PubMed · 11633012
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A C Laurell. 1976. [Not Available].. https://pubmed.ncbi.nlm.nih.gov/11633012/
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BACKGROUND: Effective gene mapping based on genetic association data will require detailed knowledge of patterns of linkage disequilibrium (LD) in human populations. It has been recently suggested that linkage disequilibrium in humans may be organized in a block-like structure, with islands of high LD separated by regions of rapid breakdown of LD due to recombination hotspots. The experimental data to date, however, are limited, and fundamental questions remain about the implications of recombination rate heterogeneity. Here, we use computer simulations to evaluate how such heterogeneity influences patterns of LD, and we develop formal criteria to assess whether the patterns are functionally block like in the context of association mapping. RESULTS: Our analyses suggest that, even in models of extreme recombination rate heterogeneity, some human populations will have a functionally block-like structure to the pattern of LD, but others will not, depending on their precise demographic histories. In fact, for many models, we find that, following an LD-generating event, populations may move through discrete phases that can be functionally described as pre-block, block, and post-block. An analysis of observed and expected patterns of LD surrounding hotspots within the MHC Class II region confirms these theoretical expectations. CONCLUSIONS: Even if highly punctuated patterns of recombination are the rule, patterns of LD are still likely to show differences among populations and among genomic regions that are of practical importance in the design of genetic association studies. The notion that the average extent of LD is a useful concept for the design of association studies must be abandoned in light of the experimental and theoretical evidence.
Over the last decade, new information has been developed and collected to measure the extent of food insecurity and hunger in the United States. Common measurement of the phenomenon of hunger and food insecurity has become possible through efforts of the U.S. Department of Agriculture (USDA) to develop a set of survey questions that can be used to obtain estimates of the prevalence and severity of food insecurity. We evaluated the measurement of food insecurity and the effect of household variables on measured food insecurity. The effects of demographic and survey-specific variables on the food insecurity/hunger scale were evaluated using a generalized linear model with mixed effects. Data came from the 1995, 1997 and 1999 Food Security Module of the Current Population Survey. The results generally validated the model currently used by the USDA. In addition, our approach made it possible to consider the effect of demographics and several survey design variables on food security among measurably food-insecure households, as well as interactions between these factors and the food security questions. The analysis of the expanded model with the 1995 data found results similar to those reported based on the Rasch model used by the USDA. Even though the sample size was reduced and a number of screening and questionnaire changes were introduced in 1997 and 1999, the results for those years appear mostly unchanged and confirm the robustness of the scale in measuring food insecurity. There is some evidence that interpretation of questions may vary among different demographic groups.
The authors examine the research evidence on the effect of residential segregation on health, identify research gaps, and propose new research directions. Four recommendations are made on the basis of a review of the sociological and social epidemiology literature on residential segregation: (1) develop multilevel research designs to examine the effects of individual, neighborhood, and metropolitan-area factors on health outcomes; (2) continue examining the health effects of residential segregation among African Americans but also initiate studies examining segregation among Hispanics and Asians; (3) consider racial/ethnic segregation along with income segregation and other metropolitan area factors such as poverty concentration and metropolitan governance fragmentation; and (4) develop better conceptual frameworks of the pathways that may link various segregation dimensions to specific health outcomes.