Simulation studies of age-specific lifetime major depression prevalence

Abstract

Background: The lifetime prevalence (LTP) of Major Depressive Disorder (MDD) is the proportion of a population having met criteria for MDD during their life up to the time of assessment. Expectation holds that LTP should increase with age, but this has not usually been observed. Instead, LTP typically increases in the teenage years and twenties, stabilizes in adulthood and then begins to decline in middle age. Proposed explanations for this pattern include: a cohort effect (increasing incidence in more recent birth cohorts), recall failure and/or differential mortality. Declining age-specific incidence may also play a role.

Methods: We used a simulation model to explore patterns of incidence, recall and mortality in relation to the observed pattern of LTP. Lifetime prevalence estimates from the 2002 Canadian Community Health Survey, Mental Health and Wellbeing (CCHS 1.2) were used for model validation and calibration.

Results: Incidence rates predicting realistic values for LTP in the 15-24 year age group (where mortality is unlikely to substantially influence prevalence) lead to excessive LTP later in life, given reasonable assumptions about mortality and recall failure. This suggests that (in the absence of cohort effects) incidence rates decline with age. Differential mortality may make a contribution to the prevalence pattern, but only in older age categories. Cohort effects can explain the observed pattern, but only if recent birth cohorts have a much higher (approximately 10-fold greater) risk and if incidence has increased with successive birth cohorts over the past 60-70 years.

Conclusions: The pattern of lifetime prevalence observed in cross-sectional epidemiologic studies seems most plausibly explained by incidence that declines with age and where some respondents fail to recall past episodes. A cohort effect is not a necessary interpretation of the observed pattern of age-specific lifetime prevalence.

Figures

Figure 1

Lifetime prevalence of major depression in the Canadian Community Health Survey 1.2, Mental Health and Wellbeing (error bars represent 95% confidence intervals).

Figure 2

Layout for animations of model simulations.

Figure 3

Simulated age-specific LTP: constant incidence, no false negatives, no effect of depression on mortality. C = 0.01, r = 0, false negative rate = 0, MR = 1, error bars represent 95% CIs.

Figure 4

Simulated age-specific LTP: declining incidence with age, no false negatives, no effect of depression on mortality. C = 0.01, r = 0.05, false negative rate = 0, MR = 1, error bars represent 95% CIs

Figure 5

Simulated age-specific LTP: declining incidence with age, 15% false negatives after 5 years, no effect of depression on mortality. C = 0.01, r = 0.05, false negative rate 15% per 5 years, no effect of depression on mortality, error bars represent 95% CIs. One set of simulated values represents the actual lifetime prevalence, the other the apparent lifetime prevalence in which false negative results are not counted in the numerator of the prevalence proportion.

Figure 6

Simulated age-specific LTP: effect of mortality with incidence that declines with age. The dark line represents a strong effect of mortality (MR = 2.0) in the absence of false negative ratings and declining incidence: C = 0.01, r = 0, false negative rate = 0. The lighter line represents a more realistic effect of mortality (MR = 1.4) in the absence of false negative ratings and declining incidence: C = 0.01, r = 0, false negative rate = 0. The error bars represent 95% CIs.

Figure 7

Simulated age-specific LTP: effect of mortality with incidence that declines with age. The dark line depicts constant incidence C = 0.01 that declines with age (r = 0.05) and there are no false negative ratings. This is the same simulation depicted in Figure 4 and is presented here for comparison to the lighter line, which represents a simulation based on the same assumptions except that MR is 1.4.

Figure 8

Simulated age-specific LTP in women: model parameters optimized to CCHS 1.2 data. C = 0.13, r = 0.08, MR = 1.2, FNR = 0.10. These parameter values derive from multiple simulations seeking to minimize the sum or squares of differences between simulated and observed age and sex-specific LTP estimates. The r parameter represents a decline in incidence with age > 15 (an age effect).

Figure 9

Simulated age-specific LTP in men: model parameters optimized to CCHS 1.2 data. C = 0.15, r = 0.03, MR = 1.7, FNR = 0.23. These parameter values derive from multiple simulations seeking to minimize the sum or squares of differences between simulated and observed age and sex-specific LTP estimates. The r parameter represents a decline in incidence with age > 15 (an age effect). The simulation includes an adjustment that places the LTP at 5% at the low end of the age range (age 15).

Figure 10

Simulated and observed LTP in men and women and estimated actual LTP for men and women, with model constrained to a single value for the false negative rate. The false negative rate is constrained to a single value, which was optimized at 0.14 per five year period, or approximately 3% per year.

Figure 11

Contour plot depicting model fit at various combinations of the false negative rate and r parameter. The vertical axis is the sum of squared difference between observed age-specific LTP and simulated age-specific LTP. Lower elevation on the contour plot indicates a better concordance between observed and simulated age-specific LTP. The blue region at the lowest contour tracks diagonally across the plane at the base, indicating that higher r values provide a better fit when the false negative rate is low whereas lower r values provide a better fit when the false negative rate is higher.

Figure 12

Simulated age-specific LTP in women: model parameters optimized to CCHS 1.2 data under the assumption that incidence does not decline with age. C = 0.14, r = 0.08, MR = 1.7, FNR = 0.33. These parameter values derive from multiple simulations seeking to minimize the sum or squares of differences between simulated and observed age and sex-specific LTP estimates.

Figure 13

Simulated age-specific LTP in men: model parameters optimized to CCHS 1.2 data under the assumption that incidence does not decline with age. C = 0.14, r = 0.03, MR = 1.5, FNR = 0.40. These parameter values derive from multiple simulations seeking to minimize the sum or squares of differences between simulated and observed age and sex-specific LTP estimates. The r parameter represents a decline in incidence with age > 15 (an age effect).

Figure 14

Simulated age- and sex-specific LTP, by birth cohort in women. The light lines represent the projected age-specific LTP pattern experienced by the birth cohorts assuming no change in incidence with age (r = 0) and no false negative ratings. The MR is set at 1.4 in these simulations.

Figure 15

Simulated age- and sex-specific LTP, by birth cohort in men. The light lines represent the projected age-specific LTP pattern experienced by the birth cohorts assuming no change in incidence with age (r = 0) and no false negative ratings. The MR is set at 1.4 in these simulations.