Person:

Kessler, Ronald

Background: The question of whether neighborhood environment contributes directly to the development of obesity and diabetes remains unresolved. The study reported on here uses data from a social experiment to assess the association of randomly assigned variation in neighborhood conditions with obesity and diabetes. Methods: From 1994 through 1998, the Department of Housing and Urban Development (HUD) randomly assigned 4498 women with children living in public housing in high-poverty urban census tracts (in which ≥40% of residents had incomes below the federal poverty threshold) to one of three groups: 1788 were assigned to receive housing vouchers, which were redeemable only if they moved to a low-poverty census tract (where <10% of residents were poor), and counseling on moving; 1312 were assigned to receive unrestricted, traditional vouchers, with no special counseling on moving; and 1398 were assigned to a control group that was offered neither of these opportunities. From 2008 through 2010, as part of a long-term follow-up survey, we measured data indicating health outcomes, including height, weight, and level of glycated hemoglobin (HbA(_{1c})).

Background: World population growth is projected to be concentrated in megacities, with increases in social inequality and urbanization-associated stress. São Paulo Metropolitan Area (SPMA) provides a forewarning of the burden of mental disorders in urban settings in developing world. The aim of this study is to estimate prevalence, severity, and treatment of recently active DSM-IV mental disorders. We examined socio-demographic correlates, aspects of urban living such as internal migration, exposure to violence, and neighborhood-level social deprivation with 12-month mental disorders. Methods and Results: A representative cross-sectional household sample of 5,037 adults was interviewed face-to-face using the WHO Composite International Diagnostic Interview (CIDI), to generate diagnoses of DSM-IV mental disorders within 12 months of interview, disorder severity, and treatment. Administrative data on neighborhood social deprivation were gathered. Multiple logistic regression was used to evaluate individual and contextual correlates of disorders, severity, and treatment. Around thirty percent of respondents reported a 12-month disorder, with an even distribution across severity levels. Anxiety disorders were the most common disorders (affecting 19.9%), followed by mood (11%), impulse-control (4.3%), and substance use (3.6%) disorders. Exposure to crime was associated with all four types of disorder. Migrants had low prevalence of all four types compared to stable residents. High urbanicity was associated with impulse-control disorders and high social deprivation with substance use disorders. Vulnerable subgroups were observed: women and migrant men living in most deprived areas. Only one-third of serious cases had received treatment in the previous year. Discussion: Adults living in São Paulo megacity had prevalence of mental disorders at greater levels than similar surveys conducted in other areas of the world. Integration of mental health promotion and care into the rapidly expanding Brazilian primary health system should be strengthened. This strategy might become a model for poorly resourced and highly populated developing countries.

Background: Motor vehicle collisions (MVCs) are a substantial contributor to the global burden of disease and lead to subsequent post-traumatic stress disorder (PTSD). However, the relevant literature originates in only a few countries, and much remains unknown about MVC-related PTSD prevalence and predictors. Methods: Data come from the World Mental Health Survey Initiative, a coordinated series of community epidemiological surveys of mental disorders throughout the world. The subset of 13 surveys (5 in high income countries, 8 in middle or low income countries) with respondents reporting PTSD after life-threatening MVCs are considered here. Six classes of predictors were assessed: socio-demographics, characteristics of the MVC, childhood family adversities, MVCs, other traumatic experiences, and respondent history of prior mental disorders. Logistic regression was used to examine predictors of PTSD. Mental disorders were assessed with the fully-structured Composite International Diagnostic Interview using DSM-IV criteria. Results: Prevalence of PTSD associated with MVCs perceived to be life-threatening was 2.5 % overall and did not vary significantly across countries. PTSD was significantly associated with low respondent education, someone dying in the MVC, the respondent or someone else being seriously injured, childhood family adversities, prior MVCs (but not other traumatic experiences), and number of prior anxiety disorders. The final model was significantly predictive of PTSD, with 32 % of all PTSD occurring among the 5 % of respondents classified by the model as having highest PTSD risk. Conclusion: Although PTSD is a relatively rare outcome of life-threatening MVCs, a substantial minority of PTSD cases occur among the relatively small proportion of people with highest predicted risk. This raises the question whether MVC-related PTSD could be reduced with preventive interventions targeted to high-risk survivors using models based on predictors assessed in the immediate aftermath of the MVCs. Electronic supplementary material The online version of this article (doi:10.1186/s12888-016-0957-8) contains supplementary material, which is available to authorized users.

Objective: To assess the prevalence, symptom severity, functional impairment, and treatment of major depressive episode (MDE) in the Iraqi general population. Methods: The Iraq Mental Health Survey is a nationally representative face-to-face survey of 4,332 non-institutionalized adults aged 18+ interviewed in 2006–2007 as part of the WHO World Mental Health Surveys. Prevalence and correlates of DSM-IV MDE were determined with the WHO Composite International Diagnostic Interview (CIDI). Findings: Lifetime and 12-month prevalence of MDE were 7.4% and 4.0%, respectively. Close to half (46%) of the 12-month MDE cases were severe/very severe. MDE was more common among women and those previously married. Median age of onset was 25.2. Only one-seventh of 12-month MDE cases received treatment despite being associated with very substantial role impairment (on average 70 days out of role in the past year). Conclusions: MDE is a commonly occurring disorder in the Iraqi general population and is associated with considerable disability and low treatment. Efforts are needed to decrease the barriers to treatment and to educate general medical providers in Iraq about the recognition and treatment of depression.

Heterogeneity of major depressive disorder (MDD) illness course complicates clinical decision-making. While efforts to use symptom profiles or biomarkers to develop clinically useful prognostic subtypes have had limited success, a recent report showed that machine learning (ML) models developed from self-reports about incident episode characteristics and comorbidities among respondents with lifetime MDD in the World Health Organization World Mental Health (WMH) Surveys predicted MDD persistence, chronicity, and severity with good accuracy. We report results of model validation in an independent prospective national household sample of 1,056 respondents with lifetime MDD at baseline. The WMH ML models were applied to these baseline data to generate predicted outcome scores that were compared to observed scores assessed 10–12 years after baseline. ML model prediction accuracy was also compared to that of conventional logistic regression models. Area under the receiver operating characteristic curve (AUC) based on ML (.63 for high chronicity and .71–.76 for the other prospective outcomes) was consistently higher than for the logistic models (.62–.70) despite the latter models including more predictors. 34.6–38.1% of respondents with subsequent high persistence-chronicity and 40.8–55.8% with the severity indicators were in the top 20% of the baseline ML predicted risk distribution, while only 0.9% of respondents with subsequent hospitalizations and 1.5% with suicide attempts were in the lowest 20% of the ML predicted risk distribution. These results confirm that clinically useful MDD risk stratification models can be generated from baseline patient self-reports and that ML methods improve on conventional methods in developing such models.

Background: Although a number of risk factors are known to predict mortality within the first years after myocardial infarction, little is known about interactions between risk factors, whereas these could contribute to accurate differentiation of patients with higher and lower risk for mortality. This study explored the effect of interactions of risk factors on all-cause mortality in patients with myocardial infarction based on individual patient data meta-analysis. Methods: Prospective data for 10,512 patients hospitalized for myocardial infarction were derived from 16 observational studies (MINDMAPS). Baseline measures included a broad set of risk factors for mortality such as age, sex, heart failure, diabetes, depression, and smoking. All two-way and three-way interactions of these risk factors were included in Lasso regression analyses to predict time-to-event related all-cause mortality. The effect of selected interactions was investigated with multilevel Cox regression models. Results: Lasso regression selected five two-way interactions, of which four included sex. The addition of these interactions to multilevel Cox models suggested differential risk patterns for males and females. Younger women (age <50) had a higher risk for all-cause mortality than men in the same age group (HR 0.7 vs. 0.4), while men had a higher risk than women if they had depression (HR 1.4 vs. 1.1) or a low left ventricular ejection fraction (HR 1.7 vs. 1.3). Predictive accuracy of the Cox model was better for men than for women (area under the curves: 0.770 vs. 0.754). Conclusions: Interactions of well-known risk factors for all-cause mortality after myocardial infarction suggested important sex differences. This study gives rise to a further exploration of prediction models to improve risk assessment for men and women after myocardial infarction. Electronic supplementary material The online version of this article (doi:10.1186/s12916-014-0242-y) contains supplementary material, which is available to authorized users.

Although epilepsy is associated with substantial role impairment, it is also highly comorbid with other physical and mental disorders, making unclear the extent to which impairments associated with epilepsy are actually due to comorbidities. This issue was explored in the National Comorbidity Survey Replication (NCS-R), a nationally representative household survey of 5,692 US adults. Medically-recognized epilepsy was ascertained with self-report, comorbid physical disorders with a chronic conditions checklist, and comorbid DSM-IV mental disorders with the Composite International Diagnostic Interview (CIDI). Lifetime epilepsy prevalence was estimated at 1.8%. Epilepsy was comorbid with numerous neurological and general medical conditions and with a sporadic cluster of mental comorbidities (panic, PTSD, conduct disorder, and substance use disorders). Although comorbid disorders explain part of the significant gross associations of epilepsy with impairment, epilepsy remains significantly associated with work disability, cognitive impairment, and days of role impairment after controlling comorbidities. The net association of epilepsy with days of role impairment after controlling for comorbidities is equivalent to an annualized 89.4 million excess role impairment days among US adults with epilepsy, arguing that role impairment is a major component of the societal costs of epilepsy per se rather than merely due to disorders comorbid with epilepsy. This estimated burden is likely conservative as some parts of the effects of epilepsy are presumably mediated by secondary comorbid disorders.

OBJECTIVES: To investigate the relative importance of common physical and mental disorders with regard to the number of days out-of-role (DOR; number of days for which a person is completely unable to work or carry out normal activities because of health problems) in a population-based sample of adults in the São Paulo Metropolitan Area, Brazil. METHODS: The São Paulo Megacity Mental Health Survey was administered during face-to-face interviews with 2,942 adult household residents. The presence of 8 chronic physical disorders and 3 classes of mental disorders (mood, anxiety, and substance use disorders) was assessed for the previous year along with the number of days in the previous month for which each respondent was completely unable to work or carry out normal daily activities due to health problems. Using multiple regression analysis, we examined the associations of the disorders and their comorbidities with the number of days out-of-role while controlling for socio-demographic variables. Both individual-level and population-level associations were assessed. RESULTS: A total of 13.1% of the respondents reported 1 or more days out-of-role in the previous month, with an annual median of 41.4 days out-of-role. The disorders considered in this study accounted for 71.7% of all DOR; the disorders that caused the greatest number of DOR at the individual-level were digestive (22.6), mood (19.9), substance use (15.0), chronic pain (16.5), and anxiety (14.0) disorders. The disorders associated with the highest population-attributable DOR were chronic pain (35.2%), mood (16.5%), and anxiety (15.0%) disorders. CONCLUSIONS: Because pain, anxiety, and mood disorders have high effects at both the individual and societal levels, targeted interventions to reduce the impairments associated with these disorders have the highest potential to reduce the societal burdens of chronic illness in the São Paulo Metropolitan Area.

Background: Associations between lifetime traumatic event (LTE) exposures and subsequent physical ill-health are well established but it has remained unclear whether these are explained by PTSD or other mental disorders. This study examined this question and investigated whether associations varied by type and number of LTEs, across physical condition outcomes, or across countries. Methods: Cross-sectional, face-to-face household surveys of adults (18+) were conducted in 14 countries (n = 38, 051). The Composite International Diagnostic Interview assessed lifetime LTEs and DSM-IV mental disorders. Chronic physical conditions were ascertained by self-report of physician's diagnosis and year of diagnosis or onset. Survival analyses estimated associations between the number and type of LTEs with the subsequent onset of 11 physical conditions, with and without adjustment for mental disorders. Findings: A dose-response association was found between increasing number of LTEs and odds of any physical condition onset (OR 1.5 [95% CI: 1.4–1.5] for 1 LTE; 2.1 [2.0–2.3] for 5+ LTEs), independent of all mental disorders. Associations did not vary greatly by type of LTE (except for combat and other war experience), nor across countries. A history of 1 LTE was associated with 7/11 of the physical conditions (ORs 1.3 [1.2–1.5] to 1.7 [1.4–2.0]) and a history of 5+ LTEs was associated with 9/11 physical conditions (ORs 1.8 [1.3–2.4] to 3.6 [2.0–6.5]), the exceptions being cancer and stroke. Conclusions: Traumatic events are associated with adverse downstream effects on physical health, independent of PTSD and other mental disorders. Although the associations are modest they have public health implications due to the high prevalence of traumatic events and the range of common physical conditions affected. The effects of traumatic stress are a concern for all medical professionals and researchers, not just mental health specialists.

Objectives: Using data from a randomized experiment, to examine whether moving youth out of areas of concentrated poverty, where a disproportionate amount of crime occurs, prevents involvement in crime. Methods: We draw on new administrative data from the U.S. Department of Housing and Urban Development’s Moving to Opportunity (MTO) experiment. MTO families were randomized into an experimental group offered a housing voucher that could only be used to move to a low-poverty neighborhood, a Section 8 housing group offered a standard housing voucher, and a control group. This paper focuses on MTO youth ages 15–25 in 2001 (n = 4,643) and analyzes intention to treat effects on neighborhood characteristics and criminal behavior (number of violent- and property-crime arrests) through 10 years after randomization. Results: We find the offer of a housing voucher generates large improvements in neighborhood conditions that attenuate over time and initially generates substantial reductions in violent-crime arrests and sizable increases in property-crime arrests for experimental group males. The crime effects attenuate over time along with differences in neighborhood conditions. Conclusions: Our findings suggest that criminal behavior is more strongly related to current neighborhood conditions (situational neighborhood effects) than to past neighborhood conditions (developmental neighborhood effects). The MTO design makes it difficult to determine which specific neighborhood characteristics are most important for criminal behavior. Our administrative data analyses could be affected by differences across areas in the likelihood that a crime results in an arrest.