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Objective: To determine if caffeine intake before and during pregnancy was associated with an increased risk for fetal loss.Design: Incidence-density case-control study.Setting: University-affiliated obstetric and pediatric hospital in Montréal, Québec.Participants: A total of 331 women with fetal loss and 993 controls with a normal pregnancy at the same period of pregnancy as the case.Outcome Measures: Crude and adjusted odds ratios (ORs) for fetal loss were estimated using conditional logistic regression. A trend test for increasing caffeine intake was also used.Results: Caffeine intake was divided into quartiles; the baseline for comparison was less than 48 mg per day. The adjusted ORs for fetal loss associated with caffeine intake before pregnancy were 1.29 (95% confidence interval [CI], 0.85 to 1.95) for 48 to 162 mg; 1.37 (95% CI, 0.92 to 2.04) for 163 to 321 mg; and 1.85 (95% CI, 1.18 to 2.89) for more than 321 mg. The same comparisons were made for caffeine intake during pregnancy, and the respective adjusted ORs were 1.15 (95% CI, 0.82 to 1.63), 1.95 (95% CI, 1.29 to 2.93), and 2.62 (95% CI, 1.38 to 5.01). After controlling for confounding factors, there was a strong association of caffeine intake during pregnancy and fetal loss, compatible with a linear trend on the logistic scale in which ORs increased by a factor of 1.22 (1.10 to 1.34) for each 100 mg of caffeine ingested daily during pregnancy.Conclusions: Caffeine intake before and during pregnancy was associated with an increased risk of fetal loss, supporting the US Food and Drug Administration recommendation to pregnant women, largely based on animal studies, to reduce their caffeine intake. [ABSTRACT FROM AUTHOR]

In the first 2 articles of this series, we reviewed the basic genetics concepts necessary to understand genetic association studies, and we enumerated the major issues in judging the validity of these studies. In this third article, we review the issues relating to the applicability of the results in the clinical situation. How large and precise are the associations? Many genetic effects are expected to be smaller in magnitude than traditional risk factors. Does the genetic association improve predictive power beyond easily measured clinical variables? In some cases, the additional genetic information adds only a small increment in the predictive ability of a diagnostic or prognostic test. What are the absolute vs relative effects? Even if the genetic risk is high in relative terms, the baseline risk may be very low in absolute terms. Is the risk-associated allele likely to be present in my patient? A risk allele may have a strong effect but be rare in a particular ethnic group. Is the patient likely better off knowing the genetic information? Given that genes cannot be modified, one must weigh whether the genetic information is likely to be helpful in planning other health interventions or initiating behavior change. [ABSTRACT FROM AUTHOR]

In the first article of this series, we reviewed the basic genetics concepts necessary to understand genetic association studies. In this second article, we enumerate the major issues in judging the validity of these studies, framed as critical appraisal questions. Was the disease phenotype properly defined and accurately recorded by someone blind to the genetic information? Have any potential differences between disease and nondisease groups, particularly ethnicity, been properly addressed? In genetic studies, one potential cause of spurious associations is differences between cases and controls in ethnicity, a situation termed population stratification. Was measurement of the genetic variants unbiased and accurate? Methods for determining DNA sequence variation are not perfect and may have some measurement error. Do the genotype proportions observe Hardy-Weinberg equilibrium? This simple mathematic rule about the distribution of genetic groups may be one way to check for errors in reading DNA information. Have the investigators adjusted their inferences for multiple comparisons? Given the thousands of genetic markers tested in genome-wide association studies, the potential for false-positive and false-negative results is much higher than in traditional medical studies, and it is particularly important to look for replication of results. [ABSTRACT FROM AUTHOR]