Does Alcohol Use Differ by Metropolitan Status in Young Adult Females in the United States General Population?
Received: 01-Jun-2018 / Accepted Date: 07-Jun-2018 / Published Date: 14-Jun-2018
Abstract
Purpose: Alcohol use can lead to serious health concerns and even death, but findings are inconsistent regarding whether consumption differs by where people live. The purpose of this study was to assess whether alcohol use differs by metropolitan status in young adult females ages 25-44 in the general population. Methods: This cross-sectional analysis used data from the 2016 Behavioral Risk Factor Surveillance System (BRFSS) for females ages 25-44 in California (N=271), Colorado (N=428), Florida (N=1,109), New York (N=1,456), and Texas (N=482). Ordered logistic regression analysis was used with combined state data to assess the relationship between alcohol use and metropolitan status while controlling for demographic and health-related factors. Results: Across states, over half of participants reported alcohol use (49-65%), with about one-fifth reporting excessive alcohol use (14-26%). Metropolitan status varied among urban (12-54%), suburban (24-51%), and rural (5- 42%) residents. The results of adjusted analysis indicated that metropolitan status, current smoking, and mental health status were significantly related to alcohol use. Conclusion: Overall, alcohol use differed by metropolitan status in female adults ages 25-44, with urban women reporting drinking more than their rural counterparts. In a primary care setting, providers may expect about half of young adult females to drink alcohol, less than half to have mental health issues, and few to be smokers. Providers need to be aware that current smokers and those with mental health issues are more likely to report alcohol use. Providers should continue to screen all women ages 25-44 for alcohol use, with special attention to those from urban areas. Because smoking and mental health status were related to alcohol use, providers should screen for all of these if any are present and provide education and referrals to substance abuse programs and mental health counseling as necessary.
Keywords: Alcohol Consumption; Women’s Health; Urban Population; Suburban Population; Rural Population; Mental Health; Tobacco Use
Introduction
Alcohol misuse is responsible for 6% of deaths worldwide, especially in those ages 15-39, and contributes to serious and often life-altering health issues [1-5]. Alcohol misuse is associated with health conditions such as heart disease, liver disease, cancer, and alcoholism [1,3-6]; high rates of crime and traffic accidents [1,7]; and risky sexual behaviors and violence [8,9]. In the United States, alcohol use remains a steadfast part of our culture even though the economic cost of alcohol-related health issues exceeds $240 billion [2,9,10].
Several health and social factors play a role in alcohol consumption [1,4,6-8,11,12]. Poor mental health can contribute to engaging in inappropriate use of alcohol [7], as those who report higher alcohol consumption also report problems with anxiety, living in stressful environments, and dealing with negative life events [1,7]. In addition, people who smoke usually drink alcohol, and up to 90 percent of those who are diagnosed with alcoholism also smoke [11]. Furthermore, the need for socialization increases the use of alcohol; however, those of African, Asian, and Latino descent may drink less than those of Caucasian descent [4,8].
Demographic factors are shown to be associated with alcohol consumption. Research indicates that those with a higher socioeconomic status tend to drink more often, whereas those with a lower socioeconomic status drink larger amounts at one time [4,13]. Findings for educational status vary [7,8,14,15] as some research indicates that male heavy drinkers are less likely to complete a college education than males who do not drink heavily, and people with lower levels of education have an increased use of alcohol [7,14], whereas other findings report that those with a lack of education are more likely to abstain from alcohol and refrain from drinking to intoxication [15]. When considering race, Caucasians are more likely to drink alcohol than other races [4,12,15,16].
Furthermore, gender, age, and metropolitan status may relate to alcohol use. Overall, men tend to consume more alcohol than women [1,4-6] and are also more likely to drink heavily [6,13] and to binge drink [12,15]. However, when taking age into account, younger women are more likely to binge drink than younger men [10,17]. Additionally, males in metropolitan or urban areas are more likely to drink any amount and more heavily than non-metropolitan males [8,16]. Other research shows that rural adults are more likely to engage in risky drinking than urban adults [1,13,15]. However, research on metropolitan status and alcohol use utilizes different definitions for “urban,” “metropolitan,” and “rural” status, and with no standardized qualifications, it is difficult to know if results are consistent and comparable [16]. In addition, there is limited research focusing solely on alcohol use based on metropolitan status and female gender in young adults [4,17]. Such findings are of particular interest for the purposes of prevention and treatment [10,16]. Therefore, the purpose of this study was to assess whether alcohol use differs by metropolitan status in young adult females ages 25-44 in the general population.
Methods
Design
This cross-sectional analysis used data from the 2016 Behavioral Risk Factor Surveillance System (BRFSS) conducted by the Centers for Disease Control and Prevention (CDC) [18]. BRFSS consists of state data acquired from telephone surveys with U.S. residents regarding their health-related risk behaviors, chronic conditions, and use of preventative services. BRFSS results are collected in all 50 states as well as the District of Columbia and three U.S. territories. More than 400,000 adult interviews are conducted through BRFSS annually. The CDC compiles all BRFSS data and makes de-identified data available to researchers for secondary data analysis. This study was given exempt status by Institutional Review Board of The University of North Texas Health Science Center.
Sample
The sample for this study included females ages 25-44 in California (N=271), Colorado (N=428), Florida (N=1,109), New York (N=1,456), and Texas (N=482) with data for metropolitan status. This target population was chosen because there is limited research focusing solely on alcohol use and metropolitan status in young adult females [4,17]. These states were chosen because they represent different parts of the country that have more inclusion of urban, suburban, and rural areas compared to the rest of the continental United States when compared to the other U.S. States [19].
Data
The outcome was alcohol use. BRFSS measured alcohol use as the average number of drinks per day in the last 30 days and we categorized these responses for women as “no use,” indicating no consumption of alcohol at all, “light use,” indicating less than one alcoholic drink, “moderate use,” indicating 1-3 alcoholic drinks, and “excessive use,” indicating 4 or more alcoholic drinks per day [20]. The factor of interest, metropolitan status, was categorized as “urban” (i.e., living in the center city of a Metropolitan statistical area), “suburban” (i.e., living outside the center city of a metropolitan statistical area, but inside the county containing the center city or inside a suburban county of the metropolitan statistical area), or “rural” (i.e., not living in a metropolitan statistical area).
The control variables included age, race, educational status, employment status, income level, general health status, depression, mental health status, physical health status, tobacco use, and state. Age was categorized as “25-34” and “35-44.” Because the majority of participants were white, race was measured as “white, non-Hispanic” versus “other.” Educational level was measured as “having graduated from college or technical school” versus “not having graduated from college or technical school.” Employment status was measured as “being employed” versus “not being employed.” Income level was classified as an annual income “greater than or equal to $50,000” or “less than $50,000.” General health status was reported as “good or better” versus “fair or poor.” Depression was measured as “yes” versus “no” to having ever been diagnosed with any form of depression or dysthymia. Mental health status was measured as “30 days of good mental health in the past 30 days” versus “less than 30 days of good mental health in the past 30 days.” Physical health status was measured as having “30 days of good physical health in the past 30 days” versus “less than 30 days of good physical health in the past 30 days.” Tobacco use was measured as “yes” or “no” to current smoker.
Analysis
Frequency distributions were reported by state to describe the samples and to identify any issues with the distributions of variables. We chose to combine data across all states (as compared to analyzing data separately by state) for adjusted analysis to increase the numbers of females per metropolitan status category. We used ordered logistic regression analysis with combined state data to assess the relationship between alcohol use and metropolitan status in young adult females after controlling for demographic factors, health-related factors, and state. An ordered logistic regression model is used to estimate a relationship between an ordinal dependent variable and a set of independent variables. The proportional odds produced for each independent variable relates “proportionally” or applies equally to comparisons of dependent variable groups greater than k versus those who are in groups less than or equal to k, where k is any level of the response variable. Therefore, the interpretation of an associated odds ratio is that for a one unit change in the predictor variable, the odds for a group that is greater than k versus less than or equal to k are the proportional odds times larger. Any observations with missing data for any variables were excluded from the adjusted analysis. All analyses were conducted in STATA 15 (version 15.1, copyright 1985-2017 StataCorp LLC).
Results
Descriptive statistics
Table 1 lists participant characteristics for female adults ages 25- 44 in California, Colorado, Florida, New York, and Texas. Almost half of participants reported no alcohol use (36-50%) and about one-fifth reported excessive use of alcohol (14-26%). For metropolitan status, there was a varied distribution among urban (12-54%), suburban (24- 51%), and rural (5-42%) residents. The majority of participants were 35-44 years old (63-76%), and participants with white, non-Hispanic race status varied across states (29-76%). For socioeconomic status, the majority did not graduate from college or technical school (47-66%) and reported being employed (59-69%), and about one-half reported having an income of $50,000 or more per year (41-68%). For health status, most of the participants had good or better health (83-91%) and had never been diagnosed with any form of depression or dysthymia (75-90%).
Variables | California (N=271) | Colorado (N=428) | Florida (N=1109) | New York (N=1456) | Texas (N=482) | |||||
---|---|---|---|---|---|---|---|---|---|---|
N | % | N | % | N | % | N | % | N | % | |
Alcohol Use | 264 | 97 | 406 | 95 | 1068 | 96 | 1388 | 95 | 453 | 94 |
No use | 125 | 47 | 145 | 36 | 538 | 50 | 585 | 42 | 227 | 50 |
Light | 37 | 14 | 72 | 18 | 201 | 19 | 277 | 20 | 87 | 19 |
Moderate | 44 | 17 | 84 | 21 | 160 | 15 | 260 | 19 | 74 | 16 |
Excessive | 58 | 22 | 105 | 26 | 169 | 16 | 266 | 19 | 65 | 14 |
Metropolitan Status | 271 | 100 | 428 | 100 | 1109 | 100 | 1456 | 100 | 482 | 100 |
Urban | 119 | 44 | 233 | 54 | 131 | 12 | 487 | 33 | 244 | 51 |
Suburban | 138 | 51 | 101 | 24 | 512 | 46 | 512 | 35 | 178 | 37 |
Rural | 14 | 5 | 94 | 22 | 466 | 42 | 457 | 31 | 60 | 12 |
Age | 271 | 100 | 428 | 100 | 1109 | 100 | 1456 | 100 | 482 | 100 |
25-34 | 72 | 27 | 101 | 24 | 412 | 37 | 537 | 37 | 137 | 28 |
35-44 | 199 | 73 | 327 | 76 | 697 | 63 | 919 | 63 | 345 | 72 |
Race | 270 | 99 | 421 | 98 | 1092 | 98 | 1431 | 98 | 479 | 99 |
White, non-Hispanic | 79 | 29 | 312 | 74 | 711 | 65 | 1094 | 76 | 214 | 45 |
Other | 191 | 71 | 109 | 26 | 381 | 35 | 337 | 24 | 265 | 55 |
Educational Status | 270 | 99 | 428 | 100 | 1105 | 99 | 1452 | 99 | 482 | 100 |
Graduated college or technical school | 125 | 46 | 225 | 53 | 377 | 34 | 612 | 42 | 202 | 42 |
Did not graduate college or technical school | 145 | 54 | 203 | 47 | 728 | 66 | 840 | 58 | 280 | 58 |
Employment Status | 269 | 99 | 425 | 99 | 1099 | 99 | 1441 | 99 | 473 | 98 |
Employed | 166 | 62 | 294 | 69 | 712 | 65 | 962 | 67 | 279 | 59 |
Not employed | 103 | 38 | 131 | 31 | 387 | 35 | 479 | 33 | 194 | 41 |
Income Level | 228 | 84 | 385 | 90 | 970 | 87 | 1290 | 89 | 422 | 88 |
$50,000 or more a year | 119 | 52 | 260 | 68 | 396 | 41 | 710 | 55 | 202 | 48 |
Less than $50,000 a year | 109 | 48 | 125 | 32 | 574 | 59 | 580 | 45 | 220 | 52 |
General Health Status | 271 | 100 | 428 | 100 | 1107 | 99 | 1452 | 99 | 478 | 99 |
Good or better | 239 | 88 | 389 | 91 | 946 | 85 | 1285 | 89 | 398 | 83 |
Fair or poor | 32 | 12 | 39 | 9 | 161 | 15 | 167 | 11 | 80 | 17 |
Depression | 270 | 99 | 428 | 100 | 1102 | 99 | 1454 | 99 | 480 | 99 |
Yes | 27 | 10 | 105 | 25 | 214 | 19 | 243 | 17 | 83 | 17 |
No | 243 | 90 | 323 | 75 | 888 | 81 | 1211 | 83 | 397 | 83 |
Mental Health Status | 269 | 99 | 423 | 99 | 1095 | 99 | 1439 | 99 | 475 | 99 |
30 days good | 159 | 59 | 201 | 48 | 682 | 62 | 847 | 59 | 267 | 56 |
Less than 30 days good | 110 | 41 | 222 | 52 | 413 | 38 | 592 | 41 | 208 | 44 |
Physical Health Status | 269 | 99 | 425 | 99 | 1097 | 99 | 1434 | 98 | 469 | 97 |
30 days good | 173 | 64 | 276 | 65 | 731 | 67 | 915 | 64 | 299 | 64 |
Less than 30 days good | 96 | 36 | 149 | 35 | 366 | 33 | 519 | 36 | 170 | 36 |
Current Smoker | 246 | 91 | 396 | 93 | 1061 | 96 | 1369 | 94 | 462 | 96 |
Yes | 19 | 8 | 58 | 15 | 213 | 20 | 262 | 19 | 52 | 11 |
No | 227 | 92 | 338 | 85 | 848 | 80 | 1107 | 81 | 410 | 89 |
Table 1: Participant Characteristics by State.
In addition, the majority reported good mental health (48-62%) and good physical health (64-67%) in the past 30 days, and most reported not smoking (80-92%).
Adjusted statistics
Predicting Alcohol use (none vs. light vs. moderate vs. excessive) | Combined State Data | ||
---|---|---|---|
Metropolitan Status | AOR | 95% CI | |
Urban | ref | - | - |
Suburban | 0.87 | 0.73 | 1.04 |
Rural | 0.71 | 0.58 | 0.86 |
Race | |||
Other | ref | - | - |
White, non-Hispanic | 1.50 | 1.27 | 1.76 |
Age | |||
25-34 | ref | - | - |
35-44 | 1.07 | 0.92 | 1.24 |
Education Level | |||
Did not graduate college or technical school | ref | - | - |
Graduated college or technical school | 1.36 | 1.16 | 1.60 |
Employment Status | |||
Not employed | ref | - | - |
Employed | 1.60 | 1.37 | 1.88 |
Income Level | |||
Less than $50,000 a year | ref | - | - |
$50,000 or more a year | 2.12 | 1.80 | 2.50 |
General Health Status | |||
Fair or poor | ref | - | - |
Good or better | 1.60 | 1.25 | 2.04 |
Depression or dysthymia | |||
No | ref | - | - |
Yes | 1.13 | 0.93 | 1.37 |
Mental Health Status | |||
Less than 30 days good | ref | - | - |
30 days good | 0.72 | 0.62 | 0.84 |
Physical Health Status | |||
Less than 30 days good | ref | - | - |
30 days good | 1.09 | 0.93 | 1.28 |
Current smoker | |||
No | ref | - | - |
Yes | 1.49 | 1.22 | 1.80 |
State | |||
California | ref | - | - |
Colorado | 1.07 | 0.76 | 1.50 |
Florida | 0.87 | 0.65 | 1.19 |
New York | 0.94 | 0.70 | 1.26 |
Texas | 0.85 | 0.61 | 1.18 |
Table 2: Adjusted results across states.
As shown in Table 2, the results of ordered logistic regression analysis for females ages 25-44 in California, Colorado, Florida, Texas, and New York indicated that after controlling for all other variables in the model, when compared to those who lived in an urban area, those who lived in a rural area were about 1.4 times less likely to report each successive level of alcohol use. In addition, compared to those who did not report 30 days of good mental health, those who did report 30 days of mental health were about 1.4 times less likely to report each successive level of alcohol use. In contrast, compared to their referent groups, the following participants were more likely to report each successive level of alcohol use: those who reported white race, graduating from college or technical school, being employed, making less than $50,000 per year, good or better general health, and being current smokers.
Discussion
The purpose of this study was to assess whether alcohol use was related to metropolitan status in young adult females ages 25-44 in the general population when controlling for other factors that may be related to alcohol use. The results of adjusted analysis indicated that those living in rural areas were about 1.4 times less likely to report each successive level of alcohol use than those living in urban areas. Although there has been limited research on alcohol use and metropolitan status in women [4,17], our results are similar to what has been observed in the research for males. Prior studies indicate that males in metropolitan or urban areas were more likely to drink any amount and more heavily than non-metropolitan males [8,16]. In addition, the results of the study indicated that those who smoke are more likely to report each successive level of alcohol use than non-smokers. This finding is similar to previous research findings that indicate that the use of alcohol and tobacco are highly related behaviors [11]. This relationship is, of course, problematic since both behaviors can contribute to further health issues.
Moreover, the results of this study indicate that those who report good mental health were less likely to report each successive level of alcohol use. This is similar to the prior research findings showing relations between poor mental health and alcohol use [7]. In contrast, those who reported good or better general health in this study were more likely to report each successive level of alcohol use. This is different than the results of previous research that relates poor physical health and alcohol use [7]. This inconsistency may be attributed to varying target populations, as the previous research included males of all ages and the current study is based on young adult females.
Limitations
Use of the 2016 BRFSS data allowed access to a large populationbased sample for a specific target group with data for many factors shown to be related to alcohol consumption. However, the measurement of metropolitan status categories may be problematic. Categories were based on proximity to cities within county lines, which could have led to possible misclassification of groups of people who live near a city but across county lines. Future research assessing the relationship between alcohol use and metropolitan status may consider defining metropolitan areas differently, taking into account the distance from a major city and the population of a specific area despite county lines. This would allow for more of the cultural aspects of metropolitan status to be assessed. In addition, information related to alcohol use lacked information for dangerous behaviors associated with drinking, such as driving while intoxicated, physical altercations, criminal activity, and risky sexual behavior. These behaviors would elevate the seriousness of the problem and further indicate the need for intervention. Furthermore, because the BRFSS data was collected by telephone survey, young women may not be truthful about alcohol consumption when speaking to an interviewer. Future research may consider other routes of data collection for young adult females including online surveys.
Conclusion
Because we used population-based data, the results of this study may generalize to young adult females ages 25-44 in primary care settings. In these settings, the majority of this target population may report drinking alcohol, but only about one-fifth may drink excessively. Primary care providers should be aware of patterns in alcohol use and metropolitan status in this target population and continue to follow The U.S. Prevention Services Task Force (USPSTF) guidelines for screening all adults for alcohol misuse and providing counseling and referrals as needed [21], perhaps with special attention to young adult females in urban areas. In addition, providers may expect less than one-fifth of the target population to smoke, about one-tenth to report fair or poor general health, and about one-half to report mental health issues. Because of significant relationships between these variables and alcohol use and USPSTF standards for screening all adults on tobacco use [22] and depression [23], providers should screen for all of these if any are present in their young adult female patients. Providers should counsel and provide resources for smoking cessation in addition to assessing the severity and management of mental and physical health issues, counseling on coping and management strategies, and making referrals to psychiatry or other specialists as needed.
Disclaimers
No author has any conflict of interest.
References
- Miller PG, Coomber K, Staiger P, Zinkiewicz L, Toumbourou JW (2010) Review of rural and regional alcohol research in Australia. Aust J Rural Health 18: 110-117.
-  Alcohol Facts and Statistics. National Institutes of Health (NIH), (2017) USA.
- Scott S, Reilly J, Giles EL, Hillier-Brown F, Ells L, et al. (2017) Socio-ecological influences on adolescent (aged 10-17) alcohol use and linked unhealthy eating behaviors: Protocol for a systematic review and synthesis of qualitative studies. Syst Rev 6: 1-8.
- Sudhinaraset M, Wigglesworth C, Takeuchi DT (2016) Social and cultural contexts of alcohol use: Influences in a socio-ecological framework. Alcohol Res 38: 35-45.
- Cheng HG, Deng F, Xiong W, Phillips MR (2015) Prevalence of alcohol use disorders in mainland China: A systematic review. Addiction 110: 761-774.
- Roche AM, Lee NK, Battams S, Fisher JA, Cameron JP, et al. (2015) Alcohol use among workers in male-dominated industries: A systematic review of risk factors. Saf Sci 78: 124-141.
- Abebe W (2013) Prevalence and consequences of substance use among high school and college students in Ethiopia: A review of the literature. Afr J Drug Alcohol Stud 12: 107-118.
- Centers for Disease Control and Prevention (CDC) (2018) Fact Sheets- Alcohol Use and Your Health.
- Keyes KM, Li G, Hasin DS (2011) Birth cohort effects and gender differences in alcohol epidemiology: A review and synthesis. Alcohol Clin Exp Res 35: 2101-2112.
- Drobes DJ (2002) National Institute of Alcohol Abuse and Alcoholism: Concurrent Alcohol and Tobacco Dependence.
- White A, Hingson R (2013) The burden of alcohol use: Excessive alcohol consumption and related consequences among college students. Alcohol Res 35: 201-218.
- Chan GC, Leung J, Quinn C, Kelly AB, Connor JP, et al. (2016) Rural and urban differences in adolescent alcohol use, alcohol supply, and parental drinking. J Rural Health 32: 280-286.
- McCambridge J, McAlaney J, Rowe R (2011) Adult consequences of late adolescent alcohol consumption: A systematic review of cohort studies. PLoS Med 8: 1-13.
- Slutske WS, Deutsch AR, Piasecki TM (2016) Neighborhood contextual factors, alcohol use, and alcohol problems in the United States: Evidence from a nationally representative study of young adults. Alcohol Clin Exp Res 40: 1010-1019.
- Dixon MA, Chartier KG (2016) Alcohol use patterns among urban and rural residents: Demographic and social influences Alcohol Res 38: 69-77.
- Levinson D, Rosca P, Vilner D, Brimberg I, Stall Y, et al. (2017) Binge drinking among young adults in an urban tertiary care emergency department in Israel. Isr J Health Policy Res 6: 1-7.
- Centers for Disease Control & Prevention (CDC) (2016) BRFSS Prevalence & Trends Data.
- Centers for Disease Control and Prevention (CDC) (2018) Alcohol and Public Health: Frequently Asked Questions.
- U.S. Preventive Services Task Force (2013) Alcohol Misuse: Screening and Behavioral Counseling Interventions in Primary Care.
- U.S. Preventive Services Task Force (2015) Tobacco Smoking Cessation in Adults, Including Pregnant Women: Behavioral and Pharmacotherapy Interventions.
- U.S. Preventive Services Task Force (2016) Depression in Adults: Screening.
Citation: Dainty MA, Weise LJ, Story SE, Dempsey BL, Thompson F, et al. (2018) Does Alcohol Use Differ by Metropolitan Status in Young Adult Females in the United States General Population? J Health Care Prev 1: 104.
Copyright: © 2018 Dainty MA, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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