Glycemic control: Risk factors, quality of life, workforce participation, and mortality among US adults with type 2 diabetes

Despite research showing the benefits of glycemic control, it remains suboptimal among adults with diabetes in the United States. Possible reasons include unaddressed risk factors as well as lack of awareness of its immediate and long term consequences. The objectives of this study were to, using cross-sectional data, (1) ascertain the association between suboptimal (Hemoglobin A1c (HbA1c) .7%), borderline (HbA1c 7-8.9%), and poor (HbA1c .9%) glycemic control and potentially new risk factors (e.g. work characteristics), and (2) assess whether aspects of poor health and well-being such as poor health related quality of life (HRQOL), unemployment, and missed-work are associated with glycemic control; and (3) using prospective data, assess the relationship between mortality risk and glycemic control in US adults with type 2 diabetes. Data from the 1988-1994 and 1999-2004 National Health and Nutrition Examination Surveys were used. HbA1c values were used to create dichotomous glycemic control indicators. Binary logistic regression models were used to assess relationships between risk factors, employment status and glycemic control. Multinomial logistic regression analyses were conducted to assess relationships between glycemic control and HRQOL variables. Zero-inflated Poisson regression models were used to assess relationships between missed work days and glycemic control. Cox-proportional hazard models were used to assess effects of glycemic control on mortality risk. Using STATA software, analyses were weighted to account for complex survey design and non-response. Multivariable models adjusted for socio-demographics, body mass index, among other variables. Results revealed that being a farm worker and working over 40 hours/week were risk factors for suboptimal glycemic control. Having greater days of poor mental was associated with suboptimal, borderline, and poor glycemic control. Having greater days of inactivity was associated with poor glycemic control while having greater days of poor physical health was associated with borderline glycemic control. There were no statistically significant relationships between glycemic control, self-reported general health, employment, and missed work. Finally, having an HbA1c value less than 6.5% was protective against mortality. The findings suggest that work-related factors are important in a person’s ability to reach optimal diabetes management levels. Poor glycemic control appears to have significant detrimental effects on HRQOL.^

The effectiveness of explicit individualized phonemic awareness instruction by a speech -language pathologist to preschool children with phonological speech disorders

This study investigated the effects of an explicit individualized phonemic awareness intervention administered by a speech-language pathologist to 4 prekindergarten children with phonological speech sound disorders. Research has demonstrated that children with moderate-severe expressive phonological disorders are at-risk for poor literacy development because they often concurrently exhibit weaknesses in the development of phonological awareness skills (Rvachew, Ohberg, Grawburg, & Heyding, 2003).^ The research design chosen for this study was a single subject multiple probe design across subjects. After stable baseline measures, the participants received explicit instruction in each of the three phases separately and sequentially. Dependent measures included same-day tests for Phase I (Phoneme Identity), Phase II (Phoneme Blending), and Phase III (Phoneme Segmentation), and generalization and maintenance tests for all three phases.^ All 4 participants made substantial progress in all three phases. These skills were maintained during weekly and biweekly maintenance measures. Generalization measures indicated that the participants demonstrated some increases in their mean total number of correct responses in Phase II and Phase III baseline while the participants were in Phase I intervention, and more substantial increases in Phase III baseline while the participants were in Phase II intervention. Increased generalization from Phases II to III could likely be explained due to the response similarities in those two skills (Cooper, Heron, & Heward, 2007).^ Based upon the findings of this study, speech-language pathologists should evaluate phonological awareness in the children in their caseloads prior to kindergarten entry, and should allocate time during speech therapy to enhance phonological awareness and letter knowledge to support the development of both skills concurrently. Also, classroom teachers should collaborate with speech-language pathologists to identify at-risk students in their classrooms and successfully implement evidence-based phonemic awareness instruction. Future research should repeat this study including larger groups of children, children with combined speech and language delays, children of different ages, and ESOL students.^

The Effectiveness of Explicit Individualized Phonemic Awareness Instruction By a Speech-Language Pathologist to Preschool Children With Phonological Speech Disorders

This study investigated the effects of an explicit individualized phonemic awareness intervention administered by a speech-language pathologist to 4 prekindergarten children with phonological speech sound disorders. Research has demonstrated that children with moderate-severe expressive phonological disorders are at-risk for poor literacy development because they often concurrently exhibit weaknesses in the development of phonological awareness skills (Rvachew, Ohberg, Grawburg, & Heyding, 2003). The research design chosen for this study was a single subject multiple probe design across subjects. After stable baseline measures, the participants received explicit instruction in each of the three phases separately and sequentially. Dependent measures included same-day tests for Phase I (Phoneme Identity), Phase II (Phoneme Blending), and Phase III (Phoneme Segmentation), and generalization and maintenance tests for all three phases. All 4 participants made substantial progress in all three phases. These skills were maintained during weekly and biweekly maintenance measures. Generalization measures indicated that the participants demonstrated some increases in their mean total number of correct responses in Phase II and Phase III baseline while the participants were in Phase I intervention, and more substantial increases in Phase III baseline while the participants were in Phase II intervention. Increased generalization from Phases II to III could likely be explained due to the response similarities in those two skills (Cooper, Heron, & Heward, 2007). Based upon the findings of this study, speech-language pathologists should evaluate phonological awareness in the children in their caseloads prior to kindergarten entry, and should allocate time during speech therapy to enhance phonological awareness and letter knowledge to support the development of both skills concurrently. Also, classroom teachers should collaborate with speech-language pathologists to identify at-risk students in their classrooms and successfully implement evidence-based phonemic awareness instruction. Future research should repeat this study including larger groups of children, children with combined speech and language delays, children of different ages, and ESOL students

Glycemic Control: Risk Factors, Quality of Life, Workforce Participation, and Mortality Among US Adults with Type 2 Diabetes

Despite research showing the benefits of glycemic control, it remains suboptimal among adults with diabetes in the United States. Possible reasons include unaddressed risk factors as well as lack of awareness of its immediate and long term consequences. The objectives of this study were to, using cross-sectional data, 1) ascertain the association between suboptimal (Hemoglobin A1c (HbA1c) ≥7%), borderline (HbA1c 7-8.9%), and poor (HbA1c ≥9%) glycemic control and potentially new risk factors (e.g. work characteristics), and 2) assess whether aspects of poor health and well-being such as poor health related quality of life (HRQOL), unemployment, and missed-work are associated with glycemic control; and 3) using prospective data, assess the relationship between mortality risk and glycemic control in US adults with type 2 diabetes. Data from the 1988-1994 and 1999-2004 National Health and Nutrition Examination Surveys were used. HbA1c values were used to create dichotomous glycemic control indicators. Binary logistic regression models were used to assess relationships between risk factors, employment status and glycemic control. Multinomial logistic regression analyses were conducted to assess relationships between glycemic control and HRQOL variables. Zero-inflated Poisson regression models were used to assess relationships between missed work days and glycemic control. Cox-proportional hazard models were used to assess effects of glycemic control on mortality risk. Using STATA software, analyses were weighted to account for complex survey design and non-response. Multivariable models adjusted for socio-demographics, body mass index, among other variables. Results revealed that being a farm worker and working over 40 hours/week were risk factors for suboptimal glycemic control. Having greater days of poor mental was associated with suboptimal, borderline, and poor glycemic control. Having greater days of inactivity was associated with poor glycemic control while having greater days of poor physical health was associated with borderline glycemic control. There were no statistically significant relationships between glycemic control, self-reported general health, employment, and missed work. Finally, having an HbA1c value less than 6.5% was protective against mortality. The findings suggest that work-related factors are important in a person’s ability to reach optimal diabetes management levels. Poor glycemic control appears to have significant detrimental effects on HRQOL.