TEMPORAL
DISTRIBUTION
LEE W. VA Center
FREDERIKSEN
OF SMOKING*
and MARK
FRAZIER
and University of Mississippi Medical Jackson. Mississippi. U.S.A.
Center.
Abstract-Two experiments were conducted to determine the relationship between temporal distribution of cigarette consumption and overall smoking rate. In Experiment I, three groups (ii = 18 per group) of smokers (high. medium and low rate) were compared. Mean hourly smoking rates were highly correlated across groups with smoking rate accelerating throughout the morning, stabilizing and rapidly decelerating in late evening. Lower overall smoking rates were associated with a lower peak smoking rate and shorter smoking days. In Experiment 2, individual temporal distribution data was presented for eight subjects under high and low rate smoking conditions. A good deal of inter-subject and intra-subject variation was noted. Within subjects temporal distribution during high and low rate conditions tended to be poorly correlated. Low rate smoking was associated with a significantly shorter smoking day.
Little is currently known about the temporal distribution of smoking. A computerized literature search conducted by the National Clearinghouse for Smoking and Health yielded only a single article dealing directly with this topic. In this study, five subjects recorded the time of day that they smoked each cigarette (Hoffman-Tennov, 1972). Recording was continued over an extended time period ranging from 45 to 125 days. Results showed that the number of cigarettes smoked per day remained fairly constant during the recording period. The temporal distribution of smoking throughout the day also remained quite stable. Smoking was found to accelerate during the morning hours to a peak rate occurring at approximately mid-day. This rate was either maintained or decreased slowly until late evening when a rapid deceleration was observed. However, the conclusions that can be drawn from this study are limited. An extremely small sample was used (data was presented for only three subjects with the highest smoking rate being 18 cigarettes per day) and no recording reliability was reported. Nevertheless, the author concludes that smoking is not a fixed-interval phenomena but is probably more related to activity. This conclusion receives some indirect support from a recent study (Epstein & Collins, 1977). Self-monitoring data from 14 subjects showed a high degree of temporal and situational control of smoking. However, the specific time periods (morning, afternoon or evening) and situations (e.g. studying, driving, watching television) that were most closely associated with smoking varied a good deal across subjects. The current study examines the relationship between temporal distribution of smoking and overall smoking rate. In Experiment 1, between subject methodology is employed to compare temporal distribution in high, medium and low rate smokers. Experiment 2 uses within subject methodology to determine if a change in temporal distribution accompanies a reduction in overall smoking rate.
EXPERIMENT IN
HIGH.
1: TEMPORAL
MEDIUM
AND
LOW
DISTRIBUTION RATE
SMOKERS
Method Subjects. Subjects were sampled from two different geographic areas, Athens, Ohio and Jackson, Mississippi. The Ohio sample was comprised of students attending Ohio University (40%) and members of the local community (60”,!,). The Mississippi sample was comprised of members of the local community (6X”/,) and patients at the Veterans * Reprint requests should Jackson, MS 39216, U.S.A.
be directed
to Dr. Lee W. Frederiksen. 187
Department
of Psychology,
VA Center,
Administration Hospital (32”,,). All subjects reported being regular smokers for at least one year. Subjects were divided into three groups based on sell-monitored smoking rate (see below). The low group consisted of subjects smoking between 1.00 and IS.99 cigarettes per day (mean rate = 9.90). the medium group ranged from I6.00 to 24.W (mean rate = 19.08) and the high group had reported rates grcator thnn 25.00 cigarettes per duy (mean rate = 29.87). The high rate group was cotnpriscd of 12 males and 6 rcmales. The tnedium and low rate groups each contained 7 males and 1 I females. Geogntphically. the high rate group was comprised of 8 subjects from the Mississippi sample and IO from the Ohio sample. Both the medium and low rate groups contained 7 sub,jects from Mississippi and 11 l”rom Ohio. Proccdurc~. Each sukject continuully self-monitored his smoking over four consecutive days. Instructions were to stnokc as LISLMI hut record the e.xact time of’ day on ;I small card attached to the cigarette package just prior to smoking ench cigarette (Frederiksen, Epstein. & Kosevsky, I975). The first day of recording w;ts randotni/ed ;tcross days of the week. Self-monitoring reliability was obtained by huving each sub.jcct choose ;tn observer from his daily environment. This confederate observer checked the reliability of the subject’s recording for a minitnum of four hours during the four duy period. Observers were to surreptitiously note each time the subject smoked. An agreement wx scored if both the subject and confederate observer recorded ;I cigareltc ;ts starting at the same time (&4 minutes). Discrepancies or omissions were scored ;IS disagreements. Pcrcent agreement (agreements over agreements plus disagreements) ranged from W’,, to 100”,, with :I mean of 94.59”,,.
The mean hourly smoking rates for 311 three experimental groups ;tre shown in Fig. I. For each group. smoking rate accelerated throughout the morning hours to ;I maximum rate occurring at about noon. A high but somcwh;tt unstable smoking rate w;ts maintained until late evening (9-I I p.m.) when a rapid dccrcase in smoking w:ts observed. To ;tccess the extent to which this pattern of tcmporu1 distribution was common to all groups Pearson product moment correlations were calculated among the Mcdinm LOW = 0.96 (d.f. = 31. groups : High Mediutn = 0.90: High Low = 0.89: ~7< O.OOl). Since almost no smoking occurred during the nighttime hours. the inclusion of these hours in the calculations may lead to ;t biased estimation 01’ the shared variance.
Temporal
distribution
189
of smoking
To control for this possibility, the correlation coefficients were also calculated including only the hours 8 a.m.-midnight. The resulting correlations were of a lower magnitude but still statistically significant: High-Medium = 0.70; High-Low = 0.65; MediumLow = 0.85 (d.f. = 14, p < 0.01). To test the hypothesis that smoking is a fixed-interval phenomena, the observed distribution of cigarette consumption was compared to a fixed-interval (equal distribution) model using a chi-square analysis. Again, to avoid bias, only data from 8 a.m. to midnight were included in the analysis. The observed distributions, analyzed in two hour time blocks, each differed significantly from a fixed-interval model (High X’ (7) = 95.15; Medium X’ (7) = 125.46; Low X2 (7) = 24.94, p < 0.001). For each subject a mean smoking day (number of hours from first to last cigarette of the day) was calculated based on the four days of recording. The obtained group means (High = 16.15, Medium = 14.80, Low = 13.1 1) were significantly different (F(2.51) = 11.15, p < 0.01). Post-hoc comparisons among the groups (Duncan’s Multiple Range Test) were all significant at p < 0.05 or better. Finally, to assess intergroup differences a two factor ANOVA (Groups x Hours) was completed. Significant F-ratios were obtained on the main factors of Groups (F(2,51) = 50.67, p < 0.0001) and Hours (F(23,l 173) = 40.42, p 0.05
this program subjects tither underwent behavioral contracting (contract) or a self-control procedure designed to decrease smoking by imposing increasing delays in the chain of consumatory behavior (delay). Demographic, smoking history and treatment proccdure tbr each subject are shown in Table I. l+oc&rc~. Subjects recorded each cigarette smoked and reliability was assessed as described in Experiment 1. The mean hourly smoking rate and number of hours from first to last cigarette were calculated for four consecutive days of baseline recording (high rate condition) and also during four consecutive days following treatment (lob rate condition). For each of the eight subjects all of the confederate observer’s reliability checks were in complete agreement (k4 min) with the subject’s self-monitoring data.
The mean hourly smoking rates for all subjects under high and low rate conditions arc shown in Fig. 2. There is 21good deal of between subject variation in the temporal distribution of smoking. For example. during the high rate condition Subjects 6 and X both averaged 18.00 cigarettes per day. However, the temporal distribution of this
4 6 6 a.m.
10 12 2
p.m.
4
6
6
4
10 12 2
6
a.m.
a.m.
6
10 12 2
_
high
4
6
8
.--low
10 12 2
p.m.
a.m.
TIME Fig. 2. Mean
hourly
smoking
rntcs for each individual suhjcct smoking conditions.
under
both
Hugh and
low rate
Temporal
distribution
191
of smoking
consumption varied a good deal. Further, the consistent temporal patterning found in Experiment 1 is not evident in the individual subject data. Within each subject there is also a good deal of variation in the hourly smoking rates. Examination of individual correlation coefficients indicates a weak relationship between hourly smoking rates in high and low rate conditions (Table 1). However, as in Experiment 1, smoking is clearly not a fixed-interval (equal distribution) phenomena. Each subject’s mean smoking rate during high and low rate conditions is shown in Table 1. For each subject their smoking day during the low rate condition was shorter than during high rate condition. The difference between these conditions was statistically significant (t(7) = 4.36. p < 0.01).
Gerwwl
discussiorz
Cigarette consumption is clearly not a fixed-interval phenomena. This conclusion is consistent across both grouped and individual subject data. If smoking is not equally distributed throughout the day, what is the nature of the distribution? The results of Experiment 1 indicate that smoking tends to accelerate throughout the morning hours and remain elevated until the late evening at which time a rapid deceleration occurs. However, the examination of individual subject data (Experiment 2) indicates a good deal of inter-subject and intra-subject variability. One finding that is consistent. is that virtually every subject does have at least one period of “peak” consumption (Fig. 2). While it can be said that smoking is not a fixed-interval phenomena it cannot be said that the pattern of temporal distribution found with grouped data is necessarily applicable to any particular smoker. Nor is there necessarily within subject consistency in temporal distribution across smoking rates. This latter conclusion must be qualified with the fact the individuals in Experiment 2 were engaged in a smoking control program. An unexpected and previously unreported finding is the variation in “smoking day”. Both between and within subjects, higher overall smoking rates were associated with longer smoking days. Thus high rate smokers not only smoke more during the smoking day but they also start smoking earlier and/or continue smoking later in the day. Systematically shortening the smoking day may prove to be a “natural” stimulus control technique with therapeutic possibilities. The between group similarity in temporal distribution found in Experiment I raises the possibility that there is a common pattern of temporal distribution that may be biologically based. However, enthusiasm about an “underlying” distribution must be tempered with the large inter-subject difference found in Experiment 2. It is likely that any common patterning is strongly influenced by individual situational control. Finally. temporal distribution may in itself have important health implications. For example, blood carboxyhemoglobin can be influenced not only by how many cigarettes are smoked. but also by how closely they are spaced in time (Wald. Howard. Smith & Bailey, 197.5). Other important factors that need to be taken into account in the assessment of health risks are \~hat is smoked (substance) and /ZO\Vit is smoked (smoking topography) as well as when and how frequently smoking occurs (Fredcriksen, Miller & Peterson, 1977).
REFERENCES Epstein. 1977.
L. H. & Collins,
F.. The measurement
of situational
intluences
of smoking.
Addictiw
Bchriors.
2. 47-53.
Frederiksen. L. W., Single-case designs in the modification of smoking. Addicrice Bch~iors. 1976. 1. 3 I I- 3 19. Frederlksen. L. W., Epstein. L. H. & Kosevsky. B. P. Reliability and controlling effects of three procedures for self-monitoring smoking. Ps~~cl?o/oqica/ Record. 1975. 25. 25.5-763. Fredcriksen. L. W.. Peterson. G. L. & Murphy. W. D., Controlled smoking: Development and maintenance. A~/~/rc~/ir~c 13~~ll~rr-ioIxI Y7h. I. I ‘J3 196.
192
LI:C W. FKI:IXRIKSENand MARK FKALKR
Frederiksen, L. W.. Miller, P. M. & Peterson. G. L.. Topographical components of smoking behavior. .dr/t/icrirc, &~llal~ioKF. 1977. 2. 55-61. Hoffmali-Tennov. D., Self-reports of cigarette smoking. In R. G. Richardson (Ed.). T/IC s~wutt/ wwltl COII/CYI~CC, 011 sw~kiq und hrulrh. London: Pitman Medical. 1972. Wald, N.. Howard. S.. Smith, P. G. & Bailey. A.. Use of carboxyhemoglobin levels to predict the dcvelopmcnt of diseases associated with cigarette smoking. Tlwr-a\-. 1975, 30. 133-140.
DISTRIBUTION
LEE W. VA Center
FREDERIKSEN
OF SMOKING*
and MARK
FRAZIER
and University of Mississippi Medical Jackson. Mississippi. U.S.A.
Center.
Abstract-Two experiments were conducted to determine the relationship between temporal distribution of cigarette consumption and overall smoking rate. In Experiment I, three groups (ii = 18 per group) of smokers (high. medium and low rate) were compared. Mean hourly smoking rates were highly correlated across groups with smoking rate accelerating throughout the morning, stabilizing and rapidly decelerating in late evening. Lower overall smoking rates were associated with a lower peak smoking rate and shorter smoking days. In Experiment 2, individual temporal distribution data was presented for eight subjects under high and low rate smoking conditions. A good deal of inter-subject and intra-subject variation was noted. Within subjects temporal distribution during high and low rate conditions tended to be poorly correlated. Low rate smoking was associated with a significantly shorter smoking day.
Little is currently known about the temporal distribution of smoking. A computerized literature search conducted by the National Clearinghouse for Smoking and Health yielded only a single article dealing directly with this topic. In this study, five subjects recorded the time of day that they smoked each cigarette (Hoffman-Tennov, 1972). Recording was continued over an extended time period ranging from 45 to 125 days. Results showed that the number of cigarettes smoked per day remained fairly constant during the recording period. The temporal distribution of smoking throughout the day also remained quite stable. Smoking was found to accelerate during the morning hours to a peak rate occurring at approximately mid-day. This rate was either maintained or decreased slowly until late evening when a rapid deceleration was observed. However, the conclusions that can be drawn from this study are limited. An extremely small sample was used (data was presented for only three subjects with the highest smoking rate being 18 cigarettes per day) and no recording reliability was reported. Nevertheless, the author concludes that smoking is not a fixed-interval phenomena but is probably more related to activity. This conclusion receives some indirect support from a recent study (Epstein & Collins, 1977). Self-monitoring data from 14 subjects showed a high degree of temporal and situational control of smoking. However, the specific time periods (morning, afternoon or evening) and situations (e.g. studying, driving, watching television) that were most closely associated with smoking varied a good deal across subjects. The current study examines the relationship between temporal distribution of smoking and overall smoking rate. In Experiment 1, between subject methodology is employed to compare temporal distribution in high, medium and low rate smokers. Experiment 2 uses within subject methodology to determine if a change in temporal distribution accompanies a reduction in overall smoking rate.
EXPERIMENT IN
HIGH.
1: TEMPORAL
MEDIUM
AND
LOW
DISTRIBUTION RATE
SMOKERS
Method Subjects. Subjects were sampled from two different geographic areas, Athens, Ohio and Jackson, Mississippi. The Ohio sample was comprised of students attending Ohio University (40%) and members of the local community (60”,!,). The Mississippi sample was comprised of members of the local community (6X”/,) and patients at the Veterans * Reprint requests should Jackson, MS 39216, U.S.A.
be directed
to Dr. Lee W. Frederiksen. 187
Department
of Psychology,
VA Center,
Administration Hospital (32”,,). All subjects reported being regular smokers for at least one year. Subjects were divided into three groups based on sell-monitored smoking rate (see below). The low group consisted of subjects smoking between 1.00 and IS.99 cigarettes per day (mean rate = 9.90). the medium group ranged from I6.00 to 24.W (mean rate = 19.08) and the high group had reported rates grcator thnn 25.00 cigarettes per duy (mean rate = 29.87). The high rate group was cotnpriscd of 12 males and 6 rcmales. The tnedium and low rate groups each contained 7 males and 1 I females. Geogntphically. the high rate group was comprised of 8 subjects from the Mississippi sample and IO from the Ohio sample. Both the medium and low rate groups contained 7 sub,jects from Mississippi and 11 l”rom Ohio. Proccdurc~. Each sukject continuully self-monitored his smoking over four consecutive days. Instructions were to stnokc as LISLMI hut record the e.xact time of’ day on ;I small card attached to the cigarette package just prior to smoking ench cigarette (Frederiksen, Epstein. & Kosevsky, I975). The first day of recording w;ts randotni/ed ;tcross days of the week. Self-monitoring reliability was obtained by huving each sub.jcct choose ;tn observer from his daily environment. This confederate observer checked the reliability of the subject’s recording for a minitnum of four hours during the four duy period. Observers were to surreptitiously note each time the subject smoked. An agreement wx scored if both the subject and confederate observer recorded ;I cigareltc ;ts starting at the same time (&4 minutes). Discrepancies or omissions were scored ;IS disagreements. Pcrcent agreement (agreements over agreements plus disagreements) ranged from W’,, to 100”,, with :I mean of 94.59”,,.
The mean hourly smoking rates for 311 three experimental groups ;tre shown in Fig. I. For each group. smoking rate accelerated throughout the morning hours to ;I maximum rate occurring at about noon. A high but somcwh;tt unstable smoking rate w;ts maintained until late evening (9-I I p.m.) when a rapid dccrcase in smoking w:ts observed. To ;tccess the extent to which this pattern of tcmporu1 distribution was common to all groups Pearson product moment correlations were calculated among the Mcdinm LOW = 0.96 (d.f. = 31. groups : High Mediutn = 0.90: High Low = 0.89: ~7< O.OOl). Since almost no smoking occurred during the nighttime hours. the inclusion of these hours in the calculations may lead to ;t biased estimation 01’ the shared variance.
Temporal
distribution
189
of smoking
To control for this possibility, the correlation coefficients were also calculated including only the hours 8 a.m.-midnight. The resulting correlations were of a lower magnitude but still statistically significant: High-Medium = 0.70; High-Low = 0.65; MediumLow = 0.85 (d.f. = 14, p < 0.01). To test the hypothesis that smoking is a fixed-interval phenomena, the observed distribution of cigarette consumption was compared to a fixed-interval (equal distribution) model using a chi-square analysis. Again, to avoid bias, only data from 8 a.m. to midnight were included in the analysis. The observed distributions, analyzed in two hour time blocks, each differed significantly from a fixed-interval model (High X’ (7) = 95.15; Medium X’ (7) = 125.46; Low X2 (7) = 24.94, p < 0.001). For each subject a mean smoking day (number of hours from first to last cigarette of the day) was calculated based on the four days of recording. The obtained group means (High = 16.15, Medium = 14.80, Low = 13.1 1) were significantly different (F(2.51) = 11.15, p < 0.01). Post-hoc comparisons among the groups (Duncan’s Multiple Range Test) were all significant at p < 0.05 or better. Finally, to assess intergroup differences a two factor ANOVA (Groups x Hours) was completed. Significant F-ratios were obtained on the main factors of Groups (F(2,51) = 50.67, p < 0.0001) and Hours (F(23,l 173) = 40.42, p 0.05
this program subjects tither underwent behavioral contracting (contract) or a self-control procedure designed to decrease smoking by imposing increasing delays in the chain of consumatory behavior (delay). Demographic, smoking history and treatment proccdure tbr each subject are shown in Table I. l+oc&rc~. Subjects recorded each cigarette smoked and reliability was assessed as described in Experiment 1. The mean hourly smoking rate and number of hours from first to last cigarette were calculated for four consecutive days of baseline recording (high rate condition) and also during four consecutive days following treatment (lob rate condition). For each of the eight subjects all of the confederate observer’s reliability checks were in complete agreement (k4 min) with the subject’s self-monitoring data.
The mean hourly smoking rates for all subjects under high and low rate conditions arc shown in Fig. 2. There is 21good deal of between subject variation in the temporal distribution of smoking. For example. during the high rate condition Subjects 6 and X both averaged 18.00 cigarettes per day. However, the temporal distribution of this
4 6 6 a.m.
10 12 2
p.m.
4
6
6
4
10 12 2
6
a.m.
a.m.
6
10 12 2
_
high
4
6
8
.--low
10 12 2
p.m.
a.m.
TIME Fig. 2. Mean
hourly
smoking
rntcs for each individual suhjcct smoking conditions.
under
both
Hugh and
low rate
Temporal
distribution
191
of smoking
consumption varied a good deal. Further, the consistent temporal patterning found in Experiment 1 is not evident in the individual subject data. Within each subject there is also a good deal of variation in the hourly smoking rates. Examination of individual correlation coefficients indicates a weak relationship between hourly smoking rates in high and low rate conditions (Table 1). However, as in Experiment 1, smoking is clearly not a fixed-interval (equal distribution) phenomena. Each subject’s mean smoking rate during high and low rate conditions is shown in Table 1. For each subject their smoking day during the low rate condition was shorter than during high rate condition. The difference between these conditions was statistically significant (t(7) = 4.36. p < 0.01).
Gerwwl
discussiorz
Cigarette consumption is clearly not a fixed-interval phenomena. This conclusion is consistent across both grouped and individual subject data. If smoking is not equally distributed throughout the day, what is the nature of the distribution? The results of Experiment 1 indicate that smoking tends to accelerate throughout the morning hours and remain elevated until the late evening at which time a rapid deceleration occurs. However, the examination of individual subject data (Experiment 2) indicates a good deal of inter-subject and intra-subject variability. One finding that is consistent. is that virtually every subject does have at least one period of “peak” consumption (Fig. 2). While it can be said that smoking is not a fixed-interval phenomena it cannot be said that the pattern of temporal distribution found with grouped data is necessarily applicable to any particular smoker. Nor is there necessarily within subject consistency in temporal distribution across smoking rates. This latter conclusion must be qualified with the fact the individuals in Experiment 2 were engaged in a smoking control program. An unexpected and previously unreported finding is the variation in “smoking day”. Both between and within subjects, higher overall smoking rates were associated with longer smoking days. Thus high rate smokers not only smoke more during the smoking day but they also start smoking earlier and/or continue smoking later in the day. Systematically shortening the smoking day may prove to be a “natural” stimulus control technique with therapeutic possibilities. The between group similarity in temporal distribution found in Experiment I raises the possibility that there is a common pattern of temporal distribution that may be biologically based. However, enthusiasm about an “underlying” distribution must be tempered with the large inter-subject difference found in Experiment 2. It is likely that any common patterning is strongly influenced by individual situational control. Finally. temporal distribution may in itself have important health implications. For example, blood carboxyhemoglobin can be influenced not only by how many cigarettes are smoked. but also by how closely they are spaced in time (Wald. Howard. Smith & Bailey, 197.5). Other important factors that need to be taken into account in the assessment of health risks are \~hat is smoked (substance) and /ZO\Vit is smoked (smoking topography) as well as when and how frequently smoking occurs (Fredcriksen, Miller & Peterson, 1977).
REFERENCES Epstein. 1977.
L. H. & Collins,
F.. The measurement
of situational
intluences
of smoking.
Addictiw
Bchriors.
2. 47-53.
Frederiksen. L. W., Single-case designs in the modification of smoking. Addicrice Bch~iors. 1976. 1. 3 I I- 3 19. Frederlksen. L. W., Epstein. L. H. & Kosevsky. B. P. Reliability and controlling effects of three procedures for self-monitoring smoking. Ps~~cl?o/oqica/ Record. 1975. 25. 25.5-763. Fredcriksen. L. W.. Peterson. G. L. & Murphy. W. D., Controlled smoking: Development and maintenance. A~/~/rc~/ir~c 13~~ll~rr-ioIxI Y7h. I. I ‘J3 196.
192
LI:C W. FKI:IXRIKSENand MARK FKALKR
Frederiksen, L. W.. Miller, P. M. & Peterson. G. L.. Topographical components of smoking behavior. .dr/t/icrirc, &~llal~ioKF. 1977. 2. 55-61. Hoffmali-Tennov. D., Self-reports of cigarette smoking. In R. G. Richardson (Ed.). T/IC s~wutt/ wwltl COII/CYI~CC, 011 sw~kiq und hrulrh. London: Pitman Medical. 1972. Wald, N.. Howard. S.. Smith, P. G. & Bailey. A.. Use of carboxyhemoglobin levels to predict the dcvelopmcnt of diseases associated with cigarette smoking. Tlwr-a\-. 1975, 30. 133-140.
