Case Control Study Open Access
Copyright ©The Author(s) 2016. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Gastrointest Oncol. Feb 15, 2016; 8(2): 207-214
Published online Feb 15, 2016. doi: 10.4251/wjgo.v8.i2.207
Risk factors for the development of colorectal carcinoma: A case control study from South India
Santhana Krishnan Iswarya, Kariyarath Cheriyath Premarajan, Sitanshu Sekhar Kar, Departments of Preventive and Social Medicine, Jawaharlal Institute of Postgraduate Medical Education and Research, Pondicherry 605006, India
Sathasivam Suresh Kumar, Vikram Kate, Department of Surgery, Jawaharlal Institute of Postgraduate Medical Education and Research, Pondicherry 605006, India
Author contributions: Iswarya SK, Premarajan KC and Kate V designed the research; Iswarya SK collected data; Iswarya SK, Kar SS and Kumar SS analyzed the data and prepared the manuscript; Premarajan KC, Kumar SS and Kate V corrected and revised the manuscript; and Kate V is the guarantor.
Institutional review board statement: The study was reviewed and approved by the JIPMER Institute Human Ethics Committee.
Informed consent statement: All patients gave informed written consent to participate in the study before enrollment.
Conflict-of-interest statement: No benefits in any form have been received or will be received from any party related directly or indirectly to the subject of this article.
Data sharing statement: Technical appendix, statistical code and dataset available with the corresponding author at drvikramkate@gmail.com.
Open-Access: This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
Correspondence to: Vikram Kate, MS, FRCS (Eng.), FRCS (Ed.), FRCS (Glasg.), PhD, MAMS, FIMSA, MASCRS, FACS, FACG, MFSTEd, Professor of General and Gastrointestinal Surgery, Department of Surgery, Jawaharlal Institute of Postgraduate Medical Education and Research, Temple Road, Dhanvantri Nagar, Pondicherry 605006, India. drvikramkate@gmail.com
Telephone: +91-413-2296741 Fax: +91-413-2272066
Received: June 6, 2015
Peer-review started: June 8, 2015
First decision: August 26, 2015
Revised: September 15, 2015
Accepted: November 13, 2015
Article in press: November 13, 2015
Published online: February 15, 2016
Processing time: 240 Days and 21 Hours

Abstract

AIM: To study the association of colorectal carcinoma (CRC) with diet, smoking, alcohol, physical activity, body mass index, family history and diabetes.

METHODS: All consecutive patients with CRC confirmed by histopathology diagnosis were included. Age (± 5 years) and gender matched controls were selected among the patients admitted in surgery ward for various conditions without any co-existing malignancy. Food frequency questionnaire (FFQ) was developed and validated after pretesting by investigator trained in data collection techniques. Cases and controls were interviewed ensuring privacy, in similar interview setting, with same duration of time for both cases and controls without any leading question. Biological variables like family history of CRC in first degree relatives, history of diabetes mellitus; behavioral factors like tobacco use both smoking and smokeless form, alcohol consumption and physical activity were recorded. Dietary details were recorded using a FFQ consisting 29 food items with seven categories. Analysis was done using appropriate statistical methods.

RESULTS: Ninety-four histopathologically confirmed cases of CRC and equal number of age and gender matched controls treated over a period of two years were studied. Age distribution, mean age, male to female ratio, education level and socioeconomic status were similar in cases and controls. Intake of food items was categorized into tertile due to skewed distribution of subjects as per recommended cut off for consumption of food item. On univariate analysis red meat [OR = 7.4 (2.935-18.732)], egg [OR = 5.1 (2.26-11.36)], fish, fried food and oil consumption were found to be risk factors for CRC. On multivariate analysis red meat consumption of more than 2-3 times a month (OR = 5.4; 95%CI: 1.55-19.05) and egg consumption of more than 2-3 times a week (OR = 3.67; 95%CI: 1.23-9.35) were found to be independent risk factors for the development of CRC.

CONCLUSION: Egg and red meat consumption found to be independent risk factors for CRC. Smoking, alcohol, physical activity and family history were not associated with increased risk.

Key Words: Dietary factors, Smoking, Rectal cancer, Red meat, Colorectal malignancy

Core tip: In this hospital based case control study, egg consumption of 2-3 times a week and red meat consumption of 2-3 times a month were found to be independent risk factors for the development of colorectal carcinoma. On the other hand smoking, alcohol, physical activity, diabetes and family history were not associated with an increased risk. There was no conclusive evidence to suggest that fruits and vegetable consumption has protective effect on colorectal carcinoma. Since red meat and egg had an increased risk, the community needs to be educated to reduce the consumption of red meat such as mutton and egg.



INTRODUCTION

Colorectal cancer (CRC) is one amongst the leading cause of cancer related morbidity and mortality. CRC share 10% of the total cancers worldwide and accounts for 8% of all cancer related mortality; caused 608000 deaths worldwide[1,2]. In India data from population based cancer registry at Bangalore, Chennai and Delhi showed significantly increased incidence of CRC from 1982-2006[3].

Epidemiological studies have estimated that up to 70%-80% of CRCs could be ascribed to dietary, environmental and lifestyle factors; suggesting majority of the risk factors are modifiable[4]. It has been demonstrated that diet significantly influences the risk of developing CRC, and up to 70% reduction in the cancer burden can be achieved by changing the food habits[5]. Many epidemiological studies across the globe have tried to evaluate the role of dietary and life style factors in the development of CRC, however a fair share of controversies exist among the observations[6]. Majority of the studies that investigated the role of high vegetable and fruit diet failed to prove any significant reduction in the incidence of CRC.

For a long time, it was believed that low meat intake and high fiber vegetarian diet by Indian population is the reason for the low incidence of CRC in India. It was found that only two studies have been reported in literature from India regarding factors associated with CRC[7,8]. Identifying the factors associated with decreased CRC incidence among Indian population may help in the prevention of CRC. Hence an attempt was made to study these factors through a case control study. The objective of the study was to find the association of CRC with life style variables (diet, smoking, alcohol, physical activity) and Biological Variables [body mass index (BMI), family history of CRC in 1st -degree relatives, history of diabetes mellitus].

MATERIALS AND METHODS

The study was conducted in Department of Preventive and Social Medicine in collaboration with department of Surgery in a tertiary care referral and research institute of India. This study was conducted from period of two years. This study was approved by the Institute Ethics Committee. The nature, methodology of the study was explained to the patient and informed consent was obtained. All the information collected was kept confidential and patient was given full freedom to withdraw from the study at any point during the study. All provisions of the Declaration of Helsinki were followed in this study.

All consecutive patients with confirmed histopathology diagnosis were included. Histopathology was done either pre-operatively or postoperatively. Diagnosis of CRC was confirmed by per-rectal sigmoidoscopic or endoscopic biopsy. In case where resection for colorectal malignancy was done as an emergency surgical procedure, the diagnosis was confirmed post operatively. CRC patients with co-existing malignancy were excluded. Age (± 5 years) and gender matched controls were selected among the patients admitted in Surgery ward for various conditions like inguinal hernia, varicose veins, necrotizing fasciitis and diabetic foot.

Patients with co-existing malignancies, familial adenomatous polyposis and patients admitted with any abdominal disorders were excluded from the study. Controls were selected within one week after selecting the case. When more than one control was eligible then control was selected by simple random methods using lots. During initial phase of the study, food frequency questionnaire (FFQ) was developed and face validation was carried out by circulating among the faculty who were involved in the study. Pre-testing was done among 10 patients admitted in the surgery ward by investigator trained in data collection techniques. It helped to estimate the average time taken for questionnaire administration, examination and to check for comprehensibility of participants to the questions.

After pre-testing of questionnaire necessary modifications were carried out. After obtaining informed consent cases and controls were interviewed ensuring privacy, in similar interview setting, with same duration of time for both cases and controls without any leading question. Average time taken for each interview was around 45 min. Anthropometric measurements was taken at the end of the interview. Pre-tested questionnaire which elicited information on demographic parameters like name, age, gender; Social variables like education, occupation, income, presenting complaints; biological variables like family history of CRC in first degree relatives, history of diabetes mellitus; behavioral factors like tobacco use both smoking and smokeless form, alcohol consumption and physical activity.

The alcohol consumption among study participants was measured and classified as per the World Health Organization STEPwise approach to surveillance of non-communicable diseases. The STEPS questionnaires used for the study are available in the internet from: http://www.who.int/ncd_surviellance/en/steps_framework_dec03.pdf. The alcohol consumption pattern of drinkers (amount, type and frequency) was noted and converted in terms of average alcohol consumed in grams per day. These were further classified as abstainers (who never consumed alcohol in past 12 mo), grade 1 (< 39.9 g/d), grade 2 (40-59.9 g/d) and grade 3 (> 60 g/d). The physical activity was measured using international physical activity questionnaire-short version. Metabolic equivalent (MET) levels for walking, moderate and vigorous intensity activities were taken as 3.3, 4.0 and 8.0. The activities were measured separately (MET level × minutes of activity/day × days per week) and expressed as total MET min/wk. Based on the total scores, study participants were categorized in to low (< 600 MET min/wk), moderate (600-3000 MET min/wk) and high (> 3000 MET min/wk) level of physical activity.

Dietary details were recorded using a FFQ consisting 29 food items with seven categories (never or hardly ever, once a month, 2-3 times a month, once a week, 2-3 times a week, 4-6 times a week, once a day or more) for egg, chicken, mutton, beef, pork, fruits, vegetables, fried foods, type of oil, type of food, tea, coffee; anthropometric measurements including weight, height, hip circumference, waist circumference also were recorded.

Sample size was calculated using n Master software 2.0 for matched case control study, taking exposure in controls for non-vegetarian food as 58% and OR 3.38 at 95%CI, 80% power the minimum sample size was 93[9].

Analysis was done using SPSS version 20[10]. Socio-demographic details and frequency of food intake were expressed in proportions. Univariate analysis for categorical variables (diet, smoking, alcohol, physical activity, BMI, history of diabetes, family history) were done using χ2 test. Seven frequencies of food item intake were categorized into tertile. Tertile1 corresponds to lowest frequency of intake and tertile 3 corresponds to highest frequency of intake. OR was calculated for highest tertile of intake relative to lowest tertile by logistic regression. Factors having P value < 0.05 in univariate analysis were included as parameter for multivariate analysis using logistic regression. Results of multivariate analysis were given as OR with 95%CI. All P values were two tailed and significant when values were less than 0.05.

RESULTS

A total of 94 cases and controls were included in the study. The mean age group of cases and controls were 54.1 ± 11.5 years and 55 ± 11.8 years respectively. Age distribution of cases and controls were in the range of 17-78 years. There was almost equal distribution of males and females 48.9% and 51.1% respectively among the study subjects (Table 1). Around 39.4% cases and 35.1% of controls never attended school. In both cases and controls more than 50% of them belonged to class V socio economic status.

Table 1 Socio demographic details of study population, n (%).
VariableCasesControls
Age (yr)
< 409 (9.6)7 (7.4)
40-4921 (22.3)18 (19.1)
50-5928 (29.8)29 (30.9)
60-6930 (31.9)32 (34)
≥ 706 (6.4)8 (8.5)
Educational status
Never attended school37 (39.4)33 (35.1)
1-423 (24.5)34 (36.2)
5-715 (16)10 (10.6)
8-1014 (14.9)9 (9.6)
11-121 (1.1)6 (6.4)
Graduation4 (4.3)2 (2.1)
Occupation
Non worker23 (24.5)19 (20.2)
Skill I44 (46.8)59 (62.8)
Skill II25 (26.6)16 (17)
Skill III2 (2.1)0
PCI in indian rupees/mo
Class I > 44001 (1.1)0
Class II 2200-43991 (1.1)2 (2.1)
Class III 1320-21995 (5.3)6 (6.4)
Class IV 660-131934 (36.2)38 (40.4)
Class V < 66053 (56.4)48 (51.1)

The distribution of subjects as per recommended cut off for consumption of food item was much skewed as shown in (Table 2). Among cases 22.3% consumed egg 2-3 times a week compared to only 8.5% among the controls. In cases about one-fourth 24.5% never or hardly ever consumed mutton compared to 46.8% in controls. Beef consumption was reported to be low among both cases and controls, 72.3% of cases and 86.2% of controls never or hardly ever consumed beef. Similarly more than 80% of cases and controls never or hardly ever consumed pork. Majority of cases 78.7% and controls 89.4% consumed vegetables once a day.

Table 2 Frequency of food intake among cases and controls, n (%).
Food itemNever or hardly everOnce a month2-3 times/moOnce a week2-3 times/wk4-6 times/wkOnce a dayTotal
EggCase7 (7.4)17 (18.1)6 (6.4)28 (29.8)21 (22.3)7 (7.4)8 (8.5)94
Control8 (8.5)36 (38.3)10 (10.6)27 (28.7)8 (8.5)-5 (5.3)94
ChickenCase13 (13.8)31 (33)9 (9.6)36 (38.3)5 (5.3)--94
Control12 (12.8)45 (47.9)14 (14.9)19 (20.2)4 (4.3)--94
MuttonCase23 (24.5)40 (42.6)4 (4.3)25 (26.6)1 (1.1)1 (1.1)-94
Control44 (46.8)42 (44.7)3 (3.2)4 (4.3)1 (1.1)--94
FishCase26 (27.7)49 (52.1)2 (2.1)6 (6.4)10 (10.6)1 (1.1)-94
Control27 (28.7)61 (64.9)1 (1.1)2 (2.1)1 (1.1)2 (2.1)-94
BeefCase68 (72.3)1 (1.1)1 (1.1)18 (19.1)6 (6.4)--94
Control81 (86.2)6 (6.4)-7 (7.4)---94
PorkCase81 (86.2)9 (9.6)1 (1.1)2 (2.1)1 (1.1)--94
Control87 (92.6)5 (5.3)-2 (2.1)---94
Fried foodsCase3 (3.2)32 (34.0)6 (6.4)35 (37.2)18 (19.1)--94
Control5 (5.3)45 (47.9)14 (14.9)28 (29.8)2 (2.1)--94
FruitsCase32 (34.0)37 (39.4)7 (7.4)6 (6.4)5 (5.3)3 (3.2)4 (4.3)94
Control36 (38.3)23 (24.5)14 (14.9)13 (13.8)3 (3.2)-5 (5.3)94
VegetablesCase----13 (13.8)7 (7.4)74 (78.7)94
Control----2 (2.1)8 (8.5)84 (89.4)94
CoffeeCase81 (86.2)----13 (13.8)94
Control87 (92.6)-----7 (7.4)94
TeaCase20 (21.2)----74 (78.7)94
Control11 (11.7)-----83 (88.3)94

As distribution of subjects as per recommended cut off for consumption of food item was much skewed, intake of food items was categorized into tertile. The frequency cut-off into tertile is not same for all the food items. For certain food items (beef, pork, vegetables, tea, coffee) ranking into tertile was not possible due to its skewed distribution. Univariate logistic regression analysis was done considering these tertile groups as shown in (Table 3). It was observed that consumption of egg for more than 2-3 times a week increases the risk of getting CRC by five times [OR = 5.1 (2.26-11.36)] compared to those who never or hardly consume egg. Mutton consumption of more than 2-3 times a month increases the risk of CRC by 7 times [OR = 7.4 (2.935-18.732)] compared to those never or hardly consumes mutton. Consuming fish and fried foods more than 2-3 times a month increases the risk for CRC. Coffee consumption was not significantly associated with CRC [OR = 1.95 (0.76-5.43)]. Similarly Tea consumption also did not show any significant association with CRC in the present study [OR = 0.49 (0.22-1.70)].

Table 3 Colorectal carcinoma risk associated with individual dietary item.
Food itemAdjusted OR (CI)P value
EggTertile 1Never or hardly ever1
Tertile 2Once a month1.6 (0.85-3.33)0.133
Tertile 3> 2-3 times a week5.1 (2.26-11.36)0.001
ChickenTertile 1Never or hardly ever1
Tertile 2Once a month0.6 (0.25-1.51)0.297
Tertile 3Once a week1.6 (0.64-4.19)0.297
MuttonTertile 1Never or hardly ever1
Tertile 2Once a month1.8 (0.93-3.45)0.070
Tertile 3More than 2-3 times a month7.4 (2.93-3.45)0.001
FishTertile 1Never or hardly ever1
Tertile 2Once a month0.8 (0.44-1.60)0.588
Tertile 3More than 2-3 times a month3.2 (1.13-9.53)0.028
BeefTertile 1---
Tertile 2Never or hardly ever1
Tertile 3More than once a month2.3 (0.13-4.99)0.237
FruitsTertile 1Never or hardly ever1
Tertile 2Once a month1.8 (0.89-3.64)0.099
Tertile 3More than 2-3 times a month0.8 (0.39-1.68)0.540
VegetablesTertile 12-3 times a week1
Tertile 2Once a day0.4 (0.19-1.00)0.050
Tertile 3---
Fried foodsTertile 1Never or hardly ever1
Tertile 2Once a month0.61 (0.21-1.74)0.350
Tertile 32-3 times a month2.52 (1.35-4.70)0.004

Compared to never smokers, subjects who smoked < 10 pack years, 10-20 pack years and > 20 pack years were not at increased risk for CRC. Alcohol consumption of < 39.9 g/d, 40-59.9 g/d and > 60 g/d was not associated with increased risk for CRC compared to non-users. High (3000 METs/wk) and moderate (600-3000 METs/wk) level of physical activity was not protective for CRC. BMI greater than 25 is not associated with CRC risk. History of diabetes was not significantly associated with CRC risk (Table 4). Multivariate logistic regression results (Table 5) for those factors found to be statistically significant in univariate analysis (mutton, egg, fish, fried foods and type of oil) showed egg and mutton as independent risk factor.

Table 4 Association of variables with colorectal carcinoma, n (%).
VariableCasesControlsOR (CI)
Type of oil
Refined29 (30.9)22 (23.4)1
Groundnut15 (16)42 (44.7)0.271 (0.12-0.61)
Palm50 (53.2)30 (31.9)1.264 (0.62-2.59)
Type of food
Moderate spicy73 (77.7)82 (87.2)1
Very spicy21 (22.3)12 (12.8)1.97 (0.91-4.28)
Smoking status
Non-smoker74 (78.7)75 (79.7)1
< 10 pack years3 (3.19)5 (5.31)0.60 (0.14-2.63)
10-20 pack years5 (5.31)10 (10.6)0.50 (0.16-1.55)
> 20 pack years12 (12.8)4 (4.3)3.04 (0.93-9.85)
Alcohol use
Non users68 (72.3)74 (78.7)1
Grade I (< 39.9 g/d)19 (20.2)10 (10.6)2.06 (0.89- 4.75)
Grade II (40-59.9 g/d)4 (4.2)6 (6.3)0.72 (0.19-2.68)
Grade III (> 60 g/d)3 (3.2)4 (4.2)0.81 (0.17-3.78)
Physical activity (METs/wk)
Low (< 600)18 (19.1)24 (25.5)1
Moderate (600-3000)51 (54.3)44 (46.8)1.54 (0.74-3.21)
High (> 3000)25 (26.6)26 (27.7)1.28 (0.56-2.91)
BMI (kg/m2)
< 18.5 (underweight)19 (20.2)10 (10.6)1
18.5-22.99 (normal)47 (50)57 (60.6)0.43 (0.18-1.02)
23-24.99 (over weight)14 (14.9)17 (18.1)0.43 (0.15-1.22)
≥ 25 (obese)14 (14.9)10 (10.6)0.73 (0.24-2.24)
Diabetes mellitus
No73 (53.3)67 (46.7)1
yes21 (41.2)30 (58.8)1.62 (0.85-3.12)
Table 5 Factors independently associated with colorectal carcinoma.
Food itemAdjusted OR (CI)P value
MuttonTertile 1Never or hardly ever1
Tertile 2Once a month2.62 (0.08-6.33)0.137
Tertile 3> 2-3 times a month5.41 (1.55-19.05)0.008
EggTertile 1Never or hardly ever1
Tertile 2Once a month1.54 (0.63-3.70)0.340
Tertile 3> 2-3 times a week3.67 (1.23-9.35)0.013
Fried foodsTertile 1Never or hardly ever1
Tertile 2Once a month0.76 (0.22-2.54)0.655
Tertile 3> 2-3 times a month2.03 (0.95-4.43)0.060
FishTertile 1Never or hardly ever1
Tertile 2Once a month0.02 (0.08-0.58)0.195
Tertile 3> 2-3 times a month0.39 (0.09-1.62)0.237
Type of oilRefinedNA1
Ground nutNA0.4 (0.15-1.00)0.068
PalmNA1.6 (0.75-4.04)0.240
DISCUSSION

Though population based cancer registries showed a statistically significant increase in the incidence of CRC in India from 1982-2006, very few studies have been done in India to document the association of modifiable risk factors with CRC. The present study attempted to identify the modifiable risk factors so that appropriate preventive measures can be planned. Red meat consumption more than 2-3 times a month found to be an independent risk factor in multivariate regression analysis and increased the odds of developing CRC by 5.41 (1.55-19.05) times compared to those never or hardly consume. This was similar to study by Nayak et al[7] which reported beef consumption more than once a week has increased risk compared to those who do not consume beef [OR = 4.25 (2.02-8.94)]. A study from Uruguay[9] reported a positive association between CRC and high intake of red meat with OR = 3.38 (2.37-6.20). Similarly Singh et al[11] reported red meat intake more than once a week increased the risk compared to non-consumers [RR = 1.90 (1.16-3.11)].

In the western studies red meat consumption included beef, pork and mutton. However, in present study population due to cultural practices and beliefs beef and pork consumption were minimal. Subjects who consumed egg more than 2-3 times a week had 3.6 (1.23-9.35) times higher risk compared to those who never or hardly ever consume egg. This was similar to the study[12] which reported consumption of egg more than 2-3 times/wk is associated with increased risk of CRC compared to those who never or hardly consume egg [OR = 2.95 (1.75-5)]. In the present study fish consumption more than 2-3 times a month is associated with increased risk for CRC in univariate analysis. In contrast Nayak et al[7] from Kerala showed 20% decreased risk of CRC with consumption of fish with every meal [OR = 0.32 (0.13-0.98)]. European study reported fish consumption more than 80 g/d was inversely associated with CRC compared to those consuming < 10 g/d [OR = 0.69 (0.54-0.88)][13]. Discrepancy between present study finding and other studies could be due to difference in type of fish consumed, amount of fish consumed, method of cooking and method of preservation.

Fruits and vegetable consumption was not found to be protective for CRC, similar to the findings reported in studies from Western countries[14-16]. Frequent intake of fried food a proxy variable for high fat intake was associated with CRC [OR = 2.52 (1.35-4.70)] in univariate analysis but it was not an independent risk factor. In contrast studies reported consuming deep fried foods more than once a month was not associated with increased risk[17,18]. Coffee consumption was not significantly associated with CRC [OR = 1.95 (0.76-5.43)]. A meta-analysis by Je et al[19] in 2008 showed no significant association between coffee consumption and colorectal cancer [RR = 0.91 (0.81-1.02)], nevertheless; studies have also shown protective effect of coffee in the development of CRC. Kato et al[20] in Japan found daily coffee consumption had protective effect on both colon and rectal carcinoma compared with the non drinkers with RR = 0.43 (0.25-0.73) and RR = 0.53 (0.27-1.03), respectively. Reasons for varying results across studies are due to difference in type of coffee, serving size, brewing method and also cutoffs for high and low exposure categories varies between studies. Tea consumption did not show any significant association with CRC in the present study [OR = 0.49 (0.22-1.70)]. Similar findings were found by Nayak et al[7] where highest quartile of tea consumption has not shown any risk difference compared to lowest quartile with OR = 1.03 (0.62-1.71). In 2005, Michels et al[14] from United States reported that tea consumption of more than 5 cups per day was not significantly associated with CRC [HR = 1.01 (0.83-1.22)].

Smoking and alcohol use was not associated with CRC in contrast to increased risk reported in few studies[21-25]. As smoking and alcohol were considered as undesirable behavior in community people tend to under report the use due to social desirability bias[26]. This could be the reason for no association in the present study. High level of physical activity was not associated with decreased risk for CRC compared to low level of physical activity as reported in other studies[27,28]. BMI was not significantly associated with CRC; in contrast studies reported high BMI increased risk for CRC[29,30]. This could be due to underlying limitation of hospital based case-control study, where cases are ill and admitted to the hospital in late stage of disease. By the time patients seek medical attention they would have lost considerable amount of weight. The weight recorded at the time of admission may not find the true association.

Selection of appropriate controls is crucial to establish the true association between exposure (diet, smoking, alcohol, physical activity) and outcome (CRC). Selection of controls remains a major concern when designing a case-control study due to the issues involved in the internal validity and cost. Scientifically there is scope for introducing bias (selection bias and information bias) while selecting hospital based controls[31]. However there is several advantage of selecting hospital controls such as feasibility, cost, travel time and better recall among hospital controls. Validation studies conducted by Li et al[32], González et al[33], Inoue et al[34] showed that hospital based controls elicit similar information to community controls in assessment of dietary risk factors. Hospital controls are preferred in a hospital based case-control study in view of the issues of practicability. It also reduces the cost involved in the travel and decreases the time taken for face-to-face interviews at field. It has also been demonstrated that the capacity to recall and report the exposures are better in those who are actively seeking health care advise than the members randomly selected from the population[35].

Since it measures long term, average and habitual dietary intake; FFQ as a mean of dietary assessment have been found appropriate in many nutritional and epidemiological studies[36]. FFQ captures pattern of food consumption over a period of time ranging from months to years. Pandey et al[37] from India reported FFQ had good correlation (0.8) with 5 d diet record and was reproducible. The quantity of food consumed is considered an important factor in estimating the dietary intake of an individual; however, the frequency rather than the serving size has been found to be a better contributor to the variance in the intake of most foods.

Primary limitation of the study was dietary items were not quantified. Though efforts were taken to minimize the recall bias, change in dietary pattern of cases after development of symptoms might have led to biased reporting of their diet.

In conclusion, this hospital based case control study showed egg consumption of 2-3 times a week and mutton consumption 2-3 times a month as independent risk factor. On other hand smoking, alcohol, physical activity, history of diabetes and family history were not associated with increased risk for CRC and no conclusive evidence to suggest fruits and vegetable consumption as protective factor. Cohort study is required to assess the risk associated with commonly consumed dietary items in a given population.

As it was found that persons consuming red meat (mutton) had an increased risk of developing CRC (OR = 5.4), the community needs to be educated to reduce the consumption of red meat such as mutton, so that they can minimize their risk for developing CRC. Similarly, egg consumption was found to increase the odds of developing CRC (OR = 3.6), people especially adults need to be advised to reduce the egg consumption.

ACKNOWLEDGMENTS

We thank the entire faculty who helped in validation and pretesting of the food frequency questionnaire. We also thank all the medical staff who helped in interviewing the patients.

COMMENTS
Background

Epidemiological studies have shown that significant proportion of colorectal cancer (CRC) incidence could be ascribed to dietary, environmental and lifestyle factors; suggesting majority of the risk factors are modifiable. Regional variation in the dietary and social habit could play a vital role in the causation of CRC and may be responsible for the geographical variations in the occurrence of CRC.

Research frontiers

For a long time, it was believed that low meat intake and high fiber vegetarian diet by Indian population is the reason for the low incidence of CRC in India. Only two studies have been reported in literature from India regarding factors associated with CRC and more research studies are require to evaluate or to confirm the risk factors. Identifying the factors associated with decreased CRC incidence among Indian population may help in the primary prevention of CRC across the globe.

Innovations and breakthrough

This study found that red meat consumption of more than 2-3 times a month egg consumption of more than 2-3 times a week are independent risk factors for the development of CRC. Contrary to common belief the study showed no association between CRC and smoking, alcohol consumption, physical activity, body mass index or diabetes. Consumption of coffee or tea were also not associated with CRC.

Applications

As it was found that persons consuming red meat (mutton) had an increased risk of developing CRC (OR = 5.4), the community needs to be educated to reduce the consumption of red meat such as mutton, so that they can minimize their risk for developing CRC. Similarly, egg consumption was found to increase the odds of developing CRC (OR = 3.6), people especially adults need to be advised to reduce the egg consumption.

Peer-review

This is a good case control study taken a very relevant and significant problem to be studied. The article evaluated important life style and dietary factors for the possible relationship with colorectal cancer in South Indian population. The study showed significant association between red meat and egg consumption and certainly gives better insight and understandings about the other risk factors including smoking, alcohol consumption, body mass index, diabetes and physical activity, etc.

Footnotes

P- Reviewer: Giraldi G S- Editor: Gong ZM L- Editor: A E- Editor: Lu YJ

References
1.  Ferlay J, Shin HR, Bray F, Forman D, Mathers C, Parkin DM. Estimates of worldwide burden of cancer in 2008: GLOBOCAN 2008. Int J Cancer. 2010;127:2893-2917.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 11128]  [Cited by in F6Publishing: 11649]  [Article Influence: 896.1]  [Reference Citation Analysis (4)]
2.  Jemal A, Bray F, Center MM, Ferlay J, Ward E, Forman D. Global cancer statistics. CA Cancer J Clin. 2010;61:69-90.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 23762]  [Cited by in F6Publishing: 25229]  [Article Influence: 1940.7]  [Reference Citation Analysis (6)]
3.  Swaminathan R, Shanta V, Ferlay J, Balasubramanian S, Bray F, Sankaranarayanan R. Trends in cancer incidence in Chennai city (1982-2006) and statewide predictions of future burden in Tamil Nadu (2007-16). Natl Med J India. 2011;24:72-77.  [PubMed]  [DOI]  [Cited in This Article: ]
4.  Franco A, Sikalidis AK, SolísHerruzo JA. Colorectal cancer: influence of diet and lifestyle factors. Rev EspEnferm Dig. 2005;97:432-448.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 12]  [Cited by in F6Publishing: 13]  [Article Influence: 0.7]  [Reference Citation Analysis (0)]
5.  Willett WC. Diet and cancer: an evolving picture. JAMA. 2005;293:233-234.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 91]  [Cited by in F6Publishing: 101]  [Article Influence: 5.3]  [Reference Citation Analysis (0)]
6.  Mohandas KM. Colorectal cancer in India: controversies, enigmas and primary prevention. Indian J Gastroenterol. 2011;30:3-6.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 56]  [Cited by in F6Publishing: 45]  [Article Influence: 3.5]  [Reference Citation Analysis (0)]
7.  Nayak SP, Sasi MP, Sreejayan MP, Mandal S. A case-control study of roles of diet in colorectal carcinoma in a South Indian Population. Asian Pac J Cancer Prev. 2009;10:565-568.  [PubMed]  [DOI]  [Cited in This Article: ]
8.  Ganesh B, Talole SD, Dikshit R. A case-control study on diet and colorectal cancer from Mumbai, India. Cancer Epidemiol. 2009;33:189-193.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 16]  [Cited by in F6Publishing: 26]  [Article Influence: 1.7]  [Reference Citation Analysis (0)]
9.  Aune D, De Stefani E, Ronco A, Boffetta P, Deneo-Pellegrini H, Acosta G, Mendilaharsu M. Meat consumption and cancer risk: a case-control study in Uruguay. Asian Pac J Cancer Prev. 2009;10:429-436.  [PubMed]  [DOI]  [Cited in This Article: ]
10.  IBM Corp IBM SPSS Statistics for Windows, Version 20.0. Armonk, NY: IBM Corp 2011; .  [PubMed]  [DOI]  [Cited in This Article: ]
11.  Singh PN, Fraser GE. Dietary risk factors for colon cancer in a low-risk population. Am J Epidemiol. 1998;148:761-774.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 203]  [Cited by in F6Publishing: 216]  [Article Influence: 8.3]  [Reference Citation Analysis (0)]
12.  SoleraAlbero J, TárragaLópez PJ, CarbayoHerencia JA, López Cara MA, Celada Rodríguez A, Cerdán Oliver M, OcañaLópez JM. [Influence of diet and lifestyle in colorectal cancer]. Rev EspEnferm Dig. 2007;99:190-200.  [PubMed]  [DOI]  [Cited in This Article: ]
13.  Norat T, Bingham S, Ferrari P, Slimani N, Jenab M, Mazuir M, Overvad K, Olsen A, Tjønneland A, Clavel F. Meat, fish, and colorectal cancer risk: the European Prospective Investigation into cancer and nutrition. J Natl Cancer Inst. 2005;97:906-916.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 580]  [Cited by in F6Publishing: 491]  [Article Influence: 25.8]  [Reference Citation Analysis (0)]
14.  Michels KB, Edward Giovannucci KJ, Rosner BA, Stampfer MJ, Fuchs CS, Colditz GA, Speizer FE, Willett WC. Prospective study of fruit and vegetable consumption and incidence of colon and rectal cancers. J Natl Cancer Inst. 2000;92:1740-1752.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 305]  [Cited by in F6Publishing: 318]  [Article Influence: 13.3]  [Reference Citation Analysis (0)]
15.  van Duijnhoven FJ, Bueno-De-Mesquita HB, Ferrari P, Jenab M, Boshuizen HC, Ros MM, Casagrande C, Tjønneland A, Olsen A, Overvad K. Fruit, vegetables, and colorectal cancer risk: the European Prospective Investigation into Cancer and Nutrition. Am J Clin Nutr. 2009;89:1441-1452.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 209]  [Cited by in F6Publishing: 216]  [Article Influence: 14.4]  [Reference Citation Analysis (0)]
16.  Koushik A, Hunter DJ, Spiegelman D, Beeson WL, van den Brandt PA, Buring JE, Calle EE, Cho E, Fraser GE, Freudenheim JL. Fruits, vegetables, and colon cancer risk in a pooled analysis of 14 cohort studies. J Natl Cancer Inst. 2007;99:1471-1483.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 188]  [Cited by in F6Publishing: 196]  [Article Influence: 11.5]  [Reference Citation Analysis (0)]
17.  Lee SA, Shu XO, Yang G, Li H, Gao YT, Zheng W. Animal origin foods and colorectal cancer risk: a report from the Shanghai Women’s Health Study. Nutr Cancer. 2009;61:194-205.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 70]  [Cited by in F6Publishing: 69]  [Article Influence: 4.6]  [Reference Citation Analysis (0)]
18.  Galeone C, Talamini R, Levi F, Pelucchi C, Negri E, Giacosa A, Montella M, Franceschi S, La Vecchia C. Fried foods, olive oil and colorectal cancer. Ann Oncol. 2007;18:36-39.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 31]  [Cited by in F6Publishing: 35]  [Article Influence: 1.9]  [Reference Citation Analysis (0)]
19.  Je Y, Liu W, Giovannucci E. Coffee consumption and risk of colorectal cancer: a systematic review and meta-analysis of prospective cohort studies. Int J Cancer. 2009;124:1662-1668.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 86]  [Cited by in F6Publishing: 93]  [Article Influence: 6.2]  [Reference Citation Analysis (0)]
20.  Kato I, Tominaga S, Matsuura A, Yoshii Y, Shirai M, Kobayashi S. A comparative case-control study of colorectal cancer and adenoma. Jpn J Cancer Res. 1990;81:1101-1108.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 160]  [Cited by in F6Publishing: 167]  [Article Influence: 4.9]  [Reference Citation Analysis (0)]
21.  Lüchtenborg M, White KK, Wilkens L, Kolonel LN, Le Marchand L. Smoking and colorectal cancer: different effects by type of cigarettes. Cancer Epidemiol Biomarkers Prev. 2007;16:1341-1347.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 34]  [Cited by in F6Publishing: 35]  [Article Influence: 2.1]  [Reference Citation Analysis (0)]
22.  Gram IT, Braaten T, Lund E, Le Marchand L, Weiderpass E. Cigarette smoking and risk of colorectal cancer among Norwegian women. Cancer Causes Control. 2009;20:895-903.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 24]  [Cited by in F6Publishing: 22]  [Article Influence: 1.5]  [Reference Citation Analysis (0)]
23.  Nisa H, Kono S, Yin G, Toyomura K, Nagano J, Mibu R, Tanaka M, Kakeji Y, Maehara Y, Okamura T. Cigarette smoking, genetic polymorphisms and colorectal cancer risk: the Fukuoka Colorectal Cancer Study. BMC Cancer. 2010;10:274.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 39]  [Cited by in F6Publishing: 46]  [Article Influence: 3.3]  [Reference Citation Analysis (0)]
24.  Fedirko V, Tramacere I, Bagnardi V, Rota M, Scotti L, Islami F, Negri E, Straif K, Romieu I, La Vecchia C. Alcohol drinking and colorectal cancer risk: an overall and dose-response meta-analysis of published studies. Ann Oncol. 2011;22:1958-1972.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 381]  [Cited by in F6Publishing: 400]  [Article Influence: 30.8]  [Reference Citation Analysis (0)]
25.  Cho E, Smith-Warner SA, Ritz J, van den Brandt PA, Colditz GA, Folsom AR, Freudenheim JL, Giovannucci E, Goldbohm RA, Graham S. Alcohol intake and colorectal cancer: a pooled analysis of 8 cohort studies. Ann Intern Med. 2004;140:603-613.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 314]  [Cited by in F6Publishing: 279]  [Article Influence: 14.0]  [Reference Citation Analysis (0)]
26.  Davis CG, Thake J, Vilhena N. Social desirability biases in self-reported alcohol consumption and harms. Addict Behav. 2010;35:302-311.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 269]  [Cited by in F6Publishing: 292]  [Article Influence: 20.9]  [Reference Citation Analysis (0)]
27.  Satia-Abouta J, Galanko JA, Potter JD, Ammerman A, Martin CF, Sandler RS. Associations of total energy and macronutrients with colon cancer risk in African Americans and Whites: results from the North Carolina colon cancer study. Am J Epidemiol. 2003;158:951-962.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 41]  [Cited by in F6Publishing: 50]  [Article Influence: 2.4]  [Reference Citation Analysis (0)]
28.  Arafa MA, Waly MI, Jriesat S, Al Khafajei A, Sallam S. Dietary and lifestyle characteristics of colorectal cancer in Jordan: a case-control study. Asian Pac J Cancer Prev. 2011;12:1931-1936.  [PubMed]  [DOI]  [Cited in This Article: ]
29.  Adams KF, Leitzmann MF, Albanes D, Kipnis V, Mouw T, Hollenbeck A, Schatzkin A. Body mass and colorectal cancer risk in the NIH-AARP cohort. Am J Epidemiol. 2007;166:36-45.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 71]  [Cited by in F6Publishing: 74]  [Article Influence: 4.4]  [Reference Citation Analysis (0)]
30.  Matsuo K, Mizoue T, Tanaka K, Tsuji I, Sugawara Y, Sasazuki S, Nagata C, Tamakoshi A, Wakai K, Inoue M. Association between body mass index and the colorectal cancer risk in Japan: pooled analysis of population-based cohort studies in Japan. Ann Oncol. 2012;23:479-490.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 57]  [Cited by in F6Publishing: 65]  [Article Influence: 5.0]  [Reference Citation Analysis (0)]
31.  Grimes DA, Schulz KF. Compared to what Finding controls for case-control studies. Lancet. 2005;365:1429-1433.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 272]  [Cited by in F6Publishing: 262]  [Article Influence: 13.8]  [Reference Citation Analysis (0)]
32.  Li L, Zhang M, Holman CD. Hospital outpatients are satisfactory for case-control studies on cancer and diet in China: a comparison of population versus hospital controls. Asian Pac J Cancer Prev. 2013;14:2723-2729.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 4]  [Cited by in F6Publishing: 5]  [Article Influence: 0.6]  [Reference Citation Analysis (0)]
33.  González CA, Torrent M, Agudo A, Riboli E. Hospital versus neighbourhood controls in the assessment of dietary risk factors. Int J Epidemiol. 1990;19:354-361.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 12]  [Cited by in F6Publishing: 13]  [Article Influence: 0.4]  [Reference Citation Analysis (0)]
34.  Inoue M, Tajima K, Hirose K, Hamajima N, Takezaki T, Kuroishi T, Tominaga S. Epidemiological features of first-visit outpatients in Japan: comparison with general population and variation by sex, age, and season. J Clin Epidemiol. 1997;50:69-77.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 111]  [Cited by in F6Publishing: 118]  [Article Influence: 4.4]  [Reference Citation Analysis (0)]
35.  Schulz KF, Grimes DA. Case-control studies: research in reverse. Lancet. 2002;359:431-434.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 266]  [Cited by in F6Publishing: 241]  [Article Influence: 11.0]  [Reference Citation Analysis (0)]
36.  Willett W Nutritional epidemiology. New York, NY: Oxford University Press 1998; .  [PubMed]  [DOI]  [Cited in This Article: ]
37.  Pandey D, Bhatia V, Boddula R, Singh HK, Bhatia E. Validation and reproducibility of a food frequency questionnaire to assess energy and fat intake in affluent north Indians. Natl Med J India. 2005;18:230-235.  [PubMed]  [DOI]  [Cited in This Article: ]