Multilevel community health promotion: How can we make it work?

The need for multilevel, comprehensive health promotion programmeshas become widely accepted, as has the importance of communityapproaches. However, many health promotion programmes focuson change at the individual level, no doubt partly due to thedifficulty of implementing all-inclusive health promotion. Thispaper discusses two strategies for guiding multilevel projects:multiple methods for community assessment and charting projectactivities by level of change (a possibility framework). Thesestrategies help ensure a multilevel focus and provide valuableinformation that can assist with the implementation of multilevelhealth promotion research projects in specific community contexts.Our primary purpose, therefore, is not to focus on theory orresearch findings. Rather, our goal is to make visible two strategiesthat have been helpful in one health promotion research projectin Victoria, British Columbia, Canada.     

Inequality and fiscal policies in Uruguay by race

The aim of this study is to analyze the effect of fiscal policy by race, disaggregating to consider Uruguayans with primarily European, African and indigenous ancestry. We perform an incidence analysis, an estimation of the effect of fiscal policy on the poverty exit rate and an assessment of the impact on the average ethno-racial gaps. The findings support the idea that fiscal policy reduces (but does not eliminate) ethnic gaps. This result is led by health care and educational transfers, and to a lesser degree by direct transfers. We do not consider quality issues with public services, which may affect the estimated narrowing of gaps. Finally, we find that Afro-descendants and indigenous individuals do not capture the full potential of education transfers because of their high drop-out rate.     

Scaling Back and Finding Flexibility: Gender Differences in Parents' Strategies to Manage Work–Family Conflict

Studies show that fathers report work–family conflict levels comparable to mothers. The authors examine gender differences in work‐related strategies used to ease such conflicts. The authors also test whether the presence of young children at home shapes parents' use of different strategies. They address these focal questions using panel data from the Canadian Work, Stress, and Health study (N = 306 fathers, 474 mothers). The authors find that mothers with young children are more likely to scale back on work demands when compared with fathers with young children, but mothers and fathers with older children are equally likely to pursue these strategies. Furthermore, women with young children and men with older children are more likely to seek increased schedule control as a result of work–family conflict when compared with their parent counterparts. The authors situate these findings in the vast literature on the consequences of work–family conflict.     

Family Responsibilities,Productivity, and Earnings: A Study of Gender Differences Among Canadian Lawyers

This study examines whether men and women invest in different determinants of productivity and whether these investments affect productivity and salary in different ways. Hypotheses are tested from human and social capital theories that include more direct measures for family responsibilities and family-friendly firm arguments. Data from 670 law firm lawyers were used given they report a standardized measure of productivity in billable hours. Despite men investing more in their careers and women investing more in their families, both report similar productivity and their productivity is affected similarly by these factors. In addition, equally productive men and women are paid the same. The findings further our understanding of productivity and salary and the relevance of family responsibilities and family-friendly firms.

Estimating survival curves with left truncated and interval censored data via the ems algorithm

It is well-known that the nonparametric maximum likelihood estimator (NPMLE) of a survival function may severely underestimate the survival probabilities at very early times for left truncated data. This problem might be overcome by instead computing a smoothed nonparametric estimator (SNE) via the EMS algorithm. The close connection between the SNE and the maximum penalized likelihood estimator is also established. Extensive Monte Carlo simulations demonstrate the superior performance of the SNE over that of the NPMLE, in terms of either bias or variance, even for moderately large Samples. The methodology is illustrated with an application to the Massachusetts Health Care Panel Study dataset to estimate the probability of being functionally independent for non-poor male and female groups rcspectively.