EXPLORING THE RELATIONSHIP BETWEEN ECONOMIC INSECURITY AND HEALTH OUTCOMES by Barry Watson Submitted in partial fulfilment of the requirements for the degree of Doctor of Philosophy Dalhousie University Halifax, Nova Scotia April 2015 c Copyright by Barry Watson, 2015 Table of Contents List of Tables. vi List of Figures. ix List of Abbreviations Used. xi Chapter 1: Introduction.
1 Chapter 2: Is Job Insecurity Associated with Mental Health for Working Age Adults? .1 Economic Burden of Mental Health .1 Dependent Variable: Mental Health .2 Perceived Job Insecurity .4 Additional Explanatory Variables .1 Pooled Descriptive Statistics .2 Within Variation Descriptive Statistics .3 Regression Results - Pooled OLS .4 Regression Results - Fixed Effects (FE) .7 Results Based on Respondent Being a Parent. 64 Chapter 3: Is There an Association Between Economic Insecurity and Body Mass for Canadian Labour Force Participants? .5 The Economic Insecurity Index .1 25 percent Short Fall Dummy Variable .2 Probability of a 25 percent Short Fall Variable .3 Probability of Short Fall Explanatory Variables .6 Econometric Model Predicting Body Mass .2 Dependent Variable Specification .3 Additional Explanatory Variables .2 Pooled Ordinary Least Squares Results (Males) .3 Pooled Ordinary Least Squares Results (Females). 115 Chapter 4: Is There a Relationship Between Economic Security and Body Mass for Canadian Adults? A Natural Experiment Approach 128 4.1 Economic Insecurity and Obesity .2 A Brief History of Unemployment Insurance in Canada .1 Extension: Low Education Sample Restriction .2 Additional Explanatory Variables .3 Dependent Variable Specification: Body Mass Index. 180 v List of Tables Table 2.
Pooled Descriptive Statistics - Males. Pooled Descriptive Statistics - Females. Percentage of Respondents with Variation in their Responses for Each Variable During the Study Period. Pooled OLS Model Results.
FE Model Results. Descriptive Statistics - Mean Values. Probability of a 25 Percent Short Fall in Actual Versus Trend Real Equivalent Household Income. Average Marginal Effects (∂y/∂x) for the Probability of a 25 Percent Short Fall in Actual Versus Trend Real Equivalent Household Income.
BMI Pooled Ordinary Least Squares Model - Males. BMI Pooled Ordinary Least Squares Model - Females. BMI Quantile Regression - Males. BMI Quantile Regression - Females.
Mean Values - Males. Mean Values - Females. Difference-In-Difference Regression Model. Difference-In-Difference Regression Model with Education Restriction 170 Table 4.
Difference-In-Difference Regression - Placebo Model. Robustness Check: Difference-In-Difference Regression Model. Robustness Check: Difference-In-Difference Regression Model with Education Restriction. 173 vii List of Figures Figure 2.
Mean Standardized Psychological Distress Scores Based on Response to the Question: “My job security is good ”. Male Average and Median BMI Across Years. Female Average and Median BMI Across Years. Average Male BMI Across Age Groups for 1998-99 and 2008-09.
Average Female BMI Across Age Groups for 1998-99 and 2008-09. Male BMI Score at each Percentile by Year. Female BMI Score at each Percentile by Year. BMI Kernel Density - Males.
BMI Kernel Density - Females. Ordinary Least Squares and Quantile Regression Estimates - Males. Ordinary Least Squares and Quantile Regression Estimates - Females 127 Figure 4. Male Average Change in BMI (Full Sample).
Female Average Change in BMI (Full Sample). Male Average Change in BMI (Low Education Sample). Female Average Change in BMI (Low Education Sample). Change in BMI and Employment Status Before and After Bill C-12.
Unemployment Rate for Males Aged 25-64 in Canada. Unemployment Rate for Females Aged 25-64 in Canada. Beneficiary to Unemployed Ratio (B/U Ratio). 177 viii Abstract This dissertation examines the relationship between economic insecurity and health outcomes for Canadians age 25 to 64 using the National Population Health Survey (NPHS) - a longitudinal dataset.
Chapter 2 examines the relationship between perceived job insecurity and mental health (measured as psychological distress) using a person-specific fixed effects model. I find that for males and females, the occurrence of perceived job insecurity is associated with an increase in psychological distress of 0.09 standard deviations respectively. If the sample is restricted to those who are parents of children under 18, perceived job insecurity is associated with a 0.18 standard deviation increase in psychological distress for fathers. For mothers, this relationship is statistically insignificant (P-value = 0.
These findings are consistent with a “breadwinner” role for fathers whereby increased psychological distress occurs in light of perceived job insecurity. Chapters 3 and 4 examine whether an increase in economic insecurity is associated with an increase in body mass (measured using self-reported height and weight). Chapter 3 defines economic insecurity as the probability of experiencing a 25 percent short fall in actual versus predicted income. For males and females, a 1 percent increase in this probability is associated with a 0.04 point increase in BMI respectively.
However, for females the result is statistically insignificant at the 5 percent level (P-value = 0. A quantile regression model produces results statistically similar to pooled OLS results. Chapter 4 uses a difference-in-difference model to evaluate a natural experiment. In July 1996, a major policy change (Bill C-12) reduced Canadian unemployment insurance benefits considerably.
For males with a high school education or less, the onset of unemployment in the post-policy period increases BMI by 3. For low education females, the result regarding the onset of unemployment in the post-policy period is statistically insignificant at the 5 percent level (P-value = 0. These results are again consistent with the hypothesis that male self-identification with a breadwinner role means that economic insecurity has greater adverse health impacts for men than women. ix List of Abbreviations Used BMI Body Mass Index B/U Beneficiary-to-Unemployed Ratio CPI Consumer Price Index ESI Rockefellers Economic Security Index FE Fixed Effects MET Metabolic Energy Cost NAICS North American Industrial Classification System NPHS National Population Health Survey OLS Ordinary Least Squares PD Psychological Distress UE Unemployed x Acknowledgments I wish to humbly thank Dr.
Lars Osberg, Dr. Shelley Phipps and Dr. Courtney Ward for all their help and insight throughout this entire process. Their guidance during these past 4 years has been invaluable.
Furthermore, I would like to thank my partner Amy Tanner for her help, encouragement and patience during this time. I would also like to acknowledge Nan Zhou from the Research Data Centre in Fredericton New Brunswick for his help in allowing me to disclose all the results presented in this paper. Given the rules and regulations of data disclosure, his expertise was greatly appreciated. Last but certainly not least, I would like to thank my parents for all their support during this time.
I am truly grateful to be surrounded by such great people during these past years as a thesis student at Dalhousie University. Without these individuals I can safely say my time as a PhD student would have undoubtedly suffered. xi Chapter 1 Introduction This dissertation examines the relationship between economic insecurity and the health of working age Canadians using data collected by the National Population Health Survey (NPHS) - a longitudinal dataset. Economic research on the determinants of health outcomes have largely focused on the occurrence, and not the probability of, negative economic shocks.
This dissertation addresses this gap in the literature by focusing on the probability of a negative economic shock - a concept known as economic insecurity - as a determinant of health. Two health outcomes are analyzed in this dissertation: (i) mental health and (ii) body mass. About 1 in 5 individuals in Canada and the United States are estimated to be affected by a mental health problem in any given year (Center for Disease Control, 2004; Smetanin et al., 2011; World Health Organization, 2001). Estimates of the economic burden of mental health in Canada range from 1 to 4 percent of Canadian GDP - i.8 billion Canadian dollars annually (in 2014 dollars).
Furthermore, over the past 20 to 30 years there has also been a dramatic increase in the prevalence of obesity in North America (Obesity in Canada, 2010; Tremblay et al., 2002; World Health Organization, 2011). The report “Obesity in Canada” (2010) suggests that during the past 25 years, the prevalence of obesity has roughly doubled in Canada. Additionally, they estimate the current economic burden of obesity in Canada to be about 0.3 percent of Canadian GDP - i.7 billion Canadian dollars annually (in 2014 dollars). 1 Economic insecurity is defined as “inability to obtain protection against subjectively significant potential economic losses” (Osberg, 1998, p.
In particular, Osberg & Sharpe (2009) outline four key aspects of economic insecurity; the probability of: (i) unemployment, (ii) illness and disability, (iii) divorce and (iv) poverty in old age. Moreover, Hacker et al. (2010) defines the occurrence of economic insecurity as a 25 percent drop in year over year real household income after adjusting for medical expenses and debt servicing. Both authors have found compelling evidence that economic insecurity has increased in Canada over the past 20 to 30 years.
Currently, there is no universally accepted metric for economic insecurity. While several well-accepted measures for a related concept, income inequality, exist (e. Gini Coefficient, Atkinson Index, Coefficient of Variation, etc.), there is no generally accepted measure of economic insecurity. As a result, researchers have used a variety of models to capture this concept of economic insecurity.
As mentioned above, Hacker et al. (2010) measure economic insecurity as the occurrence of a 25 percent drop in year over year real household income after a set of adjustments. Moreover, Smith et al. (2009) evaluate economic insecurity using four methods: (i) the probability of becoming unemployed in a particular time period, (ii) the number of 50 percent or greater drops in real household income over a period of time, (iii) the volatility of an individual’s income over time, and (iv) the existence (or lack thereof) of social safety nets such as health insurance.
Based on the above, it is clear that past research has used various proxies to capture the concept of economic insecurity. For instance, the perceived likelihood of job loss is a key component of economic insecurity. Those who feel their job is in jeopardy are likely to be facing an elevated probability of a severe negative shock to their income stream. In Chapter 2, I explore the potential link between perceived job insecurity and mental health using a person-specific fixed effects regression model to control for unobserved heterogeneity.
I measure mental health using the K6 questionnaire developed by Kessler and colleagues (2002) - a well-known and validated index of psychological distress. 2 Results for males age 25 to 64 suggest the onset of perceived job insecurity is associated with an increase in psychological distress of 0. For working age females, the occurrence of perceived job insecurity is associated with an increase in psychological distress of approximately 0. When the sample is restricted to those who are parents of children under the age of 18, an interesting result emerges: the association between perceived job insecurity and mental health intensifies for fathers (in comparison to working age males) and is statistically insignificant for mothers.
This result suggests the possibility of a defined “breadwinner” role for fathers which when jeopardized through the presence of perceived job insecurity, deteriorates mental health. That is, given their breadwinner role (whether perceived or actual), the onset of perceived job insecurity is associated with a greater increase in psychological distress in comparison to mothers. Chapters 3 and 4 evaluate the association between economic insecurity and body mass. While some argue that obesity is the result of consumer choice (i.
an evaluation of the marginal benefits and costs of weight gain), recent work suggests optimized decision-making may be greatly affected by an evolutionary biological response (Smith, 2009). That is, as an individual experiences stress, their optimal response is driven by an evolutionary trait to store fat which is in turn, driven by the possibility of starvation.