Irregularidade do ciclo menstrual no Menacme como marcador para fatores de risco cardiovasculares na pós-menopausa

A associação entre fatores de risco cardiovascular (FRCV) na pósmenopausa e o antecedente de irregularidade menstrual no menacme foi avaliado em estudo caso-controle envolvendo 414 mulheres na pósmenopausa com idade de 60,4 ± 5,5 anos e IMC de 25,3 ± 4,7 kg/m2. As variáveis consideradas foram: caracterização do ciclo menstrual entre 20 e 35 anos (independente) e relato atual sobre ocorrência de hipertensão arterial, dislipidemia, diabetes mellitus e doença arterial coronariana (dependentes). Utilizou-se o teste qui-quadrado e modelos de regressão logística, ajustados para outras variáveis implicadas no risco para doenças CV, com nível de significância 5%. Observou-se que mulheres que relataram irregularidade menstrual prévia estiveram associadas com risco aumentado para ocorrência de algum FRCV [odds ratio ajustado (OR)= 2,14; IC-95%= 1,02–4,48], quando comparadas àquelas com ciclos regulares. Análise estratificada demonstrou as seguintes associações significativas com o antecedente de irregularidade menstrual: hipertensão arterial (OR= 2,4; 95% IC= 1,39–5,41), hipercolesterolemia (OR= 2,32; 95% IC= 1,17–4,59), hipertrigliceridemia (OR= 2,09; 95% IC= 1,10–4,33) e angioplastia coronariana (OR= 6,82; 95% IC= 1,44–32,18). Os dados sugerem que o antecedente de irregularidade menstrual, indicativo da ocorrência da síndrome dos ovários policísticos na idade reprodutiva, pode estar relacionado com aumento do risco para doenças CV na pós-menopausa __________________________________________________ABSTRACT Menstrual Cycle Irregularity as a Marker of Cardiovascular Risk Factors at Postmenopausal Years.To evaluate the association between cardiovascular risk factors (CVRF)during postmenopausal years and previous menstrual irregularity during reproductive years, we performed a case-control study in 414 postmenopausal women (mean age 60.4 ± 5.5 years; BMI 25.3 ± 4.7 kg/m2). The variables assessed were: menstrual cycle characteristics at age 20–35y (independent) and records of arterial hypertension, dyslipidemia, diabetes mellitus, and coronary heart disease (dependent). Statistical analysis used the chi-square test and logistic regression, adjusting for potential confounders for cardiovascular risk, with significance set at 5%. Women reporting previous menstrual irregularity were associated with increased risk for some CVRF [adjusted odds ratio (OR) 2.14; CI-95%= 1.02–4.48], when compared with those reporting regular menstrual cycles. Stratified analysis demonstrated significant associations of previous menstrual irregularity with: arterial hypertension [OR= 2.74; CI-95%= 1.39–5.41), hypercholesterolemia (OR= 2.32; CI-95%= 1.17–4.59), hypertriglyceridemia (OR= 2.09; CI-95%=1.10–4.33), and coronary angioplasty (OR= 6.82; CI-95%= 1.44–32.18). These data suggest that a prior history of menstrual irregularity, as indicative of polycystic ovary syndrome, may be related to increased risk for CVD during postmenopausal years

Swimming training repercussion on metabolic and structural bone development: benefits of the incorporation of whole body vibration or pilometric training; the RENACIMIENTO project

Introduction: Enviromental factors such as exercise participation and nutrition have often been linked to bone improvements. However, not all sports have the same effects, being non-osteogenic sports such as swimming defined as negative or neutral sports to practice regarding bone mass by some authors, similarly exercise-diet interaction in especific groups is still not clear. Objective: To present the methodology of the RENACIMENTO project that aims to evaluate body composition and more specifically bone mass by several techniques in adolescent swimmers and to observe the effects and perdurability of whole body vibration (WBV) and jumping intervention (JIN) on body composition and fitness on this population and explore posible diet interactions. Design: Randomized controlled trial. Methods: 78 swimmers (12-17 y) and 26 sex- and age-matched controls will participate in this study. Dual energy X-ray, peripheral Quantitative Computed Tomography, Quantitative Ultrasound, Bioelectrical Impedance Analysis, and anthropometry measurements will be performed in order to evaluate body composition. Physical activity, nutrition, pubertal development and socio-economical status may act as confounders of body composition and therefore will also be registered. Several fitness factors regarding strength, endurance, performance and others will also be registered to evaluate differences with controls and act as confounders. A 7-month WBV therapy will be performed by 26 swimmers consisting of a training of 15 minutes 3 times per week. An 8 month JIM will also be performed by 26 swimmers 3 times per week. The remaining 26 swimmers will continue their normal swimming training. Four evaluations will be performed, the first one in order to describe differences between swimmers and controls. The second one to describe the effects of the interventions and the third and fourth evaluations to describe the perdurability of the effects of the WBV and JIN. Conclusion: The RENACIMIENTO project will allow to answer several questions regarding body composition, fitness, bone mass and interaction with diet of adolescent swimmers, describe swimming as a positive, negative or neutral sport to practice regarding these parameters and elucidate the effects and perdurability of WBV and JIM on body composition.

Is there a relation between environmental exposure to teratogenic substances during pregnancy and congenital anomalies in the newborn? A pilot study in Portugal

Background: Maternal occupation as a proxy of environmental exposure has been consistently associated with specific congenital anomalies (CA) in the foetus and newborn. On the other hand, geographical location of the mother such as place of residence and place of work have not been used as proxy for environmental exposures during pregnancy. We designed a pilot study aiming to investigate the association between maternal place of residence and workplace during pregnancy and CA in Portugal. Methods: Cases and controls are identified in the maternity unit. Cases are all live births with at least one CA delivered in the Barreiro hospital located in a heavy industrial area near Lisboa. Controls are the two normal births following each case. Residents outside the study area, stillbirths and women who decline to participate or are incapable of giving consent are excluded. A health professional interviews the mothers using a questionnaire adapted from the registry form of the Portuguese national registry of CA and includes information on places during pregnancy (residence, workplace, leisure), and demographic characterization as place of birth, infant sex, weight, description of CA, age of mother, ethnicity, maternal birth place. Maternal health and obstetric history, education, smoking, alcohol, drugs and medication use is also collected as potential confounders. Results: The pilot study started in January 2016 and at the moment two cases and four controls have been recruited without refusals. The study will continue to be implemented and it is proposed to start in other hospital units during 2016.

Efetividade da vacina antigripal sazonal na época 2015/2016: resultados do projeto EuroEVA

O projeto EuroEVA pretende obter estimativas da efetividade da vacina antigripal (EV), para a população geral e para o grupo-alvo para o qual é recomendada. Os resultados apresentados correspondem à sua implementação na época 2015/2016. Utilizou-se um delineamento caso-controlo teste negativo, onde os casos, indivíduos com síndrome gripal (SG) e com diagnóstico laboratorial positivo para o vírus da gripe, foram comparados com os controlos, indivíduos com SG e diagnóstico laboratorial negativo para o vírus da gripe. Os participantes foram selecionados entre os doentes com SG observados em consulta de cuidados de saúde primários. Foi recolhida informação clinica e epidemiológica e um exsudado da nasofaringe para diagnóstico laboratorial. A EV foi estimada através de 1- odd ratio de estar vacinado nos casos vs. controlos, ajustado para a idade, presença de doença crónica, número de consultas com médico de família (MF) nos últimos 12 meses, número de coabitantes, nível de escolaridade, sexo e mês de início de sintomas. Entre as semanas 48/2015 e 17/2016, foram recrutados 310 indivíduos com SG sendo que, após exclusão de 26 indivíduos por não cumprirem os critérios de inclusão, foram incluídos 124 casos e 186 controlos. De entre os casos, 89,5% eram positivos para o vírus da gripe do subtipo A(H1) pdm09 e 8,9% para o tipo B/Victoria. Relativamente à vacina antigripal, a cobertura era de 10,5% nos casos e 23,7% nos controlos. Após ajustamento, a EV em 2015/2016 foi de 56,1% (IC95%: 3,5%; 80,0%) e 65,8% (IC95%:12,5%; 86,7%), respetivamente na população geral e no grupo-alvo para a vacinação antigripal. Estes resultados sugerem que a vacina antigripal nesta época conferiu uma proteção moderada. As estimativas da EV estão em linha com resultados publicados por outros países europeus.

Analyzing change in medication use - statistical approaches

The objective of this study was to gain an understanding of the effects of population heterogeneity, missing data, and causal relationships on parameter estimates from statistical models when analyzing change in medication use. From a public health perspective, two timely topics were addressed: the use and effects of statins in populations in primary prevention of cardiovascular disease and polypharmacy in older population. Growth mixture models were applied to characterize the accumulation of cardiovascular and diabetes medications among apparently healthy population of statin initiators. The causal effect of statin adherence on the incidence of acute cardiovascular events was estimated using marginal structural models in comparison with discrete-time hazards models. The impact of missing data on the growth estimates of evolution of polypharmacy was examined comparing statistical models under different assumptions for missing data mechanism. The data came from Finnish administrative registers and from the population-based Geriatric Multidisciplinary Strategy for the Good Care of the Elderly study conducted in Kuopio, Finland, during 2004–07. Five distinct patterns of accumulating medications emerged among the population of apparently healthy statin initiators during two years after statin initiation. Proper accounting for time-varying dependencies between adherence to statins and confounders using marginal structural models produced comparable estimation results with those from a discrete-time hazards model. Missing data mechanism was shown to be a key component when estimating the evolution of polypharmacy among older persons. In conclusion, population heterogeneity, missing data and causal relationships are important aspects in longitudinal studies that associate with the study question and should be critically assessed when performing statistical analyses. Analyses should be supplemented with sensitivity analyses towards model assumptions.

Reference ranges for uterine artery pulsatility index during the menstrual cycle: a cross-sectional study

Cyclic endometrial neoangiogenesis contributes to changes in local vascular patterns and is amenable to non-invasive assessment with Doppler sonography. We hypothesize that the uterine artery (UtA) impedance, measured by its pulsatility index (PI), exhibits a regular pattern during the normal menstrual cycle. Therefore, the main study objective was to derive normative new day-cycle-based reference ranges for the UtA-PI during the entire cycle from days 1 to 34 according to the isolated time effect and potential confounders such as age and parity.

The cytokinesis-block micronucleus (CBMN) assay in human populations exposed to styrene: a systematic review and meta-analysis

Styrene is a building-block of several compounds used in a wide array of materials and products. The most important human exposure to this substance occurs in industrial settings, especially among reinforced-plastics industry workers. The effect of occupational exposure to styrene on cytogenetics biomarkers has been previously reviewed with positive association observed for chromosomal aberrations, and inconclusive data for the micronucleus assay. Some limitations were noted in those studies, including inadequate exposure assessment and poor epidemiological design. Furthermore, in earlier studies micronuclei frequency was measured with protocols not as reliable as cytokinesis-block micronucleus (CBMN) assay. Aim of the present systematic review and meta-analysis is to investigate genomic instability and DNA damage as measured by the CBMN assay in lymphocytes of subjects exposed to styrene. A total of 11 studies published between 2004 and 2012 were included in the meta-analysis encompassing 479 styrene-exposed workers and 510 controls. The quality of each study was estimated by a quality scoring system which ranked studies according to the consideration of major confounders, exposure characterization, and technical parameters. An overall increase of micronuclei frequencies was found in styrene-exposure workers when compared to referents (meta-MR 1.34; 95% CI 1.18–1.52), with significant increases achieved in six individual studies. The consistency of results in individual studies, the independence of this result from major confounding factors and from the quality of the study strengthens the reliability of risk estimates and supports the use of the CBMN assay in monitoring genetic risk in styrene workers.

Quantification of air quality in space and time and its effects on health

The long-term adverse effects on health associated with air pollution exposure can be estimated using either cohort or spatio-temporal ecological designs. In a cohort study, the health status of a cohort of people are assessed periodically over a number of years, and then related to estimated ambient pollution concentrations in the cities in which they live. However, such cohort studies are expensive and time consuming to implement, due to the long-term follow up required for the cohort. Therefore, spatio-temporal ecological studies are also being used to estimate the long-term health effects of air pollution as they are easy to implement due to the routine availability of the required data. Spatio-temporal ecological studies estimate the health impact of air pollution by utilising geographical and temporal contrasts in air pollution and disease risk across $n$ contiguous small-areas, such as census tracts or electoral wards, for multiple time periods. The disease data are counts of the numbers of disease cases occurring in each areal unit and time period, and thus Poisson log-linear models are typically used for the analysis. The linear predictor includes pollutant concentrations and known confounders such as socio-economic deprivation. However, as the disease data typically contain residual spatial or spatio-temporal autocorrelation after the covariate effects have been accounted for, these known covariates are augmented by a set of random effects. One key problem in these studies is estimating spatially representative pollution concentrations in each areal which are typically estimated by applying Kriging to data from a sparse monitoring network, or by computing averages over modelled concentrations (grid level) from an atmospheric dispersion model. The aim of this thesis is to investigate the health effects of long-term exposure to Nitrogen Dioxide (NO2) and Particular matter (PM10) in mainland Scotland, UK. In order to have an initial impression about the air pollution health effects in mainland Scotland, chapter 3 presents a standard epidemiological study using a benchmark method. The remaining main chapters (4, 5, 6) cover the main methodological focus in this thesis which has been threefold: (i) how to better estimate pollution by developing a multivariate spatio-temporal fusion model that relates monitored and modelled pollution data over space, time and pollutant; (ii) how to simultaneously estimate the joint effects of multiple pollutants; and (iii) how to allow for the uncertainty in the estimated pollution concentrations when estimating their health effects. Specifically, chapters 4 and 5 are developed to achieve (i), while chapter 6 focuses on (ii) and (iii). In chapter 4, I propose an integrated model for estimating the long-term health effects of NO2, that fuses modelled and measured pollution data to provide improved predictions of areal level pollution concentrations and hence health effects. The air pollution fusion model proposed is a Bayesian space-time linear regression model for relating the measured concentrations to the modelled concentrations for a single pollutant, whilst allowing for additional covariate information such as site type (e.g. roadside, rural, etc) and temperature. However, it is known that some pollutants might be correlated because they may be generated by common processes or be driven by similar factors such as meteorology. The correlation between pollutants can help to predict one pollutant by borrowing strength from the others. Therefore, in chapter 5, I propose a multi-pollutant model which is a multivariate spatio-temporal fusion model that extends the single pollutant model in chapter 4, which relates monitored and modelled pollution data over space, time and pollutant to predict pollution across mainland Scotland. Considering that we are exposed to multiple pollutants simultaneously because the air we breathe contains a complex mixture of particle and gas phase pollutants, the health effects of exposure to multiple pollutants have been investigated in chapter 6. Therefore, this is a natural extension to the single pollutant health effects in chapter 4. Given NO2 and PM10 are highly correlated (multicollinearity issue) in my data, I first propose a temporally-varying linear model to regress one pollutant (e.g. NO2) against another (e.g. PM10) and then use the residuals in the disease model as well as PM10, thus investigating the health effects of exposure to both pollutants simultaneously. Another issue considered in chapter 6 is to allow for the uncertainty in the estimated pollution concentrations when estimating their health effects. There are in total four approaches being developed to adjust the exposure uncertainty. Finally, chapter 7 summarises the work contained within this thesis and discusses the implications for future research.

Exploring the potential role of allostatic load biomarkers in risk assessment of patients presenting with depressive symptoms

Background: Depression is a major health problem worldwide and the majority of patients presenting with depressive symptoms are managed in primary care. Current approaches for assessing depressive symptoms in primary care are not accurate in predicting future clinical outcomes, which may potentially lead to over or under treatment. The Allostatic Load (AL) theory suggests that by measuring multi-system biomarker levels as a proxy of measuring multi-system physiological dysregulation, it is possible to identify individuals at risk of having adverse health outcomes at a prodromal stage. Allostatic Index (AI) score, calculated by applying statistical formulations to different multi-system biomarkers, have been associated with depressive symptoms. Aims and Objectives: To test the hypothesis, that a combination of allostatic load (AL) biomarkers will form a predictive algorithm in defining clinically meaningful outcomes in a population of patients presenting with depressive symptoms. The key objectives were: 1. To explore the relationship between various allostatic load biomarkers and prevalence of depressive symptoms in patients, especially in patients diagnosed with three common cardiometabolic diseases (Coronary Heart Disease (CHD), Diabetes and Stroke). 2 To explore whether allostatic load biomarkers predict clinical outcomes in patients with depressive symptoms, especially in patients with three common cardiometabolic diseases (CHD, Diabetes and Stroke). 3 To develop a predictive tool to identify individuals with depressive symptoms at highest risk of adverse clinical outcomes. Methods: Datasets used: ‘DepChron’ was a dataset of 35,537 patients with existing cardiometabolic disease collected as a part of routine clinical practice. ‘Psobid’ was a research data source containing health related information from 666 participants recruited from the general population. The clinical outcomes for 3 both datasets were studied using electronic data linkage to hospital and mortality health records, undertaken by Information Services Division, Scotland. Cross-sectional associations between allostatic load biomarkers calculated at baseline, with clinical severity of depression assessed by a symptom score, were assessed using logistic and linear regression models in both datasets. Cox’s proportional hazards survival analysis models were used to assess the relationship of allostatic load biomarkers at baseline and the risk of adverse physical health outcomes at follow-up, in patients with depressive symptoms. The possibility of interaction between depressive symptoms and allostatic load biomarkers in risk prediction of adverse clinical outcomes was studied using the analysis of variance (ANOVA) test. Finally, the value of constructing a risk scoring scale using patient demographics and allostatic load biomarkers for predicting adverse outcomes in depressed patients was investigated using clinical risk prediction modelling and Area Under Curve (AUC) statistics. Key Results: Literature Review Findings. The literature review showed that twelve blood based peripheral biomarkers were statistically significant in predicting six different clinical outcomes in participants with depressive symptoms. Outcomes related to both mental health (depressive symptoms) and physical health were statistically associated with pre-treatment levels of peripheral biomarkers; however only two studies investigated outcomes related to physical health. Cross-sectional Analysis Findings: In DepChron, dysregulation of individual allostatic biomarkers (mainly cardiometabolic) were found to have a non-linear association with increased probability of co-morbid depressive symptoms (as assessed by Hospital Anxiety and Depression Score HADS-D≥8). A composite AI score constructed using five biomarkers did not lead to any improvement in the observed strength of the association. In Psobid, BMI was found to have a significant cross-sectional association with the probability of depressive symptoms (assessed by General Health Questionnaire GHQ-28≥5). BMI, triglycerides, highly sensitive C - reactive 4 protein (CRP) and High Density Lipoprotein-HDL cholesterol were found to have a significant cross-sectional relationship with the continuous measure of GHQ-28. A composite AI score constructed using 12 biomarkers did not show a significant association with depressive symptoms among Psobid participants. Longitudinal Analysis Findings: In DepChron, three clinical outcomes were studied over four years: all-cause death, all-cause hospital admissions and composite major adverse cardiovascular outcome-MACE (cardiovascular death or admission due to MI/stroke/HF). Presence of depressive symptoms and composite AI score calculated using mainly peripheral cardiometabolic biomarkers was found to have a significant association with all three clinical outcomes over the following four years in DepChron patients. There was no evidence of an interaction between AI score and presence of depressive symptoms in risk prediction of any of the three clinical outcomes. There was a statistically significant interaction noted between SBP and depressive symptoms in risk prediction of major adverse cardiovascular outcome, and also between HbA1c and depressive symptoms in risk prediction of all-cause mortality for patients with diabetes. In Psobid, depressive symptoms (assessed by GHQ-28≥5) did not have a statistically significant association with any of the four outcomes under study at seven years: all cause death, all cause hospital admission, MACE and incidence of new cancer. A composite AI score at baseline had a significant association with the risk of MACE at seven years, after adjusting for confounders. A continuous measure of IL-6 observed at baseline had a significant association with the risk of three clinical outcomes- all-cause mortality, all-cause hospital admissions and major adverse cardiovascular event. Raised total cholesterol at baseline was associated with lower risk of all-cause death at seven years while raised waist hip ratio- WHR at baseline was associated with higher risk of MACE at seven years among Psobid participants. There was no significant interaction between depressive symptoms and peripheral biomarkers (individual or combined) in risk prediction of any of the four clinical outcomes under consideration. Risk Scoring System Development: In the DepChron cohort, a scoring system was constructed based on eight baseline demographic and clinical variables to predict the risk of MACE over four years. The AUC value for the risk scoring system was modest at 56.7% (95% CI 55.6 to 57.5%). In Psobid, it was not possible to perform this analysis due to the low event rate observed for the clinical outcomes. Conclusion: Individual peripheral biomarkers were found to have a cross-sectional association with depressive symptoms both in patients with cardiometabolic disease and middle-aged participants recruited from the general population. AI score calculated with different statistical formulations was of no greater benefit in predicting concurrent depressive symptoms or clinical outcomes at follow-up, over and above its individual constituent biomarkers, in either patient cohort. SBP had a significant interaction with depressive symptoms in predicting cardiovascular events in patients with cardiometabolic disease; HbA1c had a significant interaction with depressive symptoms in predicting all-cause mortality in patients with diabetes. Peripheral biomarkers may have a role in predicting clinical outcomes in patients with depressive symptoms, especially for those with existing cardiometabolic disease, and this merits further investigation.

Effort-reward imbalance and sedentary lifestyle: an observational study in a large occupational cohort

Objectives: To investigate the association between effort-reward imbalance (ERI) at work and sedentary lifestyle. Methods: Cross-sectional data from the ongoing Finnish Public Sector Study related to 30 433 women and 7718 men aged 17-64 were used (n = 35 918 after exclusion of participants with missing values in covariates). From the responses to a questionnaire, an aggregated mean score for ERI in a work unit was assigned to each participant. The outcome was sedentary lifestyle defined as <2.00 metabolic equivalent task (MET) hours/day. Logistic regression with generalized estimating equations was used as an analysis method to include both individual and work unit level predictors in the models. Adjustments were made for age, marital status, occupational status, job contract, smoking, and heavy drinking. Results: Twenty five percent of women and 27% of men had a sedentary lifestyle. High individual level ERI was associated with a higher likelihood of sedentary lifestyle both among women (odds ratio (OR) = 1.08, 95% CI 1.01 to 1.16) and men (OR = 1.17, 95% CI 1.02 to 1.33). These associations were not explained by relevant confounders and they were also independent of work unit level job strain measured as a ratio of job demands and control. Conclusions: A mismatch between high occupational effort spent and low reward received in turn seems to be associated with an elevated risk of sedentary lifestyle, although this association is relatively weak.

Association of body composition indices with insulin resistance in European adolescents: the HELENA study

Background: The different body components may contribute to the development of insulin resistance and type 2 diabetes mellitus. The aim of the present study was to examine the association of fat mass and fat free mass indices with markers of insulin resistance, independently of each other and giving, at the same time, gender-specific information in a wide cohort of European adolescents. Methods: A cross-sectional study in a school setting was conducted in 925 (430 males) adolescents (14.9 ± 1.2 years). Weight, height, anthropometric, bioimpedance and blood parameters were measured. Indices for fat mass and fat free mass, and homeostatic model assessment (HOMA) were calculated. Multiple regression analyses were performed adjusting for several confounders including fat free mass and fat mass when possible. Results: Indices of fat mass were positively associated with HOMA (all p < 0.01) after adjusting for all the confounders including fat free mass indices, in both sexes. Fat free mass indices were associated with HOMA, in both males and females, after adjusting for center, pubertal status, socioeconomic status and cardiorespiratory fitness, but the associations disappear when including fat mass indices in the adjustment's model. Conclusion: Fat mass indices derived from different methods are positively associated with insulin resistance independently of several confounders including fat free mass indices. In addition, the relationship of fat free mass with insulin resistance is influenced by the amount of fat mass in European adolescents. Nevertheless, future studies should focus not only on the role of fat mass, but also on other body components such as fat free mass because its role could vary depending of the level and distribution of fat mass.

Estimating the risk of cardiovascular disease using an obese-years metric

OBJECTIVE: To examine the association between obese-years and the risk of cardiovascular disease (CVD).

STUDY DESIGN: Prospective cohort study.

SETTING: Boston, USA.

PARTICIPANTS: 5036 participants of the Framingham Heart Study were examined.

METHODS: Obese-years was calculated by multiplying for each participant the number of body mass index (BMI) units above 29 kg/m(2) by the number of years lived at that BMI during approximately 50 years of follow-up. The association between obese-years and CVD was analysed using time-dependent Cox regression adjusted for potential confounders and compared with other models using the Akaike information criterion (AIC). The lowest AIC indicated better fit.

PRIMARY OUTCOME CVD RESULTS: The median cumulative obese-years was 24 (range 2-556 obese-years). During 138,918 person-years of follow-up, 2753 (55%) participants were diagnosed with CVD. The incidence rates and adjusted HR (AHR) for CVD increased with an increase in the number of obese-years. AHR for the categories 1-24.9, 25-49.9, 50-74.9 and ≥75 obese-years were, respectively, 1.31 (95% CI 1.15 to 1.48), 1.37 (95% CI 1.14 to 1.65), 1.62 (95% CI 1.32 to 1.99) and 1.80 (95% CI 1.54 to 2.10) compared with those who were never obese (ie, had zero obese-years). The effect of obese-years was stronger in males than females. For every 10 unit increase in obese-years, the AHR of CVD increased by 6% (95% CI 4% to 8%) for males and 3% (95% CI 2% to 4%) for females. The AIC was lowest for the model containing obese-years compared with models containing either the level of BMI or the duration of obesity alone.

CONCLUSIONS: This study demonstrates that obese-years metric conceptually captures the cumulative damage of obesity on body systems, and is found to provide slightly more precise estimation of the risk of CVD than the level or duration of obesity alone.

Association between maternal education and objectively measured physical activity and sedentary time in adolescents

BACKGROUND: Investigating socioeconomic variation in physical activity (PA) and sedentary time is important as it may represent a pathway by which socioeconomic position (SEP) leads to ill health. Findings on the association between children's SEP and objectively assessed PA and/or sedentary time are mixed, and few studies have included international samples.

OBJECTIVE: Examine the associations between maternal education and adolescent's objectively assessed PA and sedentary time.

METHODS: This is an observational study of 12 770 adolescents (10-18 years) pooled from 10 studies from Europe, Australia, Brazil and the USA. Original PA data were collected between 1997 and 2009. The associations between maternal education and accelerometer variables were examined using robust multivariable regression, adjusted for a priori confounders (ie, body mass index, monitor wear time, season, age and sex) and regression coefficients combined across studies using random effects meta-analyses. Analyses were conducted in March 2014.

RESULTS: Adolescents of university educated mothers spent more time sedentary (9.5 min/day, p=0.005) and less time in light activity (10 min/day, p<0.001) compared with adolescents of high school educated mothers. Pooled analysis across two studies from Brazil and Portugal (analysed separately because of the different coding of maternal education) showed that children of higher educated mothers (tertiary vs primary/secondary) spent less time in moderate to vigorous PA (MVPA) (6.6 min/day, p=0.001) and in light PA (39.2 min/day: p<0.001), and more time sedentary (45.9 min/day, p<0.001).

CONCLUSIONS: Across a number of international samples, adolescents of mothers with lower education may not be at a disadvantage in terms of overall objectively measured PA.

Housing tenure and affordability and mental health following disability acquisition in adulthood

Acquiring a disability in adulthood is associated with a reduction in mental health and access to secure and affordable housing is associated with better mental health. We hypothesised that the association between acquisition of disability and mental health is modified by housing tenure and affordability. We used twelve annual waves of data (2001-2012) (1913 participants, 13,037 observations) from the Household, Income and Labour Dynamics in Australia survey. Eligible participants reported at least two consecutive waves of disability preceded by two consecutive waves without disability. Effect measure modification, on the additive scale, was tested in three fixed-effects linear regression models (which remove time-invariant confounding) which included a cross-product term between disability and prior housing circumstances: housing tenure by disability; housing affordability by disability and, in a sub-sample (896 participants 5913 observations) with housing costs, tenure/affordability by disability. The outcome was the continuous mental component summary (MCS) of SF-36. Models adjusted for time-varying confounders. There was statistical evidence that prior housing modified the effect of disability acquisition on mental health. Our findings suggested that those in affordable housing had a -1.7 point deterioration in MCS (95% CI -2.1, -1.3) following disability acquisition and those in unaffordable housing had a -4.2 point reduction (95% CI -5.2, -1.4). Among people with housing costs, the largest declines in MCS were for people with unaffordable mortgages (-5.3, 95% CI -8.8, -1.9) and private renters in unaffordable housing (-4.0, 95% CI -6.3, -1.6), compared to a -1.4 reduction (95% CI -2.1, -0.7) for mortgagors in affordable housing. In sum, we used causally-robust fixed-effects regression and showed that deterioration in mental health following disability acquisition is modified by prior housing circumstance with the largest negative associations found for those in unaffordable housing. Future research should test whether providing secure, affordable housing when people acquire a disability prevents deterioration in mental health.

An investigation of neighborhood-level social, economic and physical factors for railway suicide in Victoria, Australia

BACKGROUND: This study investigates the associations between railway suicide and neighborhood social, economic, and physical determinants using postcode-level data. It also examines whether the associations are influenced by having high concentration of high-risk individuals in a neighborhood area. METHODS: Railway suicide cases from Victoria, Australia for the period of 2001-2012, their age, sex, year of death, usual residential address and suicide location were obtained from the National Coronial Information System. Univariate negative binomial regression models were used to estimate the association between railway suicide and neighborhood-level social, economic and physical factors. Variables which were significant in these univariate models were then assessed in a multivariate model, controlling for age and sex of the deceased and other known confounders. RESULTS: Findings from the multivariate analysis indicate that an elevated rate of railway suicide was strongly associated with neighborhood exposure of higher number of railway stations (IRR=1.30 95% CI=1.16-1.46). Other significant neighborhood risk factors included patronage volume (IRR=1.06, 95% CI=1.02-1.11) and train frequency (IRR=1.02, 95% CI=1.01-1.04). An increased number of video surveillance systems at railway stations and carparks was significantly associated with a modest reduction in railway suicide risk (IRR=0.93, 95% CI=0.88-0.98). These associations were independent of concentration of high-risk individuals. LIMITATIONS: Railway suicide may be under-reported in Australia. CONCLUSIONS: Interventions to prevent railway suicide should target vulnerable individuals residing in areas characterized by high station density, patronage volume and train frequency.