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.

Background: Diabetes is the seventh leading cause of death in the United States. More and more people have suffered from diabetes and its serious complications including heart disease, blindness, etc. The U.S. Department of Veterans Affairs (VA) reported that nearly 25% of veterans, enrolled in the Veterans Health Administration (VHA),have diabetes, which is much higher than the general population. Objective: This study aimed to estimate the prevalence of diabetes in the U.S. veterans using the up-to-date National Health and Nutrition Examination Survey (NHANES) data since VHA has a relatively low coverage (less than 30% of veterans each year were enrolled). Methods: Five biennial cross sectional surveys (NHANES) from 2005-2014 were used in this study. Total 2,940 veterans were included to estimate the prevalence of diabetes. Total diabetes was defined as any participant who had at least one of four conditions: (1) a hemoglobin A1c at least 6.5%, (2) fasting plasma glucose (FPG) at least 126mg/dL, (3)a 2-hour plasma glucose (PG) at least 200mg/dL, (4) diagnosed with diabetes by a doctor or other health professional. Results: The overall prevalence of total diabetes(including diagnosed and undiagnosed diabetes), undiagnosed diabetes and obesity were 20.54%, 3.37% and 40.68%, respectively. The family poverty level and education were significantly associated with the presence of diabetes with p=0.005 and 0.03,respectively. Highest prevalence diabetes and obesity existed in veterans aged 65yrs and over and 45-64yrs, respectively. The overall prevalence trend of diabetes significantly increased from 15.52% (95%CI: 12.36-18.68%) in 2005-2006 to 20.54% (95%CI:15.92-25.17%) (p=0.04 for trend test) and prevalence significantly increased in male veterans (p=0.04) and those who did not finish high school education (p=0.04) and who had college education (p=0.03). Conclusion: In 2013-2014, the estimated prevalence of diabetes was 20.54% among U.S. veterans, with higher prevalence among participants who were 65 years old or older, and had low socioeconomic status (including less education and poverty status).

The objective of this thesis is to assess the prevalence of low quality of life in adult cancer survivors and predictors for these low scores, separately for physical and mental quality of life. Possible predictors can include sociodemographic, clinical, and behavioral factors. The data source for this thesis is the National Health and Nutrition Examination Survey (NHANES) 2005-2012. The sample population included 1244 cancer survivors 20 years or older that answered “yes” to the question “have you ever been told by a doctor or other health professional that had cancer or malignancy of any kind?” Mental and physical health scores were determined based on the number of days physical and mental health was not good and dichotomized according to mean value. The four groups identified were low mental health and low physical health (n=148, 11.9%), low mental health and high physical health (n=239, 19.2%), high mental health and low physical health (n=143, 11.5%), and high mental health and high physical health (n=714, 57.4%). The diet quality was calculated using the Healthy Eating Index 2015, which measures adherence to the Dietary Guidelines for Americans 2015-2020. The SAS Survey Analysis Procedures was used to account for the random multi-stage sampling of NHANES. Also, ANOVA and chi-square tests were used to determine the possible predictors of low quality of life while multivariable logistic regression analysis was performed to examine the independent predictors of low physical and mental health. Statistical significance was set at a two-sided p-value of

The study sample was comprised of 18,953 subjects aged 18 years and older who participated in the Third National Health and Nutrition Examination Survey. Preference for diet soda over regular soda was higher in females as compared to males and in Caucasians as compared to other races. Mean alcohol consumption was almost three times higher in males than in females. Undiagnosed hypertension was more common in males than in females, in 65-90 than in 50-64 year olds, and in people with less than high school education compared to those with higher education. Diastolic pressure was correlated with the level of consumption of diet soda, coffee, tea, and alcohol. Diet soda and alcohol consumption had a statistically significant positive relationship with hypertension even after adjusting for demographic variables and body mass index. The study provides useful information of the patterns of beverage uses and the prevalence of hypertension in the United States.

No description available.

Sarcopenia is a growing health problem in this country as more Americans are living well into old age. It has been thought that a higher protein intake may be related to greater lean muscle mass as well as greater muscular strength and physical functioning. The purpose of this research was to examine protein intake and its relationship to lean body mass and physical functioning in a nationally representative sample of U.S. adults. This research used cross-sectional data from the NHANES 2003-2004 to examine the relationship between protein intake, as an average from two 24h recalls, and dual X-ray absorptiometry (DXA) lean body mass measures. Additionally, these lean body mass measures were examined as predictive of Physical Limitation Score (PLS), an index created from self-reported difficulty in performing basic activities of daily living. Protein intake was examined as total grams of intake, a percentage of total daily energy and as a percent contributed by animal foods. The lean body mass measures used in this analysis included: total lean mass, appendicular lean mass, muscle mass index [lean mass / height (m2)], appendicular lean mass [appendicular lean mass / height (m2)] and percent lean body mass. Questions used to create the self-reported index of functioning, the Physical Limitation Score (PLS), included difficulty in independently: walking ¼ mile, walking up ten stairs without resting, lifting and carrying 10lbs and standing from an armless straight chair. It was found that protein intake significantly, positively predicted lean body mass in select age-gender groups, while more often in men than in women. Total grams of protein intake positively predicted total and appendicular muscle mass index in men ages 19-50 (p-value <0.05), appendicular muscle mass index in men ages 51-70 (p-value 0.038) and percent lean mass in men 71+ years (p-value 0.026). Protein as a percent of energy was a significant, positive predictor of appendicular lean mass in men 19-50 (p-value 0.048), muscle mass index in women 19-50 (p-value 0.007), appendicular muscle mass index in women 19-50 (p-value 0.024) and percent lean mass in men 71+ years (p-value 0.019). Protein as a percent of energy was a significant negative predictor of percent lean mass in older women 71+ years (p-value 0.046). Protein as a percent contributed by animal foods was not a significant predictor of lean mass in any age-gender group. It was also found that Physical Limitation Score (PLS) was surprisingly positively predicted by total and appendicular lean and total and appendicular muscle mass index in nearly all age-gender groups (p-value <0.05) or at least moderately, positively predicted by these (p-value <0.10), meaning that having a greater amount of lean mass predicted greater physical limitation. The only exception was percent lean mass, which was a significant negative predictor of PLS in men and women 60-70 years (p-value <0.05). In this case, a higher percent lean mass was associated with less physical limitation. Additional follow-up analyses revealed that total body fat mass (kg) and percent body fat were significant positive predictors of PLS in most age-gender groups (p-value <0.05), indicating that higher amounts of body fat predicted greater self-reported limitation. Protein expressed as total grams per day or as a percent of total daily energy were generally significant or marginally significant predictors of lean mass in men of all ages but not often in women while protein as a percent contributed by animal foods was not found to be a significant predictor in any age-gender group. Total lean mass, total fat mass and total percent body fat were generally significant positive predictors of physical limitation, calling into question the functional implications of body composition in an older population. Results suggest that in older adults, excess body fat may be a stronger predictor of physical limitation than low lean muscle mass.

BACKGROUND: Periodontal disease is a major chronic disease worldwide and one of the most prevalent oral pathologies. Some factors that may lead to periodontal disease include poor nutrition, chronic illness, poor lifestyle choices, smoking, and excessive alcohol consumption. Previous studies have also revealed a biological link between diabetes or obesity and periodontal health status. Because physical activity can reduce the risk of diabetes and obesity, it would follow that physical activity may also lead to improved periodontal health. However, to date, there has been limited research on the effects of physical activity on periodontal disease risk. Our investigation answers the following question: Do people who are more physically active have better periodontal health than those who are inactive? OBJECTIVE: The purpose of our research initiative was to evaluate the prevalence of periodontal disease among people who are physically inactive versus those who are physically active using data from NHANES. METHODS: In this study, we utilized the publicly available NHANES 2011-2012 datasets of 9756 observations before exclusions. Our study included individuals (30-80 years of age) consisting of 49.4% male and 50.6% female who provided demographic data, periodontal and dentition examination data, and self-reported smoking and physical activity data (Table 3). There were a total of 3327 observations meeting our inclusion criteria. Weighted prevalence estimates and odds ratios (OR) were calculated for physical activity adjusted by age, gender, race, education level, and economic status. Physical activity was categorized by domains of transportation physical activity, occupation physical activity, leisure time physical activity, and sedentary behavior. Physical activity was also categorized into a dichotomous total amount of physical activity by adding the three major physical activity domains. RESULTS: We observed higher rates of periodontal disease in men, in older adults, smokers, and individuals with diabetes mellitus. We also observed that individuals with higher total physical activity and leisure time physical activity and lower amount of total sedentary activity had lower periodontal disease rates. After adjusting for confounders, lower sedentary time was associated with lower periodontal disease rates (OR 1.18; 95% CI (Confidence Interval) 1.01,1.38; p=0.0416), but total physical activity and leisure time was not significantly associated with periodontal disease (OR 1.00; 95% CI 0.79,1.28; p=0.98) (OR 1.14; 95% CI 0.81,1.61; p=0.42) (Table 5). CONCLUSION: Our findings indicate sedentary time is associated with higher rates of periodontal disease. Future prospective longitudinal studies and strategies are needed to investigate implications further and define the magnitude of the association between physical activity and periodontal disease.

Background: Type 2 diabetes mellitus is one of the leading chronic diseases affecting Americans. There is a lack of literature discussing the link between diet and prognosis of those already diagnosed with DM. Objective: To provide insight into which diet is better for the outlook of diabetes mellitus by examining the associations between the low-carbohydrate diet (LCD) score and three diabetes-related health indicators: blood hemoglobin (HbA1c), triglycerides, and retinopathy. Methods: A total of 3,313 U.S. adults with DM were selected from the National Health and Nutrition Examination Survey 2005-2016. Presence of retinopathy was ascertained through self-reporting. Dietary intake was measured with 24- hour dietary recalls, and LCD scores were calculated from the proportion of energy of three macronutrients. Scores ranged from 0-30, with a higher score indicating lower carbohydrate intake. Results: There was no significant difference in HbA1c levels between the highest and the lowest quintile of LCD score (mean = 7.42% [95% CI: 7.23, 7.61] vs. 7.32% [95% CI: 7.13, 7.51]). There was no significant association between blood triglyceride levels and LCD score, comparing quintile 1 to quintile 5 (mean= 168.64 mg/dl; 95% CI = [150.14, 187.14] vs. mean= 162.44 mg/dl; 95% CI = [143.76, 181.11]). In multivariable logistic regression analysis, the odds ratio of having retinopathy comparing the highest to the lowest quintile was 1.01 (95% CI: 0.59, 1.72). Conclusion: Proportion of carbohydrate in diet was not associated with DM prognosis factors. Future studies should focus on carbohydrate quality as well as quantity.

10,291 participants, aged 20 to 85 years of age, available from the 1999 through 2002 NHANES databases participated in this study. Only 8,485 (82%) of these participants were included in the data analysis. Participants who were pregnant (n = 603), not examined at a mobile examination center (n = 820), or had missing values for height (n = 164) and/or weight (n = 125) were eliminated. Individuals were classified into four groups (underweight, normal, overweight and obese) based on body mass index (BMI). Variables measured in the study included body mass index, physical fitness, dietary folic acid, c-reactive protein, homocysteine, folate, serum total cholesterol, serum triglycerides, HDL-C, and glucose. All data was collected at Mobile Examination Centers (MEC). The results of the present study showed that being overweight and obese were associated with a poor serum lipid profile, higher serum glucose levels, lower participation in physical activity and a lower physical fitness level. Being overweight and obese was also associated with higher serum levels of inflammatory markers for cardiovascular disease (CVD). Overweight and obese individuals are also being diagnosed with coronary heart disease (CHD) at a younger age.

No description available.