Weight change following diagnosis with psychosis: a retrospective cohort study in Greater Manchester, UK.

INTRODUCTION: Weight gain in the months/years after diagnosis/treatment of severe enduring mental illness (SMI) is a major predictor of future diabetes, dysmetabolic profile and increased risk of cardiometabolic diseases. There is limited data on the longer-term profile of weight change in people with a history of SMI and how this may differ between individuals. We here report a retrospective study on weight change over the 5 years following an SMI diagnosis in Greater Manchester UK, an ethnically and culturally diverse community, with particular focus on comparing non-affective psychosis (NAP) vs affective psychosis (AP) diagnoses. METHODS: We undertook an anonymised search in the Greater Manchester Care Record (GMCR). We reviewed the health records of anyone who had been diagnosed for the first time with first episode psychosis, schizophrenia, schizoaffective disorder, delusional disorder (non-affective psychosis = NAP) or affective psychosis (AP). We analysed body mass index (BMI) change in the 5-year period following the first prescription of antipsychotic medication. All individuals had taken an antipsychotic agent for at least 3 months. The 5-year follow-up point was anywhere between 2003 and 2023. RESULTS: We identified 9125 people with the diagnoses above. NAP (n = 5618; 37.3% female) mean age 49.9 years; AP (n = 4131; 60.5% female) mean age 48.7 years. 27.0% of NAP were of non-White ethnicity vs 17.8% of AP individuals. A higher proportion of people diagnosed with NAP were in the highest quintile of social disadvantage 52.4% vs 39.5% for AP. There were no significant differences in baseline BMI profile. In a subsample with HbA1c data (n = 2103), mean HbA1c was higher in NAP at baseline (40.4 mmol/mol in NAP vs 36.7 mmol/mol for AP). At 5-year follow-up, there was similarity in both the overall % of individuals in the obese ≥ 30 kg/m2 category (39.8% NAP vs 39.7% AP), and % progressing from a normal healthy BMI transitioned to obese/overweight BMI (53.6% of NAP vs 55.6% with AP). 43.7% of those NAP with normal BMI remained at a healthy BMI vs 42.7% with AP. At 5-year follow-up for NAP, 83.1% of those with BMI ≥ 30 kg/m2 stayed in this category vs 81.5% of AP. CONCLUSION: The results of this real-world longitudinal cohort study suggest that the changes in BMI with treatment of non-affective psychosis vs bipolar disorder are not significantly different, while 43% maintain a healthy weight in the first 5 years following antipsychotic prescription.

Changes in prescribing of psychotropic vs some physical health medication in primary care through the COVID-19 pandemic in England: a national-level survey.

INTRODUCTION: The COVID-19 pandemic globally impacted healthcare provision. Prescribing changes in common medications can be used as a marker for new diagnoses. We describe how the prescribing of specific psychotropics was impacted by the pandemic. METHODS: Primary Care Prescribing data for different classes of drugs from March 2017 to February 2022 were considered. To capture the impact during periods of restricted access to health services for new diagnoses/existing conditions, repeat prescriptions/episodic prescribing were included with account taken of historical trends. The pre-pandemic prescriptions issued each month from March 2018 to February 2020 were linearly extrapolated forward to give an expected annual growth (EAG). The monthly average expected prescriptions for the pandemic period (March 2020-February 2022) were compared. RESULTS: Physical health medications had lower monthly prescriptions during the pandemic, most markedly for antibiotics - 12.5% (EAG - 1.3%). Bronchodilator prescribing showed a marked increase in the early pandemic months from March 2020 of 5% (EAG 0.1%). Mental health medication prescribing increased above trend for hypnotics/anxiolytics by 0.2% (EAG - 2.3%), while antidepressants fell by - 0.2% (EAG 5.0%), with no net change for antipsychotics (EAG 2.8%), but a temporary increase in antipsychotic prescribing in the early pandemic period. For all the main antidepressants prescribed in England (Sertraline, Mirtazapine, Venlafaxine, Fluoxetine and Citalopram), prescribing actually decreased in the main pandemic period vs historical trend. CONCLUSIONS: The increase in anxiolytic/hypnotic prescribing above trend links to pandemic effects on anxiety/worry. If anything, there was a slight fall in prescribing of the main antidepressants prescribed, which given prevailing circumstances at the time, suggests that access to services may have restricted access to timely assessment.

A Longitudinal Clinical Trajectory Analysis Examining the Accumulation of Co-morbidity in People with Type 2 Diabetes (T2D) Compared with Non-T2D Individuals.

BACKGROUND: Type 2 diabetes mellitus (T2D) is commonly associated with an increasing complexity of multimorbidity. While some progress has been made in identifying genetic and non-genetic risk factors for T2D, understanding the longitudinal clinical history of individuals before/after T2D diagnosis may provide additional insights. METHODS: In this study, we utilised longitudinal data from the DARE (Diabetes Alliance for Research in England) study to examine the trajectory of clinical conditions in individuals with and without T2D. Data from 1932 individuals (T2D n = 1196 vs. matched non-T2D controls n = 736) were extracted and subjected to trajectory analysis over a period of up to 50 years (25 years pre-diagnosis/25 years post-diagnosis). We also analysed the cumulative proportion of people with diagnosed coronary artery disease (CAD) in their general practice (GP) record with an analysis of lower respiratory tract infection (RTI) as a comparator group. RESULTS: The mean age of diagnosis of T2D was 52.6 (95% confidence interval 52.0-53.4) years. In the years leading up to T2D diagnosis, individuals who eventually received a T2D diagnosis consistently exhibited a considerable increase in several clinical phenotypes. Additionally, immediately prior to T2D diagnosis, a significantly greater prevalence of hypertension (35%)/RTI (34%)/heart conditions (17%)/eye, nose, throat infection (19%) and asthma (12%) were observed. The corresponding trajectory of each of these conditions was much less dramatic in the matched controls. Post-T2D diagnosis, proportions of T2D individuals exhibiting hypertension/chronic kidney disease/retinopathy/infections climbed rapidly before plateauing. At the last follow-up by quintile of disadvantage, the proportion (%) of people with diagnosed CAD was 6.4% for quintile 1 (least disadvantaged) and 11% for quintile 5 (F = 3.4, p = 0.01 for the difference between quintiles). CONCLUSION: These findings provide novel insights into the onset/natural progression of T2D, suggesting an early phase of inflammation-related disease activity before any clinical diagnosis of T2D is made. Measures that reduce social inequality have the potential in the longer term to reduce the social gradient in health outcomes reported here.

First episode psychosis and weight gain a longitudinal perspective in Cheshire UK: a comparison between individuals with nonaffective versus affective psychosis.

Early weight gain following initiation of antipsychotic treatment predicts longer-term weight gain, with attendant long-term consequences including premature cardiovascular events/death. An important question is whether there is a difference in weight change over time between people with affective versus nonaffective psychosis. Here we describe the results of a real-world analysis of the BMI change in the months postdiagnosis with affective versus nonaffective psychosis. Methods: We undertook an anonymised search across one Primary Care Network in Cheshire, UK with a total population of 32 301 individuals. We reviewed the health records of anyone who had been diagnosed over a 10-year period between June 2012 and June 2022 for the first time with first episode nonaffective psychosis versus psychosis associated with depression or bipolar affective disorder (affective psychosis). Results: The overall % change in BMI was +8% in nonaffective psychosis individuals and +4% in those with a diagnosis of affective psychosis - however, the distribution was markedly skewed for nonaffective psychosis patients. Using caseness as >30% increase in BMI; affective = 4% cases and nonaffective = 13% cases, there was a three-fold difference in terms of increase in BMI. In regression analysis, the r2 linking the initial BMI to % change in BMI was 0.13 for nonaffective psychosis and 0.14 for affective psychosis. Conclusion: The differences observed here in the distribution of weight change over time between individuals with affective versus nonaffective psychosis may relate to underlying constitutional differences. The phenotypic and genetic factors underlying this difference remain to be defined.