Observational studies: practical tips for avoiding common statistical pitfalls

Sterrantino, Anna Freni

doi:10.1016/j.lansea.2024.100415

The Lancet Regional Health - Southeast Asia

2024

DOI: 10.1016/j.lansea.2024.100415

|View full text |Cite

Observational studies: practical tips for avoiding common statistical pitfalls

Anna Freni Sterrantino

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2024

Publication Types

Select...

Article2

Relationship

Self Cite0

Independent2

Authors

Journals

Cited by 2 publications

References 45 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

Appropriate Methodology for Studies on Normative Data: Correspondence

Anne,

Mathai,

Thakur

et al. 2024

Indian Pediatr

View full text Add to dashboard Cite

Appropriate Methodology for Studies on Normative Data: Correspondence

Anne,

Mathai,

Thakur

et al. 2024

Indian Pediatr

View full text Add to dashboard Cite

Emerging Biomarkers and Determinants of Lipoprotein Profiles to Predict CVD Risk: Implications for Precision Nutrition

Andersen,

Fernandez

2024

Nutrients

View full text Add to dashboard Cite

Biomarkers constitute a valuable tool to diagnose both the incidence and the prevalence of chronic diseases and may help to inform the design and effectiveness of precision nutrition interventions. Cardiovascular disease (CVD) continues to be the foremost cause of death all over the world. While the reasons that lead to increased risk for CVD are multifactorial, dyslipidemias, plasma concentrations of specific lipoproteins, and dynamic measures of lipoprotein function are strong biomarkers to predict and document coronary heart disease incidence. The aim of this review is to provide a comprehensive evaluation of the biomarkers and emerging approaches that can be utilized to characterize lipoprotein profiles as predictive tools for assessing CVD risk, including the assessment of traditional clinical lipid panels, measures of lipoprotein efflux capacity and inflammatory and antioxidant activity, and omics-based characterization of lipoprotein composition and regulators of lipoprotein metabolism. In addition, we discuss demographic, genetic, metagenomic, and lifestyle determinants of lipoprotein profiles—such as age, sex, gene variants and single-nucleotide polymorphisms, gut microbiome profiles, dietary patterns, physical inactivity, obesity status, smoking and alcohol intake, and stress—which are likely to be essential factors to explain interindividual responses to precision nutrition recommendations to mitigate CVD risk.

show abstract

scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.

Contact Info

customersupport@researchsolutions.com

10624 S. Eastern Ave., Ste. A-614

Henderson, NV 89052, USA

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Blog Terms and Conditions API Terms Privacy Policy Contact Cookie Preferences Do Not Sell or Share My Personal Information

Made with 💙 for researchers

Part of the Research Solutions Family.

Observational studies: practical tips for avoiding common statistical pitfalls

Cited by 2 publications

References 45 publications

Appropriate Methodology for Studies on Normative Data: Correspondence

Appropriate Methodology for Studies on Normative Data: Correspondence

Emerging Biomarkers and Determinants of Lipoprotein Profiles to Predict CVD Risk: Implications for Precision Nutrition

Contact Info

Product

Resources

About