Association between average daily television viewing time and the incidence of ovarian cancer: findings from the Japan Collaborative Cohort Study

Association between leisure sedentary behaviour and uterine fibroids in non-menopausal women: a population-based study

OBJECTIVE

Sedentary behaviour is associated with a variety of adverse health outcomes, including obesity, oestrogen metabolism and chronic inflammation, all of which are related to the pathogenesis of uterine fibroids (UFs). This study aimed to explore the relationship between leisure sedentary time (LST) and UFs.

DESIGN

Cross-sectional.

SETTING

We conducted a cross-sectional analysis of data from patients from the Yunnan region in the China Multi-Ethnic Cohort Study.

PARTICIPANTS

A total of 6623 non-menopausal women aged 30-55 years old were recruited. Menstrual status was self-reported. Participants who lacked a unique national identity card, suffered from serious mental illness, did not have a clear diagnosis of UFs, or provided incomplete information were excluded.

PRIMARY AND SECONDARY OUTCOME

UFs were diagnosed by abdominal B-ultrasound. Leisure sedentary behaviour was assessed by using a face-to-face questionnaire interview. Logistic regression and restricted cubic spline were employed to explore the relationship between LST and UFs.

RESULTS

A total of 562 participants had UFs, with a prevalence rate of 8.5% (7.8%, 9.2%). Multivariate adjusted logistic regression analysis showed that the risk of UFs in women with LST≥6 hour/day was 2.008 times that in women with LST<2 hour/day (95% CI 1.230 to 3.279). The restricted cubic spline results showed that there was a linear dose‒response relationship between LST and UFs (p for non-linearity>0.05). According to the results of the stratified analysis for menstrual status and body mass index (BMI), there was a correlation between LST and the prevalence of UFs only in women with a BMI<24 kg/m2 or perimenopause.

CONCLUSION

LST was independently associated with the prevalence of UFs, and a linear dose‒response relationship was observed. Our study provides evidence on the factors influencing UFs, and further research is needed to propose feasible measures for UFs prevention.

Constant light exposure and/or pinealectomy increases susceptibility to trichloroethylene-induced hepatotoxicity and liver cancer in male mice

Exposure to light at night, pineal gland impairment, and the environmental pollutant trichloroethylene (TCE) have serious implications for health and contribute to illness, including liver cancer. The adverse effect of the association of continuous exposure to light with decreased melatonin levels and TCE-induced toxicity is not disclosed in target organs. This work explored the role of light and pineal impairment in increasing susceptibility to liver toxicity and cancer upon exposure to TCE. Male albino mice were divided into groups as follows: control group (12-h light/12-h dark cycle), constant light (24-h light), pinealectomized (Pnx) mice, sham surgically treated group, TCE-treated groups subjected to two doses (500 and 1000 mg/kg) at two different light regimens, and combination of Pnx and TCE-treated mice kept at a 12-h light/12-h dark cycle. Melatonin levels were significantly decreased in both Pnx mice and TCE-treated animals at both light regimens. Aspartate transaminase, alanine aminotransferase, activities, and serum bilirubin levels were significantly elevated, whereas albumin levels were markedly decreased in Pnx mice, TCE-treated mice, and the combination group. Histopathological investigations reflected changes in liver function parameters indicating liver injury and induction of cancer. These effects were accompanied by significant increase of the liver cancer biomarker alpha-fetoprotein and the expression of the metastatic markers CD44, TGFβ-1, and VEGF, along with increased oxidative stress indicators and inflammatory cytokines (IL-6, IL-1β, and TNF-α) in both Pnx and TCE-treated mice and the combination group at both light regimens. Taken together, our findings indicated that low melatonin levels, exposure to constant light, and the combination of both factors increases susceptibility to the toxic and carcinogenic effects of TCE on the liver.

Sedentary behaviour in relation to ovarian cancer risk: a systematic review and meta-analysis

Sedentary behaviour is an emerging risk factor for several site-specific cancers. Ovarian cancers are often detected at late disease stages and the role of sedentary behaviour as a modifiable risk factor potentially contributing to ovarian cancer risk has not been extensively examined. We systematically searched relevant databases from inception to February 2020 for eligible publications dealing with sedentary behaviour in relation to ovarian cancer risk. We conducted a systematic review and meta-analysis, calculating summary relative risks (RR) and 95% confidence intervals (CI) using a random-effects model. We calculated the E-Value, a sensitivity analysis for unmeasured confounding. We tested for publication bias and heterogeneity. Seven studies (three prospective cohort studies and four case–control studies) including 2060 ovarian cancer cases were analysed. Comparing highest versus lowest levels of sedentary behaviour, the data indicated a statistically significant increase in the risk of ovarian cancer in relation to prolonged sitting time (RR = 1.29, 95% CI = 1.07–1.57). Sub-analyses of prospective cohort studies (RR = 1.33, 95% CI = 0.92–1.93) and case–control studies (RR = 1.28, 95% CI = 0.98–1.68) showed statistically non-significant results. Sensitivity analysis showed that an unmeasured confounder would need to be related to sedentary behaviour and ovarian cancer with a RR of 1.90 to fully explain away the observed RR of 1.29. Our analyses showed a statistically significant positive association between sedentary behaviour and ovarian cancer risk.

A Theoretical Approach for Correlating Proteins to Malignant Diseases

Malignant Tumors are developed over several years due to unknown biological factors. These biological factors induce changes in the body and consequently, they lead to Malignant Tumors. Some habits and behaviors initiate these biological factors. In effect, the immune system cannot recognize a Malignant Tumor as foreign tissue. In order to discover a fascinating pattern of these habits, behaviors, and diseases and to make effective decisions, different machine learning techniques should be used. This research attempts to find the association between normal proteins (environmental factors) and diseases that are difficult to diagnose and propose justifications for those diseases. This paper proposes a technique for medical data mining using association rules. The proposed technique overcomes some of the limitations in current association algorithms such as the Apriori algorithm and the Equivalence CLAss Transformation (ECLAT) algorithm. A modification to the Apriori algorithm has been proposed to mine Erythrocytes Dynamic Antigens Store (EDAS) data in a more efficient and tractable way. The experiments inferred that there is a relation between normal proteins as environment proteins, food proteins, commensal proteins, tissue proteins, and disease proteins. Also, the experiments show that habits and behaviors are associated with certain diseases. The presented tool can be used in clinical laboratories to discover the biological causes of malignant diseases.

Sedentary Behavior and Health: Update from the 2018 Physical Activity Guidelines Advisory Committee

PURPOSE

To provide an overview of relationships between sedentary behavior and mortality as well as incidence of several noncommunicable diseases and weight status reported in the 2018 Physical Activity Guidelines Advisory Committee Scientific Report (2018 PAGAC Scientific Report), and to update the evidence from recent studies.

METHODS

Evidence related to sedentary behavior in the 2018 PAGAC Scientific Report was summarized, and a systematic review was undertaken to identify original studies published between January 2017 and February 2018.

RESULTS

The 2018 PAGAC Scientific Report concluded there was strong evidence that high amounts of sedentary behavior increase the risk for all-cause and cardiovascular disease (CVD) mortality and incident CVD and type 2 diabetes. Moderate evidence indicated sedentary behavior is associated with incident endometrial, colon and lung cancer. Limited evidence suggested sedentary behavior is associated with cancer mortality and weight status. There was strong evidence that the hazardous effects of sedentary behavior are more pronounced in physically inactive people. Evidence was insufficient to determine if bout length or breaks in sedentary behavior are associated with health outcomes. The new literature search yielded seven new studies for all-cause mortality, two for CVD mortality, two for cancer mortality, four for type 2 diabetes, one for weight status, and four for cancer; no new studies were identified for CVD incidence. Results of the new studies supported the conclusions in the 2018 PAGAC Scientific Report.

CONCLUSIONS

The results of the updated search add further evidence on the association between sedentary behavior and health. Further research is required on how sex, age, race/ethnicity, socioeconomic status, and weight status may modify associations between sedentary behavior and health outcomes.

Applying Machine Learning of Erythrocytes Dynamic Antigens Store in Medicine

Erythrocytes Dynamic Antigens Store (EDAS) is a new discovery. EDAS consists of self-antigens and foreign (non-self) antigens. In patients with infectious diseases or malignancies, antigens of infection microorganism or malignant tumor exist in EDAS. Storing EDAS of normal individuals and patients in a database has, at least, two benefits. First, EDAS can be mined to determine biomarkers representing diseases which can enable researchers to develop a new line of laboratory diagnostic tests and vaccines. Second, EDAS can be queried, directly, to reach a precise diagnosis without the need to do many laboratory tests. The target is to find the minimum set of proteins that can be used as biomarkers for a particular disease. A hypothetical EDAS is created. Hundred-thousand records are randomly generated. The mathematical model of hypothetical EDAS together with the proposed techniques for biomarker discovery and direct diagnosis are described. The different possibilities that may occur in reality are experimented. Biomarkers' proteins are identified for pathogens and malignancies, which can be used to diagnose conditions that are difficult to diagnose. The presented tool can be used in clinical laboratories to diagnose disease disorders.

Television viewing time, walking time, and risk of type 2 diabetes in Japanese men and women: The Japan Collaborative Cohort Study

We examined the effect of television viewing and walking on the risk of type 2 diabetes among an Asian population. A total of 25,240 participants (9786 men and 15,454 women) aged 40-79 years, with no history of diabetes, stroke, coronary heart disease, or cancer at the baseline (1988-1990) and who have completed the 5-year follow-up questionnaire were included. During the 5-year follow-up, 778 new cases of type 2 diabetes were reported (397 men and 381 women). Television viewing time was positively associated with risk of type 2 diabetes (p for trend = 0.01). The multivariable OR (95% CI) for ≥5 h/day versus <2 h/day television viewing was 1.51 (1.03-2.19) in women and 1.06 (0.71-1.59) in men (p for interaction = 0.82). Walking time was inversely associated with type 2 diabetes risk in a fully adjusted model (p for trend = 0.02). The multivariable OR for type 2 diabetes of ≥1 h/day walking time was 0.87 (0.71-1.06) compared with 0.5 h/day walking time. The inverse association was found in men (p for trend = 0.02), but not in women (p for trend = 0.38) (p for interaction = 0.36). The multivariable OR for type 2 diabetes of <5 h/day television viewing and ≥1 h/day walking times was 0.72 (0.55-0.94) in fully adjusted model compared with ≥5 h/day television viewing and <1 h/day walking times. Limiting television viewing time and increasing walking time may reduce risk of type 2 diabetes among Japanese.

Associations of Daily Walking Time With Pneumonia Mortality Among Elderly Individuals With or Without a Medical History of Myocardial Infarction or Stroke: Findings From the Japan Collaborative Cohort Study

Background

The association between daily walking and pneumonia mortality, stratified by the presence of disease conditions, such as myocardial infarction (MI) or stroke, was investigated.

Methods

The study participants were 22,280 Japanese individuals (9,067 men and 13,213 women) aged 65–79 years. Inverse propensity weighted competing risk model was used to calculate the hazard ratio (HR) and 95% confidence interval (CI) for pneumonia mortality.

Results

After a median of 11.9 years of follow-up, 1,203 participants died of pneumonia. Participants who did not have a history of MI or stroke and who walked for 1 hour/day or more were less likely to die from pneumonia (HR 0.90; 95% CI, 0.82–0.98) than those walked for 0.5 hours/day. A similar inverse association of pneumonia and walking (0.5 hours/day) was observed among participants with a history of MI (HR 0.66; 95% CI, 0.48–0.90). Among the participants with a history of stroke, those who walked for 0.6–0.9 hours/day were less likely to die because of pneumonia (HR 0.65; 95% CI, 0.43–0.98).

Conclusions

Regular walking for ≥1 hour/day may reduce the risk of pneumonia mortality in elderly individuals with or without cardiovascular disease history.