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Study Title and Description

Nonfatal acute myocardial infarction in Costa Rica: modifiable risk factors, population-attributable risks, and adherence to dietary guidelines.



Key Questions Addressed
1 For [population], is caffeine intake above [exposure dose], compared to intakes [exposure dose] or less, associated with adverse effects on cardiovascular outcomes?
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Primary Publication Information
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TitleData
Title Nonfatal acute myocardial infarction in Costa Rica: modifiable risk factors, population-attributable risks, and adherence to dietary guidelines.
Author EK Kabagambe,A Baylin,H Campos,
Country
Year 2007
Numbers

Secondary Publication Information
There are currently no secondary publications defined for this study.


Extraction Form: Cardiovascular Design
Design Details
Question... Follow Up Answer Follow-up Answer
What outcome is being evaluated in this paper? Cardiovascular
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What is the objective of the study (as reported by the authors)? In the present study, we report on the relation between the overall diet, lifestyle factors, and their impact on MI (as measured by population-attributable risk [PAR]) in Costa Rica.
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Provide a general description of the methods as reported by the authors. Information should be extracted based on relevance to the SR (i.e., caffeine related methods) Study Population All subjects were Hispanic Americans who lived in the central valley of Costa Rica between 1994 and 2004. The details of the study design have been published elsewhere. Briefly, eligible cases were men and women diagnosed as survivors of a first acute MI by 2 independent cardiologists at any of the 6 recruiting hospitals in the catchment area. To achieve 100% ascertainment, fieldworkers carried out daily visits to the 6 hospitals. All cases met the World Health Organization criteria for MI, which require typical symptoms plus either elevations in cardiac enzyme concentrations or diagnostic changes in the ECG. Cases were ineligible if they died during hospitalization, were >/= 75 years of age on the day of their first MI, or were physically or mentally unable to answer the questionnaire. Enrollment was carried out while cases were in the step-down unit of the hospital. Cases were matched by age (+/- 5 years), sex, and area of residence to population controls who were randomly identified with the aid of data from the National Census and Statistics Bureau of Costa Rica. Because of the comprehensive social services provided in Costa Rica, all persons living in the catchment area had access to medical care without regard to income, education, or private insurance. Therefore, controls came from the source population that gave rise to the cases and are not likely to have had CVD that was not diagnosed because of poor access to medical care. Controls were ineligible if they had ever had an MI or if they were physically or mentally unable to answer the questionnaires. All cases and controls were visited at their homes for the collection of dietary and health information, anthropometric measurements, and biological specimens. Participation was 98% for cases and 88% for controls. Data Collection Trained personnel visited all study participants at their homes. Sociodemographic characteristics, smoking, socioeconomic status, physical activity, and medical history data were collected during an interview using validated questionnaires. Each subject provided a fasting blood sample for the assessment of plasma lipids. We collected dietary data using a semiquantitative food-frequency questionnaire developed and validated specifically to assess nutrient intake among the Costa Rican population. To avoid the potential for recall bias among cases, data were collected as close to the diagnosis of MI as possible. Another questionnaire assessed nondietary potential confounders and recorded anthropometric measurements. The latter were measured in duplicate, and an average was recorded. Total physical activity was calculated by multiplying the frequency, duration, and intensity (in metabolic equivalents) of each physical activity and then summing up energy expenditure from all activities as described by Campos and Siles. Statistical Analysis SAS (SAS Institute, Inc., Cary, NC) and the Interactive Risk Attributable Program (National Cancer Institute, Bethesda, Md) software were used for statistical analyses. Diabetes and hypertension could influence people’s diets and other lifestyle attributes. From the initial study population (n=4547), we excluded all subjects with a history of diabetes (n=861), hypertension (n=1508), or regular use of medication for chronic conditions (n=1788). Subjects with missing data on potential confounders or major explanatory variables also were excluded, leaving 889 MI cases and 1167 controls for the final analysis. These exclusions caused case-control pairs to be broken. To minimize further loss of subjects, we used unconditional logistic regression that included matching variables in each model as proposed by Rosner and Hennekens and implemented by Yusuf et al. The HDS and other continuous variables were distributed into quartiles and tested for their association with MI. Multivariate unconditional logistic regression with stepwise variable selection was used to identify variables for the final model. The probability for a variable to enter into or stay in the model was set at 0.05. The variables offered to the model were smoking, income, education, abdominal obesity, physical activity, HDS, and intake of alcohol, caffeine, folate, and total energy. Physical activity, a known risk factor for CVD, and the matching variables were forced into the model.
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How many outcome-specific endpoints are evaluated? 1
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What is the (or one of the) endpoint(s) evaluated? (Each endpoint listed separately) Non-fatal acute myocardial infarction (MI)
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List additional health endpoints (separately). 2
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List additional health endpoints (separately).3
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List additional health endpoints (separately).4
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List additional health endpoints (separately).5
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List additional health endpoints (separately).6
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Clinical, physiological, other Clinical
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What is the study design? Case-Control
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Randomized or Non-Randomized?
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What were the diagnostics or methods used to measure the outcome? Objective
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Optional: Name of Method or short description All cases met the World Health Organization criteria for MI, which require typical symptoms plus either elevations in cardiac enzyme concentrations or diagnostic changes in the ECG.
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Caffeine (general) Caffeine (general)
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Coffee, Chocolate, energy drink, gum, medicine/supplement, soda, tea, other?
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Measured or self reported? Self-report
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Children, adolescents, adults, or pregnant included? Adults
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What was the reference, comparison, or control group(s)? (e.g. high vs low consumption, number of cups, etc.) Less than/equal to 151 mg caffeine per day
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What were the listed confounders or modifying factors as stated by the authors? (e.g. multi-variable components of models.  Copy from methods) Ors adjusted for age, sex, area of residence, and total energy intake
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What conflicts of interest were reported? No information provided
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Refid 17339565
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What were the sources of funding? This study was supported by grants HL071888 and HL60692 from the National Institutes of Health.
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Results & Comparisons

No Results found.