A novel framework for classification of selection processes in epidemiological research

Ice cleat distribution programmes and ice cleat use among older adults: repeated cross-sectional evidence from 63 municipal interventions in Sweden

INTRODUCTION

Ice cleats may help prevent ice-related falls in places with icy roads, but there is limited evidence about the association between ice cleat distribution and ice cleat use. Our study examined the association between Swedish municipal distribution programmes and ice cleat use among older adults (65+ years).

METHODS

We combined data on municipal ice cleat distribution programmes (n=63) with repeated cross-sectional self-reports of ice cleat use in Sweden from 2007, 2010, 2014 and 2018. Respondents (n=63 234) were classified as exposed if they lived in a municipality with a programme, belonged to an eligible age group and responded after distribution (n=2507). Dose-response was assessed using distributed ice cleat pairs per capita (mean: 0.38). Linear probability models were used to estimate probability differences in ice cleat use between exposed and unexposed respondents, adjusting for age, sex, country of birth, education, survey wave and municipality. Ineligible age groups living in programme municipalities, who should be unaffected by ice cleat distribution, were used for bias assessment.

RESULTS

Exposure to ice cleat distribution programmes was associated with 7.5 percentage points (95% CI 4.2 to 10.9) higher self-reported ice cleat use after confounding adjustment. The association was larger in municipalities that distributed one pair of ice cleats per capita (17.3 percentage points (95% CI 11.2 to 23.4)). No association was found among the ineligible age groups (-2.3 (95% CI -5.5 to 1.0)).

CONCLUSION

Distributing ice cleats to older adults may help increase their use of ice cleats in settings with icy road conditions.

The value of combining individual and small area sociodemographic data for assessing and handling selective participation in cohort studies: Evidence from the Swedish CardioPulmonary bioImage Study

Objectives

To study the value of combining individual- and neighborhood-level sociodemographic data to predict study participation and assess the effects of baseline selection on the distribution of metabolic risk factors and lifestyle factors in the Swedish CardioPulmonary bioImage Study (SCAPIS).

Methods

We linked sociodemographic register data to SCAPIS participants (n = 30,154, ages: 50–64 years) and a random sample of the study’s target population (n = 59,909). We assessed the classification ability of participation models based on individual-level data, neighborhood-level data, and combinations of both. Standardized mean differences (SMD) were used to examine how reweighting the sample to match the population affected the averages of 32 cardiopulmonary risk factors at baseline. Absolute SMDs >0.10 were considered meaningful.

Results

Combining both individual-level and neighborhood-level data gave rise to a model with better classification ability (AUC: 71.3%) than models with only individual-level (AUC: 66.9%) or neighborhood-level data (AUC: 65.5%). We observed a greater change in the distribution of risk factors when we reweighted the participants using both individual and area data. The only meaningful change was related to the (self-reported) frequency of alcohol consumption, which appears to be higher in the SCAPIS sample than in the population. The remaining risk factors did not change meaningfully.

Conclusions

Both individual- and neighborhood-level characteristics are informative in assessing study selection effects. Future analyses of cardiopulmonary outcomes in the SCAPIS cohort can benefit from our study, though the average impact of selection on risk factor distributions at baseline appears small.

Reweighting a Swedish health questionnaire survey using extensive population register and self-reported data for assessing and improving the validity of longitudinal associations

Background

In cohorts with voluntary participation, participants may not be representative of the underlying population, leading to distorted estimates. If the relevant sources of selective participation are observed, it is however possible to restore the representativeness by reweighting the sample to resemble the target population. So far, few studies in epidemiology have applied reweighting based on extensive register data on socio-demographics and disease history, or with self-reported data on health and health-related behaviors.

Methods

We examined selective participation at baseline and the first two follow-ups of the Scania Public Health Cohort (SPHC), a survey conducted in Southern Sweden in 1999/2000 (baseline survey; n = 13,581 participants, 58% participation rate), 2005 (first follow-up, n = 10,471), and 2010 (second follow-up; n = 9,026). Survey participants were reweighted to resemble the underlying population with respect to a broad range of socio-demographic, disease, and health-related characteristics, and we assessed how selective participation impacted the validity of associations between self-reported overall health and dimensions of socio-demographics and health.

Results

Participants in the baseline and follow-up surveys were healthier and more likely to be female, born in Sweden, middle-aged, and have higher socioeconomic status. However, the differences were not very large. In turn, reweighting the samples to match the target population had generally small or moderate impacts on associations. Most examined regression coefficients changed by less than 20%, with virtually no changes in the directions of the effects.

Conclusion

Overall, selective participation with respect to the observed factors was not strong enough to substantially alter the associations with self-assessed health. These results are consistent with an interpretation that SPHC has high validity, perhaps reflective of a relatively high participation rate. Since validity must be determined on a case-by-case basis, however, researchers should apply the same method to other health cohorts to assess and potentially improve the validity.