What is lifetime prevalence

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Changes in the effects of predictors across cohort were evaluated by including interactions between predictors and cohort. Standard errors of prevalence estimates and survival coefficients were estimated using the Taylor series linearization method 14 implemented in the SUDAAN software system. Standard errors of lifetime risk estimates were estimated using the jackknife repeated replication method 16 implemented in a SAS macro.

The most prevalent lifetime disorders Table 2 were major depressive disorder Anxiety disorders were the most prevalent class of disorders The lifetime prevalence of any disorder was Prevalence estimates varied significantly with age for all but a handful of disorders.

A monotonic increase in prevalence was generally found from the youngest years to a higher for the most part, years age group and then a decline in the older age group s. The most dramatic differences of this sort were for drug abuse and drug dependence, posttraumatic stress disorder, and bipolar I and II disorders.

Prevalence differences were much less marked among the other three age groups. The distributions of cumulative lifetime risk estimates were standardized and examined for fixed percentiles Table 3. Two patterns emerged. First, the median age of onset ie, 50th percentile on the age-of-onset distribution was much earlier for anxiety disorders age 11 years and impulse-control disorders age 11 years than for substance use disorders age 20 years and mood disorders age 30 years.

Second, age of onset was concentrated in a very narrow age range for most disorders, with interquartile ranges IQRs ie, the number of years between the 25th and 75th percentiles of the age-of-onset distributions of only 8 years age years for impulse-control disorders, 9 years age years for substance use disorders, and 15 years age years for anxiety disorders compared with 25 years age years for mood disorders.

Most disorder-specific age-of-onset distributions shared important features with other disorders in their class. In particular, the median age of onset was earlier for each impulse-control disorder age years than for any substance age years or mood age years disorder, while the IQR was consistently narrower for each of the impulse-control years and substance use years disorders than for any mood disorder years. The age-of-onset distributions of anxiety disorders were more diverse, with specific phobia and separation anxiety disorder having very early median ages of onset age 7 years and very narrow IQRs years , social phobia having a later median age of onset age 13 years and a narrow IQR range 7 years , and other anxiety disorders having much later median ages of onset age years and much wider IQRs years.

Predictably, disorders with the largest increases between prevalence and projected risk were those with late age-of-onset distributions: major depressive disorder, generalized anxiety disorder, and posttraumatic stress disorder.

Consistent with the prevalence data, projected risk was highest for anxiety disorders Substance use disorders had the lowest projected risk The individual disorders with the highest projected risk were identical to those with the highest prevalence.

This can be seen by noting that the overall projected lifetime risk in the total sample was only 4. Dummy variables defining age groups 18 through 29, 30 through 44, 45 through 59, and 60 years or older corresponding roughly to cohorts born in the years or later, , , and earlier than were used to predict lifetime disorders using discrete-time survival analysis.

The odds ratios ORs were statistically significant in the vast majority of comparisons, with a consistent positive association between recency of cohort and OR of onset Table 4. The largest cohort effects were associated with drug use disorders and the smallest with phobias and childhood-onset impulse-control disorders. The cohort model was elaborated to evaluate whether intercohort differences decreased significantly with increasing age, a pattern that might be expected either if lifetime risk was actually constant across cohorts but appeared to vary with cohort because onsets occurred earlier in more recent cohorts than in earlier cohorts due to either secular changes in environmental triggers or age-related differences in age-of-onset recall accuracy or if differential mortality had an increasingly severe effect on sample selection bias with increasing age.

Differences were examined separately for first onsets in the age ranges 1 through 12, 13 through 19, 20 through 29, 30 through 39, 40 through 49, and 50 through 59 years, the last of these age intervals being the upper end of the age distribution of the second-oldest cohort quartile, making it impossible to study intercohort differences beyond this age. No evidence of decreasing cohort effects with increasing age was found for anxiety or mood disorders Table 5.

In contrast, dramatic differences emerged for substance use disorders, with much higher cohort effects in the teens and 20s than in either childhood or the 30s through 50s. A number of sociodemographic variables were significantly related to lifetime risk of NCS-R disorders in survival analyses that controlled for cohort Table 6.

Women had a significantly higher risk than men of anxiety and mood disorders. Men had a significantly higher risk than women of impulse-control and substance use disorders.

Non-Hispanic blacks and Hispanics had a significantly lower risk than non-Hispanic whites of anxiety, mood, and substance use disorders the latter only among non-Hispanic blacks. Low education was associated with a high risk of substance use disorders. Marital disruption was associated with 3 of the 4 classes of disorder, the exception being impulse-control disorder. To determine whether increasing prevalence in more recent cohorts was concentrated in certain population segments, we also examined whether sociodemographic correlates varied by cohort.

Although at least one significant interaction was found for each sociodemographic predictor, the pattern was not consistent results available on request from the authors.

The most notable results were as follows: Sex differences in anxiety, mood, and impulse-control disorders did not differ across cohorts, but women were more similar to men in substance use disorders in recent cohorts. The significant inverse associations with substance use disorders of education and being married existed only in recent cohorts. The results reported herein are limited by four possible biases, all of which make the prevalence and risk estimates conservative.

First, people with a history of mental illness might have been less likely than others to participate in the survey either because of sample frame exclusions eg, excluding homeless people from the sampling frame , differential mortality, or greater reluctance to participate. There is evidence that bias of the latter sort reluctance to participate exists in psychiatric epidemiological surveys, 17 although no evidence of such bias was found in a nonrespondent survey carried out in conjunction with the NCS-R.

Second, lifetime prevalence was likely to be underreported in the sample because of the well-known bias against reporting embarrassing behaviors. Experimental studies to evaluate the effects of strategies designed to decrease embarrassment and to increase accurate reporting have consistently shown significant increases in reports of mental illness.

Third, the method used to estimate lifetime risk was based on the assumption of constant conditional risk of first onset in a given year of life among people who differ in age at interview. This assumption is almost certainly incorrect in light of evidence for significant intercohort differences in lifetime prevalence.

Because the estimated prevalence was higher in more recent cohorts, lifetime risk in younger cohorts will be underestimated in models based on the assumption of constant intercohort conditional risk.

Fourth, age at onset can be recalled incorrectly, possibly as a function of age at interview and in conjunction with age-related failure to recall lifetime disorders. This kind of age-related age-at-onset telescoping in conjunction with age-related failure to report past disorders can create the false appearance of a cohort effect.

Based on these considerations of possible bias, the NCS-R estimates of lifetime prevalence and projected risk are likely to be conservative. The estimates of anxiety, mood, and substance use disorders are broadly consistent with those found in previous community surveys in the United States 3 , 23 and elsewhere in the world 24 , 25 : 1 A high proportion of the population met the criteria for one or more of these disorders at some time in their life.

The main inconsistency with previous results is that the estimated prevalence of substance use disorders was considerably lower in the NCS-R than in the NCS. High prevalence estimates in previous psychiatric epidemiological surveys have been a source of two concerns to mental health policy analysts. The first is that the estimates are so high as to be scientifically implausible. However, it is noteworthy that preliminary analyses of the month NCS-R data show that even those month WMH-CIDI disorders that were classified as mild were associated with levels of impairment equivalent to those caused by clinically significant chronic physical disorders.

Low education level was associated only with substance use disorders. Younger ages were significant predictors for all disorder classes cohort effects. The associations with gender and education were also examined by age, to test if there were variations in predicting psychiatric disorders across cohorts results available upon request.

Gender differences in anxiety and mood disorders did not differ across cohorts. For impulse-control disorders, a higher risk was observed among men only among the oldest cohort; there was also significant interaction between education and age at interview, with stronger negative associations in more recent cohorts.

This study showed that mental disorders are common in the SPMA, with These estimates are amongst the highest reported in the world. Higher levels of psychiatric morbidity are associated with poor living conditions in large urban conglomerates, 20 as social groups living in adverse situations under chronic stress would be more likely to present mental disorders.

Social exclusion, amplified by poor access to education, was reported to be an important risk factor for mental disorders. Moreover, social tension and urban violence may arise from inequity, due to poverty and wealth extremes being sharing space within the city. Aside from the fact that fewer psychiatric disorders were assessed, differences could also be explained by the higher socioeconomic status of the population studied, with better housing and living conditions, and easier access to health services.

However similar the methodological procedures might have been, the only two countries that used all WMH-CIDI clinical modules and, thus, assessed a wider range of mental disorders were the U. For instance, New Zealand did not assess OCD, separation anxiety either adult or childhood and none of the impulse-control disorders, and France, as well as other Western European countries, did not assess OCD, separation anxiety, drug abuse or dependence, bipolar disorder, dysthymia and intermittent explosive disorder.

Indeed, there is a wide variation in the estimated lifetime prevalence of mental disorders in the WMH surveys, possibly more than what could be explained only by such differential assessments.

Finally, the lifetime prevalence estimate of OCD in our study was high 6. Since the CIDI is based on the assessment of symptoms that compose diagnostic criteria for psychiatric disorders, it may have detected mild cases with no clinical relevance, contributing to the high prevalence rates. Nevertheless, widely consistent with earlier prevalence studies and most WHO-WMH surveys, anxiety disorders are the most frequent class and mood disorders are also common, with major depressive disorder, phobias and alcohol abuse being the most prevalent individual disorders.

The gender distribution observed in this study also replicates the general findings, with women having more anxiety and mood disorders and men having higher rates of substance use disorder. However, there were no gender differences for impulse-control disorders, reported to be higher among men in most previous studies Colombia, Mexico, NCS-R, France, Germany, Italy, China ; the only exception being conduct disorders, which were 3 times more prevalent among men.

Lifetime comorbidity was also quite common, with the sum of prevalence rates for all disorders almost doubling the prevalence for any disorder Within class, co-occurrence was higher among anxiety disorders Finally, it is worth noting that non-affective psychoses were not assessed in this survey, which may not be highly prevalent, but are, nevertheless, usually severe, greatly impairing and associated with enormous social and family burden.

Although questions regarding psychotic-like experiences were asked, these data were not used herein. Standardized AOO distributions in our study showed strong consistency with most WMH surveys, with impulse-control disorders having the earliest AOO distribution, especially attention-deficit and oppositional defiant disorders.

Anxiety disorders also followed the same pattern of other countries, falling into two distinct sets, with phobias and separation anxiety having early AOO, while GAD, panic disorder and PTSD having a much later AOO, similar to those in mood disorders. For substance use disorders, it is also consistent with the international pattern, with earlier AOO for drug abuse and dependence and later for alcohol dependence.

Although the WHO-WMH version of the CIDI included questions encouraging precision in answering AOO of symptoms and syndromes, the possibility of recall bias has to be considered, especially as a function of age at interview, with older respondents tending to have more imprecise recall of onset of long-time past events. As co-morbidity is common, one may argue that the bulk of disorders occur within the first decades of life and that late-onset disorders largely occur as secondary comorbid conditions.

It is worthwhile to emphasize that the results reported herein corroborate the increased burden associated with mental disorders, as they occur early in life, have a long course, are associated with disability and often present with other mental comorbid disorders, 38,39 distinct from chronic physical disorders, which mostly occur later in life. These projections were also calculated for other WMH survey countries 35 and are the highest so far, closely followed by the U.

The highest proportional increase was observed in countries exposed to sectarian violence Israel The PLR was estimated on the assumptions of constant conditional risk of first onset of a disorder in a given year of life, ascertained among people with different ages at interview. Since there were cohort differences in lifetime prevalence, the PLR for younger cohorts is likely to be underestimated, as it was based on the assumption of constant inter-cohort conditional risk.

Since the sum of individual disorder projected prevalences within disorder classes is much higher than the overall PLR estimate, it also corroborates that late-onset disorders are likely to be onsets of secondary comorbid conditions. These considerations, coupled with the magnitude of such projections point out to the important role of early treatment of early-onset disorders, in order to prevent later comorbidity and more severely impairing conditions, as well as greater individual and societal burden which has tremendous public health implications.

The same approach was used in estimating the cohort effects in the WMH surveys, using discrete-time survival analysis to predict onset of disorders across age groups, similar to that of this study. Information available from 17 WHO-WMH participating countries showed that younger cohorts presented higher rates of anxiety disorders in all but three countries Italy, Ukraine and China , of mood disorders in all countries but South Africa, and of substance use disorders in all but three countries South Africa, Italy and Japan , whereas in most countries there were no observed cohort effects for impulse-control disorders except for Mexico.

Similar results were obtained in our study, and cohort differences remained significant after controlling for time of disorder onset in the lifespan and age at interview. We did not test, however, for impulse-control disorders, as the numbers were too small and the age of onset range too narrow.

Although only prospective studies can directly and accurately appraise cohort effects, it can be persuasively argued that we were successful in obtaining a fine approximation. Our findings are similar to most previous population-based reports regarding gender and age predicting mental disorders, as discussed above. When gender and age interactions were explored, new features were seen only for substance use disorder, with women rates of abuse and dependence increasing in more recent cohorts, approximating male patterns.

Similar behavior was observed in impulse-control disorders, where gender differences were only seen in older cohorts. It is worth noting that these analyses were performed only taking into account disorder classes i. These findings are consistent with international reports. It is possible that education favors better reporting on psychiatric symptoms.

Respondents with low education might be less capable of understanding long and complex research questioning, while underestimating the risk posed by the symptoms. Other socioeconomic correlates, such as personal and family income and occupational history, will be further examined.

Finally, the results reported in this paper should be interpreted taking into account several limitations. First, there is no clinical gold-standard assessment to check the consistency of the diagnoses produced by the WMH-CIDI on the disorders assessed in this study. Recall bias may also impair the accuracy of retrospective information, especially when the occurrence is likely to have happened long before the interview.

Although the WMH-CIDI was rebuilt taking into consideration a series of strategies to minimize recall bias and information bias while approaching sensitive issues or preceding information, 2 it is unlikely that they were completely ruled out. Selection bias leading to underestimating the true general population prevalence rates also likely occurred, as people with mental illness are less likely to be truly represented in the adopted sampling frame excluding the homeless and individuals living in institutions , more likely to be exclude from selection as ineligible to participate due to impeding physical, mental or cognitive conditions or may present differential mortality.

Moreover, people with mental problems are known to be more reluctant to participate in epidemiological surveys of this sort. All these plausible biases were, therefore, likely to have yielded conservative rates of psychiatric morbidity, according to the adopted system of classification. It is the first epidemiological study providing population-based information on several disorders in Brazil, such as of post-traumatic stress disorder, obsessive-compulsive disorder, separation anxiety disorder, dysthymia, as well as on all impulse-control disorders oppositional-defiant, conduct, attention-deficit and intermittent explosive disorders.