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Why was the cohort set up? Latin America and the Caribbean (LAC) are characterized by much diversity in terms of socio-economic status, ecology, environment, access to health care,1,2 as well as the frequency of risk factors for and prevalence or incidence of non-communicable diseases;3–7 importantly, these differences are observed both between and within countries in LAC.8,9 LAC countries share a large burden of non-communicable (e.g. diabetes and hypertension) and cardiovascular (e.g. ischaemic heart disease) diseases, with these conditions standing as the leading causes of morbidity, disability and mortality in most of LAC.10–12 These epidemiological estimates—e.g. morbidity—cannot inform about risk factors or risk prediction, which are relevant to identify prevention avenues. Cohort studies, on the other hand, could provide this evidence. Pooled analysis, using data from multiple cohort studies, have additional strengths such as increased statistical power and decreased statistical uncertainty.13 LAC cohort studies have been under-represented,14 or not included at all,15–17 in international efforts aimed at pooling data from multiple cohort studies. We therefore set out to pool data from LAC cohorts to address research questions that individual cohort studies would not be able to answer. Drawing from previous successful regional enterprises (e.g. Asia Pacific Cohort Studies Collaboration),18,19 we established the Cohorts Consortium of Latin America and the Caribbean (CC-LAC). The main aim of the CC-LAC is to start a collaborative cohort data pooling in LAC to examine the association between cardio-metabolic risk factors (e.g. blood pressure, glucose and lipids) and non-fatal and fatal cardiovascular outcomes (e.g. stroke or myocardial infarction). In so doing, we aim to provide regional risk estimates to inform disease burden metrics, as well as other ambitious projects including a cardiovascular risk score to strengthen cardiovascular prevention in LAC. Initial funding has been provided by a fellowship from the Wellcome Trust Centre for Global Health Research at Imperial College London (Strategic Award, Wellcome Trust–Imperial College Centre for Global Health Research, 100693/Z/12/Z). Additional funding is being provided by an International Training Fellowship from the Wellcome Trust (214185/Z/18/Z). At the time of writing, the daily operations and pooled database are hosted at Imperial College London, though a mid-term goal is to transfer this expertise and operations to LAC. The collaboration relies fundamentally on a strong regional network of health researchers and practitioners

Background: The extent to which adult height, a biomarker of the interplay of genetic endowment and early-life experiences, is related to risk of chronic diseases in adulthood is uncertain. Methods: We calculated hazard ratios (HRs) for height, assessed in increments of 6.5 cm, using individual-participant data on 174 374 deaths or major non-fatal vascular outcomes recorded among 1 085 949 people in 121 prospective studies. Results: For people born between 1900 and 1960, mean adult height increased 0.5-1 cm with each successive decade of birth. After adjustment for age, sex, smoking and year of birth, HRs per 6.5 cm greater height were 0.97 (95% confidence interval: 0.96-0.99) for death from any cause, 0.94 (0.93-0.96) for death from vascular causes, 1.04 (1.03-1.06) for death from cancer and 0.92 (0.90-0.94) for death from other causes. Height was negatively associated with death from coronary disease, stroke subtypes, heart failure, stomach and oral cancers, chronic obstructive pulmonary disease, mental disorders, liver disease and external causes. In contrast, height was positively associated with death from ruptured aortic aneurysm, pulmonary embolism, melanoma and cancers of the pancreas, endocrine and nervous systems, ovary, breast, prostate, colorectum, blood and lung. HRs per 6.5 cm greater height ranged from 1.26 (1.12-1.42) for risk of melanoma death to 0.84 (0.80-0.89) for risk of death from chronic obstructive pulmonary disease. HRs were not appreciably altered after further adjustment for adiposity, blood pressure, lipids, inflammation biomarkers, diabetes mellitus, alcohol consumption or socio-economic indicators. Conclusion: Adult height has directionally opposing relationships with risk of death from several different major causes of chronic diseases. Published by Oxford University Press on behalf of the International Epidemiological Association © The Author 2012; all rights reserved.

Background Non-uniform reporting of relevant relationships and metrics hampers critical appraisal of the clinical utility of C-reactive protein (CRP) measurement for prediction of later coronary events.Methods We evaluated the predictive performance of CRP in the Northwick Park Heart Study (NPHS-II) and the Edinburgh Artery Study (EAS) comparing discrimination by area under the ROC curve (AUC), calibration and reclassification. We set the findings in the context of a systematic review of published studies comparing different available and imputed measures of prediction. Risk estimates per-quantile of CRP were pooled using a random effects model to infer the shape of the CRP-coronary event relationship.Results NPHS-II and EAS ( 3441 individuals, 309 coronary events): CRP alone provided modest discrimination for coronary heart disease (AUC 0.61 and 0.62 in NPHS-II and EAS, respectively) and only modest improvement in the discrimination of a Framingham-based risk score ( FRS) ( increment in AUC 0.04 and -0.01, respectively). Risk models based on FRS alone and FRS+CRP were both well calibrated and the net reclassification improvement (NRI) was 8.5% in NPHS-II and 8.8% in EAS with four risk categories, falling to 4.9% and 3.0% for 10-year coronary disease risk threshold of 15%. Systematic review ( 31 prospective studies 84 063 individuals, 11 252 coronary events): pooled inferred values for the AUC for CRP alone were 0.59 (0.57, 0.61), 0.59 ( 0.57, 0.61) and 0.57 (0.54, 0.61) for studies of 10 years follow up, respectively. Evidence from 13 studies ( 7201 cases) indicated that CRP did not consistently improve performance of the Framingham risk score when assessed by discrimination, with AUC increments in the range 0-0.15. Evidence from six studies ( 2430 cases) showed that CRP provided statistically significant but quantitatively small improvement in calibration of models based on established risk factors in some but not all studies. The wide overlap of CRP values among people who later suffered events and those who did not appeared to be explained by the consistently log-normal distribution of CRP and a graded continuous increment in coronary risk across the whole range of values without a threshold, such that a large proportion of events occurred among the many individuals with near average levels of CRP.Conclusions CRP does not perform better than the Framingham risk equation for discrimination. The improvement in risk stratification or reclassification from addition of CRP to models based on established risk factors is small and inconsistent. Guidance on the clinical use of CRP measurement in the prediction of coronary events may require updating in light of this large comparative analysis.

BACKGROUND: It is unclear wheather the association between C-reactive protein (CRP) and incident coronary events is free from bias and confounding. Individuals homozygous for a +1444C>T polymorphism in the CRP gene have higher circulating concentrations of CRP. Since the distribution of this polymorphism occurs at random during gamete formation, its association with coronary events should not be biased or confounded. METHODS: We calculated the weighted mean difference in CRP between individuals with variants of the +1444C>T polymorphism in the CRP gene among 4,659 European men from six studies (genotype-intermediate phenotype studies). We used this difference together with data from previous observational studies to compute an expected odds ratio (OR) for non-fatal myocardial infarction (MI) among individuals homozygous for the T allele. We then performed four new genetic association studies (6,201 European men) to obtain a summary OR for the association between the +1444C>T polymorphism and non-fatal MI (genotype-disease studies). RESULTS: CRP was 0.68 mg/l [95% confidence interval (95% CI) 0.31-1.10; P = 0.0001] higher among subjects homozygous for the +1444-T allele, with no confounding by a range of covariates. The expected ORs among TT subjects for non-fatal MI corresponding to this difference in CRP was 1.20 (95% CI 1.07-1.38) using the Reykjavik Heart study data and 1.25 (1.09-1.43) for all observational studies to 2004. The estimate for the observed adjusted-OR for non-fatal MI among TT subjects was 1.01 (95% CI 0.74-1.38), lower than both expected ORs. CONCLUSIONS: A common CRP gene polymorphism is associated with important differences in CRP concentrations, free from confounding. The null association of this variant with coronary events suggests possible residual confounding (or reverse causation) in the CRP-coronary event association in observational studies, though the confidence limits are still compatible with a modest causal effect. Additional studies of genotype (or haplotype) and coronary events would help clarify whether or not the link between CRP and coronary events in observational studies is causal.