Background: The Ethiopian regions have a relatively higher prevalence of under-nutrition are found in the lowlands of the country, with the exception of the highlands of Tigiray, where under-nutrition is also prevalent. The intention of this study was to compare anthropometric nutritional status and associated factors of lactating women between lowland and highland communities of district Raya Alamata, Southern Tigiray, Ethiopia. Methods: A community based comparative cross-sectional study design was conducted from January 27-March 7, 2014. Sample size was determined by two population estimation formula. The total calculated sample size was 456. A stratified sampling technique was used to stratify the study area to highland and lowland. Study participants were selected by simple random sampling technique. Data were collected using anthropometric measurements and structured questionnaire. The raw data were entered and analyzed using SPSS version 20.0. Bivariate and multivariable Logistic regression was done to determine the association between explanatory variable with chronic energy deficiency (CED) using body mass index (BMI), by computing odds ratio at 95% confidence level. A P – value <0.05 was considered as statistically significant. Result: The prevalence of CED of lactating mothers from lowland and highland was 17.5% and 24.6% respectively. After multivariable logistic regression: age, husband occupation, taking vitamin A immediately after delivery or within the first 8 weeks after delivery and consumption of extra food during lactation time were factors associated with chronic energy deficiency for lowland lactating women whereas parity, number of meals per day and household consumption of iodized salt were factors associated with chronic energy deficiency for highland lactating women. Conclusion: CED in both comparative studies were a serious public health problem. As it is known food security does not mean nutritionally secured, Therefore, the need to develop nutrition intervention such as nutrition security programs to address under-nutrition in the study area is significant, as it was found food secured participants were slightly vulnerable than food insecure. The dietary diversity score of the participants were very low so that encourage the community about nutrition diversification is substantial for adequate nutrient intake.
The study was conducted in district Raya Alamata. It is one of the districts in the Tigiray Region of Ethiopia. It is located 600 km north of Addis Ababa and about 180 km south of the Tigiray Regional capital Mekelle. Altitude in the area ranges from1178 to 3148 m. 75% of the district is lowland (1500 m above sea level or below) and only 25% is found in intermediate highlands (between 1500 and 3148 m above sea level). Shortage of rainfall is a major constraint of agricultural production in the district. Based on the 2007 national census conducted by the Central Statistical Agency of Ethiopia (CSA), this district had a total population of 85,403, of whom 42,483 were men and 42,920 women. The study period was from January 27–March 7, 2014. The study design was community based comparative cross sectional survey. The Sample size was determined using two population estimation formula, that is were P = (P1 + P2)/2, pooled estimation of P1 and P2, Z is the value of standard normal distribution which is 1.96, P1 and P2 is estimated prevalence of chronic energy deficiency that is 31% and 19.1% in the lowland and highland respectively [14]. Assumptions were 95% confidence level, 5% marginal error, Power (1-β): 80%, Non-response rate: 10%. Therefore, the total calculated sample size was 464. Stratified sampling technique was used to stratify the study area in to lowland and highland. The district has a total of fifteen lowest administrative levels (Kebeles). Among these lowest administrative levels, ten of them were lowlands and five of them were highlands. Since the purpose of this study is to compare the two groups, thus three lowest administrative levels (kebeles) from highland and lowland were selected. The total calculated sample size 464 was shared equally into two; 232 for the lowland and 232 for the highland participants. The two divided sample sizes were distributed to each selected lowest administrative levels (kebeles) using proportional allocation to size (PAS). Finally participants were selected by simple random sampling technique. Structured questionnaire was prepared from related literatures, and the questionnaire was translated to local language Tigrigna. It was administered to the participants by health professionals who are fluent speakers of the local language. The dietary diversity of the lactating women was collected using women dietary diversity score (WDDS). It is a simple count of food groups that an individual has consumed over the preceding 24 h. It is calculated by summing the number of food groups consumed by the individual respondent over the 24-h recall period. WDDS uses the following nine food groups: starchy staples, dark green leafy vegetables, vitamin A-rich vegetables and fruits, other fruits and vegetables, organ meat, flesh meat and fish, eggs, dairy, and legumes and nuts [15]. Study participants were asked whether or not they had eaten each food group over the last 24 h. The cut off point for the micronutrient adequacy of women’s diet is consumption of at least five of ten food groups [16]. Household food insecurity of study participants was collected using household food insecurity access scale (HFIAS). It is the measure of the degree of food insecurity in the household in the past 4 weeks (30 days). It consists of two types of related questions. The first question type is called an occurrence question. There are nine occurrence questions that ask whether a specific condition associated with the experience of food insecurity ever occurred during the previous 4 weeks (30 days). Each severity question is followed by a frequency of occurrence question, which asks how often a reported condition occurred during the previous 4 weeks. There are three response options representing a range of frequencies (1 = rarely, 2 = sometimes, 3 = often). HFIAS score is calculated for each household by summing each frequency of occurrence question. The maximum score for a household is 27 (the household response to all nine frequency of occurrence questions was “often”, coded with response code of 3); the minimum score is 0 (the household responded “no” to all occurrence questions, the higher the score, the more food insecurity the household experienced. The lower the score, the less food insecurity a household experienced [17]. Then the households were classified as most food secure scores of 0–11; medium food secure = 12–16; and least food secure = 17 or more [18]. Weights of the lactating women were measured to the nearest 0.1 kg with weight measuring scale (Prestige Model) and heights were measured to the nearest 0.1 cm using a wooden height-measuring board with a sliding head bar. During anthropometric measurement Calibrated equipment and standardized techniques [19] was used to take anthropometric (body) measurements on the lactating women. The measurements were taken with the women wearing light clothing and no shoes to minimize error. Weighing scales were checked before and after each measurement for their accuracy by an object with known weight. Pre-test was carried out 5% of the sample size. During data collection data collectors were strictly follow standard measuring procedure to measure height and weight. Questionnaires were checked for their completeness every day after data collection. For data collectors regular supervisions and follow up were carried by supervisors and principal investigator. The diagnostic criteria for chronic energy deficiency were based on BMI which was calculated as weight in kilograms divided by the square of height in meters (kg/m2). It was classified according to WHO classification, BMI 30 kg/m2) were not considered having chronic energy deficiency. The raw data were coded, entered, cleaned and analyzed using SPSS version 20. The 95% confidence level was used in significance analysis. The association between each explanatory variable with dependent variable was examined through bivariate analysis, by computing odds ratio at 95% confidence level. Variables from bivariate analysis were selected and transferred to multivariable logistic regression by using preset p-value of <0.25 [20]. To identify factors associated with outcome variables, multiple logistic regressions at 95% confidence level was used. A p-value 5 was used as cutoff point [20]. The final model was then tested for its goodness of fit by Hosmer and Lemeshow p-value and a p-value >0.05 was best fit. Maternal chronic energy deficiency was measured using maternal BMI which was calculated as weight/height2 (kg/m2); BMI < 18•5 kg/m2 was considered to be underweight, while ≥18.5 kg/m2 was considered as normal weight. For the purpose of analysis CED was taken as a dichotomous measure based on body mass index cutoff <18.5 kg/m2 and above. Since the interest is in identifying women at risk of underweight, the dependent variables were coded as 1 if the woman was underweight (BMI < 18.5 kg/m2) and coded as 0 if not.
N/A