Strenuous occupational physical activity: Potential association with esophageal squamous cell carcinoma risk

Abstract

Objective:

The impact of recreational physical activity (RPA) on cancer risk has been extensively studied. However, the association of occupational physical activity (OPA), which differs in dose and intensity from RPA, with different cancers including esophageal squamous cell carcinoma (ESCC), has received less attention.

Materials and methods:

We conducted a hospital-based case–control study in Kashmir, India, majorly a rural population, to evaluate the association of OPA with ESCC risk. Histopathologically confirmed 703 ESCC cases and 1664 controls, individually matched to the respective cases for age, sex and district of residence, were recruited.

Main outcome measures:

Information on type, duration and intensity of physical activity was obtained in face-to-face interviews with participants using a structured questionnaire. Conditional logistic regression models were used to calculate odds ratios (ORs) and 95% confidence intervals (95% CIs). Body mass index was unable to be accounted for in the analysis.

Results:

A high level of OPA was associated with increased ESCC risk (OR = 2.17, 95% CI; 1.41–3.32), compared to subjects with moderate OPA. The association with ESCC risk was stronger in strenuous workers (OR = 3.64, 95% CI; 2.13–6.20). The association of strenuous OPA with ESCC risk persisted only in subjects that were involved in strenuous activities for equal to or greater than five days/week.

Conclusions:

Our study suggests a possible association of strenuous OPA with ESCC risk. Although our results were adjusted for multiple factors, including indicators of socioeconomic status, more replicative occupational epidemiological studies are needed to rule out any residual confounding.

Keywords

Esophageal cancer risk strenuous physical activity occupation Kashmir

Introduction

Esophageal cancer is the sixth most common cause of cancer-related deaths in the world.¹ Its two main histological types, esophageal adenocarcinoma (EADC) and esophageal squamous cell carcinoma (ESCC) have different etiology and geographical distribution.² The incidence of EADC is higher in the developed world, while ESCC is more common in the developing nations, particularly in Asia, which together contributes about 83% of the total global ESCC burden.² Unlike EADC,³ the etiology of ESCC is attributed to various indicators of low socioeconomic status (SES)⁴ pervasive in the developing nations. Although many such factors, including low fruit and vegetable intake,^5,6 poor oral hygiene,^7,8 low SES^9,10 and frequent and close contact with animals like ruminants^11,12 have been associated with ESCC risk, the overall etiology of ESCC is not completely understood yet.^13,14 Moreover, unlike low-risk regions of ESCC, tobacco and alcohol use are not strongly associated with ESCC risk in these high-risk populations.¹⁴ Hence, other possible risk factors in these high-incidence regions of ESCC need to be explored.

Compared to the developed world, developing economies lack potential industrialization and usually have low technological advantages. As a consequence, most of the occupations like farming, shoveling, heavy weightlifting and construction works, etc., involve human exertions and demand excessive physical labor. Such strenuous and exhaustive occupational physical activities (OPAs) involved in such jobs are done for many hours a day, for most of the days per week, most often carried out for many years, and, thus, cannot be compared with recreational physical activity (RPA). Hence, OPA in the developing world offers a different setting to study its association with cancer risk. Moreover, the perception is now building that there is a threshold line up to which physical activity can be beneficial. Reports keep coming with unprecedented findings on the relation between physical activity and cancer risk. Specifically in the case of ESCC, two recent independent studies have reported that higher OPA levels increase ESCC risk.^15,16

ESCC is the most common cancer in Kashmir, India,¹⁷ which is under economic transition. The majority of the population lives in rural areas, which contributes to the maximum number of ESCC cases.¹⁸ The rural inhabitants are commonly engaged in farming activities and other unskilled jobs that, by nature, involve strenuous physical activity, while the jobs that involve fewer efforts, like in government services and business, are less common.⁹ We conducted a case-control study and reported the association of a number of risk factors in the study population with ESCC risk.^8,11,19–22 We previously reported that the people involved in active or very active OPA have a higher risk of ESCC, as compared to sedentary life behavior.⁹ Here, we further analyze the data on OPA to investigate the association between the intensity and frequency of OPA with ESCC risk in Kashmir.

Materials and methods

Subject selection

We conducted a hospital-based case–control study to identify the various risk factors of the ESCC in Kashmir, whose details of the study design and related information has been reported previously.^8,9,11,22 Briefly, all histopathologically confirmed ESCC cases (n = 703), who had no previous cancer, were recruited from the Regional Cancer Centre and Department of Radiation Oncology of Sher-i-Kashmir Institute of Medical Sciences (SKIMS) from 2008 to 2012. For each case, at least one control (n = 1664) individually matched to the sex, age (± 5 years) and district of residence was recruited from in-patient wards of SKIMS, Government Medical College Hospital, Srinagar and 10 district hospitals. Patients were enrolled as controls only when the disease for which they had been admitted did not have a strong association with tobacco or alcohol consumption. The participation rate for cases and controls was 96% (732 invited, 29 refusals) and 98% (1697 invited, 34 refusals), respectively. The majority of those who refused were too ill to participate in the study. We were able to recruit one control for 45 cases, two controls for 377 cases, three controls for 269 cases and more than three controls for 13 cases. Informed consent was obtained from all subjects. This study was reviewed and approved by the Institutional Ethics Committee of Sheri Kashmir Institute of Medical Sciences, Srinagar.

Data collection

Structured questionnaires were administered in face-to-face interviews at hospitals by trained interviewers in primary language. A limited number of staff conducted the interviews and no proxies were used. Detailed information on demographic characteristics, habits, including lifelong history for use of alcohol, several tobacco products and intake of fresh fruits and vegetables was collected. The ever use of alcohol and tobacco products was defined as the use of the respective product at least weekly for a period of six months or more. To assess the SES, information on the potential parameters of SES was obtained, including education level (highest level attained), occupation, professional work intensity, income, house type, cooking fuel, place of residence and ownership of several household appliances, including personal automobile, motorbike, black and white television, color television, refrigerator, washing machine, vacuum cleaner, computer and bath in the residence. The detailed information about consumption of the various fruits and vegetables was collected using a semi-quantitative food frequency questionnaire. We asked about the usual frequency of use in a day, week or month, and the amount of use in each instance. Using this information, we calculated the intake of each fruit and vegetable in g/day. In order to cover the intake of seasonal fruits/vegetables, we also collected data on the number of months in which any of these fruits were consumed: the daily intake in these cases was multiplied by the number of months of consumption and divided by 12. The daily intake of all fruits and vegetables were summed up to estimate the total fruit/vegetable intake per day.

Assessment of physical activity

We collected information on the type of occupations and nature of the physical activity, as well as on the many potential risk factors prevailing in the Kashmiri population. The information collected from participants includes almost all the parameters in the different sections of the International Physical Activity Questionnaire (IPAQ). Participants who were involved in occupations involving strenuous physical activity (like shoveling, farming, brick or stone setters, landscape workers, loggers, construction workers, etc.) were further asked if the strenuous physical activity was a part of their daily activities. As an indicator of strenuous activity, the subjects were asked if they sweated a lot and if their heart rate increased during their working time.²³ Information on the frequency of work done in a week (number of days worked per week) by the subject was recorded as: (a) 1–2 days/week; (b) 3–4 days/week; (c) ⩾ 5 days/week. The information on RPA was also obtained. All interviews were carried out in the participants’ local language.

Statistical analysis

Numbers and percentages were calculated and presented for categorical variables, as well as means and standard deviations (SDs) or median and interquartile ranges for continuous variables. Fruit and vegetable intake data (g/day) were transformed to logarithmic values following the addition of 0.1 to original values. To assess the SES, we built a composite score for wealth, based on appliances ownership and other variables, using multiple correspondence analysis (MCA).¹⁰ Information on the MCA method is provided elsewhere.¹⁰ Conditional logistic regression was used to calculate unadjusted and adjusted odds ratios (ORs) and corresponding 95% confidence intervals (CIs). By design, case and control subjects were matched by age, sex and district of residence. Adjusted ORs (95% CIs) were obtained from two models. In the first model, ORs (95% CIs) were adjusted for demographic factors, including age, ethnicity, place of residence (rural/urban), religion and education level. Age was included in the multivariate models, because the matching for age was not perfect (±5 years). We adjusted the results for religion because an earlier study from this region had suggested dissimilar incidence of ESCC among people with different religions.²⁴ In the second group of models, in addition to the aforementioned demographic factors, some biologic factors, including daily fresh fruit and vegetable intake (logarithmic scale), cumulative use of cigarettes, hookahs and nass, and ever use of bidi, gutka and alcohol, were included individually, and then collectively. The OPAs were categorized into two groups: 1) participants with low levels of physical activity in their jobs (occupations involving minimum exertion, such as clerks, engineers, teachers, business people, etc.); and 2) very active workers (occupations like shoveling, farming, brick or stone setters, landscape workers, loggers, construction workers, etc.). Further, among the active works, those who reported a lot of sweating and a substantial increase in their heart rates during working hours were grouped as strenuous occupational workers. The number of subjects with 1–2 days or 3–4 days of work/week was modest, and so were grouped together and subsequently categorized into two categories: 1) ⩽ 4 days of work/week; and 2) ⩾ 4 days of work/week. All statistical analysis was carried out using Stata software, version 12 (Stata Corp., College Station, TX, USA). Two-sided P-values < 0.05 were considered statistically significant.

Results

A total of 703 ESCC cases and 1664 matched controls were recruited in this study. The distribution of demographic factors, socioeconomic indicators, and tobacco and alcohol use by case status are shown in Table 1. The mean age of cases and controls was 61.6 and 59.8 years, respectively, and ~55% were males. The majority of ESCC cases resided in rural areas (95%). More cases were involved in occupations, which by nature involve strenuous physical activities than the respective controls, while as the jobs like government services and business were more in controls (17%) than the cases (6%). A sizable proportion of ESCC cases comprised active workers (88%), as compared to the controls (64%). The percentage of cases (38%) with strenuous OPA was higher than in the respective controls (20%). A larger number of cases comprised participants who were smokers and had low levels of formal education than their respective controls. Fresh fruit and vegetable consumption and SES were higher in controls than in their respective cases. None of the participants reported any RPA.

Table 1.

Characteristics of 703 ESCC cases and 1664 controls from Kashmir Valley, India, 2008–2012.^a

Characteristics	Cases (%)	Controls (%)	P-value
Age, mean (SD) years	61.6 (11.1)	59.8 (11.1)
Sex			0.78
Male	393 (55.9)	920 (55.3)
Female	310 (44.1)	744 (44.7)
Place of residence			<0.001
Urban	29 (4.1)	146 (8.8)
Rural	674 (95.9)	1518 (91.2)
Ethnicity			0.58
Kashmiri	682 (97.0)	1619 (97.3)
Gojri	11 (1.6)	16 (1.0)
Pahari	9 (1.3)	27 (1.6)
Other	1 (0.1)	2 (0.1)
Religion			0.03
Muslim	695(98.9)	1648 (99.0)
Hindu	5 (0.7)	2 (0.1)
Sikh	3 (0.4)	14 (0.8)
Fresh fruit and vegetable intake, median g/day (IQR)	7.9 (3.8–12.6)	25.2 (12.0–60.9)	<0.001
Hookah smoking (hookah/year)			<0.001
Never	282 (40.2)	964 (58.0)
1–139	97 (13.8)	228 (13.7)
140–240	110 (15.7)	245 (14.8)
> 240	213 (30.3)	224 (13.5)
Cigarette smoking (packs/year)			0.01
Never	632 (90.0)	1437 (86.4)
1–6.2	23 (3.3)	77 (4.6)
6.3–13.1	21 (3.0)	73(4.4)
⩾ 13.2	26 (3.7)	76 (4.6)
Bidi ever-smoking	15 (2.1)	3 (0.2)	<0.001
Nass chewing (nass/year)			<0.001
Never	501 (71.6)	1471 (88.5)
1–119	46 (5.6)	52 (3.1)
120–199	36 (5.1)	71 (4.3)
⩾ 200	117 (16.7)	69 (4.1)
Gutka ever-chewing	10 (1.4)	13 (0.8)	0.01
Alcohol ever-use	8 (1.1)	0 (0.0)	<0.001
Animal contact			<0.001
No or occasional contact	164 (23.3)	774 (46.5)
Daily contact	175 (24.9)	616 (37.0)
Daily and close contact	364 (51.8)	274 (16.5)
Second-hand smoking			0.022
No second-hand smoke exposure	642 (91.4)	1504 (93.9)
Exposure to second-hand smoke	61 (8.6)	97 (6.1)
Family history of cancer			<0.001
Negative history	462 (65.7)	1544 (92.8)
Positive history	241 (34.3)	120 (7.2)
Oral hygiene			<0.001
Does not brush teeth	161 (22.9)	101 (6.2)
Brushes once/week	366 (52.1)	785 (47.9)
Brushes twice or thrice/week	94 (13.4)	345 (21.1)
Brushes daily	81 (11.6)	405 (24.8)
Tea type			0.041
Other	09 (1.3)	51 (3.1)
Salt tea	693 (98.7)	1612 (96.9)
Monthly income (INR)			<0.001
1000–5000	514 (77.0)	988 (59.5)
6000–10,000	102 (14.5)	384 (23.1)
> 10,000	60 (8.5)	290 (17.4)
Wealth score			<0.001
Quintile 1 (lowest)	397 (56.5)	337 (20.2)
Quintile 2	112 (15.9)	328 (19.7)
Quintile 3	66 (9.4)	334 (20.1)
Quintile 4	70 (10.0)	333 (20.0)

Although cases and controls were individually matched, the percentages of cases and controls are not necessarily equal in each sex category, because some cases have one matched control and others have more controls. Numbers may not add up to the total numbers due to missing data in some variables. P-values were calculated using chi-squared tests for categorical variables (chi-square for trend in variables with more than two categories) and Wilcoxon Rank-Sum tests for continuous variables.

SD: standard deviation; IQR: interquartile range.

The ever use of alcohol and tobacco products was defined as the use of the respective product at least weekly for a period of six months or more.

An increased risk of ESCC was observed in very active workers (OR = 2.17, 95% CI; 1.41–3.32) as compared to workers with moderate activity. Upon further stratification of the active group into strenuous and non-strenuous workers, the association was stronger in strenuous workers (OR = 3.64, 95% CI; 2.13–6.20), but did not persist in non-strenuous workers. The strenuous activity effect on ESCC risk persisted only in subjects who carried out strenuous work ⩾5 days/week (OR = 3.52, 95% CI; 1.97–6.31) (Table 2). We assessed the differences in the ESCC risk associated with the intensity and frequency of physical activity as determined by gender; the risk persisted only in males (3.39, 95% CI; 1.96–5.88), but was lost in females, possibly because of the low numbers in the model (Table 3). We further classified the subjects into two groups: one group included farmers, while the other group included non-farming professionals. The ESCC risk was retained in both groups, albeit with wider CIs than in the non-farmer group, possibly due to low numbers in the latter subgroup. On further sub-classification of the subjects based on their cumulative wealth score and monthly income, we observed high ESCC risk in the subjects with strenuous physical activity and low wealth scores, and this risk was almost significant in participants with high wealth scores as well (Table 4). The outcome of the study did not change when adjustment was made, individually, for socioeconomic indicators, education, income and cumulative wealth score (Table 5). Upon further stratification of subjects, based on their smoking habits, the association of OPA with ESCC was observed in both smokers as well as non-smokers, but did not persist in the adjusted model in the non-smoker group (Table 6), possibly due to the small number of participants in this group.

Table 2.

Association between physical activity and ESCC risk, Kashmir Valley, India.

Physical activity	Cases (%)	Controls (%)	Unadjusted OR^* (95% CI)	Adjusted OR^a (95% CI)	Adjusted OR^b (95% CI)
Occupational physical activity
Sedentary/moderate levels of activity	536 (76.2)	1506 (90.6)	Referent	Referent	Referent
High levels of activity	167 (23.8)	157 (9.4)	3.32 (2.52–4.36)	2.53 (1.87–3.43)	2.17 (1.41–3.32)
Intensity of work
Non-strenuous	41 (5.8)	83 (5.0)	1.48 (0.98–2.23)	1.18 (0.75–1.84)	1.11 (0.57–1.72)
Strenuous	126 (17.9)	74 (4.6)	5.63 (3.97–7.99)	4.19 (2.87–6.13)	3.64 (2.13–6.20)
Frequency of strenuous work
⩾ 4 days/week	6 (0.9)	7 (0.4)	2.74 (0.76–9.92)	2.16 (0.43–10.98)	2.29 (0.27–19.58)
⩽ 5 days/week	120 (18.1)	67 (4.2)	5.80 (3.98–8.44)	4.23 (2.82–6.34)	3.52 (1.97–6.31)
P for trend			<0.001	<0.001	<0.001

OR: odds ratio; CI: confidence interval.

Note: numbers may not add up to the total numbers due to missing data in some variables.

By design, controls were individually matched to cases for age, sex and district of residence.

Adjusted for age, ethnicity, place of residence, religion and education.

Adjusted for age, ethnicity, place of residence, religion, education, daily fresh fruit and vegetable intake (logarithmic scale), wealth score, monthly income, cumulative use of cigarettes, hookahs and nass, and ever-use of bidi, gutka and alcohol, exposure to passive smoking, family history of any cancer, oral hygiene, consumption of salt tea, contact with animals.

Table 3.

Association between physical activity and ESCC risk, Kashmir Valley, India, stratified on the basis of gender.

Males						Females
Physical activity and intensity	Cases (%)	Controls (%)	Unadjusted OR^* (95% CI)	Adjusted OR^a (95% CI)	Adjusted OR^b (95% CI)	Cases (%)	Controls (%)	Unadjusted OR^* (95% CI)	Adjusted OR^a (95% CI)	Adjusted OR^b (95% CI)
Occupational physical activity
Sedentary/moderate levels of activity	239 (60.8)	778 (84.7)	Referent	Referent	Referent	297 (95.8)	728 (97.9)	Referent	Referent	Referent
High levels of activity	154 (39.2)	141 (15.3)	3.50 (261–4.69)	2.59 (1.88–3.56)	2.08 (1.31–3.302)	13 (4.2)	16 (2.1)	2.20 (1.00–4.85)	2.81 (1.12–7.07)	3.40 (0.94–12.40)
Intensity of work
Non-strenuous	30 (7.6)	68 (7.40)	1.37 (0.86–2.19)	1.04 (0.63–1.73)	0.86 (0.42–1.578)	11 (3.6)	15 (2.0)	1.90 (0.82–4.41)	2.23 (0.83–6.01)	2.62 (0.59–8.63)
Strenuous	124 (31.6)	73 (7.9)	5.56 (3.90–7.92)	4.04 (2.76–5.90)	3.39 (1.96–5.88)	2 (0.65)	1 (0.1)	6.62 (0.59–73.41)	11.30 (.93–138.0)	126.72 (0.47–1529)
P for trend				<0.001	<0.001				0.058	0.067
Frequency of strenuous work
1–4 days/week	6 (1.6)	7 (0.8)	2.74 (0.76–9.91)	2.30 (0.48–11.10)	2.205 (0.26–18.27)	0 (0.0)	0 (0.0)	−	−	−
Daily	118 (32.5)	66 (7.8)	5.78 (3.95–8.45)	4.14 (2.76–6.21)	3.39 (1.85–6.20)	2 (0.7)	1 (0.01)	6.62 (0.60–73.41	11.28 (0.92–137.6	25.29 (0.46–2342)
P for trend			<0.001	<0.001	<0.001			0.151	0.058	0.111

OR: odds ratio; CI: confidence interval.

Note: numbers may not add up to the total numbers due to missing data in some variables.

By design, controls were individually matched to cases for age and district of residence.

Adjusted for age, ethnicity, place of residence, religion and education.

Adjusted for age, ethnicity, place of residence, religion, education, daily fresh fruit and vegetable intake (logarithmic scale), wealth score, monthly income, cumulative use of cigarettes, hookahs and nass, and ever-use of bidi, gutka and alcohol, contact with animals, consumption of salt tea, exposure to passive smoking, family history of cancer.

Table 4.

Association between physical activity and ESCC risk in subjects stratified by occupation, wealth score and monthly income.

Occupational physical activity	Cases	Controls	AOR (95% CIs)	Cases	Controls	AOR (95% CIs)
Farmers				Others ^*
Moderate/sedentary activity	166 (59.7)	463 (81.4)	Referent	370 (87.1)	1043 (95.3)	Referent
Non-strenuous work	28 (10.1)	52 (9.1)	0.98 (0.36–2.63)	13 (3.1)	31 (2.8)	0.49 (0.09–2.24)
Strenuous work	84 (30.2)	54 (9.5)	4.10 (1.69–9.94)	42 (9.9)	20 (1.8)	36.13 (2.85–456.9)
In low-socioeconomic-status group				In high-socioeconomic-status group
Moderate/sedentary activity	372 (73.1)	578 (87.1)	Referent	164 (84.5)	928 (92.9)	Referent
Non-strenuous work	28 (5.5)	36 (5.4)	0.77 (0.24–2.48)	13 (6.7)	47 (4.7)	1.44 (0.29–7.12)
Strenuous work	109 (21.4)	50 (7.5)	5.93 (2.67–13.19)	17 (8.8)	24 (2.4)	47.18 (1.52–146.4)
In group with monthly income of ⩾ INR5000				In group with monthly income of < INR5000
Moderate/sedentary activity	401 (74.1)	877 (88.8)	Referent	135 (83.3)	627 (93.0)	Referent
Non-strenuous work	31 (5.7)	50 (5.1)	1.22 (0.54–2.72)	10 (6.2)	33 (4.9)	0.12 (0.01–3.17)
Strenuous work	109 (20.2)	60 (0.1)	3.41 (1.79–6.47)	17 (10.5)	14 (2.1)	−

CI: confidence interval; AOR = adjusted odds ratio – adjusted for age, ethnicity, place of residence, religion, education, daily fresh fruit and vegetable intake (logarithmic scale), contact with animals, cumulative use of cigarettes, hookahs and nass, and ever-use of bidi, gutka and alcohol.

Other group included all non-farming occupations.

Table 5.

Association between physical activity and ESCC risk, Kashmir Valley, India, in relation to different indicators of SES.

Physical activity	Cases (%)	Controls (%)	Unadjusted OR(95% CI)	Adjusted OR^a (95% CI)	Adjusted OR^b (95% CI)	Adjusted OR^c (95% CI)	Adjusted OR^d (95% CI)	Adjusted OR^e (95% CI)
Sedentary or moderate levels of activity	536 (76.2)	1506 (90.6)	Referent	Referent	Referent		Referent	Referent
High levels of activity	167 (23.8)	157 (9.4)	3.32 (2.52–4.36)	2.53 (1.87–3.43)	2.42 (1.69–3.47)	2.14 (1.48–3.09)	2.14 (1.48–3.09)	2.17 (1.41–3.32)
Intensity of work
Non-strenuous work	41 (5.8)	83 (5.0)	1.48 (0.98–2.23)	1.18 (0.75–1.84)	1.13 (0.67–1.92)	0.99 (0.58–1.69)	0.99 (0.58–1.69)	1.11 (0.57–1.72)
Strenuous work	126 (17.9)	74 (4.6)	5.63 (3.97–7.99)	4.19 (2.87–6.13)	4.15 (2.62–6.55)	3.74 (2.34–5.98)	3.74 (2.34–5.98)	3.64 (2.13–6.20)
Frequency of strenuous work
⩾ 4 days/week	5 (0.9)	7 (0.4)	2.74 (0.76–9.92)	3.49 (0.91–13.48)	2.70 (0.55–13.34)	1.56 (0.29–8.76)	1.56 (0.28–8.76)	2.29 (0.27–19.58)
Daily	120 (18.1)	67 (4.2)	5.80 (3.98–8.43)	5.25 (3.57–7.73)	3.95 (2.42–6.45)	3.67 (2.22–6.07)	3.66 (2.21–6.06)	3.52 (1.97–6.531)
P for trend			<0.001	<0.001	<0.001	<0.001	<0.001	<0.001

OR: odds ratio; CI: confidence interval.

Note: numbers may not add up to the total numbers due to missing data in some variables. By design, controls were individually matched to cases for age, sex and district of residence.

Adjusted for age, ethnicity, place of residence and religion.

Adjusted for age, ethnicity, place of residence, religion, daily fresh fruit and vegetable intake (logarithmic scale), cumulative use of cigarettes, hookahs and nass, and ever-use of bidi, gutka and alcohol, exposure to passive smoking, family history of any cancer, consumption of salt tea and contact with animals.

OR (95% CI) adjusted for education in addition to the covariates in OR^b.

OR (95% CI) adjusted for monthly income in addition to the covariates in OR^c.

OR (95% CI) adjusted for wealth score in addition to the covariates in OR^d.

Table 6.

Association between physical activity and ESCC risk in Kashmir, India, in the subjects stratified on the basis of tobacco consumption.

Non-smokers					Smokers
Occupational physical activity	Cases (%)	Controls (%)	Unadjusted OR^* (95% CI)	Adjusted OR^a (95% CI)	Cases (%)	Controls (%)	Unadjusted OR(95% CI)	Adjusted OR^a (95% CI)
Sedentary/moderate levels of activity	233 (85.9)	801 (95.9)	Referent	Referent	303 (70.1)	705 (85.1)	Referent	Referent
High levels of activity	38 (14.1)	34 (4.1)	3.99 (1.07–9.20)	2.09 (0.29–14.74)	129 (29.9)	123 (14.9)	2.56 (1.79–3.67)	2.12 (1.26–3.56)

OR: odds ratio; CI: confidence interval; AOR: adjusted odds ratio – adjusted for age, ethnicity, place of residence, religion, education, daily fresh fruit and vegetable intake (logarithmic scale), contact with animals, cumulative use of cigarettes, hookahs and nass, and ever-use of bidi, gutka and alcohol.

Discussion

Our study identified an association between OPA and ESCC risk. The risk was stronger in strenuous workers, which was retained in men in a dose-dependent manner. The risk of ESCC was independent of SES and did not persist in non-strenuous workers, suggesting that this association in the very active group is the proxy of strenuous OPA.

Previous epidemiological studies have consistently reported an inverse association of RPA with the risk of different cancers.^25–29 In relation to esophageal cancer, most of these studies are either from the developed world or on EADC. The risk reduction observed in the case of EADC amongst the most physically active people compared to the least active people has been attributed to the reduction in obesity-associated chronic inflammation,³⁰ which plays a critical role in the etiology of EADC.³¹ Conversely, reports on the association of OPA with different cancers have shown mixed results; it has been positively associated with lung cancer,³² but inversely associated with gastric cancer,³³ bladder cancer,³⁴ endometrial cancer, breast cancer, colorectal cancer³⁵ and EADC.^30,36–38 A recent study, based on a large sample size from Montreal Canada, has also reported a positive association of OPA with lung cancer in men.³⁹ Further, in relation with ESCC, four studies are available on OPA; one reported no association,³⁷ while another reported an inverse association⁴⁰ in females only. The latter study,⁴⁰ unlike ours, did not stratify the subjects into strenuous and non-strenuous workers and was conducted on a relatively smaller sample size. Two earlier studies^15,16 reported an elevated risk of ESCC with high levels of physical activity. Therefore, the similar outcome from these three studies, including the current study conducted in three different ethnic groups, cannot be mere chance and warrants a serious approach to develop deeper insight into the subject. The findings from these studies,^15,16 and ours, have strengthened the notion that the risk of cancer can increase with high levels of physical activity.

In the current study, the risk of ESCC increased with the level of OPA. It would be unreasonable to extend the protective effect of RPA, at least through inflammation reduction²⁶ to strenuous workers, who get more exhaustion for longer times and are unlikely to be overweight.⁴¹ Interestingly, none of the participants recruited in the study reported any RPA and, thus making this study unique in its ability to detect an effect of OPA. In the current study, the association is unlikely a manifestation of any known risk factor of ESCC, as we have adjusted extensively with many such confounders.

To explain the biology of the association of ESCC risk with strenuous occupational activities, one of the plausible mechanisms can be linked to high energy demand that warrants excessive aerobic metabolism. During strenuous exercise, muscle oxygen utilization increases,⁴² thus increasing reactive oxygen species (ROS) production, which is over and above the capacity of the antioxidant scavenging system of the cell.⁴³ Hence, during strenuous work, oxidative stress is caused due to ROS and free radicals.^43–45

ROS react with cellular components, carbohydrates, proteins, lipids and DNA, and results in cellular or tissue injury, potentially leading to cancer development.^46–48 For example, DNA oxidation by these reactive species generates 8-hydroxy-2’-deoxyguanosine, a product able to generate mutations in DNA, eventually leading to the development of cancers.⁴⁹ Further, our argument regarding the enhanced risk of ROS linked to strenuous OPA is supported by various recent reports, which have associated oxidative stress with ESCC,⁵⁰ oral squamous cell carcinoma,^51,52 gastric cancer,⁵³ breast cancer,⁵⁴ lung cancer⁵⁵ and pancreatic cancers.⁵⁶ The dose-dependent association of the severity of the OPA with ESCC is in line with our argument of enhanced ROS production during higher working loads on muscles.

Some ROS-initiated reactions that escape enzymatic degradation are normally terminated by chain-breaking antioxidants, including water-soluble ascorbate, vitamin E, ubiquinone and β-carotene.⁵⁷ Fresh fruits and vegetables are good sources of such antioxidants.⁵⁸ In the current study, fresh fruit and vegetable consumption was higher in the controls than in their respective cases. So, high oxidative stress on one hand and low antioxidant supply to the body on the other is more likely to compound the problem.

In the study population, more males are associated with the high-energy-demanding jobs than females, who are more engaged in non-strenuous household activities.⁵⁹ Further, we had a very low representation of female strenuous workers in the current study, and the risk associated with strenuous OPA was retained only in males and, thus, could not be compared with females. However, if the association is causal, this observation could be a contributing link for the male dominance in ESCC cases in general; however, further research in this direction is warranted to understand the exact biology underneath.

Unlike adenocarcinoma of the esophagus, ESSC is considered to be the disease of the poor. People who have low SES are more likely to be involved in jobs demanding strenuous physical activity. Low SES has shown some association with ESCC in this population.⁹ To exclude the possibility of residual confounding, we adjusted the results for several SES indicators alone or in combination; however, the association of ESCC with strenuous OPA persisted in each group, and the effect of indicators of SES did not affect the outcome of the study. Moreover, upon stratification of the subjects based on wealth scores, we observed that ESCC risk persisted in the subjects irrespective of their wealth scores. These observations support our argument that the association of strenuous OPA with ESCC risk is independent of wealth score.

The maximum representation of ESCC cases in the current study was from rural areas, where most people are occupied in farming and farming-related occupations. Upon classifying the subjects into farmers and other professions (the ‘other’ group included all non-farming occupations), the ESCC risk persisted in the subjects that were used to strenuous work in both groups.

Histological verification of ESCC, relatively large sample size and adjustment of the results for multiple potential confounding factors and SES indicators are the major strengths of this study. Information provided by a subject on strenuous physical activity is unlikely to be biased, as job or occupation details are less forgettable. Further, strenuous physical activity is not an established risk factor for ESCC, so it is unlikely that participants would preferentially misreport activity levels at work.

Like other case–control studies with retrospective exposure assessments, recall and interviewer bias may also be a concern in this study. However a limited number of interviewers interviewed the participants, and the nature of a subject’s job/occupation is less forgettable. Many important variables with regards to association with OPA were missing and, thus, were not adjusted for. These included height, weight, body mass index (BMI), factors associated with health, disease and physical fitness, exposures to occupational hazards, etc. More numbers of cases in the study population were from rural areas engaged in farming and farming-related activities, rendering them exposed to many occupational hazards including fungicides, pesticides and herbicides.¹¹ Strenuous workers get more exhaustion for longer times, and are unlikely to be overweight.⁴¹ Unlike EADC, BMI has been inversely associated with ESCC with unclear underlying mechanisms.⁶⁰ Therefore, residual confounding of BMI and exposure to occupational hazards cannot be ruled out in the current study as they might not be included in the adjustments due to missing information. Further, this case–control study was not designed as an occupational epidemiologic study; we were not able to validate the measures of physical activity as in IPAQ or metabolic equivalents of task-hours. The cases and controls were not matched on occupation and can result in a selection bias, and seasonal variation in job and other activities were not considered. Other information on the indicators that influence sweating and heart rate are not available. The details of total physical activity (non-occupation-related, such as from household chores, etc.) are missing. Thus, the study needs to be reproduced, working on these limitations.

In conclusion, the study showed that strenuous OPA is associated with the increased risk of ESCC, in a dose-dependent manner in males. However, this association requires further validation by additional occupational epidemiological studies.

Footnotes

Acknowledgements

The authors thank all the participants for volunteering in the study. The authors also thank Abdul Rouf Banday for his critical comments and review during the preparation of the manuscript.

Author contributions

ND, PB, MTR, MML and GNL designed the study.

IAS, GAB, RR, NN and MM recruited subjects.

IAS and ND analyzed the data.

IAS wrote the first draft of the manuscript.

All authors reviewed and approved the final draft of the paper.

Availability of data and materials

The datasets generated and analyzed during the current study are available from the corresponding author.

Declaration of conflicting interests

None declared.

Ethical approval

This study was reviewed and approved by the Institutional Ethics Committee of Sheri Kashmir Institute of Medical Sciences Srinagar J&K India. File number: SIMS 131 IEC 2008-03.

Funding

This study was supported by extramural grants from the Indian Council of Medical Research (ICMR), New Delhi, India (grant number 5/13/37/2007/-NCD-III), and the Department of Science and Technology, Government of India (grant number SR/SO/HS-07/2009). IAS was awarded Senior Research Fellowship by ICMR (grant number 3/2/2137/2012/NCD-III).

ORCID iD

Nazir Ahmad Dar

Informed consent

Written informed consent was obtained from all subjects for their anonymized information to be published in this article.

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