Influence of self-perceived oral health and socioeconomic predictors on the utilization of dental care services by schoolchildren

The influence of socioeconomic factors and self-rated oral health on children's dental health assistance was assessed. This study followed a cross-sectional design, with a multistage random sample of 792 12-year-old schoolchildren from Santa Maria, a city in southern Brazil. A dental examination provided information on the prevalence of dental caries (DMFT index). Data about the use of dental service, socioeconomic status, and self-perceived oral health were collected by means of structured interviews. These associations were assessed using Poisson regression models (prevalence ratio; 95% confidence interval). The prevalence of regular use of dental service was 47.8%. Children from low socioeconomic backgrounds and those who rated their oral health as "poor" used the service less frequently. The distribution of the kind of oral healthcare assistance used (public/private) varied across socioeconomic groups. The better-off children were less likely to have used the public service. Clinical, socioeconomic, and psychosocial factors were strong predictors for the utilization of dental care services by schoolchildren.

Inactive Australian college students' preferred activities, sources of assistance, and motivators

Participation in regular physical activity reduces the risk of cardiovascular disease and all-cause mortality as well as providing numerous health benefits.' The steepest decline in physical activity occurs during adolescence (approximately 15 to 18 years of age) and young adulthood (20 to 25 years).(2) Australian population studies have found that levels of physical inactivity are twice as high for those 20 to 29 years old as they are for those under 20 years old.(3,4) As college students move through this period of changing roles within family and peer groups, they may be expected to have specific preferences and expected outcomes for physical activity participation that are different from those they had previously as high school students.(5) Studies of physical activity determinants suggest that while there are some similarities between males and females, there are differences in preferences for specific types of activity.(6) Calfas et al.(5) found that women reported body image factors (weight loss, dissatisfaction with body) to be more motivating, while young men rated strength (muscle gain, muscle tone) and social aspects (organized competition, meeting people) of physical activity more highly than did young women. We examined preferred physical activities, sources of assistance to be more active, and perceived motivators for activity in a sample of inactive college students. Differences between males and females were examined, and the implications for campus-based physical activity promotion strategies are considered.

A survey of contact with offspring and assistance with child care among parents with psychotic disorders

To help improve services for parents with psychotic disorders, patients with such disorders in three treatment agencies in Queensland, Australia, were surveyed about whether they were parents, how much contact they had with their offspring, and who provided assistance with child care. Of the 342 individuals with psychotic disorders mho participated in the study, 124 were parents. Forty-eight parents in the study had children under age 16, and 20 of these parents (42 percent) had their children living with them. Most parents relied on relatives or friends for assistance with child care. Barriers to child care services identified by parents were inability to pay, lack of local services, and fear of losing custody of children.

Mobi_System: A Personal Travel Assistance for Electrical Vehicles in Smart Cities

In this work it is proposed the design of a mobile system to assist car drivers in a smart city environment oriented to the upcoming reality of Electric Vehicles (EV). Taking into account the new reality of smart cites, EV introduction, Smart Grids (SG), Electrical Markets (EM), with deregulation of electricity production and use, drivers will need more information for decision and mobility purposes. A mobile application to recommend useful related information will help drivers to deal with this new reality, giving guidance towards traffic, batteries charging process, and city mobility infrastructures (e. g. public transportation information, parking places availability and car & bike sharing systems). Since this is an upcoming reality with possible process changes, development must be based on agile process approaches (Web services).

Socioeconomic inequalities in the access to and quality of health care services

OBJECTIVE To assess the inequalities in access, utilization, and quality of health care services according to the socioeconomic status. METHODS This population-based cross-sectional study evaluated 2,927 individuals aged ≥ 20 years living in Pelotas, RS, Southern Brazil, in 2012. The associations between socioeconomic indicators and the following outcomes were evaluated: lack of access to health services, utilization of services, waiting period (in days) for assistance, and waiting time (in hours) in lines. We used Poisson regression for the crude and adjusted analyses. RESULTS The lack of access to health services was reported by 6.5% of the individuals who sought health care. The prevalence of use of health care services in the 30 days prior to the interview was 29.3%. Of these, 26.4% waited five days or more to receive care and 32.1% waited at least an hour in lines. Approximately 50.0% of the health care services were funded through the Unified Health System. The use of health care services was similar across socioeconomic groups. The lack of access to health care services and waiting time in lines were higher among individuals of lower economic status, even after adjusting for health care needs. The waiting period to receive care was higher among those with higher socioeconomic status. CONCLUSIONS Although no differences were observed in the use of health care services across socioeconomic groups, inequalities were evident in the access to and quality of these services.

A-1 Monthly Public Assistance Statistical Report Family Investment Program, December 2003

Monthly Public Assistance Statistical Report Family Investment Program

G-1 Appeal Activity in the Public Assistance Programs, January 2004

Monthly report from the Iowa Department of Human Services

A-1 Monthly Public Assistance Statistical Report Family Investment Program, January 2004

Monthly Public Assistance Statistical Report Family Investment Program

A-1 Monthly Public Assistance Statistical Report Family Investment Program, February 2004

Monthly Public Assistance Statistical Report Family Investment Program

G-1 Appeal Activity in the Public Assistance Programs, March 2004

Monthly report from the Iowa Department of Human Services

F-1, Food Assistance Program - State Summary, April 2004

The Food Assistance Monthly Participation Report is a monthly summary of Food Assistance program participation, Statewide and for each Iowa county. Breakouts are reported for participants also in the FIP program, those only receiving Food Assistance, and those that are receiving economic assistance under other programs (primarily Medicaid). This report may also be known as the F-1 Report.

A-1 Monthly Public Assistance Statistical Report Family Investment Program, March 2004

Monthly Public Assistance Statistical Report Family Investment Program

G-1 Appeal Activity in the Public Assistance Programs, April 2004

Monthly report from the Iowa Department of Human Services

A-1 Monthly Public Assistance Statistical Report Family Investment Program, April 2004

Monthly Public Assistance Statistical Report Family Investment Program

F-1, Food Assistance Program - State Summary, June 2004

The Food Assistance Monthly Participation Report is a monthly summary of Food Assistance program participation, Statewide and for each Iowa county. Breakouts are reported for participants also in the FIP program, those only receiving Food Assistance, and those that are receiving economic assistance under other programs (primarily Medicaid). This report may also be known as the F-1 Report.