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American Journal of Epidemiology Advance Access originally published online on November 6, 2007
American Journal of Epidemiology 2008 167(3):330-340; doi:10.1093/aje/kwm293
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American Journal of Epidemiology © The Author 2007. Published by the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oxfordjournals.org.

ORIGINAL CONTRIBUTIONS

Joint Effects of Tobacco Use and Body Mass on All-Cause Mortality in Mumbai, India: Results from a Population-based Cohort Study

Mangesh S. Pednekar1,2, Prakash C. Gupta1, James R. Hebert3 and Matti Hakama2

1 Healis-Sekhsaria Institute for Public Health, Belapur, India
2 Tampere School of Public Health, University of Tampere, Tampere, Finland
3 Department of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, Columbia, SC

Correspondence to Mangesh S. Pednekar, Healis-Sekhsaria Institute for Public Health, 601/B, Great Eastern Chambers, Plot No. 28, Sector 11, CBD Belapur, India (e-mail: pednekarmangesh{at}rediffmail.com, pcgupta{at}healis.org).

Received for publication June 11, 2007. Accepted for publication September 12, 2007.


   ABSTRACT
TOP
 ABSTRACT
INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 References
 
The joint effects of tobacco use and body mass on mortality have not been well characterized, although evidence regarding the effect of smoking on the association between body mass and mortality is accumulating. To study the joint effects of these important risk factors, the authors conducted a prospective cohort study of 148,173 men and women aged ≥35 years in Mumbai, India. Subjects were recruited during 1991–1997 and then followed for approximately 5–6 years (1997–2003). During 774,129 person-years of follow-up, 13,261 deaths were observed. Tobacco use increased the risk of death across different categories of body mass, with particularly high risks being observed in extreme body mass categories. Among men, obese smokers and obese never users of tobacco were at 56% and 34% increased risks of death, respectively, compared with overweight never users of tobacco. Similarly, at highest risk were extremely thin males who smoked bidis (relative risk = 3.45) or cigarettes (relative risk = 3.32). Body mass and all forms of tobacco use had independent as well as multiplicative joint effects on mortality risk. Tobacco use and undernutrition are serious problems in India. The current study indicates that obesity may emerge as a serious public health problem with which tobacco use may interact.

body mass index; India; mortality; obesity; thinness; smoking; tobacco; tobacco, smokeless

Abbreviations: BMI, body mass index


   INTRODUCTION
TOP
 ABSTRACT
 INTRODUCTION
MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 References
 
In developed countries, smoking and excess body weight (weight adjusted for height) are two of the most important risk factors for chronic disease and premature death (1–4). Both factors have strong behavioral determinants, but neither has been controlled adequately by population-based approaches to behavior change (5). Although the prevalence of smoking has declined modestly in some countries over the past 30 years, prevalences of overweight and obesity have risen steadily; additionally, there is evidence that these two trends are partly related (6).

In recent years, many prospective epidemiologic studies have evaluated the relation between mortality and body mass index (BMI; weight (kg)/height (m)2) (7–14). Findings vary as to whether the relation is best described as linear, J-shaped, or U-shaped; this inconsistency may be due to the confounding effects of smoking behavior and some serious illnesses that are associated with higher mortality and lower BMI (15, 16). Thus, a low BMI may either be reflective of a healthy lifestyle (i.e., balanced caloric intake and physical-activity energy expenditure) or be secondary to smoking or illness. Understanding the effects of BMI on mortality may require consideration of tobacco use and the potential effects of weight loss owing to preexisting illnesses (15, 16). Most investigators have either adjusted for tobacco use or stratified by tobacco use in assessing the association of mortality with BMI. However, to our knowledge, none of the large prospective studies have assessed the joint effects of tobacco use and BMI on mortality.

In India, public health attention has traditionally been focused on the problem of undernutrition (17). However, there is now evidence of a double burden of overnutrition as well as undernutrition (17–19). Tobacco use is a public health concern worldwide, as well as in India. However, patterns of tobacco use in India are quite different from those observed in other developed countries. In India, tobacco is used in various forms (20). For example, handmade cigarettes called bidis are more commonly smoked than regular cigarettes. Bidis are made by rolling a dried rectangular piece of temburni leaf (Diospyros melanoxylon) with 0.15–0.25 g of a sun-dried flake form of tobacco. In addition, use of smokeless tobacco, in a variety of forms, is widespread among both men and women (20). The most common form of smokeless tobacco used in Mumbai (formerly Bombay) is mishri, a black powder obtained by roasting and powdering tobacco, which is then applied to the gums using a finger. Another common form is betel quid, which is a combination of betel leaf, areca nut, slaked lime, tobacco, and other condiments; ingredients may be added according to individual preferences. Use of all forms of tobacco is associated with higher all-cause mortality in the Indian population (21–23). Previously, we reported that tobacco use (smoking and smokeless) is associated with low BMI in India (19, 24). The high prevalence of tobacco use in India and its association with low BMI raises important questions about the public health impact of tobacco use in India, a country which has a high prevalence of low BMI among adults. Thus, as part of the Mumbai Cohort Study, we conducted a detailed analysis of the joint effects of tobacco use and BMI on all-cause mortality.


   MATERIALS AND METHODS
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
RESULTS
 DISCUSSION
 References
 
Recruitment
Mumbai is a large, densely populated cosmopolitan city in southwestern India. It is divided into three parts: the main city, suburbs, and extended suburbs. The Mumbai Cohort Study was conducted in the main city of Mumbai, with mortality as the endpoint. A total of 148,173 persons aged ≥35 years were recruited during 1991–1997.

House-to-house interviews were conducted face-to-face using a structured questionnaire. Voters' lists were used as the sampling frame. These lists provided information on name, age, sex, and address for all persons aged ≥18 years and were grouped according to polling stations comprising 1,000–1,500 voters. We excluded polling stations that served upper-middle-class and upper-class housing complexes. Such complexes were not accessible to us because of security issues (i.e., they were essentially "gated communities"). The proportion of polling stations excluded varied from area to area. Some areas that were known to be affluent—for example, those containing only skyscraper apartment complexes—were excluded completely, whereas fewer than 10 percent of polling stations were excluded in others. The interviews were conducted by trained field investigators using handheld computers (electronic diaries). With the exception of very sick or bedridden persons, the field investigators were not allowed to exclude any building, household, or individual.

The study satisfied all of the criteria regarding the ethical treatment of human subjects, especially those formulated by the Indian Council of Medical Research. Details regarding the recruitment procedures have been published previously (25).

Follow-up
Active house-to-house follow-up was conducted approximately 5–6 years after the initial survey. The field investigators were instructed to revisit each person. If the person was alive and available, a face-to-face reinterview was conducted. If the person was reported to have died, the date and place of death were recorded as accurately as feasible. Permanent migration from the study area was considered withdrawal from the study, and the date of migration was noted. The reinterviews were conducted during 1997–2003. The results of follow-up have been described elsewhere (21, 26).

Data sources
The baseline survey included the following two components: 1) anthropometric measurements taken using a bathroom scale that was calibrated to the nearest kilogram and a measuring tape that was calibrated to the nearest centimeter and 2) interviewer administration of a structured questionnaire. For this study, data regarding age, sex, education (a proxy for socioeconomic status), religion, mother tongue, height, and weight, as well as details on tobacco use, were abstracted from the baseline data.

Statistical analysis
Person-years of follow-up were calculated using the date of recruitment and the date of endpoint ascertainment (defined as the date of death, reinterview, migration, or censoring). Additional details regarding the estimation of person-years of follow-up, anthropometric measurements, and information collected from the structured questionnaire have been published elsewhere (19, 21, 24–26).

Age-adjusted death rates for men and women were calculated using the overall 5-year age-specific person-years as weights (i.e., the direct method). Multivariate analysis was performed using Cox proportional hazards regression modeling (27). The response variable, death, was coded as a dichotomous variable (yes/no), and the time to event (or censoring) was regarded as a continuous variable. BMI categories were defined by using the cutoff points of 18.5 and 25.0 for underweight and overweight, respectively. The underweight category was further subdivided into three groups: extremely thin (BMI < 16.0), very thin (BMI 16.0–<17.0), and thin (BMI 17.0–<18.5); similarly, the overweight category was further subdivided into two categories: overweight (BMI 25.0–<30.0) and obese (BMI ≥ 30.0). Details regarding the BMI distribution in the Mumbai cohort have been published elsewhere (19, 24). Respondents were broadly classified as having never used tobacco, using smokeless tobacco only, being a smoker only, or being a mixed user of tobacco (both smokeless and smoking). Smokers and mixed users were grouped together and are referred to as "smokers" throughout this paper; furthermore, smokers were subdivided into those who smoked cigarettes only and those who smoked bidis (which included combined smokers of both cigarettes and bidis). Information regarding the frequency of smokeless tobacco use was subdivided into three groups: 1–5 times per day, 6–10 times per day, and >10 times per day. Similarly, the frequency of smoking was further subdivided into four groups: 1–5 times per day, 6–10 times per day, 11–15 times per day, and >15 times per day. Duration of tobacco use was subdivided into ≤15 years and >15 years for both smokeless tobacco users and smokers.

Age, education, religion, mother tongue, tobacco use, and BMI were fitted as independent variables in the final Cox proportional hazards model (27). Adjusted relative risks and 95 percent confidence intervals were estimated for the joint effects of tobacco use and BMI on mortality, stratified by gender. In addition, to study the multiplicative effect of tobacco use and BMI on mortality, we calculated expected relative risks, by multiplying individual relative risks for different categories of tobacco use with those for different categories of BMI.


   RESULTS
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
DISCUSSION
 References
 
Of the 148,173 cohort members (59,515 women and 88,658 men), 7,265 were not traceable (table 1). The most common reason for nontraceability among these persons was demolition of their residential building (n = 6,452) for the purpose of redevelopment. Among the remaining 140,908 persons, 25,777 subjects, although alive, had left the study area; thus, 115,131 subjects were recontacted. A total of 13,261 deaths were reported. For 260 deaths, the date of expiration was found to precede the date of recruitment; hence, these subjects were excluded. Detailed investigation of a sample of these deaths revealed that the deaths had occurred very close to the dates of recruitment of these subjects. Reinterviews were conducted for 90,282 persons; the remaining 11,588 persons, although assessed to be alive and traceable, were not available despite multiple visits. In the latter group, the last date of attempted follow-up was regarded as the withdrawal date.


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  		TABLE 1. Distribution of house-to-house follow-up in a cohort study of the joint effects of smoking and body mass on mortality, Mumbai, India, 1991–2003

 
A total of 774,129 person-years of observation were compiled. Across all BMI categories, death rates among never-using and smokeless tobacco-using men (table 2) were higher than the corresponding rates among never-using and smokeless tobacco-using women (table 3). The lowest death rates were observed among overweight (BMI 25.0–<30.0) men and women, not among those of normal weight (BMI 18.5–<25.0) or the obese (BMI ≥30.0). We performed Cox regression analysis separately for the largest group (BMI 18.5–<25.0), using BMI as a continuous variable. We found β coefficients of –0.033 for women and –0.048 for men, both with p values less than 0.01 (results not shown), indicating a significant trend.


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  		TABLE 2. Person-years of follow-up, numbers of deaths, and death rates among men, according to tobacco use and body mass index category, Mumbai, India, 1991–2003

 

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  		TABLE 3. Person-years of follow-up, numbers of deaths, and death rates among women,* according to tobacco use and body mass index category, Mumbai, India, 1991–2003

 
Never users of tobacco who had BMIs of 25–<30 were used as the reference group in tables 4–6. In comparison with the reference group, an elevated risk of death was observed across different tobacco-use groups in different BMI categories, except among never tobacco users with a normal BMI (18.5–<25.0) and smokeless tobacco users with a BMI of 25.0 or more (i.e., the overweight and obese) (table 4). This was true for both men and women. Among men, obese never users of tobacco and obese smokers were at 34 percent and 56 percent increased risks of death, respectively, when compared with the reference group. Furthermore, the risk of death was observed to increase with increasing frequency of smoking at both ends of the BMI continuum. The highest risk of death was observed among extremely thin (relative risk = 3.64) and obese (relative risk = 1.86) men who smoked more than 15 times a day (table 5).


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  		TABLE 4. Relative risk* of all-cause mortality according to body mass index category and tobacco use in men and women, using overweight never users of tobacco as the reference group, Mumbai, India, 1991–2003

 

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  		TABLE 5. Relative risk* of all-cause mortality according to body mass index category and frequency and duration of tobacco use in men and women, using overweight never users of tobacco as the reference group, Mumbai, India, 1991–2003

 

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  		TABLE 6. Multiplicative effect of tobacco use and body mass index on risk of mortality, Mumbai, India, 1991–2003

 
Table 6 shows the joint effects of tobacco use and BMI on mortality. The observed multiplicative effect was similar to the expected effect across different categories of tobacco use and BMI.


   DISCUSSION
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
References
 
Worldwide, there are two major risk factors underlying the major causes of death: tobacco use and body habitus (28–32). Their effects are now increasing rapidly, with high prevalence rates of smoking and other forms of tobacco use in many parts of the world (33, 34) and a virtual epidemic of overweight/obesity and chronic undernutrition in other parts of the world (35–37). If the current patterns persist, there will be approximately 1 billion deaths from tobacco use in the 21st century, compared with only about 0.1 billion (100 million) during the entire 20th century. Of the 55.9 million deaths occurring annually worldwide, tobacco use and BMI are responsible for approximately 20 percent (32). Diseases, especially chronic diseases, and injuries are almost always caused by multiple risk factors (38, 39). Estimating the joint effects of multiple distal and proximal risk factors is particularly important because many factors act through complicated pathways (32). Additionally, they often act in combination with other intermediate factors that interact with one another and with either tobacco or body habitus or both (40–42). Considerable but not conclusive evidence has been provided regarding the effect of smoking on the BMI-mortality association (1). However, to our knowledge, no researchers have reported on the joint effects of tobacco use and BMI on mortality. This is the first report of such an effort from India.

In developed countries, smoking and excess body weight are two of the most important risk factors implicated in chronic diseases and premature death (1, 43). Smoking is associated with lower body mass; quitting smoking has been associated with significant weight gain (44). In fact, smoking cessation was estimated to be responsible for about one quarter of the increase in the prevalence of overweight among US men during the 1980s (6). In this study, increased risk was observed not only among underweight and obese smokers but also among underweight and obese never users of tobacco (table 4). The population of India is not immune to obesity (38); however, patterns of tobacco use in India (45) are very different from those observed in other developed countries. Specifically, smoking is common among men, and it is mainly in the form of bidis, followed by cigarette smoking (20, 45). Bidi smoking is at least as harmful as cigarette smoking, and it was previously found to be an independent risk factor for mortality in this population (21), as well as being a risk factor across different BMI categories in the current study (table 4).

Findings of an elevated risk of death in the thinnest persons have been attributed to inadequate adjustment for smoking (16, 46). Smokers tend to weigh less and have higher mortality rates than nonsmokers (16). In our study, smokers weighed less (24) and had higher mortality (table 2). Some investigators have adjusted for smoking (7, 12, 47), whereas others have questioned whether statistical adjustment for smoking is entirely satisfactory (16). Thus, the alternative proposed has been to restrict analyses to never smokers. In our study, there was no change in the shape of the curve after we restricted the analysis to never users of tobacco; this finding contrasts with that of the Nurses' Heath Study, a US study (47). The present results showed no change in the risk pattern observed for different BMI categories stratified by tobacco-use habits (never use, smokeless tobacco use, and smoking).

In India, nearly half of all rural adults and one quarter of urban adults have a low BMI (BMI <18.5) (48). Although chronic energy deficiency due to an inadequate diet may be the main factor placing the population at risk of low BMI, factors other than diet may play a significant role in explaining the low BMI within this population. These factors may act directly (by affecting appetite or other aspects of physiology) or indirectly (by decreasing purchasing power to buy food). We previously reported that all forms of tobacco use were associated with low BMI independently of (i.e., after accounting for) age, education, mother tongue, and religion in the same population (24). In this study, the risks of death among men increased from never users of tobacco with a BMI of 18.5–<25.0 to smokers with a BMI of <16.0, when compared with the reference group. A similar increasing pattern of risk was observed for overweight/obese men; the risk of death increased from smokeless tobacco users with a BMI of 25.0–<30 to smokers with a BMI of ≥30.0. Although there was a low prevalence of obesity among men in Mumbai (3 percent of never tobacco users, 2 percent of smokeless tobacco users, and 3 percent of smokers), never tobacco users as well as smokers who had a BMI of ≥30.0 were at 34 percent and 56 percent increased risks of death, respectively. Thus, a joint adverse effect of smoking and obesity is discernable from this study. Men and women using different types of smokeless tobacco and having a BMI less than 16.0 had approximately twice the risk of death as the reference group (table 4). Similar increasing risks were observed for different types of smoking habits (mainly bidi and cigarette smoking).

We previously reported that education (generally used as a proxy for socioeconomic status) was associated with both tobacco use (25) and BMI (19) in Mumbai. Additionally, low BMI was associated with lower educational attainment, while higher education was associated with high BMI, a pattern that was observed for both men and women (19). Higher mortality was observed among both extremely thin men and women and obese men and women in Mumbai. One possible explanation might be the relation between occupation and education. In countries in economic transition, less-educated people tend to be employed in labor-intensive occupations and people with higher education generally lead more sedentary lifestyles. This is in contrast to economically advanced countries, where lower education may be associated with higher unemployment or low-paid jobs that are not necessarily labor-intensive. Thus, the increased risk of death among obese men across different tobacco-use habits may be an indication of an upcoming obesity epidemic in India. The protective effect that we observed in overweight (but not obese) persons (tables 2 and 3) may be an artifact of where India stands in its socioeconomic transition; that is, these persons may have been in normal weight categories just a few years earlier (19), and this risk estimate may be a residual effect of being normal weight for a long time. This finding raises important questions about the magnitude of the adverse joint impact of tobacco use and BMI on public health.

In this population, infectious agents and pollution are the other environmental factors that may play a role in the interaction between tobacco use and body habitus. Tobacco use (49–51) and poor nutrition (52) impair the immune system. Hence, tobacco users are more susceptible to infectious agents. For example, in several studies in rural and urban India, smoking has been associated with a higher relative risk of tuberculosis mortality and the prevalence of active tuberculosis (23). In corroboration of this, increased risk of mortality from tuberculosis was observed in Mumbai. In addition, the risk was higher for bidi-smoking, which is the predominant smoking habit in this population (53). Additionally, the present analysis also showed the highest risk of death among extremely thin bidi smokers. On the other hand, infections further increase levels of oxidative stress in tobacco users. Hence, the interactions between malnutrition, tobacco use, and infections make this group more vulnerable to smoking-related mortality and morbidity.

Besides its direct physiologic effect, tobacco use among the economically disadvantaged is known to reduce the resources available to purchase food, clothing, health care, and education, all factors that contribute to poor nutritional status (54). This helps to explain why changes in the relation between smoking and BMI vary with the secular shift toward affluence (55).

The current study not only underscores the importance of the joint effects of tobacco use and BMI on mortality but also demonstrates that the joint effects are multiplicative. For example, the effect is most prominent for male smokers with BMIs of <16.0 or ≥30.0.

Most of the limitations of this study, including loss to follow-up due to high migration and its impact on the tobacco-mortality association (21, 53) and limitations in BMI (e.g., very few obese persons) (19, 24), were discussed in earlier publications.

This study shows that all forms of tobacco use and BMI (a proxy for nutritional status) have independent, as well as multiplicative, joint effects on mortality. Tobacco use and undernutrition are known to be serious problems in India, and the current study indicates that obesity may soon emerge as a major public health concern. Since the prevalence of obesity is currently low, obesity is thus far associated with modest excess mortality. It appears that the joint impact is stronger than the individual effects. Thus, tobacco control research and intervention, together with improvements in nutritional status, will help to improve public health in India and prevent the emergence of an "obesity epidemic" such as that which has appeared in other developed countries.


   ACKNOWLEDGMENTS
 
This study was conducted in collaboration with the International Agency for Research on Cancer (Lyon, France) (Collaborative Research Agreement DEP/89/12), the Clinical Trial Service Unit of the University of Oxford (Oxford, United Kingdom), and the World Health Organization (Geneva, Switzerland). All of these entities provided funding for the study.

Every author had access to the data used in this paper.

Conflict of interest: none declared.


   References
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 References
 

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