of ethical the clearance to carry out this research. We would also like to acknowledge the Department of Labor and Social Affairs of Bahir Dar City for the assistance in providing essential information. Our deepest gratitude goes to the study participants for their involvement in this study and the data collectors and supervisors for their patience during the data collection process. Authors' information 1. Department of Physiotherapy, School of medicine, College of Medicine and Health Science, Bahir Dar University: Yibeltal Wolelaw, Addisu Yihenew, Belayneh Addis Mekuria, Gebremariam Bekele, Gebremeskel Birhanie Gebru, Yeshambel Ejigu and Berihun Assefa Demissie 2. Department of Pediatrics and Child Health Nursing, school of Health Sciences, College of Medicine and Health Science, Bahir Dar University: Awoke Kebede References He W, Goodkind D, Kowal P (2016) An aging world: 2015. US Department of Commerce. Economics and Statistics Administration Sert AN (2019) Senior Tourism in the aging world. Theory and practice in social sciences. :488 – 98 Charles T, Tesfayi G, Hassan A (2009) Population dynamics, food/nutrition security and health in ethiopia. Delicate balance of vulnerability & resilience IUSSP marrakech Juergens F (2019) HelpAge International. Coverage of older people in Ethiopia’s social protection system Rynning E (2008) The ageing populations of Europe—implications for health systems and patients' rights. Eur J health law 15(3):297–306 Organization WH (2015) World report on ageing and health MURPHY K (2011) Malnutrition in the community and hospital setting. The patient association. August Martins VJ, Toledo Florêncio TM, Grillo LP, Franco MCP, Martins PA, Clemente APG et al (2011) Long-lasting effects of undernutrition. Int J Environ Res Public Health 8(6):1817–1846 Cereda E, Valzolgher L, Pedrolli C (2008) Mini nutritional assessment is a good predictor of functional status in institutionalised elderly at risk of malnutrition. Clin Nutr 27(5):700–705 International HA (2013) Vulnerability of Older People in Ethiopia: The Case of Oromia, Amhara and SNNP Regional States. Help Age International in Ethiopia Addis Ababa Rasheed S, Woods RT (2013) Malnutrition and quality of life in older people: a systematic review and meta-analysis. Ageing Res Rev 12(2):561–566 Sserwanja Q, Mukunya D, Habumugisha T, Mutisya LM, Tuke R, Olal E (2020) Factors associated with undernutrition among 20 to 49 year old women in Uganda: a secondary analysis of the Uganda demographic health survey 2016. BMC Public Health 20:1–10 Hickson M (2006) Malnutrition and ageing: This article is part of a series on ageing edited by Professor Chris Bulpitt. Postgrad Med J 82(963):2–8 Amarya S, Singh K, Sabharwal M (2015) Changes during aging and their association with malnutrition. J Clin Gerontol Geriatr 6(3):78–84 Raynaud-Simon A, Revel-Delhom C, Hébuterne X (2011) Clinical practice guidelines from the French Health High Authority: nutritional support strategy in protein-energy malnutrition in the elderly. Clin Nutr 30(3):312–319 Ross AC, Caballero B, Cousins RJ, Tucker KL (2020) Modern nutrition in health and disease. Jones & Bartlett Learning Ritchie CS, Locher JL, Roth DL, McVie T, Sawyer P, Allman R (2008) Unintentional weight loss predicts decline in activities of daily living function and life-space mobility over 4 years among community-dwelling older adults. Journals Gerontol Ser A: Biol Sci Med Sci 63(1):67–75 Kvamme J-M, Grønli O, Florholmen J, Jacobsen BK (2011) Risk of malnutrition is associated with mental health symptoms in community living elderly men and women: The Tromsø Study. BMC Psychiatry 11:1–8 Cabrera MAS, Mesas AE, Garcia ARL, de Andrade SM (2007) Malnutrition and depression among community-dwelling elderly people. J Am Med Dir Assoc 8(9):582–584 Freijer K, Tan SS, Koopmanschap MA, Meijers JM, Halfens RJ, Nuijten MJ (2013) The economic costs of disease related malnutrition. Clin Nutr 32(1):136–141 Hiesmayr M, Schindler K, Pernicka E, Schuh C, Schoeniger-Hekele A, Bauer P et al (2009) Decreased food intake is a risk factor for mortality in hospitalised patients: the NutritionDay survey 2006. Clin Nutr 28(5):484–491 Arvanitakis M, Vandewoude M, Perkisas S, Van Gossum A (2013) Undernutrition in community dwelling elderly. e-SPEN J 8(5):e213–e5 Tesfaye A, Sisay G, Kabthymer RH, Tesfaye T (2022) Under-nutrition and associated factors among pregnant women in public health care hospitals of Gedeo Zone, southern Ethiopia: A cross-sectional study. Heliyon. ;8(5) Jésus P, Guerchet M, Pilleron S, Fayemendy P, Mouanga AM, Mbelesso P et al (2017) Undernutrition and obesity among elderly people living in two cities of developing countries: prevalence and associated factors in the EDAC study. Clin Nutr ESPEN 21:40–50 Adebusoye LA, Ajayi I, Dairo M, Ogunniyi A (2011) Factors associated with undernutrition and overweight in elderly patients presenting at a primary care clinic in Nigeria. South Afr Family Pract 53(4):355–360 Chalermsri C, Assantachai P, Pramyothin P, Pengsorn N, Muangpaisan W (2018) Prevalence of and factors associated with undernutrition in a geriatric outpatient setting: Results from a multidimensional nutritional assessment. Siriraj Med J 70(5):413–418 Farre TB, Formiga F, Ferrer A, Plana-Ripoll O, Almeda J, Pujol R (2014) Risk of being undernourished in a cohort of community‐dwelling 85‐year‐olds: The O ctabaix study. Geriatr Gerontol Int 14(3):702–709 Agarwalla R, Saikia AM, Baruah R (2015) Assessment of the nutritional status of the elderly and its correlates. J Family Community Med 22(1):39–43 Adigeh DT, Abebe BG (2023) The practice of peri-urban land acquisition by expropriation for housing purposes and the implications: the case of Bahir Dar, Ethiopia. Urban Sci 7(2):41 Tessfamichael D, Gete AA, Wassie MM (2014) High prevalence of undernutrition among elderly people in Northwest Ethiopia: a cross sectional study. Read Write 244:322 Söderhamn U, Dale B, Sundsli K, Söderhamn O (2012) Nutritional screening of older home-dwelling Norwegians: a comparison between two instruments. Clinical interventions in aging. :383 – 91 Scherbov S, Sanderson W (2019) New measures of population ageing. United Nations report Greenberg SA (2007) How to try this: the geriatric depression scale: short form. AJN Am J Nurs 107(10):60–69 Asresahegn H, Tadesse F, Beyene E (2017) Prevalence and associated factors of hypertension among adults in Ethiopia: a community based cross-sectional study. BMC Res Notes 10:1–8 Semwal J, Vyas S, Juyal R, Sati HC (2014) Nutritional status and associated comorbidities among the elderly in Doiwala block, Dehradun. Indian J Community Health 26(Supp 2):197–203 Tamang MK, Yadav UN, Hosseinzadeh H, Kafle B, Paudel G, Khatiwada S et al (2019) Nutritional assessment and factors associated with malnutrition among the elderly population of Nepal: a cross-sectional study. BMC Res Notes 12:1–5 Rathnayake KM, Wimalathunga M, Weech M, Jackson KG, Lovegrove JA (2015) High prevalence of undernutrition and low dietary diversity in institutionalised elderly living in Sri Lanka. Public Health Nutr 18(15):2874–2880 Bore C (2019) Assessment Of Determinants Of Under-Nutrition And Food Security Among The Elderly In Moiben Sub-County. University of Eldoret, Uasin Gishu County Chen ST, Ngoh HJ, Harith S (2012) Prevalence of malnutrition among institutionalized elderly people in Northern Peninsular Malaysia: gender, ethnicity and age-specific. Sains Malaysiana 41(1):141–148 Forster S, Gariballa S (2005) Age as a determinant of nutritional status: a cross sectional study. Nutr J 4:1–5 Majumder M, Saha I, Chaudhuri D (2014) Assessment of nutritional risk in community-dwelling older adults (65 to 75 years) in Kolkata, India. J Nutr Gerontol Geriatr 33(2):126–134 Aganiba BA, Owusu W, Steiner-Asiedu M, Dittoh S (2015) Association between lifestyle and health variables with nutritional status of the elderly in the northern region of Ghana. Afr J Food Agric Nutr Dev 15(4):10198–10216 Santos ALMd A, TMdSPFd, Borges NPGFB (2015) Undernutrition and associated factors in a Portuguese older adult community. Revista de Nutrição 28(3):231–240 Locher JL, Ritchie CS, Roth DL, Baker PS, Bodner EV, Allman RM (2005) Social isolation, support, and capital and nutritional risk in an older sample: ethnic and gender differences. Soc Sci Med 60(4):747–761 Ross CE, Mirowsky J (2010) Why education is the key to socioeconomic differentials in health. Handb Med Sociol 6:33–51 Lin W-Q, Wang H, Yuan L-X, Li B, Jing M-J, Luo J-L et al (2017) The unhealthy lifestyle factors associated with an increased risk of poor nutrition among the elderly population in China. J Nutr health aging 21(9):943–953 Additional Declarations The authors declare no competing interests. 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-6084340","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":419391607,"identity":"abec6986-afd7-4d72-876a-ae9c190901ff","order_by":0,"name":"Yibeltal Wolelaw Admas","email":"","orcid":"","institution":"Bahir Dar University","correspondingAuthor":false,"prefix":"","firstName":"Yibeltal","middleName":"Wolelaw","lastName":"Admas","suffix":""},{"id":419391608,"identity":"27063456-5e6a-4847-9d4a-91d31c64e12b","order_by":1,"name":"Addisu Yihenew","email":"","orcid":"","institution":"Bahir Dar University","correspondingAuthor":false,"prefix":"","firstName":"Addisu","middleName":"","lastName":"Yihenew","suffix":""},{"id":419391609,"identity":"420d0f26-cc41-467a-8322-27747410942b","order_by":2,"name":"Belayneh Addis Mekuria","email":"","orcid":"","institution":"Bahir Dar university","correspondingAuthor":false,"prefix":"","firstName":"Belayneh","middleName":"Addis","lastName":"Mekuria","suffix":""},{"id":419391610,"identity":"bcf946d8-e1ab-4371-a1a4-1a3a7a29a91b","order_by":3,"name":"Gebremariam Bekele","email":"","orcid":"","institution":"Bahir Dar university","correspondingAuthor":false,"prefix":"","firstName":"Gebremariam","middleName":"","lastName":"Bekele","suffix":""},{"id":419391611,"identity":"21dd87a1-3a4f-4038-ae81-d7d1c4b57edc","order_by":4,"name":"Gebremeskel Birhanie Gebru","email":"","orcid":"","institution":"Bahir Dar University","correspondingAuthor":false,"prefix":"","firstName":"Gebremeskel","middleName":"Birhanie","lastName":"Gebru","suffix":""},{"id":419391899,"identity":"3b024cb4-131e-4a64-9583-e281ad46d904","order_by":5,"name":"Yeshambel Ejigu","email":"","orcid":"","institution":"Bahir Dar University","correspondingAuthor":false,"prefix":"","firstName":"Yeshambel","middleName":"","lastName":"Ejigu","suffix":""},{"id":419391900,"identity":"2c8e4600-28ed-4ac3-a1e2-9847ffdb7ad8","order_by":6,"name":"Awoke Kebede","email":"","orcid":"","institution":"Bahir Dar University","correspondingAuthor":false,"prefix":"","firstName":"Awoke","middleName":"","lastName":"Kebede","suffix":""},{"id":419391901,"identity":"d45bcb65-e846-4adb-a002-1fee7e5d79a9","order_by":7,"name":"Berihun Assefa Demissie","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA70lEQVRIiWNgGAWjYBACAyA+DGEyPmD4AKTY2InXwmzAOAOkhZkILcwwLcw8DAguTmDO3vvwcGHbHXn59mbGzza/tsnzMTMwfviYg1uLZc9xg8Mz254ZbjhzmFk6t++2YRszA7PkzG14HHYjjeEwb9thxg0S+Qekc3tuMwK1sDHz4tNy/xlYi/38+Y+Zf1v23LYnrOUGG1hLYsMNZjZphh+3EwlqsewBOozn3OHkDWeS2Sx7G24ntzEzNuP1izn7MebPPGWHbee3H2a+8ePPbSCj+eCHj3i0oALGNjDZQKx6EPhDiuJRMApGwSgYKQAAidBSFYJbbCkAAAAASUVORK5CYII=","orcid":"https://orcid.org/0000-0003-1490-8012","institution":"Bahir Dar University","correspondingAuthor":true,"prefix":"","firstName":"Berihun","middleName":"Assefa","lastName":"Demissie","suffix":""}],"badges":[],"createdAt":"2025-02-22 08:49:52","currentVersionCode":1,"declarations":{"humanSubjects":true,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":true,"humanSubjectConsent":true,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-6084340/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6084340/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":77305097,"identity":"650fdcbf-d110-4d2b-b4ed-374ab61f27f7","added_by":"auto","created_at":"2025-02-27 08:57:07","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":63588,"visible":true,"origin":"","legend":"\u003cp\u003eHealth-related, psychological and lifestyle-related factors of study participants living in Bahir Dar City, Northwest Ethiopia, 2024 (n = 567)\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-6084340/v1/4948245d1fdf01a0d3705645.png"},{"id":77307381,"identity":"13d6a3fe-a619-4431-82cd-6b31c1bf41da","added_by":"auto","created_at":"2025-02-27 09:21:08","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1210895,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6084340/v1/374685f8-fc72-4877-902e-66774d0b5e58.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003e\u003cstrong\u003eUndernutrition and associated factors among older adults living in Bahir Dar City, Northwest Ethiopia.\u003c/strong\u003e\u003c/p\u003e","fulltext":[{"header":"Background","content":"\u003cp\u003eThe global population is increasing in both developed and developing nations, especially with an increase in the number of older people (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). According to the United Nations, the population of older adults (aged 60 and above) will double by 2050 and triple in 2100 (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e), which accounts for11% of the world population (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). Although there is a serious shortage of recent data, this aging population in Ethiopia was 5.2\u0026nbsp;million in 2015, accounting for more than 5% of the total population, and is expected to rise to 6.1% in 2030 and 10.4% in 2050 (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). Consequently, as the world\u0026rsquo;s population ages and lifespan rises within the older population, there are numerous public health challenges that require continuous and specialized medical care particularly in developing nations where the healthcare system is underdeveloped and resources are scarce (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). These include: chronic non-communicable diseases like heart disease, stroke, and others, nutritional problems, especially undernutrition (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eUndernutrition is a common health issue in older individuals, characterized by a decline in appetite, inadequate food intake, dietary imbalances, deficiencies of specific nutrients, involuntary weight loss (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e), and an inability to meet the requirements of the body to ensure growth, maintenance, and specific functions (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). It is described as protein-energy deficiency, particularly in vulnerable older adults (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e) and adversely affecting physiological functions and clinical outcomes such as quality of life, infection rates and complications, hospitalization outcomes and mortality rate (\u003cspan additionalcitationids=\"CR11\" citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn the aging group undernutrition is an important problem that has been seen in hospitals, residential care and in the community (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). It is a substantial problem globally among older individuals and is associated with serious negative consequences such as an altered body composition (impaired muscle function, decreased bone mass), delayed recovery from surgery, higher hospital readmission rates, is recognized as an important predictor of morbidity and mortality (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e), leads to increases the risk of falls and fractures (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e), decrease resistance to infection, slow wound healing (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). Additionally, without adequate care undernutrition may result in decline functional status (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e) and activities of daily living (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e), reduced cognitive function (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e), and high healthcare costs (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e), induces or worsens a state of frailty and dependence, and affects quality of life and life expectancy (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAccording to the literature, undernutrition in older adults may be associated with several individual factors encompassing demographic variables such as age, gender (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e), low monthly income, unable to read and write (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e). In addition, smoking (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e), history of hospitalization, the presence of chronic morbidities like hypertension, cerebrovascular disease, osteoarthritis (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e), depression (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e), and high number of prescription drugs (polypharmacy) (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e) have all been linked to under nutrition. Despite these, the health and nutrition of the older adults are usually ignored; many of the intervention activities are directed towards neonates, children, adolescents, expectant and nursing mothers (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eMore generally, undernutrition in Ethiopia has been given little attention concerning the older adult age group, despite the country's demographic transition toward an aging society, however; most of the studies conducted on undernutrition in Ethiopia focus on mothers and children. Thus, relevant research is needed for the early identification of older people who are at risk and to clearly state the magnitude of undernutrition among those individuals. This helps to develop strategies for preventing vulnerable older adults as early as possible that allows older people to live as long as possible, thereby improving health, which is paramount to ensuring quality of life. Data obtained from this study will also be useful for raising awareness of the nutritional needs of older people and will be a base for policy makers and planners.\u003c/p\u003e \u003cp\u003eAs far as the authors\u0026rsquo; best search, there are limited studies which assess undernutrition and its determinant factors among these segments of the population in Northwest Ethiopia. Therefore, the aim of this study was to determine the prevalence and associated factors of undernutrition among community-dwelling older adults aged 60 years and older living in Bahir Dar city, Amhara regional state, Northwest Ethiopia.\u003c/p\u003e"},{"header":"Methods and Materials","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy design and setting\u003c/h2\u003e \u003cp\u003eA community-based cross-sectional study was conducted from September 1 to October 30, 2024. The study was conducted in Bahir Dar City, Amhara regional state, Northwest Ethiopia. Bahir Dar is the capital city of Amara, regional state located in Northwestern Ethiopia, 565 kilometers from Addis Ababa, the capital city of Ethiopia. The Ethiopian Central Statistics Agency estimated the city's population to be ~\u0026thinsp;455,901 in 2022 (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e). According to the data obtained from the Bahir Dar City administration Bureau of Labor and Social Affairs, the city is divided into six sub-cities and a total of 26 kebeles. The total number of older adults in the age group of 60 years and older who lived in the city was 11,930 (5351 males and 6579 females), and the profile of all older adults living in the city is given by their full addresses: name, age, sex, house number, and their respective kebeles.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eSource population and study population\u003c/h3\u003e\n\u003cp\u003eThe source population included all older adults aged 60 years and above who were permanent residents in Bahir Dar City for more than six months. The study population consisted of older adults aged 60 years and older who were officially registered in Bahir Dar City in the selected kebeles during the study period.\u003c/p\u003e\n\u003ch3\u003eInclusion criteria and exclusion criteria\u003c/h3\u003e\n\u003cp\u003eAll older adults of both genders, aged 60 years and older, who registered in the Social and Labor Office and were available during the data collection period in the selected kebeles, were included in this study. On the other hand, participants who were unable to respond due to a critical illness during the data collection period were excluded from this study.\u003c/p\u003e\n\u003ch3\u003eSample size determination\u003c/h3\u003e\n\u003cp\u003eThe sample size was determined using a single population proportion formula with the following assumptions: a 21.9% anticipated proportion of undernutrition from a previous study done in Gondar town (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e), a 95% confidence level (Zα/2\u0026thinsp;=\u0026thinsp;1.96), a 5% margin of error (d), a 10% none response rate and 2 design effect.\u003c/p\u003e \u003cp\u003en = \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\frac{{(Z{\\alpha\\:}/2)}^{2}\\:\\:\\left(p\\right)\\:(1-P)}{{\\text{d}}^{2}}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;263\u003c/p\u003e \u003cp\u003eAfter considering the 2 design effect and adding a 10% non-response rate, the required final sample size was 579.\u003c/p\u003e\n\u003ch3\u003eSampling technique and procedure\u003c/h3\u003e\n\u003cp\u003eA multistage sampling technique was employed to select the study participants. Bahir Dar city has six sub-cities and 26 kebeles. To obtain an adequate final sample size, a total of 13 kebeles (50 percent of the total kebeles) from each sub-city was selected by a simple random sampling technique. Primarily the total number of households was identified through reviewing records from the social and labor office. Then we considered a proportional allocation of the total sample size to allocate participants for each selected kebeles. All individuals were then framed using their particular code number of the house and their name. Then the study participants were selected by systematic random sampling technique after the Kth interval value was calculated by dividing the total older adults of the selected kebeles into actual sample sizes (k\u0026thinsp;=\u0026thinsp;N/n\u0026thinsp;=\u0026thinsp;5471/579\u0026thinsp;\u0026asymp;\u0026thinsp;10 for each selected kebele). Where N\u0026thinsp;=\u0026thinsp;total number of older adults in the selected kebeles and n\u0026thinsp;=\u0026thinsp;the required final sample size. A lottery method was used to get the first sampled individual from 1\u0026ndash;10 sampling intervals and another older adult was selected at every tenth sampling interval from the initial older adult. Whenever more than one eligible older adult was found in the same selected household, only one of them was chosen using the lottery method. If no participants in the selected household fulfilled the criteria, the next household was selected.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eVariables of the study\u003c/h2\u003e \u003cp\u003eUnder-nutrition as dependent variable and gender, age, educational status, marital status, income, history of hospitalization, polypharmacy, comorbidities, depression, smoking, and alcohol consumption were explanatory variables.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eOperational definitions\u003c/h3\u003e\n\u003cp\u003e \u003cstrong\u003eNutritional status\u003c/strong\u003e \u003cp\u003eFor this study, nutritional status was determined using the Mini Nutritional Assessment Short-Form (MNA-SF) tool, and participants with a score of \u0026gt;\u0026thinsp;7 were considered as having normal nutritional status (by merging normal nutrition and risk of undernutrition), while those with a score of \u0026le;\u0026thinsp;7 were considered as undernourished (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e).\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eOlder adult\u003c/strong\u003e \u003cp\u003eA person aged 60 years and older referred to as older adult (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e).\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eDepression\u003c/strong\u003e \u003cp\u003eWas assessed using the Geriatric Depression Scale short form (GDS-15). The 15 items in the GDS-SF were extracted from the original 30-item GDS and consists of yes/no questions, yielding a total score ranging from 0 to 15. Participants with a score of \u0026ge;\u0026thinsp;5 were considered as having depressive symptoms (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e).\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eSmoker\u003c/strong\u003e \u003cp\u003eFor this study, those who have smoked more than 100 cigarettes in their lifetime and now smoke every day were considered current smokers, whereas those who have smoked more than 100 cigarettes in their lifetime but haven\u0026rsquo;t smoked in the last 28 days were considered previous smokers (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e).\u003c/p\u003e \u003c/p\u003e\n\u003ch3\u003eData collection tool and procedure\u003c/h3\u003e\n\u003cp\u003eThe data was collected using a structured interview questionnaire adopted from different literature and nutritional status using the MNA-SF screening tool. The MNA-SF tool has a maximum of 14 points, consisting of five questionnaires and one anthropometric measuring tool on food intake, weight loss, mobility, psychological stress or acute disease, presence of dementia and body mass index (BMI) (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e). If height and/or weight could not be assessed, the measurement of the calf circumference was used instead of the BMI as an alternate scoring. The questionnaire had three sections that included sociodemographic variables, nutritional status using the MNA-SF tool, health-related and psychological factors, and lifestyle factors. The questionnaire was first prepared in English and translated into the local language (Amharic) and then back-translated to English to ensure its consistency. An explanation of the purpose and potential benefits of the study was provided for the participants. Written informed consent was obtained from each participant, ensuring that they fully understood their involvement and voluntarily agreed to participate. Older adults who were willing to participate in the study were screened based on inclusion and exclusion criteria. Then, trained data collectors conducted face-to-face interviews with the participants to gather the necessary data for this study.\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eData quality control\u003c/h2\u003e \u003cp\u003eTo ensure the quality of data, the questionnaires were first prepared in English then translated into the local language (Amharic), and then back to English to keep its consistency. Then, data collectors and supervisors were given a one-day training by the principal investigator before the actual data collection about how to use the Kobo toolbox, the purpose of the study, the details of the data collection tools (questionnaires), how to approach and interview the participants and importance of privacy and ensuring confidentiality of the respondents. Then, the questionnaires were pretested before the actual data collection period to check language clarity and appropriateness of the tool, to estimate time on 10% of the total sample size selected from kebeles that were not included in the study. Daily close supervision during the data collection was done and the collected data were reviewed and checked for completeness by supervisors and investigators to take timely corrective measures.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eData processing and analysis\u003c/h2\u003e \u003cp\u003eData was collected using the Kobo toolbox, entered into Microsoft Excel, and then exported to SPSS version 25 for analysis, summary presentation, and estimation. Descriptive statistics were done for all the variables in the study using statistical measurements: frequency tables, figures, percentages, means, and standard deviations. Multicollinearity test was performed to check the correlation between independent variables using collinearity statistics (variance inflation factors\u0026thinsp;\u0026gt;\u0026thinsp;10 was considered suggestive of multicollinearity) and model fitness was checked by the Hosmer-Lemeshow goodness of fit test. All variables were taken into bivariable logistic regression analysis at a P-value\u0026thinsp;\u0026lt;\u0026thinsp;0.25 and were employed to identify the potential predictors fitted into the multivariable logistic regression analysis to determine statistically significant factors of undernutrition at a P-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05. Then, the adjusted odds ratio with a 95% confidence interval was used to interpret the findings of the final model.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\n \u003ch2\u003eSociodemographic characteristics of the study participants\u003c/h2\u003e\n \u003cp\u003eOf the total 579, 567 older adults were participated in this study, yielding a response rate of 97.93%. Among the study participants, more than half, (54.5%, n\u0026thinsp;=\u0026thinsp;309)), were females, and the age of respondents ranged between 60 and 94 years, with a mean age and standard deviation of 70.89\u0026thinsp;\u0026plusmn;\u0026thinsp;8.28 years. In addition, the majority of them, (39.7%, n\u0026thinsp;=\u0026thinsp;225) were married. Likewise, more than one-third of the participants, (36.5%, n\u0026thinsp;=\u0026thinsp;207) had completed secondary school. Moreover, in terms of monthly income, most (40.6%, n\u0026thinsp;=\u0026thinsp;230), had monthly income\u0026thinsp;\u0026ge;\u0026thinsp;3501 ETB. See Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e for more details.\u0026nbsp;\u003c/p\u003e\u0026nbsp;\u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eSociodemographic characteristics of the study participants of older adults who lived in Bahir Dar City, Northwest Ethiopia, 2024 (n\u0026thinsp;=\u0026thinsp;567)\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth style=\"width: 48.0896%;\" align=\"left\"\u003e\n \u003cp\u003eVariables\u003c/p\u003e\n \u003c/th\u003e\n \u003cth style=\"width: 28.96%;\" align=\"left\"\u003e\n \u003cp\u003eFrequency (n)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth style=\"width: 22.8492%;\" align=\"left\"\u003e\n \u003cp\u003ePercent (%)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth style=\"width: 48.0896%;\" align=\"left\"\u003e\n \u003cp\u003eGender\u003c/p\u003e\n \u003c/th\u003e\n \u003cth style=\"width: 28.96%;\" align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth style=\"width: 22.8492%;\" align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 48.0896%;\" align=\"left\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28.96%;\" align=\"left\"\u003e\n \u003cp\u003e258\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22.8492%;\" align=\"left\"\u003e\n \u003cp\u003e45.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 48.0896%;\" align=\"left\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28.96%;\" align=\"left\"\u003e\n \u003cp\u003e309\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22.8492%;\" align=\"left\"\u003e\n \u003cp\u003e54.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 48.0896%;\" align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge (in years\u003c/strong\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28.96%;\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd style=\"width: 22.8492%;\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 48.0896%;\" align=\"left\"\u003e\n \u003cp\u003e60\u0026ndash;69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28.96%;\" align=\"left\"\u003e\n \u003cp\u003e184\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22.8492%;\" align=\"left\"\u003e\n \u003cp\u003e32.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 48.0896%;\" align=\"left\"\u003e\n \u003cp\u003e70\u0026ndash;79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28.96%;\" align=\"left\"\u003e\n \u003cp\u003e226\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22.8492%;\" align=\"left\"\u003e\n \u003cp\u003e39.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 48.0896%;\" align=\"left\"\u003e\n \u003cp\u003e80 and older\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28.96%;\" align=\"left\"\u003e\n \u003cp\u003e157\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22.8492%;\" align=\"left\"\u003e\n \u003cp\u003e27.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 48.0896%;\" align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eEducational level\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28.96%;\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd style=\"width: 22.8492%;\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 48.0896%;\" align=\"left\"\u003e\n \u003cp\u003eUnable to read and write\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28.96%;\" align=\"left\"\u003e\n \u003cp\u003e96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22.8492%;\" align=\"left\"\u003e\n \u003cp\u003e16.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 48.0896%;\" align=\"left\"\u003e\n \u003cp\u003ePrimary education\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28.96%;\" align=\"left\"\u003e\n \u003cp\u003e162\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22.8492%;\" align=\"left\"\u003e\n \u003cp\u003e28.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 48.0896%;\" align=\"left\"\u003e\n \u003cp\u003eSecondary education\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28.96%;\" align=\"left\"\u003e\n \u003cp\u003e207\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22.8492%;\" align=\"left\"\u003e\n \u003cp\u003e36.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 48.0896%;\" align=\"left\"\u003e\n \u003cp\u003eCollege and above\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28.96%;\" align=\"left\"\u003e\n \u003cp\u003e102\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22.8492%;\" align=\"left\"\u003e\n \u003cp\u003e18%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 48.0896%;\" align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eMonthly income (in ETB)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28.96%;\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd style=\"width: 22.8492%;\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 48.0896%;\" align=\"left\"\u003e\n \u003cp\u003e\u0026le;\u0026thinsp;1500\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28.96%;\" align=\"left\"\u003e\n \u003cp\u003e168\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22.8492%;\" align=\"left\"\u003e\n \u003cp\u003e29.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 48.0896%;\" align=\"left\"\u003e\n \u003cp\u003e1501\u0026ndash;3500\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28.96%;\" align=\"left\"\u003e\n \u003cp\u003e169\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22.8492%;\" align=\"left\"\u003e\n \u003cp\u003e29.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 48.0896%;\" align=\"left\"\u003e\n \u003cp\u003e\u0026ge;\u0026thinsp;3501\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28.96%;\" align=\"left\"\u003e\n \u003cp\u003e230\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22.8492%;\" align=\"left\"\u003e\n \u003cp\u003e40.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 48.0896%;\" align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eMarital status\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28.96%;\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd style=\"width: 24.9747%;\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 48.0896%;\" align=\"left\"\u003e\n \u003cp\u003eMarried\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28.96%;\" align=\"left\"\u003e\n \u003cp\u003e225\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22.8492%;\" align=\"left\"\u003e\n \u003cp\u003e39.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 48.0896%;\" align=\"left\"\u003e\n \u003cp\u003eDivorced\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28.96%;\" align=\"left\"\u003e\n \u003cp\u003e138\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22.8492%;\" align=\"left\"\u003e\n \u003cp\u003e24.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 48.0896%;\" align=\"left\"\u003e\n \u003cp\u003eWidowed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28.96%;\" align=\"left\"\u003e\n \u003cp\u003e204\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22.8492%;\" align=\"left\"\u003e\n \u003cp\u003e36%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\n \u003ch2\u003eHealth-related, psychological and lifestyle-related factors of study participants\u003c/h2\u003e\n \u003cp\u003eRegarding the health-related characteristics of study participants, 111 (19.6%), had commodities, majority, 378 (66.7%) had no history of visiting any hospital in the past year. In terms of psychological and lifestyle-related factors, 163(28.7%) of the participants had depressed symptoms and 123 (21.7%) were smokers. See table 2 for more details.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\n \u003ch2\u003ePrevalence of undernutrition\u003c/h2\u003e\n \u003cp\u003eOut of 567 older adults, the overall prevalence of undernutrition among older adults living in Bahir Dar City was found to be 139 (24.5%) (95% CI: 21.0 to 28.3). Among the participants 48 (16.8%) males and 91 (29.4%) females were suffered from undernutrition. Likewise, 56 (33.3%) participants who had monthly income\u0026thinsp;\u0026le;\u0026thinsp;1500 ETB and 65(31.9%) widowed individuals were undernourished. Regarding health-related, psychological and lifestyle-related characteristics of study participants 42 (37.8%) had comorbidities, 51(27%) had history of hospitalization in the past one year, 23 (24.2%) participants took 5 or more prescribed drugs and 47(28.8%) with depression symptoms were had undernutrition. Moreover, among smokers and alcohol drinkers, 44(35.8%) and 5(5.4%) were undernourished respectively.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\n \u003ch2\u003eFactors associated with undernutrition among older adults\u003c/h2\u003e\n \u003cp\u003ePrimarily, the independent variables were entered into bivariable logistic regression analysis, and variables with a p-value of less than 0.25 were drawn into multivariable logistic regression analysis together. In bivariable logistic regression gender (being female), age, education (being unable to read and write and primary education), marital status of divorced and widowed, smoking, depression symptoms were positively associated with undernutrition, whereas, being female, age 80 years and older, unable to read and write, widowed and smoking were remained significantly associated with undernutrition on the multivariable logistic regression (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e\n \u003cp\u003eParticipants aged 80 years and older had 1.73 times higher odds of developing undernutrition than those older adults who were 60\u0026ndash;69 years older (AOR\u0026thinsp;=\u0026thinsp;1.73, CI 1.03\u0026ndash;2.91). The odds of undernutrition were more than 1.81 times higher among female participants compared to male participants (AOR\u0026thinsp;=\u0026thinsp;1.81, CI 1.19\u0026ndash;2.76). Regarding educational status, being unable to read and write increased the odds of undernutrition among the study participants as compared with those who had an educational status of college and above (AOR\u0026thinsp;=\u0026thinsp;3.06,CI 1.54\u0026ndash;6.08). This study also revealed that older adults who were widowed had 1.63 times more likely to be undernourished than those who were married (AOR\u0026thinsp;=\u0026thinsp;1.63, CI 1.00-2.63). Furthermore, study participants who smoked were 1.88 times more likely to be undernourished compared to those who did not smoke (AOR\u0026thinsp;=\u0026thinsp;1.88, CI 1.19\u0026ndash;2.99). See Table \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e for more details.\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\u0026nbsp;\u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eFactors associated with undernutrition in older people living in Bahir Dar City, 2024 (n\u0026thinsp;=\u0026thinsp;567).\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr style=\"height: 35px;\"\u003e\n \u003cth style=\"height: 35px;\" align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth style=\"height: 35px;\" colspan=\"3\" align=\"left\"\u003e\n \u003cp\u003e\u003cspan class=\"Underline\"\u003eUndernutrition\u003c/span\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth style=\"height: 35px;\" colspan=\"2\" align=\"left\"\u003e\n \u003cp\u003e\u003cspan class=\"Underline\"\u003eOR (95% CI)\u003c/span\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth style=\"width: 10.5339%; height: 35px;\" align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr style=\"height: 35px;\"\u003e\n \u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariables\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"height: 35px;\" colspan=\"2\" align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eYes\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eNo\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eCOR (95% CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 21.0678%; height: 35px;\" align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eAOR ( 95% CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.5339%; height: 35px;\" align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eP-Value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr style=\"height: 35px;\"\u003e\n \u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eGender\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"height: 35px;\" colspan=\"2\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd style=\"height: 35px;\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd style=\"height: 35px;\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd style=\"width: 21.0678%; height: 35px;\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd style=\"width: 10.5339%; height: 35px;\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr style=\"height: 35px;\"\u003e\n \u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"height: 35px;\" colspan=\"2\" align=\"left\"\u003e\n \u003cp\u003e48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n \u003cp\u003e210\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 21.0678%; height: 35px;\" align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.5339%; height: 35px;\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr style=\"height: 35px;\"\u003e\n \u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"height: 35px;\" colspan=\"2\" align=\"left\"\u003e\n \u003cp\u003e91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n \u003cp\u003e218\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n \u003cp\u003e1.82(1.22\u0026ndash;2.71)\u003cstrong\u003e*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 21.0678%; height: 35px;\" align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.81(1.19\u0026ndash;2.76) **\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.5339%; height: 35px;\" align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.006\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr style=\"height: 35px;\"\u003e\n \u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge (in years)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"height: 35px;\" colspan=\"2\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd style=\"height: 35px;\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd style=\"height: 35px;\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd style=\"width: 21.0678%; height: 35px;\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd style=\"width: 10.5339%; height: 35px;\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr style=\"height: 35px;\"\u003e\n \u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n \u003cp\u003e60\u0026ndash;69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"height: 35px;\" colspan=\"2\" align=\"left\"\u003e\n \u003cp\u003e39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n \u003cp\u003e145\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 21.0678%; height: 35px;\" align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.5339%; height: 35px;\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr style=\"height: 35px;\"\u003e\n \u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n \u003cp\u003e70\u0026ndash;79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"height: 35px;\" colspan=\"2\" align=\"left\"\u003e\n \u003cp\u003e45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n \u003cp\u003e181\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n \u003cp\u003e0.92(0.57\u0026ndash;1.49)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 21.0678%; height: 35px;\" align=\"left\"\u003e\n \u003cp\u003e0.97(0.59\u0026ndash;1.61)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.5339%; height: 35px;\" align=\"left\"\u003e\n \u003cp\u003e0.93\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr style=\"height: 35px;\"\u003e\n \u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n \u003cp\u003e80 and older\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"height: 35px;\" colspan=\"2\" align=\"left\"\u003e\n \u003cp\u003e55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n \u003cp\u003e102\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n \u003cp\u003e2.00 (1.23\u0026ndash;3.24)\u003cstrong\u003e*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 21.0678%; height: 35px;\" align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.73(1.03\u0026ndash;2.91)**\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.5339%; height: 35px;\" align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.037\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr style=\"height: 35px;\"\u003e\n \u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eEducational status\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"height: 35px;\" colspan=\"2\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd style=\"height: 35px;\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd style=\"height: 35px;\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd style=\"width: 21.0678%; height: 35px;\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd style=\"width: 10.5339%; height: 35px;\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr style=\"height: 35px;\"\u003e\n \u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n \u003cp\u003eUnable to read \u0026amp; Write\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"height: 35px;\" colspan=\"2\" align=\"left\"\u003e\n \u003cp\u003e34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n \u003cp\u003e62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n \u003cp\u003e2.39 (1.25\u0026ndash;4.59)\u003cstrong\u003e*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 21.0678%; height: 35px;\" align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e3.06 (1.54\u0026ndash;6.08) **\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.5339%; height: 35px;\" align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr style=\"height: 35px;\"\u003e\n \u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n \u003cp\u003ePrimary education\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"height: 35px;\" colspan=\"2\" align=\"left\"\u003e\n \u003cp\u003e42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n \u003cp\u003e120\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n \u003cp\u003e1.52 (0.83\u0026ndash;2.81)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 21.0678%; height: 35px;\" align=\"left\"\u003e\n \u003cp\u003e1.77 (0.93\u0026ndash;3.36)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.5339%; height: 35px;\" align=\"left\"\u003e\n \u003cp\u003e0.077\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr style=\"height: 35px;\"\u003e\n \u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n \u003cp\u003eSecondary education\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"height: 35px;\" colspan=\"2\" align=\"left\"\u003e\n \u003cp\u003e44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n \u003cp\u003e163\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n \u003cp\u003e1.17 (0.64\u0026ndash;2.14)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 21.0678%; height: 35px;\" align=\"left\"\u003e\n \u003cp\u003e1.48 (0.78\u0026ndash;2.78)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.5339%; height: 35px;\" align=\"left\"\u003e\n \u003cp\u003e0.222\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr style=\"height: 35px;\"\u003e\n \u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n \u003cp\u003eCollege and above\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"height: 35px;\" colspan=\"2\" align=\"left\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n \u003cp\u003e83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 21.0678%; height: 35px;\" align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.5339%; height: 35px;\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr style=\"height: 35px;\"\u003e\n \u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eMarital status\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"height: 35px;\" colspan=\"2\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd style=\"height: 35px;\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd style=\"height: 35px;\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd style=\"width: 21.0678%; height: 35px;\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd style=\"width: 10.5339%; height: 35px;\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr style=\"height: 35px;\"\u003e\n \u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n \u003cp\u003eMarried\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"height: 35px;\" colspan=\"2\" align=\"left\"\u003e\n \u003cp\u003e41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n \u003cp\u003e184\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 21.0678%; height: 35px;\" align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.5339%; height: 35px;\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr style=\"height: 35px;\"\u003e\n \u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n \u003cp\u003eDivorced\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"height: 35px;\" colspan=\"2\" align=\"left\"\u003e\n \u003cp\u003e33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n \u003cp\u003e105\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n \u003cp\u003e1.41 (0.84\u0026ndash;2.36)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 21.0678%; height: 35px;\" align=\"left\"\u003e\n \u003cp\u003e1.25 (0.73\u0026ndash;2.16)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.5339%; height: 35px;\" align=\"left\"\u003e\n \u003cp\u003e0.405\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr style=\"height: 35px;\"\u003e\n \u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n \u003cp\u003eWidowed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"height: 35px;\" colspan=\"2\" align=\"left\"\u003e\n \u003cp\u003e65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n \u003cp\u003e139\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n \u003cp\u003e2.09 (1.34\u0026ndash;3.28)\u003cstrong\u003e*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 21.0678%; height: 35px;\" align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.63 (1.00-2.63) **\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.5339%; height: 35px;\" align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.046\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr style=\"height: 35px;\"\u003e\n \u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eSmoking\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"height: 35px;\" colspan=\"2\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd style=\"height: 35px;\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd style=\"height: 35px;\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd style=\"width: 21.0678%; height: 35px;\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd style=\"width: 10.5339%; height: 35px;\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr style=\"height: 35.0579px;\"\u003e\n \u003ctd style=\"height: 35.0579px;\" align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"height: 35.0579px;\" colspan=\"2\" align=\"left\"\u003e\n \u003cp\u003e95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"height: 35.0579px;\" align=\"left\"\u003e\n \u003cp\u003e349\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"height: 35.0579px;\" align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 21.0678%; height: 35.0579px;\" align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.5339%; height: 35.0579px;\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr style=\"height: 35px;\"\u003e\n \u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"height: 35px;\" colspan=\"2\" align=\"left\"\u003e\n \u003cp\u003e44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n \u003cp\u003e79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n \u003cp\u003e2.04 (1.32\u0026ndash;3.15)\u003cstrong\u003e*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 21.0678%; height: 35px;\" align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.88 (1.19\u0026ndash;2.99) **\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.5339%; height: 35px;\" align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.007\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr style=\"height: 35px;\"\u003e\n \u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eDepression\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"height: 35px;\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd style=\"height: 35px;\" colspan=\"2\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd style=\"height: 35px;\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd style=\"width: 21.0678%; height: 35px;\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd style=\"width: 8.8023%; height: 35px;\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr style=\"height: 35px;\"\u003e\n \u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n \u003cp\u003e92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"height: 35px;\" colspan=\"2\" align=\"left\"\u003e\n \u003cp\u003e312\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 21.0678%; height: 35px;\" align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"height: 35px;\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr style=\"height: 35px;\"\u003e\n \u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n \u003cp\u003e47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"height: 35px;\" colspan=\"2\" align=\"left\"\u003e\n \u003cp\u003e116\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n \u003cp\u003e1.37 (0.91\u0026ndash;2.07)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 21.0678%; height: 35px;\" align=\"left\"\u003e\n \u003cp\u003e1.29 (0.83-2.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n \u003cp\u003e0.242\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr style=\"height: 26px;\"\u003e\n \u003ctd style=\"height: 26px;\" colspan=\"7\"\u003e\u003cstrong\u003eNote\u003c/strong\u003e: COR: Crude Odds ratio; AOR: Adjusted Odd ratio; CI: Confidence interval; 1\u0026thinsp;=\u0026thinsp;Reference category,*: statistically significant at P\u0026thinsp;\u0026lt;\u0026thinsp;0.25 and **: statistically significant at P\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study aimed to assess the magnitude and associated factors of undernutrition among older adults living in Bahir Dar City. In this study, the overall prevalence of undernutrition among older adults living in the study area was found to be 24.5% (95% CI: 21.0\u0026ndash;28.3). This finding indicates that undernutrition is a significant a high public health burden and health problem among community dweller older adults living in Bahir Dar City. The result of the present study revealed that undernutrition among older adults was significantly associated with age 80 years and older, being female, widowed, and unable to read and write and smoking.\u003c/p\u003e \u003cp\u003eThe prevalence of undernutrition in current study was comparable with the findings from other studies conducted on Nutritional status and associated factors among the older people in Derham City, India (21.8%) (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e), Nepal (24.8%) (\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e) and Gondar town (21.9%) (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e). This might be due to the similar study designs and assessment tools used and the comparable mean ages of the study participants. For instance, similar to our study, the study conducted in Nepal and Gondar town were a community-based cross-sectional studies that employed a multistage sampling techniques. Additionally, the mean ages of the study participants in these studies were comparable to those in our study, which could contribute to the consistency in results. Furthermore, the study done in Derham City of India utilized a cross-sectional study design and similar assessment tool.\u003c/p\u003e \u003cp\u003eHowever, the prevalence found in our study was lower compared to what was reported from studies conducted in Sri Lanka (30%) (\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e), Barcelona, Spain (34.5%) (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e), Belgium (57.1%) (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e), and Eldoret, Kenya (41%) (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e). This difference could be due to variations in geographic settings, lifestyle characteristics, socioeconomic factors, and health status of the study populations. In addition, these differences could be created by the variation of inclusion or exclusion criteria of the study participants.\u003c/p\u003e \u003cp\u003eOur study revealed that age 80 years and older are significantly associated with undernutrition. This was similar to a study done in Belgium (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e) and Gondar town (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e). The possible reason might be as age advances the risk of undernutrition increases. This might be due to the natural aging process, which is accompanied by physiological changes that can have a detrimental impact on nutritional status and lead to inadequate nutrition (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e). This study revealed a significant difference between females and males. Females were significantly associated with more likely to be undernourished than males. This was supported by studies done in Kolkata, India (\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e) and Belgium (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e). The possible implication could be that female older individuals are more vulnerable for undernutrition due to the fact that the older population is predominantly female and tends to live longer than males, and it may also be due to the fact that older females still remain the caretakers of their grandchildren, and they receive less than the care necessary for themselves (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e). Another possible explanation could be that older female adults are often economically dependent and may face gender discrimination, along with reduced health-seeking behavior. These factors can negatively impact their health and nutritional status, leading to undernutrition. According to the findings of our study marital status was one of the factors affecting nutritional status of older people. Individuals who are widowed/widower were more likely to be undernourished compared to married individuals. This finding was supported by study done in Ghana (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e). The reason could be that being alone as a result of the death of one of the mates decrease social relations, exposure to loneliness and economic deficiencies. These changes may cause inadequate nutrition (\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e). The loss of one\u0026rsquo;s mate may also be associated with loss of motivation to prepare and eat food, thereby increases the risk of undernourishment (\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e). Regarding educational status, participants who were unable to read and write were more likely to be undernourished compared to those with an educational status of college and above. This is similar to other reported studies in the aging population in Gondar town, Ethiopia (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e). This because education is an essential factor in improving health status; educated individuals develop habits, skills, resources, and the ability to achieve a better life (\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e). Additionally, knowledge might encourage individuals to consume diversified foods, and educated people are more likely to have better feeding practices and healthy lifestyles. Furthermore, being a smoker was found to be an independent predictor of undernutrition as compared to their counterparts in this study. This finding is in-line with reports from Northern Ghana (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e). The plausible explanation is related to the fact that smoking might influence appetite (\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e), reduce the desire to consume foods, and decrease the need to take vitamin-rich fruits and vegetables, as a result increasing the likelihood of being undernourished.\u003c/p\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003eConclusions and recommendations\u003c/h2\u003e \u003cp\u003eThis community-based study among older adults found the overall prevalence of undernutrition in the study area was high, making it an important public health burden. The findings of this study have shown that being female, age 80 years and older, being widowed, being unable to read and write, and smoking were independent factors significantly associated with undernutrition among older people. To improve the nutritional status of older people, education focusing on very old and female older people need to be initiated in improving dietary practice, including behavioral support interventions to assist in the cessation of smoking, especially targeting vulnerable groups identified in this study. Further studies are needed to create a comprehensive database for effective policymaking and design a national strategy on nutrition targeting the whole population of older adults to promote healthy aging. Additionally, further research including potential unaddressed factors contributing to undernutrition in older adults in the present study, is also recommended.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003eLimitations and the strengths of the study\u003c/h2\u003e \u003cp\u003eFirst, since our study was conducted only in one district and included only urban older adults, the finding of the study is not generalizable to the entire rural population. Second, due to the nature of a cross-sectional study, it is difficult to know the exposure and outcome inferences. Despite these drawbacks, to the best of our knowledge, this is the first study of its kind to look at undernutrition in older individuals, conducted in Bahir Dar City, Ethiopia. In addition, because the study was conducted in a community to determine the prevalence and associated factors of undernutrition among older adults, it may address the huge gap of evidence about undernutrition and reflects the actual nature of the issue in the study area.\u003c/p\u003e \u003c/div\u003e"},{"header":"Abbreviations","content":"\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 22.7273%;\"\u003e\n \u003cp\u003eAOR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77.2727%;\"\u003e\n \u003cp\u003eAdjusted Odds Ratio\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 22.7273%;\"\u003e\n \u003cp\u003eBMI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77.2727%;\"\u003e\n \u003cp\u003eBody Mass Index\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 22.7273%;\"\u003e\n \u003cp\u003eCI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77.2727%;\"\u003e\n \u003cp\u003eConfidence Interval\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 22.7273%;\"\u003e\n \u003cp\u003eCOR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77.2727%;\"\u003e\n \u003cp\u003eCrude Odds Ratio\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 22.7273%;\"\u003e\n \u003cp\u003eETB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77.2727%;\"\u003e\n \u003cp\u003eEthiopian Birr\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 22.7273%;\"\u003e\n \u003cp\u003eGDS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77.2727%;\"\u003e\n \u003cp\u003eGeriatric Depression Scale\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 22.7273%;\"\u003e\n \u003cp\u003eGDS-SF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77.2727%;\"\u003e\n \u003cp\u003eGeriatric Depression Scale Short Form\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 22.7273%;\"\u003e\n \u003cp\u003eMNA-SF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77.2727%;\"\u003e\n \u003cp\u003eMini Nutritional Assessment Short Form\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 22.7273%;\"\u003e\n \u003cp\u003eOR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77.2727%;\"\u003e\n \u003cp\u003eOdds Ratio\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 22.7273%;\"\u003e\n \u003cp\u003eSPSS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77.2727%;\"\u003e\n \u003cp\u003eStatistical Package for Social Science fiction\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthical approval\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eand informed consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was conducted following the Declaration of Helsinki version-2013\u0026nbsp;that embraces Ethical Principles for Medical Research involving Human Subjects. Ethical approval was obtained from the institutional ethical review board of the School of Medicine, College of Medicine and Health Sciences, Bahir Dar University, (Ref. 1545/Med/2024). Informed consent was obtained from each study participants after the purpose of the study was explained. Participants were informed that their participation was voluntary and the information obtained from them would be kept confidential, with no individual identifiers linked to their personal information.\u003c/p\u003e\n\u003ch3\u003eConsent for publication\u003c/h3\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability statement\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll essential datasets generated and/or analyzed during the current study are not publicly available due to privacy issues but are available from the primary author\u0026nbsp;(Yibeltal Wolelaw Admas).\u003c/p\u003e\n\u003ch3\u003eCompeting interests\u003c/h3\u003e\n\u003cp\u003eAll authors declared they have no conflict of interest\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo funding\u0026nbsp;\u003c/p\u003e\n\u003cp id=\"_Toc184040468\"\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eGenerally, all authors contributed to several revisions and approved the final version of the manuscript.\u003c/p\u003e\n\u003cp\u003eYibeltal Wolelaw: Has contributed to develop the research project, coordinate, supervised data collection process and finalized the manuscript.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAddisu Yihenew: Has taken part to supervise the data collection and review process.\u003c/p\u003e\n\u003cp\u003eBelayneh Addis: Has participated in data clearing and entry activities.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eGebremariam Bekele: He has participated in in the data entry and analysis process.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eGebremeskel Birhanie: He has contributed to the methodology designing and sampling procedures.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eYesahmbel Ejigu: Has also contributed to initiate the idea of the research project and wrote the introduction part of the manuscript.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAwoke Kebede: Contributed in the write up process of the manuscript\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eBerihun Assefa: Has contributed to the overall write up, review and submission process of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgment\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe would like to thank Bahir Dar University for approval of ethical the clearance to carry out this research. We would also like to acknowledge the Department of Labor and Social Affairs of Bahir Dar City for the assistance in providing essential information. Our deepest gratitude goes to the study participants for their involvement in this study and the data collectors and supervisors for their patience during the data collection process.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; information\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e1. Department of Physiotherapy, School of medicine, College of Medicine and Health Science, Bahir Dar University:\u003c/p\u003e\n\u003cp\u003eYibeltal Wolelaw, Addisu Yihenew, Belayneh Addis Mekuria, Gebremariam Bekele, Gebremeskel Birhanie Gebru, Yeshambel Ejigu and Berihun Assefa Demissie\u003c/p\u003e\n\u003cp\u003e2. Department of Pediatrics and Child Health Nursing, school of Health Sciences, College of Medicine and Health Science, Bahir Dar University: Awoke Kebede\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eHe W, Goodkind D, Kowal P (2016) An aging world: 2015. US Department of Commerce. Economics and Statistics Administration\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSert AN (2019) Senior Tourism in the aging world. Theory and practice in social sciences. :488\u0026thinsp;\u0026ndash;\u0026thinsp;98\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCharles T, Tesfayi G, Hassan A (2009) Population dynamics, food/nutrition security and health in ethiopia. Delicate balance of vulnerability \u0026amp; resilience IUSSP marrakech\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJuergens F (2019) HelpAge International. Coverage of older people in Ethiopia\u0026rsquo;s social protection system\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRynning E (2008) The ageing populations of Europe\u0026mdash;implications for health systems and patients' rights. Eur J health law 15(3):297\u0026ndash;306\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOrganization WH (2015) World report on ageing and health\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMURPHY K (2011) Malnutrition in the community and hospital setting. The patient association. August\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMartins VJ, Toledo Flor\u0026ecirc;ncio TM, Grillo LP, Franco MCP, Martins PA, Clemente APG et al (2011) Long-lasting effects of undernutrition. Int J Environ Res Public Health 8(6):1817\u0026ndash;1846\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCereda E, Valzolgher L, Pedrolli C (2008) Mini nutritional assessment is a good predictor of functional status in institutionalised elderly at risk of malnutrition. Clin Nutr 27(5):700\u0026ndash;705\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eInternational HA (2013) Vulnerability of Older People in Ethiopia: The Case of Oromia, Amhara and SNNP Regional States. Help Age International in Ethiopia Addis Ababa\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRasheed S, Woods RT (2013) Malnutrition and quality of life in older people: a systematic review and meta-analysis. Ageing Res Rev 12(2):561\u0026ndash;566\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSserwanja Q, Mukunya D, Habumugisha T, Mutisya LM, Tuke R, Olal E (2020) Factors associated with undernutrition among 20 to 49 year old women in Uganda: a secondary analysis of the Uganda demographic health survey 2016. BMC Public Health 20:1\u0026ndash;10\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHickson M (2006) Malnutrition and ageing: This article is part of a series on ageing edited by Professor Chris Bulpitt. Postgrad Med J 82(963):2\u0026ndash;8\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAmarya S, Singh K, Sabharwal M (2015) Changes during aging and their association with malnutrition. J Clin Gerontol Geriatr 6(3):78\u0026ndash;84\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRaynaud-Simon A, Revel-Delhom C, H\u0026eacute;buterne X (2011) Clinical practice guidelines from the French Health High Authority: nutritional support strategy in protein-energy malnutrition in the elderly. Clin Nutr 30(3):312\u0026ndash;319\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRoss AC, Caballero B, Cousins RJ, Tucker KL (2020) Modern nutrition in health and disease. Jones \u0026amp; Bartlett Learning\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRitchie CS, Locher JL, Roth DL, McVie T, Sawyer P, Allman R (2008) Unintentional weight loss predicts decline in activities of daily living function and life-space mobility over 4 years among community-dwelling older adults. Journals Gerontol Ser A: Biol Sci Med Sci 63(1):67\u0026ndash;75\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKvamme J-M, Gr\u0026oslash;nli O, Florholmen J, Jacobsen BK (2011) Risk of malnutrition is associated with mental health symptoms in community living elderly men and women: The Troms\u0026oslash; Study. BMC Psychiatry 11:1\u0026ndash;8\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCabrera MAS, Mesas AE, Garcia ARL, de Andrade SM (2007) Malnutrition and depression among community-dwelling elderly people. J Am Med Dir Assoc 8(9):582\u0026ndash;584\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFreijer K, Tan SS, Koopmanschap MA, Meijers JM, Halfens RJ, Nuijten MJ (2013) The economic costs of disease related malnutrition. Clin Nutr 32(1):136\u0026ndash;141\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHiesmayr M, Schindler K, Pernicka E, Schuh C, Schoeniger-Hekele A, Bauer P et al (2009) Decreased food intake is a risk factor for mortality in hospitalised patients: the NutritionDay survey 2006. Clin Nutr 28(5):484\u0026ndash;491\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eArvanitakis M, Vandewoude M, Perkisas S, Van Gossum A (2013) Undernutrition in community dwelling elderly. e-SPEN J 8(5):e213\u0026ndash;e5\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTesfaye A, Sisay G, Kabthymer RH, Tesfaye T (2022) Under-nutrition and associated factors among pregnant women in public health care hospitals of Gedeo Zone, southern Ethiopia: A cross-sectional study. Heliyon. ;8(5)\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJ\u0026eacute;sus P, Guerchet M, Pilleron S, Fayemendy P, Mouanga AM, Mbelesso P et al (2017) Undernutrition and obesity among elderly people living in two cities of developing countries: prevalence and associated factors in the EDAC study. Clin Nutr ESPEN 21:40\u0026ndash;50\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAdebusoye LA, Ajayi I, Dairo M, Ogunniyi A (2011) Factors associated with undernutrition and overweight in elderly patients presenting at a primary care clinic in Nigeria. South Afr Family Pract 53(4):355\u0026ndash;360\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChalermsri C, Assantachai P, Pramyothin P, Pengsorn N, Muangpaisan W (2018) Prevalence of and factors associated with undernutrition in a geriatric outpatient setting: Results from a multidimensional nutritional assessment. Siriraj Med J 70(5):413\u0026ndash;418\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFarre TB, Formiga F, Ferrer A, Plana-Ripoll O, Almeda J, Pujol R (2014) Risk of being undernourished in a cohort of community‐dwelling 85‐year‐olds: The O ctabaix study. Geriatr Gerontol Int 14(3):702\u0026ndash;709\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAgarwalla R, Saikia AM, Baruah R (2015) Assessment of the nutritional status of the elderly and its correlates. J Family Community Med 22(1):39\u0026ndash;43\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAdigeh DT, Abebe BG (2023) The practice of peri-urban land acquisition by expropriation for housing purposes and the implications: the case of Bahir Dar, Ethiopia. Urban Sci 7(2):41\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTessfamichael D, Gete AA, Wassie MM (2014) High prevalence of undernutrition among elderly people in Northwest Ethiopia: a cross sectional study. Read Write 244:322\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eS\u0026ouml;derhamn U, Dale B, Sundsli K, S\u0026ouml;derhamn O (2012) Nutritional screening of older home-dwelling Norwegians: a comparison between two instruments. Clinical interventions in aging. :383\u0026thinsp;\u0026ndash;\u0026thinsp;91\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eScherbov S, Sanderson W (2019) New measures of population ageing. United Nations report\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGreenberg SA (2007) How to try this: the geriatric depression scale: short form. AJN Am J Nurs 107(10):60\u0026ndash;69\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAsresahegn H, Tadesse F, Beyene E (2017) Prevalence and associated factors of hypertension among adults in Ethiopia: a community based cross-sectional study. BMC Res Notes 10:1\u0026ndash;8\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSemwal J, Vyas S, Juyal R, Sati HC (2014) Nutritional status and associated comorbidities among the elderly in Doiwala block, Dehradun. Indian J Community Health 26(Supp 2):197\u0026ndash;203\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTamang MK, Yadav UN, Hosseinzadeh H, Kafle B, Paudel G, Khatiwada S et al (2019) Nutritional assessment and factors associated with malnutrition among the elderly population of Nepal: a cross-sectional study. BMC Res Notes 12:1\u0026ndash;5\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRathnayake KM, Wimalathunga M, Weech M, Jackson KG, Lovegrove JA (2015) High prevalence of undernutrition and low dietary diversity in institutionalised elderly living in Sri Lanka. Public Health Nutr 18(15):2874\u0026ndash;2880\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBore C (2019) Assessment Of Determinants Of Under-Nutrition And Food Security Among The Elderly In Moiben Sub-County. University of Eldoret, Uasin Gishu County\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChen ST, Ngoh HJ, Harith S (2012) Prevalence of malnutrition among institutionalized elderly people in Northern Peninsular Malaysia: gender, ethnicity and age-specific. Sains Malaysiana 41(1):141\u0026ndash;148\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eForster S, Gariballa S (2005) Age as a determinant of nutritional status: a cross sectional study. Nutr J 4:1\u0026ndash;5\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMajumder M, Saha I, Chaudhuri D (2014) Assessment of nutritional risk in community-dwelling older adults (65 to 75 years) in Kolkata, India. J Nutr Gerontol Geriatr 33(2):126\u0026ndash;134\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAganiba BA, Owusu W, Steiner-Asiedu M, Dittoh S (2015) Association between lifestyle and health variables with nutritional status of the elderly in the northern region of Ghana. Afr J Food Agric Nutr Dev 15(4):10198\u0026ndash;10216\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSantos ALMd A, TMdSPFd, Borges NPGFB (2015) Undernutrition and associated factors in a Portuguese older adult community. Revista de Nutri\u0026ccedil;\u0026atilde;o 28(3):231\u0026ndash;240\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLocher JL, Ritchie CS, Roth DL, Baker PS, Bodner EV, Allman RM (2005) Social isolation, support, and capital and nutritional risk in an older sample: ethnic and gender differences. Soc Sci Med 60(4):747\u0026ndash;761\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRoss CE, Mirowsky J (2010) Why education is the key to socioeconomic differentials in health. Handb Med Sociol 6:33\u0026ndash;51\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLin W-Q, Wang H, Yuan L-X, Li B, Jing M-J, Luo J-L et al (2017) The unhealthy lifestyle factors associated with an increased risk of poor nutrition among the elderly population in China. J Nutr health aging 21(9):943\u0026ndash;953\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"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":"Undernutrition, Older adults, Prevalence, Bahir Dar, Ethiopia","lastPublishedDoi":"10.21203/rs.3.rs-6084340/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6084340/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eIntroduction: \u003c/strong\u003eIn any society, older adults are among the vulnerable and high-risk groups in health status. In this age group undernutrition is a major health concern, multifactorial, and has serious negative consequences including decreased resistance to infection, declined functional status, loss of independence, and affected quality of life but it is inadequately recognized and addressed. Despite their growing numbers and nutritional needs, older people in Ethiopia have been given little attention, and there are limited studies done about undernutrition in this population in Northern Ethiopia. Hence, this study aimed to assess the prevalence of undernutrition and its associated factors among older adults living in Bahir Dar City, Northwest Ethiopia, 2024.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods: \u003c/strong\u003eA community-based cross-sectional study design was conducted from September 5 to November 25, 2024. A multistage sampling technique was employed to recruit a total of 579 study participants aged 60 and above. The MNA-SF tool was used to assess undernutrition. The data was collected through the Kobo toolbox using face-to-face interviews, entered into Microsoft Excel, and then exported to SPSS version 25 for analysis. Variables having a p \u0026lt; 0.25 at bivariable logistic regression were included in the multivariable logistic regression. Finally, variables with a p-value \u0026lt; 0.05 at a 95% CI and adjusted odds ratio were statistically significant in multivariable logistic regression.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003eAmong the 567 participants enrolled, the overall prevalence of undernutrition was 24.5% (95% CI: 21.0–28.3). Being female (AOR = 1.81, CI 1.19-2.76), age 80 years and older (AOR = 1.73, CI 1.03-2.91), being unable to read and write (AOR= 3.06, CI 1.54-6.08), being widowed (AOR = 1.63, CI 1.00-2.63) and smoking (AOR = 1.88, CI 1.19-2.99) were significantly associated with undernutrition.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion and recommendation:\u003c/strong\u003e This study found that the prevalence of undernutrition among older adults in the study area was high, making it an important public health issue. Being female, age 80 years and older, being widowed, being unable to read and write, and smoking were factors associated with undernutrition. Therefore, we suggest that education focus on very old and female older adults in improving dietary practice, incorporating behavioral supports to assist in the cessation of smoking to ensure healthy aging.\u003c/p\u003e","manuscriptTitle":"Undernutrition and associated factors among older adults living in Bahir Dar City, Northwest Ethiopia.","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-02-27 08:57:02","doi":"10.21203/rs.3.rs-6084340/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":"fc567dcf-6826-46e0-bfe8-79c69a6d31a4","owner":[],"postedDate":"February 27th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":44717911,"name":"Nutrition \u0026 Dietetics"}],"tags":[],"updatedAt":"2025-02-27T08:57:02+00:00","versionOfRecord":[],"versionCreatedAt":"2025-02-27 08:57:02","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6084340","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6084340","identity":"rs-6084340","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}