Study used Seemingly Unrelated Regression (SUR) and Tobit methods to estimate models. The study found that physical and mental health are negatively correlated with market hours and positively correlated with sleep and leisure. These results are consistent for both the male sample and the female sample. The study also focused on prime-age individuals and found that physical health and mental health significantly reduced time spent on work and significantly increased leisure time for both males and females. The result of this study that self-rated poor health negatively correlates with time spent on market work is consistent with the findings of other relevant studies reviewed in this paper. The finding of this research that poor health is associated with more time spent on leisure is consistent with the results. This study finds that health is not associated with time used in non-market work. This result is similar to the finding. However, this finding is different from who found a significant association between health and non-market work. To the best of this author's knowledge, this is the first Canadian study to examine the relationship between health and time use. Unlike other studies in this area, this study also examined the relationship between mental health and time use. The study has significant policy implications. Irrespective of the age group or the age group, the study consistently found that both physical health and mental health were negatively associated with market work hours. These results are true for both males and females. Unlike physical health's effect, mental health's impact on market work is not widely recognized. This results of this study suggest that while calculating the cost-benefit of public health-care spending, policymakers need to consider that both physical and mental health are likely to impact an individual's performance in the labor market. A major shortcoming of this study is that it could not control for possible endogeneity arising from the reverse causality between time use and health. For example, excessive time spent on work may negatively impact physical and mental health. A method to take reverse causality into account is using instrumental variable regression. However, the data used in the study do not have instruments to run instrumental variable regressions. Thus the results of the study should be considered with caution. Future studies can control unobserved individual-specific heterogeneities if panel data is available for time use. With more informative data, future studies can also consider possible reverse causalities.