Parental transmission of smoking among middle-aged and older populations in Russia and Belarus
Abstract
Objectives
The very high rates of smoking among men and the rapid changes among women in the Post-Soviet countries mean that this region offers an opportunity to understand better the intergenerational role of parental influences on smoking.
Methods
In this study, we exploit a unique data set, the PrivMort cohort study conducted in 30 Russian and 20 Belarusian towns in 2014–2015, which collects information on behaviours of middle-aged and older individuals and their parents, including smoking. We explored the associations between smoking by parents and their offspring using multiply imputed data sets and multilevel mixed-effect Poisson regressions.
Results
Adjusting for a wide array of social origin, socio-demographic, and socio-economic variables, our analysis suggests that sons of regularly smoking fathers have prevalence ratios of 1.35 [95% confidence intervals (CI) 1.21–1.50] and 1.39 (CI 1.23–1.58) of smoking, while the figures for daughters of regularly smoking mothers are 1.91 (CI 1.40–2.61) and 2.30 (CI 1.61–3.28), respectively, in Russia and Belarus.
Conclusions
Intergenerational paternal and maternal influences on smoking should be taken into account in studies seeking to monitor the rates of smoking and the impact of tobacco control programmes.
Keywords
Intergenerational transmission Smoking Demographic cohort study Russia Belarus Multilevel Poisson analysisIntroduction
According to the World Health Organization’s (WHO) estimates, post-Soviet countries, including Russia and Belarus, have some of the highest prevalence of smoking among adult men anywhere in the world, while rates have been increasing rapidly among women in the past 2 decades (McKee et al. 1998; Perlman et al. 2007; Roberts et al. 2012; Quirmbach and Gerry 2016; WHO 2016). The previous research has studied the macro-level effects of economic transition and market entry of transnational tobacco companies on these patterns (Gilmore and McKee 2005; Gilmore et al. 2011; Lillard and Dorofeeva 2015), as well as individual-level factors such as age, marital status, family disruption, education, urban residency, household economic situation, self-reported material deprivation, unemployment, occupation, and religious denomination (Gilmore et al. 2001; Pomerleau et al. 2004; Bobak et al. 2006; Perlman et al. 2007; Kislitsyna et al. 2010; Roberts et al. 2012). One area that has largely been overlooked in this research has been intergenerational transmission of propensity to smoke from parents to their offspring in the post-Soviet context.
Studies on social determinants of smoking have repeatedly demonstrated intergenerational transmission of smoking in various settings, populations, and times (Bailey et al. 1993; McGee et al. 2006; Brook et al. 2013; Christopoulou et al. 2013; Kandel et al. 2015). Nonetheless, one major limitation of this literature is that it is almost exclusively concerned with intergenerational transmission of smoking to adolescents and individuals in their 20s and 30s, while the role of parental smoking later in life is under-researched. The available research also suggests that, if they are to identify the net intergenerational transmission of smoking, empirical studies should adequately account for socio-economic status in each generation, which independently affects tobacco use (Conrad et al. 1992; Jefferis et al. 2003; Schori et al. 2014). Lower parental education and material deprivation in childhood, for instance, predicts an individuals’ increased risk of smoking in their adulthood and may explain spurious evidence of an intergenerational transmission of smoking (Fagan et al. 2005). Few existing studies account for social origin variables separately for fathers and mothers and so might overestimate the effect of parental smoking on their children’s smoking propensity.
The very high rates of smoking among men and the rapid changes among women in Russia and Belarus mean that these countries offer an opportunity to understand better the intergenerational role of parental influences on smoking. We are aware of only two studies in post-Soviet settings that investigate the link between parents and their offspring smoking (Kemppainen et al. 2006; Kislitsyna et al. 2010). These are limited in that they only include adolescents, cover limited geographical areas with small samples, do not account for effects with social origins, such as fathers’ and mothers’ education, and do not consider a wide array of confounding factors in an individual’s life, such as labour market characteristics, that might explain intergenerational transmission of smoking between parents and their children. The goal of the study is to exploit a unique data set from Russia and Belarus that can address many of the limitations of previous research by examining the association between fathers’ and mothers’ smoking and smoking in their middle-aged and older offspring, after taking account of those offspring’s social origin, socio-demographic, and socio-economic characteristics.
Methods
Data set
Our analysis is based on the PrivMort data set, collected in 2014–2015 within a multi-disciplinary project whose main objective is to investigate the post-socialist morbidity and mortality crisis by means of a cross-sectional retrospective cohort study. Initially, the PrivMort collected basic economic, demographic, and enterprise-level data on all towns with 10,000–100,000 inhabitants in the European part of Russia and in Belarus, excluding the regions of the North Caucasus. A set of 30 and 20 towns was selected from the pool of 539 and 96, respectively, in Russia and Belarus, using the method of propensity score matching based on the following pre-transition demographic and socio-economic characteristics of the towns: (1) crude death rates per 1000 population; (2) population size, (3) dependency ratio; (4) average wage in US dollars; (5) number of physicians per 10,000 population; (6) floor area per person; (7) death rates from alcohol poisoning per 100,000 population; and (8) emission of pollutants into the atmosphere from stationary sources, thousand tons.
In the selected towns, a random walk procedure was used for sampling the respondents. The towns were divided into street-centred clusters, which were then distributed among the interviewers using the method of random numbers. Interviewers conducted face-to-face interviews using structured questionnaires. Response rate was higher in Russia (48%) than in Belarus (39%). Full details concerning the selection of towns and other aspects of the PrivMort methodology are given elsewhere (Irdam et al. 2016; Azarova et al. 2017; Gugushvili et al. 2018).
To be included in the survey, a potential respondent had to be born before 1972. This criterion ensured that a respondent had reached working age by 1991. The respondent sample, therefore, includes only those aged 42 and over. For robustness of analysis, we further censor our sample to working age individuals 65 and younger. In addition to information collected on respondents’ smoking, socio-demographic, and socio-economic characteristics, the PrivMort survey collected data on their fathers’ and mothers’ characteristics, including their smoking patterns, and educational attainment. The actual data set that we employ is one derived from a multiple imputation exercise via the MICE (Multiple Imputation using Chained Equations) package in Stata 14, allowing for 20 sets of multiple imputations and combining them using Rubin’s (1987) rules. We undertake the latter procedure to compensate for the extent of missing data in our key variables—paternal and maternal smoking. Overall, our analytical samples consist of 15,098 individuals interviewed in Russia and 10,370 in Belarus. Although we stratify our analysis by gender, in both countries, women are overrepresented in the data set (70.3 and 71.6%, respectively).
Statistical analysis
To understand the patterns of intergenerational transmission of smoking among men and women, accounting for various individual-level covariates described in “Results” section, we create a dummy variable for regular smokers that takes value of 1 if they smoked at the time of interview and zero otherwise. We consecutively fit age-adjusted bivariate and multivariate multilevel mixed-effect Poisson regressions with robust variance separately by gender. In the latter models, level 1 consists of individuals and level 2 consists of towns in which the PrivMort survey was conducted. For the latter level, we account for the size of population (the mean value is 29,885 in Russia and 47,556 in Belarus). Models are estimated using Stata 14 function “mepoisson” and the results are presented as prevalence ratios (OR) with corresponding 95% confidence intervals (CI). In addition to reporting relative measures of intergenerational transmission of smoking, we also calculate post-estimation predicted probabilities for men and women with varying patterns of parental smoking averaged across the relevant populations in Russia and Belarus.
Results
The prevalence of smoking
Prevalence of smoking among respondents and their parents, percent (PrivMort retrospective cohort study conducted in Russia and Belarus, 2014–2015)
| Men | Women | |||||||
|---|---|---|---|---|---|---|---|---|
| Russia | Belarus | Russia | Belarus | |||||
| Sons | Fathers | Sons | Fathers | Daughters | Mothers | Daughters | Mothers | |
| Never | 25.0 | 22.6 | 31.3 | 28.3 | 84.7 | 96.6 | 87.7 | 96.7 |
| Regular smoker | 53.3 | 58.5 | 51.9 | 53.6 | 9.4 | 1.6 | 8.3 | 2.0 |
| Quit | 21.8 | 18.9 | 16.7 | 18.1 | 5.9 | 1.8 | 4.0 | 1.3 |
Table 1 also shows the prevalence of smoking among the sample of fathers and mothers in Russia and Belarus. Respondents reported their parents’ current smoking behaviour if they were alive at the time of interview, and for deceased parents information on smoking characteristics was collected before their death. Since answer options for parents, as for respondents, include ‘used to smoke but quit’, we are able obtain a good approximation of smoking histories of all parents. By comparing the shares of regular smokers between respondents’ and parental generations, we see that, among men, the prevalence of smoking decreased by about 5 and 2 percentage points, respectively, in Russia and Belarus. Among mothers, the share of those who smoked regularly or smoked and ceased was marginal, at 1.6–2.0 and 1.8–1.3% in considered countries. In both countries, we observe that fathers are less likely to be never smokers than sons, while mothers are more likely to be never smokers than daughters.
Covariates
Descriptive statistics of covariates of regular smoking, percent (PrivMort retrospective cohort study conducted in Russia and Belarus, 2014–2015)
| Men | Women | |||
|---|---|---|---|---|
| Russia | Belarus | Russia | Belarus | |
| Father’s education | ||||
| Primary | 59.5 | 50.5 | 64.3 | 55.1 |
| Secondary | 34.8 | 23.2 | 30.7 | 20.5 |
| Tertiary | 5.7 | 26.2 | 5.0 | 24.4 |
| Mother’s education | ||||
| Primary | 60.8 | 51.7 | 66.1 | 59.0 |
| Secondary | 32.4 | 18.8 | 29.4 | 16.0 |
| Tertiary | 6.8 | 29.5 | 4.5 | 25.0 |
| Childhood deprivation | ||||
| Never | 87.9 | 91.5 | 87.9 | 92.2 |
| Occasionally went to bed hungry | 9.9 | 7.6 | 10.0 | 6.7 |
| Often went to bed hungry | 1.6 | 0.5 | 1.3 | 0.7 |
| Constantly hungry | 0.6 | 0.3 | 0.8 | 0.4 |
| Age group | ||||
| 42–45 | 24.6 | 14.6 | 18.5 | 9.9 |
| 46–50 | 18.4 | 16.6 | 15.8 | 14.1 |
| 51–55 | 16.0 | 17.5 | 15.2 | 16.7 |
| 56–60 | 19.3 | 23.3 | 21.3 | 26.0 |
| 61–65 | 21.7 | 27.9 | 29.2 | 33.3 |
| Marital status | ||||
| Single | 8.7 | 6.7 | 5.0 | 2.9 |
| Married | 69.9 | 68.6 | 59.5 | 59.7 |
| Separated/divorced | 16.1 | 20.0 | 15.5 | 15.5 |
| Widow/widower | 5.3 | 4.7 | 20.0 | 21.9 |
| Education | ||||
| Primary | 29.0 | 25.3 | 25.6 | 20.9 |
| Secondary | 53.1 | 57.4 | 54.6 | 61.4 |
| Tertiary | 17.9 | 17.4 | 19.8 | 17.8 |
| Employment | ||||
| Not working | 38.2 | 38.5 | 46.7 | 53.9 |
| Working | 61.8 | 61.5 | 53.3 | 46.1 |
| Long-term unemployment | ||||
| No | 77.4 | 85.8 | 82.1 | 90.7 |
| Yes | 22.6 | 14.2 | 17.9 | 9.3 |
| Supervisory status | ||||
| No | 77.5 | 78.8 | 80.0 | 80.2 |
| Yes | 22.5 | 21.2 | 20.0 | 19.8 |
| Religion | ||||
| Orthodox | 89.1 | 83.6 | 94.3 | 85.8 |
| Other Christian | 1.2 | 9.9 | 1.3 | 12.6 |
| Muslim | 1.2 | 0.2 | 1.3 | 0.1 |
| Other | 8.5 | 6.4 | 3.0 | 1.5 |
| Observations | 4517 | 3029 | 10,581 | 7341 |
Bivariate analysis
Age-adjusted bivariate prevalence ratios of regular smoking from multilevel mixed-effect Poisson regressions (PrivMort retrospective cohort study conducted in Russia and Belarus, 2014–2015)
| Men | Women | |||
|---|---|---|---|---|
| Russia PR [95 CI] | Belarus PR [95 CI] | Russia PR [95 CI] | Belarus PR [95 CI] | |
| Intercept | 0.39 [0.35, 0.42] | 0.36 [0.30, 0.42] | 0.03 [0.02, 0.04] | 0.02 [0.01, 0.03] |
| Father’s smoking | ||||
| Never smoked | 1.00 | 1.00 | 1.00 | 1.00 |
| N | 987 | 804 | 2425 | 2127 |
| Regular smoker | 1.38 [1.24, 1.53] | 1.45 [1.29, 1.64] | 1.40 [1.19, 1.66] | 1.36 [1.08, 1.72] |
| N | 2610 | 1623 | 6221 | 3937 |
| Quit | 1.11 [0.99, 1.24] | 1.28 [1.13, 1.44] | 0.93 [0.73, 1.19] | 1.20 [0.95, 1.51] |
| N | 920 | 602 | 1935 | 1.313 |
| Mother’s smoking | ||||
| Never smoked | 1.00 | 1.00 | 1.00 | 1.00 |
| N | 4351 | 2901 | 10,236 | 7129 |
| Regular smoker | 1.16 [0.96, 1.40] | 1.13 [0.88, 1.45] | 2.16 [1.60, 2.91] | 2.66 [1.95, 3.63] |
| N | 76 | 69 | 170 | 139 |
| Quit | 1.00 [0.79, 1.27] | 0.87 [0.68, 1.12] | 1.92 [1.33, 2.79] | 1.64 [1.12, 2.39] |
| N | 90 | 60 | 175 | 73 |
| Random intercept | 0.01 [0.00, 0.02] | 0.01 [0.00, 0.04] | 0.28 [0.12, 0.64] | 0.13 [0.05, 0.32] |
| Model statistics | ||||
| Towns | 30 | 20 | 30 | 20 |
| Observations | 4517 | 3029 | 10,581 | 7341 |
Multivariate analysis
Age-adjusted multivariate prevalence ratios of regular smoking from multilevel mixed-effect Poisson regressions (PrivMort retrospective cohort study conducted in Russia and Belarus, 2014–2015)
| Men | Women | |||
|---|---|---|---|---|
| Russia PR [95 CI] | Belarus PR [95 CI] | Russia PR [95 CI] | Belarus PR [95 CI] | |
| Fixed effects | ||||
| Intercept | 0.27 [0.21, 0.35] | 0.28 [0.25, 0.31] | 0.02 [0.01, 0.03] | 0.01 [0.01, 0.01] |
| Parental and childhood variables | ||||
| Father’s smoking | ||||
| Never | 1.00 | 1.00 | 1.00 | 1.00 |
| Regular smoker | 1.35 [1.21, 1.50] | 1.39 [1.23, 1.58] | 1.40 [1.17, 1.66] | 1.33 [1.04, 1.69] |
| Quit | 1.11 [0.99, 1.24] | 1.23 [1.10, 1.38] | 0.95 [0.74, 1.21] | 1.21 [0.97, 1.52] |
| Mother’s smoking | ||||
| Never | 1.00 | 1.00 | 1.00 | 1.00 |
| Regular smoker | 1.13 [0.93, 1.36] | 1.05 [0.84, 1.33] | 1.91 [1.40, 2.61] | 2.30 [1.61, 3.28] |
| Quit | 0.97 [0.77, 1.22] | 0.88 [0.68, 1.15] | 1.83 [1.23, 2.72] | 1.44 [0.93, 2.21] |
| Father’s education | ||||
| Primary | 1.00 [0.82, 1.22] | 0.93 [0.82, 1.04] | 0.65 [0.51, 0.84] | 0.99 [0.77, 1.27] |
| Secondary | 1.05 [0.89, 1.24] | 0.93 [0.83, 1.04] | 0.78 [0.59, 1.02] | 0.93 [0.72, 1.21] |
| Tertiary | 1.00 | 1.00 | 1.00 | 1.00 |
| Mother’s education | ||||
| Primary | 1.06 [0.91, 1.24] | 1.05 [0.95, 1.15] | 0.97 [0.69, 1.38] | 0.71 [0.56, 0.91] |
| Secondary | 1.14 [0.99, 1.31] | 1.03 [0.94, 1.13] | 1.15 [0.82, 1.62] | 0.96 [0.81, 1.13] |
| Tertiary | 1.00 | 1.00 | 1.00 | 1.00 |
| Childhood deprivation | ||||
| Never | 1.00 | 1.00 | 1.00 | 1.00 |
| Occasionally went to bed hungry | 1.00 [0.88, 1.14] | 0.92 [0.79, 1.06] | 1.19 [0.97, 1.47] | 1.29 [1.06, 1.56] |
| Often went to bed hungry | 1.21 [1.01, 1.45] | 0.79 [0.45, 1.38] | 1.61 [0.98, 2.63] | 1.17 [0.45, 3.04] |
| Constantly hungry | 1.19 [0.80, 1.79] | 1.25 [0.79, 2.00] | 1.52 [0.91, 2.55] | 2.62 [1.13, 6.06] |
| Respondents’ characteristics | ||||
| Marital status | ||||
| Single | 0.91 [0.79, 1.05] | 1.05 [0.94, 1.17] | 1.74 [1.35, 2.25] | 1.87 [1.26, 2.78] |
| Married | 1.00 | 1.00 | 1.00 | 1.00 |
| Separated/divorced | 1.07 [0.98, 1.17] | 1.21 [1.11, 1.33] | 1.74 [1.47, 2.06] | 1.84 [1.53, 2.22] |
| Widow/widower | 1.09 [0.95, 1.24] | 1.09 [0.95, 1.25] | 1.76 [1.53, 2.04] | 1.71 [1.40, 2.08] |
| Education | ||||
| Primary | 1.45 [1.27, 1.66] | 1.49 [1.36, 1.62] | 1.93 [1.49, 2.51] | 2.02 [1.55, 2.64] |
| Secondary | 1.38 [1.21, 1.56] | 1.41 [1.30, 1.53] | 1.39 [1.08, 1.79] | 1.59 [1.36, 1.87] |
| Tertiary | 1.00 | 1.00 | 1.00 | 1.00 |
| Employment | ||||
| Not working | 1.00 | 1.00 | 1.00 | 1.00 |
| Working | 0.95 [0.89, 1.02] | 0.92 [0.83, 1.01] | 0.95 [0.75, 1.20] | 0.74 [0.60, 0.91] |
| Long-term unemployment | ||||
| No | 1.00 | 1.00 | 1.00 | 1.00 |
| Yes | 1.09 [1.00, 1.18] | 1.12 [1.01, 1.24] | 1.52 [1.28, 1.82] | 1.49 [1.17, 1.91] |
| Supervisory status | ||||
| No | 1.00 | 1.00 | 1.00 | 1.00 |
| Yes | 0.90 [0.83, 0.98] | 0.95 [0.88, 1.03] | 0.92 [0.77, 1.11] | 1.09 [0.90, 1.31] |
| Religion | ||||
| Orthodox | 1.00 | 1.00 | 1.00 | 1.00 |
| Other Christian | 0.69 [0.45, 1.05] | 0.88 [0.77, 1.01] | 1.10 [0.73, 1.65] | 1.08 [0.87, 1.34] |
| Muslim | 1.01 [0.81, 1.27] | 0.81 [0.46, 1.41] | 1.29 [0.83, 2.01] | 0.91 [0.49, 1.72] |
| Other | 1.09 [1.00, 1.19] | 0.90 [0.79, 1.03] | 1.28 [0.97, 1.71] | 0.95 [0.64, 1.41] |
| Macro-level variable | ||||
| Size of town (standardized) | 0.98 [0.94, 1.01] | 0.94 [0.90, 0.98] | 1.03 [0.88, 1.21] | 1.23 [0.99, 1.52] |
| Random intercept | 0.01 [0.00, 0.03] | 0.01 [0.00, 0.13] | 0.25 [0.11, 0.55] | |
| Model statistics | ||||
| Towns | 30 | 20 | 30 | 20 |
| Observations | 4517 | 3029 | 10,581 | 7341 |
Once parental smoking behaviour is accounted for, parental educational attainment is not significantly linked to offspring’s likelihood of smoking. However, compared to having tertiary educated fathers, women with low educated fathers in Russia are less likely to be regular smokers. Among women in Belarus, we also see that the daughters of low educated mothers in comparison to tertiary educated mothers have 29% lower prevalence of smoking. We do not find that childhood deprivation is systematically and significantly related to smoking. However, Russian men that often went to bed hungry, and Belarusian women who occasionally and constantly went to bed hungry when they were children, are more likely to be regular smokers.
When examined by marital status, single and widowed women and separated/divorced men and women have significantly higher prevalence of smoking than married individuals. Respondents’ own educational attainment is a strong predictor of regular smoking in both countries and across gender. For instance, men with primary education have prevalence ratios of 1.45 (CI 1.27–1.66) and 1.49 (CI 1.36–1.62) of being regular smokers in Russia and Belarus compared with those with tertiary education. Turning to labour market characteristics, being in employment, is associated with lower prevalence of smoking among women in Belarus, while long-term unemployment significantly increases the chances of regular smoking with prevalence ratios of 1.09 (CI 1.00–1.18) and 1.12 (CI 1.01–1.24) for men in Russia and Belarus and prevalence ratios of 1.52 (CI 1.28–1.82) and 1.49 (CI 1.17–1.91) for women in the same countries. Men with supervisory status attainment are also less likely to smoke in Russia. Neither respondent’s religious denomination nor the size of population in towns where the PrivMort retrospective cohort study was conducted is significantly and systematically related to regular smoking.
Predicted probabilities of regular smoking among men conditioned by parental smoking (PrivMort retrospective cohort study conducted in Russia and Belarus, 2014–2015). Error bars represent 95% confidence intervals
Predicted probabilities of regular smoking among women conditioned by parental smoking (PrivMort retrospective cohort study conducted in Russia and Belarus, 2014–2015). Error bars represent 95% confidence intervals
Further analysis
In unreported analysis, we have also conducted additional tests. To check if having both parents as smokers carry additional risks for their offspring smoking, we have interacted fathers’ and mothers’ smoking characteristics in multilevel mixed-effects Poisson regressions with the same specifications, as in Table 4. We have not found that there is such an association. Furthermore, through interacting age and parental smoking behaviour, we did not detect any systemic and significant differences in intergenerational transmission of smoking across different age groups in either Russia or in Belarus.
Discussion
In this article, we examined intergenerational transmission of smoking among middle-aged and older populations in Russia and Belarus using the newly available data from the PrivMort retrospective cohort study. This data set is a unique source for understanding the association of parental smoking behaviour on their offspring’s tobacco use in post-communist countries. The validity of our analysis is strengthened by the fact that the prevalence of smoking in our sample for men, 53.3 and 51.9%, respectively, in Russia and Belarus, comes close to the latest available estimates for adult populations derived from the Russia Longitudinal Monitoring Survey of RLMS-HSE for 2014 (49.0%) (Quirmbach and Gerry 2016) and the Health in Times of Transition Study (HITT) for Belarus in 2010 (42.8%) (Roberts et al. 2012). The main reason why the prevalence of current smoking among women in our data set is lower than that reported in the above-mentioned nationally representative surveys (9.4 vs. 14.4% for Russia and 8.3 vs. 13.2% for Belarus) is that the PrivMort does not include groups aged 41 and below who have the highest prevalence of smoking.
Adjusting for social origin, socio-demographic, and socio-economic variables, we find that paternal smoking significantly increases the chances of smoking among sons, while having a regularly smoking mother significantly increases the chances of smoking among daughters. In absolute terms, this equates to about 9–12 percentage points higher prevalence of smoking in Russia and Belarus among women with smoking mothers in comparison to women with never smoking mothers, which is remarkable, considering that in our sample of middle-aged and older women, the rate of smoking in Russia and Belarus is less than 10%. These results are in line both with psycho-analytic theory (Boyd 1989) which claims that daughters tend to unconsciously internalise maternal values and behaviours as well as with social learning theory (Bandura 1977) that emphasises principles of intergenerational modelling and suggests that girls are consistently and positively reinforced when they learn to be like their mothers and imitate maternal behaviour. Daughters also tend to spend significantly more time with their mothers than sons do (Kislitsyna et al. 2010). Our results complement the earlier findings on the parental transmission of smoking that do not usually emphasise the varying roles of paternal and maternal tobacco use in middle-aged and older sons and daughters smoking behaviour (e.g., Brenner and Scharrer 1996; Bricker et al. 2006; Chassin et al. 1998; Kandel and Wu 1995; Melchior et al. 2010).
Our study has a number of limitations. Due to the survey design, we do not have information on smoking for those parents who died before 1982. Therefore, information on maternal smoking had to be imputed for 10 and 7% of male and 12 and 7% of female respondents, respectively, in Russia and Belarus. Furthermore, the data set is not a nationally representative survey of Russia and Belarus and the findings cannot be generalised to these countries’ entire populations. Another limitation of this study is recall bias and measurement error that can stem from asking questions about circumstances and events related to respondents’ parents and their childhood. Such misclassification can lead to misestimating of the strengths of associations between parental and offspring smoking. The design of the questionnaire we use, however, mitigates this limitation by introducing auxiliary sentences and incorporating active visualisation memory cards that can assist people in remembering various characteristics of their parents’ and their own childhood more easily.
Our findings not only contribute to the existing scholarship on intergenerational transmission of socio-economic disadvantage in post-communist contexts (Gugushvili 2015, 2016, 2017a, b), but are also relevant in interpreting trends and patterns of smoking among middle-aged and older Russian and Belarusian men and women, with implications for subsequent generations, an issue of importance given increasing smoking among women. Of course, we cannot assume that the strength of intergenerational transmission of smoking will be the same in the future, given the many other factors involved such as shrinking gender differences in smoking. Nonetheless, if parents are aware of the implications of smoking and how much they can influence their sons and daughters’ propensity to smoke even in the later stages of their life course, some might have an extra reason not to start smoking or to quit after smoking initiation (Bricker et al. 2006; Roberts et al. 2013).
However, the main implication of our results for research on prevention and control of tobacco use is that intergenerational transmission of smoking does not seem to be a methodological artefact of inadequately accounting for social origin variables and the many potentially confounding factors throughout individuals’ lives. Parental influence on smoking is a significant factor not only for adolescents but also for middle-aged and older populations in the considered post-communist countries. Therefore, to understand thoroughly the confounding factors of smoking in the region and, arguably, beyond, the existing longitudinal and cross-sectional surveys, such as Global Adult Tobacco Survey (GATS) and RLMS-HSE, should explicitly enquire into smoking behaviours of respondents’ parents. Intergenerational influences on smoking should also be taken into account of in studies seeking to monitor rates of smoking and the impact of tobacco control programmes.
Notes
Compliance with ethical standards
The study has been approved by the University of Cambridge Department of Sociology ethics committee. All data are anonymized to prevent any potential identification of individual respondents.
References
- Azarova A, Irdam D, Gugushvili A et al (2017) The effect of rapid privatisation on mortality in mono-industrial towns in post-Soviet Russia: a retrospective cohort study. Lancet Public Health 2:e231–e238. https://doi.org/10.1016/S2468-2667(17)30072-5 CrossRefPubMedPubMedCentralGoogle Scholar
- Bailey SL, Ennett ST, Ringwalt CL (1993) Potential mediators, moderators, or independent effects in the relationship between parents’ former and current cigarette use and their children’s cigarette use. Addict Behav 18:601–621. https://doi.org/10.1016/0306-4603(93)90015-2 CrossRefPubMedGoogle Scholar
- Bandura A (1977) Social learning theory. Prentice Hall, Englewood CliffsGoogle Scholar
- Bobak M, Gilmore A, McKee M et al (2006) Changes in smoking prevalence in Russia, 1996–2004. Tob Control 15:131–135. https://doi.org/10.1136/tc.2005.014274 CrossRefPubMedPubMedCentralGoogle Scholar
- Boyd CJ (1989) Mothers and daughters: a discussion of theory and research. J Marriage Fam 51:291. https://doi.org/10.2307/352493 CrossRefGoogle Scholar
- Brenner H, Scharrer SB (1996) Parental smoking and sociodemographic factors related to smoking among German medical students. Eur J Epidemiol 12:171–176. https://doi.org/10.1007/BF00145503 CrossRefPubMedGoogle Scholar
- Bricker JB, Peterson AV, Leroux BG et al (2006) Prospective prediction of children’s smoking transitions: role of parents’ and older siblings’ smoking. Addiction 101:128–136. https://doi.org/10.1111/j.1360-0443.2005.01297.x CrossRefPubMedGoogle Scholar
- Brook JS, Rubenstone E, Zhang C et al (2013) The intergenerational transmission of smoking in adulthood: a 25-year study of maternal and offspring maladaptive attributes. Addict Behav 38:2361–2368. https://doi.org/10.1016/j.addbeh.2013.03.008 CrossRefPubMedPubMedCentralGoogle Scholar
- Chassin L, Presson CC, Todd M et al (1998) Maternal socialization of adolescent smoking: the intergenerational transmission of parenting and smoking. Dev Psychol 34:1189–1201. https://doi.org/10.1037/0012-1649.34.6.1189 CrossRefPubMedGoogle Scholar
- Christopoulou R, Lillard DR, Balmori De La Miyar JR (2013) Smoking behavior of Mexicans: patterns by birth-cohort, gender, and education. Int J Public Health 58:335–343. https://doi.org/10.1007/s00038-012-0376-7 CrossRefPubMedGoogle Scholar
- Conrad KM, Flay BR, Hill D (1992) Why children start smoking cigarettes: predictors of onset. Addiction 87:1711–1724. https://doi.org/10.1111/j.1360-0443.1992.tb02684.x CrossRefGoogle Scholar
- Fagan P, Brook JS, Rubenstone E, Zhang C (2005) Parental occupation, education, and smoking as predictors of offspring tobacco use in adulthood: a longitudinal study. Addict Behav 30:517–529. https://doi.org/10.1016/j.addbeh.2004.08.002 CrossRefPubMedGoogle Scholar
- Gilmore AB, McKee M (2005) Exploring the impact of foreign direct investment on tobacco consumption in the former Soviet Union. Tob Control 14:13–21. https://doi.org/10.1136/tc.2003.005082 CrossRefPubMedPubMedCentralGoogle Scholar
- Gilmore AB, McKee M, Rose R (2001) Prevalence and determinants of smoking in Belarus: a national household survey, 2000. Eur J Epidemiol 17:245–253. https://doi.org/10.1023/A:1017999421202 CrossRefPubMedGoogle Scholar
- Gilmore AB, Fooks G, McKee M (2011) A review of the impacts of tobacco industry privatisation: implications for policy. Glob Public Health 6:621–642. https://doi.org/10.1080/17441692.2011.595727 CrossRefPubMedPubMedCentralGoogle Scholar
- Gugushvili A (2015) Economic liberalization and intergenerational mobility in occupational status. Comp Sociol 14:790–820. https://doi.org/10.1163/15691330-12341368 CrossRefGoogle Scholar
- Gugushvili A (2016) Intergenerational objective and subjective mobility and attitudes towards income differences: evidence from transition societies. J Int Comp Soc Policy 32:199–219. https://doi.org/10.1080/21699763.2016.1206482 CrossRefGoogle Scholar
- Gugushvili A (2017a) Political democracy, economic liberalization, and macro-sociological models of intergenerational mobility. Soc Sci Res 66:58–81CrossRefPubMedGoogle Scholar
- Gugushvili A (2017b) Change or continuity? Intergenerational social mobility and post-communist transition. Res Soc Stratif Mob 52:59–71Google Scholar
- Gugushvili A, McKee M, Murphy M et al (2018) Intergenerational mobility in relative educational attainment and health-related behaviours. Soc Indic Res. https://doi.org/10.1007/s11205-017-1834-7 Google Scholar
- Irdam D, King L, Gugushvili A et al (2016) Mortality in transition: study protocol of the PrivMort Project, a multilevel convenience cohort study. BMC Public Health 16:672. https://doi.org/10.1186/s12889-016-3249-9 CrossRefPubMedPubMedCentralGoogle Scholar
- Jefferis B, Graham H, Manor O, Power C (2003) Cigarette consumption and socio-economic circumstances in adolescence as predictors of adult smoking. Addiction 98:1765–1772. https://doi.org/10.1111/j.1360-0443.2003.00552.x CrossRefPubMedGoogle Scholar
- Kandel DB, Wu P (1995) The contributions of mothers and fathers to the intergenerational transmission of cigarette smoking in adolescence. J Res Adolesc 5:225–252. https://doi.org/10.1207/s15327795jra0502_4 CrossRefGoogle Scholar
- Kandel DB, Griesler PC, Hu MC (2015) Intergenerational patterns of smoking and nicotine dependence among US adolescents. Am J Public Health 105:e63–e72. https://doi.org/10.2105/AJPH.2015.302775 CrossRefPubMedPubMedCentralGoogle Scholar
- Kemppainen U, Tossavainen K, Vartiainen E et al (2006) Environmental factors as predictors of smoking among ninth-grade adolescents in pitkäranta (Russian karelia) and in eastern Finland. Res Nurs Health 29:543–555. https://doi.org/10.1002/nur.20170 CrossRefPubMedGoogle Scholar
- Kislitsyna O, Stickley A, Gilmore A, McKee M (2010) The social determinants of adolescent smoking in Russia in 2004. Int J Public Health 55:619–626. https://doi.org/10.1007/s00038-010-0196-6 CrossRefPubMedGoogle Scholar
- Lillard DR, Dorofeeva Z (2015) Smoking in Russia and Ukraine before, during and after the Soviet union. In: Lillard DR, Christopoulou R (eds) Life-course smoking behavior. Oxford University Press, Oxford, pp 1–29CrossRefGoogle Scholar
- McGee R, Williams S, Reeder A (2006) Parental tobacco smoking behaviour and their children’s smoking and cessation in adulthood. Addiction 101:1193–1201. https://doi.org/10.1111/j.1360-0443.2006.01486.x CrossRefPubMedGoogle Scholar
- McKee M, Bobak M, Rose R et al (1998) Patterns of smoking in Russia. Tob Control 7:22–26. https://doi.org/10.1136/tc.7.1.22 CrossRefPubMedPubMedCentralGoogle Scholar
- Melchior M, Chastang J-F, Mackinnon D et al (2010) The intergenerational transmission of tobacco smoking—the role of parents’ long-term smoking trajectories. Drug Alcohol Depend 107:257–260. https://doi.org/10.1016/j.drugalcdep.2009.10.016 CrossRefPubMedGoogle Scholar
- Perlman F, Bobak M, Gilmore A, McKee M (2007) Trends in the prevalence of smoking in Russia during the transition to a market economy. Tob Control 16:299–305. https://doi.org/10.1136/tc.2006.019455 CrossRefPubMedPubMedCentralGoogle Scholar
- Pomerleau J, Gilmore A, McKee M et al (2004) Determinants of smoking in eight countries of the former Soviet Union: results from the living conditions, lifestyles and health study. Addiction 99:1577–1585. https://doi.org/10.1111/j.1360-0443.2004.00885.x CrossRefPubMedGoogle Scholar
- Quirmbach D, Gerry CJ (2016) Gender, education and Russia’s tobacco epidemic: a life-course approach. Soc Sci Med 160:54–66. https://doi.org/10.1016/j.socscimed.2016.05.008 CrossRefPubMedGoogle Scholar
- Roberts B, Gilmore A, Stickley A et al (2012) Changes in smoking prevalence in 8 countries of the former Soviet Union between 2001 and 2010. Am J Public Health 102:1320–1328. https://doi.org/10.2105/AJPH.2011.300547 CrossRefPubMedPubMedCentralGoogle Scholar
- Roberts B, Stickley A, Gilmore AB et al (2013) Knowledge of the health impacts of smoking and public attitudes towards tobacco control in the former Soviet Union. Tob Control 22:e12. https://doi.org/10.1136/tobaccocontrol-2011-050249 CrossRefPubMedGoogle Scholar
- Rubin DB (1987) Multiple imputation for nonresponse in surveys. Wiley, New YorkCrossRefGoogle Scholar
- Schori D, Hofmann K, Abel T (2014) Social inequality and smoking in young Swiss men: intergenerational transmission of cultural capital and health orientation. Int J Public Health 59:261–270. https://doi.org/10.1007/s00038-013-0537-3 CrossRefPubMedGoogle Scholar
- WHO (2016) Prevalence of tobacco smoking: age-standardized prevalence of current tobacco smoking among persons aged 15 years and older (%), 2015: male, female. Global Health Observatory (GHO). http://www.who.int/gho/tobacco/use/en/
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