Department of Health and Society, Linköping University, S-581 85 Linköping, Sweden
Correspondence: Kent Lindqvist, Division of Preventive and Social Medicine, Department of Health and Society, Faculty of Health Sciences, Linköping University, S-581 85 Linköping, Sweden. E-mail: kenli{at}ihs.liu.se
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Abstract |
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Methods A quasi-experimental design was used with pre- and post-implementation data collection covering the total populations <65 years of age during one year in the programme implementation municipality (population 41 000) and in a control municipality (population 26 000). Changes in injury rates were studied using prospective registration of all acute care episodes with regard to social standing in both areas during the study periods.
Results Male members of households categorized as not vocationally active displayed the highest pre-intervention injury rates. Also after the intervention, males in households classified as not vocationally active displayed notably elevated injury rates in both the control and study areas. Households in the study area in which the significant member was employed showed a post-intervention decrease in injury rate among both men (P < 0.001) and women (P < 0.01). No statistically significant change was observed in households in which the significant member was self-employed or not vocationally active. In the control area, only an aggregate-level decrease (P < 0.05) among members of households in which the significant member was employed was observed.
Conclusions The study displayed areas for improvement in the civic network-based WHO Safe Community model. Even though members of non-vocationally active households, in particular men, were at higher pre-intervention injury risk, they were not affected by the interventions. This fact has to be addressed when planning future community-based injury prevention programmes.
To handle the fact that unintentional injuries are growing into a global public health problem, injury prevention programmes have been introduced at national and local levels in many countries.1 Community-based programme development, building interventions into the existing networks in the civic environment and emphasizing broad participation, has long been known as a promising model in public health practice.2 For example, in Sweden, interventions in injury prevention based on local popular participation and inter-sectoral co-operation between authorities have been in use for more than two decades. The scope of the interventions includes empowerment of the socially weak and continuous tracking of high-risk environments and groups. Guided by participatory action research,3 the structure of these programmes has been developed by researchers, local politicians, civil servants, representatives of non-government organizations, and public health workers in co-operation.4,5 Injury prevention programmes based on self-governing civic networks of this type have been evaluated with respect to the programme processes,4 effects on the total injury incidence,68 and with respect to specific areas such as child injuries,9 sports injuries,10 and traffic injuries.11 Since 1989, the civic network model for community-based injury prevention has also been used as the basis for the WHO Safe Community accreditation. The accreditation criteria define the norms that communities have to fulfil to be eligible for Safe Community status (Table 1). In 2002, there were 70 Safe Communities, in both industrialized and developing countries.12 However, although awareness of social stratification is central to the definition of community-based programmes, the outcomes with regard to differences in social standing have not been analysed. This is an unsatisfactory situation, because previous studies have shown that different forms of social deprivation are associated with injury risk in different population groups. For instance, the risk of childhood injury has been reported to be associated with the income level in the residential area13 and the parents' educational level.14 For adults, the injury risk has been found to be related mainly to social class, and this association is stronger for men than for women.15,16
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The WHO Safe Community model |
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Materials and methods |
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Validity and reliability tests
To identify confounding social trends, data regarding population age and gender mix, sites of residency, education, income, and employment were collected, retrospectively, from national registers (Statistics Sweden) for the study periods. Systematic differences between the areas concerning injured people seeking care outside the registration areas were obtained by analysing all visits to the emergency departments of Linköping University Hospital during September 1984. Fatal injuries, other than those recorded in the study, were researched by analysing local police records.
Data collection
Data were collected from two sources. For all patients contacting a health-care unit located in the study area during the study periods, a report form with the time of contact and standard personal data was filled in by staff at the care unit. The same form included whether unintentional injury was a possible reason for the contact. For the registered patients, specially trained nurses recorded an International Classification of Diseases, Eighth Revision (ICD-8) based diagnostic classification using medical records and discussions with physicians. The routine for data collection was tested in a pilot project. Before starting each study period, the staff at all relevant health-care units were carefully informed, and the routine was trained in practice for 2 weeks.
The SEI classification was used for the primary representation of the social standing of the individuals in the intervention and control areas. SEI data for all individuals in the intervention and control areas were collected from Statistics Sweden. Due to the changes in household structure in relation to retirement and ageing, individuals >65 years of age were excluded from the analyses.23 For the pre-implementation registration, SEI data originated in the census survey conducted in 1985; and for the post-implementation registration, the data originated in the census survey conducted in 1990. Considering that the WHO Safe Community model strongly relies on existing civic networks, the detailed SEI categories were used for coding individuals into three secondary categories based on the relation that the household had to the labour market; households in which the vocationally significant member was employed, households in which the vocationally significant member was an entrepreneur or self-employed, and households in which the adults not were vocationally active. This classification did not contain any vertical intra-group stratification, i.e. income or education differences within the social groups were not accounted for. The group self-employed also included farmer's households. Temporarily unemployed individuals were coded according to their most recent occupation. The group not vocationally active household comprised households in which the adult members had not been able to settle in the labour market, were on long-term sick leave, or had recently arrived in the country as immigrants. The group not vocationally active household also comprised individuals who were institutionalized.
Statistical methods
Rates of injuries (expressed as per 100 person-years) were calculated by community (study and control municipality) for each study period (1983/84 and 1989), by socioeconomic group (employed, self-employed, and not vocationally active), by gender, as well as for women and men together. 95% CI were provided for injury rates. For individuals injured more than once, only the first episode was included in the calculations.
The differences in injury rates between 1989 and 1983/84 were computed with 95% CI and significance tests were performed. A P-value<0.05 was considered as statistically significant. All computations were performed using SPSS statistical software (release 11.5).
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Results |
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Quality of injury data
During the pre-implementation registration period, identity data were missing for less than 1% of the injured patients in the study and control areas. During the post-implementation registration, less than 0.5% of the injured patients in the study and control areas could not be identified in medical records. A lower share of all injured residents from the study area (11/422), 3% (95% CI: 1%, 5%), compared with the control area (28/253), 11% (95% CI: 7%, 15%), were found to have been directly provided with acute care outside the local health-care units during the month of the control study. Police records did not disclose previously unrecorded injuries.
Pre-intervention injury rates
Male members of not vocationally active households displayed the highest pre-intervention injury rate in both the control and study areas (Table 4). Also in households in which the vocationally significant member was employed, males showed higher injury rates than females. There was no difference between men and women among members of households in which the vocationally significant member was self-employed.
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Discussion |
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One possible explanation for these observations follows from the fact that the quality and quantity of the interaction in social networks vary between different social groups.26 The post-intervention injury rates observed in the present study may reflect the fact that the social networks available for households in which the adults are not vocationally active, and for self-employed households, have a different structure compared with households in which the adults are employees. Close social connections within groups in a community may in fact not necessarily be beneficial for all individuals in the population.27 In the present study, although for different reasons, the households in which the adults were not vocationally active and the households of self-employed adults were not exposed to safety information provided through traditional workplace sources, and these households can also be expected to participate less in local civic activities. Because of their high pre-intervention injury rates, this situation is especially negative for households in which the adults are not vocationally active. To reach this group, experience from previous successful programmes aimed at socially deprived groups can be employed.2830 For example, in the evaluated programme, it is possible that engaging social workers, in home inspections, in family empowerment and educational programmes, was not fully exploited. However, when planning an extended professional outreach to members of households with small social networks, the benefit of targeting individuals at high risk must always be balanced against the possible intrusion on personal integrity. A first step could be to analyse the social networks available to these households to identify the organizations that are the most suitable to take the main responsibility for implementing the interventions.
A second explanation can be gender-related role behaviour, i.e. that in certain everyday settings men and women share behavioural patterns, whereas in other comparable settings they act according to different gender roles. One display of such gender-related behaviour is apparent in working life, where the distribution of occupations between men and women is highly differentiated. This differentiation has been suggested to have an influence on work-related illness and sick leave patterns.31 Such gender-related variation in risk exposure may also explain some of the differences in injury rates between men and women found in this study. For instance, it may explain the fact that while there were small pre-intervention gender differences in injury rates in self-employed households, there were significant differences in households in which the adults were employees. It can be assumed that the type of daily labour is more similar when comparing men and women in self-employed households, whereas the division of labour is more traditional in households in which the significant member is employed. It is thus possible that the higher injury rate among women in self-employed households is a consequence of a stressful general life situation, i.e. that the women take the main responsibility for the home and children, while also working in the family enterprise. However, although it may have had an influence on pre-intervention risks, gender segregation does not explain why the post-intervention injury rates among women in self-employed households remained constant. Therefore, before interventions are planned for women belonging to self-employed households, more knowledge is required both about direct injury risks, and the existing information and structural barriers that impede implementation of safety interventions.
At the aggregate level, the injury incidence in the control area only decreased for members of households in which the significant member was employed, and this decrease was significantly lower than in the study area. This observation suggests that the decrease in injury rates in the intervention area cannot be explained solely by general societal trends. A trend towards higher general utilization of health-care during the period of post-implementation registration was also observed in both areas, implying that the reduced injury rates cannot be explained by a lower availability of health-care services during the post-implementation registration. An evident weakness of the present study is that it is not based on a randomized design. For this reason, a set of confounders were prospectively followed in the study and control communities. Confounders with possible influence on the results that not were followed include alcohol consumption and number of immigrants. Retrospective analyses of the latter aspects using official statistics from each respective area did not display any evident differences between the areas or extraordinary rates. Another type of confounder that may have influenced the results is interventions performed at a national level that may have influenced the groups under study in different ways, e.g. general programmes on work-place safety. No adjustment for such programme effects were made in the present analyses. Nevertheless, although a randomized trial is the preferred benchmark test of community-based injury prevention, these observations correspond with previous studies which suggest that quasi-experimental approaches using cohorts can provide realistic appraisals of effectiveness.32
In conclusion, few studies have examined the impact of interventions in injury prevention in different social groups.33 Without such evidence, it remains difficult for safety promotion professionals to understand how to target social inequalities in injury rates. This study displayed important areas for improvement in the civic network-based WHO Safe Community model for safety promotion. The results showed that particularly non-vocationally active households not only were at higher pre-intervention injury risk, but they were also not reached by the interventions. This fact has to be addressed in planning future community-based injury prevention programmes. The revised programme models should include interventions that are informed by local injury data stratified not only by age and gender, but also by social standing. Only then can adequate outreach to high-risk groups be planned and implemented, taking into account the structure and qualities of local civic networks.
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Acknowledgments |
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References |
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