Costa Rica’s trans-fat ban impact on cardiovascular disease: a macrosimulation study Article Swipe
Rafael Monge‐Rojas
,
Rulamán Vargas-Quesada
,
Victor E Villalobos-Daniel
,
Eduardo Augusto Fernandes Nilson
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.26633/rpsp.2025.97
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.26633/rpsp.2025.97
Objective: This study uses a modeling framework to assess the potential impact of implementing the World Health Organization (WHO) REPLACE strategy to reduce the intake of industrially produced trans-fatty acids (IP-TFAs) on cardiovascular disease (CVD) in Costa Rica. Methods: The TFA Macrosimulation Model was used to estimate reductions in CVD mortality under three regulatory scenarios: (1) setting IP-TFA limits at 2% in oils and fats and 5% in other foods; (2) applying a uniform 2% IP-TFA limit across all foods; and (3) implementing a complete ban on partially hydrogenated oils (PHOs). Results: The model estimates that enforcing a 2% IP-TFA limit across all foods could prevent or delay approximately 128 deaths annually (3.0% of CVD mortality), while a full PHO ban could avert about 215 deaths per year (5.0% of CVD mortality). Economically, the PHO ban could yield annual savings of approximately US$2.1 million by reducing productivity losses associated with premature mortality. Conclusion: Implementing the WHO REPLACE strategy has the potential to substantially reduce CVD mortality, while also improving the population’s health and economic productivity. These findings offer strong evidence to advocate for regulatory actions in Costa Rica and other nations across the Americas region to eliminate IP-TFAs from the food supply.
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- Language
- en
- Landing Page
- https://doi.org/10.26633/rpsp.2025.97
- https://iris.paho.org/bitstream/10665.2/68854/1/v49e972025.pdf
- OA Status
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All OpenAlex metadata
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Costa Rica’s trans-fat ban impact on cardiovascular disease: a macrosimulation studyWork title
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enPrimary language
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2025Year of publication
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2025-10-10Full publication date if available
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Rafael Monge‐Rojas, Rulamán Vargas-Quesada, Victor E Villalobos-Daniel, Eduardo Augusto Fernandes NilsonList of authors in order
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https://doi.org/10.26633/rpsp.2025.97Publisher landing page
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https://iris.paho.org/bitstream/10665.2/68854/1/v49e972025.pdfDirect link to full text PDF
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diamondOpen access status per OpenAlex
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https://iris.paho.org/bitstream/10665.2/68854/1/v49e972025.pdfDirect OA link when available
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0Total citation count in OpenAlex
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| abstract_inverted_index.under | 55 |
| abstract_inverted_index.while | 122, 174 |
| abstract_inverted_index.yield | 143 |
| abstract_inverted_index.</sec> | 40, 95, 158, 210 |
| abstract_inverted_index.Health | 18 |
| abstract_inverted_index.IP-TFA | 61, 79, 105 |
| abstract_inverted_index.US$2.1 | 148 |
| abstract_inverted_index.across | 81, 107, 199 |
| abstract_inverted_index.annual | 144 |
| abstract_inverted_index.assess | 10 |
| abstract_inverted_index.deaths | 116, 131 |
| abstract_inverted_index.foods; | 73, 83 |
| abstract_inverted_index.health | 179 |
| abstract_inverted_index.impact | 13 |
| abstract_inverted_index.intake | 26 |
| abstract_inverted_index.limits | 62 |
| abstract_inverted_index.losses | 153 |
| abstract_inverted_index.reduce | 24, 171 |
| abstract_inverted_index.region | 202 |
| abstract_inverted_index.strong | 186 |
| abstract_inverted_index.(PHOs). | 94 |
| abstract_inverted_index.IP-TFAs | 205 |
| abstract_inverted_index.REPLACE | 21, 164 |
| abstract_inverted_index.actions | 192 |
| abstract_inverted_index.disease | 35 |
| abstract_inverted_index.million | 149 |
| abstract_inverted_index.nations | 198 |
| abstract_inverted_index.prevent | 111 |
| abstract_inverted_index.savings | 145 |
| abstract_inverted_index.setting | 60 |
| abstract_inverted_index.supply. | 209 |
| abstract_inverted_index.uniform | 77 |
| abstract_inverted_index.Americas | 201 |
| abstract_inverted_index.advocate | 189 |
| abstract_inverted_index.annually | 117 |
| abstract_inverted_index.applying | 75 |
| abstract_inverted_index.complete | 88 |
| abstract_inverted_index.economic | 181 |
| abstract_inverted_index.estimate | 50 |
| abstract_inverted_index.evidence | 187 |
| abstract_inverted_index.findings | 184 |
| abstract_inverted_index.modeling | 7 |
| abstract_inverted_index.produced | 29 |
| abstract_inverted_index.reducing | 151 |
| abstract_inverted_index.strategy | 22, 165 |
| abstract_inverted_index.(IP-TFAs) | 32 |
| abstract_inverted_index.eliminate | 204 |
| abstract_inverted_index.enforcing | 102 |
| abstract_inverted_index.estimates | 100 |
| abstract_inverted_index.framework | 8 |
| abstract_inverted_index.improving | 176 |
| abstract_inverted_index.mortality | 54 |
| abstract_inverted_index.partially | 91 |
| abstract_inverted_index.potential | 12, 168 |
| abstract_inverted_index.premature | 156 |
| abstract_inverted_index.associated | 154 |
| abstract_inverted_index.mortality, | 173 |
| abstract_inverted_index.mortality. | 157 |
| abstract_inverted_index.reductions | 51 |
| abstract_inverted_index.regulatory | 57, 191 |
| abstract_inverted_index.scenarios: | 58 |
| abstract_inverted_index.mortality), | 121 |
| abstract_inverted_index.mortality). | 137 |
| abstract_inverted_index.trans-fatty | 30 |
| abstract_inverted_index.Implementing | 161 |
| abstract_inverted_index.Organization | 19 |
| abstract_inverted_index.hydrogenated | 92 |
| abstract_inverted_index.implementing | 15, 86 |
| abstract_inverted_index.industrially | 28 |
| abstract_inverted_index.productivity | 152 |
| abstract_inverted_index.Economically, | 138 |
| abstract_inverted_index.approximately | 114, 147 |
| abstract_inverted_index.productivity. | 182 |
| abstract_inverted_index.substantially | 170 |
| abstract_inverted_index.cardiovascular | 34 |
| abstract_inverted_index.population’s | 178 |
| abstract_inverted_index.Macrosimulation | 45 |
| abstract_inverted_index.<title>ABSTRACT</title> | 0 |
| abstract_inverted_index.<title>Methods:</title> | 42 |
| abstract_inverted_index.<title>Results:</title> | 97 |
| abstract_inverted_index.<title>Objective:</title> | 2 |
| abstract_inverted_index.<title>Conclusion:</title> | 160 |
| cited_by_percentile_year | |
| countries_distinct_count | 3 |
| institutions_distinct_count | 4 |
| citation_normalized_percentile.value | 0.57765603 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |