Development and Validation of a Risk Score Predicting Substantial Weight Gain over 5 Years in Middle-Aged European Men and Women

Annika Steffen; Thorkild I.A. Sørensen; Sven Knüppel; Noemie Travier; María-José Sánchez; José María Huerta; J Ramón Quirós; Eva Ardanaz; Miren Dorronsoro; Birgit Teucher; Kuanrong Li; H Bas Bueno-de-Mesquita; Daphne van der A; Amalia Mattiello; Domenico Palli; Rosario Tumino; Vittorio Krogh; Paolo Vineis; Antonia Trichopoulou; Philippos Orfanos; Dimitrios Trichopoulos; Bo Hedblad; Peter Wallström; Kim Overvad; Jytte Halkjær; Anne Tjønneland; Guy Fagherazzi; Laureen Dartois; Francesca Crowe; Kay-Tee Khaw; Nick Wareham; Lefkos Middleton; Anne M May; Petra H M Peeters; Heiner Boeing

doi:10.1371/journal.pone.0067429

Development and Validation of a Risk Score Predicting Substantial Weight Gain over 5 Years in Middle-Aged European Men and Women

Annika Steffen, Thorkild I.A. Sørensen, Sven Knüppel, Noemie Travier, María-José Sánchez, José María Huerta, J Ramón Quirós, Eva Ardanaz, Miren Dorronsoro, Birgit Teucher, Kuanrong Li, H Bas Bueno-de-Mesquita, Daphne van der A, Amalia Mattiello, Domenico Palli, Rosario Tumino, Vittorio Krogh, Paolo Vineis, Antonia Trichopoulou, Philippos OrfanosDimitrios Trichopoulos, Bo Hedblad, Peter Wallström, Kim Overvad, Jytte Halkjær, Anne Tjønneland, Guy Fagherazzi, Laureen Dartois, Francesca Crowe, Kay-Tee Khaw, Nick Wareham, Lefkos Middleton, Anne M May, Petra H M Peeters, Heiner Boeing

Department of Public Health

14 Citations (Scopus)

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Abstract

Background:Identifying individuals at high risk of excess weight gain may help targeting prevention efforts at those at risk of various metabolic diseases associated with weight gain. Our aim was to develop a risk score to identify these individuals and validate it in an external population.Methods:We used lifestyle and nutritional data from 53°758 individuals followed for a median of 5.4 years from six centers of the European Prospective Investigation into Cancer and Nutrition (EPIC) to develop a risk score to predict substantial weight gain (SWG) for the next 5 years (derivation sample). Assuming linear weight gain, SWG was defined as gaining ≥10% of baseline weight during follow-up. Proportional hazards models were used to identify significant predictors of SWG separately by EPIC center. Regression coefficients of predictors were pooled using random-effects meta-analysis. Pooled coefficients were used to assign weights to each predictor. The risk score was calculated as a linear combination of the predictors. External validity of the score was evaluated in nine other centers of the EPIC study (validation sample).Results:Our final model included age, sex, baseline weight, level of education, baseline smoking, sports activity, alcohol use, and intake of six food groups. The model's discriminatory ability measured by the area under a receiver operating characteristic curve was 0.64 (95% CI = 0.63-0.65) in the derivation sample and 0.57 (95% CI = 0.56-0.58) in the validation sample, with variation between centers. Positive and negative predictive values for the optimal cut-off value of ≥200 points were 9% and 96%, respectively.Conclusion:The present risk score confidently excluded a large proportion of individuals from being at any appreciable risk to develop SWG within the next 5 years. Future studies, however, may attempt to further refine the positive prediction of the score.

Original language	English
Article number	e67429
Journal	P L o S One
Volume	8
Issue number	7
Pages (from-to)	1-11
Number of pages	11
ISSN	1932-6203
DOIs	https://doi.org/10.1371/journal.pone.0067429
Publication status	Published - 16 Jul 2013

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Steffen, A., Sørensen, T. I. A., Knüppel, S., Travier, N., Sánchez, M-J., Huerta, J. M., Quirós, J. R., Ardanaz, E., Dorronsoro, M., Teucher, B., Li, K., Bueno-de-Mesquita, H. B., van der A, D., Mattiello, A., Palli, D., Tumino, R., Krogh, V., Vineis, P., Trichopoulou, A., ... Boeing, H. (2013). Development and Validation of a Risk Score Predicting Substantial Weight Gain over 5 Years in Middle-Aged European Men and Women. P L o S One, 8(7), 1-11. [e67429]. https://doi.org/10.1371/journal.pone.0067429

Steffen, A, Sørensen, TIA, Knüppel, S, Travier, N, Sánchez, M-J, Huerta, JM, Quirós, JR, Ardanaz, E, Dorronsoro, M, Teucher, B, Li, K, Bueno-de-Mesquita, HB, van der A, D, Mattiello, A, Palli, D, Tumino, R, Krogh, V, Vineis, P, Trichopoulou, A, Orfanos, P, Trichopoulos, D, Hedblad, B, Wallström, P, Overvad, K, Halkjær, J, Tjønneland, A, Fagherazzi, G, Dartois, L, Crowe, F, Khaw, K-T, Wareham, N, Middleton, L, May, AM, Peeters, PHM & Boeing, H 2013, 'Development and Validation of a Risk Score Predicting Substantial Weight Gain over 5 Years in Middle-Aged European Men and Women', P L o S One, vol. 8, no. 7, e67429, pp. 1-11. https://doi.org/10.1371/journal.pone.0067429

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title = "Development and Validation of a Risk Score Predicting Substantial Weight Gain over 5 Years in Middle-Aged European Men and Women",

abstract = "Background:Identifying individuals at high risk of excess weight gain may help targeting prevention efforts at those at risk of various metabolic diseases associated with weight gain. Our aim was to develop a risk score to identify these individuals and validate it in an external population.Methods:We used lifestyle and nutritional data from 53°758 individuals followed for a median of 5.4 years from six centers of the European Prospective Investigation into Cancer and Nutrition (EPIC) to develop a risk score to predict substantial weight gain (SWG) for the next 5 years (derivation sample). Assuming linear weight gain, SWG was defined as gaining ≥10% of baseline weight during follow-up. Proportional hazards models were used to identify significant predictors of SWG separately by EPIC center. Regression coefficients of predictors were pooled using random-effects meta-analysis. Pooled coefficients were used to assign weights to each predictor. The risk score was calculated as a linear combination of the predictors. External validity of the score was evaluated in nine other centers of the EPIC study (validation sample).Results:Our final model included age, sex, baseline weight, level of education, baseline smoking, sports activity, alcohol use, and intake of six food groups. The model's discriminatory ability measured by the area under a receiver operating characteristic curve was 0.64 (95% CI = 0.63-0.65) in the derivation sample and 0.57 (95% CI = 0.56-0.58) in the validation sample, with variation between centers. Positive and negative predictive values for the optimal cut-off value of ≥200 points were 9% and 96%, respectively.Conclusion:The present risk score confidently excluded a large proportion of individuals from being at any appreciable risk to develop SWG within the next 5 years. Future studies, however, may attempt to further refine the positive prediction of the score.",

author = "Annika Steffen and S{\o}rensen, {Thorkild I.A.} and Sven Kn{\"u}ppel and Noemie Travier and Mar{\'i}a-Jos{\'e} S{\'a}nchez and Huerta, {Jos{\'e} Mar{\'i}a} and Quir{\'o}s, {J Ram{\'o}n} and Eva Ardanaz and Miren Dorronsoro and Birgit Teucher and Kuanrong Li and Bueno-de-Mesquita, {H Bas} and {van der A}, Daphne and Amalia Mattiello and Domenico Palli and Rosario Tumino and Vittorio Krogh and Paolo Vineis and Antonia Trichopoulou and Philippos Orfanos and Dimitrios Trichopoulos and Bo Hedblad and Peter Wallstr{\"o}m and Kim Overvad and Jytte Halkj{\ae}r and Anne Tj{\o}nneland and Guy Fagherazzi and Laureen Dartois and Francesca Crowe and Kay-Tee Khaw and Nick Wareham and Lefkos Middleton and May, {Anne M} and Peeters, {Petra H M} and Heiner Boeing",

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T1 - Development and Validation of a Risk Score Predicting Substantial Weight Gain over 5 Years in Middle-Aged European Men and Women

AU - Steffen, Annika

AU - Sørensen, Thorkild I.A.

AU - Knüppel, Sven

AU - Travier, Noemie

AU - Sánchez, María-José

AU - Huerta, José María

AU - Quirós, J Ramón

AU - Ardanaz, Eva

AU - Dorronsoro, Miren

AU - Teucher, Birgit

AU - Li, Kuanrong

AU - Bueno-de-Mesquita, H Bas

AU - van der A, Daphne

AU - Mattiello, Amalia

AU - Palli, Domenico

AU - Tumino, Rosario

AU - Krogh, Vittorio

AU - Vineis, Paolo

AU - Trichopoulou, Antonia

AU - Orfanos, Philippos

AU - Trichopoulos, Dimitrios

AU - Hedblad, Bo

AU - Wallström, Peter

AU - Overvad, Kim

AU - Halkjær, Jytte

AU - Tjønneland, Anne

AU - Fagherazzi, Guy

AU - Dartois, Laureen

AU - Crowe, Francesca

AU - Khaw, Kay-Tee

AU - Wareham, Nick

AU - Middleton, Lefkos

AU - May, Anne M

AU - Peeters, Petra H M

AU - Boeing, Heiner

N1 - OA

PY - 2013/7/16

Y1 - 2013/7/16

N2 - Background:Identifying individuals at high risk of excess weight gain may help targeting prevention efforts at those at risk of various metabolic diseases associated with weight gain. Our aim was to develop a risk score to identify these individuals and validate it in an external population.Methods:We used lifestyle and nutritional data from 53°758 individuals followed for a median of 5.4 years from six centers of the European Prospective Investigation into Cancer and Nutrition (EPIC) to develop a risk score to predict substantial weight gain (SWG) for the next 5 years (derivation sample). Assuming linear weight gain, SWG was defined as gaining ≥10% of baseline weight during follow-up. Proportional hazards models were used to identify significant predictors of SWG separately by EPIC center. Regression coefficients of predictors were pooled using random-effects meta-analysis. Pooled coefficients were used to assign weights to each predictor. The risk score was calculated as a linear combination of the predictors. External validity of the score was evaluated in nine other centers of the EPIC study (validation sample).Results:Our final model included age, sex, baseline weight, level of education, baseline smoking, sports activity, alcohol use, and intake of six food groups. The model's discriminatory ability measured by the area under a receiver operating characteristic curve was 0.64 (95% CI = 0.63-0.65) in the derivation sample and 0.57 (95% CI = 0.56-0.58) in the validation sample, with variation between centers. Positive and negative predictive values for the optimal cut-off value of ≥200 points were 9% and 96%, respectively.Conclusion:The present risk score confidently excluded a large proportion of individuals from being at any appreciable risk to develop SWG within the next 5 years. Future studies, however, may attempt to further refine the positive prediction of the score.

AB - Background:Identifying individuals at high risk of excess weight gain may help targeting prevention efforts at those at risk of various metabolic diseases associated with weight gain. Our aim was to develop a risk score to identify these individuals and validate it in an external population.Methods:We used lifestyle and nutritional data from 53°758 individuals followed for a median of 5.4 years from six centers of the European Prospective Investigation into Cancer and Nutrition (EPIC) to develop a risk score to predict substantial weight gain (SWG) for the next 5 years (derivation sample). Assuming linear weight gain, SWG was defined as gaining ≥10% of baseline weight during follow-up. Proportional hazards models were used to identify significant predictors of SWG separately by EPIC center. Regression coefficients of predictors were pooled using random-effects meta-analysis. Pooled coefficients were used to assign weights to each predictor. The risk score was calculated as a linear combination of the predictors. External validity of the score was evaluated in nine other centers of the EPIC study (validation sample).Results:Our final model included age, sex, baseline weight, level of education, baseline smoking, sports activity, alcohol use, and intake of six food groups. The model's discriminatory ability measured by the area under a receiver operating characteristic curve was 0.64 (95% CI = 0.63-0.65) in the derivation sample and 0.57 (95% CI = 0.56-0.58) in the validation sample, with variation between centers. Positive and negative predictive values for the optimal cut-off value of ≥200 points were 9% and 96%, respectively.Conclusion:The present risk score confidently excluded a large proportion of individuals from being at any appreciable risk to develop SWG within the next 5 years. Future studies, however, may attempt to further refine the positive prediction of the score.

U2 - 10.1371/journal.pone.0067429

DO - 10.1371/journal.pone.0067429

M3 - Journal article

C2 - 23874419

SN - 1932-6203

VL - 8

SP - 1

EP - 11

JO - PLoS Computational Biology

JF - PLoS Computational Biology

IS - 7

M1 - e67429

ER -

Development and Validation of a Risk Score Predicting Substantial Weight Gain over 5 Years in Middle-Aged European Men and Women

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