Understanding the relationship between obesity and female-specific cancers (FSCs) is crucial for public health planning and policy development. The current data paper presented a dataset that includes obesity prevalence and incidence rates of breast, ovarian, cervical, and uterine cancers among women in Middle Eastern countries. This dataset could be used for time-trend analysis and different forecasting models. Moreover, exploring the relationship between obesity and FSCs is important to develop preventive healthcare services, especially among developing countries. The dataset comprises official statistics obtained from reputable sources including the world bank and global burden of disease (GBD) database. The data include a total of 405 observations across 15 middle-eastern countries, from 1990 to 2016. Key variables are obesity prevalence and incidence rate of four major cancers in women including breast cancer, ovarian cancer, cervical cancer, and uterine cancer. This panel data is mainly prepared to investigate the temporal relationship between obesity prevalence and FSC incidence rates, and also performing Counterfactual analysis. Moreover, this data could be utilized for advanced machine learning techniques to estimate future shifts in trend and patterns over time.

Mirzababaei A, et al. Clin Nutr Res. 2022 Apr;11(2):120-132. https://doi.org/10.7762/cnr.2022.11.2.120

Background Cardiovascular diseases (CVDs) are the leading cause of mortality worldwide and significantly impact patients’ quality of life (QoL) and mental health. A healthy lifestyle has been recognized as an essential factor in reducing the burden of CVD and improving patient outcomes. This study aimed to investigate the relationship between the Healthy Lifestyle Index and QoL and depression among patients with CVD. Methods and materials This descriptive-analytical cross-sectional study was conducted in 2024 among 182 patients with confirmed CVD who were referred to Imam Khomeini Hospital in Tehran. Data were collected using three validated instruments: a demographic questionnaire, the Short Form-12 Health Survey (SF-12) to assess QoL, and the Patient Health Questionnaire-9 (PHQ-9) to measure depression. The Healthy Lifestyle Index included physical activity, dietary habits, smoking, alcohol use, and social interaction. Generalized linear models were used to examine the associations between lifestyle components and outcomes (QoL and depression), adjusting for key confounders. All statistical analyses were performed using SPSS software version 22. Results The findings showed that the mean SF-12 QoL score among participants was 84.29 (SD = 7.53), and the mean age was 59.54 years (SD = 11.73). Physically active patients had significantly higher QoL scores (mean = 88.3) compared to inactive individuals (mean = 82.1) (P < 0.001). Greater social interaction was also associated with better QoL (mean = 87.9 vs. 80.4, P < 0.001). In contrast, alcohol consumption was associated with lower QoL (mean = 79.2 vs. 85.1, P = 0.04). Smoking status, BMI, and healthy eating score were not significantly related to QoL. Moreover, participants with higher Healthy Lifestyle Index scores had lower depression scores (mean PHQ-9 = 5.2 vs. 8.7, P < 0.01). Conclusion The results highlight the importance of promoting physical activity, reducing alcohol consumption, and encouraging social engagement as key components of healthy lifestyle interventions for patients with CVD. These strategies may effectively improve QoL and reduce depressive symptoms, underscoring the need for holistic and behaviorally focused approaches in the routine care of cardiovascular patients.

Background Gestational diabetes mellitus (GDM) poses significant health risks for both mothers and infants, necessitating accurate and timely diagnosis. Current diagnostic methods involve invasive blood tests, but salivary biomarkers may offer a non-invasive alternative. This scoping review aims to summarize the available evidence on the diagnostic potential of salivary biomarkers for GDM. Methods A systematic search was conducted in the PubMed, Scopus, Web of Science, and ProQuest databases up to January 1, 2024, using the keywords "Gestational diabetes" and "saliva." The review included observational studies that compared salivary biomarkers between women with gestational diabetes mellitus (GDM) and those with normal glucose tolerance (NGT). Multiple independent reviewers performed screening, quality assessment, and data extraction. The extracted data included author names, publication year, country of study, study design, diagnostic method for GDM, number of cases and controls, markers studied, summary of findings, and conclusions. Results From a total of 853 records identified through the database search, nineteen articles met the inclusion criteria. Most of the studies were cross-sectional (N = 13, 68%) and were conducted in Turkey (N = 13, 47%). The salivary biomarkers investigated included oxidative markers (N = 13, 47%), inflammatory markers (N = 6, 32%), and adipokines (N = 5, 26%). The studies consistently demonstrated elevated levels of certain biomarkers in gestational diabetes mellitus (GDM), including Total Antioxidant Capacity (TAC), Malondialdehyde (MDA), inflammatory factors like Interleukin-6 (IL-6), and adipokines such as chemerin and resistin. Conclusion Salivary biomarkers hold promise for the early detection of gestational diabetes mellitus (GDM). Further research with larger sample sizes is needed to validate these findings and refine diagnostic approaches.

Objectives: Social media text mining has been widely used to extract information about the experiences and needs of patients regarding various diseases, especially cancer. Understanding these issues is necessary for further management in primary care. Researchers have identified that lifestyle factors such as diet, exercise, alcohol, and Smoking are associated with cancer risks, particularly women’s cancer. Considering the growing trend in the global burden of women’s cancer, it is essential to monitor up-to-date data sources using text mining. Data description: We have prepared six independent datasets regarding lifestyle components and women’s cancer: (1) a dataset of nutrition containing 10,161 tweets; (2) a dataset of exercise containing 9412 tweets; (3) a dataset of alcohol containing 2132 tweets; (4) a dataset of Smoking containing 4316 tweets; and (5) a dataset of lifestyle (term) containing 1861 tweets. We also construct an additional dataset: (6) a dataset by summing other components containing 27,882 tweets. These data are provided to discover people’s perspectives, knowledge, and experiences regarding lifestyle and women’s cancer. Hence, it should be valuable for healthcare providers to develop more efficient patient management approaches.

Regular breakfast consumption plays a crucial role in the overall health and well-being of children and adolescents, making it an essential factor in maintaining healthy lifestyle habits. This study examined the association between breakfast skipping (BS) and unhealthy lifestyle behaviors in US adolescents using the Youth Risk Behavior Surveillance System (YRBS) 2018 survey. The prevalence of BS was significantly linked to age and race but not gender. After adjusting for confounding variables, a significant positive correlation was observed between BS and low physical activity, smoking, alcohol consumption, and high TV time. No such association was found with high video-game time. The findings highlight the importance of regular breakfast consumption as a vital component of healthy lifestyles among youth. Encouraging regular breakfast habits may reduce the risk of developing unhealthy behaviors and obesity in this population