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Background Alcohol use is a leading risk factor for death and disability and there is a need for evidence-based policy measures to tackle excess alcohol consumption and related harms. The aim of this study was to examine attitudes towards alcohol control measures among the general public in the context of significant reforms undertaken in the Irish alcohol policymaking landscape. Methods A representative household survey was conducted among individuals aged 18+ years in Ireland. Descriptive and univariate analyses were used. Results A total of 1069 participants took part (48% male) and there was broad support (>50%) for evidence-based alcohol policies. Support was strongest for a ban on alcohol advertising near schools and creches (85.1%) and for warning labels (81.9%). Women were more likely than men to support alcohol control policy measures while participants with harmful alcohol use patterns were significantly less likely to support these measures. Respondents with a greater awareness of the health risks of alcohol showed higher levels of support, while those who had experienced harms due to other people’s drinking showed lower support compared with those who had not experienced such harms. Conclusions This study provides evidence of support for alcohol control policies in Ireland. However, notable differences were found in levels of support according to sociodemographic characteristics, alcohol consumption patterns, knowledge of health risks and harms experienced. Further research on reasons behind public support towards alcohol control measures would be worthwhile, given the importance of public opinion in the development of alcohol policy.

Background There has been considerable debate around the liberalization of cannabis laws in many countries. Given recent changes in cannabis policy, and the current discussion regarding cannabis legalization in Ireland, the aim of this study was to examine changes in attitudes over time towards permitting recreational cannabis use. Methods We analyzed data from Ireland’s 2002/03 (n = 4918); 2006/07 (n = 4967); 2010/11 (n = 5119); 2014/15 (n = 5937); 2019/20 (n = 3982) National Drug Prevalence Surveys. Multivariable logistic regression analyses were used to examine factors associated with being in favour of the use of cannabis for recreational purposes. Results The results indicate that there is minority support for permitting recreational cannabis use, which ranged from 19.1% in 2006/07 to 29.9% in 2019/20. In multivariable analysis being male and living in Dublin were significant predictors of agreeing with recreational cannabis use, as were being either a recent or past cannabis user, knowing cannabis users, perceiving cannabis use as not being a great risk, and not disapproving of cannabis use. Subjects aged less than 35 years and those who had completed primary education only were significantly less likely to agree with permitting recreational cannabis use. Conclusion The results from this study indicate that there is minority support for allowing recreational cannabis use. Support was highest among recent cannabis users, consistent with previous studies. The relative lack of support for recreational cannabis use among younger respondents was surprising and warrants further research.

Background Public awareness of the carcinogenic effects of alcohol is low, particularly the association between alcohol use and the risk of developing breast cancer. Breast cancer is the third most common cancer in Ireland and alcohol use remains high. This study examined factors related to awareness of the association between alcohol use and breast cancer risk. Methods Using data from Wave 2 of the national Healthy Ireland Survey, a representative sample of 7,498 Irish adults aged 15 + years, descriptive and logistic regression analyses were conducted to investigate relationships between demographic characteristics, type of drinker and awareness of breast cancer risk. Results A low level of awareness of the risk of alcohol use (drinking more than the recommended low–risk limit) associated with breast cancer was found, with just 21% of respondents correctly identifying the relationship. Multivariable regression analyses found that factors most strongly associated with awareness were sex (female), middle age (45—54 years) and higher educational levels. Conclusion As breast cancer is a prevalent disease among women in Ireland, it is essential that the public, in particular women who drink, are made aware of this association. Public health messages that highlight the health risks associated with alcohol use, and which target individuals with lower educational levels, are warranted.

Purpose To assess relationships between the Dietary Approaches to Stop Hypertension (DASH), Mediterranean Diet (MD), Dietary Inflammatory Index (DII®) and Energy-adjusted DII (E-DII™) scores and pro-inflammatory cytokines, adipocytokines, acute-phase response proteins, coagulation factors and white blood cells. Methods This was a cross-sectional study of 1862 men and women aged 46–73 years, randomly selected from a large primary care centre in Ireland. DASH, MD, DII and E-DII scores were derived from validated food frequency questionnaires. Correlation and multivariate-adjusted linear regression analyses with correction for multiple testing were performed to examine dietary score relationships with biomarker concentrations. Results In fully adjusted models, higher diet quality or a less pro-inflammatory diet was associated with lower concentrations of c-reactive protein, neutrophils (all dietary scores), complement component 3 [C3], interleukin 6 [IL-6], tumour necrosis factor-alpha [TNF-α], white blood cell count [WBC], the neutrophil-to-lymphocyte ratio [NLR] (DASH, DII and E-DII), monocytes (DASH and DII) and resistin (DII and E-DII). After accounting for multiple testing, relationships with C3 (DASH: β = − 2.079, p = .011 and DII: β = 2.521, p = .036), IL-6 (DASH: β = − 0.063, p = .011), TNF-α (DASH: β = − 0.027, p = .034), WBC (DASH: β = − 0.028, p = .001 and DII: β = 0.029, p = .02), neutrophils (DASH: β = − 0.041, p = .001; DII: β = 0.043, p = .007; E-DII: β = 0.029, p = .009) and the NLR (DASH: β = − 0.035, p = .011) persisted. Conclusions Better diet quality, determined by the DASH score, may be more closely associated with inflammatory biomarkers related to health in middle- to older-aged adults than the MD, DII and E-DII scores.

BACKGROUND: Adverse childhood experiences (ACE) have been associated with poor later life health outcomes, including cardiovascular disease (CVD). Limited research investigating potential underlying biological mechanisms linking ACE to CVD exists, particularly regarding lipid biomarkers. OBJECTIVES: The aim of this study was to examine the associations between childhood adversity and unfavourable lipid profiles and derived atherogenic risk indices in a middle-to-older aged population. METHODS: This cross-sectional study includes 1820 participants from the Mitchelstown cohort (49% male) in Ireland. Participants' self-reported history of childhood adversity (overall and by subtypes household dysfunction, abuse and neglect) were assessed through a validated 10-item ACE questionnaire. Lipid profiles were determined and atherogenic risk indices including Castelli's Risk Index 1 and 2 (CRI-I and CRI-II), Atherogenic Coefficient (AC) and Atherogenic Index Plasma (AIP) were generated. Logistic regression analysed ACE associations with unfavourable lipid outcomes, controlling for potential confounders. RESULTS: ACE history (reported by 23% of sample), in particular childhood exposure to household dysfunction, was associated with later-life non-optimal TG and HDL-C concentrations and atherogenic risk indices CRI-II and AC in age and sex-adjusted models (all p

Summary Background and objectives Lipoprotein particle concentrations and size are associated with increased risk for atherosclerosis and premature cardiovascular disease. Studies also suggest that certain dietary behaviours may be cardioprotective. Limited comparative data regarding any dietary score/index-lipoprotein particle subclass associations exist. Thus, our objective was to assess relationships between the Dietary Approaches to Stop Hypertension (DASH), Health Eating Index-2015 (HEI-2015), Mediterranean Diet (MD) and Energy-adjusted Dietary Inflammatory Index (E-DII™) scores and plasma lipids and lipoprotein profiles to test the hypothesis that healthier diet (better quality and more anti-inflammatory) would be associated with a more favourable lipoprotein profile. Materials and methods This was a cross-sectional study of 1862 men and women aged 46–73 years, randomly selected from a large primary care centre in Ireland. DASH, HEI-2015, MD and E-DII scores were derived from food frequency questionnaires. Lipoprotein subclass particle concentrations and size were determined using nuclear magnetic resonance spectroscopy. Correlation and multivariate-adjusted linear regression analyses with correction for multiple testing were performed to examine dietary score relationships with lipoprotein particle subclasses. Results In fully adjusted models, higher diet quality or a more anti-inflammatory diet was associated with less large and medium very low-density lipoprotein (VLDL) (DASH and HEI-2015), intermediate-density lipoprotein (IDL) (DASH, MD and E-DII) and small high-density lipoprotein (HDL) (DASH, HEI-2015 and E-DII) particles. After accounting for multiple testing, relationships with large VLDL (DASH: β = -0.102, p = .037), IDL (DASH: β = -0.089, p = .037) and small HDL (DASH: β = -0.551, p = .014 and E-DII: β = 0.483, p = .019) concentrations persisted. Conclusions These findings provide evidence that better diet quality, determined by the DASH score, may be more closely associated with a more favourable lipoprotein particle subclass profile in middle-to older-aged adults than the HEI-2015, MD and E-DII scores. A less pro-atherogenic lipoprotein status may be a potential mechanism underlying the cardioprotective effects of higher dietary quality.

Background Accurately measuring BMI in large epidemiological studies is problematic as objective measurements are expensive, so subjective methodologies must usually suffice. The purpose of this study is to explore a new subjective method of BMI measurement: BMI self-selection. Methods A cross-sectional analysis of the Mitchelstown Cohort Rescreen study, a random sample of 1,354 men and women aged 51–77 years recruited from a single primary care centre. BMI self-selection was measured by asking patients to select their BMI category: underweight, normal weight, overweight, obese. Weight and height were also objectively measured. Results 79% were overweight or obese: 86% of males, 69% of females (P Conclusions BMI self-selection may be useful for self-reporting BMI. Clinicians need to be aware of disparities between BMI self-selection at higher and lower BMI levels among overweight/obese patients and encourage preventative action for those at the lower levels to avoid weight gain and thus reduce their all-cause mortality risk.

Objectives: A 24-hour day is made up of time spent in a range of physical activity (PA) behaviours, including sleep, sedentary time, standing, light-intensity PA (LIPA) and moderate-to-vigorous PA (MVPA), all of which may have the potential to alter an individual’s health through various different pathways and mechanisms. This study aimed to explore the relationship between PA behaviours and the gut microbiome in older adults. Design: Cross-sectional study. Settings and Participants: Participants (n=100; age 67.76 years [3.02]; 44% female) from the Mitchelstown Cohort Rescreen (MCR) Study (2015-2017). Methods: Participants provided measures of gut microbiome composition (profiled by sequencing 16S rRNA gene amplicons), and objective measures of PA behaviours (by a 7-day wear protocol using an activPAL3 Micro). Results: Standing time was positively correlated with the abundance of butyrate-producing and anti-inflammatory bacteria, including Ruminococcaceae, Lachnospiraceae and Bifidobacterium, MVPA was positiv ely associated with the abundance of Lachnospiraceae bacteria, while sedentary time was associated with lower abundance of Ruminococcaceae and higher abundance of Streptococcus spp Conclusion: Physical activity behaviours appear to influence gut microbiota composition in older adults, with different PA behaviours having diverging effects on gut microbiota composition. yes

Background: The Cork and Kerry Diabetes and Heart Disease Study was established to investigate the prevalence of diabetes and cardiovascular disease among middle-aged adults in Ireland. The Mitchelstown cohort was recruited from a single large primary care centre between 2010–2011. A rescreen of this cohort was conducted in 2015. Methods: Data were collected on cardiovascular health and associated risk factors. In addition, the rescreen incorporated new measures which included information on cognition and frailty, medication adherence, dietary factors and the collection of stool samples with RNA sequencing of the gut microbiome. Results: Of 2047 participants in the original cohort, 237 (11.6%) were deceased, too ill to participate or were lost to follow-up. Of the remaining 1810 baseline study participants, 1378 men and women aged 51–77 years agreed to take part in the rescreen (response rate of 76.1%). The prevalence of hypertension was high, ranging from 50% to 64% depending on the measurement method. An investigation of the association of gut microbiota with metabolic syndrome and obesity indicated greater microbiome diversity in metabolically healthy non-obese individuals relative to their unhealthy counterparts. Analysis of prescribing data over time demonstrated a high prevalence of potentially inappropriate prescribing among older-aged people in primary care which increased as they progressed to more advanced old age. Conclusions: The rescreen has provided new insights into cardiovascular health. In addition, this study is embedded in a single primary care centre, enabling passive follow-up of study participants through electronic health records. All data collected at baseline and rescreen are maintained and stored at the School of Public Health, University College Cork and specific proposals for future collaborations are welcome.

Background Knowledge of factors relating to patterns of cannabis use is important for informing drug policy. This study determined factors associated with recent and current cannabis use. In addition, we explored factors related to having a cannabis use disorder (CUD)—defined using the Diagnostic and Statistical Manual of Psychiatric Disorders—among current users. Methods We analyzed data from Ireland’s 2010–11 and 2014–15 National Drug Prevalence Surveys, which recruited 5134 and 7005 individuals respectively, aged 15 years or more, living in private households. Multinomial logistic regression was used to identify factors associated with recent (last year) and current (last month) cannabis use compared to experiential use. Binary logistic regression was used to determine factors related to CUD among current users. Results The weighted prevalence of experiential cannabis use was 18.3%, with 3.0% and 3.3% of participants indicating recent or current use, respectively; 41.3% of current users indicated having a CUD. Factors associated with both recent or current cannabis use included younger age, not being married or cohabiting, having no dependent children and current use of tobacco or alcohol. Male gender, younger age and lower educational levels were significantly related to CUD among current users. Conclusions Males, adolescents/young adults and individuals with lower educational levels are more likely to be current users of cannabis and are at a greater risk of having a CUD. Health professionals should be aware of these factors to improve detection and prevention of CUD.

Low-grade systemic inflammation is associated with a range of conditions. Diet may modulate inflammation and public health strategies are needed to guide consumers’ dietary choices and help prevent diet-related disease. The Food Standards Agency nutrient profiling system (FSAm-NPS) constitutes the basis of the five-colour front-of-pack Nutri-Score labelling system. No study to date has examined FSAm-NPS dietary index associations with biomarkers of inflammation. Therefore, our objective was to test relationships between the FSAm-NPS and a range of inflammatory biomarkers in a cross-sectional sample of 2006 men and women aged 46–73 years. Individual participant FSAm-NPS scores were derived from food frequency questionnaires. Pro-inflammatory cytokine, adipocytokine, acute-phase response protein, coagulation factor and white blood cell count concentrations were determined. Correlation and linear regression analyses were used to examine FSAm-NPS relationships with biomarker levels. In crude and adjusted analyses, higher FSAm-NPS scores, reflecting poorer nutritional quality, were consistently and positively associated with biomarkers. In fully adjusted models, significant associations with concentrations of complement component 3, c-reactive protein, interleukin 6, tumour necrosis factor alpha, resistin, white blood cell count, neutrophils, eosinophils and the neutrophil-to-lymphocyte ratio persisted. These results suggest that dietary quality, determined by Nutri-Score rating, is associated with inflammatory biomarkers related to health.

Background and objectives Epidemiological studies show that the use of cannabis is related to the use of other illicit drugs, including stimulants such as cocaine and ecstasy. However, few studies have examined how patterns of cannabis use relate to the use of stimulants. In this research we determined relationships between patterns of cannabis use and recent stimulant use, drawing on data from two large nationally representative surveys. We also explored how frequency of cannabis use relates to stimulant use and whether subjects with a cannabis use disorder (CUD)–defined as cannabis abuse or dependence–are more likely to be recent users of cocaine or ecstasy. Materials and methods We analysed data from Ireland’s 2010/11 and 2014/15 National Drug Prevalence Surveys,which recruited 5,134 and 7,005 individuals respectively, aged 15 years and over, living in private households. We included only those people who reported some past cannabis use. Multivariable logistic regression analysis was used to examine associations between patterns of cannabis use and recent stimulant use. Results Among survey participants who had used cannabis in the last month, 17.9% reported recent cocaine use, while almost one-quarter (23.6%) reported recent ecstasy use. There was a significant linear relationship between patterns of cannabis use and recent use of cocaine, ecstasy or any stimulant, with last month cannabis users displaying greater odds (OR = 12.03, 95% CI: 8.15–17.78) of having recent stimulant use compared to last year (OR = 4.48, 95% CI: 2.91–6.91) and former (reference) cannabis users. Greater frequency of cannabis use in the last 30 days was also significantly related to the use of stimulants. In addition, results demonstrated an association between CUD and recent use of cocaine or ecstasy (OR = 2.28, 95% CI: 1.55–3.35). Conclusions Findings from this study suggest a relationship between patterns and frequency of cannabis use and recent use of stimulants and an association between CUD and stimulant use. As the use of cannabis with stimulants may increase the risk of negative health consequences, education in community and medical settings about polydrug use and its increased risks may be warranted.

Background From a secondary prevention perspective, it is useful to know who is at greatest risk of progressing from substance initiation to riskier patterns of future use. Therefore, the aim of this study was to determine relationships between age at first use of alcohol, tobacco and cannabis and patterns of cannabis use, frequency of use and whether age of substance use onset is related to having a cannabis use disorder (CUD). Methods We analysed data from Ireland’s 2010/11 and 2014/15 National Drug Prevalence Surveys, which recruited 5134 and 7005 individuals respectively, aged 15 years and over, living in private households. We included only those people who reported lifetime cannabis use. Multinomial, linear and binary logistic regression analyses were used to determine relationships between age of substance use onset and patterns of cannabis use, frequency of use and having a CUD. Results When compared to former users, the odds of being a current cannabis user were found to be reduced by 11% (OR = 0.89; 95% CI: 0.83, 0.95) and 4% (OR = 0.96; 95% CI: 0.92, 1.00) for each year of delayed alcohol and cannabis use onset, respectively. Among current users, significant inverse linear relationships were noted, with increasing age of first use of tobacco (β = − 0.547; P P Conclusions Among people who report past cannabis use, it is those with a more precocious pattern of early use of substances, including alcohol, and especially tobacco and cannabis, who are more likely to report ongoing, heavy and problematic cannabis use. Secondary prevention initiatives should prioritise people with a pattern of very early onset substance use.

Introduction: Given the increased prevalence of cannabis use in Ireland and increase in cannabis potency, this study aimed to estimate the size of the potential population in Ireland that may be in need of cannabis treatment and the percentage of people with cannabis use disorder (CUD) who actually access treatment. We also compared the profile of those with CUD in the general population to those who receive treatment for their cannabis use to explore whether certain subgroups are more or less likely to enter treatment. Method: This was a retrospective, multi-source database study. Data were obtained from (1) Ireland’s 2014/2015 national general population survey (GPS) on drug use and (2) treatment data from the Irish National Drug Treatment Reporting System (NDTRS) for 2015. The profiles of GPS cases with CUD and NDTRS cases were compared using 2-sided t tests designed for independent samples. Results: The prevalence of last year cannabis use among adults aged 15 and older was 6.5% and the prevalence of CUD was 2.6%, representing 94,515 of the Irish population. A total of 4,761 cases entered treatment for problem cannabis use. NDTRS treatment cases were significantly more likely than GPS cases to be unemployed (63.7% vs. 26.6%) and have no or primary level only educational attainment (56.3% vs. 21.2%). Over half (53.3%) of NDTRS cases first used cannabis before the age of 15 years, compared to 14.7% of CUD cases in the population. Discussion/Conclusion: Our findings suggest that earlier users and those with more complex or disadvantaged lives are more likely to seek treatment. A broad population health approach that engages multiple sectors such as health, social welfare, and education is recommended to ensure that there is increased opportunity for people with CUD to be identified and signposted towards treatment.

BACKGROUND/OBJECTIVES Certain lifestyle behaviours may have a protective effect against low-grade systemic inflammation, which is linked to chronic disease. Our objective was to examine associations between a five-component protective lifestyle behaviour (PLB) score and a range of pro-inflammatory cytokines, adipocytokines, acute-phase response proteins, coagulation factors and white blood cells. SUBJECTS/METHODS This was a cross-sectional study of 2045 middle-to-older aged men and women. Low-risk behaviours included never smoking, moderate alcohol intake, moderate-to-vigorous physical activity, a high-quality diet (upper 40% Dietary Approaches to Stop Hypertension score) and a normal body mass index (BMI) (18.5-24.9 kg/m2). Linear and logistic regression analyses tested individual protective behaviour and PLB score associations with biomarkers. RESULTS Analysis of individual low-risk behaviours revealed varied associations depending on the biomarker, with normal BMI showing the most consistent associations. Examination of the PLB score showed that compared to subjects with 4-5 protective behaviours, those with 0-1 protective behaviours had 1.4-3.8 increased odds of having a less favourable inflammatory profile. Following adjustment for BMI, significant trend relationships were observed between the number of protective behaviours and complement component 3 (P

Background and objectives Type 2 diabetes is a leading cause of death and disability worldwide and pre-diabetes is a strong predictor of diabetes development. To date, studies estimating the prevalence of pre-diabetes in the Irish population are sparse and conflicting. Monitoring the prevalence of pre-diabetes and a knowledge of associated factors is required to inform policies and to prevent development of type 2 diabetes. Therefore, this research examined the prevalence and correlates of pre-diabetes in a sample of middle- to older-aged Irish adults using three different methods for diagnosis. Materials and methods The Mitchelstown Cohort Rescreen (2016/17) was a follow-up, cross-sectional study of the Mitchelstown Cohort Study (2010/11). 1,378 participants were recruited from a random sample of patients attending a single primary care centre. Pre-diabetes was defined using three diagnostic criteria: American Diabetes Association (ADA) glycated haemoglobin A1c (HbA1c) cut-offs between 5.7%–6.4% (39–46 mmol/mol), World Health Organization International Expert Committee (WHO-IEC) HbA1c cut-offs between 6.0%–6.4% (42–46 mmol/mol) and ADA fasting plasma glucose (FPG) cut-offs between 5.6–6.9 mmol/l. Univariate and multivariable logistic regression analyses were used to determine factors associated with pre-diabetes. Results The prevalence of pre-diabetes was found to be 43.9% (95% CI: 41.2%─46.5%), 14.5% (95% CI: 12.7%─16.5%) and 15.8% (95% CI: 13.9%─17.8%) according to HbA1c ADA, HbA1c WHO-IEC and FPG ADA definitions, respectively. Depending on diagnostic method, factors associated with pre-diabetes in univariate analyses included sex, age, marital status, health rating, education and poor diet quality. In multivariable analysis, subjects classified by the FPG ADA pre-diabetes criterion displayed the least optimal metabolic profile defined by overweight and obesity (OR = 2.88, 95% CI: 1.53–5.43), hypertension (OR = 2.27, 95% CI: 1.51–3.40) and low high-density lipoprotein cholesterol concentrations (OR = 1.75, 95% CI: 1.07–2.87). Conclusions The discordance between prevalence estimates according to method of diagnosis is concerning. A National Diabetes Prevention Programme is currently being developed in Ireland. Monitoring the prevalence of pre-diabetes over time will be important to assess the effectiveness of this programme. This study will inform national decision-makers on which definition of pre-diabetes to use for monitoring purposes.

Low-grade systemic inflammation is associated with a range of chronic diseases. Diet may modulate inflammation and represents a promising therapeutic target to reduce metabolic dysfunction. To date, no study has examined Healthy Eating Index-2015 (HEI-2015) diet score associations with biomarkers of inflammation. Thus, our objective was to assess relationships between the HEI-2015 score and a range of inflammatory biomarkers in a cross-sectional sample of 1989 men and women aged 46&ndash, 73 years, to test the hypothesis that better dietary quality would be associated with more favourable circulating levels of inflammatory biomarkers. Pro-inflammatory cytokines, adipocytokines, acute-phase response proteins, coagulation factors and white blood cell counts were determined. Correlation and linear regression analyses were used to test HEI-2015 diet score relationships with biomarker concentrations. Higher dietary quality as determined by the HEI-2015 was associated with lower c-reactive protein (CRP) and interleukin 6 concentrations, white blood cell (WBC) counts and its constituents, adjusting for sex and age. Associations with CRP concentrations and WBC counts persisted in the fully adjusted models. No associations with complement component 3, tumour necrosis factor alpha, adiponectin, leptin, resistin or plasminogen activator inhibitor-1 levels were identified. Our data suggest that dietary quality, determined by the HEI-2015 score, in middle-to-older aged adults is associated with inflammatory biomarkers related to cardiometabolic health.

Background and aims: Lipoprotein particle size is associated with increased atherosclerosis and cardiovascular disease risk. Certain lifestyle behaviours may be cardioprotective. We examined lipoprotein particle size and concentration relationships with a protective lifestyle behaviour (PLB) score. Methods: This was a cross-sectional analysis of 2045 middle-to older-aged adults. Lipoprotein particle subclass size and concentrations were determined using nuclear magnetic resonance spectroscopy. Five protective behaviours included never smoking, moderate alcohol intake, moderate to vigorous physical activity, a high-quality diet (upper 40% Dietary Approaches to Stop Hypertension score) and a normal body mass index (BMI) (18.5–24.9 kg/m2). Linear and logistic regression analyses tested individual protective behaviour and PLB score associations with lipoprotein subclasses. Results: Individual behaviour associations varied according to lipoprotein subclass, with normal BMI showing the greatest number of significant relationships. Logistic regression analyses revealed that subjects with the fewest number of protective behaviours had 1.4–2.8 increased odds of having less favourable lipoprotein profiles defined as above or below median level lipoprotein particle subclass size or concentration. Following additional adjustment for BMI, significant trend relationships were observed between the PLB score and large and medium very low-density lipoprotein (p = 0.001 and p < 0.001), total and smaller low-density lipoprotein (LDL) concentrations (p = 0.008 and p < 0.001), LDL size (p = 0.003) and a lipoprotein insulin resistance score (p = 0.003). Conclusions: Results show a cumulative protective effect of healthy lifestyle behaviours against an unfavourable potentially pro-atherogenic lipoprotein profile in middle-to older-aged adults, highlighting the importance of lifestyle promotion in healthy ageing.

Emerging evidence links the gut microbiota with several chronic diseases. However, the relationships between metabolic syndrome (MetS), obesity and the gut microbiome are inconsistent. This study aimed to investigate associations between gut microbiota composition and diversity and metabolic health status in older adults (n = 382, median age = 69.91 [&plusmn, 5 years], male = 50.79%) with and without obesity. Gut microbiome composition was determined by sequencing 16S rRNA gene amplicons. Results showed that alpha diversity and richness, as indicated by the Chao1 index (p = 0.038), phylogenetic diversity (p = 0.003) and observed species (p = 0.038) were higher among the metabolically healthy non-obese (MHNO) individuals compared to their metabolically unhealthy non-obese (MUNO) counterparts. Beta diversity analysis revealed distinct differences between the MHNO and MUNO individuals on the phylogenetic distance scale (R2 = 0.007, p = 0.004). The main genera contributing to the gut composition among the non-obese individuals were Prevotella, unclassified Lachnospiraceae, and unclassified Ruminococcaceae. Prevotella, Blautia, Bacteroides, and unclassified Ruminococcaceae mainly contributed to the variation among the obese individuals. Co-occurrence network analysis displayed different modules pattern among different metabolic groups and revealed groups of microbes significantly correlated with individual metabolic health markers. These findings confirm relationships between metabolic health status and gut microbiota composition particularly, among non-obese older adults.

ObjectivesIreland has high per capita alcohol consumption and also has high levels of problematic drinking patterns. While it is accepted that patterns of alcohol consumption in Ireland are a cause for concern, it is not clear if Irish people are actually aware of the extent of their hazardous or harmful pattern of drinking. The aim of this study was to determine awareness of drinking pattern in an Irish population using a representative random sample and to identify characteristics associated with self-awareness of hazardous or harmful drinking.MethodsWe analysed data from Ireland’s 2014/2015 Drug Prevalence Survey which recruited a stratified clustered sample of 7005 individuals aged 15 years and over living in private households. Logistic regression analysis was used to determine characteristics associated with self-awareness of hazardous or harmful drinking.ResultsAlmost one half of drinkers had a hazardous or harmful pattern of drinking; 38% engaged in monthly risky single occasion drinking (RSOD) and 10.5% met Diagnostic and Statistical Manual version IV (DSM-IV) criteria for alcohol dependence. Of the 2420 respondents who had a hazardous or harmful pattern of drinking, 67% were unaware of this and misclassified themselves as being either a light or moderate drinker who did not engage in RSOD. An adjusted logistic regression model identified that hazardous and harmful drinkers were more likely to be aware of their drinking pattern if they had completed third level education (OR=1.80, 95% CI: 1.30 to 2.49) while older drinkers (aged 65 and over) were less likely to be aware of their drinking pattern (OR=0.30, 95% CI: 0.14 to 0.65). Subjects who engaged in risk taking behaviours such as illicit drug use and gambling were also significantly more likely to be aware of their drinking pattern.ConclusionsThe results of this study suggest that patterns of alcohol use in Ireland are problematic. Older respondents and those with lower educational attainment are less likely to be aware of their hazardous or harmful drinking pattern. There is also a population of younger, more-educated drinkers who engage in potentially risk-taking behaviours and these subjects are aware of their harmful drinking pattern. Initiatives to reduce overall alcohol consumption and raise awareness around drinking patterns are required.

Background and ObjectivesCognitive impairment among the elderly is an important concern worldwide. Evidence suggests that certain lifestyle behaviours may have a protective effect against cognitive decline. In this study we examined the relationship between a 5-component protective lifestyle behaviour score and cognitive function to determine whether the number of protective lifestyle behaviours is related to cognitive decline.Materials and MethodsThis was a cross-sectional analysis of the Mitchelstown Cohort Rescreen study, a random sample of men and women aged 51–77 years recruited from a single primary care centre. Cognitive function was assessed using the Mini Mental State Exam (MMSE) and cognitive data were available for 1,022 participants. Cognitive impairment was classified as an upper 75th percentile reversed MMSE score value for the study sample. We defined 5 low-risk protective lifestyle behaviours as never smoking, moderate alcohol intake, moderate to vigorous physical activity, a high-quality diet score (upper 40%) and a body mass index between 18.5 to 24.9 kg/m2. Linear and logistic regression analyses were used to test associations between a protective factor score and the MMSE.ResultsThere was a linear relationship between the number of protective lifestyle behaviours and mean cognitive score values and a significant inverse association was observed between a protective lifestyle score and the MMSE cognitive score (β = -0.20, 95% CI: -0.30, -0.10). Logistic regression suggested a dose-response relationship, with odds ratios of having poorer cognitive functioning being noticeably increased in subjects with 0 or 1 PLBs (OR = 2.18, 95% CI: 1.06, 4.52) when compared to participants with 4 or 5 PLBs in multivariable analysis.ConclusionsThese data imply that a combination of healthy lifestyle behaviours protects against cognitive impairment. As all of the examined factors are modifiable, small behavioural changes may help in preventing cognitive decline in an elderly population.

Background and aims: Acute myeloid leukaemia (AML) is a relatively rare haematological malignancy which is the most common acute leukaemia in adults. Patients with AML often have a substantial comorbidity burden. Consequently, different scores are used in clinical practice to predict outcomes in patients with multiple comorbidities. The Charlson Comorbidity Index (CCI), calculated based on 19 different medical conditions, weighs the comorbidities to measure a patient's burden of disease. Previous publications have suggested that the CCI may be useful in determining survival in AML patients. However, the CCI is not in routine use in Ireland for assessing patients with AML. In this study we examined the usefulness of the CCI to predict early mortality in AML patients, drawing on data from the Extended Blood Cancer Registration (EBCR) in Ireland. Methods: The EBCR was undertaken by National Cancer Registry Ireland registrars trained by consultant haematologists and deployed in national centres. Data collection began in 2017 and continued to 2019; 141 AML patients underwent extended data registration. Comorbidities were identified by ICD-9 codes and chart review. Kaplan Meier curves and Cox regression analyses were used to determine the usefulness of the CCI to predict early mortality in AML patients. Results: Of the 141 AML patients, 82% were between 50 and 70 years of age and 84 had died by 31/12/2019 (median survival time = 289.0 days). The median survival time for patients in the lowest tertile of the CCI was 498.5 days, compared to 246.0 and 116.5 days for subjects in tertiles 2 and 3, respectively (Figure 1. Log rank P-value Conclusions: Although results demonstrate a strong relationship between the CCI and early mortality in AML patients, our findings suggest that the CCI provides little or no additional prognostic information beyond that which is obtained from age at AML diagnosis alone. This study highlights the importance of validating risk assessment tools in order to determine their potential usefulness in a clinical setting and emphasise the importance of weighing in the treatment decision making paradigm. The Blood Cancer Network Ireland (BCNI) thank the Science Foundation of Ireland (SFI) and the Irish Cancer Society (ICS) for funding (2015-2021). We also thank our colleagues in the National Cancer Registry Ireland for assistance, advice and guidance. Figure 1 Figure 1. Disclosures Quinn: Takeda: Honoraria. O'Dwyer: Bristol Myers Squibb: Research Funding; Janssen: Consultancy; ONK Therapeutics: Current Employment, Current equity holder in publicly-traded company, Membership on an entity's Board of Directors or advisory committees. Szegezdi: ONK Therapeutics: Research Funding.

Background: Type 2 diabetes (T2DM) is a significant cause of morbidity and mortality, thus early identification is of paramount importance. A high proportion of T2DM cases are undiagnosed highlighting the importance of effective detection methods such as non-invasive diabetes risk scores (DRSs). Thus far, no DRS has been validated in an Irish population. Therefore, the aim of this study was to compare the ability of nine DRSs to detect T2DM cases in an Irish population. Methods: This was a cross-sectional study of 1,990 men and women aged 46–73 years. Data on DRS components were collected from questionnaires and clinical examinations. T2DM was determined according to a fasting plasma glucose level ≥7.0 mmol/l or a glycated haemoglobin A1c level ≥6.5% (≥48 mmol/mol). Receiver operating characteristic curve analysis assessed the ability of DRSs and their components to discriminate T2DM cases. Results: Among the examined scores, area under the curve (AUC) values ranged from 0.71–0.78, with the Cambridge Diabetes Risk Score (AUC=0.78, 95% CI: 0.75–0.82), Leicester Diabetes Risk Score (AUC=0.78, 95% CI: 0.75–0.82), Rotterdam Predictive Model 2 (AUC=0.78, 95% CI: 0.74–0.82) and the U.S. Diabetes Risk Score (AUC=0.78, 95% CI: 0.74–0.81) demonstrating the largest AUC values as continuous variables and at optimal cut-offs. Regarding individual DRS components, anthropometric measures displayed the largest AUC values. Conclusions: The best performing DRSs were broadly similar in terms of their components; all incorporated variables for age, sex, BMI, hypertension and family diabetes history. The Cambridge Diabetes Risk Score, had the largest AUC value at an optimal cut-off, can be easily accessed online for use in a clinical setting and may be the most appropriate and cost-effective method for case-finding in an Irish population.

Background Accurately measuring BMI in large epidemiological studies is problematic as objective measurements are expensive, so subjective methodologies must usually suffice. A number of subjective methodologies have been shown to be inaccurate, resulting in misclassification to a lower BMI category and a subsequent underestimation of obesity prevalence. The purpose of this study is to explore a new subjective method of measuring BMI, BMI perception. Methods A cross-sectional analysis of the Mitchelstown Cohort Rescreen study, a random sample of 1 354 men and women aged 51–77 years recruited from a single primary care centre. Data were collected using self-administered questionnaires. BMI perception was measured by asking “Do you think you are underweight, normal weight, overweight or obese?” Weight and height were also objectively measured. Results 79% of the cohort were overweight or obese: 86% of males, 69% of females, P

Background According to the prevention paradox, the majority of alcohol-related harms in the population occur among low-to-moderate risk drinkers, simply because they are more numerous in the population, although high-risk drinkers have a higher individual risk of experiencing alcohol-related harms. In this study we explored the prevention paradox in the Irish population by comparing alcohol-dependent drinkers (high-risk) to low-risk drinkers and non-dependent drinkers who engage in heavy episodic drinking (HED). Methods Data were generated from the 2013 National Alcohol Diary Survey (NADS), a nationally representative cross-sectional survey of Irish adults aged 18–75. Data were available for 4338 drinkers. Respondents dependent on alcohol (as measured by DSM-IV criteria), respondents who engaged in monthly HED or occasional HED (1–11 times a year) and low-risk drinkers were compared for distribution of eight alcohol-related harms. Results Respondents who were dependent on alcohol had a greater individual risk of experiencing each harm (p Conclusions Our results indicate that the majority of alcohol consumption and related harms in the Irish population are accounted for by low- and moderate-risk drinkers, and specifically by those who engage in heavy episodic drinking. A population-based approach to reducing alcohol-related harm is most appropriate in the Irish context. Immediate implementation of the measures in the Public Health (Alcohol) Act (2018) is necessary to reduce alcohol-related harm in Ireland.

Background A definition of metabolic syndrome (MetS) has been recommended as a tool to help identify individuals at risk of developing type 2 diabetes. However, an agreed protocol for defining MetS does not exist and some studies have shown MetS definitions to be inferior at predicting diabetes compared to a single measurement of fasting glucose. In this study we examined the ability of five proposed MetS definitions to discriminate incident cases in order to determine whether MetS more accurately predicts type 2 diabetes. Methods This was a prospective study involving a random sample of 1,754 men and women aged 46–73 years. Receiver operating characteristic curve and net reclassification improvement (NRI) analyses were used to evaluate the ability of MetS definitions and components to accurately classify high-risk subjects. Results A model including proposed MetS components displayed a significantly (P=0.02) higher area under the curve (AUC) to discriminate diabetes (AUC=0.90, 95% CI: 0.87–0.93) compared to fasting glucose alone (AUC=0.88, 95% CI: 0.83–0.92). Models using the European Group for the Study of Insulin Resistance MetS criterion, and which included glucose as a mandatory component, demonstrated significant overall NRI when compared to recommended and optimal fasting glucose cut-offs. A final model had a sensitivity of 0.91 and a specificity of 0.73. Conclusion In this population there is evidence that a combination of MetS components may help predict diabetes beyond that which is measured by glucose alone. Proposed MetS definitions should include fasting glucose as a mandatory component.

Background: It is challenging to measure BMI accurately in population studies because it is an expensive and time-consuming task. As a result, subjectively measured BMI, calculated from self-reported height and weight, which we know to be inaccurate, is often used. The purpose of this study is to determine whether using a different, subjective method of measuring BMI, BMI self-selection, would be more accurate. BMI self-selection is determined by asking participants to place themselves in one of the BMI categories, underweight, normal weight, overweight or obese. Methods: A quantitative survey conducted in the outpatient departments of two hospitals in the South West of Ireland. Participants >18 years were included. Pregnant women were excluded. The final sample included 70 participants. Survey completion, including self-reported height and weight and BMI self-selection, preceded the objectively measured weight and height. Demographic and lifestyle factors were also recorded. Results: 59% of the sample were overweight or obese –63% of females and 54% of males. The sensitivity for correct BMI self-selection for normal weight, overweight and obese categories was 90%, 36% and 33% respectively. The sensitivity for BMI categories calculated from self-reported height and weight was 83%, 57% and 59% respectively. In analysis, age, regular alcohol consumption, unhealthy diet and lower levels of physical activity were all associated with underestimation of BMI. Conclusion: BMI self-selection is an accurate tool when used with normal weight individuals but shows poorer ability to demonstrate accurate measurement in overweight and obese BMI categories. It is inferior to the traditional self-reported BMI method for measuring BMI levels in the general population. Presently, we recommend continuing with self-reported BMI for BMI measurement in large population studies. However, further testing of BMI classification in larger studies is suggested and investigation into alternative objective methods of measurement is warranted.

Background: The prevalence of overweight and obesity among children may have reached a plateau in some developed countries, including Ireland. The aim of this study was to examine 12-year trends in the prevalence of overweight and obesity among primary-school-aged children in the Republic of Ireland between 2002 and 2014. Methods: Two large-scale oral health cross-sectional surveys of primary-school-aged children aged 4–13 years were conducted 12 years apart in 2002 (n=14,055; response rate=68%) and 2014 (n=5,223; response rate=67%). Both surveys included standardised and calibrated height and weight measures. Ownership of a means-tested medical card determined economic status. Standard International Obesity Task Force criteria were applied to determine the prevalence of overweight and obesity. Results: The overall prevalence of overweight/obesity among 4–13-year-olds significantly decreased from 26% (95% CI: 25.1%–26.5%) in 2002 to 24% (95% CI: 22.4%–24.7%) in 2014. Among boys and girls aged 4–13 years, the significant decrease was from 23% (95% CI: 22.1%–24.1%) to 20% (95% CI: 18.9%–22.0 and 28% (95% CI: 27.4%–29.5%) to 27% (95% CI: 25.0%–28.4%), respectively. Among 5-year-old children, the overall prevalence of overweight and obesity significantly decreased from 25% (95% CI: 23.7%–26.2%) to 22% (95% CI: 19.9%–23.4%). In 2002, the estimated prevalence of overweight/obesity was similar in children with and without medical cards, whereas in 2014, overall prevalence was higher in those with medical cards. Conclusions: Results suggest a fall in the prevalence of overweight/obesity between 2002 and 2014, and may suggest a favourable cohort effect. Despite this fall, the overall prevalence remains high and socioeconomic disparities have increased.

Background Despite the increased global awareness of childhood obesity, a high proportion of parents and children continue to misclassify child weight status. The aim of this study was to determine parent and child misperception of child weight and identify the determinants influencing this misperception. Methods A cross-sectional study involving 1 075 children, aged 8–11 years, drawn from primary schools in Cork city and county in Ireland. Data were collected using child and parent self-administered questionnaires. Physical measurements were taken by trained researchers according to standard procedures. Univariate and multivariable logistic regression analysis was used to examine factors influencing parental and child perceptions regarding child weight. Results Almost one-quarter of parents of all children misclassified their child’s weight status. Forty four per cent of parents of overweight or obese children underestimated their child’s weight. In all children, factors associated with parental misperception of child weight included the child being female (OR=1.95; 95% CI 1.36 to 2.81, p Conclusion Findings suggest that in an obesogenic society, where overweight and obesity has become the norm, the capacity of both parents and children to correctly classify child weight status is significantly impaired. Health care professionals should be aware of the frequent misperception of weight status, especially when dealing with parents of younger children and children who are overweight or obese.

Background A novel obesity classification method has been proposed using body mass index (BMI) and waist–height ratio (WHtR) together. However, the utility of this approach is unclear. In this study we compare the metabolic profiles in subjects defined as overweight or obese by both measures. We examine a range of metabolic syndrome features, pro-inflammatory cytokines, acute-phase response proteins, coagulation factors and white blood cell counts to determine whether a combination of both indices more accurately identifies individuals at increased obesity-related cardiometabolic risk. Methods This was a cross-sectional study involving a random sample of 1856 men and women aged 46–73 years. Metabolic and anthropometric profiles were assessed. Linear and logistic regression analyses were used to compare lipid, lipoprotein, blood pressure, glycaemic and inflammatory biomarker levels between BMI and WHtR tertiles. Multinomial logistic regression was performed to determine cardiometabolic risk feature associations with BMI and WHtR groupings. Receiver operating characteristic curve analysis was used to evaluate index discriminatory ability. Results The combination of BMI and WHtR tertiles identified consistent metabolic variable differences relative to those characterised on the basis of one index. Similarly, odds ratios of having cardiometabolic risk features were noticeably increased in subjects classified as overweight or obese by both measures when compared to study participants categorised by either BMI or WHtR separately. Significant discriminatory improvement was observed for detecting individual cardiometabolic risk features and adverse biomarker levels. In a fully adjusted model, only individuals within the highest tertile for both indices displayed a significant and positive association with pre-diabetes, OR: 3.4 (95 % CI: 1.9, 6.0), P

Objectives Glycated haemoglobin A1c (HbA1c) measurement is recommended as an alternative to fasting plasma glucose (FPG) for the diagnosis of pre-diabetes and type 2 diabetes. However, evidence suggests discordance between HbA1c and FPG. In this study we examine a range of metabolic risk features, pro-inflammatory cytokines, acute-phase response proteins, coagulation factors and white blood cell counts to determine which assay more accurately identifies individuals at increased cardiometabolic risk. Materials and Methods This was a cross-sectional study involving a random sample of 2,047 men and women aged 46-73 years. Binary and multinomial logistic regression were employed to examine risk feature associations with pre-diabetes [either HbA1c levels 5.7-6.4% (39-46 mmol/mol) or impaired FPG levels 5.6-6.9 mmol/l] and type 2 diabetes [either HbA1c levels >6.5% (>48 mmol/mol) or FPG levels >7.0 mmol/l]. Receiver operating characteristic curve analysis was used to evaluate the ability of HbA1c to discriminate pre-diabetes and diabetes defined by FPG. Results Stronger associations with diabetes-related phenotypes were observed in pre-diabetic subjects diagnosed by FPG compared to those detected by HbA1c. Individuals with type 2 diabetes exhibited cardiometabolic profiles that were broadly similar according to diagnosis by either assay. Pre-diabetic participants classified by both assays displayed a more pro-inflammatory, pro-atherogenic, hypertensive and insulin resistant profile. Odds ratios of having three or more metabolic syndrome features were also noticeably increased (OR: 4.0, 95% CI: 2.8-5.8) when compared to subjects diagnosed by either HbA1c (OR: 1.4, 95% CI: 1.2-1.8) or FPG (OR: 3.0, 95% CI: 1.7-5.1) separately. Conclusions In middle-aged Caucasian-Europeans, HbA1c alone is a poor indicator of cardiometabolic risk but is suitable for diagnosing diabetes. Combined use of HbA1c and FPG may be of additional benefit for detecting individuals at highest odds of type 2 diabetes development.

Gaye, Amadou Marcon, Yannick Isaeva, Julia LaFlamme, Philippe Turner, Andrew Jones, Elinor M Minion, Joel Boyd, Andrew W Newby, Christopher J Nuotio, Marja-Liisa Wilson, Rebecca Butters, Oliver Murtagh, Barnaby Demir, Ipek Doiron, Dany Giepmans, Lisette Wallace, Susan E Budin-Ljosne, Isabelle Oliver Schmidt, Carsten Boffetta, Paolo Boniol, Mathieu Bota, Maria Carter, Kim W deKlerk, Nick Dibben, Chris Francis, Richard W Hiekkalinna, Tero Hveem, Kristian Kvaloy, Kirsti Millar, Sean Perry, Ivan J Peters, Annette Phillips, Catherine M Popham, Frank Raab, Gillian Reischl, Eva Sheehan, Nuala Waldenberger, Melanie Perola, Markus van den Heuvel, Edwin Macleod, John Knoppers, Bartha M Stolk, Ronald P Fortier, Isabel Harris, Jennifer R Woffenbuttel, Bruce H R Murtagh, Madeleine J Ferretti, Vincent Burton, Paul R eng MC_UP_A540₁021/Medical Research Council/United Kingdom MR/K006525/1/Medical Research Council/United Kingdom Medical Research Council/United Kingdom Wellcome Trust/United Kingdom Research Support, Non-U.S. Gov't England 2014/09/30 06:00 Int J Epidemiol. 2014 Dec;43(6):1929-44. doi: 10.1093/ije/dyu188. Epub 2014 Sep 26.; International audience; BACKGROUND: Research in modern biomedicine and social science requires sample sizes so large that they can often only be achieved through a pooled co-analysis of data from several studies. But the pooling of information from individuals in a central database that may be queried by researchers raises important ethico-legal questions and can be controversial. In the UK this has been highlighted by recent debate and controversy relating to the UK's proposed 'care.data' initiative, and these issues reflect important societal and professional concerns about privacy, confidentiality and intellectual property. DataSHIELD provides a novel technological solution that can circumvent some of the most basic challenges in facilitating the access of researchers and other healthcare professionals to individual-level data. METHODS: Commands are sent from a central analysis computer (AC) to several data computers (DCs) storing the data to be co-analysed. The data sets are analysed simultaneously but in parallel. The separate parallelized analyses are linked by non-disclosive summary statistics and commands transmitted back and forth between the DCs and the AC. This paper describes the technical implementation of DataSHIELD using a modified R statistical environment linked to an Opal database deployed behind the computer firewall of each DC. Analysis is controlled through a standard R environment at the AC. RESULTS: Based on this Opal/R implementation, DataSHIELD is currently used by the Healthy Obese Project and the Environmental Core Project (BioSHaRE-EU) for the federated analysis of 10 data sets across eight European countries, and this illustrates the opportunities and challenges presented by the DataSHIELD approach. CONCLUSIONS: DataSHIELD facilitates important research in settings where: (i) a co-analysis of individual-level data from several studies is scientifically necessary but governance restrictions prohibit the release or sharing of some of the required data, and/or render data access unacceptably slow; (ii) a research group (e.g. in a developing nation) is particularly vulnerable to loss of intellectual property-the researchers want to fully share the information held in their data with national and international collaborators, but do not wish to hand over the physical data themselves; and (iii) a data set is to be included in an individual-level co-analysis but the physical size of the data precludes direct transfer to a new site for analysis.

The increasing obesity epidemic has become a significant public health concern worldwide, as excess body fat has been shown to be strongly related to cardiometabolic risk. Measurement of adiposity is commonly used as an indicator of health and various anthropometric measurement procedures have been proposed to characterise individual susceptibility to cardiometabolic conditions. Although extensive research has attempted to quantify relationships between different adiposity measures and morbidity, results have been conflicting and inconclusive, and considerable controversy still exists as to which anthropometric measurement most accurately defines nonoptimal body fat distribution.In this review we describe the most commonly used indices of general and central adiposity and review the most recently completed meta-analytic studies to determine which adiposity measure is most strongly associated with, and the best discriminator of, type 2 diabetes, cardiovascular disease and mortality.

Background The prevalence of type 2 diabetes within the Republic of Ireland is poorly defined, although a recent report suggested 135,000 cases in adults aged 45+, with approximately one-third of these undiagnosed. This study aims to assess the prevalence of undiagnosed and diagnosed diabetes in middle-aged adults and compare features in order to investigate why certain individuals remain undetected. Methods This was a cross-sectional study involving a random sample of 2,047 men and women aged 50–69 years. Logistic regression was used to explore socio-economic, metabolic and other health-related feature associations with undiagnosed or diagnosed diabetes. Clinically relevant variables identified in regression analyses were assessed using the receiver operating characteristic curve. Results The total prevalence of diabetes was 8.5% (95% CI: 7.4%-8.8%); 72 subjects (3.5%) had undiagnosed diabetes (95% CI: 2.8%-4.4%) and 102 subjects (5.0%) had diagnosed diabetes (95% CI: 4.1%-6.0%). Obesity, dyslipidaemia, and having a family diabetes history were positively associated with both undiagnosed and diagnosed type 2 diabetes. Compared with diagnosed subjects, study participants with undiagnosed diabetes were significantly more likely to have low levels of physical activity and were less likely to be on treatment for diabetes-related conditions or to have private medical insurance. Conclusion A considerable proportion of diabetes cases were undiagnosed (41%), emphasising the need for more effective detection strategies and equitable access to primary healthcare.

Background A novel obesity classification method has been proposed utilising body mass index (BMI) and waist-height ratio (WHtR) together. However, the utility of this approach is unclear. In this study we compare the metabolic profiles in subjects defined as overweight or obese by both measures. We examine a range of metabolic risk features, pro-inflammatory cytokines, acute-phase response proteins, coagulation factors and white blood cell counts to determine whether a combination of both indices more accurately identifies individuals at increased cardiometabolic risk. Methods This was a cross-sectional study involving a random sample of 2,047 men and women aged 50–69 years. Metabolic and anthropometric profiles were assessed in study participants. Independent t or Mann-Whitney U tests were used to compare lipid, lipoprotein, blood pressure, glycaemic and inflammatory biomarker levels between BMI and WHtR tertiles. Multinomial logistic regression was performed to determine adverse metabolic feature and biomarker associations with BMI and WHtR groupings. Results The combination of BMI and WHtR tertiles identified consistent metabolic variable differences relative to those characterised on the basis of one index. Similarly, odds ratios for cardiometabolic risk factors were noticeably increased in subjects classified by both measures when compared to study participants categorised by either BMI or WHtR separately. In a fully adjusted model, only individuals within the highest percentile for both indices displayed a significant and positive association with pre-diabetes (OR: 3.4, 95% CI: 2.0–6.0, P Conclusion Risk stratification using a composite index may provide a more accurate method for identifying high and low-risk subjects.

Background Inflammation has been suggested a possible mechanism linking adiposity with type 2 diabetes. Central obesity indicated by waist circumference (WC) measurement is thought to be a greater risk factor for chronic low-grade inflammation compared to general obesity characterised by body mass index (BMI). However, evidence for this association is still equivocal. In this study we compare biomarker relationships with BMI and WC measures and type 2 diabetes. We examine a range of pro-inflammatory cytokines, acute-phase response proteins, coagulation factors, white blood cell counts and a combination of these markers to determine which measurement is more strongly associated with diabetes-related inflammation. Methods This was a cross-sectional study involving a random sample of 2,002 men and women aged 50–69 years. Correlation and logistic regression analyses were used to explore general and central obesity measurement relationships with non-optimal biomarker levels, biomarker combinations and type 2 diabetes. Results When compared to BMI, WC was more strongly related to a majority of inflammatory markers, adverse biomarker clustering and type 2 diabetes. In multivariable analysis, only WC remained significantly associated with type 2 diabetes (OR: 2.96, 95% CI: 1.93–4.55) after adjusting for BMI (OR: 0.73, 95% CI: 0.49–1.10) four or more markers (OR: 4.67, 95% CI: 2.64–8.27) and other potential confounders. Conclusion These data suggest that central obesity is a greater risk factor for chronic inflammation and type 2 diabetes than BMI. However, our results also indicate that relationships between markers of inflammation and diabetes cannot be completely explained by surrogate measures of adiposity.

Objectives Despite recommendations that central obesity assessment should be employed as a marker of cardiometabolic health, no consensus exists regarding measurement protocol. This study examined a range of anthropometric variables and their relationships with cardiometabolic features and type 2 diabetes in order to ascertain whether measurement site influences discriminatory accuracy. In particular, we compared waist circumference (WC) measured at two sites: (1) immediately below the lowest rib (WC rib) and (2) between the lowest rib and iliac crest (WC midway), which has been recommended by the World Health Organisation and International Diabetes Federation. Materials and Methods This was a cross-sectional study involving a random sample of 2,002 men and women aged 46-73 years. Metabolic profiles and WC, hip circumference, pelvic width and body mass index (BMI) were determined. Correlation, logistic regression and area under the receiver operating characteristic curve analyses were used to evaluate obesity measurement relationships with metabolic risk phenotypes and type 2 diabetes. Results WC rib measures displayed the strongest associations with non-optimal lipid and lipoprotein levels, high blood pressure, insulin resistance, impaired fasting glucose, a clustering of metabolic risk features and type 2 diabetes, in both genders. Rib-derived indices improved discrimination of type 2 diabetes by 3-7% compared to BMI and 2-6% compared to WC midway (in men) and 5-7% compared to BMI and 4-6% compared to WC midway (in women). A prediction model including BMI and central obesity displayed a significantly higher area under the curve for WC rib (0.78, P=0.003), Rib/height ratio (0.80, P

Background Despite recommendations that central obesity assessment should be employed as a marker of cardiometabolic health, no consensus exists regarding measurement protocol. This study examined a range of anthropometric variables and their relationships with cardiometabolic features and type 2 diabetes in order to ascertain whether measurement site influences discriminatory accuracy. In particular, we compared waist circumference (WC) measured at two sites: (1) below the lowest rib (WC rib) and (2) between the lowest rib and iliac crest (WC midway), which has been recommended by the World Health Organisation (WHO) and International Diabetes Federation (IDF). Methods This was a cross-sectional study involving a random sample of 2,002 men and women aged 50–69 years. Metabolic profiles and WC, hip circumference, pelvic width and body mass index (BMI) were determined in study participants. Correlation, logistic regression and covariate-adjusted area under the receiver operating characteristic curve analyses were used to evaluate obesity measurement associations and discrimination for metabolic risk phenotypes and type 2 diabetes. Results Rib measurements displayed, without exception, the strongest associations for non-optimal lipid profiles, high blood pressure, insulin resistance, impaired fasting glucose, a clustering of metabolic risk features and type 2 diabetes, in both genders. Rib-derived indices improved discrimination for type 2 diabetes by 3–7% compared to BMI and 2–6% compared to WC midway (in men) and 5–7% compared to BMI and 4–6% compared to WC midway (in women). Conclusion WC rib is easier to measure and our data suggest that it is a better method for determining obesity-related cardiometabolic risk than WC midway. Rib measurements may provide a more convenient and precise method for discriminating cardiometabolic outcomes. The clinical utility of rib-derived indices as potentially more accurate predictors of type 2 diabetes, compared to WHO and IDF-recommended WC midway measurement or BMI, requires further investigation.

Background The American Diabetes Association (ADA) have recommended glycated haemoglobin A 1c (HbA 1c ) measurement as an alternative to fasting plasma glucose (FPG) for the diagnosis of pre-diabetes and type 2 diabetes. However, evidence suggests discordance between HbA 1c and FPG. The aim of this study was to compare the metabolic profiles in subjects with pre-diabetes and type 2 diabetes, using ADA-recommended HbA 1c and FPG diagnostic thresholds. In particular, we examined a range of traditional diabetes risk factors, metabolic syndrome (MetS) features, pro-inflammatory cytokines, acute-phase response proteins, coagulation factors and white blood cell counts to determine which test most accurately identified a greater proportion of subjects at increased cardiometabolic risk. Methods This was a cross-sectional study involving a random sample of 2047 men and women aged 50–69 years. Binary and multinomial logistic regression were used to explore risk feature associations with pre-diabetes [either HbA 1c levels 5.7–6.4% (39–46 mmol/mol) or impaired FPG levels 5.6–6.9 mmol/l] and type 2 diabetes [either HbA 1c >6.5% ( >48 mmol/mol) or FPG >7.0 mmol/l]. Receiver operating characteristic curve analysis was used to compare the ability of HbA 1c to discriminate pre-diabetes or diabetes defined by FPG. Results A higher percentage of pre-diabetic individuals with diabetes-related phenotypes were identified by FPG compared to HbA 1c . Cardiometabolic profiles in diabetic subjects were broadly similar according to diagnosis by either assay. Odds ratios for obesity, elevated blood pressure, high insulin levels, inflammatory biomarkers and MetS were noticeably increased in pre-diabetic participants classified by both tests, with four-fold increased odds (OR: 4.0, 95% CI: 2.8–5.8) of having three or more MetS features compared to subjects diagnosed by either HbA 1c (OR: 1.4, 95% CI: 1.2–1.8) or FPG (OR: 3.0, 95% CI: 1.7–5.1) individually. Conclusion In middle-aged Caucasian-Europeans, HbA 1c alone is a poor indicator of diabetes risk compared to FPG. However, combined use of HbA 1c and FPG may be of additional benefit for identifying individuals at substantially increased cardiometabolic risk. Earlier identification of high-risk subjects could enable earlier targeted interventions or therapies, thus attenuating development of type 2 diabetes and associated cardiometabolic complications.

Background The prevalence of type 2 diabetes within the Republic of Ireland is poorly defined, although a recent report suggested 135,000 cases in adults aged 45+, with approximately one-third of these undiagnosed. This study aims to assess the prevalence of undiagnosed and diagnosed diabetes in middle-aged adults, and compare features related to either condition, in order to investigate why certain individuals remain undetected. Methods This was a cross-sectional study involving a sample of 2,047 men and women, aged between 50–69 years, randomly selected from a large primary care centre. Univariate logistic regression was used to explore socio-economic, metabolic and other health related variable associations with undiagnosed or diagnosed diabetes. A final multivariate analysis was used to determine odds ratios and 95% confidence intervals for having undiagnosed compared to diagnosed diabetes, adjusted for gender, age and significant covariates determined from univariate models. Principle Findings The total prevalence of diabetes was 8.5% (95% CI: 7.4%–8.8%); 72 subjects (3.5%) had undiagnosed diabetes (95% CI: 2.8%–4.4%) and 102 subjects (5.0%) had diagnosed diabetes (95% CI: 4.1%–6.0%). Obesity, dyslipidaemia, and family history of diabetes were positively associated with both undiagnosed and diagnosed type 2 diabetes. Compared with diagnosed subjects, study participants with undiagnosed diabetes were significantly more likely to have low levels of physical activity and were less likely to be on treatment for diabetes-related conditions or to have private medical insurance. Conclusions The prevalence of diabetes within the Cork and Kerry Diabetes and Heart Disease Study is comparable to recent estimates from the Slan National Health and Lifestyle Survey, a study which was nationally representative of the general population. A considerable proportion of diabetes cases were undiagnosed (41%), emphasising the need for more effective detection strategies and equitable access to primary healthcare.