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Background Lifestyles profoundly determine the quality of an individual’s health and life since his childhood. Many diseases in adulthood are avoidable if health-risk behaviors are identified and improved at an early stage of life. The aim of the present research was to characterize a cohort of children aged 6–8 years selected in order to perform an epidemiological molecular study (the MAPEC_LIFE study), investigate lifestyles of the children that could have effect on their health status, and assess possible association between lifestyles and socio-cultural factors. Methods A questionnaire composed of 148 questions was administered in two different seasons to parents of children attending 18 primary schools in five Italian cities (Torino, Brescia, Pisa, Perugia and Lecce) to obtain information regarding the criteria for exclusion from the study, demographic, anthropometric and health information on the children, as well as some aspects on their lifestyles and parental characteristics. The results were analyzed in order to assess the frequency of specific conditions among the different seasons and cities and the association between lifestyles and socio-economic factors. Results The final cohort was composed of 1,164 children (50.9 boys, 95.4% born in Italy). Frequency of some factors appeared different in terms of the survey season (physical activity in the open air, the ways of cooking certain foods) and among the various cities (parents’ level of education and rate of employment, sport, traffic near the home, type of heating, exposure to passive smoking, ways of cooking certain foods). Exposure to passive smoking and cooking fumes, obesity, residence in areas with heavy traffic, frequency of outdoor play and consumption of barbecued and fried foods were higher among children living in families with low educational and/or occupational level while children doing sports and consuming toasted bread were more frequent in families with high socio-economic level. Conclusions The socio-economic level seems to affect the lifestyles of children enrolled in the study including those that could cause health effects. Many factors are linked to the geographical area and may depend on environmental, cultural and social aspects of the city of residence.

Maternal Age at Birth and Childhood Type 1 Diabetes: A Pooled Analysis of 30 Observational Studies Chris R. Cardwell 1 , Lars C. Stene 2 , 3 , Geir Joner 4 , Max K. Bulsara 5 , Ondrej Cinek 6 , Joachim Rosenbauer 7 , Johnny Ludvigsson 8 , Mireia Jané 9 , Jannet Svensson 10 , Michael J. Goldacre 11 , Thomas Waldhoer 12 , Przemysława Jarosz-Chobot 13 , Suely G.A. Gimeno 14 , Lee-Ming Chuang 15 , Roger C. Parslow 16 , Emma J.K. Wadsworth 17 , Amanda Chetwynd 18 , Paolo Pozzilli 19 , Girts Brigis 20 , Brone Urbonaitė 21 , Sandra Šipetić 22 , Edith Schober 23 , Gabriele Devoti 24 , Constantin Ionescu-Tirgoviste 25 , Carine E. de Beaufort 26 , Denka Stoyanov 27 , Karsten Buschard 28 and Chris C. Patterson 1 1 Centre for Public Health, Queen's University Belfast, Belfast, U.K.; 2 Division of Epidemiology, Norwegian Institute of Public Health, Oslo, Norway; 3 Oslo Research Centre, Oslo University Hospital, Oslo, Norway; 4 Institute of Health Management and Health Economics, University of Oslo, Oslo, Norway; 5 Institute of Health and Rehabilitation Research, University of Notre Dame, Freemantle, Australia; 6 The 2nd Medical School, Charles University, Prague, Czech Republic; 7 Institute of Biometrics and Epidemiology, German Diabetes Centre, Leibniz Institute at Dusseldorf University, Dusseldorf, Germany; 8 Department of Paediatrics and Diabetes Research Centre, Linkoping University, Linkoping, Sweden; 9 Public Health Division, Department of Health, Barcelona, Spain; 10 Pediatric Department, Glostrup University Hospital, Glostrup, Denmark; 11 Department of Public Health, Oxford University, Oxford, U.K.; 12 Department of Epidemiology, Medical University of Vienna, Vienna, Austria; 13 Department of Pediatric Endocrinology and Diabetes, Medical University of Silesia, Katowice, Poland; 14 Preventive Medicine Department, Federal University of Sao Paulo, Sao Paulo, Brazil; 15 Department of Internal Medicine, National Taiwan University Hospital, Taipei, Taiwan; 16 Paediatric Epidemiology Group, University of Leeds, Leeds, U.K.; 17 Centre for Occupational and Health Psychology, Cardiff University, Cardiff, U.K.; 18 Mathematics & Statistics Department, Lancaster University, Lancaster, U.K.; 19 University Campus Bio-Medico, Rome, Italy; 20 Department of Public Health and Epidemiology, Riga Stradins University, Riga, Latvia; 21 Institute of Endocrinology, Kaunas University of Medicine, Kaunas, Lithuania; 22 Institute of Epidemiology, School of Medicine, Belgrade University, Belgrade, Serbia; 23 Department of Paediatrics, Medical University of Vienna, Vienna, Austria; 24 Department of Social Sciences and Communication, University of Lecce, Lecce, Italy; 25 Nutrition and Metabolic Diseases Clinic, “N. Paulescu” Institute of Diabetes, Bucharest, Romania; 26 Clinique Pediatrique, Luxembourg, Luxembourg; 27 Children's Diabetic Centre, Sofia, Bulgaria; 28 Bartholin Instituttet, Rigshospitalet, Copenhagen, Denmark. Corresponding author: Chris Cardwell, c.cardwell{at}qub.ac.uk . Abstract OBJECTIVE The aim if the study was to investigate whether children born to older mothers have an increased risk of type 1 diabetes by performing a pooled analysis of previous studies using individual patient data to adjust for recognized confounders. RESEARCH DESIGN AND METHODS Relevant studies published before June 2009 were identified from MEDLINE, Web of Science, and EMBASE. Authors of studies were contacted and asked to provide individual patient data or conduct prespecified analyses. Risk estimates of type 1 diabetes by maternal age were calculated for each study, before and after adjustment for potential confounders. Meta-analysis techniques were used to derive combined odds ratios and to investigate heterogeneity among studies. RESULTS Data were available for 5 cohort and 25 case-control studies, including 14,724 cases of type 1 diabetes. Overall, there was, on average, a 5% (95% CI 2–9) increase in childhood type 1 diabetes odds per 5-year increase in maternal age ( P = 0.006), but there was heterogeneity among studies (heterogeneity I 2 = 70%). In studies with a low risk of bias, there was a more marked increase in diabetes odds of 10% per 5-year increase in maternal age. Adjustments for potential confounders little altered these estimates. CONCLUSIONS There was evidence of a weak but significant linear increase in the risk of childhood type 1 diabetes across the range of maternal ages, but the magnitude of association varied between studies. A very small percentage of the increase in the incidence of childhood type 1 diabetes in recent years could be explained by increases in maternal age. Footnotes The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked “advertisement” in accordance with 18 U.S.C. Section 1734 solely to indicate this fact. Received August 6, 2009. Accepted October 23, 2009. © 2010 by the American Diabetes Association.

To investigate if there is a reduced risk of type 1 diabetes in children breastfed or exclusively breastfed by performing a pooled analysis with adjustment for recognized confounders. Relevant studies were identified from literature searches using MEDLINE, Web of Science, and EMBASE. Authors of relevant studies were asked to provide individual participant data or conduct prespecified analyses. Meta-analysis techniques were used to combine odds ratios (ORs) and investigate heterogeneity between studies. Data were available from 43 studies including 9,874 patients with type 1 diabetes. Overall, there was a reduction in the risk of diabetes after exclusive breast-feeding for >2 weeks (20 studies; OR = 0.75, 95% CI 0.64-0.88), the association after exclusive breast-feeding for >3 months was weaker (30 studies; OR = 0.87, 95% CI 0.75-1.00), and no association was observed after (nonexclusive) breast-feeding for >2 weeks (28 studies; OR = 0.93, 95% CI 0.81-1.07) or >3 months (29 studies; OR = 0.88, 95% CI 0.78-1.00). These associations were all subject to marked heterogeneity (I(2) = 58, 76, 54, and 68%, respectively). In studies with lower risk of bias, the reduced risk after exclusive breast-feeding for >2 weeks remained (12 studies; OR = 0.86, 95% CI 0.75-0.99), and heterogeneity was reduced (I(2) = 0%). Adjustments for potential confounders altered these estimates very little. The pooled analysis suggests weak protective associations between exclusive breast-feeding and type 1 diabetes risk. However, these findings are difficult to interpret because of the marked variation in effect and possible biases (particularly recall bias) inherent in the included studies.

Short interbirth interval has been associated with maternal complications and childhood autism and leukemia, possibly due to deficiencies in maternal micronutrients at conception or increased exposure to sibling infections. A possible association between interbirth interval and subsequent risk of childhood type 1 diabetes has not been investigated. A secondary analysis of 14 published observational studies of perinatal risk factors for type 1 diabetes was conducted. Risk estimates of diabetes by category of interbirth interval were calculated for each study. Random effects models were used to calculate pooled odds ratios (ORs) and investigate heterogeneity between studies. Overall, 2,787 children with type 1 diabetes were included. There was a reduction in the risk of childhood type 1 diabetes in children born to mothers after interbirth intervals <3 years compared with longer interbirth intervals (OR 0.82 [95% CI 0.72-0.93]). Adjustments for various potential confounders little altered this estimate. In conclusion, there was evidence of a 20% reduction in the risk of childhood diabetes in children born to mothers after interbirth intervals <3 years.

The relationship of socioeconomic indicators (education, occupation and residence) to short-term all cause mortality and coronary heart disease (CHD) mortality was evaluated in an Italian population sample. Socioeconomic indicators (education, occupational level and residence) and major CHD risk factors were measured in 12,361 males aged 40-69 years; mortality data by cause were collected for the next 6 years. All cause and CHD mortality risk ratio (RR) in the different educational and occupational levels and residence were computed by Cox proportional hazards models. After 6 years 385 men died, of whom 105 were coronary fatalities. No association with educational level was found for all cause mortality (RR: 1.00 high, 0.71 medium, 0.77 low) and for CHD mortality (RR: 1.00 high, 0.39 intermediate, 0.71 low). Occupational level was significantly associated (p < 0.031) with all cause mortality (RR: 1.00 high-intermediate, 1.27 low). Urban vs. rural residence (RR: 1.00) showed a RR for all cause mortality of 1.33 (p < 0.011). Adjustment for bio-behavioral risk factors did not change the above results; only mortality for CHD of urban vs. rural residents increased (RR: 1.94, p = 0.004). In conclusion the negative association of mortality with occupational level, albeit not with education, indicates that occupation is a better indicator of socioeconomic status in Italy. Status incongruity as well as residence in an urban environment could be risk conditions for total and CHD mortality.

This paper presents a theoretical and mathematical framework for the design of a conformal reconfigurable intelligent surface (RIS) that adapts to non-planar geometries, which is a critical advancement for the deployment of RIS on non-planar and irregular surfaces as envisioned in smart radio environments. Previous research focused mainly on the optimization of RISs assuming a predetermined shape, while neglecting the intricate interplay between shape optimization, phase optimization, and mutual coupling effects. Our contribution, the T3DRIS framework, addresses this fundamental problem by integrating the configuration and shape optimization of RISs into a unified model and design framework, thus facilitating the application of RIS technology to a wider spectrum of environmental objects. The mathematical core of T3DRIS is rooted in optimizing the 3D deployment of the unit cells and tuning circuits, aiming at maximizing the communication performance. Through rigorous full-wave simulations and a comprehensive set of numerical analyses, we validate the proposed approach and demonstrate its superior performance and applicability over contemporary designs. This study-the first of its kind-paves the way for a new direction in RIS research, emphasizing the importance of a theoretical and mathematical perspective in tackling the challenges of conformal RISs.