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©The Author(s) 2020.
World J Clin Oncol. Apr 24, 2020; 11(4): 217-242
Published online Apr 24, 2020. doi: 10.5306/wjco.v11.i4.217
Published online Apr 24, 2020. doi: 10.5306/wjco.v11.i4.217
Table 1 Inclusion/exclusion criteria: Two papers were identified under different titles, published in different journals but had the same study design and results
| Inclusion criteria | Exclusion criteria |
| Papers reporting on obesity of physical inactivity as a risk factor for BC within the GCCCs | Studies on countries outside the GCCCs |
| Studies looking at the prevalence of obesity and insufficient exercise within the GCCCs | Papers on metabolic syndrome, other cancers, BC awareness, screening and perceptions |
| Randomised controlled trials, case-controlled studies and observational studies | Systematic reviews, Meta-Analysis, Editorials, Letters and commentaries |
| Studies involving females aged ≥ 30 yr | Papers solely on children, adolescents (10-19 yr) and young adults (< 30 yr) |
Table 2 Results from papers looking at the prevalence of obesity and physical inactivity in the Gulf Cooperation Council countries
| Ref. | Sample size and characteristics | Participant age range (mean ± SD) | Exposure measures | Anthropometric measurements | Physical activity | Key findings | Other findings |
| [36] | 105 female volunteers recruited from Riyadh city, KSA | 18-45 yr (26.3 ± 7.1) | Pedometer used to measure daily steps; Weight and height measured accurately in the clinic | Mean BMI (± SD): 25 (± 4.2) | Mean steps (± SD) - 5114 (± 2213). Classified as “low-active” | There was no significant correlation between step count and any participant demographics | Step count had a strong correlation with self-efficacy |
| [32] | 277 healthy adult Omani women from 5/11 governates in Oman | 18-48 yr, IPAQ (n = 229) - 29.6 ± 7.3; D-SSTQ (n = 191) – 31 ± 7.1; Accelerometer (n = 80) – 29 ± 8.0 | 2 questionnaires and use of accelerometer to measure PA; IPAQ (n = 229); D-SSTQ (n = 191); Accelerometer (n = 80), weight and height measured accurately | IPAQ (n = 229) - Mean (± SD): 25.9 (± 6.3); 52.8% overweight/obese; D-SSTQ (n = 191) -Mean (± SD): 26.7 (± 5.9); 58.6% overweight/obese; Accelerometer (n = 80) - Mean (± SD): 25.1 (± 6.1) | IPAQ (n = 229) - 34% minimally active, 32% moderately active, 34% physically active; D-SSTQ (n = 191) - Mean self-reported sitting; 450 min on working day and 448 min on non-working day. Accelerometer (n = 80) - Mean time wearing was 813.7 ± 101.6 min/d. Time spent in sedentary behaviour was 62%, 35% in light PA and 3% in moderate-vigorous PA | From the IPAQ: a median ± IQR of 75 ± 249 min/wk spent in moderate PA, 0 ± 80 min/wk in vigorous PA and 120 ± 330 min/wk walking. Adults spent significantly (P ≤ 0.05) more time in moderate PA than the younger participants; There was no significance between PA levels and BMI. For the D-SSTQ: adults spent significantly (P < 0.001) more time watching television then the young adults. Generally, women 30-48 yr were more PA then younger adults | There was a significant decrease (P ≤ 0.0001) in the amount of PA in participants that had degree level education. Unemployed participated in more vigorous PA than employed (P ≤ 0.001). Postgraduate degree holders reported significantly more sitting time (P ≤ 0.001). There was no significant correlation between BMI and sitting time |
| [38] | 600 healthy Saudi females from Riyadh KSA | 16-45 yr (26.1 ± 7.7) | Weight and height measured by standard techniques | Mean BMI (± SD): 25.7 (± 5.6); 52.63% had a BMI > 24.9 (range was 14.7-50.3) | N/A | Majority of the participants were either overweight or obese | Married women had a significantly higher prevalence of overweight and obesity There is a statistically significant (P < 0.001) correlation between BMI and age. BMI increased with age and morbid obesity was greatest in the 36-45-year-old age group. There was no significant correlation in BMI between students and housewives |
| [33] | 237 female staff and students from Hail University, KSA | 18-30 yr (NB: 96% < 30) | The short version of the IPAQ for PA; Weight and height accurately measured | 42% overweight or obese | 57%- Inactive 41%- Moderate 2%- Physically active (health-enhancing PA level) | A high percentage of females were inactive | A significant correlation between increasing age and BMI and body fat (P < 0.0001); There was an inverse correlation between the intake of dietary fibre and BMI (P = 0.047) |
Table 3 Results from papers looking at the prevalence of obesity and physical inactivity in the Gulf Cooperation Council countries (continued Table 2)
| Ref. | Sample size and characteristics | Participant age range (mean ± SD) | Exposure measures | Anthropometric measurements | Physical activity | Key findings | General findings |
| [27] | 420 Saudi females, from 8 office-based worksites in Riyadh | 18-60 yr (31.7 ± 8.3) | PA questionnaire was completed then METs were calculated; Weight and height measured accurately and appropriately | Mean BMI (± SD): 27.1 (± 5.9) 58.3% overweight or obese | 52.1%- low-active 41.2%-moderately active 6.7%-Highly active | Sitting time significantly increased with increasing BMI (P = 0.008) | Majority of participants were aware that prolonged sitting was bad for health; The participants working in the private sector had a predicted 80-min increase in sitting time/day; Mean age at menopause was 47.5 ± 7.1 yr |
| [34] | 535 UAE female citizens living in the Urban area of Al Ain medical district. Surveyed September 2000 to August 2001 | 20-79 (34.3 ± 14.7), ~50% between 20-30 yr | Trained healthcare worker provided the questionnaire to assess PA; Weight and Height were accurately measured | 27% overweight; 35% obese | 84% report sufficiently active (above minimum recommendations for the elderly) | Prevalence of obesity declined with increasing age Women over the age of 40 were classified as obese by their % of body fat but not their BMI. Age was the only significant predictor of obesity is multivariate logistic regression analysis | Participants that had higher education were significantly more PA (P < 0.001); Younger females were significantly more active (P < 0.001); 84% of the sample are pre-menopausal |
| [37] | 438 non-pregnant married women. All Saudi and were born and resident in the Southwestern region of KSA | Divided into 2 age groups 18-39 yr (n = 305) and 40-60 yr (n = 133) | Weight and Height and WC measured accurately; Lipid Research Clinic questionnaire for strenuous exercise assessment | Mean BMI (± SD) of the 18-39 age group: 29.8 (± 6.5); Mean BMI (± SD) of 40-60 age group: 32.4 (± 5.9); Overall Mean BMI (± SD): 30.6 (± 6.5); 41.1% abdominally obese (WC > 88 cm); 52.2 % totally obese (BMI > 30) | Mean strenuous exercise score was 2.74 (score of 2 is “non-strenuous”, 4 is infrequently strenuous, 6 regularly strenuous) | Mean BMI and WC were significantly greater in the 40-60 age group (P < 0.0001); There was no significance found between abdominal obesity and strenuous exercise score, though the non-strenuous group contained the highest proportion of women with abdominal obesity | Women the 18-39 age group had a significantly higher level of education (P < 0.0001). The prevalence of abdominal obesity was greater in illiterate women (54.1%) |
| [35] | 549 female Qatari nationals. Recruited from the public, universities and companies | 18-64 yr (37.4 ± 11.7) | Weight and Height self-reported; Accelerometer to measure steps | Median BMI (IQR) - 28.8 (24.8-33.5) | 44%- Sedentary (< 5000 steps/d); 32.4%- low-active (5000-7499 steps/d); 23.5%- Physically active (≥ 7500 steps/d) | There was no significant difference between PA level and BMI; There was a significant difference (P < 0.0001) between activity level and age. Middle age females (45-64) were more PA | PA levels decreased during the summer months |
Table 4 Paper results from case-control trials exploring the association of obesity and breast cancer
| Ref. | Sample size and characteristics | Cases | Controls | Association between BC and obesity | Other findings | ||
| Age (mean ± SD) | Anthropometric Measurements | Age (mean ± SD) | Anthropometric measurements | ||||
| [40] | 348 Saudi women (58 newly diagnosed with BC and 290 controls) | 48.5 ± 7.1 | BMI > 30: 71.4% | 49.2 ± 6.9 | BMI > 30: 70.7% | There was no significant association between BMI and BC | BC was significantly correlated with age at marriage and age at menopause; There was no significant correlation between PA and BC; 62.1% of cases were pre-menopausal and 44.8% were post-menopausal |
| [41] | 500 women (250 newly diagnosed with BC, 250 no previous history of any cancer) from 2 hospitals in Riyadh, KSA | 45.7 ± 7.8 | Mean (± SD): 31.2 (± 7.0) | 43.9 ± 7.5 | Mean ± SD 30.7 ± 7.6 | No significant difference between the BMI of the cases and controls | There was a slight significance (P = 0.011) between the age of the 2 groups; Women with BC entered menopause significantly younger than the controls (P = 0.022); Mean (± SD) of menopause was 46.6 (± 6.4) for the controls and 48.7 (± 5.2) which was significant (P = 0.022) |
| [61] | 997 women from 1 research centre in Riyadh, KSA. 499 newly diagnosed and confirmed BC and 498 age-matched controls | 44.8 ± 11.5 | Mean (± SD); 29.5 (± 6.2) | 36.8 ± 12.8 | Mean ± SD 29.4 ± 6.2 | There was no significant difference between the BMI of the cases and controls | BC patients were significantly older than controls (P = 0.0001); A positive association between the highest quartile triglyceride level and BC risk (OR = 2.90); Mean ± SD menopausal age for cases was 48.2 ± 7.6 yr and 47.9 ± 8.1 yr for the controls |
| [39] | 1172 women aged 18+, 534 histologically confirmed primary BC cases and 638 unmatched controls that were BC free | 43.6 ± 8.3; 15% ≤ 35 yr, 85% > 35 yr | 29.4% overweight and 46.4% obese | Mean not provided; 31.5% ≤ 35 yr, 68.5% > 35 yr | 30.3% overweight and 31.0% obese | Overweight/ obese BMI significantly increased the BC risk compared to normal BMI (OR = 2.29). It is an independent risk factor for BC. Obesity/obese proportion was significantly high in BC group than controls (OR = 1.74 and P < 0.0001); Being overweight or obese in the pre- and postmenopausal ages were both significantly associated with increased BC risk compared to controls | Low education, unemployment and marriage were significantly associated with higher BMI (P < 0.0001); Low education was associated with an increased risk of BC (P < 0.0001); 49.7% of cases were premenopausal and 50.3% were postmenopausal. Post-menopausal women were found to have a positive association with BC risk |
Table 5 Paper results for non- case-controlled studies on obesity and physical activity in association with breast cancer
| Ref. | Type of study | Sample size and characteristics | Age range (mean ± SD) | Anthropometric measurements | PA | Key findings | Other findings |
| [81] | Single-institute retrospective study | 224 females (72.4% Saudi National) who underwent mastectomy, MRM or WLE with axillary dissection | 26-93 yr (48.8 ± 12.2); 61.7% of females < 50 yr | Mean BMI; 32; 38.3% overweight; 42.8% obese | N/A | Most of the participants in both age groups had a BMI > 30 | 92.6% of females had invasive BC; Ten-year survival rate did not differ significantly with females ≤ 45 or > 45. Only 12% of patients presented with early-stage disease |
| [42] | Data-analysis of patients treated with BCS and MRM between February 1988 and August 2008 | 112 Saudi women. Not included if had distant metastasis or neoadjuvant chemotherapy | 23-76 yr (47.0 ± 10.3) | Range: 15-52.8; Mean BMI (± SD): 31.8 (± 7.2); 28.6% overweight 53.6% obese | N/A | BMI < 18.5 was significantly associated (P = 0.002) to locoregional recurrences; BMI 26-30 (overweight) was significantly associated with locoregional recurrence (P = 0.002); In multivariate analysis age < 35 was an independent risk factor for locoregional recurrence. The risk of locoregional recurrence was not significant in obese females | Only 8.93% had locoregional recurrences, 83% of women were premenopausal and 17% were postmenopausal |
| [43] | Retrospective cross-sectional secondary data analysis study | 112 Saudi women diagnosed with BC that had either BCS with axillary lymph node dissection or MRM following neoadjuvant therapy | No range; 47 ± 10 | Mean BMI (± SD): 32 (± 7.16); 27.3% overweight 56.4% obese | N/A | BC receptor expression was not influenced by BMI | Obesity did not influence the TNM stage of the breast tumour; 82.7% of the sample were premenopausal and 17.3% were postmenopausal |
Table 6 Paper results for non- case-controlled studies on obesity and physical activity in association with breast cancer (continued Table 5)
| Ref. | Type of study | Sample size and characteristics | Age range (mean ± SD) | Anthropometric measurements | PA | Key findings | Other findings |
| [45] | Cross-section- Data collection from 10 randomly selected primary healthcare facilities | 1488 Qatar and Arab national women. 64.7% were Qatari and 35.3% were Arab expats | 35-65 yr (47 ± 10.8) | 42.8% overweight and 30.0% obese | PA walking per day: 27.5%-30 min, 12.0%- 60 min, 60.5%- none | 72.8% overweight/obese; Using the Gail model (n = 1338) BMI was significantly associated with a high 5-yr risk of BC (P < 0.001); In linear regression analysis, BMI was not associated with 5-yr or lifetime risk of BC. PA declined in the hot weather | Chronological age, age at menarche, menopausal age and occupation were all associated with a 5-yr risk of BC; 39.4% were premenopausal and 60.6% were postmenopausal |
| [44] | A retrospective epidemiological study. Results from KSA females compared with statistics from United States cancer registry (SEER) | 262 female patients in 1 hospital in the eastern provenience of KSA diagnosed with invasive BC | 24-94 yr, median age 48 | 31.9% overweight, 51.5% obese | N/A | The % of BC cases with a BMI > 30 was higher among the females in KSA than the females on the SEER database | BC diagnosis occurred at a significantly younger age when compared to females on the SEER database (United States); BC was significantly more aggressive than females on the SEER database, 58.7% were premenopausal and 41.3% were postmenopausal |
Table 7 Critical appraisal of observational cohort and cross-sectional studies using the National Institutes of health study quality checklists
| Al Saeed et al[42], 2015 | Al-Eisa and Al-Sobayel[36], 2012 | Al-Habsi et al[32], 2015 | Al-Malki et al[38], 2003 | Al-Shammari et al[33], 2015 | Alabdulkarim et al[81], 2018 | Albawardi et al[27], 2017 | Alsaeed et al[43], 2017 | Bener et al[45], 2017 | Carter et al[34], 2004 | Khalid[37], 2007 | Rudat et al[44], 2012 | Sayegh et al[35], 2016 | |
| Was the research question or objective clearly stated? | Y | Y | Y | N | N | N | Y | Y | Y | Y | Y | N | Y |
| Was the study population clearly specified and defined? | Y | N | Y | N | Y | Y | Y | Y | Y | Y | Y | Y | Y |
| Was the participation rate of eligible persons at least 50%? | CD | Y | Y (but N for accelerometer) | Y | Y | Y | Y | Y | Y | Y | Y | NA | NA |
| Were all subjects selected or recruited from the same or similar populations? Were inclusion/exclusion criteria prespecified? | N | Y | Y | N | Y | Y | Y | Y | Y | Y | Y | Y | Y |
| Was a sample size justification, power description or variance and effect estimates provided? | N | N | N | N | Y | N | Y | Y | Y | Y | Y | N | N |
| Was the exposure of interest measured prior to the outcome being measured? | Y | N | N | N | N | Y | N | Y | N | N | N | N | Y |
| Was the timeframe sufficient for an association to be seen? | Y | N | N | N | N | Y | N | N | N | N | N | N | Y |
| For exposures that can vary in amount or level, did the study examine different levels of the exposure as related to the outcome? | Y | N | Y | NA | Y | NA | Y | NA | Y | Y | Y | Y | Y |
| Were the exposure measures (independent variables) clearly defined, valid and reliable and implemented consistently across all study participants? | Y | Y | Y | Y | Y | Y | Y | CD | Y | Y | Y | Y | Y |
| Was the exposure measured more than once over time? | N | Y | Y | N | N | Y | N | N | N | N | N | N | Y |
Table 8 Critical appraisal of observational cohort and cross-sectional studies using the National Institutes of health study quality checklists (continued Table 7)
| Al Saeed et al[42], 2015 | Al-Eisa and Al-Sobayel[36], 2012 | Al-Habsi et al[32], 2015 | Al-Malki et al[38], 2003 | Al-Shammari et al[33], 2015 | Alabdulkarim et al[81], 2018 | Albawardi et al[27], 2017 | Alsaeed et al[43], 2017 | Bener et al[45], 2017 | Carter et al[34], 2004 | Khalid[37], 2007 | Rudat et al[44], 2012 | Sayegh et al[35], 2016 | |
| Were the outcome measures (dependent variables) clearly defined, valid, reliable and implemented consistently across all study participants? | NR | Y | Y | NA | Y | Y | Y | Y | Y | Y | Y | N | Y |
| Were the outcome assessors blinded to the exposure status of the participants | N | CD | N | N | N | CD | N | N | Y | Y | Y | N | N |
| Was loss to follow-up after baseline 20% or less? | NR | NA | NA | NA | NA | N | Y | NA | NA | NA | NA | NA | Y |
| Were key potential confounding variables measured and adjusted statistically for their impact on the relationship between exposure and outcome? | Y | N | N | Y | N | Y | Y | Y | Y | Y | Y | N | N |
| Quality rating | Poor | Poor | Poor | Poor | Poor | Fair | Good | Good | Fair | Fair | Good | Poor | Poor |
| Additional comments | Selection bias, no blinding | Confounding bias | Confounding and recall bias | Selection bias | Selection and confounding bias | Confounding and selection bias | Confounding and recall bias for BMI |
Table 9 Critical appraisal of case-controlled studies using National Institutes of health study quality checklists
| Critical assessment of case-controlled studies | ||||
| Al-Amri et al[40], 2015 | AlFaris et al[41], 2018 | Alothaimeen et al[61], 2004 | Elkum et al[39], 2014 | |
| Was the research question or objective clearly stated? | Y | Y | Y | Y |
| Was the study population clearly specified and defined? | Y | Y | Y | Y |
| Did the authors include a sample size justification? | Y | N | Y | N |
| Were controls selected or recruited from the same or similar population that gave rise to the cases? | Y | Y | Y | Y |
| Were the definitions, inclusion and exclusion criteria, algorithms or processes used to identify or select cases and controls valid, reliable and implemented consistently across all study participants? | Y | Y | N | Y |
| Were the cases clearly defined and differentiated from controls? | Y | Y | Y | Y |
| If less than 100% of eligible cases/controls were selected for the study, were the cases/controls randomly selected from those eligible? | NA | NA | NA | Y |
| Was there use of concurrent controls? | N | N | N | Y |
| Were the investigators able to confirm that the exposure/risk occurred prior to the development of the condition or event that defined a participant as a case? | Y | N | CD | N |
| Were the measures of exposure/risk clearly defined, valid, reliable and implemented consistently across all the study participants? | N | Y | y | Y |
| Were the assessors of exposure/risk blinded to the case to the case or control status of participants? | Y | N | N | Y |
| Were key potential confounding variables measured and adjusted statistically in the analyses? If matching was used, did the investigators account for matching during study analysis? | Y | N | Y | Y |
| Quality rating | Poor | Poor | Poor | Good |
| Additional comments | Controls not well defined and were not concurrent | High risk of bias and confounding not adjusted for | Cases were significantly older than the controls (P = 0.0001). High risk of bias | |
Table 10 Quality of evidence using the GRADE criteria for 3 domains; risk of bias, indirectness and imprecision
| GRADE criteria | |||||
| Ref. | Study design | Risk of bias, No, serious (-1), very serious (-2) | Indirectness, No, serious (-1), very serious (-2) | Imprecision, No, serious (-1), very serious (-2) | Quality of evidence, RCT (starts at high quality), Non-RCT (starts at low) |
| Al Saeed et al[42], 2015 | Retrospective data analysis | No | -1 | -1 | Very Low |
| Al-Amri et al[40], 2015 | Case-control study | -1 | No | -1 | Very low |
| Al-Eisa and Al-Sobayel[36], 2012 | Cross-sectional | -2 | -1 | -2 | Very low |
| Al-Habsi et al[32], 2015 | Cross-sectional | -1 | -1 | -1 | Very low |
| Al-Malki et al[38], 2003 | Cross-sectional | No | -1 | No | Very low |
| Al-Shammari et al[33], 2015 | Cross-sectional | -1 | -2 | -1 | Very low |
| Alabdulkarim et al[81], 2018 | Single-institute retrospective | No | No | -1 | Very low |
| Albawardi et al[27], 2017 | Cross-sectional | -1 | -1 | No | Very low |
| AlFaris et al[41], 2018 | Case-control and cross-sectional design | -1 | -1 | No | Very low |
| Alothaimeen et al[61], 2004 | Case-control | -2 | No | -1 | Very low |
| Alsaeed et al[43], 2017 | Retrospective cross-sectional | No | -1 | -1 | Very low |
| Bener et al[45], 2017 | Cross-sectional | -1 | No | No | Very low |
| Carter et al[34], 2004 | Cross-sectional | -1 | -1 | No | Very low |
| Elkum et al[39], 2014 | Case-control | No | No | No | Low |
| Khalid[37], 2007 | Cross-sectional | -1 | No | No | Very low |
| Rudat et al[44], 2012 | Retrospective epidemiological | No | No | -1 | Very low |
| Sayegh et al[35], 2016 | Retrospective data analysis | -1 | -1 | No | Very low |
- Citation: Tanner LTA, Cheung KL. Correlation between breast cancer and lifestyle within the Gulf Cooperation Council countries: A systematic review. World J Clin Oncol 2020; 11(4): 217-242
- URL: https://www.wjgnet.com/2218-4333/full/v11/i4/217.htm
- DOI: https://dx.doi.org/10.5306/wjco.v11.i4.217