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Hepatitis C virus in Mexican Americans: a population-based study reveals relatively high prevalence and negative association with diabetes

Published online by Cambridge University Press:  19 June 2015

G. P. WATT*
Affiliation:
School of Public Health, University of Texas Health Science Center at Houston, Brownsville Regional Campus, Brownsville, TX, USA
K. P. VATCHEVA
Affiliation:
School of Public Health, University of Texas Health Science Center at Houston, Brownsville Regional Campus, Brownsville, TX, USA
L. BERETTA
Affiliation:
Department of Molecular and Cellular Oncology, University of Texas MD Anderson Cancer Center, Houston, TX, USA
J. J. PAN
Affiliation:
Department of Internal Medicine, University of Texas Health Science Center at Houston Medical School, Houston, TX, USA
M. B. FALLON
Affiliation:
Department of Internal Medicine, University of Texas Health Science Center at Houston Medical School, Houston, TX, USA
J. B. McCORMICK
Affiliation:
School of Public Health, University of Texas Health Science Center at Houston, Brownsville Regional Campus, Brownsville, TX, USA
S. P. FISHER-HOCH
Affiliation:
School of Public Health, University of Texas Health Science Center at Houston, Brownsville Regional Campus, Brownsville, TX, USA
*
*Author for correspondence: Mr G. P. Watt, School of Public Health, University of Texas Health Science Center at Houston, Brownsville Regional Campus, 1 W. University Blvd, Brownsville, TX 78520, USA. (Email: [email protected])
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Summary

This study aimed to estimate the prevalence and risk factors for hepatitis C virus (HCV) infection in Mexican Americans living in South Texas. We tested plasma for the presence of HCV antibody from the Cameron County Hispanic Cohort (CCHC), a randomized, population-based cohort in an economically disadvantaged Mexican American community on the United States/Mexico border with high rates of chronic disease. A weighted prevalence of HCV antibody of 2·3% [n = 1131, 95% confidence interval (CI) 1·2–3·4] was found. Participants with diabetes had low rates of HCV antibody (0·4%, 95% CI 0·0–0·9) and logistic regression revealed a statistically significant negative association between HCV and diabetes (OR 0·20, 95% CI 0·05–0·77) after adjusting for sociodemographic and clinical factors. This conflicts with reported positive associations of diabetes and HCV infection. No classic risk factors were identified, but important differences between genders emerged in analysis. This population-based study of HCV in Mexican Americans suggests that national studies do not adequately describe the epidemiology of HCV in this border community and that unique risk factors may be involved.

Type
Original Papers
Copyright
Copyright © Cambridge University Press 2015 

INTRODUCTION

Hepatitis C virus (HCV) is one of the main causes of chronic viral hepatitis [Reference Guidotti and Chisari1]. Worldwide, the estimated prevalence of HCV is 2·2%, or about 130 million people [Reference Alter2]. In the United States, the prevalence has been decreasing since 1992, from 2·4% to ~1·6%, where it has remained relatively stable since 2006 [Reference Armstrong3, Reference Klevens4]. While the acute phase of HCV infection is not typically life-threatening, complications associated with chronic HCV – fibrosis, cirrhosis, and hepatocellular carcinoma – carry a poor prognosis and represent a significant societal and financial burden [Reference Colvin and Mitchell5Reference Seeff7].

Despite the identification of HCV over 25 years ago, data on HCV epidemiology in minority groups are sparse [Reference Kuniholm8]. It has been established, largely through the National Health and Nutrition Examination Survey (NHANES) that racial and ethnic disparities in HCV epidemiology exist, but little is known about prevalence in communities with the greatest health disparities, particularly those along the United States/Mexico border. Currently, passive surveillance of HCV infection is inadequate to estimate prevalence [9], so randomized population-based seroprevalence studies are a practical way to estimate the prevalence of HCV in particular communities in the United States .

To our knowledge, there are two data sources that have stratified HCV epidemiology in US Hispanics by ethnic subgroup. Kuniholm and co-workers used NHANES data to conduct stratified analysis of HCV epidemiology, comparing Mexican Americans to ‘other Hispanic’. These data suggest that Mexican American Hispanics may have a decreased risk of HCV compared with non-Mexican Hispanics [Reference Kuniholm8]. These data were supplemented using the Hispanic Community Health Study/Study of Latinos (HCHS/SOL), which recruited urban Hispanic/Latino participants from the Bronx, Miami, Chicago, and San Diego to participate in HCV research [Reference Kuniholm8]. They found that Hispanics constitute a strikingly heterogeneous group in HCV epidemiology, with anti-HCV prevalence in Mexican Americans [1·9%, 95% confidence interval (CI) 1·1–3·4] falling between the low prevalence seen in South American Hispanics (0·4%, 95% CI 0·1–1·9) and the high prevalence seen in Puerto Rican Hispanics (11·6%, 95% CI 9·4–14·1) [Reference Kuniholm8]. However, we have previously shown that national studies such as HCHS/SOL tend to underestimate the burden of disease in Mexican Americans in Cameron County, Texas [Reference Pan10, Reference Perez11], and we sought to validate national Mexican American HCV prevalence studies in a discrete, homogenous population of Mexican Americans with high rates of obesity, diabetes, and other chronic disease [Reference Fisher-Hoch12]. Further, since we have previously observed high rates of cirrhosis with no known aetiology in Cameron County [Reference Perez11], it is urgent to fully characterize the unique risk factors and causes of chronic liver disease in this Mexican American community on the United States–Mexico border.

METHODS

This study aimed to estimate the prevalence of, and determine the risk factors for, HCV in Mexican Americans in Cameron County, Texas, using data from a population-based cohort study, the Cameron County Hispanic Cohort (CCHC, n = 3300). This is a ‘Framingham-like’ cohort of a Mexican American community, recruited from households, active since 2004 [Reference Fisher-Hoch13]. Households are stratified by socioeconomic strata and randomly selected by census tract/block; all occupants aged ⩾18 years are invited to participate. Participants then visit our Clinical Research Unit, where extensive sociodemographic, clinical, and laboratory data are collected, and are followed-up at 5-year intervals [Reference Fisher-Hoch12]. In the present work, we designed a cross-sectional study of baseline data, accessing archived plasma samples from the CCHC. Plasma samples were selected sequentially, beginning with the first participant in the CCHC, thus preserving the two-stage sampling design.

We tested 1331 samples for the presence of hepatitis C Antibody (anti-HCV) using the ORTHO® HCV version 3.0 test system (Ortho-Clinical Diagnostics, USA). Plates were read in a Spectramax M5 spectrophotometer (Molecular Devices, USA) at a wavelength of 490 nm with a reference wavelength of 620 nm. Reactive and non-reactive results were determined according to the manufacturer's specifications. Results were then merged with the existing CCHC database for analysis.

Ethical standards

The study was approved by the Committee for the Protection of Human Subjects of the University of Texas Health Science Center at Houston as HSC-SPH-03-007-B.

The authors assert that all procedures contributing to this work comply with the ethical standards of the relevant national and institutional committees on human experimentation and with the Helsinki Declaration of 1975, as revised in 2008.

Definitions

Any participant with a positive HCV antibody assay was considered to be in the HCV group. In analysing diabetes mellitus (DM) results, ‘diabetes status’ was categorized into three groups in accordance with the American Diabetes Association's 2010 diagnostic criteria: normal, impaired fasting glucose (hereafter ‘pre-diabetes’) and diabetic (hereafter, ‘DM’) [14]. We considered participants to have a history of smoking if they had smoked more than 100 cigarettes in their life, and considered ‘alcohol consumption’ to be any participant that drinks at least occasionally (compared to not at all). Finally, when discussing liver function tests (LFTs), we refer only to alanine transaminase (ALT) and aspartate aminotransferase (AST) levels.

Statistical methods

We conducted design-based analyses using age- and gender-adjusted sampling weights to scale the sample to the population and also accounted for the potential clustering effect in participants from the same household. For descriptive purposes of the sample, categorical variables for demographic and clinical characteristics were summarized in unweighted frequencies and weighted percentages, and continuous variables for demographic and clinical characteristics were summarized using weighted means and their standard errors. Of participants with HCV, we counted the number who reported taking any of the commonly prescribed anti-HCV medications in the United States and Mexico (peginterferon, ribavirin, and protease inhibitors, or any of their marketed names – including generics – in English and Spanish). Design-adjusted, weighted prevalence of HCV was calculated and analyses were conducted for various risk factors (1) in the entire sample and (2) in the sample stratified by gender. The Rao-Scott design-adjusted χ 2 test was used to test for equality of proportions across the risk factors groups. Odds ratios (ORs) with 95% Wald confidence limits were reported for dichotomous categorical variables, and P values were reported for non-dichotomous categorical variables. Univariable survey-weighted logistic regression analyses were performed to assess the effects of continuous variables on presence of HCV antibody.

Multivariable survey-weighted logistic regression analyses were performed to assess the independent effects of risk factors on HCV antibody detection, selected from the univariable analysis with moderate (P < 0·10) association, in addition to demographic variables classically associated with HCV infection: age, gender, socioeconomic indicators, and smoking and drinking history. Harmful multicollinearity effects between the independent variables of interest in the survey-weighted logistic regression multivariable model were not observed (variance inflation factor < 1·5). Two-way multiplicative scale interaction effect between the independent variables were tested by including their product terms in the regression model and evaluating the Wald χ 2 test statistics of their coefficient estimates. A two-sided test with P < 0·05 was considered significant for all analyses. The survey-weighted logistic regression model fit was evaluated with F-adjusted mean residual goodness-of-fit test using Stata v. 13 software (StataCorp LP, USA). All other weighted analyses were conducted using SAS v. 9·4 (SAS Institute Inc., USA).

RESULTS

We tested a sample of the CCHC consisting of 1331 subjects for the presence of anti-HCV. Their average age was 48·7 years, and 40·7% were male. The sample did not differ significantly in age or gender from the cohort from which it was sampled. The majority (61·2%) were born in Mexico, 50·6% were overweight or obese, 26·3% had diabetes, and 31·2% had abnormal LFTs (Table 1). Nearly half (46·8%) of those with diabetes had not been previously diagnosed (data not shown).

Table 1. Descriptive statistics for selected categorical and continuous variables, Cameron County Hispanic Cohort (2004–2012)

LFT, Liver function test; s.e., standard error.

a All frequencies reflect unweighted data.

b All percentages reflect weighted data.

c Includes any type of public or private health coverage.

d Defined as body mass index ⩾30.

e According to the 2010 diagnostic criteria of the American Diabetes Association.

f Defined as abnormal alanine transaminase or abnormal aspartate aminotransferase levels.

g Weighted mean.

Thirty out of 1331 participants’ plasma tested positive for anti-HCV. This generated a weighted prevalence of 2·3% (95% CI 1·2–3·4).

A range of sociodemographic variables were tested for univariable association with HCV. Variables for gender, age, income, education level, nativity, and socioeconomic status had no significant association with HCV. Similarly, proxies for risky behaviour (smoking history and alcohol consumption) did not yield significant associations.

In univariable analyses of clinical and biological variables, there was a significant association between the three categories of diabetes status (normal, pre-diabetes, DM) and HCV (P < 0·005). The HCV rate was 0·4% (95% CI 0·0–0·9) in participants with DM, 4·0% (95% CI 1·6–6·6) in participants with pre-diabetes, and 1·1% (95% CI 0·02–2·2) in normal participants. Elevated ALT and AST levels were significantly associated with HCV (OR 1·02, 95% CI 1·00–1·03; OR 1·03, 95% CI 1·01–1·05, respectively) (Table 2). None of the participants with HCV reported taking any anti-HCV medication, and only 4/30 (12·2%, 95% CI 5·3–18·1) participants with HCV reported any history of viral hepatitis.

Table 2. Weighted univariable analysis of HCV by categorical and continuous variables, Cameron County Hispanic Cohort (2004–2012)

OR, Odds ratio; CI, confidence interval; BMI, body mass index; ALT, alanine transaminase; AST, aspartate aminotransferase; s.e., standard error.

a All percentages weighted.

b According to the 2010 diagnostic criteria of the American Diabetes Association.

c Includes any type of public or private health coverage.

d Defined as ever having smoked more than 100 cigarettes.

e Continuous variable: mean (s.e.) and OR (95% Wald CI) estimates are given.

* Statistically significant with P < 0·05.

In gender-stratified univariable analysis, increased age was associated with HCV in females (OR 1·04, 95% 1·01–1·06), but not in males. The average age of women with HCV was significantly higher than the average age of men with HCV (57·4 vs. 44·5, P < 0·005). Further, there was a significant association between diabetes classification and HCV in females (P < 0·005), with an HCV prevalence of 0·6% (95% CI 0–1·3) in participants with DM, 4·4% (95% CI 1·5–7·3) in participants with pre-diabetes, and 1·1% (95% CI 0·02–2·2) in normal participants. The association was not significant in males (P = 0·1765). A history of smoking was significantly associated with HCV in males (OR 5·3, 95% CI 1·1–25·1), but not in females. Alcohol consumption in males had a significant positive association with HCV (OR 15·2, 95% CI 1·8–130·5), and a significant negative association with HCV in females (OR 0·2, 95% CI 0·1–0·7). Finally, ALT and AST levels were associated with HCV in females (OR 1·03, 95% CI 1·01–1·05; OR 1·05, 95% CI 1·02–1·07, respectively), but not in males (Table 3).

Table 3. Weighted univariable analysis of HCV by categorical and continuous variables, stratified by gender, Cameron County Hispanic Cohort (2004–2012)

OR, Odds ratio; CI, confidence interval; SES, socioeconomic status; BMI, body mass index; ALT, alanine transaminase; AST, aspartate aminotransferase; s.e., standard error.

a All percentages weighted.

b According to the 2010 diagnostic criteria of the American Diabetes Association.

c Includes any type of public or private health insurance.

d Defined as ever having smoked more than 100 cigarettes.

e Continuous variable: mean (s.e.) and OR (95% Wald CI) estimates are given.

* Statistically significant with P < 0·05.

In the regression analysis, DM (compared to ‘normal’) was independently negatively associated with HCV (OR 0·20, 95% CI 0·05–0·77) after controlling for age, gender, socioeconomic quartile, employment status, obesity, ALT and AST levels, and smoking and drinking history. Pre-diabetes was not significantly associated with HCV (compared to ‘normal’). No other significant effects emerged in the model, and no interaction effects were found to contribute significantly to the fit of the model (Table 4). As an alternative analysis, we ran the same regression, but used DM as the reference value instead of ‘normal’. Here, pre-diabetes (compared to DM) was significantly positively associated with HCV (OR 8·93, 95% CI 2·48–32·15), as was ‘normal’ (compared to DM) (OR 5·30, 95% CI 1·30–21·54) (data not shown).

Table 4. Multivariable logistic regression analysis of predictors of anti-HCV in serum, Cameron County Hispanic Cohort (2004–2012)

OR, Odds ratio; CI, confidence interval; SES, socioeconomic status; ALT, alanine aminotransferase; AST, aspartate transaminase.

a Continuous variable.

b Defined as body mass index ⩾30.

c Defined as ever having smoked more than 100 cigarettes.

d According to the 2010 diagnostic criteria of the American Diabetes Association.

e Compared to non-diabetic, non-impaired fasting glucose.

f According to the 2010 criteria of the American Diabetes Association, definition for ‘impaired fasting glucose’.

* Statistically significant with P < 0·05.

DISCUSSION

The Centers for Disease Control and Prevention (CDC) estimated that there were 16 000 new cases of HCV in the United States in 2009 [15], most of which will go undiagnosed and many of which will progress to chronic infection. Klevens and co-workers consider injection drug users to be the ‘center of the current hepatitis C epidemic’ [Reference Klevens4]. There are few data on injection drug use in the United States/Mexico border region, although one population-based study showed that the lifetime prevalence of injection drug use is low (1·0%) in Cameron County [Reference Wallisch and Spence16].

The prevalence of HCV in this population (2·3%) is similar to the national population-based rate found in Mexican Americans in NHANES (2·1%) and HCHC/SOL (1·9%) [Reference Kuniholm8]. However, this community differs from previous studies of HCV in Mexican Americans. First, the region is dominated by the Brownsville metropolitan area (population 400 000, 85% Mexican American), a network of small cities and towns on the United States–Mexico border, considered among the poorest in the United States [Reference Clark1719]. As such, this is not a scattered urban population sample like that in HCHC/SOL, but rather a single non-urban population. It is also tightly integrated with Matamoros, Tamaulipas, Mexico, so it was important to consider the prevalence of HCV in northern Mexico. It is thought that the nationwide prevalence of HCV in Mexico is lower (1·0–1·4) than in the United States [Reference Kershenobich20, Reference Valdespino21], but that the northern Mexican states have a slightly higher rate at 1·7% [Reference Burguete-García22]. It therefore appears that the rate of HCV in Cameron County is slightly higher than the rate in northern Mexico, and similar to that of Mexican Americans in the United States.

We have previously quantified poor health outcomes and high rates of undiagnosed chronic disease in Cameron County. For instance, the prevalence of DM is 30·7% (49·7% undiagnosed), hypercholesterolaemia, 48·2% (48·7% undiagnosed) and hypertension, 30·5% (16% undiagnosed) [Reference Fisher-Hoch12]. In the present study, at least 87·8% of those with HCV had no known history of viral hepatitis. For comparison, current national estimates suggest that between 50% and 75% of those infected with HCV are unaware of their infection [Reference Coffin23]. This suggests that HCV may be more often undiagnosed, and therefore untreated, in Cameron County than in the rest of the country. This is not surprising, considering 65·1% of the CCHC has no insurance of any kind, and the rates of undiagnosed chronic disease are high [Reference Pan10Reference Fisher-Hoch12].

It is surprising that certain risk factors seen in previous HCV studies did not emerge in this work. We hypothesized that the risk factors seen in HCHS/SOL (male gender and US nativity, for instance) would present in our data, but there were no significant associations with these variables. In gender-stratified analysis, there were several associations – marital status, age, ALT levels, and AST levels – that emerged only in females. This is partially attributable to the low unweighted sample size of males (n = 393), which limited statistical power for gender-stratified tests. It also suggests that significant epidemiological differences between men and women in this cohort exist. For example, the proportion of male participants with abnormal LFTs is significantly higher than the proportion of female participants with abnormal LFTs (38·6% vs. 26·1%, P < 0·005).

Most marked, however, was the strong negative association between DM and HCV. As shown, the prevalence of HCV was highest in those with pre-diabetes, and lowest in those with DM. While we do not propose that diabetes is protective, per se, for HCV in this population, our results do indicate a negative association between HCV and DM, even after controlling for a variety of sociodemographic and clinical factors. There is considerable controversy surrounding this relationship, as many researchers have previously found positive associations between DM and HCV. There is both epidemiological [Reference Antonelli24, Reference Knobler25] and direct experimental evidence [Reference Shintani26] that suggests that DM may predispose HCV infection, and that HCV might play a role in the progression of DM, although these interactions have been contested [Reference Mangia27, Reference Ruhl28]. In one systematic review of this association, researchers found 45 out of 46 studies proposed a positive association between DM and HCV [Reference Mhatre29].  On the other hand, there are two studies that report a result of low prevalence of HCV in diabetics [Reference Mangia27, Reference Adegoke30], although these studies were not population-based and do not account for ascertainment bias. More recently, Ruhl and co-workers, using NHANES data, were unable to demonstrate a relationship between DM and HCV [Reference Ruhl28]. Instead, the authors suggest that elevated liver enzymes had a non-negligible effect on the association between DM and HCV [Reference Ruhl28]. In the present work, we have shown that DM is independently negatively associated with HCV even when controlling for ALT and AST. The widely varying prevalence of HCV in the three categories of DM, and the result of an independent effect of DM status on HCV in multivariable regression modelling, together suggest an important association in this population. The literature on this association, however, especially the recent work by Ruhl and co-workers using NHANES, urges caution in interpreting these findings, and further study is needed to examine the effect of liver enzymes on this association.

Additionally, there are important differences between the CCHC and NHANES, although both are population-based cohort studies. CCHC is an ethnically homogenous study population, which allows for detailed analysis of Mexican Americans in particular, whereas NHANES samples from a heterogeneous national population. Other distinctions between this study and the recent NHANES work are that the prevalence of diabetes is much higher in this cohort (26·8% vs. 10·5%), and this study is community-based, rather than national. These differences, especially the much higher prevalence of diabetes in Cameron County, allow for the possibility of a DM–HCV association that is present in this community but not detectable at the national level.

The high rate of HCV in those with pre-diabetes (4·0%) is cause for some concern. Obesity, insulin resistance, and diabetes are associated with a more rapid progression of fibrosis in HCV-infected individuals [Reference Hourigan31Reference Ratziu33]. Higher levels of insulin resistance are also associated with a poorer response to antiviral therapy for HCV [Reference D'souza, Sabin and Foster34]. Moreover, because this community suffers high rates of insulin resistance [Reference Qu35], diabetes, obesity, and all-cause liver disease, it may be prudent to incorporate HCV screening efforts into pre-diabetes and DM education and outreach already in place.

Finally, there are some limitations to this study. This cohort does not contain data on risky behavior (such as illicit drug use, risky sexual practices, tattoos, or unhygienic medical procedures), which are often significant in HCV epidemiology. Despite this, the CCHC provides the only available large population-based data on community-dwelling Mexican Americans in the country, and the present study has effectively shown that the epidemiology of HCV in this population differs from that of existing national studies. Second, an anti-HCV assay does not provide data on the burden of active disease, and as such the burden of acute or chronic HCV remains unknown in this region. Using an HCV antibody test, however, allowed us to compare prevalence estimates with other studies, like NHANES and HCHS/SOL, which also used anti-HCV to estimate prevalence.

In conclusion, this study may be seen as preliminary work in understanding the unique epidemiology of HCV in a border-dwelling Mexican American community with severe health disparities. Our results – particularly the low prevalence of HCV in participants with diabetes, despite overall elevated prevalence of HCV and rampant diabetes – contrast with a large body of previous work. Moving forward, it will be important to: (1) explore risk factors for HCV exposure unique to Cameron County, and (2) determine the genotype and seroprevalence of HCV RNA, in order to characterize the burden of active disease in this community. We have shown, much like previous studies, that diabetes is an important consideration in the epidemiology of HCV. In a Mexican American population with high prevalence of diabetes, obesity, and non-alcoholic liver disease, it is critical to characterize any factors, such as chronic viral hepatitis, that might further insult the health of the liver.

ACKNOWLEDGEMENTS

We thank our cohort team, particularly Rocío Uribe and her team, who recruited and documented the participants. We also thank Pablo Sánchez and Israel Hernández for data management, Marcela Morris and other laboratory staff for their contributions, and Christina Villarreal for administrative support. We thank the Valley Baptist Medical Center in Brownsville for housing our Clinical Research Unit.

This work was supported by the Center for Clinical and Translational Sciences, which is funded by National Institutes of Health Clinical and Translational Award UL1 TR000371 from the National Center for Advancing Translational Sciences. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Center for Advancing Translational Sciences or the National Institutes of Health.

DECLARATION OF INTEREST

None.

References

REFERENCES

1. Guidotti, LG, Chisari, FV. Immunobiology and pathogenesis of viral hepatitis. Annual Review of Pathology: Mechanisms of Disease 2006; 1: 2361.Google Scholar
2. Alter, M. Epidemiology of hepatitis C virus infection. World Journal of Gastroenterology 2007; 13: 24362441.CrossRefGoogle ScholarPubMed
3. Armstrong, GL, et al. The prevalence of hepatitis C vrus infection in the united states, 1999 through 2002. Annals of Internal Medicine 2006; 144: 705–W162.Google Scholar
4. Klevens, RM, et al. Evolving epidemiology of hepatitis C virus in the United States. Clinical Infectious Disease 2012; 55 (Suppl. 1): S3S9.Google Scholar
5. Colvin, HM, Mitchell, AE (eds). Hepatitis and Liver Cancer: A National Strategy for Prevention and Control of Hepatitis B and C. Washington, DC: National Academies Press, 2010, pp. 232.Google Scholar
6. Hoofnagle, JH. Course and outcome of hepatitis C. Hepatology 2002; 36: S21S29.Google ScholarPubMed
7. Seeff, LB. Natural history of chronic hepatitis C. Hepatology 2002; 36: S35S46.Google Scholar
8. Kuniholm, MH, et al. Prevalence of hepatitis C virus infection in US Hispanic/Latino adults: results from the NHANES 2007–2010 and HCHS/SOL Studies. Journal of Infectious Diseases 2014; 209: 15851590.Google Scholar
9. Centers for Disease Control and Prevention. Surveillance for viral hepatitis – United States, 2011. Division of Viral Hepatitis (http://www.cdc.gov/hepatitis/Statistics/2011Surveillance/Commentary.htm).Google Scholar
10. Pan, J-J, et al. Prevalence of metabolic syndrome and risks of abnormal serum alanine aminotransferase in Hispanics: A population-based study. PLoS ONE 2011; 6: e21515.CrossRefGoogle ScholarPubMed
11. Perez, A, et al. High frequency of chronic end-stage liver disease and hepatocellular carcinoma in a Hispanic population. Journal of Gastroenterology and Hepatology 2004; 19: 289295.Google Scholar
12. Fisher-Hoch, SP, et al. Socioeconomic status and prevalence of obesity and diabetes in a Mexican American community, Cameron County, Texas, 2004–2007. Preventing Chronic Disease 2010; 7: A53.Google Scholar
13. Fisher-Hoch, SP, et al. Missed opportunities for diagnosis and treatment of diabetes, hypertension, and hypercholesterolemia in a Mexican American population, Cameron County Hispanic Cohort, 2003–2008. Preventing Chronic Disease 2012; 9 (E135).Google Scholar
14. American Diabetes Association. Diagnosis and classification of diabetes mellitus. Diabetes Care 2010; 33 (Suppl. 1): S62S69.Google Scholar
15. Centers for Disease Control and Prevention. Surveillance data for acute viral hepatitis – United States, 2009. Viral hepatitis statistics and surveillance, 2012 (http://www.cdc.gov/hepatitis/Statistics/2009Surveillance/index.htm).Google Scholar
16. Wallisch, LS, Spence, RT. Alcohol and drug use, abuse, and dependence in urban areas and colonias of the Texas-Mexico border. Hispanic Journal of Behavioral Science 2006; 28: 286307.Google Scholar
17. Clark, S. Census Bureau: Brownsville poorest city in U.S. Brownsville Herald. Brownsville, TX, 7 November 2013 (http://www.brownsvilleherald.com/news/local/article_b630f374-475c-11e3-a86e-001a4bcf6878.html).Google Scholar
18. Sauter, AEMH, Frohlich, TC, Michael, B. America's richest (and poorest) cities. 24/7 Wall Street, 2013 (http://247wallst.com/special-report/2013/10/24/americas-the-richest-and-poorest-cities/).Google Scholar
19. US Census Bureau. Brownsville, Texas. State and county quick facts, 2014 (http://quickfacts.census.gov/qfd/states/48/4810768.html).Google Scholar
20. Kershenobich, D, et al. Trends and projections of hepatitis C virus epidemiology in Latin America. Liver International 2011; 31: 1829.Google Scholar
21. Valdespino, JL, et al. Seroprevalence of hepatitis C in Mexican adults: an emerging public health problem? Salud Pública de México 2007; 49: S395S403.CrossRefGoogle Scholar
22. Burguete-García, AI, et al. Hepatitis C seroprevalence and correlation between viral load and viral genotype among primary care clients in Mexico. Salud Pública de México 2011; 53: 712.Google Scholar
23. Coffin, PO, et al. Cost-effectiveness and population outcomes of general population screening for hepatitis C. Clinical Infectious Diseases 2012; 54: 12591271.Google Scholar
24. Antonelli, A, et al. Hepatitis C virus infection evidence for an association with type 2 diabetes. Diabetes Care 2005; 28: 25482550.Google Scholar
25. Knobler, H, et al. Increased risk of type 2 diabetes in noncirrhotic patients with chronic hepatitis C virus Infection. Mayo Clinic Proceedings 2000; 75: 355359.Google Scholar
26. Shintani, Y, et al. Hepatitis C virus infection and diabetes: direct involvement of the virus in the development of insulin resistance. Gastroenterology 2004; 126: 840848.Google Scholar
27. Mangia, A, et al. HCV and diabetes mellitus: evidence for a negative association. American Journal of Gastroenterology 1998; 93: 23632367.CrossRefGoogle ScholarPubMed
28. Ruhl, CE, et al. Relationship of hepatitis C virus infection with diabetes in the U.S. population. Hepatology 2014; 60: 11391149.Google Scholar
29. Mhatre, A. The association between diabetes and hepatitis C: a systematic review of epidemiological evidence (dissertation). Ann Arbor, United States, 2008, 40 pp.Google Scholar
30. Adegoke, OA, et al. Seroprevalence of hepatitis C virus infection in Nigerians with type 2 diabetes mellitus. Nigerian Journal of Clinical Practice 2008; 11: 199201.Google ScholarPubMed
31. Hourigan, LF, et al. Fibrosis in chronic hepatitis C correlates significantly with body mass index and steatosis. Hepatology 1999; 29: 12151219.Google Scholar
32. Hui, JM, et al. Insulin resistance is associated with chronic hepatitis C and virus infection fibrosis progression. Gastroenterology 2003; 125: 16951704.Google Scholar
33. Ratziu, V, et al. Fibrogenic impact of high serum glucose in chronic hepatitis C. Journal of Hepatology 2003; 39: 10491055.Google Scholar
34. D'souza, R, Sabin, C, Foster, GR. Insulin resistance plays a significant role in liver fibrosis in chronic hepatitis C and in the response to antiviral therapy. American Journal of Gastroenterology. 2005; 100: 15091515.Google Scholar
35. Qu, H-Q, et al. The definition of insulin resistance using HOMA-IR for Americans of Mexican Descent using machine learning. PLoS ONE 2011; 6: e21041.Google Scholar
Figure 0

Table 1. Descriptive statistics for selected categorical and continuous variables, Cameron County Hispanic Cohort (2004–2012)

Figure 1

Table 2. Weighted univariable analysis of HCV by categorical and continuous variables, Cameron County Hispanic Cohort (2004–2012)

Figure 2

Table 3. Weighted univariable analysis of HCV by categorical and continuous variables, stratified by gender, Cameron County Hispanic Cohort (2004–2012)

Figure 3

Table 4. Multivariable logistic regression analysis of predictors of anti-HCV in serum, Cameron County Hispanic Cohort (2004–2012)