Childhood anxious/withdrawn behaviour and later anxiety disorder: a network outcome analysis of a population cohort.

BACKGROUND: Several previous studies have identified a continuity between childhood anxiety/withdrawal and anxiety disorder (AD) in later life. However, not all children with anxiety/withdrawal problems will experience an AD in later life. Previous studies have shown that the severity of childhood anxiety/withdrawal accounts for some of the variability in AD outcomes. However, no studies to date have investigated how variation in features of anxiety/withdrawal may relate to continuity prognoses. The present research addresses this gap. METHODS: Data were gathered as part of the Christchurch Health and Development Study, a 40-year population birth cohort of 1265 children born in Christchurch, New Zealand. Fifteen childhood anxiety/withdrawal items were measured at 7-9 years and AD outcomes were measured at various interviews from 15 to 40 years. Six network models were estimated. Two models estimated the network structure of childhood anxiety/withdrawal items independently for males and females. Four models estimated childhood anxiety/withdrawal items predicting adolescent AD (14-21 years) and adult AD (21-40 years) in both males and females. RESULTS: Approximately 40% of participants met the diagnostic criteria for an AD during both the adolescent (14-21 years) and adult (21-40 years) outcome periods. Outcome networks showed that items measuring social and emotional anxious/withdrawn behaviours most frequently predicted AD outcomes. Items measuring situation-based fears and authority figure-specific anxious/withdrawn behaviour did not consistently predict AD outcomes. This applied across both the male and female subsamples. CONCLUSIONS: Social and emotional anxious/withdrawn behaviours in middle childhood appear to carry increased risk for AD outcomes in both adolescence and adulthood.

Reported sources of health inequities in Indigenous Peoples with chronic kidney disease: a systematic review of quantitative studies.

BACKGROUND: To summarise the evidentiary basis related to causes of inequities in chronic kidney disease among Indigenous Peoples. METHODS: We conducted a Kaupapa Maori meta-synthesis evaluating the epidemiology of chronic kidney diseases in Indigenous Peoples. Systematic searching of MEDLINE, Google Scholar, OVID Nursing, CENTRAL and Embase was conducted to 31 December 2019. Eligible studies were quantitative analyses (case series, case-control, cross-sectional or cohort study) including the following Indigenous Peoples: Maori, Aboriginal and Torres Strait Islander, Métis, First Nations Peoples of Canada, First Nations Peoples of the United States of America, Native Hawaiian and Indigenous Peoples of Taiwan. In the first cycle of coding, a descriptive synthesis of the study research aims, methods and outcomes was used to categorise findings inductively based on similarity in meaning using the David R Williams framework headings and subheadings. In the second cycle of analysis, the numbers of studies contributing to each category were summarised by frequency analysis. Completeness of reporting related to health research involving Indigenous Peoples was evaluated using the CONSIDER checklist. RESULTS: Four thousand three hundred seventy-two unique study reports were screened and 180 studies proved eligible. The key finding was that epidemiological investigators most frequently reported biological processes of chronic kidney disease, particularly type 2 diabetes and cardiovascular disease as the principal causes of inequities in the burden of chronic kidney disease for colonised Indigenous Peoples. Social and basic causes of unequal health including the influences of economic, political and legal structures on chronic kidney disease burden were infrequently reported or absent in existing literature. CONCLUSIONS: In this systematic review with meta-synthesis, a Kaupapa Maori methodology and the David R Williams framework was used to evaluate reported causes of health differences in chronic kidney disease in Indigenous Peoples. Current epidemiological practice is focussed on biological processes and surface causes of inequity, with limited reporting of the basic and social causes of disparities such as racism, economic and political/legal structures and socioeconomic status as sources of inequities.

Expanding the system: A brief psychosocial complex systems model of internalising disorder.

BACKGROUND: The aetiology of internalising disorders remains poorly understood. Recently, a bottom-up network perspective has suggested mental disorders are best conceptualised as emergent systems, and may be explained by mapping systems of symptoms embedded within a complex biopsychosocial environment. Under this framework, the complex system in which internalising disorders are embedded remains poorly understood. The present research outlines a brief psychosocial system of internalising disorders as a basis for future research. METHODS: A Mixed Graphical Model was fitted on 15 psychosocial variables (including depression and anxiety) collected during the Christchurch Health and Development Study, a representative population birth cohort of 1265 people born in 1977 in Christchurch, New Zealand. RESULTS: The model demonstrates that psychosocial risk factors for internalising disorders tend to be inter-related. The psychosocial system accounted for 19.9% of the variance in the diagnostic depression variable, and 5.0% of the variance in diagnostic anxiety. Most variables (10/13) were associated with depression and anxiety either directly or indirectly. LIMITATIONS: First, the estimated model is undirected, so causal directions are unspecified except for longitudinal relationships. Second, binary diagnostic variables were used for depression and anxiety, meaning the model does include symptom-level complexity. Third, the model does not account for within-person effects. CONCLUSIONS: This exploratory model may serve as a basis for the mapping of greater (bio) psychosocial complexity around internalising disorders. The model concisely demonstrates the need for researchers to "embrace complexity", but also underscores the conceptual scope that is required to do so on a broader (bio) psychosocial level.