Nadia Rojas

834 total citations · 1 hit paper
10 papers, 574 citations indexed

About

Nadia Rojas is a scholar working on Public Health, Environmental and Occupational Health, General Health Professions and Sociology and Political Science. According to data from OpenAlex, Nadia Rojas has authored 10 papers receiving a total of 574 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Public Health, Environmental and Occupational Health, 4 papers in General Health Professions and 3 papers in Sociology and Political Science. Recurrent topics in Nadia Rojas's work include Obesity, Physical Activity, Diet (6 papers), Food Security and Health in Diverse Populations (4 papers) and Nutritional Studies and Diet (3 papers). Nadia Rojas is often cited by papers focused on Obesity, Physical Activity, Diet (6 papers), Food Security and Health in Diverse Populations (4 papers) and Nutritional Studies and Diet (3 papers). Nadia Rojas collaborates with scholars based in United States and Colombia. Nadia Rojas's co-authors include Jennifer Falbe, Kristine A. Madsen, Charles E. McCulloch, Hannah R. Thompson, Christina M. Becker, Anna H. Grummon, Scott Kaplan, Matthew M. Lee, Lynn Silver and Suzanne Ryan‐Ibarra and has published in prestigious journals such as SHILAP Revista de lepidopterología, American Journal of Public Health and The Journals of Gerontology Series B.

In The Last Decade

Nadia Rojas

7 papers receiving 552 citations

Hit Papers

Impact of the Berkeley Excise Tax on Sugar-Sweetened Beve... 2016 2026 2019 2022 2016 100 200 300

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Nadia Rojas United States 6 447 165 155 102 53 10 574
Suzanne Ryan‐Ibarra United States 9 296 0.7× 158 1.0× 88 0.6× 70 0.7× 39 0.7× 14 487
Christina M. Becker United States 4 269 0.6× 107 0.6× 72 0.5× 57 0.6× 38 0.7× 5 349
Mariana Molina Mexico 7 374 0.8× 157 1.0× 79 0.5× 171 1.7× 41 0.8× 14 498
Julien Leider United States 15 415 0.9× 275 1.7× 129 0.8× 52 0.5× 63 1.2× 62 646
Tayyab Mumtaz Khan Pakistan 5 299 0.7× 92 0.6× 75 0.5× 88 0.9× 27 0.5× 34 442
Ilya Rahkovsky United States 12 325 0.7× 135 0.8× 121 0.8× 21 0.2× 47 0.9× 26 605
Matthew M. Lee United States 9 227 0.5× 115 0.7× 50 0.3× 35 0.3× 28 0.5× 16 373
Daniel Clarke United Kingdom 6 278 0.6× 113 0.7× 54 0.3× 74 0.7× 21 0.4× 9 499
Tara Duhaney Canada 6 409 0.9× 87 0.5× 25 0.2× 96 0.9× 84 1.6× 8 555

Countries citing papers authored by Nadia Rojas

Since Specialization
Citations

This map shows the geographic impact of Nadia Rojas's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Nadia Rojas with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nadia Rojas more than expected).

Fields of papers citing papers by Nadia Rojas

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Nadia Rojas. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Nadia Rojas. The network helps show where Nadia Rojas may publish in the future.

Co-authorship network of co-authors of Nadia Rojas

This figure shows the co-authorship network connecting the top 25 collaborators of Nadia Rojas. A scholar is included among the top collaborators of Nadia Rojas based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Nadia Rojas. Nadia Rojas is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

10 of 10 papers shown
2.
Rojas, Nadia, et al.. (2021). Sugar-Sweetened Beverage Consumption, Perceptions, and Disparities in Children and Adolescents. Journal of Nutrition Education and Behavior. 53(7). 553–563. 29 indexed citations
3.
Falbe, Jennifer, et al.. (2020). Higher Sugar-Sweetened Beverage Retail Prices After Excise Taxes in Oakland and San Francisco. American Journal of Public Health. 110(7). 1017–1023. 47 indexed citations
4.
Falbe, Jennifer, Anna H. Grummon, Nadia Rojas, et al.. (2020). Implementation of the First US Sugar-Sweetened Beverage Tax in Berkeley, CA, 2015–2019. American Journal of Public Health. 110(9). 1429–1437. 33 indexed citations
5.
Madsen, Kristine A., et al.. (2019). Purchasing patterns in low-income neighbourhoods: implications for studying sugar-sweetened beverage taxes. Public Health Nutrition. 22(10). 1807–1814. 9 indexed citations
6.
7.
Rojas, Nadia, et al.. (2016). Exploración de atributos de valor percibido en operadores de telefonía móvil. Características y relaciones. SHILAP Revista de lepidopterología. 27–39.
8.
Falbe, Jennifer, Hannah R. Thompson, Christina M. Becker, et al.. (2016). Impact of the Berkeley Excise Tax on Sugar-Sweetened Beverage Consumption. American Journal of Public Health. 106(10). 1865–1871. 312 indexed citations breakdown →
9.
Falbe, Jennifer, Nadia Rojas, Anna H. Grummon, & Kristine A. Madsen. (2015). Higher Retail Prices of Sugar-Sweetened Beverages 3 Months After Implementation of an Excise Tax in Berkeley, California. American Journal of Public Health. 105(11). 2194–2201. 143 indexed citations
10.
Rojas, Nadia, et al.. (2014). Análisis del valor percibido de operadores de telefonía móvil y sus relaciones con perfiles de usuario: un estudio empírico en Bogotá. 1 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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