Early-life characteristics and educational disparities in smoking

The emergence of socioeconomic inequalities in smoking during adolescence and early adulthood

BACKGROUND

While it is known that educational inequalities in smoking start during early and middle adolescence, it is unknown how they further develop until adulthood. The aim of this article is to map, in the Portuguese context, how educational inequalities in smoking emerge from pre-adolescence until young adulthood.

METHODS

This study used longitudinal data from the EPITeen Cohort, which recruited adolescents enrolled in schools in Porto, Portugal. We included the 1,038 participants followed at ages 13 (2003/2004), 17, 21, and 24 years. We computed the odds ratio (OR) for the prevalence of smoking states (never smoking, experimenter, less-than-daily, daily and former smoker) and the incidence of transitions between these states, as function of age and education, stratified by sex. We also added interaction terms between age and education.

RESULTS

Educational inequalities in daily smoking prevalence, with higher prevalence among those with lower educational level, emerged at 17 years old and persisted until higher ages. They were formed in a cumulative way by the increased risk of experimenting between 13 and 17 years, and increased risk of becoming daily smoker between 17 and 21 years. The incidence of smoking cessation was higher among the higher educated. Inequalities were formed similarly for women and men, but with lower level and showed no significance among women.

CONCLUSIONS

These results highlight that actions to prevent smoking should also take in account the potential impact in smoking inequalities, and should focus not only on middle adolescence but also on late adolescence and early adulthood.

Diverging Trends and Expanding Educational Gaps in Smoking in China

Introduction: The male smoking rate in China declined moderately through the 1990s and early 2000s, but the decline has since stagnated. It is unclear why the decline stalled and whether it stalled uniformly across all social strata. Theories that view socioeconomic status as a fundamental cause of health predict that socioeconomic gaps in smoking may widen, but theories emphasizing the cultural context of health behavior cast doubt on the prediction. We investigated changes in the socioeconomic gaps in smoking during recent decades in China. Methods: We applied growth-curve models to examine inter- and intra-cohort changes in socioeconomic gaps in male smoking in China using data from a national longitudinal survey spanning 25 years. Results: We found diverging trends in smoking in men with different education levels among the post-1980 cohorts; for high-education men, smoking participation consistently declined, but for low-education men, the decline stopped and possibly reversed. The stagnation in the decline in overall smoking rate since 2010 was mostly due to the stalling of the decline of smoking among low-education men in the most recent cohorts. The diverging trends were a continuation of a general trend in expanding educational gaps in smoking that emerged in the cohorts born after 1960. Our analysis also identified widening educational gaps over age within each cohort. Conclusion: We identified a long-term widening in educational gaps in smoking in China. An effective way to reduce smoking, social inequality in smoking and possibly health disparities in China is to target the smoking behavior of vulnerable groups.

Social inequalities in tobacco-attributable mortality in Spain. The intersection between age, sex and educational level

INTRODUCTION

First study of social inequalities in tobacco-attributable mortality (TAM) in Spain considering the joint influence of sex, age, and education (intersectional perspective).

METHODS

Data on all deaths due to cancer, cardiometabolic and respiratory diseases among people aged ≥35 years in 2016 were obtained from the Spanish Statistical Office. TAM was calculated based on sex-, age- and education-specific smoking prevalence, and on sex-, age- and disease-specific relative risks of death for former and current smokers vs lifetime non-smokers. As inequality measures, the relative index of inequality (RII) and the slope index of inequality (SII) were calculated using Poisson regression. The RII is interpreted as the relative risk of mortality between the lowest and the highest educational level, and the SII as the absolute difference in mortality.

RESULTS

The crude TAM rate was 55 and 334 per 100,000 in women and men, respectively. Half of these deaths occurred among people with the lowest educational level (27% of the population). The RII for total mortality was 0.39 (95%CI: 0.35-0.42) in women and 1.61 (95%CI: 1.55-1.67) in men. The SII was -41 and 111 deaths per 100,000, respectively. Less-educated women aged <55 years and men (all ages) showed an increased mortality risk; nonetheless, less educated women aged ≥55 had a reduced risk.

CONCLUSIONS

TAM is inversely associated with educational level in men and younger women, and directly associated with education in older women. This could be explained by different smoking patterns. Appropriate tobacco control policies should aim to reduce social inequalities in TAM.

Inequalities in adolescent self-rated health and smoking in Europe: comparing different indicators of socioeconomic status

Background

Although there is evidence for socioeconomic inequalities in health and health behaviour in adolescents, different indicators of socioeconomic status (SES) have rarely been compared within one data sample. We examined associations of five SES indicators with self-rated health (SRH) and smoking (ie, a leading cause of health inequalities) in Europe.

Methods

Data of adolescents aged 14–17 years old were obtained from the 2013 SILNE survey (smoking inequalities: learning from natural experiments), carried out in 50 schools in 6 European cities (N=10 900). Capturing subjective perceptions of relative SES and objective measures of education and wealth, we measured adolescents’ own SES (academic performance, pocket money), parental SES (parental educational level) and family SES (Family Affluence Scale, subjective social status (SSS)). Logistic regression models with SRH and smoking as dependent variables included all SES indicators, age and gender.

Results

Correlations between SES indicators were weak to moderate. Low academic performance (OR=1.96, 95% CI 1.53 to 2.51) and low SSS (OR=2.75, 95% CI 2.12 to 3.55) were the strongest indicators of poor SRH after adjusting for other SES-indicators. Results for SSS were consistent across countries, while associations with academic performance varied. Low academic performance (OR=5.71, 95% CI 4.63 to 7.06) and more pocket money (OR=0.21, 95% CI 0.18 to 0.26) were most strongly associated with smoking in all countries.

Conclusions

Socioeconomic inequalities in adolescent health were largest according to SES indicators more closely related to the adolescent’s education as well as the adolescent’s perception of relative family SES, rather than objective indicators of parental education and material family affluence. For future studies on adolescent health inequalities, consideration of adolescent-related SES indicators was recommended.

Wide educational disparities in young adult cardiovascular health

Widening educational differences in overall health and recent stagnation in cardiovascular disease mortality rates highlight the critical need to describe and understand educational disparities in cardiovascular health (CVH) among U.S. young adults. We use two data sets representative of the U.S. population to examine educational disparities in CVH among young adults (24-34) coming of age in the 21st century: the National Health and Nutrition Examination Survey (2005-2010; N= 689) and the National Longitudinal Study of Adolescent to Adult Health (2007-2008; N=11,200). We employ descriptive statistics and regression analysis. The results show that fewer than one in four young adults had good CVH (at least 5 out of 7 ideal cardiovascular indicators). Young adults who had not attained a college degree demonstrate particularly disadvantaged CVH compared with their college-educated peers. Such educational disparities persist after accounting for a range of confounders, including individuals' genetic propensity to develop coronary artery disease. The results indicate that the CVH of today's young adults is troubling and especially compromised for individuals with lower levels of educational attainment. These results generate substantial concern about the future CVH of the US population, particularly for young adults with a low level of education.

Education is the strongest socio-economic predictor of smoking in pregnancy

AIMS

To investigate socio-economic disparities in smoking in pregnancy (SIP) by the mother's education, occupational class and current economic conditions.

DESIGN

Cross-sectional analysis with linked survey and register data.

SETTING

South-western Finland.

PARTICIPANTS

A total of 2667 pregnant women [70% of the original sample (n = 3808)] from FinnBrain, a prospective pregnancy cohort study.

MEASUREMENTS

The outcome was smoking during the first pregnancy trimester, measured from the Finnish Medical Birth Register. Education and occupational class were linked from population registers. Income support recipiency and subjective economic wellbeing were questionnaire-based measures of current economic conditions. These were adjusted for age, partnership status, residential area type, parental separation, parity, childhood socio-economic background, childhood adversities (the Trauma and Distressing Events During Childhood scale) and antenatal stress (Edinburgh Postnatal Depression Scale). Logistic regressions and attributable fractions (AF) were estimated.

FINDINGS

Mother's education was the strongest socio-economic predictor of SIP. Compared with university education, adjusted odds ratios (aORs) of SIP were: 2.2 [95% confidence interval (CI) = 1.2-3.9; P = 0.011] for tertiary vocational education, 4.4 (95% CI = 2.1-9.0; P < 0.001) for combined general and vocational secondary education, 2.9 (95% CI = 1.4-6.1; P = 0.006) for general secondary education, 9.5 (95% CI 5.0-18.2; P < 0.001) for vocational secondary education and 14.4 (95% CI = 6.3-33.0; P < 0.001) for compulsory schooling. The total AF of education was 0.5. Adjusted for the other variables, occupational class and subjective economic wellbeing did not predict SIP. Income support recipiency was associated positively with SIP (aOR = 1.8; 95% CI = 1.1-3.1; P = 0.022). Antenatal stress predicted SIP (aOR = 2.0; 95% CI = 1.4-2.8; P < 0.001), but did not attenuate its socio-economic disparities.

CONCLUSIONS

In Finland, socio-economic disparities in smoking in pregnancy are attributable primarily to differences in the mother's educational level (low versus high) and orientation (vocational versus general).

Daily and Nondaily Smoking Varies by Acculturation among English-Speaking, US Latino Men and Women

Background

Higher smoking prevalence and quantity (cigarettes per day) has been linked to acculturation in the United States among Latinas, but not Latino men. Our study examines variation between a different and increasingly important target behavior, smoking level (nondaily vs daily) and acculturation by sex.

Methods

An online English-language survey was administered to 786 Latino smokers during July through August 2012. The Brief Acculturation Rating Scale for Mexican Americans-II (ARSMA-II) and other acculturation markers were used. Multinomial logistic regression models were implemented to assess the association between smoking levels (nondaily, light daily, and moderate/heavy daily) with acculturation markers.

Results

Greater ARMSA-II scores (relative risk ratio, RRR=.81, 95% CI: .72-.91) and being born inside the United States (RRR=.42, 95% CI: .24-.74) were associated with lower relative risk of nondaily smoking. Greater Latino orientation (RRR=1.29, 95% CI: 1.11-1.48) and preference for Spanish language (RRR=1.06, 95% CI: 1.02-1.10) and media (RRR=1.12, 95% CI: 1.05-1.20) were associated with higher relative risk of nondaily smoking. The relationship between acculturation and smoking level did not differ by sex.

Conclusion

This study found that among both male and female, English-speaking Latino smokers, nondaily smoking was associated with lower acculturation, while daily smoking was linked with higher acculturation.

The role of self-control and cognitive functioning in educational inequalities in adolescent smoking and binge drinking

Background

Large differences in substance use between educational levels originate at a young age, but there is limited evidence explaining these inequalities. The aim of this study was to test whether a) smoking and binge drinking are associated with lower levels of self-control and cognitive functioning, and b) associations between educational track and smoking and binge drinking, respectively, are attenuated after controlling for self-control and cognitive functioning.

Methods

This study used cross-sectional survey data of 15 to 20-year-olds (N = 191) from low, middle, and high educational tracks. We measured regular binge drinking and regular smoking (more than once a month), cognitive functioning (cognitive ability, reaction time and memory span), and self-control. Logistic regression models were used to assess the associations between educational track and smoking and binge drinking controlled for age, gender and social disadvantage, and for self-control and cognitive functioning.

Results

According to models that controlled for age, gender and social disadvantage only, respondents in the low educational track were more likely to drink heavily (OR = 3.25, 95% CI = 1.48–7.17) and smoke (OR = 5.74, 95% CI = 2.31–14.29) than adolescents in the high educational track. The association between educational track and binge drinking was hardly reduced after adjustment for self-control and cognitive ability (OR = 2.88, 95% CI = 1.09–7.62). Adjustment for self-control and cognitive functioning, especially cognitive ability, weakened the association between education and smoking (OR = 3.40, 95% CI = 1.11–10.37). However, inequalities in smoking remained significant and substantial.

Conclusions

In this study population, pre-existing variations between adolescents in terms of self-control and cognitive functioning played a minor role in educational inequalities in smoking, but not in binge drinking.

Why Do College Graduates Behave More Healthfully than Those Who Are Less Educated?

College graduates live much healthier lives than those with less education, but research has yet to document with certainty the sources of this disparity. This study examines why U.S. young adults who earn college degrees exhibit healthier behavior than those with less education. I use data from the National Longitudinal Study of Adolescent to Adult Health (Add Health), which offers information on education and health behaviors across adolescence and young adulthood (N=14,265). Accounting for selection into college degree attainment substantially reduces the associations between college degree attainment and health behavior, but college degree attainment demonstrates a strong causal effect on young adult health. Financial, occupational, social, cognitive, and psychological resources explain less than half of the association between college degree attainment and health behavior. The healthier behaviors of college graduates are the result of sorting into educational attainment, embedding of human capital, and mechanisms other than socioeconomic and psychosocial resources.

How is low parental socioeconomic status associated with future smoking and nicotine dependence in offspring? A population-based longitudinal 13-year follow-up

AIMS

Low socioeconomic status (SES) characterizes smoking and nicotine dependence in adult samples. However, less is known about how parental SES is linked to smoking in offspring and the potential mechanisms at work.

METHODS

A population-based longitudinal study ( n=1380) from Norway was used. Participants were followed from their mid-teens until their late 20s using survey and register data. Data were collected on parental education, parental smoking, educational aspirations and expectations, school grades and school-related conduct problems. Register data monitored education, unemployment and social welfare assistance. Risk factors for smoking and nicotine dependence were identified by means of multinomial logistic regression analyses. Mediation analyses were used to investigate the pathways between parental SES and future smoking.

RESULTS

Future smokers were recruited from families with low educational levels. Poor school grades, school dropout and low educational aspirations were also predictors. Unemployment and social welfare assistance additionally increased the risk. Parental smoking, no high school exam and welfare assistance were mediators between low parental education and high levels of nicotine dependence in young adulthood.

CONCLUSIONS

Socialization to smoking reflects a multifaceted process fuelled by low parental SES. However, parental influences may be masked behind influences from schools or peers. Future research should try to capture the multiple sources of SES-related influence at work. Prevention strategies should target adolescents from low SES backgrounds, who orient towards the manual working class and who have problems entering the labour force.