Lifelong smoking trajectories of Northern Finns are characterized by sociodemographic and lifestyle differences in a 46-year follow-up

The trajectory of smoking cessation after treatment and its related factors in Taiwan

Smoking has multiple negative effects on health; therefore, the Taiwanese government provides smoking cessation clinics to smokers. This study aimed to explore the trajectory of smoking cessation after smokers received treatment and the variables related to different trajectories. A retrospective longitudinal study was conducted, in which 735 adult smokers who received smoking cessation medications were recruited. The participants' demographic characteristics, chronic diseases, smoking characteristics, and cigarette dependence were collected from chart review. The amount of smoking was collected at baseline, and at 1 week, 1 month, 3 months, and 6 months after treatment. The Proc Traj procedure for group-based modeling and multinomial logistic regression were used for statistical analysis. Three trajectories were identified: early quitters (28.03%), late quitters (11.43%) and reducers (60.54%). Compared with early quitters, reducers were younger and had a higher probability of severe cigarette dependence. Compared with early quitters, late quitters had a higher number of taking smoking cessation medications. The findings revealed that approximately 60% of participants who received smoking cessation treatment could not completely quit smoking, and that age, number of medications taken, and cigarette dependence were significant predictors of different trajectories.

Productivity costs of lifelong smoking-the Northern Finland Birth Cohort 1966 study

BACKGROUND

Smoking is one of the leading causes of impaired health and mortality. Loss of paid and unpaid work and replacements due to morbidity and mortality result in productivity costs. Our aim was to investigate the productivity costs of lifelong smoking trajectories and cumulative exposure using advanced human capital method (HCM) and friction cost method (FCM).

METHODS

Within the Northern Finland Birth Cohort 1966 (NFBC1966), 10 650 persons were followed from antenatal period to age 55 years. The life course of smoking behaviour was assessed with trajectory modelling and cumulative exposure with pack-years. Productivity costs were estimated with advanced HCM and FCM models by using detailed, national register-based data on care, disability, mortality, education, taxation, occupation and labour market. A two-part regression model was used to predict productivity costs associated with lifelong smoking and cumulative exposure.

RESULTS

Of the six distinct smoking trajectories, lifetime smokers had the highest productivity costs followed by late starters, late adult quitters, young adult quitters and youth smokers. Never-smokers had the lowest productivity costs. The higher the number of pack-years, the higher the productivity costs. Uniform patterns were found in both men and women and when estimated with HCM and FCM. The findings were independent of other health behaviours.

CONCLUSIONS

Cumulative exposure to smoking is more crucial to productivity costs than starting or ending age of smoking. This suggests that the harmful effects of smoking depend on dose and duration of smoking and are irrespective of age when smoking occurred.

Healthy lifestyle change and all-cause and cancer mortality in the European Prospective Investigation into Cancer and Nutrition cohort

BACKGROUND

Healthy lifestyles are inversely associated with the risk of noncommunicable diseases, which are leading causes of death. However, few studies have used longitudinal data to assess the impact of changing lifestyle behaviours on all-cause and cancer mortality.

METHODS

Within the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort, lifestyle profiles of 308,497 cancer-free adults (71% female) aged 35-70 years at recruitment across nine countries were assessed with baseline and follow-up questionnaires administered on average of 7 years apart. A healthy lifestyle index (HLI), assessed at two time points, combined information on smoking status, alcohol intake, body mass index, and physical activity, and ranged from 0 to 16 units. A change score was calculated as the difference between HLI at baseline and follow-up. Associations between HLI change and all-cause and cancer mortality were modelled with Cox regression, and the impact of changing HLI on accelerating mortality rate was estimated by rate advancement periods (RAP, in years).

RESULTS

After the follow-up questionnaire, participants were followed for an average of 9.9 years, with 21,696 deaths (8407 cancer deaths) documented. Compared to participants whose HLIs remained stable (within one unit), improving HLI by more than one unit was inversely associated with all-cause and cancer mortality (hazard ratio [HR]: 0.84; 95% confidence interval [CI]: 0.81, 0.88; and HR: 0.87; 95% CI: 0.82, 0.92; respectively), while worsening HLI by more than one unit was associated with an increase in mortality (all-cause mortality HR: 1.26; 95% CI: 1.20, 1.33; cancer mortality HR: 1.19; 95% CI: 1.09, 1.29). Participants who worsened HLI by more than one advanced their risk of death by 1.62 (1.44, 1.96) years, while participants who improved HLI by the same amount delayed their risk of death by 1.19 (0.65, 2.32) years, compared to those with stable HLI.

CONCLUSIONS

Making healthier lifestyle changes during adulthood was inversely associated with all-cause and cancer mortality and delayed risk of death. Conversely, making unhealthier lifestyle changes was positively associated with mortality and an accelerated risk of death.

Characterization of trajectories of physical activity and cigarette smoking from early adolescence to adulthood

BACKGROUND

Cigarette smoking and physical inactivity are two critical risk factors for noncommunicable diseases and all-cause mortality. However, few studies have compared the long-term trajectories of both behaviors, as well as multilevel factors associated with trajectory patterns. Using the National Longitudinal Study of Adolescent to Adult Health (Add Health) Wave I through V survey data, this study characterized distinct subgroups of the population sharing similar behavioral patterns from adolescence to adulthood, as well as predictors of subgroup membership for physical activity (PA) and cigarette smoking behavior respectively.

METHODS

Using the Add Health Wave I through V survey data, we identified the optimal number of latent classes and class-specific trajectories of PA and cigarette smoking from early adolescence to adulthood, fitting latent growth mixture models with standardized PA score and past 30-day cigarette smoking intensity as outcome measures and age as a continuous time variable. Associations of baseline sociodemographic factors, neighborhood characteristics, and sociopsychological factors with trajectory class membership were assessed using multinomial logistic regression.

RESULTS

We identified three distinct subgroups of non-linear PA trajectories in the study population: moderately active group (N = 1067, 5%), persistently inactive group (N = 14,257, 69%) and worsening activity group (N = 5410, 26%). Foror cigarette smoking, we identified three distinct non-linear trajectory subgroups: persistent non-smoker (N = 14,939, 72%), gradual quitter (N = 2357, 11%), and progressing smoker (N = 3393, 16%). Sex, race/ethnicity, neighborhood environment and perceived peer support during adolescence were significant predictors of both physical activity and cigarette smoking trajectory subgroup membership from early adolescence to adulthood.

CONCLUSIONS

There are three distinct subgroups of individuals sharing similar PA and cigarette smoking behavioral profile respectively from adolescence to adulthood in the Add Health study population. Behavioral interventions that focus on neighborhood environment (e.g. establish community-based activity center) and relationship to peers during adolescence (e.g. peer counseling) could be key to long-term PA promotion and cigarette smoking cessation.

The role of social support and self-control in tobacco consumption: a cross-sectional study among tobacco consumers and non-consumers

INTRODUCTION

Tobacco use is recognized as one of the most important causes of preventable death due to non-communicable diseases and disability worldwide. The present study was conducted with the aim of comparing social support and self-control between tobacco consumers and non-consumers in Hormozgan Province.

METHODS

The present cross-sectional study was conducted on the adult population above the age of 15 years living in Hormozgan province. A total number of 1,631 subjects were selected using a convenient sampling method. An online questionnaire was used to collect the data, which consisted of three sections: demographic information, Zimet's perceived social support and Tangney's self-control questionnaires. In the present study, Cronbach's alpha coefficients of social support and self-control questionnaires were 0.886 and 0.721, respectively. Data were analyzed using chi-squared test, Mann-Whitney U-test, and logistic regression analysis with SPSS software (v. 25).

RESULTS

Among the participants, 842 (51.6%) reported to be tobacco non-consumers, and 789 (48.4%) reported to be consumers. The mean scores of perceived social support among the consumers and non-consumers were 4.6 ± 1.012 and 4.93 ± 0.518, respectively. The mean scores of self-control among the consumers and non-consumers were 2.74 ± 0.356 and 2.75 ± 0.354, respectively. There was a significant difference among tobacco consumers and non-consumers in gender, age, education level and job status (p < 0.001). The results showed that the mean scores of social support, support received from family and others were significantly higher in non-consumers than in consumers (p < 0.001). There was no statistically significant difference between the mean scores of self-control, self-discipline, and impulse control in consumers and non-consumers (p > 0.05).

CONCLUSION

According to our findings, tobacco consumers received more social support from family and others compared to non-consumers. Considering the important role of perceived support in tobacco consumption, this variable should receive copious attention in developing interventions and trainings, especially family education workshops.

Mortality risk according to smoking trajectories after cancer diagnosis among Korean male cancer survivors: A population-based cohort study

INTRODUCTION

Previous research on post-diagnosis smoking among cancer survivors mainly relied on smoking status, which may not fully reflect the impact of changes in smoking levels. This study aimed to evaluate mortality risk according to smoking trajectories among Korean male cancer survivors, using a trajectory approach to comprehensively capture smoking patterns.

METHODS

The study included 110555 men diagnosed with cancer between 2002 and 2018 from the Korean National Health Information Database. Group-based trajectory modelling was used to identify post-diagnosis smoking trajectories among pre-diagnosis current smokers (n=45331). Cox hazards models were fitted to evaluate mortality risk according to smoking trajectories for pooled cancers, pooled smoking-related cancers, smoking-unrelated cancers, and gastric, colorectal, liver, and lung cancers.

RESULTS

Smoking trajectories included light-smoking quitters, heavy-smoking quitters, consistent moderate smokers, and decreasing heavy smokers. Smoking significantly increased all-cause and cancer mortality risks in cancer patients for pooled cancers, pooled smoking-related cancers, and pooled smoking-unrelated cancers. Compared to non-smokers, all-cause mortality risk for pooled cancers significantly increased according to smoking trajectories:(AHR=1.33; 95% CI: 1.27-1.40), (AHR=1.39; 95% CI: 1.34-1.44), (AHR=1.44; 95% CI: 1.34-1.54), and (AHR=1.47; 95% CI: 1.36-1.60), respectively. Smoking increased all-cause and cancer mortality risks in gastric and colorectal cancer patients and cancer-specific mortality in lung cancer patients. The significant associations of smoking trajectories with all-cause and cancer mortality risks were primarily observed in 5-year survivors but not in short-term survivors. Among heavy smokers, smoking cessation significantly reduced all-cause mortality risk in the long-term.

CONCLUSIONS

The post-diagnosis smoking trajectory independently predicts cancer prognosis among male cancer patients. Proactive cessation support should be strengthened, particularly for those who smoke heavily.

Lifetime Sunburn Trajectories and Associated Risks of Cutaneous Melanoma and Squamous Cell Carcinoma Among a Cohort of Norwegian Women

Importance

To our knowledge, no study has prospectively investigated sunburn patterns over age periods from childhood to adulthood and their associations with skin cancer risk.

Objective

To identify lifetime trajectories of sunburns and compare the association between these trajectories and subsequent risk of cutaneous melanoma and squamous cell carcinoma (cSCC).

Design, Setting, and Participants

This population-based cohort study included participants from the Norwegian Women and Cancer Study, established in 1991, with follow-up through 2018. Baseline questionnaires were issued from 1991 to 2007, with follow-up questionnaires every 5 to 7 years. Data analysis was performed from March 16, 2021, to December 4, 2021.

Exposures

Participants reported pigmentation factors, sunbathing vacations, and indoor tanning. Annual frequencies of sunburns were reported for childhood, adolescence, and adulthood.

Main Outcomes and Measures

Information on cancer diagnoses, emigration, and death were obtained through linkage to the Cancer Registry of Norway using the unique personal identification number of Norwegian citizens.

Results

Of the 172 472 women (age range, 31-70 years) who returned questionnaires, 169 768 received questions about sunburns at study inclusion. Five classes (stable low, low-moderate-low, low to high, high to low, and stable high) of individual lifetime sunburn trajectories with similar shapes were estimated in 3 samples up to 39 years (n = 159 773), up to 49 years (n = 153 297), and up to 59 years (n = 119 170). Mean follow-up ranged from 14.3 to 19.5 years in the 3 samples, during which 1252 to 1774 women were diagnosed with incident primary melanoma and 739 to 871 women with incident primary cSCC. With hazard ratios (HRs) and 95% CIs estimated using a Cox proportional hazards model, the stable high and high to low trajectories showed statistically significant increased melanoma and cSCC risks compared with the stable low trajectory across all samples (≤39 years for stable high and high to low trajectories: melanoma: HR, 1.50 [95% CI, 1.28-1.75] and HR, 1.44 [95% CI, 1.20-1.73]; cSCC: HR, 1.51 [95% CI, 1.22-1.87] and HR, 1.47 [95% CI, 1.14-1.91]). Other trajectories showed increased risk, though generally weaker and mainly estimates that were not statistically significant. There was no statistically significant heterogeneity between melanoma and cSCC estimates.

Conclusion and Relevance

This cohort study showed that high sunburn frequency throughout life was associated with increased melanoma and cSCC risk. Furthermore, sunburns in childhood are especially important for subsequent risk of these skin cancers. Avoiding sunburns throughout life, in particular in childhood, is therefore crucial.

Healthy lifestyle over the life course: Population trends and individual changes over 30 years of the Doetinchem Cohort Study

For five health-related lifestyle factors (physical activity, weight, smoking, sleep, and alcohol consumption) we describe both population trends and individual changes over a period of 30 years in the same adult population. Dichotomous indicators (healthy/unhealthy) of lifestyle were analyzed for 3,139 participants measured every 5 years in the Doetinchem Cohort Study (1987-2017). Population trends over 30 years in physical inactivity and "unhealthy" alcohol consumption were flat (i.e., stable); overweight and unhealthy sleep prevalence increased; smoking prevalence decreased. The proportion of the population being healthy on all five lifestyle factors declined from 17% in the round 1 to 10.8% in round 6. Underlying these trends a dynamic pattern of changes at the individual level was seen: sleep duration and physical activity level changed in almost half of the individuals; Body Mass Index (BMI) and alcohol consumption in one-third; smoking in one-fourth. Population trends don't give insight into change at the individual level. In order to be able to gauge the potential for change of health-related lifestyle, it is important to take changes at the individual level into account.

Chronotypes and disabling musculoskeletal pain: A Finnish birth cohort study

BACKGROUND

It has been suggested that chronotype, the individual preference for 24-hour circadian rhythms, influences health. Sleep problems and mental distress are among the greatest risk factors for musculoskeletal (MS) pain. The aims of this study were first, to explore the associations between chronotypes and MS pain, with special reference to disabling MS pain, and second, to test whether mental distress and insomnia have a modifying role in the associations between chronotypes and MS pain.

METHODS

The dataset of 4,961 individuals was composed of Northern Finns surveyed on MS pain, chronotypes, and confounding factors (sex, insomnia, sleep duration, smoking, mental distress, occupational status, education level, and number of co-existing diseases) at 46 years. The relationships between chronotypes (evening [E], intermediate [I], and morning [M]) and MS pain were evaluated using multinomial logistic regression. To address the second aim, we included an interaction term (chronotype*mental distress, chronotype*insomnia) in the logistic model.

RESULTS

Compared to the M-types, both the E- and I-types had increased odds of suffering 'disabling pain' in the unadjusted model (odds ratio [OR] 1.79, 95% confidence interval [CI] 1.37-2.33; OR 1.54, 95% CI 1.29-1.84, respectively). However, the association remained statistically significant only after adjusting for all covariates among the I-types (OR 1.39, 95% CI 1.15-1.67). Neither mental distress nor insomnia was found to modify the chronotype-MS pain association.

CONCLUSIONS

The results highlight the importance of chronotypes for individuals' MS health but suggest the presence of confounding factors in the interplay between these factors.

Differential trajectories of tobacco smoking in people at ultra-high risk for psychosis: Associations with clinical outcomes

OBJECTIVE

People at ultra-high risk (UHR) for psychosis have a high prevalence of tobacco smoking, and rates are even higher among the subgroup that later develop a psychotic disorder. However, the longitudinal relationship between the course of tobacco smoking and clinical outcomes in UHR subjects is unknown.

METHODS

We investigated associations between tobacco smoking and clinical outcomes in a prospective study of UHR individuals (n = 324). Latent class mixed model analyses were used to identify trajectories of smoking severity. Mixed effects models were applied to investigate associations between smoking trajectory class and the course of attenuated psychotic symptoms (APS) and affective symptoms, as assessed using the CAARMS.

RESULTS

We identified four different classes of smoking trajectory: (i) Persistently High (n = 110), (ii) Decreasing (n = 29), (iii) Persistently Low (n = 165) and (iv) Increasing (n = 20). At two-year follow-up, there had been a greater increase in APS in the Persistently High class than for both the Persistently Low (ES = 9.77, SE = 4.87, p = 0.046) and Decreasing (ES = 18.18, SE = 7.61, p = 0.018) classes. There were no differences between smoking classes in the incidence of psychosis. There was a greater reduction in the severity of emotional disturbance and general symptoms in the Decreasing class than in the High (ES = -10.40, SE = 3.41, p = 0.003; ES = -22.36, SE = 10.07, p = 0.027), Increasing (ES = -11.35, SE = 4.55, p = 0.014; ES = -25.58, SE = 13.17, p = 0.050) and Low (ES = -11.38, SE = 3.29, p = 0.001; ES = -27.55, SE = 9.78, p = 0.005) classes, respectively.

CONCLUSIONS

These findings suggests that in UHR subjects persistent tobacco smoking is associated with an unfavorable course of psychotic symptoms, whereas decrease in the number of cigarettes smoked is associated with improvement in affective symptoms. Future research into smoking cessation interventions in the early stages of psychoses is required to shine light on the potential of modifying smoking behavior and its relation to clinical outcomes.

Improving and maintaining healthy lifestyles are associated with a lower risk of diabetes: A large cohort study

AIMS

It is well known that healthy lifestyles measured at one time-point are inversely associated with diabetes risk. The impact of transitions in combined lifestyles in real settings remains unknown.

MATERIALS AND METHODS

The trajectory patterns of combined lifestyles over three years were identified using group-based trajectory modeling in 26,647 adults in Japan. Two types of indices (not having the unhealthy lifestyle [easy goal] and having healthiest lifestyles [challenging goal]) were developed using five lifestyle factors: smoking, alcohol consumption, exercise, sleep duration, and body weight control. This index was calculated using the yearly total score (0-5; higher score indicated healthier lifestyles). Diabetes was defined by high plasma glucose level, high hemoglobin A1c level, and self-report.

RESULTS

Five trajectory patterns were identified for each index and it was shown that healthier patterns are associated with a lower risk of type 2 diabetes during 6.6 years of average follow-up. For example, with a challenging-goal, compared with a persistently very unhealthy pattern, the adjusted hazard ratios (95% confidence intervals) were 0.65 (0.59, 0.73), 0.50 (0.39, 0.64), 0.43 (0.38, 0.48), and 0.33 (0.27, 0.41) for 'persistently unhealthy', 'improved from unhealthy to moderately healthy', 'persistently moderately healthy', and 'persistently mostly healthy' patterns, respectively.

CONCLUSIONS

Our data reinforce the importance of improving and maintaining health-related lifestyles to prevent diabetes.

Modeling the Multidimensional Predictors of Multisite Musculoskeletal Pain Across Adulthood-A Generalized Estimating Equations Approach

Background: Multisite pain is commonly chronic and often lacks its initial role as a potential tissue damage signal. Chronic pain among working-age individuals is a risk for disability and imposes a major burden on health care systems and society. As effective treatments for chronic pain are largely lacking, better identification of the factors associated with pain over working years is needed. Methods: Members of the Northern Finland Birth Cohort 1966 participated in data collection at the ages of 31 (n = 4,028) and 46 (n = 3,429). Using these two time points, we performed a multivariable analysis of the association of socioeconomic, occupational, psychological and lifestyle factors (i.e., low education, living alone, low household income, unemployment, occupational physical exposures [hard physical labor, leaning forward, back twisting, constant moving, lifting loads of ≥ 1 kg], physical inactivity, regular smoking, regular drinking, overweight, and psychiatric symptoms) with the number of musculoskeletal pain sites (i.e., upper extremity, lower extremity, lower back, and the neck-shoulder region; totalling 0-4 pain sites). The data were analyzed using generalized estimating equations. Results: At the age of 31, multisite pain was reported by 72.5% of men and 78.6% of women. At the age of 46, the prevalence of multisite pain was 75.7% among men and 82.7% among women. Among men, the number of pain sites was positively associated with age (rate ratio 1.05, 95% confidence interval 1.01-1.08), low household income (1.05, 1.01-1.08), unemployment (1.13, 1.06-1.19), any occupational exposure (1.17, 1.12-1.22), regular smoking (1.06, 1.02-1.11), and psychiatric symptoms (1.21, 1.17-1.26). Among women, the number of pain sites was positively associated with age (1.06, 1.04-1.10), unemployment (1.10, 1.05-1.15), any occupational exposure (1.10, 1.06-1.13), regular smoking (1.06, 1.02-1.10), overweight (1.08, 1.05-1.11), and psychiatric symptoms (1.19, 1.15-1.22); living alone was negatively associated with the number of pain sites (0.95, 0.91-0.99). Conclusion: Of the studied predictors, psychiatric symptoms, occupational physical exposures and unemployment were most strongly associated with multisite pain among both sexes. The results of this study deepen the understanding of the underlying factors of and comorbidities behind multisite pain, and help develop pain relief and rehabilitation strategies for working-age individuals with multisite pain.