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Growth Mixture Modelling for Life Course Epidemiology

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Modern Methods for Epidemiology

Abstract

Life course epidemiology is the study of how physical and social exposures occurring across the entire life course, or even inter-generationally, can impact chronic disease risk later in life (Ben-Shlomo and Kuh 2002). The life course approach to chronic disease epidemiology is not a new one, though it was overshadowed during much of the twentieth century by research on the importance of adulthood lifestyle risk factors such as smoking and diet (Kuh and Ben-Shlomo 2004). Recently, however, the life course approach to epidemiology has been given more attention by researchers, funding agencies, and policy makers (Ben-Shlomo and Kuh 2002; De Stavola et al. 2006; Kuh and Ben-Shlomo 2004; Kuh et al. 2003; Pickles et al. 2007).

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Author information

Authors and Affiliations

  1. Division of Biostatistics, Centre for Epidemiology and Biostatistics, Leeds Institute of Genetics, Health & Therapeutics, University of Leeds, Leeds, UK

    Darren L. Dahly

Authors
  1. Darren L. Dahly
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Corresponding author

Correspondence to Darren L. Dahly .

Editor information

Editors and Affiliations

  1. Leeds Institute of Genetics, University of Leeds, Division of Biostatistics, Clarendon Way, Worsley Building, Room 8.01, Level 8, Leeds, LS2 9JT, United Kingdom

    Yu-Kang Tu

  2. Leeds Institute of Genetics, University of Leeds, Division of Biostatistics, Clarendon Way, Worsley Building, Room 8.01, Level 8, Leeds, LS2 9JT, United Kingdom

    Darren C. Greenwood

Appendices

Appendix 1

13.1.1 : Latent Growth Curve Model for Mplus

! Factor loadings defining the growth curve

i1 s1 | bmi0@0 bmi2@1 bmi4* bmi6* bmi8* bmi10* bmi12* bmi14* bmi16* bmi18* bmi20* bmi22* bmi24*;

! Freely estimated factor variances, means, and covariance

i1*;

s1*;

[i1*];

[s1*];

i1 WITH s1*;

! Freely estimated error variances

bmi0*;

bmi2*;

bmi4*;

bmi6*;

bmi8*;

bmi10*;

bmi12*;

bmi14*;

bmi16*;

bmi18*;

bmi20*;

bmi22*;

bmi24*;

Appendix 2

13.2.1 : 2-Class Latent Class Growth Analysis for Mplus

Variable:

Classes = c (2); ! Increase this for more classes

Analysis:

Type = Mixture ;

STARTS = 100 20;

STITERATIONS = 20;

Model:

%OVERALL%

! Factor loadings defining the growth curve

i1 s1 | bmi0@0 bmi2@1 bmi4* bmi6* bmi8* bmi10* bmi12* bmi14* bmi16* bmi18* bmi20* bmi22* bmi24*;

! Freely estimated factor means; variances constrained as zero

i1@0;

s1@0;

[i1*];

[s1*];

! Freely estimated error variances

bmi0*;

bmi2*;

bmi4*;

bmi6*;

bmi8*;

bmi10*;

bmi12*;

bmi14*;

bmi16*;

bmi18*;

bmi20*;

bmi22*;

bmi24*;

%c#1%

[Repeat code from OVERALL model]

%c#2%

[Repeat code from OVERALL model]

! Add more class models as needed

Appendix 3

13.3.1 : 6-Class Latent Class Growth Analysis with Covariates for Mplus

Variable:

Classes = c (2);

Analysis:

Type = Mixture ;

STARTS = 100 20;

STITERATIONS = 20;

Model:

! Factor loadings defining the growth curve

i1 s1 | bmi0@0 bmi2@1 bmi4* bmi6* bmi8* bmi10* bmi12* bmi14* bmi16* bmi18* bmi20* bmi22* bmi24*;

! Freely estimated factor means; variances constrained as zero

i1@0;

s1@0;

[i1*];

[s1*];

! Freely estimated error variances

bmi0*;

bmi2*;

bmi4*;

bmi6*;

bmi8*;

bmi10*;

bmi12*;

bmi14*;

bmi16*;

bmi18*;

bmi20*;

bmi22*;

bmi24*;

! Covariates

! Multinomial logit of C on SES

c ON ses0;

! Linear regression of SES in young adulthood on SES at birth

ses258 ON ses0;

! Linear regression of systolic blood pressure on SES and waist circumference

sys258 ON waist258 ses258;

! Linear regression of waist circumference on SES

waist258 ON ses258;

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Dahly, D.L. (2012). Growth Mixture Modelling for Life Course Epidemiology. In: Tu, YK., Greenwood, D. (eds) Modern Methods for Epidemiology. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-3024-3_13

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