Research On Health And Wellbeing In Workplace In The Uk

Health and wellbeing in workplace are important topics that concern sociologists in most resent years. Many social studies suggest that it is important to study the subjective general health of employees in work given the fact that health is found to be a fundamental aspect for improving the economic growth in most of the developing countries (Sousa-Poza, 2000). For instance, Bloom and Canning (2000) show in their study that health and education are very important elements of human capital. In their study Bloom and Canning suggest that high levels of subjective wellbeing of employees have a strong relationship with economic growth. To be more precise, the more the employees are in good health conditions and satisfied the higher their productivity in labour market and thus their income increase.

Danna and Griffin (1999) examined the factors that have potential effects on the level of health and wellbeing in work place. In their study, the authors investigate how the workers health and wellbeing affected by many workplace conditions such as, work overload, quality of work condition (i.e. poor conditions), workers health and safety, long working hours, and the social relations among workers. Danna and Griffin conclude that dangerous and hazardous work conditions would lead to a high level of illnesses and diseases which could eventually lead to increase in sickness absence of the employee from their work. Furthermore, this study suggests that poor working conditions negatively affect the level of wellbeing of the workers. Put differently, people who work in places characterised by insufficient working conditions report poor communication with other workers, low job satisfaction, and poor psychological well-being. The aforementioned study further suggests the improving the work place by enhancing work condition is challenging task that is worth the effort from authorities. To study the effect of gender and work conditions on wellbeing level, a study conducted by Loscocco and Spitze (1990) to compare between men and women in different work settings. This study examines the effects of four working conditions on the level of wellbeing for both men and women. Those four conditions are job demands, workplace with lack of material 2 benefits, physical environment, and work-related social support. The findings of this study suggest that work conditions affect the level of wellbeing of employees in general, but the striking result was that effects were almost equal across men and women. In other words, gender has no impact on the relationship between job condition and wellbeing level.

Drawing on the previous studies mentioned above, this current report examines the relationship between job status and subjective general health. Further, this report will study the effect of gender on the relationship between job status and wellbeing. The hypotheses presented in this repot are as follow:

H1: There is a relationship between job status and subjective wellbeing. I anticipate that people who worked or are working in low status occupation [jobstat] will report lower level of subjective wellbeing [GHQ].

H2: Gender moderates the relationship between job status and level of subjective wellbeing. Because men tend to work in poor conditions more than women I predict that the relationship between lower job status and bad subjective general health will be stronger for men compared to women.

To observe the relationship between job status and subjective general health, I use data from Understanding Society. I use the variables [jobstat] (job status: 1: Management professional, 2: Intermediate, 3: Small employers own account, 4: Lower supervisory technical, 5: Semi-routine, routine and never worked/long term unemployed) and [GHQ] Subjective general health that measured on a scale from (0= the least distressed to 36 =the most distressed). To present the descri ptive statistics for the dependent variable (Subjective general health) and the independent variables (Job status), and gender, I create table 1 that shows the frequencies and percentage of those variables. Table 1 show that the mean of the subjected wellbeing in our sample is 10.66 on a scale ranges from 0 to 36 points. There are almost 37% of participants in high job states (Management and Professional), whereas, 31% of participants were in semi routine, and routine work this category also include people who never worked and have long-term unemployment. Also in this sample, there were 47% male participants and 53% female participants.

Testing the first hypotheses:

To test whether there is a linear relationship between the dependent and the independent variables, I run a simple regression presented in Model 1 table 2. The results in Model 1 show that people in higher status occupations reported high subjective general health (with 0.62 points less) compared to those in Intermediate job status (the omitted category) with standard error equal to.116. Whereas, people in Semi routine job, unemployed, and never worked scored 0.39 more on the subjective general health scale compared to those in intermediate job status. The constant in the regression model presents the expected value that the dependent variable when all the independent variables equal to zero, in this case Intermediate job status. In other words, people with intermediate job states score 10.7 on scale of subjective general health. In other words, people who work in lower job status generally reported lower subjective general health and people in higher status jobs have better mental health. The 2 for this model is 0.7% that means that there are other factors that would affect the subjective general health and are not included in this model. This results support my first hypotheses of lower status job employees have lower subjective general health compared to those in high job status. This result seems also to support the study of Danna and Griffin (1999) that conclude the effect of poor job conditions on the level of wellbeing of employees.

Testing the second hypothesis:

The second hypothesis is that gender moderates the relationship between job status and subjective general health. Due to the fact that men tend to work in more demanding and inadequate job conditions than women, I anticipate that the relationship between lower job status and lower subjective general health to be stronger for men compared with women. To test this relationship, I run multiple regressions to test the effect of the third variable (Gender) on model 2 presented in table 2. In model 2, I control for job status to test the effect of gender on the bivariate relationship. It is clear as presented in model 2 that men have good subjective general health more than women, they score 0.77 less on the subjective general health scale with standard error equal to .97 and it is significant (P-value<. 00). Now I control for gender to see the effect of job status on the relationship. In general, people in high job status have a high level of subjective general health compared to those in lower job status. The constant in this model presents that women in intermediate job status score 11.13 on a scale of subjective general health with standard error equal to 0.96. The coefficients for the occupation status variables are slightly changed from model 1 (-0.62) to model 2 (-0.58) and with a Pvalue<0.05. In this case, I can say that male seem not to CONFOUND the relationship between subjective general health and job status. The 2 for model 2 is 0.013 and this means that only 1.3% of the changes in gender and job status can contribute to the changes of the subjective general health, there are other factors affecting the changes in health but are not included in this model. To test whether gender moderates the relationship between job status and subjective general health, I create an interaction term and run another model including the main effect of gender on the relationship (as shown in model 2) and the newly created interaction term. To test these interactions, I create model 3 presented in table 2. In this model, male in intermediate occupation have better health than women in intermediate job status. The interaction presented in model 3 show that gender dose not moderate the relationship between job status and subjective general health. This is because the interaction effect of gender and job status is not statically significant (for Pro/Mang*male, P-value is 0.861), (for semi routine*Male, Pvalue is (0.186). Based on this result I can conclude that the second hypothesis is not supported, gender is not found to be a moderator in this analysis. This finding support Loscocco and Spitze s study (1990) of gender has no effect on the relationship between job conditions and level of wellbeing. Because of the interaction terms in model 3, job status and gender have to be studied together not independently i.e. the effect of job status now must be evaluated separately for men and for women. Similarly, the effect of gender must be now evaluated separately by job status. To do so, I have to add the main effect and the interaction effect together. So the negative effects for men in semi routine job is [.467(main effect)-.322 (interaction effect) =0.145] differences in health scale compared to men in intermediate job. However, the health differences for women in semi routine job is higher (0.467) compared to men in semi routine job status. In other words, women in semi routine job have worse health, relative to those in intermediate occupations, than men. However, women and men report almost similar results in the differences of health scale when comparing between high statuses positions (managerial and professional) and intermediate job status. For men in high occupation is (-0.567-0.041 = - 0.526), for women is -0.567. In other words, the positive relationship between high job status and subjective general health is strong for men and women.

To understand the differences between gender and job status overall, I create a comparison table of predicted value by completing the regression equation: 1: For men in high job status: Y (Subjective general health) = constant (11.08) + pro/mange (- 0.567) +Male (-0.66) +pro/mange*Male (-0.041) = 9.812

2: for women in high job status: (11.08) + pro/mange (-0.567) =10.513 3: For men in semi routine job status: Y = constant (11.08) + semi routine (0.467) +Male (-0.66) +semi routine*Male (-0.322) =10.565 4: for women in semi routine job status: Y = constant (11.08) + semi routine (0.467)=11.547 5: for men in intermediate job status: Y = constant (11.08) +Male (0.66) =10.42 6: for women in intermediate job status: Y = 11.08 (constant)