Identifying health inequalities in individuals with major mental illness (MMI) using routine data

Abstract and Summary of Thesis: Background: Individuals with Major Mental Illness (such as schizophrenia and bipolar disorder) experience increased rates of physical health comorbidity compared to the general population. They also experience inequalities in access to certain aspects of healthcare. This ultimately leads to premature mortality. Studies detailing patterns of physical health comorbidity are limited by their definitions of comorbidity, single disease approach to comorbidity and by the study of heterogeneous groups. To date the investigation of possible sources of healthcare inequalities experienced by individuals with Major Mental Illness (MMI) is relatively limited. Moreover studies detailing the extent of premature mortality experienced by individuals with MMI vary both in terms of the measure of premature mortality reported and age of the cohort investigated, limiting their generalisability to the wider population. Therefore local and national data can be used to describe patterns of physical health comorbidity, investigate possible reasons for health inequalities and describe mortality rates. These findings will extend existing work in this area. Aims and Objectives: To review the relevant literature regarding: patterns of physical health comorbidity, evidence for inequalities in physical healthcare and evidence for premature mortality for individuals with MMI. To examine the rates of physical health comorbidity in a large primary care database and to assess for evidence for inequalities in access to healthcare using both routine primary care prescribing data and incentivised national Quality and Outcome Framework (QOF) data. Finally to examine the rates of premature mortality in a local context with a particular focus on cause of death across the lifespan and effect of International Classification of Disease Version 10 (ICD 10) diagnosis and socioeconomic status on rates and cause of death. Methods: A narrative review of the literature surrounding patterns of physical health comorbidity, the evidence for inequalities in physical healthcare and premature mortality in MMI was undertaken. Rates of physical health comorbidity and multimorbidity in schizophrenia and bipolar disorder were examined using a large primary care dataset (Scottish Programme for Improving Clinical Effectiveness in Primary Care (SPICE)). Possible inequalities in access to healthcare were investigated by comparing patterns of prescribing in individuals with MMI and comorbid physical health conditions with prescribing rates in individuals with physical health conditions without MMI using SPICE data. Potential inequalities in access to health promotion advice (in the form of smoking cessation) and prescribing of Nicotine Replacement Therapy (NRT) were also investigated using SPICE data. Possible inequalities in access to incentivised primary healthcare were investigated using National Quality and Outcome Framework (QOF) data. Finally a pre-existing case register (Glasgow Psychosis Clinical Information System (PsyCIS)) was linked to Scottish Mortality data (available from the Scottish Government Website) to investigate rates and primary cause of death in individuals with MMI. Rate and primary cause of death were compared to the local population and impact of age, socioeconomic status and ICD 10 diagnosis (schizophrenia vs. bipolar disorder) were investigated. Results: Analysis of the SPICE data found that sixteen out of the thirty two common physical comorbidities assessed, occurred significantly more frequently in individuals with schizophrenia. In individuals with bipolar disorder fourteen occurred more frequently. The most prevalent chronic physical health conditions in individuals with schizophrenia and bipolar disorder were: viral hepatitis (Odds Ratios (OR) 3.99 95% Confidence Interval (CI) 2.82-5.64 and OR 5.90 95% CI 3.16-11.03 respectively), constipation (OR 3.24 95% CI 3.01-3.49 and OR 2.84 95% CI 2.47-3.26 respectively) and Parkinson’s disease (OR 3.07 95% CI 2.43-3.89 and OR 2.52 95% CI 1.60-3.97 respectively). Both groups had significantly increased rates of multimorbidity compared to controls: in the schizophrenia group OR for two comorbidities was 1.37 95% CI 1.29-1.45 and in the bipolar disorder group OR was 1.34 95% CI 1.20-1.49. In the studies investigating inequalities in access to healthcare there was evidence of: under-recording of cardiovascular-related conditions for example in individuals with schizophrenia: OR for Atrial Fibrillation (AF) was 0.62 95% CI 0.52 - 0.73, for hypertension 0.71 95% CI 0.67 - 0.76, for Coronary Heart Disease (CHD) 0.76 95% CI 0.69 - 0.83 and for peripheral vascular disease (PVD) 0.83 95% CI 0.72 - 0.97. Similarly in individuals with bipolar disorder OR for AF was 0.56 95% CI 0.41-0.78, for hypertension 0.69 95% CI 0.62 - 0.77 and for CHD 0.77 95% CI 0.66 - 0.91. There was also evidence of less intensive prescribing for individuals with schizophrenia and bipolar disorder who had comorbid hypertension and CHD compared to individuals with hypertension and CHD who did not have schizophrenia or bipolar disorder. Rate of prescribing of statins for individuals with schizophrenia and CHD occurred significantly less frequently than in individuals with CHD without MMI (OR 0.67 95% CI 0.56-0.80). Rates of prescribing of 2 or more anti-hypertensives were lower in individuals with CHD and schizophrenia and CHD and bipolar disorder compared to individuals with CHD without MMI (OR 0.66 95% CI 0.56-0.78 and OR 0.55 95% CI 0.46-0.67, respectively). Smoking was more common in individuals with MMI compared to individuals without MMI (OR 2.53 95% CI 2.44-2.63) and was particularly increased in men (OR 2.83 95% CI 2.68-2.98). Rates of ex-smoking and non-smoking were lower in individuals with MMI (OR 0.79 95% CI 0.75-0.83 and OR 0.50 95% CI 0.48-0.52 respectively). However recorded rates of smoking cessation advice in smokers with MMI were significantly lower than the recorded rates of smoking cessation advice in smokers with diabetes (88.7% vs. 98.0%, p<0.001), smokers with CHD (88.9% vs. 98.7%, p<0.001) and smokers with hypertension (88.3% vs. 98.5%, p<0.001) without MMI. The odds ratio of NRT prescription was also significantly lower in smokers with MMI without diabetes compared to smokers with diabetes without MMI (OR 0.75 95% CI 0.69-0.81). Similar findings were found for smokers with MMI without CHD compared to smokers with CHD without MMI (OR 0.34 95% CI 0.31-0.38) and smokers with MMI without hypertension compared to smokers with hypertension without MMI (OR 0.71 95% CI 0.66-0.76). At a national level, payment and population achievement rates for the recording of body mass index (BMI) in MMI was significantly lower than the payment and population achievement rates for BMI recording in diabetes throughout the whole of the UK combined: payment rate 92.7% (Inter Quartile Range (IQR) 89.3-95.8 vs. 95.5% IQR 93.3-97.2, p<0.001 and population achievement rate 84.0% IQR 76.3-90.0 vs. 92.5% IQR 89.7-94.9, p<0.001 and for each country individually: for example in Scotland payment rate was 94.0% IQR 91.4-97.2 vs. 96.3% IQR 94.3-97.8, p<0.001. Exception rate was significantly higher for the recording of BMI in MMI than the exception rate for BMI recording in diabetes for the UK combined: 7.4% IQR 3.3-15.9 vs. 2.3% IQR 0.9-4.7, p<0.001 and for each country individually. For example in Scotland exception rate in MMI was 11.8% IQR 5.4-19.3 compared to 3.5% IQR 1.9-6.1 in diabetes. Similar findings were found for Blood Pressure (BP) recording: across the whole of the UK payment and population achievement rates for BP recording in MMI were also significantly reduced compared to payment and population achievement rates for the recording of BP in chronic kidney disease (CKD): payment rate: 94.1% IQR 90.9-97.1 vs.97.8% IQR 96.3-98.9 and p<0.001 and population achievement rate 87.0% IQR 81.3-91.7 vs. 97.1% IQR 95.5-98.4, p<0.001. Exception rates again were significantly higher for the recording of BP in MMI compared to CKD (6.4% IQR 3.0-13.1 vs. 0.3% IQR 0.0-1.0, p<0.001). There was also evidence of differences in rates of recording of BMI and BP in MMI across the UK. BMI and BP recording in MMI were significantly lower in Scotland compared to England (BMI:-1.5% 99% CI -2.7 to -0.3%, p<0.001 and BP: -1.8% 99% CI -2.7 to -0.9%, p<0.001). While rates of BMI and BP recording in diabetes and CKD were similar in Scotland compared to England (BMI: -0.5 99% CI -1.0 to 0.05, p=0.004 and BP: 0.02 99% CI -0.2 to 0.3, p=0.797). Data from the PsyCIS cohort showed an increase in Standardised Mortality Ratios (SMR) across the lifespan for individuals with MMI compared to the local Glasgow and wider Scottish populations (Glasgow SMR 1.8 95% CI 1.6-2.0 and Scotland SMR 2.7 95% CI 2.4-3.1). Increasing socioeconomic deprivation was associated with an increased overall rate of death in MMI (350.3 deaths/10,000 population/5 years in the least deprived quintile compared to 794.6 deaths/10,000 population/5 years in the most deprived quintile). No significant difference in rate of death for individuals with schizophrenia compared with bipolar disorder was reported (6.3% vs. 4.9%, p=0.086), but primary cause of death varied: with higher rates of suicide in individuals with bipolar disorder (22.4% vs. 11.7%, p=0.04). Discussion: Local and national datasets can be used for epidemiological study to inform local practice and complement existing national and international studies. While the strengths of this thesis include the large data sets used and therefore their likely representativeness to the wider population, some limitations largely associated with using secondary data sources are acknowledged. While this thesis has confirmed evidence of increased physical health comorbidity and multimorbidity in individuals with MMI, it is likely that these findings represent a significant under reporting and likely under recognition of physical health comorbidity in this population. This is likely due to a combination of patient, health professional and healthcare system factors and requires further investigation. Moreover, evidence of inequality in access to healthcare in terms of: physical health promotion (namely smoking cessation advice), recording of physical health indices (BMI and BP), prescribing of medications for the treatment of physical illness and prescribing of NRT has been found at a national level. While significant premature mortality in individuals with MMI within a Scottish setting has been confirmed, more work is required to further detail and investigate the impact of socioeconomic deprivation on cause and rate of death in this population. It is clear that further education and training is required for all healthcare staff to improve the recognition, diagnosis and treatment of physical health problems in this population with the aim of addressing the significant premature mortality that is seen. Conclusions: Future work lies in the challenge of designing strategies to reduce health inequalities and narrow the gap in premature mortality reported in individuals with MMI. Models of care that allow a much more integrated approach to diagnosing, monitoring and treating both the physical and mental health of individuals with MMI, particularly in areas of social and economic deprivation may be helpful. Strategies to engage this “hard to reach” population also need to be developed. While greater integration of psychiatric services with primary care and with specialist medical services is clearly vital the evidence on how best to achieve this is limited. While the National Health Service (NHS) is currently undergoing major reform, attention needs to be paid to designing better ways to improve the current disconnect between primary and secondary care. This should then help to improve physical, psychological and social outcomes for individuals with MMI.

Biochemical and epidemiological investigations of non-steroidal anti-inflammatory drug usage and related side effects in equids

Non-steroidal anti-inflammatory drugs (NSAIDs) are widely used in equine veterinary practice. These drugs exert their effect by inhibiting cyclooxygenase (COX) enzymes, which control prostaglandin production, a major regulator of tissue perfusion. Two isoforms of COX enzymes exist: COX-1 is physiologically present in tissues, while COX-2 is up-regulated during inflammation and has been indicated as responsible for the negative effects of an inflammatory response. Evidence suggests that NSAIDs that inhibit only COX-2, preserving the physiological function of COX-1 might have a safer profile. Studies that evaluate the effect of NSAIDs on COX enzymes are all performed under experimental conditions and none uses actual clinical patients. The biochemical investigations in this work focus on describing the effect on COX enzymes activity of flunixin meglumine and phenylbutazone, two non-selective COX inhibitors and firocoxib, a COX-2 selective inhibitor, in clinical patients undergoing elective surgery. A separate epidemiological investigation was aimed at describing the impact that the findings of biochemical data have on a large population of equids. Electronic medical records (EMRs) from 454,153 equids were obtained from practices in the United Kingdom, United States of America and Canada. Information on prevalence and indications for NSAIDs use was extracted from the EMRs via a text mining technique, improved from the literature and described and validated within this Thesis. Further the prevalence of a clinical sign compatible with NSAID toxicity, such as diarrhoea, is reported along with analysis evaluating NSAID administration in light of concurrent administration of other drugs and comorbidities. This work confirms findings from experimental settings that NSAIDs firocoxib is COX-2 selective and that flunixin meglumine and phenylbutazone are non-selective COX inhibitors and therefore their administration carries a greater risk of toxicity. However the impact of this finding needs to be interpreted with caution as epidemiological data suggest that the prevalence of toxicity is in fact small and the use of these drugs at the labelled dose is quite safe.

Studies of antihypertensive drug persistence and adherence in the Glasgow Blood Pressure Clinic

Hypertension (HTN) is a major risk factor for cardiovascular diseases including stroke, coronary heart disease (CHD), chronic renal failure, peripheral vascular disease, myocardial infarction, congestive heart failure and premature death. The prevalence of HTN in Scotland is very high and although a high proportion of the patients receive antihypertensive medications, blood pressure (BP) control is very low. Recommendations for starting a specific antihypertensive class have been debated between various guidelines over the years. Some guidelines and HTN studies have preferred to start with a combination of an antihypertensive class instead of using a single therapy, and they have found greater BP reductions with combination therapies than with monotherapy. However, it has been shown in several clinical trials that 20% to 35% of hypertensive patients could not achieve the target BP, even though they received more than three antihypertensive medications. Several factors were found to affect BP control. Adherence and persistence were considered as the factors contributing the most to uncontrolled hypertension. Other factors such as age, sex, body mass index (BMI), alcohol intake, baseline systolic BP (SBP), and the communication between physicians and patients have been shown to be associated with uncontrolled BP and resistant hypertension. Persistence, adherence and compliance are interchangeable terms and have been used in the literature to describe a patient’s behaviour with their antihypertensive drugs and prescriptions. The methods used to determine persistence and adherence, as well as the inclusion and exclusion criteria, vary between persistence and adherence studies. The prevalence of persistence and adherence have varied between these studies, and were determined to be high in some studies and low in others. The initiation of a specific antihypertensive class has frequently been associated with an increase or decrease in adherence and persistence. The tolerability and efficacy of the initial antihypertensive class have been the most common methods of explaining this association. There are also many factors that suggest a relationship with adherence and persistence. Some factors in previous studies, such as age, were frequently associated with adherence and persistence. On the other hand, relationships with certain factors have varied between the studies. The associations of age, sex, alcohol use, smoking, baseline systolic blood pressure (SBP) and diastolic BP (DBP), the presence of comorbidities, an increase in the number of pills and the relationship between patients and physicians with adherence and persistence have been the most commonly investigated factors. Most studies have defined persistence in terms of a patient still taking medication after a period of time. A medication possession ratio (MPR) ≥ 80 has been used to define compliance. Either of these terminologies, or both, have been used to estimate adherence. In this study, I used the same definition for persistence to identify patients who have continued with their initial treatment, and used persistence and MPR to define patients who adhered to their initial treatment. The aim of this study was to estimate the prevalence of persistence and adherence in Scotland. Also, factors that could have had an effect on persistence and adherence were studied. The number of antihypertensive drugs taken by patients during the study and factors that led to an increase in patients being on a combination therapy were also evaluated. The prevalence of resistance and BP control were determined by taking the BP after the last drug had been taken by persistent patients during five follow-up studies. The relationship of factors such as age, sex, BMI, alcohol use, smoking, estimated glomerular filtration rate (eGFR), and albumin levels with BP reductions for each antihypertensive class were determined. Information Services Division (ISD) data, which includes all antihypertensive drugs, were collected from pharmacies in Scotland and linked to the Glasgow Blood Pressure Clinic (GBPC) database. This database also includes demographic characteristics, BP readings and clinical results for all patients attending the GBPC. The case notes for patients who attended the GBPC were reviewed and all new antihypertensive drugs that were prescribed between visits, BP before and after taking drugs, and any changes in the hypertensive drugs were recorded. A total of 4,232 hypertensive patients were included in the first study. The first study showed that angiotensin converting enzyme inhibitor (ACEI) and beta-blockers (BB) were the most prescribed antihypertensive classes between 2004 and 2013. Calcium channel blockers (CCB), thiazide diuretics and angiotensin receptor blockers (ARB) followed ACEI and BB as the most prescribed drugs during the same period. The prescription trend of the antihypertensive class has changed over the years with an increase in prescriptions for ACEI and ARB and a decrease in prescriptions for BB and diuretics. I observed a difference in antihypertensive class prescriptions by age, sex, SBP and BMI. For example, CCB, thiazide diuretics and alpha-blockers were more likely to be prescribed to older patients, while ACEI, ARB or BB were more commonly prescribed for younger patients. In a second study, 4,232 and 3,149 hypertensive patients were included to investigate the prevalence of persistence in the Scottish population in 1- and 5-year studies, respectively. The prevalence of persistence in the 1-year study was 72.9%, while it was only 62.8% in the 5-year study. Those patients taking ARB and ACEI showed high rates of persistence and those taking diuretics and alpha blockers had low rates of persistence. The association of persistence with clinical characteristics was also investigated. Younger patients were more likely to totally stop their treatment before restarting their treatment with other antihypertensive drugs. Furthermore, patients who had high SBP tended to be non-persistent. In a third study, 3,085 and 1,979 patients who persisted with their treatment were included. In the first part of the study, MPR was calculated, and patients with an MPR ≥ 80 were considered as adherent. Adherence rates were 29.9% and 23.4% in the 1- and 5-year studies, respectively. Patients who initiated the study with ACEI were more likely to adhere to their treatments. However, patients who initiated the study with thiazide diuretics were less likely to adhere to their treatments. Sex, age and BMI were different between the adherence and non-adherence groups. Age was an independent factor affecting adherence rates during both the 1- and 5-year studies with older patients being more likely to be adherent. In the second part of the study, pharmacy databases were checked with patients' case notes to compare antihypertensive drugs that were collected from the pharmacy with the antihypertensive prescription given during the patient’s clinical visit. While 78.6% of the antihypertensive drugs were collected between clinical visits, 21.4% were not collected. Patients who had more days to see the doctor in the subsequent visit were more likely to not collect their prescriptions. In a fourth study, 3,085 and 1,979 persistent patients were included to calculate the number of antihypertensive classes that were added to the initial drug during the 1-year and 5-year studies, respectively. Patients who continued with treatment as a monotherapy and who needed a combination therapy were investigated during the 1- and 5-year studies. In all, 55.8% used antihypertensive drugs as a monotherapy and 44.2% used them as a combination therapy during the 1-year study. While 28.2% of patients continued with treatment without the required additional therapy, 71.8% of the patients needed additional therapy. In all, 20.8% and 46.5% of patients required three different antihypertensive classes or more during the 1-year and 5-year studies, respectively. Patients who started with ACEI, ARB and BB were more likely to continue as monotherapy and less likely to need two more antihypertensive drugs compared with those who started with alpha-blockers, non-thiazide diuretics and CCB. Older ages, high BMI levels, high SBP and high alcohol intake were independent factors that led to an increase in the probability of patients taking combination therapies. In the first part of the final study, BPs were recorded after the last drug had been taken during the 5 year study. There were 815 persistent patients who were assigned for this purpose. Of these, 39% had taken one, two or three antihypertensive classes and had controlled BP (controlled hypertension [HTN]), 29% of them took one or two antihypertensive classes and had uncontrolled BP (uncontrolled HTN), and 32% of the patients took three antihypertensive classes or more and had uncontrolled BP (resistant HTN). The initiation of an antihypertensive drug and the factors affecting BP pressure were compared between the resistant and controlled HTN groups. Patients who initiated the study with ACEI were less likely to be resistant compared with those who started with alpha blockers and non-thiazide diuretics. Older patients, and high BMI tended to result in resistant HTN. In the second part of study, BP responses for patients who initiated the study with ACEI, ARB, BB, CCB and thiazide diuretics were compared. After adjusting for risk factors, patients who initiated the study with ACEI and ARB were more respondent than those who took CCB and thiazide diuretics. In the last part of this study, the association between BP reductions and factors affecting BP were tested for each antihypertensive drug. Older patients responded better to alpha blockers. Younger patients responded better to ACEI and ARB. An increase in BMI led to a decreased reduction in patients on ACEI and diuretics (thiazide and non-thiazide). An increase in albumin levels and a decrease in eGFR led to decreases in BP reductions in patients on thiazide diuretics. An increase in eGFR decreased the BP response with ACEI. In conclusion, although a high percentage of hypertensive patients in Scotland persisted with their initial drug prescription, low adherence rates were found with these patients. Approximately half of these patients required three different antihypertensive classes during the 5 years, and 32% of them had resistant HTN. Although this study was observational in nature, the large sample size in this study represented a real HTN population, and the large pharmacy data represented a real antihypertensive population, which were collected through the support of prescription data from the GBPC database. My findings suggest that ACEI, ARB and BB are less likely to require additional therapy. However, ACEI and ARB were better tolerated than BB in that they were more likely to be persistent than BB. In addition, users of ACEI, and ARB have good BP response and low resistant HTN. Linkage patients who participated in these studies with their morbidity and mortality will provide valuable information concerning the effect of adherence on morbidity and mortality and the potential benefits of using ACEI or ARB over other drugs.

An exploration of treatment burden and patient capacity in people with stroke

Background and aims: Advances in modern medicine have led to improved outcomes after stroke, yet an increased treatment burden has been placed on patients. Treatment burden is the workload of health care for people with chronic illness and the impact that this has on functioning and well-being. Those with comorbidities are likely to be particularly burdened. Excessive treatment burden can negatively affect outcomes. Individuals are likely to differ in their ability to manage health problems and follow treatments, defined as patient capacity. The aim of this thesis was to explore the experience of treatment burden for people who have had a stroke and the factors that influence patient capacity. Methods: There were four phases of research. 1) A systematic review of the qualitative literature that explored the experience of treatment burden for those with stroke. Data were analysed using framework synthesis, underpinned by Normalisation Process Theory (NPT). 2) A cross-sectional study of 1,424,378 participants >18 years, demographically representative of the Scottish population. Binary logistic regression was used to analyse the relationship between stroke and the presence of comorbidities and prescribed medications. 3) Interviews with twenty-nine individuals with stroke, fifteen analysed by framework analysis underpinned by NPT and fourteen by thematic analysis. The experience of treatment burden was explored in depth along with factors that influence patient capacity. 4) Integration of findings in order to create a conceptual model of treatment burden and patient capacity in stroke. Results: Phase 1) A taxonomy of treatment burden in stroke was created. The following broad areas of treatment burden were identified: making sense of stroke management and planning care; interacting with others including health professionals, family and other stroke patients; enacting management strategies; and reflecting on management. Phase 2) 35,690 people (2.5%) had a diagnosis of stroke and of the 39 co-morbidities examined, 35 were significantly more common in those with stroke. The proportion of those with stroke that had >1 additional morbidities present (94.2%) was almost twice that of controls (48%) (odds ratio (OR) adjusted for age, gender and socioeconomic deprivation; 95% confidence interval: 5.18; 4.95-5.43) and 34.5% had 4-6 comorbidities compared to 7.2% of controls (8.59; 8.17-9.04). In the stroke group, 12.6% of people had a record of >11 repeat prescriptions compared to only 1.5% of the control group (OR adjusted for age, gender, deprivation and morbidity count: 15.84; 14.86-16.88). Phase 3) The taxonomy of treatment burden from Phase 1 was verified and expanded. Additionally, treatment burdens were identified as arising from either: the workload of healthcare; or the endurance of care deficiencies. A taxonomy of patient capacity was created. Six factors were identified that influence patient capacity: personal attributes and skills; physical and cognitive abilities; support network; financial status; life workload, and environment. A conceptual model of treatment burden was created. Healthcare workload and the presence of care deficiencies can influence and be influenced by patient capacity. The quality and configuration of health and social care services influences healthcare workload, care deficiencies and patient capacity. Conclusions: This thesis provides important insights into the considerable treatment burden experienced by people who have had a stroke and the factors that affect their capacity to manage health. Multimorbidity and polypharmacy are common in those with stroke and levels of these are high. Findings have important implications for the design of clinical guidelines and healthcare delivery, for example co-ordination of care should be improved, shared decision-making enhanced, and patients better supported following discharge from hospital.

Exploring the role of miR-34a in regulating adipose inflammation during obesity

Background: Obesity is not a new disease, with roots that can be traced back to 400 BC. However, with the staggering increase in individuals that are overweight and obese since the 1980s, now over a quarter of individuals in Europe and the Americas are classed as obese. This presents a global health problem that needs to be addressed with novel therapies. It is now well accepted that obesity is a chronic, low-grade inflammatory condition that could predispose individuals to a number of comorbidities. Obesity is associated with cardiovascular diseases (CVDs) and type 2 diabetes (T2D) as part of “the metabolic syndrome,” and as first identified by Dr Vauge, central distribution of white adipose tissue (WAT) is an important risk factor in the development of these diseases. Subsequently, visceral WAT (vWAT) was shown to be an important factor in this association with CVDs and T2D, and increasing inflammation. As the obese WAT expands, mainly through hypertrophy, there is an increase in inflammation that recruits numerous immune cells to the tissue that further exacerbate this inflammation, causing local and systemic inflammatory and metabolic effects. One of the main types of immune cell involved in this pathogenic process is pro-inflammatory M1 adipose tissue macrophages (ATMs). MicroRNAs (miRNAs) are a species of small RNAs that post-transcriptionally regulate gene expression by targeting gene mRNA, causing its degradation or translational repression. These miRNAs are promiscuous, regulating numerous genes and pathways involved in a disease, making them useful therapeutic targets, but also difficult to study. miR-34a has been shown to increase in the serum, liver, pancreas, and subcutaneous (sc)WAT of patients with obesity, non- alcoholic fatty liver disease (NAFLD) and T2D. Additionally, miR-34a has been shown to regulate a number of metabolic and inflammatory genes in numerous cell types, including those in macrophages. However, the role of miR-34a in regulating vWAT metabolism and inflammation is poorly understood. Hypothesis: miR-34a is dysregulated in the adipose tissue during obesity, causing dysregulation of metabolic and inflammatory pathways in adipocytes and ATMs that contribute to adipose inflammation and obesity’s comorbidities, particularly T2D. Method/Results: The role of miR-34a in adipose inflammation was investigated using a murine miR-34a-/- diet-induced obesity model, and primary in vitro models of adipocyte differentiation and inflammatory bone marrow-derived macrophages (BMDMs). miR-34a was shown to be ubiquitously expressed throughout the murine epididymal (e)WAT of obese high-fat diet (HFD)-fed WT mice and ob/ob mice, as well as omental WAT from patients with obesity. Additionally, miR-34a transcripts were increased in the liver and brown adipose tissue (BAT) of ob/ob and HFD-fed WT mice, compared to WT controls. When miR-34a-/- mice were fed HFD ad libitum for 24 weeks they were significantly heavier than their WT counterparts by the end of the study. Ex vivo examinations showed that miR-34a-/- eWAT had a smaller adipocyte area on chow, which significantly increased to WT levels during HFD-feeding. Additionally, miR-34a-/- eWAT showed basal increases in cholesterol and fatty acid metabolism genes Cd36, Hmgcr, Lxrα, Pgc1α, and Fasn. miR-34a-/- iBAT showed basal reductions in Cebpα and Cebpβ, with increased Pgc1α expression during HFD- feeding. The miR-34a-/- liver additionally showed increased basal transcript expression of Pgc1α, suggesting miR-34a may broadly regulate PGC1α. Accompanying the ex vivo changes in cholesterol and fatty acid metabolism genes, in vitro miR-34a-/- white adipocytes showed increased lipid content. An F4/80high macrophage population was identified in HFD-fed miR-34a-/- eWAT, with increased Il-10 transcripts and serum IL-5 protein. Following these ex vivo observations, BMDMs from WT mice upregulated miR-34a expression in response to TNFα stimulation. Additionally, miR-34a-/- BMDMs showed an ablated CXCL1 response to TNFα. Conclusion: These findings suggest miR-34a has a multi-factorial role in controlling a susceptibility to obesity, by regulating inflammatory and metabolic pathways, potentially through regulation of PGC1α.