BACKGROUND: Sex-specific prediabetes estimates are not available for older-adult Americans. PURPOSE: To estimate prediabetes prevalence, using nationally representative data, in civilian, non-institutionalized, older U.S. adults. METHODS: Data from 7,995 participants aged ≥50 years from the 1999-2010 National Health and Nutrition Examination Surveys were analyzed in 2013. Prediabetes was defined as hemoglobin A1c=5.7%-6.4% (39-47 mmol/mol [HbA1c5.7]), fasting plasma glucose of 100-125 mg/dL (impaired fasting glucose [IFG]), or both. Crude and age-adjusted prevalences for prediabetes, HbA1c5.7, and IFG by sex and three age groups were calculated, with additional adjustment for sex, age, race/ethnicity, poverty status, education, living alone, and BMI. RESULTS: From 1999 to 2005 and 2006 to 2010, prediabetes increased for adults aged 50-64 years (38.5% [95% CI=35.3, 41.8] to 45.9% [42.3, 49.5], p=0.003) and 65-74 years (41.3% [37.2, 45.5] to 47.9% [44.5, 51.3]; p=0.016), but not significantly for adults aged ≥75 years (45.1% [95% CI=41.1, 49.1] to 48.9% [95% CI=45.2, 52.6]; p>0.05). Prediabetes increased significantly for women in the two youngest age groups, and HbA1c5.7 for both sexes (except men aged ≥75 years), but IFG remained stable for both sexes. Men had higher prevalences than women for prediabetes and IFG among adults aged 50-64 years, and for IFG among adults aged ≥75 years. Across demographic subgroups, adjusted prevalence gains for both sexes were similar and most pronounced for HbA1c5.7, virtually absent for IFG, but greater for women than men for prediabetes. CONCLUSIONS: Given the large, growing prediabetes prevalence and its anticipated burden, older adults, especially women, are likely intervention targets.

PURPOSE: There has not been a recent comprehensive effort to examine existing studies on resting metabolic rate (RMR) of adults to identify the effect of common population demographic and anthropometric characteristics. Thus, we reviewed the literature on RMR (kcalkgh) to determine the relationship of age, sex, and obesity status to RMR as compared to the commonly accepted value for the metabolic equivalent or the MET (e.g., 1.0 kcalkgh). METHODS: Using several databases, scientific articles published 1980 to 2011 were identified that measured RMR and from those, others dating back to 1920 were identified. 197 studies were identified resulting in 397 publication estimates of RMR that could represent a population subgroup. Inverse variance weighting technique was applied to compute means and 95% confidence interval (CI). RESULTS: The mean value for RMR was 0.863 (95% CI = 0.852[FIGURE DASH]0.874) kcalkgh; higher for men than women; decreasing with increasing age; and less in overweight than normal weight adults. Regardless of sex, adults with BMI ≥30 kgm had the lowest RMR (<0.741 kcalkgh). CONCLUSION: No single value for RMR is appropriate for all adults. Adhering to the nearly universally accepted MET convention may lead to overestimation of RMR of about 10% for men and almost 15% for women, and be as high as 20[FIGURE DASH]30% for some demographic and anthropometric combinations. These large errors raise questions about the longstanding adherence to the conventional MET value for RMR. Failure to recognize this discrepancy may result in important miscalculations of energy expended from interventions using physical activity for diabetes and other chronic disease prevention efforts.

OBJECTIVE: To use structural modeling to test a hypothesized model of causal pathways related with prediabetes among older adults in the U.S. RESEARCH DESIGN AND METHODS: Cross-sectional study of 2,230 older adults (≥50 years) without diabetes included in the morning fasting sample of the 2001-2006 National Health and Nutrition Examination Surveys. Demographic data included age, income, marital status, race/ethnicity, and education. Behavioral data included physical activity (metabolic equivalent hours per week for vigorous, moderate, muscle-strengthening, walking/biking, and house/yard work), and poor diet (refined grains, red meat, added sugars, solid fats, and high-fat dairy). Structural-equation modeling was performed to examine the interrelationships among these variables with family history of diabetes, high blood pressure, BMI, large waist (waist circumference: women, ≥35 inches; men, ≥40 inches), triglycerides ≥200 mg/dL, and total- and HDL (≥60 mg/dL) cholesterol. RESULTS: After dropping BMI and total cholesterol, our best-fit model included three single factors: socioeconomic position (SEP), physical activity, and poor diet. Large waist had the strongest direct effect on prediabetes (0.279), followed by male sex (0.270), SEP (-0.157), high blood pressure (0.122), family history of diabetes (0.070), and age (0.033). Physical activity had direct effects on HDL (0.137), triglycerides (-0.136), high blood pressure (-0.132), and large waist (-0.067); poor diet had direct effects on large waist (0.146) and triglycerides (0.148). CONCLUSIONS: Our results confirmed that, while including factors known to be associated with high risk of developing prediabetes, large waist circumference had the strongest direct effect. The direct effect of SEP on prediabetes suggests mediation by some unmeasured factor(s).

OBJECTIVE: Using a nationally representative sample of the civilian noninstitutionalized U.S. population, we estimated prediabetes prevalence and its changes during 1999-2010. RESEARCH DESIGN AND METHODS: Data were from 19,182 nonpregnant individuals aged ≥12 years who participated in the 1999-2010 National Health and Nutrition Examination Surveys. We defined prediabetes as hemoglobin A1c 5.7 to <6.5% (39 to <48 mmol/mol, A1C5.7) or fasting plasma glucose (FPG) 100 to <126 mg/dL (impaired fasting glucose [IFG]). We estimated the prevalence of prediabetes, A1C5.7, and IFG for 1999-2002, 2003-2006, and 2007-2010. We calculated estimates age-standardized to the 2000 U.S. census population and used logistic regression to compute estimates adjusted for age, sex, race/ethnicity, poverty-to-income ratio, and BMI. Participants with self-reported diabetes, A1C ≥6.5% (≥48 mmol/mol), or FPG ≥126 mg/dL were included. RESULTS: Among those aged ≥12 years, age-adjusted prediabetes prevalence increased from 27.4% (95% CI 25.1-29.7) in 1999-2002 to 34.1% (32.5-35.8) in 2007-2010. Among adults aged ≥18 years, the prevalence increased from 29.2% (26.8-31.8) to 36.2% (34.5-38.0). As single measures among individuals aged ≥12 years, A1C5.7 prevalence increased from 9.5% (8.4-10.8) to 17.8% (16.6-19.0), a relative increase of 87%, whereas IFG remained stable. These prevalence changes were similar among the total population, across subgroups, and after controlling for covariates. CONCLUSIONS: During 1999-2010, U.S. prediabetes prevalence increased because of increases in A1C5.7. Continuous monitoring of prediabetes is needed to identify, quantify, and characterize the population of high-risk individuals targeted for ongoing diabetes primary prevention efforts.

Diabetes (diagnosed or undiagnosed) affects 10.9 million US adults aged 65 years and older. Almost 8 in 10 have some form of dysglycemia, according to tests for fasting glucose or hemoglobin A1c. Among this age group, diagnosed diabetes is projected to reach 26.7 million by 2050, or 55% of all diabetes cases. In 2007, older adults accounted for $64.8 billion (56%) of direct diabetes medical costs, $41.1 billion for institutional care alone. Complications, comorbid conditions, and geriatric syndromes affect diabetes care, and medical guidelines for treating older adults with diabetes are limited. Broad public health programs help, but effective, targeted interventions and expanded surveillance and research and better policies are needed to address the rapidly growing diabetes burden among older adults. (Am J Public Health. Published online ahead of print June 14, 2012: e1-e16. doi:10.2105/AJPH.2011.300616).

OBJECTIVE: To estimate the prevalence of diagnosed arthritis among U.S. adults and the proportion of arthritis-attributable activity limitation (AAAL) among those with arthritis by diagnosed diabetes mellitus (DM) status. RESEARCH DESIGN AND METHODS: We estimated prevalences and their ratios using 2008-2010 U.S. National Health Interview Survey of noninstitutionalized U.S. adults aged ≥18 years. Respondents' arthritis and DM status were both based on whether they reported a diagnosis of these diseases. Other characteristics used for stratification or adjustment included age, sex, race/ethnicity, education level, BMI, and physical activity level. RESULTS: Among adults with DM, the unadjusted prevalences of arthritis and proportion of AAAL among adults with arthritis (national estimated cases in parentheses) were 48.1% (9.6 million) and 55.0% (5.3 million), respectively. After adjusting for other characteristics, the prevalence ratio of arthritis and of AAAL among arthritic adults with versus without DM (95% CI) were: 1.44 (1.35-1.52) and 1.21 (1.15-1.28), respectively. The prevalence of arthritis increased with age and BMI and was higher for women, non-Hispanic whites, and inactive adults compared with their counterparts both among adults with- and without DM (all P values < 0.05). Among adults with diagnosed DM and arthritis, the proportion of AAAL was associated with being obese, but was not significantly associated with age, sex, and race/ethnicity. CONCLUSION: Among U.S. adults with diagnosed DM, nearly half also have diagnosed arthritis; moreover, more than half of those with both diseases had AAAL. Arthritis can be a barrier to physical activity among adults with diagnosed DM.

BACKGROUND: Current estimates from objective accelerometer data suggest that American adults are sedentary for approximately 7.7 h/day. Historically, sedentary behaviour was conceptualized as one end of the physical activity spectrum but is increasingly being viewed as a behaviour distinct from physical activity. METHODS: Prospective studies examining the associations between screen time (watching television, watching videos and using a computer) and sitting time and fatal and non-fatal cardiovascular disease (CVD) were identified. These prospective studies relied on self-reported sedentary behaviour. RESULTS: The majority of prospective studies of screen time and sitting time has shown that greater sedentary time is associated with an increased risk of fatal and non-fatal CVD. Compared with the lowest levels of sedentary time, risk estimates ranged up to 1.68 for the highest level of sitting time and 2.25 for the highest level of screen time after adjustment for a series of covariates, including measures of physical activity. For six studies of screen time and CVD, the summary hazard ratio per 2-h increase was 1.17 (95% CI: 1.13-1.20). For two studies of sitting time, the summary hazard ratio per 2-h increase was 1.05 (95% CI: 1.01-1.09). CONCLUSIONS: Future prospective studies using more objective measures of sedentary behaviour might prove helpful in quantifying better the risk between sedentary behaviour and CVD morbidity and mortality. This budding science may better shape future guideline development as well as clinical and public health interventions to reduce the amount of sedentary behaviour in modern societies.

INTRODUCTION: Physical activity helps diabetic older adults who have physical impairments or comorbid conditions to control their disease. To enable state planners to select physical activity programs for these adults, we calculated synthetic state-specific estimates of inactive older adults with diabetes, categorized by defined health status groups. METHODS: Using data from the 2000 through 2009 National Health Interview Survey (NHIS) and the Behavioral Risk Factor Surveillance System (BRFSS), we calculated synthetic state-specific estimates of inactive adults with diabetes who were aged 50 years or older for 5 mutually exclusive health status groups: 1) homebound, 2) frail (functional difficulty in walking one-fourth mile, climbing 10 steps, standing for 2 hours, and stooping, bending, and kneeling), 3) functionally impaired (difficulty in 1 to 3 of these functions), 4) having 1 or more comorbid conditions (with no functional impairments), and 5) healthy (no impairments or comorbid conditions). We combined NHIS regional proportions for the health status groups of inactive, older diabetic adults with BRFSS data of older diabetic adults to estimate state-specific proportions and totals. RESULTS: State-specific estimates of health status groups among all older adults ranged from 2.2% to 3.0% for homebound, 5.8% to 8.8% for frail, 20.1% to 26.1% for impaired, 34.9% to 43.7% for having comorbid conditions, and 4.0% to 6.9% for healthy; the remainder were older active diabetic adults. Except for the homebound, the percentages in these health status groups varied significantly by region and state. CONCLUSION: These state-specific estimates correspond to existing physical activity programs to match certain health status characteristics of groups and may be useful to program planners to meet the needs of inactive, older diabetic adults.

BACKGROUND: Walking is commonly recommended for enhancing energy expenditure (EE), a basic principle in weight management, and cardiorespiratory fitness. However, walking EE varies with characteristics of a given population, especially by sex and age. PURPOSE: To measure EE of walking as influenced by physical and physiological characteristics of a sample of adults (≥ 20 years) living in Niteroi, Rio de Janeiro, Brazil. METHODS: Walking EE and heart rate were measured during a sub-maximal multi-stage treadmill test. The test stages lasted for 3 minutes each and started at a speed of 1.11 m/s and a grade of 0%. In the second stage, the grade was maintained at 0% but the speed was increased to 1.56 m/s and maintained at this speed but with grade raised by 2.5% at each stage until 10% at stage 6. The resting metabolic equivalent (METm) was measured via oxygen consumption prior to the test with the participants sitting quietly. RESULTS: METm (mean mL O2/kg/min +/- standard error) was lower both in women (2.85 +/- 0.03) and men (2.97 +/- 0.04) by almost 19% and 15%, respectively, compared with the conventionally-estimated MET (METe) of 3.5 mL O2/kg/min. Walking EE for any given speed and grade had an absolute intensity, expressed as multiples of METm or METe, that was practically equal between sexes and age groups, but, it incurred higher individual physiological demand, or relative intensity, for women and older adults. CONCLUSION: Resting EE reflected by using METe is overestimated in the adult population of Niteroi. Prescription of activities to counteract the existing wordwide obesity epidemic should be ideally based on individual physiological information, especially among women and older individuals.

OBJECTIVE: To examine the American-Canadian difference in physical activity (PA) and its association with diabetes prevalence. METHODS: We used cross-sectional data from nationally representative samples of adults (8688 persons aged ≥18years) participating in the 2004 Joint Canada/U.S. Survey of Health. Using data on up to 22 activities in the past 3months, we defined 3 PA groups (in MET-hours/day) as: low (<1.5), moderate (1.5-2.9), and high (≥3.0). We employed logistic regression models in our analyses. RESULTS: Self-reported diabetes prevalence was 7.6% in the U.S. and 5.4% in Canada. The prevalence of low PA was considerably higher in the U. S. (70.9%) than in Canada (52.3%), while levels of moderate and high PA were higher in Canada (24.6% and 23.1%, respectively) than in the U.S. (14.3% and 14.8%, respectively). Using nationality (Canada as reference) to predict diabetes status, the adjusted odds ratio was 1.48 (95%CI, 1.22-1.79), and became 1.38 (95%CI, 1.15-1.66) when additionally adjusting for PA level. We estimate that 20.8% of the U.S.-Canada difference in diabetes prevalence is associated with PA. CONCLUSIONS: The difference in the prevalence of diabetes between U.S. and Canadian adults may be partially explained by differences in PA between the two countries.

BACKGROUND: To examine the prevalence of television (TV) viewing, computer use, and their combination and associations with demographic characteristics and body mass index (BMI) among U.S. youth. METHODS: The 1999 to 2006 National Health and Nutrition Examination Survey (NHANES) was used. Time spent yesterday sitting and watching television or videos (TV viewing) and using the computer or playing computer games (computer use) were assessed by questionnaire. RESULTS: Prevalence (%) of meeting the U.S. objective for TV viewing (< or =2 hours/day) ranged from 65% to 71%. Prevalence of no computer use (0 hours/day) ranged from 23% to 45%. Non-Hispanic Black youth aged 2 to 15 years were less likely than their non-Hispanic White counterparts to meet the objective for TV viewing. Overweight or obese school-age youth were less likely than their normal weight counterparts to meet the objective for TV viewing. CONCLUSIONS: Computer use is prevalent among U.S. youth; more than half of youth used a computer on the previous day. The proportion of youth meeting the U.S. objective for TV viewing is less than the target of 75%. Time spent in sedentary behaviors such as viewing TV may contribute to overweight and obesity among U.S. youth.