Faculty Bibliography

BACKGROUND:At the beginning of the COVID-19 pandemic in the United States in the spring of 2020, many Americans avoided the healthcare system, while those with COVID-19 symptoms were faced with decisions about seeking healthcare services for this novel virus. METHODS:Using a probability sample (n = 1088) from the Michigan adult population of PCR-confirmed COVID-19 cases who were diagnosed prior to July 31, 2020, we used logistic regression to examine sociodemographic and symptom severity predictors of care-seeking behaviors. The analyses examined three different outcomes: (1) whether respondents sought care and, among those who sought care, whether they sought care from (2) a primary care provider or (3) an emergency room. Final models were adjusted for sex, age, race and ethnicity, income, education, marital status, living arrangement, health insurance, and self-reported symptom severity. RESULTS:We found that participants ages 65 and older had 4.00 times higher odds of seeking care than 18-34-year-olds (95% CI: 2.21, 7.24), while adults reporting very severe symptoms had roughly 15 times higher odds of seeking care than those with mild symptoms (95% CI: 7.73, 27.01). Adults who were non-Hispanic Black or were uninsured had lower odds of seeking care from a primary care physician versus seeking care from other locations in comparison to adults who were non-Hispanic White or were privately insured, respectively (non-Hispanic Black: aOR = 0.27, 95% CI: 0.16, 0.44; Uninsured: aOR = 0.19, 95% CI: 0.09, 0.42). Conversely, adults who were older or reported more severe symptoms had higher odds of seeking care from an emergency room versus other locations in comparison to adults who were younger or reported less severe symptoms (Age 65+: aOR = 2.96, 95% CI: 1.40, 6.28; Very Severe Symptoms: aOR = 6.63, 95% CI: 3.33, 13.20). CONCLUSIONS:Our results suggest differential utilization of healthcare services early in the COVID-19 pandemic. Further analyses are needed to examine the reasons for these differences.

OBJECTIVES:This study evaluated whether a range of demographic, social and geographic factors had an influence on glycaemic control longitudinally after an initial diagnosis of diabetes. DESIGN, SETTING AND PARTICIPANTS:We used the US Veterans Administration Diabetes Risk national cohort to track glycaemic control among patients 20-79-year old with a new diagnosis of type 2 diabetes. PRIMARY OUTCOME AND METHODS:We modelled associations between glycaemic control at follow-up clinical assessments and geographic factors including neighbourhood race/ethnicity, socioeconomic, land use and food environment measures. We also adjusted for individual demographics, comorbidities, haemoglobin A1c (HbA1c) at diagnosis and duration of follow-up. These factors were analysed within strata of community type: high-density urban, low-density urban, suburban/small town and rural areas. RESULTS:We analysed 246 079 Veterans who developed a new type 2 diabetes diagnosis in 2008-2018 and had at least 2 years of follow-up data available. Across all community types, we found that lower baseline HbA1c and female sex were strongly associated with a higher likelihood of within-range HbA1c at follow-up. Surprisingly, patients who were older or had more documented comorbidities were more likely to have within-range follow-up HbA1c results. While there was variation by community type, none of the geographic measures analysed consistently demonstrated significant associations with glycaemic control across all community types.

PURPOSE/OBJECTIVE:The COVID-19 pandemic has had wide-ranging impacts on mental health, however, less is known about predictors of mental health outcomes among adults who have experienced a COVID-19 diagnosis. We examined the intersection of demographic, economic, and illness-related predictors of depressive and anxiety symptoms within a population-based sample of adults diagnosed with COVID-19 in the U.S. state of Michigan early in the pandemic. METHODS:Data were from a population-based survey of Michigan adults who experienced a COVID-19 diagnosis prior to August 1, 2020 (N = 1087). We used weighted prevalence estimates and multinomial logistic regression to examine associations between mental health outcomes (depressive symptoms, anxiety symptoms, and comorbid depressive/anxiety symptoms) and demographic characteristics, pandemic-associated changes in accessing basic needs (accessing food/clean water and paying important bills), self-reported COVID-19 symptom severity, and symptom duration. RESULTS:Relative risks for experiencing poor mental health outcomes varied by sex, age, race/ethnicity, and income. In adjusted models, experiencing a change in accessing basic needs associated with the pandemic was associated with higher relative risks for anxiety and comorbid anxiety/depressive symptoms. Worse COVID-19 symptom severity was associated with a higher burden of comorbid depressive/anxiety symptoms. "Long COVID" (symptom duration greater than 60 days) was associated with all outcomes. CONCLUSION/CONCLUSIONS:Adults diagnosed with COVID-19 may face overlapping risk factors for poor mental health outcomes, including pandemic-associated disruptions to household and economic wellbeing, as well as factors related to COVID-19 symptom severity and duration. An integrated approach to treating depressive/anxiety symptoms among COVID-19 survivors is warranted.

BACKGROUND:We examined associations between smoke-free laws and smoking outcomes in a nationally representative sample of US adults, including exploring whether these associations differed for heterosexual and sexual minority (SM) adults. METHODS:We constructed county-level variables representing the percent of the population covered by state-, county-, or city-level smoke-free laws in workplaces and hospitality venues. We combined this information with restricted individual-level adult data with masked county identifiers from the National Health Interview Survey (NHIS), 2013-2018. We used modified Poisson regression to explore associations between each type of smoke-free law and the prevalence ratio (PR) of current smoking, and we used linear regression to explore associations with smoking intensity (mean cigarettes per day). We assessed interactions between smoke-free laws and SM status on the additive scale to determine whether associations were different for SM and heterosexual adults. RESULTS:In adjusted models without interaction terms, smoke-free laws in hospitality venues were associated with lower prevalence of current smoking (PR = 0.93, 95% confidence interval (CI) = 0.89, 0.98). Both types of smoke-free laws were associated with lower mean cigarettes per day (workplace law change in mean =  - 0.50, 95% CI =  - 0.89, - 0.12; hospitality law change in mean =  - 0.72, 95% CI =  - 1.14,-0.30). We did not observe any statistically significant interactions by SM status, though statistical power was limited. CONCLUSIONS:We did not find evidence that smoke-free laws were differentially associated with smoking outcomes for heterosexual and SM adults. Additional studies are needed to further explore the potential for tobacco control policies to address the elevated risk of smoking in SM communities.

INTRODUCTION:The purpose of this study is to examine the associations between built environments and life expectancy across a gradient of urbanicity in the U.S. METHODS:Census tract‒level estimates of life expectancy between 2010 and 2015, except for Maine and Wisconsin, from the U.S. Small-Area Life Expectancy Estimates Project were analyzed in 2022. Tract-level measures of the built environment included: food, alcohol, and tobacco outlets; walkability; park and green space; housing characteristics; and air pollution. Multilevel linear models for each of the 4 urbanicity types were fitted to evaluate the associations, adjusting for population and social characteristics. RESULTS:Old housing (built before 1979) and air pollution were important built environment predictors of life expectancy disparities across all gradients of urbanicity. Convenience stores were negatively associated with life expectancy in all urbanicity types. Healthy food options were a positive predictor of life expectancy only in high-density urban areas. Park accessibility was associated with increased life expectancy in all areas, except rural areas. Green space in neighborhoods was positively associated with life expectancy in urban areas but showed an opposite association in rural areas. CONCLUSIONS:After adjusting for key social characteristics, several built environment characteristics were salient risk factors for decreased life expectancy in the U.S., with some measures showing differential effects by urbanicity. Planning and policy efforts should be tailored to local contexts.

BACKGROUND:The prevalence of smoking is higher among sexual minority (SM) individuals compared with heterosexuals. The impact of televised anti-tobacco mass media campaigns on smoking outcomes among SMs is not known. AIMS:We examined whether televised anti-tobacco advertising was differentially associated with current smoking and smoking intensity for SM and heterosexual adults. METHOD:We combined county-level anti-tobacco advertising data (gross rating points) with restricted, geocoded individual-level National Health Interview Survey data on smoking (2013-2015). We estimated associations between advertising and smoking outcomes, including potential effect modification by SM status. RESULTS:Greater anti-tobacco advertising exposure was associated with lower smoking prevalence (prevalence ratio [PR] = 0.97; 95% confidence interval [CI] = [0.94, 1.00]). Although the direction of the association differed for heterosexual and SM adults, differences were not statistically significant. No significant associations were observed with regard to smoking intensity. CONCLUSION:Associations between anti-tobacco advertising and smoking were not significantly different for heterosexual and SM adults.

This study investigates the association between the strength of TRL ordinances and adult cigarette use, and differences in the relationship by sociodemographic characteristics, using California as a case study. We merged geocoded data from the California Health Interview Survey with the State of Tobacco Control Reports from the American Lung Association from 2012 to 2019. Each jurisdiction was graded (A-strongest to F-weakest) based on the strength of their TRL ordinance while current cigarette use was defined as respondents who had smoked 100 or more cigarettes in their lifetime and currently smoke cigarettes every day or some days. We estimated multilevel logistic regression models to test the relationship between the strength of the TRL ordinance and current cigarette use and tested for effect modification by including interaction terms for race/ethnicity, income, and education in separate models. 11.6 % of sample participants from all years (n = 132,209) were current cigarette smokers. Adults in jurisdictions with stronger grades (A-D) had lower odds of current cigarette use (OR = 0.89, 95 % CI: 0.79-1.01) compared to adults in jurisdictions with the weakest grade (F), but the association was not statistically significant (p < 0.07). We found no evidence of effect modification by race/ethnicity, income, or education. We found limited evidence that stronger TRL ordinances were associated with lower adult cigarette smoking in California. However, future studies testing the relationship between TRL ordinances and adult smoking outcomes should examine the role of TRL fees across jurisdictions and adult cigarette use.

BACKGROUND:While emerging studies suggest that the COVID-19 pandemic caused disruptions in routine healthcare utilization, the full impact of the pandemic on healthcare utilization among diverse group of patients with type 2 diabetes is unclear. The purpose of this study is to examine trends in healthcare utilization, including in-person and telehealth visits, among U.S. veterans with type 2 diabetes before, during and after the onset of the COVID-19 pandemic, by demographics, pre-pandemic glycemic control, and geographic region. METHODS:We longitudinally examined healthcare utilization in a large national cohort of veterans with new diabetes diagnoses between January 1, 2008 and December 31, 2018. The analytic sample was 733,006 veterans with recently-diagnosed diabetes, at least 1 encounter with veterans administration between March 2018-2020, and followed through March 2021. Monthly rates of glycohemoglobin (HbA1c) measurements, in-person and telehealth outpatient visits, and prescription fills for diabetes and hypertension medications were compared before and after March 2020 using interrupted time-series design. Log-linear regression model was used for statistical analysis. Secular trends were modeled with penalized cubic splines. RESULTS:In the initial 3 months after the pandemic onset, we observed large reductions in monthly rates of HbA1c measurements, from 130 (95%CI,110-140) to 50 (95%CI,30-80) per 1000 veterans, and in-person outpatient visits, from 1830 (95%CI,1640-2040) to 810 (95%CI,710-930) per 1000 veterans. However, monthly rates of telehealth visits doubled between March 2020-2021 from 330 (95%CI,310-350) to 770 (95%CI,720-820) per 1000 veterans. This pattern of increases in telehealth utilization varied by community type, with lowest increase in rural areas, and by race/ethnicity, with highest increase among non-hispanic Black veterans. Combined in-person and telehealth outpatient visits rebounded to pre-pandemic levels after 3 months. Despite notable changes in HbA1c measurements and visits during that initial window, we observed no changes in prescription fills rates. CONCLUSIONS:Healthcare utilization among veterans with diabetes was substantially disrupted at the onset of the pandemic, but rebounded after 3 months. There was disparity in uptake of telehealth visits by geography and race/ethnicity.

Smoke-free housing policies are intended to reduce the deleterious health effects of secondhand smoke (SHS) exposure, but there is limited evidence regarding their health impacts. We examined associations between implementation of a federal smoke-free housing rule by the New York City Housing Authority (NYCHA) and pediatric Medicaid claims for asthma, lower respiratory infections (LRIs), and upper respiratory infections (URIs) in the early post-policy period. We used geocoded address data to match children living in tax lots with NYCHA buildings (exposed to policy) to children living in lots with other subsidized housing (unexposed to policy). We constructed longitudinal difference-in-differences models to assess relative changes in monthly rates of claims between November 1, 2015 and December 31, 2019 (policy introduction was July 30, 2018). We also examined effect modification by baseline age group (0-2, 3-6, 7-15). In NYC, introduction of a smoke-free policy was not associated with lower rates of Medicaid claims for any outcomes in the early post-policy period. Exposure to the smoke-free policy was associated with slightly higher than expected rates of outpatient URI claims (IRR=1.05, 95% CI=1.01, 1.08), a result most pronounced among children ages 3-6. Ongoing monitoring is essential to understanding long-term health impacts of smoke-free housing policies.