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Articles by E. Yeung
Total Records ( 2 ) for E. Yeung
  J. Brite , E. J. Shiroma , K. Bowers , E. Yeung , S. K. Laughon , J. G. Grewal and C. Zhang
 

Aims

Gestational diabetes is a common pregnancy complication affecting races/ethnicities disproportionally. Adult height, an indicator of both genetic and early-life factors, is inconsistently associated with gestational diabetes risk. We examined the association and whether it varies by races in a nationally representative US cohort.

Methods

Analyses were conducted among 135 861 pregnancies in the Consortium on Safe Labor, 5567 of which were diagnosed with gestational diabetes based on medical records review. Generalized estimating equations were used to estimate odds ratios (95% confidence intervals) of gestational diabetes, controlling for other risk factors including body weight. Additionally, a meta-analysis of 15 761 pregnancies with gestational diabetes and 205 828 without gestational diabetes was conducted to estimate the pooled mean difference in height between those with gestational diabetes and control subjects.

Results

Height was inversely associated with gestational diabetes risk across races/ethnicities, with the strongest association among Asians (P for interaction < 0.01). Comparing extreme quartiles (> 168 vs. < 157 cm), adjusted odds ratios (95% confidence intervals) were 0.18 (0.09-0.36) for Asians/Pacific Islanders, 0.33 (0.29-0.38) for non-Hispanic white women, 0.39 (0.31-0.51) for Hispanics and 0.59 (0.47-0.75) for non-Hispanic black women. Meta-analysis found women with gestational diabetes to be significantly shorter than others.

Conclusions

Taller women are at lower risk of developing gestational diabetes, with the magnitude of association varying significantly across races/ethnicities.

  A Ali , S Klasa and E. Yeung
 

Industry concentration measures calculated with Compustat data, which cover only the public firms in an industry, are poor proxies for actual industry concentration. These measures have correlations of only 13% with the corresponding U.S. Census measures, which are based on all public and private firms in an industry. Also, only when U.S. Census measures are used is there evidence consistent with theoretical predictions that more-concentrated industries, which should be more oligopolistic, are populated by larger and fewer firms with higher price-cost margins. Further, the significant relations of Compustat-based industry concentration measures with the dependent variables of several important prior studies are not obtained when U.S. Census measures are used. One of the reasons for this occurrence is that Compustat-based measures proxy for industry decline. Overall, our results indicate that product markets research that uses Compustat-based industry concentration measures may lead to incorrect conclusions.

 
 
 
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