**4.1 Description of the study area**

The Suba district is located in the Nyanza province in southwestern Kenya along Lake Victoria (**Figure 1**). The district is one of the poorest in Kenya, comprising approximately

**Figure 1.** *Map of the study areas [29].*

#### *Climate Change, Rural Livelihoods, and Human Well-Being: Experiences from Kenya DOI: http://dx.doi.org/10.5772/intechopen.104965*

200,000 people who are densely populated in the Lake Victoria basin [30]. More than one-third (35.5%) of the population in Kenya lives below the poverty line of US\$1.90 per day [31], but in the Suba district, the poverty incidence is as high as 52% [32].

Apart from mixed farming practices, some people in this district are highly dependent on the adjacent Lake Victoria for fishing at both subsistence and commercial scale. The Suba district is, therefore, mainly dominated by natural resource-based livelihoods comprising smallholder subsistence farming and fishing households. Unfortunately, the rapidly declining fish stock sizes and catches in Lake Victoria – the result of, among others, serious pollution problems over the past 20 years – are now threatening the food security and survival of more than one million Kenyans [16]. Major crops in the Suba district include maize, sorghum, cassava, and legumes, while bananas and sweet potatoes are grown widely as security crops that withstand drought periods and feed households in times of famine [33]. Livestock husbandry is also common in the form of households rearing cattle, goats, chickens, and donkeys.

The Suba district faces inadequate health provisions and high levels of poverty that have exacerbated the risk of climate-related diseases [32, 34]. Cholera, dysentery, and typhoid tend to increase as people are in constant contact with bacteria from inappropriate sewerage and waste disposal. The poor access to health care services is exacerbated by adverse climatic disasters that are posing health risks through malaria and cholera among households [35]. Communities in the Suba district are, therefore, now highly vulnerable to epidemics associated with extreme climate disasters.

**Figure 1** shows the study areas comprising Mfangano Island, Rusinga Island, and Mbita point in the Suba district. All areas are located along the shores of Lake Victoria, giving inhabitants an opportunity for either fishing or farming livelihoods, depending on the landholdings and fishing rights, or availability of resources.

#### **4.2 Research design and sampling**

The research design was exploratory in nature and used a case study approach to investigate climate change impacts in the three selected villages of the Suba district. A quantitative research methodology was followed where the principal researcher [36] conducted face-to-face interviews using a semi-structured questionnaire as a measuring instrument.

A multi-stage sampling design was employed where, firstly, the three pre-selected villages of Rusinga Island, Mfangano Island, and Mbita point were purposefully sampled based on the already known prevalence of livelihood activities of farming and fishing in the area. Databases from the Kenya National Bureau of Statistics containing a list with the names and addresses of all 2640 households in the three villages served as the sampling frame. In each village a total of 30 households were systematically sampled, bringing the total sample size to 90 households. This relatively small sample size resulted in a confidence interval (error level) of 10.2% at a 95% confidence level, which means that caution should be taken when extrapolating the findings to the rest of the target population. In all cases, personal interviews were conducted with the heads of households allowing the latter to seek consensus responses from their families.

#### **4.3 Measuring instrument, data collection, and data analysis**

The Sustainable Livelihoods Framework was used to inform the construction of the questionnaire. More precisely, the questionnaire was divided into segments that comprised of—i) household demographics (assessment of the human capital), which included questions such as: *How many members are in your household? As a family, what do you practice as a primary source of livelihood?* ii) Livelihoods, assets or ownership of properties including livestock, production and diversity of produce/yield levels, accessibility to safe drinking water, current fishing or farming constraints, awareness or perceptions on climate change, observed and expected climate change phenomena, climate change impacts, and coping strategies. Some of the questions asked to respondents were: *What assets do you possess? What major crops and livestock do you produce? Have you experienced any changes in temperatures in the last few years? How do you cope with these impacts of climate change?*

The questionnaire was initially drafted in English and then translated into the dominant local languages of Kiswahili and Kijaluo. All selected respondents were informed beforehand about the research to gain oral consent for their participation in the study. The principal researcher also approached community leaders or gatekeepers of the communities and explained the study to them and obtained formal permission for entering the communities. Apart from the principal researcher, an additional three enumerators of Kenyan origin were employed to aid in data collection. Data quality checks were done close to the data sources as well as during data entry. Because of the statistical limitations of the sample size as explained earlier, data analysis was restricted to the use of descriptive statistics and no inferential tests were run on the data.

While a strength of this study was our ability to draw on data from three villages that were interlinked, a limitation was that the sample size was limited, and further research, preferably a longitudinal study, could be done to explore climate variability and the perceptions of farmers and fishermen at different intervals over a longer period of time, instead of a cross-sectional survey. The study results were based on the respondents' lived experiences and personal observations and as such might contain an element of subjectivity. Any bias in this study has nevertheless been minimized by asking respondents to make comparisons with historical trends benchmarked against previous farming or fishing seasons. Some of the responses, especially those pertaining to trends in temperature change and rainfall patterns, have also been compared with long-term official data and findings of other studies on climate trends in rainfall and temperature in Kenya.
