Elsevier

Annals of Epidemiology

Volume 16, Issue 10, October 2006, Pages 782-788
Annals of Epidemiology

The Importance of Estimating Selection Bias on Prevalence Estimates Shortly After a Disaster

https://doi.org/10.1016/j.annepidem.2006.04.008Get rights and content

Purpose

The aim was to study selective participation and its effect on prevalence estimates in a health survey of affected residents 3 weeks after a man-made disaster in The Netherlands (May 13, 2000).

Methods

All affected adult residents were invited to participate. Survey (questionnaire) data were combined with electronic medical records of residents' general practitioners (GPs). Data for demographics, relocation, utilization, and morbidity 1 year predisaster and 1 year postdisaster were used.

Results

The survey participation rate was 26% (N = 1171). Women (odds ratio [OR], 1.46; 95% confidence interval [CI], 1.28–1.67), those living with a partner (OR, 2.00; 95% CI, 1.72–2.33), those aged 45 to 64 years (OR, 2.00; 95% CI, 1.59–2.52), and immigrants (OR, 1.50; 95% CI, 1.30–1.74) were more likely to participate. Participation rate was not affected by relocation because of the disaster. Participants in the survey consulted their GPs for health problems in the year before and after the disaster more often than nonparticipants. Although there was selective participation, multiple imputation barely affected prevalence estimates of health problems in the survey 3 weeks postdisaster.

Conclusions

Estimating actual selection bias in disaster studies gives better information about the study representativeness. This is important for policy making and providing effective health care.

Introduction

In the aftermath of disasters, both short- and long-term health problems have been reported, such as feelings of anxiety or depression, severe sleeping difficulties, medically unexplained physical symptoms, and posttraumatic stress disorder 1, 2, 3, 4, 5. Representative prevalence estimates of these health problems are needed after disasters to adequately organize health care for those who need professional help. Policy makers and health care providers need to know whether, and to what extent, an increase in use of health care facilities can be expected (6).

In the wake of the chaos that follows a disaster, it often is very difficult to obtain a representative sample. In addition, apart from material losses and injuries, there are no objective criteria to define who is a victim and who is not, making it difficult to create a methodologically sound sample. Nearly half the health surveys after disasters do not report a participation rate (4), prompting one to question whether participants in those surveys are representative of all survivors. It is common knowledge that representativeness of health surveys can be affected by selection in demographic and health factors. Shortly after disasters, disaster-related experiences additionally might contribute to selective participation. How these experiences influence participation is unknown. One may speculate that survivors who were highly affected by the disaster or had high levels of postdisaster distress would be more motivated to participate in the health survey than survivors who were less affected. Conversely, highly exposed or distressed survivors could be less likely to respond because they do not want to be reminded of the stressful event.

Determining selective participation with regard to demographic-, health-, and disaster-related factors is important, but understanding whether that selection leads to actual bias in the outcome measures in a survey is essential for policy makers and health care providers. To our knowledge, none of the health studies after disasters presents information on the selection of adult survivors on the basis of health characteristics and disaster experiences, let alone the effect of the selection on outcome measures. Investigators of the few longitudinal studies that had predisaster data and described the impact of the disaster on postdisaster attrition rate did not comment on the representativeness of respondents 7, 8, 9.

To investigate selective participation and its potential bias on prevalence estimates of health problems in residents in a survey 3 weeks after a man-made disaster, we had the unique opportunity to combine these survey data with predisaster and postdisaster data retrieved from residents' general practitioners (GPs). The direction of the selective participation was studied with respect to demographics, disaster experience, use of the GP, and health problems presented to the GP. Furthermore, we used multiple imputation to examine the magnitude of selection bias on prevalence estimates of self-reported health problems.

Section snippets

Methods

On May 13, 2000, a firework storage facility exploded in a residential area of Enschede, The Netherlands. The explosion and subsequent fires killed 23 persons, more than 900 people were injured, and about 500 homes were destroyed. The Dutch government declared this a national disaster and the Ministry of Health, Welfare, and Sports supported the regional authorities and launched a larger health care program especially designed for the survivors (11).

Results

Participation rate in the health survey was 26% (N = 1171). Table 1 lists crude differences in participation rates for demographic variables. Compared with nonparticipants, survey participants were more likely to be women, aged between 25 and 44 or 45 and 64 years of age, live with a partner, be a single parent, and be of immigrant background. Participation rate was not affected by relocation caused by the disaster.

Survey participants consulted their GPs more often and had more than an average

Discussion

This study is unique in that we were able to estimate whether participants in a survey 3 weeks after a man-made disaster were representative of the entire cohort of affected residents on many aspects related to participation.

We observed a lower participation rate for men, young adults, and singles. This selection was observed previously in survivors of disasters 7, 10, 27. In contrast to other studies 9, 26, we observed a greater participation rate for immigrants. A possible reason is that even

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