The study was conducted in Hawassa city from 28th April to 21th June, 2012. A descriptive, cross-sectional study design was employed among 548 community dwelling elderly. Simple random sampling method was employed to select eligible elderly after preparing sampling frame prior to the study. Age (≥60 years), informed writtenconsent, living for more than six months in study area and ability to communicate during the interview were considered as inclusion criteria. All elderly people (≥60 years) who were having visible deformity of upper or lower extremities were excluded from the study. Ethical clearance was taken from Hawassa University, Health Science College ethical review board.
Assessment of nutritional status
Mini Nutrition Assessment (MNA) was administered to five hundred forty eight eligible elderly after validation of the tool. The tool was validated against BMI. BMI was used for validation instead of dietary intake or clinical data because there existsrecall bias in case of dietary data and limitation of getting high quality and full clinical data.
All interviews from MNA tool regarding the nutritional and health conditions, functional independence, quality oflife, mobility, cognition and subjective health were assessed by trained nurses as per the standard stated in the original MNA tool [12]. As a component of the full MNA, all anthropometric measurements (weight, height, mid upper arm circumference and calf circumference) were measured on the non-dominant arm and leg. Weight was recorded to the closest 0.1 kg with the subject in light dress and shoeless utilizing an electronic weight scale adjusted with 1 kg standard weights after every estimation. Height was recorded to the closest 0.1 cm utilizing a stadiometer after the subject standing erect and looking straight ahead with heels, buttocks and shoulders pressed against the stadiometer. Demispan measurement was used by quantifying the distance from the midline at the sternal notch to the web between the middle and ring fingers along outstretched arm whenever participants were unable to stand on the stadiometer. Height is then calculated using a standard formula (females height in cm = (1.35 × demispan in cm) + 60.1 and males height in cm = (1.40 × demispan in cm) + 57.8) [18]. Mid Upper Arm Circumference (MUAC) was measured to the nearest 0.1 cm at the mid-point between the tip of the acromion and the olecranon process on the back of the arm while the subject holding the forearm in horizontal position. The measurement was performed on the subject’s arm hanging freely along the trunk using inextensible MUAC tape. The widest calf circumference was measured between the ankle and knee to the nearest 0.1 cm using non stretchable tape in a sitting position with the leg bent 90° at the knee and manipulated to maintain close contact with the skin without compression of underlying tissues. Body Mass Index (BMI) was calculated as body weight in kilograms divided by the square of height in meter.
Statistical analysis and interpretation
All analysis was performed using SPSS statistical software package version 16.0. One sample Kolmogorov Smirnov test was used to check the distribution of continuous variables. Descriptive frequencies were used to look for overall distribution of the study subject with the variables under study.
Reliability of the MNA wascalculated using coefficient of Cronbach’s α and a Cronbach’s α value of 0.60, 0.70 & 0.80 were considered acceptable, adequate and good respectively [19]. Moreover, the internal consistency (reliability) of the MNA tool was evaluated after checking Spearman’s rank association between total MNA score and every items of the MNA after omitting each item in every correlation [20].
Criterion-related validity of the MNA tool was evaluated after checking a significant positive Spearman’s rank association between total MNA score and single anthropometric measurements. Besides, the concurrent validity of the tool was checked after identifying a significant positive Spearman’s rank correlation between total MNA score and self-perceived nutritional status [21]. Spearman’s rank correlation was also used to correlate categorical BMI as in the MNA tool and total MNA score while Pearson’s correlation was used to check correlation between total MNA score and the continuous variable BMI.
Finally, the construct validity of the MNA tool to identify malnutrition and at risk for malnutrition in the elderly population was assessed using receiver-operating characteristic (ROC) curve which computes the sensitivity & 1 - specificity of the tool using BMI < 18.5 kg/m2 as a marker of malnutrition [21]. The area under the ROC curve (AUC) was evaluated to determine overall accuracy of the MNA and a bigger AUC symbolizes a better reliability. Youden index (Sensitivity + specificity _ 1) was used to conclude the best cut-off point of MNA [22].