| Literature DB >> 20187928 |
John Macleod1, Lorraine Copeland, Matthew Hickman, James McKenzie, Jo Kimber, Daniela De Angelis, James R Robertson.
Abstract
BACKGROUND: Injection drug use is an important public health problem. Epidemiological understanding of this problem is incomplete as longitudinal studies in the general population are difficult to undertake. In particular little is known about early life risk factors for later drug injection or about the life course of injection once established including the influence of medical and social interventions.Entities:
Mesh:
Year: 2010 PMID: 20187928 PMCID: PMC2841670 DOI: 10.1186/1471-2458-10-101
Source DB: PubMed Journal: BMC Public Health ISSN: 1471-2458 Impact factor: 3.295
Figure 1Geographic distribution of the EAC cohort including the 20 misclassified cases (n = 814). "pie diagram" showing the distribution of cohort members at follow up.
Figure 2Geographic location of follow-up interviews (n = 448). UK map showing location of follow-up interviews
Cohort characteristics at recruitment
| Characteristic | N | ||
|---|---|---|---|
| Male (%) | 794 | 543 (68.4) | |
| Born in Edinburgh (%) | 794 | 530 (66.7) | |
| Mean age (SD, min-max) at first injection | 606* | 19.9 (5.1, 11-41) | |
| Mean age (SD, min-max) at recruitment | 606 | 26.7 (6.3, 16-52) | |
| Mean years (SD, min-max) first injection to recruitment | 606 | 6.9 (5.7, 0-28) | |
| Recruited within 5 years of injection onset (%) | 606 | 306 (50.5) |
* Only 606 cohort members had information on age of first injection
Follow-up status of cases and comparison of the current health status of cases and controls
| Follow-up status of cases | N = 794 (%) | % Interviewed (N = 432) |
|---|---|---|
| Deceased | 228 (28.7) | 0.1a |
| Interviewed | 432 (54.4) | 100 |
| Case notes available | 654 (82.2) | 100 |
| Lost to follow-up | 139 (17.5) | - |
| Mean years follow-up | 10.2 (SD 6.8, range < 1-25) | |
| Current injector | 135 | 31.3 |
| Current OST | 302 | 70.0 |
| Opiate free1 | 75 | 17.4 |
| Smoker | 255 (59.0) | 403 (93.2)* |
| High risk alcohol use2 | 60 (13.9) | 87 (20.1)# |
| Anxious3 | 87 (20.1) | 209 (48.3)* |
| Depressed4 | 49 (11.3) | 114 (26.4)* |
| Mean subjective QoL (SD)5 | 63.8 (22.7) | 50.3( 23.6)^ |
Notes: a: Five interviewees subsequently died before the end of the follow-up period. 1. Not in OST or injecting illicit opiates 2. Based on AUDIT score of ≥ 16 which indicates high risk or harmful drinking in the past year [48] 3. Based on a HADS anxiety subscale score ≥ 11 indicating caseness [49] 4. Based on a HADS depression subscale score ≥ 11 indicating caseness [49] 5. Mean EqVAS score, where a score of 0 is worst imaginable health state and of 100 is best imaginable health state[50]. Chi square test for difference: # p < 0.01, *p > 0.001, ^ t-test for equality of means: p < 0.001.
Comparison records available across different data sources (NB. lack of comparison record does not necessarily imply failure of linkage as some individuals will not have experienced record generating events in relation to all data sources)
| Data source | Records attempted to link | Linkage successful |
|---|---|---|
| Scottish Morbidity Register (live confirmed cases) | 432 | 432 |
| Primary care records (live confirmed cases) | 432 | 432 |
| Primary care records (dead confirmed cases) | 223 | 182 |
| General Register Office for Scotland (dead confirmed cases) | 223 | 222 |
| Scottish Prison Service (live confirmed cases) | 432 | 198 |
| Lothian and Borders Police (subset of live confirmed cases) | 100 | 94 |
Comparison of agreement across different data sources of selected data items
| Variable | Reported at interview | Noted in primary care records | Agreement (%) |
|---|---|---|---|
| Ever on OST | 398 | 396 | 99% |
| Ever injected* | 406 | 393 | 97% |
| Ever referred to specialist drug treatment service | 324 | 387 | 84% |
| Ever overdosed and been seen by a doctor | 214 | 152 | 71% |
| Ever seen a doctor regarding alcohol problems | 72 | 71 | 99% |
| Current smoker | 403 | 281 | 70% |
| Currently medically unfit for work | 300 | 324 | 93% |
* See text for discussion
Potential biases, their influence and how this may be mitigated
| Potential source of bias | Impact of this bias | Possible strategies to minimise this and other relevant considerations |
|---|---|---|
| Selection bias with regard to initial case ascertainment since cases were all service users and IDU were not selected at onset of injecting | Causes, consequences, natural history and duration of IDU amongst injectors who do not present to services may be different | Impossible to avoid however likely to be less of an issue than in studies where cases are recruited from specialist clinics as this involves additional level of selection. In addition, time from onset of injecting to recruitment in this study shorter than in most other cohorts. |
| Survival bias with regard to case follow-up | Patterns of association between the factors under study may have been different amongst living compared to dead cohort members | Information on most factors of interest was available through record linkage on both living and dead cohort members |
| Selection bias with regard to case follow-up. Cases successfully followed up were willing to be interviewed. Unwillingness to be interviewed may have reflected either more chaotic current circumstances or a reluctance to discuss long resolved drug problems. | Patterns of association between the factors under study may be different amongst those lost to follow-up. Outcomes of IDU may have either been over or underestimated | Impossible to avoid though loss to follow-up was relatively low and much was due to structural factors (e.g. GP unwillingness to recruit) unlikely to be related to participant characteristics |
| Selection bias with regard to control recruitment as controls were all attending a health facility | If controls were more likely to have health problems than the general population this may have diluted associations between some risk factors and outcomes in case-control comparisons | The majority of the population use primary care services relatively regularly often for reasons unrelated to a significant health problem and any "unhealthy participant" effect is therefore likely to be small |
| Selection bias with regard to control recruitment as controls may not have been a representative sample of service users | Potential controls declining recruitment may have been different from those agreeing with regard to the factors under study | Consecutive eligible service users were approached during control recruitment. Only 3% declined suggesting substantial bias is unlikely |
| Selection bias with regard to control recruitment as controls were not recruited at the same time as cases | To be recruited controls must be alive and resident in the practice area. Despite age and sex matching this may have introduced bias. | Impossible to avoid as control selection from reconstructed historical practice list was unfeasible (see text). Impact may not have been substantial since healthier controls would be both more likely to be living but may also have been more likely to leave practice area. These influences would tend to cancel each other out in terms of resulting bias. |
| Social desirability bias in relation to interview measures | Cases may have been more likely to disclose drug use and other socially sensitive behaviours and exposures leading to overestimation of the association between these factors and IDU | Assurances of confidentiality and good relationship with practice team should have mitigated this. Where possible objective corroboration with measures collected through linkage was sought |
| Recall bias in relation to interview measures | Case recall of some early life exposures may have been influenced by their own beliefs around causes of IDU leading to overestimation of the association between these factors and IDU. Substance use may also have impaired case recall of previous exposures leading to underestimation of the association between these factors and IDU. | Use of the life-grid approach should have mitigated this. Where possible objective corroboration with measures collected through linkage was sought |
| Strong association between disadvantage and IDU may lead to confounding of case-control comparisons | Some apparent effects of both IDU itself and possible risk factors may in reality be effects of other correlates of disadvantage | Recruitment of controls from the same community as cases should mitigate any bias of this type and measurement of individual social position allows further adjustment |
Figure 3Multi-state model of injecting history. graphical depiction of the multi-state model of injecting history used in the analysis