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      Predictors of undernutrition among the elderly in Sodo zuriya district Wolaita zone, Ethiopia

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          Abstract

          Background

          In any society, the elderly are among the vulnerable and high risk groups with regard to health status. In persons over the age of 60 years, nutrition is among the important determinants of health. However, undernutrition among the elderly is often under diagnosed and/or neglected. Hence, in this study, we looked at prevalence and factors associated with undernutrition among the elderly.

          Methods

          A community based cross-sectional study was conducted at Sodo Zuriya district. Multi-stage systematic sampling method was used to select 578 elderly. A structured questionnaire was used to collect data on socio-demographics, dietary diversity, and health status of the elderly.

          Measurements of weight and height were taken using digital weighing scale and stadio-meter, respectively. Data was entered and cleaned in Epi-Data version3.1and exported to SPSS version 20 for analysis. Binary and multivariate logistic regressions were done and odds ratios with 95% confidence intervals were calculated.

          Results

          The overall prevalence of undernutrition was 17.1%. On multivariate logistic regression, being unable to read and write (AOR = 2.09), not being married (AOR = 2.02), history of decline in food intake (AOR = 2.1), smoking (AOR = 4.9) and monthly income <$20 (AOR = 7.5) were factors positively associated with undernutrition.

          Conclusion

          The study revealed that prevalence of undernutrition in the district was relatively high. Hence, it is among the major public health burdens in the district. Hence, to improve nutritional status of elderly the district health office and health professionals should consider behavioral support interventions to assist in cessation of smoking. There is also a need to financially empower the elderly in the district.

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          Most cited references12

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          Changes during aging and their association with malnutrition

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            Body mass index categories in observational studies of weight and risk of death.

            The World Health Organization (Geneva, Switzerland) and the National Heart, Lung, and Blood Institute (Bethesda, Maryland) have developed standard categories of body mass index (BMI) (calculated as weight (kg)/height (m)(2)) of less than 18.5 (underweight), 18.5-24.9 (normal weight), 25.0-29.9 (overweight), and 30.0 or more (obesity). Nevertheless, studies of BMI and the risk of death sometimes use nonstandard BMI categories that vary across studies. In a meta-analysis of 8 large studies that used nonstandard BMI categories and were published between 1999 and 2014 and included 5.8 million participants, hazard ratios tended to be small throughout the range of overweight and normal weight. Risks were similar between subjects of high-normal weight (BMI of approximately 23.0-24.9) and those of low overweight (BMI of approximately 25.0-27.4). In an example using national survey data, minor variations in the reference category affected hazard ratios. For example, choosing high-normal weight (BMI of 23.0-24.9) instead of standard normal weight (BMI of 18.5-24.9) as the reference category produced higher nonsignificant hazard ratios (1.05 vs. 0.97 for men and 1.06 vs. 1.02 for women) for the standard overweight category (BMI of 25.0-29.9). Use of the standard BMI groupings avoids problems of ad hoc and post hoc category selection and facilitates between-study comparisons. The ways in which BMI data are categorized and reported may shape inferences about the degree of risk for various BMI categories.
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              Malnutrition in a home-living older population: prevalence, incidence and risk factors. A prospective study.

              To prospectively investigate and describe the prevalence and incidence of malnutrition among home-living older people, related to demographic and medical factors, self-perceived health and health-related quality of life. Another aim was to find predictors for developing risk of malnutrition. Risk factors for malnutrition have previously been identified as diseases, several medications, low functional status, symptoms of depression and inadequate nutrient intake. Most studies are cross-sectionally performed at hospitals or in nursing care settings. A prospective study with a sample of 579 home-living older people, randomly selected from a local national register. Examinations were performed at baseline and yearly follow-ups two to four times. Questionnaires validated and tested for reliability, to detect risk of malnutrition (Mini Nutritional Assessment), symptoms of depression (Geriatric Depression Scale-20), cognitive function (Mini Mental State Examination), health-related quality of life (Nottingham Health Profile), well-being (Philadelphia Geriatric Center Multilevel Assessment Instrument) self-perceived health, demographic factors, anthropometry and biochemical examinations. Predictors were searched for through multiple logistic regression analysis with the MNA as dependent factor. The prevalence of risk for malnutrition was 14.5%, according to the MNA. Two risk factors for malnutrition were lower handgrip strength and lower self-perceived health. The incidence of risk for malnutrition at follow-ups was between 7.6% and 16.2%. Predictors for developing malnutrition were higher age, lower self-perceived health and more symptoms of depression. Men with symptoms of depression had a higher risk of developing malnutrition. Lower self-perceived health had the highest power to predict risk for malnutrition, with increased number of depression symptoms and higher age as second and third predictors. A regular and combined assessment using the Mini Nutrition Assessment, Geriatric Depression Scale-20 and self-perceived health as a base for identifying people in need, is one way to prevent the development of malnutrition.
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                Author and article information

                Contributors
                kidistwondeye2007@gmail.com
                aberanet@gmail.com
                tsegdems@gmail.com
                felekeh86@gmail.com
                Journal
                BMC Nutr
                BMC Nutr
                BMC nutrition
                BioMed Central (London )
                2055-0928
                8 November 2019
                8 November 2019
                2019
                : 5
                : 50
                Affiliations
                [1 ]Terepeza Development Association (TDA), Wolaita District Office Project Facilitator, Wolaita sodo, Ethiopia
                [2 ]ISNI 0000 0000 8953 2273, GRID grid.192268.6, School of Public Health, College of Health Sciences and Medicine, , Hawassa University, ; Hawassa, Ethiopia
                [3 ]ISNI 0000 0004 4901 9060, GRID grid.494633.f, School of Public Health, College of Health Sciences and Medicine, , Wolaita Sodo University, ; Wolaita sodo, Ethiopia
                Author information
                http://orcid.org/0000-0001-8848-2822
                Article
                320
                10.1186/s40795-019-0320-9
                7050837
                32153963
                5a836327-6b32-4299-bf50-2dbbd778f14f
                © The Author(s). 2019

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 24 September 2018
                : 1 November 2019
                Categories
                Research Article
                Custom metadata
                © The Author(s) 2019

                elderly,undernutrition,associated factors,southern ethiopia

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