We investigate the effects of climate variables on food and nutrition security and the probability of a household being food and nutrition insecure. Panel data methods from three waves of the Tegemeo Institute Household survey data (2004, 2007, and 2010) are used. Climate change is measured by long-term averages of temperature and rainfall, all measured at the peak precipitation month and extreme values of the Standardised Precipitation-Evapotranspiration Index (SPEI).

Non-Communicable Diseases (NCDs) have become one of the leading causes of morbidity and mortality in Kenya. Their claim on financial and time resources adversely affects household welfare. Households predominantly pay healthcare costs for NCDs in Kenya as Out of Pocket expenditure (OOP). Health expenditure on NCDs stands at 6.2% of total health expenditure, which is 0.4% of the total gross domestic product of the country. This expenditure scenario has implications on household welfare through catastrophic expenditure in Kenya.

Despite a remarkable progress in the control and management of communicable diseases over the past century, the world is not better-off as the prevalence of Non-Communicable Diseases (NCD) is on the increase, both in developed and developing countries. The upsurge in NCD prevalence is attributable to risk factors both outside and within the control of individuals. One risk factor that has received less attention than it deserves is the social interactions variable.

Non-Communicable Diseases (NCDs) have been on the increase in Kenya over the past decade. This rising trend has led NCDs to account for over 30% of the annual total disease-related deaths in the country. Between 2005 and 2009, major NCDs (cancer, cardiovascular diseases, respiratory ailments and diabetes) accounted for over half of the top 20 causes of disease-related deaths in Kenya.

Despite its importance in benefit-cost analyses in the water supply, transportation, and health care sectors, there are relatively few empirical estimates of the value of travel time savings (VTT) in low-income countries, particularly in rural areas. Analysts instead often rely on a textbook “rule of thumb” of valuing time at 50% of prevailing unskilled wage rates, though these benchmarks have little empirical support in these settings. We estimate the value of travel time through the use of a repeated discrete choice stated preference exercise.