Study Area and Period
This study was conducted in Harari region, Eastern Parts of Ethiopia. Harar is found 526km from Addis Ababa, capital city of Ethiopia. According to the Ethiopian central statics authority’s 2007 report, Harari region has a total population of 183, 344 of whom 92,258 were men and 91,086 women and majority of its population lives in 99,321 or 54.17% of the population lives in urban (CSA 2007 report). Ethnic groups in the region include the Oromo (52.3%), Amhara (32.6%), Harari (7.1%) and others like Tigre and Guraghe etc. According to 2010 Harari Region population projection there are 250, 093 with 146, 913 living in urban and 122, 942 are male with total house hold of 64, 334.
Based on the study Ethiopian demography 2018 , in Ethiopia 2.91% are elderly. Using this conversion factor the expected number of elderly was calculated. This Quantitative cross sectional study was conducted from March 01 to 30, 2019.
Population and eligibility
All peoples age >=65 years of age in Harar region were the target population for this study to which the result is considered to be applied. While, those randomly selected people age greater than or equals to 65 years from the selected kebeles, were study population and included in the current survey. Those community dwellers aged above or equals to 65 years with or without their care givers residing in the selected kebles (lower administrative unit in Ethiopia) were included in the current survey. Those elderly who have no any caregiver and unable to communicate and give information were excluded from the study as we are unable to get reliable data from them. In addition, those who were not volunteers to take part in the survey were also excluded from the study. Study subjects with severe spinal curvature (kyphosis or scoliosis), both extremities amputation were not included in the study.
Sample size determination
To determine the minimum sample size for the first objective, single proportion samples size formula with P as prevalence of malnutrition from the previous study (21.9) , 95 % confidence level, “Z” critical value at 95% CI and marginal error of “d” 5% and became 263. (see Formula 1 in the Supplementary Files)
For factors associated with malnutrition the sample size is determined using OpenEpiSave software for cross sectional survey taking empirical statistics like odds ratio, proportion of exposed with malnutrition and power of 80%, with ratio of exposed to non-exposed as 1 and 5% level of significance. Taking the larger sample size calculated from objective two (286), design effect of 2, and 10% non-response rate, the final sample size was (572+0.1(572)) = 630. Thus, this study tried to interview and include 630 study subjects (elderly).
Multi stage sampling was used to select eligible elderly peoples from randomly selected Kebles from each Woreda. Then from each selected woredas using simple random sampling, we select two Kebles randomly from each woreda. Then the sample size was proportionally allocated for each respective selected woredas and then to the selected Kebles. Then, the data collector located the center of the kebeles and then randomly select a random direction using random spinning a pen. Then all HHs with elderly people were interviewed in that selected direction until the sample size is achieved. However, when the required sample size is not achieved, another random direction were selected in the similar way and data collected similarly.
Methods of data Collection
Data were collected using set of structured questionnaires including Socio demographic situations, Full Mini nutritional Assessment, Geriatrics Depression scale, psycho social issues and others. Data were collected by trained graduating health science students from house to house visit. Data collectors got the data by interviewing either their care giver if the subject is unable to communicate or the study subject directly in their local languages in Amharic, Harari, or Affan Oromo.
The full MNA tool is worldwide validated too with 80% specificity and 90% sensitivity making it as the best, effective, affordable and quick malnutrition screening tool among elderly. It has also showing greater importance in identifying over malnutrition and risk of malnutrition early, for effective public Health Interventions. Thus the full MNA tool was contextualized, translated to Amharic and pretested before data collection.
The weight of the subjects were measured using calibrated electronic weighting scale to the nearest 0.1kg. The height was measured using adult stadiometre for those who can stand. While for those who are unable to stand the Arm span from the sterna notch to tip of finger or knee height was to be used as proxy indicator for height of the subjects using specific formula for the specific sex, ethnic group. The BMI was calculated by dividing the weight in Kg by the height in m square and was expressed in kg/m2. However when the height measurement is not possible, calf circumference was used instead of BMI and the status was classified according to the nestle recommendations.
The mid upper arm circumference (MUAC) was measured using non-stretchable tape meter on the left arm at midpoint between the acromion process of clavicle and elbow joint. It was measured in arm extended and recorded in centimeter. Short twenty four hour dietary recall was used to assess the dietary intake pattern of the clients, as it reduce the recall bias secondary to memory lapse.
The Geriatric depression score was used to assess the psychological condition off the elderly. A fifteen item depression scale assessment were used by direct interviewing the respondent. This tool has shown almost equal sensitivity in identifying depression level which have direct influence on malnutrition among elderly.
Data Quality Assurance
Pair of trained graduating health students were employed to collect the data from study subjects as anthropometric measurement need curiosity and two individuals during measurement. Two day training appropriate interview techniques, anthropometric measurements like height and weight, practices were performed before actual data collection. After that constructive feedbacks were given for the data collectors by investigators and supervisor until they become clear of the checklist implementation. Anthropometric reliability assessment were done on 10 study subjects and inter and interobserver variation were calculated. Cranach’s Alpha measure of reliability used and kappa above 0.7 were considered acceptable and all within the acceptable range. All standard measuring procedures and instruments were strictly followed while data collection. During data entry in to EpiData the data quality was kept by making legal ranges, skipping patterns, appropriate coding and careful data entry. The intra observer and inter observers technical error of measurement were calculated after training of the data collectors and supervisors, to measure the reliability of the weight and height anthropometric measurements.
Methods of Data Analysis
After checking for completeness ad inconsistencies, the collected data were entered in to EpiData Version 3.02 and Exported to SPSS version 20.0 for analysis. The data is presented in tables, graphs, percentages, frequencies, mean, medians and standard deviations. After measurement of weight and height, body mass index was calculated automatically. Similarly geriatric depression score was computed using the compute command. The outcome variable malnutrition status was categorized as those with malnutrition, at risk of malnutrition and normal nutritional status based on the overall sum score of each subject. Malnutrition was assessed using the full MNA score (out of 30) and calculated using the compute command in SPSS. Those who scored below 17 (malnourished), 17 to 23.5 (at risk of malnutrition) and otherwise normal . At the same time the GDS was calculated using 15 items yes or no (1- yes for the presence of one of the depression symptoms. A GDS of 10 to 15 were considered as severe while, 5 to 9 as mild depression and no depression otherwise.
Then both bivariate and multivariable ordinal logistic regression were conducted using crude and adjusted odds Ratio at 95% confidence interval reported. The odds ratio corresponding to each variable were calculated using PLum command and by exporting the result to excel as needed. Those variables with P value less than 0.20 and important predictors in bivariate analysis were taken to multivariable ordinal logistic regression analysis. P value less than 0.05 at multivariable analysis were declared as statistically significant association.
Nutritional status of elderly (ordinal scale) was the dependent variable whereas, demographic variables (age, sex, income, occupation, pension, education, and parental support), smoking, depression, appetite, chronic disease, oral health problems and physical exercise were independent variables.
Ethical clearance was taken from Dire Dawa University Research and Technology Interchange directorate. Then, it was forwarded to Harari health bureau then to respective woredas and Kebles. Verbal informed consent were obtained from the respondents who are able to give consent otherwise it will be taken from caregivers or their parents. The data is used only for this research only and also in the future. Personal identification of clients like name, personal location and others were not be recorded. For those having severe malnutrition, nutritional counseling were done. In addition, counseling in order to have health care service in the nearest health facility were advised in advance for them and caregiver.