Micronutrient deficiency is a common global health problem, and accurately assessing micronutrient biomarkers is crucial for planning and managing effective intervention programs. However, analyzing micronutrient data and applying appropriate cutoffs to define deficiencies can be challenging, particularly when considering the confounding effects of inflammation on certain micronutrient biomarkers. To address this challenge, we developed the Statistical Apparatus of Micronutrient Biomarker Analysis (SAMBA) R package, a new tool that increases ease and accessibility of population-based micronutrient biomarker analysis. The SAMBA package can analyze various micronutrient biomarkers to assess status of iron, vitamin A, zinc, and B vitamins, adjust for inflammation, account for complex survey design when appropriate, and produce reports of summary statistics and prevalence estimates of micronutrient deficiencies using recommended age- and sex-specific cutoffs. We have provided a step-by-step procedure for how to use the SAMBA R package, including how to customize it for broader use, and made both the package and user manual publicly available on GitHub. SAMBA was validated by comparing results from analyzing 24 datasets on non-pregnant women of reproductive age from 23 countries and 30 datasets on preschool-age children from 26 countries with those obtained by an independent analyst. SAMBA generated identical means, percentiles, and prevalence of micronutrient deficiencies to those calculated by the independent analyst. In conclusion, SAMBA simplifies and standardizes the process for deriving survey-weighted and inflammation-adjusted (when appropriate) estimates of the prevalence of micronutrient deficiencies, reducing the time from data cleaning to result generation. SAMBA is a valuable tool that facilitates the accurate and rapid analysis of population-based micronutrient biomarker data, which can inform public health research, programs, and policy across contexts.

The Biomarkers Reflecting Inflammation and Nutritional Determinants of Anemia (BRINDA) research group was formed over a decade ago to improve the interpretation of micronutrient biomarkers in settings with inflammation. The BRINDA inflammation adjustment method uses regression correction to adjust for the confounding effects of inflammation on select micronutrient biomarkers and has provided important insights to micronutrient research, policy, and programming. However, users may face challenges when applying the BRINDA inflammation adjustment methods to their own data due to varying guidance on the adjustment approach for different biomarkers and the need to develop statistical programming to conduct these analyses. This may result in lost opportunities to have results of micronutrient data readily available during critical decision-making periods. Our research objectives are to 1) provide an all-in-one summary of the BRINDA method in adjusting multiple micronutrient biomarkers for inflammation, 2) evaluate whether malaria as a binary variable should be included in the BRINDA inflammation adjustment method, and 3) present standardized and user-friendly BRINDA adjustment R package and SAS macro. This paper serves as a practical guidebook for the BRINDA inflammation adjustment approach and aids users to use the BRINDA R package and SAS to streamline their analyses.

OBJECTIVE: This study employed analysis of workers' compensation (WC) claims in the landscaping services industry to identify occupational factors associated with claims from workers of different ages. METHODS: Private sector claims for 2005-2017 to the Ohio Bureau of Workers' Compensation (OHBWC) and their free-text descriptions were used along with data from the U.S. Census Bureau American Community Survey to examine rates and types of WC claims by worker age. RESULTS: Although the claim rate for younger workers was higher than for older workers overall (593 vs. 261 per 10,000 full-time equivalent employees, p < 0.001), claims from older workers had higher nonzero median cost ($1002 vs. $522, p < 0.001). CONCLUSION: Analysis of WC claim rates shows significant differences between claims in different age groups. These differences can be used to target safety interventions for the greatest impact.

BACKGROUND: The landscaping services industry is one of the more dangerous in the United States, with higher rates of both fatal and nonfatal injuries than the all-industry average. This study uses claims from the Ohio Bureau of Workers' Compensation (OHBWC) database to identify high rates of occupational injuries and illnesses in this industry in Ohio. The causes of those illnesses and injuries are highlighted to identify common factors. METHODS: The OHBWC database includes injured-worker industry identification, occupation, business size, demographics, diagnoses, and free-text descriptions of injury circumstances. We identified landscaping service industry claims from 2001 to 2017, and describe annual claim counts and rates. RESULTS: Over the 17-year period, 18,037 claims were accepted, with "Struck by object or equipment" and "Overexertion involving outside sources" being the most common events or exposures. Sprains and fractures were the most prevalent of the more serious lost-time (LT) injuries. Free-text descriptions of claims indicate that arborist work and loading/unloading of work vehicles and trailers are particularly hazardous. Younger and shorter-tenured workers were injured most frequently, although the average workers' age was higher for LT claims. The total cost of claims to the OHBWC from the landscaping services industry for 2001-2017 was over $226,000,000. Almost $214,000,000, or 94.4%, was for LT injuries and illnesses, even though LT claims comprise only 18% of total claims. CONCLUSIONS: Targeted improvements in landscaper safety could come from controlling events leading to LT claims. Engineering controls and improved training are strongly recommended to reduce falls, overexertion, and struck-by injuries.