Potentials and limitations of a food group-based algorithm to assess dietary nutrient intake of women in rural areas in Tanzania.

The aim of this study was to evaluate the accuracy of nutrient intake assessment with the food group-based algorithm "Calculator of Inadequate Micronutrient Intake" (CIMI) in comparison to the established nutrition software NutriSurvey. Using Food Frequency Questionnaires and 24-h dietary recalls of 1010 women from two rural districts in Tanzania, 23 relevant typical Tanzanian food groups were identified and subsequently the dietary protocols assessed via CIMI algorithm were compared by bivariate correlations and Bland-Altman analysis with the results of the NutriSurvey software (reference) and were set in relation to blood biomarkers of 666 participants. CIMI and NutriSurvey calculations regarding macro- and micronutrient intakes were similar. The Bland-Altman analyses and correlation coefficients of energy (0.931), protein (0.898), iron (0.775) and zinc (0.838) confirm the agreement of both calculations. The food group based CIMI algorithm is a practical tool to identify the inadequacy of macro- and micronutrient intake at population level.

Anthropometrics, Hemoglobin Status and Dietary Micronutrient Intake among Tanzanian and Mozambican Pigeon Pea Farmers.

Inadequate consumption of micronutrient-dense and protein-rich foods such as vegetables, legumes and meat is an important contributing cause for anemia and deficiencies of vitamin A and iron in rural communities of Tanzania and Mozambique. A cross-sectional study was conducted to assess the nutritional status (anthropometrics and hemoglobin) and diets in particular micronutrient intake of female and male pigeon pea farmers from Lindi, Tanzania, and Gurué, the Zambézia province of Mozambique. A total of 1526 farmers (669 from Tanzania, 857 from Mozambique) were studied, of whom 16% were overweight and 35% were anemic. The highest prevalence of overweight and anemia, at 35% and 48%, was observed in Tanzanian and Mozambican women, respectively. Overall, only a small proportion of women and men reached the recommended daily dietary intake of vitamin A (10%), iron (51%) and zinc (44%). Multiple regression models revealed that dark green leafy vegetables (DGLVs) highly predicted vitamin A intake, whereas legumes in Tanzania and starchy plants in Mozambique were actually the dominant sources of vitamin A. Cereals covered over half of the iron and the zinc intake in both countries. An increased consumption of micronutrient-rich DGLVs and legumes, while reducing the high amounts of refined maize or polished rice, is suggested to counteract the high prevalence of anemia and overweight among smallholder farmers in East and South Eastern Africa.

High Prevalence of Overweight and Its Association with Mid-Upper Arm Circumference among Female and Male Farmers in Tanzania and Mozambique.

The increasing prevalence of overweight/obesity may already have reached the farmers in Tanzania and Mozambique. Here, the measurement of the mid-upper-arm-circumference (MUAC) could become a simple and sensitive tool for early detection of at-risk groups of overweight as well as underweight. Body Mass Index (BMI) and MUAC of female and male farmers (n = 2106) from different regions of Tanzania and the Zambézia province, Mozambique, were analyzed by region, sex, age, and correlates. MUAC cut-offs, calculated via BMI cut-offs (<18.5, ≥25, and ≥30 kg/m2), and multiple linear regression (MLR), compared to those selected by highest Youden's index (YI) value, were assessed. The study showed an overall higher prevalence of overweight (19%) than underweight (10%) due to the high number of overweight female farmers (up to 35%) in southern Tanzania. BMI, which was mainly and positively predicted by MUAC, was higher in Tanzania and among female farmers, and decreased significantly from the age of ≥65 years. MUAC cut-offs of <24 cm and ≥30.5 cm, calculated by MLR, detected 55% of farmers being underweight and 74% being overweight, with a specificity of 96%; the higher cut-off <25 cm and lower cut-off ≥29 cm, each selected according to YI, consequently detected more underweight (80%) and overweight farmers (91%), but on the basis of a lower specificity (87-88%). Overweight was evident among female farmers in East Africa. MUAC cut-offs, whether defined via linear regression or Youden's Index, could prove to be easy-to-use tools for large-scale screenings of both underweight and overweight.

Consumption of Dark Green Leafy Vegetables Predicts Vitamin A and Iron Intake and Status among Female Small-Scale Farmers in Tanzania.

Inadequate consumption of micronutrient-dense foods such as vegetables and meat are an important contributing cause for anemia and deficiencies of iron and vitamin A in rural communities of Tanzania. A cross-sectional study was conducted in 2016 to examine nutritional and micronutrient status and their associations to the diet of female small-scale farmers in the sub-humid Kilosa (n = 333) and the semi-arid Chamwino (n = 333) districts, in the Morogoro and Dodoma region. An overall higher prevalence of overweight (19.7%) and obesity (7.1%) than of underweight (5.9%) was detected. Significantly more women in the two villages of Kilosa (27-40%) than in the two villages of Chamwino district (19-21%) were overweight/obese, but also more frequently had anemia (34-41% vs. 11-17%), iron deficiency (24-32% vs. 15-17%), and low serum retinol (21-24% vs. 8-9%). Overall, only a small proportion of women reached recommended daily micronutrient intakes: 27% for vitamin A, 17% for iron, 7% for zinc, and 12-38% for B-vitamins. The amount of dark green leafy vegetables (DGLV) consumed was the main determinant of vitamin A and iron intake by women in Chamwino and corresponded to higher hemoglobin, serum retinol and iron status than in the villages of the Kilosa district; in agreement, DGLV consumption also predicted iron and vitamin A intake in Kilosa district. DGLV consumed with wholemeal millet was advantageous in terms of women's vitamin A and iron intake and status over the predominantly maize-rice-based diet lacking vegetables.

Prevalence of food insecurity among food bank users in Germany and its association with population characteristics.

The prevalence of food insecurity (FI) among food bank users in many European countries is unknown. The study aims to examine FI prevalence and associated population characteristics among this particular group of disadvantaged people in Germany. Food insecurity status was assessed among 1033 adult food bank users with a mean age of 53 years (57% female, 43% male) in Germany in 2015 using the food insecurity experience scale (FIES). About half of the participants (55.8%) were single with no children and born in Germany. Over 37% had a self-reported BMI of 30 kg/m2 or above and 37.4% indicated to smoke. Over 70% of the food bank users can be described as food insecure. Of those, about 35% were considered mildly food insecure. Almost 30% were categorized as moderately food insecure while over 7% were categorized as severely food insecure. Significant associations with food insecurity were found for gender, age, subjective health status, smoking, duration of food bank use, school education and family type. Among this socially disadvantaged population, food insecurity is highly prevalent and public health efforts should be focusing on this vulnerable population taken into account the identified population and behavioral characteristics associated with food insecurity.

Migration Background Influences Consumption Patterns Based on Dietary Recommendations of Food Bank Users in Germany.

People with low income tend to eat less balanced than people with higher income. This seems to be particularly the case for people with migration background. This cross-sectional study examined the relation of consumption patterns of 597 food bank users with different migration background in Germany. Questionnaires were distributed assessing sociodemographic information and consumption patterns. Analyses were conducted using binary logistic regressions. Models were controlled for age, gender, type of household and education. The group of German food bank users consumed fewer fruits and vegetables and less fish compared to all other groups with migration background (former USSR, Balkan region, Middle East). A significant predictor for fruit and vegetable consumption was migration status. Participants from the former USSR consumed less often SSBs compared to the other groups. Dietary recommendations for low income populations should take into consideration other aspects besides income such as migration status.