Relationship between smoking and marital adjustment & social support among women with spouses experiencing alcohol/substance use disorders

Abstract

Background

Women’s smoking is a serious and growing problem worldwide. Determining the variables related to smoking to stop this increase is important for the protection of women in special groups with psychological and social risks such as dependent relatives. It was aimed to determine the smoking use of women with dependent spouses and its relationship with marital adjustment and perception of social support.

Methods

The research is a cross-sectional study. Population of the study consists of 1.500 women who are the spouses of men with the diagnosis of alcohol/substance use disorder and alcohol withdrawal syndrome. The population was calculated with a 20% prevalence 4% margin of error and a 95% confidence interval, and the sample size was 306. The research was carried out between November 2019 and July 2021. Statistical significance level was accepted as P < 0.05. Chi-square Test was used in the analysis of categorical data. Logistic Regression Analysis was used in multivariate analysis.

Results

The spouses of 250 people experiencing alcohol or substance use disorder were included in the study. The coverage of the research is 81.7%. Smoking frequency of women is 65.2%. In bivariate analysis, women’s smoking was found to be statistically significant with the variables of spouse’s addiction type, age, longest place of residence, educational status, history of chronic disease, need for mental support, and presence of hobbies(p < 0.05). In multivariate analysis, it was observed that each unit increase in age, social support score and marital adjustment score was associated with 1.08 (95% CI: 1.01–1.15), 1.35 (95% CI: 1.18–1.55) and 1.12 (95% CI: 1.00–1.12) times increase in smoking risk, respectively.

Conclusions

In this study, two out of three women with spouses experiencing alcohol/substance use disorder were found to smoke. It has been determined that the risk of smoking is high in women whose spouses have substance use disorder, have a high education level, have a chronic illness, need mental support, do not have a hobby, have a low perception of social support, and have an incompatible marriage. High rate of smoking in this population indicates need for preventive studies with people experiencing alcohol/substance use disorder and their relatives. In addition, it would be beneficial to develop smoking cessation programs with cognitive-behavioral interventions and that strengthen psycho-social support systems in addition to pharmacological treatments.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12905-025-03947-1.

Introduction

Women’s smoking is a serious and growing problem worldwide. Approximately 20% of the world’s more than 1 billion smokers are women. As socio-economic and cultural norms change, women’s smoking characteristics also change. It has been previously documented that women with higher socio-economic status in Southern Europe smoke more [1] and that a similar pattern is observed in women in Turkey [2]. While the smoking rate among women in Turkey was 15.2% in 2008, this rate decreased to 13.1% in 2012. However, it increased to 19.2% in 2016 [3–5]. Identifying the factors that lead women to smoking is very important in terms of stopping this increase, preventing the transition to other substances and protecting women’s health.

Despite the known high rates of smoking among women, there is a lack of focused research on specific disadvantaged subgroups, such as women with spouses experiencing alcohol/substance use disorder (AUD/SUD). AUD/SUD is a chronic disease consisting of genetic, neurobiological and sociocultural factors, known for the use of drugs or substances at a level that affects a person’s physical and mental health and family life [6]. In this respect, the concept of “relatives of individuals with SUD” has attracted attention in recent years. The presence of a person with AUD/SUD in the family can disrupt the family structure and lead to social problems [7]. AUD/SUD is considered as a family disease, especially affecting the spouses of users, and accordingly, it is stated that family relatives need mental support [8].

Scientific studies on gender differences in smoking have reported that women and men show different patterns of smoking. Studies conducted in different geographies show that women are more likely than men to smoke to cope with psychological distress, negative mood and stress, using smoking as a form of self-medication [9–12]. Women are reported to experience more smoking-related mental and physiological problems than men [13]. Additionally, the perception and impact of social support can vary by gender, with women generally experiencing greater benefits from social support in terms of stress reduction and improved mental health outcomes compared to men [14].

Marital adjustment, the process by which couples accommodate to each other’s needs and maintain a harmonious relationship, can be significantly disrupted by AUD/SUD. Previous research has established that poor marital adjustment and low levels of social support are significant predictors of increased anxiety and stress among women [15], which in turn can lead to higher rates of smoking as a coping mechanism [16]. The presence of a spouse struggling with AUD/SUD compounds these issues, creating a complex environment where marital dissatisfaction and lack of social support can further influence smoking behavior. It has been found that depression, anxiety and stress levels are higher in women whose spouses have AUD and that there are more problems in terms of marital adjustment [17, 18]. The stress associated with managing a household and caring for a spouse with alcohol/substance use issues often leads to chronic stress [19], which has been shown to increase smoking frequency as a means of coping [20]. Additionally, cultural norms and social pressures may make smoking less acceptable for women in general, but those with spouses experiencing AUD/SUD might experience more permissive attitudes toward smoking as a coping mechanism for dealing with their spouse’s disorder and related stress.

Coping theories elucidate the mechanisms by which individuals navigate stress and challenging situations, positing that all coping reactions are inherently adaptive and serve to initially mitigate distress. Within health theory of coping, a recent addition to coping theories, these strategies are categorized as maladaptive, such as smoking, or adaptive, such as seeking social support [21]. In this study, both smoking and social support are examined as key variables, highlighting the dual role of smoking as a stress response and social support as a healthier alternative. Research indicates that both coping mechanisms are prevalent among wives of spouses experiencing alcohol use disorder, underscoring the need for evaluations that address these patterns [22].Although substantial literature exists on the general factors influencing smoking among women and the impact of having relatives struggling with AUD/SUD on marital adjustment and social support [23–25], there is a distinct lack of studies exploring these dimensions in conjunction with women’s smoking behaviors in Turkey. This study aims to fill this gap by enhancing the understanding of how marital and social dynamics influence smoking habits within this vulnerable population through scrutinizing these interrelated factors. The rationale for focusing on women with dependent spouses lies in the significant psychological and social risks they face, which are exacerbated by their spouse’s AUD/SUD.

The objective of this study is to investigate the relationship between smoking and various socio-economic and demographic factors, health status, habits, marital adjustment, and social support among women with spouses experiencing AUD/SUD, with an emphasis on elucidating gender differences within these dynamics. The findings are anticipated to contribute the formulation of targeted interventions that address both marital adjustment and social support, thereby fostering healthier coping mechanisms and reducing smoking rates among these women.

Method

The research is a cross-sectional study. This study was conducted between November 2019 and July 2021. The preparatory phase, including ethics approval, permissions, and instrument development, occurred between November 2019 and January 2020. Data were collected between January 2020 and April 2020. The remaining period (April 2020–July 2021) included data cleaning, statistical analysis, and manuscript preparation. Prior to data collection, permission was obtained from the Izmir Provincial Health Directorate. Subsequently, necessary permissions were secured from the university hospital where the research was to be conducted through consultations with the hospital administration. Participants were first provided with information about the form and the research itself. Considering the principle of voluntariness, informed consent was obtained from the participants using the “Informed Voluntary Consent” form. Data were collected in the waiting areas of the addiction clinics using a self-report information form and scales prepared for the participants.

Population and sample of the study

The population of the study consisted of women who were the spouses of men who received inpatient or outpatient treatment with a diagnosis of AUD/SUD at the AMATEM Unit of İzmir Katip Celebi University Atatürk Education and Research Hospital between January 2020 and April 2020. Annual admission to the AMATEM unit is approximately 1500 people. The sample size is calculated by Epi Info program v5.5.15. Calculated sample size for a population of 1500 people is 306 people with a prevalence of 20% [5], a margin of error of 4% and a %95 confidence interval. Considering that approximately 50% of the applicants came with their spouses, the data collection period was determined as approximately 3 months. The exclusion criteria of the study were not being volunteer to participate, not filling the key variables in the questionnaire. 30 people were excluded from the study because they refused to participate, 10 people were excluded because they were discharged before they could complete the questionnaire, and 16 people were excluded because they did not answer the main variables. As a result, 250 spouses of individuals experiencing AUD/SUD, all of whom were women, were included in the study (Supplementary Fig. 1).

Variables

The dependent variable of this study is “smoking”. Participants were questioned about their smoking status, how many years they had been smoking, the age at which they started smoking, how many cigarettes they smoked per day, in which emotions/situations the desire to smoke arose, the reasons for continuing to smoke, and whether they had ever attempted to quit smoking. Fagerström Nicotine Dependence Test was used to determine the addiction level of women. The test scores were stratified into five distinct categories for evaluation: individuals with scores ranging from 0 to 2 were categorized as having a very low level of nicotine dependence, those with scores between 3 and 4 were identified as having a low level, a score of 5 denoted a moderate level, scores within the 6–7 range indicated a high level, and scores of 8 or above signified a very high level of nicotine dependence. The Cronbach’s alpha value of the scale was found to be 0.56 in Turkish sample [26].

The independent variables of the study were socioeconomic and demographic characteristics, current health status, habits, social support and marital adjustment. Socioeconomic and demographic characteristics were identified with the personal information form prepared by the researcher. In this context, type of addiction, age, place of residence, educational status, employment status, income status, year, number and type of marriage and number of children were asked. In the form, women were also questioned about their current health status, history of chronic diseases and need for mental support. For habits, the status ofhaving a hobby and the amount of alcohol use were questioned. Continuous variables were categorized to allow for meaningful group comparisons. Age was grouped into ≤ 30, 31–40, 41–50, and > 50 years based on distributional characteristics and life-stage transitions. Age at marriage was categorized as ≤ 18 years, 19–25 years, and > 25 years to reflect early, typical, and later marriage patterns.

The Marital Adjustment Scale (MAS) was used to measure marital adjustment. The scale consists of 15 items. The scale measures relationship style such as general marital satisfaction, quality of marriage, family planning, sexual life, expression of emotions such as anger and joy, friendship relations, agreement or disagreement on issues such as social rules, utilization of leisure time between the couples, doing activities outside the home, and conflict resolution [27]. For instance, sample items might inquire, “To what extent do you and your spouse experience disagreements regarding financial decisions?” or “How consistently do you feel emotionally supported by your partner?” Respondents typically utilize a Likert scale to quantify their experiences and perceptions, with responses ranging from “strongly disagree” to “strongly agree.” Validity and reliability study to determine usability of MAS in marriage studies in our country is performed in 1999. The reliability of the test for marital adjustment was determined to be r = 0.84. As a result of scoring, point level is determined as 43.5 to differentiate between people with compatible and incompatible marriage [28]. The scale has been reliably used as an instrument to assess marital adjustment among wives of patients with AUD in Turkey [29].

In order to determine the social support characteristics of the participants, data were collected using the Multidimensional Scale of Perceived Social Support (MSPSS). Multidimensional Scale of Perceived Social Support (MSPSS) is an easy-to-administer, short scale developed for the subjective assessment of perceived social support adequacy from three different sources [30]. The MSPSS consists of a total of 12 items. The scale includes three different sources of social support, each consisting of four items. These sources are friends, a special person and family. Sample items include: “My family really tries to help me” (Family Subscale).“I have friends with whom I can share my joys and sorrows” (Friends Subscale). Each item is rated on a 7-point scale. The subscale score is formed by summing the four item scores in the subscales and the total score of the scale is reached by summing the subscale scores. A high scale score means a high level of perceived social support The cronbach’s alpha value for the scale ranges between 0.77 and 0.92 for different samples [31]. The maximum score that can be obtained from the scale is 84. The scale is utilized to assess perceived social support among wives of individuals with AUD [25].

The mean social support score of the participants was found to be 35.6 and this value was determined as the cut-off point for grouping. Those with a scale score less than 35.6 were considered to have low social support, while those with a high score were considered to have high social support. In line with the mean scores of the participants in the perceived social support subscales, cut-off points were determined for the grouping of the subscales. In our study, the mean score of the “Friends” subscale was found to be 13.2; the mean score of the “Special person support” subscale was found to be 10.04; and the mean score of the “Family” subscale was found to be 13.0. These values were used as cut-off points. Scores below these values were categorized as “low” and scores above these values were categorized as “high”.

Data analysis and evaluation techniques

The data were recorded in a database prepared with Statistical Package for Social Sciences for Windows TM 23.0. P < 0.05 was accepted as the level of statistical significance. Descriptive analyses and continuous variables are given as mean and standard deviation. Categorical variables are given as number and percentage. For the evaluation of the relationship between dependent and independent variables; Chi-Square Test was used in the analysis of categorical data. Effect sizes were calculated for establishing the differences between smokers and non-smokers in relation to the independent variables. (phi) coefficient was used for 2 × 2 contingency tables and Cramér’s V was used for the tables larger than 2 × 2 for the estimation of effect size [32]. Variables that were significant and not correlated with each other in the Chi-Square test were included in the Logistic Regression Analysis. Age, perceived social support, and marital adjustment are incorporated into the regression model as continuous variables.

Results

The coverage rate of the study was 81.7%. Within the scope of the study, 250 women with spouses with AUD/SUD were interviewed. Table 1 shows the smoking status of the participants in relation to their socioeconomic, demographic and health data.

Table 1.

Smoking status of the study group in relation to socioeconomic, demographic and health data

Variables		Smoking				Total*		Effect Size	p
		Yes		No		N	%
		N	%	N	%
Age Group	30 and below	9	36.0	16	64.0	25	10.0	0.357	< 0.001
	31–40 years old	67	84.8	12	15.2	79	31.6
	41–50 years old	80	80.8	19	19.2	99	39.6
	51 and above	27	57.4	20	42.6	47	18.8
Longest Place of Residence	Village	3	23.1	10	76.9	13	5.2	0.226	0.005
	Small Town/Neighborhood	11	14.9	40	85.1	51	20.4
	City	60	76.9	18	23.1	78	31.2
	Metropolitan	92	82.1	20	17.9	112	44.8
Education	Middle School and Lower	70	59.8	47	40.2	117	46.8	0.150	0.009
	High School	47	65.2	25	34.8	72	28.8
	University and Higher	40	78.4	11	21.6	51	20.4
Employment	Unemployed	115	72.8	43	27.2	158	63.2	0.012	0.883
	Employed	68	73.9	24	26.1	92	36.8
Job type	Housewife	115	72.8	43	27.2	158	63.2	0.037	0.839
	Blue Collar	30	76.9	9	23.1	39	15.6
	White Collar	38	71.7	15	28.3	53	21.2
Income Status	Income Less than Expenditure	86	72.3	33	27.7	119	47.6	0.129	0.124
	Income Equivalent to Expenditure	65	69.1	29	30.9	94	37.6
	Income More than Expenditure	32	86.5	5	13.5	37	14.8
Type of Marriage	Arranged Marriage	51	78.5	14	21.5	65	26	0.218	0.103
	Consanguineous Marriage	0	0	4	100	4	1.6
	Love Marriage	132	72.9	49	27.1	181	72.4
Age at the Time of Marriage	18 and below	43	23.5	10	14.9	53	21.2	0.099	0.291
	19–25 years old	108	59	46	68.7	154	61.6
	26 and above	32	17.5	11	16.4	43	17.2
Children	Yes	134	71.7	53	28.3	187	74.8	0.060	0.412
	No	49	77.8	14	22.2	63	25.2
History of Chronic Illness	Yes	31	57.4	23	42.6	54	21.6	0.187	0.003
	No	152	77.6	44	22.4	196	78.4
Need of Mental Support	Yes	152	79.2	40	20.8	192	76.8	0.245	< 0.001
	No	31	53.4	27	46.6	58	23.2
Hobbies	Yes	80	61.1	51	38.9	131	52.4	0.287	< 0.001
	No	103	86.6	16	13.4	119	47.6
Alcohol Consumption	Yes	76	73.8	27	26.2	103	41.2	0.011	0.886
	No	107	72.8	40	27.2	147	58.8
Spouse’s Addiction Type	Alcohol	117	67.6	56	32.4	173	69.2	0.188	0.003
	Substance	66	85.7	11	14.3	77	30.8

*Column percentage was used

When the demographic characteristics of the participants are evaluated; 39.6% of the women are between the ages of 41–50 and 31.6% are between the ages of 31–40. 44.8% have spent most of their lives in metropolitan cities. Among the women, 50.8% are middle school graduates or below, 28.8% are high school graduates, and 20.4% are university graduates. 63.2% are not working. 21.2% have a white-collar job and 15.6% have a blue-collar job. In terms of income distribution, 47.6% of the respondents have an income less than their expenses. When the marital characteristics were analyzed, it was learned that 61.6% were married between the ages of 19–25 and 21.2% were married under the age of 18. Among the women, the rate of marrying for love is 72.4% and the rate of having at least one child is 74.8%.

When the existing health status and habits of the participants are evaluated; it was found that 78.4% do not have a history of chronic illness. 76.8% state that they need mental support. 52.4% have a hobby. 58.8% do not use alcohol. The spouses of the participants with alcohol or substance use disorder were interviewed to determine their alcohol and cigarette use. According to the data obtained; the frequency of alcohol use in spouses is 84% and the frequency of smoking is 77.2%.

Women’s smoking was found to be statistically significant with the variables of spouse’s addiction type, age, longest place of residence, educational status, history of chronic disease, need for mental support, and presence of hobbies. Women’s cigarette use was found to be higher in those with SUD than in those with AUD (p = 0.003, phi = 0.188), indicating a small effect size. Women in the 30–40 age range had significantly higher rates of smoking compared to the women in other age ranges (p < 0.010, Cramer’s V = 0.357), indicating a medium effect size. Women who spent most of their lives in cities or metropolitan areas had significantly higher rates of cigarette use than those who lived in other settlements (p = 0.005, Cramer’s V = 0.226), which reveals a medium effect size. It was observed that smoking increased as women’s educational level increased (p = 0.005, Cramer’s V = 0.150), which indicates a small effect size. Women who did not have a chronic disease had significantly higher smoking rates than the other group (p = 0.003, phi = 0.187), reflecting a small effect size. Smoking was found to be higher in the women who needed mental support than in those who did not (p < 0.01, phi = 0.245), indicating a small effect size. Women who did not have a hobby were significantly more likely to smoke than those who had a hobby (p < 0.01, phi = 0.287), reflecting a small effect size. No statistical significance was found between smoking and employment status, type of work, presence of children, income status, age at marriage, alcohol use, and spouse’s smoking (p > 0.05).

Table 2 shows the smoking status of the participants in relation to marital adjustment and social support characteristics. Detailed data on marital adjustment scale and perceived social support scale scores can be found in supplementary documents (supplementary Tables 1 and supplementary graph 1).

Table 2.

Participants’ smoking status in relation to marital adjustment and social support characteristics

Variables	Options	Smoking				Total*		Effect Size	p
		Yes		No
Marital Adjustment	Compatible	N	%	N	%	N	%	0.656	< 0.001
		41	39.0	64	61.0	105	42.0
	Incompatible	142	97.9	3	2.1	145	58.0
Multidimensional Scale of Perceived Social Support	Low	109	78.4	30	21.6	139	55.6	0.677	< 0.001
	High	44	39.6	67	60.4	111	44.4

*Column percentage was used

Women with lower levels of marital adjustment and perceived social support were found to smoke more (p < 0.001, phi = 0.656 and phi = 0.677, respectively), indicating large effect sizes for both variables.

The results of the regression analysis of the variables associated with participants’ smoking are presented in Table 3.

Table 3.

Regression analysis of variables predicting participants’ smoking

	OR (%95 CI)	P value
Type of Addiction
Substance	OR = 1.16 (CI:0.16–8.40)	0.877
Alcohol(ref)	1	1
Age	OR = 1.08 (CI:1.01–1.15)	0.25
Place of Residence
Metropolitan	OR = 2.43 (CI:0.39–15.20)	0.342
City	OR = 1.92 (CI:0.38–9.78)	0.433
Village (ref)	1	1
Education Status
University and higher	OR = 2.98 (CI: 0.40-21.79)	0.284
High school	OR = 2.02 (CI:0.22–18.34)	0.533
Middle school and below (ref)	1	1
Need for Mental Support
No	OR = 4.4 (CI:0.70-28.38)	0.115
Yes(ref)	1	1
Hobbies
No	OR = 5.09 (CI:0.74–38.82)	0.97
Yes(ref)	1	1
Perceived Social Support	OR = 1.35 (CI:1.18–1.55)	< 0.001
Low High(ref)
Marital Adjustment	OR = 1.12 (CI: 1.00-1.26)	0.048
Incompatible Compatible(ref)

R2 = 0.849 (Nagelkerke)

Hosmer and Lemeshow test = 0.970

When the factors affecting women’s smoking were analyzed, it was observed that each unit increase in age, social support score and marital adjustment score was associated with 1.08 (95% CI: 1.01–1.15), 1.35 (95% CI: 1.18–1.55) and 1.12 (95% CI: 1.00–1.12) times increase in smoking risk, respectively. No significant association was found between hobbies, education level, mental support need and smoking (p > 0.05). The model explained 85% (Nagelkerke R2) of the variance in smoking status.

Discussion

This study was conducted with the spouses of patients diagnosed with AUD/SUD and treated as inpatients or outpatients at the AMATEM Unit of İzmir Katip Çelebi University Atatürk Education and Research Hospital. Within the scope of the study, 250 women with spouses experiencing AUD/SUD were interviewed.

As a result of the analysis, it was found that two out of every three women (65.2%) smoked cigarettes. Compared to the general population, smoking rates in this sample are quite high [33]. Among women, 28.3% had very high and 26.4% had high levels of nicotine dependence. As a result of the research, it is seen that all four hypotheses were confirmed in terms of certain variables. As a result of bivariate and multivariate analysis, the risk of smoking was found to be higher among those whose spouse experiencing SUD, those who graduated from university, those who did not have a chronic disease, those who needed mental support, those who did not have a hobby, women with low levels of perceived social support, and those who had an incompatible marriage. While the variables of substance type, hobbies, and the need for mental support lost their significance in the multivariate analysis, they proved significant in pairwise comparisons. In the multivariate analysis, it was observed that each unit increase in age, social support score and marital adjustment score was associated with 1.1, 1.4 and 1.1 times increase in smoking risk, respectively.

Strengths and limitations

A potential limitation of this study is its single-center design, which may affect the generalizability of the findings. While the results provide important insights into a specific and underserved population, caution should be exercised in extending the findings to other contexts. Variability in cultural norms, healthcare access, and treatment settings may influence the observed relationships. Future studies employing multicenter or cross-cultural designs are recommended to enhance external validity. The research was planned cross-sectionally, the cause-and-effect relationship was examined at the same time, so the power to determine the cause-and-effect relationship is low. The answers given to the questions in the questionnaire are limited to the accuracy of the answers given by the participants. Since the study is cross-sectional, it does not give the direction of the cause-and-effect relationship. To address the limitations of current study, future research can be designed using cohort or case-control studies. The COVID-19 pandemic has had profound effects on public health research, including data collection for this study. It might have affected the participation rates due to restricted mobility, heightened psychological distress, or limited access to services. Additionally, the pandemic context may have influenced respondents’ mental health and social support experiences, potentially introducing bias into self-reported measures. These factors should be considered when interpreting the findings.In our study, the relationship between the frequency of smoking in the study group and socio-demographic and economic factors, daily habits, health status, marital adjustment and social support characteristics is examined. In order to determine the effect of marital and social support characteristics on smoking in women, scales with validity and reliability studies were used. The fact that the sample group consisted of women whose spouses had AUD/SUD is another distinctive feature of our study, as this population remains underrepresented in existing literature despite experiencing elevated psychosocial burdens such as caregiver stress, relational instability, and social stigma.

Interpretation of results with literature findings

In our study, smoking prevalence was notably elevated among women whose husbands used substances than in women whose husbands used alcohol. It is known that SUD is associated with more diverse and complex problems such as legal problems compared to alcohol use. Studies have reported that personality disorders are frequently diagnosed in people with SUD and the rate of unemployment is significantly higher in substance users compared to alcohol users [34, 35]. It is thought that all these problems affect the spouses and family relationships of substance abusers more. The fact that the majority of the participants needed mental support and expressed themselves as unhappy supports this notion.

In our study, the risk of smoking was found to be higher in university graduates. According to WHO [36], the prevalence of smoking among women in countries with low socioeconomic status is 2.8%, while this rate is 19.4% in countries with high socioeconomic status. In a study conducted in our country, it was found that smoking prevalence was lowest among illiterate adults and highest among those with high school education and above [37]. The results of our study are in parallel with the literature. Higher education emerges as a risk factor in women’s smoking [38]. As the level of education increases, women’s status in the society rise; their welfare, and their influence over their own lives increase, and they are able to make their own decisions and plan their lives. Women having more educational opportunities, economic independence and earning a regular income facilitate the availability of cigarettes [39]. It is thought that smoking is seen as a symbol of independence and economic freedom among women with high levels of education [40].

In our study, an increased likelihood of smoking was observed in women without a history of chronic disease than in women with a history of disease. One of the reasons for the higher risk of smoking among those without chronic diseases may be the level of awareness of individuals about their chronic diseases. For example, in a study conducted with 4500 people, it was observed that smokers were less likely to be aware that they had hypertension and to receive treatment compared to people who had never smoked or quit smoking [41]. Another explanation can be based on the health belief model. This model predicts an increase in preventive health behaviors when a chronic disease is diagnosed. Accordingly, when faced with a health risk such as chronic disease, motivation for non-smoking behavior may increase as an emotional response [42, 43]. Research results showing that people with chronic diseases have higher motivation to quit smoking compared to people without chronic diseases support these data [44]. On the other hand, there are contradictory results indicating that women with chronic diseases exhibit higher rates of smoking compared to their healthier counterparts. Some studies show that the persistent smoking prevalence among women with chronic conditions, is driven by the stress and emotional burden associated with managing their health issues [45]. This finding contrasts with current research suggesting higher smoking rates among women without chronic diseases, which may be due to differing study populations, methodologies, and socio-cultural factors influencing smoking behavior. Besides, some studies may not account for the intensive medical interventions and smoking cessation support typically provided to chronically ill patients.

In our study, the risk of smoking was found to be higher in those who needed mental support. The self-medication hypothesis states that smoking is an attempt to self-medicate [46]. Tobacco use disorder is more common in schizophrenia, major depression, bipolar disorder, attention deficit disorder, anxiety disorder, panic disorder, traumatic stress disorder and alcohol substance use disorders than in the general population. In a study conducted with individuals facing alcohol use issues and their spouses, it was found that 32.1% of women who were spouses of people experiencing AUD had a history of psychiatric illness [18]. In another study conducted with the spouses of individuals struggling with AUD, it was reported that women with alcohol dependent spouses had lower self-esteem and self-neglect was higher than the other group. In the same study, it was found that women with alcohol dependent spouses had higher anxiety levels compared to others, the spouses of the people with AUD showed significantly more stress and depression symptoms, their satisfaction with life decreased and they were more hopeless about looking to the future [47]. It is seen that women with spouses struggling with AUD experience mental distress more frequently. In a study conducted with people who applied to a smoking cessation outpatient clinic, impulsivity, type D personality, depression, and anxiety were reported as predictors of smoking [48]. These results suggest that mental problems are a risk factor for smoking in women. This is particularly relevant in cultures as it is in Turkish culture [49], where mental health issues are frequently stigmatized, and individuals might resort to smoking as a socially acceptable coping mechanism, which is in line with the health theory of coping [21].

Another factor affecting women’s smoking is hobby status. In our study, smoking was found to be higher in women who did not have a hobby than in women who had a hobby. A person’s evaluation of leisure time with physical activity, having a hobby such as painting, handicraft, or playing a musical instrument is a protective factor in SUD treatment and recovery process [50]. It is seen that the results of the study support these data. It is stated that physical activity is important in the prevention and treatment of nicotine, AUD/SUD [51]. In this context, in the prevention and treatment process of smoking, AUD/SUD, changing the individuals’ old lifestyle, improving the existing activity areas, physical activity that will keep the individuals busy in daily life, efforts to relax and reduce stress with activities such as breathing exercises and yoga, and physical, social and intellectual activities that will increase life satisfaction are very important.

The employment status of women with spouses experiencing AUD/SUD does not appear to exert a significant influence on their smoking behavior. This result is in line with Oshio (2018), which identified no substantial correlation between employment status and smoking behavior among women, attributing this lack of significant correlation to socio-cultural factors that may mitigate the impact of employment on smoking behavior [52]. Similarly, the type of marriage and the smoking status of the partner do not exert a significant influence on the smoking behavior of women with spouses experiencing alcohol/drug use disorder. Research elucidated that the correlation in smoking behavior between spouses is primarily attributable to individual habits rather than marital status per se [53, 54]. These findings suggest that the interpersonal dynamics and individual behaviors within the marriage are more consequential in shaping smoking habits than the type of marital union. The relationship between women’s smoking and social support levels was examined and the risk of smoking was found to higher in women with low levels of perceived social support. It was found that the risk of smoking varied according to the source of social support. Smoking was found to be significantly higher in women with low perceived social support from family. The results of the study are in parallel with the literature data [55, 56] showing that the perceived social support score is higher in non-smokers. In Yalcin and Unal’s study [57], family and social support were found to be effective in smoking cessation. These results suggest that both the absence of social support may be a risk factor for smoking and the presence of social support may have a positive effect on smoking cessation.

In our study, the effect of marital adjustment on women’s smoking was researched and the risk of smoking was found to be higher in women with a low level of marital adjustment. In studies examining the predictors of women’s health behaviors such as smoking status during pregnancy, a positive relationship was found between marital adjustment and healthy behaviors [58, 59]. These studies show that marital adjustment is not only an effective factor for smoking, but also effective in the process of smoking cessation. In our study, the rate of smoking among women who characterized themselves as “unhappy” in their marriages was found to be higher than those who were happy. In a study investigating the smoking characteristics of women living in slums, it was reported that smoking behavior increased in women who were victims of violence, women who did not have children and divorced women [60]. It is seen that problems between spouses, domestic violence and marital satisfaction are factors affecting smoking behavior in women. These results suggest that smoking is used as a coping method for problems related to marital life and that smoking may be a result of low marital adjustment rather than a factor affecting marital adjustment, which can also be grounded on the health theory of coping. Marital discord and domestic stress are significant contributors to smoking. Cultural norms around marriage and family life play a crucial role in this context.

When women’s marital adjustment and perceived social support levels are examined in terms of psychological resilience, which is an important concept, a new explanation can be brought to the relationship between these variables and smoking risk [61]. Psychological resilience is seen as a process of adaptation, recovery and coping with difficulties against important stress sources such as familial and relational problems. In the sub-dimensions of psychological resilience measurements, it is seen that the components related to perceived social support have an important place. Depending on the perceived social support of the person, psychological resilience and the ability to cope with stressful situations vary. Another sub-component of psychological resilience is the happiness felt within the family. This factor, which is also considered in the measurement of marital adjustment, plays a decisive role in the differences between individuals’ coping and recovery skills and whether they will use smoking as a coping method [62].

The pandemic period posed several challenges and had notable implications. The pandemic significantly increased stress and mental health problems globally. For women with spouses experiencing SUD/AUD, the compounded stress of the pandemic likely exacerbated smoking behaviors as a coping mechanism. The data collected during this period might reflect heightened levels of psychological distress, which underscores the need for robust mental health support systems. Secondly, the pandemic disrupted access to healthcare and support services, making it difficult for participants to receive mental health support or engage in preventive health behaviors. These changes could have amplified the risk factors identified in the study, such as low marital adjustment and lack of hobbies.

Conclusion and recommendations

This study was conducted to determine smoking in women whose husbands have AUD/SUD and to evaluate its relationship with social support characteristics and marital adjustment. Two out of every three women were found to be smokers. The high rate of smoking in this population indicates the necessity of protective, preventive and therapeutic programs in the related field. Women whose husbands experience SUD, who had a high level of education, who did not have chronic diseases, who needed mental support, who did not have a hobby, who perceived low social support, and who had incompatible marriages had a higher smoking frequency in the formation of tobacco use disorder. As a disadvantaged group, it is important to strengthen the social support and psychological resilience elements of women who are the spouses of people with AUD/SUD; to try to increase their marital adjustment through marriage and family counseling; and to make their coping skills healthy by ensuring that they develop hobbies.

In practical terms, these findings suggest that women married to substance users are more than three times as likely to smoke themselves, highlighting a substantial public health concern that warrants targeted intervention. The need for mental support and lack of hobbies underscore the importance of addressing mental health and promoting engaging activities to mitigate smoking risk. Moreover, the strong influence of low social support and marital incompatibility on smoking behavior indicates the critical need for social and relational interventions.

These results underscore the importance of comprehensive support systems for spouses of people experiencing AUD/SUD, addressing not only substance use but also mental health, social support, and relationship quality. Health practitioners in primary care settings, addiction treatment centers, and community mental health services working with women whose spouses have AUD/SUD and smoke should adopt a holistic and integrated care approach. This includes tailored smoking cessation programs incorporating behavioral therapies, stress management, and support groups, ideally coordinated by public health departments and specialized addiction services. Enhancing social support through peer networks, family involvement, and community resources (e.g., local NGOs, municipal family support units) is crucial. Regular screening and treatment for mental health issues, facilitated by psychiatric services, along with individual and couples counseling, offered through family counseling centers and clinical psychologists, can improve marital adjustment. Educational programs on health risks and AUD/SUD, developed by public health agencies in collaboration with universities and disseminated through local health authorities, coupled with policy advocacy by ministries of health and social policy for better support services, are also essential. These strategies collectively aim to address smoking habits, improve marital satisfaction, and enhance overall well-being for these women.

Authors’ contributions

GA, HH and GY designed the study, GA prepared the data, GA and GY analyzed the data, GA, GY, HH and DA interpreted the data. GA, HH, GY and DA wrote the paper, with critical revisions from HH and GY. All authors have read and approved the final version of this paper.

Funding

The authors received no financial support from any funding agency, commercial entity, or not-for-profit organization for the research, authorship and/or publication of this article.

Data availability

The datasets used and/or analyzed during the current study available from the corresponding author on reasonable request.

Declarations

Ethics approval and consent to participate

The study was approved by Ege University Medical Research Ethics Committee on 27th September, 2019. We confirm that the methods were performed under the relevant regulations and guidelines. We confirm that informed consent was obtained from all subjects, underscoring the voluntary nature of their involvement. Ethical considerations were meticulously addressed in this study. Comprehensive measures were implemented to ensure the confidentiality of participants and the security of their data. All personal identifiers were anonymized, and data was securely stored in encrypted databases, accessible only to authorized personnel. Participants received full information about the study’s purpose, data usage, and their right to withdraw at any time. These protocols were established in strict adherence to the principles outlined in the Declaration of Helsinki, maintaining the highest standards of ethical research practice and ensuring the protection and respect of all individuals involved.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.