Skip to content. | Skip to navigation

Personal tools

Navigation

You are here: Home

Search results

436 items matching your search terms.
Filter the results.
Item type









































New items since



Sort by relevance · date (newest first) · alphabetically
Time Use Across the Life Course
2018 Conference
Located in Coming Up
Article ReferenceTime-use Profiles, Chronic Role Overload, and Women’s Body Weight Trajectories from Middle to Later Life in the Philippines
Although chronic life strain is often found to be associated with adverse health outcomes, empirical research is lacking on the health implications of persistent role overload that many women around the world are subject to, the so-called double burden of work and family responsibilities. Using data from the Cebu Longitudinal Health and Nutrition Survey (1994-2012), we examined the linkage between time-use profiles and body mass index (BMI) trajectories for Filipino women over an 18-year span. Out of the four classes of women with differential levels of a combination of work and family duties, the group with the heaviest double burden has the highest average BMI. In addition, those who have remained in this class for three or more waves of data not only have higher BMI on average but also have experienced the steepest rate of increase in BMI upon transition from midlife to old age.
Located in Retired Persons / Feinian Chen, Ph.D. / Feinian Chen Publications
Article Reference Troff document (with manpage macros)Tobacco smoking, chewing habits, alcohol drinking and the risk of head and neck cancer in Nepal
Although tobacco smoking, pan chewing and alcohol drinking are important risk factors for head and neck cancer (HNC), the HNC risks conferred by products available in Nepal for these habits are unknown. We assessed the associations of tobacco smoking, chewing habits, and alcohol drinking with HNC risk in Nepal. A case–control study was conducted in Nepal with 549 incident HNC cases and 601 controls. Odds ratios (OR) and 95% confidence intervals (CI) were estimated using unconditional logistic regression adjusting for potential confounders. We observed increased HNC risk for tobacco smoking (OR: 1.54; 95% CI: 1.14, 2.06), chewing habits (OR: 2.39; 95% CI: 1.77, 3.23), and alcohol drinking (OR: 1.57; 95% CI: 1.14, 2.18). The population attributable fraction (PAF) was 24.3% for tobacco smoking, 39.9% for chewing habits and 23.0% for alcohol drinking. Tobacco smoking, chewing habits, and alcohol drinking might be responsible for 85.3% of HNC cases. Individuals who smoked tobacco, chewed products and drank alcohol had a 13‐fold increase in HNC risk (OR: 12.83; 95% CI: 6.91, 23.81) compared to individuals who did not have any of these habits. Both high frequency and long duration of these habits were strong risk factors for HNC among the Nepalese with clear dose–response trends. Preventive strategies against starting these habits and support for quitting these habits are necessary to decrease the incidence of HNC in Nepal.
Located in MPRC People / Amir Sapkota, Ph.D. / Amir Sapkota Publications
Article ReferenceTop 10 Blockchain Predictions for the (Near) Future of Healthcare
To review blockchain lessons learned in 2018 and near-future predictions for blockchain in healthcare, Blockchain in Healthcare Today (BHTY) asked the world's blockchain in healthcare experts to share their insights. Here, our internationally-renowned BHTY peer-review board discusses their major predictions. Based on their responses, presented in detail below, ten major themes (Table ) for the future of blockchain in healthcare will emerge over the 12 months.
Located in MPRC People / Manouchehr (Mitch) Mokhtari, Ph.D. / Mitch Mokhtari Publications
Article Reference Troff document (with manpage macros)Trajectories of childhood adversity and the risk of depression in young adulthood: Results from the Avon Longitudinal Study of Parents and Children
  BACKGROUND: The significance of the timing and chronicity of childhood adversity for depression outcomes later in life is unclear. Identifying trajectories of adversity throughout childhood would allow classification of children according to the accumulation, timing, and persistence of adversity, and may provide unique insights into the risk of subsequent depression. METHODS: Using data from the Avon Longitudinal Study of Parents and Children, we created a composite adversity score comprised of 10 prospectively assessed domains (e.g., violent victimization, inter-parental conflict, and financial hardship) for each of eight time points from birth through age 11.5 years. We used semiparametric group-based trajectory modeling to derive childhood adversity trajectories and examined the association between childhood adversity and depression outcomes at the age of 18 years. RESULTS: Among 9,665 participants, five adversity trajectories were identified, representing stable-low levels (46.3%), stable-mild levels (37.1%), decreasing levels (8.9%), increasing levels (5.3%), and stable-high levels of adversity (2.5%) from birth through late childhood. Approximately 8% of the sample met criteria for probable depression at 18 years and the mean depression severity score was 3.20 (standard deviation = 3.95, range 0-21). The risk of depression in young adulthood was elevated in the decreasing (odds ratio [OR] = 1.72, 95% confidence interval [CI] = 1.19-2.48), increasing (OR = 1.81, 95% CI = 1.15-2.86), and stable-high (OR = 1.80, 95% CI = 1.00-3.23) adversity groups, compared to those with stable-low adversity, when adjusting for potential confounders. CONCLUSIONS: Children in trajectory groups characterized by moderate or high levels of adversity at some point in childhood exhibited consistently greater depression risk and depression severity, regardless of the timing of adversity.
Located in Retired Persons / Natalie Slopen, Sc.D. / Natalie Slopen Publications
U.S. Women Veteran's Experiences of War
Jones awarded NEH grant to document 100 years of women veteran's war experiences
Located in Research / Selected Research
Uchechi Mitchell, University of Illinois at Chicago
When is Hope Enough? Hopefulness, Discrimination and Racial Disparities in Physiological Dysregulation
Located in Coming Up
Ukraine and the Refugee Crisis
Center for Global Migration Studies panel
Located in Coming Up
Article Reference Troff document (with manpage macros)Use of social media, search queries, and demographic data to assess obesity prevalence in the United States
Obesity is a global epidemic affecting millions. Implementation of interventions to curb obesity rates requires timely surveillance. In this study, we estimated sex-specific obesity prevalence using social media, search queries, demographics and built environment variables. We collected 3,817,125 and 1,382,284 geolocated tweets on food and exercise respectively, from Twitter’s streaming API from April 2015 to March 2016. We also obtained searches related to physical activity and diet from Google Search Trends for the same time period. Next, we inferred the gender of Twitter users using machine learning methods and applied mixed-effects state-level linear regression models to estimate obesity prevalence. We observed differences in discussions of physical activity and foods, with males reporting higher intensity physical activities and lower caloric foods across 40 and 48 states, respectively. In addition, counties with the highest percentage of exercise and food tweets had lower male and female obesity prevalence. Lastly, our models separately captured overall male and female spatial trends in obesity prevalence. The average correlation between actual and estimated obesity prevalence was 0.797(95% CI, 0.796, 0.798) and 0.830 (95% CI, 0.830, 0.831) for males and females, respectively. Social media can provide timely community-level data on health information seeking and changes in behaviors, sentiments and norms. Social media data can also be combined with other data types such as, demographics, built environment variables, diet and physical activity indicators from other digital sources (e.g., mobile applications and wearables) to monitor health behaviors at different geographic scales, and to supplement delayed estimates from traditional surveillance systems.
Located in MPRC People / Quynh Nguyen, Ph.D., M.S.P.H. / Quynh Nguyen Publications
Using Big Data to measure discrimination impacts on birth outcomes
New National Institute on Minority Health and Health Disparities grant
Located in Research / Selected Research