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Smoking intensity (pack/day) is a better measure than pack-years or smoking status for modeling cardiovascular disease outcomes.

ABSTRACT: OBJECTIVES:Smoking as an epidemiological exposure can be quantified in many ways including duration, intensity, pack-years, recency, and age at initiation. However, it is not clear which of these are most important for cardiovascular disease (CVD) and how they should be modeled. STUDY DESIGN AND SETTING:Using the Multi-Ethnic Study of Atherosclerosis, Cox models for time to incident CVD adjusted for age, sex, race/ethnicity, education category, and income category were compared which included various characterizations of smoking history. RESULTS:Duration, age at starting, time since quitting, and noncigarette forms of smoking were not independently associated with CVD, whereas baseline current intensity was associated with CVD [e.g., hard CVD hazard ratio 1 pack/d of 1.85 95% confidence interval (1.33, 2.57)]. Former smokers, regardless of duration, intensity, or recency, were not at increased risk, suggesting that risk may risk may drop precipitously from the time of quitting. For CVD events, representing smoking exposure as baseline smoking intensity produced better model fit as measured by Akaike information criterion than models using smoking status or pack-years. CONCLUSION:The association of smoking with incident CVD events was well captured by including a simple term for baseline smoking intensity.

SUBMITTER: Nance R

PROVIDER: S-EPMC5318261 | biostudies-literature | 2017 Jan

REPOSITORIES: biostudies-literature

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Smoking intensity (pack/day) is a better measure than pack-years or smoking status for modeling cardiovascular disease outcomes.

Nance Robin R Delaney Joseph J McEvoy John W JW Blaha Michael J MJ Burke Gregory L GL Navas-Acien Ana A Kaufman Joel D JD Oelsner Elizabeth C EC McClelland Robyn L RL

Journal of clinical epidemiology 20161018

<h4>Objectives</h4>Smoking as an epidemiological exposure can be quantified in many ways including duration, intensity, pack-years, recency, and age at initiation. However, it is not clear which of these are most important for cardiovascular disease (CVD) and how they should be modeled.<h4>Study design and setting</h4>Using the Multi-Ethnic Study of Atherosclerosis, Cox models for time to incident CVD adjusted for age, sex, race/ethnicity, education category, and income category were compared wh ...[more]

PMID: 27769836

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Project description:BACKGROUND:Cigarette smoking is the strongest risk factor for COPD. Smoking burden is frequently measured in pack-years, but the relative contribution of cigarettes smoked per day versus duration towards the development of structural lung disease, airflow obstruction and functional outcomes is not known. METHODS:We analysed cross-sectional data from a large multicentre cohort (COPDGene) of current and former smokers. Primary outcome was airflow obstruction (FEV1/FVC); secondary outcomes included five additional measures of disease: FEV1, CT emphysema, CT gas trapping, functional capacity (6?min walk distance, 6MWD) and respiratory morbidity (St George's Respiratory Questionnaire, SGRQ). Generalised linear models were estimated to compare the relative contribution of each smoking variable with the outcomes, after adjustment for age, race, sex, body mass index, CT scanner, centre, age of smoking onset and current smoking status. We also estimated adjusted means of each outcome by categories of pack-years and combined groups of categorised smoking duration and cigarettes/day, and estimated linear trends of adjusted means for each outcome by categorised cigarettes/day, smoking duration and pack-years. RESULTS:10?187 subjects were included. For FEV1/FVC, standardised beta coefficient for smoking duration was greater than for cigarettes/day and pack-years (P<0.001). After categorisation, there was a linear increase in adjusted means FEV1/FVC with increase in pack-years (regression coefficient ?=-0.023±SE0.003; P=0.003) and duration over all ranges of smoking cigarettes/day (?=-0.041±0.004; P<0.001) but a relatively flat slope for cigarettes/day across all ranges of smoking duration (?=-0.009±0.0.009; P=0.34). Strength of association of duration was similarly greater than pack-years for emphysema, gas trapping, FEV1, 6MWD and SGRQ. CONCLUSION:Smoking duration alone provides stronger risk estimates of COPD than the composite index of pack-years. TRIAL REGISTRATION NUMBER:Post-results; NCT00608764.

Project description:Smoking status does not indicate the amount or length of tobacco use, and thus, it is an imperfect measure to assess the association between cigarette smoking and severe coronavirus disease 2019 (COVID-19) outcomes. This investigation assessed whether cigarette smoking status, intensity of smoking (i.e., average daily packs of cigarettes smoked), duration of smoking, and pack-years of smoking are associated with severe outcomes among adults diagnosed with COVID-19. We conducted a retrospective, cross-sectional study in which we identified consecutive patients diagnosed with COVID-19 at the University of Cincinnati healthcare system between 13 March 2020 and 30 September 2020 who had complete information on smoking status, severe COVID-19 outcomes, and covariates (i.e., demographics and comorbidities). We used logistic regression to evaluate the associations of smoking status and intensity of smoking with COVID-19 severity, defined as hospitalization, admission to intensive care unit (ICU), or death, adjusting for sociodemographics and comorbidities. Among the 4611 COVID-19 patients included in the analysis, 18.2% were current smokers and 20.7% were former smokers. The prevalence of COVID-19 outcomes was 28.9% for hospitalization, 9.8% for ICU admission, and 1.4% for death. In the adjusted analysis, current smoking (AOR: 1.23, 95% CI: 1.02-1.49), former smoking (AOR: 1.28, 95% CI: 1.07-1.54), and pack-years of smoking (AOR: 1.09, 95% CI: 1.02-1.17) were associated with a higher prevalence of hospitalization. Average daily packs of cigarettes smoked was associated with a higher prevalence of hospitalization (AOR: 1.30, 95% CI: 1.10-1.53) and ICU admission (AOR: 1.23, 95% CI: 1.04-1.44). Smoking status, pack-years, and intensity of smoking were associated with hospitalizations in patients with COVID-19 and intensity of smoking was associated with ICU admission. The findings underscore the need for detailed information beyond smoking status when evaluating smokers with COVID-19 so that the potential for adverse sequelae may be optimally managed in at-risk patients.

Project description:ContextAccurate assessment of insulin sensitivity may better identify individuals at increased risk of cardio-metabolic diseases.ObjectivesTo examine whether a combination of anthropometric, biochemical and imaging measures can better estimate insulin sensitivity index (ISI) and provide improved prediction of cardio-metabolic risk, in comparison to HOMA-IR.Design and participantsHealthy male volunteers (96 Chinese, 80 Malay, 77 Indian), 21 to 40 years, body mass index 18-30 kg/m(2). Predicted ISI (ISI-cal) was generated using 45 randomly selected Chinese through stepwise multiple linear regression, and validated in the rest using non-parametric correlation (Kendall's tau ?). In an independent longitudinal cohort, ISI-cal and HOMA-IR were compared for prediction of diabetes and cardiovascular disease (CVD), using ROC curves.SettingThe study was conducted in a university academic medical centre.Outcome measuresISI measured by hyperinsulinemic euglycemic glucose clamp, along with anthropometric measurements, biochemical assessment and imaging; incident diabetes and CVD.ResultsA combination of fasting insulin, serum triglycerides and waist-to-hip ratio (WHR) provided the best estimate of clamp-derived ISI (adjusted R(2) 0.58 versus 0.32 HOMA-IR). In an independent cohort, ROC areas under the curve were 0.77±0.02 ISI-cal versus 0.76±0.02 HOMA-IR (p>0.05) for incident diabetes, and 0.74±0.03 ISI-cal versus 0.61±0.03 HOMA-IR (p<0.001) for incident CVD. ISI-cal also had greater sensitivity than defined metabolic syndrome in predicting CVD, with a four-fold increase in the risk of CVD independent of metabolic syndrome.ConclusionsTriglycerides and WHR, combined with fasting insulin levels, provide a better estimate of current insulin resistance state and improved identification of individuals with future risk of CVD, compared to HOMA-IR. This may be useful for estimating insulin sensitivity and cardio-metabolic risk in clinical and epidemiological settings.

Dataset Information

Smoking intensity (pack/day) is a better measure than pack-years or smoking status for modeling cardiovascular disease outcomes.

Publications

Smoking intensity (pack/day) is a better measure than pack-years or smoking status for modeling cardiovascular disease outcomes.

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