We estimate the effects of U.S. Metropolitan Statistical Area housing prices on a variety of health outcomes and health‐related behaviors separately for homeowners and tenants. The constructed data set consists of information on individuals from the 2002–2012 Behavioral Risk Factor Surveillance System combined with homeownership data from the March Current Population Survey and housing prices from Freddie Mac. We estimate positive effects on homeowners' mental health when housing prices increase. We also find negative effects on tenants' health and health‐related behaviors with increases in housing prices. These estimated contemporaneous effects are concentrated among low‐income homeowners and tenants, and the effects for tenants are not persistent in the long run. However, the cumulative effects of an increase in housing prices on obesity become more pronounced for homeowners in the long run, resulting in worse self‐reported health.

About 800 foodborne disease outbreaks are reported in the United States annually. Few are associated with food recalls. We compared 226 outbreaks associated with food recalls with those not associated with recalls during 2006-2016. Recall-associated outbreaks had, on average, more illnesses per outbreak and higher proportions of hospitalisations and deaths than non-recallassociated outbreaks. The top confirmed aetiology for recall-associated outbreaks was Salmonella. Pasteurised and unpasteurised dairy products, beef, and mollusks were the most frequently implicated foods. The most common pathogen-food pairs for outbreaks with recalls were Escherichia coli-beef and norovirus-mollusks; the top pairs for non-recall-associated outbreaks were scombrotoxin-fish and ciguatoxin-fish. For outbreaks with recalls, 48% of the recalls occurred after the outbreak, 27% during the outbreak, 3% before the outbreak, and 22% were inconclusive or had unknown recall timing. Fifty per cent of recall-associated outbreaks were multistate, compared with 2% of non-recall-associated outbreaks. The differences between recall-associated outbreaks and non-recall-associated outbreaks help define the types of outbreaks and food vehicles that are likely to have a recall. Improved outbreak vehicle identification and traceability of rarely recalled foods could lead to more recalls of these products, resulting in fewer illnesses and deaths.

Objective. Adolescent idiopathic scoliosis (AIS) affects 1%-4% of adolescents in the early stages of puberty, but there is still no effective prediction method. This study aimed to establish a prediction model and validated the accuracy and efficacy of this model in predicting the occurrence of AIS. Methods. Data was collected from a population-based school scoliosis screening program for AIS in China. A sample of 884 children and adolescents with the radiological lateral Cobb angle≥10° was classified as an AIS case, and 895 non-AIS subjects with a Cobb angle<10° were randomly selected from the screening system. All selected subjects were screened by visual inspection of clinical signs, the Adam’s forward-bending test (FBT), and the measurement of angle of trunk rotation (ATR). LR and receiver operating characteristic (ROC) curves were used to preliminarily screen the influential factors, and LR models with different adjusted weights were established to predict the occurrence of AIS. Results. Multivariate LR and ROC curves indicated that angle of thoracic rotation (adjusted odds ratios AOR=5.18−10.06), angle of thoracolumbar rotation (AOR=4.67−7.22), angle of lumbar rotation (AOR=6.97−8.09), scapular tilt (area under the curve AUC=0.77, 95% CI: 0.75-0.80), shoulder-height difference, lumbar concave, and pelvic tilt were the risk predictors for AIS. LR models with different adjusted weights (by AOR, AUC, and AOR+AUC) performed similarly in predicting the occurrence of AIS compared with multivariate LR. The sensitivity (82.55%-83.27%), specificity (82.59%-83.33%), Youden’s index (0.65-0.67), positive predictive value (82.85%-83.58%), negative predictive value (82.29%-83.03%), and total accuracy (82.57%-83.30%) manifested that LR could accurately identify patients with AIS. Conclusions. LR model is a relatively high accurate and feasible method for predicting AIS. Increased performance of LR models using clinically relevant variables offers the potential to early identify high-risk groups of AIS.

Objectives: Adolescent idiopathic scoliosis (AIS) affects between 1 and 4% of adolescents, and severe curvature may be related to their adverse long-term outcomes. However, whether the change in body appearance is related to AIS remains largely unclear. We aimed to explore the association between incorrect posture and AIS among Chinese adolescents. Methods: Data were collected from a population-based (595,057) school scoliosis screening program in China. A sample of 3,871 adolescents was classified as cases with a diagnosed radiological lateral Cobb angle ≥10 • , and 3,987 control subjects with a Cobb angle <10 • were randomly selected from the screening system. Adolescents were accessed with demographic information and incorrect posture measured by visual inspection of physical signs, Adam's forward bending test (FBT), and the angle of trunk rotation (ATR). Logistic regression (LR) models were used to examine the associations. Results: Multivariate LR showed that shoulder-height difference, scapula tilt, lumbar concave, and pelvic tilt were associated with AIS. Adolescents with angle of thoracic rotation ≥5 • [adjusted odds ratio (AOR) = 5.33-14.67, P < 0.001], thoracolumbar rotation ≥5 • (AOR = 4.61-5.79, P < 0.001), or lumbar rotation ≥5 • (AOR = 7.49-7.85, P < 0.001) were at especially higher risk for AIS than those with ATR <5 •. Conclusions: Incorrect posture may be the potential risk factor for developing AIS, and ATR ≥5 • was an important indicator for predicting the occurrence of scoliosis. Early monitoring of incorrect posture for school adolescents should be considered as a routine intervention to effectively identify the progress of scoliosis.