Breast cancer is a multifactorial disease; several socioeconomic, food factors and lifestyle are incriminated in its development. It is the first cancer of women in the world and in Algeria, in terms of incidence and mortality. In Batna, the standardized incidence has doubled, from 13.6 in 2001 to 25.3 in 2011. OBJECTIVE The main objective is to study the dietary risk factors associated with the occurrence of breast cancer in women in the region of Batna. METHODS A case-control study with 1-1 matching by age and address was conducted from January 1st, 2013 to December 31rd, 2014. The total sample consisted of 160 women. RESULTS Eating fast-food every day increases the risk of breast cancer by 7 times as well as fat from red meat. Consumption of sausage and poultry skin by 5 times. Cooking vegetables in sauce increases the risk by 5 times (p <0.0001), Taking olive oil each day reduces the risk of 25% with a p <0.02, the consumption of milk mixed or not with coffee reduces the risk of one third and the fact of nibbling rarely reduced it with OR = 0,117 (0,023- 0.59) p = 0.009. DISCUSSION The associations between dietary risk factors and breast cancer are discordant in the various studies carried out in the world, our results are in line with studies but require further research

Purpose The purpose of this paper is to validate a fuzzy risk graph model through a case study results carried out on a safety instrumented system (SIS). Design/methodology/approach The proposed model is based on an inference fuzzy system and deals with uncertainty data used as inputs of the conventional risk graph method. The coherence and redundancy of the developed fuzzy rules base are first verified in the case study. A new fuzzy model is suggested for a multi-criteria characterization of the avoidance possibility parameter. The fuzzy safety integrity level (SIL) is determined for two potential accident scenarios. Findings The applicability of the proposed fuzzy model on SIS shows the importance and pertinence of the proposed fuzzy model as decision-making tools in preventing industrial hazards while taking into consideration uncertain aspects of the data used on the conventional risk graph method. The obtained results show that the use of continuous fuzzy scales solves the problem of interpreting results and provides a more flexible structure to combine risk graph parameters. Therefore, a decision is taken on the basis of precise integrity level values and protective actions in the real world are suggested. Originality/value Fuzzy logic-based safety integrity assessment allows assessment of the SIL in a more realistic way by using the notion of the linguistic variable for representing information that is qualitative and imprecise and, therefore, ensures better decision making on risk prevention.

Purpose The purpose of this paper is to validate a fuzzy risk graph model through a case study results carried out on a safety instrumented system (SIS). Design/methodology/approach The proposed model is based on an inference fuzzy system and deals with uncertainty data used as inputs of the conventional risk graph method. The coherence and redundancy of the developed fuzzy rules base are first verified in the case study. A new fuzzy model is suggested for a multi-criteria characterization of the avoidance possibility parameter. The fuzzy safety integrity level (SIL) is determined for two potential accident scenarios. Findings The applicability of the proposed fuzzy model on SIS shows the importance and pertinence of the proposed fuzzy model as decision-making tools in preventing industrial hazards while taking into consideration uncertain aspects of the data used on the conventional risk graph method. The obtained results show that the use of continuous fuzzy scales solves the problem of interpreting results and provides a more flexible structure to combine risk graph parameters. Therefore, a decision is taken on the basis of precise integrity level values and protective actions in the real world are suggested. Originality/value Fuzzy logic-based safety integrity assessment allows assessment of the SIL in a more realistic way by using the notion of the linguistic variable for representing information that is qualitative and imprecise and, therefore, ensures better decision making on risk prevention.