Imperial College London

ProfessorAlinaRodriguez

Faculty of MedicineSchool of Public Health

Visiting Professor
 
 
 
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Contact

 

+44 (0)20 7594 0941a.rodriguez

 
 
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Location

 

168Medical SchoolSt Mary's Campus

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Summary

 

Publications

Publication Type
Year
to

77 results found

Rodriguez A, 2021, The link between Attention Deficit Hyperactivity Disorder (ADHD) symptoms and obesity-related traits: Genetic and prenatal explanations, Translational Psychiatry, Vol: 11, Pages: 1-8, ISSN: 2158-3188

Attention-deficit/hyperactivity disorder (ADHD) often co-occurs with obesity, however the potential causality between the traits remains unclear. We examined both genetic and prenatal evidence for causality using Mendelian Randomisation (MR) and polygenic risk scores (PRS). We conducted bi-directional MR on ADHD liability and six obesity-related traits using summary statistics from the largest available meta-analyses of genome-wide association studies. We also examined the shared genetic aetiology between ADHD symptoms (inattention and hyperactivity) and body mass index (BMI) by PRS association analysis using longitudinal data from Northern Finland Birth Cohort 1986 (NFBC1986, n = 2984). Lastly, we examined the impact of prenatal environment by association analysis of maternal pre-pregnancy BMI and offspring ADHD symptoms, adjusted for PRS of both traits, in NFBC1986 dataset. Through MR analyses, we found evidence for bidirectional causality between ADHD liability and obesity-related traits. PRS association analyses showed evidence for genetic overlap between ADHD symptoms and BMI. We found no evidence for a difference between inattention and hyperactivity symptoms, suggesting that neither symptom subtype is driving the association. We found evidence for association between maternal pre-pregnancy BMI and offspring ADHD symptoms after adjusting for both BMI and ADHD PRS (association p-value = 0.027 for inattention, p = 0.008 for hyperactivity). These results are consistent with the hypothesis that the co-occurrence between ADHD and obesity has both genetic and prenatal environmental origins.

Journal article

van der Laan CM, Morosoli-García JJ, van de Weijer SGA, Colodro-Conde L, ACTION Consortium, Lupton MK, Mitchell BL, McAloney K, Parker R, Burns JM, Hickie IB, Pool R, Hottenga J-J, Martin NG, Medland SE, Nivard MG, Boomsma DIet al., 2021, Continuity of genetic risk for aggressive behavior across the life-course, Behavior Genetics: an international journal devoted to research in the inheritance of behavior in animals and man, Vol: 51, Pages: 592-606, ISSN: 0001-8244

We test whether genetic influences that explain individual differences in aggression in early life also explain individual differences across the life-course. In two cohorts from The Netherlands (N = 13,471) and Australia (N = 5628), polygenic scores (PGSs) were computed based on a genome-wide meta-analysis of childhood/adolescence aggression. In a novel analytic approach, we ran a mixed effects model for each age (Netherlands: 12-70 years, Australia: 16-73 years), with observations at the focus age weighted as 1, and decaying weights for ages further away. We call this approach a 'rolling weights' model. In The Netherlands, the estimated effect of the PGS was relatively similar from age 12 to age 41, and decreased from age 41-70. In Australia, there was a peak in the effect of the PGS around age 40 years. These results are a first indication from a molecular genetics perspective that genetic influences on aggressive behavior that are expressed in childhood continue to play a role later in life.

Journal article

Ip HF, van der Laan CM, Krapohl EML, Brikell I, Sanchez-Mora C, Nolte IM, St Pourcain B, Bolhuis K, Palviainen T, Zafarmand H, Colodro-Conde L, Gordon S, Zayats T, Aliev F, Jiang C, Wang CA, Saunders G, Karhunen V, Hammerschlag AR, Adkins DE, Border R, Peterson RE, Prinz JA, Thiering E, Seppala I, Vilor-Tejedor N, Ahluwalia TS, Day FR, Hottenga J-J, Allegrini AG, Rimfeld K, Chen Q, Lu Y, Martin J, Soler Artigas M, Rovira P, Bosch R, Espanol G, Ramos Quiroga JA, Neumann A, Ensink J, Grasby K, Morosoli JJ, Tong X, Marrington S, Middeldorp C, Scott JG, Vinkhuyzen A, Shabalin AA, Corley R, Evans LM, Sugden K, Alemany S, Sass L, Vinding R, Ruth K, Tyrrell J, Davies GE, Ehli EA, Hagenbeek FA, De Zeeuw E, Van Beijsterveldt TCEM, Larsson H, Snieder H, Verhulst FC, Amin N, Whipp AM, Korhonen T, Vuoksimaa E, Rose RJ, Uitterlinden AG, Heath AC, Madden P, Haavik J, Harris JR, Helgeland O, Johansson S, Knudsen GPS, Njolstad PR, Lu Q, Rodriguez A, Henders AK, Mamun A, Najman JM, Brown S, Hopfer C, Krauter K, Reynolds C, Smolen A, Stallings M, Wadsworth S, Wall TL, Silberg JL, Miller A, Keltikangas-Jarvinen L, Hakulinen C, Pulkki-Raback L, Havdahl A, Magnus P, Raitakari OT, Perry JRB, Llop S, Lopez-Espinosa M-J, Bonnelykke K, Bisgaard H, Sunyer J, Lehtimaki T, Arseneault L, Standl M, Heinrich J, Boden J, Pearson J, Horwood LJ, Kennedy M, Poulton R, Eaves LJ, Maes HH, Hewitt J, Copeland WE, Costello EJ, Williams GM, Wray N, Jarvelin M-R, McGue M, Iacono W, Caspi A, Moffitt TE, Whitehouse A, Pennell CE, Klump KL, Burt SA, Dick DM, Reichborn-Kjennerud T, Martin NG, Medland SE, Vrijkotte T, Kaprio J, Tiemeier H, Davey Smith G, Hartman CA, Oldehinkel AJ, Casas M, Ribases M, Lichtenstein P, Lundstrom S, Plomin R, Bartels M, Nivard MG, Boomsma DIet al., 2021, Genetic association study of childhood aggression across raters, instruments, and age, Translational Psychiatry, Vol: 11, Pages: 1-9, ISSN: 2158-3188

Childhood aggressive behavior (AGG) has a substantial heritability of around 50%. Here we present a genome-wide association meta-analysis (GWAMA) of childhood AGG, in which all phenotype measures across childhood ages from multiple assessors were included. We analyzed phenotype assessments for a total of 328 935 observations from 87 485 children aged between 1.5 and 18 years, while accounting for sample overlap. We also meta-analyzed within subsets of the data, i.e., within rater, instrument and age. SNP-heritability for the overall meta-analysis (AGGoverall) was 3.31% (SE = 0.0038). We found no genome-wide significant SNPs for AGGoverall. The gene-based analysis returned three significant genes: ST3GAL3 (P = 1.6E–06), PCDH7 (P = 2.0E–06), and IPO13 (P = 2.5E–06). All three genes have previously been associated with educational traits. Polygenic scores based on our GWAMA significantly predicted aggression in a holdout sample of children (variance explained = 0.44%) and in retrospectively assessed childhood aggression (variance explained = 0.20%). Genetic correlations (rg) among rater-specific assessment of AGG ranged from rg = 0.46 between self- and teacher-assessment to rg = 0.81 between mother- and teacher-assessment. We obtained moderate-to-strong rgs with selected phenotypes from multiple domains, but hardly with any of the classical biomarkers thought to be associated with AGG. Significant genetic correlations were observed with most psychiatric and psychological traits (range

Journal article

Mireku MO, Rodriguez A, 2021, Sleep duration and waking activities in relation to the national sleep foundation's recommendations: an analysis of US population sleep patterns from 2015 to 2017, International Journal of Environmental Research and Public Health, Vol: 18, Pages: 1-15, ISSN: 1660-4601

The objective was to investigate the association between time spent on waking activities and nonaligned sleep duration in a representative sample of the US population. We analysed time use data from the American Time Use Survey (ATUS), 2015–2017 (N = 31,621). National Sleep Foundation (NSF) age-specific sleep recommendations were used to define recommended (aligned) sleep duration. The balanced, repeated, replicate variance estimation method was applied to the ATUS data to calculate weighted estimates. Less than half of the US population had a sleep duration that mapped onto the NSF recommendations, and alignment was higher on weekdays (45%) than at weekends (33%). The proportion sleeping longer than the recommended duration was higher than those sleeping shorter on both weekdays and weekends (p < 0.001). Time spent on work, personal care, socialising, travel, TV watching, education, and total screen time was associated with nonalignment to the sleep recommendations. In comparison to the appropriate recommended sleep group, those with a too-short sleep duration spent more time on work, travel, socialising, relaxing, and leisure. By contrast, those who slept too long spent relatively less time on each of these activities. The findings indicate that sleep duration among the US population does not map onto the NSF sleep recommendations, mostly because of a higher proportion of long sleepers compared to short sleepers. More time spent on work, travel, and socialising and relaxing activities is strongly associated with an increased risk of nonalignment to NSF sleep duration recommendations.

Journal article

Curtis F, Laparidou D, Bridle C, Law GR, Durrant S, Rodriguez A, Pierzycki RH, Siriwardena ANet al., 2021, Effects of cognitive behavioural therapy on insomnia in adults with tinnitus: Systematic review and meta-analysis of randomised controlled trials, SLEEP MEDICINE REVIEWS, Vol: 56, ISSN: 1087-0792

Journal article

LBD Double Burden of Malnutrition Collaborators, 2020, Author correction: Mapping local patterns of childhood overweight and wasting in low- and middle-income countries between 2000 and 2017., Nature Methods, Vol: 26, Pages: 1308-1308, ISSN: 1548-7091

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Journal article

Bert Valdespino J, Naranjo Bert I, Morales AR, 2020, Las redes de apoyo en el contexto educativo escolar, familiar y comunitario: debate imprescindible para las prácticas educativas inclusivas, Revista Científica Ciencia y Tecnología, Vol: 27, Pages: 1-9, ISSN: 1390-6321

<jats:p>La formación del profesional de la educación, sobre todo la concerniente al campo de actuación de la enseñanza básica elemental, tiene retos esenciales dentro de su proceso de prácticas relativas a la inclusión. En este trabajo se dejan una serie de reflexiones de las autoras basadas primero en los referentes teóricos que sobresalen en la región y el mundo sobre el tema y segundo desde la experiencia práctica y la investigación del tema que ya acumula más de veinte años. El análisis lleva a las personas que por su vínculo directo representan un apoyo imprescindible para los niños con los que el estudiante trabaja desde su práctica y de los que necesita para incorporar modos de actuación loables en su formación.</jats:p>

Journal article

Neumann A, Nolte IM, Pappa I, Ahluwalia TS, Pettersson E, Rodriguez A, Whitehouse A, van Beijsterveldt CEM, Benyamin B, Hammerschlag AR, Helmer Q, Karhunen V, Krapohl E, Lu Y, van der Most PJ, Palviainen T, Pourcain BS, Seppälä I, Suarez A, Vilor-Tejedor N, Tiesler CMT, Wang C, Wills A, Zhou A, Alemany S, Bisgaard H, Bønnelykke K, Davies GE, Hakulinen C, Henders AK, Hyppönen E, Stokholm J, Bartels M, Hottenga J-J, Heinrich J, Hewitt J, Keltikangas-Järvinen L, Korhonen T, Kaprio J, Lahti J, Lahti-Pulkkinen M, Lehtimäki T, Middeldorp CM, Najman JM, Pennell C, Power C, Oldehinkel AJ, Plomin R, Räikkönen K, Raitakari OT, Rimfeld K, Sass L, Snieder H, Standl M, Sunyer J, Williams GM, Bakermans-Kranenburg MJ, Boomsma DI, van IJzendoorn MH, Hartman CA, Tiemeier Het al., 2020, A genome-wide association study of total child psychiatric problems scores

<jats:title>ABSTRACT</jats:title><jats:p>Substantial genetic correlations have been reported across psychiatric disorders and numerous cross-disorder genetic variants have been detected. To identify the genetic variants underlying general psychopathology in childhood, we performed a genome-wide association study using a total psychiatric problem score. We analyzed 6,844,199 common SNPs in 38,418 school-aged children from 20 population-based cohorts participating in the EArly Genetics and Lifecourse Epidemiology (EAGLE) consortium. The SNP heritability of total psychiatric problems was 5.4% (SE=0.01) and two loci reached genome-wide significance: rs10767094 and rs202005905. We also observed an association of <jats:italic>SBF2</jats:italic>, a gene associated with neuroticism in previous GWAS, with total psychiatric problems. The genetic effects underlying the total psychiatric problem score were shared with known genetic variants for common psychiatric disorders only (attention-deficit/hyperactivity disorder, anxiety, depression, insomnia) (r<jats:sub>G</jats:sub> &gt; 0.49), but not with autism or the less common adult disorders (schizophrenia, bipolar disorder, or eating disorders) (r<jats:sub>G</jats:sub> &lt; 0.01). Importantly, the total psychiatric problem score also showed at least a moderate genetic correlation of with intelligence, educational attainment, wellbeing, smoking, and body fat (r<jats:sub>G</jats:sub> &gt; 0.29).The results suggest that many common genetic variants are associated with childhood psychiatric symptoms and related phenotypes in general instead of with specific symptoms. Further research is needed to establish causality and pleiotropic mechanisms between psychiatric disorders and related traits.</jats:p>

Journal article

LBD Double Burden of Malnutrition Collaborators, 2020, Mapping local patterns of childhood overweight and wasting in low- and middle-income countries between 2000 and 2017, Nature Medicine, Vol: 26, Pages: 750-759, ISSN: 1078-8956

A double burden of malnutrition occurs when individuals, household members or communities experience both undernutrition and overweight. Here, we show geospatial estimates of overweight and wasting prevalence among children under 5 years of age in 105 low- and middle-income countries (LMICs) from 2000 to 2017 and aggregate these to policy-relevant administrative units. Wasting decreased overall across LMICs between 2000 and 2017, from 8.4% (62.3 (55.1–70.8) million) to 6.4% (58.3 (47.6–70.7) million), but is predicted to remain above the World Health Organization’s Global Nutrition Target of <5% in over half of LMICs by 2025. Prevalence of overweight increased from 5.2% (30 (22.8–38.5) million) in 2000 to 6.0% (55.5 (44.8–67.9) million) children aged under 5 years in 2017. Areas most affected by double burden of malnutrition were located in Indonesia, Thailand, southeastern China, Botswana, Cameroon and central Nigeria. Our estimates provide a new perspective to researchers, policy makers and public health agencies in their efforts to address this global childhood syndemic.

Journal article

Mireku MO, Rodriguez A, 2020, Family income gradients in adolescent obesity, overweight and adiposity persist in extremely deprived and extremely affluent neighbourhoods but not in middle-class Neighbourhoods: evidence from the UK millennium cohort study, International Journal of Environmental Research and Public Health, Vol: 17, Pages: 1-12, ISSN: 1660-4601

We investigated whether family income gradients in obesity, overweight, and adiposity persist at geographic-level deprivation quintiles using a nationally representative cohort of UK adolescents. Data from 11,714 eligible adolescents from the sixth sweep of the Millennium Cohort Study (14 years old) were analysed in this study. The International Obesity Task Force age- and sex-specific thresholds were used to define obesity and overweight. Self-reported family income was standardized using the Organisation for Economic Co-operation and Development (OECD)’s equivalised income scale. Geographic-level deprivation was defined by the index of multiple deprivation 2004. Results showed that the prevalence of obesity and overweight was 8.0% and 27.2%, respectively. Mean percentage body fat was 16.9% (standard error, SE = 0.2%) in male and 27.3% (SE = 0.1%) in female adolescents. Risk of obesity, overweight, and adiposity increased with decreasing family income quintiles (p for trend <0.001). After stratifying by geographic-level deprivation quintiles, a U-shaped association emerged, whereby family income gradients in the risk of adolescent obesity and adiposity persisted in extremely affluent and extremely deprived neighbourhoods but attenuated to non-significance in middle-class neighbourhoods. These results focus on the findings from England. Recognition of the persistence of inequalities in the risk of obesity in the most deprived and affluent neighbourhoods may be necessary in planning public health resources and interventions.

Journal article

Karhunen V, Jarvelin M-R, Evangelou M, Rodriguez Aet al., 2019, A MENDELIAN RANDOMISATION STUDY ON CAUSALITY BETWEEN ATTENTION-DEFICIT/HYPERACTIVITY DISORDER AND MULTIPLE OBESITY-RELATED TRAITS, 27th World Congress of Psychiatric Genetics (WCPG), Publisher: ELSEVIER, Pages: S114-S115, ISSN: 0924-977X

Conference paper

Alves AC, De Silva NMG, Karhunen V, Sovio U, Das S, Rob Taal H, Warrington NM, Lewin AM, Kaakinen M, Cousminer DL, Thiering E, Timpson NJ, Bond TA, Lowry E, Brown CD, Estivill X, Lindi V, Bradfield JP, Geller F, Speed D, Coin LJM, Loh M, Barton SJ, Beilin LJ, Bisgaard H, Bønnelykke K, Alili R, Hatoum IJ, Schramm K, Cartwright R, Charles MA, Salerno V, Clément K, Claringbould AAJ, Van Duijn CM, Moltchanova E, Eriksson JG, Elks C, Feenstra B, Flexeder C, Franks S, Frayling TM, Freathy RM, Elliott P, Widén E, Hakonarson H, Hattersley AT, Rodriguez A, Banterle M, Heinrich J, Heude B, Holloway JW, Hofman A, Hyppönen E, Inskip H, Kaplan LM, Hedman AK, Läärä E, Prokisch H, Grallert H, Lakka TA, Lawlor DA, Melbye M, Ahluwalia TS, Marinelli M, Millwood IY, Palmer LJ, Pennell CE, Perry JR, Ring SM, Savolainen MJ, Rivadeneira F, Standl M, Sunyer J, Tiesler CMT, Uitterlinden AG, Schierding W, Sullivan OM, Prokopenko I, Herzig KH, Smith GD, O'Reilly P, Felix JF, Buxton JL, Blakemore AIF, Ong KK, Jaddoe VWV, Grant SFA, Sebert S, McCarthy MI, Järvelin MRet al., 2019, GWAS on longitudinal growth traits reveals different genetic factors influencing infant, child, and adult BMI, Science Advances, Vol: 5, ISSN: 2375-2548

Early childhood growth patterns are associated with adult health, yet the genetic factors and the developmental stages involved are not fully understood. Here we combine genome-wide association studies with modelling of longitudinal growth traits to study the genetics of infant and child growth, followed by functional, pathway, genetic correlation, risk score and co-localization analyses to determine how developmental timings, molecular pathways and genetic determinants of these traits overlap with those of adult health. We found a robust overlap between the genetics of child and adult BMI, with variants associated with adult BMI acting as early as 4-6 years old. However, we demonstrated a completely distinct genetic makeup for peak BMI during infancy, influenced by variation at the LEPR/LEPROT locus. These findings suggest that different genetic factors control infant and child BMI. In light of the obesity epidemic, these findings are important to inform the timing and targets of prevention strategies.

Journal article

Rodriguez A, 2019, Dysregulation in early life is a marker of persistent regulatory problems, 49th Annual Conference of the International-Society-of-Psychoneuroendocrinology - 50 Years of Psychoneuroendocrinology - Returning to Where It All Began, Publisher: PERGAMON-ELSEVIER SCIENCE LTD, Pages: 64-65, ISSN: 0306-4530

Conference paper

Wiklund P, Karhunen V, Richmond RC, Parmar P, Rodriguez A, De Silva M, Wielscher M, Rezwan FI, Richardson TG, Veijola J, Herzig KH, Holloway JW, Relton CL, Sebert S, Järvelin MRet al., 2019, DNA methylation links prenatal smoking exposure to later life health outcomes in offspring, Clinical Epigenetics, Vol: 11, ISSN: 1868-7075

Background: Maternal smoking during pregnancy is associated with adverse offspring health outcomes across their life course. We hypothesize that DNA methylation is a potential mediator of this relationship. Methods: We examined the association of prenatal maternal smoking with offspring blood DNA methylation in 2821 individuals (age 16 to 48 years) from five prospective birth cohort studies and perform Mendelian randomization and mediation analyses to assess whether methylation markers have causal effects on disease outcomes in the offspring. Results: We identify 69 differentially methylated CpGs in 36 genomic regions (P value < 1 × 10-7) associated with exposure to maternal smoking in adolescents and adults. Mendelian randomization analyses provided evidence for a causal role of four maternal smoking-related CpG sites on an increased risk of inflammatory bowel disease or schizophrenia. Further mediation analyses showed some evidence of cg25189904 in GNG12 gene mediating the effect of exposure to maternal smoking on schizophrenia-related outcomes. Conclusions: DNA methylation may represent a biological mechanism through which maternal smoking is associated with increased risk of psychiatric morbidity in the exposed offspring.

Journal article

Middeldorp CM, Felix JF, Mahajan A, McCarthy MI, EArly Genetics Lifecourse Epidemiology EAGLE consortium, Early Growth Genetics EGG, Rodriguez Aet al., 2019, The Early Growth Genetics (EGG) and EArly Genetics and Lifecourse Epidemiology (EAGLE) consortia: design, results and future prospects, European Journal of Epidemiology, Vol: 34, Pages: 279-300, ISSN: 0393-2990

The impact of many unfavorable childhood traits or diseases, such as low birth weight and mental disorders, is not limited to childhood and adolescence, as they are also associated with poor outcomes in adulthood, such as cardiovascular disease. Insight into the genetic etiology of childhood and adolescent traits and disorders may therefore provide new perspectives, not only on how to improve wellbeing during childhood, but also how to prevent later adverse outcomes. To achieve the sample sizes required for genetic research, the Early Growth Genetics (EGG) and EArly Genetics and Lifecourse Epidemiology (EAGLE) consortia were established. The majority of the participating cohorts are longitudinal population-based samples, but other cohorts with data on early childhood phenotypes are also involved. Cohorts often have a broad focus and collect(ed) data on various somatic and psychiatric traits as well as environmental factors. Genetic variants have been successfully identified for multiple traits, for example, birth weight, atopic dermatitis, childhood BMI, allergic sensitization, and pubertal growth. Furthermore, the results have shown that genetic factors also partly underlie the association with adult traits. As sample sizes are still increasing, it is expected that future analyses will identify additional variants. This, in combination with the development of innovative statistical methods, will provide detailed insight on the mechanisms underlying the transition from childhood to adult disorders. Both consortia welcome new collaborations. Policies and contact details are available from the corresponding authors of this manuscript and/or the consortium websites.

Journal article

Rodriguez A, Wang Y, Khan AA, Cartwright R, Gissler M, Jarvelin M-Ret al., 2019, Antenatal corticosteroid therapy (ACT) and size at birth: A population-based analysis using the Finnish Medical Birth Register, PLoS Medicine, Vol: 16, ISSN: 1549-1277

BackgroundAntenatal corticosteroid therapy (ACT) is used clinically to prepare the fetal lung for impending preterm birth, but animal and human studies link corticosteroids to smaller birth size. Whether ACT is associated with birth size is debated; therefore, we assessed differences in birth size in treated versus untreated pregnancies.Methods and findingsThis observational register-based study used data from the Finnish Medical Birth Register (FMBR) covering all births in Finland (January 1, 2006–December 31, 2010). We used unadjusted and adjusted regression analyses as well as propensity score matching (PSM) to analyze whether birth size differed by ACT exposure. PSM provides a stringent comparison, as subsamples were created matched on baseline and medical characteristics between treated and untreated women. All analyses were stratified by timing of birth. The primary study outcome was birth size: birth weight (BWT), birth length (BL), ponderal index (PI), and head circumference (HC) measured immediately after birth and recorded in the FMBR. Additional analyses explored indicators of neonatal health in relation to ACT exposure and birth size. A total of 278,508 live-born singleton births with ≥24 gestational completed weeks were registered in the FMBR during the 5-year study period. Over 4% of infants were born preterm, and 4,887 women were treated with ACT (1.75%). More than 44% of the exposed infants (n = 2,173) were born at term. First, results of unadjusted regression analyses using the entire sample showed the greatest reductions in BWT as compared to the other analytic methods: very preterm −61.26 g (±SE 24.12, P < 0.01), preterm −232.90 g (±SE 17.24, P < .001), near term −171.50 g (±SE 17.52, P < .001), and at term −101.95 g (±SE 10.89, P < .001). Second, using the entire sample, regression analyses adjusted for baseline and medical conditions showed significant differences in BWT be

Journal article

Wiklund P, Karhunen V, Richmond RC, Rodriguez A, De Silva M, Wielscher M, Rezwan FI, Richardson TG, Veijola J, Heinz-Herzig K, Holloway JW, Relton CL, Sebert S, Järvelin M-Ret al., 2018, DNA methylation links prenatal smoking exposure to later life health outcomes in offspring, Publisher: Cold Spring Harbor Laboratory

<jats:title>Abstract</jats:title><jats:p>Maternal smoking during pregnancy is associated with adverse offspring health outcomes across their life course. We hypothesize that DNA methylation is a potential mediator of this relationship. To test this, we examined the association of prenatal maternal smoking with DNA methylation in 2,821 individuals (age 16 to 48 years) from five prospective birth cohort studies and perform Mendelian randomization and mediation analyses to assess, whether methylation markers have causal effects on disease outcomes in the offspring. We identify 69 differentially methylated CpGs in 36 genomic regions (P &lt; 1×10<jats:sup>−7</jats:sup>), and show that DNA methylation may represent a biological mechanism through which maternal smoking is associated with increased risk of psychiatric morbidity in the exposed offspring.</jats:p>

Working paper

Karhunen V, Wiklund P, Jarvelin M-R, Rodriguez Aet al., 2018, Joint genetic factors of body mass index and ADHD components, 27th Annual Meeting of the International-Genetic-Epidemiology-Society (IGES), Publisher: WILEY, Pages: 709-709, ISSN: 0741-0395

Conference paper

Nordstrom T, Hurtig T, Rodriguez A, Savolainen J, Rautio A, Moilanen I, Taanila A, Ebeling Het al., 2017, Different Risk Factors Between Disruptive Behavior Disorders and ADHD in Northern Finland Birth Cohort 1986, JOURNAL OF ATTENTION DISORDERS, Vol: 21, Pages: 904-912, ISSN: 1087-0547

Journal article

Reitsma MB, Fullman N, Ng M, Salama JS, Abajobir A, Abate KH, Abbafati C, Abera SF, Abraham B, Abyu GY, Adebiyi AO, Al-Aly Z, Aleman AV, Ali R, Al Alkerwi A, Allebeck P, Al-Raddadi RM, Amare AT, Amberbir A, Ammar W, Amrock SM, Antonio CAT, Asayesh H, Atnafu NT, Azzopardi P, Banerjee A, Barac A, Barrientos-Gutierrez T, Basto-Abreu AC, Bazargan-Hejazi S, Bedi N, Bell B, Bello AK, Bensenor IM, Beyene AS, Bhala N, Biryukov S, Bolt K, Brenner H, Butt Z, Cavalleri F, Cercy K, Chen H, Christopher DJ, Ciobanu LG, Colistro V, Colomar M, Cornaby L, Dai X, Damtew SA, Dandona L, Dandona R, Dansereau E, Davletov K, Dayama A, Degfie TT, Deribew A, Dharmaratne SD, Dimtsu BD, Doyle KE, Endries AY, Ermakov SP, Estep K, Faraon EJA, Farzadfar F, Feigin VL, Feigl AB, Fischer F, Friedman J, Ghiwot TT, Gall SL, Gao W, Gillum RF, Gold AL, Gopalani SV, Gotay CC, Gupta R, Gupta R, Gupta V, Hamadeh RR, Hankey G, Harb HL, Hay SI, Horino M, Horita N, Hosgood HD, Husseini A, Ileanu BV, Islami F, Jiang G, Jiang Y, Jonas JB, Kabir Z, Kamal R, Kasaeian A, Kesavachandran CN, Khader YS, Khalil I, Khang Y-H, Khera S, Khubchandani J, Kim D, Kim YJ, Kimokoti RW, Kinfu Y, Knibbs LD, Kokubo Y, Kolte D, Kopec J, Kosen S, Kotsakis GA, Koul PA, Koyanagi A, Krohn KJ, Krueger H, Defo BK, Bicer BK, Kulkarni C, Kumar GA, Leasher JL, Lee A, Leinsalu M, Li T, Linn S, Liu P, Liu S, Lo L-T, Lopez AD, Ma S, Abd El Razek HM, Majeed A, Malekzadeh R, Malta DC, Manamo WA, Martinez-Raga J, Mekonnen AB, Mendoza W, Miller TR, Mohammad KA, Morawska L, Musa KI, Nagel G, Neupane SP, Quyen N, Nguyen G, Oh I-H, Oyekale AS, Mahesh PA, Pana A, Park E-K, Patil ST, Patton GC, Pedro J, Qorbani M, Rafay A, Rahman M, Rai RK, Ram U, Ranabhat CL, Refaat AH, Reinig N, Roba HS, Rodriguez A, Roman Y, Roth G, Roy A, Sagar R, Salomon J, Sanabria J, Santos IDS, Sartorius B, Satpathy M, Sawhney M, Sawyer S, Saylan M, Schaub MP, Schluger N, Schutte AE, Sepanlou SG, Serdar B, Shaikh MA, She J, Shin M-J, Shiri R, Shishani K, Shiue I, Sigfusdottiret al., 2017, Smoking prevalence and attributable disease burden in 195 countries and territories, 1990-2015: a systematic analysis from the Global Burden of Disease Study 2015, LANCET, Vol: 389, Pages: 1885-1906, ISSN: 0140-6736

Background:The scale-up of tobacco control, especially after the adoption of the Framework Convention for Tobacco Control, is a major public health success story. Nonetheless, smoking remains a leading risk for early death and disability worldwide, and therefore continues to require sustained political commitment. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) offers a robust platform through which global, regional, and national progress toward achieving smoking-related targets can be assessed.Methods:We synthesised 2818 data sources with spatiotemporal Gaussian process regression and produced estimates of daily smoking prevalence by sex, age group, and year for 195 countries and territories from 1990 to 2015. We analysed 38 risk-outcome pairs to generate estimates of smoking-attributable mortality and disease burden, as measured by disability-adjusted life-years (DALYs). We then performed a cohort analysis of smoking prevalence by birth-year cohort to better understand temporal age patterns in smoking. We also did a decomposition analysis, in which we parsed out changes in all-cause smoking-attributable DALYs due to changes in population growth, population ageing, smoking prevalence, and risk-deleted DALY rates. Finally, we explored results by level of development using the Socio-demographic Index (SDI).Findings:Worldwide, the age-standardised prevalence of daily smoking was 25·0% (95% uncertainty interval [UI] 24·2–25·7) for men and 5·4% (5·1–5·7) for women, representing 28·4% (25·8–31·1) and 34·4% (29·4–38·6) reductions, respectively, since 1990. A greater percentage of countries and territories achieved significant annualised rates of decline in smoking prevalence from 1990 to 2005 than in between 2005 and 2015; however, only four countries had significant annualised increases in smoking prevalence between 2005 and 2015 (Congo [Brazz

Journal article

Hinney A, Kesselmeier M, Jall S, Volckmar AL, Föcker M, Antel J, GCAN, WTCCC3, Heid IM, Winkler TW, GIANT, Grant SF EGG, Guo Y, Bergen AW, Kaye W, Berrettini W, Hakonarson H, Price Foundation Collaborative Group, Childrens Hospital of PhiladelphiaPrice Foundation, Herpertz-Dahlmann B, de Zwaan M, Herzog W, Ehrlich S, Zipfel S, Egberts KM, Adan R, Brandys M, van Elburg A, Boraska Perica V, Franklin CS, Tschöp MH, Zeggini E, Bulik CM, Collier D, Scherag A, Müller TD, Hebebrand Jet al., 2017, Evidence for three genetic loci involved in both anorexia nervosa risk and variation of body mass index., Mol Psychiatry, Vol: 22, Pages: 192-201

The maintenance of normal body weight is disrupted in patients with anorexia nervosa (AN) for prolonged periods of time. Prior to the onset of AN, premorbid body mass index (BMI) spans the entire range from underweight to obese. After recovery, patients have reduced rates of overweight and obesity. As such, loci involved in body weight regulation may also be relevant for AN and vice versa. Our primary analysis comprised a cross-trait analysis of the 1000 single-nucleotide polymorphisms (SNPs) with the lowest P-values in a genome-wide association meta-analysis (GWAMA) of AN (GCAN) for evidence of association in the largest published GWAMA for BMI (GIANT). Subsequently we performed sex-stratified analyses for these 1000 SNPs. Functional ex vivo studies on four genes ensued. Lastly, a look-up of GWAMA-derived BMI-related loci was performed in the AN GWAMA. We detected significant associations (P-values <5 × 10(-5), Bonferroni-corrected P<0.05) for nine SNP alleles at three independent loci. Interestingly, all AN susceptibility alleles were consistently associated with increased BMI. None of the genes (chr. 10: CTBP2, chr. 19: CCNE1, chr. 2: CARF and NBEAL1; the latter is a region with high linkage disequilibrium) nearest to these SNPs has previously been associated with AN or obesity. Sex-stratified analyses revealed that the strongest BMI signal originated predominantly from females (chr. 10 rs1561589; Poverall: 2.47 × 10(-06)/Pfemales: 3.45 × 10(-07)/Pmales: 0.043). Functional ex vivo studies in mice revealed reduced hypothalamic expression of Ctbp2 and Nbeal1 after fasting. Hypothalamic expression of Ctbp2 was increased in diet-induced obese (DIO) mice as compared with age-matched lean controls. We observed no evidence for associations for the look-up of BMI-related loci in the AN GWAMA. A cross-trait analysis of AN and BMI loci revealed variants at three chromosomal loci with potential joint impact. The chromosome 10 locus is particularly pr

Journal article

Forouzanfar MH, Afshin A, Alexander LT, Anderson HR, Bhutta ZA, Biryukov S, Brauer M, Burnett R, Cercy K, Charlson FJ, Cohen AJ, Dandona L, Estep K, Ferrari AJ, Frostad JJ, Fullman N, Gething PW, Godwin WW, Griswold M, Kinfu Y, Kyu HH, Larson HJ, Liang X, Lim SS, Liu PY, Lopez AD, Lozano R, Marczak L, Mensah GA, Mokdad AH, Moradi-Lakeh M, Naghavi M, Neal B, Reitsma MB, Roth GA, Salomon JA, Sur PJ, Vos T, Wagner JA, Wang H, Zhao Y, Zhou M, Aasvang GM, Abajobir AA, Abate KH, Abbafati C, Abbas KM, Abd-Allah F, Abdulle AM, Abera SF, Abraham B, Abu-Raddad LJ, Abyu GY, Adebiyi AO, Adedeji IA, Ademi Z, Adou AK, Adsuar JC, Agardh EE, Agarwal A, Agrawal A, Kiadaliri AA, Ajala ON, Akinyemiju TF, Al-Aly Z, Alam K, Alam NKM, Aldhahri SF, Aldridge RW, Alemu ZA, Ali R, Alkerwi A, Alla F, Allebeck P, Alsharif U, Altirkawi KA, Martin EA, Alvis-Guzman N, Amare AT, Amberbir A, Amegah AK, Amini H, Ammar W, Amrock SM, Andersen HH, Anderson BO, Antonio CAT, Anwari P, Ärnlöv J, Artaman A, Asayesh H, Asghar RJ, Assadi R, Atique S, Avokpaho EFGA, Awasthi A, Quintanilla BPA, Azzopardi P, Bacha U, Badawi A, Bahit MC, Balakrishnan K, Barac A, Barber RM, Barker-Collo SL, Bärnighausen T, Barquera S, Barregard L, Barrero LH, Basu S, Batis C, Bazargan-Hejazi S, Beardsley J, Bedi N, Beghi E, Bell ML, Bello AK, Bennett DA, Bensenor IM, Berhane A, Bernabé E, Betsu BD, Beyene AS, Bhala N, Bhansali A, Bhatt S, Biadgilign S, Bikbov B, Bisanzio D, Bjertness E, Blore JD, Borschmann R, Boufous S, Bourne RRA, Brainin M, Brazinova A, Breitborde NJK, Brenner H, Broday DM, Brugha TS, Brunekreef B, Butt ZA, Cahill LE, Calabria B, Campos-Nonato IR, Cárdenas R, Carpenter DO, Casey DC, Castañeda-Orjuela CA, Rivas JC, Castro RE, Catalá-López F, Chang J, Chiang PP, Chibalabala M, Chimed-Ochir O, Chisumpa VH, Chitheer AA, Choi JJ, Christensen H, Christopher DJ, Ciobanu LG, Coates MM, Colquhoun SM, Cooper LT, Cooperrider K, Cornaby L, Cortinovis M, Crump JA, Cuevas-Nasu L, Damasceno A, Dandona R, Darby SC, Dargan PIet al., 2016, Global, regional, and national comparative risk assessment of 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks, 1990-2015: a systematic analysis for the Global Burden of Disease Study 2015, The Lancet, Vol: 388, Pages: 1659-1724, ISSN: 0140-6736

SummaryBackground The Global Burden of Diseases, Injuries, and Risk Factors Study 2015 provides an up-to-date synthesis of the evidence for risk factor exposure and the attributable burden of disease. By providing national and subnational assessments spanning the past 25 years, this study can inform debates on the importance of addressing risks in context. Methods We used the comparative risk assessment framework developed for previous iterations of the Global Burden of Disease Study to estimate attributable deaths, disability-adjusted life-years (DALYs), and trends in exposure by age group, sex, year, and geography for 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks from 1990 to 2015. This study included 388 risk-outcome pairs that met World Cancer Research Fund-defined criteria for convincing or probable evidence. We extracted relative risk and exposure estimates from randomised controlled trials, cohorts, pooled cohorts, household surveys, census data, satellite data, and other sources. We used statistical models to pool data, adjust for bias, and incorporate covariates. We developed a metric that allows comparisons of exposure across risk factors—the summary exposure value. Using the counterfactual scenario of theoretical minimum risk level, we estimated the portion of deaths and DALYs that could be attributed to a given risk. We decomposed trends in attributable burden into contributions from population growth, population age structure, risk exposure, and risk-deleted cause-specific DALY rates. We characterised risk exposure in relation to a Socio-demographic Index (SDI). Findings Between 1990 and 2015, global exposure to unsafe sanitation, household air pollution, childhood underweight, childhood stunting, and smoking each decreased by more than 25%. Global exposure for several occupational risks, high body-mass index (BMI), and drug use increased by more than 25% over the same period. All risks jointly evaluated

Journal article

Young SJ, Absoud M, Blackburn C, Branney P, Colley B, Farrag E, Fleisher S, Gudjonsson G, Kim K, O'Malley K, Plant M, Rodriguez A, Ozer S, Takon I, Woodhouse E, Mukherjee Ret al., 2016, Guidelines for identification ad treatment of individuals with Attention Deficit/Hyperactivity Disorder and associated Fetal Alcohol Spectrum disorders based upon expert consensus, BMC Psychiatry, Vol: 16, ISSN: 1471-244X

Background: The association of attention deficit/hyperactivity disorder (ADHD) and fetal alcoholspectrum disorders (FASD) results in a complex constellation of symptoms that complicates thesuccessful diagnosis and treatment of the affected individual. Current literature lacks formal guidelines,randomized control trials, and evidence-based treatment plans for individuals with ADHD and associatedFASD. Therefore, a meeting of professional experts was organized with the aim of producing a 3consensus on identification and treatment guidelines that will aid clinicians in caring for this uniquepatient population.Methods: Experts from multiple disciplines in the fields of ADHD and FASD convened in London, UnitedKingdom, for a meeting hosted by the United Kingdom ADHD Partnership (UKAP; www.UKADHD.com) inJune 2015. The meeting provided the opportunity to address the complexities of ADHD and FASD fromdifferent perspectives and included presentations, discussions, and group work. The attendees workedtowards producing a consensus for a unified approach to ADHD and associated FASD.Results: The authors successfully came to consensus and produced recommended guidelines withspecific regards to identification and assessment, interventions and treatments, and multiagencyliaisons and care management, highlighting that a lifespan approach to treatment needs to be adoptedby all involved. Included in the guidelines are: 1) unique ‘red flags’, which when identified in the ADHDpopulation can lead to an accurate associated FASD diagnosis, 2) a treatment decision tree, and 3)recommendations for multiagency care management.Conclusions: While clinically useful guidelines were achieved, more research is still needed to contributeto the knowledge base about the diagnosis, treatment, and management of those with ADHD andassociated FASD.

Journal article

GBD 2015 Collaborators, Piel FBJ, 2016, Measuring the health-related Sustainable Development Goals in 188 countries: a baseline analysis from the Global Burden of Disease Study 2015, The Lancet, Vol: 388, Pages: 1813-1850, ISSN: 0140-6736

BackgroundIn September, 2015, the UN General Assembly established the Sustainable Development Goals (SDGs). The SDGs specify 17 universal goals, 169 targets, and 230 indicators leading up to 2030. We provide an analysis of 33 health-related SDG indicators based on the Global Burden of Diseases, Injuries, and Risk Factors Study 2015 (GBD 2015).MethodsWe applied statistical methods to systematically compiled data to estimate the performance of 33 health-related SDG indicators for 188 countries from 1990 to 2015. We rescaled each indicator on a scale from 0 (worst observed value between 1990 and 2015) to 100 (best observed). Indices representing all 33 health-related SDG indicators (health-related SDG index), health-related SDG indicators included in the Millennium Development Goals (MDG index), and health-related indicators not included in the MDGs (non-MDG index) were computed as the geometric mean of the rescaled indicators by SDG target. We used spline regressions to examine the relations between the Socio-demographic Index (SDI, a summary measure based on average income per person, educational attainment, and total fertility rate) and each of the health-related SDG indicators and indices.FindingsIn 2015, the median health-related SDG index was 59·3 (95% uncertainty interval 56·8–61·8) and varied widely by country, ranging from 85·5 (84·2–86·5) in Iceland to 20·4 (15·4–24·9) in Central African Republic. SDI was a good predictor of the health-related SDG index (r2=0·88) and the MDG index (r2=0·92), whereas the non-MDG index had a weaker relation with SDI (r2=0·79). Between 2000 and 2015, the health-related SDG index improved by a median of 7·9 (IQR 5·0–10·4), and gains on the MDG index (a median change of 10·0 [6·7–13·1]) exceeded that of the non-MDG index (a median change of 5·5 [2·1–8·

Journal article

Rodriguez A, 2016, Are maternal depression symptoms related to umbilical cord cortisol and neurological integrity in the newborn?, 46th Annual Conference of the International-Society-of-Psychoneuroendocrinology - Personalized Medicine in the Neurosciences - Genetics, Imaging, and Hormones, Publisher: PERGAMON-ELSEVIER SCIENCE LTD, Pages: 37-37, ISSN: 0306-4530

Conference paper

Pappa I, St Pourcain B, Benke K, Cavadino A, Hakulinen C, Nivard MG, Nolte IM, Tiesler CMT, Bakermans-Kranenburg MJ, Davies GE, Evans DM, Geoffroy M-C, Grallert H, Groen-Blokhuis MM, Hudziak JJ, Kemp JP, Keltikangas-Jarvinen L, McMahon G, Mileva-Seitz VR, Motazedi E, Power C, Raitakari OT, Ring SM, Rivadeneira F, Rodriguez A, Scheet PA, Seppala I, Snieder H, Standl M, Thiering E, Timpson NJ, Veenstra R, Velders FP, Whitehouse AJO, Smith GD, Heinrich J, Hypponen E, Lehtimaki T, Middeldorp CM, Oldehinkel AJ, Pennell CE, Boomsma DI, Tiemeier Het al., 2016, A Genome-Wide Approach to Children's Aggressive Behavior: The EAGLE consortium, AMERICAN JOURNAL OF MEDICAL GENETICS PART B-NEUROPSYCHIATRIC GENETICS, Vol: 171, Pages: 562-572, ISSN: 1552-4841

Journal article

Alderete E, Bejarano I, Rodriguez A, 2016, Beverage intake and obesity in early childhood: evidence form primary health care clients in Northwest Argentina, JOURNAL OF DEVELOPMENTAL ORIGINS OF HEALTH AND DISEASE, Vol: 7, Pages: 244-252, ISSN: 2040-1744

Journal article

Kyu HH, Pinho C, Wagner JA, Brown JC, Bertozzi-Villa A, Charlson FJ, Coffeng LE, Dandona L, Erskine HE, Ferrari AJ, Fitzmaurice C, Fleming TD, Forouzanfar MH, Graetz N, Guinovart C, Haagsma J, Higashi H, Kassebaum NJ, Larson HJ, Lim SS, Mokdad AH, Moradi-Lakeh M, Odell SV, Roth GA, Serina PT, Stanaway JD, Misganaw A, Whiteford HA, Wolock TM, Hanson SW, Abd-Allah F, Abera SF, Abu-Raddad LJ, AlBuhairan FS, Amare AT, Antonio CAT, Artaman A, Barker-Collo SL, Barrero LH, Benjet C, Bensenor IM, Bhutta ZA, Bikbov B, Brazinova A, Campos-Nonato I, Castaneda-Orjuela CA, Catala-Lopez F, Chowdhury R, Cooper C, Crump JA, Dandona R, Degenhardt L, Dellavalle RP, Dharmaratne SD, Faraon EJA, Feigin VL, Fuerst T, Geleijnse JM, Gessner BD, Gibney KB, Goto A, Gunnell D, Hankey GJ, Hay RJ, Hornberger JC, Hosgood HD, Hu G, Jacobsen KH, Jayaraman SP, Jeemon P, Jonas JB, Karch A, Kim D, Kim S, Kokubo Y, Defo BK, Bicer BK, Kumar GA, Larsson A, Leasher JL, Leung R, Li Y, Lipshultz SE, Lopez AD, Lotufo PA, Lunevicius R, Lyons RA, Majdan M, Malekzadeh R, Mashal T, Mason-Jones AJ, Melaku YA, Memish ZA, Mendoza W, Miller TR, Mock CN, Murray J, Nolte S, Oh I-H, Olusanya BO, Ortblad KF, Park E-K, Paternina Caicedo AJ, Patten SB, Patton GC, Pereira DM, Perico N, Piel FB, Polinder S, Popova S, Pourmalek F, Quistberg DA, Remuzzi G, Rodriguez A, Rojas-Rueda D, Rothenbacher D, Rothstein DH, Sanabria J, Santos IS, Schwebel DC, Sepanlou SG, Shaheen A, Shiri R, Shiue I, Skirbekk V, Sliwa K, Sreeramareddy CT, Stein DJ, Steiner TJ, Stovner LJ, Sykes BL, Tabb KM, Terkawi AS, Thomson AJ, Thorne-Lyman AL, Towbin JA, Ukwaja KN, Vasankari T, Venketasubramanian N, Vlassov VV, Vollset SE, Weiderpass E, Weintraub RG, Werdecker A, Wilkinson JD, Woldeyohannes SM, Wolfe CDA, Yano Y, Yip P, Yonemoto N, Yoon S-J, Younis MZ, Yu C, Zaki MES, Naghavi M, Murray CJL, Vos Tet al., 2016, Global and National Burden of Diseases and Injuries Among Children and Adolescents Between 1990 and 2013 Findings From the Global Burden of Disease 2013 Study, JAMA PEDIATRICS, Vol: 170, Pages: 267-287, ISSN: 2168-6203

Journal article

Forouzanfar MH, Alexander L, Anderson HR, Bachman VF, Biryukov S, Brauer M, Burnett R, Casey D, Coates MM, Cohen A, Delwiche K, Estep K, Frostad JJ, Astha KC, Kyu HH, Moradi-Lakeh M, Ng M, Slepak EL, Thomas BA, Wagner J, Aasvang GM, Abbafati C, Ozgoren AA, Abd-Allah F, Abera SF, Aboyans V, Abraham B, Abraham JP, Abubakar I, Abu-Rmeileh NME, Aburto TC, Achoki T, Adelekan A, Adofo K, Adou AK, Adsuar JC, Afshin A, Agardh EE, Al Khabouri MJ, Al Lami FH, Alam SS, Alasfoor D, Albittar MI, Alegretti MA, Aleman AV, Alemu ZA, Alfonso-Cristancho R, Alhabib S, Ali R, Ali MK, Alla F, Allebeck P, Allen PJ, Alsharif U, Alvarez E, Alvis-Guzman N, Amankwaa AA, Amare AT, Ameh EA, Ameli O, Amini H, Ammar W, Anderson BO, Antonio CAT, Anwari P, Cunningham SA, Arnlov J, Arsenijevic VSA, Artaman A, Asghar RJ, Assadi R, Atkins LS, Atkinson C, Avila MA, Awuah B, Badawi A, Bahit MC, Bakfalouni T, Balakrishnan K, Balalla S, Balu RK, Banerjee A, Barber RM, Barker-Collo SL, Barquera S, Barregard L, Barrero LH, Barrientos-Gutierrez T, Basto-Abreu AC, Basu A, Basu S, Basulaiman MO, Ruvalcaba CB, Beardsley J, Bedi N, Bekele T, Bell ML, Benjet C, Bennett DA, Benzian H, Bernabe E, Beyene TJ, Bhala N, Bhalla A, Bhutta ZQA, Bikbov B, Bin Abdulhak AA, Blore JD, Blyth FM, Bohensky MA, Basara BB, Borges G, Bornstein NM, Bose D, Boufous S, Bourne RR, Brainin M, Brazinova A, Breitborde NJ, Brenner H, Briggs ADM, Broday DM, Brooks PM, Bruce NG, Brugha TS, Brunekreef B, Buchbinder R, Bui LN, Bukhman G, Bulloch AG, Burch M, Burney PGJ, Campos-Nonato IR, Campuzano JC, Cantoral AJ, Caravanos J, Cardenas R, Cardis E, Carpenter DO, Caso V, Castaneda-Orjuela CA, Castro RE, Catala-Lopez F, Cavalleri F, Cavlin A, Chadha VK, Chang J-C, Charlson FJ, Chen H, Chen W, Chen Z, Chiang PP, Chimed-Ochir O, Chowdhury R, Christophi CA, Chuang T-W, Chugh SS, Cirillo M, Classen TKD, Colistro V, Colomar M, Colquhoun SM, Contreras AG, Cooper C, Cooperrider K, Cooper LT, Coresh J, Courville KJ, Criqui MH, Cuevas-Nasu L, Damsere-Deet al., 2015, Global, regional, and national comparative risk assessment of 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks in 188 countries, 1990-2013: a systematic analysis for the Global Burden of Disease Study 2013, LANCET, Vol: 386, Pages: 2287-2323, ISSN: 0140-6736

Journal article

Newton JN, Briggs ADM, Murray CJL, Dicker D, Foreman KJ, Wang H, Naghavi M, Forouzanfar MH, Ohno SL, Barber RM, Vos T, Stanaway JRD, Schmidt JC, Hughes AJ, Fay DFJ, Ecob R, Gresser C, McKee M, Rutter H, Abubakar I, Ali R, Anderson HR, Banerjee A, Bennett DA, Bernabe E, Bhui KS, Biryukov SM, Bourne RR, Brayne CEG, Bruce NG, Brugha TS, Burch M, Capewell S, Casey D, Chowdhury R, Coates MM, Cooper C, Critchley JA, Dargan PI, Dherani MK, Elliott P, Ezzati M, Fenton KA, Fraser MS, Fuerst T, Greaves F, Green MA, Gunnell DJ, Hannigan BM, Hay RJ, Hay SI, Hemingway H, Larson HJ, Looker KJ, Lunevicius R, Lyons RA, Marcenes W, Mason-Jones AJ, Matthews FE, Moller H, Murdoch ME, Newton CR, Pearce N, Piel FB, Pope D, Rahimi K, Rodriguez A, Scarborough P, Schumacher AE, Shiue I, Smeeth L, Tedstone A, Valabhji J, Williams HC, Wolfe CDA, Woolf AD, Davis ACJet al., 2015, Changes in health in England, with analysis by English regions and areas of deprivation, 1990-2013: a systematic analysis for the Global Burden of Disease Study 2013, Lancet, Vol: 386, Pages: 2257-2274, ISSN: 1474-547X

Journal article

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