Abstract
Objective
Food intake, aging, and immune function share complex influences. Therefore, the purpose of this study was to examine relationships between nutrient intakes from food and dietary supplements and a biomarker of immune function.
Design
Data were collected from participants in a cross-sectional study as well as baseline data from a longitudinal study [n=89]. Subjects completed 24-hour food recalls including supplement intake [n=89]. Polyclonal mitogen phytohemmagluttin (PHA) was the immune function stimulator used. Height and weight were used to calculate body mass index.
Statistical analysis performed
Descriptive, bivariate correlation, Spearman's Rho for nonparametric data, t-tests, and stepwise regression with nutrient intakes as independent variables and T cell proliferation as dependent variables.
Results
Significant positive correlations (P≤ .05) were found between PHA-induced proliferation and intake of docosahexaenoic acid (DHA), eicosahexaenoic acid (EPA), sodium, and selenium, although intakes of DHA plus EPA were inadequate when compared to recommended intakes. A significant negative correlation with total vitamin A, with many vitamin A levels being above the upper limit of safety. Regression analyses found these nutrients to be variables significant in explaining the variance in PHA (p=0.005).
Conclusions
Selenium, sodium, DHA, EPA and vitamin A intake from diet and supplements were associated with PHA-induced proliferative responses. Clients may be counseled to have adequate selenium, EPA, DHA intake, and vitamin A, but avoid excess vitamin A.
The responsiveness of the human immune system has been shown to decrease with age (1). Generally the immune system is represented as either innate, which includes the complement system, natural killer cells, and phagocytosis, or adaptive. Adaptive immune include cell-mediated and humoral immunity. When innate immunity components are not able to clear the infection adaptive immunity components become involved. Both adaptive and innate immunity are adversely affected by aging in terms of the adaptiveness of T cells in the former and the effectiveness of natural killer cells in the latter (2). Specifically, T cell proliferation to polyclonal mitogens and specific pathogens is known to decrease with age (3). The clinical implications of immunosenescence include a poor response to vaccination, progressive loss in the ability to recognize foreign antigens, increased autoantibodies, and increased susceptibility to infections and chronic disease (4).
As a person ages, nutrient intake in general may be inadequate (5,6), increasing susceptibility for compromised immune function. A study comparing healthy elderly with healthy young adults showed that lower nutritional status was associated with the lower T cell functions in the elderly (7). While the effects of specific individual nutrient deficiencies on immune function are generally known, how aging, nutritional status, and immune function impact each other is not fully elucidated (8). This study examined nutrient intake, supplement use, and immune function and the relationships among these variables in an elderly community-living population.
METHODS
Subject Recruitment and Study Design
A convenience sample of males and females 65–80 years old were recruited from the Champaign, Illinois vicinity through local media and contacts with area health facilities, senior centers, and additional public places. This study used data from two sources: a cross-sectional study and the baseline data from longitudinal study of aging and immune function and exercise intervention. Only independently community living individuals were recruited. Subjects responding to the recruitment campaign were pre-screened by telephone and sent eligibility questionnaires. Subjects were selected based on age, gender, and medication usage. Exclusion criteria included a self-reported history of: cancer or strong allergies, abnormal blood tests (complete blood counts, fasting glucose, potassium), primary immunodeficiencies, mental illness, pre-menopausal status, recent (< 6 months) vaccination, illness, smoking, alcohol or drug abuse, heart disease, involvement in competitive athletics or a highly physically active lifestyle. All participants signed informed consent according to the approved University of Illinois Institutional Review Board protocol. Attempts were made to obtain a full vaccination history from each participant, including whether or not they received a full primary tetanus series. Subjects who had a tetanus booster within the previous 3 years were excluded. Blood was drawn and transferred to the medical center laboratory on ice as part of routine blood testing for complete blood counts, comprehensive metabolic panel, and total cholesterol. Participants would have been excluded if results were outside of the normal range, but all were normal (Normal ranges in Table 1).
Table 1.
Normal lab values
| Test | Expected Range | Units |
|---|---|---|
| Hematology: | ||
| White Blood Cells | 4.00–11.00 | 103/ul |
| Red Blood Cells | 4.10–5.70 | 106/ul |
| Hemoglobin | 12.0–18.0 | g/dl |
| Hematocrit | 37.0–51.0 | % |
| Mean Corpuscular Volume | 80.0–100.0 | fl |
| Mean Corpuscular Hemoglobin | 27.0–33.0 | pg |
| Mean Corpuscular Hemoglobin Concentration | 32.0–36.0 | g/dl |
| Red Blood Cell Distribution Width | 12.0–15.0 | % |
| Red Blood Cell Distribution Width Standard Deviation | 38.0–52.0 | fl |
| Platelet | 140–400 | 10^3/ul |
| Mean Platelet Volume | 9.0–12.0 | fl |
| Neutrophil | 40.0–70.0 | % |
| Lymphocyte | 20.0–45.0 | % |
| Monocyte | 0.0–10.0 | % |
| Eosinophil | 0.0–5.0 | % |
| Basophil | 0.0–2.0 | % |
| Absolute Neutrophil | 1.60–7.70 | 103/ul |
| Absolute Lymphocyte | 1.00–4.90 | 103/ul |
| Absolute Monocyte | 0.00–1.10 | 103/ul |
| Absolute Eosinophil | 0.00–0.50 | 103/ul |
| Absolute Basophil | 0.00–0.20 | 103/ul |
| Chemistry: | ||
| Calcium | 8.5–10.5 | mg/dl |
| Glucose | 60–99 | mg/dl |
| Blood Urea Nitrogen | 6–20 | mg/dl |
| Creatinine | 0.5–1.2 | mg/dl |
| Protein, Serum Total | 6.0–8.1 | gm/dl |
| Albumin | 3.2–5.5 | gm/dl |
| Bilirubin, Total | 0.2–1.0 | mg/dl |
| Aspartate Aminotransferase | 12–50 | IU/L |
| Alanine Aminotransferase | 10–75 | IU/L |
| Alkaline Phosphatase | 42–121 | IU/L |
| Sodium | 135–145 | mmol/L |
| Potassium | 3.6–5.0 | mmol/L |
| Chloride | 101–111 | mmol/L |
| Carbon Dioxide | 21.0–31.0 | mmol/L |
| Cholesterol, Total | <200 | mg/dl |
All subjects were asked to refrain from use of certain medications such as corticosteroids, non-steroidal anti-inflammatory drugs, or anti-histamines 4 days prior to immune testing.
Diet Assessment
Subjects were instructed on recording their intakes from the previous day relative to portion sizes and specificity of foods eaten, and asked to complete a 1-day food recall at the lab. A registered dietitian reviewed the recall with each participant, clarifying food terms, ingredients, brands, and portion sizes, following a method similar to the multi-pass method so that the 1-day food recall was reviewed multiple times for portions, forgotten foods, and clarification of any food items (9,10). Information about supplement use was obtained at the time of 1-day food recall review as well, including brand and quantity for supplement taken. Subjects whose recall represented a non-typical day were omitted from the analysis (n=4). Dietary Reference Intakes (DRI) and their Estimated Average Requirement (EAR), Recommended Dietary Allowances (RDA) or Adequate Intake (AI) values were used to assess nutrient intake adequacy (11–17), the exception being docosahexaenoic acid (DHA) and eicosahexaenoic acid (EPA). The range of optimal intake of 0.5 to 1.8 g/day for combination of DHA and EPA from diet and supplements and intake of α-linolenic acid of 1.5 to 3.0 g/day were used for reference ranges (18).
Anthropometrics
Height was measured without shoes using a stadiometer to the nearest 0.25 inch (Seca,Corp., Hamburg, Germany). Weight was measured on a calibrated digital scale to the nearest 0.25 pound (Tanita BWB-600, Wedderburn, Australia). An average of three measures was used to ensure accuracy. Body mass index (BMI) was calculated as kg/meter2 and compared to the classification of BMI of the National Heart, Lung, and Blood Institute (19).
Serum Measures
Fasting blood (12 hours) was drawn for immune function, transferred on ice to the medical center laboratory for in vitro proliferation after stimulation with the polyclonal mitogen phytohemagglutinin (PHA) determinations. Healthy lymphocytes respond to PHA stimulation by proliferating vigorously in a polyclonal manner. The ability to proliferate in such a way has been routinely used as a general indicator of T lymphocyte function (20). Triplicate cultures were stimulated for 3 days with PHA in concentration of 0.5, 1.0, 2.0, 4.0, and 8.0 µg/ml (Sigma, St. Louis, MO) in 50 µl volumes in 96-well round bottom plates. All cultures were maintained in AIM-V media and incubated at 37°C in 5% CO2. After 3 day culture, 1.0 µCi of (methyl-3H) thymidine (ICN, Irvine, CA) was added to each cell culture well. The amount of radioactivity incorporated into the cultures was determined by harvesting the contents of each well after 4 hours incubation with tracer onto glass fiber filters using a cell harvester (Cambridge Technologies, Watertown, MA). Radioactivity of the filters was determined using a Packard liquid scintillation counter (Packard, Meridian, CT). Net proliferation was calculated as stimulant cultures (PHA) minus cultures containing no stimulant. The same lot numbers of PHA were utilized in all experiments.
Data Analyses
Twenty-four hour recalls were analyzed using Nutritionist V (First Data Bank, version 2.3, San Bruno, CA, 2000) and entered into SPSS for analyses. Quality assurance for data entry included outlier examination using boxplots and verification with original data source as well as continuous random inspection data entry and original source equivalency. Statistical analysis for descriptive, bivariate correlation, Spearman's Rho for nonparametric data, t-tests, and stepwise regression with nutrient intakes as independent variables and t cell proliferation as dependent variables were completed using SPSS with significance set at (P< .05) (version 15.0, Chicago, IL, 2006).
RESULTS
Thirty-six men and 57 women participated and had complete dietary, supplement, and PHA data. Four were omitted from analyses because they had non-typical food intake during the recall period, leaving 35 men and 54 women for analyses. Their mean age was 69.7 ± 5.5 years and a mean BMI of 27.8 ± 4.7 kg/m2 (Table 1). Means did not differ by gender. Only 20 (22%) of participants were classified as normal weight, with most being overweight or obese, and 3 classified as extremely obese.
Mean nutrient intakes for diet alone and diet plus supplements are listed in Table 2. Mean energy intake for women was 1638 ± 458 kcal and for men 2177 ± 596. Most (80%) achieved recommended caloric and protein intake (78%). Many consumed a diet higher than recommended in total fat (≥ 35% calories by 60% of participants) and saturated fat (>10% calories by 49% of participants). Few participants met recommended levels for linoleic and linolenic acid (≤ 35 % of participants), and only 6% had diets meeting the DHA plus EPA recommendations. More than 50% of participants had diets not meeting the recommended amounts for potassium, calcium, magnesium, vitamin D, vitamin E, vitamin K, folate, and pantothenic acid (Table 3).
Table 2.
Nutritional adequacy of diet compared to nutritional adequacy of diet with supplementation in elderly subjects, n=89
| Nutrient | EAR or AI for age group | % reaching EAR or AI with diet alone (n) | % reaching EAR or AI with diet + supp. (n) | % ≥ UL, diet + supp. (n) |
|---|---|---|---|---|
| Calories16 | ||||
| Males | 2,587 | 20 (7) | 20 (7) | |
| Females | 2,067 | 20 (11) | 20 (11) | |
| Protein g/kg16 | 0.66 | 78 (69) | 78 (69) | |
| Carbohydrate g16 | 100 | 96 (85) | 96 (85) | |
| Fat16 | 35 % total energy | 60 (53) | 60 (53) | |
| Saturated fat16 | 10 % total energy | 49 (44) | 49 (44) | |
| Monounsaturated fat16 | 15 % total energy | 89 (79) | 89 (79) | |
| Polyunsaturated fat16 | 10 % total energy | 89 (79) | 89 (79) | |
| Linoleic acid g16 | ||||
| Males | 14 | 9 (3) | 9 (3) | |
| Females | 11 | 22 (12) | 22 (12) | |
| Linolenic acid g16 | ||||
| Males | 1.6 | 9 (3) | 9 (3) | |
| Females | 1.1 | 24 (13) | 24 (13) | |
| DHA + EPA18 | 0.3–0.5 | 6 (5) | 13 (12) | |
| Sodium g17 | 1.2 | 89 (100) | 89 (100) | |
| Potassium g17 | 4.7 | 6 (5) | 6 (5) | |
| Vitamin A (mcg RE)15 | ||||
| Males | 624 | 89 (31) | 91 (32) | 29 (10) |
| Females | 500 | 93 (50) | 93 (50) | 36 (23) |
| Vitamin C mg13 | ||||
| Males | 75 | 71 (25) | 89 (31) | |
| Females | 60 | 93 (50) | 98 (53) | |
| Vitamin D IU11 | 400 | 4 (4) | 69 (61) | 1 |
| Vitamin E mg13 | 12 | 13 (12) | 74 (66) | 1 (supp. only) |
| Vitamin K mcg15 | ||||
| Males | 120 | 14 (5) | 14 (5) | |
| Females | 90 | 31 (17) | 31 (17) | |
| Thiamin mg12 | ||||
| Males | 1.0 | 83 (29) | 91 (32) | |
| Females | 0.9 | 87 (47) | 96 (52) | |
| Riboflavin mg12 | ||||
| Males | 1.1 | 89 (31) | 94 (33) | |
| Females | 0.9 | 87 (47) | 96 (52) | |
| Niacin mg12 | ||||
| Males | 12 | 89 (31) | 94 (33) | 59 (20) |
| Females | 11 | 80 (43) | 91 (49) | 54 (28) |
| Vitamin B-6 mg12 | ||||
| Males | 1.4 | 63 (22) | 80 (28) | |
| Females | 1.3 | 69 (37) | 87 (47) | |
| Folate mcg DFE12 | 544 | 38 (34) | 74 (66) | 6 (5) |
| Vitamin B-12 mcg12 | 2.0 | 71 (63) | 90 (80) | |
| Pantothenic acid mg12 | 5 | 13 (12) | 66 (59) | |
| Calcium mg11 | 1200 | 19 (17) | 42 (37) | 3 (3) |
| Iron mg15 | 8 | 91 (81) | 92 (82) | 3 (3) |
| Magnesium mg11 | ||||
| Males | 350 | 20 (7) | 46 (16) | 49 (17) |
| Females | 265 | 43 (23) | 72 (39) | 39 (21) |
| Zinc mg15 | ||||
| Males | 9.4 | 40 (14) | 74 (26) | 3 (1) |
| Females | 6.8 | 72 (39) | 93 (50) | 4 (2) |
| Selenium mcg13 | 45 | 64 (57) | 81 (72) |
EAR=estimated average requirements
AI=adequate intake
UL=upper level of safety
RE= Retinyl equivalents
EPA = eicosahexaenoic acid
DHA = docosahexaenoic acid
DFE= dietary folate equivalents
Table 3.
Mean (standard deviation) intakes of nutrients from diet alone and diet plus supplements in elderly subjects, n=89
| Mean ± SD Diet only | Mean ± SD Diet + supplements | t,p1 | |
|---|---|---|---|
| Potassium, mg | 2814.6 ± 1011.8 | 2864.1 ± 1022.7 | 11.9, .0001 |
| Vitamin A, mcg RE | 1225.1 ± 933.4 | 2098.6 ± 3225.9 | 2.6, .010 |
| β-carotene, mcg RE | 1232.2 ± 3477.4 | 1727.7 ± 3463.3 | 13.5, .0001 |
| Vitamin C, mg | 165.5 ± 187.8 | 315.7 ± 295.5 | 5.7, .0001 |
| Vitamin D, IU | 190.3 ± 494.4 | 498.2 ± 498.0 | 12.8, .0001 |
| Vitamin E, IU | 9.9 ± 9.0 | 153.7 ± 212.5 | 6.4, .0001 |
| Vitamin K ug | 79.9 ± 100.7 | 86.5 ± 100.9 | 12.8, .0001 |
| Thiamin, mg | 1.6 ± 0.8 | 2.6 ± 1.1 | 13.2, .0001 |
| Riboflavin, mg | 1.7 ± 0.8 | 2.9 ± 1.2 | 13.2, .0001 |
| Niacin, mg | 19.4 ± 9.1 | 32.6 ± 13.0 | 13.2, .0001 |
| Vitamin B6 mg | 1.8 ± 0.8 | 5.3 ± 9.3 | 3.6, .0001 |
| Folate, ug DFE | 518.4 ± 272.2 | 953.9 ± 454.9 | 11.9, .0001 |
| Vitamin B12 ug | 3.8 ± 3.2 | 28.0 ± 61.7 | 3.7, .0001 |
| Pantothanic acid, ug | 3.6 ± 2.8 | 9.9 ± 5.7 | 12.2, .0001 |
| Calcium, mg | 790.2 ± 449.7 | 1135.9 ± 609.3 | 8.1, .0001 |
| Iron, mg | 14.8 ± 6.6 | 18.4 ± 9.3 | 4.7, .0001 |
| Magnesium, mg | 286.0 ± 112.3 | 351.2 ± 127.7 | 12.8, .0001 |
| Zinc, mg | 9.9 ± 5.3 | 21.4 ± 13.0 | 8.9, .0001 |
| Selenium, mg | 0.1 ± 0.04 | 17.9 ± 22.0 | 7.7, .0001 |
paired t, significance
RE=retinol equivalents
β-carotene reported in IU, converted from µg by conversion factor of 3.33
IU=international units
DFE= dietary folate equivalents
Supplements improved nutrient intake for all nutrients included in the supplements (P< .05). With supplementation to the diet, there was an increase in the percentage of subjects meeting the recommended levels for all vitamins and minerals. However, vitamin K intake did not improve greatly for most despite the dietary supplementation. In addition, >25% met or exceeded the upper limit of safety for niacin, magnesium and vitamin A (Table 3).
Bivariate correlations were used to assess the relationship between T cell PHA-induced proliferation and nutrient intake, with Spearman’s Rho when data were nonparametric as assessed by Kolmogorov-Smirnov one-sample test. Poor proliferative response being associated with less immunocompetence and greater prolierative response with better immunocompetence. Significant correlations were found between PHA proliferation (0.5, 1.0, and 2.0 µg/ml) and DHA plus EPA intake, and for DHA or EPA alone (0.5, 1.0, and 2.0 µg/ml). Significant negative correlations were found for total vitamin A (2.0, 4.0, and 8.0 µg/ml) and positive correlations for dietary selenium and sodium intake at higher concentrations of PHA (2.0, 4.0, and 8.0 µg/ml) (Table 4).
Table 4.
Correlation between polyclonal mitogen response [PHA] with nutrients in elderly subjects, n=89
| EPA + DHA | Protein g/kg | DHA (diet) | Vitamin A RE (diet) | Vitamin A (total) | Sodium (diet) | EPA (diet) | Riboflavin (diet) | Selenium (diet) | |
|---|---|---|---|---|---|---|---|---|---|
| r (p) | r (p) | r (p) | r (p) | r (p) | r (p) | r (p) | r (p) | r (p) | |
| PHA 0 µg/ml | .09 (.387) | .10 (.341) | .09 (.405) | −.04 (.694) | −.18 (.103) | .12 (.258) | .10 (.346) | −.05 (.670) | .06 (.606) |
| PHA .5 µg/ml | .65 (<.001) | −.12 (.262) | .67 (<.001) | −.07 (.515) | −.16 (.158) | .09 (.409) | .59 (<.001) | .23 (.034) | .11 (.296) |
| PHA 1 µg/ml | .52 (<.001) | −.07 (.491) | .53 (<.001) | −.07 (.501) | −.10 (.355) | .08 (.417) | .48 (<.001)) | .23 (.033) | .18 (.094) |
| PHA 2 µg/ml | .26 (.015) | −.21 (.046) | .27 (.012) | −.17 (.113) | −.23 (.037) | .21 (.046) | .23 (.029) | .13 (.220) | .29 (.006) |
| PHA 4 µg/ml | .02 (.839) | −.19 (.069) | .03 (.810) | −.21 (.044) | −.26 (.018) | .25 (.020) | .01 (.928) | .06 (.607) | .27 (.009) |
| PHA 8 µg/ml | −.07 (.545) | −.15 (.155) | −.06 (.572) | −.20 (.063) | −.26 (.016) | .22 (.043) | −.08 (.479) | −.02 (.878) | −.12 (.264) |
EPA = eicosahexaenoic acid
DHA = docosahexaenoic acid
Values bolded are significant p≤ 0.05.
Stepwise regression analysis was used to determine if nutrient intakes as independent variables were able to predict the variation in PHA-induced proliferation. Five significant equations were found, explaining 9 to 58% of the variance (Table 5). Significant variables in these equations included DHA plus EPA, fat, dietary selenium, and vitamin A.
Table 5.
Regression analyses explaining variance in immune function response, n=89
| Dependent Variable | Independent variables | F | P |
|---|---|---|---|
| T-cell proliferation with PHA concentration of .5 µg/ml | 8296 + 113969 [DHA diet] – 72749 [EPA + DHA diet] + 4 [fat] - .14 [vitamin A total]; R = .763; R2 = .582 | 27 | .028 |
| T-cell proliferation with PHA concentration of 1.0 µg/ml | 12183 + 20921 [DHA diet] + 20 [saturated fat kcal]; R = .566; R2 = .320 | 20 | .038 |
| T-cell proliferation with PHA concentration of 2.0 µg/ml | 33246 + 170124 [selenium] – 11761 [protein g/kg] + 11638 [DHA]; R = .475, R2 = .225 | 8 | .043 |
| T-cell proliferation with PHA concentration of 4.0 µg/ml | 54593 + 230093 [selenium] – 18099 [protein g/kg]; R = .368; R2 = .135 | 7 | .016 |
| T-cell proliferation with PHA concentration of 8.0 µg/ml | 48195 + 84 [carbohydrate] – 8 [vitamin A RE diet]; R = .307; R2 = .094 | 4 | .038 |
PHA= Polyclonal mitogen phytohemmagluttin
EPA = Eicosahexaenoic acid
DHA = Docosahexaenoic acid
Vitamin A RE = Retinol equivalents
DISCUSSION
Although zinc deficiency has been associated with impaired immune function, zinc intake was adequate for most subjects with diet alone, similar to a European study of community-dwelling elders (21). Total zinc intake (supplemental zinc plus dietary zinc) was adequate for all but 9 men and 4 women. Similarly, intakes from diet alone were in the range of those found for elderly European men and women for vitamin A and folate (22). Comparison with US studies of dietary intake of the elderly are difficult since results are often reported as percentages of recommended intake levels that are no longer current (23) or had recruitment criteria that included certain dietary patterns (24).
The deficiency of a number of nutrients have been linked to immune function, notably vitamin A (25), vitamin C and zinc (26), vitamin B6 (27), iron and copper (28) and selenium (29). Few of the participants in the current study had dietary intakes of these nutrients below the recommended levels, and most of those reached the recommended level with supplementation, an exception being selenium where 17 individuals continued to not meet recommended selenium intakes.
Marginal selenium status has been associated with compromised immune function (30). Selenium supplementation in animals has been shown to improve immune function. For lymphocytes, improvement in proliferation was reported if the supplementation was low, but was inhibited if supplementation was high (31). In humans, selenium supplementation has also been reported to have a beneficial effect on immune function (32,33). Results of the present study could not suggest selenium deficiency, but is in accordance with an association between selenium intake and immune function. Mean dietary selenium was improved significantly with supplements, but 31 participants had no supplement containing selenium, 51 had low levels of supplementation (20 µg) and 6 had supplements of 70–120 µg. A recent study reported a correlation between blood selenium levels and immune function with an increased proliferation in lymphocytes that reflects the findings of the present study (34).
The omega-3 fatty acids DHA and EPA were significantly correlated with lymphocyte proliferation at the 0.5, 1.0, and 2.0 µg/ml concentrations and were a significant variable in regression equations explaining the variance in proliferation at these concentrations as well. However, these relationships were not found at higher lymphocyte concentrations. Clinical trials of relative high levels of DHA have demonstrated no effect on lymphocyte proliferation (35–37). Although EPA and DHA have been reported to suppress lymphocyte proliferation (38,39) these in vitro studies added EPA to cell cultures creating a much different interaction than dietary EPA may have in vivo. A small study of 4 volunteers consuming 2.4 g EPA/day for 6 weeks reported no consistent changes in immune responses (40). Forty-two participants received either placebo, 4.7 g EPA, or 4.9 g DHA for 4 weeks. Lymphocyte activation as measured by CD69 expression, an early marker of lymphocyte proliferation, was suppressed by DHA. This is in contradiction to others reports and may reflect an affect on function but not proliferation (41).
Total vitamin A intake included dietary and supplemental vitamin A but did not include dietary or supplemental β carotene. Total vitamin A intake was negatively correlated with lymphocyte proliferation at 2.0, 4.0, and 8.0 µg/ml and was a negative variable in significant regression equations for these levels of PHA. While deficiency of vitamin A has been associated with a negative effect on immune function (25), our data do not reflect poor vitamin A intake. Supplementation resulted in intakes at or above the UL for many participants. Vitamin A supplementation has been reported to have a negative immune function effect in the elderly (42), and could account for the negative correlation and negative weight in regression equations in the current study.
The relationship between sodium intake and immune response was not expected. Sodium intake has been associated with hypertension in population-based observational studies as well as intervention studies (17). Interestingly, there is growing evidence indicating a relationship between immune function and hypertension. Not only may vascular damage elicit immune responses, but also that an abnormal immune system may contribute to the develop of hypertension (43,44). The current correlation supports neither of these hypotheses but does suggest that additional research may be warranted.
While relationships between nutrition and immunology in the elderly have been identified both in the present study and previous research, the relationships are not distinct nor are mechanisms of interaction known. Although protein energy malnutrition has a detrimental effect on immunity (45), none of these participants were underweight. Conversely overweight and obesity have been shown to be associated with increased immune cell counts in women, although PHA were not specifically assessed (46). The number of participants in each BMI category was too small to adequately assess the impact of under- or overnutrition on PHA.
There are several limitations inherent in any study of dietary intake. Using the EAR for assessing dietary adequacy is complex but can be used to examine the probability that intake is inadequate for individuals or to assess the prevalence of inadequate intakes within a group (14). However, EAR have only been calculated for the B vitamins, vitamins C and E, selenium, and phosphorus and RDA should not be used for assessing group data. Although 24-hour recalls are more reliable than food frequency questionnaires (47), they are still subjective tools that represent a one day’s frame of usual intake. As with any dietary analysis, the completeness of the database may under-represent nutrient intake. An earlier version of the database used compared favorably with other databases analyzed (48), however food products continue to change and manufacturer's analysis may not include EPA and DHA in particular.
In addition, this is a cross-sectional study and not a nutrition intervention project. A previous small intervention with community-living elderly [n=31] found no effect of a micronutrient supplement on lymphocyte proliferation as measured by concanavalin A (49). Authors concluded that adequate intake of nutrients known to affect immune health was a message for all elders. Our study concurs with this conclusion but adds that dietitians should assess for high as well as low nutrient intake.
CONCLUSIONS
Selenium, omega-three fatty acids, sodium and vitamin A intake from diet and supplements were found to be associated with in vitro T lymphocyte PHA-induced proliferative responses. Lower than recommended intakes of selenium and omega-three fatty acids and higher than recommended intakes of vitamin A should be further investigated for their impact on overall immune function in the elderly. Dietitians need to assess dietary and supplemental vitamin A in relation to the UL to prevent excess vitamin A intake in their elderly clients. Clients should be counseled concerning good dietary sources of EPA and DHA as well as selenium to improve or maintain dietary status.
Acknowledgements
This project was supported by NIH/NIA AG-18861 grant to J. Woods.
Footnotes
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