Medication Adherence and Characteristics of Patients Who Spend Less on Basic Needs to Afford Medications.

INTRODUCTION: Among individuals with low income, cost is a well-established barrier to medication adherence. Spending less on basic needs to pay for medication is a particularly concerning cost-coping strategy and may be associated with worse health outcomes. The aims of this study were (1) to describe the demographic and health status characteristics of those who report spending less on basic needs to pay for medication, and (2) to understand the associated psychosocial and financial challenges of these individuals. METHODS: We administered a survey to primarily low-income adults (n = 270) in St. Louis, MO, as part of a larger study from 2016 to 2018. Logistic regression was used to model odds of reporting spending less on basic needs to pay for medication. RESULTS: Spending less on basic needs to pay for medication was significantly more likely in individuals with fair or poor health status, greater number of chronic conditions, greater medication expenditure, and difficulty paying bills. Individuals who spent less on basic needs were less likely to be fully adherent to their medication regimen. CONCLUSIONS: Screening for unmet basic needs and offering referrals to social safety net programs in the primary care setting may help patients achieve sustainable medication adherence.

Urban-Rural Disparities in Access to Low-Dose Computed Tomography Lung Cancer Screening in Missouri and Illinois.

INTRODUCTION: Low-dose computed tomography (LDCT) lung cancer screening is recommended for current and former smokers who meet eligibility criteria. Few studies have quantitatively examined disparities in access to LDCT screening. The objective of this study was to examine relationships between 1) rurality, sociodemographic characteristics, and access to LDCT lung cancer screening and 2) screening access and lung cancer mortality. METHODS: We used census block group and county-level data from Missouri and Illinois. We defined access to screening as presence of an accredited screening center within 30 miles of residence as of May 2019. We used mixed-effects logistic models for screening access and county-level multiple linear regression models for lung cancer mortality. RESULTS: Approximately 97.6% of metropolitan residents had access to screening, compared with 41.0% of nonmetropolitan residents. After controlling for sociodemographic characteristics, the odds of having access to screening in rural areas were 17% of the odds in metropolitan areas (95% CI, 12%-26%). We observed no association between screening access and lung cancer mortality. Southeastern Missouri, a rural and impoverished area, had low levels of screening access, high smoking prevalence, and high lung cancer mortality. CONCLUSION: Although access to LDCT is lower in rural areas than in urban areas, lung cancer mortality in rural residents is multifactorial and cannot be explained by access alone. Targeted efforts to implement rural LDCT screening could reduce geographic disparities in access, although further research is needed to understand how increased access to screening could affect uptake and rural disparities in lung cancer mortality.

A stepped-wedge randomized trial protocol of a community intervention for increasing lung screening through engaging primary care providers (I-STEP).

Lung cancer screening with low-dose computed tomography (LDCT) reduces lung cancer mortality, yet few eligible high-risk patients receive it annually. This protocol describes a community-partnered intervention (Toolkit) designed to support primary care practices in making referrals for lung screening and guiding patients into appropriate screening pathways. This study uses a stepped-wedge implementation design. Screening centers are randomized by readiness level to enter the intervention phase in three-month "steps" with pre-intervention data serving as the control. The primary outcome is whether delivery of the Toolkit to primary care practices results in a monthly increase in number of initial LDCT screenings. Six participating centers will identify 10 practices and reach 2-3 providers per practice to train them to use the Toolkit. The Toolkit will address known barriers to screening and referral at the patient and provider levels and provide support for required elements of screening. Toolkit components include adaptable evidence-based interventions to maximize compatibility with workflows. We hypothesize that after nine months of intervention delivery, the number of initial screening per center will double. Involving 60 practices achieves 80% power at 5% level of significance. Implementation outcomes such as adoption, acceptability, feasibility, adaptation, and sustainability will be assessed through field-notes and activity logs. LDCT for lung cancer screening currently reaches a small fraction of eligible adults. To reach the full potential to reduce mortality, primary care practices are an important venue for increasing appropriate referrals. This multidisciplinary trial will encourage acceptability and sustainability by using local knowledge and promoting partnership between providers and patients. Trial registration: ClinicalTrials.gov, NCT03958253.

Relationships between consumption of ultra-processed foods, gestational weight gain and neonatal outcomes in a sample of US pregnant women.

BACKGROUND: An increasingly large share of diet comes from ultra-processed foods (UPFs), which are assemblages of food substances designed to create durable, convenient and palatable ready-to-eat products. There is increasing evidence that high UPF consumption is indicative of poor diet and is associated with obesity and metabolic disorders. This study sought to examine the relationship between percent of energy intake from ultra-processed foods (PEI-UPF) during pregnancy and maternal gestational weight gain, maternal lipids and glycemia, and neonatal body composition. We also compared the PEI-UPF indicator against the US government's Healthy Eating Index-2010 (HEI-2010). METHODS: Data were used from a longitudinal study performed in 2013-2014 at the Women's Health Center and Obstetrics & Gynecology Clinic in St. Louis, MO, USA. Subjects were pregnant women in the normal and obese weight ranges, as well as their newborns (n = 45). PEI-UPF and the Healthy Eating Index-2010 (HEI-2010) were calculated for each subject from a one-month food frequency questionnaire (FFQ). Multiple regression (ANCOVA-like) analysis was used to analyze the relationship between PEI-UPF or HEI-2010 and various clinical outcomes. The ability of these dietary indices to predict clinical outcomes was also compared with the predictive abilities of total energy intake and total fat intake. RESULTS: An average of 54.4 ± 13.2% of energy intake was derived from UPFs. A 1%-point increase in PEI-UPF was associated with a 1.33 kg increase in gestational weight gain (p = 0.016). Similarly, a 1%-point increase in PEI-UPF was associated with a 0.22 mm increase in thigh skinfold (p = 0.045), 0.14 mm in subscapular skinfold (p = 0.026), and 0.62 percentage points of total body adiposity (p = 0.037) in the neonate. DISCUSSION: PEI-UPF (percent of energy intake from ultra-processed foods) was associated with and may be a useful predictor of increased gestational weight gain and neonatal body fat. PEI-UPF was a better predictor of all tested outcomes than either total energy or fat intake, and a better predictor of the three infant body fat measures than HEI-2010. UPF consumption should be limited during pregnancy and diet quality should be maximized in order to improve maternal and neonatal health.