Knowledge-related fire hazards reduction capabilities amongst households in Kibera settlements, Nairobi County, Kenya

The purpose of the study was to determine knowledge-related fire hazards reduction capabilities amongst households in Kibera Settlements, Nairobi County, Kenya. The study was conducted in Kibera Slums. Descriptive cross-sectional study design was used. A total of 423 respondents were used in the study. Data was collected using Questionnaires, observation checklists and Focus Group Discussions. Data analysis was done using SPSS v.20. The study found out that the community’s knowledge and awareness was fairly good, with no respondent (0%) willing to indicate total lack of school-based education. The respondents defined fire hazards as the causes, events and effects of fires without arriving at a clear definition of fire hazards. Males had better reduction capability than females. The study therefore recommends programs by the local authorities to train the community on preventive measures as well as gender-focused fire hazard reduction empowerment. Introduction Over 4 million people die prematurely from illness attributable to the household air pollution from cooking with solid fuels and more than 50% of premature deaths among children under 5 because of pneumonia caused by soot inhaled from household air pollution WHO (2014). According to WFSC (2015), all across the globe, people have neglected the need to forecast the possible occurrences of fire when constructing buildings. For Europe as a whole, the annual toll of fire deaths is measured in many thousands, with those suffering fire injuries numbered at many times more. Burns caused by fire hazards are among the most devastating of all injuries, resulting to physical impairments and disfigurement, to emotional and European International Journal of Science and Technology ISSN: 2304-9693 www.eijst. org.uk 2 mental consequences. SCDF (2015) agrees with this burden projected. It states that in 2014, 588 more cases were reported than in 2013 in the whole of Singapore. This was approximately a 14% increase. Despite the fact that injury due to burns is largely preventable, Africa carries an extraordinary burden of fire related injuries. Background Capability refers to the power to handle or just the inherent ability to cope with. In the case of fire hazards, reduction capabilities could cover from factors as small as carelessness to more complex factors such as the makeup of the house such as inclination, access or ventilation. The capability to reduce fire hazards can be measured in terms of preparation, reaction or the risk factors. This study will focus on how all these contribute to an overall rate of fire hazard occurrences (Ono & Da Silva, 2000). Fire is crucial for the development of human society, and it has become an important part of human civilization. Among different types of disasters, fire constitutes a significant threat to life and property in urban and rural areas (Dube, 2015). Fire hazards refer to all types of live flames, causes of sparks, hot objects, and chemicals that are potential for ignition, or that can aggravate a fire to become large; In addition fire hazards could also mean the potential threats to fire prevention practices, firefighting, built-in fire safety systems and situations that restrict the escape of people from an affected building or area in the event of a fire. Some common fire hazards are kitchen fires from unattended cooking, such as frying, boiling, and simmering, electrical systems that are overloaded, resulting in hot wiring or connections, or failed components, combustible storage areas with insufficient protection (Claret et al., 2012). Research Questions The study addressed the following questions: 1. What is the level of fire hazards knowledge and awareness amongst the households in Kibera settlements? 2. What are the demographic characteristics contributing to fire hazards reduction capabilities in Kibera settlements? 3. What are the socio-economic characteristics contributing to fire hazards reduction capabilities in Kibera settlements? Methods Study Subjects The study area was conducted in Kibera Slums within Nairobi County, purposely selected since it was the largest slum in Kenya, as at the time of study. Kibera is located 5km southwest of Nairobi City Central Business District. Kibera has a population of approximately 177,000 (2009) The target population consisted of Kibera residents who were above 18 years and who had been residents for the preceding one year in the study area (Fihlani, 2015). The study population was the household heads at Kibera settlements. Any adult above 18 years present in the absence of a household head also took part. The total number of households used was 1977 (KNBS, 2009). Study Designs Cross-sectional study design was used to determine the fire hazards amongst the households in Kibera settlements. Quantitative data was solicited through questionnaires conducted on house hold heads and Focus Group discussions were also used to compliment the quantitative data. Observation checklists were used to ascertain the findings from the questionnaire as well as provide qualitative data (Moskal&Leydens, European International Journal of Science and Technology Vol. 5 No. 9 December 2016 3 2000). Every household head or adult or mature minors found in the household and consented to take part in the study was included. Pretesting was conducted at Kawangware slums in Nairobi so as to ensure the reliability and suitability of the questionnaires and in-depth interviews. The pretest was used as a means of training enumerators who were involved in the main survey. Instruments to be used for the collection of data included in-depth interviews, observation checklist and Focus group discussions. As for the Collection procedure, First, the local administrators were consulted so as facilitate field entry. A sampling frame was then developed from which the sample populations for the household survey were drawn. A sample of 423 respondents was used for the study. Data was collected on fire hazards reduction capabilities amongst households Analytical Techniques Once questionnaires had been completed the data collected was systematically arranged according to the codes of the questions to facilitate analysis. Verification of all filled questionnaire for completeness and made a follow-up to make sure all questions were as appropriately answered as possible. The questionnaires were then presented to the Statistician for Cleaning and Analysis. Incomplete, irrelevant, inconsistent or inaccurate records were removed from the database. Panel data were sorted as so for ease of analysis with creation of new variables for appropriateness of the analysis process as per objectives. Data was analyzed using SPSS package version 22. Tables and graphs were used to present the results. Cross tabulations were generated to determine the relationships between variables. Chi-square and correlation analysis were used to test for associations among variables. Results Characteristics of the Respondents Demographic Characteristics of the Respondents Table 4.3. 1 and Table 4.3. 2 show the demographic characteristics of the respondents. Those aged 35years and above were more. Male respondents were also fewer than females. Those who had been widowed or divorced were the majority. The mean number of household members was 5.99 with the median and mode being 5. The standard deviation from the mean for household members was 1.402. This means that the values were close to each other and not widely variant. However, the minimum number was 1 since there were a good number of single people involved in the study. The differences between capabilities across the ages were statistically significant [p>0.05], with those aged 35 and above found to be more. Gender, however, varied significantly with the outcome variable [p=0.04] with more female than male respondents. Most households had many members, above the mean household number. Table 4.3. 1: Demographic Characteristics Variable Values Number, N Percentage (%) Age ≤ 35 221 52.24 > 35 202 47.75 Gender Male 201 47.52 Female 222 52.48 Marital Status Single 137 32.39 Married 138 32.62 Divorce/Widowed 148 34.99