Critically Apprise the Journal Article Entitled “Determinants of breast cancer in Saudi women from Makkah region: a case-control study (breast cancer risk factors among Saudi women) “using the check list provided.

Please kindly find the Journal Article and the Check List in the attached files.

Write a critical review of about 2 pages regarding the given article and fill the check list attached.

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Course name:	Health Care Research Methods
Course number:	PHC 215
Assignment title or task: (You can write a question)	Assignment 1 Critical Appraisal of a Journal Article: Critically Apprise the Journal Article Entitled “Determinants of breast cancer in Saudi women from Makkah region: a case-control study (breast cancer risk factors among Saudi women) “using the check list provided. Please kindly find the Journal Article and the Check List in the attached files.
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1. Were the groups comparable other than the presence of disease in cases or the absence of disease in controls?

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1. Were cases and controls matched appropriately?

1. Were the same criteria used for identification of cases and controls?

1. Was exposure measured in a standard, valid and reliable way?

1. Was exposure measured in the same way for cases and controls?

1. Were confounding factors identified?

1. Were strategies to deal with confounding factors stated?

1. Were outcomes assessed in a standard, valid and reliable way for cases and controls?

1. Was the exposure period of interest long enough to be meaningful?

1. Was appropriate statistical analysis used?

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: fsazzeh@uqu.edu.sa
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

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http://creativecommons.org/publicdomain/zero/1.0/

mailto:fsazzeh@uqu.edu.sa

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 6 months. 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

Alsolami et al. BMC Public Health (2019) 19:1554 Page 3 of 8

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

Alsolami et al. BMC Public Health (2019) 19:1554 Page 4 of 8

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%)

< 6 months 76 (45.5%) 48 (27.6%)

6–12 months 42 (25.1%) 70 (40.2%)

> 13 months 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

Alsolami et al. BMC Public Health (2019) 19:1554 Page 5 of 8

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

Alsolami et al. BMC Public Health (2019) 19:1554 Page 6 of 8

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.

Alsolami et al. BMC Public Health (2019) 19:1554 Page 7 of 8

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

References

1. Bray F, Ferlay J, Soerjomataram I, Siegel RL, Torre LA, Jemal A. Global Cancer

statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide
for 36 cancers in 185 countries. CA Cancer J Clin. 2018;68:394–424.

2. Kingdom of Saudi Arabia, Saudi Health Council, Saudi Cancer Registry.
Cancer Incidence Report in Saudi Arabia; 2014. https://nhic.gov.sa/eServices/
Documents/2014 . Accessed 29 Sept 2018.

3. McPherson K, Steel C, Dixon S. Breast cancer-epidemioloy, risk factors
genetics. BMJ. 2000;321:624–8.

4. Davies N, Batehup L, Thomas R. The role of diet and physical activity in
breast, colorectal, and prostate Cancer survivorship: a review of the
literature. Br J Cancer. 2011;8:105.

5. Surakasula A, Nagarjunapu GC, Raghavaiah KV. A comparative study of pre-
and post-menopausal breast cancer: risk factors, presentation, characteristics
and management. J Res Pharm Pract. 2014;3:12–8.

6. Alford SH, Schwartz K, Soliman A, et al. Breast cancer characteristics at
diagnosis and survival among Arab-American women compared to European-
and African American women. Breast Cancer Res Treat. 2009;114:339–46.

7. Hemminki K, Mosuavi SM, Sundquist J, Brandt A. Does the breast Cancer
age at diagnosis differ by ethnicity? A study on immigrants to Sweden.
Oncologist. 2011;16:146–54.

8. Wilson LF, Page AN, Dunn NA, Pandeya N, Protani MM, Taylor RJ. Population
attributable risk of modifiable risk factors associated with invasive breast
cancer in women aged 45-69 years in Queensland, Australia. Maturitas.
2013;76:370–6.

9. Narod S. Women with Cancer in low-income countries. Curr Oncol. 2017;24:217–9.
10. Bcheraoui C, Basulaiman M, Wilson S, et al. Breast Cancer screening in Saudi

arabia: free but almost no takers. PLoS One. 2015;10:e0119051.
11. Trieu PDY, Mello-Thoms C, Peat J, Do T, Brennan P. Risk factors of female breast

Cancer in Vietnam: a case-control study. Cancer Res Treat. 2017;49:990.
12. Azzeh FS. Determinants of exclusive breastfeeding and patterns of

complementary feeding practices in Mecca City, Saudi Arabia. Int J Child
Health Nutr. 2017;6:80–9.

13. Newcomb PA, Egan KM, Titus-Ernstoff L, Trentham-Dietz A, Greenberg ER,
Baron JA, Willett WC, Stampfer MJ. Lactation in relation to postmenopausal
breast cancer. Am J Epidemiol. 1999;150:174–82.

14. Al Otaibi S, Al Harbi M, Al Kahmoas A, et al. General breast Cancer awareness
among women in Riyadh City. Asian Pac J Cancer Prev. 2017;18:159–63.

15. Simmons R, Cosgrove SC, Romney MC, et al. Health literacy: Cancer
prevention strategies for early adults. Am J Prev Med. 2017;53:S73–7.

16. Patel K, Kanu M, Liu J, et al. Factors influencing breast Cancer screening in low-
income African Americans in Tennessee. J Community Health. 2014;39:943–50.

17. Bertoglia MP, Gormaz JG, Libuy M, et al. The population impact of obesity,
sedentary lifestyle, and tobacco and alcohol consumption on the
prevalence of type 2 diabetes: analysis of a health population survey in
Chile, 2010. PLoS One. 2017;12:e0178092.

18. Sun L, Zhu Y, Qian Q, Tang L. Body mass index and prognosis of breast
cancer. Medicine (Baltimore). 2018;97:26.

19. Queiroz SA, de Sousa I, Silva F, et al. Nutritional and environmental risk
factors for breast Cancer: a case-control study. Sci Med. 2018;28:ID28723.

20. Picon-Ruiz M, Morata-Tarifa C, Valle-Goffin JJ, Friedman ER, Slingerland JM.
Obesity and adverse breast Cancer risk and outcome: mechanistic insights
and strategies for intervention. CA Cancer J Clin. 2017;67:378–97.

21. Kim S, Cho Y, Kim S. Weight gain and its correlates among breast Cancer
survivors. Asian Nurs Res. 2013;7:161–7.

22. Alshaikh M, Filippidis F, Al-Omar H, et al. The ticking time bomb in lifestyle-
related diseases among women in the Gulf cooperation council countries:
review of systematic review. BMC Public Health. 2017;17:536.

23. Azzeh F, Bukhari HM, Header EA, et al. Trends in overweight or obesity and
other anthropometric indices in adults aged 18-60 years in Westren Saudi
Arabia. Ann Saudi Med. 2017;37:106–13.

24. Lee IM. Physical activity and Cancer prevention-data from epidemiologic
studies. Med Sci Sports Exerc. 2003;35:1823–7.

25. Friedenreich C, Cust A. Physical activity and breast Cancer risk: impact of
timing, type and dose of activity and population subgroup effects. Br J
Sports Med. 2008;42:636–47.

26. Al-Hazaa H. The public health burden of physical inactivity in Saudi Arabia. J
Fam Community Med. 2004;11:45–51.

27. Albawardi N, Jradi H, Almalki AA, Al-Hazzaa HM. Level of sedentary behavior
and its associated factors among Saudi women working in office-based
jobs in Saudi Arabia. Int J Environ Res Public Health. 2017;14:659.

28. Kispert S, McHowat J. Recent insights into cigarette smoking as a lifestyle
risk factor for breast cancer. Breast Cancer Targets Ther. 2017;9:127–32.

29. Jones M, Schoemaker MJ, Wright LB, Ashworth A, Swerdlow AJ. Smoking
and risk of breast Cancer in the generations study cohort. Breast Cancer
Res. 2017;19:118.

30. Colditz G, Bohlke K, Berkey C. Breast Cancer risk accumulation starts early:
prevention must also. Breast Cancer Res. 2014;145:567–79.

31. Bodicoat DH, Schoemaker MJ, Jones ME, et al. Timing of pubertal stages
and breast cancer risk: the breakthrough generations study. Breast Cancer
Res. 2014;16:R18.

32. Collaborative Group on Hormonal Factors in Breast Cancer. Menarche,
menopause, and breast Cancer risk: individual participant meta-analysis,
including 118 964 women with breast Cancer from 117 epidemiological
studies. Lancet Oncol. 2012;13:1141–51.

33. Hunter D. Oral contraceptives and the small increased risk of breast Cancer.
N Engl J Med. 2017;377:2276–7.

34. Morch L, Naftolin F, Keefe DL. Contemporary hormonal contraception and
the risk of breast Cancer. N Engl J Med. 2018;378:1265.

35. Zolfaroli I, Tarin J, Cano A. Hormonal contraceptives and breast Cancer:
clinical data. Eur J Obstet Gynecol Reprod Biol. 2018;230:212–6.

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https://nhic.gov.sa/eServices/Documents/2014

https://nhic.gov.sa/eServices/Documents/2014

Abstract
Background
Methods
Results
Conclusion
Background
Methods
Study design and setting
Participants
Data collection
Statistical analysis
Results
Discussion
Low-income, family size and employment
Education and Cancer awareness
Obesity and exercise
Smoking
Menarche
Contraceptives
Conclusion
Abbreviations
Acknowledgments
Authors’ contributions
Funding
Availability of data and materials
Ethics approval and consent to participate
Consent for Publication
Competing interests
Author details
References
Publisher’s Note