Challenges and benefits of integrating diverse sampling strategies in the observation of cardiovascular risk factors (ORISCAV-LUX 2) study.


Journal

BMC medical research methodology
ISSN: 1471-2288
Titre abrégé: BMC Med Res Methodol
Pays: England
ID NLM: 100968545

Informations de publication

Date de publication:
04 02 2019
Historique:
received: 18 06 2018
accepted: 28 01 2019
entrez: 6 2 2019
pubmed: 6 2 2019
medline: 25 1 2020
Statut: epublish

Résumé

It is challenging to manage data collection as planned and creation of opportunities to adapt during the course of enrolment may be needed. This paper aims to summarize the different sampling strategies adopted in the second wave of Observation of Cardiovascular Risk Factors (ORISCAV-LUX, 2016-17), with a focus on population coverage and sample representativeness. Data from the first nationwide cross-sectional, population-based ORISCAV-LUX survey, 2007-08 and from the newly complementary sample recruited via different pathways, nine years later were analysed. First, we compare the socio-demographic characteristics and health profiles between baseline participants and non-participants to the second wave. Then, we describe the distribution of subjects across different strategy-specific samples and performed a comparison of the overall ORISCAV-LUX2 sample to the national population according to stratification criteria. For the baseline sample (1209 subjects), the participants (660) were younger than the non-participants (549), with a significant difference in average ages (44 vs 45.8 years; P = 0.019). There was a significant difference in terms of education level (P < 0.0001), 218 (33%) participants having university qualification vs. 95 (18%) non-participants. The participants seemed having better health perception (p < 0.0001); 455 (70.3%) self-reported good or very good health perception compared to 312 (58.2%) non-participants. The prevalence of obesity (P < 0.0001), hypertension (P < 0.0001), diabetes (P = 0.007), and mean values of related biomarkers were significantly higher among the non-participants. The overall sample (1558 participants) was mainly composed of randomly selected subjects, including 660 from the baseline sample and 455 from other health examination survey sample and 269 from civil registry sample (constituting in total 88.8%), against only 174 volunteers (11.2%), with significantly different characteristics and health status. The ORISCAV-LUX2 sample was representative of national population for geographical district, but not for sex and age; the younger (25-34 years) and older (65-79 years) being underrepresented, whereas middle-aged adults being over-represented, with significant sex-specific difference (p < 0.0001). This study represents a careful first-stage analysis of the ORISCAV-LUX2 sample, based on available information on participants and non-participants. The ORISCAV-LUX datasets represents a relevant tool for epidemiological research and a basis for health monitoring and evidence-based prevention of cardiometabolic risk in Luxembourg.

Sections du résumé

BACKGROUND
It is challenging to manage data collection as planned and creation of opportunities to adapt during the course of enrolment may be needed. This paper aims to summarize the different sampling strategies adopted in the second wave of Observation of Cardiovascular Risk Factors (ORISCAV-LUX, 2016-17), with a focus on population coverage and sample representativeness.
METHODS
Data from the first nationwide cross-sectional, population-based ORISCAV-LUX survey, 2007-08 and from the newly complementary sample recruited via different pathways, nine years later were analysed. First, we compare the socio-demographic characteristics and health profiles between baseline participants and non-participants to the second wave. Then, we describe the distribution of subjects across different strategy-specific samples and performed a comparison of the overall ORISCAV-LUX2 sample to the national population according to stratification criteria.
RESULTS
For the baseline sample (1209 subjects), the participants (660) were younger than the non-participants (549), with a significant difference in average ages (44 vs 45.8 years; P = 0.019). There was a significant difference in terms of education level (P < 0.0001), 218 (33%) participants having university qualification vs. 95 (18%) non-participants. The participants seemed having better health perception (p < 0.0001); 455 (70.3%) self-reported good or very good health perception compared to 312 (58.2%) non-participants. The prevalence of obesity (P < 0.0001), hypertension (P < 0.0001), diabetes (P = 0.007), and mean values of related biomarkers were significantly higher among the non-participants. The overall sample (1558 participants) was mainly composed of randomly selected subjects, including 660 from the baseline sample and 455 from other health examination survey sample and 269 from civil registry sample (constituting in total 88.8%), against only 174 volunteers (11.2%), with significantly different characteristics and health status. The ORISCAV-LUX2 sample was representative of national population for geographical district, but not for sex and age; the younger (25-34 years) and older (65-79 years) being underrepresented, whereas middle-aged adults being over-represented, with significant sex-specific difference (p < 0.0001).
CONCLUSION
This study represents a careful first-stage analysis of the ORISCAV-LUX2 sample, based on available information on participants and non-participants. The ORISCAV-LUX datasets represents a relevant tool for epidemiological research and a basis for health monitoring and evidence-based prevention of cardiometabolic risk in Luxembourg.

Identifiants

pubmed: 30717671
doi: 10.1186/s12874-019-0669-0
pii: 10.1186/s12874-019-0669-0
pmc: PMC6360765
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

27

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Auteurs

Ala'a Alkerwi (A)

Luxembourg Institute of Health (LIH), Department of Population Health, 1A rue Thomas Edison, L-1445, Strassen, Luxembourg. alaa.alkerwi@lih.lu.

Jessica Pastore (J)

Luxembourg Institute of Health (LIH), Department of Population Health, 1A rue Thomas Edison, L-1445, Strassen, Luxembourg.

Nicolas Sauvageot (N)

Luxembourg Institute of Health (LIH), Department of Population Health, 1A rue Thomas Edison, L-1445, Strassen, Luxembourg.

Gwenaëlle Le Coroller (GL)

Luxembourg Institute of Health (LIH), Department of Population Health, 1A rue Thomas Edison, L-1445, Strassen, Luxembourg.

Valéry Bocquet (V)

Luxembourg Institute of Health (LIH), Department of Population Health, 1A rue Thomas Edison, L-1445, Strassen, Luxembourg.

Marylène d'Incau (M)

Luxembourg Institute of Health (LIH), Department of Population Health, 1A rue Thomas Edison, L-1445, Strassen, Luxembourg.

Gloria Aguayo (G)

Luxembourg Institute of Health (LIH), Department of Population Health, 1A rue Thomas Edison, L-1445, Strassen, Luxembourg.

Brice Appenzeller (B)

Luxembourg Institute of Health (LIH), Department of Population Health, 1A rue Thomas Edison, L-1445, Strassen, Luxembourg.

Dritan Bejko (D)

Luxembourg Institute of Health (LIH), Department of Population Health, 1A rue Thomas Edison, L-1445, Strassen, Luxembourg.

Torsten Bohn (T)

Luxembourg Institute of Health (LIH), Department of Population Health, 1A rue Thomas Edison, L-1445, Strassen, Luxembourg.

Laurent Malisoux (L)

Luxembourg Institute of Health (LIH), Department of Population Health, 1A rue Thomas Edison, L-1445, Strassen, Luxembourg.

Sophie Couffignal (S)

Luxembourg Institute of Health (LIH), Department of Population Health, 1A rue Thomas Edison, L-1445, Strassen, Luxembourg.

Stephanie Noppe (S)

Centre Hospitalier du Luxembourg (CHL), Luxembourg City, Luxembourg.

Charles Delagardelle (C)

Centre Hospitalier du Luxembourg (CHL), Luxembourg City, Luxembourg.

Jean Beissel (J)

Centre Hospitalier du Luxembourg (CHL), Luxembourg City, Luxembourg.

Anna Chioti (A)

Ministry of Health, Directorate of Health, Luxembourg City, Luxembourg.

Saverio Stranges (S)

Luxembourg Institute of Health (LIH), Department of Population Health, 1A rue Thomas Edison, L-1445, Strassen, Luxembourg.
Department of Epidemiology & Biostatistics, Schulich School of Medicine & Dentistry, Western University, London, ON, N6A 5C1, Canada.

Jean-Claude Schmit (JC)

Ministry of Health, Directorate of Health, Luxembourg City, Luxembourg.

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