New evidence on the effect of smoking on the obesity risk among adults, Findings from the China Health and Nutrition Survey (CHNS, 1991-2015)

Background: To estimate the approximately causal effects of smoking on the obesity risk among Chinese adults. Methods: Using China Health and Nutrition Survey (CHNS) datasets from 1991 to 2015, this study consisted of 35,907 males and 39,441females aged 18-65 years. Using ordinary-least squares and probit models to investigate the effects of smoking on risk of obesity among Chinese adults. Results: Male current smokers had a higher dietary energy intake (23.28 unit), percentage of dietary energy intake from fat (0.47 unit), physical activity (9.96 unit), drinking (0.61 unit) but less likely to be general obesity (0.17 unit) and abdominal obesity (0.12 unit) than nonsmokers. Female current smokers less likely to be general obesity (0.03 unit) and abdominal obesity (0.12 unit) than nonsmokers. Male heavy smokers (>25 cigarettes/d) had higher dietary energy intake (89.65 unit), physical activity (15.31 unit), drinking (0.08 unit) and more likely to be general obesity (0.18 unit) and abdominal obesity (0.10 unit) than other smokers. Conclusions: Compared with nonsmokers, current smokers had lower probability of being general obesity and abdominal obesity among Chinese adults regardless of gender. Male heavy smokers increased the risk of obesity than other smokers. These findings may improve the understanding on how cigarette smoking affects fat distribution and provide scientific evidence regarding intervention in smoking and obesity, especially for male heavy smokers


Introduction
Smoking alone or in combination with obesity poses the major public health burden in western societies as well as many developing countries [1]. Generally, obesity epidemic is mostly attributed to behavioral risks, however, smoking may seriously influence individual risk of obesity as well. [2][3][4]. Understanding pathways that contribute to these risk factors, and the nature of the relationship between them, is therefore of paramount importance for disease prevention [5].
Existing evidences about the effects of smoking on obesity risks are complex and not yet completely understood [6,7]. Numerous cross-sectional studies have reported that BMI are lower in current smokers than in nonsmokers while other studies have found a Ushaped relationship between smoking and BMI [8,9].However, heavy smoking has been found to be associated with higher BMI [10]. Moreover, some studies have reported that current smokers have more abdominal obesity than never smokers [11][12][13],but other studies indicated no evidence for this association [14,15]or have even found the opposite [16,17]. There is a general perception that smoking decreases body weight due to reasons like decrease in appetite and calorie intake, enhanced metabolism, and reduced fat accumulation [18].However, despite their lower body weights, current smokers do not eat less than nonsmokers and tend to eat slightly more [19]. Evidences shows that smoking is associated with more physical activity due to specific occupational groups and activity types [20,21],while smoking reduced activity is more commonly found [22]. These conflicting results may be because of data differences and model specifications [23]. More empirical evidences are needed to figure out the effects of smoking on obesity risk.
China is the world's largest consumer and manufacturer of tobacco, which is also experiencing a steady rise in obesity rates. Our objectives therefore were to evaluate, in a representative longitudinal study of Chinese adults, how smoking influenced the risk of obesity, how this was related to be general obesity and abdominal obesity, and whether these relationships varied by smoking intensity.

Study Population and Data Collection
Data from the China Health and Nutrition Survey (CHNS,1991(CHNS, -2015, which is a largescale, longitudinal household-based survey initiated in 1989 that consists of representative participants of varying economic status, health indicators, and geographic areas throughout China [24]. Further information on survey procedures and the sampling scheme was reported in detail elsewhere [25]. We excluded participants who were pregnant, lactating, missing key variables from the analysis. Hence, our final sample consisted of 75,348 person-year observations aged 18-65 years with complete data on demographic, smoking status, obesity indicators.

Obesity indicators
Well-trained health workers measured the height, weight, and wasit circumstance (WC) following standardized procedures. Dividing weight (in kg) by the square of height (in m 2 ) we got BMI and grouped it into thin (<18.5 kg/m 2 ), normal (18.5-23.9 kg/m 2 ), overweight (24-27.9 kg/m 2 )and obesity (>28 kg/m 2 ) [26]. We defined participants as having abdominal obesity if the WC ≥85 cm in females and ≥90 cm in males In accordance with the national health and family commission for Chinese adults (2013)[27].

Smoking indicators
In the CHNS questionnaire, two variables were constructed to measure smoking behavior.
The first was smoking status, which was classified into "current smoker" or "nonsmoker".

Other variables
We grouped participants into three education level (primary/illiterate, middle, and high school/above), two marital statuses (single / married), two geographical regions (rural / urban), three income levels (low / medium / high) and two drinking status (yes/no). The per-capital annual income in each survey was inflated to values in 2015. Participants reported all physical activities (PA) in average hours per week, and we converted the time spent in each activity into a metabolic equivalent of task (MET) hours per week based on the Compendium of Physical Activities [28].Dietary intake at the individual level was assessed by using three consecutive 24-h dietary recalls in each wave of the CHNS [24].
Based on the Chinese Food Composition Table, we measured nutrition intake data by (1) the respondent's daily calorie intake per day during a 3-day measurement period and (2) the dietary structure as indicated by the percentage of fat in the respondent's daily calorie intake [26].

3.Statistical Analysis
Statistical analyses were performed using the STATA 13.0 (STATA, Stata Corp). We first employed a pooled ordinary least square (OLS) model covering from1991 to 2015.
Outcome variables including dietary energy intake, the percentage of dietary intake from fat and physical activity.
The equation we used for this model is K abc = α 0 + α 1 SMOKE abc + α 2 X abc + δ c + α b + ε abc (1) K abc denote the lifestyle behavior of individual a in province b and year c. SMOKE abc indicating whether the individual is current smoker or nonsmoker in year c; X abc contains control variables; δ c and α b indicate time and province fixed-effects, respectively; ε abc is the random error that varies with individual, province and year. α 1 indicates the impact of smoking on the lifestyle behavior.
When we investigate the effects of smoking intensity on lifestyle behaviors. We change the SMOKE abc in model 1-3 to SMOKEI abc . SMOKEI abc is dummy variable indicating whether the current smoker is heavy smoker (1 = yes, 0 = no), moderate smoker (1 = yes, 0 = no) or light smoker (1 = yes, 0 = no). kcal/d) (p < 0.001). Nonsmokers consumed more percentage of energy intake from fat than current smokers (30.30% vs. 29.70%) (p < 0.001). The average rates of general obesity and abdominal obesity were significantly higher in nonsmokers than in smokers (8% vs. 6% and 41% vs. 35%, respectively) (p < 0.001). Table 2 shows the trends of characteristic of current smokers. From 1991 to 2015, heavy smokers increased from 8% to 14% (p < 0.001). while light smokers decreased from 45% to 39% (p < 0.001). Dietary energy intake of current smokers decreased from 2,890 kcal to 2,240 kcal (p < 0.001), while the percentage of energy intake from fat increased from 25.93% to 36.72% (p < 0.001). It is noteworthy, the prevalence of overweight and obesity in current smokers increased significantly in mainland China from CHNS 1991 to 2015 (p < 0.001) (Figure 1).

Effects of smoking behavior on risk of obesity among the whole population
The OLS and Probit results were presented in Table 3 and Table 4, respectively. There was a significant correlation between smoking behavior and obesity risk. Male current smokers had higher dietary energy intake, percentage of energy intake from fat, physical activity and likelihood being drinking by 23.28 unit, 0.47 unit, 9.96 unit and 0.61 unit than nonsmokers, respectively. Female current smokers also had higher percentage of energy intake from fat and likelihood being drinking by 0.60 unit and 0.79 unit than female nonsmokers, respectively (Table 3).
After controlling for confounding factors, current smokers had a lower BMI and WC than nonsmokers regardless of gender. Smoking decreased the likelihood being general obesity by 0.17 unit in males and 0.03 unit in females, and abdominal obesity by 0.12 unit in males and females (Table 4). While there were no differences among smoking intensities in female (  (Table 4).

Smoking and risk of obesity
Using a representative cohort with more than 20-year follow-up, in summarize, it appears that male current smokers declared higher intakes of dietary energy, fat and alcohol than  (2) Participants in this survey, aged between 18 and 65, were more likely to be involved in professional work activities. It may be that people with a manual occupation are more likely to smoke and to drink heavily, in addition to being more physically active due to the nature of their work, as compared to people with a nonmanual occupation [34].Moreover, previous studies performed mostly among working-age people have shown smokers to be leaner than nonsmokers [35,36].
In this longitudinal survey among Chinese adults, we found that current smokers had lower BMI than nonsmokers is consistent with many previous studies [37][38][39]. While the association between smoking and abdominal obesity yielded inconsistent findings. . In the present study, after adjusting for potential confounders, we found that current smokers had a lower WC compared with nonsmokers regardless of gender. These contradictory findings show that the association still requires more attention.

Smoking intensity and risk of obesity
Moreover, the notable finding in the present study is that male who smoke equal to or more than 25 cigarettes per day increased the risk of the onset of general obesity and abdominal obesity compare to other smokers both independently and significantly. The heavy frequency of smoking was positively associated with BMI in male was in line with previous studies [43][44][45].Moreover, it is suggested that heavy smokers have a higher risk of obesity than light smokers among working-age people [46]. In our study, we find that heavy smoking increased dietary energy intake, physical inactivity and likelihood being drinking. After adjusting for these variables considerably change the estimated mean difference in BMI between heavy and other smokers. One possible explanation from firstly, lower levels of androgens in male current smokers has been found to increase abdominal obesity [51].Secondly, male heavy smokers are more likely to have unhealthy behaviors such as more calorie intake , increased alcohol use, which was also found in our study. These unhealthy behaviors may favor weight gain and partly explain the accumulation of visceral fat mass in abdominal area.

Strengths and limitations
First of strengths in this study was that we examined the association between smoking and risk of obesity by combine use smoking status and smoking intensity (based on the number of cigarette smoked in a day). Second, the longitudinal study design could confirmative evidence to causality. Third, we controlled several important sociodemographic and behavioral confounders and assess sex differences in estimated associations, which helped to improve the validity of our findings.
However, some limitations need to be mentioned. First, we were not able to control for former smokers' body weight status in smoke quitting period because of data usage restrictions that might lead to selection effect. Second, dietary data were collected using

Availability of data and material
The datasets used and analysed during the current study are available from the corresponding author on reasonable request.

Acknowledgement
The authors thank the team at the National Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention and the Carolina Population Center, University of North Carolina at Chapel Hill. The authors are also grateful to the participants for their involvement in the survey.

Author's Contributions
All authors contributed significantly to this article. JZ analyzed the data and wrote the manuscript, JS critically revised the manuscript for important intellectual content. All authors read and approved the final manuscript.

Competing Interests
The authors have no conflict of interest to declare          Trends of general obesity and abdominal obesity in Chinese adults by smoking intensity from CHNS1991 to 2015