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Abstract
In the last thirty years, in the context of structural changes in the global economy, mental health has become a major public health concern worldwide. Using the National Health Interview Survey (NHIS) data for 2013 and 2014, this article evaluates the relationship between the labor market and psychological well-being in the United States from a gender perspective. More specifically, this article uses a logit regression methodology to estimate the impact of unemployment on the likelihood of developing depression and anxiety for both men and women. The findings of this analysis indicate that unemployment has a similar, negative effect on the mental health of both men and women. This is consistent with the predictions of the dual breadwinner model, on the basis of which both men and women shoulder the financial responsibilities of the household, and is relevant for policy considerations.
Notes
1 These estimates include both direct costs (i.e. medical expenses for diagnosis, treatments, and drugs) and indirect costs (i.e. nonmedical expenses related to the illness, such as transportation costs for medical care, income loss, and costs of information and education). To keep these figures in perspective, costs for mental illness in 2010 are estimated to be around 37% of total world costs for major diseases, calculated as the sum of expenses for cancer, chronic respiratory diseases, cardiovascular diseases, diabetes and mental illness. This share is estimated to remain the same in 2030 (Bloom et al., Citation2011).
2 In 2001, the WHO for the first time focused its annual World Health Report on mental health to raise awareness of the critical importance of mental health for overall health, to educate on the individual and social costs associated with mental illness, and to provide policy recommendations. In addition, in 2013 the WHO adopted the “Mental Health Action Plan 2013-2020,” which calls for an expansion of research and services for prevention and treatment.
3 As part of the health goal, which is the third of seventeen goals, world leaders agreed on the following two sub-targets: “By 2030, reduce by one third premature mortality from non-communicable diseases through prevention and treatment and promote mental health and well-being” (target 3.4); and “strengthen the prevention and treatment of substance abuse, including narcotic drug abuse and harmful use of alcohol” (target 3.5).
4 Anxiety and depression are identified as the two most common disorders (Center for Behavioral Health Statistics & Quality, Citation2015).
5 Since the early 1980s, privatization, de-unionization, deregulation, and liberalization—in the context of rapid technological innovation and “commodification” of social protection—have led to a decline of workers’ bargaining power. In turn, this has generated loss of job security, increase in weekly working hours, and stagnant real wages (Wolff, Citation2013).
6 For a review of the empirical literature on work and mental health (excluding gender considerations), see Piovani and Aydiner-Avsar (Citation2015).
7 2013 and 2014 represent years of slow economic growth for the United States (1.5 and 2.4%, respectively), but these are non-recessionary years in which the labor market continued improving after the 2008/2009 global crisis (the unemployment rate was 7.4 and 6.2, respectively). The analysis presented in this article considers both years to obtain more robust estimates. The outcome for unemployed and those outside the labor force is the result of a comparison with the outcome of those employed.
8 For a review of these models, see Piovani and Aydiner-Avsar (Citation2015).
9 In regards to labor market conditions, it is worth noting that the WHO framework indicates that both unemployment and employment characteristics (for those employed) are influential for one's mental health. Based on the findings in the literature, work characteristics associated with adverse mental effects include excessive demands, insufficient control, low social support in the workplace, lack of job security, and lack of fairness in rewarding productivity (Barnay, Citation2014).
10 The only study in this regard—to the authors’ knowledge—is by Liu, MacPhail and Dong (Citation2018), which finds that in China, prime age, employed women have worse mental health than men due to higher work burdens (including both paid employment and unpaid care work).
11 According to the U.S. Census Bureau (2016), more than 80% of the 12 million single-parent families are headed by single mothers (http://www.census.gov/newsroom/facts-for-features/2016/cb16-ff09.html).
12 The National Health Interview Survery (NHIS) is the main source of information on the health of the U.S. civilian non-institutionalized population. Designed by the Centers for Disease Control and prevention (CDC) and initiated in 1957, the NHIS provides cross-sectional household interview survey data. The data is collected through personal household interviews run by the U.S. Census Bureau. Interviewers visit 35,000–40,000 households across the country and collect data on 75,000–100,000 individuals. After a household has been sampled, one adult and one child (if any are present) is selected to complete the Sample Adult and Sample Child components of the survey. Once selected, respondents cannot be replaced with anyone else.
13 We do not use objective measures of mental health, which are based on the use of prescription drugs, because this approach leads to a much smaller sample (restricted by the ability to access health care). It is also common in the health economics literature to use self-assessed measures of health status.
14 Descriptive statistics are presented for all adults in the sample, whereas estimations are run for a sub-sample only (as will be explained in Section 3.2). This explains why the number of observations in Table 1 is higher than in Table 2.
15 Based on NHIS data availability, welfare payments are defined as government assistance payments because of low income. Such payments exclude food stamps, supplemental security income (SSI), energy assistance, or medical assistance payments.
16 Even though the economy affects mental health through a number of channels, labor market status remains the prominent variable.
17 Person-level population weights are equal to the inverse probability of selection into the sample. These weights are adjusted for nonresponses with post-stratification adjustments for age, race/ethnicity, and sex using the Census Bureau's population control totals. The sum of these weights corresponds to the civilian, noninstitutionalized U.S. population in each year. For additional information, see: https://nhis.ipums.org/nhis/userNotes_weights.shtml.
18 Education could be considered a candidate instrument highly correlated with one’s labor market status, but it also helps explain one’s health status so it cannot serve as an instrument.
19 Specifically, the question is as follows: “Compared with 12 months ago, would you say that your health is better, worse, or about the same?” A person’s health status is thus based on self-assessment.
20 Marginal effects indicate by how much the probability of the dependent variable changes when a binary independent variables changes from 0 to 1.
21 The probabilities presented from here on should always be interpreted as relative to the base group. For brevity, this will not always be reiterated throughout the discussion of the empirical results.
22 For an analysis of gender identities by ethnic groups, please see Mutari, Power, and Figart (Citation2002).