Objective: Retinoids (natural and synthetic derivatives of vitamin A) have cancer chemotherapeutic and chemopreventive activities. Retinoic acid (RA) treatment has been associated with significant regression of preneoplastic lesions. However, serious toxicity associated with some therapies has made long-term chemoprevention in healthy populations unfeasible. Recently, serum RA has been shown to increase in response to oral retinol (vitamin A) supplementation. Here, we assess the variability of circulating RA levels and the lifestyle, demographic, and nutritional factors that explain such variability.

Method: Total RA concentration and the concentrations of RA isomers (all-trans-RA, 13-cis-RA, and 9-cis-RA) were measured by high-pressure liquid chromatography in serum samples obtained 4 months apart from 502 women participating in the Ludwig-McGill Cohort (São Paulo, Brazil).

Results: The relative abundance of the three RA isomers was similar for each visit (baseline and month 4), with 13-cis-RA having the highest concentrations followed by 9-cis-RA and all-trans-RA. The within-person variability of total RA and individual isomers was low. Using multivariate logistic regression models (upper tertile versus low/middle tertile of serum RA), we found that age, race, oral contraceptive use, total number of pregnancies, and season of initial blood draw were significantly associated with at least one endogenous RA isomer level. All endogenous RA isomers were positively associated with serum retinol, β-carotene, and β-cryptoxanthin levels.

Conclusion: These results have implications for the design of future epidemiologic studies focused on assessing RA-disease association and intervention studies aimed at modulating RA levels.

Retinoic acid (RA) is required for many biological processes including vision, development, and reproduction (1-3). RA mediates these activities by binding to nuclear retinoid receptors, members of the steroid hormone receptor superfamily (4), and altering transcriptional activity (1, 5). To date, two families of receptors have been identified, RA receptor (RAR) and retinoid X receptor (5). RAR binds all-trans-RA and 9-cis-RA with equal affinity, whereas retinoid X receptor preferentially binds 9-cis-RA (6). Each receptor family has at least three subtypes (α, β, and γ), and within these subtypes, there are many different isoforms (7). Due to the different receptor isoforms, retinoid receptors can interact with a diverse number of receptors forming homodimers and heterodimers not only with retinoid receptors but also with other steroid hormone nuclear receptors such as vitamin D receptors and the estrogen receptor (8).

Through this potent activity as transcriptional regulators, retinoids (natural and synthetic derivatives of vitamin A) have been shown to be cancer chemotherapeutic and chemopreventive (see also refs. 5, 9, 10 for reviews). RA treatment (all-trans-RA) has been associated with significant regression of several preneoplastic lesions, including oral leukoplakia (11), cervical dysplasia (12), and actinic keratoses (5). Although retinoid chemoprevention is effective, there are toxicities associated with therapy such as varying degrees of teratogenicity and mucocutaneous cytotoxicity (5, 13). These toxicities make long-term chemoprevention among healthy populations with naturally occurring RA unfeasible. 13-Cis-RA (isotretinoin) and N-(4-hydroxyphenyl)retinamide (Fenretinide) have been shown to have lower toxicities, but it remains unclear if these drugs are able to induce retinoid receptor–mediated changes. An alternative retinoid chemoprevention approach is to develop a method for increasing endogenous concentrations of RA. Such an approach was shown to be feasible by Sedjo et al., (36) who reported the modulation of endogenous RA following chemopreventive doses of retinyl palmitate. The focus of this article is to examine if the variability of endogenous RA is associated with variability of dietary intake, implying that diet may modulate levels of RA safely.

Prior to developing research and programs to modulate endogenous RA levels, a reliable method for measuring endogenous RA levels is required and an understanding of the factors that influence endogenous RA levels is needed. For over a decade, various methodologies have been reported for the detection of RA in serum (14-24). Recent improvements in high-pressure liquid chromatography (HPLC) methodologies have facilitated the measurement of endogenous RA within the context of epidemiologic studies. The key improvements include an improved separation of three RA isomers and implementation of high-throughput methods. Using refined methodology for measuring circulating RA levels, it is now possible to assess the variability of RA and the factors associated with endogenous RA levels. This information is essential to the design of future epidemiologic studies focused on assessing RA-disease associations and intervention studies aimed at modulating RA levels.

Using blood samples collected 4 months apart in an ongoing prospective study, the Ludwig-McGill Cohort (São Paulo, Brazil), we investigated the variability of serum RA concentrations and its three major isomers (all-trans-RA, 13-cis-RA, and 9-cis-RA) over a 4-month period. We also examined whether certain lifestyle, demographic, and nutritional factors are associated with the variability in such measurements.

We used blood samples collected previously and stored as part of the Ludwig-McGill Cohort study of the natural history of human papillomavirus infection and cervical neoplasia (25). Briefly, from 1993 to 1997, the Ludwig-McGill Cohort enrolled a systematic sample of 2,528 women attending a comprehensive maternal and child health maintenance program catering to low-income families in the city of São Paulo. The clinic setting where participants were being accrued is part of a network of primary, secondary, and tertiary health care institutions maintained by the municipal health department. Cohort participants were examined every 4 months in the first year and twice yearly thereafter for a total of 5 years. At each study visit, participants were interviewed based on a structured questionnaire specific for the current visit (25). As described previously, the mean age at enrollment was 31 years (median, 33 years; ref. 25). The institutional review boards and ethical committees of all institutions with which the authors are affiliated approved these protocols. Each study participant signed an approved informed consent document.

Study Sample

Of the 2,528 women in the cohort, we identified a subcohort of women (n = 1,392), representing mostly those entering the study during the first 2 years (1993-1995) and who had provided long-term follow-up. We then selected the 846 women who provided data and serum for all four visits within the first year. Of these women, 810 had sufficient serum for RA analysis at visits 1 (month 0) and 2 (month 4). We then limited the study sample to those women that were human papillomavirus negative and had normal cervical cytology (n = 502).

Diet Questionnaire

Information on the frequency of consumption of selected food items and the consumption of vitamin and mineral supplements was obtained at visit 2 (month 4). This dietary questionnaire was specifically designed for application within the Ludwig-McGill Cohort to low-income women in São Paulo. Participants were asked to recall the usual frequency of consumption, during the past 5 years, of the following 15 food items: oranges, lemons, carrots, pumpkin, papaya, cauliflower, spinach, broccoli, lettuce, other vegetables, eggs, milk and yogurt, cheese, butter, and liver. These foods contributed substantially to variation in intake of carotenoids and tocopherols among Brazilian women living in São Paulo. The food consumption-frequency categories were as follows: never, <1 time monthly, 2 to 3 times monthly, 1 to 3 times weekly, 4-6 times weekly, and ≥1 time daily. Women in this study did not report a substantial consumption of vitamin and mineral supplements (26).

Nutrient Intake Values

Diet provides retinol (preformed vitamin A) in the form of retinol ester from animal products (liver, eggs, milk, cheese, and butter) or as pro–vitamin A carotenoids (e.g., β-carotene, α-carotene, and β-cryptoxanthin; refs. 1-3). Through a series of controlled metabolic reactions, retinol and pro–vitamin A carotenoids are converted to RA in vivo. Therefore, nutrient intake of vitamin A and carotenoid-rich foods was focused on in this report. The determination of nutrient values for this population has been reported in detail previously (26). In brief, nutrient values were calculated from the participants' reported dietary intake by use of the U.S. Food and Drug Administration's Continuing Survey of Food Intake of Individuals (1986) and Nationwide Food Consumption Survey (1987-1988), unless Brazil-specific nutrient values were available. When available, food carotenoid values (e.g., β-carotene, lutein/zeaxanthin, and β-cryptoxanthin) were derived from published values for foods consumed in São Paulo (27). Dietary intake calculations used age-specific portion sizes for women, as described elsewhere (28). From these databases, nutrient values were obtained for vitamin A, carotenoids (α-carotene, β-carotene, β-cryptoxanthin, and lutein/zeaxanthin), and vitamin C.

Because the questionnaire used in this study was short, we examined the association between consumption of certain fruits and vegetables and corresponding serum concentrations of carotenoids. Serum concentrations of certain carotenoids were correlated with consumption of citrus fruits and carrots (26) in a group of 100 women. In addition, we evaluated the crude and energy-adjusted (29) associations between intake of carotenoids and serum concentrations of carotenoids and found stronger associations when the energy-adjusted intake values for carotenoids were used (data not shown). The primary purpose of energy adjustment of nutrient values was to adjust for the tendency of individuals to consistently underreport or overreport intake values when a frequency checklist is used (29). Therefore, all dietary intake analyses used energy-adjusted nutrient values.

Sample Processing and Storage

All nonfasting blood samples (∼10 mL) were collected by venipuncture into green top vacutainers by a trained nurse at the time of the clinic visit. The samples were centrifuged within 6 to 8 hours of collection. Aliquots (1 mL) of serum were stored in 1.8 mL Nunc cryovials at −20°C in a non-frost-free freezer until shipped for analyses. Serum from the first two clinical visits (months 0 and 4) was used to measure RA. To address the known variability of serum carotenoids (30), we determined serum retinol and carotenoids in four serum samples obtained within the first year (months 0, 4, 8, and 12). Total cholesterol was determined at the third visit (month 8) by coupled enzymatic, colorimetric assay (Sigma kit 401-25P, Sigma Chemical Co., St. Louis, MO).

Serum RA HPLC Analytic Procedures

RA analyses were conducted on serum samples from the first two visits (months 0 and 4). The 9-cis-RA and all-trans-RA were purchased from Sigma Chemical and 13-cis-RA was obtained from ICN Biomedicals (Aurora, OH). The following reagents were used for sample preparation and analysis: butylated hydroxytoluene, hexane, ethanol, methanol, acetonitrile, HCl, NaOH, and acetic acid. All solvents were HPLC grade or equivalent and were used without further treatment.

Sample extraction and preparation was done using a modification of the method reported by Miyagi et al. (14). After thawing 500 μL aliquots of serum, samples were deproteinated with 500 μL of acetonitrile/methanol (19:1) containing 0.01% butylated hydroxytoluene and made alkaline with 100 μL of 2 N NaOH. Samples were extracted by vortex mixing for 45 seconds with 1.5 mL of hexane containing 0.025% butylated hydroxytoluene as an antioxidant. The organic phase was discarded. Samples were acidified with 200 μL of 2 N HCl and extracted three times with 1.5 mL of hexane with butylated hydroxytoluene. The combined supernatant was evaporated under nitrogen. The residue was dissolved by vortex mixing with 120 μL of mobile phase consisting of 75% acetonitrile, 5% methanol, and 20% of 1% acetic acid. The injection volume was 90 μL.

The HPLC separation was done using a modified method reported by Dimitrova et al. (15). HPLC analysis was done using a ThermoSeparation Products liquid chromatograph with the following components: P4000 solvent delivery system, vacuum degasser, AS3000 autosampler, Spectra FOCUS scanning UV-visible detector, and PC1000 computer-controlled data system (Fremont, CA). On the autosampler, samples were refrigerated at 10°C and the column was maintained at 30°C. RA isomers were monitored at 350 nm. The analytic column was a Spherisorb ODS2 (3 μm, 4.0 × 250 mm) with Javelin guard column containing Keystone ODS2 (3 μm, Keystone Scientific, Inc., Bellefonte, PA). The mobile phase had a flow rate of 1 mL/min.

Linear calibration curves were prepared consisting of three concentrations of RA isomers that spanned the physiologic levels in serum. Quantification was done by external standard calibration using peak area ratios. In-house quality control samples were analyzed at the beginning and end of each sample queue. The relative SD of analytes in the quality control samples ranged from 10% to 15%. This system had a limit of detection of 0.1 ng/mL and limit of quantification of 0.3 ng/mL (5 pmol/L). Samples below the limit of quantification were assigned a value halfway between zero and the lower limits of detection: these accounted for 10 (1%) all-trans-RA, 20 (2%) 13-cis-RA, and 85 (8.5%) 9-cis-RA samples of the 1,004 samples analyzed.

Serum Retinol and Carotenoids HPLC Analytic Procedures

Archival serum from all four visits within the first year (months 0, 4, 8, and 12) on study were analyzed to detect retinol and carotenoids in serum using a modification of the procedures described by Nomura et al. (31). The percentage coefficient of variation was ≤8% for retinol and all carotenoids measured. This HPLC system's limit of quantification was 0.004 μg/mL for the carotenoids. Of the total 2,008 samples analyzed over four clinical visits, the following numbers of samples (%) were below the limit of quantification and assigned a value halfway between zero and the lower limits of detection: retinol 2 (<0.1%), α-cryptoxanthin 654 (33%), β-cryptoxanthin 187 (9%), α-carotene 514 (26%), trans-β-carotene 296 (15%), cis-β-carotene 621 (30%), lutein 10 (0.5%), and lycopene 425 (21%). Due to many samples being below the detectable limit for α-cryptoxanthin and α-carotene, these results will not be used in the analyses. Trans-β-carotene and cis-β-carotene were combined for a measure of total serum β-carotene.

Statistical Analysis

RA concentrations were right skewed; therefore, we used nonparametric statistical methods for most analyses. Differences between month 0 (visit 1) and month 4 (visit 2) were assessed using a Wilcoxon rank sum test, and correlations between paired nutrient values were examined by calculating Spearman correlation coefficients. To assess the between-woman and within-woman variability of RA, we estimated a linear mixed effects model using log-transformed nutrient values. Only samples that were above the detectable limit of the assay were included in this analysis. The mixed models analyses were done using PROC MIXED in SAS version 9.0 (Cary, NC; ref. 32).

As the differences in RA concentrations were low between visits (Table 1), we calculated the mean of two RA measures per individual. We determined if there was a difference in the rank distribution of total RA and each isomer by lifestyle and demographic characteristics using the Wilcoxon rank sum test (2 categories) or Kruskal-Wallis test (≥3 categories) without regard to the ordering. For factors that were ordered, a nonparametric test for trend, which is an extension of the Wilcoxon rank sum test (33), was used to test whether there was a significant trend across ordered groups. Spearman correlations were calculated between total RA and each isomer, serum retinol, and serum β-carotene for each visit, adjusting for laboratory batch analysis.

Table 1.

Endogenous levels of RA, retinol, and β-carotene in Brazilian women (n = 502)

Visit 1
Visit 2
P*
Mean (SD)MedianRangeMean (SD)MedianRange
Total RA (ng/mL) 3.21 (1.23) 3.07 0.81-8.90 3.19 (1.33) 3.12 0.44-9.91 0.958 
    Cis-isomer (ng/mL)        
        13-Cis-RA 1.35 (0.74) 1.21 0.15-5.60 1.30 (0.74) 1.25 0.15-7.00 0.604 
        9-Cis-RA 1.02 (0.58) 1.06 0.15-3.90 1.05 (0.59) 1.08 0.15-3.83 0.445 
    All-trans-isomer 0.83 (0.39) 0.76 0.15-3.50 0.83 (0.45) 0.76 0.15-5.14 0.810 
Retinol (μg/mL) 0.465 (0.169) 0.437 0.007-2.083 0.446 (0.172) 0.416 0.075-1.998 0.012 
Total β-carotene (μg/mL) 0.044 (0.079) 0.020 0.004-0.650 0.032 (0.039) 0.021 0.004-0.609 0.762 
Visit 1
Visit 2
P*
Mean (SD)MedianRangeMean (SD)MedianRange
Total RA (ng/mL) 3.21 (1.23) 3.07 0.81-8.90 3.19 (1.33) 3.12 0.44-9.91 0.958 
    Cis-isomer (ng/mL)        
        13-Cis-RA 1.35 (0.74) 1.21 0.15-5.60 1.30 (0.74) 1.25 0.15-7.00 0.604 
        9-Cis-RA 1.02 (0.58) 1.06 0.15-3.90 1.05 (0.59) 1.08 0.15-3.83 0.445 
    All-trans-isomer 0.83 (0.39) 0.76 0.15-3.50 0.83 (0.45) 0.76 0.15-5.14 0.810 
Retinol (μg/mL) 0.465 (0.169) 0.437 0.007-2.083 0.446 (0.172) 0.416 0.075-1.998 0.012 
Total β-carotene (μg/mL) 0.044 (0.079) 0.020 0.004-0.650 0.032 (0.039) 0.021 0.004-0.609 0.762 
*

Ps testing the null hypothesis that the difference between visits 1 and 2 is zero using the Wilcoxon rank sum test.

Multiple logistic regression was done to estimate the magnitude of the associations [odds ratio (OR) and 95% confidence interval (95% CI)] with RA levels and various sociodemographic and lifestyle factors. The study aim was to determine factors independently associated with elevated levels of RA, total and isomer specific. Therefore, we categorized women as having high values if their endogenous RA level fell within the upper tertile of the overall distribution and women as having low to medium levels if their level was below the upper tertile. Modeling began by using backward stepwise logistic regression models to identify the lifestyle and demographic factors that were independently associated with total RA or individual isomers with a probability of removal set at 0.1. Factors that were considered in the first set of models were race (White versus non-White), oral contraceptive (OC) use, total number of pregnancies, smoking status, alcohol consumption, season of enrollment, education, and income. Age, in intervals of 5 years, was included in all final models regardless of significance level. A stabilization of the Brazilian economy occurred in July 1994, 9 months following initial enrollment in the study, which most likely effected women's socioeconomic status and spending patterns. We found this to be associated with differences in serum carotenoids and controlled for this confounding variable by inputting an indicator variable (enrollment before July 1994 or after) into the final multivariate models. Finally, a difference in chromatographic results across HPLC run batches was observed. This was controlled statistically by including a variable for HPLC batch in all analyses. However, because the RA category was the same for all samples in two batches, these data were dropped during statistical modeling (n = 49 and 107, respectively). As a result, a smaller number of women were included in these logistic regression models (n = 451 for 13-cis-RA, 393 for 9-cis-RA, and 501 for all-trans-RA). To assess the influence of these two batches on our modeling, we repeated the logistic regression analyses removing all samples from the specified batches and found no differences in our conclusions (data not shown).

Using the above as a base model, we examined whether serum retinol and carotenoids (pro–vitamin A: β-carotene, α-carotene, β-cryptoxanthin, and lutein and non-pro–vitamin A: lycopene) were independently associated with RA levels using multivariate logistic regression. In addition, we examined if RA levels were associated with increased vitamin A and pro–vitamin A carotenoid intake and consumption of select foods. To test for linear trends, we treated all nutrient variables as continuous in the multivariate logistic regression models. Statistical significance was set at the 0.05 level and all analyses were two sided. Univariate and logistic regression analyses were done in Stata version 7.0 (College Station, TX), and mixed models analyses and adjusted Spearman correlations were done in SAS version 9.0 (34).

The mean, median, and range of the concentrations of endogenous RA, retinol, and β-carotene at each visit are presented in Table 1. Overall, total RA concentrations ranged from 0.81 to 8.90 ng/mL (2.70-29.6 nmol/L) at visit 1 and from 0.44 to 9.91 ng/mL (1.46-32.98 nmol/L) at visit 2 and did not differ by visit. Median (range) baseline endogenous concentrations among the 502 women were 1.30 (0.15-4.90), 1.10 (0.15-3.23), and 0.76 (0.15-3.17) ng/mL for 13-cis-RA, 9-cis-RA, and all-trans-RA, respectively. The relative abundance of the three RA isomers was similar for each visit, with 13-cis-RA having the highest concentrations followed by 9-cis-RA and all-trans-RA. Median serum retinol levels were significantly lower at visit 2 compared with visit 1. However, when assessed over four available visits, no significant difference in retinol across visits was observed (P = 0.08; data not shown).

Spearman correlation coefficients for total RA, RA isomers, retinol, and β-carotene between visits 1 and 2 are shown in Table 2. Total endogenous RA level over a 4-month period was highly correlated (Spearman ρ = 0.67), as were the three isomers, with 9-cis-RA having the highest correlation (Spearman ρ = 0.79). The within-person variability of total RA and individual isomers was low, with the between-person variance to within-person variance ratios ranging from 1.05 for 3.09 (Table 2).

Table 2.

Spearman correlation coefficients, between-person and within-person variances, and between-person to within-person ratios of serum retinoids

Spearman correlation*nBetween-person varianceWithin-person varianceBetween-person/within-person ratio
Total RA (ng/mL) 0.67 502 0.122 0.068 1.796 
    Cis-isomer (ng/mL)      
        13-Cis-RA 0.57 480 0.139 0.132 1.053 
        9-Cis-RA 0.79 424 0.165 0.053 3.092 
    All-trans-isomer 0.56 485 0.100 0.086 1.161 
Spearman correlation*nBetween-person varianceWithin-person varianceBetween-person/within-person ratio
Total RA (ng/mL) 0.67 502 0.122 0.068 1.796 
    Cis-isomer (ng/mL)      
        13-Cis-RA 0.57 480 0.139 0.132 1.053 
        9-Cis-RA 0.79 424 0.165 0.053 3.092 
    All-trans-isomer 0.56 485 0.100 0.086 1.161 
*

All P < 0.001.

Random effects models were restricted to data above limit of quantitation; n varies by nutrient. Spearman correlation coefficient includes 502 women.

Log-transformed nutrient values used in random effects analysis.

We also examined RA isomer concentrations by lifestyle and demographic factors using the mean concentration of visits 1 and 2 for each woman (Table 3). Total RA and its isomers increased with age (Ptrend < 0.001, all-trans-RA Ptrend < 0.05), increasing number of pregnancies (Ptrend < 0.001, all-trans-RA Ptrend < 0.05), and increasing level of serum retinol (Ptrend < 0.001). Median 13-cis-RA and 9-cis-RA levels increased with increasing income (Ptrend < 0.001), whereas all-trans-RA decreased with increasing income (Ptrend = 0.02). For all factors examined, results were similar when RA concentrations were evaluated for visits 1 and 2 separately rather than as the mean (data not shown). Median total RA and two isomers (13-cis-RA and 9-cis-RA) differed by cigarette smoking status (never, current, or former). Median all-trans-RA was higher among White women compared with non-White women.

Table 3.

Serum total RA and RA isomer concentrations in women stratified by lifestyle and demographic characteristics (mean RA concentration at visits 1 and 2 per individual)

Median concentration (ng/mL)
nTotal RA13-Cis-RA9-Cis-RAAll-trans-RA
Age (y)      
    <20 21 2.75 1.22 1.04 0.61 
    20-29 198 2.84 1.11 0.91 0.74 
    30-39 176 3.46 1.45 1.22 0.78 
    ≥40 106 3.39 1.32 1.21 0.79 
    Ptrend <0.001 <0.001 <0.001 0.04 
Race      
    White 328 3.19 1.30 1.12 0.79 
    Non-White 173 3.07 1.28 1.07 0.71 
Cigarette smoking      
    Never 277 3.09 1.22 1.09 0.74 
    Current 147 3.20 1.33 1.13 0.79 
    Former 77 3.24 1.33 1.11 0.76 
Alcohol (glass/wk)      
    Never 174 3.20 1.37 1.10 0.74 
    ≤1 262 3.10 1.25 1.07 0.79 
    >1 66 3.25 1.33 1.22 0.74 
Years consuming alcohol      
    Never 174 3.20 1.37 1.10 0.74 
    ≤5 113 3.18 1.35 1.10 0.70 
    6-10 84 2.88 1.06 1.00 0.85 
    11-15 38 3.25 1.25 1.14 0.90 
    >15 73 3.36 1.41 1.20 0.78 
    Ptrend  0.78 0.81 0.80 0.06 
OC use (y)      
    Never 78 3.16 1.41 1.07 0.73 
    <6 276 3.06 1.20 1.06 0.74 
    ≥6 147 3.40 1.39 1.20 0.80 
    Ptrend  0.10 0.53 0.18 0.07 
Total no. pregnancies      
    0-1 87 2.87 1.11 1.01 0.72 
    2-3 214 3.02 1.20 1.06 0.73 
    ≥4 199 3.47 1.41 1.18 0.80 
    Ptrend  <0.001 <0.001 <0.001 0.05 
Education      
    Illiterate 35 3.19 1.33 1.23 0.74 
    <Elementary 77 3.24 1.30 1.08 0.76 
    Elementary 283 3.10 1.29 1.10 0.75 
    >High school 43 3.11 1.35 1.07 0.70 
    ≥High school 63 3.26 1.38 1.13 0.84 
    Ptrend  0.76 0.94 0.28 0.61 
Income (US$)      
    <250 126 2.81 1.05 1.00 0.82 
    250-450 123 3.13 1.20 1.07 0.75 
    451-725 118 3.19 1.33 1.15 0.79 
    >725 118 3.30 1.41 1.17 0.69 
    Ptrend  <0.001 <0.001 <0.001 0.02 
Total no. household members      
    1-3 108 3.15 1.25 1.10 0.87 
    4 148 3.10 1.30 1.07 0.73 
    5 119 3.28 1.30 1.13 0.73 
    ≥6 126 3.11 1.32 1.10 0.73 
    Ptrend  0.99 0.34 0.96 0.04 
Season§      
    Fall 198 3.20 1.38 1.10 0.82 
    Winter 95 3.19 1.21 1.20 0.72 
    Spring 99 3.10 1.31 1.05 0.62 
    Summer 110 2.55 0.85 0.81 0.83 
Total serum cholesterol (mg/dL)      
    44-134 126 2.83 1.19 0.99 0.73 
    135-160 118 3.28 1.38 1.11 0.73 
    161-188 127 3.13 1.25 1.13 0.73 
    189-386 129 3.37 1.34 1.20 0.84 
    Ptrend  <0.001 0.01 <0.001 0.08 
Tertiles of serum retinol (μg/mL)      
    Low (0.165-0.392) 165 2.88 1.19 1.00 0.71 
    Medium (0.393-0.478) 177 3.19 1.33 1.12 0.73 
    High (0.479-1.550) 160 3.46 1.40 1.22 0.88 
    Ptrend  <0.001 <0.001 <0.001 <0.001 
Tertiles of serum β-carotene (μg/mL)      
    Low (0.004-0.017) 165 2.98 1.27 1.05 0.67 
    Medium (0.018-0.031) 159 3.22 1.32 1.15 0.82 
    High (0.032-0.287) 178 3.33 1.30 1.17 0.83 
    Ptrend  0.26 0.69 0.21 <0.001 
Median concentration (ng/mL)
nTotal RA13-Cis-RA9-Cis-RAAll-trans-RA
Age (y)      
    <20 21 2.75 1.22 1.04 0.61 
    20-29 198 2.84 1.11 0.91 0.74 
    30-39 176 3.46 1.45 1.22 0.78 
    ≥40 106 3.39 1.32 1.21 0.79 
    Ptrend <0.001 <0.001 <0.001 0.04 
Race      
    White 328 3.19 1.30 1.12 0.79 
    Non-White 173 3.07 1.28 1.07 0.71 
Cigarette smoking      
    Never 277 3.09 1.22 1.09 0.74 
    Current 147 3.20 1.33 1.13 0.79 
    Former 77 3.24 1.33 1.11 0.76 
Alcohol (glass/wk)      
    Never 174 3.20 1.37 1.10 0.74 
    ≤1 262 3.10 1.25 1.07 0.79 
    >1 66 3.25 1.33 1.22 0.74 
Years consuming alcohol      
    Never 174 3.20 1.37 1.10 0.74 
    ≤5 113 3.18 1.35 1.10 0.70 
    6-10 84 2.88 1.06 1.00 0.85 
    11-15 38 3.25 1.25 1.14 0.90 
    >15 73 3.36 1.41 1.20 0.78 
    Ptrend  0.78 0.81 0.80 0.06 
OC use (y)      
    Never 78 3.16 1.41 1.07 0.73 
    <6 276 3.06 1.20 1.06 0.74 
    ≥6 147 3.40 1.39 1.20 0.80 
    Ptrend  0.10 0.53 0.18 0.07 
Total no. pregnancies      
    0-1 87 2.87 1.11 1.01 0.72 
    2-3 214 3.02 1.20 1.06 0.73 
    ≥4 199 3.47 1.41 1.18 0.80 
    Ptrend  <0.001 <0.001 <0.001 0.05 
Education      
    Illiterate 35 3.19 1.33 1.23 0.74 
    <Elementary 77 3.24 1.30 1.08 0.76 
    Elementary 283 3.10 1.29 1.10 0.75 
    >High school 43 3.11 1.35 1.07 0.70 
    ≥High school 63 3.26 1.38 1.13 0.84 
    Ptrend  0.76 0.94 0.28 0.61 
Income (US$)      
    <250 126 2.81 1.05 1.00 0.82 
    250-450 123 3.13 1.20 1.07 0.75 
    451-725 118 3.19 1.33 1.15 0.79 
    >725 118 3.30 1.41 1.17 0.69 
    Ptrend  <0.001 <0.001 <0.001 0.02 
Total no. household members      
    1-3 108 3.15 1.25 1.10 0.87 
    4 148 3.10 1.30 1.07 0.73 
    5 119 3.28 1.30 1.13 0.73 
    ≥6 126 3.11 1.32 1.10 0.73 
    Ptrend  0.99 0.34 0.96 0.04 
Season§      
    Fall 198 3.20 1.38 1.10 0.82 
    Winter 95 3.19 1.21 1.20 0.72 
    Spring 99 3.10 1.31 1.05 0.62 
    Summer 110 2.55 0.85 0.81 0.83 
Total serum cholesterol (mg/dL)      
    44-134 126 2.83 1.19 0.99 0.73 
    135-160 118 3.28 1.38 1.11 0.73 
    161-188 127 3.13 1.25 1.13 0.73 
    189-386 129 3.37 1.34 1.20 0.84 
    Ptrend  <0.001 0.01 <0.001 0.08 
Tertiles of serum retinol (μg/mL)      
    Low (0.165-0.392) 165 2.88 1.19 1.00 0.71 
    Medium (0.393-0.478) 177 3.19 1.33 1.12 0.73 
    High (0.479-1.550) 160 3.46 1.40 1.22 0.88 
    Ptrend  <0.001 <0.001 <0.001 <0.001 
Tertiles of serum β-carotene (μg/mL)      
    Low (0.004-0.017) 165 2.98 1.27 1.05 0.67 
    Medium (0.018-0.031) 159 3.22 1.32 1.15 0.82 
    High (0.032-0.287) 178 3.33 1.30 1.17 0.83 
    Ptrend  0.26 0.69 0.21 <0.001 
*

Nonparametric test for linear trend across ordered groups.

P < 0.05, differences in RA concentration using Wilcoxon rank sum test (2 categories) or the Kruskal-Wallis test (≥3 categories).

P < 0.01, differences in RA concentration using Wilcoxon rank sum test (2 categories) or the Kruskal-Wallis test (≥3 categories).

§

For season of blood sampling, only the visit 1 concentrations were shown.

P < 0.001, differences in RA concentration using Wilcoxon rank sum test (2 categories) or the Kruskal-Wallis test (≥3 categories).

Tertiles distribution of mean of four measurements per women within 12 months.

Table 4 presents results of multivariate modeling of lifestyle and demographic factors independently associated with RA levels. Age, measured in 5-year intervals, was positively associated with total RA and 9-cis-RA levels (adjusted OR, 1.34; 95% CI, 1.11-1.62 and adjusted OR, 1.62; 95% CI, 1.34-1.95, respectively). Season of blood draw was significantly associated with 13-cis-RA and all-trans-RA (spring versus fall, adjusted OR, 0.36; 95% CI, 0.15-0.85 and adjusted OR, 0.29; 95% CI, 0.12-0.72, respectively).

Table 4.

Associations of total RA and RA isomers with lifestyle and demographic factors among Brazilian women

Total RA (n = 451)*
13-Cis-RA (n = 451)*
9-Cis-RA (n = 393)*
All-trans-RA (n = 501)*
Low-medium RA (n = 281)High RA (n = 170)Crude ORAdjusted OR (95% CI)Low-medium RA (n = 282)High RA (n = 169)Crude ORAdjusted OR (95% CI)Low-medium RA (n = 233)High RA (n = 160)Crude ORAdjusted OR (95% CI)Low-medium RA (n = 334)High RA (n = 168)Crude ORAdjusted OR (95% CI)
Age, 5 y (mean ± SD) 29 ± 8.3 35 ± 8.5 1.42 1.34 (1.11-1.62) 30 ± 8.6 33 ± 8.5 1.07 1.05 (0.89-1.23) 29 ± 8.5 34 ± 8.3 1.57 1.62 (1.34-1.95) 31 ± 8.6 32 ± 8.6 1.00 0.95 (0.81-1.12) 
Race                 
    White 180 111 1.00  177 114 1.00  140 115 1.00 1.00 (Reference) 211 117 1.00  
    Non-White 101 59 0.98  105 55 0.81  93 45 0.58 0.63 (0.39-1.02) 123 50 0.65  
Season (visit 1)                 
    Fall 105 77 1.00  97 80 1.00 1.00 (Reference) 89 65 1.00  112 86 1.00 1.00 (Reference) 
    Winter 61 34 1.03  61 34 0.67 0.68 (0.32-1.44) 43 39 1.18  74 21 0.43 0.44 (0.21-0.91) 
    Spring 60 32 0.58  65 27 0.34 0.36 (0.15-0.85) 60 32 0.64  82 17 0.35 0.29 (0.12-0.72) 
    Summer 55 18 0.65  60 23 0.42 0.45 (0.22-0.92) 42 24 0.74  66 44 0.66 0.86 (0.47-1.58) 
OC use (y)                 
    Never 41 31 1.00 1.00 (Reference) 43 29 1.00  38 27 1.00  55 23 1.00  
    <6 172 74 0.50 0.47 (0.24-0.91) 162 84 0.64  135 76 0.72  187 89 1.17  
    >6 68 65 1.17 0.89 (0.43-1.83) 77 56 0.93  60 57 1.31  92 55 1.43  
Total no. pregnancies                 
    0-1 61 16 1.00 1.00 (Reference) 55 22 1.00  47 22 1.00  64 23 1.00 1.00 (Reference) 
    2-3 125 66 2.26 1.90 (0.91-3.97) 127 64 1.31  100 61 1.28  147 67 1.16 1.19 (0.61-2.33) 
    >4 95 88 3.48 2.42 (1.13-5.18) 100 83 1.75  86 77 1.84  123 76 1.67 1.89 (0.93-3.85) 
Total RA (n = 451)*
13-Cis-RA (n = 451)*
9-Cis-RA (n = 393)*
All-trans-RA (n = 501)*
Low-medium RA (n = 281)High RA (n = 170)Crude ORAdjusted OR (95% CI)Low-medium RA (n = 282)High RA (n = 169)Crude ORAdjusted OR (95% CI)Low-medium RA (n = 233)High RA (n = 160)Crude ORAdjusted OR (95% CI)Low-medium RA (n = 334)High RA (n = 168)Crude ORAdjusted OR (95% CI)
Age, 5 y (mean ± SD) 29 ± 8.3 35 ± 8.5 1.42 1.34 (1.11-1.62) 30 ± 8.6 33 ± 8.5 1.07 1.05 (0.89-1.23) 29 ± 8.5 34 ± 8.3 1.57 1.62 (1.34-1.95) 31 ± 8.6 32 ± 8.6 1.00 0.95 (0.81-1.12) 
Race                 
    White 180 111 1.00  177 114 1.00  140 115 1.00 1.00 (Reference) 211 117 1.00  
    Non-White 101 59 0.98  105 55 0.81  93 45 0.58 0.63 (0.39-1.02) 123 50 0.65  
Season (visit 1)                 
    Fall 105 77 1.00  97 80 1.00 1.00 (Reference) 89 65 1.00  112 86 1.00 1.00 (Reference) 
    Winter 61 34 1.03  61 34 0.67 0.68 (0.32-1.44) 43 39 1.18  74 21 0.43 0.44 (0.21-0.91) 
    Spring 60 32 0.58  65 27 0.34 0.36 (0.15-0.85) 60 32 0.64  82 17 0.35 0.29 (0.12-0.72) 
    Summer 55 18 0.65  60 23 0.42 0.45 (0.22-0.92) 42 24 0.74  66 44 0.66 0.86 (0.47-1.58) 
OC use (y)                 
    Never 41 31 1.00 1.00 (Reference) 43 29 1.00  38 27 1.00  55 23 1.00  
    <6 172 74 0.50 0.47 (0.24-0.91) 162 84 0.64  135 76 0.72  187 89 1.17  
    >6 68 65 1.17 0.89 (0.43-1.83) 77 56 0.93  60 57 1.31  92 55 1.43  
Total no. pregnancies                 
    0-1 61 16 1.00 1.00 (Reference) 55 22 1.00  47 22 1.00  64 23 1.00 1.00 (Reference) 
    2-3 125 66 2.26 1.90 (0.91-3.97) 127 64 1.31  100 61 1.28  147 67 1.16 1.19 (0.61-2.33) 
    >4 95 88 3.48 2.42 (1.13-5.18) 100 83 1.75  86 77 1.84  123 76 1.67 1.89 (0.93-3.85) 
*

Cut point between low-medium and high RA levels: total RA, 3.65 ng/mL; 13-cis-RA, 1.53 ng/mL ; 9-cis-RA, 1.30 ng/mL; and all-trans-RA, 0.92 ng/mL.

Crude models are adjusted for laboratory analysis batch.

Adjusted simultaneously for all variables for each specific RA isomer, laboratory analysis batch, and economy.

Table 5 presents independent associations between nutritional factors and serum RA. There were strong, positive associations among all retinoids and serum retinol, β-carotene, and β-cryptoxanthin. Consistent with the proposed RA metabolism, carotenoids lacking the appropriate ring structure, such as lycopene, were not associated with serum RA isomer levels. In addition, RA isomer levels were not associated with serum lutein. These results are key in supporting the specificity of the associations found with serum RA isomers and select pro–vitamin A carotenoids. The associations between intake of specific nutrients and circulating concentrations of RA isomers are also reported in Table 5. Increased intake of vitamin A was significantly positively associated with 13-cis-RA (adjusted OR, 2.65; 95% CI, 1.48-4.73) and 9-cis-RA (adjusted OR, 1.85; 95% CI, 1.04-3.27) and marginally associated with total RA (adjusted OR, 1.74; 95% CI, 0.98-3.08). Increased intake of β-carotene was positively associated with 13-cis-RA (adjusted OR, 1.78; 95% CI, 1.01-3.12). Increased consumption of liver, pumpkin, and oranges was significantly positively associated with RA levels (total RA, 13-cis-RA, or 9-cis-RA) and may be the contributing sources for the positive associations shown with vitamin A and β-carotene intake and serum RA levels (data not shown).

Table 5.

Association of total RA and RA isomers and nutritional factors

Total RA (ng/mL; n = 451)
13-Cis-RA (ng/mL; n = 451)
9-Cis-RA (ng/mL; n = 393)
All-trans-RA (ng/mL; n = 501)
Low-medium RAHigh RACrude OR*Adjusted OR (95% CI)Low-medium RAHigh RACrude OR*Adjusted OR (95% CI)Low-medium RAHigh RACrude OR*Adjusted OR (95% CI)Low-medium RAHigh RACrude OR*Adjusted OR (95% CI)
A. Circulating nutrients                 
Serum retinol (μg/mL)                 
    Low (0.165-0.392) 103 37 1.00 1.00 95 45 1.00 1.00 83 31 1.00 1.00 119 45 1.00 1.00 
    Medium (0.393-0.478) 98 66 2.30 2.18 (1.20-3.95) 104 60 1.27 1.34 (0.76-2.36) 80 63 2.73 2.55 (1.43-4.54) 122 55 1.54 1.65 (0.93-2.95) 
    High (0.479-1.550) 78 68 3.38 3.32 (1.74-6.32) 83 63 2.04 2.30 (1.26-4.19) 69 66 4.21 3.84 (2.08-7.09) 92 67 3.34 4.04 (2.16-7.54) 
    Ptrend    0.001    0.006    0.001    0.001 
Serum β-carotene (μg/mL)                 
    Low (0.165-0.392) 93 51 1.00 1.00 93 51 1.00 1.00 101 40 1.00 1.00 110 40 1.00 1.00 
    Medium (0.393-0.478) 97 46 1.07 0.99 (0.53-1.84) 95 48 0.89 0.84 (0.45-1.56) 74 46 1.50 1.31 (0.72-2.38) 97 57 1.83 1.82 (0.98-3.39) 
    High (0.479-1.550) 62 68 4.23 4.58 (2.12-9.89) 69 61 3.04 3.17 (1.48-6.77) 36 67 4.98 4.86 (2.22-10.63) 100 60 2.08 3.04 (1.42-6.55) 
    Ptrend    0.001    0.008    0.001    0.004 
Serum β-cryptoxanthin (μg/mL)                 
    Low (0.002-0.012) 116 44 1.00 1.00 107 53 1.00 1.00 111 40 1.00 1.00 124 44 1.00 1.00 
    Medium (0.013-0.029) 90 61 2.14 1.97 (1.09-3.56) 95 56 1.21 1.20 (0.68-2.14) 81 51 1.56 1.22 (0.69-2.16) 107 59 1.63 1.82 (1.03-3.23) 
    High (0.03-1.47) 73 66 4.19 3.76 (1.89-7.48) 80 59 2.04 2.24 (1.14-4.42) 40 69 4.32 3.21 (1.65-6.26) 102 64 1.82 2.39 (1.23-4.64) 
    Ptrend    0.001    0.022    0.001    0.009 
Serum lutein (μg/mL)                 
    Low (0.009-0.027) 109 46 1.00 1.00 102 53 1.00 1.00 92 45 1.00 1.00 119 49 1.00 1.00 
    Medium (0.028-0.040) 90 63 1.45 1.38 (0.78-2.45) 89 63 1.38 1.21 (0.69-2.11) 78 56 1.27 1.07 (0.61-1.89) 109 58 1.10 1.18 (0.68-2.07) 
    High (0.041-0.219) 80 63 2.22 2.12 (1.17-3.83) 91 52 1.41 1.35 (0.76-2.41) 62 59 1.85 1.55 (0.86-2.79) 105 60 1.23 1.57 (0.89-2.76) 
    Ptrend    0.013    0.360    0.147    0.120 
Serum lycopene (μg/mL)                 
    Low (0.002-0.0093) 109 52 1.00 1.00 108 53 1.00 1.00 104 45 1.00 1.00 120 52 1.00 1.00 
    Medium (0.0094-0.018) 92 60 1.29 1.15 (0.65-2.04) 93 59 1.05 1.06 (0.60-1.87) 82 54 1.44 1.37 (0.78-2.42) 102 60 1.35 1.31 (0.75-2.27) 
    High (0.0181-0.1203) 78 59 1.72 1.56 (0.77-3.16) 81 56 1.53 1.55 (0.77-3.11) 46 61 2.00 1.70 (0.83-3.49) 111 55 0.93 1.15 (0.59-2.25) 
    Ptrend    0.230    0.253    0.129    0.580 
B. Energy-adjusted nutrient intake value                 
Vitamin A (retinol)                 
    Low 109 41 1.00 1.00 110 40 1.00 1.00 97 40 1.00 1.00 122 46 1.00 1.00 
    Medium 86 65 1.99 1.90 (1.07-3.38) 89 62 2.45 2.33 (1.31-4.17) 71 58 1.78 1.70 (0.96-3.02) 105 62 1.18 1.17 (0.68-2.02) 
    High 86 65 1.90 1.74 (0.98-3.08) 84 67 2.75 2.65 (1.48-4.73) 66 62 2.00 1.85 (1.04-3.27) 107 60 1.07 1.04 (0.60-1.81) 
    Ptrend    0.063    0.001    0.038    0.917 
α-Carotene (μg/mg)                 
    Low 91 57 1.00 1.00 96 52 1.00 1.00 80 52 1.00 1.00 111 57 1.00 1.00 
    Medium 95 58 0.95 0.89 (0.51-1.57) 100 53 1.02 0.97 (0.56-1.69) 75 56 1.13 0.94 (0.54-1.66) 106 61 1.23 1.19 (0.70-2.03) 
    High 95 56 0.80 0.70 (0.40-1.24) 87 64 1.25 1.25 (0.72-2.17) 79 52 0.89 0.78 (0.44-1.38) 117 50 1.10 0.72 (0.42-1.25) 
    Ptrend    0.227    0.419    0.391    0.245 
β-Carotene (μg/mg)                 
    Low 95 54 1.00 1.00 101 48 1.00 1.00 77 58 1.00 1.00 119 49 1.00 1.00 
    Medium 91 59 1.26 1.21 (0.68-2.13) 93 57 1.56 1.57 (0.88-2.78) 77 51 0.86 0.73 (0.41-1.29) 107 60 1.12 1.23 (0.71-2.13) 
    High 95 58 1.11 1.07 (0.61-1.90) 89 64 1.90 1.78 (1.01-3.12) 80 51 0.84 0.71 (0.41-1.26) 108 59 0.72 1.08 (0.63-1.85) 
    Ptrend    0.826    0.049    0.252    0.820 
β-Cryptoxanthin (μg/mg)                 
    Low 98 51 1.00 1.00 94 55 1.00 1.00 76 53 1.00 1.00 118 50 1.00 1.00 
    Medium 94 58 1.11 1.02 (0.57-1.81) 100 51 0.97 0.97 (0.55-1.70) 76 58 1.13 0.96 (0.55-1.69) 112 55 1.10 1.08 (0.63-1.87) 
    High 89 63 1.49 1.39 (0.79-2.48) 89 63 1.41 1.39 (0.80-2.41) 82 50 0.91 0.73 (0.41-1.31) 104 63 1.56 1.60 (0.93-2.77) 
    Ptrend    0.249    0.232    0.291    0.088 
Lutein (μg/mg)                 
    Low 97 52 1.00 1.00 94 55 1.00 1.00 75 54 1.00 1.00 119 49 1.00 1.00 
    Medium 97 55 1.06 1.00 (0.56-1.78) 104 48 0.92 0.93 (0.53-1.63) 78 54 1.04 0.89 (0.51-1.57) 109 58 1.22 1.17 (0.68-2.01) 
    High 87 64 1.51 1.44 (0.81-2.54) 85 66 1.56 1.57 (0.90-2.72) 81 52 0.95 0.80 (0.45-1.41) 106 61 1.57 1.63 (0.94-2.83) 
    Ptrend    0.206    0.101    0.434    0.080 
Total RA (ng/mL; n = 451)
13-Cis-RA (ng/mL; n = 451)
9-Cis-RA (ng/mL; n = 393)
All-trans-RA (ng/mL; n = 501)
Low-medium RAHigh RACrude OR*Adjusted OR (95% CI)Low-medium RAHigh RACrude OR*Adjusted OR (95% CI)Low-medium RAHigh RACrude OR*Adjusted OR (95% CI)Low-medium RAHigh RACrude OR*Adjusted OR (95% CI)
A. Circulating nutrients                 
Serum retinol (μg/mL)                 
    Low (0.165-0.392) 103 37 1.00 1.00 95 45 1.00 1.00 83 31 1.00 1.00 119 45 1.00 1.00 
    Medium (0.393-0.478) 98 66 2.30 2.18 (1.20-3.95) 104 60 1.27 1.34 (0.76-2.36) 80 63 2.73 2.55 (1.43-4.54) 122 55 1.54 1.65 (0.93-2.95) 
    High (0.479-1.550) 78 68 3.38 3.32 (1.74-6.32) 83 63 2.04 2.30 (1.26-4.19) 69 66 4.21 3.84 (2.08-7.09) 92 67 3.34 4.04 (2.16-7.54) 
    Ptrend    0.001    0.006    0.001    0.001 
Serum β-carotene (μg/mL)                 
    Low (0.165-0.392) 93 51 1.00 1.00 93 51 1.00 1.00 101 40 1.00 1.00 110 40 1.00 1.00 
    Medium (0.393-0.478) 97 46 1.07 0.99 (0.53-1.84) 95 48 0.89 0.84 (0.45-1.56) 74 46 1.50 1.31 (0.72-2.38) 97 57 1.83 1.82 (0.98-3.39) 
    High (0.479-1.550) 62 68 4.23 4.58 (2.12-9.89) 69 61 3.04 3.17 (1.48-6.77) 36 67 4.98 4.86 (2.22-10.63) 100 60 2.08 3.04 (1.42-6.55) 
    Ptrend    0.001    0.008    0.001    0.004 
Serum β-cryptoxanthin (μg/mL)                 
    Low (0.002-0.012) 116 44 1.00 1.00 107 53 1.00 1.00 111 40 1.00 1.00 124 44 1.00 1.00 
    Medium (0.013-0.029) 90 61 2.14 1.97 (1.09-3.56) 95 56 1.21 1.20 (0.68-2.14) 81 51 1.56 1.22 (0.69-2.16) 107 59 1.63 1.82 (1.03-3.23) 
    High (0.03-1.47) 73 66 4.19 3.76 (1.89-7.48) 80 59 2.04 2.24 (1.14-4.42) 40 69 4.32 3.21 (1.65-6.26) 102 64 1.82 2.39 (1.23-4.64) 
    Ptrend    0.001    0.022    0.001    0.009 
Serum lutein (μg/mL)                 
    Low (0.009-0.027) 109 46 1.00 1.00 102 53 1.00 1.00 92 45 1.00 1.00 119 49 1.00 1.00 
    Medium (0.028-0.040) 90 63 1.45 1.38 (0.78-2.45) 89 63 1.38 1.21 (0.69-2.11) 78 56 1.27 1.07 (0.61-1.89) 109 58 1.10 1.18 (0.68-2.07) 
    High (0.041-0.219) 80 63 2.22 2.12 (1.17-3.83) 91 52 1.41 1.35 (0.76-2.41) 62 59 1.85 1.55 (0.86-2.79) 105 60 1.23 1.57 (0.89-2.76) 
    Ptrend    0.013    0.360    0.147    0.120 
Serum lycopene (μg/mL)                 
    Low (0.002-0.0093) 109 52 1.00 1.00 108 53 1.00 1.00 104 45 1.00 1.00 120 52 1.00 1.00 
    Medium (0.0094-0.018) 92 60 1.29 1.15 (0.65-2.04) 93 59 1.05 1.06 (0.60-1.87) 82 54 1.44 1.37 (0.78-2.42) 102 60 1.35 1.31 (0.75-2.27) 
    High (0.0181-0.1203) 78 59 1.72 1.56 (0.77-3.16) 81 56 1.53 1.55 (0.77-3.11) 46 61 2.00 1.70 (0.83-3.49) 111 55 0.93 1.15 (0.59-2.25) 
    Ptrend    0.230    0.253    0.129    0.580 
B. Energy-adjusted nutrient intake value                 
Vitamin A (retinol)                 
    Low 109 41 1.00 1.00 110 40 1.00 1.00 97 40 1.00 1.00 122 46 1.00 1.00 
    Medium 86 65 1.99 1.90 (1.07-3.38) 89 62 2.45 2.33 (1.31-4.17) 71 58 1.78 1.70 (0.96-3.02) 105 62 1.18 1.17 (0.68-2.02) 
    High 86 65 1.90 1.74 (0.98-3.08) 84 67 2.75 2.65 (1.48-4.73) 66 62 2.00 1.85 (1.04-3.27) 107 60 1.07 1.04 (0.60-1.81) 
    Ptrend    0.063    0.001    0.038    0.917 
α-Carotene (μg/mg)                 
    Low 91 57 1.00 1.00 96 52 1.00 1.00 80 52 1.00 1.00 111 57 1.00 1.00 
    Medium 95 58 0.95 0.89 (0.51-1.57) 100 53 1.02 0.97 (0.56-1.69) 75 56 1.13 0.94 (0.54-1.66) 106 61 1.23 1.19 (0.70-2.03) 
    High 95 56 0.80 0.70 (0.40-1.24) 87 64 1.25 1.25 (0.72-2.17) 79 52 0.89 0.78 (0.44-1.38) 117 50 1.10 0.72 (0.42-1.25) 
    Ptrend    0.227    0.419    0.391    0.245 
β-Carotene (μg/mg)                 
    Low 95 54 1.00 1.00 101 48 1.00 1.00 77 58 1.00 1.00 119 49 1.00 1.00 
    Medium 91 59 1.26 1.21 (0.68-2.13) 93 57 1.56 1.57 (0.88-2.78) 77 51 0.86 0.73 (0.41-1.29) 107 60 1.12 1.23 (0.71-2.13) 
    High 95 58 1.11 1.07 (0.61-1.90) 89 64 1.90 1.78 (1.01-3.12) 80 51 0.84 0.71 (0.41-1.26) 108 59 0.72 1.08 (0.63-1.85) 
    Ptrend    0.826    0.049    0.252    0.820 
β-Cryptoxanthin (μg/mg)                 
    Low 98 51 1.00 1.00 94 55 1.00 1.00 76 53 1.00 1.00 118 50 1.00 1.00 
    Medium 94 58 1.11 1.02 (0.57-1.81) 100 51 0.97 0.97 (0.55-1.70) 76 58 1.13 0.96 (0.55-1.69) 112 55 1.10 1.08 (0.63-1.87) 
    High 89 63 1.49 1.39 (0.79-2.48) 89 63 1.41 1.39 (0.80-2.41) 82 50 0.91 0.73 (0.41-1.31) 104 63 1.56 1.60 (0.93-2.77) 
    Ptrend    0.249    0.232    0.291    0.088 
Lutein (μg/mg)                 
    Low 97 52 1.00 1.00 94 55 1.00 1.00 75 54 1.00 1.00 119 49 1.00 1.00 
    Medium 97 55 1.06 1.00 (0.56-1.78) 104 48 0.92 0.93 (0.53-1.63) 78 54 1.04 0.89 (0.51-1.57) 109 58 1.22 1.17 (0.68-2.01) 
    High 87 64 1.51 1.44 (0.81-2.54) 85 66 1.56 1.57 (0.90-2.72) 81 52 0.95 0.80 (0.45-1.41) 106 61 1.57 1.63 (0.94-2.83) 
    Ptrend    0.206    0.101    0.434    0.080 
*

Crude model adjusted for analysis batch.

Logistic regression model adjusted simultaneously for associated demographic and lifestyle variables (Table 4), laboratory analysis batch, economy, and cholesterol (circulating nutrients only).

We characterized total serum RA and three individual RA isomers (13-cis-RA, 9-cis-RA, and all-trans-RA) in a large sample of women and determined factors associated with these levels. The relative abundance of the three RA isomers was similar for each visit, with 13-cis-RA having the highest concentrations followed by 9-cis-RA and all-trans-RA. Overall, we observed a wide range of values for this population (total RA 0.71-7.79 ng/mL), which may reflect the heterogeneity of this sample of low-income Brazilian women. Whereas the between-person variability was high, we observed low within-person variability of two measures of serum RA obtained ∼4 months apart.

Sociodemographic factors were related to RA level. Age, race, OC use, total number of pregnancies, and season of initial blood draw were significantly associated with endogenous RA concentrations; however, factors significantly contributing to RA levels differed for each isomer. All endogenous RA isomers assessed in this study were positively associated with serum retinol, β-carotene, and β-cryptoxanthin levels. Associations were confirmed by observing significant associations with preformed vitamin A intake and increased consumption of pro–vitamin A–containing foods. Consistent with the proposed RA metabolism, carotenoids lacking the appropriate ring structure, such as lycopene, were not associated with serum RA isomer levels. These associations differed slightly for each RA isomer, suggesting the possibility of independent mechanisms for modulating specific isomer level. Additional laboratory research and population studies are required to define the mechanisms leading to RA isomerization and factors that modify this process. Now, it seems that the measurement of multiple isomers of RA within epidemiologic studies provides added information compared with only assessing total endogenous RA level.

The observed concentrations of 13-cis-RA in these women are similar to reports published previously (16-19). Soderlund et al. (16) reported an average 13-cis-RA concentration of 1.35 ng/mL (range 1.26-1.5) in a small sample of northern European women (mean age, 36 years). Others reported higher values (20-22) of 13-cis-RA, which may reflect differences in study participants (e.g., diet, age, sex, or presence of benign disease) or laboratory methods used. Sedjo et al.(36) assessed baseline levels of RA concentrations in a chemoprevention trial and found a relative abundance of each isomer similar to what we observed in this study (13-cis-RA > 9-cis-RA > all-trans-RA).

We examined the variability of RA measures obtained ∼4 months apart. Levels of serum RA isomers were relatively stable within women, with ratios of between-person to within-person variability all >1.0. This stability is similar to the results published by Tang et al. (23), demonstrating no change in 13-cis-RA and all-trans-RA over a 3-month period in healthy controls (n = 13). Overall, Soderlund et al. (16) reported within-person coefficients of variability of 13.4% for 13-cis-RA and 13.6% for all-trans-RA, which were not influenced by period of menstrual cycle among 17 women. The ratios of between-person to within-person variability for 13-cis-RA and all-trans-RA (1.57 and 1.17, respectively) are very similar to those we are reporting in this study (16). Yamakoshi et al. (20) also found low between-day variances in serum RA isomers, all-trans-RA (coefficient of variation, 11%) and 13-cis-RA (coefficient of variation, 8.4%), in six healthy subjects. Altogether, these results indicate that a single RA measurement may be sufficient to accurately classify a woman's RA level.

Soderlund et al. (16) have reported individuals' seasonal variation for 13-cis-RA, with lower mean values during winter and spring (November-March) compared with summer months; however, these differences were small and were interpreted as being of little biological significance. In these Brazilian women, we found lower median values of 13-cis-RA in summer, and in the multivariate analyses, women were significantly more likely to have lower 13-cis-RA levels in spring and summer than in fall. In contrast to Soderlund et al. (16), we found significant seasonal differences in all-trans-RA, with women more likely to have lower levels in winter and spring than in fall. It may be that the seasonal differences we find may be due to differences in dietary intake; however, we did not formally test this question. Future research in this area needs to be conducted.

In this study, serum RA levels were positively associated with serum retinol and β-carotene levels. Our data are consistent with a previous study in patients with inflammation, which reported lower levels of serum retinol occurring together with low serum levels of RA (19). β-Carotene supplementation (30 mg/d) was shown to increase serum levels of all-trans-RA after 3 months in patients with colon polyps (increase from 2.32 ± 0.26 to 3.00 ± 0.41 ng/mL); however, no increase in 13-cis-RA, total RA, or retinol with supplementation was observed (23). Our results are further supported by a recent finding that supplementation with retinyl palmitate substantially increased endogenous RA levels, with all-trans-RA having the highest percentage increase over time followed by 13-cis-RA (36).

The current study was conducted within a sample of women living in São Paulo between 1993 and 1996. This population of women may have different dietary practices and sociodemographic profiles than typically found among women residing in western Europe and the United States. Results from the current study are therefore applicable to countries of similar sociodemographic characteristics. Caution should be exercised in generalizing the results to populations such as western European and American women.

To address whether similar associations might be observed among U.S. women, we compared the median retinol value of our Brazilian population with that reported by the Third National Health and Nutrition Examination Survey for women ages ≥19 years to determine how different our two populations are with respect to retinoid status. As reported by Ballew et al. (35) from the Third National Health and Nutrition Examination Survey, the median serum retinol levels for women ages 19 to 30 and 31 to 50 years were 0.53 and 0.43 μg/mL, respectively. This is similar to what we observed among our Brazilian study population where values of 0.43 and 0.48 μg/mL were seen, respectively. Although Brazilian women seem to have slightly lower median retinol values than U.S. women, these differences are not as dramatic as one might expect. We also conducted analyses restricting our population to women who have serum retinol values at or above the median reported in the National Health and Nutrition Examination Survey. Using this approach, we find consistent positive associations between serum RA isomers and serum β-carotene and β-cryptoxanthin concentrations among women with serum retinol >0.43 μg/mL. These results lead us to hypothesize that we would observe similar associations in a population of U.S. women. However, these preliminary associations need to be confirmed by conducting the appropriate study within the target U.S. population.

In this study, we are reporting serum levels of 9-cis-RA ranging from below detection (0.3 ng/mL) up to 3.8 ng/mL and contributing a relatively high proportion of total RA. The most likely explanations for the elevated 9-cis-RA levels include (a) incomplete resolution of 9-cis-RA from components in the matrix or other isomers (e.g., 9,13-dicis-RA), (b) isomerization to 9-cis-RA during long-term storage at −20°C, and/or (c) unidentified dietary or environmental factors leading to elevated levels. Currently, we do not have a standard for 9,13-dicis-RA to compare the retention time to determine if there was coelution to address the first possible explanation. We did not see significant isomerization when spiked samples were carried through our extraction and do not believe that artifacts were created during our extraction process. However, because the serum samples used in this study were not stored under ideal conditions at −80°C, the second explanation is a possibility.

Lanvers et al. (24) reported no degradation of all-trans-RA or 13-cis-RA in plasma during storage for 3 months at −20°C, whereas others have reported long-term storage may result in degradation of 13-cis-RA (18). To address this issue, we examined mean levels of RA among women enrolled 2 years apart and found that the mean RA levels were similar or elevated among samples obtained during the first year of enrollment compared with those obtained during the third year (data not shown). Therefore, our RA concentrations do not seem to be affected by serum storage conditions. In addition, we have comparable overall levels of total RA to other studies (16-19), and we have compared our study to one whose samples were stored ideally (36), and there were no significant differences (data not shown). Further research in this area needs to be conducted to clarify these results.

As with all observational studies, this study has limitations that need to be recognized. The serum samples obtained within this cohort study were not originally designated for measurement of RA; therefore, not all precautions were taken to ideally store these samples, including storage at −20°C and exposure to some UV light. Similar to other biological markers, the values of RA presented in this report may not reflect the absolute value of endogenous RA due to losses that may have occurred during storage or in the extraction process. However, the relative levels of each isomer should not have changed; therefore, the associations found in this study are assumed valid. The magnitude of the associations will potentially be lower than the true association due to any methodologic errors. Serum samples were not fasting samples; therefore, there is a potential for recent food consumption to have influenced serum RA values. However, due to the low within-person variability over a ∼4-month period and the small variance surrounding mean RA at each visit, we do not believe this to be an issue. As this study included Brazilian women only, our results cannot be generalized to men. We have no reason to believe that this relatively disease-free sample of women are different than other groups of women, leading us to infer that the results presented here may be of relevance to other female populations.

The Ludwig-McGill Cohort offered a unique opportunity to assess the association between endogenous RA levels and lifestyle, demographic, and nutritional factors in a sample of >500 women. There were multiple serum samples available for measurement of RA allowing for the first assessment of RA variability over time. In addition, we assessed serum retinol and carotenoids at four time points, which reduces the inherent variability of these measures, thereby reducing misclassification of serum nutrient level. Nutrient intake was estimated using Brazil-specific carotenoid food content to increase accuracy in estimating carotenoid intake (26).

RA has been given to patient populations to regress preneoplastic lesions; however, when RA is given p.o., there are significant toxicities associated. These toxicities have decreased its utilization in some populations, specifically among reproductive age women. By identifying factors that are associated with increased endogenous levels of RA, there is potential that modification of these factors will increase levels of RA, leading to prevention of preneoplastic lesions without the toxicity of supplemental treatment. This could be potentially beneficial to women of reproductive age, especially women at risk for cervical cancer, for which RA has been effective at regressing cervical dysplasia (12). Future studies need to investigate whether increased levels of endogenous RA are associated with a decreased risk of preneoplastic cervical lesions.

Grant support National Cancer Institute grants CA70269 and CA81310, Canadian Institutes of Health Research grants MA-13647 and MOP-49396, Ludwig Institute for Cancer Research intramural grant, Canadian Institutes of Health Research Distinguished Scientist Award (E.L. Franco), and National Cancer Institute Cancer Prevention and Control predoctoral fellowship grant R25CA078447 (E.M. Siegel).

The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

Note: Presented in part at the AACR Annual Conference, San Francisco, California, 2002 and AACR Frontiers in Cancer Prevention Conference, Phoenix, Arizona, 2003.

We thank Maria L. Baggio and Lenice Galan for management of the patients and specimen collections; Silvaneide Ferreira for data entry, sample retrieval and shipment, and laboratory analysis; and Drs. Robin Harris, Elena Martinez, and Jesse Martinez for thoughtful comments on this article.

1
Napoli JL. Interactions of retinoid binding proteins and enzymes in retinoid metabolism.
Biochim Biophys Acta
1999
;
1440
:
139
–62.
2
Ross AC. Vitamin A, retinoids. In: Shils ME, Olson JA, Shine M, Ross AC, editors. Modern nutrition in health and disease. Baltimore: Lippincott Williams & Wilkins; 1999.
3
Institute of Medicine. Dietary reference intakes: vitamin A, vitamin K, arsenic, boron, chromium, copper, iodine, iron, manganese, molybdenum, nickel, silicon, vanadium, and zinc. Washington (DC): National Academy Press; 2001.
4
Mangelsdorf DJ, Thummel C, Beato M, et al. The nuclear receptor superfamily: the second decade.
Cell
1995
;
83
:
835
–9.
5
Sun SY, Lotan R. Retinoids and their receptors in cancer development and chemoprevention.
Crit Rev Oncol Hematol
2002
;
41
:
41
–55.
6
Heyman RA, Mangelsdorf DJ, Dyck JA, et al. 9-Cis retinoic acid is a high affinity ligand for the retinoid X receptor.
Cell
1992
;
68
:
397
–406.
7
Chambon P. A decade of molecular biology of retinoic acid receptors.
FASEB J
1996
;
10
:
940
–54.
8
Blumberg B, Evans RM. Orphan nuclear receptors—new ligands and new possibilities.
Genes Dev
1998
;
12
:
3149
–55.
9
Lippman SM, Lotan, R. Advances in the development of retinoids as chemopreventive agents.
J Nutr
2000
;
130
:
479
–82S.
10
Niles RM. Recent advances in the use of vitamin A (retinoids) in the prevention and treatment of cancer.
Nutrition
2000
;
16
:
1084
–9.
11
Klaassen I, Braakhuis BJ. Anticancer activity and mechanism of action of retinoids in oral and pharyngeal cancer.
Oral Oncol
2002
;
38
:
532
–42.
12
Meyskens FL Jr, Surwit E, Moon TE, et al. Enhancement of regression of cervical intraepithelial neoplasia II (moderate dysplasia) with topically applied all-trans-retinoic acid: a randomized trial.
J Natl Cancer Inst
1994
;
86
:
539
–43.
13
Zusi FC, Lorenzi MV, Vivat-Hannah V. Selective retinoids and rexinoids in cancer therapy and chemoprevention.
Drug Discov Today
2002
;
7
:
1165
–74.
14
Miyagi M, Yokoyama H, Shiraishi H, Matsumoto M, Ishii H. Simultaneous quantification of retinol, retinal, and retinoic acid isomers by high-performance liquid chromatography with a simple gradiation.
J Chromatogr B Biomed Sci Appl
2001
;
757
:
365
–8.
15
Dimitrova B. Isocratic reversed-phase liquid chromatography of all-trans-retinoic acid and its major metabolites in new potential supplementary test systems for developmental toxicology.
J Chromatogr B Biomed Sci Appl
1996
;
681
:
153
–60.
16
Soderlund MB, Sjoberg A, Svard G, Fex G, Nilsson-Ehle P. Biological variation of retinoids in man.
Scand J Clin Lab Invest
2002
;
62
:
511
–9.
17
Berggren Soderlund M, Fex G, Nilsson-Ehle P. Decreasing serum concentrations of all-trans, 13-cis retinoic acids and retinol during fasting and caloric restriction.
J Intern Med
2003
;
253
:
375
–80.
18
Wyss R, Bucheli F. Determination of endogenous levels of 13-cis-retinoic acid (isotretinoin), all-trans-retinoic acid (tretinoin) and their 4-oxo metabolites in human and animal plasma by high-performance liquid chromatography with automated column switching and ultraviolet detection.
J Chromatogr B
1997
;
700
:
31
–47.
19
Fex GA, Larsson K, Nilsson-Ehle I. Serum concentration of all-trans and 13-cis retinoic acid and retinol are closely correlated.
J Nutr Biochem
1996
;
7
:
162
–5.
20
Yamakoshi Y, Fukasawa H, Yamauchi T, et al. Determination of endogenous levels of retinoic acid isomers in type II diabetes mellitus patients. Possible correlation with HbA1c values.
Biol Pharm Bull
2002
;
25
:
1268
–71.
21
Copper MP, Klaassen I, Teerlink T, Snow GB, Braakhuis BJ. Plasma retinoid levels in head and neck cancer patients: a comparison with healthy controls and the effect of retinyl palmitate treatment.
Oral Oncol
1999
;
35
:
40
–4.
22
Yeum KJ, Ahn SH, Rupp de Paiva SA, Lee-Kim YC, Krinsky NI, Russell RM. Correlation between carotenoid concentrations in serum and normal breast adipose tissue of women with benign breast tumor or breast cancer.
J Nutr
1998
;
128
:
1920
–6.
23
Tang G, Shiau A, Russell RM, Mobarhan S. Serum retinoic acid levels in patients with resected benign and malignant colonic neoplasias on β-carotene supplementation.
Nutr Cancer
1995
;
23
:
291
–8.
24
Lanvers C, Hempel G, Blaschke G, Boos J. Simultaneous determination of all-trans-, 13-cis- and 9-cis-retinoic acid, their 4-oxo metabolites and all-trans-retinol in human plasma by high-performance liquid chromatography.
J Chromatogr B Biomed Sci Appl
1996
;
685
:
233
–40.
25
Franco E, Villa L, Rohan T, Ferenczy A, Petzl-Erler M, Matlashewski G. Design and methods of the Ludwig-McGill longitudinal study of the natural history of human papillomavirus infection and cervical neoplasia in Brazil. Ludwig-McGill Study Group.
Rev Panam Salud Publica
1999
;
6
:
223
–33.
26
Giuliano AR, Siegel EM, Roe DJ, et al. Dietary intake and risk of persistent human papillomavirus (HPV) infection: the Ludwig-McGill HPV natural history study.
J Infect Dis
2003
;
188
:
1508
–16.
27
Rodriguez-Amaya DB. Latin American food sources of carotenoids.
Arch Latinoam Nutr
1999
;
49
:
74
–84S.
28
Thomson CA, Giuliano A, Rock CL, et al. Measuring dietary change in a diet intervention trial: comparing food frequency questionnaire and dietary recalls.
Am J Epidemiol
2003
;
157
:
754
–62.
29
Willett WC, Howe GR, and Kushi LH. Adjustment for total energy intake in epidemiologic studies.
Am J Clin Nutr
1997
;
65
:
1220
–8S; discussion 1229–31S.
30
Tangney CC, Shekelle RB, Raynor W, Gale M, Betz EP. Intra- and interindividual variation in measurements of β-carotene, retinol, and tocopherols in diet and plasma.
Am J Clin Nutr
1987
;
45
:
764
–9.
31
Nomura AM, Stemmermann GN, Lee J, Craft NE. Serum micronutrients and prostate cancer in Japanese Americans in Hawaii.
Cancer Epidemiol Biomarkers Prev
1997
;
6
:
487
–91.
32
Littell RM, Milliken GA, Stroup WW, Wolfinger RD. SAS systems for mixed models. Cary (NC): SAS Institute, Inc.; 1996.
33
Cuzick J. A Wilcoxon-type test for trend.
Stat Med
1985
;
4
:
87
–90.
34
SAS/STAT software: changes and enhancements through release 6.11. Cary (NC): SAS Institute, Inc.; 1996.
35
Ballew C, Bowman BA, Sowell AL, Gillespie C. Serum retinol distributions in residents of the United States: Third National Health and Nutrition Examination Survey, 1988-1994.
Am J Clin Nutr
2001
;
73
:
586
–93.
36
Sedjo RL, Ranger-Moore J, Foote J, et al. Circulating endogenous retinoic acid concentrations among participants enrolled in a randomized placebo-controlled clinical trial of retinyl palmitate. Cancer Epidemiol Biomarkers Prev 2004;13, this issue.