Age Related Differences in Individual Quality of Life Domains in Youth with Type 1 Diabetes.

BACKGROUND: Investigating individual, as opposed to predetermined, quality of life domains may yield important information about quality of life. This study investigated the individual quality of life domains nominated by youth with type 1 diabetes. METHODS: Eighty young people attending a diabetes summer camp completed the Schedule for the Evaluation of Individual Quality of Life-Direct Weighting interview, which allows respondents to nominate and evaluate their own quality of life domains. RESULTS: The most frequently nominated life domains were 'family', 'friends', 'diabetes', 'school', and 'health' respectively; ranked in terms of importance, domains were 'religion', 'family', 'diabetes', 'health', and 'the golden rule'; ranked in order of satisfaction, domains were 'camp', 'religion', 'pets', and 'family' and 'a special person' were tied for fifth. Respondent age was significantly positively associated with the importance of 'friends', and a significantly negatively associated with the importance of 'family'. Nearly all respondents nominated a quality of life domain relating to physical status, however, the specific physical status domain and the rationale for its nomination varied. Some respondents nominated 'diabetes' as a domain and emphasized diabetes 'self-care behaviors' in order to avoid negative health consequences such as hospitalization. Other respondents nominated 'health' and focused more generally on 'living well with diabetes'. In an ANOVA with physical status domain as the independent variable and age as the dependent variable, participants who nominated 'diabetes' were younger (M = 12.9 years) than those who nominated 'health' (M = 15.9 years). In a second ANOVA, with rationale for nomination the physical status domain as the independent variable, and age as the dependent variable, those who emphasized 'self care behaviors' were younger (M = 11.8 years) than those who emphasized 'living well with diabetes' (M = 14.6 years). These differences are discussed in terms of cognitive development and in relation to the decline in self-care and glycemic control often observed during adolescence. CONCLUSIONS: Respondents nominated many non-diabetes life domains, underscoring that QOL is multidimensional. Subtle changes in conceptualization of diabetes and health with increasing age may reflect cognitive development or disease adjustment, and speak to the need for special attention to adolescents. Understanding individual quality of life domains can help clinicians motivate their young patients with diabetes for self-care. Future research should employ a larger, more diverse sample, and use longitudinal designs.

Dynamic Smile Analysis : Changes with Age

Introduction: The objective of this study was to define age-related changes in the human smile. The areas of interest were: upper lip length at smile and repose, upper lip thickness at smile and repose, maxillary incisal display at smile, interlabial gap height at smile, smile index, percent buccal corridors, intercommissural width at rest, smile height, and smile arc. A secondary objective was to study the perioral changes from rest to smile and compare them on the basis of age. Materials and Method: Video equipment was used to capture video for 261 subjects. Two frames for each subject were selected; one frame representing the lips and rest and the second representing the widest smile. After excluding 40 subjects the data for the remaining 221 subjects was analyzed. Results: There was a decrease of 1.5 to 2 mm in the maxillary incisor display during smile, with increase in age. Smile index significantly increased with increase in age. Most (78%) subjects displayed an average smile height. No subjects in the 50 and over age group displayed a high smile while no subjects in the 15-19 year old age group presented with a low smile. All the dynamic measures indicated there was a pattern of decreasing change from rest to smile especially evident after the 30-39 year old age group. Conclusions: This study helps to establish age related dynamic norms. As the person ages the smile gets narrower vertically and wider transversely. The dynamic measures indicate that the muscles' ability to create a smile decreases with increasing age.

A Dynamic Analysis: the Smile and Display of Dentition during Speech

The objective of this retrospective study is to follow up on a previous Dynamic Smile Analysis and videographically analyze and develop averages for soft tissue norms with respect to the display of dentition during speech. These values would then be compared cross-sectionally across different age groups to see whether changes attributable to the aging process could be seen. A secondary objective was to compare averages for soft tissue norms in the display of dentition during speech to averages for soft tissue norms in the display of dentition during the smile. Materials and Method: Records from a previous study in which video equipment was used to capture video for 26 1 subjects were re-evaluated to find appropriate frames to analyze for speech. Two frames for each subject were selected; one frame representing the maximal display of maxillary incisors during speech and the second representing the widest transverse display of dentition during speech. After excluding 40 subjects the data for the remaining 221 subjects was analyzed. These averages were then compared to averages attained in the previous study to compare the display of the dentition during speech to the display of the dentition during smile. Results: On average, a difference in 1.29 mm was seen in the display of the maxillary incisors during speech at maximal display and during the smile. An average of 7.23 mm of maxillary incisors is readily visible during maximum display of maxillary incisors during speech, as compared to 8.52 mm during the smile. The constructed smile index was also smaller when measured during the speech when compared to the smile index by an average of 2.58 units. Conclusion: This study helps to establish age-related dynamic norms for the display of dentition during speech. The dynamic measures indicate that the display of dectition is greater, on average, during the smile than at speech.

Barriers to Timely Screening Colonoscopy

Objective: Colorectal cancer (CRC) can be largely prevented or effectively treated in its early stages, yet disparities exist in timely screening. The aim of this study was to explore the disparities in CRC screening on the basis of health insurance status including private, Medicare, Medicaid, and State Administered General Assistance (SAGA). Methods: A retrospective chart review for the period January 2000 to May 2007 (95 records) was conducted at two clinic sites; a private clinic and a university hospital clinic. All individuals at these sites who met study criteria (>50 years old with screening colonoscopy) were included. Age, gender, date of first clinic visit when screening referral was made, and date of completed procedure (screening colonoscopy) were recorded. Groups were dichotomized between individuals with private health insurance and individuals with public health insurance. Individuals with any history of CRC, known pre-cancerous conditions as well as family history of CRC requiring frequent colonoscopy were excluded from the study. Linear model analysis was performed to compare the average waiting time to receiving screening colonoscopy between the groups. T-test was performed to analyze age or gender related differences between the two groups as well as within each group. Results: The average waiting time (33 days) for screening colonoscopy in privately insured individuals was significantly lower than publicly insured individuals (200 days). The time difference between the first clinic visit and the procedure was statistically significant (p < 0.0001) between the two groups. There was no statistical difference (p=0.089) in gender between these groups (public vs. private). There were also no statistically significant gender or age related differences found within each group. Conclusions: Disparities exist in timely screening for CRC and one of the barriers leading to delayed CRC screening includes health insurance status of an individual. Even within the insured group, type of insurance plays major role. There is a negative correlation between public health insurance status and timely screening. Differences in access to medical care and delivery of care experienced by patients who are publicly insured through Medicaid, Medicare, and SAGA, suggests that the State of Connecticut needs to implement changes in health care policies that would provide timely screening colonoscopy. It is evident that health insurance coverage facilitates timely access to healthcare. Therefore, there is a need for increased efforts in advocacy for policy, payment and physician participation in public insurance programs. A state-wide comprehensive program involving multiple components targeting different levels of change such as provider, patients and the community should help reduce some of the observed causes of healthcare disparities based on the insurance status.