July 2011
Volume 52, Issue 8
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Clinical and Epidemiologic Research  |   July 2011
Dietary Omega-3 Fatty Acids and the Risk for Age-Related Maculopathy: The Alienor Study
Author Affiliations & Notes
  • Bénédicte Merle
    From the INSERM U897, Bordeaux, France;
    Université Bordeaux Segalen, Bordeaux, France; and
  • Marie-Noëlle Delyfer
    From the INSERM U897, Bordeaux, France;
    Université Bordeaux Segalen, Bordeaux, France; and
    CHU de Bordeaux, Service d'Ophtalmologie, Bordeaux, France.
  • Jean-François Korobelnik
    From the INSERM U897, Bordeaux, France;
    Université Bordeaux Segalen, Bordeaux, France; and
    CHU de Bordeaux, Service d'Ophtalmologie, Bordeaux, France.
  • Marie-Bénédicte Rougier
    CHU de Bordeaux, Service d'Ophtalmologie, Bordeaux, France.
  • Joseph Colin
    Université Bordeaux Segalen, Bordeaux, France; and
    CHU de Bordeaux, Service d'Ophtalmologie, Bordeaux, France.
  • Florence Malet
    CHU de Bordeaux, Service d'Ophtalmologie, Bordeaux, France.
  • Catherine Féart
    From the INSERM U897, Bordeaux, France;
    Université Bordeaux Segalen, Bordeaux, France; and
  • Mélanie Le Goff
    From the INSERM U897, Bordeaux, France;
    Université Bordeaux Segalen, Bordeaux, France; and
  • Jean-François Dartigues
    From the INSERM U897, Bordeaux, France;
    Université Bordeaux Segalen, Bordeaux, France; and
  • Pascale Barberger-Gateau
    From the INSERM U897, Bordeaux, France;
    Université Bordeaux Segalen, Bordeaux, France; and
  • Cécile Delcourt
    From the INSERM U897, Bordeaux, France;
    Université Bordeaux Segalen, Bordeaux, France; and
Investigative Ophthalmology & Visual Science July 2011, Vol.52, 6004-6011. doi:10.1167/iovs.11-7254
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      Bénédicte Merle, Marie-Noëlle Delyfer, Jean-François Korobelnik, Marie-Bénédicte Rougier, Joseph Colin, Florence Malet, Catherine Féart, Mélanie Le Goff, Jean-François Dartigues, Pascale Barberger-Gateau, Cécile Delcourt; Dietary Omega-3 Fatty Acids and the Risk for Age-Related Maculopathy: The Alienor Study. Invest. Ophthalmol. Vis. Sci. 2011;52(8):6004-6011. doi: 10.1167/iovs.11-7254.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Purpose.: Previous studies have suggested a lower risk for age-related maculopathy (ARM) in subjects with high dietary intake of long-chain omega-3 polyunsaturated fatty acids (PUFA). The authors report the associations of ARM with past dietary intakes in French elderly subjects.

Methods.: The Alienor Study is a population-based epidemiologic study on nutrition and age-related eye diseases performed in residents of Bordeaux 73 years of age and older. Six hundred sixty-six subjects (1289 eyes) with complete data were included in the analyses. ARM was classified from retinal photographs taken in 2006 to 2008 in five exclusive stages: late neovascular ARM (n = 21 subjects, 29 eyes); late atrophic ARM (n = 19 subjects, 33 eyes); large soft indistinct drusen and/or reticular drusen and/or large distinct drusen with pigment abnormalities (early ARM2, n = 67 subjects, 100 eyes); large soft distinct drusen alone or pigment abnormalities alone (early ARM1, n = 119 subjects, 163 eyes); and no ARM (n = 440 subjects, 964 eyes). Dietary intakes were estimated from a 24-hour dietary recall performed by dieticians (2001–2002). Associations were estimated using logistic Generalized Estimating Equation.

Results.: After multivariate adjustment, subjects with high intake of long-chain omega-3 PUFA showed a decreased risk for early ARM1 (odds ratio [OR], 0.83; 95% confidence interval [95% CI], 0.71–0.98; P = 0.03) and late neovascular ARM (OR, 0.26; 95% CI, 0.08–0.83; P = 0.02). Associations with late atrophic ARM were in the same direction but did not reach statistical significance (OR, 0.74; 95% CI, 0.52–1.06; P = 0.10). Overall, high intakes of long-chain omega-3 PUFA were associated with reduced risk for late ARM (OR, 0.59; 95% CI, 0.39–0.88; P = 0.01).

Conclusions.: These results confirm a decreased risk for ARM in subjects with high intake of long-chain omega-3 PUFA.

Age-related maculopathy (ARM) is the leading cause of blindness in industrialized countries and is becoming increasingly prevalent because of the aging of populations. 1 New treatments stabilize vision, but they are not curative and are limited to the neovascular form of the disease. 2 Genetics appears to explain a large proportion of the variability in risk, but it is not modifiable. 2 Epidemiologic studies suggest the influence of environmental factors, including smoking 3 and nutritional factors. 2 Risk factor identification and preventive strategies, therefore, may have the potential to reduce the impact and burden of ARM on the global aging population. The potential preventive role of nutritional factors, including long-chain omega-3 polyunsaturated fatty acids (PUFA), has aroused increasing interest mainly because of their major structural and protective functions in the retina. 4  
Indeed, very high levels of docosahexaenoic acid (DHA) are present in the membranes of photoreceptors in the retina, while eicosapentaenoic acid (EPA) has vasoregulatory and anti-inflammatory properties; inflammation appears to play a major role in ARM. 4 Long-chain omega-3 PUFA demonstrate antiangiogenic, antivasoproliferative, and neuroprotective actions on factors and processes implicated in the pathogenesis of proliferative and degenerative retinal diseases. 4 Moreover, they have the capacity to affect pathogenic factors and processes implicated in retinal neovascularization. Several epidemiologic studies have suggested inverse associations of ARM risk with dietary long-chain omega-3 PUFA 5 13 and fish intake. 5 7,9 11,13 15 The protective effect of fish consumption has notably been attributed to its high content of long-chain omega-3 PUFA, in particular EPA and DHA, whereas intake of EPA or DHA was usually not estimated separately. 5,8 10,12,13 In addition, few studies presented separate data for atrophic and neovascular ARM, two late forms that may have different etiologies. 16  
We present the associations of ARM with dietary intake of omega-3 PUFA and other fatty acids in French elderly subjects. Our analyses distinguish late atrophic from neovascular ARM and EPA from DHA intakes, taking into account potential confounders, including major genetic factors involved in ARM. 
Subjects and Methods
Study Purpose
The Alienor (Antioxydants, LIpids Essentiels, Nutrition et maladies OculaiRes) Study is a population-based prospective study aimed at assessing the associations of age-related eye diseases (ARM, glaucoma, cataract, dry eye syndrome) with nutritional factors (in particular antioxidants, macular pigment, and fatty acids), determined from plasma measurements and estimations of dietary intake. 17 It also accounts for other major determinants of eye diseases, including gene polymorphisms and environmental and vascular factors. As stated in the protocol, the potential association of ARM with omega-3 PUFA status was one of the main hypotheses tested in this study. 17  
Study Sample
Subjects of the Alienor Study were recruited from an ongoing population-based study (Three-City [C3] Study) on the vascular risk factors for dementia. 18 The 3C Study included 9294 subjects aged 65 years and older from three French cities (Bordeaux, Dijon, Montpellier), among whom 2104 were recruited in Bordeaux. Subjects were contacted individually from the electoral rolls. They were initially recruited in 1999 to 2001 and were followed-up about every 2 years since baseline. Data collected at each examination included cognitive testing with diagnosis of dementia and assessment of vascular risk factors. In addition, fasting blood and DNA samples were collected at baseline and kept frozen at −80°C. 
The Alienor Study consisted of an eye examination, which was proposed to all participants of the third follow-up (2006–2008) of the 3C cohort in Bordeaux. Among the 1450 alive participants reexamined in 2006 to 2008, 963 (66.4%) participated in the Alienor Study, and 487 (33.5%) declined participation. Detailed characteristics of participants and nonparticipants have been published elsewhere. 17  
This research followed the tenets of the Declaration of Helsinki. Participants gave written consent for participation in the study. The design of the Alienor Study has been approved by the Ethical Committee of Bordeaux (Comité de Protection des Personnes Sud-Ouest et Outre-Mer III) in May 2006. 
Eye Examination
The eye examination took place in the Department of Ophthalmology of the University Hospital of Bordeaux. It included a recording of ophthalmological history, measures of visual acuity, refraction, two 45° nonmydriatic color retinal photographs (one centered on the macula, the other centered on the optic disc), measures of intraocular pressure and central corneal thickness, and break-up time test. A self-completed questionnaire on risk factors specific to the eye and dry eye symptoms was completed at home and brought back on the day of the eye examination. 
Retinal photographs were performed using a nonmydriatic retinograph (TRC NW6S; Topcon, Tokyo, Japan) and were interpreted in duplicate by two specially trained technicians. Inconsistencies between the two interpretations were adjudicated by a retina specialist for classification of ARM and other retinal diseases and by a glaucoma specialist for classification of glaucoma. All cases of late ARM, other retinal diseases, and glaucoma were reviewed and confirmed by specialists. None of the persons involved in the interpretation of retinal photographs had access to plasma fatty acid measurements or dietary surveys, which were performed several years before. 
Classification of ARM
Retinal photographs were interpreted according to the international classification 19 and to a modification of the grading scheme used in the Multi-Ethnic Study of Atherosclerosis for drusen size, location, and area. 20 Late ARM was defined by the presence of neovascular ARM or geographic atrophy within the grid (3000 μm from the foveola). Neovascular ARM included serous or hemorrhagic detachment of the retinal pigment epithelium (RPE) or sensory retina, subretinal or sub-RPE hemorrhages, and fibrous scar tissue. Geographic atrophy was defined as a discrete area of retinal depigmentation, 175 μm in diameter or larger, characterized by a sharp border and the presence of visible choroidal vessels. Five cases of late ARM had no gradable photographs and were classified by ophthalmological history of ARM and ARM therapy (in particular, antiangiogenic agents and photodynamic therapy) and confirmed by their treating ophthalmologist. Because etiologies of neovascular and atrophic ARM may be different, 16 we separated two groups: subjects with neovascular ARM (with or without geographic atrophy) and subjects with late atrophic ARM (geographic atrophy without neovascular ARM). 
Early ARM was classified in two groups (in the absence of late ARM): early ARM1, characterized by soft distinct drusen without pigmentary abnormalities or pigmentary abnormalities without large drusen (>125 μm); or early ARM2, characterized by soft indistinct drusen and/or reticular drusen and/or soft distinct drusen associated with pigmentary abnormalities (hyperpigmentation or hypopigmentation). Soft distinct and soft indistinct drusen were larger than 125 μm in diameter and had, respectively, uniform density and sharp edges or decreasing density from the center outward and fuzzy edges. Pigmentary abnormalities were defined as areas of hyperpigmentation and/or hypopigmentation (without visibility of choroidal vessels). 
Eyes were classified according to 1 of the 5 exclusive groups: no ARM, early ARM1, early ARM2, late atrophic ARM, late neovascular ARM. These definitions of ARM are similar to those used in other large epidemiologic studies of ARM, such as the Blue Mountains Eye Study, 21 the Rotterdam Study, 22 and the EUREYE Study, 23 to facilitate comparisons with these studies. 
Dietary Assessment
Dietary intake of fatty acids and other nutrients was determined by a 24-hour dietary recall performed in 2001 to 2002. All consenting participants were visited at home by specifically trained dieticians who administered a Food Frequency Questionnaire and a 24-hour dietary recall during a face-to-face interview. These dieticians received collective training and monitoring to optimize the standardization of the nutritional interviews. During the 24-hour recall, the dietician registered all the meals and beverages consumed in the 24-hour period before the subject awoke on the day of the interview. None were recorded of weekend days. Quantities were assessed according to a book of photographs 24 edited for the SU.VI.MAX Study. 25 The book showed three portion sizes for each food and proposed two intermediate categories plus one below the smallest and one above the largest; in other words, seven portion sizes were available for each of the 236 foods or beverages. A table gave the correspondence between the portion size and the weight of the food item. Photographs of dishes and glasses with the corresponding volume were also available. The same dietician then entered the data of the 24-hour recall software (Bilnut; Nutrisoft, Cerelles, France) to obtain an estimate of the daily nutrient intake of each participant. Food composition tables for France 26 are included in this software. Detailed data for fatty acids from the food composition and nutrition tables edited by Souci et al. 27 were added. Because the 24-hour recall was open-ended, additional data were found by consulting a French table developed by the Institut National de la Santé et de la Recherche Médicale (INSERM) and the University of Montreal, 28 the United States Department of Agriculture National Nutrient Database, on food packaging, and by contact with food manufacturers. Some specific data for fatty acids were directly provided by the Institut des Corps Gras Centre technique Industriel in Bordeaux, France. The results are expressed in quantities per day and in proportion to the total energy intake with or without alcohol. As suggested by Willett et al., 29 the validity of dietary questionnaires was assessed by the evaluation of the inverse association between total fat intake estimated from the 24-hour recall and ln (plasma triglycerides) assessed at baseline (r = −0.05; P = 0.038 in the present study 30 ). This association is based on a meta-analysis 31 showing that replacement of carbohydrates by fat decreased the level of plasma triglycerides. 
Our Food Frequency Questionnaire was not suited for accurate estimation of omega-3 PUFA intake. Therefore, only data from the 24-hour recall were used in the present study. For all statistical models, dietary fatty acids (g/d) were included with Willett's residual method adjusting for total energy intake (kcal/d). 32  
Fatty acids were grouped. Saturated fatty acids (SFA) were the sum of myristic, palmitic, and stearic acids. Monounsaturated fatty acids (MUFA) were the sum of palmitoleic and oleic acids. Total polyunsaturated fatty acids (total PUFA) were the sum of linoleic acid (LA), α-linolenic acid (ALA), arachidonic acid (AA), EPA, and DHA. Omega-6 PUFA was the sum of LA and AA. Total omega-3 PUFA was the sum of ALA, EPA, and DHA; long-chain omega-3 PUFA was the sum of EPA and DHA. 
Other Variables
We selected the following potential confounders, already documented in the literature as associated with the risk for ARM or with fatty acid status: age, sex, educational level, monthly income, smoking, physical activity, dietary antioxidant intake (vitamins C and E, zinc), body mass index (BMI), plasma HDL-cholesterol, complement factor H (CFH) Y402H, age-related maculopathy susceptibility 2 (ARMS2) A69S, and apolipoprotein E2 (ApoE2) and ApoE4 polymorphisms. Except for dietary data, which were collected from 2001 to 2002, these data were collected from baseline, in 1999 to 2001. Physical exercise was assessed by two questions: “Do you practice sports?” and “Do you perspire when you practice sports?” A three-level variable was computed to describe the intensity of physical exercise: none, moderate, or high intensity. Genetic polymorphisms were determined by the Lille Genopôle, from the DNA samples collected at baseline (1999–2001). Plasma lipids were measured at the Biochemistry Laboratory of the University Hospital of Dijon from baseline fasting blood samples. BMI (kg/m2) was calculated as weight/height, 2 using weight and height measured at baseline. Other variables were collected through face-to-face standardized interview. 
The genetic factors included have been shown to be very strong predictors of risk for ARM in the present and previous 33 36 studies. They were included in the multivariate models for two main reasons. First, although no confounding is to be expected, even a slight disequilibrium of fatty acid consumption between the genotypes may induce nonnegligible effects on the estimates of the odds ratio (OR) because of the very strong associations of these genotypes with ARM. Second, the inclusion of these genetic factors in our multivariate models allows implementation of a better specified model, with a higher proportion of variation explained by the model, allowing for a better estimation of the specific effects of fatty acids (as shown by slightly narrower confidence intervals for fatty acids in the complete models). 
Statistical Analyses
For the comparison of subjects included or not included in the statistical analyses, we first performed χ2 and Student's t-tests. We then estimated age- and sex-adjusted P values using logistic regression. 
Associations of each of the four stages of ARM with each of the dietary fatty acids were estimated using logistic Generalized Estimating Equation models, 37 taking into account the data from both eyes and their correlation. In all analyses, subjects without any ARM were considered the reference group. 
In sensitivity analyses, potential gene-environment interactions were first introduced in the models. We withdrew interaction terms, in a stepwise manner, when they were not statistically significant (P > 0.05). All statistical analyses were performed using statistical software (SAS, version 9.1; SAS Institute Inc., Cary, NC). 
Results
Of the 963 participants included in the Alienor Study, 84 (8.7%) subjects had ungradable photographs in both eyes, and 213 (22.1%) had missing data for dietary intake, potential confounders, or both. Thus, the statistical analyses were conducted on 666 subjects, representing 1289 gradable eyes because of ungradable retinal photographs in 43 eyes. 
By comparison with nonparticipants and participants with missing data, participants without missing data showed some differences in sociodemographic status: they were younger, more often males, and had higher educational levels and higher monthly incomes (Table 1). However, after adjustment for age and sex, ARM and nutritional status were not significantly different between these groups of subjects, apart from a difference for total dietary PUFA (8.5 g/d vs. 7.5 g/d, P = 0.04). 
Table 1.
 
Comparison of the Characteristics of Subjects of Alienor Study Included and Excluded for Missing Data and Subjects Not Included in Alienor Study
Table 1.
 
Comparison of the Characteristics of Subjects of Alienor Study Included and Excluded for Missing Data and Subjects Not Included in Alienor Study
Alienor Participants Alienor Participants without versus with Missing Data P Alienor Nonparticipants (n = 487) Alienor Participants without Missing Data versus Alienor Nonparticipants P
Without Missing Data (n = 666) With Missing Data (n = 297)
Sex
    Women 415 (62.3) 182 (61.3) 334 (68.6)
    Men 251 (37.7) 115 (38.7) 0.76 153 (31.4) 0.02
Age, y 80.0 (4.4) 80.5 (4.5) 0.09 82.9 (5.1) <0.0001
Educational level n = 296 0.38 n = 485 <0.001
    No education or primary school only 191 (28.7) 84 (28.4) 211 (43.5)
    Secondary school 185 (27.8) 78 (26.3) 131 (27.0)
    High school 73 (11.0) 24 (8.1) 43 (8.9)
    University 217 (32.5) 110 (37.2) 100 (20.6)
Monthly income, euros n = 291 0.68 n = 476 0.0003
    <750 44 (6.6) 24 (8.3) 57 (12.0)
    750–1500 206 (30.9) 81 (27.8) 191 (40.1)
    1500–2250 176 (26.4) 74 (25.4) 89 (18.7)
    >2250 206 (30.9) 93 (32.0) 106 (22.3)
Not answered 34 (5.2) 19 (6.5) 33 (6.9)
Age-related maculopathy n = 213 0.82
    None 440 (66.0) 140 (65.7)
    Early ARM 1 119 (17.9) 39 (18.3)
    Early ARM 2 67 (10.1) 25 (11.7)
    Late atrophic ARM 19 (2.9) 5 (2.4)
    Late neovascular ARM 21 (3.1) 4 (1.9)
Dietary fatty acids, g/day n = 247 n = 375
    SFA 25.4 (13.2) 25.8 (12.1) 0.67 24.9 (13.5) 0.79
    Monounsaturated 21.6 (11.5) 21.4 (10.6) 0.80 19.9 (10.7) 0.10
    Total PUFA 8.5 (6.1) 8.9 (7.1) 0.44 7.5 (5.4) 0.04
Total omega-6 PUFA 6.6 (5.3) 6.8 (5.9) 0.61 5.8 (4.7) 0.11
Total omega-3 PUFA 1.3 (1.4) 1.3 (1.6) 0.22 1.08 (1.2) 0.10
Alpha-linolenic acid 0.8 (0.8) 0.9 (1.1) 0.23 0.7 (0.7) 0.14
Long-chain omega-3 PUFA 0.4 (1.1) 0.5 (1.1) 0.54 0.4 (0.9) 0.32
    EPA 0.1 (0.3) 0.3 (0.4) 0.46 0.1 (0.3) 0.32
    DHA 0.3 (0.7) 0.3 (0.8) 0.61 0.3 (0.6) 0.33
Energy intake, kcal/day 1716 (551) 1740 (512) 0.54 1626 (558) 0.20
They also were not statistically different with regard to smoking, physical activity, BMI, dietary vitamins C and E, zinc, plasma HDL-cholesterol, CFH Y402H, ApoE4, and ARMS2 polymorphisms (data not shown). However, the frequency of the ApoE2 allele was lower in subjects retained for the statistical analysis: 12.2% versus 17.4% (P = 0.046). 
After adjustment for age, sex, and total energy intake (model 1), high intakes of long-chain omega-3 PUFA, EPA, and DHA were associated with a significantly reduced risk for early ARM1 (Table 2). These associations were not affected by further adjustment for smoking, monthly income, educational level, physical activity, BMI, dietary vitamins C and E, zinc, plasma HDL-cholesterol, CFH Y402H, ApoE4, ApoE2, and ARMS2 A69S polymorphisms (model 2). 
Table 2.
 
Associations of Dietary Omega-3 PUFA with ARM in the Alienor Study
Table 2.
 
Associations of Dietary Omega-3 PUFA with ARM in the Alienor Study
Fatty Acids None (n = 964) Early ARM 1 (n = 163) Early ARM 2 (n = 100) Late Atrophic ARM (n = 33) Late Neovascular ARM (n = 29)
Total omega-3 PUFA*
Mean† ± SD 1.25 ± 1.38 1.10 ± 0.87 1.40 ± 1.84 1.30 ± 1.42 0.80 ± 0.40
Model 1‡ OR§ 0.87 1.05 0.89 0.50
(95% CI) (0.75–1.00) (0.92–1.20) (0.63–1.26) (0.29–0.87)
P 0.06 0.48 0.52 0.01
Model 2‖ OR 0.83 1.03 0.74 0.26
(95% CI) (0.71–0.98) (0.85–1.24) (0.52–1.06) (0.08–0.83)
P 0.03 0.78 0.10 0.02
ALA
Mean ± SD 0.79 ± 0.82 0.79 ± 0.61 0.99 ± 1.25 0.92 ± 1.26 0.64 ± 0.33
Model 1 OR 0.98 1.26 1.01 0.46
(95% CI) (0.79–1.23) (1.03–1.56) (0.56–1.83) (0.15–1.40)
P 0.89 0.03 0.97 0.17
Model 2 OR 0.95 1.17 0.81 0.19
(95% CI) (0.75–1.21) (0.91–1.51) (0.42–1.54) (0.04–0.88)
P 0.69 0.21 0.51 0.03
Long-chain omega-3 PUFA¶
Mean ± SD 0.46 ± 1.11 0.31 ± 0.62 0.40 ± 1.42 0.38 ± 0.82 0.16 ± 0.21
Model 1 OR 0.81 0.92 0.82 0.51
(95% CI) (0.66–0.98) (0.70–1.20) (0.50–1.35) (0.30–0.87)
P 0.03 0.52 0.43 0.01
Model 2 OR 0.78 0.93 0.73 0.38
(95% CI) (0.62–0.97) (0.67–1.28) (0.47–1.13) (0.15–0.97)
P 0.03 0.65 0.16 0.04
EPA
Mean ± SD 0.15 ± 0.37 0.10 ± 0.21 0.13 ± 0.42 0.12 ± 0.24 0.06 ± 0.10
Model 1 OR 0.52 0.77 0.50 0.22
(95% CI) (0.30–0.92) (0.37–1.61) (0.13–2.00) (0.06–0.91)
P 0.02 0.48 0.33 0.04
Model 2 OR 0.45 0.83 0.32 0.12
(95% CI) (0.24–0.85) (0.35–1.96) (0.08–1.33) (0.01–1.19)
P 0.01 0.67 0.12 0.07
DHA
Mean ± SD 0.31 ± 0.77 0.21 ± 0.43 0.27 ± 1.01 0.26 ± 0.58 0.10 ± 0.12
Model 1 OR 0.74 0.88 0.77 0.33
(95% CI) (0.56–0.99) (0.59–1.31) (0.38–1.57) (0.14–0.80)
P 0.04 0.53 0.47 0.01
Model 2 OR 0.71 0.89 0.66 0.22
(95% CI) (0.51–0.98) (0.55–1.45) (0.36–1.21) (0.05–0.88)
P 0.04 0.64 0.18 0.03
High intakes of total and long-chain omega-3 PUFA, EPA, and DHA were associated with a significantly reduced risk for late neovascular ARM in model 1. After further adjustments for all confounders (model 2), risk for late neovascular ARM remained significantly lower among subjects who consumed high amounts of total omega-3 PUFA (OR, 0.26; 95% confidence interval [CI], 0.08–0.83), long-chain omega-3 PUFA (OR, 0.38; 95% CI, 0.15–0.97), and DHA (OR, 0.22; 95% CI, 0.05–0.88). The precursor ALA was also significantly associated with late neovascular ARM after full adjustment (model 2, OR, 0.19; 95% CI, 0.04–0.89). Associations between late atrophic ARM and all omega-3 fatty acids were in the same direction but did not reach statistical significance. 
To compare our results with those of previous studies, which gave only associations with late ARM, we pooled late atrophic and neovascular ARM. We found significant negative associations between late ARM and total omega-3 PUFA (OR, 0.59; 95% CI, 0.39–0.88; P = 0.01), long-chain omega-3 PUFA (OR, 0.58; 95% CI, 0.35–0.94; P = 0.03), EPA (OR, 0.18; 95% CI, 0.04–0.79; P = 0.02), and DHA (OR, 0.47; 95% CI, 0.24–0.93; P = 0.03). 
High consumption of ALA was associated with a significantly increased risk for early ARM2 in model 1 but not in model 2. Among other fatty acids (SFA, MUFA, omega-6 PUFA, LA, and AA), only MUFA showed a positive association with early ARM2 (OR, 1.04; 95% CI, 1.01–1.08; P = 0.004) and a negative association with late atrophic ARM (OR, 0.94; 95% CI, 0.89–0.99; P = 0.02) (Table 3). 
Table 3.
 
Associations of Dietary Fatty Acids with ARM in the Alienor Study
Table 3.
 
Associations of Dietary Fatty Acids with ARM in the Alienor Study
Fatty Acids None (n = 964) Early ARM 1 (n = 163) Early ARM 2 (n = 100) Late Atrophic ARM (n = 33) Late Neovascular ARM (n = 29)
SFA*
Mean ± SD† 24.93 ± 13.17 25.94 ± 12.47 27.18 ± 13.32 28.94 ± 16.82 28.31 ± 17.48
Model 1‡ OR§ 1.00 1.03 1.00 1.02
(95% CI) (0.99–1.02) (1.00–1.05) (0.96–1.04) (0.97–1.06)
P 0.62 0.08 0.92 0.48
Model 2‖ OR 1.01 1.03 1.01 1.00
(95% CI) (0.99–1.03) (0.99–1.06) (0.97–1.05) (0.95–1.05)
P 0.33 0.09 0.67 0.99
MUFA¶
Mean ± SD 21.13 ± 11.17 22.77 ± 11.31 23.23 ± 12.90 22.05 ± 10.69 24.17 ± 15.39
Model 1 OR 1.02 1.03 0.96 1.03
(95% CI) (1.00–1.04) (1.01–1.07) (0.93–1.00) (0.97–1.08)
P 0.10 0.02 0.06 0.36
Model 2 OR 1.03 1.05 0.94 1.03
(95% CI) (1.00–1.05) (1.01–1.08) (0.89–0.99) (0.96–1.11)
P 0.08 0.004 0.01 0.43
Omega-6
PUFA (LA+AA)
Mean ± SD 6.44 ± 5.14 6.77 ± 4.85 7.29 ± 7.05 8.50 ± 6.75 5.47 ± 2.64
Model 1 OR 1.01 1.03 1.03 0.92
(95% CI) (0.98–1.05) (0.99–1.08) (0.96–1.11) (0.83–1.02)
P 0.53 0.13 0.41 0.11
Model 2 OR 1.00 1.04 0.99 0.91
(95% CI) (0.95–1.05) (0.99–1.09) (0.90–1.08) (0.78–1.06)
P 0.95 0.13 0.77 0.23
LA
Mean ± SD 6.28 ± 5.11 6.61 ± 4.81 7.15 ± 7.03 8.29 ± 6.75 5.29 ± 2.61
Model 1 OR 1.01 1.03 1.03 0.92
(95% CI) (0.98–1.05) (0.99–1.08) (0.96–1.11) (0.83–1.02)
P 0.52 0.12 0.43 0.11
Model 2 OR 1.00 1.04 0.98 0.91
(95% CI) (0.95–1.05) (0.99–1.09) (0.90–1.08) (0.78–1.06)
P 0.95 0.13 0.73 0.23
AA
Mean ± SD 0.16 ± 0.21 0.17 ± 0.20 0.14 ± 0.14 0.21 ± 0.16 0.18 ± 0.17
Model 1 OR 0.86 0.50 3.22 1.07
(95% CI) (0.20–3.79) (0.11–2.28) (0.50–20.70) (0.08–13.65)
P 0.85 0.37 0.22 0.96
Model 2 OR 1.00 0.87 3.83 0.81
(95% CI) (0.21–4.88) (0.18–4.12) (0.46–31.98) (0.03–25.26)
P 0.99 0.86 0.21 0.91
In addition, we explored the relative contributions of types of fats over levels by including PUFA in a MUFA model and other fatty acids models. We did not find any OR variation in these models (data not shown). 
Finally, in models with genetic factors, ORs were not modified but 95% CIs were slightly reduced, probably because of a better specification of the models (Tables 2, 3). Because these genetic polymorphisms are involved in inflammation (CFH) and retinal extracellular matrix (ARMS2), both of which may be affected by omega-3 PUFA status, we tested interactions between omega-3 PUFA status and these genotypes. No statistically significant interactions were found (data not shown). 
Discussion
Our results confirmed that the high intake of long-chain omega-3 PUFA was associated with a reduced risk for ARM. Associations were stronger with early ARM1 and neovascular ARM. These associations were independent of genetic susceptibility factors and other known or potential risk factors for ARM (smoking, obesity, HDL-cholesterol). 
All previous studies 5 10,12 15,38 42 but two 43,44 have found a reduced risk for ARM in subjects with high intakes of total and long-chain omega-3 PUFA. Although all results were in the same direction, they did not always reach statistical significance. In a meta-analysis of nine of these studies, subjects with high intakes of omega-3 PUFA showed a 38% decreased risk for ARM (OR, 0.62; 95% CI; 0.48–0.82). 45 Results of the present study are consistent with these data, with a 43% reduction in risk for late ARM in subjects with high intakes of long-chain omega-3 PUFA (OR, 0.57; 95% CI, 0.35–0.96). 
Recently published studies have the advantage of separate analyses for late atrophic and neovascular ARM. 7 10,12 Significantly reduced risk for neovascular ARM in subjects with high consumption of fish or omega-3 PUFA was found in three studies 7,8,12 but not in two others. 9,10 In the AREDS Study, no association between geographic atrophy and dietary omega-3 PUFA was found in the initial case-control study, 6 but a significant association with incident geographic atrophy was evidenced both at 6 and 12 years of follow-up. 8,9 In the present study, the association between omega-3 PUFA and neovascular ARM was statistically significant, whereas the association with late atrophic ARM was in the same direction but did not reach statistical significance. 
With regard to early ARM, results of previous studies were generally in the protective direction but were not always statistically significant. 15,40,42 In the present study, we found inverse statistically significant associations between early ARM1 and total omega-3 PUFA, long-chain omega-3 PUFA, EPA, and DHA. 
We found a negative association between ALA and neovascular ARM (OR, 0.19; 95% CI, 0.04–0.88; P = 0.03). Although ALA is a minor fatty acid in the macula, it is the precursor of long-chain omega-3 PUFA. However, the lack of a specific biological mechanism for ALA and the known low conversion from ALA to long-chain omega-3 PUFA in humans, 4 together with the multiplicity of statistical tests, emphasize the need for further assessments of these associations. 
Increasing levels of MUFA were associated with an increased risk for early ARM2 (OR, 1.05; 95% CI, 1.01–1.08; P = 0.004) and a decreased risk for late atrophic ARM (OR, 0.94; 95% CI, 0.89–0.99; P = 0.01). The Blue Mountain Eye Study (BMES) 42 has shown similar results for early ARM in cross-sectional analyses (OR, 1.48; P = 0.05), but no association was found in prospective analyses. 6 Other studies did not show significant associations. 10,13 With regard to late ARM, results have been inconsistent, with four studies 5,10,13,39 showing an increased risk and two (BMES 6 and the present study) showing a decreased risk for high intakes. 
In the present study, no significant associations were found between SFA dietary intake and ARM, consistent with many other studies. 7,10,13,15,41,42 The causal pathway of higher saturated dietary fat intake, leading to increased atherosclerosis and the development of ARM, is a plausible hypothesis increased ARM in high intakes of SFA. 46 However, most epidemiologic studies did not evidence a significant association. 
Most published studies have shown a negative relationship between fish consumption and ARM. Fish consumption represents the main dietary source of long-chain omega-3 PUFA and can be considered a proxy for the intake of long-chain omega-3 PUFA. However, it can be a crude estimation, especially if fish consumption is estimated by only a few food items. Indeed, the content of long-chain omega-3 PUFA (EPA+DHA) is extremely variable in the different fish species, ranging, for instance, from 0.19 g/100 g in sole to 3.46 g/100 g in mackerel. One strength of the Alienor Study was the accurate assessment of omega-3 PUFA using 24-hour recall and a food composition table that contained the composition of approximately 700 foods, including 72 kinds of fish and seafood. Dietary omega-3 PUFA was assessed not only in fish but in all dietary items (e.g., eggs, oils, margarine, nuts). 
Dietary intake was assessed 5 years before eye examination. More than half the patients with late ARM included in our analysis (67.5%; n = 27) did not report a history of ARM at the time of the 24-hour recall (2001–2002), thus limiting reverse causality (changes in eating habits because of the knowledge of the disease or the induced disability). Moreover, none of the participants used omega-3 supplements in 2001 to 2002. 
Another strength of this study is that major potential confounding factors were taken into account, including sociodemographic status, factors related to lipid metabolism, dietary antioxidants, and especially the major genetic polymorphisms ApoE2, ApoE4, CFH, and ARMS2. 
One limitation to our study could be the representativeness of the sample. The Alienor subsample tended to overrepresent subjects who were younger and of higher socioeconomic status. 18 Included subjects might have been healthier and might have had different lifestyles, especially with regard to diet and physical activity, than the general population. These imperfections might have affected the distribution of nutritional parameters or the prevalence of eye diseases. However, even if our sample was imperfectly representative of the general population, it seems to have had little impact on the prevalence of ARM, which was similar to other studies performed in Europe and other industrialized countries. 22,47 Data collection was performed in the same way in all subjects regardless of their stage of ARM. In particular, people responsible for grading photographs had no access to dietary data, which were collected several years before the eye examination. We can, therefore, assume that the error was not differential and was unlikely to have biased the estimation of the associations of ARM with dietary fatty acids. 
Assessment of dietary consumption, including fatty acids, is particularly difficult in humans. Dietary recall methods rely on the subjects' memories and face the difficulties of the extreme day-to-day variability of the human diet, the hidden nature of many fats used for dressings and cooking, the bias in reporting because of social standards and nutritional recommendations, and the estimation of the nutritional content of foods. This might have led to misclassification of the nutritional status of subjects and, therefore, might have biased the observations toward the null hypothesis. 
In particular, we collected a single 24-hour recall. It would have been more informative to use the average of several 24-hour recalls from different days of the week and from different seasons. One 24-hour recall cannot capture long-term dietary intake patterns for each subject because of high intraindividual variation. However, if sample sizes are sufficiently large, they may be used to determine the average intake in defined subgroups of a population, 48 such as groups of subjects with different types of ARM as in the present study. 
Another limitation of our study was the small number of patients with late ARM, which might have induced insufficient statistical power for detecting some of the associations with dietary fatty acids. This may in part explain the absence of significant relationships with late atrophic ARM. 
In conclusion, this study shows inverse associations of ARM (in particular early ARM1 and neovascular ARM) with long-chain omega-3 PUFA, which is consistent with most previous studies. These results must be confirmed by other large-scale prospective cohort studies and clinical trials (such as AREDS2), which have only the capacity to determine the causal nature of these associations. 
Footnotes
 Supported by Laboratoires Théa (Clermont-Ferrand, France), Fondation Voir et Entendre (Paris, France), and Conseil Régional d'Aquitaine Grant 20091301029. Laboratoires Théa participated in the design of the study but not in the collection, management, or statistical analysis and interpretation of the data or in the preparation, review, or approval of the present manuscript.
Footnotes
 Disclosure: B. Merle, None; M.-N. Delyfer, Théa (C); J.-F. Korobelnik, Bausch & Lomb (C), Novartis (C), Théa (C), Alcon (C), Bayer (C); M.-B. Rougier, Théa (C), Merck Serono (C); J. Colin, None; F. Malet, None; C. Féart, None; M. Le Goff, None; J.-F. Dartigues, Novartis (C), Eisai (C), Janssen (C), Lundbeck (C), Ipsen (C); P. Barberger-Gateau, None; C. Delcourt, Bausch & Lomb (C), Novartis (C), Pfizer (C), Théa (C)
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Table 1.
 
Comparison of the Characteristics of Subjects of Alienor Study Included and Excluded for Missing Data and Subjects Not Included in Alienor Study
Table 1.
 
Comparison of the Characteristics of Subjects of Alienor Study Included and Excluded for Missing Data and Subjects Not Included in Alienor Study
Alienor Participants Alienor Participants without versus with Missing Data P Alienor Nonparticipants (n = 487) Alienor Participants without Missing Data versus Alienor Nonparticipants P
Without Missing Data (n = 666) With Missing Data (n = 297)
Sex
    Women 415 (62.3) 182 (61.3) 334 (68.6)
    Men 251 (37.7) 115 (38.7) 0.76 153 (31.4) 0.02
Age, y 80.0 (4.4) 80.5 (4.5) 0.09 82.9 (5.1) <0.0001
Educational level n = 296 0.38 n = 485 <0.001
    No education or primary school only 191 (28.7) 84 (28.4) 211 (43.5)
    Secondary school 185 (27.8) 78 (26.3) 131 (27.0)
    High school 73 (11.0) 24 (8.1) 43 (8.9)
    University 217 (32.5) 110 (37.2) 100 (20.6)
Monthly income, euros n = 291 0.68 n = 476 0.0003
    <750 44 (6.6) 24 (8.3) 57 (12.0)
    750–1500 206 (30.9) 81 (27.8) 191 (40.1)
    1500–2250 176 (26.4) 74 (25.4) 89 (18.7)
    >2250 206 (30.9) 93 (32.0) 106 (22.3)
Not answered 34 (5.2) 19 (6.5) 33 (6.9)
Age-related maculopathy n = 213 0.82
    None 440 (66.0) 140 (65.7)
    Early ARM 1 119 (17.9) 39 (18.3)
    Early ARM 2 67 (10.1) 25 (11.7)
    Late atrophic ARM 19 (2.9) 5 (2.4)
    Late neovascular ARM 21 (3.1) 4 (1.9)
Dietary fatty acids, g/day n = 247 n = 375
    SFA 25.4 (13.2) 25.8 (12.1) 0.67 24.9 (13.5) 0.79
    Monounsaturated 21.6 (11.5) 21.4 (10.6) 0.80 19.9 (10.7) 0.10
    Total PUFA 8.5 (6.1) 8.9 (7.1) 0.44 7.5 (5.4) 0.04
Total omega-6 PUFA 6.6 (5.3) 6.8 (5.9) 0.61 5.8 (4.7) 0.11
Total omega-3 PUFA 1.3 (1.4) 1.3 (1.6) 0.22 1.08 (1.2) 0.10
Alpha-linolenic acid 0.8 (0.8) 0.9 (1.1) 0.23 0.7 (0.7) 0.14
Long-chain omega-3 PUFA 0.4 (1.1) 0.5 (1.1) 0.54 0.4 (0.9) 0.32
    EPA 0.1 (0.3) 0.3 (0.4) 0.46 0.1 (0.3) 0.32
    DHA 0.3 (0.7) 0.3 (0.8) 0.61 0.3 (0.6) 0.33
Energy intake, kcal/day 1716 (551) 1740 (512) 0.54 1626 (558) 0.20
Table 2.
 
Associations of Dietary Omega-3 PUFA with ARM in the Alienor Study
Table 2.
 
Associations of Dietary Omega-3 PUFA with ARM in the Alienor Study
Fatty Acids None (n = 964) Early ARM 1 (n = 163) Early ARM 2 (n = 100) Late Atrophic ARM (n = 33) Late Neovascular ARM (n = 29)
Total omega-3 PUFA*
Mean† ± SD 1.25 ± 1.38 1.10 ± 0.87 1.40 ± 1.84 1.30 ± 1.42 0.80 ± 0.40
Model 1‡ OR§ 0.87 1.05 0.89 0.50
(95% CI) (0.75–1.00) (0.92–1.20) (0.63–1.26) (0.29–0.87)
P 0.06 0.48 0.52 0.01
Model 2‖ OR 0.83 1.03 0.74 0.26
(95% CI) (0.71–0.98) (0.85–1.24) (0.52–1.06) (0.08–0.83)
P 0.03 0.78 0.10 0.02
ALA
Mean ± SD 0.79 ± 0.82 0.79 ± 0.61 0.99 ± 1.25 0.92 ± 1.26 0.64 ± 0.33
Model 1 OR 0.98 1.26 1.01 0.46
(95% CI) (0.79–1.23) (1.03–1.56) (0.56–1.83) (0.15–1.40)
P 0.89 0.03 0.97 0.17
Model 2 OR 0.95 1.17 0.81 0.19
(95% CI) (0.75–1.21) (0.91–1.51) (0.42–1.54) (0.04–0.88)
P 0.69 0.21 0.51 0.03
Long-chain omega-3 PUFA¶
Mean ± SD 0.46 ± 1.11 0.31 ± 0.62 0.40 ± 1.42 0.38 ± 0.82 0.16 ± 0.21
Model 1 OR 0.81 0.92 0.82 0.51
(95% CI) (0.66–0.98) (0.70–1.20) (0.50–1.35) (0.30–0.87)
P 0.03 0.52 0.43 0.01
Model 2 OR 0.78 0.93 0.73 0.38
(95% CI) (0.62–0.97) (0.67–1.28) (0.47–1.13) (0.15–0.97)
P 0.03 0.65 0.16 0.04
EPA
Mean ± SD 0.15 ± 0.37 0.10 ± 0.21 0.13 ± 0.42 0.12 ± 0.24 0.06 ± 0.10
Model 1 OR 0.52 0.77 0.50 0.22
(95% CI) (0.30–0.92) (0.37–1.61) (0.13–2.00) (0.06–0.91)
P 0.02 0.48 0.33 0.04
Model 2 OR 0.45 0.83 0.32 0.12
(95% CI) (0.24–0.85) (0.35–1.96) (0.08–1.33) (0.01–1.19)
P 0.01 0.67 0.12 0.07
DHA
Mean ± SD 0.31 ± 0.77 0.21 ± 0.43 0.27 ± 1.01 0.26 ± 0.58 0.10 ± 0.12
Model 1 OR 0.74 0.88 0.77 0.33
(95% CI) (0.56–0.99) (0.59–1.31) (0.38–1.57) (0.14–0.80)
P 0.04 0.53 0.47 0.01
Model 2 OR 0.71 0.89 0.66 0.22
(95% CI) (0.51–0.98) (0.55–1.45) (0.36–1.21) (0.05–0.88)
P 0.04 0.64 0.18 0.03
Table 3.
 
Associations of Dietary Fatty Acids with ARM in the Alienor Study
Table 3.
 
Associations of Dietary Fatty Acids with ARM in the Alienor Study
Fatty Acids None (n = 964) Early ARM 1 (n = 163) Early ARM 2 (n = 100) Late Atrophic ARM (n = 33) Late Neovascular ARM (n = 29)
SFA*
Mean ± SD† 24.93 ± 13.17 25.94 ± 12.47 27.18 ± 13.32 28.94 ± 16.82 28.31 ± 17.48
Model 1‡ OR§ 1.00 1.03 1.00 1.02
(95% CI) (0.99–1.02) (1.00–1.05) (0.96–1.04) (0.97–1.06)
P 0.62 0.08 0.92 0.48
Model 2‖ OR 1.01 1.03 1.01 1.00
(95% CI) (0.99–1.03) (0.99–1.06) (0.97–1.05) (0.95–1.05)
P 0.33 0.09 0.67 0.99
MUFA¶
Mean ± SD 21.13 ± 11.17 22.77 ± 11.31 23.23 ± 12.90 22.05 ± 10.69 24.17 ± 15.39
Model 1 OR 1.02 1.03 0.96 1.03
(95% CI) (1.00–1.04) (1.01–1.07) (0.93–1.00) (0.97–1.08)
P 0.10 0.02 0.06 0.36
Model 2 OR 1.03 1.05 0.94 1.03
(95% CI) (1.00–1.05) (1.01–1.08) (0.89–0.99) (0.96–1.11)
P 0.08 0.004 0.01 0.43
Omega-6
PUFA (LA+AA)
Mean ± SD 6.44 ± 5.14 6.77 ± 4.85 7.29 ± 7.05 8.50 ± 6.75 5.47 ± 2.64
Model 1 OR 1.01 1.03 1.03 0.92
(95% CI) (0.98–1.05) (0.99–1.08) (0.96–1.11) (0.83–1.02)
P 0.53 0.13 0.41 0.11
Model 2 OR 1.00 1.04 0.99 0.91
(95% CI) (0.95–1.05) (0.99–1.09) (0.90–1.08) (0.78–1.06)
P 0.95 0.13 0.77 0.23
LA
Mean ± SD 6.28 ± 5.11 6.61 ± 4.81 7.15 ± 7.03 8.29 ± 6.75 5.29 ± 2.61
Model 1 OR 1.01 1.03 1.03 0.92
(95% CI) (0.98–1.05) (0.99–1.08) (0.96–1.11) (0.83–1.02)
P 0.52 0.12 0.43 0.11
Model 2 OR 1.00 1.04 0.98 0.91
(95% CI) (0.95–1.05) (0.99–1.09) (0.90–1.08) (0.78–1.06)
P 0.95 0.13 0.73 0.23
AA
Mean ± SD 0.16 ± 0.21 0.17 ± 0.20 0.14 ± 0.14 0.21 ± 0.16 0.18 ± 0.17
Model 1 OR 0.86 0.50 3.22 1.07
(95% CI) (0.20–3.79) (0.11–2.28) (0.50–20.70) (0.08–13.65)
P 0.85 0.37 0.22 0.96
Model 2 OR 1.00 0.87 3.83 0.81
(95% CI) (0.21–4.88) (0.18–4.12) (0.46–31.98) (0.03–25.26)
P 0.99 0.86 0.21 0.91
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