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Television viewing and cardiovascular risk factors in young adults: The CARDIA study
ELSEVIER
Television Viewing The CARDIA Study
and Cardiovascular
Risk Factors in Young
STEPHEN SIDNEY, MD, BARBARA STERNFXLD, PHD, WILLIAM DAVID R. JACOBS, JR., PHD, MARGARET A. CHESNEY, PHD, AND STEPHEN B. HULLEY, MD
L. HASKELL,
Adults:
PHD,
Cross-sectional associations between self-reported hours of television (TV) viewing per day and cardiovascular risk factors were assessedin a biracial (black and white) study p~@&ion of 4280 men and women, ages 23 to 3.5 years, undergoing the year-5 follow-up examination for the Cardiovascular Risk Development in Young Adults {CARDZA) study in 1990 to 1991. Number of hours of TV viewing per day was higher in blacks than in whites and was inversely associated with education and income. Relative to “light” TV viewers (0 to 1 h/d), “heavy” TV viewers (Z 4 h/d) had a higher prevalence (P < 0.05) of obesity, smoking, and high hostility score in all rare/gender grouts, and of physical inactivity in all groups except black men. Among whites, “heavy” TV viewers had higher depression scores, and among blacks, reported more alcohol use. TV viewing was not associated with hypertension and lipid abnormalities. Heavy TV viewing is a modifiable behaoior that is associated with increased prevalence of several cardiovascular risk factors. Ann Epidemiol 1996;6: 154-l 59. KEY WORDS:
hypertension,
Alcohol consumption, smoking, television.
blood pressure, cholesterol, depression, hostility,
INTRODUCTION Television (TV) viewing is a nearly ubiquitous activity in the United States, ranking behind only work and sleep in the amount of time consumed by Americans (1). According to a report from Neilsen Media Research, 98% of US households have TV sets, and over a third of households have three sets or more (2). It can be calculated from this report that there are more than 200 million TV sets in American households, making the population of TV sets similar to the population of people. Average TV viewing time is more than 4 h/d for adults and more than 3 h/d for children (2). TV viewing has been associated with obesity in crosssectional studies (3-7). This relationship may be mediated by an inverse relationship of TV viewing to physical activity or by association with dietary habits. One study demonstrated that TV viewing lowered the metabolic rate of children to below the resting level (8). The relationship of TV
From the Kaiser Permanente Medical Care Program Division of Research, Oakland (S.S., B.S.); Stanford University, Center for Research in Disease Protection, Palo Alto (W.L.H.); University of Minnesota, Division of Epidemiology/School of Public Health, Minneapolis, MN (D.R.J.); and University of California, San Francisco, Center for AIDS Prevention Studies, San Francisco (M.A.C., S.B.H.), CA. Address reprint requests to: Stephen Sidney, MD, Kaiser Permanente Medical Care Program Division of Research, 3505 Broadway, Oakland, CA 94611. Received May 10, 1995; revised October 6, 1995; accepted October 23, 1995. 0 1996 by Elsevier Science Inc. 655 Avenue of the Americas, New York.
NY
10010
viewing to other cardiovascular risk factors has been less studied. Two studies showed a higher prevalence of hypercholesterolemia associated with TV viewing (9, 10). We assessed the duration of TV viewing in young adults who were participants in a study of cardiovascular risk factor development. The purpose was to examine (a) the distribution of duration of TV viewing in this study population by race, gender, and other sociodemographic characteristics; and (b) the relationship of TV viewing to physiologic, biochemical, and psychological and behavioral risk factors for cardiovascular diseases.
METHODS Study Population The study population was composed of 4352 young adults who were between the ages of 23 and 35 years at the time of the year-5 follow-up examination for the Cardiovascular Risk Development in Young Adults (CARDIA) study in 1990 to 1991, representing 86% (excluding deaths) of the cohort of 5115 young adults who were recruited for the CARDIA baseline examination, which took place in 1985 to 1986 (11). CARDIA subjects were recruited from four geographic locations (Birmingham, Alabama; Chicago, Illinois; Minneapolis, Minnesota; and Oakland, California). Community-Based sampling was performed in Birmingham, Chicago, and Minneapolis, while in Oakland, subjects
SSDI
1047-2797/%/$15.00 1047-2797(95)00135-2
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:khey cc al TV AND CARDIOVASCL ‘LAR RISK
were sampled from the membership of a large prepaid health care program. Recruitment efforts for the baseline examination were successful in achieving the aim of a study population that was approximately balanced by age (45% aged 18 to 24, 55% aged 25 to 30), race (52% black, 48% white), gender (46% men, 54% women), and education (40% having completed d 12 years of education, 60% having completed > 12 years of education). Further details of the recruitment process and description of the study population have been published elsewhere (11, 12). The present analysis was restricted to 4280 participants who reported duration of TV viewing. Assessment of Duration
of TV Viewing
Duration of TV viewing was assessedby the answers to the following questions on a self-administered questionnaire: 1. During leisure time do you watch television (a) never, (b) seldom, (c) sometimes, (d) often, or (e) very often? If the answer to question 1 is either b, c, d, ore, then answer question 2: 2. On the average, about how many hours per day do you hours watch television? If the individual answered “never” to question 1, he or she was considered to watch “0” hour of television per day.
Sociodemographic
Characteristics
Standardized questionnaires were used to assesseducation, income, and work status. Work status was assessedby answers to the following questions: “Are you working fulltime?” and “Are you working part-time?”
Physiologic
Variables
Resting systolic and diastolic blood pressures were taken using a random zero sphygmomanometer with the subject seated, after 5 minutes of rest. The average of the second and third measurements was used for analysis (13). Hypertensive patients were those having a systolic blood pressure of at least 140 mm Hg or diastolic blood pressure of at least 90 mm Hg, or those taking an antihypertensive medication. Height and weight were measured with the subject lightly clothed without shoes (13). Body mass index was calculated as weight (kg) divided by height (m’). Obesity was defined as a body mass index of at least 27.8 kg/m* for men and 27.3 kg/m* for women, with the cutoff points corresponding to 85th percentile body mass index for 20- to 29-year-old men and women in the National Health and Nutrition Examination Survey, 1976 to 1980 (NHANES II) (14).
Biochemical
15s
Measurements
Total cholesterol and triglyceride concentrations were determined using enzyme procedures on the ABA 200 Biochromatic instrument (Abbott Laboratories, North Chicago, Illinois) (15). High-density lipoprotein (HDL) was determined by precipitation with dextran sulfate/magnesium (16). Low-density lipoprotein (LDL) was calculated using an equation proposed by Friedewald and colleagues (17). Personality
Characteristics
Hostility was assessedusing the Cook-Medley scale; scores range from 0 to 50 (low to high) (18). Depressive symptomatology was assessedby the Center for Epidemiologic Studies Depression Scale (CES-0); scores range from 0 to 60 (low to high) (19). Habits Cigarette smoking status (current, prior, never) was defined by the following questions: “Have you ever smoked cigarettes regularly for at least 3 months? By ‘regularly’ we mean at least five cigarettes per week, almost every week.” An additional question defined current use: “Do you still smoke cigarettes regularly?” Alcohol use was assessedby the answer to the question: “How many drinks (wine or beer or hard liquor) do you usually have per week?” Current use of alcohol was defined by a nonzero answer to this question. Physical activity was assessedby interviewer-administered questionnaire, which assessedthe amount of time spent in 13 different activities of either heavy (> 5 metabolic equivalents (METS)) or moderate (3 to 4 METS) intensity (12 leisure, one occupation) during the last year (20). The score for the eight heavy-intensity activities included ir: rhe assessment was used in all analyses (20). Statistical Methods The Statistical Analysis System (SAS) was used for all statistical analyses (21). Multiple linear regression was used to examine the relationship of hours of television viewing per day to continuous outcome variables, and multiple logistic regression was used to assessodds ratios for dichotomous outcome variables associated with 4 or more hours of TV viewing relative to 0 to 1 hour of TV viewing per day. RESULTS TV Viewing
and Sociodemographic
Characteristics
Reported number of hours of TV viewing was higher in blacks than in whites. Heavy TV viewing (> 4 h d) was reported by more than one-third of blacks and less than 10% of whites (Table 1). TV viewing was unrelated to age except for a weak association among white women, ofwhom those 30 years and over reported slightly less time watching TV than did those of younger ages (Table 2). A strong
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No. of hours
Black men (N=882)
White men (N= 1045)
Black women (N=ll95)
White women (N=ll58)
3.4 13.5 23.2 20.6 39.2
12.0 36.5 29.6 12.2 9.9
5.4 13.8 24.9 22.3 33.7
18.7 33.6 27.0 12.5 8.2
0 1 2 3 ,4
than did people who did not work, with an intermediate level of mean duration of TV viewing in those working part-time. viewing
TABLE 1. Distribution of number of hours per day of television viewing, by age and gender (%)
inverse association between education and TV viewing was present in all race/gender groups; the difference in hours of TV viewing between blacks and whites was significant (P < 0.001) for both men and women after adjustment for age and education (data not shown). Income was inversely associated withTV viewing in all race/gender groups. There were significant center differences in TV viewing; mean hours of TV viewing was highest in Birmingham for three of the four race/gender groups (black men excepted), and was lowest in Oakland for all race/gender groups. People who worked full-time had a shorter mean duration of TV
Associations of Cardiovascular with Heavy TV Viewing
Risk Factors
The race- and gender-specific prevalence of risk factors and behaviors is shown in Table 3. The prevalence of hypertension and of cholesterol/lipoprotein abnormalities was below 10% in all race/gender groups (except for the 14.2% prevalence of low HDL in white men). Heavy TV viewing (2 4 h/d) was associated with a statistically significant higher risk (estimated by the odds ratio) of obesity, smoking, and hostility in all race/gender groups, and of low physical activity score in all except black men (adjusted for age, education, examination center, and as appropriate, body mass index, physical activity, smoking, and alcohol use) (Table 4). The odds ratios ranged from 1.5 to 2.3 for obesity, 1.7 to 2.8 for smoking, and 1.7 to 2.8 for hostility. Heavy TV viewing was associated with increased alcohol use in blacks (odds ratio 1.8 for black men, 1.5 for black women) but not in whites (P < 0.05 for race by TV
2. Mean number of hours per day (h/d) of TV viewing by race and gender and selected sociodemographic characteristics (standard error in parentheses) TABLE
White men
Black men
Black women
White women
h/d
N
h/d
N
h/d
N
h/d
N
3.8 (0.3) 3.3 (0.1) 3.4 (0.1) NS
121 335 426
2.1 (0.3) 1.9 (0.1) 1.8 (0.1) NS
59 321 665
3.1 (0.2) 3.3 (0.1) 3.2 (0.1) NS
163 434 598
1.8 (0.2) 1.9 (0.1) 1.6 (0.1) < 0.01
78 344 736
< 12.0 4.6 (0.4) 12.0-15.9 3.5 (0.1) 16.0+ 2.4 (0.1) < 0.001 P value Income (thousandsof dollars) < 15.9 4.0 (0.2) 16.0-34.9 3.5 (0.1) 35.0-49.9 3.0 (0.2) 50.0+ 2.7 (0.2) P value < O.OQl Center Birmingham 3.4 (0.2) Chicago 3.4 (0.2) Minneapolis 4.0 (0.2) Oakland 2.9 (0.1) P value” < 0.001 Employed full-time or part-time No 4.5 (0.3) Part-time 4.3 (0.2) Full-time 3.0 (0.1) P value < 0.001
92 612 175
3.8 (0.5) 2.0 (0.1) 1.6 (0.1) < 0.001
48 442 554
4.5 (0.3) 3.3 (0.1) 2.5 (0.1) < 0.001
85 846 264
3.7 (0.5) 1.9 (0.1) 1.4 (0.0) < 0.001
38 466 654
235 352 137 137
2.5 (0.3) 1.9 (0.1) 1.9 (0.1) 1.5 (0.1) < 0.001
128 348 223 335
3.9 (0.1) 3.0 (0.1) 2.6 (0.1) 2.6 (0.2) < 0.001
386 444 168 172
1.9 (0.2) 1.7 (0.1) 1.8 (0.1) 1.5 (0.1) NS
149 380 252 365
223 170 226 261
2.3 (0.1) 1.6 (0.1) 1.8 (0.1) 1.6 (0.1) < 0.001
240 235 395 224
3.7 (0.2) 3.0 (0.1) 3.5 (0.2) 2.9 (0.1) < 0.001
266 263 236 424
2.1 (0.1) 1.7 (0.1) 1.6 (0.1) 1.5 (0.1) < 0.001
201 252 389 316
145 106 628
2.6 (0.3) 2.0 (0.2) 1.8 (0.1) < 0.001
80 93 871
4.5 (0.2) 3.4 (0.2) 2.7 (0.1) < 0.001
280 138 777
2.4 (0.2) 1.6 (0.1) 1.5 (0.4) < 0.001
210 214 734
Characteristic
Age (Y) < 25 25-29 30+ P value”
Education (y)
a P value asmciatedwith F value. NS, not significant.
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Sidney et al. TV AND CARDIOVASCULAR RISK
TABLE 3. Race- and gender-specific
prevalence
of risk factors and behaviors
Black men 6.9 31.9 6.6 8.9 8.1 23.6 37.3 62.4 41.5 34.4
Hypertension Obesity Cholesterol 3 240 mg/dL LDL cholesterol 2 160 mg/dL HDL cholesterol < 35 mg/dL Low physical activity’ Smoking Alcohol use High hostility scoreb High depression scoreb O1 Lowest gender-specificquartile. b Highest gender-specificquartile. LDL, low,density lipoprotein; HDL,
high-density
(61) (280) (57) (77) (70) (208) (329) (550) (356) (299)
with n in parentheses)
White men
Black women
White women
4.3 (45) 23.1 (241) 6.3 (65) 9.0 (92) 14.2 (147) 25.8 (270) 24.7 (257) 7 1.4 (746) 13.7 (140) 20.9 (217)
5.8 (69) 46.2 (551) 3.0 (34) 4.4 (50) 2.7 (31) 29.6 (354) 32.2 (384) 38.2 (456) 39.2 (450) 33.0 (390)
1.4 (16) 19.5 (226) 4.1 (46) 4.8 (54) 2.9 (33) 18.7 (217) 21.9 (253) SO.3(582) 14.4 (162) 2 1.4 (247)
lipoprotein.
viewing interaction terms in gender-specific models). It is of interest to note, however, that the mean daily consumption of alcohol among alcohol users was highest among “heavy” TV viewers in all race-gender groups (data not shown). Heavy TV viewing was associated with an increased risk of high depression score in white men (odds ratio 2. I), and a nearly significant increased risk in white women (odds ratio 1.6). Heavy TV viewing was, in general, not associated with a significantly increased risk of hypertension or high cholesterol lipoprotein levels (except for hypertension in white men, and high LDL levels in black women). The findings within educational strata were generally consistent with the overall race and gender data. Using multiple linear regression, we also examined the relationship of TV viewing to these outcome variables assessed continuously rather than dichotomously, for example, systolic blood pressure, diastolic blood pressure, and total cholesterol (except for smoking and alcohol use; data not shown). In general, the findings were similar. TV view-
TABLE 4. Adjusted odds ratios for risk factors and behaviors per day relative to 0 to 1 hour of television viewing per day”
ing was positively associated with body mass index, hostility, and depression in all race/gender groups, but was not associated with systolic or diastolic blood pressure, or total cholesterol, LDL cholesterol, and HDL cholesterol levels.
DISCUSSION In this study, we found associations of self-reported heavy TV viewing with obesity, physical inactivity, negative psychological characteristics, and smoking. We also confirmed findings in previous studies that found the markedly higher level of TV viewing in blacks than in whites, and within each race/gender group, in those with lower education and income (2). The direct association between TV viewing and obesity was observed in several studies of children (3, 5, 7) and adults (4,6). Most studies of this association, including the present one, were cross-sectional. A statistically weak positive association between TV viewing and obesity was found
associated with
Black men Hypertension Obesityb Total cholesterol b 240 mg/dL LDL cholesterol I 160 mg/dL HDL cholesterol < 35 mg/dL Smoking Alcohol use d Low physical activity’ High hostility score High depression scote
(percentage,
157
1.0 (0.4, 1.7 (1.1, 1.8 (0.6, 1.2 (0.6, 1.1 (0.5, 2.8 (1.7, 1.8 (1.2, 1.4 (0.9, 2.2 (1.4, 1.5 (0.9,
” Adjusted for age, education, body mass index, physical activity, h Body rnas~, index not included in adjustment. ’ Smoking not included in adjustment. ’ Alcohol use not included in adjustment. ’ Physical activity score not included in adjustment. LDL, lowdensity lipoprotein; HDL, high-density lipoprotein.
more than 4 hours of television
White men 4.3 (1.6, 2.0 (1.2, 1.2 (0.5, 0.9 (0.4, 1.5 (0.8, 2.5 (1.5, 1.3 (0.8, 2.3 (1.4, 2.8 (1.6, 2.1 (1.3,
2.5) 2.7) 5.0) 2.6) 2.3) 4.6) 2.8) 2.3) 3.5) 2.3) smoking,
viewing
alcohol
11.6) 3.4) 2.7) 2.1) 2.8) 4.2) 2.1) 3.7) 5.0) 3.5)
use, and examination
center.
Black women
White women
1.3 (0.6,,3.0) 1.5 (1.1, 2.2) 1.5 (0.5, 4.1) 3.0 (1.1, 8.3) 1.6 (0.5, 5.2) 1.7 (1.1, 2.5) 1.6 (1.1, 2.3) 1.9 (1.3, 2.8) 1.7 (1.2, 2.5) 1.3 (0.9, 1.9)
0.3 (0, 1.9) 2.3 (1.4, 3.9) I .o (0.3, 3.0) 0.6 (0.2, 2.1) 1.0 (0.3, 3.2) 2.4 (1.4, 4.1) 0.9 (0.6, 1.5) 3.9 (2.3, 6.7) 1.9 (1.1, 3.5) 1.6 (1.0, 2.6)
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RISK
in the longitudinal assessment of 2153 children whose TV viewing was assessed during cycle II (1963 to 1965) of the National Health Examination Survey and who underwent anthropometric measurements in cycle III (1966 to 1970) (7). One mechanism by which TV viewing might cause obesity is through decreased physical activity. An inverse relationship between TV viewing and physical activity or physical fitness was demonstrated in other studies (5, 22), though the association between TV viewing and obesity persisted when physical activity was accounted for in the analysis (4). Another potential mechanism is by the effect of TV on metabolic rate. Metabolic rate during TV viewing was lower than during rest in 31 children (equivalent to 211 kcal/d lower) (8). Another potential mediator in the relationship of TV viewing to obesity is diet. Advertising of foods, often relatively nonnutritious, is common on TV, and watching TV correlates with consumption of advertised food (23, 24). Finally, the association of TV viewing with obesity may be mediated in part by socioeconomic status. TV viewing and obesity are strongly associated with socioeconomic status. The inverse relationship between obesity and socioeconomic status is complex, with evidence in the scientific literature supporting all three possible types of linkages between obesity and socioeconomic status, namely that obesity influences socioeconomic status, socioeconomic status influences obesity, or there are common factors influencing both obesity and socioeconomic status (25). Two studies reported an association between TV viewing and serum cholesterol, after adjustment for adiposity (9, 10). In the CARDIA study, the odds of high serum cholesterol was not significantly higher than 1 in any of the race/ gender groups, and there was no association between TV viewing and cholesterol assessed as a continuous variable. None of the studies in which this association was examined had data regarding dietary intake. We are unaware of any studies that examined the relationship of TV viewing to blood pressure or the lipoprotein variables evaluated in this report. Heavy TV viewing was not associated with increased risk of high levels of these risk factors, with the exception of hypertension in white men and high LDL cholesterol in black women. The association of TV viewing with smoking in part reflects the sociodemographic composition of “heavy” TV viewers, since lower education level is associated with heavy TV use and with greater usage of tobacco (26). However, “heavy” TV viewers were more likely to be smokers than were “light” viewers regardless of educational status in each of the race/gender groups (data not shown). It is unclear why the association between TV viewing and alcohol use is different in blacks and in whites. TV use may influence the use of tobacco and alcohol through advertising (in the case of alcohol) and through the depiction of their use in the program content. The associations of TV viewing with the psychological
variables, hostility (in all race/gender groups) and depression (in whites), are of particular interest in light of the current concern about TV violence (27, 28). This study cannot shed light on whether TV viewing leads to higher levels of hostility or depression or whether individuals with these characteristics seek out more TV. Research suggests that TV violence is correlated with aggressive behavior (29). The most compelling evidence indicating a link between violence and viewer aggression is provided by laboratory studies with children examining the effects of video violence. These studies demonstrated that aggressive thoughts increase as video programs become more violent (30, 31), and that observing video violence can lead to immediate aggressive behavior in viewers (29, 32). It may be that the subjects in this study who were characterized by higher scores in hostility turned to TV viewing as a form of coping or escaping from stress. Unfortunately, the literature does not support a view that observing violence leads to a vicarious gratification or catharsis of aggression. On the contrary, and what is of concern here, is that the literature suggests that TV may increase the likelihood that the subjects characterized by negative psychological characteristics will be exposed to violence and will see their negative psychological state reinforced. These data suggest that duration of TV viewing may serve as an important addition to measures of activity, in that it may be able to further differentiate people who would be all clumped together at the bottom of traditional activity measures. We believe that this study shows that assessment of TV viewing should be considered in the design of physical activity measurement instruments for epidemiologic studies. In summary, TV viewing was significantly associated with measures of obesity, physical activity (inverse association), smoking, and adverse psychological measures. Because of the cross-sectional nature of this analysis, causality cannot be inferred. However, it seems likely that a causal relationship of TV viewing to obesity and to physical inactivity does exist because of the inherent plausibility of these associations, and because of the increasing volume of published research supporting these associations. To the extent that it contributes negatively to health, heavy TV viewing (a 4 h/d) is a public health problem that is more prevalent in blacks than in whites, and in those with lower education and income.
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Television Viewing The CARDIA Study
and Cardiovascular
Risk Factors in Young
STEPHEN SIDNEY, MD, BARBARA STERNFXLD, PHD, WILLIAM DAVID R. JACOBS, JR., PHD, MARGARET A. CHESNEY, PHD, AND STEPHEN B. HULLEY, MD
L. HASKELL,
Adults:
PHD,
Cross-sectional associations between self-reported hours of television (TV) viewing per day and cardiovascular risk factors were assessedin a biracial (black and white) study p~@&ion of 4280 men and women, ages 23 to 3.5 years, undergoing the year-5 follow-up examination for the Cardiovascular Risk Development in Young Adults {CARDZA) study in 1990 to 1991. Number of hours of TV viewing per day was higher in blacks than in whites and was inversely associated with education and income. Relative to “light” TV viewers (0 to 1 h/d), “heavy” TV viewers (Z 4 h/d) had a higher prevalence (P < 0.05) of obesity, smoking, and high hostility score in all rare/gender grouts, and of physical inactivity in all groups except black men. Among whites, “heavy” TV viewers had higher depression scores, and among blacks, reported more alcohol use. TV viewing was not associated with hypertension and lipid abnormalities. Heavy TV viewing is a modifiable behaoior that is associated with increased prevalence of several cardiovascular risk factors. Ann Epidemiol 1996;6: 154-l 59. KEY WORDS:
hypertension,
Alcohol consumption, smoking, television.
blood pressure, cholesterol, depression, hostility,
INTRODUCTION Television (TV) viewing is a nearly ubiquitous activity in the United States, ranking behind only work and sleep in the amount of time consumed by Americans (1). According to a report from Neilsen Media Research, 98% of US households have TV sets, and over a third of households have three sets or more (2). It can be calculated from this report that there are more than 200 million TV sets in American households, making the population of TV sets similar to the population of people. Average TV viewing time is more than 4 h/d for adults and more than 3 h/d for children (2). TV viewing has been associated with obesity in crosssectional studies (3-7). This relationship may be mediated by an inverse relationship of TV viewing to physical activity or by association with dietary habits. One study demonstrated that TV viewing lowered the metabolic rate of children to below the resting level (8). The relationship of TV
From the Kaiser Permanente Medical Care Program Division of Research, Oakland (S.S., B.S.); Stanford University, Center for Research in Disease Protection, Palo Alto (W.L.H.); University of Minnesota, Division of Epidemiology/School of Public Health, Minneapolis, MN (D.R.J.); and University of California, San Francisco, Center for AIDS Prevention Studies, San Francisco (M.A.C., S.B.H.), CA. Address reprint requests to: Stephen Sidney, MD, Kaiser Permanente Medical Care Program Division of Research, 3505 Broadway, Oakland, CA 94611. Received May 10, 1995; revised October 6, 1995; accepted October 23, 1995. 0 1996 by Elsevier Science Inc. 655 Avenue of the Americas, New York.
NY
10010
viewing to other cardiovascular risk factors has been less studied. Two studies showed a higher prevalence of hypercholesterolemia associated with TV viewing (9, 10). We assessed the duration of TV viewing in young adults who were participants in a study of cardiovascular risk factor development. The purpose was to examine (a) the distribution of duration of TV viewing in this study population by race, gender, and other sociodemographic characteristics; and (b) the relationship of TV viewing to physiologic, biochemical, and psychological and behavioral risk factors for cardiovascular diseases.
METHODS Study Population The study population was composed of 4352 young adults who were between the ages of 23 and 35 years at the time of the year-5 follow-up examination for the Cardiovascular Risk Development in Young Adults (CARDIA) study in 1990 to 1991, representing 86% (excluding deaths) of the cohort of 5115 young adults who were recruited for the CARDIA baseline examination, which took place in 1985 to 1986 (11). CARDIA subjects were recruited from four geographic locations (Birmingham, Alabama; Chicago, Illinois; Minneapolis, Minnesota; and Oakland, California). Community-Based sampling was performed in Birmingham, Chicago, and Minneapolis, while in Oakland, subjects
SSDI
1047-2797/%/$15.00 1047-2797(95)00135-2
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:khey cc al TV AND CARDIOVASCL ‘LAR RISK
were sampled from the membership of a large prepaid health care program. Recruitment efforts for the baseline examination were successful in achieving the aim of a study population that was approximately balanced by age (45% aged 18 to 24, 55% aged 25 to 30), race (52% black, 48% white), gender (46% men, 54% women), and education (40% having completed d 12 years of education, 60% having completed > 12 years of education). Further details of the recruitment process and description of the study population have been published elsewhere (11, 12). The present analysis was restricted to 4280 participants who reported duration of TV viewing. Assessment of Duration
of TV Viewing
Duration of TV viewing was assessedby the answers to the following questions on a self-administered questionnaire: 1. During leisure time do you watch television (a) never, (b) seldom, (c) sometimes, (d) often, or (e) very often? If the answer to question 1 is either b, c, d, ore, then answer question 2: 2. On the average, about how many hours per day do you hours watch television? If the individual answered “never” to question 1, he or she was considered to watch “0” hour of television per day.
Sociodemographic
Characteristics
Standardized questionnaires were used to assesseducation, income, and work status. Work status was assessedby answers to the following questions: “Are you working fulltime?” and “Are you working part-time?”
Physiologic
Variables
Resting systolic and diastolic blood pressures were taken using a random zero sphygmomanometer with the subject seated, after 5 minutes of rest. The average of the second and third measurements was used for analysis (13). Hypertensive patients were those having a systolic blood pressure of at least 140 mm Hg or diastolic blood pressure of at least 90 mm Hg, or those taking an antihypertensive medication. Height and weight were measured with the subject lightly clothed without shoes (13). Body mass index was calculated as weight (kg) divided by height (m’). Obesity was defined as a body mass index of at least 27.8 kg/m* for men and 27.3 kg/m* for women, with the cutoff points corresponding to 85th percentile body mass index for 20- to 29-year-old men and women in the National Health and Nutrition Examination Survey, 1976 to 1980 (NHANES II) (14).
Biochemical
15s
Measurements
Total cholesterol and triglyceride concentrations were determined using enzyme procedures on the ABA 200 Biochromatic instrument (Abbott Laboratories, North Chicago, Illinois) (15). High-density lipoprotein (HDL) was determined by precipitation with dextran sulfate/magnesium (16). Low-density lipoprotein (LDL) was calculated using an equation proposed by Friedewald and colleagues (17). Personality
Characteristics
Hostility was assessedusing the Cook-Medley scale; scores range from 0 to 50 (low to high) (18). Depressive symptomatology was assessedby the Center for Epidemiologic Studies Depression Scale (CES-0); scores range from 0 to 60 (low to high) (19). Habits Cigarette smoking status (current, prior, never) was defined by the following questions: “Have you ever smoked cigarettes regularly for at least 3 months? By ‘regularly’ we mean at least five cigarettes per week, almost every week.” An additional question defined current use: “Do you still smoke cigarettes regularly?” Alcohol use was assessedby the answer to the question: “How many drinks (wine or beer or hard liquor) do you usually have per week?” Current use of alcohol was defined by a nonzero answer to this question. Physical activity was assessedby interviewer-administered questionnaire, which assessedthe amount of time spent in 13 different activities of either heavy (> 5 metabolic equivalents (METS)) or moderate (3 to 4 METS) intensity (12 leisure, one occupation) during the last year (20). The score for the eight heavy-intensity activities included ir: rhe assessment was used in all analyses (20). Statistical Methods The Statistical Analysis System (SAS) was used for all statistical analyses (21). Multiple linear regression was used to examine the relationship of hours of television viewing per day to continuous outcome variables, and multiple logistic regression was used to assessodds ratios for dichotomous outcome variables associated with 4 or more hours of TV viewing relative to 0 to 1 hour of TV viewing per day. RESULTS TV Viewing
and Sociodemographic
Characteristics
Reported number of hours of TV viewing was higher in blacks than in whites. Heavy TV viewing (> 4 h d) was reported by more than one-third of blacks and less than 10% of whites (Table 1). TV viewing was unrelated to age except for a weak association among white women, ofwhom those 30 years and over reported slightly less time watching TV than did those of younger ages (Table 2). A strong
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No. of hours
Black men (N=882)
White men (N= 1045)
Black women (N=ll95)
White women (N=ll58)
3.4 13.5 23.2 20.6 39.2
12.0 36.5 29.6 12.2 9.9
5.4 13.8 24.9 22.3 33.7
18.7 33.6 27.0 12.5 8.2
0 1 2 3 ,4
than did people who did not work, with an intermediate level of mean duration of TV viewing in those working part-time. viewing
TABLE 1. Distribution of number of hours per day of television viewing, by age and gender (%)
inverse association between education and TV viewing was present in all race/gender groups; the difference in hours of TV viewing between blacks and whites was significant (P < 0.001) for both men and women after adjustment for age and education (data not shown). Income was inversely associated withTV viewing in all race/gender groups. There were significant center differences in TV viewing; mean hours of TV viewing was highest in Birmingham for three of the four race/gender groups (black men excepted), and was lowest in Oakland for all race/gender groups. People who worked full-time had a shorter mean duration of TV
Associations of Cardiovascular with Heavy TV Viewing
Risk Factors
The race- and gender-specific prevalence of risk factors and behaviors is shown in Table 3. The prevalence of hypertension and of cholesterol/lipoprotein abnormalities was below 10% in all race/gender groups (except for the 14.2% prevalence of low HDL in white men). Heavy TV viewing (2 4 h/d) was associated with a statistically significant higher risk (estimated by the odds ratio) of obesity, smoking, and hostility in all race/gender groups, and of low physical activity score in all except black men (adjusted for age, education, examination center, and as appropriate, body mass index, physical activity, smoking, and alcohol use) (Table 4). The odds ratios ranged from 1.5 to 2.3 for obesity, 1.7 to 2.8 for smoking, and 1.7 to 2.8 for hostility. Heavy TV viewing was associated with increased alcohol use in blacks (odds ratio 1.8 for black men, 1.5 for black women) but not in whites (P < 0.05 for race by TV
2. Mean number of hours per day (h/d) of TV viewing by race and gender and selected sociodemographic characteristics (standard error in parentheses) TABLE
White men
Black men
Black women
White women
h/d
N
h/d
N
h/d
N
h/d
N
3.8 (0.3) 3.3 (0.1) 3.4 (0.1) NS
121 335 426
2.1 (0.3) 1.9 (0.1) 1.8 (0.1) NS
59 321 665
3.1 (0.2) 3.3 (0.1) 3.2 (0.1) NS
163 434 598
1.8 (0.2) 1.9 (0.1) 1.6 (0.1) < 0.01
78 344 736
< 12.0 4.6 (0.4) 12.0-15.9 3.5 (0.1) 16.0+ 2.4 (0.1) < 0.001 P value Income (thousandsof dollars) < 15.9 4.0 (0.2) 16.0-34.9 3.5 (0.1) 35.0-49.9 3.0 (0.2) 50.0+ 2.7 (0.2) P value < O.OQl Center Birmingham 3.4 (0.2) Chicago 3.4 (0.2) Minneapolis 4.0 (0.2) Oakland 2.9 (0.1) P value” < 0.001 Employed full-time or part-time No 4.5 (0.3) Part-time 4.3 (0.2) Full-time 3.0 (0.1) P value < 0.001
92 612 175
3.8 (0.5) 2.0 (0.1) 1.6 (0.1) < 0.001
48 442 554
4.5 (0.3) 3.3 (0.1) 2.5 (0.1) < 0.001
85 846 264
3.7 (0.5) 1.9 (0.1) 1.4 (0.0) < 0.001
38 466 654
235 352 137 137
2.5 (0.3) 1.9 (0.1) 1.9 (0.1) 1.5 (0.1) < 0.001
128 348 223 335
3.9 (0.1) 3.0 (0.1) 2.6 (0.1) 2.6 (0.2) < 0.001
386 444 168 172
1.9 (0.2) 1.7 (0.1) 1.8 (0.1) 1.5 (0.1) NS
149 380 252 365
223 170 226 261
2.3 (0.1) 1.6 (0.1) 1.8 (0.1) 1.6 (0.1) < 0.001
240 235 395 224
3.7 (0.2) 3.0 (0.1) 3.5 (0.2) 2.9 (0.1) < 0.001
266 263 236 424
2.1 (0.1) 1.7 (0.1) 1.6 (0.1) 1.5 (0.1) < 0.001
201 252 389 316
145 106 628
2.6 (0.3) 2.0 (0.2) 1.8 (0.1) < 0.001
80 93 871
4.5 (0.2) 3.4 (0.2) 2.7 (0.1) < 0.001
280 138 777
2.4 (0.2) 1.6 (0.1) 1.5 (0.4) < 0.001
210 214 734
Characteristic
Age (Y) < 25 25-29 30+ P value”
Education (y)
a P value asmciatedwith F value. NS, not significant.
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TABLE 3. Race- and gender-specific
prevalence
of risk factors and behaviors
Black men 6.9 31.9 6.6 8.9 8.1 23.6 37.3 62.4 41.5 34.4
Hypertension Obesity Cholesterol 3 240 mg/dL LDL cholesterol 2 160 mg/dL HDL cholesterol < 35 mg/dL Low physical activity’ Smoking Alcohol use High hostility scoreb High depression scoreb O1 Lowest gender-specificquartile. b Highest gender-specificquartile. LDL, low,density lipoprotein; HDL,
high-density
(61) (280) (57) (77) (70) (208) (329) (550) (356) (299)
with n in parentheses)
White men
Black women
White women
4.3 (45) 23.1 (241) 6.3 (65) 9.0 (92) 14.2 (147) 25.8 (270) 24.7 (257) 7 1.4 (746) 13.7 (140) 20.9 (217)
5.8 (69) 46.2 (551) 3.0 (34) 4.4 (50) 2.7 (31) 29.6 (354) 32.2 (384) 38.2 (456) 39.2 (450) 33.0 (390)
1.4 (16) 19.5 (226) 4.1 (46) 4.8 (54) 2.9 (33) 18.7 (217) 21.9 (253) SO.3(582) 14.4 (162) 2 1.4 (247)
lipoprotein.
viewing interaction terms in gender-specific models). It is of interest to note, however, that the mean daily consumption of alcohol among alcohol users was highest among “heavy” TV viewers in all race-gender groups (data not shown). Heavy TV viewing was associated with an increased risk of high depression score in white men (odds ratio 2. I), and a nearly significant increased risk in white women (odds ratio 1.6). Heavy TV viewing was, in general, not associated with a significantly increased risk of hypertension or high cholesterol lipoprotein levels (except for hypertension in white men, and high LDL levels in black women). The findings within educational strata were generally consistent with the overall race and gender data. Using multiple linear regression, we also examined the relationship of TV viewing to these outcome variables assessed continuously rather than dichotomously, for example, systolic blood pressure, diastolic blood pressure, and total cholesterol (except for smoking and alcohol use; data not shown). In general, the findings were similar. TV view-
TABLE 4. Adjusted odds ratios for risk factors and behaviors per day relative to 0 to 1 hour of television viewing per day”
ing was positively associated with body mass index, hostility, and depression in all race/gender groups, but was not associated with systolic or diastolic blood pressure, or total cholesterol, LDL cholesterol, and HDL cholesterol levels.
DISCUSSION In this study, we found associations of self-reported heavy TV viewing with obesity, physical inactivity, negative psychological characteristics, and smoking. We also confirmed findings in previous studies that found the markedly higher level of TV viewing in blacks than in whites, and within each race/gender group, in those with lower education and income (2). The direct association between TV viewing and obesity was observed in several studies of children (3, 5, 7) and adults (4,6). Most studies of this association, including the present one, were cross-sectional. A statistically weak positive association between TV viewing and obesity was found
associated with
Black men Hypertension Obesityb Total cholesterol b 240 mg/dL LDL cholesterol I 160 mg/dL HDL cholesterol < 35 mg/dL Smoking Alcohol use d Low physical activity’ High hostility score High depression scote
(percentage,
157
1.0 (0.4, 1.7 (1.1, 1.8 (0.6, 1.2 (0.6, 1.1 (0.5, 2.8 (1.7, 1.8 (1.2, 1.4 (0.9, 2.2 (1.4, 1.5 (0.9,
” Adjusted for age, education, body mass index, physical activity, h Body rnas~, index not included in adjustment. ’ Smoking not included in adjustment. ’ Alcohol use not included in adjustment. ’ Physical activity score not included in adjustment. LDL, lowdensity lipoprotein; HDL, high-density lipoprotein.
more than 4 hours of television
White men 4.3 (1.6, 2.0 (1.2, 1.2 (0.5, 0.9 (0.4, 1.5 (0.8, 2.5 (1.5, 1.3 (0.8, 2.3 (1.4, 2.8 (1.6, 2.1 (1.3,
2.5) 2.7) 5.0) 2.6) 2.3) 4.6) 2.8) 2.3) 3.5) 2.3) smoking,
viewing
alcohol
11.6) 3.4) 2.7) 2.1) 2.8) 4.2) 2.1) 3.7) 5.0) 3.5)
use, and examination
center.
Black women
White women
1.3 (0.6,,3.0) 1.5 (1.1, 2.2) 1.5 (0.5, 4.1) 3.0 (1.1, 8.3) 1.6 (0.5, 5.2) 1.7 (1.1, 2.5) 1.6 (1.1, 2.3) 1.9 (1.3, 2.8) 1.7 (1.2, 2.5) 1.3 (0.9, 1.9)
0.3 (0, 1.9) 2.3 (1.4, 3.9) I .o (0.3, 3.0) 0.6 (0.2, 2.1) 1.0 (0.3, 3.2) 2.4 (1.4, 4.1) 0.9 (0.6, 1.5) 3.9 (2.3, 6.7) 1.9 (1.1, 3.5) 1.6 (1.0, 2.6)
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in the longitudinal assessment of 2153 children whose TV viewing was assessed during cycle II (1963 to 1965) of the National Health Examination Survey and who underwent anthropometric measurements in cycle III (1966 to 1970) (7). One mechanism by which TV viewing might cause obesity is through decreased physical activity. An inverse relationship between TV viewing and physical activity or physical fitness was demonstrated in other studies (5, 22), though the association between TV viewing and obesity persisted when physical activity was accounted for in the analysis (4). Another potential mechanism is by the effect of TV on metabolic rate. Metabolic rate during TV viewing was lower than during rest in 31 children (equivalent to 211 kcal/d lower) (8). Another potential mediator in the relationship of TV viewing to obesity is diet. Advertising of foods, often relatively nonnutritious, is common on TV, and watching TV correlates with consumption of advertised food (23, 24). Finally, the association of TV viewing with obesity may be mediated in part by socioeconomic status. TV viewing and obesity are strongly associated with socioeconomic status. The inverse relationship between obesity and socioeconomic status is complex, with evidence in the scientific literature supporting all three possible types of linkages between obesity and socioeconomic status, namely that obesity influences socioeconomic status, socioeconomic status influences obesity, or there are common factors influencing both obesity and socioeconomic status (25). Two studies reported an association between TV viewing and serum cholesterol, after adjustment for adiposity (9, 10). In the CARDIA study, the odds of high serum cholesterol was not significantly higher than 1 in any of the race/ gender groups, and there was no association between TV viewing and cholesterol assessed as a continuous variable. None of the studies in which this association was examined had data regarding dietary intake. We are unaware of any studies that examined the relationship of TV viewing to blood pressure or the lipoprotein variables evaluated in this report. Heavy TV viewing was not associated with increased risk of high levels of these risk factors, with the exception of hypertension in white men and high LDL cholesterol in black women. The association of TV viewing with smoking in part reflects the sociodemographic composition of “heavy” TV viewers, since lower education level is associated with heavy TV use and with greater usage of tobacco (26). However, “heavy” TV viewers were more likely to be smokers than were “light” viewers regardless of educational status in each of the race/gender groups (data not shown). It is unclear why the association between TV viewing and alcohol use is different in blacks and in whites. TV use may influence the use of tobacco and alcohol through advertising (in the case of alcohol) and through the depiction of their use in the program content. The associations of TV viewing with the psychological
variables, hostility (in all race/gender groups) and depression (in whites), are of particular interest in light of the current concern about TV violence (27, 28). This study cannot shed light on whether TV viewing leads to higher levels of hostility or depression or whether individuals with these characteristics seek out more TV. Research suggests that TV violence is correlated with aggressive behavior (29). The most compelling evidence indicating a link between violence and viewer aggression is provided by laboratory studies with children examining the effects of video violence. These studies demonstrated that aggressive thoughts increase as video programs become more violent (30, 31), and that observing video violence can lead to immediate aggressive behavior in viewers (29, 32). It may be that the subjects in this study who were characterized by higher scores in hostility turned to TV viewing as a form of coping or escaping from stress. Unfortunately, the literature does not support a view that observing violence leads to a vicarious gratification or catharsis of aggression. On the contrary, and what is of concern here, is that the literature suggests that TV may increase the likelihood that the subjects characterized by negative psychological characteristics will be exposed to violence and will see their negative psychological state reinforced. These data suggest that duration of TV viewing may serve as an important addition to measures of activity, in that it may be able to further differentiate people who would be all clumped together at the bottom of traditional activity measures. We believe that this study shows that assessment of TV viewing should be considered in the design of physical activity measurement instruments for epidemiologic studies. In summary, TV viewing was significantly associated with measures of obesity, physical activity (inverse association), smoking, and adverse psychological measures. Because of the cross-sectional nature of this analysis, causality cannot be inferred. However, it seems likely that a causal relationship of TV viewing to obesity and to physical inactivity does exist because of the inherent plausibility of these associations, and because of the increasing volume of published research supporting these associations. To the extent that it contributes negatively to health, heavy TV viewing (a 4 h/d) is a public health problem that is more prevalent in blacks than in whites, and in those with lower education and income.
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