Using Instrumental Variables to Measure Causation over Time in Cross-Lagged Panel Models

Cross-lagged panel models (CLPMs) are commonly used to estimate causal influences between two variables with repeated assessments. The lagged effects in a CLPM depend on the time interval between assessments, eventually becoming undetectable at longer intervals. To address this limitation, we incorporate instrumental variables (IVs) into the CLPM with two study waves and two variables. Doing so enables estimation of both the lagged (i.e., "distal") effects and the bidirectional cross-sectional (i.e., "proximal") effects at each wave. The distal effects reflect Granger-causal influences across time, which decay with increasing time intervals. The proximal effects capture causal influences that accrue over time and can help infer causality when the distal effects become undetectable at longer intervals. Significant proximal effects, with a negligible distal effect, would imply that the time interval is too long to estimate a lagged effect at that time interval using the standard CLPM. Through simulations and an empirical application, we demonstrate the impact of time intervals on causal inference in the CLPM and present modeling strategies to detect causal influences regardless of the time interval in a study. Furthermore, to motivate empirical applications of the proposed model, we highlight the utility and limitations of using genetic variables as IVs in large-scale panel studies.

MR-DoC2: Bidirectional Causal Modeling with Instrumental Variables and Data from Relatives

Establishing causality is an essential step towards developing interventions for psychiatric disorders, substance use and many other conditions. While randomized controlled trials (RCTs) are considered the gold standard for causal inference, they are unethical in many scenarios. Mendelian randomization (MR) can be used in such cases, but importantly both RCTs and MR assume unidirectional causality. In this paper, we developed a new model, MRDoC2, that can be used to identify bidirectional causation in the presence of confounding due to both familial and non-familial sources. Our model extends the MRDoC model (Minică et al. in Behav Genet 48:337-349,  https://doi.org/10.1007/s10519-018-9904-4 , 2018), by simultaneously including risk scores for each trait. Furthermore, the power to detect causal effects in MRDoC2 does not require the phenotypes to have different additive genetic or shared environmental sources of variance, as is the case in the direction of causation twin model (Heath et al. in Behav Genet 23:29-50,  https://doi.org/10.1007/BF01067552 , 1993).

Population-level risks of alcohol consumption by amount, geography, age, sex, and year: a systematic analysis for the Global Burden of Disease Study 2020

BACKGROUND

The health risks associated with moderate alcohol consumption continue to be debated. Small amounts of alcohol might lower the risk of some health outcomes but increase the risk of others, suggesting that the overall risk depends, in part, on background disease rates, which vary by region, age, sex, and year.

METHODS

For this analysis, we constructed burden-weighted dose-response relative risk curves across 22 health outcomes to estimate the theoretical minimum risk exposure level (TMREL) and non-drinker equivalence (NDE), the consumption level at which the health risk is equivalent to that of a non-drinker, using disease rates from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2020 for 21 regions, including 204 countries and territories, by 5-year age group, sex, and year for individuals aged 15-95 years and older from 1990 to 2020. Based on the NDE, we quantified the population consuming harmful amounts of alcohol.

FINDINGS

The burden-weighted relative risk curves for alcohol use varied by region and age. Among individuals aged 15-39 years in 2020, the TMREL varied between 0 (95% uncertainty interval 0-0) and 0·603 (0·400-1·00) standard drinks per day, and the NDE varied between 0·002 (0-0) and 1·75 (0·698-4·30) standard drinks per day. Among individuals aged 40 years and older, the burden-weighted relative risk curve was J-shaped for all regions, with a 2020 TMREL that ranged from 0·114 (0-0·403) to 1·87 (0·500-3·30) standard drinks per day and an NDE that ranged between 0·193 (0-0·900) and 6·94 (3·40-8·30) standard drinks per day. Among individuals consuming harmful amounts of alcohol in 2020, 59·1% (54·3-65·4) were aged 15-39 years and 76·9% (73·0-81·3) were male.

INTERPRETATION

There is strong evidence to support recommendations on alcohol consumption varying by age and location. Stronger interventions, particularly those tailored towards younger individuals, are needed to reduce the substantial global health loss attributable to alcohol.

FUNDING

Bill & Melinda Gates Foundation.

Estimation of the global prevalence of dementia in 2019 and forecasted prevalence in 2050: an analysis for the Global Burden of Disease Study 2019

BACKGROUND

Given the projected trends in population ageing and population growth, the number of people with dementia is expected to increase. In addition, strong evidence has emerged supporting the importance of potentially modifiable risk factors for dementia. Characterising the distribution and magnitude of anticipated growth is crucial for public health planning and resource prioritisation. This study aimed to improve on previous forecasts of dementia prevalence by producing country-level estimates and incorporating information on selected risk factors.

METHODS

We forecasted the prevalence of dementia attributable to the three dementia risk factors included in the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 (high body-mass index, high fasting plasma glucose, and smoking) from 2019 to 2050, using relative risks and forecasted risk factor prevalence to predict GBD risk-attributable prevalence in 2050 globally and by world region and country. Using linear regression models with education included as an additional predictor, we then forecasted the prevalence of dementia not attributable to GBD risks. To assess the relative contribution of future trends in GBD risk factors, education, population growth, and population ageing, we did a decomposition analysis.

FINDINGS

We estimated that the number of people with dementia would increase from 57·4 (95% uncertainty interval 50·4-65·1) million cases globally in 2019 to 152·8 (130·8-175·9) million cases in 2050. Despite large increases in the projected number of people living with dementia, age-standardised both-sex prevalence remained stable between 2019 and 2050 (global percentage change of 0·1% [-7·5 to 10·8]). We estimated that there were more women with dementia than men with dementia globally in 2019 (female-to-male ratio of 1·69 [1·64-1·73]), and we expect this pattern to continue to 2050 (female-to-male ratio of 1·67 [1·52-1·85]). There was geographical heterogeneity in the projected increases across countries and regions, with the smallest percentage changes in the number of projected dementia cases in high-income Asia Pacific (53% [41-67]) and western Europe (74% [58-90]), and the largest in north Africa and the Middle East (367% [329-403]) and eastern sub-Saharan Africa (357% [323-395]). Projected increases in cases could largely be attributed to population growth and population ageing, although their relative importance varied by world region, with population growth contributing most to the increases in sub-Saharan Africa and population ageing contributing most to the increases in east Asia.

INTERPRETATION

Growth in the number of individuals living with dementia underscores the need for public health planning efforts and policy to address the needs of this group. Country-level estimates can be used to inform national planning efforts and decisions. Multifaceted approaches, including scaling up interventions to address modifiable risk factors and investing in research on biological mechanisms, will be key in addressing the expected increases in the number of individuals affected by dementia.

FUNDING

Bill & Melinda Gates Foundation and Gates Ventures.

Migration of Junior Doctors: The Case of Psychiatric Trainees in Portugal

INTRODUCTION

In the last few decades, the rates of international medical migration have continuously risen. In Psychiatry, there is great disparity in the workforce between high and low-income countries. Yet, little is known about the 'push' and 'pull' factors and the migratory intentions of trainees. This study aims to assess the factors impacting the decisions of psychiatric trainees in Portugal towards migration.

MATERIAL AND METHODS

A questionnaire was developed in the Brain Drain study and was distributed to psychiatric trainees in Portugal.

RESULTS

The sample consists of 104 psychiatric trainees (60.6% female). Overall, 40.4% of the trainees had prior experience of living abroad and the majority (96.9%) felt that this experience influenced their attitude towards migration in a positive way. About 75% of trainees had 'ever' considered leaving the country, but the majority (70.0%) had not taken any 'practical steps' towards migration. The main reasons to stay in Portugal were personal, while the main reason to leave was financial. The majority of the trainees (55.7%) were dissatisfied or very dissatisfied with their income, working conditions and academic opportunities.

DISCUSSION

Working conditions, salaries and academic opportunities are the main triggers for the migration of psychiatric trainees from Portugal.

CONCLUSION

These results may inform the decisions of stakeholders in the health and education sectors and point out the necessary investments required and the impact it may have on the workforce.

Association between homicide rates and suicide rates: a countrywide longitudinal analysis of 5507 Brazilian municipalities

OBJECTIVE

To estimate the association between homicide and suicide rates in Brazilian municipalities over a period of 7 years.

DESIGN

We conducted a longitudinal ecological study using annual mortality data from 5507 Brazilian municipalities between 2008 and 2014. Multivariable negative binomial regression models were used to examine the relationship between homicide and suicide rates. Robustness of results was explored using sensitivity analyses to examine the influence of data quality, population size, age and sex on the relationship between homicide and suicide rates.

SETTING

A nationwide study of municipality-level data.

PARTICIPANTS

Mortality data and corresponding population estimates for municipal populations aged 10 years and older.

PRIMARY AND SECONDARY OUTCOME MEASURES

Age-standardised suicide rates per 100 000.

RESULTS

Municipal suicide rates were positively associated with municipal homicide rates; after adjusting for socioeconomic and demographic factors, a doubling of the homicide rate was associated with 22% increase in suicide rate (rate ratio=1.22, 95% CI: 1.13 to 1.33). A dose-response effect was observed with 4% increase in suicide rates at the third quintile, 9% at the fourth quintile and 12% at the highest quintile of homicide rates compared with the lowest quintile. The observed effect estimates were robust to sensitivity analyses.

CONCLUSIONS

Municipalities with higher homicide rates have higher suicide rates and the relationship between homicide and suicide rates in Brazil exists independently of many sociodemographic and socioeconomic factors. Our results are in line with the hypothesis that changes in homicide rates lead to changes in suicide rates, although a causal association cannot be established from this study. Suicide and homicide rates have increased in Brazil despite increased community mental health support and incarceration, respectively; therefore, new avenues for intervention are needed. The identification of a positive relationship between homicide and suicide rates suggests that population-based interventions to reduce homicide rates may also reduce suicide rates in Brazil.

Schizophrenia moderates the relationship between white matter integrity and cognition

Cognitive impairment is a primary feature of schizophrenia, with alterations in several cognitive domains appearing in the pre-morbid phase of the disorder. White matter microstructure is also affected in schizophrenia and considered to be related to cognition, but the relationship of the two is unclear. As interaction between cognition and white matter structure involves the interplay of several brain structures and cognitive abilities, investigative methods which can examine the interaction of multiple variables are preferred. A multiple-groups structural equation model (SEM) was used to assess the relationship between diffusion tension imaging data (fractional anisotropy of selected white matter tracts) and cognitive abilities of 196 subjects - 135 healthy subjects and 61 patients with schizophrenia. It was found that multiple-indicators, multiple-causes model best fitted the data analysed. Schizophrenia moderated the relation of white matter function on cognition with a large effect size. This paper extends previous work on modelling intelligence within a SEM framework by incorporating neurological elements into the model, and shows that white matter microstructure in patients with schizophrenia interacts with cognitive abilities.

First episode psychosis moderates the effect of gray matter volume on cognition

Patients with first episode psychosis (FEP) present with cognitive deficits and volume differences in certain brain areas. Brain volumetric information further correlates with cognitive testing, and multiple brain areas shows different strengths of correlation with the cognitive functions being tested. Traditionally, these cognitive functions are independently related to volumetric differences, but these functions share variance. Failing to account for this aspect of cognition hinders the proper representation of cognition in neuroimaging studies. We used modeling methods which account for this shared variance to investigate the differences of correlations between cognitive abilities and brain areas. A multiple-groups structured equation model (SEM) approach was used to design and test a model representing the relation between gray matter volumetric data and neuropsychological test scores in a sample of 100 Brazilian FEP patients and 94 controls. Models with a latent variable formed by neurological measures and reflecting cognitive measures performed better on fit tests. FEP moderated the relation between gray matter volumes and cognition by altering the profile of correlations between groups. This moderation had a large effect size. SEM provides a fine grained picture of the interdependence of structural brain changes and cognition.