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      Impact of Physical Inactivity on Risk of Developing Cancer of the Uterine Cervix : A Case-Control Study

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          Abstract

          <div class="section"> <a class="named-anchor" id="S1"> <!-- named anchor --> </a> <h5 class="section-title" id="d1104146e283">Objective</h5> <p id="P1">In this study, we investigated whether physical inactivity was associated with risk of cervical cancer in women treated at an American cancer hospital. </p> </div><div class="section"> <a class="named-anchor" id="S2"> <!-- named anchor --> </a> <h5 class="section-title" id="d1104146e288">Methods</h5> <p id="P2">This case-control study included 128 patients with cervical cancer and 512 controls matched on age. Controls were women suspected of having but not ultimately diagnosed with a neoplasm. Physical inactivity was defined in accordance with the 2008 Physical Activity Guidelines for Americans. Thus, participants reporting on average no moderate or vigorous recreational physical activity were classified as inactive. Unconditional logistic regression was used to estimate odds ratios (OR) and 95% confidence intervals (CIs). </p> </div><div class="section"> <a class="named-anchor" id="S3"> <!-- named anchor --> </a> <h5 class="section-title" id="d1104146e293">Results</h5> <p id="P3">Compared to non-cancer controls, those with cervical cancer had significantly increased odds of reporting abstinence from recreational physical activity (OR = 2.43, 95% CI: 1.56-3.80). No association was noted between occupational -related physical inactivity and cervical cancer (OR = 0.88, 95% CI: 0.58-1.36). </p> </div><div class="section"> <a class="named-anchor" id="S4"> <!-- named anchor --> </a> <h5 class="section-title" id="d1104146e298">Conclusions</h5> <p id="P4">Our findings suggest that abstinence from regular recreational physical activity is associated with increased odds of cervical cancer. To our knowledge, this is the first US-based study examining these associations. Given the 2008 Physical Activity Guidelines for Americans, this study has identified yet another potential public health benefit to regular physical activity. Further investigation is needed using a larger sample and prospectively collected data to characterize dose of activity to mitigate risk and the optimal window of susceptibility. </p> </div>

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          Most cited references15

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          Objective vs. Self-Reported Physical Activity and Sedentary Time: Effects of Measurement Method on Relationships with Risk Biomarkers

          Purpose Imprecise measurement of physical activity variables might attenuate estimates of the beneficial effects of activity on health-related outcomes. We aimed to compare the cardiometabolic risk factor dose-response relationships for physical activity and sedentary behaviour between accelerometer- and questionnaire-based activity measures. Methods Physical activity and sedentary behaviour were assessed in 317 adults by 7-day accelerometry and International Physical Activity Questionnaire (IPAQ). Fasting blood was taken to determine insulin, glucose, triglyceride and total, LDL and HDL cholesterol concentrations and homeostasis model-estimated insulin resistance (HOMAIR). Waist circumference, BMI, body fat percentage and blood pressure were also measured. Results For both accelerometer-derived sedentary time ( 50% lower for the IPAQ-reported compared to the accelerometer-derived measure (p<0.0001 for both interactions). The relationships for moderate-to-vigorous physical activity (MVPA) and risk factors were less strong than those observed for sedentary behaviours, but significant negative relationships were observed for both accelerometer and IPAQ MVPA measures with glucose, and insulin and HOMAIR values (all p<0.05). For accelerometer-derived MVPA only, additional negative relationships were seen with triglyceride, total cholesterol and LDL cholesterol concentrations, BMI, waist circumference and percentage body fat, and a positive relationship was evident with HDL cholesterol (p = 0.0002). Regression coefficients for HOMAIR, insulin and triglyceride were 43–50% lower for the IPAQ-reported compared to the accelerometer-derived MVPA measure (all p≤0.01). Conclusion Using the IPAQ to determine sitting time and MVPA reveals some, but not all, relationships between these activity measures and metabolic and vascular disease risk factors. Using this self-report method to quantify activity can therefore underestimate the strength of some relationships with risk factors.
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            Is Open Access

            Relationship between Smoking and Obesity: A Cross-Sectional Study of 499,504 Middle-Aged Adults in the UK General Population

            Background There is a general perception that smoking protects against weight gain and this may influence commencement and continuation of smoking, especially among young women. Methods A cross-sectional study was conducted using baseline data from UK Biobank. Logistic regression analyses were used to explore the association between smoking and obesity; defined as body mass index (BMI) >30kg/m2. Smoking was examined in terms of smoking status, amount smoked, duration of smoking and time since quitting and we adjusted for the potential confounding effects of age, sex, socioeconomic deprivation, physical activity, alcohol consumption, hypertension and diabetes. Results The study comprised 499,504 adults aged 31 to 69 years. Overall, current smokers were less likely to be obese than never smokers (adjusted OR 0.83 95% CI 0.81-0.86). However, there was no significant association in the youngest sub-group (≤40 years). Former smokers were more likely to be obese than both current smokers (adjusted OR 1.33 95% CI 1.30-1.37) and never smokers (adjusted OR 1.14 95% CI 1.12-1.15). Among smokers, the risk of obesity increased with the amount smoked and former heavy smokers were more likely to be obese than former light smokers (adjusted OR 1.60, 95% 1.56-1.64, p<0.001). Risk of obesity fell with time from quitting. After 30 years, former smokers still had higher risk of obesity than current smokers but the same risk as never smokers. Conclusion Beliefs that smoking protects against obesity may be over-simplistic; especially among younger and heavier smokers. Quitting smoking may be associated with temporary weight gain. Therefore, smoking cessation interventions should include weight management support.
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              Physical activity and risk of cancer in the NHANES I population.

              We studied the relation between self-reported physical activity and cancer in the first National Health and Nutrition Examination Survey (NHANES I) cohort, originally examined between 1971-75, and followed prospectively through the Epidemiologic Follow-up Study (NHEFS), conducted between 1982-84. Among 5,138 men and 7,407 women 25-74 years old, for nonrecreational activity we observed increased risk of cancer among inactive individuals compared to very active persons (for men, relative risk [RR] 1.8, 95% confidence interval [CI] = 1.4, 2.4; for women RR 1.3, 95% CI = 1.0, 1.8). These findings were unchanged after adjustment for cigarette smoking, body mass index (BMI), and other potential confounders. Sites which demonstrated stronger inactivity-cancer associations included colorectum (RR 1.6, 95% CI = 0.7, 3.5) and lung (RR 1.6; 95% CI = 1.2, 3.5) among men, and breast (post-menopausal) (RR 1.7; 95% CI = 0.8, 2.9) and cervix (RR 5.2; 95% CI = 1.4, 14.5) among women, although these findings for women were based on relatively few cases. The association between inactivity and cancer was greater among persons of moderate (or lower) BMI, those cases occurring three or more years after baseline, and, in women, those more than 60 years old. In contrast, recreational exercise showed little relation to cancer, with the exception of prostate cancer. The results suggest that inactive individuals are at increased risk of cancer.
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                Author and article information

                Journal
                Journal of Lower Genital Tract Disease
                Journal of Lower Genital Tract Disease
                Ovid Technologies (Wolters Kluwer Health)
                1089-2591
                2016
                July 2016
                : 20
                : 3
                : 230-233
                Article
                10.1097/LGT.0000000000000210
                4920713
                27105330
                e839a49a-b1ad-4ba2-9e9c-a53f851c2053
                © 2016
                History

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