Abstract:FEP patients from a visible minority or who were victims of childhood physical abuse have higher levels of HbA1c at admission compared with other patients. This might suggest an increase in risk for the development of future DGM. If confirmed, preventive strategies could be tailored for these groups.
“…One study found that social determinants of health were inversely associated with glycated hemoglobin in first-episode psychosis [9]. However, patients had very short prior psychotropic treatment exposure and the cross-sectional design precluded the investigation of the impact of SES factors on treatment-related metabolic health evolution.…”
Section: Translational Psychiatrymentioning
confidence: 99%
“…8 Service of General Psychiatry, Department of Psychiatry, Lausanne University Hospital, University of Lausanne, Prilly, Switzerland. 9 Service of Child and Adolescent Psychiatry, Department of Psychiatry, Lausanne University Hospital, University of Lausanne, Lausanne, Switzerland. 10 Service of Old Age Psychiatry, Department of Psychiatry, Lausanne University Hospital, University of Lausanne, Prilly, Switzerland.…”
Weight gain and metabolic complications are major adverse effects of many psychotropic drugs. We aimed to understand how socio-economic status (SES), defined as the Swiss socio-economic position (SSEP), is associated with cardiometabolic parameters after initiation of psychotropic medications known to induce weight gain. Cardiometabolic parameters were collected in two Swiss cohorts following the prescription of psychotropic medications. The SSEP integrated neighborhood-based income, education, occupation, and housing condition. The results were then validated in an independent replication sample (UKBiobank), using educational attainment (EA) as a proxy for SES. Adult patients with a low SSEP had a higher risk of developing metabolic syndrome over one year versus patients with a high SSEP (Hazard ratio (95% CI) = 3.1 (1.5–6.5), n = 366). During the first 6 months of follow-up, a significant negative association between SSEP and body mass index (BMI), weight change, and waist circumference change was observed (25 ≤ age < 65, n = 526), which was particularly important in adults receiving medications with the highest risk of weight gain, with a BMI difference of 0.86 kg/m2 between patients with low versus high SSEP (95% CI: 0.03–1.70, n = 99). Eventually, a causal effect of EA on BMI was revealed using Mendelian randomization in the UKBiobank, which was notably strong in high-risk medication users (beta: −0.47 SD EA per 1 SD BMI; 95% CI: −0.46 to −0.27, n = 11,314). An additional aspect of personalized medicine was highlighted, suggesting the patients’ SES represents a significant risk factor. Particular attention should be paid to patients with low SES when initiating high cardiometabolic risk psychotropic medications.
“…One study found that social determinants of health were inversely associated with glycated hemoglobin in first-episode psychosis [9]. However, patients had very short prior psychotropic treatment exposure and the cross-sectional design precluded the investigation of the impact of SES factors on treatment-related metabolic health evolution.…”
Section: Translational Psychiatrymentioning
confidence: 99%
“…8 Service of General Psychiatry, Department of Psychiatry, Lausanne University Hospital, University of Lausanne, Prilly, Switzerland. 9 Service of Child and Adolescent Psychiatry, Department of Psychiatry, Lausanne University Hospital, University of Lausanne, Lausanne, Switzerland. 10 Service of Old Age Psychiatry, Department of Psychiatry, Lausanne University Hospital, University of Lausanne, Prilly, Switzerland.…”
Weight gain and metabolic complications are major adverse effects of many psychotropic drugs. We aimed to understand how socio-economic status (SES), defined as the Swiss socio-economic position (SSEP), is associated with cardiometabolic parameters after initiation of psychotropic medications known to induce weight gain. Cardiometabolic parameters were collected in two Swiss cohorts following the prescription of psychotropic medications. The SSEP integrated neighborhood-based income, education, occupation, and housing condition. The results were then validated in an independent replication sample (UKBiobank), using educational attainment (EA) as a proxy for SES. Adult patients with a low SSEP had a higher risk of developing metabolic syndrome over one year versus patients with a high SSEP (Hazard ratio (95% CI) = 3.1 (1.5–6.5), n = 366). During the first 6 months of follow-up, a significant negative association between SSEP and body mass index (BMI), weight change, and waist circumference change was observed (25 ≤ age < 65, n = 526), which was particularly important in adults receiving medications with the highest risk of weight gain, with a BMI difference of 0.86 kg/m2 between patients with low versus high SSEP (95% CI: 0.03–1.70, n = 99). Eventually, a causal effect of EA on BMI was revealed using Mendelian randomization in the UKBiobank, which was notably strong in high-risk medication users (beta: −0.47 SD EA per 1 SD BMI; 95% CI: −0.46 to −0.27, n = 11,314). An additional aspect of personalized medicine was highlighted, suggesting the patients’ SES represents a significant risk factor. Particular attention should be paid to patients with low SES when initiating high cardiometabolic risk psychotropic medications.
“…12 Nineteen studies described the sample and together they included 13,976 participants (including 5656 healthy controls). The studies were done in USA, 15,20,24 Canada, 22,28,29 UK, 16 Italy, 12,13,27 Switzerland, 12 Poland, 1,17,23 Norway, 11,21 Spain, Netherlands, Germany, 24 Belgium, and France, 14 Brazil, 19 Turkey, 18 Australia, 26 and India. 25 Figure 1.PRISMA flow diagram.…”
Section: Resultsmentioning
confidence: 99%
“…846 were excluded at the title and abstract level and 62 studies that met the inclusion criteria were retrieved and assessed at full text level. Twenty articles 1,[11][12][13][14][15][16][17][18][19][20][21][22][23][24][25][26][27][28][29] (Figure 1) published between 2011 and 2021 met the criteria for our final review. The majority of these studies (n = 12) were cross-sectional, 14,[17][18][21][22][23][24][25][26][27][28][29] while seven were case-control studies, 1,11,13,15,16,19,20 and one study was prospective, monitoring the weight gain in the participants for a year.…”
Objective A history of adverse childhood experiences (ACE) is common among people with severe mental illness (SMI), and they are also associated with physical health problems, including metabolic syndrome (MetS) in general adult populations. We aimed to evaluate and synthesise the evidence relating to the association between ACE and MetS and/or its components in patients with SMI. Methods We systematically searched multiple databases (MEDLINE, PubMed, PsycINFO, EMBASE, Emcare, Cochrane Library, Health Technology Assessments, Joanna Briggs Institute, and Maternity and Infant Care database) and reviewed studies that described an association between ACE and MetS or its components in SMI adult patients. Results Twenty studies were reviewed. Most studies described a significant association between ACE and at least one to three components of MetS, with obesity being the most studied and, therefore, showing a more consistent association compared to the other MetS components. ACE and the components of MetS did not remain significant, in most of the studies, after adjusting for confounders. None of the studies showed an association with MetS as a whole entity. Conclusion Adults with SMI with a history of ACE are more likely to demonstrate health problems such as MetS and cardiovascular disease-related risk factors.
“…Several studies have described factors affecting antipsychotic-induced weight gain in FEP patients, which can be theoretically translated as factors of glucose abnormalities ( 4 , 36 ). However, only a few studies have focused on the effect of early life events, either perinatal ( 20 , 22 – 25 ) or postnatal ( 37 , 38 ).…”
First episode of psychosis (FEP) patients display a wide variety of metabolic disturbances at onset, which might underlie these patients’ increased morbidity and early mortality. Glycemic abnormalities have been previously related to pharmacological agents; however, recent research highlights the impact of early life events. Birth weight (BW), an indirect marker of the fetal environment, has been related to glucose abnormalities in the general population over time. We aim to evaluate if BW correlates with glucose values in a sample of FEP patients treated with different antipsychotics. Two hundred and thirty-six patients were included and evaluated for clinical and metabolic variables at baseline and at 2, 6, 12, and 24 months of follow-up. Pearson correlations and linear mixed model analysis were conducted to analyze the data. Antipsychotic treatment was grouped due to its metabolic risk profile. In our sample of FEP patients, BW was negatively correlated with glucose values at 24 months of follow-up [r=-0.167, p=0.037]. BW showed a trend towards significance in the association with glucose values over the 24-month period (F=3.22; p=0.073) despite other confounders such as age, time, sex, body mass index, antipsychotic type, and chlorpromazine dosage. This finding suggests that BW is involved in the evolution of glucose values over time in a cohort of patients with an FEP, independently of the type of pharmacological agent used in treatment. Our results highlight the importance of early life events in the later metabolic outcome of patients.
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