Association between four anthropometric indices with age-related Macular Degeneration from NHANES 2005-2008

Abstract

Background: Age-related macular degeneration (AMD) decrease vision and presents considerable challenges for both public health and clinical management strategies. Obesity is usually implicated with increased AMD, and body mass index (BMI) does not reflect body fat distribution. An array of studies has indicated a robust relationship between body fat distribution and obesity. This research is to evaluate the relationship between anthropometric measurements and AMD in the United States citizens in a cohort of patients.

Methods: Our study included a cohort of 3,127 participants, all of whom were selected from the National Health and Nutrition Examination Survey (NHANES) conducted between 2005 and 2008. Various anthropometric indices, including weight (WT), waist circumference (WC), Body Mass Index (BMI), waist-to-height ratio (WtHR), circularity index (CI), weight-adjusted waist circumference index (WWI), body roundness index (BRI), a body size index (ABSI), and visceral adiposity index (VAI), have been studied extensively within public health and nutrition to assess body fat distribution. Odds ratios (OR) for each anthropometric index, in relation to AMD and its different stages, were computed, adjusting for confounding variables. Smoothed curve fitting, coupled with weighted multivariable logistic regression analysis, was used to examine the impact of these anthropometric measures on the prevalence of AMD. Subgroup analyses were conducted according to gender, age, BMI, drinking, smoking, CVD, diabetes, hypertension, cataract operation, and glaucoma.

Results: After adjusting for all variables, significant positive correlations were observed between WtHR (OR = 1.237 (1.065-1.438)), BRI (OR = 1.221 (1.058-1.410)), CI (OR = 1.189 (1.039-1.362)), and WWI (OR = 1.250 (1.095-1.425)) with AMD, particularly for early AMD. However, no significant effects of these indicators were observed in late AMD. CI exhibited a positive linear relationship with AMD. Two-segment linear regression modeling revealed positive nonlinear associations between WtHR, BRI, and WWI with AMD. The positive association was more pronounced with excessive alcohol consumption for WtHR, BRI, CI, and WWI (P for interaction = 0.0033, 0.0021, 0.0194, and 0.0022, respectively). Additionally, WWI and CI exhibited stronger associations with AMD in females (P for interaction = 0.0146 and 0.0117, respectively). Furthermore, WtHR was associated with AMD in non-smokers (P for interaction = 0.0402).

Conclusion: This study confirmed a increased risk between four anthropometric measures, including WtHR, BRI, CI, and WWI, with AMD, especially early AMD. The findings suggest that these four anthropometric indices should be more broadly utilized to improve early AMD prevention and treatment strategies. Additionally, we found that the positive association between these four body measurement indices and AMD was more pronounced in individuals with high alcohol consumption.

Keywords: Age-related macular degeneration; Anthropometric indicators; National health and nutrition examination survey.

Fig. 1

Diagram of participants included in the analyses

Fig. 2

Subgroup analyses to determine the correlation of WtHR and AMD. Multivariable weight logistic analyses were conducted after adjusting for age, gender, BMI, drink, smoke, CVD, diabetes, hypertension, cataract operation, glaucoma

Fig. 3

Subgroup analyses to determine the correlation of CI and AMD. Multivariable weight logistic analyses were conducted after adjusting for age, gender, BMI, drink, smoke, CVD, diabetes, hypertension, cataract operation, glaucoma

Fig. 4

Subgroup analyses to determine the correlation of BRI and AMD. Multivariable weight logistic analyses were conducted after adjusting for age, gender, BMI, drink, smoke, CVD, diabetes, hypertension, cataract operation, glaucoma

Fig. 5

Subgroup analyses to determine the correlation of WWI and AMD. Multivariable weight logistic analyses were conducted after adjusting for age, gender, BMI, drink, smoke, CVD, diabetes, hypertension, cataract operation, glaucoma

Fig. 6

Smooth curve fitting models evaluated the correlation between four anthropometric indices with AMD. Adjusted smooth curve fitting models adjusted for gender, age, race, marital status, education, drinking, smoking, hypertension, diabetes, CVD, cataract operation, and glaucoma. The red line illustrates the smoothed curve that fits the data points, while the blue shaded areas indicate the 95% CI around the fit. (A) Smooth curve fitting model of WtHR. (B) Smooth curve fitting model of CI. (C) Smooth curve fitting model of BRI. (D) Smooth curve fitting model of WWI