2 results
Association of organic food consumption with obesity in a nationally representative sample
- Corentin J. Gosling, Aurélie Goncalves, Mickaël Ehrminger, Richard Valliant
-
- Journal:
- British Journal of Nutrition / Volume 125 / Issue 6 / 28 March 2021
- Published online by Cambridge University Press:
- 17 August 2020, pp. 703-711
- Print publication:
- 28 March 2021
-
- Article
-
- You have access Access
- HTML
- Export citation
-
The increased prevalence and adverse health consequences of obesity have made it one of the leading public health issues in recent years. Importantly, several epidemiological studies have revealed significant associations between BMI and organic food consumption. However, although these studies have suggested that this factor holds promise to prevent obesity, they all suffer from methodological limitations, including self-reporting methods to assess BMI, not controlling for potential confounding factors or using a non-representative sample. Moreover, all were restricted to an adult sample. We present the results of a cross-sectional epidemiological study assessing the association of organic food consumption with BMI and obesity in a representative lifespan French sample (INCA3 study). Objective methods were used to measure BMI, and several potentially confounding variables were controlled for. In total, 1775 children and adolescents and 2121 adults underwent anthropometric measurements and completed questionnaires concerning their dietary habits and lifestyle. Unadjusted models systematically revealed negative associations between organic food consumption and both BMI and obesity across all age groups. These associations tended to remain statistically significant even after controlling for several confounding variables concerning socio-economic status, quality of the diet and physical activity. The effect sizes were, however, small. These data confirm the association between organic food consumption and obesity during both childhood and adulthood. Evidence from randomised controlled trials is required to investigate causality between organic food consumption and lower BMI or obesity rate.
20 - Recent developments of sampling hard-to-survey populations: an assessment
-
- By Sunghee Lee, University of Michigan, James Wagner, University of Michigan, Richard Valliant, University of Michigan, Steve Heeringa, University of Michigan
- Edited by Roger Tourangeau, Brad Edwards, Timothy P. Johnson, University of Illinois, Chicago, Kirk M. Wolter, University of Chicago, Nancy Bates
-
- Book:
- Hard-to-Survey Populations
- Published online:
- 05 September 2014
- Print publication:
- 28 August 2014, pp 424-444
-
- Chapter
- Export citation
-
Summary
Introduction
While there are difficulties in precisely defining hard-to-survey (H2S), hard-to-find, rare, hidden, or elusive populations (see Chapter 1 for a discussion of definitions), there is general agreement that it is very difficult to locate certain population subgroups. Studying such groups using cross-sectional surveys of the general population is challenging, because sample sizes are often too small to provide reasonable precision for point estimates and statistical power for comparisons. If the H2S groups are the target population of a study, sampling of their members becomes an issue.
Sampling for scientific data collection with these H2S populations is one of the most notable challenges discussed in the sampling literature (e.g., Kalton, 2009; Sudman, Sirken, & Cowan, 1988). Some studies mistakenly argue that frames do not exist for these populations (e.g., Paquette & de Wit, 2010). It is true that there are no readily available sampling frames exclusively of these population members. However, it is technically possible to sample from the general population and screen for the target population members. This type of screening presents two challenges. First, building a sampling frame for such H2S populations is costly. Assume that a study has HIV positive cigarette smokers as its target population, as in Humfleet, Delucchi, Kelley, Hall, Dilley, and Harrison (2009). A large number of households sampled from the general population need to be screened to find enough people who meet the criteria of both being HIV positive and smoking cigarettes. Second, depending on the level of social stigma and discrimination associated with the H2S population of interest, some population members may misreport their eligibility intentionally in the screening interviews in order not to reveal their identity. HIV positive cigarette smokers are associated with socially stigmatized HIV status as well as the socially undesirable status of being a smoker. For these reasons, traditional probability sampling approaches, although ideal, are often regarded as being infeasible and impractical. Although expensive to conduct, there are many studies of H2S populations using probability samples (see Table 15.1 of Binson, Blair, Huebner, & Woods, 2007). Examples include the use of multistage area probability samples and random digit dialed (RDD) telephone samples (e.g., Catania, Osmond, Stall, Pollack, Paul, Blower et al., 2001; Cochran & Mays, 2000).