Comparison of participants and non-participants to the ORISCAV-LUX population-based study on cardiovascular risk factors in Luxembourg

BACKGROUND: Poor response is a major concern in public health surveys. In a population-based ORISCAV-LUX study carried out in Grand-Duchy of Luxembourg to assess the cardiovascular risk factors, the non-response rate was not negligible. The aims of the present work were: 1) to investigate the representativeness of study sample to the general population, and 2) to compare the known demographic and cardiovascular health-related profiles of participants and non-participants. METHODS: For sample representativeness, the participants were compared to the source population according to stratification criteria (age, sex and district of residence). Based on complementary information from the "medical administrative database", further analysis was carried out to assess whether the health status affected the response rate. Several demographic and morbidity indicators were used in the univariate comparison between participants and non-participants. RESULTS: Among the 4452 potentially eligible subjects contacted for the study, there were finally 1432 (32.2%) participants. Compared to the source population, no differences were found for gender and district distribution. By contrast, the youngest age group was under-represented while adults and elderly were over-represented in the sample, for both genders. Globally, the investigated clinical profile of the non-participants was similar to that of participants. Hospital admission and cardiovascular health-related medical measures were comparable in both groups even after controlling for age. The participation rate was lower in Portuguese residents as compared to Luxembourgish (OR = 0.58, 95% CI: 0.48-0.69). It was also significantly associated with the professional status (P < 0.0001). Subjects from the working class were less receptive to the study than those from other professional categories. CONCLUSION: The 32.2% participation rate obtained in the ORISCAV-LUX survey represents the realistic achievable rate for this type of multiple-stage, nationwide, population-based surveys. It corresponds to the expected rate upon which the sample size was calculated. Given the absence of discriminating health profiles between participants and non-participants, it can be concluded that the response rate does not invalidate the results and allows generalizing the findings for the population

Practical considerations for sensitivity analysis after multiple imputation applied to epidemiological studies with incomplete data

<p>Abstract</p> <p>Background</p> <p>Multiple Imputation as usually implemented assumes that data are Missing At Random (MAR), meaning that the underlying missing data mechanism, given the observed data, is independent of the unobserved data. To explore the sensitivity of the inferences to departures from the MAR assumption, we applied the method proposed by Carpenter <it>et al.</it> (2007).</p> <p>This approach aims to approximate inferences under a Missing Not At random (MNAR) mechanism by reweighting estimates obtained after multiple imputation where the weights depend on the assumed degree of departure from the MAR assumption.</p> <p>Methods</p> <p>The method is illustrated with epidemiological data from a surveillance system of hepatitis C virus (HCV) infection in France during the 2001–2007 period. The subpopulation studied included 4343 HCV infected patients who reported drug use. Risk factors for severe liver disease were assessed. After performing complete-case and multiple imputation analyses, we applied the sensitivity analysis to 3 risk factors of severe liver disease: past excessive alcohol consumption, HIV co-infection and infection with HCV genotype 3.</p> <p>Results</p> <p>In these data, the association between severe liver disease and HIV was underestimated, if given the observed data the chance of observing HIV status is high when this is positive. Inference for two other risk factors were robust to plausible local departures from the MAR assumption.</p> <p>Conclusions</p> <p>We have demonstrated the practical utility of, and advocate, a pragmatic widely applicable approach to exploring plausible departures from the MAR assumption post multiple imputation. We have developed guidelines for applying this approach to epidemiological studies.</p

The impact of non-response bias due to sampling in public health studies: A comparison of voluntary versus mandatory recruitment in a Dutch national survey on adolescent health

Background: In public health monitoring of young people it is critical to understand the effects of selective non-response, in particular when a controversial topic is involved like substance abuse or sexual behaviour. Research that is dependent upon voluntary subject participation is particularly vulnerable to sampling bias. As respondents whose participation is hardest to elicit on a voluntary basis are also more likely to report risk behaviour, this potentially leads to underestimation of risk factor prevalence. Inviting adolescents to participate in a home-sent postal survey is a typical voluntary recruitment strategy with high non-response, as opposed to mandatory participation during school time. This study examines the extent to which prevalence estimates of adolescent health-related characteristics are biased due to different sampling methods, and whether this also biases within-subject analyses. Methods: Cross-sectional datasets collected in 2011 in Twente and IJsselland, two similar and adjacent regions in the Netherlands, were used. In total, 9360 youngsters in a mandatory sample (Twente) and 1952 youngsters in a voluntary sample (IJsselland) participated in the study. To test whether the samples differed on health-related variables, we conducted both univariate and multivariable logistic regression analyses controlling for any demographic difference between the samples. Additional multivariable logistic regressions were conducted to examine moderating effects of sampling method on associations between health-related variables. Results: As expected, females, older individuals, as well as individuals with higher education levels, were over-represented in the voluntary sample, compared to the mandatory sample. Respondents in the voluntary sample tended to smoke less, consume less alcohol (ever, lifetime, and past four weeks), have better mental health, have better subjective health status, have more positive school experiences and have less sexual intercourse than respondents in the mandatory sample. No moderating effects were found for sampling method on associations between variables. Conclusions: This is one of first studies to provide strong evidence that voluntary recruitment may lead to a strong non-response bias in health-related prevalence estimates in adolescents, as compared to mandatory recruitment. The resulting underestimation in prevalence of health behaviours and well-being measures appeared large, up to a four-fold lower proportion for self-reported alcohol consumption. Correlations between variables, though, appeared to be insensitive to sampling bias

Unit Nonresponse in a Population-Based Study of Prostate Cancer

Low unit response rates can increase bias and compromise study validity. Response rates have continued to fall over the past decade despite all efforts to increase participation. Many factors have been linked to reduced response, yet relatively few studies have employed multivariate approaches to identify characteristics that differentiate respondents from nonrespondents since it is hard to collect information on the latter. We aimed to assess factors contributing to enrollment of prostate cancer (PCa) patients. We combined data from the North Carolina-Louisiana (LA) PCa Project's LA cohort, with additional sources such as US census tract and LA tumor registry data. We included specific analyses focusing on blacks, a group often identified as hard to enroll in health-related research. The ability to study the effect of Hurricane Katrina, which occurred amidst enrollment, as a potential determinant of nonresponse makes our study unique. Older age (≥ 70) for blacks (OR 0.65) and study phase with respect to Hurricane Katrina for both races (OR 0.59 for blacks, OR 0.48 for whites) were significant predictors of participation with lower odds. Neighborhood poverty for whites (OR 1.53) also was a significant predictor of participation, but with higher odds. Among blacks, residence in Orleans parish was associated with lower odds of participation (OR 0.33) before Katrina. The opposite occurred in whites, with lower odds (OR 0.43) after Katrina. Our results overall underscore the importance of tailoring enrollment approaches to specific target population characteristics to confront the challenges posed by nonresponse. Our results also show that recruitment-related factors may change when outside forces bring major alterations to a population's environment and demographics