One stream, two channels? A parallel-process latent class growth model of homicide rates and suicide rates in 183 countries, between 2000 and 2019

Background

Suicide and homicide have long been viewed in Western culture as moral, ethical and legal equivalents. This view has underpinned many theoretical and empirical explorations into their relationship over the centuries. However, there has been little evaluation of longitudinal heterogeneity.

Methods

Suicide and homicide rates in 183 countries between 2000 and 2019 were collected from the World Health Organization Global Health Observatory Repository. Corresponding structural variables (i.e., GDP per capita, unemployment rate, percentage of urban population, percentage of elderly population, and Gini index) were acquired from The World Bank and Standardized World Income Inequality Database. Parallel-process latent class growth modelling was applied to identify different classes within the joint suicide and homicide rate trajectories. Multinomial logistic regression examined relationships between the structural covariates and trajectory classes.

Results

Four trajectory classes were identified, two with inverse relationships between suicide and homicide, and two with parallel relationships: 1) countries with increasing suicide rates and decreasing homicide rates ("suicide up, homicide down": UD, n = 41) or 2) countries with decreasing suicide rates and increasing homicide rates ("suicide down, homicide up": DU, n = 17); and 3) countries where suicide and homicide rates both trended up (UU, n = 19), or 4) both trended down (DD, n = 106). A higher average annual growth rate (AAGR) of GDP per capita was related to an increased possibility of being in DD than in DU. Countries with higher AAGR in unemployment rates were more likely to be in UD and UU than in DD, while those with higher AAGR in urbanization were less likely to be in UD than in DD.

Conclusion

The over-time relationship between suicide and homicide is heterogenous and complex. It is influenced differently by GDP per capita, urbanization and unemployment in different countries, and it is not well described by a single theory.

Fostering practice-based evidence through routine outcome monitoring in a university psychotherapy service for common mental health problems: a protocol for a naturalistic, observational study

INTRODUCTION

Data-informed psychotherapy and routine outcome monitoring are growing as referents in psychotherapy research and practice. In Ecuador, standardised web-based routine outcome monitoring systems have not been used yet, precluding data-driven clinical decisions and service management. Hence, this project aims at fostering and disseminating practice-based evidence in psychotherapy in Ecuador by implementing a web-based routine outcome monitoring system in a university psychotherapy service.

METHODS AND ANALYSES

This is a protocol for an observational naturalistic longitudinal study. Progress and outcomes of treatment in the Centro de Psicología Aplicada of the Universidad de Las Américas in Quito, Ecuador will be examined. Participants will be adolescents and adults (≥11 years) seeking treatment, as well as therapists and trainees working at the centre between October 2022 and September 2025. Clients' progress will be monitored by a range of key variables: psychological distress, ambivalence to change, family functioning, therapeutic alliance and life satisfaction. Sociodemographic information and satisfaction with treatment data will be collected before and at the end of treatment, respectively. Also, semi-structured interviews to explore therapists' and trainees' perceptions, expectations and experiences will be conducted. We will analyse first contact data, psychometrics of the measures, reliable and clinically significant change, outcome predictors as well as trajectories of changes. Moreover, we will conduct a framework analysis for the interviews.

ETHICS AND DISSEMINATION

The protocol for this study was approved by the Human Research Ethics Committee of the Pontificia Universidad Católica del Ecuador (#PV-10-2022). The results will be disseminated in peer-reviewed scientific articles, at conferences and in workshops.

TRIAL REGISTRATION NUMBER

NCT05343741.

Gestational per- and polyfluoroalkyl substances exposure and infant body mass index trajectory in the New Hampshire Birth Cohort Study

Per- and polyfluoroalkyl substances (PFAS) are environmentally persistent, potential metabolic disruptors of concern for infants. Mothers participating in the New Hampshire Birth Cohort Study (NHBCS) provided a plasma sample during pregnancy to measure concentrations of seven PFAS, and infant weight and length were abstracted from well-child visits between birth and 12 months. Sex-specific growth patterns of child body mass index (BMI) were fit using a growth mixture model (GMM) and the relative risk ratios (RRR) and 95% Confidence Intervals (95% CI) for the association of maternal plasma PFAS with BMI growth patterns during infancy were estimated by using multinomial logistic model for the group probabilities in the GMM. Four growth patterns were identified: Group 1) a steep increase in BMI during the first 6 months, then a leveling off; Group 2) a gradual increase in BMI across the year; Group 3) a steep increase in BMI during months 1-3, then stable BMI; and Group 4) a gradual increase in BMI with plateau around 3 months (reference group). For boys, higher maternal pregnancy perfluorooctanoate concentrations were associated with a 60% decreased chance of being in group 3 as compared to group 4, after adjusting for potential confounding variables (RRR = 0.4; 95% CI: 0.1, 0.9). For girls, higher maternal perfluorooctane sulfonate (PFOS) concentrations during pregnancy were associated with a higher likelihood of following the growth pattern of groups 2 (RRR = 2.5; 95% CI: 1.0, 6.1) and 3 (RRR = 2.8; 95% CI: 1.0, 7.6) as compared to group 4, adjusting for potential confounding variables. In this cohort, sex-specific associations of maternal plasma PFAS concentrations during pregnancy with growth patterns during the first year of life were observed, with greater BMI growth observed among infant girls born to mothers with higher pregnancy concentrations of PFOS.

Assessment of agricultural sustainability in European Union countries: a group-based multivariate trajectory approach

Sustainability of agriculture is difficult to measure and assess because it is a multidimensional concept that involves economic, social and environmental aspects and is subjected to temporal evolution and geographical differences. Existing studies assessing agricultural sustainability in the European Union (EU) are affected by several shortcomings that limit their relevance for policy makers. Specifically, most of them focus on farm level or cover a small set of countries, and the few exceptions covering a broad set of countries consider only a subset of the sustainable dimensions or rely on cross-sectional data. In this paper, we consider yearly data on 12 indicators (5 for the economic, 3 for the social and 4 for the environmental dimension) measured on 26 EU countries in the period 2004–2018 (15 years), and apply group-based multivariate trajectory modeling to identify groups of countries with common trends of sustainable objectives. An expectation-maximization algorithm is proposed to perform maximum likelihood estimation from incomplete data without relying on an explicit imputation procedure. Our results highlight three groups of countries with distinguished strong and weak sustainable objectives. Strong objectives common to all the three groups include improvement of productivity, increase of personal income in rural areas, reduction of poverty in rural areas, increase of production of renewable energy, rise of organic farming and reduction of nitrogen balance. Instead, enhancement of manager turnover and reduction of greenhouse gas emissions are weak objectives common to all the three groups of countries. Our findings represent a valuable resource to formulate new schemes for the attribution of subsidies within the Common Agricultural Policy (CAP).

Highways to Ageing - Linking life course SEP to multivariate trajectories of health outcomes in older adults

OBJECTIVES

Ageing is a temporal, multi-faceted process subject to interacting factors. In this study, we used life course and multidimensional approaches to elucidate the association between socioeconomic forces across a lifetime and the developmental origins in health and disease of the Mexican elderly.

METHODS

Data stemmed from the Mexican Health and Ageing Study, constituting a sample of older adults (N= 5169, ≥50 years). With retrospective information on early, intermediary and contemporaneous socioeconomic indicators, life course typologies of socioeconomic position were identified using Latent Class Analysis. Based on prospective data of functional mobility, number of chronic conditions and self-rated health, multivariate trajectories of health outcomes were uncovered with Group Based Trajectory Model. Links between the extracted SEP and multivariate health latent constructs were explored with multinomial logistic regression.

RESULTS

Life course SEP classes were heterogeneous, yet a large proportion of subjects was characterized by persistent socioeconomic adversity throughout life. The health outcomes' patterns of co-evolution were diverse too, shedding light on the nature of their developmental links, while revealing variable synchronicity in their temporal decline. A graded association was observed between the life course SEP classes and ageing trajectories.

CONCLUSION

The results primarily backed the cumulative advantage/disadvantage life course framework, while finding some indication for age as a leveller hypothesis. Variability in patterns of dynamic co-action among the health outcomes depicts ageing as a naturally variable process of interconnected changes. Life course evidence for the ways socio-economic forces are differentially linked to distinct developmental profiles of ageing is provided.

An overview of mixture modelling for latent evolutions in longitudinal data: Modelling approaches, fit statistics and software

The use of finite mixture modelling (FMM) is becoming increasingly popular for the analysis of longitudinal repeated measures data. FMMs assist in identifying latent classes following similar paths of temporal development. This paper aims to address the confusion experienced by practitioners new to these methods by introducing the various available techniques, which includes an overview of their interrelatedness and applicability. Our focus will be on the commonly used model-based approaches which comprise latent class growth analysis (LCGA), group-based trajectory models (GBTM), and growth mixture modelling (GMM). We discuss criteria for model selection, highlight often encountered challenges and unresolved issues in model fitting, showcase model availability in software, and illustrate a model selection strategy using an applied example.

Heterogeneity in childhood body mass trajectories in relation to prenatal phthalate exposure

Phthalates, compounds commonly used in plastics and personal care products, have been associated with childhood obesity in cross-sectional and some longitudinal studies. Using advanced statistical methods, we characterized the heterogeneity in body mass development patterns over childhood (ages 2-14 years) and explored associations with maternal prenatal urinary concentrations of phthalates among 335 children in the Center for the Health Assessment of Mothers and Children of Salinas (CHAMACOS) cohort study. Height and weight were measured every one to two years in this cohort, which had a high prevalence of obesity and overweight. Building upon a previous analysis that showed a positive association between prenatal phthalate exposure and body mass index (BMI) in CHAMACOS children, we used three advanced statistical methods: generalized additive models, growth mixture models, and functional principal component analysis with tree-based methods to identify patterns of childhood BMI development and allow for non-linear relationships with the environmental exposures. Our results highlight the heterogeneity in childhood BMI development patterns and suggest a sex-specific non-linear association between prenatal monoethyl phthalate urinary concentrations and BMI level in children, confirmed across a variety of statistical methods. There is also evidence to suggest positive associations between DEHP metabolites and BMI stabilization during puberty for girls.