J-Curve? A Meta-Analysis and Meta-Regression of Parity and Parental Mortality

Research suggests that parity and parental health and mortality are associated significantly, although the pattern of association varies across studies. Studies ascribe long-term poor health (and mortality) to either low or high parity, and some studies show that both low and high parity increase the risk of adverse health for parents (i.e., forming a “J-shaped curve”). While a recent meta-analysis (Zeng et al., Sci Rep 6:19351, 2016) has partially addressed this gap in the literature, the present study further extends the literature by using a methodology that allows for more robust control of study heterogeneity and potential confounders. Using data on 223 measures of relative mortality risk from 37 studies, from samples gathered after 1945 from developed nations, meta-analysis and meta-regression (weighted linear regression) results show a nonlinear association (J-shaped curve) between parity and all-cause parental mortality, though the strength of the association varies by both sex and cohort. The results also suggest that the mortality hazard is partially explained by health selection effects.     

Widowhood and Mortality: A Meta-Analysis and Meta-Regression

The study of spousal bereavement and mortality has long been a major topic of interest for social scientists, but much remains unknown with respect to important moderating factors, such as age, follow-up duration, and geographic region. The present study examines these factors using meta-analysis. Keyword searches were conducted in multiple electronic databases, supplemented by extensive iterative hand searches. We extracted 1,377 mortality risk estimates from 123 publications, providing data on more than 500 million persons. Compared with married people, widowers had a mean hazard ratio (HR) of 1.23 (95% confidence interval (CI), 1.19–1.28) among HRs adjusted for age and additional covariates and a high subjective quality score. The mean HR was higher for men (HR, 1.27; 95% CI, 1.19–1.35) than for women (HR, 1.15; 95% CI, 1.08–1.22). A significant interaction effect was found between gender and mean age, with HRs decreasing more rapidly for men than for women as age increased. Other significant predictors of HR magnitude included sample size, geographic region, level of statistical adjustment, and study quality.     

Development and implementation of new technologies in the steel industry

At each successive stage in the R&D cycle leading to the commercialization of a new technology, management in any industry must reevaluate prospects and make decisions accordingly. However, for the steel industry the difficulties of this kind of decision-making throughout the usually lengthy R&D cycle are heightened by the very nature of the industry. For example, the large scale of its processes and the high capital costs for plants for new processes mean that the progressive scale-ups during a given development may themselves cost millions. From Bethlehem Steel's experience the author cites one new product and two major process developments to illustrate technical and economic considerations that enter into decision-making as R&D moves step by step toward the commercialization of new technology.