Predicting Upper Quadrant Musculoskeletal Injuries in the Military: A Cohort Study.

PURPOSE: This study aimed to identify characteristics and movement-based tests that predict upper quadrant musculoskeletal injury (UQI) in military personnel over a 12-month follow-up. METHODS: A prospective observational cohort study of military members (n = 494; 91.9% male) was conducted. Baseline predictors associated with UQI were gathered through surveys and movement-based tests. Survey data included demographic information, injury history, and biosocial factors. Movement-based tests include the following: Y Balance Tests (YBT), Functional Movement Screen, Selective Functional Movement Assessment lumbar multisegmental mobility, modified-modified Schober, side bridge, ankle mobility, modified Sorensen, and passive lumbar extension. Self-reported UQI was collected through monthly online surveys, and 87% completed the follow-up. Univariate associations were determined between potential predictors and UQI. A forward, stepwise logistic regression model was used to identify the best combination of predictors for UQI. RESULTS: Twenty-seven had UQI. Univariate associations existed with three demographic (smoking, >1 previous UQI, baseline upper quadrant function ≤90%), three pain-related (Selective Functional Movement Assessment rotation, side bridge, hurdle step), and six movement-based variables (YBT upper quarter (UQ) superolateral worst score ≤57.75 cm, YBT-UQ composite worst score ≤81.1%, failed shoulder clearance, Sorenson <72.14 s, in-line lunge total score <15, and in-line lunge asymmetry >1). Smoking, baseline upper quadrant function ≤90%, and YBT-UQ composite score ≤81.1% predicted UQI in the logistic regression while controlling for age and sex. Presenting two or more predictors resulted in good specificity (85.6%; odds ratio, 4.8; 95% confidence interval, 2.2-10.8), and at least one predictor resulted in 81.5% sensitivity (odds ratio, 3.2; 95% confidence interval, 1.2-8.7). CONCLUSIONS: A modifiable movement-based test (YBT-UQ), perceived upper limb function, and smoking predicted UQI. A specific (two or more) and sensitive (at least one predictor) model could identify persons at higher risk.

Maternal obesity characterized by gestational diabetes increases the susceptibility of rat offspring to hepatic steatosis via a disrupted liver metabolome.

Maternal obesity is associated with a high risk for gestational diabetes mellitus (GDM), which is a common complication of pregnancy. The influence of maternal obesity and GDM on the metabolic health of the offspring is poorly understood. We hypothesize that GDM associated with maternal obesity will cause obesity, insulin resistance and hepatic steatosis in the offspring. Female Sprague-Dawley rats were fed a high-fat (45%) and sucrose (HFS) diet to cause maternal obesity and GDM. Lean control pregnant rats received low-fat (LF; 10%) diets. To investigate the interaction between the prenatal environment and postnatal diets, rat offspring were assigned to LF or HFS diets for 12 weeks, and insulin sensitivity and hepatic steatosis were evaluated. Pregnant GDM dams exhibited excessive gestational weight gain, hyperinsulinaemia and hyperglycaemia. Offspring of GDM dams gained more weight than the offspring of lean dams due to excess adiposity. The offspring of GDM dams also developed hepatic steatosis and insulin resistance. The postnatal consumption of a LF diet did not protect offspring of GDM dams against these metabolic disorders. Analysis of the hepatic metabolome revealed increased diacylglycerol and reduced phosphatidylethanolamine in the offspring of GDM dams compared to offspring of lean dams. Consistent with altered lipid metabolism, the expression of CTP:phosphoethanolamine cytidylyltransferase, and peroxisomal proliferator activated receptor-α mRNA was reduced in the livers of GDM offspring. GDM exposure programs gene expression and hepatic metabolite levels and drives the development of hepatic steatosis and insulin resistance in young adult rat offspring.