Automated Author ProfileTahseen, Danyal
Tahseen, Danyal
Current S-Index
Sum of Dataset Indices for all datasets
Average Dataset Index per Dataset
Average Dataset Index per dataset
Total Datasets
Total datasets for this author
Average FAIR Score
Average FAIR Score per dataset
Total Citations
Total citations to the author's datasets
Total Mentions
Total mentions of the author's datasets
S-Index Interpretation
The S-Index (Sharing Index) is a comprehensive metric that represents the cumulative impact of all your datasets. It is calculated as the sum of Dataset Index scores across all your claimed datasets.
What it means:
- A higher S-index indicates greater overall impact of your datasets relative to typical datasets in their fields of research
- The S-Index grows as you add more datasets or as existing datasets gain more citations and mentions
- It provides a single number to track your research data impact over time
Current S-Index: 4.3 (sum of 2 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
In an increasingly diverse United States (US) population, racial disparities in preterm birth outcomes continue to widen. In this study, we examined temporal trends and risk of preterm birth among Asian American women over a quarter century (1992–2018). This is a retrospective cohort study using the 1992–2018 Natality data files. We conducted joinpoint regression analyses to examine trends in preterm birth among Asian Americans and non-Hispanic (NH) Whites. Bivariate and multivariable analyses were used to identify risk factors associated with preterm birth among Asian Americans and their ethnic sub-groups as compared to NH-Whites. There were a total of 251,278 preterm births among Asian American women, corresponding to a rate of 10.0%, which was relatively stable over time. The incidence of extremely, very and moderate-to-late preterm birth among Asian Americans was 0.4%, 0.9% and 8.7% respectively. Overall, Asian American women exhibited lower adjusted odds (OR = 0.92; 95% CI: 0.88–0.97) of preterm birth than their NH-White counterparts. Comparing Asian American subgroups to NH-Whites, Filipinas and Vietnamese mothers had increased adjusted odds, whereas Chinese, Korean, Japanese and Asian Indian women showed decreased adjusted odds for preterm birth. The risk of preterm birth varied among the ethnic subgroups of Asian Americans in the United States. Future studies should explore the socio-cultural and environmental nuances that might explain these differences.
Authors
- Dongarwar, Deepa ;
- Tahseen, Danyal ;
- Wang, Liye ;
- Aliyu, Muktar H. ;
- Salihu, Hamisu M.
In an increasingly diverse United States (US) population, racial disparities in preterm birth outcomes continue to widen. In this study, we examined temporal trends and risk of preterm birth among Asian American women over a quarter century (1992–2018). This is a retrospective cohort study using the 1992–2018 Natality data files. We conducted joinpoint regression analyses to examine trends in preterm birth among Asian Americans and non-Hispanic (NH) Whites. Bivariate and multivariable analyses were used to identify risk factors associated with preterm birth among Asian Americans and their ethnic sub-groups as compared to NH-Whites. There were a total of 251,278 preterm births among Asian American women, corresponding to a rate of 10.0%, which was relatively stable over time. The incidence of extremely, very and moderate-to-late preterm birth among Asian Americans was 0.4%, 0.9% and 8.7% respectively. Overall, Asian American women exhibited lower adjusted odds (OR = 0.92; 95% CI: 0.88–0.97) of preterm birth than their NH-White counterparts. Comparing Asian American subgroups to NH-Whites, Filipinas and Vietnamese mothers had increased adjusted odds, whereas Chinese, Korean, Japanese and Asian Indian women showed decreased adjusted odds for preterm birth. The risk of preterm birth varied among the ethnic subgroups of Asian Americans in the United States. Future studies should explore the socio-cultural and environmental nuances that might explain these differences.
Authors
- Dongarwar, Deepa ;
- Tahseen, Danyal ;
- Wang, Liye ;
- Aliyu, Muktar H. ;
- Salihu, Hamisu M.