Towards the use of mixed methods inquiry as best practice in health outcomes research

Antoine Regnault
Tom Willgoss

Skye Barbic

International Society for Quality of Life Research (ISOQOL) Mixed Methods Special Interest Group (SIG)

Towards the use of mixed methods inquiry as best practice in health outcomes research
10.1186/s41687-018-0043-8C O M M E N T A R Y Open Access
Mixed methods research (MMR) has found an increased interest in the field of health outcomes research. Consideration for both qualitative and quantitative perspectives has become key to contextualising patient experiences in a clinically meaningful measurement framework. The purpose of this paper is to outline a process for incorporating MMR in health outcomes research to guide stakeholders in their understanding of the essence of mixed methods inquiry. In addition, this paper will outline the benefits and challenges of MMR and describe the types of support needed for designing and conducting robust MMR measurement studies. MMR involves the application of a well-defined and pre-specified research design that articulates purposely and prospectively, qualitative and quantitative components to generate an integrated set of evidence addressing a single research question. Various methodological design options are possible depending on the research question. MMR designs allow a research question to be studied thoroughly from different perspectives. When applied, it allows the strengths of one approach to complement the restrictions of another. Among other applications, MMR can be used to enhance the creation of conceptual models and development of new instruments, to interpret the meaningfulness of outcomes in a clinical study from the patient perspective, and inform health care policy. Robust MMR requires research teams with experience in both qualitative and quantitative research. Moreover, a thorough understanding of the underlying principles of MMR is recommended at the point of study conception all the way through to implementation and knowledge dissemination. The framework outlined in this paper is designed to encourage health outcomes researchers to apply MMR to their research and to facilitate innovative, patient-centred methodological solutions to address the complex challenges of the field.

Background "We need a moral and methodological community that honors and celebrates paradigm and methodological diversity." Denzin, [1]; (pp.425).

Mixed methods research (MMR) has been established for more than 50 years as a methodological approach in the social and behavioural sciences and is now well accepted and commonly used in health sciences [2][3][4]. In line with the call to "measure what matters" to patients, patient reported outcomes are increasingly being used in clinical care and research. However, a recent review of studies documenting the development of patient-reported outcomes (PRO) measures highlights that only 11% of PROs have been developed by actually asking patients which outcomes are important to them [5]. This highlights a clear application for MMR to combining qualitative and quantitative methods in health research to ensure a focus on patient-identified priorities, scientific rigour, and improved patient outcomes.

In 2012, a special section of Quality of Life Research was dedicated to applied MMR [6]. In this issue, MMR was described as an approach to inform the content validity of PROs within the early development phase. The Food and Drug Administration (FDA) also outlined a clear role for MMR in their roadmap to patient focused measurement [7]. Shortly after, a Special Interest Group (SIG) was created within the International Society for Quality of Life Research (ISOQOL) to promote the use of MMR and encourage health outcomes researchers to embrace the MMR paradigm. As a SIG, we believe that there is a need for guiding principles for researchers who wish to undertake MMR. With this position paper, we aim to provide a framework for MMR in health outcomes by outlining the characteristics of this methodology, what can be expected and where caution should be exercised.

Defining features of mixed methods research

The application of the MMR paradigm in the health outcomes field can be rooted in the widely accepted definition by Tashakkori and Creswell: "Mixed Methods Research is a research in which the investigator collects and analyses data, integrates the findings, and draws inferences using both qualitative and quantitative approaches or methods in a single study or program of inquiry" [8] (pp.2).

In the spirit of pragmatism which underlies this methodology, we assert that utilizing MMR in the health outcomes field should not be limited to the application of a closed list of possible methodological options, but should be viewed as a framework characterized by three key defining features described in Table 1.

In this framework, not only should both qualitative and quantitative strands be used by the researcher, but they should be complemented in a relevant research design that is set a priori. They may address distinct, specific research questions but they contribute to the same overall end purpose of the MMR. Once the overall purpose, and the specific research questions of the qualitative and quantitative strands, are well-defined and procedures are outlined, a clear plan for interaction between the qualitative and quantitative research components is needed. This point relates to the notion of meta-inference that requires qualitative and quantitative evidence not be considered independently, but interpreted together as a single body of evidence [3]. Importantly, the importance of the specification relates to the research design, and especially the articulation of the qualitative and quantitative strands, but it obviously does not necessary apply within the research strands, as, in many instances, in particular for qualitative research, a full prespecification may not be appropriate, the research being of exploratory nature.

The characterization of MMR is driven neither by the data collection process, nor by the analysis technique. In MMR, it is not necessary that the qualitative and quantitative streams involve data collected with the same respondents. A welldesigned MMR study may combine qualitative and quantitative data from different samples of individuals to address a single research question, combining rigorous qualitative and quantitative evidence. Conversely, the collection of qualitative and quantitative data for the same individuals does not necessarily allow for a proper MMR solution as it may be done to address different research questions or without considering both data sets in an integrated approach.

Many options are available to the health outcomes researcher looking to utilize MMR, depending on the research question and design. We assert that MMR should not be restricted to any specific research design or methodology, but rather the design that is best suited to answer the research question posed. The articulation of the qualitative and quantitative elements can be performed in various designs that are well described in the methodological literature (e.g. convergent, or parallel or concurrent designs; sequential designs; embedded designs) [4]. The choice of the appropriate design and analysis technique (qualitative and quantitative) remains the responsibility of the researcher who should be guided by the principles outlined above.

Benefits and challenges of mixed methods research

Benefits MMR allows a research question to be studied from different perspectives. For example, one can combine the rich, subjective insights on complex realities from qualitative inquiry, with the standardized, generalizable data generated through quantitative research. When applied, MMR allows respective strengths and weaknesses of each approach to complement each other.

Since its conception in 2015, the Mixed Methods SIG of ISOQOL has identified and discussed many different applications of MMR in the health outcomes field: exploration of patient experiences to support the development of conceptual models with group concept mapping [9][10][11]; development of new clinical outcome assessment instruments with integrated qualitative and early quantitative analyses with Rasch model [12][13][14][15]; quantitatization of qualitative data to support conceptual saturation analyses [16,17]; use of qualitative information to support the interpretation of quantitative patient-reported outcomes results [18,19], to name but a few.

These examples show that MMR can help us to address common questions in the health outcomes field. This is typified by the inductive and iterative process characteristic of the development of new PROs. It also allows for flexibility and the ability to make the most of small samples. MMR enables a pragmatic path forward to conduct health outcomes measurement research in rare disease populations [20] or populations that are often difficult to recruit for research purposes (e.g., paediatrics, acute mental health, palliative). In a clinical research context, the versatility of MMR makes it a method of choice for hypothesis generation on PRO endpoints, especially in phase II trials. Finally, a critical strength of MMR approaches is that they typically capitalize on data reflecting individual lived experiences (in the qualitative strand). This ensures that the results are considered from the patient-perspective. Incorporating the patient voice in MMR helps ensure that the research is focused on the needs and priorities of patients. Moreover, MMR can facilitate the involvement of other key stakeholders, such as partners, family members, and/or other knowledge users, in the process of developing the research question(s) and outlining the research designs. In this context, it appears clearly that MMR is a strong option to leverage effective patient engagement and support ongoing research focused on patient-identified priorities and the improvement of patient outcomes [21].

Challenges

Despite some clear benefits, the application of MMR in the health outcomes research does not come without challenges. One major hurdle is that MMR is demanding in terms of methodological skillsets. MMR requires a team of researchers who are experienced in both qualitative and quantitative research, and in MMR designs. Indeed, as with traditional qualitative or quantitative methodologies, best practices should be applied rigorously across the multiple methods, but also in the way the quantitative and qualitative strands are articulated. A particularly critical issue in this context is that of meta-inference, in which the qualitative and quantitative strands connect. Metainference should be carefully specified, and researchers should be aware of the challenges of interpreting conflicting results.

The application of MMR can also raise practical considerations, particularly as the integration of both qualitative and quantitative data can require additional resources and time. However, it should be noted that this additional burden can often be offset against the potential benefits of MMR, particularly where multiple insights support the investigation of complex research questions or small populations.

Finally, we acknowledge that some theoretical debate still exists on how -or even whether -quantitative and qualitative paradigms can be mixed, a debate typified by the 'paradigm wars' of the second half of the twentieth century [1]. Such challenges stem from differences in the underlying ontological and epistemological positions of positivism (that a single objective reality exists) and constructivism (that reality is a subjective construct and therefore multiple realities exist). Even though the MMR paradigm goes beyond simply mixing the quantitative and qualitative paradigms and builds a third path, some purists continue to question this third paradigm, considering the very nature of the qualitative and quantitative paradigms irreconcilable. However, as Maxwell and Mittapalli argue [22], there is an alternative position to positivism and constructivismcritical realism. Critical realists deny that we have any objective or certain knowledge of the world, and accept the possibility of alternative valid accounts of any phenomenon. They argue that all theories about the world are grounded in a particular perspective and worldview, and all knowledge is partial, incomplete, and fallible. As such, critical realism provides a philosophical stance that is compatible with MMR in that it acknowledges the methodological characteristics of both qualitative and quantitative research, and can facilitate communication and cooperation between the two. Against the background of this ongoing debate, it is clear from the growing literature that the acceptance of MMR is increasing as the health outcomes research community continues to promote and celebrate methodological diversity.

Conclusions and recommended reading

Two conditions appear critical for the continued development of credible and robust MMR. First, health outcomes researchers have the potential to learn about the different MMR methodologies and outline how MMR can be used to more thoroughly answer health outcomes research questions. This may include increasing knowledge about the underlying philosophy and history of MMR, examples of MMR research designs and principles, and the pros and cons of this approach above a purely qualitative or quantitative inquiry. To support this journey we provide a list of recommended texts which can form a starting point for the curious researcher.

Second, an open dialogue and collaboration between health outcome researchers with positivist or interpretivist leanings should be encouraged to prepare the ground for robust MMR. In this context, it will be possible to design health outcomes research studies in which the whole is greater than the sum of its parts and allow the research community to further the science through providing innovative solutions to our research challenges.

Abbreviations FDA: Food and Drug Administration; ISOQOL: International Society for Quality of Life Research; MMR: Mixed Methods Research; PRO: Patient-Reported Outcomes; SIG: Special Interest Group

Table 1
1Defining features of the mixed methods research framework 1. A specific research question is to be addressed using quantitative and qualitative components (data and/or methods)2. The quantitative and qualitative components are articulated
purposely and prospectively in a well-defined, pre-specified
research design

3. The response to the research questions is supported by an
integrated set of evidence generated from both the qualitative
and quantitative component of the research (meta-inference)

AcknowledgementsThis paper was reviewed and endorsed by the membership of the International Society for Quality of Life Research (ISOQOL) Mixed Methods Research Special Interest Group. As part of this review, insightful comments from Benoit Arnould, Sophie Cleanthous, Chinmay Deshpande, and Claudia Marcela Vélez were implemented. This paper was reviewed and endorsed by the International Society for Quality of Life Research (ISOQOL) Board of Directors as an ISOQOL publication and does not reflect an endorsement of the ISOQOL membership.Authors' contributions AR, TW and SB led the preparation of this manuscript on behalf of the International Society for Quality of Life Research (ISOQOL) Mixed Methods Research Special Interest Group (MMR SIG). AR and TW submitted the original idea to the MMR SIG. AR, TW and SB drafted the manuscript and coordinated the review by the MMR SIG membership and by the ISOQOL Board of Directors. All reviewed and approved the final version.Ethics approval and consent to participate NA Competing interests AR is an employee of Modus Outcomes. TW and SB declare that they have no conflict of interest.
Key: *Recommended reading for researchers interested in MMR. Key: *Recommended reading for researchers interested in MMR

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Handbook of mixed Methods in social behavioral research. A Tashakkori, C Teddlie, Thousand Oakc. Sage PublicationsTashakkori A, Teddlie C. Handbook of mixed Methods in social behavioral research. Thousand Oakc,CA: Sage Publications; 2003.*.

Foundations of mixed methods research. C Teddlie, A Tashakkori, Sage Publications *Thousand Oaks, CATeddlie, C., & Tashakkori, A. (2009). Foundations of mixed methods research. Thousand Oaks, CA: Sage Publications *.

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Developing Conceptual Model of the Role of Elders in the Wellbeing of Australian Indigenous Communities: Group Concept Mapping Study 23rd ISOQOL Annual conference. L Busija, G Nicholson, M Toombs, R Cinelli, C Easton, K Sanders, Busija L, Nicholson G, Toombs M, Cinelli R, Easton C, Sanders K, et al. Developing Conceptual Model of the Role of Elders in the Wellbeing of Australian Indigenous Communities: Group Concept Mapping Study 23rd ISOQOL Annual conference;

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The use of concept mapping in measurement development and evaluation: Application and future directions. S R Rosas, J W Ridings, Eval Program Plann. 60Rosas, S. R., & Ridings, J. W. (2017). The use of concept mapping in measurement development and evaluation: Application and future directions. Eval Program Plann, 60, 265-276.

Patient-Centered, Mixed Methods Approach to Identifying Relevant Concepts for Patient-Reported Outcome Measures and Facilitating Participant Engagement. 21st ISOQOL Annual Conference. T Willgoss, Novel, BerlinWillgoss T. A Novel, Patient-Centered, Mixed Methods Approach to Identifying Relevant Concepts for Patient-Reported Outcome Measures and Facilitating Participant Engagement. 21st ISOQOL Annual Conference; Berlin, Germany2014.

Development and testing of the Personal Recovery Outcome Measure (PROM) for people with mental illness: Application of Mixed methods. 23rd ISOQOL Annual conference. S Barbic, CopenhagenBarbic S. Development and testing of the Personal Recovery Outcome Measure (PROM) for people with mental illness: Application of Mixed methods. 23rd ISOQOL Annual conference; Copenhagen, Denmark2016.

The Pain Assessment for Lower Back Symptoms (PAL-S) and Impacts (PAL-I): A Case Example of the Application of Mixed-Methods in PRO Instrument Development. S I Blum, D M Bushnell, K P Mccarrier, M L Martin, S Cano, H Liedgens, 23rd ISOQOL Annual ConferenceBlum SI, Bushnell DM, McCarrier KP, Martin ML, Cano S, Liedgens H, et al. The Pain Assessment for Lower Back Symptoms (PAL-S) and Impacts (PAL-I): A Case Example of the Application of Mixed-Methods in PRO Instrument Development. 23rd ISOQOL Annual Conference;

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Patterns and socioeconomic influences of tobacco exposure in tobacco cultivating rural areas of Yunnan Province, China

Le Cai
Xinan Wu
Abhinav Goyal
Yuntao Han
Wenlong Cui
Xia Xiao
Jianhui He
Keying Zhao
Ying Song
Feng Jiao
Patterns and socioeconomic influences of tobacco exposure in tobacco cultivating rural areas of Yunnan Province, China
R E S E A R C H A R T I C L E Open Access
Background: This study describes the patterns and socioeconomic influences of tobacco use among adults in tobacco-cultivating regions of rural southwest China. Methods: A cross-sectional survey was conducted in 8681 adults aged ≥18 years in rural areas of Yunnan Province, China from 2010 to 2011. A standardized questionnaire was administered to obtain data about participants' demographic characteristics, individual socioeconomic status, ethnicity, self-reported smoking habits, and exposure to secondhand smoke (SHS). The socioeconomic predictors of current smoking, nicotine addiction, and SHS exposure were analyzed using multivariate logistic regression. Results: The prevalence rates of tobacco use were much higher in men compared with women (current smoking 68.5% vs. 1.3%; and nicotine dependence 85.2% vs. 72.7%). However, the rate of SHS exposure was higher in women compared with men (76.6% vs. 70.5%). Tobacco farmers had higher prevalence rates of current smoking, nicotine dependence, and SHS exposure compared with participants not engaged in tobacco farming (P<0.01). Most tobacco users (84.5%) reported initiating smoking during adolescence. A total of 81.1% of smokers smoked in public places, and 77.6% smoked in workplaces. Individuals belonging to an ethnic minority had a lower probability of SHS exposure and nicotine dependence. Individual educational level was found to be inversely associated with the prevalence of current smoking, exposure to SHS, and nicotine dependence. Higher annual household income was associated with a greater risk of nicotine dependence. Conclusions: This study suggests that tobacco control efforts in rural southwest China must be tailored to address tobacco-cultivating status and socioeconomic factors.

Background

The health effects of smoking and exposure to secondhand smoke (SHS) are major global public health issues. The World Health Organization reported that tobacco use in the 20th century resulted in 100 million deaths worldwide [1], and this number is projected to increase to 1 billion deaths in the 21 st century. China is the most important battleground in the struggle against tobacco use globally, and it is both the world's largest producer and consumer of tobacco products. China is home to an estimated 301 million current smokers in 2010, and the rising trends in tobacco consumption are alarming [2]. The 2002 national survey reported that 51.9% of nonsmokers in China were regularly exposed to SHS [3]. Correspondingly, China also experiences a high incidence of tobacco-related diseases [4]. A previous Chinese study indicates that a total of 673,000 deaths in Chinese adults were attributable to smoking in 2005 [5], with cancer, cardiovascular disease, and respiratory disease accounting for most of these deaths. Smoking is highly prevalent, and its impact on premature death has become a major concern in China.

Only through understanding the major factors that contribute to smoking behavior can we hope to design and execute effective tobacco control policies. There is growing evidence that patterns of smoking are related to age, sex, socioeconomic status (SES), and health risk behavior [6][7][8]. People who are less educated, who earn less, and who are unemployed show higher prevalence rates of smoking in developed countries. An inverse relationship between educational attainment and the risks of environmental tobacco exposure was also identified in previous Chinese and Korean studies [9,10]. In China, several studies have examined the relationship between smoking and SES variables in the general adult Chinese population [10][11][12], and show an inverse association between education and smoking. However, little data are available concerning the associations between SES variables and tobacco use in the Chinese tobacco-cultivating adult population. It is crucial that we understand the socioeconomic factors related to tobacco use and identify target populations for tobacco control. Furthermore, the epidemiological studies conducted in China have focused mostly on urban areas or national-level data, but the literature is still sparse in tobacco-cultivating rural areas, where the rate of tobacco consumption is the highest.

The aim of this study is to describe the patterns and socioeconomic influences of tobacco use among southwest China's tobacco-cultivating rural adult population from 2010 to 2011.

Methods

Study region

This study used a community-based cross-sectional survey and was conducted in two tobacco-cultivating rural areas of Yunnan Province in southwest China. In 2010, Yunnan Province had 129 official counties and a total population of 45.9 million people. It is a relatively undeveloped province, and is a production and consumption hub for tobacco products. Roughly 70% of Yunnan Province's annual tax revenue is collected from the tobacco industry, and tobacco is cultivated in 45 of the province's counties [10]. Yunnan also has the country's largest concentration of ethnic minorities, with 25 of China's 56 state-recognized ethnicities living in the region. For decades, the regional government of Yunnan has depended on the economic engine of tobacco. As a result, the strong enforcement of existing tobacco control laws is not fully supported by the Yunnan government. The progress on tobacco control is not moving quickly in this region. More recently, Yunnan government implemented the anti-tobacco policy to prohibit smoking in public institutions including hospitals, healthcare centers and schools.

Sampling

Multi-stage stratified random sampling was used to select the study sample. In the first stage, all of Yunnan Provinces' tobaccos cultivating counties were classified into two groups according to wealth distribution (per capita Gross Domestic Product): economically advantaged (<$600) and economically disadvantaged (≥$600) based on the 2010 Yunnan Statistical Yearbook [13]. In order to guarantee the representativeness of each group, one county was randomly selected from each of these two economic groups. In the second stage, all township districts were selected for study in the two chosen counties, for a total of 21 townships. In the third stage, three villages were chosen by probability proportional to size (PPS) from each of the 21 townships. In the final stage, in each selected village, we first obtained a list of names of individuals aged ≥ 18 years from the village committee, and then simple random sampling was done with random number tables to select the individuals from this village.

Data collection and measurement

Ten 5th-year medical students and twenty master degree students from Kunming Medical University were selected and extensively trained as interviewers for data collection. A workshop was held before the fieldwork to teach interviewers how to administer the screening questionnaire, and how to take blood pressure and anthropometric measurements. Each participant was given a full explanation of the research purpose and invited to participate; signed informed consent; and was personally interviewed by one of the interviewers using a pre-tested structured questionnaire. The questionnaire asked for demographic characteristics, individual SES, ethnicity, household income, educational level, lifestyle factors such as alcohol consumption, self-reported smoking habits, exposure to SHS at home or work, and tobacco use-related health status.

Ethical approval

This study was approved by the Ethics Committee of Kunming Medical University.

Definitions

Current smoker was defined as a person who currently smoked any kind of tobacco product on a daily basis at the time of the survey. Exposure to SHS was defined as non-smokers who reported exposure to environmental tobacco smoke at home or at work for a minimum of 15 minutes at least one day per week. The location of exposure to SHS was defined as in the past seven days, the locations where others have smoked in front of a current smoker. Current drinker was defined as a person who drank alcohol regularly on 12 or more days during the past 12 months. Self-reported current smokers were assessed for nicotine dependence using six questions from the Fagerstrom Test for Nicotine Dependence (FTND) [14]. The FTND has 6 items with an overall score ranging between 0-10. Very high dependence was defined as an FTND score ranging between 8-10; high dependence, a score between 6-7; medium dependence, a score equal to 5; low dependence, a score between 3-4; and very low dependence, a score between 0-2.

Statistical analysis

Descriptive analysis techniques, chi-squared test, and multivariate logistic regression were used in this study. Yearly household income was classified into three categories: low (<$150 USD), medium ($150-600 USD), and high (>$600 USD). Categorical variables were presented as counts and percentages, and 95% confidence intervals (95% CI) for percentages were calculated according to the method described by Newcombe [15]. The sampling weights were calculated based on data from the year 2000 Yunnan Provincial Population Census and our sampling scheme. The prevalence of current smoking, nicotine dependence and exposure to SHS, however, were estimated based on weighted proportions. Chisquared test was used to determine the percentage differences between men and women. Logistic regression was used to analyze the association between individual SES variables and the weighted prevalence of current smoking, intensity of smoking, exposure to SHS, and nicotine dependence. Associations were expressed as odds ratios and 95% CI. All statistical significance decisions were based on a two-tailed P value of <0.05. Due to large differences in smoking behavior between men and women, interactions were tested to determine whether SES variables varied by sex. All data analyses were conducted with R2.9.1 software [14].

Results

A total of 8,800 individuals aged ≥18 years were invited to participate in this study. Of these, 8,681 agreed to participate (response rate = 98.6%).

As shown in Table 1, the study population included 4,068 males and 4,631 females, 22.3% of which belonged to an ethnic minority, and 77.7% of which were Han Chinese. The proportion of participants who engaged in tobacco cultivation was 28.1%. Male participants had higher educational level than female participants (P<0.05). Table 2 describes weighted prevalence of current smokers, nicotine dependence, and exposure to SHS by age, sex and tobacco-cultivating status among southwest China's rural adult population. The overall prevalence rates of current smokers and exposure to SHS were 33.7% and 74.2% respectively, and the rate of nicotine dependence among smokers was 84.8%. In general, men reported much higher rates of smoking and nicotine dependence than women (P<0.01), whereas women reported higher rate of exposure to SHS than men (P<0.05). The highest rates of current smokers, exposure to SHS, and nicotine dependence were found among individuals aged 35-44 years. Individuals who cultivated tobacco had higher prevalence rates of current smoking, exposure to SHS, and nicotine dependence than nontobacco cultivating people (P<0.01). Table 3 displays patterns of tobacco exposure among study participants. Filtered cigarette smoking was the most popular form of smoking tobacco, comprising 66.5% of all forms of tobacco consumed, followed by Hookah / Water pipe (57.7%). However, there were important differences in these findings by sex. Filtered cigarette smoking was the most popular form of smoking tobacco for men, whereas hookah / Water pipe was the most popular form of smoking tobacco for women. Age of smoking initiation occurred mostly during adolescence (84.5%). 51.9% of current smokers reported daily smoking of more than 10 cigarettes. A total of 6.8% of current smokers were highly nicotine addicted. In the 12 months before the survey, only 13.2% of smokers tried at least one attempt to quit smoking. In the past seven days, 81.1% of smokers smoked in public places  We found no association between any SES indicators and the intensity of smoking. Table 4 shows the results of logistic regression for prevalence of current smokers, nicotine dependence, and exposure to SHS after adjusting for possible confounders. After adjusting for age, sex, tobacco cultivation, drinking status, and type of county, as well as further adjusting for other measures of SES, individuals who belong to an ethnic minority had a lower probability of nicotine dependence and of being exposed to SHS. Individuals with higher levels of education had a lower probability of current smoking, exposure to SHS, and nicotine dependence. Furthermore, higher yearly household incomes were found to be associated with a higher risk of nicotine dependence, but not with current smoking or SHS exposure. Individuals who cultivated tobacco had a higher probability of current smoking, exposure to SHS, and nicotine dependence. Although we tested for possible interactions, there were no significant interactions between sex and SES variables.

Discussion

The findings indicate a high prevalence of smoking, and a high prevalence of exposure to SHS among non-smokers. There was also a high rate of SHS exposure among current smokers in public places, and a low rate of attempting to quit smoking among current smokers in rural southwest China. Individual SES was found to be independently associated with the prevalence of current smoking, exposure to SHS, and nicotine dependence.  It has been estimated that worldwide, men smoke more than women. Our finding is in concordance with other studies [16]. In this study, the prevalence of smoking among men was greater than the prevalence rate observed in 2010 China Global Adults Tobacco Survey (GATS, 56.1%) [17], other parts of rural China (66.8%) [10], adults from western countries [7,8], and other Asian and African people [18][19][20]. Smoking has been very prevalent in the Chinese tobacco cultivating rural male population. In contrast to the high prevalence of smoking, our study reported a low prevalence of smokers who have previously attempted to quit smoking (18.2%), a rate that was much lower than reported by the 2010 China GATS survey (33.1%), in other cities of China (25.3%) [21], and in other western countries (40%) [22]. These data indicate that rural communities are in need of robust smoking cessation programs.

Several previous Chinese studies indicate that most Chinese smokers initiate smoking during adolescence, and the prevalence of adolescent smoking has been increasing rapidly in China [23,24]. Our study is consistent with these prior studies, and demonstrates that over 80% of smokers start smoking during adolescence. These findings underscore an urgent need for tobacco control strategies in rural China for adolescents and young adults who are at high risk for becoming addicted to nicotine.

As shown in other Chinese studies, smoking cigarettes was the most popular form of tobacco use in rural southwest China [10,25]. Furthermore, we found that consuming tobacco through hookah / water pipes was also common in the tobacco-cultivating, ethnically diverse, rural communities. Our findings indicate that cultural forces exert a strong effect on smoking habits, as has been demonstrated in previous studies [26].

Our study showed a high rate of exposure to SHS among current smokers, particularly in public places. The rate of exposure to SHS in public places observed in this study (81.1%) is much higher than the China national survey results of 2002 (67.0%) [3], as well as results from another Chinese study (72.7%) [27], indicating public places have become the worst places for SHS exposure in rural southwest China. Furthermore, our study showed that exposure to SHS among current smokers in households mostly occurred in front of children and pregnant women. While smoking among women in the study region was at a much lower level compared with men, over 75% of women were exposed to SHS, and the rate of exposure to SHS among women was higher than among men, indicating exposure to SHS is a serious health problem for women. The impact of SHS exposure on children's and women's health requires urgent attention. Evidence has shown that the implementation of comprehensive smoke-free policies decreases the exposure to SHS and its associated health hazards in non-smokers [28]. These results suggest it is essential to strengthen people's awareness of tobacco hazards and to implement comprehensive smoke-free laws and legislations to protect people from SHS.

Our study found individuals who cultivated tobacco had higher prevalence rates of current smoking, exposure to SHS, and nicotine dependence than non-tobaccocultivating people. This is possibly due to tobacco farmers having easier access to tobacco products. These results suggest tobacco cultivating status is an important consideration when developing tobacco control policies in rural China.

Ethnic minorities had a lower risk for exposure to SHS and nicotine dependence in this study. Genetic heritability and shared environmental influences have been reported to be related to cigarette smoking in a previous study [29]. This finding suggests that ethnicity is an important determinant for tobacco use. Lower levels of education have been shown to be associated with higher risks of smoking, environmental tobacco exposure, nicotine dependence, and lower rates of quitting tobacco use, both in developed and developing countries [8,9,30]. In the present study, smoking, exposure to SHS, and nicotine dependence tended to be more prevalent in people who were less educated. Our result is in concordance with prior studies. Some previous Chinese studies also indicated an inverse association between education and smoking [2,11,12,18]. Our findings suggest community-based tobacco control efforts need to increase the knowledge related to harm of tobacco use among people with low levels of education.

While several western studies have demonstrated that people with lower incomes are more likely to consume tobacco [6][7][8][9], our study showed no association between individual income and smoking or exposure to SHS in the Chinese rural adults. However, it did show a positive relationship between individual income and nicotine dependence. A previous Chinese study reported that people with higher annual income were more likely to smoke than those with lower income [18]. The reasons for an inconsistent association between income and smoking rates in Chinese adult smokers are unknown.

A strength of our study is the large sample size and the high response rate (over 98%) in the community survey. A limitation of the study is that smoking was selfreported and exposure to SES was based on recall. The lack of validation of smoking status with nicotine testing may underestimate the prevalence of smoking.

Conclusion

In conclusion, smoking and exposure to SHS are very prevalent in rural southwest China. The results of this study suggest that future tobacco control efforts and policies should focus more on people who cultivate tobacco, who are less educated, and who belong to the Han majority.

past seven days, the conditions under which others have smoked in front of you Public spaces (schools, hospitals, etc.

Table 1
1Demographic characteristics of the study populationCharacteristics
(%)

Male
(n=4068)

Female
(n=4613)

All
(n=8681)

Age

18-34 years
1078 (26.5) 1099 (23.8) 2177 (25.1)

35-44 years
864 (21.2)
923 (20.0) 1787 (20.6)

45-54 years
702 (17.3)
850 (18.4) 1552 (17.9)

55-64 years
666 (16.4)
843 (18.3) 1509 (17.4)

≥65 years
758 (18.6)
898 (19.5) 1656 (19.1)

Tobacco cultivating

Yes
1267 (31.1) 1176 (25.5) 2443 (28.1)

No
2801 (68.9) 3437 (74.5) 6238 (71.9)

Ethnicity

Han
3226 (79.3) 3516 (76.2) 6742 (77.7)

Minorities
842 (20.7) 1097 (23.8) 1939 (22.3)

Level of education

Primary (grade 1-6) or lower 3402 (83.6)* 4107 (89.0)* 7509 (86.5)

Middle ((grade 7-9) or higher 666 (16.4)
506 (11.0) 1172 (13.5)

Level of yearly household income  †

Low
856 (21.0) 1096 (23.8) 1952 (22.5)

Medium
2285 (56.2) 2701 (58.6) 4986 (57.4)

High
927 (22.8)
816 (17.7) 1743 (20.1)

* P<0.05 from chi-squared test for difference between sexes.
 † Low income is < $150 USD; medium is $150-600 USD; and high income
is >$600.

Table 2
2Weighted prevalence of current smoking, nicotine dependence, and secondhand smoke (SHS) by age, sex and status of tobacco cultivationCharacteristics
Prevalence of
current smokers

Prevalence of nicotine
dependence among smokers

Prevalence of SHS
among non-smokers

Men
Women
All
Men
Women
All
Men
Women
All

%
(95% CI)

%
(95% CI)

%
(95% CI)

% of smokers
(95% CI)

% of smokers
(95% CI)

% of smokers
(95% CI)

% of non-smokers
(95% CI)

% of non-smokers
(95% CI)

% of non-smokers
(95% CI)

Age

18-34 years
63.3 (60.3-66.0)
0.5 (0.1-0.8)
31.3 (29.5-33.9)
82.0 (79.8-85.5)
48.8 (9.45-90.6)
82.3 (58.6-86.0)
70.8 (65.6-74.6)
76.9 (74.9-79.9)
74.7 (73.4-77.7)

35-44 years
76.7 (73.7-79.3)
0.9 (0.2-1.0)
37.5 (35.1-40.6)
86.1 (83.6-88.8)
74.6 (30.1-95.4)
87.0 (64.2-90.3)
73.0 (65.7-78.0)
80.1 (78.1-83.2)
78.7 (76.7-81.5)

45-54 years
74.0 (70.9-77.3)
1.0 (0.6-2.1)
34.4 (31.8-36.5)
88.1 (84.2-89.9)
89.3 (56.5-98.0)
87.8 (78.3-96.2)
70.2 (63.7-76.9)
81.3 (77.9-84.3)
80.1 (76.4-82.4)

55-64 years
70.1 (66.1-73.0)
1.1 (0.4-1.6)
31.0 (28.9-33.6)
84.9 (81.8-88.3)
85.4 (48.7-97.4)
85.2 (68.2-94.7)
68.8 (59.1-74.0)
77.3 (73.1-79.9)
75.4 (71.3-77.7)

≥65 years
59.0 (56.1-63.1)
1.6 (1.0-2.8)
28.4 (26.1-30.4)
83.8 (80.7-87.4)
58.7 (35.8-80.2)
83.5 (67.1-83.5)
67.2 (65.9-76.0)
64.1 (62.0-68.3)
65.3 (64.1-69.4)

Tobacco cultivating

Yes
78.0 (75.1-79.7)
1.7 (0.5-1.7)
43.0 (38.7-45.6)
89.1 (86.5-91.4)
89.2 (59.6-98.2)
89.0 (84.5-90.4)
82.3 (77.2-86.1)
86.0 (83.3-87.8)
85.1 (82.9-87.6)

No
63.9 (62.4-65.9)
0.7 (0.6-1.2)
28.9 (28.2-30.4)
82.7 (81.4-84.9)
67.1 (47.8-81.4)
82.8 (81.0-84.7)
66.2 (63.8-69.7)
72.1 (71.4-74.4)
70.6 (69.2-72.8)

All
68.5 (66.9-69.7)
1.3 (0.8-1.6)
33.7 (31.5-35.5)
85.2 (83.7-86.4)
72.7 (57.0-84.6)
84.8 (83.1-86.3)
70.5 (67.6-72.6)
76.6 (74.8-77.8)
74.2 (73.1-75.9)

Table 3
3Patterns of tobacco exposure among current smokers in rural areas of Yunnan province, ChinaVariables

Table 4
4Weighted Logistic regression coefficients for current smoking, nicotine dependence and exposure to secondhand smoke (SHS) by ethnicity and socioeconomic statusVariables
Current smokers
Nicotine dependence
SHS

(N=8681)
(N=8681)
(N=8681)

Adjusted odds ratio †
95% CI
Adjusted odds ratio †
95% CI
Adjusted odds ratio †
95% CI

Ethnicity (reference: Han)

Minorities
0.93
(0.79, 1.10)
0.79**
(0.69, 0.95)
0.84**
(0.74, 0.95)

Level of education (reference: primary (grade 1-6) or lower)

Middle (grade 7-9) or higher
0.63**
(0.51, 0.78)
0.56**
(0.46, 0.65)
0.51**
(0.43, 0.61)

Level of yearly household income (reference: Low)

Medium
1.08
(0.97, 1.20)
1.16*
(1.04, 1.31)
1.06
(0.93, 1.11)

High
1.05
(0.93, 1.18)
1.11*
(1.02, 1.19)
1.00
(0.90, 1.06)

Tobacco cultivating (reference: no)

Yes
3.18**
(2.77, 3.65)
2.42**
(2.12, 2.77)
1.35**
(1.17, 1.55)

http://www.biomedcentral.com/1471-2458/12/842
* P<0.05 from chi-squared test for difference between sexes, ** P<0.01 from chi-squared test for difference between sexes, † The current smoker used more than one form of smoking tobacco, † † The denominator is the number of current smokers living with children at home, † † † The denominator is the number of current smokers living with pregnant woman at home.
* p<0.05, ** p<0.01, † adjusted for age, sex, and alcohol drinking.
AcknowledgementsWe would like to thank Dr. Jia Shen from Emory University for her review and helpful comments regarding the manuscript. This publication isCompeting interestsThe authors declare that they have no conflicts of interest.Authors' contributions CL carried out the study and drafted and revised the manuscript. WX and HY participated in the design of the study. AG participated in the design of the study and helped to revise the manuscript. CW, XX, HJ, ZK, SY, and JF collected the data. All authors read and approved the final manuscript.Submit your next manuscript to BioMed
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Patterns and socioeconomic influences of tobacco exposure in tobacco cultivating rural areas of Yunnan Province, China. Cai, BMC Public Health. 12842Cite this article asCite this article as: Cai et al.: Patterns and socioeconomic influences of tobacco exposure in tobacco cultivating rural areas of Yunnan Province, China. BMC Public Health 2012 12:842.