Ethnic Disparities in General and Abdominal Adiposity at School Age: A Multiethnic Population-Based Cohort Study in The Netherlands

2014 ◽  
Vol 64 (3-4) ◽  
pp. 208-217 ◽  
Author(s):  
Olta Gishti ◽  
Claudia J. Kruithof ◽  
Janine F. Felix ◽  
Hein Raat ◽  
Albert Hofman ◽  
...  
BMJ Open ◽  
2014 ◽  
Vol 4 (11) ◽  
pp. e005858 ◽  
Author(s):  
Pauline Slottje ◽  
C Joris Yzermans ◽  
Joke C Korevaar ◽  
Mariëtte Hooiveld ◽  
Roel C H Vermeulen

2016 ◽  
Vol 18 (5) ◽  
pp. 537-544 ◽  
Author(s):  
Cesare Russo ◽  
Fusako Sera ◽  
Zhezhen Jin ◽  
Vittorio Palmieri ◽  
Shunichi Homma ◽  
...  

Author(s):  
Martine M.LH. Wassen ◽  
Chantal W.PM. Hukkelhoven ◽  
Hubertina C.J Scheepers ◽  
Luc J.M. Smits ◽  
Jan G. Nijhuis ◽  
...  

2013 ◽  
Vol 12 (1) ◽  
Author(s):  
Anne MJ Gilsing ◽  
Matty P Weijenberg ◽  
R Alexandra Goldbohm ◽  
Pieter C Dagnelie ◽  
Piet A van den Brandt ◽  
...  

2021 ◽  
Author(s):  
G. David Batty ◽  
Bamba Gaye ◽  
Catharine R Gale ◽  
Mark Hamer ◽  
Camille Lassale

AbstractEthnic disparities in COVID-19 hospitalizations and mortality have been reported but there is scant understanding of how these inequalities are embodied. The UK Biobank prospective cohort study comprises around half a million people who were aged 40-69 years at study induction between 2006 and 2010 when information on ethnic background and potential explanatory factors was captured. Study members were linked to a national mortality registry. In an analytical sample of 448,664 individuals (248,820 women), 354 deaths were ascribed to COVID-19 between 5th March and the end of follow-up on 17th September 2020. In age- and sex-adjusted analyses, relative to White participants, Black study members experienced around seven times the risk of COVID-19 mortality (odds ratio; 95% confidence interval: 7.25; 4.65, 11.33), while there was a doubling in the Asian group (1.98; 1.02, 3.84). Controlling for baseline comorbidities, socioeconomic circumstances, and lifestyle factors explained 53% of the differential in risk for Asian people (1.37; 0.68, 2.77) and 27% in Black study members (4.28; 2.67, 6.86). The residual risk in ethnic minority groups for COVID-19 deaths may be ascribed to unknown genetic factors or unmeasured phenotypes, most obviously racial discrimination.


2020 ◽  
Author(s):  
Yanpeng Wu ◽  
Jianhong Pan ◽  
Dong Han ◽  
Lixin Li ◽  
Yanfei Wu ◽  
...  

Abstract Background: Racial and ethnic disparities in stillbirth risk had been documented in most western countries, but it remains unknown in China. This study was to determine whether exist ethnic disparities in stillbirth risk in mainland China.Methods: Pregnancy outcomes and ethnicity data were obtained from the National Free Preconception Health Examination Project (NEPHEP), a nationwide prospective population-based cohort study conducted in Yunnan China from 2010-2018. The Han majority and other four main minorities including Yi, Dai, Miao, Hani were investigated in the analysis. The stillbirth hazards were estimated by life-table analysis. The excess stillbirth risk (ESR) was computed for Chinese minorities using multivariable logistic regression.Results: Compared with other four minorities, women in Han majority were more likely to more educated, less multiparous, and less occupied in agriculture. The pattern of stillbirth hazard of Dai women across different gestation intervals were found to be different from other ethnic groups, especially in 20-23 weeks with 3.2 times higher than Han women. The ESR of the Dai, Hani, Miao, and Yi were 45.05%, 18.70%, -4.17% and 12.28%, respectively. Adjusted for maternal age, education, birth order and other general risk factors, the ethnic disparity still persisted between Dai women and Han women. Adjusted for preterm birth further (gestation age <37 weeks) can reduce 16.91% ESR of Dai women and made the disparity insignificant. Maternal diseases and congenital anomalies explained little for ethnic disparities.Conclusions: We identified the ethnic disparity in stillbirth risk between Dai women and Han women. General risk factors including sociodemographic factors and maternal diseases explained little. Considerable ethnic disparities can be attributed to preterm birth.


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