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Department of Family and Preventive Medicine, University of California, San Diego, La Jolla, CA 92093-0901;
*
Departments of Epidemiology and Biostatistics, University of Washington and
Fred Hutchinson Cancer Research Center, Seattle, WA 98104;
**
Division of Epidemiology, University of Minnesota, Minneapolis, MN 55454;
The Procter & Gamble Company, Cincinnati, OH 45224; and
Division of Gastroenterology, Johns Hopkins School of Medicine, Baltimore, MD 21224
3To whom correspondence should be addressed. E-mail: clrock{at}ucsd.edu.
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ABSTRACT |
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 TOP ABSTRACT INTRODUCTIONSUBJECTS AND METHODSRESULTSDISCUSSIONLITERATURE CITED |
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KEY WORDS: • carotenoids • lutein • zeaxanthin • humans • dietary intake • diet assessment
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INTRODUCTION |
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TOPABSTRACTINTRODUCTIONSUBJECTS AND METHODSRESULTSDISCUSSIONLITERATURE CITED |
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). Lutein and a structurally similar carotenoid, zeaxanthin, accumulate in the retina and comprise the macular pigment (2
). Results from observational studies have suggested a possible inverse relationship between dietary or serum lutein and zeaxanthin and risk for age-related macular degeneration and cataracts (3
–6
), although results are inconsistent across studies. This has stimulated interest in the biological characteristics, dietary intakes and assessment of status for these carotenoids.
Limitations in observational nutrition research make interpretation of studies linking dietary intake or serum concentrations of carotenoids with risk for eye disease quite complex. Food and nutrient composition tables and many published reports on serum concentrations group lutein with zeaxanthin to produce one value (presented as lutein + zeaxanthin) (7
). Other components of the diet such as dietary fat (8
), fiber (9
), food source (10
) and food preparation or processing (11
) influence lutein bioavailability or serum response in experimental studies and thus could potentially influence the relationship between intake and tissue concentrations. Dietary intake is typically self-reported and only crudely quantified, even with the most well-developed methodologies, and therefore is subject to both bias and error. Finally, the high variability in food content and the limited quality and quantity of the food and nutrient composition data for the carotenoids also affect the ability to accurately interpret these data (7
).
Associations between diet or serum lutein concentration and disease outcomes in observational studies may also be confounded by other factors that influence disease risk. For example, dietary and other health-related behaviors usually covary in populations (12
,13
), and many of the other health-related behaviors and influencing lifestyle factors are unmeasured in these studies. Data on dietary and circulating lutein concentrations have been collected and reported from groups and populations with diverse demographic characteristics, health-related behaviors and lifestyle factors (14
–19
), contributing to inconsistencies and variability in findings across studies.
Interpretation of data on circulating carotenoid concentrations is dependent on knowledge of both dietary and nondietary determinants of that body pool. For example, the serum or plasma carotenoid body pool is influenced by the concentration of the cholesterol-rich lipoproteins, which transport these compounds (20
). Smoking status and alcohol consumption also must be considered, due to potential direct effects on metabolism and turnover of these compounds (21
). In previous studies of associations between circulating lutein and zeaxanthin concentrations and macular pigment density or risk for eye disease, these determinants have sometimes (22
–24
), but not always (18
,19
) been considered in the analysis, which may contribute to inconsistencies.
The primary aims of this study were to identify the correlates of dietary lutein + zeaxanthin intake and the determinants of serum lutein and zeaxanthin concentrations in a heterogeneous community-based sample of adults recruited and examined at three U.S. sites (n = 2786). An additional aim was to compare baseline and 1-y serum lutein concentrations in a cohort of 1368 study participants, to describe the variability and to identify the determinants of change over that time period. Knowledge of the factors associated with lutein + zeaxanthin intake and serum concentrations is useful in the interpretation of results from previous studies and in designing analytic studies of the relationships among dietary intake, macular pigment and risk for age-related macular degeneration and cataracts.
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SUBJECTS AND METHODS |
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TOPABSTRACTINTRODUCTIONSUBJECTS AND METHODSRESULTSDISCUSSIONLITERATURE CITED |
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,26
). Data used in this analysis were collected at the three national sites for the study, i.e., Baltimore, MD, Minneapolis, MN and San Diego, CA. Participants for the cross-sectional analysis were recruited and examined between October 1997 and April 1998, just before the introduction of olestra products in these communities. One-year follow-up data collection for the cohort participants occurred between October 1998 and October 1999. Subjects.
Participants for the cross-sectional analysis were adult volunteers identified through a random-digit-dial telephone survey. Response rates to the telephone survey were similar to those obtained in other health-related random-digit-dial surveys (27
). To be eligible for the clinic visit component of the study, participants had to be willing to visit the clinic site, complete questionnaires, provide a blood sample and anthropometric measurements, and complete follow-up telephone interviews. Those with a medical condition that would confound the measurement of associations between diet and serum fat-soluble nutrients (e.g., hemophilia, cystic fibrosis or kidney disease requiring dialysis) were excluded. Participants for the cohort analysis were a subset of those who participated in the cross section. Briefly, all cross section participants received quarterly telephone calls from study staff to monitor diet and health status. In the recruitment of a cohort, the goal was to have 20% of the adults in the cohort be nonconsumers of olestra, and for the remaining 80% to be selected from those reporting the highest levels of consumption (or greater likelihood of olestra consumption) on the follow-up calls. Thus, participants selected for the cohort described in this study consisted of a random sample of 20% of those adults who did not report eating olestra during the follow-up calls (n = 274). The remainder consisted of participants who reported at least one occasion of olestra consumption (43%, n = 588), and participants who reported the highest low-fat snack consumption, as a predictor of olestra use (37%, n = 506). For the three national sites, we invited 1586 adults to the cohort, and 1502 (95%) accepted; 1401 (88%) of those who received initial invitations completed the first follow-up visit. The final sample size number that is described herein reflects reductions due to exclusions and key missing data. Procedures for this study were approved by Institutional Review Boards of all of the organizations involved and written informed consent was obtained from all subjects.
Procedures.
Procedures for the clinic visit, anthropometric measurements, collection of data on demographics, health-related behavior and lifestyle factors, and details on blood collection, processing and analysis, were described previously (25
,26
,28
). Body mass index (BMI) was calculated as weight (kg)/height (m2). Fasting blood samples were obtained, and sera were stored at -80°C until analysis. Data on alcohol intake and smoking were obtained from an interviewer-administered questionnaire. Dietary data were obtained with a self-administered food-frequency questionnaire (FFQ) (29
), with a reference period of "over the past month." The nutrient database for the FFQ is from the University of Minnesota Nutrition Coordinating Center (NCC) nutrient database (Minneapolis, MN) and includes the USDA-NCC Carotenoid Database for U.S. Foods (7
). This database represents considerably updated carotenoid food content data, incorporating data from a large number of published articles on the carotenoid content of foods, new advances in analytical methods and extensive analysis of carotenoid-containing foods sampled from major metropolitan areas of the United States.
Serum carotenoid and cholesterol analysis.
Analysis of serum concentrations of carotenoids (
-carotene, ß-carotene, lycopene, lutein, zeaxanthin and ß-cryptoxanthin) was conducted using HPLC methodology at Quintiles Laboratories (Atlanta, GA) as previously described (26
). Accuracy was assessed by analysis of National Institute of Standards and Technology (NIST) Standard Reference Material SRM 986, Fat-Soluble Vitamins, and by participation in the NIST Micronutrients Measurement Quality Assurance Program. CV for individual analytes ranged from 2.7 to 9.8% for the low-normal sample and from 1.9 to 8.0% for the high-normal sample. Total cholesterol was measured at Quintiles Laboratories, using enzymatic methods and the Boehringer Mannheim/Hitachi 747 analyzer (Roche Laboratory Systems, Indianapolis, IN). Control samples were assayed with each batch of specimens. Precision studies were conducted using packaged reagents, pooled human serum and control sera; this cholesterol method meets the goal of 
3% for both precision and bias.
Statistical analysis.
The original sample size of the cross section was 2876. Pregnant women and those for whom pregnancy status was not ascertained (n = 50) were excluded from analysis, because pregnancy can have profound effects on serum lipid and nutrient concentrations. Further exclusions of participants were due to key missing data (n = 40), including the following: serum lutein missing (n = 12), serum cholesterol missing (n = 16), race/ethnicity missing (n = 5), sex missing (n = 4), age missing (n = 2) and smoking status missing (n = 1). Thus, the final sample size in the models was 2786. A few FFQ and BMI measurements were missing or excluded because of unreliable values [FFQ, energy intake <3347 kJ/d (800 kcal/d) or >20,920 kJ/d (5000 kcal/d) for men or <2510 kJ/d (600 kcal/d) or >16,736 kJ/d (4000 kcal/d) for women (6%); BMI <15 or >60 kg/m2 (0.5%)]. To include subjects with missing BMI in the analysis for dietary intake of lutein + zeaxanthin and serum concentrations, and to include subjects with missing or excluded FFQ in the analysis for serum concentrations, we used the following scheme to complete the data set. The values of the missing or excluded variables were set equal to the means of those variables among all subjects with valid values for the variables. Note that subjects with missing or excluded FFQ had all of their FFQ-derived variables imputed in this manner. Because the subjects who were excluded as outliers might differ systematically from the others (and the imputation of their missing or excluded data by the mean values may differ systematically from their true means), we added dummy variables to denote subjects whose FFQ was missing or excluded due to low or high calculated energy intake and subjects whose BMI was missing or excluded. In the cross-sectional analysis, the time span of data and blood collection was too limited to allow meaningful categorization for season; thus, that variable was included only in the follow-up cohort analysis.
Multiple linear regression was used to model associations between dietary lutein + zexanthin intake and serum lutein or zeaxanthin concentration (as the dependent variables) with demographic, dietary and other factors. Independent variables considered in all models were age, race/ethnicity, education level, sex, BMI, smoking status, alcohol consumption and energy intake. Exercise, sun exposure and clinic site were also used in the analysis for dietary lutein + zeaxanthin intake. Additional variables included in the models for serum lutein (and zeaxanthin) concentrations were dietary lutein + zeaxanthin intake, fiber, and the percentage of energy from fat. The model assumes that the logarithm of dietary lutein + zeaxanthin intake and the logarithm of serum lutein and zeaxanthin concentrations are linearly related. We used the log-linear model because the outcome variables have approximately a log-normal distribution; thus, the log transformation improves the properties of the parameter estimates. We also examined the effect on the association between dietary lutein + zeaxanthin and serum concentrations when demographic variables that cannot directly influence the distribution of carotenoid pools (race/ethnicity, education) were excluded.
Finally, serum lutein concentrations at baseline and 1 y in the cohort were compared. Multiple linear regression was used to model associations between change in serum lutein concentration (as the dependent variable) with change in dietary lutein + zeaxanthin intake and other potentially influencing factors.
Dietary variables (except the percentage of energy from fat) and serum lutein and zeaxanthin concentrations were log transformed before analysis to improve normality. All regression coefficients were interpreted as the percentage of change in the dependent variable associated with change in each independent variable. Values are means ± SD.
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RESULTS |
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TOPABSTRACTINTRODUCTIONSUBJECTS AND METHODSRESULTSDISCUSSIONLITERATURE CITED |
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Of the study sample (n = 2786), 61% were women and 39% were men; the mean age was 44 ± 16 y, ranging from 18 to 92 y. Clinic site was distributed as 30.6% Baltimore, 34.7% Minneapolis and 34.7% San Diego. Race/ethnicity was 73% Caucasian (not Hispanic), 14% African-American, 8% Hispanic, and 5% other (e.g., Asian-American, Native American). Mean BMI was 27.5 ± 6.1 kg/m2, and 23% were smokers. Education level was as follows: high school or less, 28%; graduate degree, 15%; the remainder had some college education. Table 1
gives means and distributions of intakes of dietary lutein + zeaxanthin, fiber, the percentage of energy from fat and serum concentrations.
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gives the results of the regression model predicting dietary lutein + zeaxanthin intake. Gender, race/ethnicity, education level, age, clinic site, BMI, alcohol consumption, sun exposure and exercise were significantly associated with dietary lutein + zeaxanthin intake (P < 0.05) in a model that explained 27% of the variance. Factors with the strongest associations with serum lutein concentration were sex (women > men), race/ethnicity (other > African-American > Hispanic > Caucasian), education (graduate degree > college > high school or less), and exercise (>60 min/d > 30–60 min/d > under 30 min/d). Smoking (compared with nonsmoking) was associated with a 12% lower lutein + zeaxanthin intake.
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gives the results of the regression models predicting serum concentrations of lutein and zeaxanthin. Demographic characteristics, dietary lutein + zeaxanthin intake, serum cholesterol concentration and lifestyle factors explained 24% of the variance in serum lutein concentration. Race/ethnicity, education level and smoking had the strongest associations with serum lutein concentration. Every 10% increase in estimated dietary intake of lutein + zeaxanthin was associated with a 2.4% increase in serum lutein concentration. The partial correlation coefficient for dietary lutein + zeaxanthin intake and serum lutein concentration was 0.24. Variables not significantly associated with serum lutein concentration in this model were alcohol consumption, fiber intake, and the percentage of energy from fat.
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With race/ethnicity and education not included in the models for serum concentrations, the percentage of change in these values per 10% increase in dietary lutein + zeaxanthin increased only slightly, from 2.4 to 2.7% [95% confidence interval (CI) 2.3, 3.0] for serum lutein concentration and from 1.2 to 1.4% (95% CI 1.0, 1.7) for serum zeaxanthin concentration.
Cohort analysis.
In these study participants (n = 1368), age was 45 ± 16 y, range 18–91 y. Mean dietary lutein + zeaxanthin intake was 1367 ± 829 and 1345 ± 831 µg/d at baseline and 1 y, and serum lutein concentration was 0.225 ± 0.111 and 0.259 ± 0.125 µmol/L at baseline and 1 y. In this subset, 82% had serum lutein concentration at 1 y that was within 5% of the value at baseline, 98% had values within 10%, and 99.9% had values within 20%.
The model predicting 1-y change in serum lutein concentration indicated that for each 10% change in dietary lutein + zeaxanthin intake, there was a 1.1% change in serum lutein concentration, adjusted for sex, race/ethnicity, smoking, baseline dietary intake and serum lutein concentration, change in serum cholesterol and BMI, and season, all of which were also significant predictors (R2 = 0.36) (data not shown). Olestra consumption was not identified as a significant predictor of change in serum lutein concentration in this subset of participants in the OPMSS during the year under study.
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DISCUSSION |
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TOPABSTRACTINTRODUCTIONSUBJECTS AND METHODSRESULTSDISCUSSIONLITERATURE CITED |
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). In our previous analysis of 1042 participants of the Indianapolis, IN, OPMSS sentinel site, lutein food content data were derived from the earlier USDA-National Cancer Institute (NCI) Carotenoid Database and food manufacturers (26
,30
), and a 10% increase in dietary lutein intake was associated with a 0.8% increase in serum lutein concentration. The strength of the association between dietary intake and serum lutein concentration observed in the present study represents a threefold increase compared with our earlier observation. We also identified an expanded scope of nondietary factors that are associated with dietary lutein + zeaxanthin intake and serum concentrations.
Several previous epidemiologic studies have examined the association between dietary lutein intake and serum concentration in smaller populations (14
–17
). Adjusted partial correlation coefficients for dietary lutein + zeaxanthin intake and serum lutein concentration in this study falls (r = 0.24) within the range reported for other studies from 0.14 in elderly males (17
) to 0.30 for healthy adults participating in cancer prevention studies (15
). In a study that used the Willett FFQ and the 1993 USDA-NCI Carotenoid Database (16
), multivariate analysis indicated that 20–22% of the variance in serum lutein concentration could be explained by age, BMI, serum cholesterol and triglyceride concentrations, lutein and energy intake, alcohol consumption and menopausal status (for women) in 162 nonsmoking women enrolled in the Nurse’s Healthy Study and 110 nonsmoking men in the Health Professionals Follow-Up Study (16
).
In comparison with these previous epidemiologic studies, the population in the present study is larger and more heterogeneous, including smokers and wider ranges of age, regions of the U.S., education level and race/ethnicity. Although the average participant in this study was overweight, the mean BMI of this group was only slightly higher than the current average BMI for U.S. adults (31
). These characteristics, in addition to lifestyle factors and health-related behaviors, were identified as important predictors of both dietary intake and serum lutein concentrations, and expands on previous reports (14
,26
,32
). Limitations in the food content data and the ability to quantify lutein intake accurately constrain efforts to describe the relationship between this dietary constituent and disease risk. Even when estimated intake is considered in the analysis, demographic and lifestyle factors that are associated with dietary lutein + zeaxanthin intake remain predictive of serum concentrations. The association between these nondietary factors and serum concentration is likely due to their effect on intake.
In small clinical studies that involve a homogeneous group of subjects, the energy-adjusted correlation between circulating lutein concentration and dietary lutein + zeaxanthin intake can be comparatively high (e.g., r = 0.68–0.89) (18
,19
). Differences in the capability of a dietary assessment tool to capture lutein intake accurately in the study subjects, and the period of assessment relative to blood collection, may in part explain this disparity. Also, similarities in the demographic characteristics, health-related behaviors and lifestyle factors in the study subjects would minimize the effect of nondietary determinants.
In experimental feeding studies, both dietary fat and fiber have been shown to influence lutein bioavailability and serum response (9
,33
). Neither of these factors appears to be predictive of serum lutein or zeaxanthin concentration in the general population. Although olestra consumption has been shown to reduce the absorption of carotenoids in experimental studies (34
), no effect on serum lutein concentration was evident when examined in these free-living subjects. However, the effects of potentially influencing factors on serum carotenoid concentrations are more difficult to detect in a study of this type when the behaviors are infrequent in a population (e.g., very-low-fat diet, olestra consumption). Food preparation and processing can influence lutein bioavailability (10
), but the effect of this factor is difficult to assess in large-scale epidemiologic studies. Differences in food preparation and processing may account for some of the unexplained variance in serum concentration in this study.
The degree of variability in serum lutein concentration over time is of interest because the characterization of long-term disease risk of individuals is often based on a sample collected at a single time point (35
). In blood samples obtained 1 y apart, we found minimal variability in the majority of subjects in this study. Changes in the determinants of serum lutein concentration that were identified in the cross-sectional analysis were found to be associated with change over time, including change in dietary lutein + zeaxanthin intake.
Limited ability to explain variance in serum zeaxanthin concentration may be attributable to the small fraction of the total serum and dietary carotenoids that is contributed by this carotenoid (1
), which results in an inherent high variability in the quantity measured. Also, lutein is the primary carotenoid represented in the summed lutein + zeaxanthin food content figure (7
,36
).
In summary, results from this study suggest that dietary lutein intake is independently and significantly predictive of serum lutein concentration in a large, heterogeneous community-based sample of adults. However, the amount of variance in serum concentration that is explained by nondietary factors such as demographic characteristics, health-related behaviors and lifestyle factors remains substantial. Several of the factors found to be predictive of lower dietary lutein + zeaxanthin intake and serum lutein concentration in this study have been independently associated with increased risk for age-related maculopathy and cataracts, such as white race/ethnicity and smoking behavior (22
,32
). Thus, interpreting results from epidemiologic studies investigating the relationship between dietary lutein intake and risk for age-related macular degeneration and cataracts requires careful consideration of these factors, which are associated with risk for eye disease and also lutein intake and serum concentrations.
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FOOTNOTES |
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2 Supported by the Procter & Gamble Company (Cincinnati, OH). By contractual agreements, scientists at the study coordinating center and field sites are solely and independently responsible for data management, analysis and publication.
4 Abbreviations used: BMI, body mass index; FFQ, food-frequency questionnaire; NCC, Nutrition Coordinating Center; NCI, National Cancer Institute; NIST, National Institute of Standards and Technology; OPMSS, Olestra Post-Marketing Surveillance Study.
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LITERATURE CITED |
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TOPABSTRACTINTRODUCTIONSUBJECTS AND METHODSRESULTSDISCUSSIONLITERATURE CITED |
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