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Depressive symptoms and the onset of menarche

Depressive symptoms and the onset of menarche. What is ALSPAC?. “Avon Longitudinal Study of Parents and Children” AKA Children of the Nineties Cohort study of ~14,000 children and their parents, based in south-west England

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Depressive symptoms and the onset of menarche

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  1. Depressive symptoms and the onset of menarche

  2. What is ALSPAC? • “Avon Longitudinal Study of Parents and Children” • AKA Children of the Nineties • Cohort study of ~14,000 children and their parents, based in south-west England • Eligibility criteria: Mothers had to be resident in Avon and have an expected date of delivery between April 1st 1991 and December 31st 1992 • Population based prospective cohort study

  3. Where’s Avon to?

  4. What data does ALSPAC have? • Self completion questionnaires • Mothers, Partners, Children, Teachers • Hands on assessments • 10% sample tested regularly since birth • Yearly clinics for all since age 7 • Data from external sources • SATS from LEA, Child Health database • Biological samples • DNA / cell lines

  5. Data for current models - outcome • Depressive symptoms • Short form of Mood and Feelings Questionnaire Angold, A., Costello, E. J., Messer, S. C., Pickles, A., Winder, F., & Silver, D. (1995). Development of a short questionnaire for use in epidemiological studies of depression in children and adolescents. International Journal of Methods in Psychiatric Research, 5, 237–249. Costello, E. J., & Angold, A. (1988). Scales to assess child and adolescent depression: Checklists, screens and nets. Journal of the American Academy of Child and Adolescent Psychiatry, 27, 726–737. • Assessed in clinic – self report • 3 time points: 10y7m, 12y10m, 13y10m

  6. Depressive symptoms – Short MFQ • I felt miserable or unhappy (True/Sometimes/Not at all) • I didn't enjoy anything at all • I felt so tired I just sat around and did nothing • I was very restless • I felt I was no good any more • I cried a lot • I found it hard to think properly or concentrate • I hated myself • I was a bad person • I felt lonely • I thought nobody really loved me • I thought I could never been as good as other kids • I did everything wrong

  7. Depressive symptoms – Short MFQ • I felt miserable or unhappy (True/Sometimes/Not at all) • I didn't enjoy anything at all • I felt so tired I just sat around and did nothing • I was very restless • I felt I was no good any more • I cried a lot • I found it hard to think properly or concentrate • I hated myself • I was a bad person • I felt lonely • I thought nobody really loved me • I thought I could never been as good as other kids • I did everything wrong

  8. Restless: non-response more common

  9. Restless: non-monotonic change

  10. Subscales: odd / even Measured using short MFQ (13 items) • I felt miserable or unhappy • I didn't enjoy anything at all • I felt so tired I just sat around and did nothing • I was very restless • I felt I was no good any more • I cried a lot • I found it hard to think properly or concentrate • I hated myself • I was a bad person • I felt lonely • I thought nobody really loved me • I thought I could never been as good as other kids • I did everything wrong

  11. Depression scales – basic stats

  12. Depression scales – basic stats

  13. Data for current models - exposure • Age at onset of menarche • Assessed repeatedly by questionnaire • Respondent = mother and/or daughter • 3 groups: • Before 11½ (14.7%) • 11½ - 13½ (65.5%) • After 13½ (19.8%)

  14. Study sample • 2063 with complete data • All are girls (obviously!) • Intention is to repeat models with boys using alternative measures of pubertal onset

  15. [1] Simple cross-sectional models

  16. [1] Standardized results ---------------------------------------------------------------- | Coef. SE t P>|t| [95% CI] ---------------+------------------------------------------------ t1 (10y7m) | Early menarche | .042 .064 0.67 0.505 -.082 .167 Late menarche | .027 .057 0.47 0.637 -.084 .137 ---------------------------------------------------------------- ---------------------------------------------------------------- t2 (12y10m) | Early menarche | .220 .063 3.48 0.001 .096 .344 Late menarche | .005 .056 0.08 0.936 -.106 .115 ---------------------------------------------------------------- ---------------------------------------------------------------- t3 (13y10m) | Early menarche | .191 .063 3.02 0.003 .067 .315 Late menarche | -.170 .056 -3.03 0.002 -.281 -.060 ----------------------------------------------------------------

  17. However… • Scales are skewed • Data is longitudinal • Heterogeneity in patterns of change • Scale properties may not be invariant across time

  18. [2] Measurement Invariance model

  19. [2] Measurement Invariance model - on items Optional Item-1 Item-12 Item-1 Item-12 Item-1 Item-12 …… …… …… F_t1 F_t2 F_t3 Menarche onset

  20. [2] Measurement Invariance model CFI 0.952 TLI 0.975 Number of Free Parameters 57 RMSEA (Root Mean Square Error Of Approximation) 0.043 WRMR (Weighted Root Mean Square Residual) 1.892 Decent fit for fully invariant model

  21. [2] Measurement Invariance results Meas Inv model Estimate (SE), P-Value Estimate (SE), P-Value F_t1 ON EARLYMEN 0.044 (0.071), p = 0.534 0.042 (0.064), p = 0.505 LATEMEN 0.025 (0.064), p = 0.700 0.027 (0.057), p = 0.637 F_t2 ON EARLYMEN 0.239 (0.073), p = 0.001 0.220 (0.063), p = 0.001 LATEMEN 0.004 (0.065), p = 0.956 0.005 (0.056), p = 0.936 F_t3 ON EARLYMEN 0.206 (0.073), p = 0.005 0.191 (0.063), p = 0.003 LATEMEN -0.198 (0.065), p = 0.002 -0.170 (0.056), p = 0.002

  22. c.f. with equivalent simple C/S results Meas Inv model Simple C/S Estimate (SE), P-Value Estimate (SE), P-Value t1/F_t1 ON EARLYMEN 0.044 (0.071), p = 0.534 0.042 (0.064), p = 0.505 LATEMEN 0.025 (0.064), p = 0.700 0.027 (0.057), p = 0.637 t2/F_t2 ON EARLYMEN 0.239 (0.073), p = 0.001 0.220 (0.063), p = 0.001 LATEMEN 0.004 (0.065), p = 0.956 0.005 (0.056), p = 0.936 t3/F_t3 ON EARLYMEN 0.206 (0.073), p = 0.005 0.191 (0.063), p = 0.003 LATEMEN -0.198 (0.065), p = 0.002 -0.170 (0.056), p = 0.002

  23. [1] C/S [2] Meas Invariant

  24. Considerable variability between subjects

  25. [3] 2nd Order Growth Model

  26. F_s2 [3] 2nd Order Growth Model – piecewise Optional t1_odd t1_even t2_odd t2_even t3_odd t3_even F_t1 F_t2 F_t3 F_i F_s1

  27. F_s2 [3] 2nd Order Growth Model – piecewise t1_odd t1_even t2_odd t2_even t3_odd t3_even F_t1 F_t2 F_t3 Zero residual variance F_i F_s1

  28. [3] Growth model fit CFI 0.972 TLI 0.970 Number of Free Parameters 13 Akaike (AIC) 46763.214 Bayesian (BIC) 46836.429 Sample-Size Adjusted BIC 46795.126 RMSEA (Root Mean Square Error Of Approximation) Estimate 0.077 90 Percent C.I. 0.068 0.088 Probability RMSEA <= .05 0.000 SRMR (Standardized Root Mean Square Residual) Value 0.037

  29. [3] Growth model parameters Two-Tailed Estimate S.E. Est./S.E. P-Value Means INTCPT 2.370 0.045 52.119 0.000 SLOPE1 0.112 0.021 5.435 0.000 SLOPE2 0.686 0.050 13.660 0.000 Variances INTCPT 3.382 0.144 23.462 0.000 SLOPE1 0.653 0.029 22.313 0.000 SLOPE2 4.053 0.170 23.864 0.000 INTCPT WITH SLOPE1 0.985 0.052 19.072 0.000 SLOPE2 -0.946 0.105 -9.003 0.000 SLOPE1 WITH SLOPE2 -0.324 0.049 -6.678 0.000

  30. [3] Growth model - add menarche INTCPT ON EARLYMEN 0.061 (0.071), p = 0.386 LATEMEN 0.037 (0.063), p = 0.559 INTCPT* ON EARLYMEN 0.237 (0.068), p = 0.001 LATEMEN -0.003 (0.061), p = 0.959 INTCPT** ON EARLYMEN 0.210 (0.066), p = 0.002 LATEMEN -0.185 (0.059), p = 0.002 SLOPE1 ON EARLYMEN 0.189 (0.073), p = 0.010 LATEMEN -0.033 (0.065), p = 0.606 SLOPE2 ON EARLYMEN 0.029 (0.071), p = 0.683 LATEMEN -0.214 (0.063), p = 0.001

  31. [3] Growth model - add menarche INTCPT ON EARLYMEN 0.061 (0.071), p = 0.386 LATEMEN 0.037 (0.063), p = 0.559 INTCPT* ON EARLYMEN 0.237 (0.068), p = 0.001 LATEMEN -0.003 (0.061), p = 0.959 INTCPT** ON EARLYMEN 0.210 (0.066), p = 0.002 LATEMEN -0.185 (0.059), p = 0.002 SLOPE1 ON EARLYMEN 0.189 (0.073), p = 0.010 LATEMEN -0.033 (0.065), p = 0.606 SLOPE2 ON EARLYMEN 0.029 (0.071), p = 0.683 LATEMEN -0.214 (0.063), p = 0.001

  32. Compare models so far

  33. Measurement Invariance model - alternative Item-1 Item-12 Item-1 Item-12 Item-1 Item-12 …… …… …… F_t1 F_t2 F_t3 Menarche onset

  34. Compare models so far

  35. Compare models so far

  36. Effect of censoring on 1st order factors Uncensored Censored t1 ?? t2 ?? t3 ??

  37. [4] Growth model with mixture

  38. [4] Growth model with mixture %overall% <. . .> c#1 on earlymen latemen; %c#1% slope1; [slope1]; slope2; [slope2]; intcpt; [intcpt]; intcpt on earlymen latemen; slope1 slope2 on earlymen latemen; intcpt with slope1 slope2; slope1 with slope2; %c#2% slope1@0; [slope1@0]; slope2@0; [slope2@0]; intcpt; [intcpt]; intcpt on earlymen latemen; intcpt with slope1@0 slope2@0; slope1 with slope2@0;

  39. [4] Growth model with mixture %overall% <. . .> c#1 on earlymen latemen; %c#1% slope1; [slope1]; slope2; [slope2]; intcpt; [intcpt]; intcpt on earlymen latemen; slope1 slope2 on earlymen latemen; intcpt with slope1 slope2; slope1 with slope2; %c#2% slope1@0; [slope1@0]; slope2@0; [slope2@0]; intcpt; [intcpt]; intcpt on earlymen latemen; intcpt with slope1@0 slope2@0; slope1 with slope2@0; No change in symptoms Change is permitted

  40. [4] Two class results LATENT CLASSES BASED ON THE ESTIMATED MODEL c1 1074.91 52.1% c2 988.09 47.9% BASED ON MODAL CLASS c1 1033 50.1% c2 1030 49.9% Average Latent Class Probabilities for Modal Class (Row) by Latent Class (Column) 1 2 1 0.958 0.042 2 0.083 0.917 Entropy 0.774

  41. [4] Two class results

  42. [4] Two class results Class 1 INTCPT ON EARLYMEN -0.002 (0.092), p=0.980 LATEMEN 0.130 (0.091), p=0.154 SLOPE1 ON EARLYMEN 0.159 (0.095), p=0.094 LATEMEN -0.061 (0.081), p=0.448 SLOPE2 ON EARLYMEN 0.003 (0.096), p=0.972 LATEMEN -0.213 (0.075), p=0.004 C#1 ON EARLYMEN 1.363 [1.016, 1.828], p = 0.039 LATEMEN 0.863 [0.619, 1.112], p = 0.254 Class 2 INTCPT ON EARLYMEN 0.136 (0.160), p=0.396 LATEMEN -0.105 (0.119), p=0.377

  43. Has that really helped with the skewness? Manifest measures within class:

  44. Has that really helped with the skewness? 1st level factors within class:

  45. What next? • Semi-continuous models • Zero-inflated models • ideal for instance where a score of zero is substantively different to score of 1+ • Split measures in binary (zero/non-zero) and cts (e.g. log of non-zero scores) • Prevalence of non-zero is 60-70% so what does such an onset mean • Limited scope for modelling of 3 binaries, i.e. i | bin_fd@0 bin_ff@2.25 bin_fg@3.25;

  46. Summary / conclusions • We have 3 skewed measures of MFQ and wish to assess the extend to which early menarche leads to an earlier and/or greater onset in depressive symptoms • The models considered thus far are in good agreement and have not altered the conclusions made on the initial figure • Inclined to favour the invariance model based on items – only model which appears to have successful dealt with skewness • Thoughts gratefully received

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