Social Support and Posttraumatic Stress Disorder among Flood Victims in Hunan, China

Social Support and Posttraumatic Stress Disorder among Flood Victims in Hunan, China SHUIDONG FENG, MPH, HONGZHUAN TAN, PHD, ABUAKU BENJAMIN, MPH, SHIWU WEN, PHD, AIZHONG LIU, PHD, JIA ZHOU, MPH, SHUOQI LI, MD, TUBAO YANG, MPH, YANBO ZHANG, PHD, XINHUA LI, MB, AND GANGQIAN LI, MB

PURPOSE: To explore the relationship between social support and posttraumatic stress disorder (PTSD) among flood victims. METHODS: A cross-sectional survey was carried out in 2000 among individuals who had suffered floods in 1998 in Hunan, China. Multistage sampling was used to select the subjects from the flood-affected areas. PTSD was diagnosed according to DSM-IV criteria, and social support was measured according to a social support rating scale. Data were collected through face-to-face interviews using a structured questionnaire. Multiple logistic regression analysis and confirmatory factor analysis was used to examine the relationship between social support and PTSD. RESULTS: Out of a total of 25,478 subjects interviewed, 2336 (9.7%) were diagnosed as having PTSD. PTSD was significantly associated with total social support (odds ratio [OR] 0.80, 95% confidence interval [CI], 0.78–0.82), subjective support (OR 0.48, 95%CI, 0.44–0.52), and support utilization (OR 0.53, 95%CI, 0.49–0.57). CONCLUSION: PTSD in flood victims is significantly associated with social support; subjective support and support utilization may play more important roles in mitigating the impact of flood than objective support. Ann Epidemiol 2007;17:827–833. Ó 2007 Elsevier Inc. All rights reserved. KEY WORDS:

Floods, Posttraumatic Stress Disorder, Social Support, Epidemiology.

INTRODUCTION Flood is one of the most common and most severe forms of natural disasters, accounting for up to one half of all natural disasters in the world (1). In China, flooding is a frequent occurrence. A severe flood that struck China’s Hunan province in 1998 left hundreds of thousands of residents homeless. Many infrastructural and agricultural projects were damaged as well. Floods can lead to direct economic and property losses, physical injuries, deaths, and psychological injuries. Posttraumatic stress disorder (PTSD) is a common disorder in disaster victims. PTSD is a severe and complex disorder precipitated by exposure to psychologically distressing

From the School of Public Health, Central South University, Changsha, Hunan, P.R., China (S.F., H.T., A.B., S.W., A.L., J.Z., S.L., T.Y., X.L., G.L.); the Department of Epidemiology, School of Public Health, Nanhua University, Hengyang, Hunan (S.F.); OMNI Research Group, Department of Obstetrics & Gynecology, University of Ottawa, Faculty of Medicine, Ottawa, Canada (S.W.); and the Department of Health Statistics, Shanxi Medical University, Taiyuan, Shanxi China (Y.Z.). Address correspondence to: Dr. Hongzhuan Tan, School of Public Health, Central South University, Xiangya Road 110, Changsha, Hunan 410008, P. R. China. Tel.: 0086-731-4805455; fax: 0086-731-4805454. E-mail: [email protected]. Received December 12, 2006; accepted April 18, 2007. Ó 2007 Elsevier Inc. All rights reserved. 360 Park Avenue South, New York, NY 10010

events (2), and it is characterized by persistent intrusive memories about the traumatic event, persistent avoidance of stimuli associated with the trauma, and persistent symptoms of increased arousal (3). In the past decades, the study of PTSD has focused on traffic accidents (4, 5), violent crimes (6), terrorist attacks (7–9), hurricanes (10), earthquakes (11), hijackings (12), rapes (13), and warfare (14). Social support has been considered to be an important factor influencing an individual’s reactions to stress and it also has a beneficial effect on PTSD (15). Although previous studies have assessed the impact of floods in terms of property loss, mortality, and morbidity (16), only a few studies have reported PTSD in flood victims (17–20), and none has reported the relationship between PTSD and social support in flood victims. In the current study, we explored the relationship between social support and PTSD among flood victims in Hunan, China.

METHODS Study Population Victims who had been directly exposed to the 1998 summer floods, which lasted for 45 days, in Hunan, China, formed the target population. The study area lies within the catchment area of Dongting Lake, which is located south of the 1047-2797/07/$–see front matter doi:10.1016/j.annepidem.2007.04.002

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Flood was classified into 3 types: soaked flood, collapsed embankment, and flash flood and was divided into 3 groups by severity: mild (affected area !50%), intermediate (affected area 50%–75%), and severe (affected area O75%).

Selected Abbreviations and Acronyms CI Z confidence interval OR Z odds ratio PTSD Z posttraumatic stress disorder

Survey Methods middle reaches of the Yangzi River in southern China, and it is also a flood-prone area (Fig. 1). The catchment area of Dongting Lake consists of 31 counties, covers an area of 31,000 km2, and has an estimated human population of 11.3 million. Residents have similar natural conditions as well as similar socioeconomic and health status. It is usually warm, humid, and rainy during summer, and most of the residents are farmers and have low educational levels. Our study area also included 7 other counties in the west of Hunan province that had been affected by the flash floods. These counties have sociodemographic characteristics similar to other counties of Dongting Lake’s catchment area. Of the 38 counties affected, 31 experienced damage from soaking and collapsed embankments, and 7 experienced flash flooding. We used a multistage stratified and cluster sampling method to select study subjects. First, we randomly selected 7 counties from 31 counties that suffered soaking and collapsed embankments (Yueyang, Lingxiang, Huarong, Qianlianghu, Ziyang, Anxiang, Datonghu) and 1 county from 7 counties that experienced flash flooding (Longshan). Then, by systematic sampling approach, we randomly sampled 50% of townships in selected counties, 50% of villages in selected townships, and 50% of households in selected villages. All family members aged 16 years and older in the selected households were included in our study. Cluster effects were handled by increasing the calculated sample size by 50%.

The survey was conducted between January and May 2000. Trained investigators, who worked at the local centers for disease control and prevention and had a bachelor’s degree or higher, carried out face-to-face interviews using a structured questionnaire to obtain demographic data, ascertain PTSD, and measure social support. These investigators received on-site supervision from psychologists. The project was approved by the ethics committee of Central South University. The diagnosis of PTSD was made according to the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV) criteria (3), which included 17 symptoms scored as 0 Z none, 1 Z slight, 2 Z moderate, 3 Z severe, and 4 Z extreme. Subjects with scores >2 were defined as positive for a specific symptom. The 17 symptoms of PTSD were further divided into 3 groups, representing 3 diagnostic criteria B, C, and D. Criterion B symptoms represented the re-experiencing cluster: namely, intrusive recollections (B1); repeated nightmares about floods (B2); acting as if the flood was occurring (B3); feeling worse when reminded of the flood (B4); and reactivity to flood reminders (B5). Subjects were defined as positive if they showed one or more positive items in the B group. Criterion C symptoms represented the avoidance cluster and included the following: efforts to avoid thoughts or feelings associated with the flood (C1); efforts to avoid activities that arouse recollections of the flood (C2); amnesia in regard to the flood (C3); diminished interest (C4); detachment or estrangement (C5); restricted range of affect (C6); and sense

FIGURE 1. Map of study area.

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of foreshortened future (C7). Subjects were defined as positive if they showed 3 or more positive items in the C group. Criterion D symptoms represented the hyperarousal cluster: namely, difficulty falling or staying asleep (D1); irritability or anger (D2); difficulty concentrating (D3); hypervigilance (D4); and exaggerated startle response (D5). Subjects were defined as positive if they showed two or more positive items in the D group. In addition, there were criteria A and E for the diagnosis of PTSD. Criterion A represented exposure to a trauma outside the range of usual experience, and criterion E represented the disturbance lasting more than 1 month. Subjects were diagnosed as having PTSD if Criteria A, B, C, D, and E symptoms were all positive. We assessed all symptoms, including the time and duration of occurrence. The questionnaire for PTSD had been tested in Chinese populations and proved valid and reproducible (17). The social support rating scale (21) included 3 categories with a total of 10 items. The first category was ‘‘objective support,’’ which had 3 items. These were ‘‘I often stay with my family members’’; ‘‘I often get economic assistance from family, friends, relatives, or neighbors when things go wrong’’; ‘‘I often get consolation and attendance from family, friends, relatives, or neighbors when things go wrong.’’ The second category was ‘‘subjective support’’ with 4 items: namely, ‘‘I can rely on my friends when things go wrong’’; ‘‘I have friendly relationship with my neighbors’’; ‘‘I have tight relationship with my colleagues’’; and ‘‘My family really tries to help me.’’ The third category was ‘‘support utilization’’ with 3 items: namely, ‘‘I often seek assistance when I am in trouble’’; ‘‘I often tell others my distress’’; and ‘‘I often take part in societal activity.’’ Every statement was scored on a 4-point Likert scale (1 Z none, 2 Z slight, 3 Z moderate, 4 Z great), and study subjects asked to select the score applicable to them for each of the 10 items. The total score for the 10 items was used as a measure of current total social support status of the subject, and the score for each category derived from scores for the corresponding items. The questionnaire for social support had also been used in Chinese populations (22) and proved to have good validity and reliability (21). All interviewers participated in a 2-day training program, which focused on the questionnaires. A working manual was provided to ensure that all interviewers had the same understanding of the questionnaire. The completed questionnaires were checked by the coordinator of the study. If a questionnaire was found to be incomplete or inconsistent, the interview was repeated for the same subject to reduce missing data as much as possible and improve response rate. Statistical Analyses We first described the characteristics of study participants and compared the PTSD rates and the means of social support score by sociodemographic characteristics, flood type

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and severity. Multistage sampling being used, the weighted PTSD rate for flood victims in Hunan province was calculated according to the actual composition of the floodaffected population (23). We then analyzed the relationship between social support (including its 3 categories) and PTSD and estimated the effect of social support on PTSD. The different types of social support were all divided into low, medium, and high categories based on established guidelines (21). Multiple logistic regression analysis was conducted to estimate odds ratios (ORs; crude and adjusted) and its 95% confidence interval (CI) for social support and PTSD. To mitigate measurement error, we employed the measurement model of Structural Equation Model to estimate the latent variable score for social support and its 3 categories; we then took the 4 estimated latent variable scores as the independent variable respectively in the logistic regression model. Each multivariate logistic regression model included only one social support variable to avoid multicollinearity among the different social support variables. Potential confounding variables included in the multiple logistic regression model were age (X1: 1 Z 16–, 2 Z 35–, 3 Z >55 years), sex (X2: 1 Z male, 2 Z female), education (X3: 1 Z illiterate, 2 Z elementary, 3 Z high school or higher), occupation (X4: 1 Z farmer, 2 Z nonfarmer), flood type (X5: 1 Z soaked flood, 2 Z collapsed flood, 3 Z flash flood, with soaked flood as the reference), and flood severity (X6: 1 Z mild, 2 Z moderate, 3 Z severe). A stepwise procedure was used in the regression modeling process, with the entry threshold set at p Z 0.05 and the exit threshold set at p Z 0.10 for all variables. All analyses were performed with SPSS Version 11.0 (SPSS, Chicago, IL).

RESULTS A total of 8 counties, 40 towns, 310 villages, 13,450 households, and 29,285 individuals aged 16 years and older were selected for the study. Of the 29,285 study subjects, 25,478 were interviewed and had complete data, yielding a response rate of 87.0%. Of this group, 13,102 (51.4%) were from the soaked flood group, 9326 (36.6%) were from the collapsed embankment group, and 3050 (12.0%) were from the flash flood group. Table 1 presents a breakdown of demographic features of the study participants. The sample was almost evenly divided by gender (52.9% male: 47.1% female), with an mean (SD) age of 39.43 (13.81) years. Respondents were predominantly farmers (91.3%) and have had elementary education (80.6%). A total of 2336 subjects were diagnosed as having PTSD, yielding a prevalence rate of 9.7% weighted by the composition of the overall target population (the composition of

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TABLE 1. Basic characteristics of study participants

Age (yr) 16– 35– >55 Gender Male Female Education Illiterate Elementary school High school or higher Occupation Farmer Nonfarmer

No.

%

11,389 10,065 4024

44.7 39.5 15.8

13,480 11,998

52.9 47.1

2468 20,528 2482

9.7 80.6 9.7

23,266 2212

91.3 8.7

the overall target population is 42.4%, 49.0%, and 8.6% for soaked flood, collapsed embankment, and flash flood, respectively). The highest rate of PTSD (24.9%) occurred in the flash flood group, followed by the collapsed embankment group (12.9%). Table 2 shows bivariate associations between key covariates and PTSD. Variables that were significantly associated with PTSD included age, gender, education, occupation, flood type, and flood severity (p ! 0.001). Table 3 describes the mean social support score and standard deviation among study participants with different TABLE 2. Distribution of PTSD-positive rate among different groups Sample

Age (yr) 16– 35– >55 Gender Male Female Education Illiterate Elementary school High school or higher Occupation Farmer Nonfarmer Flood type Soaked Collapsed embankment Flash flood Flood severity Mild Moderate Severe *Two-tailed chi-square test.

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demographic characteristics. Individuals 55 years old and older had the lowest total social support score (42.78, p ! 0.01); males had higher total social support score than females (43.27 vs. 43.00, p ! 0.01). Study subjects with higher educational levels had higher total social support scores (p ! 0.05) and support utilization scores (p ! 0.01). Farmers had lower total social support scores (42.70 vs. 43.18, p ! 0.01), subjective support scores (24.01 vs. 24.22, p ! 0.05), and support utilization scores (6.89 vs. 7.05, p ! 0.01) than nonfarmers. Table 4 presents bivariate relationship between PTSD and social support. The prevalence rate of PTSD was significantly higher in individuals with low social support than those with medium or high social support (p ! 0.001). The same relation between PTSD and social support was observed in all 3 categories of support. Table 5 shows the results of multivariate logistic regression analysis. Taking PTSD as the dependent variable, the latent variable score of total social support and its 3 categories as independent (study) variables, respectively, and key covariates mentioned above as control variables, 4 multiple logistic regression analyses were done. The results showed that the adjusted OR of PTSD was 0.80 (95% CI, 0.78–0.82) for total social support, 0.48 (95% CI, 0.44– 0.52) for subjective support; and 0.53 (95% CI, 0.49–0.57) for support utilization.

DISCUSSION

PTSD

No.

%

No.

%

p Value*

11,389 10,065 4024

44.7 39.5 15.8

1733 569 34

8.4 9.2 11.3

!0.001

13,480 11,998

52.9 47.1

1108 1228

8.2 10.2

!0.001

2468 20,528 2482

9.7 80.6 9.7

335 1795 206

13.6 8.7 8.3

!0.001

23,266 2212

91.3 8.7

2175 161

9.4 7.3

13,102 9326 3050

51.4 36.6 12.0

375 1201 760

2.9 12.9 24.9

!0.001

11,368 5685 8425

44.6 22.3 33.1

190 788 1358

1.7 13.9 16.1

!0.001

!0.001

PTSD is a common psychological disorder in disasteraffected populations. It has been widely used to evaluate the psychological impact of natural disasters, accidents, and war (4–14). Although many studies of the effects of social support on trauma victims have been conducted in the past, to our knowledge this is the first study to explore the effects of social support on flood victims’ psychological health measured by PTSD. Our study found that the overall prevalence rate of PTSD was 9.7% from a sample of 25,478 subjects. This rate is lower than the rate found in earthquake victims (24.2%) (11), rock-fall victims (43%) (24), and in road traffic accident victims (38.27%) (4). Differences in the nature and severity of the disasters coupled with the characteristics of study subjects, and study methodology may have accounted for the differences in PTSD prevalence observed in different studies. Also, floods, especially soaked flood, may not be as fearful as earthquakes, rock falls, and road traffic accidents. Our study showed that females were more likely to have PTSD than males. This compares well with findings of Kessler (25) and Lai et al. (26). Educational level was found to be associated with PTSD. Subjects with a lower educational level were at a greater risk of developing PTSD. The study

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TABLE 3. The distribution of social support score (Mean G SD) in different study groups Social support score

Age 16– 35– >55 Gender Male Female Education Illiterate Elementary school High school or above Occupation Farmer Non-farmer

Objective support

Subjective support

Support utilization

Total score

11.90 G 3.73* 12.29 G 3.52* 12.05 G 3.46*

24.24 G 4.46 24.34 G 4.37 24.07 G 4.57*

6.89 G 1.68* 6.96 G 1.66* 6.67 G 1.61*

43.04 G 7.90 43.59 G 7.65* 42.78 G 7.78*

12.07 G 3.55 12.05 G 3.50

24.21 G 4.52 24.19 G 4.42

6.99 G 1.67 6.76 G 1.61*

43.27 G 7.85 43.00 G 7.64*

11.40 G 3.56* 12.13 G 3.51* 12.09 G 3.61

23.49 G 4.42* 24.27 G 4.46* 24.38 G 4.59

6.52 G 1.69* 6.89 G 1.63* 7.15 G 1.65*

41.41 G 7.77* 43.29 G 7.70* 43.63 G 7.97#

11.83 G 3.58 11.92 G 3.52

24.01 G 4.68 24.22 G 4.45#

6.87 G 1.64 7.05 G 1.68*

42.70 G 8.02 43.18 G 7.73*

Analysis of variance (ANOVA), #P ! 0.05, *P ! 0.01, the ANOVA between group 1 and group 2 marked in group 2, between group 2 and group 3 marked in group 3, and between group 1 and group 3 marked in group 1.

of Lai et al. showed a similar result. This can be explained by the possibility of persons with a lower educational level having poorer coping skills to stress and therefore being the most affected, negatively, by floods. The study also showed that farmers had a significantly higher PTSD positive rate than nonfarmers. This could be attributed to the fact that farmers are less mobile than nonfarmers and therefore suffer the most psychological stress when they experience floods (22). Older victims had a higher prevalence rate of PTSD than younger victims. This could be as a result of the fact that the elderly are at greater risk of loss during floods by virtue of their age and may also have difficulty adjusting to deteriorated living conditions. We also found that PTSD positive rates in the collapsed embankment and flash flood groups were higher than in the soaked flood group. This may be because collapsed embankment and flash flood are often more sudden and can result in severer economic loss and casualty as compared with soaked flood and therefore may have greater influence on victims’ psychological health (22). Social support is a network of family, friends, colleagues, and other acquaintances a person can turn to, whether in times of crisis or simply for fun and entertainment. In our study area, varying categories of social support are available, including economic (money) and material assistance (e.g., clothes, quilts, drugs, tents, drinking water and foods) from government, nongovernment organizations, international organizations, and friends and relatives, and also including the concern and psychological consolation from others. Our study found that social support was closely related with demographic characteristics. There was a higher level of social support in males than in females, in the elderly than in the young, in nonfarmers than in farmers, and in

subjects with higher educational level than in those with lower educational level. These observations could possibly be attributed to the fact that the elderly have wider social interactions than the young by virtue of their age. Males often have higher educational levels than females and may therefore have better coping and social intercourse skills. This may also be true for nonfarmers, who often have higher educational levels compared with farmers.

TABLE 4. Relationship between PTSD and social support Total sample Score (mean G SD) Social support Low Medium High Objective support Low Medium High Subjective support Low Medium High Support utilization Low Medium High

No.

%

PTSD No. % p Value*

37.52 G 5.70 48.66 G 2.68 56.91 G 1.79

13,643 53.5 1733 12.7 !0.001 10,451 41.1 569 5.4 1384 5.4 34 2.5

5.13 G 1.19 10.69 G 1.65 15.96 G 1.79

1834 6.6 210 11.5 !0.001 15,093 59.0 1548 10.3 8551 34.5 578 6.8

14.18 G 2.03 21.51 G 2.04 27.73 G 2.23

1523 5.4 275 18.1 !0.001 11,125 42.5 1280 11.5 12,830 52.1 781 6.1

5.37 G 0.86 7.74 G 0.75 10.55 G 0.73

10,862 42.3 1084 10.0 !0.001 13,260 52.2 1189 9.0 1356 5.6 63 4.6

Social support scores were defined as low (12–44); medium (45–54); high (>55). Objective support scores were defined as low (1–6); medium (7–13); high (14–20). Subjective support scores were defined as low (8–16); medium (17–24); high (25– 32). Support utilization scores were defined as low (3–6); medium (7–9); high (10–12). *Two-tailed chi-square test.

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TABLE 5. Relationship between social support and PTSD among study participantsdadjusted for age, sex, education, occupation, flood type, and flood severity by multivariate logistic regression Characteristic Social support Support utilization Subjective support Objective support

Crude OR*

95%CI

Adjusted OR*

95%CI

0.78 0.42 0.45 0.86

0.76–0.80 0.39–0.45 0.42–0.49 0.83–0.89

0.80 0.53 0.48 0.96

0.78–0.82 0.49–0.57 0.44–0.52 0.93–1.01

95%CI Z 95% confidence interval; OR Z odds ratio. *The latent variable scores for social support, subjective support utilization were obtained from the measurement model of the Structural Equation Model. Thus confirmatory factor analysis was used to estimate ORs in the logistic regression model.

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because components of objective support, such as economic and material assistance, often serve as a foundation for subjective support and support utilization. The reason for the nonsignificant relationship between PTSD and objective support could be that the government evenly distributed objective support to the flood victims. In summary, our study, which was based on a large sample, found that social support, especially in terms of subjective support and support utilization, could be an asset in PTSD prevention and intervention programs among flood victims.

CONCLUSIONS We also found that total social support, subjective social support, and support utilization were significantly associated with PTSD rate. Although subjects with lower social support had significantly higher PTSD rate, no significant association was observed between objective social support score and PTSD. After adjusting for the potential confounding by multiple logistic regression analysis, the results did not change. We therefore suggest that among the 3 categories of social support, subjective support and support utilization have a more significant influence on the occurrence of PTSD than objective support in flood victims. Social support may influence the way a person copes with stress and the effectiveness of these coping efforts and may motivate individuals to seek assistance when it is needed (27). Strong social support can offset the effect of a sudden social psychological irritation and provide indirect protection for the victims’ health (28) and facilitate the psychological recovery from disaster (29). Our finding concurred with results from previous studies in combat veterans (30, 31) and road traffic accident victims (4), indicating that social support plays an important role in alleviating the psychological effect of flood. Subjective assessment of received social support has been reported to be a more powerful predictor of subsequent improvement in PTSD symptoms than objective measures of social support (32). Our study showed similar results and thus reinforces the importance of the psychological environment of flood victims. Support utilization denotes the utilizing degree of all assistance one can turn to. Our study showed that higher support utilization was significantly related to fewer flood victims having PTSD. Several studies have also observed similar associations between support utilization and PTSD (33, 34), implying that support utilization is an important factor influencing the psychological environment of flood victims. Although our study did not show any significant relationship between PTSD and objective support, it is worth mentioning that objective support is important to flood victims

We have observed that social support is significantly associated with PTSD among flood victims. Individuals living in flood-affected areas in Hunan, China, with a higher degree of social support, had a significantly lower PTSD rate. Subjective support and support utilization were more important in improving the psychological environment of flood victims and therefore play more important roles in the prevention and management of PTSD than objective support. This project was supported by grant CMB 98-689 from the Chinese Medical Board (New York). We thank Linbao Xiang, Director of the Center for Disease Prevention and Control (CDC) of Yiyang city; Xiumin Zhang, Director of the CDC of Anxiang county; Huaxian He, Director of the CDC of Yueyang city; Linlin Li, Director of the CDC of Xiangxi autonomy; and Senlin Tang, Director of the CDC of Datong Lake District, all located in Hunan, China, for their cooperation in this study.

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