Abstract
Gastric cancer (GC) and pancreatic cancer (PC) are the third and seventh most likely cancers to cause death worldwide. We aimed to determine the dietary and lifestyle factors of patients with GC or PC and their associated risk among Jordanians. This case-control study enrolled 587 adults (patients with PC, 101; patients with GC, 172; healthy controls, 314) between March 2015 and August 2018, who were assessed using interview-based personal and physical activity questionnaires. Multivariable logistic regression models were taken as measures for predictors of GC and PC risk. We showed that GC and PC patients had higher pre-diagnosis body-mass indexes, a greater proportion smoked and had a family history of cancer than controls. Furthermore, consumption of two snacks [odds ratios (OR)=0.44, 95% confidence intervals (CI): 0.23~0.85], three snacks (OR=0.04, 95% CI: 0.01~0.23) and no meals eaten outside (OR=0.31, 95% CI: 0.09~0.99) showed a protective effect against GC, and consumption of three snacks (OR=0.08, 95% CI: 0.02~0.40) reduced significantly the risk of PC. These results suggest that bodyweight, physical activity, smoking, and family history of cancer are among factors that affect GC and PC risk among Jordanians.
Keywords: body mass index, gastric cancer, pancreatic cancer, physical activity, smoking
INTRODUCTION
Gastric cancer (GC) is the third most common type of cancer to cause death and the fifth most common type worldwide (Ferlay et al., 2015). From 2007 to 2016, the incidence rate for pancreatic cancer (PC) increased by 0.7% per year in white individuals and 0.3% per year in black individuals (American Cancer Society, 2020). However, from 2008 to 2017, mortality trends demonstrated a slight increase in death rate for PC (by 0.4% per year) in white individuals and a slight decrease (by 0.5% per year) in black individuals (American Cancer Society, 2020).
GC (Carcas, 2014) and PC (Costello, 2018) are heterogeneous diseases that are commonly diagnosed in their late stages (Lee and Derakhshan, 2013). Therefore, careful attention should be given to prevent GC and PC development since prevention and early diagnosis are vital approaches for controlling and reducing mortality rates (American Cancer Society, 2020).
Established risk factors for gastric and pancreatic cancers include smoking, excess body weight, high salt intake, alcohol, physical activity, and infection by Helicobacter pylori (American Cancer Society, 2020). However, studies show contrasting results, some documenting that smoking decreases survival (Zhao et al., 2020) and others showing no significant association (Trivers et al., 2005; Sundelöf et al., 2008; Ferronha et al., 2012). An estimated 5% of cancers in men and 11% in women are related to excess body weight (Islami et al., 2018). Excess body weight (i.e., being overweight or obese) is associated with an increased risk of many types of cancers, including gastric and pancreatic cancers (American Cancer Society, 2020).
An estimated 3% of cancer cases are attributed to physical inactivity (Islami et al., 2018). Physical activity is associated with a reduced risk of stomach and pancreatic cancers (World Cancer Research Fund/American Institute for Cancer Research, 2018). A greater amount of sedentary behaviour may increase risk of several types of cancers, including GC and PC (2018 Physical Activity Guidelines Advisory Committee, 2018). Furthermore, cancer patients who are physically active are less likely to have adverse effects and die from cancers than those who are inactive (Cormie et al., 2017). In Jordan, no previous studies have evaluated the associations between GC or PC and possible modifiable and non-modifiable risk factors. The present study was conducted to investigate the potential association between these lifestyle factors and dietary habits and the risk of GC or PC among Jordanians.
MATERIALS AND METHODS
Study design and participants
This case-control study was conducted in Jordan between March 2015 and August 2018. In total, 114 patients with medically confirmed PC and 186 patients with medically confirmed GC were invited to participate, and 101 patients with PC and 172 patients with GC enrolled. The control group consisted of 314 individuals without PC and GC, who were conveniently selected from the community. Population-based controls were frequency matched to cases based on age, gender, occupation, and marital status.
Inclusion criteria included Jordanian nationality, aged 18 years or older at enrolment, able to communicate verbally, and absence of any chronic diseases that require dietary modifications, such as kidney disease, liver disease, and celiac disease. For the GC and PC cases, patients must have been diagnosed within the last six months. Exclusion criteria included individuals who were critically ill, hospitalized, or unable to communicate verbally. Informed consent was obtained from all participants before enrolment.
Cases were enrolled from four hospitals: King Hussein Cancer Center, King Abdullah University Hospital, Jordan University Hospital, and Al-Bashir Hospital. The study protocol conformed to the ethical guidelines of the 1975 Declaration of Helsinki and was approved by the Ethics Committee of the King Hussein Cancer Center (IRB No. 15 KHCC 03, Amman, Jordan).
Data collection
Data were obtained by completing personal and physical activity questionnaires, which were completed during face-to-face interviews and filed by trained research assistants.
The personal questionnaire included questions related to age, gender, marital status, educational attainment, employment status, family income/month, smoking status, previous and current health problems, family history of cancer, and the presence or absence of stomach pain and ulcers. Smoking status included non-smoker, current smoker, previous smoker, and passive smoker (second-hand smoker) (Thornton et al., 1994). Information about dietary habits, such as consumption of main meals and snacks, frequency of skipping meals (breakfast, lunch, or dinner), frequency of eating problems, and daily water intake were also collected.
Anthropometric measurements
Participants’ current body weight and height were measured using standardized techniques and calibrated tools by trained research assistants. Body weight was measured to the nearest 0.1 kg with minimal clothing and without shoes using a calibrated scale (seca GmbH & Co. KG, Hamburg, Germany). Height was measured to the nearest cm when participants in the full standing position without shoes using a calibrated measuring rod (seca GmbH & Co. KG). Body mass index (BMI) was computed as the ratio of weight (kg) to height squared (m) (Lee and Nieman, 2013), and classified according to World Health Organization guidelines (WHO, 2002). However, the usual body weight at pre-diagnosis was self-reported from the cases and controls.
Physical activity questionnaire
A validated 7-day Physical Activity Recall (PAR) questionnaire was used to estimate participant’s physical activity levels. The 7-day PAR is a structured questionnaire that depends on participant’s recall of time spent on physical activity over a 7-day period (Sallis et al., 1985). It assesses physical activity intensity (e.g. from aerobic exercise, work-related activities, walking, gardening, recreation, and leisure activities). The frequency, intensity, duration, and type of physical activity are typically taken into consideration to estimate the level of physical activity. The number of hours spent sleeping and undertaking different levels of activity levels were assessed and converted into metabolic equivalents (MET). According to the scoring instructions, sleeping was assigned a value of 1.0 MET, light activity a value of 1.5 METs, moderate activity a value of 4.0 METs, and very hard activity a value of 7.0 METs or greater (Thompson et al., 1982). Physical activity was calculated as the time (min) dedicated to each activity multiplied by the calculated MET and multiplied by the number of days the activity was undertaken during the week, as follows: MET level×min of activity/day×days per week (Sallis et al., 1985). Physical activity level was expressed as continuous data in MET-min/week, and as categorical scores [inactive, minimally active, and Health-Enhancing Physical Activity (HEPA) active] based on the standard scoring protocol of International Physical Activity questionnaire. Participants were considered inactive if their activity levels were too low to meet creteria of minimally active or HEPA active. The minimally active category included participants who met any of the following conditions: (1) vigorous activity on 3 or more days for at least 20 min per day; (2) moderate intensity activity or walking on 5 or more days for at least 30 min per day, or (3) vigorous intensity activities on 5 or more days, achieving a minimum of 600 MET-min/week. The HEPA active catogory included participants who performed either vigorous intensity activity on at least 3 days and accumulated at least 1,500 MET-min/week, or participants who performed a combination of walking, moderate intensity or vigorous intensity activities on at least 7 days, achieving a minimum of at least 3,000 MET-min/week (Forde, 2018).
Statistical analysis
Statistical analysis was performed using the Statistical Package for the Social Sciences (SPSS) version 27 (IBM Corporation, Armonk, NY, USA). Frequencies and percentages were calculated to describe categorical variables. Pearson chi-square tests was used to detect differences in personal characteristics, lifestyle variables, and eating habits among study participants. Means and standard error of the mean (SEM) were calculated for the continuous variables. One-way analysis of variance (ANOVA) and Fisher’s least significant difference post hoc tests were used to calculate differences in continuous variables between gastric and pancreatic cases and controls. The significance level was set at P<0.05. Odds ratios (OR) and 95% confidence intervals (CI) from multivariable logistic regression models were taken as measures for predictors of gastric and pancreatic cancers risk.
RESULTS
Table 1 shows the characteristics of participants with GC (n=172) and PC (n=101), and controls (n=314). Participants with GC and PC had a similar age, height, and income as controls. The pre-diagnosis BMI for participants with both GC and PC were significantly higher than controls. However, current body weight and BMI for both types of cancer were significantly lower than for controls.
Table 1.
Characteristics of the study participants
| Gastric cancer cases (n=172) | Pancreatic cancer cases (n=101) | Controls (n=314) | P-value | |
|---|---|---|---|---|
| Age (years) | 54.1±1.0 | 56.97±1.2 | 54.0±0.7 | 0.093 |
| Height (cm) | 167.9±0.7 | 166.2±0.9 | 168.0±0.5 | 0.228 |
| Pre-diagnosis body weight (kg) | 85.3±1.6a | 83.4±2.0ab | 79.4±1.2b | 0.009 |
| Current weight (kg) | 70.6±1.3b | 69.4±1.4b | 80.9±0.9a | 0.001 |
| Pre-diagnosis BMI (kg/m2) | 30.1±0.5a | 30.2±0.7a | 28.3±0.4b | 0.008 |
| Current BMI (kg/m2) | 25.0±0.5b | 25.1±0.5b | 28.7±0.3a | 0.001 |
| Income (JD) | 674.0±79.6 | 700.1±74.7 | 575.9±36.0 | 0.266 |
| Number of cigarettes/d | 13.5±1.6a | 10.8±1.6ab | 9.0±0.9b | 0.028 |
| Duration of smoking (years) | 12.4±17.1a | 13.1±26.7a | 8.8±14.7b | 0.036 |
| Total physical activity (MET-min/week)1) | 1,031.5±42.7b | 952.9±47.2b | 1,314.7±45.6a | 0.001 |
1)Inactive: not fitting in "minimally active [at least 600 metabolic equivalents (MET)-min/week]" or "HEPA active (more than 3,000 MET-min/week)".
Each value is represented as mean±SEM.
Means with different letters (a,b) within the same row are significantly different (P<0.05).
BMI, body mass index; JD, Jordan dinar.
The number of cigarettes smoked per day was 13.5±1.6 for participants with GC, 10.8±1.6 for participants with PC, and 9.0±0.9 for controls. The number of cigarette smokers in the GC group was significantly higher than for controls. The duration of smoking was 12.4±17.1 and 13.1±26.7 years for GC and PC cases, respectively, and was significantly higher than for controls (8.8±14.7 years). Total physical activity METs (MET-min/week) were 1,031.5±42.7, 952.9±47.2, and 1,314.7±45.6 for GC and PC cases, and controls, respectively. However, all participants were considered minimally active (Table 1).
Table 2 shows the demographic and lifestyle factors of participants with GC and PC, and controls. Most GC cases (57.1%) and PC cases (52.6%) were considered normal according to their BMIs. However, most were previously considered overweight (GC, 40.4%; PC, 41.1%) or obese (GC, 41.0%; PC, 41.1%). The Majority of GC (67.9%) and PC (73.9%) cases were considered stage 4.
Table 2.
Demographic and lifestyle factors of patients with gastric cancer and pancreatic cancer
| Demographic and lifestyle factors | Gastric cancer (n=173, %) | Pancreatic cancer (n=101, %) | Control (n=314, %) | P-value |
|---|---|---|---|---|
| Gender | 0.853 | |||
| Male | 107 (61.8%) | 59 (58.4%) | 191 (60.8%) | |
| Female | 66 (38.2%) | 42 (41.6%) | 123 (39.2%) | |
| Pre-diagnosis BMI categories | 0.163 | |||
| <18.5 | 0 (0.0%) | 1 (1.1%) | 6 (2.1%) | |
| 18.5~24.9 | 29 (18.6%) | 16 (16.8%) | 73 (25.9%) | |
| 25.0~29.9 | 63 (40.4%) | 39 (41.1%) | 97 (34.4%) | |
| >30.0 | 64 (41.0%) | 39 (41.1%) | 106 (37.6%) | |
| Missing1) | 17 | 6 | 32 | |
| Current BMI categories | 0.001 | |||
| <18.5 | 9 (5.8%) | 6 (6.2%) | 0 (0.0%) | |
| 18.5~24.9 | 89 (57.1%) | 51 (52.6%) | 85 (27.8%) | |
| 25.0~29.9 | 30 (19.2%) | 21 (21.6%) | 108 (35.3%) | |
| >30.0 | 28 (17.9%) | 19 (19.6%) | 113 (36.9%) | |
| Missing | 17 | 4 | 8 | |
| Cancer stages | 0.001 | |||
| No cancer | 0 (0.0%) | 0 (0.0%) | 314 (100.0%) | |
| Stage 1 | 0 (0.0%) | 1 (1.1%) | 0 (0.0%) | |
| Stage 2 | 2 (1.4%) | 1 (1.1%) | 0 (0.0%) | |
| Stage 3 | 43 (30.7%) | 21 (23.9%) | 0 (0.0%) | |
| Stage 4 | 95 (67.9%) | 65 (73.9%) | 0 (0.0%) | |
| Missing | 33 | 13 | 0 | |
| Marital status | 0.714 | |||
| Married | 148 (85.5%) | 87 (86.1%) | 273 (86.9%) | |
| Single | 8 (4.6%) | 5 (5.0%) | 20 (6.4%) | |
| Divorced | 3 (1.7%) | 3 (3.0%) | 7 (2.2%) | |
| Widowed | 14 (8.1%) | 6 (5.9%) | 14 (4.5%) | |
| Education level | 0.348 | |||
| Illiterate | 10 (5.8%) | 7 (6.9%) | 18 (5.8%) | |
| Less than high school | 54 (31.4%) | 24 (23.8%) | 80 (25.6%) | |
| High school | 43 (25.0%) | 14 (13.9%) | 72 (23.0%) | |
| Diploma | 25 (14.5%) | 18 (17.8%) | 56 (17.9%) | |
| Bachelor | 34 (19.8%) | 30 (29.7%) | 71 (22.7%) | |
| Master’s degree | 4 (2.3%) | 5 (5.0%) | 13 (4.2%) | |
| Doctorate degree | 2 (1.2%) | 3 (3.0%) | 3 (1.0%) | |
| Missing | 1 | 0 | 1 | |
| Employment status | 0.778 | |||
| Yes | 82 (47.7%) | 45 (45.0%) | 153 (49.0%) | |
| No | 90 (52.3%) | 55 (55.0%) | 159 (51.0%) | |
| Missing | 1 | 1 | 2 | |
| Smoking status | 0.001 | |||
| Total number of the smokers | 90 (52.0%) | 47 (46.5%) | 124 (39.5%) | |
| Current smoker | 56 (32.4%) | 38 (37.6%) | 99 (31.5%) | |
| Previous smoker | 23 (13.3%) | 3 (3.0%) | 13 (4.1%) | |
| Passive smoker | 11 (6.3%) | 6 (5.9%) | 12 (3.8%) | |
| Non-smoker | 83 (48.0%) | 54 (53.5%) | 190 (60.5%) | |
| Number of cigarettes/d | 0.467 | |||
| <1 | 95 (56.2%) | 60 (60.0%) | 206 (65.6%) | |
| 2~5 | 6 (3.6%) | 3 (3.0%) | 12 (3.8%) | |
| 6~10 | 5 (3.0%) | 3 (3.0%) | 12 (3.8%) | |
| 11~20 | 23 (13.6%) | 17 (17.0%) | 42 (13.4%) | |
| 21~40 | 28 (16.6%) | 12 (12.0%) | 29 (9.2%) | |
| >41 | 12 (7.1%) | 5 (5.0%) | 13 (4.1%) | |
| Missing | 4 | 1 | 0 | |
| Hookah | 0.428 | |||
| Smoker | 7 (4.0%) | 6 (5.9%) | 27 (8.6%) | |
| Non-smoker | 163 (94.2%) | 93 (92.1%) | 282 (89.8%) | |
| Previous smoker | 3 (1.7%) | 2 (2.0%) | 5 (1.6%) | |
| Hookah smoking/d | 0.381 | |||
| 0 | 163 (97.6%) | 93 (93.9%) | 284 (93.7%) | |
| 1 | 3 (1.8%) | 5 (5.1%) | 13 (4.3%) | |
| ≥2 | 1 (0.6%) | 1 (1.0%) | 6 (2.0%) | |
| Missing | 6 | 2 | 11 | |
| Health problem | 0.195 | |||
| No | 95 (54.9%) | 45 (44.6%) | 151 (48.1%) | |
| Yes | 78 (45.1%) | 56 (55.4%) | 163 (51.9%) | |
| Type of health problem | 0.004 | |||
| No | 95 (54.9%) | 45 (44.6%) | 151 (48.1%) | |
| Diabetes mellitus | 33 (19.1%) | 36 (35.6%) | 81 (25.8%) | |
| Heart | 10 (5.8%) | 10 (9.9%) | 19 (6.1%) | |
| Hypertension | 30 (17.3%) | 9 (8.9%) | 40 (12.7%) | |
| Other | 5 (2.9%) | 1 (1.0%) | 23 (7.3%) | |
| Family history of cancer | 0.001 | |||
| Yes | 84 (48.6%) | 49 (48.5%) | 100 (31.8%) | |
| No | 89 (51.4%) | 52 (51.5%) | 214 (68.2%) | |
| Cancer type for patient’s family | 0.001 | |||
| Absent | 89 (51.4%) | 52 (51.5%) | 214 (68.2%) | |
| Gastric | 7 (9.8%) | 4 (4.0%) | 10 (3.2%) | |
| Colon and/or rectal | 9 (5.2%) | 1 (1.0%) | 13 (4.1%) | |
| Pancreatic | 1 (0.6%) | 3 (3.0%) | 1 (0.3%) | |
| Bone cancer | 4 (2.3%) | 3 (3.0%) | 6 (1.9%) | |
| Lung | 5 (2.9%) | 6 (5.9%) | 11 (3.5%) | |
| Leukaemia | 3 (1.7%) | 1 (1.0%) | 10 (3.2%) | |
| Breast | 16 (9.2%) | 7 (6.9%) | 13 (4.1%) | |
| Liver | 6 (3.5%) | 4 (4.0%) | 5 (1.6%) | |
| Prostate | 2 (1.2%) | 6 (5.9%) | 4 (1.3%) | |
| Other | 21 (12.1%) | 14 (13.9%) | 27 (8.6%) | |
| Missing | 39 | 24 | 36 | |
| Stomach pain | 0.001 | |||
| Yes | 49 (28.3%) | 9 (9.0%) | 14 (4.5%) | |
| No | 124 (71.7%) | 91 (91.0%) | 300 (95.5%) | |
| Missing | 0 | 1 | 0 | |
| Stomach ulcer | 0.001 | |||
| Yes | 77 (44.8%) | 13 (13.0%) | 5 (1.6%) | |
| No | 95 (55.2%) | 87 (87.0%) | 309 (98.4%) | |
| Missing | 1 | 1 | 0 | |
| Physical activity levels2) | 0.001 | |||
| Inactive | 50 (29.1%) | 26 (26.0%) | 46 (14.6%) | |
| Minimally active | 122 (70.9%) | 73 (73.0%) | 251 (79.9%) | |
| HEPA active | 0 (0.0%) | 1 (1.0%) | 17 (5.4%) | |
| Missing | 1 | 1 | 0 |
1)The response base differs as some cases had either irrelevant responses or no response at all.
2)Inactive: not fitting in "minimally active [at least 600 metabolic equivalents (MET)-min/week]" or "HEPA active (more than 3,000 MET-min/week)".
The total number of participants who smoked (including current, previous, and passive smokers) was significantly higher for GC (52.0%) and PC (46.5%) cases than controls (39.5%). However, no significant difference was detected in the daily number of cigarettes smoked by the subjects amongst study groups.
A greater number of participants with GC (48.6%) and PC (48.5%) had a family history of cancer compared with the control group (31.8%). Participants with GC reported family histories of gastric (9.8%), colon and/or rectal (5.2%), breast (9.2%), and other (12.1%) cancers. However, participants with PC reported family histories of lung (5.9%), breast (6.9%), prostate (5.9%), and other (13.9%) cancers. Approximately 28.3% and 44.8% of participants with GC suffered from stomach pain and stomach ulcers, respectively. Despite significantly different levels of physical activity between groups, participants with GC and PC and controls were all considered minimally active (Table 2).
Table 3 illustrates dietary habits of participants with GC and PC and controls. In total, 38.2% of participants with GC and 35.6% of participants with PC consumed two main meals/d, compared with 48.4% of controls. Over half of participants with GC and PC consumed three main meals/d, compared with only 41.1% for controls. For participants in all groups, breakfast and dinner were the most frequently skipped meals. Furthermore, the number of snacks consumed daily and the number of meals consumed outside significantly differed between participants with GC and PC and controls. In addition, participants with GC and PC consumed significantly less water daily than controls (consumption of more than 5 cups of water daily: GC cases, 48.3%; PC cases, 44.6%; controls, 57.8%). The number and types of eating problems significantly differed between groups.
Table 3.
Dietary habits of gastric and pancreatic cancer patients
| Dietary habits variables | Gastric cancer (n=173, %) | Pancreatic cancer (n=101, %) | Control (n=314, %) | P-value |
|---|---|---|---|---|
| Number of main meals | 0.019 | |||
| One meal | 10 (5.8%) | 7 (6.9%) | 25 (8.0%) | |
| Two meals | 66 (38.2%) | 36 (35.6%) | 152 (48.4%) | |
| Three meals | 95 (54.9%) | 58 (57.4%) | 129 (41.1%) | |
| More than three meals | 2 (1.2%) | 0 (0.0%) | 8 (2.5%) | |
| Skipped meals | 0.057 | |||
| No | 97 (56.1%) | 55 (55.0%) | 138 (44.1%) | |
| Breakfast | 22 (12.7%) | 11 (11.0%) | 34 (10.9%) | |
| Lunch | 5 (2.9%) | 8 (8.0%) | 13 (4.2%) | |
| Dinner | 38 (22.0%) | 19 (19.0%) | 85 (27.2%) | |
| Breakfast and lunch | 4 (2.3%) | 2 (2.0%) | 21 (6.7%) | |
| Breakfast and dinner | 5 (2.9%) | 5 (5.0%) | 19 (6.1%) | |
| Lunch and dinner | 2 (1.2%) | 0 (0.0%) | 3 (1.0%) | |
| Missing1) | 0 | 1 | 1 | |
| Number of snacks | 0.002 | |||
| One | 79 (45.7%) | 42 (42.0%) | 111 (35.7%) | |
| Two | 56 (32.4%) | 37 (37.0%) | 117 (37.6%) | |
| Three | 2 (1.2%) | 2 (2.0%) | 32 (10.3%) | |
| More than three | 2 (1.2%) | 1 (1.0%) | 5 (1.6%) | |
| No | 34 (19.7%) | 18 (18.0%) | 46 (14.8%) | |
| Missing | 0 | 1 | 3 | |
| Number of meals eaten outside | 0.001 | |||
| No | 42 (24.3%) | 25 (24.8%) | 119 (37.9%) | |
| Less than once/month | 34 (19.7%) | 24 (23.8%) | 85 (27.1%) | |
| 1~3 times/month | 35 (20.2%) | 25 (24.8%) | 62 (19.7%) | |
| 1~3 times/week | 43 (24.9%) | 20 (19.8%) | 32 (10.2%) | |
| 4~6 times/week | 12 (6.9%) | 4 (4.0%) | 5 (1.6%) | |
| Daily | 7 (4.0%) | 3 (3.0%) | 11 (3.5%) | |
| Daily water amount | 0.002 | |||
| 1~3 cups | 36 (20.9%) | 23 (22.8%) | 28 (8.9%) | |
| 3~5 cups | 51 (29.7%) | 33 (32.7%) | 103 (32.9%) | |
| More than 5 cups | 83 (48.3%) | 45 (44.6%) | 181 (57.8%) | |
| I don’t know | 2 (1.2%) | 0 (0.0%) | 1 (0.3%) | |
| Missing | 1 | 0 | 4 | |
| Eating problem | 0.001 | |||
| No | 131 (75.7%) | 84 (83.2%) | 281 (89.5%) | |
| Yes | 42 (24.3%) | 17 (16.8%) | 33 (10.5%) | |
| Type of eating problem | 0.001 | |||
| Swallowing | 7 (4.0%) | 3 (3.0%) | 10 (3.2%) | |
| Not feeling the taste and smell of the food | 4 (2.3%) | 0 (0.0%) | 5 (1.6%) | |
| Loss of appetite | 3 (1.7%) | 4 (4.0%) | 9 (2.9%) | |
| Way of eating | 3 (1.7%) | 1 (1.0%) | 1 (0.3%) | |
| Add salt | 19 (11.0%) | 5 (5.0%) | 5 (1.6%) | |
| Chewing | 5 (2.9%) | 4 (4.0%) | 2 (0.6%) | |
| Vomiting | 1 (0.6%) | 0 (0.0%) | 1 (0.3%) | |
| No | 131 (75.7%) | 84 (83.2%) | 281 (89.5%) |
1)The response base differs as some cases had either irrelevant responses or no response at all.
Table 4 shows that the odd ratios for consumption of two snacks (OR=0.44, 95% CI: 0.23~0.85), three snacks (OR=0.04, 95% CI: 0.01~0.23), and no meals outside (OR=0.31, 95% CI: 0.09~0.99) were inversely associated with GC risk. Furthermore, the risk of PC were inversely associated with the odds of a family history of colon and/or rectal cancer (OR=0.10, 95% CI: 0.01~0.91) and consumption of three snacks (OR=0.08, 95% CI: 0.02~0.40).
Table 4.
Logistic regression analysis of potential predictors of gastric and pancreatic cancer
| Potential predictors | Gastric cancer | Pancreatic cancer | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|
| OR1) | 95% CI | P-value | OR1) | 95% CI | P-value | ||||||
| Lower | Upper | Lower | Upper | ||||||||
| Cancer type for patient’s family | |||||||||||
| Gastric | 2.30 | 0.79 | 6.72 | 0.127 | 0.71 | 0.17 | 2.91 | 0.635 | |||
| Colon and/or rectal | 0.85 | 0.27 | 2.66 | 0.774 | 0.10 | 0.01 | 0.91 | 0.041 | |||
| Pancreatic | 1.53 | 0.04 | 52.66 | 0.814 | 6.86 | 0.23 | 206.04 | 0.267 | |||
| Bone cancer | 1.66 | 0.33 | 8.44 | 0.538 | 1.51 | 0.26 | 8.95 | 0.648 | |||
| Lung | 0.59 | 0.15 | 2.30 | 0.443 | 1.06 | 0.27 | 4.10 | 0.932 | |||
| Leukaemia | 0.36 | 0.07 | 1.71 | 0.196 | 0.22 | 0.02 | 2.06 | 0.184 | |||
| Breast | 1.44 | 0.49 | 4.23 | 0.506 | 1.08 | 0.31 | 3.75 | 0.909 | |||
| Liver | 1.01 | 0.23 | 4.43 | 0.991 | 0.96 | 0.19 | 4.81 | 0.962 | |||
| Prostate | 0.34 | 0.05 | 2.26 | 0.262 | 2.18 | 0.46 | 10.27 | 0.324 | |||
| Other | 1 Referent | 1 Referent | |||||||||
| Number of main meals | |||||||||||
| One meal | 0.29 | 0.04 | 2.29 | 0.240 | − | − | − | − | |||
| Two meals | 0.35 | 0.05 | 2.33 | 0.279 | − | − | − | − | |||
| Three meals | 0.80 | 0.13 | 5.16 | 0.816 | − | − | − | − | |||
| More than three meals | 1 Referent | 1 Referent | |||||||||
| Number of snacks | |||||||||||
| One | 0.62 | 0.33 | 1.14 | 0.125 | 0.71 | 0.34 | 1.49 | 0.364 | |||
| Two | 0.44 | 0.23 | 0.85 | 0.015 | 0.49 | 0.23 | 1.08 | 0.076 | |||
| Three | 0.04 | 0.01 | 0.23 | 0.001 | 0.08 | 0.02 | 0.40 | 0.002 | |||
| More than three | 0.16 | 0.02 | 1.11 | 0.064 | 0.18 | 0.02 | 2.14 | 0.175 | |||
| No | 1 Referent | 1 Referent | |||||||||
| Number of meals eaten outside | |||||||||||
| No | 0.31 | 0.09 | 0.99 | 0.048 | 0.4 | 0.09 | 1.89 | 0.249 | |||
| Less than once/month | 0.39 | 0.12 | 1.29 | 0.123 | 0.81 | 0.17 | 3.83 | 0.792 | |||
| 1~3 times/month | 0.53 | 0.16 | 1.71 | 0.286 | 1.07 | 0.23 | 5.02 | 0.932 | |||
| 1~3 times/week | 1.95 | 0.59 | 6.47 | 0.273 | 2.51 | 0.52 | 12.11 | 0.252 | |||
| 4~6 times/week | 3.40 | 0.74 | 15.70 | 0.117 | 3.24 | 0.44 | 23.62 | 0.247 | |||
| Daily | 1 Referent | 1 Referent | |||||||||
1)Adjusted for: age, gender, smoking status, family history of cancer, health problem, type of health problem and physical activity.
DISCUSSION
This study aimed to assess the main demographic and lifestyle factors of participants with GC and PC. Furthermore, it aimed to investigate the association between these lifestyle factors and dietary habits and the risk of GC and PC among Jordanians.
Many risk factors associated with GC and PC. Being overweight or obese increases the risk of many cancers, therefore obtaining and maintaining a healthy weight may lower the risk. Our study showed that both weight at diagnosis and BMI were reduced in participants with GC and PC compared with pre-diagnosis. Most participants with GC (57.1%) and PC (52.6%) had a BMI range of 18.5~24.9, which is considered normal. This could be attributed to weight loss resulting from the diseases. A similar result was reported by Okada et al. (2017) who found that 69.1% of GC patients had a normal BMI in range of 18.5~24.9 (Okada et al., 2017). However, Bosetti et al. (2013) found that 39.1% of participants with PC had a BMI of 20~25.
Smoking is the most important risk factor for GC and PC. Both the number of cigarettes smoked per day and the duration of smoking in years were higher for participants with GC and PC compared with controls. The total of participants who smoked (current, previous, and passive smokers) was 52% for participants with GC and 46.5% for participants with PC. Similarly, previous studies have shown that a high percentage (66.3%) of patients with GC is smokers (Okada et al., 2017) and that 48% of PC patients are current or previous smokers (Keane et al., 2014). Further studies have reported that PC is not affected by smoking (OR=0.60, 95% CI: 0.30~1.19, P=0.141) (Jo et al., 2015), and that active and passive smoking may play an important role in the development of cardial stomach cancer (Mao et al., 2002). However, Duan et al. (2009) did not report any evidence that passive smoking had any appreciable effect on oesophageal or gastric adenocarcinomas.
Regular physical activity may lower cancer risk. Several studies have demonstrated that avoiding a sedentary lifestyle and participating in physical activities is helpful for reducing the risk of digestive system cancers (Tayyem et al., 2013; Tajabadi et al., 2019). In the current study, most participants with GC and PC (70.9% and 73.0%, respectively) were considered minimally active (physical activity level between 600~3,000 MET-min/week) and were significantly less active than the control group. Similarly, Zhang et al. (2009) showed that participants with PC were less physically active than controls. Tajabadi et al. (2019) stated that the type and intensity of physical activity associated with a protective effect against gastro-intestinal cancer is unknown. Furthermore, the exact underlying mechanisms linking physical activity to digestive system cancers are unknown. However, different mechanisms have been suggested. Physical activity may reduce growth factor 1 levels, which is associated with carcinogenesis, reduce leptin and increases adiponectin levels in serum, regulate hormones in blood circulation, increase sex hormone binding protein levels, promote antioxidant defence, and modulate immune system function. Furthermore, water intake due to physical activity may be associated with digestive system cancer risk. Water plays a role in softening content in the gut, thus increasing waste particle transit time and diluting carcinogens that can decrease the risk of colorectal cancer (Tajabadi et al., 2019).
Approximately 55.4% of participants with PC suffered from other health problems, the most common of which was diabetes mellitus (35.6%). Previously, Zhang et al. (2009) found that 27% of patients with PC suffered from diabetes mellitus, whereas Bosetti et al. (2013) showed that 18.5% of patients with PC had diabetes mellitus. Our study revealed that 9.9% of participants with PC suffered from heart problems. However, researchers in the field of PC have stated that use of beta-blockers used in heart failure may suppress cancer invasion and proliferation (Zhang et al., 2010).
Moreover, 48.6% of participants with GC and 48.5% of participants with PC had a family history of cancer. Previous studies have shown a family history of cancer increases risk of GC (Gajalakshmi and Shanta, 1996) and PC (McGuigan et al., 2018). However, a family history of colon and/or rectal cancer was inversely associated with PC (OR=0.10, 95% CI: 0.01~0.91). This may be attributed to the lower number of colon and/or rectal cancers recorded in our study. Consistent with our findings, Silverman (2001) found that a family history of cancer is associated with a 30% increase in risk of PC. Silverman (2001) showed that subjects with a family history of PC (OR=3.2) and colon cancer (OR=1.7) had a significantly higher risk of PC. In the current study, stomach pain and ulcers were significantly higher in both participants with GC and PC than controls. Several previous studies have shown that stomach pain and ulcers are significantly higher in patients with PC (Bosetti et al., 2013; Keane et al., 2014).
Most participants with cancer consumed three main meals and one snack per day. However, the American Cancer Society recommends that cancer patients instead eat several small snacks throughout the day (Rock et al., 2012). We found that consuming two snacks (OR=0.44, 95% CI: 0.23~0.85) and three snacks (OR=0.04, 95% CI: 0.01~0.23) decreased the risk of GC. Furthermore, consuming three snacks (OR=0.08, 95% CI: 0.02~0.40) was associated with a lower risk of PC. Dinner was the most skipped meal for participants with GC and PC. In contrast to this result, Lim et al. (2012) reported that breakfast was the most skipped meals for patients with GC in Korea. Furthermore, in the current study, the numbers of meals eaten outside by participants with GC and PC were significantly higher than for controls. As expected, we found that not eating meals outside (OR=0.31, 95% CI: 0.09~0.99) decreased the risk of GC. In addition, excessive consumption of salt can increase risk of GC (Okada et al., 2017). In this study, adding salt to food was the most predominant eating problem reported by participants with GC.
Several studies have shown that water intake may play a role in reducing the risk of some digestive cancers. Water helps soften gut content, to increase waste particle transit time and dilute carcinogens, both of which decrease the risk of colorectal cancer (Tayyem et al., 2013; Tajabadi et al., 2019). In this study, fewer participants with cancer consumed more than 5 cups of water per day than controls.
The strengths of this study include the population-based design, relatively large sample size, and separate investigation of GC and PC cases. Furthermore, this is the first study to evaluate GC and PC risk factors using a case-control study among Jordanians. Our study also had several limitations. For example, data may be subject to recall bias, and several factors associated with GC and PC were not measured (e.g. H. pylori infection).
In conclusion, the data of this study suggest that different dietary and lifestyle factors affect risk of GC and PC. Indeed, there was an association between certain lifestyle factors, dietary habits and risk of GC and PC among Jordanians. Our findings offer insight for further prospective investigations and for creating effective strategy to prevent GC and PC.
ACKNOWLEDGEMENTS
The authors would like to thank The Hashemite University for funding the research projects. We would like to express our thanks and gratitude for Eng Israa Al-Natsheh for help in data collection.
Footnotes
AUTHOR DISCLOSURE STATEMENT
The authors declare no conflict of interest.
AUTHORSHIP
RT and TA were responsible for the study conception and design and responsible for development of the methodology. SA, TA, AH, and YA were responsible for the acquisition of data. NA, RT, and SA were responsible for analysis and interpretation of data. NA, RT, KB, and SA were responsible for drafting the manuscript. All the authors were responsible for reviewing and/or revising the manuscript.
REFERENCES
- 2018 Physical Activity Guidelines Advisory Committee, author. [cited 2020 Oct 22];2018 Physical Activity Guidelines Advisory Committee Scientific Report. 2018 Available from: https://health.gov/sites/default/files/2019-09/PAG_Advisory_Committee_Report.pdf .
- American Cancer Society, author. [cited 2020 Oct 20];Cancer facts & figures 2020. 2020 Available from: https://www.cancer.org/content/dam/cancer-org/research/cancer-facts-and-statistics/annual-cancer-facts-and-figures/2020/cancer-facts-and-figures-2020.pdf .
- Bosetti C, Lucenteforte E, Bracci PM, Negri E, Neale RE, Risch HA, et al. Ulcer, gastric surgery and pancreatic cancer risk: an analysis from the International Pancreatic Cancer Case-Control Consortium (PanC4) Ann Oncol. 2013;24:2903–2910. doi: 10.1093/annonc/mdt336. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Carcas LP. Gastric cancer review. J Carcinog. 2014;13:14. doi: 10.4103/1477-3163.146506. https://doi.org/10.4103/1477-3163.146506 . [DOI] [PMC free article] [PubMed] [Google Scholar]
- Cormie P, Zopf EM, Zhang X, Schmitz KH. The impact of exercise on cancer mortality, recurrence, and treatment-related adverse effects. Epidemiol Rev. 2017;39:71–92. doi: 10.1093/epirev/mxx007. [DOI] [PubMed] [Google Scholar]
- Costello E. A metabolomics-based biomarker signature discrimi-nates pancreatic cancer from chronic pancreatitis. Gut. 2018;67:2–3. doi: 10.1136/gutjnl-2016-313665. [DOI] [PubMed] [Google Scholar]
- Duan L, Wu AH, Sullivan-Halley J, Bernstein L. Passive smoking and risk of oesophageal and gastric adenocarcinomas. Br J Cancer. 2009;100:1483–1485. doi: 10.1038/sj.bjc.6605023. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Ferlay J, Soerjomataram I, Dikshit R, Eser S, Mathers C, Rebelo M, et al. Cancer incidence and mortality worldwide: sources, methods and major patterns in GLOBOCAN 2012. Int J Cancer. 2015;136:E359–E386. doi: 10.1002/ijc.29210. [DOI] [PubMed] [Google Scholar]
- Ferronha I, Castro C, Carreira H, Bento MJ, Carvalho I, Peleteiro B, et al. Prediagnosis lifestyle exposures and survival of gastric cancer patients: a cohort study from Portugal. Br J Cancer. 2012;107:537–543. doi: 10.1038/bjc.2012.258. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Forde C. [cited 2020 Sep 2];Exercise prescription for the prevention and treatment of disease. 2018 Available from: https://ugc.futurelearn.com/uploads/files/bc/c5/bcc53b14-ec1e-4d90-88e3-1568682f32ae/IPAQ_PDF.pdf .
- Gajalakshmi CK, Shanta V. Lifestyle and risk of stomach cancer: a hospital-based case-control study. Int J Epidemiol. 1996;25:1146–1153. doi: 10.1093/ije/25.6.1146. [DOI] [PubMed] [Google Scholar]
- Islami F, Goding Sauer A, Miller KD, Siegel RL, Fedewa SA, Jacobs EJ, et al. Proportion and number of cancer cases and deaths attributable to potentially modifiable risk factors in the United States. CA Cancer J Clin. 2018;68:31–54. doi: 10.3322/caac.21440. [DOI] [PubMed] [Google Scholar]
- Jo SR, Joh JY, Jeong JR, Kim S, Kim YP. Health behaviors of Korean gastric cancer survivors with hypertension: a propensity analysis of KNHANES III-V (2005-2012) PLoS One. 2015;10:e0126927. doi: 10.1371/journal.pone.0126927. https://doi.org/10.1371/journal.pone.0126927 . [DOI] [PMC free article] [PubMed] [Google Scholar]
- Keane MG, Horsfall L, Rait G, Pereira SP. A case-control study comparing the incidence of early symptoms in pancreatic and biliary tract cancer. BMJ Open. 2014;4:e005720. doi: 10.1136/bmjopen-2014-005720. http://doi.org/10.1136/bmjopen-2014-005720 . [DOI] [PMC free article] [PubMed] [Google Scholar]
- Lee R, Nieman D. Nutritional assessment. 6th ed. McGraw-Hill Companies, Inc.; New York, NY, USA: 2013. p. 176. [Google Scholar]
- Lee YY, Derakhshan MH. Environmental and lifestyle risk factors of gastric cancer. Arch Iran Med. 2013;16:358–365. [PubMed] [Google Scholar]
- Lim H, Cho G, Kim S. Evaluation of nutrient intake and diet quality of gastric cancer patients in Korea. Nutr Res Pract. 2012;6:213–220. doi: 10.4162/nrp.2012.6.3.213. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Mao Y, Hu J, Semenciw R White K; Canadian Cancer Registries Epidemiology Research Group, author. Active and passive smoking and the risk of stomach cancer, by subsite, in Canada. Eur J Cancer Prev. 2002;11:27–38. doi: 10.1097/00008469-200202000-00005. [DOI] [PubMed] [Google Scholar]
- McGuigan A, Kelly P, Turkington RC, Jones C, Coleman HG, McCain RS. Pancreatic cancer: a review of clinical diagnosis, epidemiology, treatment and outcomes. World J Gastroenterol. 2018;24:4846–4861. doi: 10.3748/wjg.v24.i43.4846. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Okada E, Ukawa S, Nakamura K, Hirata M, Nagai A, Matsuda K, et al. Demographic and lifestyle factors and survival among patients with esophageal and gastric cancer: The Biobank Japan Project. J Epidemiol. 2017;27:S29–S35. doi: 10.1016/j.je.2016.12.002. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Rock CL, Doyle C, Demark-Wahnefried W, Meyerhardt J, Courneya KS, Schwartz AL, et al. Nutrition and physical activity guidelines for cancer survivors. CA Cancer J Clin. 2012;62:243–274. doi: 10.3322/caac.21142. [DOI] [PubMed] [Google Scholar]
- Sallis JF, Haskell WL, Wood PD, Fortmann SP, Rogers T, Blair SN, et al. Physical activity assessment methodology in the Five-City Project. Am J Epidemiol. 1985;121:91–106. doi: 10.1093/oxfordjournals.aje.a113987. [DOI] [PubMed] [Google Scholar]
- Silverman DT. Risk factors for pancreatic cancer: a case-control study based on direct interviews. Teratog Carcinog Mutagen. 2001;21:7–25. doi: 10.1002/1520-6866(2001)21:1<7::AID-TCM3>3.0.CO;2-A. [DOI] [PubMed] [Google Scholar]
References
- Sundelöf M, Lagergren J, Ye W. Patient demographics and lifestyle factors influencing long-term survival of oesophageal cancer and gastric cardia cancer in a nationwide study in Sweden. Eur J Cancer. 2008;44:1566–1571. doi: 10.1016/j.ejca.2008.04.002. [DOI] [PubMed] [Google Scholar]
- Tajabadi Z, Akbari ME, Hafez AA. Physical activity and gastrointestinal cancer risk: a review. Acta Medica Bulgarica. 2019;46:57–67. doi: 10.2478/amb-2019-0010. [DOI] [Google Scholar]
- Tayyem RF, Shehadeh IN, Abumweis SS, Bawadi HA, Hammad SS, Bani-Hani KE, et al. Physical inactivity, water intake and constipation as risk factors for colorectal cancer among adults in Jordan. Asian Pac J Cancer Prev. 2013;14:5207–5212. doi: 10.7314/APJCP.2013.14.9.5207. [DOI] [PubMed] [Google Scholar]
- Thompson JK, Jarvie GJ, Lahey BB, Cureton KJ. Exercise and obesity: etiology, physiology, and intervention. Psychol Bull. 1982;91:55–79. doi: 10.1037/0033-2909.91.1.55. [DOI] [PubMed] [Google Scholar]
- Thornton A, Lee P, Fry J. Differences between smokers, ex-smokers, passive smokers and non-smokers. J Clin Epidemiol. 1994;47:1143–1162. doi: 10.1016/0895-4356(94)90101-5. [DOI] [PubMed] [Google Scholar]
- Trivers KF, De Roos AJ, Gammon MD, Vaughan TL, Risch HA, Olshan AF, et al. Demographic and lifestyle predictors of survival in patients with esophageal or gastric cancers. Clin Gastroenterol Hepatol. 2005;3:225–230. doi: 10.1016/S1542-3565(04)00613-5. [DOI] [PubMed] [Google Scholar]
- WHO, author. WHO Technical Report Series 916. World Health Organization; Geneva, Switzerland: 2002. [cited 2020 Sep 20]. Diet, nutrition and the prevention of chronic diseases. Available from: https://apps.who.int/iris/bitstream/handle/10665/ 42665/WHO_TRS_916.pdf;jsessionid=6DDAB9216C4F 2659AB15335C56E777E7?sequence=1 . [Google Scholar]
- World Cancer Research Fund/American Institute for Cancer Research, author. [cited 2020 Oct 20];Diet, nutrition, physical activity and cancer: a global perspective. 2018 Available from: https:// www.wcrf.org/sites/default/files/Summary-of- Third-Expert- Report-2018.pdf .
- Zhang D, Ma QY, Hu HT, Zhang M. μ2-adrenergic antagonists suppress pancreatic cancer cell invasion by inhibiting CREB, NFκB and AP-1. Cancer Biol Ther. 2010;10:19–29. doi: 10.4161/cbt.10.1.11944. [DOI] [PubMed] [Google Scholar]
- Zhang J, Dhakal IB, Gross MD, Lang NP, Kadlubar FF, Harnack LJ, et al. Physical activity, diet, and pancreatic cancer: a population-based, case-control study in Minnesota. Nutr Cancer. 2009;61:457–465. doi: 10.1080/01635580902718941. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Zhao LL, Huang H, Wang Y, Wang TB, Zhou H, Ma FH, et al. Lifestyle factors and long-term survival of gastric cancer patients: a large bidirectional cohort study from China. World J Gastroenterol. 2020;26:1613–1627. doi: 10.3748/wjg.v26.i14.1613. [DOI] [PMC free article] [PubMed] [Google Scholar]