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ORIGINAL ARTICLES |
From the Department of Psychology, Division of Applied Psychology, University of Helsinki, Helsinki, Finland (M.K.); Finnish Institute of Occupational Health, Helsinki (M.K.) and Turku, Finland (J.V.); Department of Social Research, National Research and Development Center for Welfare and Health, Helsinki, Finland (M.E.); and Department of Public Health, University of Turku, and Turku University Central Hospital, Turku (B.L., M.V.K.), Finland.
Address reprint requests to: Mika Kivimäki, Department of Psychology, Division of Applied Psychology, P.O. Box 13, 00014 University of Helsinki, Finland. Email: mika.kivimaki{at}occuphealth.fi
| ABSTRACT |
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METHOD: The initially healthy participants were 2991 (796 men, 2195 women) municipal employees who had taken no sick leave in 1995. In 1997, they completed a questionnaire requesting information on recent life events and psychological and behavioral factors. The outcome was recorded sickness absences in 1998.
RESULTS: In men, the death or serious illness of a family member, violence, and financial difficulties increased the risk of later sickness absence. According to structural equation modeling, violence and financial difficulties also induced psychological problems such as anxiety, mental distress, and lowered sense of coherence. Psychological problems were associated with heightened cigarette and alcohol consumption, which in turn increased sickness absence. A corresponding structural model did not fit the data in relation to death or serious illness of a family member. In women, life events were associated with psychological problems and smoking but not sickness absence.
CONCLUSIONS: Longitudinal evidence suggests that increased psychological problems and behaviors involving risk to health partially mediate the effect of stressful life events on health, as indicated by sickness absence. This model received support among men and for the event categories of violence and financial difficulties. Women were less affected by stressful life events than men.
Key Words: life event, health, health-risk behaviors, anxiety, mental distress, sense of coherence.
Abbreviations: GFI = goodness-of-fit index;; SRMR = standardized root mean squared residual.
| INTRODUCTION |
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Stressful life events are a potential source of psychological problems (17, 18). For example, the number of life events in general and of specific events categorized as dangers has been associated with the onset of anxiety (3, 5, 19), and a variety of different stressful events have been associated with increased likelihood of mental distress, as assessed by the General Health Questionnaire (2022). Major or cumulative life events (eg, violence or sexual abuse) may also cause negative changes in individuals sense of coherence (8, 2325). Feldt and colleagues (26) reported that even moderate stressors (negative changes in leadership at work) predicted a decrease in the employees sense of coherence, which, in turn, was associated with a weakening of health. Sense of coherence refers to generalized appraisals of the world, characterized by meaningfulness (ie, demands are interpreted as meaningful and challenges are seen as worthy of being taken up rather than as stressors or threats), manageability (ie, one perceives oneself as having sufficient resources to deal with ones environment), and comprehensibility (ie, the environment is perceived as structured, predictable. and explicable) (23, 2729).
Stressful life events have also demonstrated a relationship with health-risk behaviors, such as smoking and alcohol abuse (8, 16, 30). Divorce, being a victim of a crime, and decrease in financial position have been positively associated with heavy drinking in men (31), but the evidence is not consistent for other event categories or life events in general (32, 33). Divorce among women, irrespective of their age or the presence of children, has predicted an increase in alcohol consumption (34, 35).
All the psychological problems and health-risk behaviors reviewed above (ie, anxiety, mental distress, low sense of coherence, smoking, and high alcohol consumption) are well-known predictors of ill health (3639). Therefore, it is reasonable to hypothesize that these factors are potentially involved in the association between stressful life events and health. Psychological problems may cause direct pathophysiological changes and increase the likelihood of health-risk behaviors (39).
| The Present Study |
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| METHODS |
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Stressful Life Events
The measure of weighted life events was based on the list of 13 negative life events derived from those used in earlier studies (42, 43). For each event, we asked the point of time for occurrence with a response format including the categories during the preceding 12 months, earlier, never and the severity of the event with the response categories 1 = not so burdensome, 2 = burdensome, 3 = extremely burdensome. Only events during the preceding 12 months were considered in this study.
Weights were squared means of severity ratings calculated for each event. Calculations were based on information from all 6442 respondents, including also those with sickness absence at baseline. The 13 events were classified into four categories: 1) death or severe illness of a family member (four items on the occurrence of death or severe illness of ones own child or spouse); 2) being a victim of physical, psychological, or sexual violence (three items); 3) severe interpersonal conflict (three items measuring divorce, breakdown of some other important social relationship, and relational problems with spouse); and 4) severe financial difficulties (three items measuring loss of ones job, unemployment of spouse, and financial hardships). The mean severity scores of events for death or illness of a family member, violence, interpersonal conflicts, and financial difficulties were 6.1, 5.5, 4.7, and 3.8, respectively. For each participant, the sum of weighted events in each category was calculated.
Psychological Factors
Psychological problems studied were anxiety, mental distress, and sense of coherence. Anxiety was measured using the six-item Anxiety-Trait Scale (items 1, 6, 10, 13, 16, and 19) (44). We used the trait scale instead of the state version because a short-term mood is not a likely risk factor for sickness absence and thus not a potential intervening factor. With the Anxiety-Trait Scale, the respondents were asked to indicate how well statements (eg, "I feel calm" and "I feel upset") describe them in general, as expressed on a scale ranging from 1 (not at all) to 4 (very much so) (Cronbach
= .84).
Mental distress was determined using the 12-item version of Goldbergs (45) General Health Questionnaire, which has produced results comparable with the longer versions of the General Health Questionnaire (46). The respondents rated the extent to which they had experienced symptoms such as depressive mood, anxiety, insomnia, and social dysfunction during the past weeks. The 12-item version has been associated with other measures of psychiatric disorders (46, 47) and has good discriminant validity in terms of the pattern of low or zero correlations with several personality dimensions (48). In the present sample, this measure was used as a sum score divided by the number of items (Cronbach = .89).
Sense of coherence was assessed using Antonovskys (27) short Orientation to Life Questionnaire measuring the aspects of meaningfulness, comprehensibility, and manageability with 13 items (eg, "How often do you have the feeling that you are not sure you can keep things under control?"). Without specifying the exact period of time, the respondents were asked to check their level of agreement with each item on a seven-point semantic differential scale with two anchoring phrases (eg, 1 = never happened, 7 = always happened) (Cronbach
= .82).
Behavioral Factors
The following behavioral factors were assessed: smoking, alcohol consumption, and alcohol intoxication. Smoking status was assessed by means of a question on whether the respondent was currently a regular smoker or not. Use of alcohol, expressed as logarithmically transformed grams of absolute alcohol consumed in an average week, was assessed using the four-item measure of Kaprio et al. (49). It requests the frequency and amount of alcohol used during an average week (or month) separately for beer, wine, and spirits. Alcohol intoxication was assessed by a single-item measure on the frequency of alcohol-induced loss of consciousness (passing out) during the last 12 months. Responses were dichotomized (no passing out vs. one or more episodes of passing out).
Sickness Absence
Our measure of sickness absence was the number of days absent from work due to sickness per person-year. We picked out all the periods coded as sick leave from January 1 to December 31, 1995 (sickness absence at baseline), and from January 1, 1997 to December 31, 1998 (the outcome) from employers records on absences. We checked the records for inconsistencies. Overlapping episodes of sick leave were combined.
Employers participating in the 8-Town Study record each sick-leave period of every employee, including the dates when each episode started and ended. In the towns studied, employees are paid full salary during their sick leave from the first day. The employers receive compensation for loss of salary due to sick leave longer than 8 days from the Finnish Social Insurance Institution. The employers are motivated to keep strict records of the sick leave because all the compensation to which they are entitled is based on the records.
Maternity leaves and absences due to caring for a sick child are not included in the sickness absences. Finnish municipality work contracts allow an employee to be absent from work without interruptions in salary payment to care for a child under 10 years old with an acute illness. Each such absence spell is fully compensated up to 3 days, and there are no limitations on the number of episodes per employee per year. Thus, the participants had no reason to wrongly report being ill when staying at home to care for their own sick child.
Statistical Analysis
The hypothetical model was tested with structural equation modeling using LISREL 8.30 (50). This statistical program offers several indices to evaluate the fit of the model. We used the
2 test, the goodness-of-fit index (GFI, values over .95 indicating acceptable fit), and SRMR (values .05 or below indicating an acceptable fit).
Testing was done separately for four major event categories (ie, the death or serious illness of a family member, violence, interpersonal conflict, and financial difficulties) in three steps: 1) testing of the null model, 2) testing of the measurement model, and 3) testing of the structural models (51). Age, life events, and sickness absence were treated as single-item factors with error variance fixed as zero. Anxiety, mental distress, and sense of coherence were observed variables for the latent construct of psychological problems. The construct of health-risk behaviors comprised measurements of smoking, use of alcohol, and alcohol intoxication.
In the null model, all observed variables were assigned to the same factor. The measurement model related the observed variables to the underlying constructs by means of confirmatory factor analysis. The next step tested the efficacy of the alternative structural models. Comparisons were made between a main effect model, containing life events, psychological problems, and health-risk behaviors as independent predictors of sickness absence, and the partial mediation model, where life events were additionally linked with psychological problems. To examine the nature of the mediated effects, comparisons were made between the partial mediation model and the full mediation model. The first-mentioned model included a direct link between life events and sickness absence, whereas the latter did not. In the full mediation model, life events were indirectly associated with sickness absence through psychological problems and health-risk behaviors.
| RESULTS |
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Of the participants, 8% (186 women and 49 men) had experienced death or severe illness of a family member, 7% (146 women and 47 men) had been a victim of a violent incident, 12% (255 women and 81 men) had been involved in interpersonal conflicts, and 11% (238 women and 95 men) had experienced financial difficulties. There were no differences in the frequency of and weighted sums of event categories between men and women.
Table 1 shows bivariate correlations among variables for men. Event categories were correlated with each other except for death or illness of a family member. Violence, interpersonal conflict, and financial difficulties were correlated with increased psychological problems as indicated by measures of anxiety, mental distress, or lowered sense of coherence. Financial difficulties and violence were correlated with unhealthy use of alcohol, but death or illness of a family member was associated with lowered use of alcohol. All life events except interpersonal conflicts were correlated with increased risk of sickness absence. Although all of the above-mentioned correlations were statistically significant, they were relatively low (coefficients between r = .08 and r = .25).
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For violence (Figure 3) and financial difficulties (Figure 4), the partial mediation model fit the data significantly better than the main effects model and the full mediation model (Table 3). The partial mediation model also reached an acceptable level of fit (GFI > .95, SRMR
.05). According to these findings, psychological problems and health-risk behaviors were linking factors between the life events and sickness absence. In addition, there was a direct link between the events and sickness absence, and this link was independent of the level of anxiety, mental distress, sense of coherence, or smoking and alcohol consumption.
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| DISCUSSION |
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In accordance with prior research, we found that all the event categories studied were associated with increased psychological problems and impaired health (115). The death and serious illness of family members are generally considered stressful life events. In the present study, they were rated as the most severe events. Holmes and Rahe (42) have specified that the loss of a spouse may be the most stressful life event. Other studies suggest that the loss of a child is at least as stressful if not more so (52).
Other life events, such as violence, interpersonal conflicts (eg, divorce), and financial difficulties were not rated as stressful as death or illness of a family member. However, a history of violence is particularly difficult to measure (53, 54). Koss (54), eg, found that many women with experiences that meet the legal definition of rape did not respond affirmatively to the study questions on this issue. Considering potential limitations in the validity of the measurement, the present results on violence may underestimate rather than overestimate health effects.
Different types of life events may be concentrated among the same people (14). Violence, interpersonal conflicts, and financial difficulties were interrelated both for men and women, but the interrelationships were moderate or weak. Death or illness of a family member was not related to other life events for men. For women, it was related to financial difficulties, which is as expected because, in many cases, the event refers to the loss of the primary wage earner in the family. A death or illness of a family member is usually entirely a person-independent event, but violence, interpersonal conflicts, and financial difficulties can be partially person dependent (14).
As in prior research (41, 5557), men were more affected by life events than women. Among both sexes, life events were associated with psychological problems such as anxiety, mental distress, and lowered sense of coherence. However, increased risk for sickness absence was observed only for men. Additional analyses of those who had had a stressful event showed smaller social support networks for men than women. Social support might help in coping with life events (14) and thus provide a partial explanation for mens higher vulnerability. These sex differences may also be related to gender-related selection into the working population and to occupational segregation.
Among men, the presently obtained parameter estimates of .08.13 between life events and sickness absence indicate significant, if relatively small, effect sizes. This is to be expected from a theoretical point of view because multiple factors influence health. These include, eg, inherited characteristics, personality traits, socioeconomic position, working conditions, job characteristics, the structure and quality of interpersonal relations at work and in private life, features of living circumstances, and exposure to epidemics.
Findings of the structural equation modeling imply that part of the adverse health effects of life events may be avoidable if the person could cope with increased psychological distress without heightened alcohol use and smoking. In prior research, psychological problems such as posttraumatic disorders have been related to the effects of traumatic events on physical health (58). Our findings in men suggest that increased psychological problems and health-risk behaviors in combination may partially mediate the association between life events and illness. This model was supported in relation to violence and financial difficulties but not in relation to death or illness of a family member and interpersonal conflicts. Unlike in other events, death or illness of a family member was related to lower levels of alcohol consumption. The literature shows that some stressful events at the workplace, eg, major downsizing, may decrease rather than increase alcohol intake among employees (9).
Methodological Considerations
Studying the effects of life events is methodologically challenging (5961). A strength of the present study is the opportunity to focus on a large nonclinical population in a longitudinal design with measurements of health status before the life event. The large sample size provided statistical power for separate analyses of different event categories.
In the present study, bias due to sample attrition or selection procedures is unlikely. Demographic characteristics of the participants corresponded with those of the racially homogenous white eligible population. Differences in survey responses between the participants and all respondents were minimal. During the follow-up period, the participants had fewer health problems than did the eligible employees, which is as expected considering that the former were initially healthy.
We measured sickness absences to determine changes in health. Although sickness absence is not a widely used health outcome, it has been argued to serve as a measure of health in the working population when health is understood as a combination of social, psychological, and physiological functioning (9, 15, 62). Such data have several advantages in the study of life events. First, they reflect major illnesses and also minor health problems that are often not possible to derive from the morbidity and mortality registers. Second, sickness absence data cover information on the health problems faced by employees on every working day of the study period. This helps in the determination of dating health problems. The quality of the data in terms of coverage, accuracy, and consistency over time can also be higher than that attained via self-reports. Third, by using records on sick leave, common-method variance with life events is avoided. Because the recording process for sick leave is a routine procedure, the impact of measurement on the studied responses is minimized.
Our estimates of the association between stressful life events and health should be regarded as conservative. We measured all sickness absences in the year after a participant had an event. Within the year, the exact point of time for the event was not requested. Some events occurred in the beginning, others in the middle, and still others at the end of the year. At least in the first two cases, the effect of the event on sickness absence may have been an underestimation due to the relatively long time lag between the measurements. Unpublished data on the men of the present cohort show that death or serious illness of a family member and interpersonal conflicts were more strongly associated with sickness absence in the year the participants had experienced the events than in the following year.
Similarly to most life-event studies (3, 16), the present study did not include a measurement of the underlying factors before the events. An ideal design would include this measurement; it would allow confirmation that the test on explanatory factors actually relates to a change in the intervening factor rather than to its stable level. Our inclusion criteria for participants, however, made confounding in this regard unlikely. To detect a psychological or behavioral factor as a link between an event and health, the factor needs to be strongly associated with health. Stable differences in such a factor between participants would create health differences at the baseline. In the present study, only initially healthy subjects at the baseline met the inclusion criterion. Thus, the effects of stable factors biasing the results were, to a large extent, eliminated.
| CONCLUSIONS |
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| ACKNOWLEDGMENTS |
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Received for publication September 29, 2000.
| REFERENCES |
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