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

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...

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Autores principales: Alkerwi, Ala’a, Pastore, Jessica, Sauvageot, Nicolas, Coroller, Gwenaëlle Le, Bocquet, Valéry, d’Incau, Marylène, Aguayo, Gloria, Appenzeller, Brice, Bejko, Dritan, Bohn, Torsten, Malisoux, Laurent, Couffignal, Sophie, Noppe, Stephanie, Delagardelle, Charles, Beissel, Jean, Chioti, Anna, Stranges, Saverio, Schmit, Jean-Claude
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6360765/
https://www.ncbi.nlm.nih.gov/pubmed/30717671
http://dx.doi.org/10.1186/s12874-019-0669-0
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author Alkerwi, Ala’a
Pastore, Jessica
Sauvageot, Nicolas
Coroller, Gwenaëlle Le
Bocquet, Valéry
d’Incau, Marylène
Aguayo, Gloria
Appenzeller, Brice
Bejko, Dritan
Bohn, Torsten
Malisoux, Laurent
Couffignal, Sophie
Noppe, Stephanie
Delagardelle, Charles
Beissel, Jean
Chioti, Anna
Stranges, Saverio
Schmit, Jean-Claude
author_facet Alkerwi, Ala’a
Pastore, Jessica
Sauvageot, Nicolas
Coroller, Gwenaëlle Le
Bocquet, Valéry
d’Incau, Marylène
Aguayo, Gloria
Appenzeller, Brice
Bejko, Dritan
Bohn, Torsten
Malisoux, Laurent
Couffignal, Sophie
Noppe, Stephanie
Delagardelle, Charles
Beissel, Jean
Chioti, Anna
Stranges, Saverio
Schmit, Jean-Claude
author_sort Alkerwi, Ala’a
collection PubMed
description 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. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12874-019-0669-0) contains supplementary material, which is available to authorized users.
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spelling pubmed-63607652019-02-08 Challenges and benefits of integrating diverse sampling strategies in the observation of cardiovascular risk factors (ORISCAV-LUX 2) study Alkerwi, Ala’a Pastore, Jessica Sauvageot, Nicolas Coroller, Gwenaëlle Le Bocquet, Valéry d’Incau, Marylène Aguayo, Gloria Appenzeller, Brice Bejko, Dritan Bohn, Torsten Malisoux, Laurent Couffignal, Sophie Noppe, Stephanie Delagardelle, Charles Beissel, Jean Chioti, Anna Stranges, Saverio Schmit, Jean-Claude BMC Med Res Methodol Research Article 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. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12874-019-0669-0) contains supplementary material, which is available to authorized users. BioMed Central 2019-02-04 /pmc/articles/PMC6360765/ /pubmed/30717671 http://dx.doi.org/10.1186/s12874-019-0669-0 Text en © The Author(s). 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Alkerwi, Ala’a
Pastore, Jessica
Sauvageot, Nicolas
Coroller, Gwenaëlle Le
Bocquet, Valéry
d’Incau, Marylène
Aguayo, Gloria
Appenzeller, Brice
Bejko, Dritan
Bohn, Torsten
Malisoux, Laurent
Couffignal, Sophie
Noppe, Stephanie
Delagardelle, Charles
Beissel, Jean
Chioti, Anna
Stranges, Saverio
Schmit, Jean-Claude
Challenges and benefits of integrating diverse sampling strategies in the observation of cardiovascular risk factors (ORISCAV-LUX 2) study
title Challenges and benefits of integrating diverse sampling strategies in the observation of cardiovascular risk factors (ORISCAV-LUX 2) study
title_full Challenges and benefits of integrating diverse sampling strategies in the observation of cardiovascular risk factors (ORISCAV-LUX 2) study
title_fullStr Challenges and benefits of integrating diverse sampling strategies in the observation of cardiovascular risk factors (ORISCAV-LUX 2) study
title_full_unstemmed Challenges and benefits of integrating diverse sampling strategies in the observation of cardiovascular risk factors (ORISCAV-LUX 2) study
title_short Challenges and benefits of integrating diverse sampling strategies in the observation of cardiovascular risk factors (ORISCAV-LUX 2) study
title_sort challenges and benefits of integrating diverse sampling strategies in the observation of cardiovascular risk factors (oriscav-lux 2) study
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6360765/
https://www.ncbi.nlm.nih.gov/pubmed/30717671
http://dx.doi.org/10.1186/s12874-019-0669-0
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