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However, the components of CS involved in this injury are unknown. Acrolein is a highly reactive a, - unsaturated aldehyde that is present in CS and in exhaled breath condensates and blood of smokers. Our preliminary data indicate that acrolein, like CS, increases lung vascular EC permeability in vivo and in vitro; disrupts actin stress fibers, adherens junctions, and focal adhesion complexes; and decreases RhoA and FAK activation.

CS- and acrolein-induced lung endothelial injury is prevented by inhibition of aldehyde stress in vivo and in vitro. Our Overall Objective is to understand the mechanism of CS-induced lung endothelial cell dysfunction. We hypothesize that acrolein mediates CS-induced EC dysfunction resulting in increased permeability pulmonary edema via carbonylation of RhoA and FAK in lung endothelial cells. The effects of acrolein on lung microvascular barrier function in vivo and in vitro, including: The effects f acrolein on mouse lung microvascular permeability.

The effects of acrolein on RhoA and FAK carbonylation and inactivation and the mechanism s of these changes. If inhibition of protein carbonylation attenuates CS- and acrolein-induced increased vascular permeability in vivo and in cultured lung EC. Of the three variables used to test the hypothesis of nicotine dependence, two were significant in the hypothesized direction.

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Scores on the FTND were not significantly different. Variables used for test of hypotheses 1 in bold; hypothesized comparison exceeding the set probability level of. The second hypothesis was confirmed by three of the four variables tested.

The two age groups did not differ on level of social participation. The third hypothesis, that there would be differences between the age groups in motivation for abstinence, was not supported. Mean scores on the scaled question assessing desire for abstinence were identical—8. With respect to abstinence goals, The fifth hypothesis was supported. A gender by age group interaction was also found. For Study 1, of the exclusions came from telephone screening.

An additional 83 individuals were screened out at the pretreatment assessments for a total of potential subjects screened from the study. For Study 2, there were ineligible participants based on telephone screenings. An additional 47 potential participants were screened out at the pretreatment assessment, for a total of Since Major Depression Disorder was not assessed during telephone screening, we can not estimate of the number of potential participants who applied to the program with current MDD.

However, at the pre-treatment assessment, 6 of the participants under 50 and 9 participants over 50 were ruled out due to current depression. They reported experiencing less stress, better moods, and better mental health than the younger smokers. There was no difference in their levels of social involvement. There were no significant differences in alcohol consumption between the two groups. However, their marijuana use, especially that of the female subjects, was less than that of smokers under 50 years of age.

Although these differences reached the preset levels of significance, for the most part they were numerically small since the large sample size provided considerable power. Despite the small differences, the differences between older and younger smokers on psychosocial variables are consistent. For example, smokers under 50 may experience episodes of poor mood more frequently and be more likely to relapse in response to them simply due to increased event frequency.

Emphasis on mood management may be less important for older smokers. The smoking behavior of older smokers has changed in the past decade. Earlier studies reported mean numbers of cigarettes smoked ranging from approximately 23— The mean in the current study was approximately 21, which, while higher than younger smokers entering the clinic, is below that reported previously. On other smoking behavior measures, however, subjects entering our clinic were similar to those of 16 years ago.

They had smoked for approximately 38 years. They remain a likely population for treatment with NRT, since their level of cigarette intake and years of smoking are higher than for younger smokers. In both groups, the percentage of individuals with alcohol abuse or dependence is high. This could reflect variables unique to our clinic—for example, word of mouth referrals among AA attendees.

We have no evidence this occurred, however. There was nothing in the materials used to solicit participants that should have differentially attracted those with depressive disorders or using antidepressants. Neither the clinic nor the studies were identified as being associated with the Department of Psychiatry. Older smokers smoked slightly more cigarettes than younger smokers, yet a smaller proportion had a nicotine dependence or a nicotine withdrawal diagnosis. There were no significant differences between the age groups in days of drinking or amount per day, yet the older smokers were less likely to have a diagnosis of alcohol dependence or abuse on the C-DIS.

These findings led to informal examination of differences in endorsement rates of smokers in the two different age categories for diagnostic category on the C-DIS. The differences on the Alcohol Abuse section of the C-DIS appeared to be driven by a single item concerning the interference of drinking or withdrawal symptoms functioning in school. Examination of the items that comprise the Nicotine Withdrawal diagnosis suggested that older individuals were less likely to endorse subjective withdrawal symptoms than younger smokers.

Examination of the Nicotine Dependence and Alcohol Dependence sections of the C-DIS did not provide information that could lead to a more systematic examination of the differences between the two age groups. Differences between smokers 50 and older and those under 50, even those that were significant, were small. This finding calls into question the Practice Guidelines use of age 50 as the dividing line for older smokers. We did inspect our data to determine whether a different age for example, 65 would provide a better cut-point, but none emerged.

A study in a larger, population based sample, might provide an useful estimate, however. On the other hand, variables correlated with age, such as level of tobacco dependence, may be more important in designing treatment programs than age itself.

Generalization is limited by the restricted nature of the sample, that is, smokers applying to a university based smoking research clinic in an urban setting. This may differentially affect the smokers aged 50 years and older, since problems with mobility may have precluded participation by those in the very oldest age groups who may have concerns that would limit their participation; for example, traveling to the clinic. Nevertheless, they are suggestive of both differences and similarities between the two age groups that should be further explored in the general population.

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1. INTRODUCTION

University of California, San Francisco. The publisher's final edited version of this article is available at Nicotine Tob Res. See other articles in PMC that cite the published article. Abstract Quitting smoking benefits older individuals, yet there are few recent data describing older smokers. We evaluated six hypotheses: Open in a separate window. Variables and Measures 2. Tobacco Dependence Tobacco dependence, evaluated in the first hypothesis, was determined by three variables: Psychosocial Functioning Psychosocial functioning was measured by four instruments: Alcohol and Marijuana Use Alcohol use was measured by two items asking the number of days the individual had an alcoholic drink and the average number of drinks per day.

Physical Functioning The Physical Composite Score of the SF was used to determine the extent to which health status limited ability to perform physical activities such as walking. Exclusions Data on reasons for exclusion for participation were taken from two sources. Statistical Methods Both studies 1 and 2 included smokers age 50 and over. Hypothesis Tests Cigarette smoking variables are shown in Table 2.

Alcohol Abuse and Dependence While Reasons for Exclusion For Study 1, of the exclusions came from telephone screening. References American Psychological Association.

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