Causality or confounding? Applying E values to examine associations between ultra-processed food consumption and risk of weight gain
Robinson E, Jones A
International journal of obesity (2005) · 7 citas
Cómo se estudió
- Diseño
- Metaanálisis (indexado por PubMed)
- Estudiado en
- Personas
- Resultado principal
- Marcadores de salud y funcionamiento
- Consumo medido con
- No se indica
Quién lo pagó
- Financiación
- Financiación independiente
- Gobierno
- National Institute for Health and Care Research
- Gobierno
- Department of Health and Social Care
Según 2 financiadores declarados.
Publicación
- Publicado
- 2024-06-15 · Int J Obes (Lond) · vol. 48 · número 9 · págs. 1342–1346
- Editorial
- Springer Nature
- Citado
- 13 citas · más que el 96% de estudios similares · 4.9× el promedio de su campo
- Impacto
- Entre el 10 % más citado de su campo
- Referencias
- 31 trabajos
- Acceso
- Acceso abierto (revista híbrida) · CC-BY
- Áreas de investigación
- Consumer Attitudes and Food Labeling · Advanced Causal Inference Techniques · Statistical Methods in Epidemiology
- Palabras clave
- ultra-processed foods, weight gain, obesity, unmeasured confounding, E-value, residual confounding, causal inference, depressive symptoms, food access
- MeSH
- humans, obesity, weight gain, prospective studies, causality, adult, female, fast foods, confounding factors, epidemiologic, food, processed
2 autores
- Eric Robinson🇬🇧 · autor de correspondenciaUniversity of Liverpool
- Andrew Jones🇬🇧Liverpool John Moores University
Resumen
El texto original del estudio, en el idioma en que se publicó.
Background
Ultra-processed food (UPF) consumption is associated prospectively with weight gain and obesity in observational studies of adults. Unaccounted for confounding is a risk when attempting to make causal inference from observational studies. Limited research has examined how feasible it is that unmeasured confounding may explain associations between UPF consumption and weight gain in observational research.
Methods
We introduce the E value to obesity researchers. The E value is defined as the minimum hypothetical strength of association that one or more unaccounted for confounding variables would need to have with an exposure (UPF consumption) and outcome (weight gain) to explain the association between the exposure and outcome of interest. We meta-analysed prospective studies on the association between UPF consumption and weight gain in adults to provide an effect estimation. Next, we applied the E value approach to this effect estimate and illustrated the potential role that unmeasured or hypothetical residual confounding variables could theoretically have in explaining associations.
Results
Higher consumption of UPFs was associated with increased weight gain in meta-analysis (RR = 1.14). The corresponding E value = 1.55, indicating that unaccounted for confounding variables with small-to-moderate sized associations with UPF consumption and weight gain (e.g., depressive symptoms, trait overeating tendencies, access to healthy and nutritious food) could individually or collectively hypothetically account for observed associations between UPF consumption and weight gain.
Conclusions
Unaccounted for confounding could plausibly explain the prospective association between UPF consumption and weight gain in adults. High quality observational research controlling for potential confounders and evidence from study types devoid of confounding are now needed.
Resumen vía Europe PMC. Los derechos de autor siguen siendo de los autores o la editorial (CC BY).
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