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Non-Smokers

Non-Smokers are individuals who have never smoked or have abstained from smoking for an extended period of time.
This population is of particular interest in medical research, as their health status can provide valuable insights into the effects of smoking and the potential benefits of smoking cessation.
Non-Smokers may be used as control groups in studies investigating the impact of smoking on various health outcomes, such as cardiovascular disease, respiratory function, and cancer risk.
Researchers can leverage the physiological and behavioral characteristics of Non-Smokers to better understand the mechanisms underlying smoking-related illnesses and develop more effective preventive and treatment strategies.
Additionaly, Non-Smokers may be a focus of public health initiatives aimed at promoting healthy lifestyles and reducing the burden of tobacco use.

Most cited protocols related to «Non-Smokers»

We contacted individuals, groups or organisations that were known to have collected representative spirometry data from asymptomatic lifelong non-smokers, using methods and techniques that complied with temporal international recommendations. Most invitations arose from searches of the literature for titles in peer reviewed journals. All data were anonymised prior to submission, and accompanied by information detailed in a data collection template. Any person, group or organisation sharing data with the working group specified in writing that their ethics committees or organisations had given permission for the data to be used in a research publication.
Publication 2012
Ethics Committees Non-Smokers Spirometry
Articles were identified by searches of PubMed and EMBASE through September 30, 2012. Details of search strategies appear in eTable 1 at http://www.jama.com. No language restrictions were applied. All articles were reviewed for inclusion by 1 reviewer (K.M.F.). An independent review of all articles was conducted by a second set of reviewers (B.K.K., H.O., and B.I.G.). The articles were reviewed to identify those that used standard BMI categories in prospective, observational cohort studies of all-cause mortality among adults with BMI measured or reported at baseline. Studies that addressed these relationships only in adolescents, only in institutional settings, or only among those with specific medical conditions or undergoing specific medical procedures were excluded. We included multiple articles from a given data set only when there was little overlap between articles by sex, age group, or some other factor.
In some cases, authors used standard BMI categories for overweight and obesity but had used a slightly broader reference BMI category of less than 25 or a slightly narrower reference BMI category of 20 to less than 25 rather than the standard normal BMI category of 18.5 to less than 25. We included these articles but have noted the cases in which the reference BMI category was less than 25 or 20 to less than 25. We classified studies that included a mix of self-reported and measured weight and height according to the preponderant type.
Abstracted items included sample size, number of deaths, age at baseline, length of follow-up, HRs and 95% confidence intervals, sex, age, type of weight and height data (measured or self-reported), country or region, source of study sample, adjustment factors, exclusion and inclusion criteria, and sensitivity analyses. Authors of screened articles were queried for additional information when necessary. In studies that only presented results stratified by smoking or health condition, we selected results for nonsmokers or never smokers or for those without the health condition. We selected the most complex model available for the full sample and used a variety of sensitivity analyses to address issues of possible over-adjustment or underadjustment.
We categorized HRs into 2 age groupings either as limited solely to people aged 65 years or older or as a mixed-age category (eg, aged 25–64 years or 40–80 years). We classified articles as adequately adjusted, possibly overadjusted, or possibly underadjusted. We categorized HRs by adjustment level, by whether the data were measured or self-reported, by whether the analysis was performed separately for men and women or for both sexes combined, and by region (North America, Europe, and other).
We used a random-effects model5 (link) to summarize the results overall and within subgroups and based statistically significant heterogeneity on a P value of less than .05. We calculated the quantity I2 to describe the degree of heterogeneity with values of 25%, 50%, and 75% considered low, moderate, and high, respectively.6 (link) We also used a sequential approach similar to that described by Patsopoulos et al7 (link) to assess consistency of findings when heterogeneity was reduced. All analyses were performed with SAS version 9.3 (SAS Institute Inc).
For sensitivity analyses, we examined the effects on HRs of incorporating results from a recent large pooled study for overweight.8 (link) For comparative purposes, we also constructed approximate HRs relative to normal weight from several recent large studies9 (link)–14 (link) that had used finer BMI groupings and thus did not meet our inclusion criteria. To do this, we averaged HRs from the finer BMI groupings over groups corresponding to the standard BMI categories, weighting the HRs by the number of deaths.
Publication 2013
Adolescent Adult Age Groups Genetic Heterogeneity Hypersensitivity Non-Smokers Obesity Woman
A stock standard solution of NNAl-d0 was prepared in 12 mM HCl and stored frozen at -20°C. A 500 pg/mL solution of NNAl-d3 was prepared in 10% methanol containing 12 mM HCl. Pooled urine, collected over several days, (2 liter batches) from a non-smoker with no known SHS exposure was used to prepare the standards and QCs. Standards and controls were stored frozen at −20°C until use.
Publication 2008
Freezing Methanol Non-Smokers Urine
Tumor slides from the internal training cohort were reviewed by 2 pathologists (K.K. and W.D.T.) who were blinded to patient clinical outcomes; they used an Olympus BX51 microscope (Olympus Optical Co. Ltd., Tokyo, Japan) with a standard 22-mm diameter eyepiece.
Tumor STAS was defined as tumor cells within air spaces in the lung parenchyma beyond the edge of the main tumor (Figure 1A and 1D) and was composed of 3 morphological patterns: 1) micropapillary structures consisting of papillary structures without central fibrovascular cores (Figure 1A and 1B),15 (link), 16 (link) which occasionally form ring-like structures within air spaces (Figure 1C); 2) solid nests or tumor islands consisting of solid collections of tumor cells filling air spaces (Figure 1D and 1E)17 (link); and 3) single cells consisting of scattered discohesive single cells (Figure 1F). The edge of the main tumor was defined as the smooth surface of the tumor which is easily recognizable at gross or at low-power field examination as highlighted with the dotted line in Figure 1A. Tumor STAS was considered present when tumor STAS, as defined above, was identified beyond the edge of the main tumor even if it existed only in the first alveolar layer from the tumor edge. Lesions of STAS consist of tumor cells which morphologically appear to be situated within air spaces as micropapillary clusters, solid nests or single cells that are detached from alveolar walls. This differs from lepidic growth where tumor cells grow in a linear fashion along the surface of alveolar walls. Extent of air space filling by tumor cells varied from abundant cellular infiltrates to very inconspicuous single cells or micropapillary clusters that were sometimes difficult to distinguish from alveolar macrophages. In addition, distance between tumor surface and farthest STAS from tumor edge was measured by a ruler. Since lung specimens were not consistently inflated during processing, in order to account for artifactual atelectasis, we also measured according to the number of alveolar spaces.
Tumor cells of STAS were distinguished from alveolar macrophages using the following methods. Macrophages in smokers typically have cytoplasm containing faint brown pigment and black carbon granules while in nonsmokers the pigment is lacking and cytoplasm is sometimes foamy. Nuclei are small, uniform, and regular, without atypia. Nuclear folds are frequent and nucleoli are inconspicuous or absent. In contrast, tumor cells of STAS typically lack cytoplasmic pigment or foamy cytoplasm. They often grow in cohesive clusters and nuclei are atypical with hyperchromasia and frequent nucleoli. The distinction of STAS from artifacts was done in the following way. Tumor floaters were favored, by the presence of clusters of cells often randomly scattered over tissue and at the edges of the tissue section. Presence of jagged edges of tumor cell clusters suggested tumor fragmentation or edges of a knife cut during specimen processing rather than STAS. Linear strips of cells that were lifted off of alveolar walls also favored the presence of artifact. Identification of tumor cells distant from the main tumor was regarded as an artifact unless intraalveolar tumor cells could be demonstrated in a continuum of airspaces containing intraalveolar tumor cells back to the tumor edge.
According to the International Association for the Study of Lung Cancer, American Thoracic Society, and European Respiratory Society histological classification, the percentage of each histologic pattern—lepidic, acinar, papillary, solid, and micropapillary—was recorded in 5% increments and tumors were classified by their predominant pattern.1 (link) Each histologic pattern was considered present in the tumor when it comprised ≥5% of the overall tumor.7 (link) Presence of visceral pleural, lymphatic, and vascular invasion was also recorded.
Publication 2015
Atelectasis Blood Vessel Carbon Black Cell Nucleolus Cell Nucleus Cells Cytoplasm Cytoplasmic Granules Europeans Lung Lung Cancer Macrophage Macrophages, Alveolar Microscopy Neoplasms Non-Smokers Pathologists Patients Pigmentation Pleura, Visceral Respiratory Rate Snup Syncope Tissues Vision
The present cohort study is being conducted by the Columbia Center for
Children’s Environmental Health (CCCEH) (Perera et al. 2003 (link)). The study was approved by the Institutional Review Board (IRB) of Columbia
University. Dominican and African-American women (ethnicity classified
by self-report) residing in Washington Heights, Central Harlem, and
the South Bronx, New York, who registered at the obstetrics/gynecology
clinics at New York Presbyterian Medical Center and Harlem Hospital
by the 20th week of pregnancy were approached in the clinics for
consent. At that time, the women agreeing to participate in the prospective
cohort study signed the IRB-approved consent form. Eligible women
were nonsmokers during the current pregnancy; were free of diabetes, hypertension, and
known HIV; had no documented or reported drug abuse; and
had resided in the area for at least 1 year. At the time of this
report, of 648 consenting and eligible mother–infant pairs, 536 were
still participating in the cohort study; 271 children had reached 3 years
of age. The retention rate for the full cohort was 83% at
the 3-year follow-up. There were no significant differences between
women retained in the study versus those who were lost to follow-up, on
maternal age, ethnicity, marital status, education, income, gestational
age, or birth weight of the newborn.
In this report we focus on the 183 children 3 years of age who had valid
prenatal PAH monitoring data, all three annual developmental assessments, prenatal
questionnaire data on ETS, measurements of cotinine in
maternal and cord blood samples ≥25 ng/mL (to exclude the possibility
that the mother was an active smoker), and CPF level in cord blood. This
group did not differ in any of the maternal or infant characteristics
or prenatal exposures in Table 1 from the 80 children 3 years of age excluded from the analysis because
of missing data. Of these, 64 children were excluded because of missing
developmental testing data.
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Publication 2006
African American Birth Weight Child Cotinine Diabetes Mellitus Drug Abuse Ethics Committees, Research Ethnicity High Blood Pressures Infant Infant, Newborn Non-Smokers Pregnancy Retention (Psychology) Umbilical Cord Blood Woman

Most recents protocols related to «Non-Smokers»

Example 4

A female peri-implantitis patient, 66 years old and non-smoker, had severe bone loss at two implant sites (as shown in FIG. 4A). The patient took during one year 5 drops of BioSil® liquid twice daily. This formulation contains choline-stabilized orthosilicic acid (ch-OSA®), wherein silicic acid is stabilized with choline chloride. The formulation furthermore contains glycerol as a diluent. After one year the bone level was significantly increased at the implant site (see FIG. 4B).

A second peri-implantitis patient, 73 years and non-smoker, with severe bone loss at the implant sites and damaged gingiva (FIG. 5a) took during one year 5 drops of BioSil® liquid twice daily. After one year the bone level was also significantly increased at the implant site (FIG. 5b, after 6 months, FIG. 5c, after 12 months). FIG. 6 shows that the gingiva regained its normal appearance with good color indicating improved vascularization in the course of the 1 year treatment.

The following treatment examples can be used as an adjunct to good mouth hygiene, scaling and root planing:

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Patent 2024
Acids Biosil Bones Choline Choline Chloride Gingiva Glycerin Non-Smokers Osteopenia Pathologic Neovascularization Patients Peri-Implantitis Periodontitis Silicic acid Woman
The patient was a 66-year-old man non-smoker with a history of hypertension. SARS-CoV-2 infection was identified by performing a real-time reverse transcriptase (RT)-PCR assay on a nasopharyngeal swab specimen and he was admitted to the hospital on 11 January 2020 with clinical symptoms of cough, fever, myalgia, and mild dyspnea. He developed respiratory failure and received lung transplantation on 25 February 2020. He died on 26 February 2020. More details of this case can be found in the following reference: Analysis of pathological changes in the epithelium in COVID-19 patient airways. Samples from the injured lungs of this patient were embedded in paraffin and sectioned for examination.
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Publication 2023
Biological Assay Cough COVID 19 Dyspnea Epithelium Fever High Blood Pressures Lung Lung Transplantation Myalgia Nasopharynx Non-Smokers Paraffin Embedding Patients Real-Time Polymerase Chain Reaction Respiratory Failure RNA-Directed DNA Polymerase
This section elicited data regarding socio-demographic characteristics, academia-related factors, and lifestyle factors. Data concerning socio-demographic characteristics included age, gender, family's monthly income, marital status, father's education, parents' marital status, birth order, body mass index (BMI), and smoking. The academia-related factors included year of study and self-reported Grade Point Average (GPA). The years of study were grouped into two academic levels (Junior: second and third year; Senior: fourth to sixth year). Lifestyle factors included smoking status, physical exercise, tea consumption, coffee consumption, and energy drink consumption. Smoking status was defined as follows: current smoker is any person who smoked regularly in the past month at the time of responding; ex-smoker, who quit smoking at least 1 month prior to the study; and nonsmoker as someone who has never smoked.
Publication 2023
Coffee Energy Drinks Ex-Smokers Gender Index, Body Mass Non-Smokers Parent
Covariates were retrieved from baseline (2002–2003). Sex and age were included, and income levels were divided into quartiles, from Q1 (lowest income) to Q4 (highest income).
Behavioral risk factors were measured, including smoking status, body mass index (BMI), and alcohol consumption. Smoking status was categorized into three groups: non-smoker, former smoker, and current smoker. BMI was classified as underweight (< 18.5 kg/m2), normal (18.5–22.9 kg/m2), overweight (23–24.9 kg/m2), and obesity (≥25 kg/m2), according to the World Health Organization (WHO) obesity standard for the Asian population [17 (link)]. Alcohol consumption was classified into the following groups: rarely drinking, 2–3 times/month, 1–2 times/week, 3–4 times/week, and almost every day. Additionally, the Charlson Comorbidity Index (CCI) was also calculated for inpatients using ICD-10 codes [18 (link)].
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Publication 2023
Asian Persons Index, Body Mass Inpatient Non-Smokers Obesity
Mean and standard deviation, median and interquartile range (IQR), or proportions were reported for clinical characteristics, hemodynamic measurements, skin temperature, and BMI. The variables were reported in total for each subpopulation and by TBI above or below 0.70 (TBI ≥ / < 0.70). Continuous variables were compared utilizing a t-test or Mann–Whitney test depending on distribution, and categorial variables were compared utilizing the χ2 test for TBI ≥ / < 0.70 for each subpopulation. Hemodynamic variables were compared between subpopulations utilizing Jonckheere-Terpstra statistical test. Plotted values of TBI were presented for each subpopulation with a corresponding boxplot with median, IQR and range.
Differences in prevalence rates were tested using the χ2 test for patients diagnosed with SCZ < 2 compared to PHC.
Utilizing logistic regression with PAD as outcome (yes/no), associations with explanatory variables were investigated. Age, sex, smoking status (smoker or non-smoker), skin temperature, BMI, comorbidities, and diagnosis of schizophrenia were utilized as explanatory variables. For patients diagnosed with SCZ < 2, PHC was used as reference. For patients with SCZ ≥ 10, patients diagnosed with SCZ < 2 were used as reference.
P-values below 0.05 were considered statistically significant. For statistical analyses, Stata version 16 was used.
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Publication 2023
Hemodynamics Non-Smokers Patients Population Group Schizophrenia Skin Temperature

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More about "Non-Smokers"

Non-tobacco users, abstainers, and never-smokers are individuals who have refrained from smoking cigarettes or other tobacco products for an extended period or their entire lives.
This population holds immense value for medical research, as their health status can provide vital insights into the impacts of smoking and the potential benefits of quitting.
Non-smokers are often utilized as control groups in studies investigating the effects of tobacco use on various health outcomes, such as cardiovascular health, respiratory function, and cancer risk.
By analyzing the physiological and behavioral characteristics of non-smokers, researchers can better understand the mechanisms underlying smoking-related illnesses and develop more effective preventive and treatment strategies.
Additionally, non-smokers may be a focus of public health initiatives aimed at promoting healthy lifestyles and reducing the burden of tobacco use.
The SAS 9.4 statistical software, SPSS version 25, and Stata 14 are commonly used tools that can help researchers analyze data related to non-smokers and smoking-related health outcomes.
These advanced analytical platforms can provide valuable insights and support the development of evidence-based policies and interventions to improve the well-being of non-smokers and the broader population.