3 resultados para random coefficient regression model
em Bioline International
Resumo:
This paper explores the factors associated with the place of death in Burkina Faso, based on mortality data from the Kaya Health and Demographic Surveillance System (Kaya HDSS). A multilevel logistic regression model with random intercept is used to determine the factors associated with the place of death. More than half of the deaths (55%) occur at home. Age, place of residence, distance to the health care centre and cause of death are statistically associated with the place of death. Seniors (50 and over) are more likely to die at home compared to other age grous (66.81 % against 35.9 % for 5-14 years and 44.9 among children under 5 years, p = 0.001). The multivariate results confirm the effect of age, place of residence, living standards quintile and cause of death. The high proportion of deaths occurring at home challenges policy makers in the health care system and calls for programs to adapt the supply of heath care.
Resumo:
Pesticide residues in food and environment pose serious health risks to human beings. Plant protection laws, among other things, regulate misuse of agricultural pesticides. Compliance with such laws consequently reduces risks of pesticide residues in food and the environment. Studies were conducted to assess the compliance with plant protection laws among tomato farmers in Mvomero District, Morogoro Region, Tanzania. Compliance was assessed by examining pesticide use practices that are regulated by the Tanzanian Plant Protection Act (PPA) of 1997. A total of 91 tomato farmers were interviewed using a structured questionnaire. Purposive sampling was used in selecting at least 30 respondent farmers from each of the three villages of Msufini, Mlali and Doma in Mvomero District, Morogoro Region. Simple Random Sampling was used to obtain respondents from the sampling frame. Individual and social factors were examined on how they could affect pesticide use practices regulated by the law. Descriptive statistics, mainly frequency, were used to analyze the data while associations between variables were determined using Chi-Square and logistic regression model. The results showed that respondents were generally aware of the existence of laws on agriculture, environment and consumer health, although none of them could name a specific Act. The results revealed further that 94.5% of the farmers read instructions on the pesticides label. However, only 21% used the correct doses of pesticides, 40.7% stored pesticides in special stores, 68.1% used protective gear, while 94.5% always read instructions on the label before using a pesticide product. Training influenced the application rate of pesticide (p < 0.001) while awareness of agricultural laws significantly influenced farmers’ tendency to read information on the labels (p < 0.001). The results showed further that education significantly influenced the use of protective gears by farmers (p = 0.042). Education also significantly affected the manner in which farmers stored pesticide-applying equipment (p = 0.024). Furthermore, farmers’ awareness of environmental laws significantly (p = 0.03) affected farmers’ disposal of empty pesticide containers. Results of this study suggest the need for express provisions on safe use and handling of pesticides and related offences in the Act, and that compliance should be achieved through education rather than coercion. Results also suggest establishment of pesticide disposal mechanisms and structures to reduce unsafe disposal of pesticide containers. It is recommended that farmers should be educated and trained on proper use of pesticides. Farmers’ awareness on laws affecting food, environment and agriculture should be improved.
Resumo:
In this study cross-section data was used to analyze the effect of farmers’ demographic, socioeconomic and institutional setting, market access and physical attributes on the probability and intensity of tissue culture banana (TCB) adoption. The study was carried out between July 2011 and November 2011. Both descriptive (mean, variance, promotions) and regression analysis were used in the analysis. A double hurdle regression model was fitted on the data. Using multistage sampling technique, four counties and eight sub-locations were randomly selected. Using random sampling technique, three hundred and thirty farmers were selected from a list of banana households in the selected sub-locations. The adoption level of tissue culture banana (TCB) was about 32%. The results also revealed that the likelihood of TCB adoption was significantly influenced by: availability of TCB planting material, proportion of banana income to the total farm income, per capita household expenditure and the location of the farmer in Kisii County; while those that significantly influenced the intensity of TCB adoption were: occupation of farmers, family size, labour source, farm size, soil fertility, availability/access of TCB plantlets to farmers, distance to banana market, use of manure in planting banana, access to agricultural extension services and index of TCB/non-TCB banana cultivar attributes which were scored by farmers. Compared to West Pokot County, farmers located in Bungoma County are more significantly and likely to adopt TCB technology. Therefore, the results of the study suggest that the probability of adoption and intensity of the use of TCB should be enhanced. This can be done by taking cognizance of these variables in order to meet the priority needs of the smallholder farmers who were the target group. This would lead to alleviating banana shortage in the region for enhanced food security. Subsequently, actors along the banana value chain are encouraged to target the intervention strategies based on the identified farmer, farm and institutional characteristics for enhanced impact on food provision. Opening up more TCB multiplication centres in different regions will make farmers access the TCB technology for enhanced impact on the target population.