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Introduction: Madagascar has one of the highest prevalence’s of malnutrition worldwide. Dietary practice is an important element to consider in the fight against malnutrition. This study aims to describe mothers’ dietary patterns and dietary diversity and to identify characteristics associated with this dietary diversity. Methods: A cross sectional study was carried-out among 670 non-pregnant mothers aged 18 to 45, who had delivered more than 6 months earlier and were living in the Amoron’i Mania region of Madagascar. The study was conducted during the post-harvest period. A food frequency questionnaire were used to assess the dietary pattern and the women’s dietary diversity score was established from the 24-hour recall data. Results: Almost all (99%) of mothers ate rice every day and 59% ate green leaves. Fifty three percent of mothers had consumed fruit less than once per week, 55% for legumes, 67% for vegetables and 91% for meat. Dietary diversity score ranged from 1 to 7 and 88% of mothers had a low dietary diversity score (<5). On multivariate analysis, factors significantly associated with low dietary diversity were: low education level (AOR=3.80 [1.58-9.02], p=0.003), parity higher than 3 (AOR=2.09 [1.22-3.56], p=0.007), birth interval ≥ 24 months (AOR=4.01 [2.08-7.74], p<0.001), rice production availability ≤ 6 months (AOR=2.33 [1.30-4.17], p=0.013), low attendance at market (AOR=4.20 [1.63-10.83], p<0.001) and low movable property possession score (AOR=4.87 [2.15-11.04], p<0.001). Conclusion: Mother’s experience poor diet diversity. Unfavorable socioeconomic conditions are associated with this poor food diversification.
Study site: The study was conducted in the Amoron'i Mania region, one of Madagascar's 22 regions and located in the central highlands of the country. The Region comprises 4 health districts, 53 communes, of which 52 are located in rural areas, and about 580,000 inhabitants. Agriculture, mainly subsistence, was the main activity of the population [7]. This region has the highest undernutrition (BMI<18.5 kg/m²) prevalence among women of reproductive age in Madagascar. It was estimated at 41.6% in the last DHS results in 2008-2009 [6]. The study focused on rural areas where undernutrition issues are much more prevalent [6]. Study population: A cross sectional study was carried out. The study population included non-pregnant mothers between 18 and 45 years of age who had given birth more than 6 months earlier. Mothers under 18 years old were not included because of the difficulty in getting the guardian's consent. Mothers over 45 years old were not included in order to include mothers within the reproduction age group, knowing that the fertility rate is very low for women between 45 and 49 years old [6]. To ensure the validity of weight measurements, we also excluded women who had given birth within the last 6 months. Indeed, there is a gradual reduction of pregnancy weight gain and stabilization of mothers' weight around the sixth month after deliveries [8,9]. Sampling: A two-stage cluster sampling was used. The first stage aimed at selecting 30 “fokotany” (the smallest administrative structure) out of the 760 in the Region. It was done by systematic random sampling. The second stage was used to select, for each “fokotany”, eligible mothers from a list established by community workers. This was done by simple random sampling. Sample size was calculated on the basis of the national prevalence of maternal undernutrition (27%), with a 5% margin of error, 95% confidence level and a design effect of 2 [10]. The sample size was estimated to be 606. Twenty-one subjects per cluster therefore had to be included. During data collection, 670 women were actually interviewed. Data collection: Data collection was conducted in July and August 2015, during the post-harvest (rice harvest) period in the region. Regarding mothers' dietary practice, two methods were used: a 24-hour recall method for mothers' dietary diversity assessment and a food frequency questionnaire for measuring dietary practice during the post-harvest period. For the 24-hour recall, interviewers asked and established the list of all food eaten by the mother the day before the survey. To minimize omissions, they focused on food intake based on the pre-established list to assess women's dietary diversity. Information about the place and the people with whom the mother ate the meal as well as the occurrence of an unusual event during the day before the survey was collected to detect unusual food consumption [11]. As for the food frequency questionnaire, it takes into account the last 3 months before the survey. This rather long period of time was chosen to have an idea about diets during the harvest period and to take rarely consumed food (less than once per month) into account. Nutritional status was assessed by use of the following anthropometric measurements: height, Body Mass Index (BMI), Mid Upper Arm Circumference (MUAC) and by hemoglobin measure for anemia. Interviewers were recruited locally. They had a bachelor's degree and were fluent in the local dialect. Samples management and transfers were dealt with by nurses working in the laboratory. Data collectors received training according to their mission. The investigator, a technician from the Nutrition Department of the Ministry of Public Health and the nutrition regional manager supervised the data collection. The study was approved by Malagasy Ministry of Health's Ethics Committee. Dietary practice: Dietary diversity score: for each woman, the consumption of 10 food groups was established from the 24-hour recall data. The consumption of one or more foods in one group was worth 1 point and the maximum score was 10. Afterwards, the score was categorized into two groups: lower than 5 and higher than or equal to 5. A score of five represents the lower limit which assures the qualitative nutrition need [12]. List of 10 food groups for the dietary diversity score of women [12]: 1) All starchy staples; 2) Beans and peas; 3) Nuts and seeds; 4) All dairy; 5) Flesh foods (including organ meat and miscellaneous small animal protein); 6) Eggs; 7) Vitamin A-rich dark green leafy vegetables; 8) Other vitamin A-rich vegetables and fruits; 9) Other vegetables; 10) Other fruits. Food consumption frequency was categorized into 4 groups: none, less than once a month, 1 to 4 times per month and more than once a week. Nutritional status: The BMI was calculated by dividing weight in kilograms by height in square meters. Hemoglobin rate was adjusted for altitude [13]. World Health Organization (WHO) defined standards were used to identify undernourished women, i.e. BMI below 18.5 kg/m², height below 145cm, and MUAC below 220cm and women affected by anemia (hemoglobin < 120 g/l) [8,13]. Social profile: Mother's age, education level (last school year taken into account), occupation, marital status and husband's occupation were collected. Information about number of pregnancies, parity, number of children aged less than 5 years old, breastfeeding and birth interval were collected. The birth interval was calculated for the last two deliveries within the last five years. Afterwards, that interval was grouped using a 24-months threshold. Mothers who did not have two childbirths within the last five years and three primiparous women were classified in the 24 months or more group. Economic profile: Three indicators of economic level were created considering the possession of household goods. We used the DHS Madagascar list to establish our list of goods. The first indicator refers to possession of movable property (furniture, radio, TV, telephone, bicycle, etc.), the second refers to possession of farming equipment and the third to possession of farm animals. The corresponding scores for these properties were established by principal components analysis (PCA). The scores were categorized into three groups (high, medium and low) based on values as close as possible to the tertiles. The period (number of months) in which a household consumes its annual rice production was also collected. It was divided in two groups with a 6 months threshold. Rice production is considered as an indicator of food security in study areas and can reflect the economic level of households. Two categorical variables on market access were defined: the number of times the household goes to the market (3 categories) and the time it takes to go to the nearest market (3 categories). Data analysis: Stata/IC 13.1 (StataCorp LP, College Station, USA) software was used to analyze the data. In bivariate analysis using logistic regression, the link between low dietary diversity (Dietary Diversity Score <5) and other variables was estimated by the Odds Ratio (OR) with its confidence interval and chi-square or chi-square for trend tests were used. Variables with a p-value <0.20 in bivariate analysis were considered for inclusion in a logistic regression model. A stepwise backward method was used for selection of statistically significant covariates. Variables with more than two categories were transformed into indicators. The backward procedure used to select variables in the final model was based on the likelihood ratio. The adequacy of the final model was checked using Hosmer Lemeshow test. The adjusted OR (AOR) and their 95% confidence intervals were computed from the final logistic model. The significance level (p-value) was set at 0.05.
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