Soft Wireless Bioelectronics Designed for Real-Time, Continuous Health Monitoring of Farmworkers.

Hotter summers caused by global warming and increased workload and duration are endangering the health of farmworkers, a high-risk population for heat-related illness (HRI), and deaths. Although prior studies using wearable sensors show the feasibility of employing field-collected data for HRI monitoring, existing devices still have limitations, such as data loss from motion artifacts, device discomfort from rigid electronics, difficulties with administering ingestible sensors, and low temporal resolution. Here, this paper introduces a wireless, wearable bioelectronic system with functionalities for continuous monitoring of skin temperature, electrocardiograms (ECG), heart rates (HR), and activities, configured in a single integrated package. Advanced nanomanufacturing based on laser machining allows rapid device fabrication and direct incorporation of sensors with a highly breathable substrate, allowing for managing excessive sweating and multimodal stresses. To validate the device's performance in agricultural settings, the device is applied to multiple farmworkers at various operations, including fernery, nursery, and crop. The accurate data recording, including high-fidelity ECG (signal-to-noise ratio: >20 dB), accurate HR (r = 0.89, r2 = 0.65 in linear correlation), and reliable temperature/activity, confirms the device's capability for multiparameter health monitoring of farmworkers.

Analyzing the predictors of health care utilization in the agricultural worker population using decision tree analysis: Does language matter?

OBJECTIVES: To analyze the predictors of health care utilization among respondents to the National Agricultural Worker Survey. Specifically, we hypothesized that English proficiency would predict utilization of health care services within the last 2 years. METHODS: Using the 2015-2016 National Agricultural Worker Survey, we performed a secondary data analysis to analyze the predictors of health care utilization within the last 2 years in the United States' agricultural worker population. Data were cleaned and analyzed using decision tree analysis, which produced a classification tree model that was trained on 90% of the data and validated on 10%. RESULTS: Exposure to English was not a predictor of health care utilization in our classification tree. The first major partition that predicted utilization was insurance status. Additional partitions were on age, gender, hypertension diagnosis, and public aid. CONCLUSIONS: By partitioning on insurance status and use of public aid, the decision tree provided evidence that systemic factors are key determinants of health care utilization in the agricultural worker community. This highlights the importance of agencies that connect agricultural workers with resources that provide insurance and improve access to health care. This is especially important given that agricultural workers are one of the highest risk groups for occupational injury or death in the United States.

Predictors of US medical students' prevention counseling practices.

OBJECTIVE: To understand predictors of medical students' prevention counseling practices. METHODS: We surveyed medical students (n=2316 individuals) in the Class of 2003 at freshman orientation, and again at entrance to wards and senior year in a nationally representative sample of 16 US medical schools (response rate=80.3%). MAIN OUTCOME MEASURES: Perceived relevance of prevention counseling and seniors' frequency of prevention counseling. RESULTS: Healthier personal practices (p<0.0001), intention to become a primary care practitioner (p=0.0007), and attending a medical school that encouraged healthy personal practices (p=0.002) significantly predicted the frequency with which seniors reported currently counseling patients about preventive interventions (using a validated measure). Perceived counseling relevance was also significantly predicted by intention to become a primary care practitioner (p<0.0001), attending a school that encouraged healthy personal practices (p=0.0007), being earlier in one's training (p<0.0001), more interested in prevention (p<0.0001), female (p<0.0001), non-White (p=0.007), and by having healthy personal practices (p=0.008). CONCLUSIONS: Several of the variables predicting physician counseling also predict US medical students' reporting counseling (especially personal health practices and specialty type). In addition, the avidity with which medical schools encourage students to be healthy significantly influences their reported patient counseling. These findings can give a fresh, evidence-based direction to help create physicians who counsel patients about prevention.

Validation of a brief diet survey instrument among medical students.

Our objective was to assess the reproducibility and accuracy of fat and of fruit and vegetable items on a 43-item food frequency questionnaire (FFQ) previously self-administered by students at 16 US medical schools. Five in-person, 24-hour recalls were administered between two FFQ administrations to 88 medical students. Reported fat intake decreased from the first (34.7%) to the second (33.1%) FFQ administration ( P <.001); the reproducibility correlation was r =0.63. Fat intake from recalls (28.4%) was lower than that from the FFQ (33.8%, P <.001). The Pearson correlation was r =0.36. Fruit and vegetable servings per day were 3.9 and 3.7 from the first and second FFQ, respectively ( P =.5); the reproducibility correlation was r =0.77. Fruit and vegetable servings were marginally higher from recalls (4.3) than from the FFQ (3.8, P =.06). The Pearson correlation for fruit and vegetable servings was r =0.50. This brief FFQ provides acceptably reproducible and valid estimates of fruit and vegetable servings per day among most groups of medical students, but overestimates fat as a percentage of energy intake.