Youth Working in Tobacco Farming: Effects on Smoking Behavior and Health

Background Cultivation of tobacco leaf raises concerns about detrimental occupational health and social consequences especially for youth, but tobacco producing countries only highlight economic benefits. We examined sociodemographic and health-related characteristics of underage youth working in tobacco farming and assessed the effects of tobacco farming on smoking behavior and health at one year. Methods We used existing data collected in the province of Jujuy, Argentina where 3188 youth 13 to 17 years of age from a random middle school sample responded to longitudinal questionnaires in 2005 and 2006. Multivariate logistic regression models predicted association of tobacco farming work with smoking behavior and health status at one year. Results 22.8% of youth in the tobacco growing areas of the province were involved in tobacco farming. The mean age of initiation was 12.6 years. Tobacco farming was associated with higher rates of fair or poor versus good or excellent self-perceived health (30.3% vs. 19.0%), having a serious injury (48.5% vs. 38.5%), being injured accidentally by someone else (7.5% vs. 4.6%), being assaulted (5.5% vs. 2.6%), and being poisoned by exposure to chemicals (2.5% vs. 0.7%). Youth working in tobacco farming had higher prevalence of ever (67.9% vs. 55.2%), current (48.0% vs. 32.6%) and established smoking (17.8% vs. 9.9%). In multivariate logistic regression (MLR) models tobacco farming in 2005 significantly increased the likelihood of serious injury (OR=1.4; 95%CI 1.1-2.0), accidental injury by someone else (OR=1.5; 95% 1.0-2.1), assault (OR=2.2; 95% CI 1.3-3.8), poisoning by exposure to chemicals (OR=2.5; 95% CI 1.2-5.4), in the same year. Tobacco farming in 2005 predicted established smoking one year later (OR=1.5; 95% CI 1.1-2.0). Conclusion Youth who work in tobacco faming face a challenging burden of adversities that increase their vulnerability. Risk assessments should guide public

underage youth working in tobacco farming. (297 words) Background Child labor is regarded as the employment of children less than 18 years of age [1]. It is associated with poverty, inadequate educational opportunities, gender inequality, and a variety of health risks as many are involved in hazardous occupations [2] [3] [4] [5].
Children who work have higher rates of mortality, malnutrition and disability compared with those who do not work [6]. An estimated 6 million work-related injuries occur among children that result in 2.5 million becoming disabled and 32,000 fatalities each year [7].
Working children are more susceptible to harm from exposures than adults [8] [9] and more susceptible to emotional and physical abuse and drug addictions [10] [11].
Widespread cultivation of tobacco leaf has raised diverse public health issues including concern for child labor and for occupational health hazards. Children contribute significantly to the tobacco farming workforce in low and middle income countries [12]. In this occupation they are exposed to unsuitable working conditions and toxic chemicals [13]. Pesticides can cause skin and eye irritation, nerve damage, and respiratory symptoms. Dermal absorption of nicotine from contact with wet tobacco leaves can cause green tobacco sickness [14] [15]. Other health effects associated with tobacco farming include, respiratory disorders, musculoskeletal injuries and psychiatric disorders [16] [17] [18] [19] [20]. Van Minh et al. (2009) [21] conducted a survey among tobacco and non-tobacco farmers in Vietnam. The occurrence of 9 out of the 16 health problems was higher among tobacco farmers. Tobacco farming was the second predictor of self-reported health problems after the effect of age, placing these workers at increased risk of injury and illness. Similarly, Le Cai (2012) [22] conducted a cross-sectional survey among 8681 adults aged ≥18 years in rural areas of the Yunnan Province, China from 2010 to 2011. Tobacco farmers had higher rates of current smoking, nicotine dependence, and second-hand smoke exposure compared with farmers not engaged in tobacco farming (P<0.01). Most tobacco users (84.5%) reported initiating smoking during adolescence.
In the past 20 years, the tobacco production in Argentina has grown and the country is among the top six worldwide. In 2009/2010 the production reached 132,869 tons, with 37.2% produced in the province of Jujuy. More than 50% of the total production is exported in the form of tobacco leaf. There is currently a gap in the state of the knowledge regarding the relationship between tobacco farming and smoking among underage youth in Latin America. This study reports on data of underage youth residing in the province of Jujuy. The analysis focuses on examining sociodemographic factors and health characteristics of youth working in tobacco farming, in comparison to those who are not engaged in this occupation. We also determined the longitudinal effect of working in tobacco farming on smoking behavior.

Setting
The Province of Jujuy, Argentina is characterized by a geographic configuration that includes lowlands where tobacco farms are located. Tobacco farming is an important contributor to the economy of the province, with 120 to 130 workdays by farmed hectare.
The majority of the tobacco workforce in Jujuy are individuals hired by mid to large scale farmers. Only 1% are small farms with less than 2 hectares of land that depend solely on family labor [25] [26]. and school coordinators present as proctors. In each school, one attempt was made to survey absent students at a subsequent date. The detailed study procedures have been described in a previous publication [27]. For this report we used data from the 3234

Questionnaire Development
The questionnaire consisted of translated items from surveys of adolescents in the U.S. [28], and questions developed through qualitative research in the target population [27].
Items in English were translated and reviewed by three Argentinean investigators and two other Spanish-speaking research staff. Pilot testing of the instrument was conducted with students in rural and urban areas evaluating situational factors, content, characteristics of the respondents, and time of administration that averaged one hour.

Demographics
Sociodemographic variables were extracted from baseline data including sex, age, ethnicity (Indigenous, mixed Indigenous and European, European), and religion. Religion was categorized as Catholic, Christian or Evangelical, and others corresponding to low frequency religions. A binary (yes/no) low socioeconomic status (SES) variable was developed by classifying the primary care taker as having up to primary education, being unemployed, or being on welfare, versus having a higher education level or being formally employed. The location of the school was reported in the questionnaire by interviewers.

Health related factors
Health related variables correspond to T1 responses. Respondents provided a selfassessment of their health status, categorized as excellent, good, fair or poor. Another set of questions probed on the occurrence of injuries. We asked if in the previous year respondents had a serious injury, if they were injured accidentally by someone else, if they had been assaulted, and if they had been poisoned by exposure to chemical products. Local agricultural workers commonly refer to pesticides as "chemicals" and the survey question was phrased accordingly.

Smoking Behavior
Smoking behavior was the main outcome and questions were developed to be comparable to those used in the Centers for Disease Control and Prevention GYTS survey [28].
Respondents were considered ever smokers if they tried at least a cigarette puff in their lifetime and never smokers had not tried even one puff. Current smokers were defined as having smoked at least one whole cigarette in their lifetime and at least one puff in the previous 30 days. Established smokers were defined as current smokers who had smoked at least 100 cigarettes in their lifetime. We used smoking information from T1 and T2.
Respondents also reported on the number of friends who smoked (none, 1 to 4, 5 or more), and whether any adult smoked in their home.

Working in Tobacco Farming
Working in tobacco farming was ascertained by questions asking if youth had ever worked in any of the tasks involved in tobacco production, growing, harvesting or selecting tobacco leaf, without discriminating the different types of tasks. We also asked the age of initiation in tobacco farming work. Hereby reported exposure variables correspond to measurements at T1.

Data Analysis
The sampling design was incorporated into all models by specifying geographic areas as strata and schools as clusters as well as including weights to adjust for disproportionate stratification. In addition, a finite population correction was applied to adjust for the relatively large proportion of available schools sampled within each geographic area. The statistical program Stata (version 14.2) was used for data analysis. Standard errors and confidence intervals were estimated via the Taylor expansion approximation using the svy procedures in Stata [29]. First, we conducted descriptive analyses by sex, to profile the sample. We calculated the prevalence of ever, current and established smoking, with chi square tests and p values at T1 and T2, and the percentage of youth who reported at T1 that they had ever worked in tobacco farming. The mean and standard deviation of the age for girls and boys, and of the age of initiation in tobacco farming was calculated.
Bivariate contingency tables examined the pairwise relationship of sociodemographic characteristics, health related factors and smoking behavior by sex, and by working in tobacco farming.
Multivariate logistic models regressed working in tobacco farming at T1 with each of the health-related variables at T1. Separate multivariate logistic models regressed working in tobacco farming at T1 onto cigarette smoking behaviors at T2 (ever, current or established smoking). Covariates included sociodemographic characteristics (sex, age, low SES, ethnicity, religion, number of friends who smoked, adult smokers at home, and for each model, the corresponding smoking behavior at T1 (ever, current or established smoking). We estimated adjusted odds ratios and 95% confidence intervals.

Results
The mean age for girls was 14 (2005), the prevalence of ever (56.6%) and current smoking (34.4%) was similar for boys and girls but established smoking was more prevalent among boys (13% vs. 8.9%, p = 0.004). The prevalence of working in tobacco farming was unevenly distributed across geographical regions, involving 22.8% of youth in the lowlands where tobacco is cultivated, and between 4.5% to 4.9% in the other areas (data not shown). Ever working in tobacco farming was reported by 11.5% of the total sample (Table 1). Involvement in tobacco farming was more prevalent among boys (12.9% vs. 10.3%, p = 0.044) but the mean age of initiation did not differ significantly between girls (12.0; 95% CI 11.4-13.0) and boys (12.7; 95% CI 12.1-13.2).

Tobacco farming sociodemographic, health factors and smoking behavior
The percentage of youth who endorsed an evangelical religion was greater among those who worked in tobacco farming (17.0% vs. 9.8%). Working in tobacco farming was also associated with having low SES (28.5% vs. 22.4%), being Indigenous (77.8% vs. 67.4%), and having more than 5 friends who smoked (60.6% vs. 46.7%).
Youth who had ever worked in tobacco farming had significantly higher prevalence of ever smoking (67.9% vs. 55.2%, p<0.001), current smoking (48.0% vs. 32.6%, p<0.001) and established smoking (17.8% vs. 9.9%, p = 0.002) at T1 (2005) ( Table 2). The prevalence of smoking behaviors increased slightly at T2 (2006) and youth with a history of working in tobacco farming had higher rates ( Table 2) established smoking were, religion other than catholic or evangelical, mixed Indigenous-European ethnicity, and having 5 or more friends who smoked versus none (Table 3).
Separate logistic models including interaction terms between tobacco farming and sex, ethnicity, and having friends who smoke, yielded no significant interaction effects (data not shown).

Discussion
As a primary finding we ascertained a one-year effect of work in tobacco farming among youth, on being an established smoker defined as current smoker of at least 100 cigarettes lifetime. To our knowledge, this finding has not been previously reported and is unique in focusing on underage youth. The sociodemographic profile of these Jujuy youth working in tobacco farming highlights the roots of the child labor problem at a global level; youth belonging to poor families and of non-dominant social groups, particularly Indigenous populations. Ethnographic field studies provide a concurrent qualitative perspective of the tobacco workforce in Jujuy [30]. Our results highlight that socioeconomically vulnerable youths may be further impaired in their development by occupational health problems and the cigarette smoking associated with a large set of health risks throughout the life course [13]. Furthermore, youth who worked in tobacco farming reported having a fair or poor self-reported health status in a greater proportion than other youth, as well as increased rates of exposure to toxic chemicals. Although we cannot ascertain the precise nature of sustained injuries, or a direct relation to the occupational context, we identified an increased risk of exposure to violence through assaults among youth working in tobacco farming. The increased exposure to interpersonal violence finding has not been reported in other studies, largely of adult populations.
Prior research postulates that there may be an association between exposure to pesticides and mental health problems [31]  was useful for examining longitudinal effects of tobacco farming. However, with this dataset we were not able to determine a precise date of initiation in tobacco farming to calculate a time of exposure variable, as this information is based on recall and it is not unusual for children to become involved in this activity at very early ages. Likewise, we were not able to determine the type of tasks performed and the amount of time in months and years of previous exposure. In addition, we cannot ascertain that injuries and poisoning with chemicals occurred while conducting tobacco farming activities. Another limitation is that we are not able to draw causal inference about health-related factors.
Although the data were collected more than 10 years ago, there is no indication that the practice of underage youth working in tobacco farming has changed.
More than 250,000 hectares of tobacco are planted throughout the globe in more than a