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Case Control Studies Critical Appraisal Tool
Answers: Yes, No, Unclear or Not/Applicable
1. Were the groups comparable other than presence of disease in cases or absence of disease in controls?
The control group should be representative of the source population that produced the cases. This is usually done by individual matching; wherein controls are selected for each case on the basis of similarity with respect to certain characteristics other than the exposure of interest. Frequency or group matching is an alternative method. Selection bias may result if the groups are not comparable.
2. Were cases and controls matched appropriately?
As in item 1, the study should include clear definitions of the source population. Sources from which cases and controls were recruited should be carefully looked at. For example, cancer registries may be used to recruit participants in a study examining risk factors for lung cancer, which typify population-based case control studies. Study participants may be selected from the target population, the source population, or from a pool of eligible participants (such as in hospital-based case control studies).
3. Were the same criteria used for identification of cases and controls?
It is useful to determine if patients were included in the study based on either a specified diagnosis or definition. This is more likely to decrease the risk of bias. Characteristics are another useful approach to matching groups, and studies that did not use specified diagnostic methods or definitions should provide evidence on matching by key characteristics. A case should be defined clearly. It is also important that controls must fulfil all the eligibility criteria defined for the cases except for those relating to diagnosis of the disease.
4. Was exposure measured in a standard, valid and reliable way?
The study should clearly describe the method of measurement of exposure. Assessing validity requires that a ‘gold standard’ is available to which the measure can be compared. The validity of exposure measurement usually relates to whether a current measure is appropriate or whether a measure of past exposure is needed.
Case control studies may investigate many different ‘exposures’ that may or may not be associated with the condition. In these cases, reviewers should use the main exposure of interest for their review to answer this question when using this tool at the study level.
Reliability refers to the processes included in an epidemiological study to check repeatability of measurements of the exposures. These usually include intra-observer reliability and inter-observer reliability.
5. Was exposure measured in the same way for cases and controls?
As in item 4, the study should clearly describe the method of measurement of exposure. The exposure measures should be clearly defined and described in detail. Assessment of exposure or risk factors should have been carried out according to same procedures or protocols for both cases and controls.
6. Were confounding factors identified?
Confounding has occurred where the estimated intervention exposure effect is biased by the presence of some difference between the comparison groups (apart from the exposure investigated/of interest). Typical confounders include baseline characteristics, prognostic factors, or concomitant exposures (e.g. smoking). A confounder is a difference between the comparison groups and it influences the direction of the study results. A high quality study at the level of case control design will identify the potential confounders and measure them (where possible). This is difficult for studies where behavioral, attitudinal or lifestyle factors may impact on the results.
7. Were strategies to deal with confounding factors stated?
Strategies to deal with effects of confounding factors may be dealt within the study design or in data analysis. By matching or stratifying sampling of participants, effects of confounding factors can be adjusted for. When dealing with adjustment in data analysis, assess the statistics used in the study. Most will be some form of multivariate regression analysis to account for the confounding factors measured. Look out for a description of statistical methods as regression methods such as logistic regression are usually employed to deal with confounding factors/ variables of interest.
8. Were outcomes assessed in a standard, valid and reliable way for cases and controls?
Read the methods section of the paper. If for e.g. lung cancer is assessed based on existing definitions or diagnostic criteria, then the answer to this question is likely to be yes. If lung cancer is assessed using observer reported, or self-reported scales, the risk of over- or under-reporting is increased, and objectivity is compromised. Importantly, determine if the measurement tools used were validated instruments as this has a significant impact on outcome assessment validity.
Having established the objectivity of the outcome measurement (e.g. lung cancer) instrument, it’s important to establish how the measurement was conducted. Were those involved in collecting data trained or educated in the use of the instrument/s? (e.g. radiographers). If there was more than one data collector, were they similar in terms of level of education, clinical or research experience, or level of responsibility in the piece of research being appraised?
9. Was the exposure period of interest long enough to be meaningful?
It is particularly important in a case control study that the exposure time was sufficient enough to show an association between the exposure and the outcome. It may be that the exposure period may be too short or too long to influence the outcome.
10. Was appropriate statistical analysis used?
As with any consideration of statistical analysis, consideration should be given to whether there was a more appropriate alternate statistical method that could have been used. The methods section should be detailed enough for reviewers to identify which analytical techniques were used (in particular, regression or stratification) and how specific confounders were measured.
For studies utilizing regression analysis, it is useful to identify if the study identified which variables were included and how they related to the outcome. If stratification was the analytical approach used, were the strata of analysis defined by the specified variables? Additionally, it is also important to assess the appropriateness of the analytical strategy in terms of the assumptions associated with the approach as differing methods of analysis are based on differing assumptions about the data and how it will respond.
RESEARCH ARTICLE Open Access
Determinants of breast cancer in Saudi women from Makkah region: a case-control study (breast cancer risk factors among Saudi women) Fatmah J. Alsolami1, Firas S. Azzeh2*, Khloud J. Ghafouri2, Mazen M. Ghaith3, Riyad A. Almaimani4, Hussain A. Almasmoum3, Rwaa H. Abdulal5, Wesam H. Abdulaal6, Abdelelah S. Jazar2 and Sufyan H. Tashtoush7
Abstract
Background: There are various factors that play a major role in influencing the overall health conditions of women diagnosed with breast cancer. The population of women in Makkah region are diverse, therefore it is significant to highlight the possible determinants of breast cancer in this population. This is a case-control study that assessed determinants of breast cancer including socioeconomic factors, health-related characteristics, menstrual histories and breastfeeding among postmenopausal women in Makkah region in Saudi Arabia.
Methods: A total of 432 female participants (214 cases and 218 controls) were recruited for this study. A validated questionnaire was completed by trained dietitians at King Abdullah Medical City Hospital in the Makkah region of Saudi Arabia.
Results: Results displayed that determinants of breast cancer were associated significantly (P < 0.05) with unemployment, large family size, lack of knowledge and awareness about breast cancer, obesity, sedentary lifestyle, smoking, starting menarche at an early age, as well as hormonal and non-hormonal contraceptive use. There was no effect of diabetes, hypertension, hyperlipidemia, and duration of breastfeeding on the incidence of breast cancer.
Conclusion: In summary, the results of this study accentuate the possible effect of socioeconomic factors, health- related characteristics and menstrual history on the incidence of breast cancer in postmenopausal women in the Makkah region. Education programs should be applied to increase breast cancer awareness and possibly decrease its incidence.
Keywords: Breast cancer, Breastfeeding practices, Economic status, Lifestyle pattern, Menstruation
Background There has been an increasing prevalence of breast cancer among females around the world [1]. In Saudi Arabia, the recent statistics regarding women diagnosed with breast cancer are shocking. Even with the current advancements in the healthcare system and the breast cancer awareness campaign, the latest prevalence published by the Saudi Health Council in 2014 showed that breast cancer
accounted for 29% of all the cancer types diagnosed in women. Unfortunately, few women present with early stages of the disease, compared to a substantial proportion of women who present in the late stages of breast cancer, when the tumour has become metastatic [2]. Previous studies have reported that there are several
common factors present in women diagnosed with breast cancer, such as their ages, ages at menarche and menopause, family histories, lifestyles and oral contra- ceptive usage [3, 4]. However, the presentation of these factors varies among different populations of women. A greater number of breast cancer diagnoses have been
© The Author(s). 2019 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
* Correspondence: [email protected] 2Department of Clinical Nutrition, Faculty of Applied Medical Sciences, Umm Al-Qura University, P.O. Box: 7067, Makkah 21955, Kingdom of Saudi Arabia Full list of author information is available at the end of the article
Alsolami et al. BMC Public Health (2019) 19:1554 https://doi.org/10.1186/s12889-019-7942-3
linked to variances in the lifestyle patterns and socioeco- nomic factors. From the point of view of epidemiological studies, exploring the predominant risk factors in a se- lected population of women can help to direct the per- spective of breast cancer prevention [4]. The population of women in the region of Makkah is
diverse, with different lifestyle patterns, economic sta- tuses and breastfeeding practices. These factors play sig- nificant roles in influencing the overall health conditions and make it an area of interest for investigating the de- terminants of breast cancer in this specific population. Furthermore, postmenopausal women were more likely to have breast cancer than premenopausal women [5]. Therefore, the aim of this study was to explore which of the socioeconomic factors, health-related characteristics, menstruation starting and ending ages and breastfeeding histories were determining factors for postmenopausal women diagnosed with breast cancer.
Methods Study design and setting This case-control study was conducted from June 2014 through November 2016 at King Abdullah Medical City Hospital (KAMC) in the Makkah region of Saudi Arabia. This hospital is the only centre that provides cancer screening and treatment for residents in Makkah region.
Participants A total of 432 female participants (214 cases and 218 controls) were recruited for this study. We included postmenopausal Saudi women of Arabic ethnicity aged > 45 years from the Makkah region who were newly di- agnosed with breast cancer that was biopsy confirmed by a cancer pathologist in KAMC. Studies have showed that factors associated to breast cancer differs in racial groups [6, 7]. Therefore, we excluded women of any other nationality and African-Asians ethnicity. We also not included any breast cancer women diagnosed with any other type of cancer and who had a metastatic (stage IV) and/or recurrent breast cancer. Any woman stopped her menstrual periods within the last 12 months was de- fined as postmenopausal. The women in the control group were made up of hospital workers and the pa- tients’ companions and friends. The controls were se- lected from the same region of cases and matched on a single year of age for both groups. Based on the above exclusion and inclusion criteria, 214 out of 229 cases were included in this study. However, some patients and healthy individuals were not recruited in this study due to; non-Saudi nationality (n = 7 cases and 12 controls), African-Asians ethnicity (n = 3 cases and 4 controls), premenopausal women and/or aged < 45 years (n = 2 cases), metastatic breast cancer diagnosis (n = 1 case),
recurrent breast cancer (n = 1 case), and diagnosis of multiple cancer types (n = 1 case).
Data collection Convenience sampling was used to collect the data for this study. As a routine work in the hospital, all newly diagnosed cancer patients should meet a registered dietitian to evaluate his/her nutritional status. During this evaluation, a self-administered questionnaire was completed by each of the participants via a face-to-face interview. The socioeconomic factors, health-related characteristics, menstrual histories as well as breastfeed- ing duration tested in this study were part of a previ- ously validated questionnaire developed by Wilson et al. (2013) [8] that focused on well-known determinants as- sociated with breast cancer in postmenopausal women. Each participant’s body mass index (BMI; kg/m2) was calculated after measuring the weight and height in the hospital and at the time of the data collection. Any par- ticipant with a BMI < 18.5 kg/m2 was classified as under- weight, normal weight was 18.5–24.9 kg/m2, overweight was 25–29.9 kg/m2 and obese was > 30 kg/m2.
Statistical analysis All of the statistical tests were completed using IBM SPSS Statistics for Windows version 20.0 (IBM Corp., Armonk, NY, USA), and a P-value < 0.05 was set for the significant differences. The Kolmogorov-Smirnov nor- mality test was used to determine the normality of distri- bution. The P-value for each parameter was determined using a suitable test, which is mentioned as a footnote in each table. In order to ascertain the differences between the cases and the controls, the data from the participants was stratified using a case-control status. A chi squared test and t-test were conducted for the parametric and nonparametric variables to determine the differences in the socioeconomic factors, health-related characteristics, menstrual histories and breastfeeding durations. To determine the possible risk factors related to breast
cancer, the odds ratio (OR), 95% confidence interval (95% CI) and β-coefficient were determined by using a logistic regression test. All of the variables were adjusted for potential confounders; age (continuous), BMI (con- tinuous), employment, family income, education, family size, marital status, physical activity, smoking, family his- tory of breast cancer, other health problems, contracep- tive use, age at menarche, age at menopause, and breastfeeding duration.
Results An overview of the socioeconomic characteristics of the participants is presented in Table 1. The participants’ ages ranged from 45 to 75 years old, and the mean ages for the case and control groups were 57 ± 7.3 years old
Alsolami et al. BMC Public Health (2019) 19:1554 Page 2 of 8
and 56.9 ± 8.6 years old, respectively. The results showed significant differences regarding some of the socioeco- nomic factors (P < 0.001), such as employment, income, education and family size. The highest employment status percentage in both
groups was 81.7% employed participants in the control group, with 73.8% unemployed in the case group. Nearly one-half of the participants in the case group (43.9%) fell in the low-income category of < 5000 Saudi Riyal (SR) of monthly income (~ 1333.17 American Dollar) when compared to the control group (9.6%). Both groups had low percentages in the highest income category of > 20, 000 SR (~ 5332.70 USD): 14.7% for the control group and 3.8% for the case group. The illiteracy rate was higher among the cases (15%)
when compared to the control group (0.9%). All of the participants in both groups reported varied results in obtaining an education, with a higher result for postsec- ondary education of 87.1% for the control group,
compared to 22.3% for the case group for the same level of education. Having a large family size (6 or more fam- ily members) was more common in the case group (81.3%), while the control group showed no noticeable difference in the percentages of having small or large family sizes (52.3 and 47.7%, respectively). There were no significant differences in the marital statuses in either group (P > 0.05); the percentages of married participants were fairly high in both groups (87.6% for the controls and 94.1% for the cases). With regard to the health-related characteristics for the
participants in this study (Table 2), the BMI (P < 0.001), regular exercise (P = 0.009), cancer awareness (P < 0.001), smoking (P < 0.001), diabetes (P < 0.001), hypertension (P < 0.001) and the use of contraceptives (P < 0.001) were significant when testing the differences between the groups. Based on these results, it was clear that there was a higher BMI (obese category) percentage of 63.6% among the cases when compared to the control group (24.3%). It was also evident that regular exercise was practiced among few of the participants in both the control and case groups (37.2% vs. 26.2%, respectively). Overall, high per- centages of the participants were aware of cancer (98.2% for the control group and 81.3% for the case group). Al- though the results of having a family history of breast can- cer were not significant (P > 0.05), the family history results of the patients with breast cancer were higher in the cases (17.8%) than in the participants in the control group (6%). The smoking status showed that 17.8% of the participants in the case group were smokers, compared to 1.4% being smokers in the control group. Additionally, the percentage of breast cancer patients
diagnosed with diabetes was higher (33.6%) than the dia- betic participants in the control group (7.8%). Similarly, hypertension was higher in the cases when compared to the control group (48.6% vs. 15.1%, respectively). The screening for positive hyperlipidaemia results showed no significant difference between the two groups, but the percentage was low in the participants in the control group (12.8%) when compared to the cases (18.7%). The use of hormonal contraceptive types was higher in the cases (43.9%), whereas the highest percentage in the control group (60.6%) included those participants not using any contraceptive methods. The results of the menstruation histories and breast-
feeding durations are shown in Table 3. Both groups re- ported higher menstruation percentages at the ages of 11–14 years old; 70.1% of the cases and 89.9% of the control group began menstruation around this age. High percentages in both groups exhibited breastfeeding his- tories, with the results showing that most of the cases (70%) breastfed for a duration of 6–12 months, while most of the participants in the control group breastfed for a duration of less than 6months. The results of the
Table 1 Socioeconomic characteristics of the study groups
Parameter Control Case P-value
Number [n (%)] 218 (50.5%) 214 (49.5%) 0.847
Age (year) 56.9 ± 8.6 57 ± 7.3 0.526
Employment
Yes 178 (81.7%) 56 (26.2%) < 0.001
No 40 (18.3%) 158 (73.8%)
Family income
< 5000 SRa 21 (9.6%) 94 (43.9%) < 0.001
5000–10000 SR 85 (39%) 88 (41.1%)
10000–20000 SR 80 (36.7%) 24 (11.2%)
> 20000 SR 32 (14.7%) 8 (3.8%)
Education
Illiterate 2 (0.9%) 32 (15%) < 0.001
Primary 3 (1.4%) 96 (44.9%)
Intermediate/secondary 23 (10.6%) 38 (17.8%)
Postsecondary 190 (87.1%) 48 (22.3%)
Family size
5 or less 114 (52.3%) 40 (18.7%) < 0.001
6 or more 104 (47.7%) 174 (81.3%)
Marital Status (Married)
Yes 191 (87.6%) 204 (94.1%) 0.087
No 27 (12.4%) 10 (5.9%)
Values are expressed as frequency (%) or Mean ± SD P-values are obtained by t-test for the parametric variable (age) or x2 for non-parametric variables aSR Saudi Riyal
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age of menopause showed no statistical difference be- tween the groups. The highest percentage was 46 years old and older for 67.3% of the cases and 56.4% of the controls. The correlations between the potential dependent vari-
ables for breast cancer are shown in Table 4. With re- gard to the socioeconomic factors, the results showed that being unemployed had an increased positive associ- ation with breast cancer (β = 1.89, OR = 6.56, 95% CI = 3.83–11.37, P < 0.001). This was similar to the results of being in the low-income category of < 5000 SR (~
1333.17 USD) (β = 3.69, OR = 39.88, 95% CI = 11.11– 143.16, P < 0.001). Additionally, the results showed a positive association between having a large family size (6 members and more) and breast cancer (β = 0.8, OR = 2.23, 95% CI = 1.15–4.3, P = 0.017). Moreover, having a primary level of education had a positive association with breast cancer (β = 4.07, OR = 58.56, 95% CI = 16.9– 202.82, P < 0.001). The health-related characteristics, such as the BMI,
exhibited positive correlations to breast cancer (β = 0.1, OR = 1.11, 95% CI = 1.07–1.14, P < 0.001), which was
Table 2 Health-related characteristics of the study groups
Parameter Control (n = 218) Case (n = 214) P-value
Weight (kg) 69.5 ± 14.7 88.5 ± 17.5 < 0.001
Height (cm) 158.6 ± 7 157.7 ± 6.7 0.637
Body Mass Index (BMI) (kg/m2) 27.7 ± 6.3 35.4 ± 10 < 0.001
BMI categories
Underweight 1 (0.4%) 0 < 0.001
Normal 69 (31.7%) 22 (10.2%)
Overweight 95 (43.6%) 56 (26.2%)
Obese 53 (24.3%) 136 (63.6%)
Cancer awareness
Yes 214 (98.2%) 174 (81.3%) < 0.001
No 4 (1.8%) 40 (18.7%)
Regularly exercise
Yes 81 (37.2%) 56 (26.2%) 0.009
No 137 (62.8%) 158 (73.8%)
Family history of breast cancer
Yes 13 (6%) 38 (17.8%) 0.072
No 205 (94%) 176 (82.2%)
Smoking
Yes 3 (1.4%) 38 (17.8%) < 0.001
No 215 (98.6%) 176 (82.2%)
Diabetes
Yes 17 (7.8%) 72 (33.6%) < 0.001
No 201 (92.2%) 142 (66.4%)
Hypertension
Yes 33 (15.1%) 104 (48.6%) < 0.001
No 185 (84.9%) 110 (51.4%)
Hyperlipidemia
Yes 28 (12.8%) 40 (18.7%) 0.062
No 190 (87.2%) 174 (81.3%)
Contraceptive use
Hormonal 55 (25.2%) 94 (43.9%) < 0.001
Not-hormonal 31 (14.2%) 32 (15%)
Don’t use 132 (60.6%) 88 (41.1%)
Values are expressed as frequency (%) P-values are obtained by Mann-Whitney test for non-parametric continuous variables (weight, height and BMI) or by x2 test for discontinuous variables
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significant in the obese BMI category (β = 1.39, OR = 4, 95% CI = 2.07–7.74, P < 0.001). Additionally, having an awareness about breast cancer and the smoking status were significant factors correlated with breast cancer. Having no awareness was positively associated with breast cancer (β = 1.87, OR = 6.47, 95% CI = 1.84–22.77, P = 0.004), while being a smoker showed an increased risk of breast factor in this study (β = 1.85, OR = 6.36, 95% CI = 1.56–26, P = 0.01). Moreover, the use of both types of contraceptive methods, hormonal and nonhormonal, in- creased the risk of breast cancer. In fact, the higher risk was involved in using a hormonal type of contraception (β = 1.91, OR = 6.78, 95% CI = 3.42–13.44, P < 0.001). Beginning one’s menstruation cycle at an early age (10
years old or less) increased the risk of breast cancer, ac- cording to the results of this study (β = 1.61, OR = 5, 95% CI = 1.12–22.29, P = 0.035). The not significantly identified variables by regression test; overweight, dia- betes, hypertension and age of stated menstruation > 15 years old, were not included in this study as determi- nants of breast cancer.
Discussion The current study investigated the effects of socioeco- nomic factors, health related characteristics, menstrual histories and breastfeeding durations on the incidence of breast cancer in postmenopausal Saudi Arabian women from the Makkah region.
Table 3 Menstrual history and breastfeeding duration of the study groups
Parameter Control (n = 218) Case (n = 214) P-value
Age of started menstruation
< 10 years old 1 (0.5) 25 (11.7%) < 0.001
11–14 years old 196 (89.9%) 150 (70.1%)
> 15 years old 21 (9.6%) 39 (18.2%)
Age at menopause
< 35 years old 2 (0.9%) 8 (3.7%) 0.271
36–40 years old 25 (11.5%) 16 (7.5%)
41–45 years old 68 (31.2%) 46 (21.5%)
> 46 years old 123 (56.4%) 144 (67.3%)
Breastfeeding duration
No 51 (23.4%) 40 (18.7%) 0.052
Yes 167 (76.6%) 174 (81.3%)
< 6months 76 (45.5%) 48 (27.6%)
6–12 months 42 (25.1%) 70 (40.2%)
> 13months 49 (29.4%) 56 (32.2%)
Values are expressed as frequency (%) Duration of breast feeding is average for each pregnancy P-values are obtained by x2 test
Table 4 Potential significant predictors related to breast cancer Independent variable β OR 95% CI P-value
Body Mass Index (BMI) (continuous) 0.1 1.11 1.07–1.14 < 0.001
BMI categories
Underweight ND ND ND ND
Normal 0 1
Overweight 0.41 1.5 0.77–2.93 0.234
Obese 1.39 4 2.07–7.74 < 0.001
Employment
Yes 0 1
No 1.89 6.56 3.83–11.37 < 0.001
Family income
< 5000 SRa 3.69 39.88 11.11–143.16 < 0.001
5000–10000 SR 2.07 7.88 2.45–25.4 0.001
10000–20000 SR 1.36 3.89 1.09–13.88 0.036
> 20000 SR 0 1
Education
Illiterate 2.98 19.7 4.33–89.54 < 0.001
Primary 4.07 58.56 16.91–202.82 < 0.001
Intermediate-secondary 1.71 5.52 2.75–11.09 < 0.001
Postsecondary 0 1
Family size
5 or less 0 1
6 or more 0.8 2.23 1.15–4.3 0.017
Regularly exercise
Yes 0 1
No 0.72 2.06 1.16–3.67 0.014
Cancer awareness
Yes 0 1
No 1.87 6.47 1.84–22.77 0.004
Smoking
Yes 1.85 6.36 1.56–26 0.01
No 0 1
Diabetes
Yes 0.5 1.65 0.81–3.35 0.165
No 0 1
Hypertension
Yes 0.51 1.67 0.91–3.04 0.097
No 0 1
Contraceptive use
Hormonal 1.91 6.78 3.42–13.44 < 0.001
None-hormonal 1.23 3.43 1.54–7.65 0.003
Don’t use 0 1
Age of started menstruation
< 10 years old 1.61 5 1.12–22.29 0.035
11–14 years old 0 1
> 15 years old 0.54 1.57 0.79–3.13 0.197
All variables were adjusted for potential confounders Abbreviations; β Beta coefficient, CI Confidence Interval, ND Not Determined, OR Odds Ratio aSR Saudi Riyal
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Low-income, family size and employment The current study showed significant findings regarding the association between being unemployed and having breast cancer, which were similar to those of having a large family and a low income. Being unemployed itself is a risk factor for having a low income, which is one of the major obstacles in the early detection of breast can- cer. In addition, the cost of diagnostic procedures is a challenge in breast cancer prevention [9]. In the current study, the majority of the women in the cases group were unemployed, which can be a clear reason for some of them being in the low-income category. In addition, an increased family size can increase the responsibility and overwhelm a family financially, which in turn, can be one reason for not being able to afford the cost of en- gaging in early breast cancer detection programs. Those cases with an increased family size in the current study were already diagnosed with breast cancer and receiving treatment, reflecting the high possibility of not having had previous preventive screenings. Unfortunately, with the increasing prevalence of breast cancer, there are still few healthcare services in Saudi Arabia that provide free screening, creating further obstacles for low-income women [10]. Trieu et al., [11] reported that postmeno- pausal women with low family size were more likely to have breast cancer than women with large family size, and this result was not in line with the study results. These conflicting results could be related to the increase ratio of breastfeeding with higher number of babies; con- sequently, decrease the possibility of breast cancer inci- dence. However, some mothers in Makkah do not like to breastfeed their babies and alternatively introduce complementary foods and/or bottle-feeding at an early age of baby’s life [12], which could increase the probabil- ity of breast cancer incidence in postmenopausal women [13]. These erroneous practices with large family size could be a risk factor for breast cancer.
Education and Cancer awareness The lack of knowledge and awareness about breast can- cer was a confirmed risk for the increasing prevalence of breast cancer. Being unaware of breast cancer showed a positive relationship toward an increased breast cancer risk in the current study (Table 4). The level of aware- ness of the cases in this study was high, which is a prom- ising value. This high number may be because breast cancer campaigns are conducted every year in Saudi Arabia on and around the breast cancer awareness day in order to spread awareness [2, 14]. Therefore, informa- tion regarding breast cancer is widely available for every- one to access via different media; however, information about breast cancer can be of less use to illiterate women. Although the percentage of women with breast cancer who had no formal education was small when
compared to the total number in the group, it still highlighted the need to consider tailored interventions for this group [15]. Health literacy remains a social de- terminant of health that affects both educated and un- educated women [16].
Obesity and exercise Research has provided evidence that a sedentary lifestyle can affect many aspects of health, such as the risk of obes- ity [17]. The results of this study showed that the rate of obesity was higher in the newly diagnosed cases with breast cancer, and that being in the higher BMI category increased the incidence of breast cancer 4-fold when com- pared to the normal weight women. These results are in line with other findings that identified a positive associ- ation between obesity and breast cancer [18, 19]. There are two reasons for these findings in newly diagnosed pa- tients. The first reflects the nature of the fat tissues (adi- pose) in obese individuals, which produce inflammatory cytokines and certain chemical mediators that assist in prompting cancer cell invasion and metastasis [20]. The second reason could be related to the gradual increase in weight while a patient is receiving cancer treatment. In newly diagnosed patients with breast cancer, a weight gain ranging from 1.0 kg to 6.0 kg has been identified in the first year after establishing treatment [21]. However, the risks contributed to obesity have become major public health problems in Saudi Arabian women [22], with more attention being paid to the trend of increasing obesity with increasing age [23]. Exercise or physical activity could be implemented to
overcome the high obesity prevalence. Exercise means a scheduled training to achieve a specific purpose, while physical activity means movement of skeletal muscle that requires some energy and can include routine daily activ- ities [24]. A lack of physical activity is a complicated facet of living a sedentary lifestyle, and the current study showed that the majority of the breast cancer cases and controls were not engaged in regular exercise routines. Regular exercise has been shown to be a significant factor that is positively associated with a decreasing incidence of breast cancer in several different studies [24, 25], similar to this study (Table 4). During the distinct stages of breast cancer, whether preventive, during treatment or post- treatment recovery, engaging in physical activity has shown its positive impact in mediating tumorigenesis and its effects on the body [26]. A sedentary lifestyle is an alarming risk on Saudi Arabian women’s health condi- tions, and interventions promoting physical activities are essential [27, 28].
Smoking The risk of smoking on the development of tumours has been tested in several types of cancer, and most of the
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published results have shown a positive association [29]. Being a smoker in this study showed a positive associ- ation with an increased risk of breast cancer of about 6 times that of nonsmokers. Smoking has been linked to an underlying tumour progression mechanism, and in- creased epithelial-to-mesenchymal transition and motil- ity have been observed in breast tumour cells after they have been exposed to cigarette smoke [29]. One cohort study that investigated the association between smoking and developing breast cancer found that among the 102, 927 women recruited for the study, during the 788,361 person-years (mean = 7.7 years) of follow up, 1815 women developed invasive breast cancer [30]. Their findings also showed that the significance of breast can- cer increased when the women started smoking at an early age (< 17-year-old) [30].
Menarche The reproductive age for women is a time when many hormonal changes arise in the body; therefore, direct ef- fects on the function and development of breast tissue can occur. The rapid increase in the production of ster- oid hormones when starting menstruation (menarche) is highly associated with an increased risk of breast cancer [31]. One meta-analysis study including 118,964 women with breast cancer (cases) and 306,091 without the dis- ease reported that the younger the age at which a woman began menstruation contributed to a greater risk of developing breast cancer, with a risk ratio of 1.05 for every year younger at the time of menarche [32]. This study revealed that starting menarche at an early age (10 years or less) increased the risk for breast cancer by 5 times when compared to those women who started at a normal age [32]. Since the beginning of the reproduct- ive age varies among women, breast cancer preventive measures will have a greater effect if they are initiated early in a woman’s life [32].
Contraceptives Obviously, the effects of the hormonal changes on a woman’s body during reproductive age can increase the risk of breast cancer, and the effects of synthetic hor- mones are no exception. Several studies have found a re- verse effect of contraceptives on breast tissue [33–35]. The combined estrogen in hormonal contraception has been identified in earlier studies as a major cause for breast cancer [33, 34]. One cohort study that followed 1.8 million women for an average of 10.9 years showed that 11,517 cases of breast cancer occurred in those women using hormonal contraception when compared to those who did not use any contraceptive methods [34]. Those study results showed a relative risk of 120 for the hormonal contraceptive users when compared to the nonusers (95% CI = 1.14–1.26) [34]. The current
study agrees with the previous findings by showing an increased risk of 6.78 times for the hormonal contracep- tive users when compared to the nonusers. Knowing the association between the hormonal contraceptive usage time and the diagnosis of breast cancer in this study can reveal other findings; however, using hormonal contra- ception for less than 1 year remains a risk factor for de- veloping breast cancer [34]. This study was limited by the convenience sampling tech-
nique, the regional sample collection, and postmenopausal women recruitment. Other determinants of breast cancer are recommended to study in Makkah region, such as diet- ary habits and breast density. However, it does highlight the importance of determining the risk factors for breast cancer using cohort studies consisting of a nationwide and large sample size, such studies are limited. Therefore, due to the paucity of research concerning of breast cancer in Makkah region, this study adds to the body of knowledge for future research to expand on this area.
Conclusion This study showed that most of the socioeconomic, health related status and menstruation history variables were de- terminant risk factors for breast cancer in postmenopausal women in the Makkah region. To illustrate, education, economic status, obesity, lack of exercise, cancer aware- ness, smoking, hormonal and non-hormonal contraceptive use and an early menstruation age were identified as sig- nificant in this study, and they should be considered in culturally sensible prevention programs for women in the Makkah region of Saudi Arabia.
Abbreviations BMI: Body mass index; CI: Confidence interval; CRC: Colorectal cancer; KAMC: King Abdullah Medical City Hospital; OR: Odds ratio; x2: Chi-squared
Acknowledgments The authors thank all staff members of KAMC in the Makkah region for their help and support. Additionally, we thank Ibrahem Dabbour, Mu’tah University, for assistance in study design.
Authors’ contributions FSA conceived and designed the study. FJA, KJG, MMG, RAA, HAA, RHA, WHA, ASJ, and SHT conducted research, provided research materials, and collected and organized data. FSA, FJA and KJG analyzed and interpreted data. All authors wrote initial and final draft of the article. All authors have critically reviewed and approved the final draft of the manuscript.
Funding The authors received no financial support for this research.
Availability of data and materials The datasets used and/or analyzed in this research cannot be publicly shared and they are available from the corresponding author on reasonable request.
Ethics approval and consent to participate The data was collected after the study was approved by the Umm Al-Qura University Ethical Committee (approval number AMSEC-2-20-5-2014), follow- ing the tenets of the Declaration of Helsinki. Eligible women who agreed to participate in this study had to read and sign the consent form before the data collection began.
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Consent for Publication Not applicable.
Competing interests The authors declare that they have no competing interests.
Author details 1Faculty of Nursing, Umm Al-Qura University, Makkah, Kingdom of Saudi Arabia. 2Department of Clinical Nutrition, Faculty of Applied Medical Sciences, Umm Al-Qura University, P.O. Box: 7067, Makkah 21955, Kingdom of Saudi Arabia. 3Department of Laboratory Medicine, Faculty of Applied Medical Sciences, Umm Al-Qura University, Makkah, Kingdom of Saudi Arabia. 4Collage of Medicine, Department of Biochemistry, Umm Al-Qura University, Makkah, Kingdom of Saudi Arabia. 5Department of Medical Laboratory Science, Faculty of Medical Sciences, Fakeeh College for Medical Sciences, Jeddah, Saudi Arabia. 6Cancer Metabolism and Epigenetic Unit, Faculty of Science, King Abdulaziz University, Jeddah, Saudi Arabia. 7Clinical Nutrition Administration, KAMC-HC, Makkah, Saudi Arabia.
Received: 14 October 2018 Accepted: 12 November 2019
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