Awan, Safia

Yakoob, javed

English

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eCommons@AKUSection of Gastroenterology Department of MedicineAugust 2011MEASURES OF SOCIO-DEMOGRAPHICFACTORS FOR CHILDjaved YakoobAga Khan University, javed.yakoob@aku.eduSafia AwanAga Khan University, safia.awan@aku.eduFollow this and additional works at: http://ecommons.aku.edu/pakistan_fhs_mc_med_gastroenterolPart of the Gastroenterology CommonsRecommended CitationYakoob, j., Awan, S. (2011). MEASURES OF SOCIO-DEMOGRAPHIC FACTORS FOR CHILD. journal of epidemiology andcommunity health., 65(Supplement.1), A69-A69.Available at: http://ecommons.aku.edu/pakistan_fhs_mc_med_gastroenterol/117CUTTING EDGE METHODOLOGYP1-6 MEASURES OF SOCIO-DEMOGRAPHIC FACTORS FOR CHILDHEALTH RESEARCHdoi:10.1136/jech.2011.142976c.1J Yakoob, S Awan.* Aga Khan University hospital, Karachi, PakistanBackground H pylori infection is one of the major causes ofhealth problems with considerable morbidity and mortality.H pylori seroprevalence is common in populations with poorstandards of sanitation and hygiene.Methods A two-stage cluster sampling technique was employedto draw the required sample. A crowding index with threecategories (low, moderate, high) was constructed by dividing thenumber of individuals per household by the number of the rooms.Assessment of socioeconomic status (SES) was calculated byHollingstead Index (HI).Results Serum of 1976 children was tested. H pylori seropositivityin 1e5 years were 53.5%. It increased with moderate crowdingindex (CRI) of 2e4 to 45.9% and to 51.2% with CRI >4. In middleSES, seropositivity was 331 (50.5%) while in lower SES 500 (47.1%).Multivariate analysis showed H pylori seroprevalence was highin 6e10 and 11e15 years (OR: 1.5, 95% CI 1.2 to 1.9 and OR: 1.9,95% CI 1.56 to 2.47, respectively), in lower-middle SES (OR: 1.6,95% CI 1.2 to 2.1 and OR: 1.5, 95% CI 1.10 to 2.0, respectively) anduneducated fathers (OR: 1.58, 95% CI 1.27 to 1.95).Conclusion H pylori seropositivity increased with age, in low-middleSES and is related to father ’s educational status.P1-7 INFLUENZA RECYCLING AND EPIDEMIOLOGIC EVOLUTION:AN ALTERNATIVE TO OMRAN’S EPIDEMIOLOGICTRANSITION THEORY FOR POPULATION CHANGEdoi:10.1136/jech.2011.142976c.2M I Azambuja.* Universidade Federal do Rio Grande do Sul, Porto Alegre, Rio Grandedo Sul, BrazilThe sustained increase in longevity initiated during the secondhalf of the 20th Century poses huge challenges upon the publicand private healthcare and pensions’ systems. Current theoriesdo not explain the observed phenomenon, what precludes predic-tions of its future trends. The authors goal was to go back toOmram’s original projectdto develop an epidemiologic theoryof the demographic changedbut looking for an explanation alter-native to the epidemiologic transition proposed by him. Thestudy expands upon a previous one, that showed, for the ﬁrst time,a cohort association between the mortality burden of 1918Inﬂuenza Pandemic and the 20th Century rise in CHD mortality.Based on an age-period-cohort analysis of USA and UK mortality(and natality) data (1933e2005) and on the epidemiology of inﬂu-enza as we know it, it is shown that, overall, temporal changes inmortality and natality accompany the recycling of inﬂuenza Aviruses, that is, the re-exposure of human populations, from time totime, to inﬂuenza A subtypes that circulated in the past. Mortality(and natality) and main causes of death change as birth cohorts(whole population and maternal) primed at early life with one(period-speciﬁc) inﬂuenza A sub-type, course through subsequentinﬂuenza A environments over time.1 The implications of this newtheory to demography and to the epidemiology of several diseasesare revolutionary.REFERENCE1. http://www.actuaries.org.uk/research-and-resources/documents/influenza-recycling-and-secular-trends-mortality-and-natality.P1-8 PRINCIPAL COMPONENTS ANALYSIS OF DIET IS NOT GOODAT IDENTIFYING FOODS THAT ARE CAUSALLY LINKED TODISEASE: A SIMULATION STUDYdoi:10.1136/jech.2011.142976c.31I Bakolis,* 2R Hooper, 1P Burney, 2S Shaheen. 1Imperial College London, London, UK;2Centre for Health Sciences, Barts & The London School of Medicine & Dentistry,London, UKIntroduction Dietary patterns derived empirically from foodfrequency questionnaire (FFQ) data using principal componentsanalysis (PCA) are widely employed for the investigation of diet-disease relationships. The aim of the study was to investigatewhether PCA performed better at identifying associations betweendiet and disease than an analysis of each individual food in theFFQ separately after adjusting for multiple testing, a process werefer to as exhaustive single food analysis (ESFA).Methods Using simulated data employing a known model for theassociations between food intakes and disease, and a realisticjoint distribution of food intakes, we investigated the performanceof PCA and ESFA in correctly identifying associations between dietand disease. Performance was assessed in terms of the power withwhich we could identify at least one association between a foodintake and disease, and the power and false discovery rate (FDR) foridentifying speciﬁc food intakes that were causally linked to diseasein the model.Results ESFA had greater power than PCA to detect an associationof at least one food with disease, and greater power and lowerFDR for identifying speciﬁc foods causally linked to disease. Withboth methods FDRs increased with sample size, even using anFDR-controlling adjustment. However, when we adjusted the ESFAfor foods that were signiﬁcant in univariate analyses, FDRs werecontrolled at the speciﬁed level.Conclusions An exhaustive analysis of single foods out-performedPCA in identifying associations between diet and disease usingFFQ data.P1-9 THE HEALTH IMPACT FUND-MEETING THE CHALLENGE OFHEALTH IMPACT ASSESSMENTdoi:10.1136/jech.2011.142976c.41A Banerjee,* 2A Hollis, 3T Pogge. 1University of Birmingham, Birmingham, WestMidlands, UK; 2University of Calgary, Calgary, Alberta, Canada; 3Yale University, NewHaven, Connecticut, USAIntroduction The Health Impact Fund (HIF) is a publicly fundedinternational agency proposed to enable pharmaceutical innovatorsto register a product for health impact rewards in exchange forselling it worldwide at cost. Supplementing the current patentregime, the HIF would improve incentives to research diseasesconcentrated among the poor. A workable HIF presupposes aconsistent, predictable, and contractible method of health impactassessment.Methods We reviewed the literature using search terms,“healthimpact assessment tools” and an exploratory workshop for allstakeholders was held at the National Institute for Health andClinical Excellence in April 2010.Results Although there are many challenges with the nature ofcurrent epidemiological data and their application to global health,there is scope for improvement and the HIF may help to trigger andsustain such enhancements. Moreover, the HIF would use muchmore information than the present system. The following steps inhealth impact assessment need to occur for each registered product:deﬁning subgroups, establishing baseline treatments, deﬁningincremental health impact by subgroup, measuring the numbers ofpatients treated in each subgroup, and a process of appeal.J Epidemiol Community Health August 2011 Vol 65 Suppl 1 A69Poster session 1group.bmj.com on October 27, 2017 - Published by http://jech.bmj.com/Downloaded from for child health researchMeasures of socio-demographic factors P1-6J Yakoob and S Awandoi: 10.1136/jech.2011.142976c.12011 65: A69 J Epidemiol Community Health  http://jech.bmj.com/content/65/Suppl_1/A69.1Updated information and services can be found at: These include:serviceEmail alertingbox at the top right corner of the online article. Receive free email alerts when new articles cite this article. Sign up in theCollectionsTopic Articles on similar topics can be found in the following collections  (1463)Mortality and morbidity (2838)Epidemiologic studiesNoteshttp://group.bmj.com/group/rights-licensing/permissionsTo request permissions go to:http://journals.bmj.com/cgi/reprintformTo order reprints go to:http://group.bmj.com/subscribe/To subscribe to BMJ go to:group.bmj.com on October 27, 2017 - Published by http://jech.bmj.com/Downloaded from 

MEASURES OF SOCIO-DEMOGRAPHIC FACTORS FOR CHILD

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MEASURES OF SOCIO-DEMOGRAPHIC FACTORS FOR CHILD

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