Danger: implants

The superheated debate over breast implants awakened a sleeping giant of an issue clouding "medical devices"--the government's clumsy nomenclature for any medical product that is not a drug, from breast implants and artificial hips to X-ray machines and surgical thread. Some 130 categories of high-risk devices are in use with little or no proof of safety, reliability or effectiveness. All appeared before 1976, the year that the Food and Drug Administration got the authority to regulate such products. Under activist chief David Kessler and with added clout from a 1990 law, the FDA plans to scrutinize the entire 130-item list. Five will get special attention starting early next year: saline-filled breast implants, inflatable penile implants, testicular implants, heart-bypass pumps and cranial stimulators. U.S. News has looked at all five devices, using FDA data obtained through the Freedom of Information Act. In-depth computer analysis suggested that penile implants deserve closer examination. Why is clear from the following report.     

Mortality in Mexico. Some considerations on rural-urban differentials

"In this essay, certain aspects related to rural-urban mortality differentials in Mexico are analyzed....[These include] the availability, advantages, and limitations of different sources of information and the disparity of levels and tendencies according to particular indicators of acceptable reliability, especially those deriving from recent demographic surveys conducted in Mexico. The findings confirm an inverse ratio between size of settlement and mortality, and reveal a widening of the differentials over time." (SUMMARY IN ENG)     

可保利益

<正> 保险并不意味着也不应该向任何人无条件地提供保险,以免在损失发生之时,使有些被保险人从赔偿中获取一种纯净的利益。在实践中,对此进行控制的相当可靠的方式,便是采取"可保利益"原则。一、坚持可保利益原则的目的在判例和成文立法中,贯穿于可保利益原则全部发展途程的两个主要目的,曾引起立法     

美国的商标和商标法

<正> 一、商标的性质商标的主要功能是识别商标所属产品的来源。它也有一种广告功能和保证功能——这后一功能,是保护产品的来源和产品在广告上被宣传的质量。在人们的心目中,商标的能力有强有弱。家用电器用具制造商——阳光公司,是注册商标"阳光"的所有权人。该公司对阳光家具公司提起诉讼。法院下令禁止被告把"阳光"这     

Fertility,development, and family planning, 1970–1980: An analysis of cases weighted by population

A series of related studies (Freedman and Berelson, 1976; Mauldin and Berelson, 1978; and Tsui and Bogue, 1978) have presented empirical findings based on multiple regression analysis which indicated that family planning program effort (FP), as measured by an index developed by Lapham and Mauldin (1972), was the single most important predictor of (or influence on) fertility reduction in less-developed countries (LDCs). The basic results have been confirmed repeatedly. A more extensive data set was used to extend the analysis to a comparison of results of corss-sectional models circa 1970 and 1980. The study builds upon the results of past studies yet differs from them in several ways. All the variables in the present study were measured at 2 points in time: circa 1970 and circa 1980, allowing a comparison between cross-sectional models for 1970 and 1980. Among the cases included in this multivariate analysis was China, a country usually excluded for lack of data. The analysis was extend to 85 countries. Cases were weighted by population, having the effect of increasing the impact of larger countries such as India and China on the outcome of the analysis. Total fertility rate (TFR) was used as an indicator of fertility. For 1970, family planning program effort had the strongest direct influence on fertility (a result consistent with previous studies). Life expectancy at birth was the other direct influence. The direct influence of life expectancy at birth was less than that of family planning, but the total influence was greater. After life expectancy and family planning, school enrollment and relative educational status of women had the strongest indirect and total influences. The other variables all had a positive influence on fertility. When the total variance attributable was considered, directly and indirectly to each of the independent variables, urbanization, carlorie supply, and per capita gross national product all accounted for less than 5% of the variance in fertility, all of it indirect. Life expectancy, family planning, and school enrollment each explained (directly plus indirectly) more than 10% of the variance in fertility. The pattern differed somewhat for 1980. Calorie supply, per capita gross national product, and relative educational status of women had no influence, direct or indirect on fertility. Also for 1980, life expectancy had a stronger direct influence on fertility than family planning. Overall, life expectancy at birth, family planning program effort, and total school enrollment emerged as the principal influences on fertility.