Objectives: Bacterial vaginosis (BV), a disturbance of vaginal microflora, is a common cause of vaginal symptoms and is associated with an increased risk of acquisition of sexually transmitted infections,HIV, and with adverse pregnancy outcomes. We determined prevalence and associations with BV among a representative sample of women of reproductive age in the United States.Study Design: Women aged 14 -49 years participating in the National Health and Nutrition Examination Survey 2001-2004 were asked to submit a self-collected vaginal swab for Gram staining. BV, determined using Nugent's score, was defined as a score of 7-10.Results: The prevalence of BV was 29.2% (95% confidence interval 27.2%-31.3%) corresponding to 21 million women with BV; only 15.7% of the women with BV reported vaginal symptoms. Prevalence was 51.4% among non-Hispanic blacks, 31.9% among Mexican Americans, and 23.2% among non-Hispanic whites (P <0.01 for each comparison). Although BV was also associated with poverty (P <0.01), smoking (P <0.05), increasing body mass index ( 2 P <0.0001 for trend), and having had a female sex partner (P <0.005), in the multivariate model, BV only remained positively associated with race/ ethnicity, increasing lifetime sex partners ( 2 P <0.001 for trend), increasing douching frequency ( 2 P for trend <0.001), low educational attainment (P <0.01), and inversely associated with current use of oral contraceptive pills (P <0.005).Conclusion: BV is a common condition; 84% of women with BV did not report symptoms. Because BV increases the risk of acquiring sexually transmitted infections, BV could contribute to racial disparities in these infections.
Our review focuses on all articles in the English language that provide sufficient data to calculate a relative risk or odds ratio for CHD at different levels of physical activity. The inverse association between physical activity and incidence of CHD is consistently observed, especially in the better designed studies; this association is appropriately sequenced, biologically graded, plausible, and coherent with existing knowledge. Therefore, the observations reported in the literature support the inference that physical activity is inversely and causally related to the incidence of CHD. The two most important observations in this review are, first, better studies have been more likely than poorer studies to report an inverse association between physical activity and the incidence of CHD and, second, the relative risk of inactivity appears to be similar in magnitude to that of hypertension, hypercholesterolemia, and smoking. These observations suggest that in CHD prevention programs, regular physical activity should be promoted as vigorously as blood pressure control, dietary modification to lower serum cholesterol, and smoking cessation. Given the large proportion of sedentary persons in the United States (91), the incidence of CHD attributable to insufficient physical activity is likely to be surprisingly large. Therefore, public policy that encourages regular physical activity should be pursued.
We report the first national data on smoking before, during, and after pregnancy. Estimates are based on the 1986 Linked Telephone Survey that reinterviewed 1,550 White women 20-44 years of age who were respondents to the 1985 National Health Interview Survey. An estimated 39 percent of White women who had smoked before pregnancy quit smoking while pregnant (27 percent when they found out they were pregnant and 12 percent later during pregnancy). Women with less than 12 years of education were five times as likely to smoke and one-fourth as likely to quit as those with 16 or more years of education. Women who smoked more than one
Exploratory data analysis involves the use of statistical techniques to identify patterns that may be hidden in a group of numbers. One of these techniques is the "box plot," which is used to visually summarize and compare groups of data. The box plot uses the median, the approximate quartiles, and the lowest and highest data points to convey the level, spread, and symmetry of a distribution of data values. It can also be easily refined to identify outlier data values and can be easily constructed by hand. We apply box plots to tabular data from two recently published articles to show how readers can use box plots to improve the interpretation of data in complex tables. The box plot, like other visual methods, is more than a substitute for a table: It is a tool that can improve our reasoning about quantitative information. We recommend that the box plot be used more frequently.
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