Determinants of under nutrition among the elderly in South Gondar Zone, Ethiopia


 Background: The number of the elderly population is expected to become the largest demographic group. Malnutrition in older adults is related with complications and premature death. The progression to malnutrition is often insidious and often undetected. No study has been ever conducted or documented to explore the nutritional status of elderly in south Gondar Zone . Hence, this study was aimed to assess the determinants of under nutrition among the elderly people aged ≥65 years. A cross-sectional study was conducted from October 1 to December 15, 2020. A community based study was conducted in south Gondar Zone, Ethiopia. A total of 290 elderly aged greater or equal to 65 years of age selected by systematic random sampling technique were included in the study. Pretested and structured questionnaire adapted from different literature was used to collect data. Anthropometric measurements; weight and height were measured following standard procedures. Mini-Nutritional Assessment (MNA) tool was used to assess nutritional status of elderly. Descriptive and summary statistics were employed. Multiple logistic regression was fitted to identify determinants of under nutrition. Odds ratios and their 95% confidence intervals were computed to determine the level of significance. Results: Based on their BMI status 27.57%, 95%CI (22.4-32.8) of elderly were underweight and 2.1%, 95% CI (0.7-3.8) were overweight. Likewise, 29.7%, 95%CI (24.5-35.2) of elderly were malnourished and 61.7%, 95% CI (55.5-67.2) were at risk of malnutrition based on Mini-Nutritional Assessment tool. Rural residence (AOR= 10.32, 95%CI (3.62-29.39)), unable to read and write (AOR = 3.54, 95%CI (1.64-7.64)), decline in food intake (AOR= 13.47, 95%CI (6.14-29.52)) and household monthly income <35.6USD (AOR = 4.32, 95%CI (1.97- 9.46)) were significantly and independently associated with under nutrition in elderly population.Conclusion: The prevalence of under nutrition among the elderly in the study area was high, and making it an important public health burden. Place of residence, educational status, food intake and household income were the determinants of under nutrition.


Introduction
The world has seen signi cant growth in the number of the elderly and anticipated to become the largest demographic group in the next few years. As per to the United Nations, in 2025, it is expected that the number of people ≥ 60 years of age will be 1.2 billion and 2 billion in 2050 taking about 22.0% of the world's population (1). High number of elderly gives an understanding to reevaluate the suitability of health infrastructures for the elderly. Eleven percent of the world population and 3.2% of Ethiopian population is categorized under elderly population aged ≥ 65 years (2). Anthropometric measurements are pointers that help determine one's nutritional status. The well-known and applied anthropometric assessment in older adults is the Body Mass Index (BMI) (3).
Malnutrition may be as a result of lack of nutrients (under-nutrition), or an excess of nutrients (overnutrition) (4). A physiologic deterioration in food intake is seen among the elderly due to change in neurotransmitters and hormones that affect the central feeding drive (5)(6)(7). Loss of lean body mass and the low metabolic rate in elderly may impact appetite and food intake. Decrement in sensation both olfaction and taste decreases the enjoyment of food, leads to reduced intake of diversi ed food.
Underlying pathology and medical treatment can cause anorexia and malnutrition (8). Chronic illness among the elderly are treated with medications and dietary restriction that affects food intake. Drugs also affect nutritional status through its side effects and through change of nutrient absorption, metabolism and excretion (9). Weight loss in older adults is often related with a loss of muscle mass and can nally affect functional status. Malnutrition in older adults is related with complications and premature life loss (10). The advancement to malnutrition is mostly treacherous and often unnoticed. On the other hand, restriction of mobility and sedentary lifestyle make them overweight and obese (11). Concerning the current corona virus (COVID -19) pandemic, studies have demonstrated that elderly patients with COVID-19 are at greatest risk of malnutrition or co-malnutrition. Additionally, COVID-19 can affect the mucosal epithelium and cause gastrointestinal symptoms, which can additionally damage the nutritional status of elderly patients with COVID-19 (12). The price of health cost which is related associated with treating the infection and/or malnutrition is high (13). The health and nutrition of the elderly is usually ignored; many of the intervention activities are directed toward neonates, children, adolescents, expectant and nursing mothers. As far as the authors' best search, no study has been ever conducted or documented to determine the nutritional status and its determinants among these segments of the population in South Gondar Zone thus far (14). Therefore, understanding the cause of under nutrition among older people has utmost importance to arrest the problem. Hence, this study was carried out to determine the magnitude and determinant factors of under nutrition among people aged ≥65 years in south Gondar Zone, Ethiopia.

Study area, design and period
The study was conducted in South Gondar Zone. South Gondar is a Zone in the Ethiopian Amhara Region. Based on the 2007 Census conducted by the Central Statistical Agency of Ethiopia (CSA), this Zone has a total population of 2,051,738. With an area of 14,095.19 square kilometers, South Gondar has a population density of 145.56; 195,619 or 9.53% are urban inhabitants. A total of 468,238 households were counted in this Zone, which results in an average of 4.38 persons to a household. There are 96 health centers, 7 primary hospitals, and 1 general hospital in the zone. According to the 2011 CSA, South Gondar zone has a total population of, 2,239,077 (female 1,103,490 male1, 135,587). And 2.8% of the total population is expected to be above the age of 65 years. A community based cross-sectional study was conducted from October 1-December 15, 2020.
Study participants, sample size and sampling techniques All old people aged ≥ 65 years old who were living in 3 randomly selected woredas of South Gondar Zone at the time of data collection were the study population. Those who were critically ill and those mentally incompetent were excluded from the study. The sample size was calculated using single population proportion formula. Taking the prevalence of under nutrition 21.9% (14), margin of error of 5%, Z value of 1.96 and taking 10% non-response rate the nal sample size was 290. First three woredas (geographic sub divisions of a Zone) were selected by lottery method from a total of 18 woredas; then census was conducted to enumerate the total number of elderly in each woredas. Then the calculated sample was allocated to each Woredas proportionally based on the number of elderly. Finally, systematic random sampling technique was used for the selection of individual respondents.

Assessment of under nutrition
The outcome variable, under nutrition was measured using Mini Nutritional Assessment (MNA) tool developed by Nestle Nutrition Institute. The MNA tool was validated in developing setting including Ethiopia (15). Based on MNA scores, elderly is categorized into non-malnutrition group (MNA [12][13][14], the group with risk of malnutrition (MNA of 8-11) and malnutrition group (MNA score ≤ 7) (16). In addition, BMI was calculated to determine the nutritional status of elderly. Arm span was used as a proxy measure for height in elderly. Thus, body mass index (BMI) was estimated as the weight in kg divided by arm span in meters squared (kg/m 2 ). Obesity was de ned ≥30.0 kg/m2., overweight was de ned as 25.0 kg/m 2 ≤BMI<29.9 kg/m 2 and underweight was de ned as BMI of less than 18.5 kg/m2 (4,13) .

Anthropometric measurements
Weight was measured in light clothes with bare feet using a beam scale (Seca®, Germany). Arm span was measured between the middle gure of one hand to the middle gure of other hand using a measuring tape (Seca®, Germany). The height and arm span accuracy were 0.1 cm. The anthropometric measurements were measured following a standard procedure (17). All measurements were done in twice, and the average value was used for analyses.

Assessment of predictors
In addition to anthropometric measurements and MNA assessment, place of residence, gender, age, economic status, marital status, occupation, educational status, illness in the past three months, food intake status, presence of known chronic disease, current medication intake, physical activity, dietary habits, 24hr dietary diversity score and alcohol consumption was assessed. The age of the elderly was de ned as age ≥ 65 years .Dietary diversity score was detected using 24 dietary recall method. Dietary diversity as categorized into poor (those who consumed less than 5 food groups out of 9 food groups) and good (those who consumed 5 or more food groups out of 9 food groups). Physical activity was de ned as doing any activities or exercise for more than 30 minutes (18).
Pretested and structured questionnaires using face-to-face interviewing with participants were used for data collection. The questionnaire was adapted from food and agriculture organization of united nation (19). Data were collected by three diploma nurses and supervised by two public Health o cers. A two days comprehensive training was given to data collectors and supervisors. The questionnaire was rst prepared in English and then translated into Amharic (the local language), and back into English to ensure consistency. To ensure the quality of the data, every day the questioner was reviewed for completeness, accuracy and clarity by the principal investigator.
Data processing and analysis The questionnaires were coded and entered into Epidata version 3.1 statistical software and then exported to SPSS windows version 25 for further analysis. Data were summarized and presented using descriptive statistics. Bi-variate and multiple logistic regressions were computed to identify the presence and strength of associations. Odds ratios with 95% CI were computed and variables having p-values less than 0.05 in the multiple logistic regression models were considered signi cantly associated with the outcome variable.

Results
Socio demographic and economic related characteristics of participants

Factors associated with under nutrition
On bivariate logistic regression; residence (living in rural area), sex, not being married, being unable to read and write, illness in the last three months, known chronic illness, decline in food intake and household monthly income <35.6USD were positively associated with under nutrition. Whereas, residence (living in rural area), being unable to read and write, decline in food intake and household monthly income <35.6USD were remained signi cantly associated with under nutrition on the multivariable logistic regression. The odds of under nutrition was more than 12 times higher among elderly who have history of decline in food intake (AOR= 13.471, 95%CI: 6.147-29.525). This study also showed that elderly whose monthly income less than 35.6USD were 4.3 times (AOR = 4.319, 95%CI: 1.971-9.460) more likely to be undernourished than their counterparts. Also, being unable to read and write increased the odds of under nutrition among the study participants (AOR = 3.542, 95%CI: 1.642-7.643). Study participants who lived in rural area were more than 10 times to be undernourished than those from urban area (AOR= 10.320, 95%CI: 3.624-29.390) ( Table 4).

Discussion
The This study pointed out that 89.31% of the elderly had poor dietary diversity score. This might be due to the study was conducted during fasting period, most of the participants were economically dependent and most of them were unable read and write.
This study has revealed that 25.52% of rural elderly people were malnourished in that participants who lived in rural areas were more than 10 times more likely to be undernourished than those from urban area.
Thus, it appears that under nutrition is much higher among the elderly residing in the rural areas. This nding is consistent with the results of studies conducted in wolaita zone Ethiopia (21), Northwest Ethiopia (22) and Ethiopia (23).
In the current study monthly income of less than 35.6USD had signi cant association with under nutrition. Similarly studies done in wolaita Zone Ethiopia (21), Northwest Ethiopia(22) and Ethiopia(23) showed that low income had negative effect on nutrition status of elderly. This might be due to food purchasing ability depends on the level of incomes and low income may make elderly to prefer not to eat.
Decreased food intake was positively associated with under nutrition. This could be due to the effects of increased age which reduces the natural drive to eat and drink and resulting in anorexia of aging; to their comorbid illness of which most of them had chronic illness and; to the medication they took since most of them took medications. This nding was similar to a study conducted in Wolaita Zone Ethiopia (21).
This study pointed out being unable to read and write was 3.5 times (AOR = 3.542, 95%CI: 1.642-7.643) more likely to be undernourished than those who can read and write. This nding is consistent with the results of earlier studies conducted in Wolaita Zone Ethiopia (21) and in Northwest Ethiopia(22) . This might be related to the fact that educated people are more likely to consume diversi ed food and follow healthy eating style.

Strength of the study
The study was community based and it can represent the population.

Limitation of the study
Page 8/17 The study did not assessed micronutrient level and fat composition of elderly.

Conclusion
The overall prevalence of under nutrition among the elderly in the study area was high making important public health burden. It was signi cantly associated with residence, being unable to read and write, decline in food intake and household monthly income. Therefore, there is a need to design and implement programs and strategies to improve nutritional status particularly focusing on female older population, those living in rural area and improving household economic status. For this, further studies are needed to generate a database for effective policy making and formulate a national policy on the nutrition of the elderly to ensure healthy aging. Then, the participants of the study were informed about the purpose of the study, the importance of their participation, and their right to withdraw at any time. All methods were carried out in accordance with ethical guidelines and regulations. Informed consent was obtained prior to data collection. To keep the con dentiality of clients' data, their names was not document. People aged ≥ 65 who were malnourished during the data collection were advised regarding their nutrition.

Consent to publish
All the authors have agreed and gave consent for the publication

Availability of data and materials
The datasets used during the current study are available from the corresponding author on a reasonable request.

Competing of interest
All authors declared that there is no competing interest at all.

Funding statement
The author(s) received no nancial support for the research, authorship, and/or publication of this article.
Authors' contributions HY, IM and MA made substantial contributions to conception and design, acquisition of data, or analysis and interpretation of data. GA, AE, MM and FT took part in drafting the article or revising it critically for important intellectual content. All authors agreed to submit to the current journal; gave nal approval of the version to be published; and agree to be accountable for all aspects of the work.