The link between mental health and job characteristics: the case of Russia
The emergence and spread of mental health problems. Characteristics and specificity of the factors affecting the mental health of the individual. The negative impact of demand on the employee's work and mental health. Evaluation of health and education.
| Рубрика | Психология |
| Вид | дипломная работа |
| Язык | английский |
| Дата добавления | 09.08.2018 |
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ФЕДЕРАЛЬНОЕ ГОСУДАРСТВЕННОЕ АВТОНОМНОЕ
ОБРАЗОВАТЕЛЬНОЕ УЧРЕЖДЕНИЕ
ВЫСШЕГО ОБРАЗОВАНИЯ
«НАЦИОНАЛЬНЫЙ ИССЛЕДОВАТЕЛЬСКИЙ УНИВЕРСИТЕТ
«ВЫСШАЯ ШКОЛА ЭКОНОМИКИ»
Факультет «Санкт-Петербургская школа экономики и менеджмента» Департамент экономики
Выпускная квалификационная работа - БАКАЛАВРСКАЯ РАБОТА
по направлению подготовки 38.03.01 «Экономика»
студентки группы № 145
образовательная программа «Экономика»
The Link between Mental Health and Job Characteristics: the Case of Russia
Barilo E.A.
Санкт-Петербург 2018
Abstract Most of the population to some extent experiencing problems with mental health: depression, sleep disorders, anxiety, obsessive feeling of loneliness, etc. Mental disorders are among the leading cases of disease and long-term disability. Therefore, they are one of the most serious public health problems in the world. One of the main factors influencing mental health is the employment characteristics of an individual. We investigate how factors of work demand affect mental health using Russian data collected using data from the annual individual survey Russian Longitudinal Monitoring Survey. We use binary choice models: logit and probit, with time fixed effects and without. Variables are selected based on the demand-control model. In addition to the main hypothesis about the negative impact of work demand on mental health, we assessed the marginal effects compared between entrepreneurs and non-entrepreneurs, as well as separately evaluated the effects for workers in the field of health and education.
Keywords Mental health Work demand Occupational health Panel data Probit model Logit model
Introduction
According to the World Health Organization (WHO), mental disorders are among the leading causes of disease and long-term disability. Therefore, they are one of the most serious public health problems in the world. These disorders cause depression, increase susceptibility to infectious diseases, diabetes, high cholesterol levels, cardiovascular diseases. This is the reason why the issue of factors of influence on MH is being investigated more and more.
Problems related to mental health, are widely distributed: 16.7% of adults have a mental health problem. Half of them have been experiencing the problem for more than 1 year. A major public health problem around the world is depression. It accounts for 15% of all disability in high income countries [7].
One of the primary questions: what is mental health? Often, mental illness means the presence of serious diseases such as Alzheimer's disease or epilepsy. Accordingly, health is the opposite. But it is wrong. According to WHO, mental health is not just the absence of mental illness, but a complete physical, mental, and social well-being. Moreover, it is when an individual fully realizes his potential, copes with stress, works productively and benefits society [26]. Mental health indicators in the literature are based on this definition.
To improve mental health, decision makers need to understand what the determinants are. The impact on mental health occurs both at the level of society and at the level of the individual. At the level of society inputs are: level of social support, environment, crises, social stability, etc. At the individual level, mental health is influenced by many factors: the well-being of the family and loved ones, relationships with people, lifestyle, health. One of the important factors of influence is work. The relationship between performance and mental health is studied by many researchers around the world. This article discusses the impact of work demand (WD) on mental health in Russia.
The paper is structured as follows. First, the modern literature on the topic is considered and the first assumptions are made. Then we consider the situation with mental health in Russia: statistics and problems. Theoretical basis considers the theories and models underlying modern articles. We provided a description of the data then and compiled mental health portrait in Russia from these data. After the initial analysis, the hypotheses of the study were written. In the section results presents quotes from interviews independently and then the results of estimating the models in order to test the hypotheses of the study. The discussion describes the further development of the research and the current problems. Then the conclusions and policy recommendations for Russia are given.
Literature review
In different works, various indicators of mental health are presented. This is due to the fact that there is no unified theory that determines unambiguous indicators of mental health. The most common indicators are:
* stress, irritability, poor sleep, anxiety [4][22],
* symptoms of frustration, depression, psychosomatic symptoms [25],
* feelings of loneliness, constant stress, insuperability of their difficulties, exhaustion or fatigue, inability to concentrate, frightening thoughts, etc. (General Health Questionnaire)
Articles written on the topic of the connection between job indicators and mental health are based on a similar theory. The most popular models for a long time are as follows:
1. Demand-Control-Support (JDC-S) model [20]
2. Job demands-resources (JDR) model [6]
3. Job Characteristics (JC) model [10]
4. Vitamin Model (VM) [32]
5. Conservation of resources (COR) theory [15]
Models are discussed in detail in the theoretical basis section.
Analysis of modern literature leads us to the following notes. WD affects the internal vigor of the people. The high rate of WD the lower "vigor", including mental vigor. The "vigor" decreases with age [1]. Women are characterized by lower levels of "vigor" [5]. Another study found a positive relationship between the severity of depression due to economic difficulties from age [27]. There is a non-linear dependence on age and the need to take into account U-curve relationship with [24].
Other studies say that WD has a positive effect on anxiety [19], on absenteeism [31]. Methods of supporting workers can compensate absenteeism to reduce it.
WD is differently manifested in workers of different professions. For jobs with high tension, WD has a stronger impact [31]. For example, such occupations include employment in the health sector [28] [18] and education [12]. Those professions where the employee often has to make responsible decisions and interact more often with people, while controlling their schedule, their intensity at work, they cannot, are at risk.
In addition to the negative influence of WD on mental health, the positive influence of freedom to make decisions, to choose working methods and the pace of work exists. For example, entrepreneurs experience a weaker impact of WD, because they can control their work schedule, they have more freedom in deciding on methods of work and goals. At the same time, entrepreneurs who have subordinates experience more stress, which is also an indicator of WD [14].
More often, mental disorders are observed in representatives of the lower social class, i.e. income and mental health are linked positively [23]. This is partly due to the inability to afford qualitative and timely treatment. In addition, representatives of the lower social class cannot afford living in a prosperous region, and therefore they are more susceptible to the negative influence of environmental factors in the urban environment [2].
Mental Health in Russia
Statistics
In the Russian Federation, the number of cases of mental and behavioural disorders has been reduced by almost half from 2000 to 2015 (Federal state statistics service of Russia). Fig. 1 shows a negative trend in the number of mental and behavioral disorders in thousands of people (vertical axis). The source of data is Federal state statistics service of Russia. This figure there is an evident of decreased by 2 times over the past 16 years.
Compared to European countries, the Russian population seems to be extremely mentally healthy. However, official data do not reflect the actual state of mental health of the population. The reason for this is the special attitude of Russians to mental problems, which is associated with historical features.
The negative trend in disease statistics in modern Russia is partly because this is a way out of the crisis, not a move forward. In addition, Russians tend not to talk about their problems if they relate to mental health. This is a legacy of the USSR.
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Historical background
Under the USSR, mental health care system was built in such a way that people were afraid to talk about problems with their heads.
The fact is that during the economic crisis after Civil War, 1918-1922, the lack of funds led to reduction in medical settings, instead of them opened agencies providing outpatient care, district dispensaries to maintain diseases prevention, hygiene, healthier living and working conditions. The principles of the young Soviet state paid full attention to preventive care. Technically the MHC system in the USSR was quite well developed. At the same time, the system was characterized by the following:
- not multiprofessional approach
- a highly - closed treatment (only by psychiatrists)
- ideological influence and institutional control
- isolation of the sick
All this facts contributed to stigmatization and stereotyping of the sick. The doctor could tell the employer about mental illness of the worker, because of what the worker could be reduced.
Only in 1992 the law, according to which the medical secret is kept when visiting a psychotherapist by a patient, was adopted. It's only been 25 years since that, it turned out to be not enough time to change the attitude to problems with MH.
The situation was aggravated by the growth of mental health problems after the fall of communism due to subsequent economic crises. Then there were serious social and health problems. Economic and political reconstruction in Russia has been accompanied by significant social upheavals, including an increase in family breaks, drug addiction, crime, poverty and suicide [3]. Russia's economic and social situation has deteriorated further since the 1998 economic crisis. Only between 2001 and 2011 the prevalence of high psychological disorders declined, but socially and economically marginalized groups continue to experience severe problems with mental health [9].
From the interview with Dr Shekhar Saxena, Director of the Department of Mental Health and Substance Abuse:
"...in Russia, psychiatrists are still afraid as a fire and postpone their visit until the last. The stamp of a psycho or suspicion that you had some problems with the psyche, in fact, closed many doors to people."
Shekhar Saxena also notes the stigmatization of patients in Russia, the small budget for health care and the lack of quality training of General practitioners and nurses.
Under-investigation
It is important to note that in the scientific community in Russia not so much attention is paid to the problems related to mental health. Research in the field of Russian mental health has arisen in relation to human rights violations, political abuse and biologo-oriented psychiatric care in the USSR. There is neither systematic analysis of Russian psychiatry, nor analysis of MH.
• However, from the available works about Russia, we can conclude the following:
• Prevalence is 70% higher than in the UK, with small differences in the type of disorders and risk factors [8].
• Determinants: psychological inquiries, the possibility of making decisions (decision latitude), the imbalance of effort and reward, poor work relationships [30]
• The risk is greater for men [30], in another paper for women [3]
• Prevalence of symptoms is comparable with some countries of the former USSR (Belarus, Ukraine, Moldova) [9]
• There is a positive trend from 2001 to 2010 [9]
Theoretical basis
The most popular models underlying the modern literature on the relationship between occupational characteristics and MH indicators are considered in the article. The field of science that studies the relationship between occupational safety and MH indicators is called occupational health psychology. In addition, we are interested in models from the theory of motivation of workers, since the motivation to work good is related to job satisfaction, which is also closely related to the satisfaction of MH.
Demand-Control-Support model
One of the dominant models in OHP is the Demand-Control-Support model or the Job-Strain model developed by R. Karasek and T. Theorell in 1990 [20]. Its essence lies in the fact that workers working in jobs with high loads (that is high demands, low job control and low social support) will be to experience a higher number of health problems, including MH problems. And the effect of job demand on mental health occurs with a delay of 1-year lag. Schematically, the model can be represented as on the Fig. 2
The model was tested by more than 100 studies, mentioned in the book of Karasek and Theorell. For example, in article [21], it is said that only 2 studies of the DCS model and cardiovascular diseases out of 16 mentioned in the article had results that contradict the model.
According to the model, all jobs are divided into 4 types. "High-strain jobs" are the most risky. They are characterized by a high level of fatigue, anxiety, depression and physical illnesses. For these jobs task latitude is low.
The employee is constantly in tension, but does not decide anything himself, does not control the work process and the application of skills fully.
The DC (DCS) model is often criticized. One of the important critical arguments is prejudice. There is a tendency among workers with a poor state of psychological health to report a greater work load than workers with good health. This problem is noticeable especially in cross-sectional and case-referent studies. To use the model, it is better to use panel data or subjective data (for example medical indicators).
DemandsResources (JD-R) Model
Another popular model among researchers is Job Demands-Resources model [6]. It is similar to the previous one, but JDR model is broader and more flexible in terms of interpretation. The model also includes the concept of work demand. It also leads to stress and to the process of deteriorating health. However, instead of the terms “control” and “support”, the term “resources” is introduced. Resources include a whole list of determinants. Their influence leads to an increase in motivation at work and, consequently, to better results and increase of productivity. These determinants include job control, and social support, as well as feedback, rewards, job security, participation in work decision process.
The scheme of the model is on the Fig. 3
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According to the model checking job demands were positively related to exhaustion (and MH too). Parameters of work demand are physical workload, time pressure, recipient contact, features of physical environment and shift working. On the other hand job resources were negatively related to disengagement. Work engagement is a state of the worker when he has internal forces leading to a positive mood and a desire to work. The concept of vigor is related to several aspects: physical vigor, mental activity, enthusiasm, a sense of significance, concentration and joy from the work process and results. High job demands can lead to burnout, which negatively affects vigor. With such influence, the worker may develop cardiovascular diseases and MH problems (for example, depression). That is, Job Demands affect MH indirectly through burnout. In the original article, the simultaneous equation modeling is used to estimate the coefficients. That is, the model allows a reverse or bi-directional causal relationship.
The popularity of models is determined by several reasons [29]. The first reason is that both models use the concept of equilibrium between positive (resources) and negative (demands) characteristics of work. The balance of equilibrium seemed attractive to researchers. The second reason for popularity concerns exactly the JSR model. Because the model includes all the work requirements and work resources that affect employee well-beeing, it can be interpreted relatively freely and applied to a large data resources. That is why there is no single model of JSR.
Conservation of resources theory (COR)
Alternative Hobfoll's COR theory also considers the impact on motivation from the point of view of "resources" [15][16]. COR theory believes that people want to receive, preserve and protect resources. If they lose resources or do not receive a return on the investment of resources (for example, material compensation), then there is stress. The contribution of the COR in the context under consideration lies in the following statement. People who have more resources are less likely to face stressful situations that adversely affect MH and well-being. The negative impact of the word demands can be diminished by increasing the resource reserves.
Job Characteristics Model (JCM)
Another model used in the theory of work design and motivation of employees is Job Characteristics Model (JCM) [10][11]. The authors of the theory investigated the conditions under which workers will be motivated to perform their work effectively. According to JCM, there are five main characteristics of work that affect three important psychological states. This is the skill variety, task identity, task significance, level of autonomy and job feedback.
Ш The variety of tasks includes the number of different tasks that the employee can solve, the variety of techniques and skills that he uses when performing tasks, the absence of routine.
Ш The identity of tasks is understood as the content of tasks and the availability of time frames for them. This helps to understand the personal contribution to the common work.
Ш Significance shows how important tasks seem to the worker, his colleagues and the whole organization. Significance allows us to evaluate the usefulness of labor.
Ш Autonomy reflects the independence of the employee in choosing the means and methods by which tasks will be performed, as well as in choosing the sequence of tasks and their time frames. Too high level of autonomy is also not a positive motivator, as the employee loses his sense of support and feels isolated.
Ш Finally, feedback is an assessment of the effectiveness and results of work on the part of the employee and the environment.
Scheme of the model is represented on the Fig. 4.
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Vitamin model
Warr's Vitamin model is also quite old, but used in some research [19][32]. The influence of job characteristics on mental health indicators was studied. These indicators are affective well-being, competence, autonomy, aspiration, and integrated functioning. The main feature of the model is the assertion of non-linear relations between job characteristics and mental health, including well-being. According to the author of the theory, the features of workplaces can be divided into 2 categories according to the shape of the influence:
- the first category: job autonomy, job demands, social support, skill utilization, skill variety, and task feedback. These are the characteristics of the work that affect the indicators of mental health by the U-shaped way. This is shown by line with “Additional Decrement” in the Fig. 5.
- the second category: salary, safety, and task significance. These characteristics affect differently: first positive, then the marginal effect reaches zero and does not decrease further. This is the line with “Constant Effect” in the figure.
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Warr compared the effect of these 2 categories with vitamins: the first category corresponds to the effects of vitamins A and D, if too much, they are harmful. The second category corresponds to vitamins C and E, which do not harm with a large amount, just the effect of each additional portion brings less and less benefit to the body.
Thus, all models considered allocate work demand as a key category. It includes factors of tension, such as an irregular working schedule, exceeding the working day, shift work, etc. Based on the analysis of the literature, it can also be concluded that work demand rises in certain areas of activity, where there is also a low level of job control. Having freedom of choice, good evaluation of work by the worker and other people, the importance of the results of work helps to compensate for the negative effects of work demand on mental health.
Data and variables
The study is conducted on the Russian Longitudinal Monitoring Survey (RLMS) data. RLMS is a series of nationally representative surveys, which have been conducted among Russian households and individuals since 1992. Today it is the largest data storage on the Russian population, combined in panel data. The panel data structure is one of the main advantages of the study. The questionnaire includes questions on health, employment, entrepreneurship, consumption and use of services.
Questions related to mental health are not included in the annual questions, but also present. Table 1 presents the questions about mental health and the years in which these questions were asked (=1 if was asked). Data that is an indicator for word demand has also been selected. These indicators are:
· work more than 8 hours a day;
· work in the health and education sector;
· managerial position (the presence of subordinates);
· entrepreneurial activity;
· additional work;
· change of employment over the past year.
Table 1 Mental health variables by years
|
Year 20** |
01 |
02 |
03 |
04 |
05 |
06 |
07 |
08 |
09 |
10 |
11 |
12 |
13 |
14 |
15 |
16 |
|
|
Are you characterized by… …frequent nervousness? |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
0 |
0 |
0 |
0 |
|
|
…anxiety, frequent panic attacks? |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
0 |
0 |
0 |
0 |
|
|
…attacks of irritation, aggression? |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
0 |
0 |
0 |
0 |
|
|
…chronic insomnia? |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
0 |
0 |
0 |
0 |
|
|
…periodic depression? 1 = yes; 0 otherwise |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
0 |
0 |
0 |
0 |
|
|
Are you feeling anxious or depressed? 1 = yes; 0 otherwise |
0 |
0 |
0 |
0 |
1 |
1 |
1 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
|
|
Have you been disturbed by frequent sleep disorders during the last 12 months? 1 = yes; 0 otherwise |
1 |
1 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
|
|
Have you had serious nervous disorders, depression during the last 12 months? 1 = yes; 0 otherwise |
0 |
0 |
1 |
1 |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
1 |
1 |
1 |
1 |
1 |
|
|
Have you been seeing a doctor about a nervous disorder in the last 12 months? 1 = yes; 0 otherwise |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
1 |
1 |
0 |
0 |
0 |
0 |
0 |
0 |
|
|
Do you have chronic neurological diseases? 1 = yes; 0 otherwise |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
1 |
1 |
1 |
1 |
Most representative questions:
1) have you had serious nervous disorders or depression during the last 12 months? The panel includes data for 6 years (2011-2016)
2) do you have chronic neurological diseases? The panel includes data for 5 years (2012-2016).
These two questions are the dependent variables. It is important to note that chronic diseases are diseases that have developed over a long period. Therefore, the impact of the variables in these two cases is expected to be different.
Control variables included in the model: gender, age, income, education, family status, smoking, type of location.
Mental health portrait
To understand who these people are that responded to the study questions is "YES", compiled by mental health portrait.
Dynamics
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The section answers the question: how many people with mental health problems in dynamics in relative calculus? Fig. shows that one third of the respondents experienced frequent sleep disorders in the last year in 2001 and 2002. Fig. shows that in 2003-2004, almost one in five respondents experienced severe nervous disorders and depression over the last year. This is a very large indicator.
Fig. shows that in 2005 more than half of the respondents at least sometimes feel depressed. In this case, Fig. shows that only 1.5-2% of people go to the doctor if they have a nervous disorder. This confirms the fact that the Russians are not inclined to go to the doctor in case of mental health problems. If we compare the indicators, it turns out that 80 out of 500 people experience serious disorders during the year, but only 10 people turn to the doctor.
Table 2 Questions from the 2012 questionnaire
|
Yes |
All |
% of “Yes” |
||
|
Are you characterized by… …frequent nervousness? |
4576 |
15764 |
29.0% |
|
|
…anxiety, frequent panic attacks? |
3216 |
15780 |
20.4% |
|
|
…attacks of irritation, aggression? |
3675 |
15717 |
23.4% |
|
|
…chronic insomnia? |
2295 |
15757 |
14.6% |
|
|
…periodic depression? |
2532 |
15773 |
16.1% |
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Table 2 confirms the problem: about a third of respondents experience frequent nervousness, which is an indicator of mental health problems. Fig. 11 shows that chronic diseases occur on average in 6% of the respondents. Chronic diseases are the result of negative effects for many years, so it is logical that the percentage is not so large. However, the strong disorder and depression experienced during the year an average of 10-11% (Fig. ). This figure is less than in 2003-2004, but still large.
Who answered “Yes”
mental health personality
In Table 3, Table 4 and Table 5 there is an information about differences in proportions by all control variables.
Table 3 Сomparison of proportions. Question "Have you had serious nervous disorders, depression during the last 12 months?"
|
Varible |
All |
Answer "Yes" |
Answer "No" |
Diff |
Sign. |
||
|
Gender |
Female |
0.547 |
0.682 |
0.563 |
-0.136 |
0.01 |
|
|
Education |
Incomplete secondary |
0.140 |
0.170 |
0.143 |
-0.030 |
0.01 |
|
|
Secondary |
0.341 |
0.358 |
0.343 |
-0.016 |
0.05 |
||
|
Secondary special |
0.257 |
0.273 |
0.259 |
-0.016 |
0.05 |
||
|
Higher |
0.262 |
0.199 |
0.254 |
0.063 |
0.01 |
||
|
Marital status |
Not marriage |
0.160 |
0.142 |
0.158 |
0.018 |
0.05 |
|
|
Marriaged |
0.563 |
0.469 |
0.552 |
0.095 |
0.01 |
||
|
Live together |
0.127 |
0.144 |
0.129 |
-0.017 |
0.1 |
||
|
Divorced |
0.081 |
0.124 |
0.086 |
-0.043 |
0.01 |
||
|
Widow |
0.068 |
0.121 |
0.075 |
-0.053 |
0.01 |
||
|
Age |
18-24 |
0.131 |
0.114 |
0.129 |
0.018 |
0.1 |
|
|
25-34 |
0.236 |
0.195 |
0.231 |
0.041 |
0.01 |
||
|
35-44 |
0.206 |
0.198 |
0.205 |
0.008 |
No |
||
|
45-54 |
0.179 |
0.192 |
0.180 |
-0.013 |
No |
||
|
55-64 |
0.166 |
0.188 |
0.169 |
-0.022 |
0.01 |
||
|
65-72 |
0.082 |
0.114 |
0.086 |
-0.032 |
0.01 |
||
|
Income |
from 10 to 5000 |
0.142 |
0.263 |
0.154 |
-0.120 |
0.01 |
|
|
5001-10000 |
0.209 |
0.256 |
0.214 |
-0.046 |
0.01 |
||
|
10001-25000 |
0.543 |
0.417 |
0.530 |
0.126 |
0.01 |
||
|
25001-50000 |
0.071 |
0.048 |
0.069 |
0.023 |
No |
||
|
50001+ |
0.035 |
0.018 |
0.033 |
0.017 |
No |
||
|
Smoke |
Smoke |
0.660 |
0.652 |
0.659 |
0.008 |
No |
|
|
Does not smoke |
0.340 |
0.348 |
0.341 |
-0.008 |
No |
||
|
Location |
Central city of the region |
0.416 |
0.425 |
0.417 |
-0.010 |
No |
|
|
City |
0.264 |
0.271 |
0.265 |
-0.006 |
No |
||
|
Village |
0.320 |
0.304 |
0.318 |
0.016 |
0.05 |
Main conclusions:
1. women have worse health
2. educated with higher education have better mental health
3. married people have better, divorced people and widowers have worse health
4. mental health is worse with age (for young is better, for old is worse)
5. poor have worse mental health
6. citizens of small town have a little better health
Table 4 Сomparison of proportions. Question " Do you have chronic neurological diseases?"
|
Varible |
All |
Answer "No" |
Answer "Yes" |
Diff |
Sign. |
||
|
Gender |
Female |
0.563 |
0.558 |
0.649 |
-0.091 |
0.01 |
|
|
Education |
Incomplete secondary |
0.140 |
0.138 |
0.177 |
-0.039 |
0.01 |
|
|
Secondary |
0.333 |
0.333 |
0.336 |
-0.003 |
No |
||
|
Secondary special |
0.257 |
0.256 |
0.264 |
-0.008 |
No |
||
|
Higher |
0.271 |
0.274 |
0.223 |
0.050 |
0.01 |
||
|
Marital status |
Not marriage |
0.159 |
0.159 |
0.150 |
0.010 |
No |
|
|
Marriaged |
0.549 |
0.554 |
0.477 |
0.077 |
0.01 |
||
|
Live together |
0.133 |
0.135 |
0.103 |
0.032 |
0.1 |
||
|
Divorced |
0.086 |
0.084 |
0.129 |
-0.045 |
0.01 |
||
|
Widow |
0.073 |
0.068 |
0.141 |
-0.073 |
0.01 |
||
|
Age |
18-24 |
0.119 |
0.123 |
0.060 |
0.063 |
0.01 |
|
|
25-34 |
0.233 |
0.241 |
0.110 |
0.131 |
0.01 |
||
|
35-44 |
0.210 |
0.214 |
0.151 |
0.063 |
0.01 |
||
|
45-54 |
0.174 |
0.173 |
0.193 |
-0.020 |
No |
||
|
55-64 |
0.181 |
0.173 |
0.299 |
-0.126 |
0.01 |
||
|
65-72 |
0.082 |
0.076 |
0.187 |
-0.111 |
0.01 |
||
|
Income |
from 10 to 5000 |
0.046 |
0.045 |
0.077 |
-0.031 |
No |
|
|
5001-10000 |
0.191 |
0.190 |
0.232 |
-0.042 |
0.05 |
||
|
10001-25000 |
0.630 |
0.632 |
0.563 |
0.069 |
0.01 |
||
|
25001-50000 |
0.089 |
0.089 |
0.079 |
0.010 |
No |
||
|
50001+ |
0.044 |
0.043 |
0.049 |
-0.005 |
No |
||
|
Smoke |
Smoke |
0.330 |
0.334 |
0.267 |
0.067 |
0.01 |
|
|
Does not smoke |
0.670 |
0.666 |
0.733 |
-0.067 |
0.01 |
||
|
Location |
Central city of the region |
0.415 |
0.409 |
0.510 |
-0.100 |
0.01 |
|
|
City |
0.269 |
0.270 |
0.246 |
0.024 |
0.1 |
||
|
Village |
0.316 |
0.320 |
0.245 |
0.076 |
0.01 |
Main conclusions:
1. Women in the sample are more likely to have chronic diseases than men
2. Those who did not finish school, more often have chronic diseases; those who received higher education-they are less likely
3. Married and living together are less likely to have chronic diseases, divorced and widowed are more likely to have.
4. With age, chronic diseases are increasingly common.
5. Smokers are less likely to have chronic diseases
6. Living in the regional centers often have a chronic disease, in the cities, rarely, even more rarely in the villages
Table 5 Сomparison of proportions. Question "Have you been disturbed by frequent sleep disorders during the last 12 months?"
|
Varible |
All |
Answer "No" |
Answer "Yes" |
Diff |
Sign. |
||
|
Gender |
Female |
0.565 |
0.509 |
0.698 |
-0.189 |
0.01 |
|
|
Education |
Incomplete secondary |
0.162 |
0.126 |
0.247 |
-0.120 |
0.01 |
|
|
Secondary |
0.383 |
0.401 |
0.340 |
0.062 |
0.01 |
||
|
Secondary special |
0.267 |
0.275 |
0.248 |
0.026 |
0.1 |
||
|
Higher |
0.188 |
0.198 |
0.166 |
0.032 |
0.05 |
||
|
Marital status |
Not marriage |
0.144 |
0.175 |
0.073 |
0.101 |
0.01 |
|
|
Marriaged |
0.582 |
0.596 |
0.549 |
0.047 |
0.01 |
||
|
Live together |
0.102 |
0.107 |
0.091 |
0.016 |
No |
||
|
Divorced |
0.084 |
0.075 |
0.105 |
-0.030 |
0.05 |
||
|
Widow |
0.087 |
0.047 |
0.181 |
-0.134 |
0.01 |
||
|
Age |
18-24 |
0.159 |
0.198 |
0.067 |
0.131 |
0.01 |
|
|
25-34 |
0.206 |
0.249 |
0.106 |
0.143 |
0.01 |
||
|
35-44 |
0.207 |
0.223 |
0.169 |
0.055 |
0.01 |
||
|
45-54 |
0.192 |
0.176 |
0.228 |
-0.052 |
0.01 |
||
|
55-64 |
0.132 |
0.094 |
0.222 |
-0.128 |
0.01 |
||
|
65-72 |
0.104 |
0.060 |
0.209 |
-0.149 |
0.01 |
||
|
Income |
from 10 to 5000 |
0.843 |
0.834 |
0.873 |
-0.039 |
0.01 |
|
|
5001-10000 |
0.122 |
0.128 |
0.100 |
0.028 |
No |
||
|
10001-25000 |
0.035 |
0.037 |
0.026 |
0.012 |
No |
||
|
25001+ |
0.001 |
0.001 |
0.002 |
0.000 |
No |
||
|
Smoke |
Smoke |
0.373 |
0.407 |
0.293 |
0.114 |
0.01 |
|
|
Does not smoke |
0.627 |
0.593 |
0.707 |
-0.114 |
0.01 |
||
|
Location |
Central city of the region |
0.433 |
0.429 |
0.442 |
-0.013 |
No |
|
|
City |
0.248 |
0.250 |
0.245 |
0.005 |
No |
||
|
Village |
0.319 |
0.321 |
0.313 |
0.008 |
No |
Main conclusions:
1. Women have a much higher rate
2. Sleep disorders is higher among those who dropped out of school, less likely to have graduated from University or higher, even less those who only graduated from high school
3. Divorced and widowers worse the sleep state, not married better (perhaps due to age)
4. Worse state of sleep with age
Thus, the portrait of the average mentally ill person is as follows: it is a non-Smoking elderly woman, divorced or widow, living in the regional center, without higher education and with low income.
For further models, we will use questions about chronic diseases and serious nervous disorders, because these questions were asked longer than others.
What professions are most risky?
Often, studies are conducted on the representatives of professions that are included in the high risk quadrant in the DCS model.
Professions with high JD and low JC:
· lawyers and judges,
· doctors, medical staff [18][28]
· teachers [12]
· blue color workers [13]
We are also interested in entrepreneurs [17][14].
Comparative statistics by industry are presented in the table in Annex 1. As expected, indicators for the health and education sectors were the most significant.
Hypothesis and methods
The following hypotheses are tested
Hypothesis 1: high rates WD => MH getting worse. Support: DC-S
Hypothesis 2: entrepreneurs and self-employed people do not experience such a strong effect, but if there are subordinates, it increases. Support: DC-S and DC-R.
Hypothesis 3: WD effects are stronger (and more significant) for health and education workers
The dependent variables are binary (the answer to the question is Yes or no), so probit and logit models of binary choice were used. In addition, the models with time fixed effects were evaluated.
Results
Evidence of low levels of doctor visits
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The General trend of health improvement is really observed, as shown in the Fig. 12.
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However, the answers to the questions from RLMS also confirm the problem of non-attendance of doctors, because of which there is a distrust of the official data on the level of health in Russia. In 2005, 63% of respondents said that "being sick" means having a serious disease (Fig. 13). Constantly feel badly or be in constant tension - insufficient in the opinion of the respondents condition. This suggests a tendency to downplay the seriousness of one's physical or mental illness. In two thirds of cases of health problems, the respondents did not consult a doctor (Fig. 14).
Results of models' evaluation
Detailed model evaluation results are presented in Annex 2. The tables 6-10 shows the limit effects and their significance.
Table 6 Marginal Effects in models for all people
|
var |
ME probit(%) |
ME probit & time effects(%) |
ME logit (%) |
ME logit & time effects(%) |
ME probit(%) |
ME probit & time effects(%) |
ME logit (%) |
ME logit & time effects(%) |
|
|
Have you had serious nervous disorders, depression during the last 12 months? |
Do you have chronic neurological diseases? |
||||||||
|
Gender = male |
-2.33% |
-2.32% |
-2.09% |
-2.08% |
-0.11% |
-0.11% |
-0.21% |
-0.20% |
|
|
age |
0.08% |
0.08% |
0.07% |
0.07% |
0.01% |
0.01% |
0.02% |
0.02% |
|
|
age^2 |
-0.001% |
-0.001% |
-0.001% |
-0.001% |
0.000% |
0.000% |
0.000% |
0.000% |
|
|
marital status: marriage |
-0.57% |
-0.57% |
-0.49% |
-0.49% |
-0.12% |
-0.12% |
-0.22% |
-0.22% |
|
|
marital status: live together |
0.18% |
0.18% |
0.17% |
0.17% |
-0.12% |
-0.12% |
-0.22% |
-0.21% |
|
|
marital status: divorced |
1.13% |
1.13% |
1.00% |
1.00% |
-0.08% |
-0.08% |
-0.15% |
-0.14% |
|
|
marital status: widow |
1.41% |
1.42% |
1.26% |
1.26% |
-0.05% |
-0.05% |
-0.10% |
-0.10% |
|
|
diplom: secondary |
-0.19% |
-0.22% |
-0.19% |
-0.21% |
0.03% |
0.02% |
0.05% |
0.04% |
|
|
diplom: secondary special |
-0.35% |
-0.37% |
-0.32% |
-0.34% |
-0.01% |
-0.01% |
-0.01% |
-0.02% |
|
|
diplom: higher |
-0.89% |
-0.91% |
-0.81% |
-0.83% |
-0.02% |
-0.03% |
-0.04% |
-0.04% |
|
|
city |
-0.49% |
-0.51% |
-0.43% |
-0.44% |
-0.09% |
-0.09% |
-0.16% |
-0.16% |
|
|
village |
-0.24% |
-0.25% |
-0.20% |
-0.22% |
-0.14% |
-0.14% |
-0.27% |
-0.26% |
|
|
logarithm of income |
-0.66% |
-0.70% |
-0.58% |
-0.62% |
-0.03% |
-0.03% |
-0.05% |
-0.05% |
|
|
smoke |
0.84% |
0.85% |
0.75% |
0.75% |
0.01% |
0.00% |
0.01% |
0.01% |
|
|
harmful production |
0.08% |
0.09% |
0.07% |
0.08% |
0.00% |
0.00% |
0.00% |
0.00% |
|
|
change... |
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