Risk Factors of Epstein-Barr Virus Infection Among United States Children

Abstract

Background: Epstein-Barr virus (EBV) has become a common medical condition in adolescents and young children. The objective of this study was to examine the association of low dietary intake and food insecurity with EBV infection. Methods: Cross-sectional data were analyzed using the National Health and Nutrition Examination Survey 2009-2010 sample population (n = 1550) aged 6 to 15 years. Self-report data on dietary intake and food security were abstracted from data files. The outcome variable was measured using EBV index from the laboratory data. Multivariable logistic regression analysis was used to determine the association between exposure and outcome variables. Results: The prevalence of EBV in this population was 56.4%. In the unadjusted analyses, adolescents who consumed 100% fruit juice (OR = 1.49, 95% CI = 1.09-2.05), beans (OR = 2.35, 95% CI = 1.12-4.94), and red meat (OR = 1.57, 95% CI = 1.09-2.24) daily had statistically significant elevated odds of EBV as compared to adolescents who consumed them monthly. Furthermore, adolescents who sometimes did not get fed a balanced meal and had to rely on low-cost food had statistically significant increased odds of EBV. However, after adjusting for potential confounders the results for both dietary factors and food insecurity were no longer statistically significant. Conclusions: Certain dietary factors and food insecurity may predispose children to EBV infection.

Introduction

The Epstein-Barr virus (EBV), a member of the herpes virus family, is a common human virus that has been shown to be related to infectious mononucleosis ¹ and certain cancers such as Burkitt’s lymphoma, ² Hodgkin lymphoma, ³ and nasopharyngeal carcinoma. Prevalence of EBV increases with age, varying from 54.1% (6-8 years old) to 82.9% (18-19 years old).^4,5 Children aged 2 to 12 months are highly susceptible to EBV infection due to the loss of maternal antibodies and a weak immune response. ⁴

Diet plays an important role in enhancing an individual’s immune response. ⁶ Low dietary intake makes children susceptible to infection by compromising their immune response, thereby resulting in severe adverse health consequences. While a number of studies have researched the association between EBV infection and various disorders or cancers,^2,3 few studies to date have explored risk factors of EBV infection and no study has examined the relationship between dietary factors and EBV infection in children. The purpose of this study was to examine the association of dietary factors and food insecurity with EBV infection among US children aged 6 to 15 years using data from the 2009-2010 National Health and Nutrition Examination Survey (NHANES).

Methods

The NHANES is an annual population-based survey conducted on the noninstitutionalized civilian population of the United States. The National Center for Health Statistics, which is a part of the Centers for Disease Control and Prevention, conducts NHANES on a sample of approximately 5000 nationally representative individuals each year and releases data in 2-year intervals. NHANES uses complex, multiple stage, probability sampling of noninstitutionalized US civilians of all ages. This study used data from the 2009-2010 NHANES. Data on EBV were collected only on adolescents between 6 and 15 years old (n = 1925). For this cross-sectional study, data were excluded if the outcome variable EBV was missing (n = 375). Thus, a total of 1550 adolescents were included in this study. The response rates for adolescents aged 6 to 15 years was approximately 87% ⁷ .

Measurement of Exposure Variables

The main exposure variables measured in this study were dietary intake and food security. The variables were obtained from the 2009-2010 NHANES dietary screener questionnaire data file. The dietary screener questionnaire contains questions on “How often drink milk and 100% fruit juice?” and “How often eat leafy lettuce, beans, whole grain bread, and red meat?” The responses were categorized as per day, per week, and per month. The NHANES 2009-2010 questionnaire file named food security contains questions on “child skip meals?” and “child not eating for a whole day?” categorized as yes or no, and “relied on low-cost food for child?” categorized as often true, sometimes true, or never true.

Measurement of Outcome Variable

The 2009-2010 NHANES laboratory data file containing the EBV test (viral capsid antigen [VCA] IgG) values were used to construct the main outcome variable coded as a binary variable (1 = positive, 0 = negative). Serum samples were collected from children aged 6 to 19 years and EBV VCA IgG antibody was measured using a commercial enzyme immunoassay kit. EBV results were determined by Epstein immunoassay indices (EIA). Samples that had an EIA index <0.90 were considered to be negative for EBV and those that were >1.10 were considered to be positive for EBV. Samples that had an EIA index ≥0.90 to 1.099 were considered as equivocal for EBV. ⁷ There were only 5 samples with an equivocal EBV response, all of which was excluded from this study.

Measurement of Covariate Variables

Age, sex, race/ethnicity, family annual income, household size, and household smoking (secondhand smoke), all abstracted from the 2009-2010 NHANES demographic data file, were considered as potential confounders while analyzing the associations between low dietary intake and food insecurity with EBV infection. Age was categorized as 6 to 8, 9 to 11, and 12 to 15 years. Race/ethnicity was categorized as Mexican American, other Hispanic, Non-Hispanic White, Non-Hispanic Black, and other race including multiracial. Family annual income was categorized as first (higher) income quartile ($75 000-$99 999), second ($55 000-$74 999), third ($25 000-$54,999), and fourth (lowest) income quartile ($0-$24 999). Household size was categorized as <5, 5 to 6, >6. Household smoking data were coded based on responses to the question “does anyone smoke inside home?” as yes (coded as 1) or no (coded as 0). ⁷

Statistical Analysis

Summary statistics which include frequency and percentages describing characteristics of NHANES 2009-2010 study population were enumerated. Unadjusted odds ratios (ORs) and 95% confidence intervals (CIs) were calculated using univariable logistic regression to obtain a crude association between risk factors (low dietary intake and food insecurity) and EBV infection. Adjusted ORs and 95% CIs were calculated using multivariable logistic regression to determine an exposure-outcome relationship. Variables such as race/ethnicity, age, sex, SES, and secondhand smoking were potential confounders in this study. A variable was considered a confounder if it changed the crude OR by at least 10%. ⁸ Data analysis was conducted using STATA statistical software, release 13 taking into account complex survey design of NHANES (STATA Corporation, College Station, TX).

Results

The variables assessed for descriptive statistics are shown in Table 1. Male children comprised 51.5% of the population. Approximately 56.6% of the population was Non-Hispanic Whites, 16.1% was Mexican American, and the rest of the race/ethnicity groups (Non-Hispanic Black, other Hispanic, and other race) made up 27.3% of the population. Families with an annual income of <$24 999 comprised 22.1% of the population, and those with an annual income of ≥$75 000 made up 34.1% of the population. Families with a household size of <5 made up 55.3% of the population and those with a household size of 5-6 accounted for 34.2% of the population. The majority of the population tested positive for EBV (56.4%), and 12.4% of the population were exposed to secondhand smoke.

Table 1.

Study Sample Characteristics of Adolescents Who Participated in the National Health and Nutrition Examination Survey According to Dietary Intake, 2009-2010.

Characteristic	n	%
Age, years
6-8	472	26.8
9-11	508	20.2
12-15	570	44.0
Race/ethnicity
Non-Hispanic white	485	56.6
Non-Hispanic black	293	12.9
Mexican American	476	16.1
Other Hispanic	194	6.7
Other race, including multiracial	102	7.7
Sex
Male	804	51.5
Female	746	48.5
Family annual income, $
0-24 999	470	22.1
25 000-34 999	215	10.6
35 000 to <54 999	253	14.9
55 000 to <74 999	151	12.2
≥75 000	342	34.1
Household size, n
<5	702	55.3
5-6	603	34.2
>6	245	10.5
Household smoking
Yes	206	12.4
No	1335	87.0
Epstein-Barr virus
No	509	43.6
Yes	1041	56.4

Table 2 summarizes the unadjusted and adjusted multivariable logistic regression model results. In the univariate (unadjusted) multivariable logistic regression analysis, ORs ranged from 0.70 to 3.2. Adolescents who drank 100% fruit juice (OR = 1.49, 95% CI = 1.09-2.05) and ate beans (OR = 2.35, 95% CI = 1.12-4.94) or red meat (OR = 1.57, 95% CI = 1.09-2.24) every day had an increased odds of EBV when compared with monthly consumption of these diets. Also, parents who sometimes could not feed their child a balanced meal (OR = 2.42, 95% CI = 1.31-4.47) and had to rely on low-cost food for their child ([Often true, OR = 2.84, 95% CI = 1.13-7.11]; [Sometimes true, OR = 2.36, 95% CI = 1.22-4.55]) had increased odds of EBV. Additionally, results showed that adolescents who ate whole grain bread every day (OR = 3.2, 95% CI = 0.84-12.20) and parents who could not feed their child a balanced meal (Often true, OR = 2.64, 95% CI = 0.48-14.65) had a statistically insignificant increased odds of EBV infection. After adjusting for confounders the association between dietary intake and food security and EBV infection among children aged 6 to 15 years was not statistically significant, and odds ratio ranged from 0.60 to 1.60 (Table 2).

Table 2.

Unadjusted and Adjusted Odds Ratios (OR) and 95% Confidence Interval (CI) of the Association Between Low Dietary Intake and Food Insecurity and Epstein-Barr Virus Infection. ^a

	Unadjusted OR (95%CI)	Adjusted OR (95%CI)
Dietary intake
How often drink milk?
Per month	1.00	1.00
Per day	0.85 (0.65-1.10)	0.81 (0.59-1.11)
Per week	0.87 (0.62-1.20)	0.61 (0.37-1.01)
How often drink 100% juice?
Per month	1.00	1.00
Per day	1.49 (1.09-2.05)	1.18 (0.69-2.02)
Per week	1.22 (0.88-1.69)	1.00 (0.62-1.59)
How often eat fruit?
Per day	0.78 (0.57-1.09)	0.76 (0.47-1.21)
Per week	0.89 (0.64-1.25)	0.79 (0.48-1.26)
Per month	1.00	1.00
How often eat leafy/lettuce salad?
Per day	1.67 (0.85-3.31)	1.39 (0.63-3.05)
Per week	0.76 (0.52-1.11)	0.68 (0.43-1.09)
Per month	1.00	1.00
How often eat whole grain bread?
Per day	3.2 (0.84-12.20)	1.60 (0.37-6.84)
Per week	1.06 (0.67-1.69)	0.85 (0.46-1.56)
Per month	1.00	1.00
How often eat beans?
Per day	2.35 (1.12-4.94)	0.93 (0.38-2.21)
Per week	0.97 (0.68-1.38)	0.89 (0.56-1.40)
Per month	1.00	1.00
How often eat red meat?
Per day	1.57 (1.09-2.24)	1.26 (0.74-2.15)
Per week	0.96 (0.72-1.29)	1.11 (0.78-1.57)
Per month	1.00	1.00
Food security
Eat less than should
No	1.00	1.00
Yes	1.05 (0.52-2.13)	1.15 (0.55-2.41)
Couldn’t feed child balanced meal
Often true	2.64 (0.48-14.65)	0.87 (0.17-4.49)
Sometimes true	2.42 (1.31-4.47)	1.20 (0.67-2.15)
Never true	1.00	1.00
Relied on low-cost food for child
Often true	2.84 (1.13-7.11)	1.15 (0.49-2.69)
Sometimes true	2.36 (1.22-4.55)	1.10 (0.55-2.20)
Never true	1.00	1.00

a

Model adjusted for age, ethnicity, gender, income, household size, and household smoking.

Discussion

The current study found that in the unadjusted model, adolescents who consumed 100% fruit juice, beans, and red meat daily had statistically significant increased odds of EBV as compared with adolescents who consumed 100% fruit juice, beans, and red meat monthly. Furthermore, adolescents who did not get fed a balanced meal and had to rely on low cost food had statistically significant increased odds of EBV. However, after adjusting for potential confounders the results were no longer statistically significant.

Although, there are a few studies that examined the relationship between diet-related factors and infection in children, no study to date has examined the association between dietary factors and EBV infection in children. Diet intake and food security play an important role in enhancing individuals’ immune response. Fruits and vegetables contain micronutrients that are helpful in protecting individuals against infections. Consuming foods rich in vitamin A helps maintain the integrity of the epithelium in the respiratory and gastrointestinal tracts. ⁶ Vitamin D is sufficient enough to enhance the immune system’s ability to withstand infection. In addition, vitamin E intake has the ability to increase both cell-dividing and interleukin-producing capacities of naïve T cells. ⁹ Children receiving daily 300 IU of vitamin D supplementation in milk had a significantly reduced risk of acute respiratory infection (risk ratio [RR] = 0.50, 95% CI = 0.28-0.88). ¹⁰ Multivitamin supplementation may benefit maternal immunity by decreasing the risk of viral infection during pregnancy and subsequent fetal transmission. Inadequate dietary intake leads to weight loss, lowered immunity, mucosal damage, invasion by pathogen, and impaired growth and development in children. ¹¹ Food insecurity likely impacts clinical prognosis, including CD4 count and viral load through macronutrient and micronutrient deficiencies that lead to weight loss, malabsorption, diarrhea, malnutrition, and suboptimal immune response and absorption of antiretroviral medications. Food insecurity can also lead to undernutrition and micronutrient deficiencies, which inhibit immune response and influence HIV disease progression. ¹² The mortality rates among malnourished exposed to pHIN1 virus infection are 3 times greater (RR = 3.07, 95% CI = 1.46-6.48) as compared with malnourished children not infected with pH1N1. ¹³

In the absence of research studies on dietary factors and EBV infection among children, direct comparison of the current study results with previous research is not feasible. However, based on findings from earlier studies, it can be concluded that nutrition plays an important role in immune system development and activation of various cells to fight infection. Malnutrition can lead to the suppression of the immune system and deactivation of cells from protecting the body from any foreign pathogens. ¹⁴

This study had several limitations. NHANES dietary questionnaire consists of participants having to recall various foods and beverages they consumed in the past 30 days. There is potential for misclassification bias to occur because some questions for dietary intake and food insecurity might not have captured the true exposure since the time frame for questioning was very small. In addition, no biological measure of dietary and food insecurity was used, which may have also resulted in misclassification of exposure. However, the misclassification of exposure is likely to be nondifferential resulting in dilution of the odds ratio. Since this study used cross-sectional data, there is a possibility of temporal bias and reverse causation that cannot be excluded. Confounding bias is minimized by controlling the confounders such as age, gender, race/ethnicity, family annual income, household size, and household smoking. However, there may be some residual confounding or confounding due to factors not included in NHANES and hence could not be controlled for.

Despite these limitations, the current study has several strengths. To the best of our knowledge, this is the first study that has evaluated the association of dietary factors and food insecurity with EBV infection among children. This study had a relatively large and racially diverse representative sample of children, which makes our results generalizable to all children in the United States. NHANES used an objective measure of EBV infection to identify EBV positive or negative individuals, which helps minimize any misclassification of the outcome. Last, the response rate of the 2009-2010 NHANES data set is 85% ⁷ for ages between 6 and 15 years, resulting in a low possibility for selection bias.

This study found a significant association between certain diets, food insecurity, and EBV infection in the unadjusted analyses only. The results are important with respect to promoting programs that help promote healthy eating and food security to enhance the immune system for the prevention of various viral infections. In the future, prospective cohort studies in lieu of cross-sectional studies are warranted to determine the long-term effects of exposures such as low dietary intake and food insecurity with EBV infection. Such studies would prove more advantageous in preventing the misclassification error due to self-report of exposure. Finally, additional research is needed to explore environmental factors and understand the underlying biological mechanism that may be at play between low dietary intake and food insecurity and EBV infection and could lead to more effective interventions to increase dietary intake and food security among adolescents.