Browsing by Subject "Farmer"

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Integration von tiergesundheitsrelevanten Daten in betriebliche Managemententscheidungen
(2010) Fick, Johanna; Doluschitz, Reiner
For many years agriculture in Germany has been subject of changes due to economic, technical and social developments. These changes are structural, market and environmental induced. Livestock owner may react with increasing turnover and/or cost reduction to face the changes and to achieve sustained success in livestock farming. Expenditures for veterinarian and pharmaceuticals in dairy farming have a large share in the expenditures. Furthermore revenue losses due to animal diseases have to be added to the costs. Strategies to reduce costs and revenue losses can only lead to success if farmers and veterinarians act jointly. Basis for this can be an established digital information exchange between the process partners. Existing data of the process participants are used, consolidated and analysed in such a digital information exchange. Previous activities to improve the animal health were mostly partial solutions of individual members of the process chain. These are partial solutions due to the fact that the existing data are not brought together and that the use as an entity is not possible. The available software merges the animal health data and the animal performance data merely partial. The target of this research focuses on the integration of relevant data on animal health in operating management decisions by conception and development of an IT-model. This IT-model links relevant but distributed, incomplete, and redundant animal health data of the process participants (farmer, veterinarians, and professional associations) in livestock farming. So this contribution shall improve the use of animal health and animal performance data. Thereby issues of veterinary medicine and dairy farming will be joined by using information technology (IT). The procedure is structured in drafting the principles, an analysis of the status quo, and a market- and potential analysis consisting the use and application of sector software by farmers and veterinarians. It is followed by the conception and development of the animal health system and the conception of the implementation with a first product test. To answer the research questions of this paper a process model has been developed which was used as methodical frame. Different explanation strategies were necessary and therefore qualitative and quantitative methods of social research were used.
Nutritional and hemoglobin status in relation to dietary micronutrient intake: studies in female and male small-scale farmers from Lindi region, Tanzania, and Gurué district, Mozambique
(2024) Eleraky, Laila; Frank, Jan
Inadequate consumption of micronutrient-dense and protein-rich foods, such as vegetables, legumes and meat, are important contributing causes for malnutrition, anemia and micronutrient deficiencies in rural communities of Tanzania and Mozambique. The increasing public health concern of the malnutrition form of overweight has repeatedly been reported in urban as well as rural areas of Sub-Sahara Africa and may have already reached farmers in Tanzania and Mozambique. Nutritional status is assessed by anthropometry, dietary intake and hemoglobin. Compared to the often-used body mass index (BMI) and traditional 24-hour recall, the mid-upper-arm-circumference (MUAC), as well as a food group-based algorithm (CIMI) can be suitable additional assessment tools, especially in resource poor environments. Cross-sectional studies within the framework of the Vegi-Leg project were conducted to assess the nutritional status (anthropometrics and hemoglobin measurements), and the dietary behaviours (Household Dietary Diversity Scores (HDDS), Food Frequency Questionnaires (FFQ) and 24-hour recalls) of female and male farmers from rural areas of Tanzania and Mozambique. Data were analysed by region, sex, age, partly season (Tanzania)and correlates. Additional data from similar projects, namely Scale-N and Trans-SEC in rural villages of Tanzania were included in MUAC and CIMI analysis. MUAC as an additional and easy-to-handle anthropometric marker for underweight, as well as overweight was evaluated using data from Vegi-Leg and Scale-N surveys. MUAC cut-offs, calculated via BMI cut-offs and multiple linear regression (MLR), compared to those selected by highest Youden’s index (YI) value, were assessed. The CIMI algorithm included 23 food groups and was tested in comparison to NutriSurvey (detailed quantitative 24 hour recalls) with data from Scale-N and Trans-SEC.A total of 1526 farmers from the Vegi-Leg project (669 from Tanzania, 857 from Mozambique) were studied, of whom 19% were overweight and 35% were anemic. The study showed an overall higher prevalence of overweight (19%) than underweight (10%), mainly due to the high prevalence of overweight female farmers (up to 35%) in southern Tanzania. The highest prevalence of overweight and anemia, at 35% and 48%, was observed in Tanzanian and Mozambican women, respectively. Regarding HDDS and FFQ data, pigeon pea farmers in Lindi and Gurué reported high consumption frequencies of cereals, legumes, vegetables and oil, while meat, fish and eggs were only consumed rarely. Overall, only a small proportion of enrolled women and men reached the recommended daily dietary intake of vitamin A (10%), iron (51%) and zinc (44%) according to the 24-hour recalls. 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 the dominant sources of vitamin A. Cereals contributed to over half of the iron and the zinc intake in both countries. Seasonal analysis revealed high fluctuations for the consumption frequency of food items from the food groups ‘legumes and pulses’, ‘green leafy vegetables’, ‘other vegetables’ and ‘fruits’, including tomatoes, pigeon peas, mangoes and oranges. The results from Lindi Tanzania revealed, that in seasons, when the availability of food groups like fruits, legumes or vegetables was low, the consumption frequency decreased significantly. BMI, which correlated positively and strongly with MUAC, was higher in Tanzania than in Mozambique and higher among female than male farmers, and decreased significantly from the age of 65 years. MUAC cut-offs of <24 cm and ≥30.5 cm, calculated by multiple linear regression, 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 Youden’s Index, consequently detected more underweight (80%) and overweight farmers (91%), but on the basis of a lower specificity (87–88%). The results of the algorithm CIMI and NutriSurvey were similar with regard to the average intake and range of data distribution. The correlation coefficients of NutriSurvey and CIMI with regards to energy (0.931), protein (0.898), iron (0.775) and zinc (0.838) intake, supported the matching of both calculations. An increased consumption of micronutrient rich DGLVs and legumes, while reducing the high amounts of refined sugar, maize and polished rice, is suggested to counteract the high prevalence of anemia and overweight among smallholder farmers in rural Tanzania and Mozambique. MUAC cut-offs to detect malnutrition whether defined via linear regression or Youden’s Index, proved to be easy-to-use tools for large-scale rural screenings of both underweight and overweight. The food group based CIMI algorithm is a valid instrument that calculates energy and nutrient intake in agreement with the preferred nutrition software NutriSurvey.