Psychological problems, such as depression and anxiety, are among the most common health problems in the world that account for 30% of the global nonfatal disease burden [
People exposed to stressful life events are more likely to report subsequent psychological problems [
Studies have been approached the relationship between stressful life events and psychological problems in two ways. One group of studies examined the relationship between a single type of stressful life events (e.g., financial problems, social relations, and family conflicts) and a number of psychological problems or symptoms [
This cross-sectional study was conducted in the framework of the “Study of the Epidemiology of Psychological, Alimentary Health and Nutrition” (SEPAHAN) project that was performed in two phases on a large sample of Iranian adults [
Stressors were measured using a valid and self-administered stressful life events (SLEs) questionnaire [
Self-administered standard questionnaires were used to collect demographic (age, gender, marital status (single/married), education level (≤12 and >12 years of formal schooling), etc.) and lifestyle factors (weight (kg), height (m), and physical activity (inactive and moderately inactive/moderately active and active) based on General Practice Physical Activity Questionnaire (GPPAQ) [
Latent factor regression for grouped outcomes was used for modeling the relationship of stressful life events, as latent predictors, with psychological problems, as the grouped outcomes. In the modeling process, we also adjusted the effect of demographic variables (i.e., age, gender, marital status, and education level) and lifestyle factors (physical activity and body mass index (BMI)).
Quantitative and qualitative variables were expressed as mean ± standard deviation (SD) and number (percentage), respectively. We used independent Student’s
Typically, studies aiming to evaluate the effects of predictors on multiple correlated outcomes estimate these effects with fitting regression models to each outcome, separately. However, separate models lack power to detect small but potentially important effects of predictors on multiple correlated outcomes [
As described by Woodard et al., there are two approaches for modeling the relationship of predictor variables with multiple correlated outcomes [
First, according to Woodard et al.’s notations, we briefly describe the random effect model for multiple outcomes [
In contrast with the first approach, in the continuous latent factor model, one or more latent variables are introduced in order to induce correlation between related outcomes, so that the outcomes are viewed as multiple manifestations of the latent variables [
Woodard et al. used the Bayesian approach, based on Markov chain Monte Carlo, in order to estimate parameters.
In the previous section, we presented an overview of latent factor regression for grouped outcomes. In the aforementioned models, the independent variables (the length-
We follow the previous notations; for subject
We considered the estimation process of the model parameters via the maximum likelihood method. In the general model formulation, let
In the following, we adopted our introduced model and random effect model as a competitor approach and the results of both modeling approaches are presented. Goodness of fit of models was guided through comparing the Akaike Information Criterion (AIC) and the Bayesian Information Criterion (BIC) indices across models. Lower BIC and AIC values indicate better model fitting.
At first, we performed a factor analysis on the 11 stressful life events dimensions, based on principal component extraction approach and orthogonal Varimax rotation procedure. We found two interpretable factors based on the loaded items in each factor; then, in the final model, a confirmatory factor analysis (CFA) was adopted for constructing latent predictors. The following statistics and indices were used for evaluating the goodness of model fitting: the comparative fit index (CFI), the Tucker-Lewis index (TLI), and the root mean square error of approximation (RMSEA). CFI and TLI values range from 0 to 1; values of 0.90 or above indicate acceptable fit. The RMSEA value ranges from 0 to 1, with smaller values of this index indicating better model fit.
Then, the proposed latent factor regression for grouped outcomes with latent predictors (obtained from a confirmatory factor analysis) was fitted among psychological problems (anxiety, depression, and psychological distress) as grouped outcomes and two extracted factors from life events stressors as confirmatory latent predictors. The effects of predictors in crude and adjusted models were evaluated with considering demographic variables (age, gender, marital status, and education level) and lifestyle characteristics (physical activity and BMI) as confounder variables.
In this study, 4763 subjects with a mean ± SD age of
Demographics, lifestyle, psychological characteristics, and stressful life events of the study participants.
Characteristics | Total ( |
Males ( |
Females ( |
|
|
---|---|---|---|---|---|
Demographic characteristics |
|
36.58 ± 8.09 | 38.59 ± 8.61 | 35.16 ± 7.39 | <0.001 |
|
|||||
Married | 3776 (81.2) | 1812 (88.1) | 1964 (75.7) | <0.001 | |
Single | 874 (18.8) | 245 (11.9) | 629 (24.3) | ||
|
|||||
Undergraduate | 1986 (42.8) | 1124 (55.0) | 862 (33.3) | <0.001 | |
Graduate | 2650 (57.2) | 921 (45.0) | 1729 (66.7) | ||
|
|||||
Lifestyle characteristics |
|
25.07 ± 4.64 | 25.53 ± 4.91 | 24.72 ± 4.39 | |
Underweight | 161 (3.5) | 45 (2.3) | 116 (4.5) | <0.001 | |
Normal | 2282 (50.0) | 893 (44.9) | 1389 (54.1) | ||
Overweight | 1672 (36.7) | 867 (43.5) | 805 (31.3) | ||
Obese | 445 (9.8) | 186 (9.3) | 259 (10.1) | ||
|
|||||
Inactive and moderately inactive | 2855 (65.2) | 1057 (54.9) | 1798 (73.4) | <0.001 | |
Moderately active and active | 1522 (34.8) | 869 (45.1) | 653 (26.6) | ||
|
|||||
Psychological problems | Psychological distress | 2.08 ± 2.74 | 1.69 ± 2.50 | 2.38 ± 2.89 | <0.001 |
Anxiety score | 3.55 ± 3.72 | 2.96 ± 3.44 | 4.01 ± 3.87 | <0.001 | |
Depression score | 6.15 ± 3.38 | 5.57 ± 3.23 | 6.60 ± 3.42 | <0.001 | |
|
|||||
Stressful life events | Home life | 0.65 ± 1.04 | 0.59 ± 1.02 | 0.69 ± 1.05 | <0.01 |
Educational concerns | 0.76 ± 1.02 | 0.81 ± 1.08 | 0.71 ± 0.97 | <0.01 | |
Loss and separation | 0.52 ± 0.73 | 0.56 ± 0.76 | 0.49 ± 0.70 | <0.01 | |
Sexual life | 0.26 ± 0.54 | 0.27 ± 0.55 | 0.26 ± 0.53 | 0.88 | |
Health concerns | 0.43 ± 0.59 | 0.37 ± 0.58 | 0.49 ± 0.60 | <0.001 | |
Financial problems | 2.92 ± 1.77 | 3.15 ± 1.72 | 2.74 ± 1.79 | <0.001 | |
Social relations | 1.75 ± 1.37 | 1.64 ± 1.39 | 1.83 ± 1.36 | <0.001 | |
Personal conflicts | 1.16 ± 1.28 | 1.10 ± 1.27 | 1.21 ± 1.28 | <0.01 | |
Job conflicts | 1.73 ± 1.26 | 1.56 ± 1.26 | 1.86 ± 1.23 | <0.001 | |
Job security | 1.63 ± 1.21 | 1.69 ± 1.24 | 1.59 ± 1.19 | <0.01 | |
Daily life | 0.59 ± 0.72 | 0.57 ± 0.71 | 0.61 ± 0.72 | 0.07 |
Values are mean ± SD and number (%).
Table
Summary results of exploratory and confirmatory factor analysis on stressful life events.
Total ( |
Males ( |
Females ( |
||||
---|---|---|---|---|---|---|
EFA | CFA | EFA | CFA | EFA | CFA | |
|
||||||
Home life | 0.69 | 0.61 | 0.65 | 0.59 | 0.71 | 0.64 |
Educational concerns | 0.34 | 0.42 | 0.39 | 0.50 | 0.36 | 0.43 |
Loss and separation | 0.58 | 0.40 | 0.61 | 0.40 | 0.60 | 0.40 |
Sexual life | 0.61 | 0.41 | 0.55 | 0.38 | 0.63 | 0.40 |
Health concerns | 0.57 | 0.47 | 0.65 | 0.52 | 0.47 | 0.49 |
|
||||||
|
||||||
Financial problems | 0.70 | 0.61 | 0.76 | 0.65 | 0.63 | 0.63 |
Social relations | 0.66 | 0.63 | 0.64 | 0.67 | 0.68 | 0.61 |
Personal conflicts | 0.53 | 0.58 | 0.59 | 0.62 | 0.47 | 0.55 |
Job conflicts | 0.64 | 0.54 | 0.66 | 0.63 | 0.65 | 0.52 |
Job security | 0.82 | 0.72 | 0.82 | 0.73 | 0.79 | 0.70 |
Daily life | 0.53 | 0.51 | 0.53 | 0.54 | 0.55 | 0.48 |
Values are factor loadings. EFA: exploratory factor analysis; CFA: confirmatory factor analysis.
The correlation analyses’ results for assessing the relationship between scores of stressful life events and scores of psychological problems have been presented in Table
Correlation between the scores of stressful life events and the scores of psychological problems.
Stressful life events | Total ( |
Males ( |
Females ( |
||||||
---|---|---|---|---|---|---|---|---|---|
Psychological distress | Anxiety | Depression | Psychological distress | Anxiety | Depression | Psychological distress | Anxiety | Depression | |
|
0.314 | 0.406 | 0.346 | 0.295 | 0.387 | 0.319 | 0.328 | 0.425 | 0.369 |
Home life | 0.302 | 0.363 | 0.313 | 0.283 | 0.344 | 0.265 | 0.310 | 0.374 | 0.340 |
Educational concerns | 0.112 | 0.158 | 0.122 | 0.138 | 0.165 | 0.141 | 0.100 | 0.168 | 0.120 |
Loss and separation | 0.106 | 0.175 | 0.156 | 0.094 | 0.176 | 0.152 | 0.125 | 0.191 | 0.175 |
Sexual life | 0.170 | 0.205 | 0.181 | 0.154 | 0.182 | 0.153 | 0.184 | 0.228 | 0.208 |
Health concerns | 0.259 | 0.333 | 0.290 | 0.239 | 0.330 | 0.258 | 0.254 | 0.317 | 0.290 |
|
|||||||||
|
0.396 | 0.466 | 0.416 | 0.414 | 0.477 | 0.406 | 0.389 | 0.469 | 0.432 |
Financial problems | 0.168 | 0.238 | 0.213 | 0.209 | 0.279 | 0.226 | 0.172 | 0.254 | 0.247 |
Social relations | 0.365 | 0.390 | 0.339 | 0.380 | 0.395 | 0.319 | 0.342 | 0.373 | 0.339 |
Personal conflicts | 0.402 | 0.425 | 0.412 | 0.408 | 0.422 | 0.404 | 0.393 | 0.424 | 0.412 |
Job conflicts | 0.216 | 0.278 | 0.236 | 0.207 | 0.280 | 0.215 | 0.196 | 0.250 | 0.221 |
Job security | 0.284 | 0.320 | 0.273 | 0.317 | 0.349 | 0.299 | 0.277 | 0.318 | 0.271 |
Daily life | 0.245 | 0.327 | 0.280 | 0.254 | 0.343 | 0.286 | 0.234 | 0.314 | 0.274 |
All Spearman rank correlation coefficients are significant at
Table
The information criteria based on random effect and continuous latent factor models.
Total ( |
Males ( |
Females ( |
||||
---|---|---|---|---|---|---|
AIC | BIC | AIC | BIC | AIC | BIC | |
Random effect model | 166256.770 | 166532.982 | 71798.297 | 72038.769 | 93967.006 | 94218.628 |
Continuous latent factor model | 109425.238 | 109713.926 | 47217.209 | 47466.144 | 62060.700 | 62322.024 |
Values are based on crude model (no adjustment was done for confounding variables). AIC: Akaike information criterion; BIC: Bayesian information criterion.
Table
Crude and adjusted regression coefficients (SE) for the association between stressful life events domains with psychological problems and their profile score based on continuous latent factor and random effect models.
Total ( |
Males ( |
Females ( |
|||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Psychological distress | Anxiety | Depression | Psychological problems profile | Psychological distress | Anxiety | Depression | Psychological problems profile | Psychological distress | Anxiety | Depression | Psychological problems profile | ||
|
|||||||||||||
Continuous latent factor model | (1) | 0.134 (0.033) |
0.261 (0.027) |
0.150 | 0.222 (0.033) |
0.115 (0.050) |
0.248 (0.043) |
0.150 | 0.129 (0.045) |
0.098 (0.043) |
0.265 (0.036) |
0.150 | 0.277 (0.044) |
(2) | 0.187 (0.044) |
0.252 (0.037) |
0.150 | 0.198 (0.042) |
0.135 (0.061) |
0.240 (0.054) |
0.150 | 0.076 (0.056) | 0.138 (0.060) |
0.252 (0.051) |
0.150 | 0.297 (0.059) |
|
Random effect model | (1) | 0.262 (0.015) |
0.324 (0.015) |
0.271 (0.015) |
— | 0.202 (0.021) |
0.252 (0.021) |
0.191 (0.022) |
— | 0.299 (0.022) |
0.370 (0.021) |
0.320 (0.020) |
— |
(2) | 0.228 (0.017) |
0.253 (0.016) |
0.217 (0.016) |
— | 0.148 (0.024) |
0.185 (0.023) |
0.147 (0.025) |
— | 0.283 (0.024) |
0.302 (0.022) |
0.262 (0.022) |
— | |
|
|||||||||||||
|
|||||||||||||
Continuous latent factor model | (1) | 0.200 (0.034) |
0.205 (0.029) |
0.150 | 0.349 (0.035) |
0.233 (0.046) |
0.191 (0.042) |
0.150 | 0.319 (0.045) |
0.165 (0.047) |
0.186 (0.041) |
0.150 | 0.410 (0.050) |
(2) | 0.208 (0.041) |
0.198 (0.034) |
0.150 | 0.365 (0.041) |
0.216 (0.055) |
0.141 (0.050) |
0.150 | 0.353 (0.053) |
0.190 (0.058) |
0.164 (0.051) |
0.150 | 0.462 (0.061) |
|
Random effect model | (1) | 0.361 (0.015) |
0.425 (0.014) |
0.415 (0.014) |
— | 0.381 (0.020) |
0.427 (0.020) |
0.446 (0.021) |
— | 0.370 (0.021) |
0.452 (0.020) |
0.423 (0.019) |
— |
(2) | 0.393 (0.017) |
0.441 (0.016) |
0.441 (0.016) |
— | 0.404 (0.024) |
0.415 (0.023) |
0.454 (0.025) |
— | 0.386 (0.023) |
0.458 (0.022) |
0.437 (0.021) |
— |
Association of stressful life events profiles scores with psychological problems based on grouped outcomes latent factor regression on latent predictors for the total sample.
Association of stressful life events profiles scores with psychological problems based on grouped outcomes latent factor regression on latent predictors for males.
Association of stressful life events profiles scores with psychological problems based on grouped outcomes latent factor regression on latent predictors for females.
At the next step, we performed an adjusted model with demographic variables (including age, gender, marital status, and educational level) and lifestyle variables (including BMI and physical activity) as confounder variables. As it was shown in Table
In this cross-sectional population-based study, a comprehensive statistical method (i.e., latent factor regression model for grouped outcomes with confirmatory latent predictors) was introduced to evaluate the association of stressful life events with psychological problems. In the present study, psychological distress, anxiety, and depression were considered as grouped outcomes and two domains of stressful life events (personal and social) as confirmatory latent predictors. Overall, according to the findings of the current study, it was observed that stressful life events directly associated with components of psychological problems and their profile scores, with greater associations in females than in males.
We found a positive association between the personal stressors, including “home life, education, loss and separation, sexual life, and health concerns” with psychological problems and their collective profile scores. In addition, in the current study, there was a positive relationship between the social stressors, including “financial problems, social relations, personal conflicts, job conflicts, job security, and daily life” and psychological disorders and their collective profile scores. Among the stressful life events, personal conflicts had notable association with psychological problems and their profile scores. These findings are in line with some previous studies that documented a significant association between stressful life events and psychological disorders [
In accordance with the present study, Feizi et al.’s study on 4583 people aged 19 and older, living in Isfahan, Iran, showed that family conflicts and social problems are significantly correlated with the levels of perceived stress, which may be related to different Iranian cultural aspects that people are more sensitive to familial and social relationships [
In conclusion, the results of the current study indicated that different stressors particularly socioeconomic related ones have effective impacts on psychological problems. The interventions targeted toward promoting financial and social equalities and social skills training have potential benefits in the studied population. In addition, it is important to consider the social and cultural background of a population for managing the stressors as an effective approach for preventing and reducing the destructive burden of psychological problems.
It is important to recognize some strengths and limitations of the present study. A major strength of our large population-based study is the application of latent factor regression model for grouped outcomes with confirmatory latent predictors for evaluating the association of stressful life events and psychological disorders. We simultaneously evaluated the association of composite measures of stressful life events with each psychological problem (depression, anxiety, and psychological distress) and a grouped outcome of psychological problems, which lead to more reliable associations. However, due to the cross-sectional design of the study, cause–effect relationships could not be inferred from our findings. It should also be mentioned that all the used information in the present analysis was collected by self-administered questionnaires that might lead to misclassifying the participants. Finally, because SEPAHAN study’s participants were working in health centers, thus, generalization of the present findings to the general population in Iran must be done with caution.
The authors declare that they have no conflicts of interest.
The present article was a research project at Isfahan University of Medical Sciences, under Project no. 194143. SEPAHAN was financially supported by a grant from the Vice Chancellery for Research and Technology, Isfahan University of Medical Sciences (IUMS). The authors would like to thank all the staff of Isfahan University of Medical Sciences (MUI) who kindly participated in this study and the staff of the Public Relations Unit and other authorities of IUMS for their excellent cooperation.