Environmental Risk Factors and Plasma Concentration of Lead and Copper in Colorectal Cancer Patients in Alexandria, Egypt: A case-control study

doi:10.21203/rs.3.rs-3089188/v1

Background:

Colorectal cancer is the third most commonly diagnosed cancer in both men and women. It is thought to result from a complex interaction between several genetic and environmental factors. Recognizing these factors that trigger the disease occurrence and progression is essential to apply more effective measures of prevention and risk reduction.

Objectives:

The main objectives of this study were to compare the plasma levels of lead and copper in colorectal cancer between patients and healthy subjects and to estimate the relation between the exposure to some environmental risk factors and colorectal cancer.

Methods:

A case-control study was performed at the clinical oncology department clinic of Alexandria Main University Hospital. The study sample consisted of 25 colorectal cancer patients, and 25 healthy controls, who matched the cases on age and sex. Data about possible environmental risk factors were collected by a pre-designed structured interviewing questionnaire. Levels of lead (Pb) and copper (Cu) of all participants were measured by graphite furnace atomic absorption spectrometry.

Results:

Higher levels of Pb and Cu were detected in colorectal cancer patients compared to healthy subjects, these findings were statistically significant (p<0.05). The multivariate stepwise logistic regression model revealed that four factors had significant association with colorectal cancer, the first rank was Living nearby solid waste collecting sites, followed by exposure to environmental tobacco smoke (ETS), then plasma Lead level (>0.164 mg /L), and lastly living in house with old oily painting(OR = 83.25, 95% CI = 1.28-5419.13; OR = 32.20, 95% CI = 1.53-678.07; OR = 31.06, 95% CI = 1.55-622.59; OR = 9.35, 95% CI = 1.02-85.79, respectively).

Conclusion:

There was a significant difference in the plasma levels of Pb and Cu between colorectal cancer patients and healthy subjects. This may be due to prolonged exposure to environmental pollutants. Chronic exposure to environmental pollutants may have important role in the pathogenesis of the colorectal cancer. However, further studies are needed to enhance our understanding of this relationship between heavy metals and their role in cancer progression.

Colorectal Cancer

Copper

Environmental Risk Factors

Lead

Colorectal cancer (CRC) is considered as one of the most common malignancies, which is responsible for 10% of worldwide cancer incidence and 9.4% of cancer deaths in 2020. It is the third most commonly detected cancer and the second cause of malignancy death. (1, 2)

The etiology of CRC is not clearly understood; it is a multifactorial disease. Many factors could share in the pathogenesis of colorectal cancer such as genetic defects and environmental risk factors. About 5% to 10% of people who develop CRC have inherited gene defects that cause the disease. (2)

Many epidemiological studies have focused on the role of diet, obesity, alcohol intake, social stress, tobacco smoking and high consumption of red meat (especially processed meat), low consumption of fruits, vegetables, dietary fibers, and sedentary life style as possible risk factors. Recently, many studies indicated the important role of environmental factors, including heavy metals. These studies proved strong association between the increased level of environmental pollution and CRC. Increased levels of different trace elements such as lead, cadmium, manganese and copper in patients with colorectal cancer compared to healthy controls may indicate the crucial role of these elements in the pathogenesis of this cancer.(3-6)

The previous factors could affect DNA and lead to genetic defects by generation of reactive oxidative species (ROS) which causes ineffective DNA repair which is an important step in cancer development. This gives an alarm for the importance of increasing the public health awareness about environmental risk factors. (7) Emre et al., (2013) had proved the previously mentioned relationship between traces of heavy metals as an epigenetic risk factor and colorectal cancer. (8) Another case-control study had proved the increased levels of heavy metals in the cancerous tissue of colorectal cancer patients compared to the normal neighboring tissue in the same patients and it was statistically significant, (p< 0.05). (9)

Environmental factors could activate or induce genetic mutations to initiate the lesions that will progress into cancerous tissue. Many studies suggested a relation between the exposure to these factors and the presence of mutations in the tissue of CRC patients such as high microsatellite instability, CpG island methylator phenotype (CIMP-positive), V-Raf murine sarcoma viral oncogene homolog B1 (BRAF–positive). (10-12)

Even passive smoking could be a risk factor for CRC. Yang et al., (2016) in a meta-analysis study found environment tobacco smoke (ETS) had a significant association with colorectal cancer (RR = 1.14; 95% CI = 1.05-1.24). (13)

Additionally, low level of education and low socioeconomic status (SES) elevate the risk of CRC development. People with low socioeconomic status exposed more to the hazardous substances during work and during living in the unhealthy residential areas. They have low awareness about the manifestations of the disease and when to seek medical advice. This could be minimized by health educational programs to increase level of public awareness and enhancing the quality of life. (14)

From the economic point of view, identifying the risk factors of CRC and increasing the population awareness about these factors would decrease the burden of the disease (by controlling the modifiable risk factors), reduce the environmental pollution, saving resources and so, it would enhance the quality of life. (15, 16)

There are many risk factors affecting colorectal cancer development and due to scarcity of researches on the relationship between environmental pollution and this cancer in Egypt. The current study tried to assess the relation between potential environmental risk factors and CRC. In addition, it measured lead and copper plasma level in healthy people and CRC patients as an objective indirect indicator for environmental pollution.

2.1. Study design and setting

A case-control study was adopted to collect data from November 2019 to October 2020. The study was conducted at the oncology outpatient clinic of Alexandria Main University Hospital, Alexandria University, Egypt.

2.2. Study Population

Twenty-five patients, who were recently diagnosed of colorectal cancer by an oncologist according to their pathological reports, were involved in the study. Twenty-five apparently healthy individuals matched to cases on age and sex were enrolled. They were chosen from other clinics complaining of minor problems or colorectal cancer patient’ relatives who came with the patients during their visit to the oncology clinic. The study participants were involved in the study through simple random sampling technique.

Subjects with history of non-colorectal cancer malignancies, metabolic disorders, nutritional disorders like Wilson’s disease, being on chemotherapy or radiotherapy and intake of nutritional supplements or vitamins including trace elements were excluded from the study.

2.3. Sample Size

Based on a case-control study carried out by Emre et al.,2013. (8) The mean level of plasma copper in patients with colon cancer was 0.241 ± 0.1004 mg/L and healthy group was 0.151 ± 0.0243mg/L. Using Alpha error = 5%, beta error = 5%, power 95%, the minimum required sample size was estimated to be 38 participants that was increased to 50 adults to compensate missing data, 25 subjects for each group. The sample size was calculated using G. Power software.

2.4. Tools of Data Collection

1. Interviewing questionnaire

A predesigned structured interviewing questionnaire was created to collect the data. It included a total of 72 questions, extracted from similar previously validated researches questionnaires. (17-19) It included questions that aimed to assign exposure to some environmental risk factors.

The questionnaire included seven parts. First part concerned with socio-demographic characteristics (i.e., age, sex, education and social status). Second part included questions about health status and family history (i.e., family history of cancer, comorbid diseases such as hypertension and diabetes mellitus, regular use of any type of medications). Third part involved questions about occupation and occupational risk factors (i.e., number of working hours per day, days per week, number of working years, type of occupation and if there was any exposure to physical, biological or chemical pollutants in the work place (17,18). Part four included questions about life-style (i.e., smoking behavior, living with other smokers, cigarettes and shisha smoking and sport practice). Part five involved questions about exposure to indoor environmental risk factors (i.e., drinking water problems type of water pipes, type of fuel source, walls cover and land cover. usage of organic solvents, paint materials, printing ink and insecticides). The exposure to outdoor environmental risk factors) i.e., place of residence, presence of high traffic roads, high way streets, gas stations, places of collecting and firing garbage, waste incinerators, waste landfill, metal plants, electricity distribution networks, mobile phone station and agriculture lands).The last part concerned with the dietary habits that could be related to colorectal cancer (i.e., Fries potato and chips, read meat, dairy products, fruits and vegetables, carbonated beverages and sea fish and Nile fish consumption).

2. Examination of anthropometric measures

Anthropometric measurement of weight and height were done in order to calculate body mass index (BMI). (20) Participants were classified as malnourished (underweight) if BMI was ≤18.5 kg/m2, normal weight if their BMI was between 18.5 and 24.9 kg/m2, overweight if between 25 and 29.9 kg/m2, and obese if ≥30 kg/m2 based on the criteria of the World Health Organization. The weight was measured by an electronic weighing machine and the height by a meter.

(BMI) was calculated using the following formula;

BMI (kg/m2) = Weight (kg) / Height (m2)

3. Laboratory investigation

All participants were tested for the plasma concentrations of lead and copper. Samples of 5 ml of venous heparinized blood were collected, then samples were applied to centrifugation process to get plasma and were kept at (-80 degree), until samples were analyzed. Determination of serum concentrations of lead and copper by flame atomic absorption spectrometry after wet digestion of the plasma samples (AAS) Shimadzu model (AA-6650) was carried out. (21, 22)

2.5. Statistical Analysis

Data were fed to the computer and analyzed using the Statistical Package for the Social Sciences (SPSS) software. A result was considered statistically significant when the significance probability was less than 5 % (p< 0.05). (23)

Descriptive measures: simple and complex frequency distribution tables were used as descriptive statistics. Qualitative variables were described through frequencies (number of cases) and relative frequencies (percentages of cases). For quantitative continuous variables, test of normality using the Kolmogorov-Smirnov test was used. Mean and standard deviation (Mean ± SD) for quantitative variables were calculated if the variable follow normal distribution, and median and interquartile range (Median ± IQR) if it does not follow normal distribution.

Pearson’s Chi-square test (X²) was used to calculate significant differences between the groups (cases and controls) for the categorical data whenever possible. If the assumptions were violated, Fisher’s exact test or Monte Carlo test were used. Independent t-test was done for normally distributed quantitative variables, to compare the means of two studied groups while Mann Whitney test was used for abnormally distributed quantitative variables.

Odds Ratio (OR) was calculated to measure the risk of colorectal cancer regarding exposure to environmental and other risk factors. The “95% confidence interval (CI)” was used to assess significance of OR. (24) Receiver operating characteristic (ROC) curve was used to identify a cut-off point between normal and abnormal values of plasma concentration of Lead and Copper to create a dichotomous variable depending on the relation between sensitivity and specificity.(25)

A multivariate stepwise logistic regression analysis was carried out to see if there were significant associations between specific exposures and the developing of colorectal cancer and to adjust for some potential confounders. The choice of the independent variables in the model was based on the results of the univariate analyses. (26)

2.6. Ethical approval

The researcher sought the approval of the Ethics Committee of the High Institute of Public Health, Alexandria University for conducting the research. Approval and permission for conducting the study at the outpatient clinic of the oncology department were obtained from the head of Alexandria clinical oncology department. All subjects participated on a voluntary basis. They were informed about the purpose and objectives of the study as well as the benefits of the study to the individual and society. A written informed consent was signed by the participants before data and sample collection. Privacy of all patients’ data was granted by code number for each patient. In addition, every participant was interviewed separately. The research followed the guidelines set out in the Declaration of Helsinki for medical research involving human subjects.(27)

3.1. Socio-economic characteristics

The study sample consisted of 25 cases of colorectal cancer that were confirmed by the consultant before starting chemotherapy or surgery and 25 healthy subjects. Cases had an age range of (23– 67) years with mean ± SD 49.72 ± 11.18 years, while the control group had an age range of (25– 64) years with mean ± SD 46.16 ± 9.90 years as presented in table (1). Fifty two percent of the participants in each group were males and 48% were females. There is no difference was detected between the two groups because they were matched on age and sex. According to educational level, 76.0% of the controls had university education while only 28.0% of the cases graduated from university. Eight percent of controls were illiterate compared to 28% of the cases. There is a significant difference between case and control groups as regards educational level (p < 0.05).

Concerning family income, only 20.0% of cases had enough income while 80.0% of the controls had enough income with statistically significant difference controls (p < 0.05). Regarding crowding index (calculated by dividing the family size by the total number of rooms in the house without kitchen and bathroom), there was a statistically significant difference between cases and controls (p < 0.05), as 56.0% cases with crowding index 2 or more compared to only 16.0% of controls. It was found that (52%) of cases were having comorbid diseases and using medications compared to only (20%) of controls with significant difference (p < 0.05).

Tobacco smoking (active or previous smoker), lack of regular exercise and frequent eating red or processed meat were not found to have significant difference between cases and controls. Also, there was no significant difference in the BMI between both groups.

3.2. Estimation of colorectal cancer risk regarding some socio-economic characteristics and environmental factors

Table (2) illustrates the association between some socio-economic characteristics and environmental factors and the risk of developing colorectal cancer. As regards level of education, the odds of being illiterate were 9.5 times higher among cases than controls (odds ratio (OR) =9.5; 95% confidence interval (CI): 1.58 – 57.16) and the odds of having primary or secondary education were significantly different also (OR=13.57; 95% CI: 1.39 – 137.45; OR=5.43; 95% CI: 1.06 – 27.83, respectively).

The odds of did not have enough income were 16 times greater in case group than in control group (OR=16.0; 95% CI: 4.0 – 63.98). Regarding the household crowding index, the odds of living in crowded houses (2+) were 6.7 times greater in case group than in control group (OR=6.68; 95% CI: 1.77 – 25.25). Concerning the used medications (due to the presence of diseases as diabetes or hypertension), the odds of using them were 4.3 times greater in cases than in controls (OR=4.33; 95% CI: 1.24 – 15.21).

Table (2) also demonstrates the exposure to some indoors risk factors. As for the exposure to Environmental tobacco smoke (ETS), the odds of being exposed to ETS were about 8 times more in case group compared to control group (odds ratio (OR)=7.94; 95% CI: 1.88 – 33.50) . It was detected that the odds for those whom had old oily household painting were 12,6 times higher in cases than in controls (OR = 12.667; 95% CI: 3.308 –48.504). As regards usage of insecticides, it was detected the odds for those whom used insecticides with high rate had 5.46 times higher in case group than in control group, (odds ratio OR=5.46; 95% CI: 1.623 – 18. 35).

Table (2) depicts the assessment of harmful effect of exposure to some outdoors environmental risk factors. The odds of being lived nearby cell phone stations were about 9 times greater in the case group than the control group (odds ratio OR=9.33; 95% CI: 1.05 – 82.78). Living nearby solid waste collecting sites elevated the odds of the cases compared to the controls (odds ratio OR=4.125; 95% CI: 0.961 – 17.04).

Concerning working conditions, the odds for those whom worked >7 hrs./day were 33 times higher in case group compared to control group (OR=33; 95% CI: 4.74 – 229.65). It was estimated that the odds for exposure history to physical factors during working (noise, excess vibrations, etc.) were 39 times greater in the case group than control group (OR=39.0; 95% CI: 4. 02 –378.20).

Regarding the association between exposure to chemical risk factors in workplaces and colorectal cancer, the odds of exposure to them were 11 times greater in the case group compared to the control group (odd ratio OR=11.0; 95% CI: 2.16 – 56.09). Concerning water supply, the odds for having problems in the drinking water (e.g. turbidity, change in taste or color of the water) were 13.5 times higher in case group compared to control group (OR=13.5; 95% CI: 3.40 – 53.68). Having water supply through old leaded pipes increased the odds to 14.6 times higher in case group compared to control group (OR=14.64; 95% CI: 2.82 – 75.95). Presence of waste water problems also increased the odds in cases than controls (OR=13.5; 95% CI: 1.56 – 117.14). The only significant risk in dietary habits was found for consumption of carbonated beverages (OR=4.57; 95% CI: 1.38 – 15.11).

3.3. Lead and Copper plasma levels

In the present study, in order to estimate the effect of exposure to lead and copper on the occurrence of colorectal cancer, the levels of lead and copper were measured in the heparinized blood of the study sample as presented in table (3). In general, the samples of the studied groups had traces of lead and copper, but the mean levels of cases are more than of the controls.

The mean concentration of lead level in cases was (0.45 ± 0.48) mg/L and it was significantly higher than the control group (0.21 ± 0.25) mg/L as U=196.50, p=0.02. The mean lead level of the case group was about twice the mean of that of the control group. Only 32 % of control group compared to 64% of case group had high lead level (> 0.164 mg/L) and the difference was significant (χ²=5.13, p=0.024).

The mean concentration of copper in cases was (1.46 ± 0.64) mg/L and it was significantly higher than the control group (1.10 ± 0.41) mg/L as U=206.50, p=0.04. Fifty six percent of cases had high copper level (>1.3 mg/L) compared to (28 %) of the control group with significant difference (χ²=4.02, p=0.045).

3.5. Estimation of Lead and Copper cut-off levels

The ROC curve was plotted to calculate Pb level cut-off points as shown in figure (1). Area under a curve (AUC) for ROC curve of Pb was (0.686) and the optimal cut-off point to diagnose colorectal cancer was (> 0.164) mg/L, table (4). The cut-off point of (> 0.164) revealed high sensitivity (64%) and high specificity (68%) as showed in table (supplementary material II). After categorization of lead level in the studied sample, the odds ratio was calculated for high level group compared to the reference group (≤0.164 mg /L). The odds of having Lead level (> 0.164) mg/L were 3.7 times higher in cases than in controls (OR=3.78; 95% CI: 1.17 – 12.19).

The Cu ROC curve was plotted to calculate cut-off point (figure 2). Area under a curve for ROC curve of Cu was (0.676) and the optimal cut-off point to diagnose colorectal cancer was (>1.3) mg/L as shown in table (4). The cut-off point of >1.3 mg/L revealed high sensitivity (56%) and high specificity (72%). The odds ratio was calculated for high level group compared to the reference group (<1.3 mg /L). The odds of having Cu level (>1.3) mg /L were 3.27 times higher in case group than in control group (OR=3.27; 95% CI: 1.01 – 10.62).

3.6. Multivariate logistic regression table showing the predictors of colorectal cancer

A multivariate stepwise logistic regression model was built in order to determine the importance of some factors in the developing of colorectal cancer; they were used as independent variables with colorectal cancer. Factors that were significant in univariate analysis were included in the multivariate logistic regression model and only four factors showed significant association with colorectal cancer. Living nearby solid waste collecting sites was the highest one with adjusted odds ratio (OR) of 83.25 (95% CI: 1.28-5419.13), followed by exposure to environmental tobacco smoke (ETS) with OR of 32.2 (95% CI: 1.53-678.07), then plasma Lead level (>0.164 mg /L) with OR of 31.06 (95% CI: 1.55 -622.59), and lastly living in house with old oily painting with OR of 9.35 (95%CI:1.02-85.79). These results giving a high concern about the harmful effect of environmental pollution on human health as shown in table (5).

The present research aimed at gaining insights into the risk factors of CRC in Egypt. It assessed the environmental risk factors and measured Pb and Cu in the plasma in cases and controls so we can determine the risks of this cancer trying to reduce its incidence and improve the environmental situation in Egypt.

4.1. Socioeconomic characteristics

The study showed an association between low educational level and increased risk of colorectal cancer, there was a significant difference between cases and controls. These results were consistent with the study held in 2022 which assess the association between sociocultural factors and the risk for CRC. It concluded that participants with high level of education were at lower colorectal cancer risk (HR = 0.81; 95% CI, 0.67–0.98). (28) Highly educated individuals have a higher knowledge about the potential risk factors and symptoms of cancer than those with low level of education. (29)

It was proved that there was a significant relation between the lower income level or high crowding index and increased risk of colorectal cancer. This finding was in accordance with a retrospective cohort study carried out by Liu et al (2016). They indicated that the risk of colorectal cancer tended to increase with decreasing median income of the studied population. (30) Low income and high crowding index are indicators for low socioeconomic class that could increase the chance of exposure to many risk factors of CRC such as pollution, hazards in work and smoking. They had low quality of life and low concern about their health. (28, 31)

As shown from the present study, chronic diseases especially diabetes mellitus and comorbidities increased the risk for CRC. This result was in accordance to a large cohort study carried out by Ma et al. (2018). They concluded that the risk for CRC among diabetic men was 1.42 times higher than non-diabetics (HR: 1.42; 95% CI: 1.12–1.81) and the risk increased also among diabetic women but to a lesser extend (HR: 1.17; 95% CI: 0.98–1.39). (32) Chronic diseases could weaken the immunity and increase the inflammatory process and markers which on the long time may lead to abnormal cell growth and cancer. (33)

4.2 indoor environmental risk factors

According to our study, active smoking had no relation with CRC while regular exposure to ETS increased the risk of CRC. Similar results were found in a case-control study held in Algeria. The study revealed no significant association between active smoking and CRC (OR, 1.45; 95% CI, 0.96-2.18) while significant association between ETS exposure and CRC (OR, 2.55; 95% CI, 1.70-3.82). (34) In the same vein, a cross sectional study held by lee et al., (2016) reported significant association between exposure to ETS and a lesion that is well-defined precursor to CRC (aOR, 4.44; 95% CI, 2.07–9.51; p < 0.001). (35) Smoking released more than 70 carcinogenic substances. Polycyclic aromatic hydrocarbons and nitrosamines may lead to abnormal DNA that can’t be repaired, permitting replication of permanent mutations. Also, tobacco smoke enhances cell proliferation and migration of colonic cancer cells. (36)

In the current study, about three quarters of the cases had drinking water problems (changing the color or odor, turbid water, and inadequate good water source) and they had significant higher odds than controls. More than half of cases had old lead water pipes and around one third of them suffering from wastewater problems. All these factors raise the risk of exposure to heavy metals, trihalomethans, nitrates and pesticide residues. These results were supported by many studies suggested that exposure to widespread drinking water chemicals may increase the risk for CRC through inflammatory processes. (36-39)

Martin et al (2018) in a Brazilian study suggested that the excessive exposure to pesticides may correlate to increased rate of colorectal cancer. (40) This evidence was supported by Santiago et al (2021) who carried out a systematic review with meta-analysis study as they reported positive evidence for the association between pesticides and CRC. (41) Pesticides may act either as carcinogens or cancer promoters. A cancer promoter usually activates transcriptional and epigenetic mechanisms that induce proliferation but inhibit apoptosis. (42)

Old wall covering paint had significant association with CRC as shown in our research. Old paint has high concentration of Pb that could induce DNA breakdown and abnormal cell proliferation which are crucial step in pathogenesis of cancer. (43)

Working condition

Concerning working condition, in the present research, working for long hours, exposure to physical hazards (noise or vibration) and chemical hazards (heavy metals, pesticides, diesel, dust or smoke) were linked to high risk of CRC.

A case–control study conducted in Spain, reported that prolonged night-shift work and excess exposure to artificial light at night were associated with increased risk for colonic cancer. This may be due to disturbance in the circadian rhythm which disrupts the immunity and normal cell proliferation. (44, 45) prolonged working hours make workers more exposed to work physical and chemical hazards and less concern with safety. (46)

Talibov et al (2019) after studying the data from Scandinavian country found that exposure to diesel was connected to a increase in the risk of CRC with dose-response relationship (OR = 1.12, 95% CI; 1.05–1.18). (47) Negrichi and Taleb stated that occupational exposure to chemical hazards were associated with high risk of CRC. (34)

4.3 outdoor environmental risk factors

The present study found significant association between living near solid waste collecting sites or landfills and CRC. The literature found weak evidence between CRC and living near garbage. Yet, Environmental contamination with chemicals and e-waste on open dump sites makes the dwellers near these areas more prone to chronic diseases included cancer. Water supply near the dump areas (mostly from illegal connections that are susceptible to breakage) may be contaminated by leachate which contains heavy metals and persistent organic pollutants. This unhealthy environment could increase the risk of cancer. (48, 49)

Living near cell phone station increased the risk of CRC as shown in the present study. Few studies assessed the relation between exposure to radiation from mobile phones and CRC. Ozgur et al. (2021) tested the radiofrequency radiation effect on colorectal cancer cell. They found exposure to radiofrequency radiation increased apoptosis and inflammatory response of cells which are indicator of bad response. This area of research still needs more efforts to illustrate the relation between modern devices and the risk of chronic diseases including cancer. (50)

Concerning dietary habits in the current study, the only diet that had significant relation with CRC was carbonated beverages. Pacheco et al. (2019) augmented this relation as they stated that consumers of fizzy drinks had a relative risk of 1.14 for CRC compared with people who rarely or never drank them. (51) Similarly, Algerian case-control study proved that soft drinks regular consumption increase the risk of CRC (OR = 2.66, 95% CI; 1.78–3.99). (34) In contrary, Chazelas et al. did not found association between sugary drinks and CRC. (52)

Carbonated beverages could lead to CRC directly through introducing harmful additives to the body and indirectly through enhancing the development hyperinsulinemia, type 2 diabetes, and an increase in inflammatory markers. They may increase visceral adiposity promoting tumorigenesis by induce DNA damages or methylation alterations. (52-54)

Lead and copper plasma levels

According to Centers for Disease Control and Prevention (CDC), the upper limit of lead concentration in blood is 5 μg/dL which means 0.05 mg/L. (55, 56) In the current study, the mean Pb level in cases was 0.45 ± 0.48 mg/L and for controls was 0.21 ± 0.25 mg/L. The mean plasma lead level in both cases and controls was higher than permissible level; however the mean plasma lead level in cases was more than double the value for controls. The results of the present study were supported by a case-control study held in China. Lin et al. (2018) examined Pb concentration in 167 patient of gastric and colorectal tumors and 112 healthy controls and proved highly significant difference between the two groups (p<0.05). (57)

According to National Institute of Health (NIH) normal serum concentration for Cu is between 63.5–158.9 μg /dL which means between 0.635- 1.589 mg/L. (58) In the present study, the mean Cu level in cases was 1.46 ± 0.64 mg/L and for controls was 1.10 ± 0.41 mg/L. The cases had mean plasma Cu concentrations near the upper permissible level and had significantly higher levels of Cu than control group. Sohrabi et al. (2018) indicated that Cu integrates in many pro-angiogenesis pathways that could be important for CRC carcinogenesis. (59)

Juloski et al (2020) investigated the levels of heavy metals in healthy and cancerous tissue in the same patients. They proved significant higher concentrations of heavy metals in malignant tissue of colorectal cancer (CRC) than adjacent healthy colonic tissue. (60) The different levels in the concentrations of Pb and Cu between diseased and healthy tissues support that trace elements played an important role in the occurrence and progression of colorectal cancer. (59, 60) High levels of heavy metals due to environmental pollution could induce abnormal cell reactions and disrupt DNA which could be crucial step in carcinogenesis. (61)

All these environmental factors should be investigated on large scale to shed the light on the role of environmental pollution in carcinogenesis and to implement integrated programs to protect health from these possible risk factors.

It was evident that colorectal cancer is a multi-factorial disease, where many risk factors interact and contribute to its development. The current study showed that the environmental exposures could share in the etiology of the colorectal cancer. Mean Pb plasma level was higher than reference value for both cases and controls and the cases had about double mean value than controls. Multivariate logistic regression model for environmental risk factors of CRC showed four factors with significant association with colorectal cancer. The highest factor sharing the risk for CRC was living nearby solid waste collecting sites, followed by exposure to environmental tobacco smoke (ETS), then plasma Lead level (>0.164 mg /L) and lastly living in old oily painting houses.

Colorectal cancer is considered as one of the most common digestive system malignancies that exhibits higher morbidity and mortality all over the world. Its prevalence rate is increasing largely in the recent decades especially in the developing countries.

Many epidemiological studies have focused on the role of diet, environmental pollution, obesity, alcohol intake, social stress, tobacco smoking and high consumption of red meat (especially processed meat), heavy metals, low consumption of fruits, vegetables, dietary fibers, and sedentary life style as possible risk factors.

the present study aimed to measure the level of lead and copper in colorectal cancer patients and healthy controls. It aimed also to identify environmental risk factors of colorectal cancer then to determine the relation between identified environmental risk factors and level of lead and copper in colorectal cancer patients.

The study was conducted at the oncology and nuclear medicine department of Alexandria Main University Hospital. Cases were colorectal cancer patients attending the oncology outpatient clinic, and controls were healthy individuals matched to cases on age and sex

Questionnaire was administered to participants and was used to collect data from cases and controls. A heparinized blood sample was drawn from each participant to measure the level of lead and copper by flame atomic absorption spectrometry after wet digestion.

By performing a multivariate stepwise logistic regression analysis, four factors showed significant association with colorectal cancer. Living nearby solid waste collecting sites was the highest one with adjusted odds ratio (OR) of 83.25 (95% CI: 1.28-5419.13), followed by exposure to environmental tobacco smoke (ETS) with OR of 32.2 (95% CI: 1.53-678.07), then Lead level (>0.164 mg /L) with OR of 31.06 (95% CI: 1.55 -622.59), and lastly living in house with old oily painting with OR of 9.35 (95%CI:1.02-85.79).

In conclusion, it was evident from the results that colorectal cancer is multi-factorial disease, where many risk factors interact and contribute to its development. The current study showed that the environmental exposures and the possible etiological mechanisms in colorectal cancer development would allow us to reduce the incidence and prevalence rates and better health care policies would be adapted to improve early detection of the disease.

The present research studied the environmental risk factors of CRC which were rarely studied in Egypt. It sheds the light towards the neglected environmental pollution that could be an important cause of many dangerous diseases. Also, It measured some of the heavy metals in the blood that could have a share in the pathogenesis of the CRC. The role of these heavy metals in different diseases was seldom studied in Egypt.

Regarding the design of the study (case-control), there is a potential risk for recall and misclassification bias as most of the exposure data were based on participants’ memory, but matching the cases and controls on some confounders, carrying out some objective blood tests and performing logistic regression model could reduce this bias. The small sample size may affect the generalization of the findings, although we apply random sampling and the sample size was calculated based on a previous study using G. Power software. The absence of genetic information for participants may affect the conclusion from the study, but we asked them about the detailed family history to detect any relevant information that could be related to genetic factors.

aOR	:	Adjusted Odds Ratio
BMI	:	Body Mass Index
CDC	:	Centers for Disease Control and Prevention
CI	:	Confidence Interval
CRC	:	Colorectal Cancer
CIMP-positive	:	CpG Island Methylator Phenotype
Cu	:	Copper
ETS	:	Environmental Tobacco Smoke
HR	:	Hazards Ratio
IQR	:	Interquartile Range
NIH	:	National Institute of Health
OR	:	Odds Ratio
Pb	:	Lead
ROC Curve	:	Receiver Operating Characteristic Curve
ROS	:	Reactive Oxidative Species
SD	:	Standard Deviation
SES	:	Socioeconomic Status
SPSS	:	the Statistical Package for the Social Sciences
WHO	:	World Health Organization
X²	:	Pearson’s Chi-square test

Supplementary Materials: Questionnaire, sensitivity and specificity of different cut o levels of Lead and Copper, ethical approval.

Author Contributions: Conceptualization, M.H.A., M.H.A., and S.S.M; Methodology, S.S.M. and M.F.H.; Selection of cases and controls: M.F.M.; Software, S.S.M; Formal Analysis, S.S.M .and M.F.H.; Resources, S.S.M.; Data Curation, S.S.M, and M.F.H.; Writing–Original Draft Preparation, S.S.M,, and M.F.H.; Writing–Review & Editing, M.F.M, M.F.H. and M.H.A.; Visualization, M.F.H.; Supervision, M.H.A. and M.F.H and M.F.M.; All authors have read and agreed to the published version of the manuscript.

Funding: This study received no external funding.

Ethics approval and consent to participate: Institutional Review Board Statement, This study was approved by the Ethics Committee of the High Institute of Public Health, Alexandria University.

Informed Consent Statement: Informed consent was obtained from all the participants involved in the research.

Data Availability Statement: All data are available upon request from the first author.

Acknowledgments:

The authors expressed deep gratitude to the participants who provided us with their time and agreed to share in our study.

Conflicts of Interest: The authors declare no conflicts of interest.

Consent for publication: not applicable

I hereby declare that no part of this article has been submitted to any other journal for publication

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Table (1): Distribution of the study sample according to some socio-demographic characteristics, family and medical history and some life style characterstics (Alexandria Main University Hospital, 2020.

Socio-demographic and life style characteristics	Cases (n = 25)		Controls (n = 25)		Test of Sig.	P
Socio-demographic and life style characteristics	No.	%	No.	%	Test of Sig.	P
Sex
Male	13	52.0	13	52.0	χ²= 0.00	^FEp= 1.000
Female	12	48.0	12	48.0	χ²= 0.00	^FEp= 1.000
Age (years)
<40®	4	16.0	5	20.0	χ²= 1.37	^MCp= 0.812
40 – 49	9	36.0	11	44.0
50 – 59	6	24.0	6	24.0
60+	6	24.0	3	12.0
Min. – Max.	23.0 – 67.0		25.0 – 64.0		t= 1.19	0.239
Mean ± SD.	49.72 ± 11.18		46.16 ± 9.90
Median (IQR)	49.0 (45.0 – 58.0)		46.0 (42.0 – 53.0)
Education Illiterate Primary/preparatory Secondary/above intermediate Higher education®	7 5 6 7	28.0 20.0 24.0 28.0	2 1 3 19	8.0 4.0 12.0 76.0	χ²= 12.63^*	^MCp= <0.006^*
Family income Not enough Just enough Enough	3 17 5	12.0 68.0 20.0	2 3 20	8.0 12.0 80.0	χ2= 19.68^*	MCp= <0.001^*
Crowding index <1( high SES) 1-(medium SES) 2+(low SES)	1 10 14	4.0 40.0 56.0	1 20 4	4.0 80.0 16.0	χ²=9.09	^MCp <0.001^*
Family history of CRC No Yes	19 6	76.0 24.0	21 4	84.0 16.0	χ²=0.50	0.48
Use of medication due to comorbid diseases Yes No®	13 12	52.0 48.0	5 20	20.0 80.0	χ²= 5.56^*	0.018
BMI (kg/m2) < 18.5 (underweight) 18.5 – (normal) 25 – (overweight) ≥ 30 (obesity)	4 9 5 7	16.0 36.0 20.0 28.0	1 11 7 6	4.0 44.0 28.0 24.0	χ2= 2.32	MCp= 0.5
Tobacco smoking No smoking Active smoker Previous smoker	14 5 6	56.0 20.0 24.0	20 4 1	80.0 16.0 4.0	χ²=4.61	^MCp= 0.08
Practicing exercise regularly No Yes	21 4	84.0 16.0	17 8	68.0 32.0	χ²=1.75	0.19
Eating red meat No Once weekly 3 – 4/week	4 16 5	16.0 64.0 20.0	1 14 10	4.0 56.0 40.0	χ2=3.41	0.22

c²: Chi square test MC: Monte Carlo test FE: Fisher Exact test

t: indeendant t-test U: Mann Whitney test

p: p value for comparing between the studied groups *: Statistically significant at p ≤ 0.05

Table (2): Estimation of the risk of colorectal cancer in relation to some socio-demographic factors, indoor and outdoor environmental risk factors (Alexandria Main University Hospital, 2020).

Socio-demographic characters

Indoor, outdoor environmental risk factors , dietary habits

Cases
(n = 25)

Controls^®
(n = 25)

Test of Sig.

P

OR (95% CI.)

No.

%

No.

%

Educational level

Illiterate
Primary
Secondary
Higher education®

7

5

6

7

28.0

20.0

24.0

28.0

2

1

3

19

8.0

4.0

12.0

76.0

χ²=
11.62^*

0.015

0.018

0.05

9.5(1.579-57.16)

13.57(1.39-137.45)

5.429(1.059-27.833)

1.000

Family income

Not enough
Enough®

20

5

80.0

20.0

5

20

20.0

80.0

χ²=
18.00^*

0.001

16.0(4.0-63.975)

1.000

Crowding index

1-®
2+

11

14

44.0

56.0

21

4

84.0

16.0

χ²=
8.681^*

0.003^*

1.000

6.682 (1.769–25.245)

Comorbidities

χ2=

6.650*

0.010^*

Yes

15

60.0

6

24.0

4.75 (1.406 –16.051)

No®

10

40.0

19

76.0

1.000

Use of medications

Yes
No®

13

12

60.0

40.0

5

20

20.0

80.0

χ²=
5.556^*

0.018

4.333 (1.235 –15.21)

1.000

Exposure to ETS

Yes
No®

13

12

52.0

48.0

2

23

8.0

92.0

χ2= 9.19*

0.002

7.94 (1.88 – 33.50)

1.00

Wall covering paint

Old oily paint
New paint®

20

5

80.0

20.0

6

19

24.0

76.0

χ2= 15.7*

<0.001

12.67(3.31 –48.50)

1.00

Usage of insecticides

sometimes
No®

18

7

72.0

28.0

8

17

32.0

68.0

χ2=8.01*

0.005

5.46 (1.63 – 18.36)

1.00

Presence of cell phone station

Yes
No ®

7

18

28.0

72.0

1

24

4.0

96.0

χ2=

5.36*

FEp=

0.045

9.33 (1.05 –82.78)

1.00

Living nearby solid waste collecting sites

Yes
No®

9

16

36.0

64.0

2

18

12.0

88.0

χ2=

3.95*

0.043

4.13 (0.96 – 17.70)

1.00

Working hrs./day

>7hrs
<=7hrs ®

11

3

78.6

21.4

3

22

10.0

90.0

χ2=

16.39

0.001

33.00(4.74–23.0)

1.00

Physical risk factors

Yes
No ®

13

1

93.0

7.0

5

15

25.0

75.0

χ2=

15.22*

<0.001

39 (4.02 –38.19)

1.00

Chemical risk factors

Yes
No ®

11

3

78.6

21.4

5

15

25.0

75.0

χ2=

9.49*

0.002

11 (2.16–56.09

1.00

Water problems

yes
No®

18

7

72.0

28.0

4

21

16.0

84.0

χ2=

13.24*

0.001*

13.5(3.40–53.68)

1.00

Water pipes

Old pipes

Plastic pipes®

14

11

56.0

44.0

2

23

8.0

92.0

χ2=

16.10*

<0.001*

14.63(2.82-75.95)

1.00

Waste water problems

Yes

No®

9

16

36.0

64.0

1

24

4.0

96.0

χ2=

8.00*

<0.01*

13.5(1.56–117.14)

1.000

Consumption of carbonated beverages

Yes

No®

16

9

64.0

36.0

7

18

28.0

72.0

χ2=

6.522*

0.01*

4.57(1.38-15.11)

1.00

χ²: Chi square test, FE: Fisher Exact,OR: Odds ratio, ®: Reference group

CI: Confidence interval,

p: p value for comparing between the studied groups

*: Statistically significant at p ≤ 0.05

Table (3): Estimation of the risk of colorectal cancer in relation to Lead and Copper plasma levels (Alexandria Main University Hospital, 2020).

	Cases (n = 25)		Controls^® (n = 25)		Test of Sig.	P	OR (95% CI.)
	No.	%	No.	%
Pb level (mg/L)
(≤0.164)^®	9	36.0	17	68.0	χ²= 5.13^*	0.024^*	1.000
(>0.164)	16	64.0	8	32.0			3.78 (1.17 – 12.19)
Min. – Max.	0.04 – 1.76		0.003 – 0.94		U= 196.50^*	0.024^*
Mean ± SD.	0.45 ± 0.48		0.21 ± 0.25				–
Median (IQR)	0.21 (0.11 – 0.66)		0.13 (0.05 – 0.30)
Cu level (mg/L)
(≤1.3)^®	11	44.0	18	72.0	χ²= 4.02^*	0.045^*	1.000
(>1.3)	14	56.0	7	28.0			3.27 (1.01 – 10.62)
Min. – Max.	0.79 – 3.79		0.10 – 1.84		U= 206.50^*	0.040^*
Mean ± SD.	1.46 ± 0.64		1.10 ± 0.41				–
Median (IQR)	1.36 (1.05 – 1.61)		1.08 (0.88 – 1.31)

χ²: Chi square test, U: Mann Whitney test,OR: Odds ratio, ®: Reference group

CI: Confidence interval,

p: p value for comparing between the studied groups

*: Statistically significant at p ≤ 0.05

BEI (Biological Exposure Index of Pb in plasma=0.0001mg/L) = (1.00 µg/L) in adults

Table (4): Area under the ROC curve of Lead and Copper levels (Alexandria Main University Hospital, 2020).

	AUC	P	95% CI	Cut off	Sensitivity	Specificity	PPV	NPV
Pb level (mg/L)	0.69	0.024^*	0.54 – 0.83	>0.164^#	64.0	68.0	66.7	65.4
Cu level (mg/L)	0.67	0.040^*	0.52 – 0.82	>1.3^#	56.0	72.0	66.7	62.1

AUC: Area Under a Curve p value: Probability value

CI: Confidence Intervals

NPV: Negative predictive value PPV: Positive predictive value

*: Statistically significant at p ≤ 0.05

Table (5): Analysis of risk factors affecting the risk of colorectal cancer by logistic regression (Alexandria Main University Hospital, 2020).

Independent variables	B	p-value	OR	95% CI
Independent variables	B	p-value	OR	LL	UL
Pb level (mg/L) (>0.14)	3.44	0.025^*	31.06	1.55	622.59
Cu level (mg/L) (>1.3)	1.74	0.123	5.70	0.63	52.02
ETS Exposure	3.47	0.026^*	32.2	1.53	678.07
Cell phone stations	0.58	0.709	1.78	0.09	36.39
Carbonated beverages Consumption	1.92	0.117	6.79	0.62	74.29
Old oily wall paints	2.24	0.043^*	9.35	1.02	85.79
Living nearby solid waste collecting sites	4.42	0.038^*	83.25	1.28	5419.13
Constant	-6.56	0.004^*

B: Unstandardized Coefficients OR: Odds ratio

CI: Confidence interval *: Statistically significant at p ≤ 0.05

No competing interests reported.

supplementarymaterials1.docx

Environmental Risk Factors and Plasma Concentration of Lead and Copper in Colorectal Cancer Patients in Alexandria, Egypt: A case-control study

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Abstract

Figures

1. Introduction

2. Methodology

3. Results

4. Discussion

5. Conclusion

Summary

Strengths of the study

Limitations of the study

Abbreviations

Declarations

References

Tables

Additional Declarations

Supplementary Files

Status:

Version 1