Your browser doesn't support javascript.
loading
Macular Layer Thickness and Effect of BMI, Body Fat, and Traditional Cardiovascular Risk Factors: The Tromsø Study.
von Hanno, Therese; Hareide, Live Lund; Småbrekke, Lars; Morseth, Bente; Sneve, Monica; Erke, Maja Gran; Mathiesen, Ellisiv Bøgeberg; Bertelsen, Geir.
Affiliation
  • von Hanno T; Department of Ophthalmology, Nordland Hospital Trust, Bodø, Norway.
  • Hareide LL; Department of Clinical Medicine, UiT The Arctic University of Norway, Tromsø, Norway.
  • Småbrekke L; Faculty of Medicine, University of Oslo, Oslo, Norway.
  • Morseth B; Department of Pharmacy, UiT The Arctic University of Norway, Tromsø, Norway.
  • Sneve M; School of Sport Sciences, UiT The Arctic University of Norway, Tromsø, Norway.
  • Erke MG; Hospital Administration, Bærum Hospital, Vestre Viken Hospital Trust, Bærum, Norway.
  • Mathiesen EB; Department of Ophthalmology, Oslo University Hospital, Oslo, Norway.
  • Bertelsen G; Department of Ophthalmology, Oslo University Hospital, Oslo, Norway.
Invest Ophthalmol Vis Sci ; 63(9): 16, 2022 08 02.
Article in En | MEDLINE | ID: mdl-35960516
ABSTRACT

Purpose:

The purpose of this study was to investigate associations between cardiovascular risk factors and the thickness of retinal nerve fiber layer (RNFL), ganglion cell-inner plexiform layer (GCIPL), and outer retina layers (ORL).

Methods:

In this population-based study, we included participants from the Tromsø Study Tromsø6 (2007 to 2008) and Tromsø7 (2015 to 2016). Persons with diabetes and/or diagnosed glaucoma were excluded from this study. Retinal thickness was measured on optical coherence tomography (Cirrus HD-OCT) macula-scans, segmented on RNFL, GCIPL, and ORL and associations were analyzed cross-sectionally (N = 8288) and longitudinally (N = 2595). We used directed acyclic graphs (DAGs) for model selection, and linear regression to adjust for confounders and mediators in models assessing direct effects. Factors examined were age, sex, blood pressure, daily smoking, serum lipids, glycated hemoglobin, body mass index (BMI), total body fat percentage (BFP), and the adjustment variables refraction and height.

Results:

The explained variance of cardiovascular risk factors was highest in GCIPL (0.126). GCIPL had a strong negative association with age. Women had thicker GCIPL than men at higher age and thinner ORL at all ages (P < 0.001). Systolic blood pressure was negatively associated with RNFL/GCIPL (P = 0.001/0.004), with indication of a U-shaped relationship with GCIPL in women. The negative association with BMI was strongest in men, with significant effect for RNFL/GCIPL/ORL (P = 0.001/<0.001/0.019) and in women for GCIPL/ORL (P = 0.030/0.037). BFP was negatively associated with GCIPL (P = 0.01). Higher baseline BMI was associated with a reduction in GCIPL over 8 years (P = 0.03).

Conclusions:

Cardiovascular risk factors explained 12.6% of the variance in GCIPL, with weight and blood pressure the most important modifiable factors.
Subject(s)

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Macula Lutea / Nerve Fibers Type of study: Etiology_studies / Prognostic_studies / Risk_factors_studies Limits: Female / Humans / Male Language: En Journal: Invest Ophthalmol Vis Sci Year: 2022 Type: Article Affiliation country: Norway

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Macula Lutea / Nerve Fibers Type of study: Etiology_studies / Prognostic_studies / Risk_factors_studies Limits: Female / Humans / Male Language: En Journal: Invest Ophthalmol Vis Sci Year: 2022 Type: Article Affiliation country: Norway