There is mixed evidence on the link between autism spectrum disorder (ASD) and diabetes. We conducted the first systematic review/meta-analysis on their association. Based on a pre-registered ...protocol (PROSPERO: CRD42021261114), we searched Pubmed, Ovid, and Web of Science databases up to 6 December 2021, with no language/type of document restrictions. We assessed study quality using the Newcastle-Ottawa Scale (NOS). We included 24 studies (total: 3427,773 individuals; 237,529 with ASD and 92,832 with diabetes) in the systematic review and 20 in the meta-analysis (mean stars number on the NOS: 5.89/10). There was a significant association, albeit characterized by significant heterogeneity, when pooling unadjusted OR (1.535, 95% CI = 1.109–2.126), which remained significant when restricting the analysis to children and type 2 diabetes, but became non-significant when considering adjusted ORs (OR: 1.528, 95% CI = 0.954–2.448). No significant prospective association was found (n = 2) on diabetes predicting ASD (HR: 1.232, 0.826–11.837). Therefore, the association between ASD and diabetes is likely confounded by demographic and clinical factors that should be systematically investigated in future studies.
•There is meta-analytic evidence of a statistically significant association between ASD and diabetes.•The relation could be stronger in children and for type 2 diabetes.•However, published studies are highly heterogeneous, limiting the confidence in the pooled meta-analytic effect.•Future research should focus on moderators and/or effect on subgroups of individuals.•Currently, systematic screening for diabetes in ASD and vice versa is not warranted.
Empirical evidence indicates a significant bidirectional association between mental disorders and physical diseases, but the prospective impact of mental disorders on clinical outcomes of physical ...diseases has not been comprehensively outlined. In this PRISMA‐ and COSMOS‐E‐compliant umbrella review, we searched PubMed, PsycINFO, Embase, and Joanna Briggs Institute Database of Systematic Reviews and Implementation Reports, up to March 15, 2022, to identify systematic reviews with meta‐analysis that examined the prospective association between any mental disorder and clinical outcomes of physical diseases. Primary outcomes were disease‐specific mortality and all‐cause mortality. Secondary outcomes were disease‐specific incidence, functioning and/or disability, symptom severity, quality of life, recurrence or progression, major cardiac events, and treatment‐related outcomes. Additional inclusion criteria were further applied to primary studies. Random effect models were employed, along with I2 statistic, 95% prediction intervals, small‐study effects test, excess significance bias test, and risk of bias (ROBIS) assessment. Associations were classified into five credibility classes of evidence (I to IV and non‐significant) according to established criteria, complemented by sensitivity and subgroup analyses to examine the robustness of the main analysis. Statistical analysis was performed using a new package for conducting umbrella reviews (https://metaumbrella.org). Population attributable fraction (PAF) and generalized impact fraction (GIF) were then calculated for class I‐III associations. Forty‐seven systematic reviews with meta‐analysis, encompassing 251 non‐overlapping primary studies and reporting 74 associations, were included (68% were at low risk of bias at the ROBIS assessment). Altogether, 43 primary outcomes (disease‐specific mortality: n=17; all‐cause mortality: n=26) and 31 secondary outcomes were investigated. Although 72% of associations were statistically significant (p<0.05), only two showed convincing (class I) evidence: that between depressive disorders and all‐cause mortality in patients with heart failure (hazard ratio, HR=1.44, 95% CI: 1.26‐1.65), and that between schizophrenia and cardiovascular mortality in patients with cardiovascular diseases (risk ratio, RR=1.54, 95% CI: 1.36‐1.75). Six associations showed highly suggestive (class II) evidence: those between depressive disorders and all‐cause mortality in patients with diabetes mellitus (HR=2.84, 95% CI: 2.00‐4.03) and with kidney failure (HR=1.41, 95% CI: 1.31‐1.51); that between depressive disorders and major cardiac events in patients with myocardial infarction (odds ratio, OR=1.52, 95% CI: 1.36‐1.70); that between depressive disorders and dementia in patients with diabetes mellitus (HR=2.11, 95% CI: 1.77‐2.52); that between alcohol use disorder and decompensated liver cirrhosis in patients with hepatitis C (RR=3.15, 95% CI: 2.87‐3.46); and that between schizophrenia and cancer mortality in patients with cancer (standardized mean ratio, SMR=1.74, 95% CI: 1.41‐2.15). Sensitivity/subgroup analyses confirmed these results. The largest PAFs were 30.56% (95% CI: 27.67‐33.49) for alcohol use disorder and decompensated liver cirrhosis in patients with hepatitis C, 26.81% (95% CI: 16.61‐37.67) for depressive disorders and all‐cause mortality in patients with diabetes mellitus, 13.68% (95% CI: 9.87‐17.58) for depressive disorders and major cardiac events in patients with myocardial infarction, 11.99% (95% CI: 8.29‐15.84) for schizophrenia and cardiovascular mortality in patients with cardiovascular diseases, and 11.59% (95% CI: 9.09‐14.14) for depressive disorders and all‐cause mortality in patients with kidney failure. The GIFs confirmed the preventive capacity of these associations. This umbrella review demonstrates that mental disorders increase the risk of a poor clinical outcome in several physical diseases. Prevention targeting mental disorders – particularly alcohol use disorders, depressive disorders, and schizophrenia – can reduce the incidence of adverse clinical outcomes in people with physical diseases. These findings can inform clinical practice and trans‐speciality preventive approaches cutting across psychiatric and somatic medicine.
In the research domain framework (RDoC), dysfunctional reward expectation has been proposed to be a cross-diagnostic domain in psychiatry, which may contribute to symptoms common to various ...neuropsychiatric conditions, such as anhedonia or apathy/avolition. We used a modified version of the Monetary Incentive Delay (MID) paradigm to obtain functional MRI images from 22 patients with schizophrenia, 24 with depression and 21 controls. Anhedonia and other symptoms of depression, and overall positive and negative symptomatology were also measured. We hypothesized that the two clinical groups would have a reduced activity in the ventral striatum when anticipating reward (compared to anticipation of a neutral outcome) and that striatal activation would correlate with clinical measures of motivational problems and anhedonia. Results were consistent with the first hypothesis: two clusters in both the left and right ventral striatum were found to differ between the groups in reward anticipation. Post-hoc analysis showed that this was due to higher activation in the controls compared to the schizophrenia and the depression groups in the right ventral striatum, with activation differences between depression and controls also seen in the left ventral striatum. No differences were found between the two patient groups, and there were no areas of abnormal cortical activation in either group that survived correction for multiple comparisons. Reduced ventral striatal activity was related to greater anhedonia and overall depressive symptoms in the schizophrenia group, but not in the participants with depression. Findings are discussed in relation to previous literature but overall are supporting evidence of reward system dysfunction across the neuropsychiatric continuum, even if the specific clinical relevance is still not fully understood. We also discuss how the RDoC approach may help to solve some of the replication problems in psychiatric fMRI research.
•The collaborative outcome study on health and functioning during infection times (COH-FIT) is a global survey on COVID-19 impact to date, involving more than 230 researchers and 120 institutions ...across all continents.•COH-FIT is an online anonymous survey, cross-sectional at the individiual level, but longitudinal at the population level, and has a multi-wave structure.•COH-FIT is available in 30 languages, deliberately including linguistic and ethnic minorities. It collects information on health and functioning of adults, but also of children (from 6 years old) and adolescents, via self-report and parental rating questionnaire.•COH-FIT collects both representative sample via polling agencies, and non-representative samples via snowball/non-probability recruiting startegies.•COH-FIT has been collecting over 150,000 responses from over 150 countries, of which 13,000 minors from the six continents from april 26th, 2020 to june 2021.
The COVID-19 pandemic has altered daily routines and family functioning, led to closing schools, and dramatically limited social interactions worldwide. Measuring its impact on mental health of vulnerable children and adolescents is crucial.
The Collaborative Outcomes study on Health and Functioning during Infection Times (COH-FIT – www.coh-fit.com) is an on-line anonymous survey, available in 30 languages, involving >230 investigators from 49 countries supported by national/international professional associations. COH-FIT has thee waves (until the pandemic is declared over by the WHO, and 6–18 months plus 24–36 months after its end). In addition to adults, COH-FIT also includes adolescents (age 14–17 years), and children (age 6–13 years), recruited via non-probability/snowball and representative sampling and assessed via self-rating and parental rating. Non-modifiable/modifiable risk factors/treatment targets to inform prevention/intervention programs to promote health and prevent mental and physical illness in children and adolescents will be generated by COH-FIT. Co-primary outcomes are changes in well-being (WHO-5) and a composite psychopathology P-Score. Multiple behavioral, family, coping strategy and service utilization factors are also assessed, including functioning and quality of life.
Up to June 2021, over 13,000 children and adolescents from 59 countries have participated in the COH-FIT project, with representative samples from eleven countries.
Cross-sectional and anonymous design.
Evidence generated by COH-FIT will provide an international estimate of the COVID-19 effect on children's, adolescents’ and families’, mental and physical health, well-being, functioning and quality of life, informing the formulation of present and future evidence-based interventions and policies to minimize adverse effects of the present and future pandemics on youth.
•The Collaborative Outcome study on Health and Functioning during Infection Times (COH-FIT) is the broadest survey on COVID-19 impact to date, involving over 230 researchers and 120 institutions ...across the six continents.•COH-FIT is an online anonymous survey, cross-sectional at the individiual level, but longitudinal at the population level, and has a multi-wave structure.•COH-FIT is available in 30 languages, being inclusive towards linguistic and ethnic minorities.•COH-FIT collects responses from adults, adolescents, and children starting from 6 years old.•COH-FIT collects both representative sample via polling agencies, and non-representative samples via snowball/non-probability recruiting approach.•COH-FIT has been collecting over 150,000 responses from over 150 countries, from the six continents from April 26th, 2020 to July 23rd, 2021.•Take the survey at www.coh-fit.com.
. High-quality comprehensive data on short-/long-term physical/mental health effects of the COVID-19 pandemic are needed.
. The Collaborative Outcomes study on Health and Functioning during Infection Times (COH-FIT) is an international, multi-language (n=30) project involving >230 investigators from 49 countries/territories/regions, endorsed by national/international professional associations. COH-FIT is a multi-wave, on-line anonymous, cross-sectional survey wave 1: 04/2020 until the end of the pandemic, 12 months waves 2/3 starting 6/24 months threreafter for adults, adolescents (14-17), and children (6-13), utilizing non-probability/snowball and representative sampling. COH-FIT aims to identify non-modifiable/modifiable risk factors/treatment targets to inform prevention/intervention programs to improve social/health outcomes in the general population/vulnerable subgrous during/after COVID-19. In adults, co-primary outcomes are change from pre-COVID-19 to intra-COVID-19 in well-being (WHO-5) and a composite psychopathology P-Score. Key secondary outcomes are a P-extended score, global mental and physical health. Secondary outcomes include health-service utilization/functioning, treatment adherence, functioning, symptoms/behaviors/emotions, substance use, violence, among others.
. Starting 04/26/2020, up to 14/07/2021 >151,000 people from 155 countries/territories/regions and six continents have participated. Representative samples of ≥1,000 adults have been collected in 15 countries. Overall, 43.0% had prior physical disorders, 16.3% had prior mental disorders, 26.5% were health care workers, 8.2% were aged ≥65 years, 19.3% were exposed to someone infected with COVID-19, 76.1% had been in quarantine, and 2.1% had been COVID 19-positive.
. Cross-sectional survey, preponderance of non-representative participants.
. Results from COH-FIT will comprehensively quantify the impact of COVID-19, seeking to identify high-risk groups in need for acute and long-term intervention, and inform evidence-based health policies/strategies during this/future pandemics.
Introduction
Although several systematic reviews (SRs)/meta-analyses (MAs) on the association between specific mental disorders and specific somatic conditions are available, an overarching evidence ...synthesis across mental disorders and somatic conditions is currently lacking. We will conduct an umbrella review of SRs/MAs to test: 1) the strength of the association between individual mental disorders and individual somatic conditions in children/adolescents and adults; 2) to which extent associations are specific to individual mental and somatic conditions .
Methods and analysis
We will search a broad set of electronic databases and contact study authors. We will include SRs with MA or SRs reporting the effect size from individual studies on the association between a number of somatic and mental conditions (as per the International Classification of Diseases, 11th Revision). We will follow an algorithm to select only one SR or MA when more than one are available on the same association. We will rate the quality of included SRs/MAs using the AMSTAR-2 tool. We will assess to which extent mental disorders are selectively associated with specific somatic conditions or if there are transdiagnostic, across-spectra or diagnostic spectrum-specific associations between mental disorders and somatic conditions based on the Transparent, Reporting, Appraising, Numerating, Showing (TRANSD) recommendations.
Discussion
The present umbrella review will shed light on the association between mental health disorders and somatic conditions, providing useful data for the care of patients with mental health disorders, in particular for early detection and intervention. This work might also add insight to the pathophysiology of mental health conditions, and contribute to the current debate on the value of a transdiagnostic approach in psychiatry.
Poisoning, a subtype of physical injury, is an important hazard in children and youth. Individuals with ADHD may be at higher risk of poisoning. Here, we conducted a systematic review and ...meta-analysis to quantify this risk. Furthermore, since physical injuries, likely share causal mechanisms with those of poisoning, we compared the relative risk of poisoning and injuries pooling studies reporting both. As per our pre-registered protocol (PROSPERO ID CRD42017079911), we searched 114 databases through November 2017. From a pool of 826 potentially relevant references, screened independently by two researchers, nine studies (84,756 individuals with and 1,398,946 without the disorder) were retained. We pooled hazard and odds ratios using Robust Variance Estimation, a meta-analytic method aimed to deal with non-independence of outcomes. We found that ADHD is associated with a significantly higher risk of poisoning (Relative Risk = 3.14, 95% Confidence Interval = 2.23 to 4.42). Results also indicated that the relative risk of poisoning is significantly higher than that of physical injuries when comparing individuals with and without ADHD (Beta coefficient = 0.686, 95% Confidence Interval = 0.166 to 1.206). These findings should inform clinical guidelines and public health programs aimed to reduce physical risks in children/adolescents with ADHD.
The Collaborative Outcome study on Health and Functioning during Infection Times (COH-FIT; www.coh-fit.com) is an anonymous and global online survey measuring health and functioning during the ...COVID-19 pandemic. The aim of this study was to test concurrently the validity of COH-FIT items and the internal validity of the co-primary outcome, a composite psychopathology “P-score”.
The COH-FIT survey has been translated into 30 languages (two blind forward-translations, consensus, one independent English back-translation, final harmonization). To measure mental health, 1–4 items (“COH-FIT items”) were extracted from validated questionnaires (e.g. Patient Health Questionnaire 9). COH-FIT items measured anxiety, depressive, post-traumatic, obsessive-compulsive, bipolar and psychotic symptoms, as well as stress, sleep and concentration. COH-FIT Items which correlated r ≥ 0.5 with validated companion questionnaires, were initially retained. A P-score factor structure was then identified from these items using exploratory factor analysis (EFA) and confirmatory factor analyses (CFA) on data split into training and validation sets. Consistency of results across languages, gender and age was assessed.
From >150,000 adult responses by May 6th, 2022, a subset of 22,456 completed both COH-FIT items and validated questionnaires. Concurrent validity was consistently demonstrated across different languages for COH-FIT items. CFA confirmed EFA results of five first-order factors (anxiety, depression, post-traumatic, psychotic, psychophysiologic symptoms) and revealed a single second-order factor P-score, with high internal reliability (ω = 0.95). Factor structure was consistent across age and sex.
COH-FIT is a valid instrument to globally measure mental health during infection times. The P-score is a valid measure of multidimensional mental health.
•COH-FIT is a global multi-language survey measuring health and functioning during infection times (over 150,000)•COH-FIT is available in 30 psychometrically validated language•COH-FIT co-primary outcome composite psychopathology P-score is psychometrically valid•COH-FIT can be used to measure health and functioning of the general population during public health crises
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