michelle jiménez de tavárez, md; flavia c. d. andrade, phd department of kinesiology and community...

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Michelle Jiménez de Tavárez, MD; Flavia C. D. Andrade, PhD Department of Kinesiology and Community Health, College of Applied Health Sciences, University of Illinois at Urbana-Champaign Impact of Education in Tobacco Use and Alcohol Consumption in the Dominican Republic: A Social Gradient Perspective Acknowledgements The authors would like to thank DHS MEASURE and the Demography of Health and Aging Laboratory writing group. References 1. Marmot M. The Status Syndrome: How Social Standing Affects Our Health and Longevity . New York, Times Books, 2004. 319 pp. 2. Yusuf S, Hawken S, Ôunpuu S, Dans T, Avezum A, Lanas F, et al. Effect of potentially modifiable risk factors associated with myocardial infarction in 52 countries (the INTERHEART study): case- control study. The Lancet. 2004; 364(9438):937-952. 3. Cowell AJ. The relationship between education and health behavior: Some empirical evidence. Health Economics. 2006; 15:125-146. 4. Yeon Kang J, Young Lee J, Hee Sung S, Mi Paek Y, In Choi T. The Comparison of Nutrient Intakes and Patterns of Alcohol Consumption According to Social Status in Workers. [Abstract] Epidemiology. 2011; 22(1):S164. Doi: 10.1097/01.ede.0000392178.94629.87 5. Pampel FC, Denney JT. Cross-National Sources of Health Inequality: Education and Tobacco Use in the World Health Survey. Demography 2011:1-22. 6. Harper S, Lynch J, Davey-Smith G. Social determinants and the decline of cardiovascular diseases: understanding the links. Annu Rev Public Health. 2011; 32:39-69. 7. Heller RF, McElduff P, & Edwards R. Impact of upward social mobility on population mortality: Analysis with routine data. BMJ. 2002; 325(7356), 134-137 8. http ://legacy.measuredhs.com/accesssurveys/data_collection.cfm 9. Centro de Estudios Sociales y Demográficos (CESDEM) y Macro International Inc. Encuesta Sociodemográfica y sobre VIH/SIDA en los bateyes Estatales de la República Dominicana 2007 . Santo Domingo, República Dominicana y Calverton, Maryland: CESDEM y Macro International Inc.; 2008. (Original in Spanish). Aims 1. To assess the impact of educational attainment on tobacco use, alcohol consumption, concurrent use of tobacco and alcohol among adults in the DR. We explore whether these relationships differ between the bateyes (sugar cane plantations) residents and the general population in the DR. We also explore gender differences. Introduction According to the social gradient socioeconomic status (SES) shape individual’s health and life expectancy. SES is associated with cardiovascular disease (CVD) and CVD risk factors, such as cigarette smoking and alcohol consumption. 2 Studies have indicated that education is negatively associated with smoking. Inequalities in tobacco use, mainly among males and young individuals increase social inequalities in health. 2-5 In contrast, higher educational attainment is associated with higher and heavier daily alcohol consumption and drinking problems, mainly among women and older individuals. 5 Evidence supports that the impact of education level on smoking 6, 7 and alcohol consumption 5 differs by gender and by residential location. 3, 4 Little is known about the impact of educational attainment on tobacco use and alcohol consumption in the Dominican Republic (DR). Methods Data We analyzed data from the Demographic and Health Surveys (DHS) collected in the DR in 2007. 8 Sample selection Sampling process: cluster randomization Eligibility criteria: all women aged 15- 49 years and men aged 15-59 years who agreed to be interviewed Final sample for data analysis n=57,178 Measurements Educational attainment: no education (ref.), incomplete primary, complete primary, incomplete secondary, complete secondary, and higher Tobacco use (Do you smoke?) : yes vs. no (ref.) Alcohol (Have you drunk alcohol?): yes vs. no (ref.) Concurrent use: both smoking and drinking vs. none smoking or drinking (ref.) Data analysis STATA SE version 12.0 was used in the analysis. Descriptive statistics were assessed and logistic regressions were conducted to estimate the impact of educational attainment on tobacco use, alcohol consumption, and concurrent use. All regression analyses included age, sex, and residential location (bateyes vs. general population). Results Most participants were aged 30 to 34 years. Residents in bateyes were less educated than the general population. Women had higher levels of educational achievement than men in the general population. Tobacco use was higher among men than among women (p<0.001) regardless the residential location. Tobacco use among the bateyes’ residents was higher than in the general population (p<0.001). Alcohol consumption was higher in the general population than in the bateyes (p<0.001). Reported drinking alcohol was higher among men than women (p<0.001) for both locations. The concurrent use of tobacco and alcohol was reported in 30.5% of all cases and was more frequent among the bateyes residents than the general Discussion Our findings support that: There is a social gradient in tobacco use in the DR: a higher educational attainment reduces the likelihood of smoking. However, alcohol-related social gradient was negatively associated with educational attainment. Higher educational attainment is negatively associated with the use of both tobacco and alcohol. Being female is a protective factor for both using tobacco or consuming alcohol. Living is the bateyes increases the likelihood of using tobacco but not alcohol. Our findings reinforce the need for gender-specific, social class- targeted interventions that are tailored to the circumstances of specific communities to prevent tobacco use and alcohol consumption in the DR. Figure 1. Percentage of adults using tobacco by gender and residential location in the DR. DHS 2007. 0 5 10 15 20 T obacco use (% ) G eneral population Bateyes Males Fem ales Males Fem ales Figure 2. Percentage of adults using alcohol by gender and residential location in the DR. DHS 2007. 0 20 40 60 80 A lcoholconsum ptio n (% ) G eneral population Bateyes Males Fem ales Males Fem ales a Odds ratios; b Reference group: no education. c Reference group: males. d Reference group: general population Tobacco use n= 57, 178 Alcohol Consumption n= 57, 178 Concurrent use n= 16, 574 OR a P- value 95%CI OR a P- value 95%CI OR a P- value 95%CI Educational attainment b Incomplete primary 0.64 <0.001 0.58 - 0.72 1.97 <0.001 1.79 - 2.16 1.21 0.012 1.04 - 1.41 Complete primary 0.52 <0.001 0.44 - 0.62 2.38 <0.001 2.11 - 2.68 1.14 0.227 0.92 - 1.41 Incomplete secondary 0.39 <0.001 0.33 - 0.45 2.73 <0.001 2.47 - 3.02 1.02 0.806 0.85 - 1.23 Complete secondary 0.30 <0.001 0.25 - 0.35 2.82 <0.001 2.49 - 3.18 0.73 0.003 0.59 - 0.89 Higher 0.22 <0.001 0.19 - 0.26 3.08 <0.001 2.75 - 3.45 0.63 <0.00 1 0.51- 0.77 Age 1.06 <0.001 1.05 - 1.06 1.00 0.527 1.00 - 1.00 1.06 <0.00 1 1.06 - 1.07 Females c 0.64 0.002 0.59 - 0.68 0.30 <0.001 0.28 - 0.31 0.18 <0.00 1 0.16 - 0.20 Bateyes d 1.23 <0.001 1.08 - 1.41 0.94 0.295 0.85 - 1.05 1.12 0.219 0.94 - 1.34 Table 2. Logistic regression results for tobacco use and alcohol consumption in DR, DHS 2007 Figure 3. Percentage of concurrent use of tobacco and alcohol by gender and residential location in the DR. DHS 2007 0 10 20 30 40 50 C o n cu rre n t u se o f b o th to b a cco a n d a lco h G eneral population Bateyes Males Fem ales Males Fem ales Contact information: Michelle Jimenez [email protected] Table 1. Educational attainment by gender and residential location in DR, DHS 2007 Participant’scharacteristics Residentiallocation Bateyes n=3,329 Generalpopulation n= 53,849 M ales Fem ales M ales Fem ales n (%) n (%) n (%) n (%) Educationalattainment N o education Incom plete prim ary Com plete prim ary Incom plete secondary Com plete secondary H igher 336 896 137 275 87 42 10.1 27.1 3.8 8.2 2.6 1.0 253 751 132 274 96 50 8.2 23.0 3.9 7.9 5.5 2.3 1,583 12,000 2,152 6,373 2,512 2,899 3.0 21.7 4.0 11.8 4.6 5.3 1,293 8,826 2,117 6,723 3,260 4,531 2.4 16.5 4.0 12.5 6.1 8.3 *** ***

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Page 1: Michelle Jiménez de Tavárez, MD; Flavia C. D. Andrade, PhD Department of Kinesiology and Community Health, College of Applied Health Sciences, University

Michelle Jiménez de Tavárez, MD; Flavia C. D. Andrade, PhDDepartment of Kinesiology and Community Health, College of Applied Health Sciences, University of Illinois at Urbana-Champaign

Impact of Education in Tobacco Use and Alcohol Consumption in the Dominican Republic: A Social Gradient Perspective

Acknowledgements

The authors would like to thank DHS MEASURE and the Demography of Health and Aging Laboratory writing group.

References1. Marmot M. The Status Syndrome: How Social Standing Affects Our Health and Longevity. New York, Times Books, 2004. 319 pp.2. Yusuf S, Hawken S, Ôunpuu S, Dans T, Avezum A, Lanas F, et al. Effect of potentially modifiable risk factors associated with myocardial

infarction in 52 countries (the INTERHEART study): case-control study. The Lancet. 2004; 364(9438):937-952. 3. Cowell AJ. The relationship between education and health behavior: Some empirical evidence. Health Economics. 2006; 15:125-146.4. Yeon Kang J, Young Lee J, Hee Sung S, Mi Paek Y, In Choi T. The Comparison of Nutrient Intakes and Patterns of Alcohol Consumption

According to Social Status in Workers. [Abstract] Epidemiology. 2011; 22(1):S164. Doi: 10.1097/01.ede.0000392178.94629.875. Pampel FC, Denney JT. Cross-National Sources of Health Inequality: Education and Tobacco Use in the World Health Survey. Demography

2011:1-22.6. Harper S, Lynch J, Davey-Smith G. Social determinants and the decline of cardiovascular diseases: understanding the links. Annu Rev Public

Health. 2011; 32:39-69. 7. Heller RF, McElduff P, & Edwards R. Impact of upward social mobility on population mortality: Analysis with routine data. BMJ. 2002;

325(7356), 134-1378. http://legacy.measuredhs.com/accesssurveys/data_collection.cfm9. Centro de Estudios Sociales y Demográficos (CESDEM) y Macro International Inc. Encuesta Sociodemográfica y sobre VIH/SIDA en los bateyes

Estatales de la República Dominicana 2007. Santo Domingo, República Dominicana y Calverton, Maryland: CESDEM y Macro International Inc.; 2008. (Original in Spanish).

Aims

1. To assess the impact of educational attainment on tobacco use, alcohol consumption, concurrent use of tobacco and alcohol among adults in the DR.

We explore whether these relationships differ between the bateyes (sugar cane plantations) residents and the general population in the DR.

We also explore gender differences.

Introduction  According to the social gradient socioeconomic

status (SES) shape individual’s health and life expectancy.

SES is associated with cardiovascular disease (CVD) and CVD risk factors, such as cigarette smoking and alcohol consumption.2

Studies have indicated that education is negatively associated with smoking. Inequalities in tobacco use, mainly among males and young individuals increase social inequalities in health.2-5

In contrast, higher educational attainment is associated with higher and heavier daily alcohol consumption and drinking problems, mainly among women and older individuals.5

Evidence supports that the impact of education level on smoking6, 7 and alcohol consumption5 differs by gender and by residential location.3, 4

Little is known about the impact of educational attainment on tobacco use and alcohol consumption in the Dominican Republic (DR).

Methods

Data We analyzed data from the Demographic and Health

Surveys (DHS) collected in the DR in 2007.8

 Sample selection Sampling process: cluster randomization

Eligibility criteria: all women aged 15-49 years and men aged 15-59 years who agreed to be interviewed

Final sample for data analysis n=57,178

Measurements Educational attainment: no education (ref.), incomplete

primary, complete primary, incomplete secondary, complete secondary, and higher

Tobacco use (Do you smoke?) : yes vs. no (ref.)

Alcohol (Have you drunk alcohol?): yes vs. no (ref.)

Concurrent use: both smoking and drinking vs. none smoking or drinking (ref.)

Data analysisSTATA SE version 12.0 was used in the analysis. Descriptive statistics were assessed and logistic regressions were conducted to estimate the impact of educational attainment on tobacco use, alcohol consumption, and concurrent use. All regression analyses included age, sex, and residential location (bateyes vs. general population).

Results

Most participants were aged 30 to 34 years. Residents in bateyes were less educated than the general

population. Women had higher levels of educational achievement than

men in the general population.

There were gender differences on educational attainment among the general population (chi2=3 986; p<0.001), but not among the bateyes (chi2=156; p=0.204).

Tobacco use was higher among men than among women (p<0.001) regardless the residential location.

Tobacco use among the bateyes’ residents was higher than in the general population (p<0.001).

Alcohol consumption was higher in the general population than in the bateyes (p<0.001).

Reported drinking alcohol was higher among men than women (p<0.001) for both locations.

The concurrent use of tobacco and alcohol was reported in 30.5% of all cases and was more frequent among the bateyes residents than the general population (p<0.001) and among men than women (p<0.001).

.

Discussion Our findings support that:

There is a social gradient in tobacco use in the DR: a higher educational attainment reduces the likelihood of smoking.However, alcohol-related social gradient was negatively associated with educational attainment.Higher educational attainment is negatively associated with the use of both tobacco and alcohol.Being female is a protective factor for both using tobacco or consuming alcohol.Living is the bateyes increases the likelihood of using tobacco but not alcohol.

Our findings reinforce the need for gender-specific, social class-targeted interventions that are tailored to the circumstances of specific communities to prevent tobacco use and alcohol consumption in the DR.

Figure 1. Percentage of adults using tobacco by gender and residential location in the DR. DHS 2007.

05

10

15

20

Tob

acco

use (

%)

General population Bateyes

Males Females Males Females

Figure 2. Percentage of adults using alcohol by gender and residential location in the DR. DHS 2007.

02

04

06

08

0A

lcoh

ol co

nsu

mptio

n (

%)

General population Bateyes

Males Females Males Females

aOdds ratios; bReference group: no education. cReference group: males. dReference group: general population

  Tobacco use

n= 57, 178

Alcohol Consumption

n= 57, 178

Concurrent use

n= 16, 574

  ORa P-value 95%CI ORa P-value 95%CI ORa P-value 95%CI

Educational attainmentb                  

Incomplete primary 0.64 <0.001 0.58 - 0.72 1.97 <0.001 1.79 - 2.16 1.21 0.012 1.04 - 1.41

Complete primary 0.52 <0.001 0.44 - 0.62 2.38 <0.001 2.11 - 2.68 1.14 0.227 0.92 - 1.41

Incomplete secondary

0.39 <0.001 0.33 - 0.45 2.73 <0.001 2.47 - 3.02 1.02 0.806 0.85 - 1.23

Complete secondary 0.30 <0.001 0.25 - 0.35 2.82 <0.001 2.49 - 3.18 0.73 0.003 0.59 - 0.89

Higher 0.22 <0.001 0.19 - 0.26 3.08 <0.001 2.75 - 3.45 0.63 <0.001 0.51- 0.77

Age 1.06 <0.001 1.05 - 1.06 1.00 0.527 1.00 - 1.00 1.06 <0.001 1.06 - 1.07

Femalesc 0.64 0.002 0.59 - 0.68 0.30 <0.001 0.28 - 0.31 0.18 <0.001 0.16 - 0.20

Bateyesd 1.23 <0.001 1.08 - 1.41 0.94 0.295 0.85 - 1.05 1.12 0.219 0.94 - 1.34

Table 2. Logistic regression results for tobacco use and alcohol consumption in DR, DHS 2007

Figure 3. Percentage of concurrent use of tobacco and alcohol by gender and residential location in the DR. DHS 2007

01

02

03

04

05

0C

on

curr

ent u

se o

f b

oth

to

ba

cco a

nd a

lcoh

ol (%

)

General population Bateyes

Males Females Males Females

Contact information:

Michelle Jimenez

[email protected]

Table 1. Educational attainment by gender and residential location in DR, DHS 2007

Participant’s characteristics

Residential location

Bateyes

n=3, 329

General population

n= 53,849

Males Females Males Females

n (%) n (%) n (%) n (%)

Educational attainment

No education

Incomplete primary

Complete primary

Incomplete secondary

Complete secondary

Higher

336

896

137

275

87

42

10.1

27.1

3.8

8.2

2.6

1.0

253

751

132

274

96

50

8.2

23.0

3.9

7.9

5.5

2.3

1,583

12,000

2,152

6,373

2,512

2,899

3.0

21.7

4.0

11.8

4.6

5.3

1,293

8,826

2,117

6,723

3,260

4,531

2.4

16.5

4.0

12.5

6.1

8.3

***

***