If the window of opportunity presented by the early years is missed, it becomes increasingly difficult to create a successful life-course. A biopsychosocial model of special educational need with an emphasis on participation and functioning moves the frame of reference from the clinic to the school and the focus from specific conditions to creating supportive environments cognisant of the needs of all children. However, evidence suggests that an emphasis on diagnosed conditions persists and that the needs of children who do not meet these criteria are not identified.
The Early Development Instrument (EDI) is a well-validated, teacher-completed population-level measure of five domains of child development. It is uniquely placed, at the interface between health and education, to explore the developmental status of children with additional challenges within a typically developing population. The aim of this study was to examine the extent to which the special educational needs of children in their first year of formal education have been identified.
This cross-sectional study was conducted in Ireland in 2011. EDI (teacher completed) scores were calculated for 1344 children. Data were also collected on special needs and on children identified by the teacher as needing assessment. Mean developmental scores were compared using one-way ANOVA.
Eighty-three children in the sample population (6.2%) had identified special educational needs. A further 132 children were judged by the teacher as needing assessment. Children with special needs had lower mean scores than typically developing children, in all five developmental domains. Children considered by the teacher as needing assessment also had lower scores, which were not significantly different from those of children with special needs. Speech, emotional or behavioural difficulties were the most commonly reported problems among children needing further assessment. There was also a social gradient among this group.
A small but significant number of children have not had their needs adequately assessed. Teacher observation is an effective means of identifying children with a level of impairment which prevents them from fully participating in their educational environment and could be integrated into a multi-disciplinary approach to meeting the needs of all children.
Child development; Special educational needs; Population-health; Social determinants of health; Educational needs assessment
Overweight and obesity prevalence has risen dramatically in recent decades. While it is known that overweight and obesity is associated with a wide range of chronic diseases, the cumulative burden of chronic disease in the population associated with overweight and obesity is not well quantified. The aims of this paper were to examine the associations between BMI and chronic disease prevalence; to calculate Population Attributable Fractions (PAFs) associated with overweight and obesity; and to estimate the impact of a one unit reduction in BMI on the population prevalence of chronic disease.
A cross-sectional analysis of 10,364 adults aged ≥18 years from the Republic of Ireland National Survey of Lifestyle, Attitudes and Nutrition (SLÁN 2007) was performed. Using binary regression, we examined the relationship between BMI and the selected chronic diseases. In further analyses, we calculated PAFs of selected chronic diseases attributable to overweight and obesity and we assessed the impact of a one unit reduction in BMI on the overall burden of chronic disease.
Overweight and obesity prevalence was higher in men (43.0% and 16.1%) compared to women (29.2% and 13.4%), respectively. The most prevalent chronic conditions were lower back pain, hypertension, and raised cholesterol. Prevalence of chronic disease generally increased with increasing BMI. Compared to normal weight persons, the strongest associations were found in obese women for diabetes (RR 3.9, 95% CI 2.5-6.3), followed by hypertension (RR 2.9, 95% CI 2.3-3.6); and in obese men for hypertension (RR 2.1, 95% CI 1.6-2.7), followed by osteoarthritis (RR 2.0, 95% CI 1.2-3.2). Calculated PAFs indicated that a large proportion of chronic disease is attributable to increased BMI, most noticeably for diabetes in women (42%) and for hypertension in men (30%). Overall, a one unit decrease in BMI results in 26 and 28 fewer cases of chronic disease per 1,000 men and women, respectively.
Overweight and obesity are major contributors to the burden of chronic disease in the population. The achievement of a relatively modest reduction in average BMI in the population has the potential to make a significant impact on the burden of chronic disease.
Overweight; Obesity; BMI; Burden; Chronic disease; Prevalence; Population attributable fraction
There are few evidence-based mobile health solutions for treating adolescent obesity. The primary aim of this parallel non-inferiority trial is to assess the effectiveness of an experimental smartphone application in reducing obesity at 12 months, compared to the Temple Street W82GO Healthy Lifestyles intervention.
The primary outcome measure is change in body mass index standardised deviation score at 12 months. The secondary aim is to compare the effect of treatment on secondary outcomes, including waist circumference, insulin sensitivity, quality of life, physical activity and psychosocial health. Adolescents with a body mass index at or above the 98th percentile (12 to 17 years) will be recruited from the Obesity clinic at Temple Street Children’s University Hospital in Dublin, Ireland. W82GO is a family-based lifestyle change intervention delivered in two phases over 12 months. In the current study, participants will be randomised for phase two of treatment to either usual care or care delivered via smartphone application. One hundred and thirty-four participants will be randomised between the two study arms. An intention-to-treat analysis will be used to compare treatment differences between the groups at 12 months.
The results of this study will be disseminated via open access publication and will provide important information for clinicians, patients and policy makers regarding the use of mobile health interventions in the management of adolescent obesity.
Obesity; Smartphone; Adolescent; Behavioural intervention; Mobile health; Telemedicine
To study the determinants of health-related quality of life (HRQoL) in Irish patients with diabetes using the Centres for Disease Controls' (CDC's) ‘Unhealthy Days’ summary measure and to assesses the agreement between this generic HRQoL measure and the disease-specific Audit of Diabetes Dependant Quality of Life (ADDQoL) measure.
Research Design and Methods
Data were analysed from the Diabetes Quality of Life Study, a cross-sectional study of 1,456 people with diabetes in Ireland (71% response rate). Unhealthy days were assessed using the CDC's ‘Unhealthy days’ summary measure. Quality of life (QoL) was also assessed using the ADDQoL measure. Analyses were conducted primarily using logistic regression. The agreement between the two QoL instruments was measured using the kappa co-efficient.
Participants reported a median of 2 unhealthy days per month. In multivariate analyses, female gender (P = 0.001), insulin use (P = 0.030), diabetes complications (P = <0.001) were significantly associated with more unhealthy days. Older patients had fewer unhealthy days per month (P = 0.003). Agreement between the two measures of QoL (unhealthy days measure and ADDQoL) was poor, Kappa = 0.234
The findings highlight the determinants of HRQoL in patients with diabetes using a generic HRQoL summary measure. The ‘Unhealthy Days’ and the ADDQoL have poor agreement, therefore the ‘Unhealthy Days’ summary measure may be assessing a different construct. Nonetheless, this study demonstrates that the generic ‘Unhealthy Days’ summary measure can be used to detect determinants of HRQoL in patients with diabetes.
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.
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.
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.
The prevalence of diabetes within the Cork and Kerry Diabetes and Heart Disease Study is comparable to recent estimates from the Slán 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.
To compare diabetes risk assessment tools in estimating risk of developing type 2 diabetes (T2DM) and to evaluate cardiometabolic risk profiles in a middle-aged Irish population.
Future risk of developing T2DM was estimated using 7 risk scores, including clinical measures with or without anthropometric, biological and lifestyle data, in the cross-sectional Mitchelstown cohort of 2,047 middle-aged men and women. Cardiometabolic phenotypes including markers of glucose metabolism, inflammatory and lipid profiles were determined.
Estimates of subjects at risk for developing T2DM varied considerably according to the risk assessment tool used (0.3% to 20%), with higher proportions of males at risk (0–29.2% vs. 0.1–13.4%, for men and women, respectively). Extrapolated to the Irish population of similar age, the overall number of adults at high risk of developing T2DM ranges from 3,378 to 236,632. Numbers of non-optimal metabolic features were generally greater among those at high risk of developing T2DM. However, cardiometabolic profile characterisation revealed that only those classified at high risk by the Griffin (UK Cambridge) score displayed a more pro-inflammatory, obese, hypertensive, dysglycaemic and insulin resistant metabolic phenotype.
Most diabetes risk scores examined offer limited ability to identify subjects with metabolic abnormalities and at risk of developing T2DM. Our results highlight the need to validate diabetes risk scoring tools for each population studied and the potential for developing an Irish diabetes risk score, which may help to promote self awareness and identify high risk individuals and diabetes hot spots for targeted public health interventions.
To assess the prevalence and determinants of haematinic deficiency (lack of B12 folate or iron) and macrocytosis in blood from a national population-based study of middle-aged and older adults.
A cross-sectional study involving 1,207 adults aged ≥45 years, recruited from a sub-study of the Irish National Survey of Lifestyle Attitudes and Nutrition (SLÁN 2007). Participants completed a health and lifestyle questionnaire and a standard food frequency questionnaire. Non-fasting blood samples were obtained for measurement of full blood count and expert morphological assessment, serum ferritin, soluble transferrin receptor assay (sTfR), B12, folate and coeliac antibodies. Blood samples were also assayed for thyroid function (T4, TSH), liver function, aminotransferase (AST) and gamma-glutamyl transferase (GGT).
The overall prevalence (95% C.I.) of anaemia (Hb <13.5g/dl men and 11.3 g/dl women) was 4.6% (2.9%–6.4%) in men and 1.0% (0.2%–1.9%) in women. Iron deficiency (ferritin <17ng/ml men and <11ng/ml in women) was detected in 6.3% of participants (3.7% in males and 8.7% in females, p<0.001). Based on both low ferritin and raised sTfR (>21nmol/ml) only 2.3% were iron-deficient. 3.0% and 2.7% were found to have low levels of serum folate (<2.3ng/ml) and serum B12 (<120ng/l) respectively. Clinically significant macrocytosis (MCV>99fl) was detected in 8.4% of subjects. Strong, significant and independent associations with macrocytosis were observed for lower social status, current smoking status, moderate to heavy alcohol intake, elevated GGT levels, deficiency of folate and vitamin B12, hypothyroidism and coeliac disease. The population attributable fraction (PAF) for macrocytosis associated with elevated GGT (25.0%) and smoking (24.6%) was higher than for excess alcohol intake (6.3%), folate deficiency (10.5%) or vitamin B12 (3.4%).
Haematinic deficiency and macrocytosis are common in middle-aged/older adults in Ireland. Macrocytosis is more likely to be attributable to an elevated GGT and smoking than vitamin B12 or folate deficiency.
Lower extremity amputation (LEA) is a complication of diabetes and a marker of the quality of diabetes care. Clinical and sociodemographic determinants of LEA in people with diabetes are well known. However, the role of service-related factors has been less well explored. Early referral to secondary healthcare is assumed to prevent the occurrence of LEA. The objective of this study is to investigate a possible association between the timing of patient access to secondary healthcare services for diabetes management, as a key marker of service-related factors, and LEA in patients with diabetes.
This is a case–control study. The source population is people with diabetes. Cases will be people with diabetes who have undergone a first major LEA, identified from the hospital discharge data at each of three regional centres for diabetes care. Controls will be patients with diabetes without LEA admitted to the same centre either electively or as an emergency. Frequency-matching will be applied for gender, type of diabetes, year and centre of LEA. Three controls per case will be selected from the same population as the cases. With a power of 90% to detect OR of 0.4 for an association between ‘good quality care’ and LEA in people with diabetes, 107 cases and 321 controls are required. Services involved in diabetes management are endocrinology, ophthalmology, renal, cardiology, vascular surgery and podiatry; timing of first contact with any of these services is the main exploratory variable. Using unconditional logistic regression, an association between this exposure and the outcome of major LEA in people with diabetes will be explored, while adjusting for confounders.
Ethics and dissemination
Ethical approval was granted by the Clinical Research Ethics Committee of the Cork Teaching Hospitals, Ireland. Results will be presented at conferences and published in peer-reviewed journals.
There is a current lack of consensus on defining metabolically healthy obesity (MHO). Limited data on dietary and lifestyle factors and MHO exist. The aim of this study is to compare the prevalence, dietary factors and lifestyle behaviours of metabolically healthy and unhealthy obese and non-obese subjects according to different metabolic health criteria.
Cross-sectional sample of 1,008 men and 1,039 women aged 45-74 years participated in the study. Participants were classified as obese (BMI ≥30kg/m2) and non-obese (BMI <30kg/m2). Metabolic health status was defined using five existing MH definitions based on a range of cardiometabolic abnormalities. Dietary composition and quality, food pyramid servings, physical activity, alcohol and smoking behaviours were examined.
The prevalence of MHO varied considerably between definitions (2.2% to 11.9%), was higher among females and generally increased with age. Agreement between MHO classifications was poor. Among the obese, prevalence of MH was 6.8% to 36.6%. Among the non-obese, prevalence of metabolically unhealthy subjects was 21.8% to 87%. Calorie intake, dietary macronutrient composition, physical activity, alcohol and smoking behaviours were similar between the metabolically healthy and unhealthy regardless of BMI. Greater compliance with food pyramid recommendations and higher dietary quality were positively associated with metabolic health in obese (OR 1.45-1.53 unadjusted model) and non-obese subjects (OR 1.37-1.39 unadjusted model), respectively. Physical activity was associated with MHO defined by insulin resistance (OR 1.87, 95% CI 1.19-2.92, p = 0.006).
A standard MHO definition is required. Moderate and high levels of physical activity and compliance with food pyramid recommendations increase the likelihood of MHO. Stratification of obese individuals based on their metabolic health phenotype may be important in ascertaining the appropriate therapeutic or intervention strategy.
Current estimates of diabetes prevalence in the Republic of Ireland (RoI) are based on UK epidemiological studies. This study uses Irish data to describe the prevalence of doctor-diagnosed diabetes amongst all adults aged 18+ years and undiagnosed diabetes amongst those aged 45+ years.
The survey of lifestyle attitudes and nutrition (SLAN) 2007 is based on a nationally representative sample of Irish adults aged 18+ years (n = 10,364). Self-reported doctor-diagnosed diabetes was recorded for respondents in the full sample. Diabetes medication use, measured height and weight, and non-fasting blood samples were variously recorded in sub-samples of younger (n = 967) and older (n = 1,207) respondents.
The prevalence of doctor-diagnosed diabetes amongst adults aged 18+ years was 3.5% (95% CI 3.1% - 3.9%). After adjustment for other explanatory variables; the risk of self-reported doctor-diagnosed diabetes was significantly related to age (p < 0.0001), employment status (p = 0.0003) and obesity (p = 0.0003). Amongst adults aged 45+ years, the prevalence of doctor-diagnosed diabetes was 8.9% (95% CI 7.3% -10.5%) and undiagnosed diabetes was 2.8% (95% CI 1.4% - 4.1%). This represented 31.2% of diabetes cases in this age group.
Notwithstanding methodological differences, these prevalence estimates are consistent with those in the UK and France. However, the percentage of undiagnosed cases amongst adults aged 45+ years appears to be higher in the RoI. Increased efforts to improve early detection and population level interventions to address adverse diet and lifestyle factors are urgently needed.
Obesity is a growing problem worldwide and can often result in a variety of negative health outcomes. In this study we aim to apply partial least squares (PLS) methodology to estimate the separate effects of age, period and cohort on the trends in obesity as measured by body mass index (BMI).
Using PLS we will obtain gender specific linear effects of age, period and cohort on obesity. We also explore and model nonlinear relationships of BMI with age, period and cohort. We analysed the results from 7,796 men and 10,220 women collected through the SLAN (Surveys of Lifestyle, attitudes and Nutrition) in Ireland in the years 1998, 2002 and 2007.
PLS analysis revealed a positive period effect over the years. Additionally, men born later tended to have lower BMI (−0.026 kg·m-2 yr-1, 95% CI: -0.030 to −0.024) and older men had in general higher BMI (0.029 kg·m-2 yr-1, 95% CI: 0.026 to 0.033). Similarly for women, those born later had lower BMI (−0.025 kg·m-2 yr-1, 95% CI: -0.029 to −0.022) and older women in general had higher BMI (0.029 kg·m-2 yr-1, 95% CI: 0.025 to 0.033). Nonlinear analyses revealed that BMI has a substantial curvilinear relationship with age, though less so with birth cohort.
We notice a generally positive age and period effect but a slightly negative cohort effect. Knowing this, we have a better understanding of the different risk groups which allows for effective public intervention measures to be designed and targeted for these specific population subgroups.
Obesity; Age-period-cohort; Partial least squares
Much research on the health and well-being of third level students is focused on poor mental health leading to a dearth of information on positive mental health and well-being. Recently, the Warwick Edinburgh Mental Well-being scale (WEMWBS) was developed as a measurement of positive mental health and well-being. The aim of this research is to investigate the distribution and determinants of positive mental health and well-being in a large, broadly representative sample of third level students using WEMWBS.
Undergraduate students from one large third level institution were sampled using probability proportional to size sampling. Questionnaires were distributed to students attending lectures in the randomly selected degrees. A total of 2,332 self-completed questionnaires were obtained, yielding a response rate of 51% based on students registered to relevant modules and 84% based on attendance. One-way ANOVAs and multivariate logistic regression were utilised to investigate factors associated with positive mental health and well-being.
The sample was predominantly female (62.66%), in first year (46.9%) and living in their parents’ house (42.4%) or in a rented house or flat (40.8%). In multivariate analysis adjusted for age and stratified by gender, no significant differences in WEMWBS score were observed by area of study, alcohol, smoking or drug use. WEMWBS scores were higher among male students with low levels of physical activity (p=0.04). Men and women reporting one or more sexual partners (p<0.001) were also more likely to report above average mental health and well-being.
This is the first study to examine positive mental health and well-being scores in a third level student sample using WEMWBS. The findings suggest that students with a relatively adverse health and lifestyle profile have higher than average mental health and well-being. To confirm these results, this work needs to be replicated across other third level institutions.
To examine the barriers to, and facilitators in, improving diabetes management from the general practice perspective, in advance of the implementation of an integrated model of care in Ireland.
Qualitative using semistructured interviews.
Primary care in the Republic of Ireland.
Purposive sample of 29 general practitioners (GPs) and two practice nurses.
Data were analysed using a framework approach.
The main barriers and facilitators occurred at the level of the health system but had a ripple effect at an organisational, professional and patient level. The lack of targeted remuneration for diabetes management in the Irish health system created apathy in general practice and was perceived to be indicative of the lack of value placed on chronic disease management in the health system. There were ‘pockets of interest’ among GPs motivated by ‘vocational’ incentives such as a sense of professional duty; however, this was not sufficient to drive widespread improvement. The hospital service was seen as an essential support for primary care management, although some participants referred to emerging tension between settings. The lack of coordination at the primary–secondary interface resulted in avoidable duplication and an ‘in the meantime’ period of uncertainty around when patients would be called or recalled by specialist services. Facilitators included the availability of nursing support and serendipitous access to services. The lack of resources in the community was considered to be at odds with policy to shift routine management to general practice, which is fast reaching saturation.
At present, intrinsic motivation is driving the improvement of diabetes care in Ireland. This will not be sufficient to implement the proposed reform including a national model of integrated care. Policymakers need to assess and prepare for the disparate levels of interest and infrastructure in primary care in Ireland to support this change.
PRIMARY CARE; DIABETES & ENDOCRINOLOGY
The extensive literature on the area‐level association between socioeconomic characteristics and suicide indicates that the more deprived and socially fragmented an area, the higher its suicide rate. Relatively few studies have examined the association between the incidence of non‐fatal suicidal behaviour and area characteristics.
This study investigated the area‐level association between hospital‐treated deliberate self‐harm, deprivation and social fragmentation in Ireland.
During 2002–2004, the Irish National Registry of Deliberate Self Harm collected data on self‐harm presentations to 38 of Ireland's 40 hospital accident and emergency (A&E) departments, using a standardised methodology that included geocoding patient addresses to small‐area level. Annual deliberate self‐harm incidence rates and levels of deprivation and social fragmentation were examined nationally and by geographic area. Negative binomial regression was used to investigate the small‐area association between deliberate self‐harm, deprivation and social fragmentation.
During 2002–2004, an estimated 32 777 deliberate self‐harm presentations to A&E departments were made by 25 797 individuals. The total, male and female annual incidence rates were 204, 172 and 237 per 100 000, respectively. There were striking geographic differences in deliberate self‐harm presentation rates which were largely explained by the distribution of deprivation, fragmentation, age and gender, and interactions between these factors. Deprivation, rather than fragmentation, had the stronger independent effect on small‐area rates of self‐harm.
The highest rates of hospital‐treated deliberate self‐harm in Ireland are in deprived urban areas. Priority should be given to these areas when implementing community‐based interventions aimed at reducing suicidal behaviour.
To estimate the potential reduction in cardiovascular (CVD) mortality possible by decreasing salt, trans fat and saturated fat consumption, and by increasing fruit and vegetable (F/V) consumption in Irish adults aged 25–84 years for 2010.
Modelling study using the validated IMPACT Food Policy Model across two scenarios. Sensitivity analysis was undertaken. First, a conservative scenario: reductions in dietary salt by 1 g/day, trans fat by 0.5% of energy intake, saturated fat by 1% energy intake and increasing F/V intake by 1 portion/day. Second, a more substantial but politically feasible scenario: reductions in dietary salt by 3 g/day, trans fat by 1% of energy intake, saturated fat by 3% of energy intake and increasing F/V intake by 3 portions/day.
Republic of Ireland.
Coronary heart disease (CHD) and stroke deaths prevented.
The small, conservative changes in food policy could result in approximately 395 fewer cardiovascular deaths per year; approximately 190 (minimum 155, maximum 230) fewer CHD deaths in men, 50 (minimum 40, maximum 60) fewer CHD deaths in women, 95 (minimum 75, maximum 115) fewer stroke deaths in men, and 60 (minimum 45, maximum 70) fewer stroke deaths in women. Approximately 28%, 22%, 23% and 26% of the 395 fewer deaths could be attributable to decreased consumptions in trans fat, saturated fat, dietary salt and to increased F/V consumption, respectively. The 395 fewer deaths represent an overall 10% reduction in CVD mortality. Modelling the more substantial but feasible food policy options, we estimated that CVD mortality could be reduced by up to 1070 deaths/year, representing an overall 26% decline in CVD mortality.
A considerable CVD burden is attributable to the excess consumption of saturated fat, trans fat, salt and insufficient fruit and vegetables. There are significant opportunities for Government and industry to reduce CVD mortality through effective, evidence-based food policies.
Modelling; Salt; Saturated Fat; Ireland
To study variation in quality of life and quality of care in patients with diabetes experiencing three different models of care: traditional hospital care, hospital/general practitioner (GP) shared care, and structured GP care.
RESEARCH DESIGN AND METHODS
A cross-sectional study involving 1,456 patients with diabetes (71% response rate) was conducted. Quality of life was assessed with the Audit of Diabetes-Dependent Quality of Life (ADDQoL) instrument and quality of care with a 10-point process-of-care report card.
The adjusted odds ratio (OR) for a high (upper quartile) ADDQoL score was significantly increased in the structured care relative to the traditional hospital care group (OR 1.7 [95% CI 1.2–2.5]). A significantly higher proportion of structured GP care patients reported compliance with seven or more key process-of-care measures compared with the other models of care.
Diabetes quality of life may be enhanced when care is provided in a primary care setting without compromising quality of care.
Early childhood development strongly influences lifelong health. The Early Development Instrument (EDI) is a well-validated population-level measure of five developmental domains (physical health and well-being, social competence, emotional maturity, language and cognitive skills, and communication skills and general knowledge) at school entry age. The aim of this study was to explore the potential of EDI as an indicator of early development in Ireland.
A cross-sectional design was used.
The study was conducted in 42 of 47 primary schools in a major Irish urban centre.
EDI (teacher completed) scores were calculated for 1243 children in their first year of full-time education. Contextual data from a subset of 865 children were collected using a parental questionnaire.
Primary and secondary outcome measures
Children scoring in the lowest 10% of the population in one or more domains were deemed ‘developmentally vulnerable’. Scores were correlated with contextual data from the parental questionnaire.
In the sample population, 29% of children were not developmentally ready to engage in school. Factors associated with increased risk of vulnerability were being male OR 2.1 (CI 1.6 to 2.7); under 5 years OR 1.5 (CI 1.1 to 2.1) and having English as a second language OR 3.7 (CI 2.6 to 5.2). Adjusted for these demographics, low birth weight, poor parent/child interaction and mother's lower level of education showed the most significant ORs for developmental vulnerability. Calculating population attributable fractions, the greatest population-level risk factors were being male (35%), mother's education (27%) and having English as a second language (12%).
The EDI and linked parental questionnaires are promising indicators of the extent, distribution and determinants of developmental vulnerability among children in their first year of primary school in Ireland.
We have previously identified in a study of both self-reported body mass index (BMI) and clinically measured BMI that the sensitivity score in the obese category has declined over a 10-year period. It is known that self-reported weight is significantly lower that measured weight and that self-reported height is significantly higher than measured height. The purpose of this study is to establish if self-reported height bias or weight bias, or both, is responsible for the declining sensitivity in the obese category between self-reported and clinically measured BMI.
We report on self-reported and clinically measured height and weight from three waves of the Surveys of Lifestyle Attitudes and Nutrition (SLÁN) involving a nationally representative sample of Irish adults. Data were available from 66 men and 142 women in 1998, 147 men and 184 women in 2002 and 909 men and 1128 women in 2007. Respondents were classified into BMI categories normal (<25 kg/m2), overweight (25–<30 kg/m2) and obese (≥30 kg/m2).
Self-reported height bias has remained stable over time regardless of gender, age or clinical BMI category. Self-reported weight bias increases over time for both genders and in all age groups. The increased weight bias is most notable in the obese category.
BMI underestimation is increasing across time. Knowledge that the widening gap between self-reported BMI and measured BMI is attributable to an increased weight bias brings us one step closer to accurately estimating true obesity levels in the population using self-reported data.
The prevalence of chronic kidney disease (CKD) using available estimating equations with the Republic of Ireland is unknown.
A randomly selected population based cross-sectional study of 1,098 adults aged 45 years and older was conducted using data from the 2007 Survey of Lifestyle, Attitudes and Nutrition (SLÁN). Estimated Glomerular Filtration Rate (eGFR) was calculated from a single IDMS aligned serum creatinine using the CKD-EPI and the MDRD equations, and albumin to creatinine ratio was based on a single random urine sample.
The sample clinical characteristics and demography was similar to middle and older age adults in the general Irish population, though with an underrepresentation of subjects >75 years and of males. All results are based on subjects with available blood and urine samples. Applying weighting to obtain survey based population estimates, using Irish population census data, the estimated weighted prevalence of CKD-EPI eGFR<60 mL/min/1.73m2 was 11.6%, (95% confidence interval; 9.0, 14.2%), 12.0% ( 9.0, 14.2%) of men and 11.2% (7.3, 15.2%) of women. Unweighted prevalence estimates were similar at 11.8% (9.9, 13.8%). Albuminuria increased with lower CKD-EPI eGFR category. 10.1% of all subjects had albuminuria and an eGFR≥60 mL/min/1.73 m2 giving an overall weighted estimated prevalence of National Kidney Foundation (NKF) defined CKD 21.3% (18.0, 24.6%), with the unadjusted estimate of 21.9% (19.5, 24.4%). MDRD related estimates for eGFR <60 mL/min/1.73 m2, and NFK defined CKD were higher than CKD-EPI and differences were greater in younger and female subjects.
CKD is highly prevalent in middle and older aged adults within the Republic of Ireland. In this population, there is poor agreement between CKD-EPI and MDRD equations especially at higher GFRs. CKD is associated with lower educational status and poor self rated health.
Chronic kidney disease; Glomerular filtration rate; Albuminuria; Population survey
Parental obesity is a predominant risk factor for childhood obesity. Family factors including socio-economic status (SES) play a role in determining parent weight. It is essential to unpick how shared family factors impact on child weight. This study aims to investigate the association between measured parent weight status, familial socio-economic factors and the risk of childhood obesity at age 9.
Cross sectional analysis of the first wave (2008) of the Growing Up in Ireland (GUI) study. GUI is a nationally representative study of 9-year-old children (N = 8,568). Schools were selected from the national total (response rate 82%) and age eligible children (response rate 57%) were invited to participate. Children and their parents had height and weight measurements taken using standard methods. Data were reweighted to account for the sampling design. Childhood overweight and obesity prevalence were calculated using International Obesity Taskforce definitions. Multinomial logistic regression examined the association between parent weight status, indicators of SES and child weight. Overall, 25% of children were either overweight (19.3%) or obese (6.6%). Parental obesity was a significant predictor of child obesity. Of children with normal weight parents, 14.4% were overweight or obese whereas 46.2% of children with obese parents were overweight or obese. Maternal education and household class were more consistently associated with a child being in a higher body mass index category than household income. Adjusted regression indicated that female gender, one parent family type, lower maternal education, lower household class and a heavier parent weight status significantly increased the odds of childhood obesity.
Parental weight appears to be the most influential factor driving the childhood obesity epidemic in Ireland and is an independent predictor of child obesity across SES groups. Due to the high prevalence of obesity in parents and children, population based interventions are required.
Suicide is a significant public health issue with almost one million people dying by suicide each year worldwide. Deliberate self harm (DSH) is the single most important risk factor for suicide yet few countries have reliable data on DSH. We developed a national DSH registry in the Republic of Ireland to establish the incidence of hospital-treated DSH at national level and the spectrum and pattern of presentations with DSH and repetition.
Methods and Findings
Between 2003 and 2009, the Irish National Registry of Deliberate Self Harm collected data on DSH presentations to all 40 hospital emergency departments in the country. Data were collected by trained data registration officers using standard methods of case ascertainment and definition. The Registry recorded 75,119 DSH presentations involving 48,206 individuals. The total incidence rate fell from 209 (95% CI: 205–213) per 100,000 in 2003 to 184 (95% CI: 180–189) per 100,000 in 2006 and increased again to 209 (95% CI: 204–213) per 100,000 in 2009. The most notable annual changes were successive 10% increases in the male rate in 2008 and 2009. There was significant variation by age with peak rates in women in the 15–19 year age group (620 (95% CI: 605–636) per 100,000), and in men in the 20–24 age group (427 (95% CI: 416–439) per 100,000). Repetition rates varied significantly by age, method of self harm and number of previous episodes.
Population-based data on hospital-treated DSH represent an important index of the burden of mental illness and suicide risk in the community. The increased DSH rate in Irish men in 2008 and 2009 coincided with the advent of the economic recession in Ireland. The findings underline the need for developing effective interventions to reduce DSH repetition rates as a key priority for health systems.
To investigate the relationship between fasting glucose levels, insulin resistance, and cognitive impairment in old age. Diabetes is associated with cognitive impairment in older people. However, the link between elevated fasting glucose levels and insulin resistance in nondiabetic individuals, and the risk of cognitive impairment is unclear.
RESEARCH DESIGN AND METHODS
We analyzed data from, in total, 8,447 participants in two independent prospective studies: the PROspective Study of Pravastatin in the Elderly at Risk (PROSPER), 5,019 participants, aged 69–84 years, and the Rotterdam Study, 3,428 participants, aged 61–97 years. Fasting glucose levels were assessed at baseline in both studies; fasting insulin levels were assessed in the Rotterdam Study only. Cognitive function was assessed in both studies at baseline and during follow-up.
Subjects with diabetes had impaired cognitive function at baseline. In contrast, in people without a history of diabetes, there was no clear association between baseline fasting glucose levels and executive function and memory, nor was there a consistent relationship between elevated baseline fasting glucose levels and the rate of cognitive decline in either cohort. Insulin resistance (homeostasis model assessment index) was also unrelated to cognitive function and decline.
Elevated fasting glucose levels and insulin resistance are not associated with worse cognitive function in older people without a history of diabetes. These data suggest either that there is a threshold for effects of dysglycemia on cognitive function or that factors other than hyperglycemia contribute to cognitive impairment in individuals with frank diabetes.
Cultural pressures to be thin and tall are postulated to cause people to misreport their body weight and height towards more socially normative (i.e., desirable) values, but a paucity of direct evidence supports this idea. We developed a novel non-linear approach to examining weight, height, and BMI misreporting biases and used this approach to examine the association between socially non-normative weight and misreporting biases in adults.
The Survey of Lifestyles, Attitudes, and Nutrition 2007 (SLÁN 2007), a nationally representative survey of the Republic of Ireland (N = 1942 analyzed) was used. Self-reported weight (height) was classified as under-reported by ≥2.0 kg (2.0 cm), over-reported by ≥2.0 kg (2.0 cm), or accurately reported within 2.0 kg (2.0 cm) to account for technical errors of measurement and short-term fluctuations in measured weight (height). A simulation strategy was used to define self-report-based BMI as under-estimated by more than 1.40 kg/m2, over-estimated by more than 1.40 kg/m2, or accurately estimated within 1.40 kg/m2. Patterns of biases in self-reported weight, height, and BMI were explored. Logistic regression was used to identify factors associated with mis-estimated BMI and to calculate adjusted odds ratios (AOR) and 99% confidence intervals (99%CI).
The patterns of bias contributing the most to BMI mis-estimation were consistently, in decreasing order of influence, (1) under-reported weight combined with over-reported height, (2) under-reported weight with accurately reported height, and (3) accurately reported weight with over-reported height. Average bias in self-report-based BMI was -1.34 kg/m2 overall and -0.49, -1.33, and -2.66 kg/m2 in normal, overweight, and obese categories, respectively. Despite the increasing degree of bias with progressively higher BMI categories, persons describing themselves as too heavy were, within any given BMI category, less likely to have under-estimated BMI (AOR 0.5, 99%CI: 0.3-0.8, P < 0.001), to be misclassified in a lower BMI category (AOR 0.3, 99%CI: 0.2-0.5, P < 0.001), to under-report weight (AOR 0.5, 99%CI: 0.3-0.7, P < 0.001), and to over-report height (OR 0.7, 99%CI: 0.6-1.0, P = 0.007).
A novel non-linear approach to examining weight, height, and BMI misreporting biases was developed. Perceiving oneself as too heavy appears to reduce rather than exacerbate weight, height, and BMI misreporting biases.
Social norms; social desirability; BMI bias; misreporting bias; weight bias; height bias; misclassification bias; survey
As the use of self-reported data to classify obesity continues, the temporal change in the accuracy of self-report measurement when compared to clinical measurement remains unclear. The objective of this study was to examine temporal trends in misclassification patterns, as well as sensitivity and specificity, of clinically measured versus self-report based body mass index (BMI) from three national lifestyle surveys over a 10-year period.
The Surveys of Lifestyle Attitudes and Nutrition (SLÁN) were interview based cross-sectional survey/measurements involving nationally representative samples in 1998, 2002 and 2007. Data from a subsample of both self-reported and measured height and weight were available from 66 men and 142 women in 1998, 147 men and 184 women in 2002 and 909 men and 1128 women in 2007. Respondents were classified into the BMI categories normal (< 25 kg m-2), overweight (25- < 30 kg m-2) and obese (≥ 30 kg m-2).
Underreporting of BMI increased across the three surveys (14%→21%→24%; p = 0.002). Sensitivity scores for the normal category exceeded 94% in all three surveys but decreased for the overweight (75%→68%→66%) and obese categories (80%→64%→53%). Simultaneously, specificity levels remained high.
BMI values based on self-reported determinations of height and weight in population samples are underestimating the true prevalence of the obesity epidemic and this underestimation is increasing with time. The decreased sensitivity and consistently high specificity scores in the obese category across time, highlights the limitation of self-report based BMI classifications and the need for simple, readily comprehensible indicators of obesity.
Background: On 29 March 2004, the Republic of Ireland (ROI) became the first EU country to introduce a nationwide ban on workplace smoking. While the focus of this measure was to protect worker health by reducing exposure to second-hand smoke, other effects such as a greater reduction in smoking prevalence and consumption were likely among bar workers. Methods: A random sample of bar workers from Cork city were surveyed before (n = 129) and after (n = 107; 82.9% follow-up rate) implementation of the smoke-free legislation. Self report and combined self report and cotinine concentration were used to determine smoking status. For comparison a cross-sectional random telephone survey of the general population (ROI) was conducted before and 1 year after the smoke-free legislation. There were 1240 pre- and 1221 participants post-ban in the equivalent age and occupational subset of the general population. Results: There was a non-significant decline in smoking prevalence among bar workers 1 year post-ban (self report: −2.8% from 51.4% to 48.6%, P = 0.51; combined self report and cotinine: −4.7% from 56.1% to 51.4%, P = 0.13), but a significant decline in consumption of four cigarettes (95% CI 2.21–6.36) per day. Within the occupationally equivalent general population sub-sample there was a significant drop (3.5%, P = 0.06) in smoking prevalence but no significant change in consumption. Conclusions: Ireland's smoke-free workplace legislation was accompanied by a drop in smoking prevalence in both bar workers and the general population sub-sample.
All Ireland Bar Study; bar workers; cigarette consumption; smoke-free legislation; smoking prevalence; tobacco control