Access to public healthcare is necessary because it improves the general well-being and productivity of a people, and is good for sustainable development. However, despite the fact that access to public healthcare is arguably cheaper compared to private facilities and allows for early diagnosis and management of physical, psychological, and societal illnesses, and is thus critical for people's overall health, its access has been worrying especially in Kenya. This study is an inquiry into the influence of social class on access to public healthcare in Kenya, a case study of Nairobi City County. To support this inquiry, intervening variables (demographic, socio-cultural and institutional) were used to investigate the relationships between social class and access to public healthcare. The study was based on households in were used to explain causal links between the two variables (independent variable-Social Class and Dependent variable-Access to Public Healthcare. The study employed descriptive and longitudinal research design. A multistage random sampling technique was employed to arrive at a sample size of 1066. The study employed both primary and secondary data sources. Semi-structured questionnaire and an interview guide were used to collect data. The study employed drop and pick later method for the questionnaire data collection while face-to-face interview was used to respond to interview guide questions. Cross tabulation analysis was done between each independent variable indicator and dependent variable, access to public healthcare. The results were presented in frequency distribution tables and correlation results for each item in the questionnaire. With regards to the qualitative data from the interview guide, content analysis was employed. The research findings confirmed robust positive correlations between independent and dependent variables. Using hypothetical variables (intervening variables), the study found that demographic variables (age, income, education, marriage, wealth, place of residence); socio-cultural variables (like inability to communicate in national languages, individual perception of public healthcare facilities, cultural practices, strict faith and attitude, social capital and poverty); and institutional variables (policies, limited health financing by the government, infrastructure, adequate and balanced distribution of health workers; few health facilities and poor distribution of health commodities and equipment; lack of basic amenities like water and sanitation; lack of citizen participation among others) explain the causal links between the independent and dependent variables. Hypothetical variables explain the causal links between the two variables(independent variable and dependent variable). The study concluded that an increase in the explanatory power of demographic variables like increased level of education and income of the citizens could help find durable solutions, hence, lead to more access to public healthcare services; Further, increased explanatory power of the intervening variables socio-cultural variables like social networks, capital, attitude and perception of health facilities could help provide solutions that could result to increased access of public healthcare. And furthermore, increases explanatory power of institutional variables (e.g. increase in financing, adequate and equitable distribution of health workers; availability of medical drugs and equipment; access to basic amenities (water and sanitation, increase in public participation could help explain the relationship between the two variables, and find solutions to can lead to increased access to public healthcare.At a policy level, the study therefore recommended that the government should use such knowledge to increase opportunities in demographic, socio-cultural and institutional factors in order for access to public healthcare to increase, especially among the poor households in the city county.At an academic level, more research should be conducted to establish why intervening variables do not explain adequately the causal relationship between the intervening variable and dependent variable. This constitutes a knowledge gap that is necessary to provide solutions in increasing access to public healthcare.

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