Obesity, Physical Activity, and Cancer Incidence in Two Geographically Distinct Populations; The Gulf Cooperation Council Countries and the United Kingdom-A Systematic Review and Meta-Analysis

Abstract

Background: The relationship between obesity, physical activity, and cancer has not been well studied across different countries. The age-standardized rate of cancer in the UK is double-triple that in the Gulf Cooperation Council Countries (GCCCs). Here, we study the association between obesity, physical activity, and cancer incidence with the aim to elucidate cancer epidemiology and risk factors in two geographically, ethnically, and climatically different parts of the world.

Methods: Our systematic search (from 2016 to 2023) in PubMed, EMBASE, Scopus, and APA PsycINFO databases resulted in 64 studies totaling 13,609,578 participants. The Cochrane risk of bias tool, GRADE, R programming language, and the meta package were used.

Results: Significant associations between obesity and cancer were found in both regions, with a stronger association in the UK (p ≤ 0.0001) than the GCCCs (p = 0.0042). While physical inactivity alone did not show a statistically significant association with cancer incidence, the pooled hazard ratio analysis revealed that the presence of both obesity and physical inactivity was associated with a significantly higher cancer incidence. The most common types of cancer were breast cancer in the UK and colorectal cancer across the GCCCs.

Conclusion: Although both regions share similarities, advanced healthcare systems, genetic characteristics, dietary habits, and cultural practices may influence cancer incidence and types.

Keywords: Gulf Cooperation Council Countries; United Kingdom; cancer; meta-analysis; obesity; physical activity; systematic review.

Figure 2

Forest plot of all studies showing the association of obesity and cancer incidence in both GCCCs and the UK. The random-effects model was used to adjust for heterogeneity. The black squares and lines represent the confidence intervals of the individual studies, the grey squares represent the study weight, and the grey diamond represents the pooled HR. CI, confidence interval, GCCCs, Gulf Cooperation Council Countries, HR, hazard ratio, SE, standard error, TE, treatment effect, UK, United Kingdom [40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,100,101,102].

Figure 4

Forest plot of 42 studies showing the association of obesity and the incidence of cancer in the UK. The random-effects model was used to adjust for heterogeneity. The black squares and lines represent the confidence intervals of the individual studies, the grey squares represent the study weight, and the diamond represents the pooled HR. CI, confidence interval, HR, hazard ratio, SE, standard error, TE: treatment effect [40,41,42,43,44,45,47,48,49,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,81,82,83,86,87,88,90,91,92].

Figure 5

Forest plot showing the association of obesity and the incidence of cancer of 22 studies of the GCCCs (A), of 9 studies of the GCCCs excluding Saudi Arabia (B) and of 13 studies of Saudi Arabia (C). The random-effects model was used to adjust for heterogeneity. The black squares and lines represent the confidence intervals of the individual studies, the grey squares represent the study weight, and the grey diamond represents the pooled HR. CI, Confidence interval, GCCCs, Gulf cooperation countries council, HR, hazard ratio, SE, standard error, TE: treatment effect [46,50,51,52,53,54,55,56,80,84,85,89,93,94,95,96,97,98,99,100,101,102].

Figure 6

Forest plot illustrating the association between cancer incidence and age group (40–60). The black squares and lines represent the confidence intervals of the individual studies; the grey squares represent the study weight. The diamond at the bottom of the plot represents the overall pooled effect size, with its width reflecting the 95% CI. CI, confidence interval, HR, hazard ratio, SE, standard error [43,51,65,68,70,74,81,84,87,88,90,91,96,99,101].

Figure 7

Meta-regression bubble plot showing the relationship between mean participant age and log hazard ratio (effect size). Each bubble represents a study, with bubble size proportional to the study’s weight in the meta-analysis. The solid line indicates the regression line, while the dashed lines represent the 95% confidence interval.

Figure 8

Forest plots show the association of gender and incidence of cancer for females and males [40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,100,101,102].

Figure 9

Forest plot showing the association of obesity and the incidence of breast and gastrointestinal cancer types. Both types of cancer had a statistically significant association with obesity. The diamond at the bottom of the plot represents the overall pooled HR. CI, confidence interval, HR, hazard ratio, SE, standard error [40,43,45,47,48,51,53,54,55,56,60,61,63,64,66,67,68,69,70,72,73,74,76,77,78,79,80,81,82,84,85,86,87,88,93,94,96,97,98,102].

Figure 10

Forest plot showing the results of a mixed-effects meta-analysis model, synthesizing data from 64 studies using the Restricted Maximum Likelihood (REML) method to estimate variance components. The model fit statistics include a log likelihood of −22.5703, deviance of 45.1406, Akaike Information Criterion (AIC) of 51.1406, Bayesian Information Criterion (BIC) of 57.5220, and a Corrected AIC (AICc) of 51.5544. Heterogeneity measures indicate substantial variability among studies, with τ² (residual heterogeneity) at 0.0194 (SE = 0.0064), I² at 80.29%, and H² at 5.07. A significant residual heterogeneity is evident from the Q_E statistic (Q_E(df = 62) = 193.2016, p ≤ 0.0001). However, the moderator effect of physical exercise is not significant (Q_M(df = 1) = 0.0266, p = 0.8705) [40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,100,101,102].

Figure 1

Flow chart of study selection for inclusion in the meta-analysis (PRISMA flow chart).

Figure 3

Funnel plot of all studies included in the meta-analysis. The x-axis displays the study estimated effect size with inverse hazard ratio (In(HR)), and the y-axis represents a measure of study precision, with standard error. The dots represent the effect sizes from individual studies plotted against their precision while the dashed lines signify the expected distribution of these studies. The distribution of the studies observed in the funnel plot could be due to the heterogeneity of the studies.