Football Increases Future Risk of Symptomatic Radiographic Knee Osteoarthritis.

INTRODUCTION: Male youth in the United States commonly participate in gridiron (American) football. There are little data substantiating current popular opinion that it is associated with knee pain or osteoarthritis (OA) later in life. We aimed to evaluate the relationship of football with these outcomes in the Osteoarthritis Initiative (OAI). METHODS: This is a study of male OAI participants with knee x-ray readings, symptom assessments, and completed surveys on lifetime physical activity. The OAI is a multicenter, observational cohort recruited from the community not based on football participation status. A history of exposure to American football was ascertained via self-report. Knee radiographs were scored for Kellgren-Lawrence grade (0-4). Radiographic OA (ROA) was defined as Kellgren-Lawrence ≥ 2 in at least one knee. Frequent knee pain meant at least one knee with frequent knee pain. Symptomatic ROA required at least one knee with both ROA and frequent knee pain. RESULTS: A total of 1166 men had a mean age of 63.7 (SD, 9.2) yr and body mass index of 28.6 (SD, 4.2) kg·m. Thirty-one percent (365/1166) played football at some point in their lives, 95% of whom participated from ages 12 to 18 yr. The ORs for symptomatic ROA from the lowest to highest football participation were 1.2, 1.5, and 2.2, respectively (P for trend = 0.004). Findings were similar for football from ages 12 to 18 yr and for outcomes of knee pain and ROA. CONCLUSION: This is the first large epidemiologic study to suggest that football participation, including in the teen years, may be detrimental toward knee health. Prospective studies evaluating football players are warranted.

Group-Based Trajectory Analysis of Physical Activity Change in a US Weight Loss Intervention.

BACKGROUND: The obesity epidemic is a global concern. Standard behavioral treatment including increased physical activity, reduced energy intake, and behavioral change counseling is an effective lifestyle intervention for weight loss. PURPOSE: To identify distinct step count patterns among weight loss intervention participants, examine weight loss differences by trajectory group, and examine baseline factors associated with trajectory group membership. METHODS: Both groups received group-based standard behavioral treatment while the experimental group received up to 30 additional, one-on-one self-efficacy enhancement sessions. Data were analyzed using group-based trajectory modeling, analysis of variance, chi-square tests, and multinomial logistic regression. RESULTS: Participants (N = 120) were mostly female (81.8%) and white (73.6%) with a mean (SD) body mass index of 33.2 (3.8) kg/m2. Four step count trajectory groups were identified: active (>10,000 steps/day; 11.7%), somewhat active (7500-10,000 steps/day; 28.3%), low active (5000-7500 steps/day; 27.5%), and sedentary (<5000 steps/day; 32.5%). Percent weight loss at 12 months increased incrementally by trajectory group (5.1% [5.7%], 7.8% [6.9%], 8.0% [7.4%], and 13.63% [7.0%], respectively; P = .001). At baseline, lower body mass index and higher perceived health predicted membership in the better performing trajectory groups. CONCLUSIONS: Within a larger group of adults in a weight loss intervention, 4 distinct trajectory groups were identified and group membership was associated with differential weight loss.

Racial/Ethnic Differences in the Associations Between Physical Activity and Sleep Duration: A Population-Based Study.

BACKGROUND: This study examined associations between physical activity (recreational, nonrecreational) and sleep duration among a nationally representative diverse sample of U.S. adults. METHODS: We used cross-sectional data from 9,205 National Health and Nutrition Examination Survey 2007 to 2012 participants aged 20 to 65 years who identified as White, Black, or Hispanic. Activity (ie, recreation, occupation, and transportation activity) was categorized into quartiles. Sleep duration was categorized as short (≤6 hours/night) or normal (>6 to ≤9 hours/night). Logistic regression was used to estimate associations of activity with sleep duration. RESULTS: Recommended levels of recreation activity and moderate levels of transportation activity were associated with normal sleep duration [Odds Ratio (OR): = 1.33, 95% Confidence Interval (CI) = 1.08, 1.65; OR = 1.28, 95% CI = 1.02, 1.62, respectively]. High occupation physical activity was associated with shorter sleep duration (OR = 0.59, 95% CI = 0.49, 0.71). Differences were observed by race/ethnicity in associations of recreation and occupation activity with sleep duration. CONCLUSIONS: White individuals who engaged in some recreation activity, relative to being inactive, had more favorable sleep duration; whereas, high levels of occupation activity were associated with worse sleep duration among White and Black individuals. Physical activity was not associated with sleep duration among Hispanics.