Low-Level Cigarette Smoking and Longitudinal Change in Serum Cholesterol Among Adolescents

Dwyer, James H.; Rieger-Ndakorerwa, Gudrun; Semmer, Norbert K.; Fuchs, Reinhard; Lippert, Peter C.

doi:10.1001/jama.1988.03720190025025

Cited by 34 publications

(9 citation statements)

References 41 publications

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“…Some researchers have confirmed that cigarette smoking can accelerate the attrition and therefore biological aging through mechanisms involving oxidative stress [10–12]. In addition, smokers have the abnormal TG tolerance and lower HDL-C [13, 14]. Although the present study is not a mechanism-driven research, it may be used to explain why a stronger association for current smokers for triglycerides, and why the positive correlation with telomere length only can be detected in ex-smokers for HDL-C.…”

Section: Discussionmentioning

confidence: 99%

Association between lipoproteins and telomere length in US adults: data from the NHANES 1999–2002

et al. 2019

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Background Evidence regarding the correlation between lipoproteins and telomere length in US adults is limited. We aimed to investigate whether lipoproteins was associated with telomere length using US National Health and Nutrition Examination Survey (NHANES) database. Methods A total of 6468 selected participants were identified in the NHANES Data Base (1999–2002). The independent and dependent variables were lipoproteins and telomere length, respectively. The covariates included demographic data, dietary data, physical examination data, and comorbidities. Results In fully-adjusted model, we found that 0.1 differences of telomere length were positively associated with HDL-C [0.19 (95% CI 0.07, 0.31)], while the associations between LDL-C [0.19 (95% CI -0.27, 0.65)], TG [− 1.00 (95% CI -2.09, 0.07) and telomere length were not detected. By nonlinearity test, only the relationship between HDL-C and telomere length was nonlinear. The inflection point we got was 1.25. On the left side of the inflection point (telomere length ≤ 1.25), a difference in 0.1 of telomere length was associated with 0.50 difference in HDL-C. Conclusion After adjusting for demographic data, dietary data, physical examination data, and comorbidities, telomere length is not associated with LDL-C and TG, but is positively associated with HDL-C when telomere length is less than 1.25. Electronic supplementary material The online version of this article (10.1186/s12944-019-1030-7) contains supplementary material, which is available to authorized users.

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Section: Discussionmentioning

confidence: 99%

Association between lipoproteins and telomere length in US adults: data from the NHANES 1999–2002

et al. 2019

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“…Thus, adolescent users are at particularly high risk for physical consequences of tobacco use later on. These consequences begin their course in adolescence (e.g., HDL level changes; [ 4 ]). Tobacco use prevalence among youth generally has been increasing over the last 15 years [ 3 ].…”

Section: Introductionmentioning

confidence: 99%

Effects of sixty six adolescent tobacco use cessation trials and seventeen prospective studies of self-initiated quitting

Sussman¹

2003

Tob. Induced Dis.

143

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Abstract

This paper provides a review of the last two and a half decades of research in adolescent and young-adult tobacco use cessation. A total of 66 tobacco cessation intervention studies – targeted or population – are reviewed. In addition, an exhaustive review is completed of adolescent self-initiated tobacco use cessation, involving 17 prospective survey studies.

Average reach and retention across the intervention studies was 61% and 78%, respectively, and was higher when whole natural units were treated (e.g., classrooms), than when units created specifically for the program were treated (e.g., school-based clinics). The mean quit-rate at a three to 12-month average follow-up among the program conditions was 12%, compared to approximately 7% across control groups. A comparison of intervention theories revealed that motivation enhancement (19%) and contingency-based reinforcement (16%) programs showed higher quit-rates than the overall intervention cessation mean. Regarding modalities (channels) of change, classroom-based programs showed the highest quit rates (17%). Computer-based (expert system) programs also showed promise (13% quit-rate), as did school-based clinics (12%).

There was a fair amount of missing data and wide variation on how data points were measured in the programs' evaluations. Also, there were relatively few direct comparisons of program and control groups. Thus, it would be difficult to conduct a formal meta-analysis on the cessation programs. Still, these data suggest that use of adolescent tobacco use cessation interventions double quit rates on the average.

In the 17 self-initiated quitting survey studies, key predictors of quitting were living in a social milieu that is composed of fewer smokers, less pharmacological or psychological dependence on smoking, anti-tobacco beliefs (e.g., that society should step in to place controls on smoking) and feeling relatively hopeful about life. Key variables relevant to the quitting process may include structuring the context of programming for youth, motivating quit attempts and reducing ambivalence about quitting, and making programming enjoyable as possible. There also is a need to help youth to sustain a quit-attempt. In this regard, one could provide ongoing support during the acute withdrawal period and teach youth social/life skills. Since there is little information currently available on use of nicotine replacement in young people, continued research in this arena might also be a useful focus for future work.

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“…The average age of post stroke survivors in the Northern Manhattan Study was 69.2 ± 10.3 years, and of participants in Marburg 71.1 ± 11.3 years [16,17]. In Italy, participants were 70 years old on average (age range 34-85) [18].…”

Section: Discussionmentioning

confidence: 99%

“…The patients who had had these risk factors had a stroke two to four times more often than those who didn't [17]. Dwyer et al [18] emphasize that smoking is a big risk factor for stroke and that stroke among young population who are passionate smokers without any other risk factor is not rare.…”

Section: Discussionmentioning

confidence: 99%

Correlation between risk factors, functional recovery, and the health-related quality of life of stroke survivors

Mandić¹,

Arandjelović

Rančić³

et al. 2017

Srp Arh Celok Lek

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Introduction/Objective It has been estimated that 50% of strokes are preventable through the control of modifiable risk factors. The objective of the paper was to determine the correlation between the risk factors, functional status, and the health-related quality of life (HRQOL) of stroke survivors. Method The prospective cohort study was used. The study included 136 patients 30-79 years old. Functional recovery was assessed using the Barthel index (BI) and the Modified Rankin Scale (mRS). The HRQOL was evaluated by the generic Short Form 36 (SF-36) questionnaire. BI and mRS were determined at admission at the rehabilitation, one, three and six months after the stroke. The SF-36 was filled out at the same time. The analysis of the repeated measure variance (Repeated Measures ANOVA) was applied, as well as the correlation analysis and Spearman's coefficient of rank correlation. Results A total number of 136 patients [66 (48.5%) male and 70 (51.5%) female] completed the questionnaire. The average age of stroke survivors was 63.72 ± 8.73. At admission, mRS was 4.75 ± 0.55, and six months after the stroke onset it decreased to 2.60 ± 1.08. The average value of BI at admission was 25 ± 24.66, and within six months it increased to 83.75 ± 18.59 (p = 0.001). The ANOVA showed that the values of mRS significantly decreased (p < 0.001) and the values of BI significantly increased (ANOVA: p < 0.001). All domains of the SF-36 questionnaire, except for the pain domain, significantly increased (p < 0.001). The physical function (r = 0.238; p < 0. 01), physical role (r = 0.199; p < 0.05), and emotional role (r = 0.237; p < 0.01) were significantly lower among alcohol addicts (r = 0.199; p < 0.05). Mental health (r = 0.244; p < 0.01) and social relationships domains were significantly lower among smokers (r = 0.272; p < 0.01). The general health (r =-0.290; p < 001) and health condition change domains were significantly lower among smokers (r = 0.225; p < 0.01). Conclusion The most important risk factor which was negatively correlated with the HRQOL was smoking. The patients who were smokers and alcohol addicts had a significantly smaller increase of the HRQOL domains compared to other patent groups. Six months after the stroke, all domains of the HRQOL significantly increased. The significant improvement of patients' functional status was positively correlated to the increase of their HRQOL.

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Low-Level Cigarette Smoking and Longitudinal Change in Serum Cholesterol Among Adolescents

Cited by 34 publications

References 41 publications

Association between lipoproteins and telomere length in US adults: data from the NHANES 1999–2002

Association between lipoproteins and telomere length in US adults: data from the NHANES 1999–2002

Effects of sixty six adolescent tobacco use cessation trials and seventeen prospective studies of self-initiated quitting

Correlation between risk factors, functional recovery, and the health-related quality of life of stroke survivors

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