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Departments of Clinical Nutrition, Food and Nutrition, College of Health Sciences, Rush University Medical Center, Chicago, IL and * Department of Mathematics, San Francisco State University, San Francisco, CA
2To whom correspondence should be addressed. E-mail: vijay_ganji{at}rush.edu.
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ABSTRACT |
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 TOP ABSTRACT SUBJECTS AND METHODSRESULTSDISCUSSIONLITERATURE CITED |
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70 y old than in those 17 to <30 y old (P < 0.0001), 7.6% lower in women than in men (P = 0.0045), 15.1% lower in people living in the South than those in the West (P < 0.0001), 10.3 and 61.0% lower in the 1st quartile than in the 4th quartile for dietary fat intake (P = 0.0173) and serum cholesterol (P < 0.0001), respectively, 11.1% lower in tomato noneaters than those who ate tomatoes 31 times/mo (P = 0.0085), 13.5% lower in pizza noneaters than those who ate pizza 16 times/mo (P = 0.0016), and 20.6% lower in pasta noneaters than those who ate pasta (with tomato sauce) 16 times/mo (P < 0.0001). Race-ethnicity, alcohol, BMI, blood pressure, and consumption of non-tomato vegetables, and fruits and juices had no association with serum lycopene concentrations. Sex, age, geographical region, socioeconomic status, serum total cholesterol, smoking, and intakes of fat, tomatoes, pizza, and pasta were significant determinants of serum lycopene concentrations in the United States.
KEY WORDS: • lycopene • NHANES III • pizza • serum cholesterol • tomatoes
Lycopene is a 40-carbon acyclic, lipophilic carotenoid with 11 conjugated double bonds arranged in a linear fashion (1). Lycopene is a potent antioxidant due to its conjugated double bonds (2). Because it lacks a ß-ionone ring, it has no provitamin A activity. Among all carotenoids present in food, lycopene has the strongest singlet oxygen (1O2) quenching capacity (3). Lycopene accounts for >50% of total serum carotenoids in humans (4). Depletion of tissue lycopene occurs rapidly when people consume a lycopene free diet for 2 wk (5). Tomatoes (Solanum lycopersicum) and tomato-based products are the primary sources of lycopene in the diet. These foods contribute to >80% of dietary lycopene in the United States (6).
Evidence suggests that a diet high in tomato and tomato-based products and high circulating serum lycopene are associated with decreased risk for cancer (7) and cardiovascular diseases (8). Little is known about the determinants of serum lycopene in the U.S. population. Age is inversely (9) and plasma cholesterol is positively associated with circulating lycopene concentrations (10). The majority of the studies on the determinants of circulating lycopene are based on a small sample size (11–13). Associations between lycopene and smoking (11,12) and alcohol consumption (13,14) are inconsistent. Very little information is available on the association between serum lycopene and BMI and blood pressure. Associations between dietary factors such as fat intake and intake of tomatoes and tomato-based products and serum lycopene have not been studied in a nationally representative sample. Therefore, the objective of this study was to investigate the relations between serum lycopene concentrations and various dietary, demographic, socioeconomic, lifestyle, and health factors in a subset of a representative sample survey of U.S. residents.
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SUBJECTS AND METHODS |
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TOPABSTRACTSUBJECTS AND METHODSRESULTSDISCUSSIONLITERATURE CITED |
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2 mo old (n = 39,695). In the NHANES III, young children, older persons, non-Hispanic blacks, and Mexican Americans were oversampled. The data used in this study were derived from the databases released for public use by the National Technical Information Service, Springfield, VA (15–17). NHANES III has 3 components, i.e., household interview, mobile clinic examination, and home examination. Of 39,695 subjects selected for the survey, 33,994 were interviewed in their homes, 30,818 subjects were examined in mobile clinics, and 493 were examined in the home because they were unable to attend the mobile clinics. Individuals identified as non-Hispanic whites, non-Hispanic blacks, and Mexican Americans were included; individuals of other race-ethnicities were excluded due to small sample size (n = 1494). We excluded subjects who had fasted <9 h (n = 19,133). Also, participants with diabetes (n = 1640), pregnant (n = 338) and lactating women (n = 100), participants with missing information for demographics and covariates, and participants with incomplete food recalls were excluded (n = 7876). After excluding the aforementioned participants, the study included 3413 subjects. Measurements. Data in the NHANES III were collected on demographic, socioeconomic status, physical and health conditions, lifestyle behaviors, biochemical measurements of blood and urine, anthropometric measurements, and dietary intakes. Blood was collected by venipuncture in the mobile examination clinics according to the standard protocol. Serum was separated by centrifugation (1115 x g for 15 min) after blood samples were held at room temperature for 30–60 min. Sera were frozen at –20°C and transported on dry ice to the CDC laboratory. Serum lycopene concentrations were measured at the CDC by reversed-phased HPLC (18). To determine smoking intensity, serum cotinine was analyzed using an ELISA (18). Serum total cholesterol and triacylglycerol were measured enzymatically with a Hitachi 704 analyzer (Boehringer Mannheim Diagnostics) (18).
Blood pressure was measured with a mercury sphygmomanometer (W. A. Baum Co.) according to the standard protocol (19). Participants who answered "yes" to the question "have you taken vitamin/mineral supplements in past month?" were considered to be supplement users. BMI was computed from height and weight measurements (kg/m2). The poverty income ratio (PIR) and years of education were used to define socioeconomic status. The PIR is the ratio of family’s income to the family’s appropriate threshold income (20). Subjects (17 y old) were asked to report their consumption of beer, wine (wine coolers, sangria, and champagne included), and hard liquor (gin, rum, whiskey, tequila, vodka, liqueurs). One drink of alcohol was described as 360 mL beer, 120 mL wine, or 30 mL hard liquor. The total number of alcoholic drinks consumed by participants was computed by adding the numbers of drinks of beer, wine, and hard liquor. Participants who reported 1 total alcoholic drink/mo were categorized as alcohol drinkers. Alcohol drinkers were further classified as light and moderate/heavy drinkers if their reported total alcohol consumption was 1–30 drinks/mo and 31 drinks/mo, respectively.
Dietary assessment. Food intake data were obtained through administration of an 80-item qualitative FFQ and one 24-h food recall. Before intake data collection, the FFQ was pretested and modified to be culturally appropriate for non-Hispanic whites, non-Hispanic blacks, and Mexican Americans (16). Participants were asked how often they ate or drank a particular food or drink over the past month. Intakes were reported as number of times consumed per day, per week, per month, or never. Food frequency consumption data were standardized as times per month, using the conversion factors 4.3 wk/mo and 30.4 d/mo rounded to the nearest whole number. Food frequency data were collected for dairy, meat, cereals, vegetables, fruits, juices, desserts, entrees, coffee, tea, and alcohol. For this study, we used frequency of food consumption data on tomatoes (fresh and stewed tomatoes, tomato juice and salsa), non-tomato vegetables, fruits and juices, pizza (calzone, and lasagna included), and pasta/spaghetti with tomato sauce as potential dietary determinants of serum lycopene because these foods contain lycopene.
Food recall data were collected using an automated, microcomputer-based dietary interview and coding system known as Dietary Data Collection. Participants reported all foods and beverages consumed except plain water for the previous 24-h time period (2400 to 2400 h). Nutrient intakes did not include nutrients from supplements, antacids, medications, and salt and seasonings added to prepared foods at the table. Nutrient composition of foods reported in food recalls was based on the USDA Survey Nutrient Databases (21). A number of quality control measures were employed to ensure the accuracy of food recalls. A detailed description of dietary intake methodology was published elsewhere (22). For this study, we used total fat intake from the food recalls as a potential determinant of serum lycopene.
Statistical analyses. We used SUDAAN statistical software (SUDAAN for Windows, version 8.0.2, Research Triangle Institute) to account for the complex survey sampling design. Sample weights were used to estimate means and SE. Sample weights incorporated the differential probabilities of selection, and included adjustments for noncoverage and nonresponse bias. A detailed description of the survey methodology was published elsewhere (21). We also used SAS (SAS for Windows, version 8.0, SAS Institute) in conjunction with SUDAAN to analyze the data files.
Adjusted means and SE for serum lycopene were calculated with multivariate analysis of covariance (ANCOVA) for demographic, socioeconomic, lifestyle, health, and dietary variables. In the model, serum lycopene was used as a dependent variable and potential determinants of serum lycopene were used as independent variables [sex (men and women), race-ethnicity (non-Hispanic white, non-Hispanic black, and Mexican American), geographical location (North, Northeast, West and South), age (17 to <30 y, 30 to <50 y, 50 to <70 y and 70 to <90 y), PIR (<1.3, 1.3–3.5 and 3.6), education (
8 y, 9–12 y, and 13 y), vitamin/mineral supplement use (yes and no), alcohol intake (0, 1–30, and 31 times/mo), serum cotinine, BMI, systolic and diastolic blood pressures, serum total cholesterol and triacylglycerol, total fat intake, and frequency of consumption of tomatoes (0, 1–15, 16–30 and 31 times/mo), non-tomato vegetables (<15, 16–30 and 31 times/mo), fruits and juices (0, 1–15, 16–30 and 31 times/mo), pizza (0, 1–15, 16 times/mo), and pasta (0, 1–15 and 16 times/mo)]. BMI, systolic and diastolic blood pressures, serum cotinine, total cholesterol and triacylglycerol, and total fat intake were categorized according to their quartiles before they were entered into the model. Within each variable, we designated 1 category as a reference category. Significance between the regression coefficient (ß) of the reference category and other categories within the variable was determined for those variables that were significant in the ANCOVA.
Additionally, multivariate adjusted linear regression analysis was performed on serum lycopene concentration as a continuous dependent variable. In the model, only those variables that were significantly associated with serum lycopene were retained. Race-ethnicity, alcohol consumption, PIR, BMI, systolic and diastolic blood pressures, and frequency of consumption of non-tomato vegetables, and fruits and juices were dropped from the model in a stepwise fashion because these variables were not significantly related to the serum lycopene. The final regression model, adjusted for sex, age, geographical location, and years of education, included serum cotinine, total cholesterol and triacylglycerol, dietary fat intake, and frequency of consumption of tomatoes, pizza, and pasta variables. We found no colinear association among the variables included in the regression model. Variance inflation factors ranged from 1.05 for serum cotinine to 1.41 for serum total cholesterol. Colinearity is a concern when variance inflation factor is >10 (23). Statistical significance for linear trend and ßs were determined. In all analyses, P < 0.05 was considered significant.
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RESULTS |
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TOPABSTRACTSUBJECTS AND METHODSRESULTSDISCUSSIONLITERATURE CITED |
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70 y old, 30% lower in those 50 to <70 y old, and 14.4% lower in those 30 to <50 y old than in those 17 to <30 y old (P < 0.0001); 7.6% lower in women than in men (P = 0.0045); 15.1% lower in individuals living in the South than in those in the West (P < 0.0001); 11.4% lower in individuals with PIR = 1.3 than in those with PIR > 3.5; 10.3% lower in individuals with low fat intake (<50.25 g/d) than in those with high fat intake (>112.73 g/d) (P = 0.0015); 61.0% lower in individuals with low serum total cholesterol (<4.39 mmol/L) than in those with high serum total cholesterol (>5.84 mmol/L) (P < 0.0001); 12.1% lower in individuals with high serum triacylglycerol (>1.72 mmol/L) than in those with low serum triacylglycerol (<0.80 mmol/L) (P = 0.0011); 11.1% lower in tomato noneaters than in those who ate tomatoes 30 times/mo (P = 0.0056); 13.5% lower in pizza noneaters than in those who ate pizza 16 times/mo (P = 0.0081); and 20.6% lower in pasta noneaters than in those who ate pasta (with tomato sauce) 16 times/mo (P < 0.0001). Race-ethnicity, vitamin and mineral supplement use, alcohol consumption, BMI, systolic blood pressure, diastolic blood pressure, and consumption of non-tomato vegetables, and fruits and juices were not associated with serum lycopene. Multivariate adjusted regression analysis of serum lycopene concentrations with lifestyle, health, and dietary intakes is presented in Table 4. After excluding nonsignificant variables in a step-wise fashion, serum cotinine (P = 0.0005 for linear trend) and serum triacylglycerol (P = 0.0004 for linear trend) were inversely, and serum cholesterol (P < 0.0001 for linear trend), dietary fat intake (P < 0.0101 for linear trend), and frequency of consumption of tomatoes (P < 0.0014 for linear trend), pizza (P < 0.0026 for linear trend) and pasta (P < 0.0098 for linear trend) were positively associated with serum lycopene concentrations.
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DISCUSSION |
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TOPABSTRACTSUBJECTS AND METHODSRESULTSDISCUSSIONLITERATURE CITED |
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In this study, serum lycopene concentrations were 
168 nmol/L, 119 nmol/L, and 65 nmol/L lower in individuals aged 70 to <90 y, 50 to <70 y, and 30 to <50 y, respectively, compared with those in the 17-to <30-y-old age group. This translates into a decrease of 14% in serum lycopene concentrations for every 2 decades of life. Also, older individuals consumed pizza and pasta less frequently and tomatoes more frequently than younger individuals (data not shown). For example, 70- to 90-y-old individuals consumed pizza <1 time/mo and pasta 2.1 times/mo compared with pizza 4.5 times/mo and pasta 3.7 times/mo by individuals 17 to 30 y old (P < 0.0001). Lycopene from processed tomatoes such as tomato sauce or paste is more bioavailable than the lycopene from unprocessed tomatoes (24). Although in varied amounts, pizza and pasta often contain tomato paste/sauce. Homogenization and heat treatment of tomatoes release lycopene from the cellular matrix (25) and make more lycopene available for incorporation into micelles (26). The bioavailability of lycopene from tomato paste is 4 times that of lycopene from fresh tomatoes (26). Additionally, fat in the pizza further improves the absorption of lycopene (27). Thus, decreased circulating lycopene in older individuals can be explained by an age-related decrease in lycopene absorption (28), decreased fat intake, and decreased consumption of foods containing processed tomato products because consumption of concentrated tomato products may be associated with heartburn (29).
Participants in the South had lower serum lycopene than those living in the Northeast (P < 0.0001), West (P < 0.0001), and North (P = 0.0008). Because tomato and tomato-based products are the major sources of lycopene, we explored the consumption patterns of lycopene-rich foods in participants living in the South and other regions. We found that the frequency of consumption of pizza was lowest (2.5 times/mo) and tomatoes was highest (14.2 times/mo) among those living in the South. Given the bioavailability differences between processed tomato products and raw tomatoes, one might speculate that differences in intakes of tomato and tomato-based products may account for some variation in serum lycopene in people living in various regions of the United States, although other factors might also affect serum lycopene.
The association between serum cholesterol and triacylglycerol and serum lycopene is not well understood. After absorption, chylomicrons transport lycopene along with dietary fat from the intestine to the blood via lymphatics and then to the liver (1). It is likely that the dietary lycopene taken up by the liver is resecreted into VLDL. Delipidation of VLDL leads to synthesis of LDL. Under fasting conditions, lycopene circulates mainly as part of LDL (30). Because most of the body’s circulating cholesterol is present in LDL, a positive association between serum lycopene and serum cholesterol is expected. What is interesting is the inverse rather than positive association we observed between serum triacylglycerol and lycopene (ß = –21.01; P = 0.0004 for linear trend). Our observation is supported indirectly by the findings of Gross et al. (31) who found an inverse association between VLDL and lycopene in fasting subjects. The combination of serum triacylglycerol, a surrogate marker for VLDL under fasting conditions, and serum total cholesterol accounted for most of the variability in serum lycopene concentrations (Table 4). Increased triacylglycerol has been linked to high intakes of fat and simple carbohydrates (32) and low intakes of fruits and vegetables (31), leading to low intakes of lycopene. This food intake pattern could lead to high triacylglycerol-rich VLDL with low lycopene (31). Thus, it is likely that the inverse association between triacylglycerol and serum lycopene may be related to the dietary intake patterns.
The weak inverse association between smoking and serum lycopene (ß = –0.02, P = 0.0005 for linear trend) is in agreement with some previous reports (5,33). Pamuk et al. (33) reported a 26% lower serum lycopene concentration in smokers compared with nonsmokers (n = 91). Rao and Agarwal (5) reported a 40% decrease in serum lycopene within 30 min after subjects smoked 3 cigarettes. The differences in serum lycopene between smokers and nonsmokers may be due to lower dietary intakes of lycopene by smokers rather than to a negative effect of smoking on the absorption of lycopene (13).
FFQs are an important dietary assessment tools used in several epidemiologic studies because the intake data derived from them is sufficiently valid (34), and the FFQ is a practical and economical method (35) with low respondent and investigator burden (36). Recently, Noethlings et al. (37) reported that data on portion sizes add little to the variance in food intake, and the major part of variance in food intake is explained by the frequency of food consumption alone. Frequencies of consumption of tomatoes and tomato-based products in this study were remarkably similar to the intakes reported earlier (38) although accuracy of dietary intakes may be improved with the additional information on portion sizes.
Cross-sectional studies that use the FFQ dietary assessment method are prone to measurement error due to participants’ inability to recall dietary intakes accurately. The current study has several strengths. Due to the large sample size and vast amount of data available in the NHANES III, we were able to adjust serum lycopene concentrations for several modifying variables. Because the NHANES III design was based on a probability sample survey, the results reported in this study can be applied to the general U.S. population.
In conclusion, in this large population study, age, gender, geographical location, smoking, serum cholesterol and triacylglycerol, and dietary intakes of fat, tomatoes, pizza and pasta were significant determinants of serum lycopene. In light of the positive association between serum lycopene and pizza intake, caution must be exercised in recommending pizza as a source of lycopene. Evidence linking dietary and serum lycopene with cancer and heart disease risk reduction is accumulating, and the exact mechanisms through which lycopene modulates the risk for chronic diseases warrants further clarification.
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FOOTNOTES |
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3 Abbreviations used: ANCOVA, analysis of covariance; NHANES, National Health and Nutrition Examination Survey; PIR, poverty income ratio.
Manuscript received 25 August 2004. Initial review completed 26 September 2004. Revision accepted 1 December 2004.
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LITERATURE CITED |
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TOPABSTRACTSUBJECTS AND METHODSRESULTSDISCUSSIONLITERATURE CITED |
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