Skip to main content
NCBI home page
NIHPA Author Manuscripts logoLink to NIHPA Author Manuscripts
. Author manuscript; available in PMC: 2018 Jun 8.
Published in final edited form as: Rural Ment Health. 2017 Jun 8;41(2):152–161. doi: 10.1037/rmh0000067

Correlates of Risky Alcohol Use Among Women from Appalachian Ohio

Golfo K Tzilos 1, Erinn M Hade 2, Mack T Ruffin 1, Electra D Paskett 3
PMCID: PMC5659387  NIHMSID: NIHMS870641  PMID: 29085525

Abstract

Women from Appalachian regions of the United States (US) face a number of health related disparities, including mental health and substance misuse. Alcohol misuse is a significant public health concern among women in the US, associated with numerous adverse consequences for the woman, her unborn children, and any children in her care, yet data on correlates of risky alcohol use is limited among women from Appalachian Ohio. The current study examines the prevalence and predictors of risky alcohol use (e.g., heavy episodic drinking) in 2,349 women from 18 clinics in the Community Awareness Resources and Education I (CARE I) study in Appalachian Ohio. Alcohol use history was collected over the past 30 days. Regression models were employed to identify predictors of heavy episodic drinking. Results indicate that 20% of the current sample reported heavy episodic drinking. Being an emerging adult (18–26), single, a current smoker, and reporting a history of four or more partners were independently associated with heavy episodic drinking. Self-identifying as Appalachian was not protective or predictive of heavy episodic drinking. Further research identifying risk factors and enhancing protective factors will inform culturally competent preventive efforts, particularly for emerging adult women from Appalachian Ohio at risk for alcohol misuse and associated morbidities.

Keywords: Women, Appalachia, alcohol use, behavioral health, primary care

Compared to women living in urban areas, women that reside in rural areas of the United States face multiple health concerns, including substance use disparities, and often at greater rates (Short, Oza-Frank, & Conrey, 2012; Weaver, Himle, Taylor, Matusko, & Abelson, 2015). These differences in prevalence have been attributed to a number of individual-level (e.g., low income status, low education, marital status) and regional-level factors (e.g., lack of access to health care facilities and to affordable health coverage) exhibited by rural women, including women from Appalachian Ohio, as this region is primarily rural (Short et al., 2012). Drug use, including illicit (e.g., heroin use) and nonmedical use of prescription drugs (e.g., pain relievers), is a growing problem in Appalachian regions, leading to a staggering number of overdose deaths (Becker, 2016; Winstanley et al., 2012). Increases in opiate and synthetic drug use are higher in this region than in other areas across the nation (Substance Abuse and Mental Health Services Administration [SAMHSA], 2014). Cigarette smoking rates also are higher among Appalachian women compared to non-Appalachian women (Zhang et al., 2008). Simply, health disparities between Appalachian and non-Appalachian women are apparent across a range of factors.

Risky Alcohol Use in Women

Alcohol misuse and associated morbidities represent significant health challenges for women and are an important public health concern. Women are more likely than men to develop specific health conditions as a direct result of their alcohol use, including an increased risk of alcoholic liver disease, alcohol-induced brain damage, alcohol-related heart disease, and breast cancer (National Institute on Alcohol Abuse and Alcoholism [NIAAA], 2015). Risky alcohol use includes heavy episodic drinking (also referred to as binge drinking), which is defined as four or more drinks in a row for women, and is prevalent, particularly among childbearing women (aged 18–44 years; SAMHSA, 2016). In a national survey, approximately 12% of adult women nationally report heavy episodic drinking 3 times a month (Centers for Disease Control and Prevention [CDC], 2016). Moreover, 5.7 million adult women – 4.6% of all adult women – in the United States reported having an alcohol use disorder (SAMHSA, 2014).

Childbearing women are a particularly vulnerable group as the health consequences associated with their alcohol use also can affect unborn children or children already in their care. Alcohol use during pregnancy can result in a number of adverse health outcomes for both the mother and infant, including Fetal Alcohol Spectrum Disorders (FASD), a group of conditions that can occur in an infant whose mother used alcohol during pregnancy (CDC, 2015). Heavy episodic drinking also is associated with risky sexual behavior in women, including sexual intercourse at a young age, having multiple partners, and having a partner who has been treated for a sexually transmitted infection (STI) (CDC, 2015). For example, in a study of 671 treatment-seeking individuals, of whom 349 were female, women who reported heavy episodic drinking were twice as likely to have multiple sex partners as nondrinking women (Hutton, McCaul, Santora, & Erbelding, 2008). Moreover, risky sex increases the likelihood of contracting an STI, having an unwanted pregnancy, and risk of cervical cancer (Reiter, Katz, Ferketich, Ruffin, & Paskett, 2009).

Alcohol continues to be the most prevalent and widely used and abused substance among Appalachian adults (CDC, 2013). Sixty one percent of Appalachian adults reported alcohol use in the past year, and 20.6% reported heavy episodic drinking (Zhang et al., 2008). Although these rates are lower than those reported by adults nationally (61.0% vs. 70.2%), risky alcohol use has implications for a number of health outcomes and warrants further study. It also is reported to be the primary reason for seeking substance abuse treatment in the Appalachian region, surpassing drug abuse (CDC, 2013; Zhang et al., 2008).

Despite the prevalence and significance of the problem, there are surprisingly few empirical studies examining risky alcohol use among women from Appalachian regions specifically, with these yielding mixed findings. A study of 298 smokers from Appalachian Ohio (67% female) found that a significant proportion, 59.4% of the sample, reported heavy episodic drinking in the past two weeks (Davison, Shoben, Pasch, & Klein, 2016). Examination of a national sample of women found that heavy episodic drinking was less prevalent among Appalachian compared to non-Appalachian women (Short et al., 2012), and that it was more common among women with higher economic status. Additional research focused on rural populations has found that alcohol use is more common among those with lower economic status. Reports that include a younger demographic suggest that underage drinking is a significant problem in rural areas (Van Gundy, 2006). Adolescent girls from Appalachian regions report heavier rates of alcohol use compared to their non-Appalachian peers (2.9% vs. 2.5%; Zhang et al., 2008). Indeed, younger women are significantly more likely than their older counterparts to engage in unhealthy behaviors, including heavy episodic drinking. Marital status has been implicated in women’s alcohol use behavior, but with mixed results, as both reductions and increases in alcohol use have been reported for married women (Bachman, Wadsworth, O’Malley, Johnston, & Schulenberg, 1997; Reczek, Pudrovska, Carr, Umberson, & Thomeer, 2016). On balance, demographic and socioeconomic factors may be associated with alcohol use among women from Appalachian regions.

Appalachian Identity

Ethnic self-identity refers to the extent to which an individual identifies with a particular ethnic group and feels a sense of belonging (Phinney, 1990). Identifying oneself with a particular ethnicity has been shown in the literature to have positive effects on various health behaviors. For example, in studies of African Americans and Mexican Americans, ethnic self-identity levels were associated with substance use, including reduction in risky alcohol use (Caldwell, Sellers, Bernat, & Zimmerman, 2004; Herd & Grube, 1996; Love, Yin, Codina, & Zapata, 2006). Moreover, greater endorsement of self-identity has been associated with increases in self-esteem, psychological well being, and physical activity (Hovick & Holt, 2016; Shrake & Rhee, 2004; Umana-Taylor & Updegraff, 2007). In previous work, we examined Appalachian self-identity in a sample of 571 women from Appalachian Ohio who completed the baseline survey in the CARE study (Reiter et al., 2009), and found the prevalence of Appalachian self-identity to be 35.2%, higher than what has been reported in previous studies. Women who endorsed being associated with religion, family, and community were more likely to self-identify as Appalachian, as were women who lived in a rural county. The literature on rural communities suggests that these women typically exhibit a pattern of stable and close relationships and community, which may be a protective factor in treatment and recovery (Van Gundy, 2006).

Given previous reports of the positive effects of self-identity on health behaviors including alcohol use, we studied the role of Appalachian self-identity as it relates to heavy episodic drinking. The aims of the current study were to examine the prevalence and correlates of risky alcohol use (defined as heavy episodic drinking) among a cohort of women from Appalachian Ohio who were seeking primary care. Further, we aimed to explore the association between heavy episodic drinking and Appalachian self-identity. Based on previous literature, our demographic and behavioral variables of interest included age, marital status, number of partners, and cigarette smoking. We hypothesized that risky alcohol use would be associated with women who were younger in age, endorsed smoking, and had a greater number of sex partners. Furthermore, we hypothesized that women who self-identified as Appalachian would report less heavy episodic drinking compared to women who did not identify as Appalachian. Finally, we aimed to explore whether the risk associated with Appalachian self-identity was modified by age, education, marital status, smoking status or number of sexual partners.

Methods

The current study was approved by the Institutional Review Boards at Ohio State University, the University of Michigan, and the Centers for Disease Control and Prevention (CDC) and utilized data from the Community Awareness, Resources, and Education I (CARE I) Project on abnormal cervical cytology, described in great detail elsewhere (Reiter et al., 2009). The goal of the CARE I Study was to investigate the interaction of environment, societal, behavioral, and biological mechanisms as they contribute to understanding of the causes and prevention of cervical cancer in Appalachian Ohio. In the current study, we report on data collected from one of the CARE I projects that investigated determinants of abnormal cervical cytology.

Participants

Between 2006 and 2008, study participants were recruited from 18 health clinics, representing 14 counties throughout Appalachian Ohio into one of the CARE I projects focused on studying determinants of abnormal cervical cytology (CARE I, P3). In order to obtain a representative sample of women from Appalachian Ohio, counties were grouped into four regions. Each county was classified as either urban or rural (using U.S. Census Bureau definitions) and within each region, two urban and two rural counties were selected and clinics were identified within the sampled counties (Northeast, East Central, Southeast, and Southwest). Counties in each region were selected with probability proportional to the estimated average annual numbers of cervical cancer cases in each county from 1998–2000. Eligibility criteria included: women at least 18 years old, resident of an Appalachian Ohio county, not pregnant, seen in a participating clinic within the last two years, and no history of hysterectomy or invasive cervical cancer. Women who were eligible were invited to participate in the CARE I, P3 during a scheduled Pap smear at one of the study clinics. Women were recruited by study nurses, signed informed consent, completed a short self-administered questionnaire, and provided lab work (blood and saliva samples). The primary design of the original CARE I, P3 on abnormal cervical cytology was to evaluate a case-control study, where cases (patients with abnormal cytology) and controls (those without abnormal cytology) were selected in a ratio of 1:3. These participants underwent further interviews, beyond the baseline assessment. In the current analysis, we utilize data from all women recruited into this project (i.e., all women with normal and abnormal cytology).

A total of 6,029 women were screened for the present study. Of those screened, 1,977 did not meet eligibility criteria. Of those who were eligible, 1,016 refused participation, and 614 were not approached. Of the 2,393 women who were eligible and recruited into the project, 2,349 had available information on alcohol use and relevant covariates.

Measures

All variables of interest were measured by self-report assessment completed at baseline. The outcome of interest was defined as heavy episodic drinking (binge drinking), a widely used screening question defined by the SAMHSA as 5 or more drinks on the same occasion on at least one day in the past 30 days. Specifically, participants were asked, “Thinking about all types of alcoholic beverages (beer, wine, wine coolers, mixed drinks and liquor), did you have 5 or more drinks on one occasion during the past month?” The baseline assessment contained questions with good validity and reliability regarding demographics, including age, race, education, employment, marital status, Pap smear test history, reproductive health, including the number of times a participant had been pregnant, and sexual activity, including the number of lifetime male partners, as well as alcohol and tobacco use, and which region of Appalachia Ohio participants reside. Appalachian self-identity was measured by the question, “Do you consider yourself to be Appalachian?” with response options of “Yes,” “No,” or “Don’t know.” This same method was used in our previous work (Reiter et al., 2009).

Statistical Methods

Modified Poisson regression models were employed to find the best predictors of heavy episodic drinking (Lumley, Kronmal, & Ma, 2006; Zou, 2004). These models estimate the adjusted relative risk (aRR) of heavy episodic drinking for each associated covariate. The relationship between each predictor of interest and heavy episodic drinking (Table 1) was estimated. Multivariable models both with and without Appalachian self-identity were developed (Table 2). Final model covariates were considered for inclusion from evidence in previous literature and from observed associations in the current data. A priori interaction terms of age, education level, marital status, smoking status, and number of partners with Appalachian identity were added to the model and tested. Analyses and data management were performed in Stata 13.0 (StataCorp, 2013) and SAS software (Version 9.3 of the SAS System for Windows). All reported p-values and confidence intervals are two sided and unadjusted for multiple comparisons.

Table 1.

Characteristics of Participants and Associations with Heavy Episodic Drinking

Heavy Episodic Drinking (n = 468) No Heavy Episodic Drinking (n = 1881) Total (n = 2349) Relative Risk (95% CI)
Age 29.5 (10.3) 37.8 (13.9) 36.2 (13.7) 0.65 (0.60, 0.70)a
Mean (SD)
 18–21 115 (30.8) 258 (69.2) 373 7.00 (4.35, 11.28)
 >21–26 143 (34.3) 274 (65.7) 417 7.79 (4.87, 12.48)
 >26–30 45 (21.2) 167 (78.8) 212 4.82 (2.86, 8.12)
 >30–35 43 (17.6) 201 (82.4) 244 4.00 (2.36, 6.78)
 >35–40 38 (15.5) 208 (84.6) 246 3.51 (2.05, 6.01)
 >40–45 32 (14.0) 197 (86.0) 229 3.18 (1.82, 5.53)
 >45–50 34 (15.5) 185 (84.5) 219 3.53 (1.82, 5.53)
 >50 18 (4.4) 391 (95.6) 409 1.0
Race/Ethnicity
 White non-Hispanic 434 (19.5) 1796 (80.5) 2230 1.0
 Other 25 (26.3) 70 (73.7) 95 1.35 (0.96, 1.91)
Education
 Less than high school 34 (13.7) 215 (86.4) 249 1.0
 High school diploma 167 (20.6 643 (79.4) 810 1.51 (1.07, 2.12)
 Some technical training or college 236 (22.65) 806 (77.4) 1042 1.66 (1.19, 2.31)
 4 year college degree or more 31 (12.50) 217 (87.5) 248 0.92 (0.58, 1.44)
Employment
 Full or part time work 309 (22.4) 1073 (77.6) 1382 1.0
 Unemployed 52 (17.9) 238 (82.1) 290 0.80 (0.62, 1.05)
 Other 102 (15.6) 551 (84.4) 653 0.70 (0.57, 0.86)
Marital status
 Single 217 (34.5) 412 (65.5) 629 2.64 (2.21, 3.16)
 Married or member of couple 82 (18.8) 355 (81.2) 437 1.44 (1.13, 1.83)
 Divorced, Separated or Widowed 162 (13.1) 1078 (86.9) 1240 1.0
Smoking status
 Current smoker 258 (30.5) 587 (69.5) 845 2.38 (1.98, 2.86)
 Former smoker 66 (17.5) 312 (82.5) 378 1.36 (1.04, 1.78)
 Never smoker 142 (12.8) 966 (87.2) 1108 1.0
Ever have abnormal
Pap smear
 No 213 (16.6) 1073 (83.4) 1286 1.0
 Yes 255 (24.0) 808 (76.0) 1063 1.45 (1.23, 1.70)
Number of pregnancies
 0 168 (30.6) 382 (69.5) 550 2.11 (1.71, 2.62)
 1 86 (20.1) 341 (79.9) 427 1.39 (1.08, 1.80)
 2 99 (16.8) 491 (83.2) 590 1.16 (0.90, 1.49)
 More than 2 110 (14.5) 651 (85.6) 761 1.0
Number of male partners
 < 4 82 (9.9) 746 (90.1) 828 1.0
 4 or more 359 (26.7) 987 (73.3) 1346 2.69 (2.15, 3.37)
Appalachian self – identity
 No or Don’t know 342 (22.0) 1214 (78.0) 1556 1.0
 Yes 124 (16.3) 637 (83.7) 761 0.74 (0.62, 0.89)
Region of Appalachian Ohio
 Northeast 196 (22.2) 686 (77.8) 882 2.10 (1.44, 3.06)
 East Central 179 (20.4) 698 (79.6) 877 1.93 (1.32, 2.82)
 South East 66 (19.7) 269 (80.3) 335 1.86 (1.23, 2.82)
 South West 27 (10.6) 228 (89.4) 255 1.0
Open in a new tab

Note: Heavy episodic drinking (also known as binge drinking) is defined by the SAMHSA as 5 or more drinks on the same occasion on at least one day in the past 30 days.

a

Relative risk for categorical covariates is the estimated risk of heavy episodic drinking in each covariate group, compared to the reference group (denoted as a relative risk of 1). The relative risk for continuous age is the estimated risk associated with presented for a 10-year increase in age.

Table 2.

Predictors of Heavy Episodic Drinking

Model with Appalachian Identity Adjusted Relative Risk (95% CI) Model without Appalachian Identity Adjusted Relative Risk (95% CI)
Age
 18–21 4.96 (2.73, 9.02) 5.16 (2.86, 9.34)
 >21–26 5.11 (2.88, 9.05) 5.23 (2.96, 9.23)
 >26–30 3.34 (1.83, 6.10) 3.36 (1.84, 6.11)
 >30–35 3.32 (1.82, 6.07) 3.38 (1.86, 6.16)
 >35–40 3.10 (1.68, 5.70) 3.14 (1.71, 5.78)
 >40–45 3.08 (1.65, 5.76) 3.05 (1.63, 5.69)
 >45–50 3.21 (1.74, 5.92) 3.16 (1.71, 5.85)
 >50 1.0 1.0
Education
 Less than high school 1.0 1.0
 High school diploma 1.58 (1.14, 2.21) 1.63 (1.17, 2.28)
 Some technical training or college 1.69 (1.22, 2.34) 1.75 (1.26, 2.42)
 4 year college degree or more 1.51 (0.95, 2.41) 1.56 (0.98, 2.49)
Marital status
 Single 1.43 (1.17, 1.74) 1.44 (1.18, 1.75)
 Married or member of couple 1.22 (0.94, 1.57) 1.23 (0.96, 1.59)
 Divorced, Separated or Widowed 1.0 1.0
Smoking status
 Current smoker 1.79 (1.47, 2.19) 1.79 (1.47, 2.19)
 Former smoker 1.25 (0.95, 1.64) 1.25 (0.95, 1.64)
 Never smoker 1.0 1.0
Number of pregnancies
 0 1.30 (1.01, 1.67) 1.29 (1.00, 1.65)
 1 0.97 (0.75, 1.26) 0.97 (0.75, 1.26)
 2 0.99 (0.78, 1.27) 1.00 (0.78, 1.28)
 More than 2 1.0 1.0
Number of male partners
 < 4 1.0 1.0
 4 or more 2.10 (1.67, 2.63) 2.08 (1.66, 2.60)
Appalachian self - identity
 No or Don’t know 1.0 -
 Yes 0.99 (0.82, 1.20) -
Region of Ohio
Appalachia
 Northeast 1.47 (1.03, 2.11) 1.48 (1.03, 2.12)
 East Central 1.24 (0.86, 1.79) 1.25 (0.87, 1.81)
 South East 1.23 (0.82 1.85) 1.24 (0.83, 1.85)
 South West 1.0 1.0
Open in a new tab

Note: Heavy episodic drinking (also known as binge drinking) is defined by the SAMHSA as 5 or more drinks on the same occasion on at least one day in the past 30 days.

Adjusted relative risk is the estimated risk of heavy episodic drinking in each covariate group, compared to the reference group (denoted as a relative risk of 1), and adjusted for all other covariates in the model.

Results

Table 1 presents characteristics of the study sample by reported recent history of heavy episodic drinking. Nearly one fifth (19.9%, 95% CI: 18.3%, 21.5%) of women reported recent heavy episodic drinking. The vast majority, 95%, of participants in our study were non-Hispanic White and all lived in Appalachian Ohio. Demographic characteristics such as age, marital status, and education level were highly associated with heavy episodic drinking, as were behavioral factors such as smoking, number of sexual partners, and number of pregnancies (Table 1). Table 2 provides the fully adjusted model with, and without Appalachian self-identity. No significant relationship between Appalachian self-identity and heavy episodic drinking was observed, once adjusted for age. In multivariable models, the adjusted risk of heavy episodic drinking for younger women (below 26 years of age) was nearly five times that of women over 50 and just over two times the adjusted risk for women with a higher number (4 or more) male sexual partners (Table 2). Moreover, adjusted for all other covariates in the model, current smokers (aRR: 1.79, 95% CI (1.47, 2.19), those who were single (aRR: 1.44, 95% CI: 1.18, 1.75), and those with four or more lifetime sexual partners (aRR: 2.08, 95% CI: 1.66, 2.60) had an increased adjusted risk of heavy episodic drinking. No clinically or statistically significant (interaction test p-value <0.01) interactions between Appalachian identity and participant characteristics were identified.

Discussion

Results of the study indicate that the prevalence of heavy episodic drinking is high (20%) in our sample of women from Appalachian Ohio. Findings identified correlates of heavy episodic drinking among this sample of women, including younger age (26 years old or younger), single status, current cigarette smokers, and reporting 4 or more sex partners. With respect to the role of Appalachian self-identity as a factor associated with risky alcohol use, contrary to what was hypothesized, our results indicated no significant contribution of self-identity to predicting heavy episodic drinking.

The present study reports a higher prevalence rate of heavy episodic drinking in our sample of women from Appalachian Ohio compared to national estimates for women (12%; CDC, 2016). These results are consistent with reports that alcohol continues to be the most widely used and abused substance and the primary reason for obtaining substance abuse treatment in the Appalachian region (CDC, 2013; Zhang et al., 2008). However, these results differ from previous reports suggesting that proportionately fewer Appalachian adults, compared to adults nationally, report heavy episodic drinking in the past year (Short et al., 2012). One interpretation of the current results may be that our sample of women from Appalachian Ohio is a vulnerable population because of a number of disadvantages that are often faced in their environment, including chronic stressors (e.g., limited resources, living in poverty) and acute stressors (e.g., violence or abuse), increasing the likelihood of higher rates of alcohol and substance use (CDC, 2015; Logan et al., 2002).

The demographic and behavioral correlates of heavy episodic drinking that we identified in our sample of Appalachian women are consistent with previous literature examining these risk factors in urban populations, particularly young age. In the present study, the risk of heavy episodic drinking for younger women (below 26 years of age) was nearly five times that of women over 50. Indeed, previous work suggests that emerging adulthood (18–25 years old), the period between high school and young adulthood, reflects a time of elevated risk for alcohol misuse and problems associated with drinking (Arnett, 2000; NIAAA, 2015; White & Jackson, 2005). Heavy episodic drinking also is associated with a broad range of risk behaviors, including tobacco use and risky sexual activity, such as unprotected sex and multiple sex partners (Hutton et al., 2008). Younger, single women may be more vulnerable as they are more likely to engage in risky sexual behavior than their married counterparts (Wayment et al., 2003).

Although the current results do not suggest a significant association between Appalachian self-identity and heavy episodic drinking, the role of self-identity can be explored further in future studies. The current methods included only a single-item assessment of self-identity and did not include the measurement of variables associated with self-identity, including religious affiliation, family and community relationships. Previous work suggests that there should be a different approach to treatment in Appalachian areas vs. non-Appalachian areas (Shannon, Havens, Mateyoke-Scrivner, & Walker, 2009), including the implementation of culturally competent and sensitive preventive interventions to identify and intervene with Appalachian women at risk for alcohol misuse and associated comorbidities (Browning, 2011).

The present study has a number of strengths including a large sample size and the inclusion of women throughout the Appalachian Ohio region. Limitations of this study include the participation of women who are accessing health services at a primary care site in Appalachian Ohio, which affects the generalizability of the findings to all women. Further, the study included a cross-sectional design that prevented causal inference. Although the assessment of heavy episodic drinking in this study is consistent with the definition recommended by the SAMHSA, it does not include the lower threshold for females (≥ 4 drinks, as opposed to ≥ 5 drinks, for men) that is consistent with the definition from the National Institute on Alcohol Abuse and Alcoholism, and this may have impacted our findings (SAMHSA, 2016). Moreover, because the focus of the CARE study was on determinants of cervical cancer, the assessment of alcohol use was not a primary aim of the original study.

There are important barriers to health services that women from Appalachian Ohio face including stigma, lack of access/providers, cultural concerns of confidentiality and trust, as well as comorbid psychiatric disorders (Stensland, Mueller, & Sutton, 2002). A qualitative study of factors influencing screening and mental health treatment among Appalachian females in primary care identified that both patients and providers described cultural values as influencing access to care (Hill, Cantrell, Edwards, & Dalton, 2016). Despite the recommendation by the US Preventive Services Task Force (2013) for providers to screen for mental health concerns, including alcohol use, cultural barriers such as stigma and lack of anonymity in small, rural settings present a challenge. This gap is particularly important to address given that rural women, including those from Appalachian regions, report higher health concerns that may be associated with, or a consequence of, unaddressed or undertreated problem alcohol use. One challenge in serving the behavioral health needs of women who live in this region is that the access to screening, treatment, and referral is often lower in rural areas (Hauenstein et al., 2006). The use of telemedicine technologies, including mobile health (mHealth), may offer advantages in overcoming these barriers and improving health outcomes for women from Appalachian communities (American College of Obstetricians and Gynecologists, 2014).

The present findings have clinical implications. As reflected in both the current results and national data, women are increasingly endorsing risky alcohol use at younger ages. Clinicians should take care to recognize health care barriers and to screen the presence of alcohol misuse among young women (Hutton et al., 2008). For example, in the clinical scenario of a young woman who endorses current smoking and four or more lifetime sexual partners, clinicians should consider this an opportunity to ask about alcohol use. With the many competing demands of the scenario, it would otherwise be easy to overlook this health risk. Moreover, lack of affordable healthcare and other problems related to low socioeconomic status in women living in this region might contribute to self-medicating or misusing alcohol to cope with daily stressors (Bahls, 2011; Warnecke et al., 2008). Indeed, there is a large literature supporting that the exposure to acute and chronic stress, including socioeconomic status and environmental stress, has negative effects on health, and that perceived stress is a risk factor for a number of diseases and health disparities (Djuric et al., 2010). Compared to non-rural women, women from Appalachian regions are more likely to experience a number of stressors and this may be a contributing factor to their risky alcohol use (Logan et al., 2002; Post et al., 2013). Future work exploring the relationship between stress and alcohol use among women in this region may shed light on opportunities for prevention. Integrating strategies to identify risk factors and enhance protective factors among these women will inform intervention efforts and reduce health disparities including risky alcohol use and associated morbidities among women from Appalachian Ohio.

Acknowledgments

This study was supported by National Institutes of Health Grant P50CA105632 and the Behavioral Measurement Shared Resource at The Ohio State University Comprehensive Cancer Center, Grant P30CA016058 from the National Cancer Institute. Dr. Ruffin’s effort on this project was supported by Dr. Max and Buena Lichter Research Professor of Family Medicine.

References

  1. American College of Obstetricians and Gynecologists. Health disparities in rural women. Committee Opinion No. 586. Obstetrics & Gynecology. 2014;123:384–388. doi: 10.1097/01.AOG.0000443278.06393.d6. [DOI] [PubMed] [Google Scholar]
  2. Arnett J. Emerging adulthood: A theory of development from the late teens through the twenties. American Psychologist. 2000;55:469–480. [PubMed] [Google Scholar]
  3. Bachman JG, Wadsworth KN, O’Malley PM, Johnston LD, Schulenberg JE. Smoking, drinking, and drug use in young adulthood: The impact of new freedoms and new responsibilities. Mahwah, NJ: Lawrence Erlbaum Associates; 1997. [Google Scholar]
  4. Bahls C. Health policy brief: achieving equity in health. Health Affairs Brief. 2011:1–6. [Google Scholar]
  5. Becker JB. The crisis of opiates in Appalachia. Marshall Journal of Medicine. 2016;2(1) Article 2. [Google Scholar]
  6. Browning AM. Community perceptions of prescription drug abuse in Eastern Kentucky. 2011 Retrieved from http://dc.etsu.edu/etd/1289.
  7. Caldwell C, Sellers R, Bernat D, Zimmerman M. Racial identity, parental support, and alcohol use in a sample of academically at-risk African American high school students. American Journal of Community Psychology. 2004;34(1):71–82. doi: 10.1023/b:ajcp.0000040147.69287.f7. [DOI] [PubMed] [Google Scholar]
  8. Centers for Disease Control and Prevention (CDC) Addressing prescription drug abuse in the United States. 2013 Retrieved from https://www.cdc.gov/drugoverdose/pdf/hhs_prescription_drug_abuse_report_09.2013.pdf.
  9. Centers for Disease Control and Prevention (CDC) Facts about FASDs. National Center on Birth Defects and Developmental Disabilities. Division of Birth Defects and Developmental Disabilities; 2016. Retrieved from http://www.cdc.gov/ncbddd/fasd/facts.html. [Google Scholar]
  10. Centers for Disease Control and Prevention (CDC) Excessive alcohol use and risks to women’s health. 2016. [Google Scholar]
  11. Centers for Disease Control and Prevention (CDC) HIV and substance use in the United States. 2016 Retrieved from http://www.cdc.gov/hiv/risk/substanceuese.html.
  12. Djuric Z, Bird C, Furumoto-Dawson A, Rauscher G, Ruffin M, Stowe R, … Masi C. Biomarkers of psychological stress in health disparities research. Open Biomarkers Journal. 2008;1:7–19. doi: 10.2174/1875318300801010007. [DOI] [PMC free article] [PubMed] [Google Scholar]
  13. Gilbert MJ. Acculturation and changes in drinking patterns among Mexican-American women: Implications for prevention. Alcohol Health and Research World. 1991;15(3):234–238. [Google Scholar]
  14. Hauenstein EJ, Petterson S, Merwin E, Rovnyak V, Heise B, Wagner D. Rurality, gender, and mental health treatment. Family Community Health. 2006;29(3):169–185. doi: 10.1097/00003727-200607000-00004. [DOI] [PubMed] [Google Scholar]
  15. Herd D, Grube J. Black identity and drinking in the US: a national study. Addiction. 1996;91(6):845–857. doi: 10.1046/j.1360-0443.1996.91684510.x. [DOI] [PubMed] [Google Scholar]
  16. Hill SK, Cantrell P, Edwards J, Dalton W. Factors influencing mental health screening and treatment among women in a rural South Central Appalachian primary care clinic. Journal of Rural Health. 2016;32(1):82–91. doi: 10.1111/jrh.12134. [DOI] [PubMed] [Google Scholar]
  17. Hovick S, Holt L. Beyond race and ethnicity: Exploring the effects of ethnic identity and its implications for cancer communication efforts. Journal of Health Communication. 2016;21(2):199–207. doi: 10.1080/10810730.2015.1058436. [DOI] [PubMed] [Google Scholar]
  18. Hutton HE, McCaul ME, Santora PB, Erbelding The relationship between recent alcohol use and sexual behaviors: Gender differences among STD clinic patients. Alcoholism: Clinical & Experimental Research. 2008;32(11):2008–2015. doi: 10.1111/j.1530-0277.2008.00788.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  19. Logan TK, Walker R, Cole J, Leukfeld C. Victimization and substance abuse among women: Contributing factors, interventions, and implications. Review of General Psychology. 2002;6:325–397. [Google Scholar]
  20. Love AS, Yin Z, Codina E, Zapata JT. Ethnic identity and risky health behaviors in school-age Mexican American children. Psychological Reports. 2006;98(3):735–744. doi: 10.2466/pr0.98.3.735-744. [DOI] [PubMed] [Google Scholar]
  21. Lumley T, Kronmal R, Ma S. Relative risk regression in medical research: models, contrasts, estimators, and algorithms. Berkeley, CA: The Berkeley Electronic Press; 2006. UW Biostatistics Working Paper Series, Working Paper 293. [Google Scholar]
  22. National Institute on Alcohol Abuse and Alcoholism (NIAAA) Alcohol – A women’s health issue. U.S. Department of Health and Human Services. National Institute of Health; 2015. NIH Publication No. 15–4956. [Google Scholar]
  23. Phinney J. Ethnic identity in adolescents and adults: A review of research. Psychological Bulletin. 1990;108:499–514. doi: 10.1037/0033-2909.108.3.499. [DOI] [PubMed] [Google Scholar]
  24. Reczek C, Pudrovska T, Carr D, Umberson D, Thomeer M. Marital histories and heavy alcohol use among older adults. Journal of Health and Social Behavior. 2016;57(1):77–96. doi: 10.1177/0022146515628028. [DOI] [PMC free article] [PubMed] [Google Scholar]
  25. Reiter PL, Katz ML, Ferketich AK, Ruffin MT, Paskett E. Appalachian self-identity among women in Ohio Appalachia. Journal of Rural Community Psychology. 2009;E12(1) [Google Scholar]
  26. SAS Institute Inc. What’s New in SAS® 9.3. Cary, NC: SAS Institute Inc; 2012. [Google Scholar]
  27. Shannon LM, Havens JR, Mateyoke-Scrivner A, Walker R. Contextual differences in substance use for rural Appalachian treatment-seeking women. The American Journal of Drug and Alcohol Abuse. 2009;35:59–62. doi: 10.1080/00952990802441394. [DOI] [PubMed] [Google Scholar]
  28. Short V, Oza-Frank R, Conrey E. Preconception health indicators: A comparison between non-Appalachian and Appalachian women. Maternal and Child Health Journal. 2012;16(2):238–249. doi: 10.1007/s10995-012-1129-1. [DOI] [PMC free article] [PubMed] [Google Scholar]
  29. Shrake EK, Rhee S. Ethnic identity as a predictor of problem behaviors among Korean American adolescents. Adolescence. 2004;39(155):601–622. [PubMed] [Google Scholar]
  30. StataCorp. Stata Statistical Software: Release 13. College Station, TX: StataCorp LP; 2013. [Google Scholar]
  31. Stensland J, Mueller C, Sutton J. An analysis of the financial conditions of health care institutions in the Appalachian region and their economic impacts 2002 [Google Scholar]
  32. Substance Abuse and Mental Health Services Administration (SAMHSA) 2014 National Survey on Drug Use and Health (NSDUH. Table 5.8A—Substance dependence or abuse in the past year among persons aged 18 or older, by demographic characteristics: Numbers in thousands, 2013 and 2014. [Google Scholar]
  33. Substance Abuse and Mental Health Services Administration (SAMHSA) Binge Drinking: Terminology and Patterns of Use. 2016 Retrieved from http://www.samhsa.gov/capt/tools-learning-resources/binge-drinking-terminology-patterns.
  34. Substance Abuse and Mental Health Services Administration. Treatment Improvement Protocol (TIP) Vol. 5. Center for Substance Abuse Treatment; Rockville (MD): 2009. Substance Abuse Treatment: Addressing the Specific Needs of Women. [PubMed] [Google Scholar]
  35. Umana-Taylor A, Updegraff K. Latino adolescents’ mental health: exploring the interrelations among discrimination, ethnic identity, cultural orientation, self-esteem, and depressive symptoms. Journal of Adolescence. 2007;30(4):549–567. doi: 10.1016/j.adolescence.2006.08.002. [DOI] [PubMed] [Google Scholar]
  36. U.S. Preventive Services Task Force. Final Update Summary: Alcohol Misuse: Screening and Behavioral Counseling Interventions in Primary Care. 2013 Retrieved from https://www.uspreventiveservicestaskforce.org/Page/Document/UpdateSummaryFinal/alcohol-misuse-screening-and-behavioral-counseling-interventions-in-primary-care.
  37. Van Gundy K. Reports on Rural America. 2. Vol. 1. Durham, New Hampshire: Carsey Institute; 2006. Substance abuse in rural and small town America. [Google Scholar]
  38. Warnecke R, Oh A, Breen N, Gehlert S, Paskett E, Tucker, … Hiatt R. Approaching health disparities from a population perspective: the National Institutes of Health Centers for Population Health and Health Disparities. American Journal of Public Health. 2008;98(9):1608–1615. doi: 10.2105/AJPH.2006.102525. [DOI] [PMC free article] [PubMed] [Google Scholar]
  39. Wayment H, Wyatt G, Tucker B, Romero G, Carmona J, … Mitchell-Kernan C. Predictors of risky and precautionary sexual behaviors among single and married White women. Journal of Applied Social Psychology. 2003;33(4):791–816. [Google Scholar]
  40. Weaver A, Himle J, Taylor R, Matusko N, Abelson J. Urban vs rural residence and the prevalence of depression and mood disorder among African American women and Non-Hispanic White women. JAMA Psychiatry. 2015;72(6):576–583. doi: 10.1001/jamapsychiatry.2015.10. [DOI] [PMC free article] [PubMed] [Google Scholar]
  41. Windle M. Alcohol Use Among Adolescents and Young Adults. National Institute on Alcohol Abuse and Alcoholism (NIAAA); 2003. Retrieved from http://pubs.niaaa.nih.gov/publications/arh27-1/79-86.htm. [PMC free article] [PubMed] [Google Scholar]
  42. Winstanley EL, Gay J, Roberts L, Moseley J, Hall O, Beeghly BC, Winhusen T, Somoza E. Prescription drug abuse as a public health problem in Ohio: a case report. Public Health Nursing. 2012;29(6):553–562. doi: 10.1111/j.1525-1446.2012.01043.x. [DOI] [PubMed] [Google Scholar]
  43. Zhang Z, Infante A, Meit M, English N. Final Report. University of Chicago. Appalachian Regional Commission; 2008. An analysis of mental health and substance abuse disparities & access to treatment services in the Appalachian region. [Google Scholar]
  44. Zou G. A modified poisson regression approach to prospective studies with binary data. American Journal of Epidemiology. 2004;159(7):702–6. doi: 10.1093/aje/kwh090. [DOI] [PubMed] [Google Scholar]

RESOURCES