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7. Ecological factors and childhood eating behaviours at 5 years of age: findings from the ROLO longitudinal birth cohort study

Author

Delahunt, A, Conway, MC, O'Brien, EC, Geraghty, AA, O'Keeffe, LM, O'Reilly, SL, McDonnell, CM, Kearney, PM, Mehegan, J, McAuliffe, FM, Delahunt, A, Conway, MC, O'Brien, EC, Geraghty, AA, O'Keeffe, LM, O'Reilly, SL, McDonnell, CM, Kearney, PM, Mehegan, J, and McAuliffe, FM

Abstract

BACKGROUND: Individual differences in children eating behaviours have been linked with childhood overweight and obesity. The determinants of childhood eating behaviours are influenced by a complex combination of hereditary and ecological factors. This study examines if key ecological predictors of childhood overweight; maternal socio-economic status (SES), children's screen time, and childcare arrangements, are associated with eating behaviours in children aged 5-years-old. METHODS: This is secondary, cross-sectional analysis of the ROLO (Randomized COntrol Trial of LOw glycemic diet in pregnancy) study, using data from the 5-year follow-up (n = 306). Weight, height, and body mass index (BMI) were obtained from mothers and children at the 5-year follow-up. Children's BMI z-scores were calculated. SES was determined using maternal education level and neighborhood deprivation score. Information on children's screen time and childcare arrangements were collected using lifestyle questionnaires. Children's eating behaviours were measured using the Children's Eating Behaviour Questionnaire (CEBQ). Multiple linear regression, adjusted for potential confounders, assessed associations between maternal SES, screen time and children's eating behaviours. One-way ANOVA, independent sample t-tests and Spearman's correlation examined childcare exposure and children's eating behaviour. RESULTS: Mothers in the lowest SES group had higher BMI and were younger than those in the highest SES group (p = < 0.001, p = 0.03 respectively). In adjusted analysis, the lowest SES group was associated with a 0.463-point higher mean score for 'Desire to Drink' (95% CI = 0.054,0.870, p = 0.027) and higher 'Slowness to Eat' (B = 0.388, 95% CI = 0.044,0.733, p = 0.027) when compared with the highest SES group. Screen time (hours) was associated with higher 'Food Fussiness' (B = 0.032, 95% CI = 0.014,0.051, p = 0.001). Those who attended childcare had higher scores for 'Desire to Drink'(p = 0.046). N

Published
2022

10. A study protocol for the development of a SPIRIT extension for trials conducted using cohorts and routinely collected data (SPIRIT-ROUTINE) [version 1; peer review: 2 approved]

Author

McCarthy, M, O'Keeffe, L, Williamson, PR, Sydes, MR, Farrin, A, Lugg-Widger, F, Davies, G, Avery, K, Chan, A-W, Kwakkenbos, L, Thombs, BD, Watkins, A, Hemkens, LG, Gale, C, Zwarenstein, M, Langan, SM, Thabane, L, Juszczak, E, Moher, D, Kearney, PM, and Canadian Institutes of Health Research

Subjects
routinely collected data, electronic health records, registry-based randomised controlled trial, education, registries, Medicine, SPIRIT, cohort, reporting guideline, humanities, electronic patient records
Abstract

Background: Protocols are an essential document for conducting randomised controlled trials (RCTs). However, the completeness of the information provided is often inadequate. To help improve the content of trial protocols, an international group of stakeholders published the Standard Protocol Items: Recommendations for Interventional Trials (SPIRIT) Initiative in 2013. Presently, there is increasing use of cohorts and routinely collected data (RCD) for RCTs because these data have the potential to improve efficiencies by facilitating recruitment, simplifying, and reducing the cost of data collection. Reporting guidelines have been shown to improve the quality of reporting, but there is currently no specific SPIRIT guidance on protocols for trials conducted using cohorts and RCD. This protocol outlines steps for developing SPIRIT-ROUTINE, which aims to address this gap by extending the SPIRIT guidance to protocols for trials conducted using cohorts and RCD. Methods: The development of the SPIRIT-ROUTINE extension comprises five stages. Stage 1 consists of a project launch and a meeting to finalise the membership of the steering group and scope of the extension. In Stage 2, a rapid review will be performed to identify possible modifications to the original SPIRIT 2013 checklist. Other key reporting guidelines will be reviewed to identify areas where additional items may be needed, such as the Consolidated Standards of Reporting Trials (CONSORT) extension for trials conducted using cohorts and RCD (CONSORT-ROUTINE). Stage 3 will involve an online Delphi exercise, consisting of two rounds and involving key international stakeholders to gather feedback on the preliminary checklist items. In Stage 4, a consensus meeting of the SPIRIT-ROUTINE steering group will finalise the items to include in the extension. Stage 5 will involve the publication preparation and dissemination of the final checklist. Conclusion: The SPIRIT-ROUTINE extension will contribute to improving design of trials using cohorts and RCD and transparency of reporting.

Published
2021

21. Study protocol: a randomised controlled trial on the clinical effects of levothyroxine treatment for subclinical hypothyroidism in people aged 80 years and over

Author

Du Puy, RS, Postmus, I, Stott, DJ, Blum, MR, Poortvliet, RKE, den Elzen, WPJ, Peeters, Robin, van Munster, BC, Wolffenbuttel, BHR, Westendorp, RGJ, Kearney, PM, Ford, I, Kean, S, Messow, CM, Watt, T, Jukemal, JW, Dekkers, OM, Smit, JWA, Rodondi, N, Gussekloo, J, Mooijaart, SP, Du Puy, RS, Postmus, I, Stott, DJ, Blum, MR, Poortvliet, RKE, den Elzen, WPJ, Peeters, Robin, van Munster, BC, Wolffenbuttel, BHR, Westendorp, RGJ, Kearney, PM, Ford, I, Kean, S, Messow, CM, Watt, T, Jukemal, JW, Dekkers, OM, Smit, JWA, Rodondi, N, Gussekloo, J, and Mooijaart, SP

Published
2018

29. Genome of the Netherlands population-specific imputations identify an ABCA6 variant associated with cholesterol levels

Author

Van Leeuwen, EM, Karssen, LC, Deelen, J, Isaacs, A, Medina-Gomez, C, Mbarek, H, Kanterakis, A, Trompet, S, Postmus, I, Verweij, N, Van Enckevort, DJ, Huffman, JE, White, CC, Feitosa, MF, Bartz, TM, Manichaikul, A, Joshi, PK, Peloso, GM, Deelen, P, Van Dijk, F, Willemsen, G, De Geus, EJ, Milaneschi, Y, Penninx, BWJH, Francioli, LC, Menelaou, A, Pulit, SL, Rivadeneira, F, Hofman, A, Oostra, BA, Franco, OH, Leach, IM, Beekman, M, De Craen, AJM, Uh, HW, Trochet, H, Hocking, LJ, Porteous, DJ, Sattar, N, Packard, CJ, Buckley, BM, Brody, JA, Bis, JC, Rotter, JI, Mychaleckyj, JC, Campbell, H, Duan, Q, Lange, LA, Wilson, JF, Hayward, C, Polasek, O, Vitart, V, Rudan, I, Wright, AF, Rich, SS, Psaty, BM, Borecki, IB, Kearney, PM, Stott, DJ, Cupples, LA, Jukema, JW, Van Der Harst, P, Sijbrands, EJ, Hottenga, JJ, Uitterlinden, AG, Swertz, MA, Van Ommen, GJB, De Bakker, PIW, Eline Slagboom, P, Boomsma, DI, Wijmenga, C, Van Duijn, CM, Neerincx, PBT, Elbers, CC, Palamara, PF, Peer, I, Abdellaoui, A, Kloosterman, WP, Van Oven, M, Vermaat, M, Li, M, Laros, JFJ, Stoneking, M, De Knijff, P, Kayser, M, Veldink, JH, Van Den Berg, LH, Byelas, H, Den Dunnen, JT, Dijkstra, M, Amin, N, Van Der Velde, KJ, and Van Setten, J

Abstract

© 2015 Macmillan Publishers Limited. All rights reserved. Variants associated with blood lipid levels may be population-specific. To identify low-frequency variants associated with this phenotype, population-specific reference panels may be used. Here we impute nine large Dutch biobanks (∼35,000 samples) with the population-specific reference panel created by the Genome of the Netherlands Project and perform association testing with blood lipid levels. We report the discovery of five novel associations at four loci (P value

Published
2015

33. Genome of the Netherlands population-specific imputations identify an ABCA6 variant associated with cholesterol levels

Author

Leeuwen, Elisa, Karssen, Lennart, Deelen, J, Isaacs, Aaron, Medina-Gomez, C, Mbarek, H, Kanterakis, A, Trompet, S, Postmus, I, Verweij, N (Niek), van Enckevort, DJ, Huffman, JE, White, CC, Feitosa, MF, Bartz, TM, Manichaikul, A, Joshi, PK, Peloso, GM, Deelen, P, Dijk, Femke, Willemsen, G, de Geus, EJ, Milaneschi, Y, Penninx, BWJH, Francioli, LC, Menelaou, A, Pulit, SL, Rivadeneira, Fernando, Hofman, Bert, Oostra, Ben, Franco Duran, OH, Leach, IM, Beekman, M, de Craen, AJM, Uh, HW, Trochet, H, Hocking, LJ, Porteous, DJ, Sattar, N, Packard, CJ, Buckley, BM, Brody, JA, Bis, JC, Rotter, JI, Mychaleckyj, JC, Campbell, H, Duan, Q, Lange, LA, Wilson, JF, Hayward, C, Polasek, O, Vitart, V, Rudan, I, Wright, AF, Rich, SS, Psaty, BM, Borecki, IB, Kearney, PM, Stott, DJ, Cupples, LA, Jukema, JW, van der Harst, P, Sijbrands, E.J.G., Hottenga, JJ (Jouke Jan), Uitterlinden, André, Swertz, MA, van Ommen, GJB, de Bakker, PIW, Slagboom, PE (Eline), Boomsma, DI, Wijmenga, C, Duijn, Cornelia, Leeuwen, Elisa, Karssen, Lennart, Deelen, J, Isaacs, Aaron, Medina-Gomez, C, Mbarek, H, Kanterakis, A, Trompet, S, Postmus, I, Verweij, N (Niek), van Enckevort, DJ, Huffman, JE, White, CC, Feitosa, MF, Bartz, TM, Manichaikul, A, Joshi, PK, Peloso, GM, Deelen, P, Dijk, Femke, Willemsen, G, de Geus, EJ, Milaneschi, Y, Penninx, BWJH, Francioli, LC, Menelaou, A, Pulit, SL, Rivadeneira, Fernando, Hofman, Bert, Oostra, Ben, Franco Duran, OH, Leach, IM, Beekman, M, de Craen, AJM, Uh, HW, Trochet, H, Hocking, LJ, Porteous, DJ, Sattar, N, Packard, CJ, Buckley, BM, Brody, JA, Bis, JC, Rotter, JI, Mychaleckyj, JC, Campbell, H, Duan, Q, Lange, LA, Wilson, JF, Hayward, C, Polasek, O, Vitart, V, Rudan, I, Wright, AF, Rich, SS, Psaty, BM, Borecki, IB, Kearney, PM, Stott, DJ, Cupples, LA, Jukema, JW, van der Harst, P, Sijbrands, E.J.G., Hottenga, JJ (Jouke Jan), Uitterlinden, André, Swertz, MA, van Ommen, GJB, de Bakker, PIW, Slagboom, PE (Eline), Boomsma, DI, Wijmenga, C, and Duijn, Cornelia

Abstract

Variants associated with blood lipid levels may be population-specific. To identify low-frequency variants associated with this phenotype, population-specific reference panels may be used. Here we impute nine large Dutch biobanks (similar to 35,000 samples) with the population-specific reference panel created by the Genome of the Netherlands Project and perform association testing with blood lipid levels. We report the discovery of five novel associations at four loci (P value < 6.61 x 10(-4)), including a rare missense variant in ABCA6 (rs77542162, p.Cys1359Arg, frequency 0.034), which is predicted to be deleterious. The frequency of this ABCA6 variant is 3.65-fold increased in the Dutch and its effect (beta(LDL-C) = 0.135, beta(TC) = 0.140) is estimated to be very similar to those observed for single variants in well-known lipid genes, such as LDLR.

Published
2015

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