Hemoglobin A1c and Mortality in Older Adults With and Without Diabetes: Results From the National Health and Nutrition Examination Surveys (1988-2011)

OBJECTIVE: Hemoglobin A1c (HbA1c) level has been associated with increased mortality in middle-aged populations. The optimal intensity of glucose control in older adults with diabetes remains uncertain. We sought to estimate the risk of mortality by HbA1c levels among older adults with and without diabetes. RESEARCH DESIGN AND METHODS: We analyzed data from adults aged ≥65 years (n = 7,333) from the Third National Health and Nutrition Examination Survey (NHANES III) (1998-1994) and Continuous NHANES (1999-2004) and their linked mortality data (through December 2011). Cox proportional hazards models were used to examine the relationship of HbA1c with the risk of all-cause and cause-specific (cardiovascular disease [CVD], cancer, and non-CVD/noncancer) mortality, separately for adults with diabetes and without diabetes. RESULTS: Over a median follow-up of 8.9 years, 4,729 participants died (1,262 from CVD, 850 from cancer, and 2,617 from non-CVD/noncancer causes). Compared with those with diagnosed diabetes and an HbA1c <6.5%, the hazard ratio (HR) for all-cause mortality was significantly greater for adults with diabetes with an HbA1c >8.0%. HRs were 1.6 (95% CI 1.02, 2.6) and 1.8 (95% CI 1.3, 2.6) for HbA1c 8.0-8.9% and ≥9.0%, respectively (P for trend <0.001). Participants with undiagnosed diabetes and HbA1c >6.5% had a 1.3 (95% CI 1.03, 1.8) times greater risk of all-cause mortality compared with participants without diabetes and HbA1c 5.0-5.6%. CONCLUSIONS: An HbA1c >8.0% was associated with increased risk of all-cause and cause-specific mortality in older adults with diabetes. Our results support the idea that better glycemic control is important for reducing mortality; however, in light of the conflicting evidence base, there is also a need for individualized glycemic targets for older adults with diabetes depending on their demographics, duration of diabetes, and existing comorbidities

Impact of 2009 American Recovery and Reinvestment Act (ARRA) health center investments on disadvantaged neighborhoods after recession

Background: Federally qualified health centers (FQHCs) are integral to the U.S. healthcare safety net and uniquely situated in disadvantaged neighborhoods. The 2009 American Recovery and Reinvestment Act (ARRA) invested $2 billion in FQHC stimulus during the Great Recession; but it remains unknown whether this investment was associated with extended benefits for disadvantaged neighborhoods. Methods: We used a propensity-score matched longitudinal design (2008-2012) to examine whether the 2009 ARRA FQHC investment was associated with local jobs and establishments recovery in FQHC neighborhoods. Job change data were obtained from the Longitudinal Employer-Household Dynamics (LEHD) survey and calculated as an annual rate per 1,000 population. Establishment change data were obtained from the National Neighborhood Data Archive (NaNDA) and calculated as an annual rate per 10,000 population. Establishment data included 4 establishment types: healthcare services, eating/drinking places, retail establishments, and grocery stores. Fixed effects were used to compare annual rates of jobs and establishments recovery between ARRA-funded FQHC census tracts and a matched control group. Results: Of 50,381 tracts, 2,223 contained ≥ 1 FQHC that received ARRA funding. A higher proportion of FQHC tracts had an extreme poverty designation (11.6% vs. 5.4%), high unemployment rate (45.4% vs. 30.3%), and > 50% minority racial/ethnic composition (48.1% vs. 36.3%). On average, jobs grew at an annual rate of 3.84 jobs per 1,000 population (95% CI: 3.62,4.06). In propensity-score weighted models, jobs in ARRA-funded tracts grew at a higher annual rate of 4.34 per 1,000 (95% CI: 2.56,6.12) relative to those with similar social vulnerability. We observed persistent decline in non-healthcare establishments (-1.35 per 10,000; 95% CI: -1.68,-1.02); but did not observe decline in healthcare establishments. Conclusions: Direct funding to HCs may be an effective strategy to support healthcare establishments and some jobs recovery in disadvantaged neighborhoods during recession, reinforcing the important multidimensional roles HCs play in these communities. However, HCs may benefit from additional investments that target upstream determinants of health to mitigate uneven recovery and neighborhood decline.</p

Caring for dementia caregivers: How well does social risk screening reflect unmet needs?

Background: Unmet social and caregiving needs can make caregiving for a person with dementia more difficult. Although national policy encourages adoption of systematic screening for health-related social risks (HRSRs) in clinical settings, the accuracy of these risk-based screening tools for detecting unmet social needs is unknown. Methods: We used baseline data from dementia caregivers (N = 343) enrolled in a randomized controlled trial evaluating CommunityRx-Dementia, a social care intervention conducted on Chicago's South Side. We assessed caregivers' (1) unmet social and caregiving needs by querying need for 14 resource types and (2) HRSRs using the Center for Medicare & Medicaid Services (CMS) Accountable Health Communities (AHC) screening tool. Using unmet social needs as the reference, we examined the sensitivity of the AHC tool to detect food, housing, and transportation needs. Analyses were stratified by gender. Results: Most caregivers were women (78%), non-Hispanic (96%), Black (81%), partnered (58%) and had an annual household income ≥$50K (64%). Unmet social and caregiving needs were similarly prevalent among women and men caregivers (87% had ≥1 need, 43% had ≥5 needs). HRSRs were also prevalent. The most common HRSR was lack of social support (45%). Housing instability, difficulty with utilities and having any HRSRs were significantly more prevalent among women (all p Conclusions: Men and women caregivers have high rates of unmet social needs that are often missed by the CMS-recommended risk-based screening method. Findings indicate a role for need-based screening in implementing social care.</p

A nurse driven care management program to engage older diabetes patients in personalized goal setting and disease management

Background and aims: Multiple diabetes care guidelines have called for the personalization of risk factor goals, medication management, and self-care plans among older patients. Study of the implementation of these recommendations is needed. This study aimed to test whether a patient survey embedded in the Electronic Healthcare Record (EHR), coupled with telephonic nurse care management, could engage patients in personalized goal setting and chronic disease management. Methods: We conducted a single-center equal-randomization delayed comparator trial at the primary care clinics of the University of Chicago Medicine from 2018.6 to 2019.12. Patients over the age of 65 years with type 2 diabetes with an active patient portal account were recruited and randomized to receive an EHR embedded goal setting and preference survey immediately in the intervention arm or after 6 months in the delayed intervention control arm. In the intervention arm, nurses reviewed American Diabetes Association recommendations for A1C goals based on health status class, established personalized goals, and provided monthly telephonic care management phone calls for a maximum of 6 months. Our primary outcome was the documentation of a personalized A1C goal in the EHR. Results: A total of 100 patients completed the trial (mean age, 72.51 [SD, 5.22] years; mean baseline A1C, 7.14% [SD, 1.06%]; 68% women). The majority were in the Healthy (59%) followed by Complex (30%) and Very Complex (11%) health status classes. Documentation of an A1C goal in the EHR increased from 42% to 90% (p Conclusions: Older patients can be engaged in personalized goal setting and disease management through an embedded EHR intervention. The clinical impact of the intervention may differ if deployed among older patients with more complex health needs and higher glucose levels. Trial registration: ClinicalTrials.gov Identifier: NCT03692208.</p

Male Gender Expressivity and Diagnosis and Treatment of Cardiovascular Disease Risks in Men

Importance: Male gender expressivity (MGE), which reflects prevalent sociocultural pressures to convey masculinity, has been associated with health. Yet, little is known about associations of MGE with the diagnosis and treatment of modifiable cardiovascular disease (CVD) risks. Objective: To investigate associations of MGE with modifiable CVD risk diagnoses and treatment in men. Design, Setting, and Participants: This population-based cohort study included data from waves I (1994-1995), IV (2008-2009), and V (2016-2018) of the US National Longitudinal Study of Adolescent to Adult Health (Add Health). Participants were male adolescents (age 12-18 years) followed up longitudinally through younger adulthood (age 24-32 years) and adulthood (age 32-42 years). Data were analyzed from January 5, 2023, to August 28, 2024. Exposure: Male gender expressivity was quantified in adolescence and younger adulthood using an empirically-derived and validated measurement technique that incorporates participants' responses to existing Add Health survey items to capture how similarly participants behave to same-gendered peers. Main Outcomes and Measures: Outcomes included self-reported diagnoses of CVD risk conditions (hypertension, diabetes, or hyperlipidemia) in adult men with elevated blood pressure, hemoglobin A1c, or non–high-density lipoprotein cholesterol levels, and self-reported treatment with antihypertensive, hypoglycemic, or lipid-lowering medications in adults reporting hypertension, diabetes, or hyperlipidemia. Multivariable regression was used to examine associations of adolescent and younger adult MGE with adult CVD risk diagnoses and treatment, adjusting for sociodemographic covariates. Results: Among 4230 eligible male participants, most were non-Hispanic White (2711 [64%]) and privately insured (3338 [80%]). Their mean (SD) age was 16.14 (1.81) years in adolescence, 29.02 (1.84) years in younger adulthood, and 38.10 (1.95) years in adulthood. Compared with participants whose younger adult MGE was below average, those with higher younger adult MGE were overall less likely to report hypertension (22% vs 26%; P  Conclusions and Relevance: In this cohort study of US males, higher adolescent and younger adult MGE was associated with lower adult hypertension and diabetes diagnoses and treatment. These findings suggest that males with high MGE may bear distinctive risks and correspondingly benefit from tailored public health efforts to prevent downstream CVD.</p

CommunityRx, a social care assistance intervention for family and friend caregivers delivered at the point of care: Two concurrent blinded randomized controlled trials

Background: CommunityRx is an evidence-based social care intervention delivered to family and friend caregivers (“caregivers”) at the point of healthcare to address health-related social risks (HRSRs). Two CommunityRx randomized controlled trials (RCTs) are being fielded concurrently on Chicago’s South Side, a predominantly African American/Black community. CommunityRx-Hunger is a double-blind RCT enrolling caregivers of hospitalized children. CommunityRx-Dementia is a single-blind RCT enrolling caregivers of community-residing people with dementia. RCTs with caregivers face recruitment barriers, including caregiver burden and lack of systematic strategies to identify caregivers in clinical settings. COVID-19 pandemic-related visitor restrictions exacerbated these barriers and prompted the need for iteration of the protocols from in-person to remote operations. This study describes these protocols and methods used for successful iteration to overcome barriers. Methods and findings: CommunityRx uses individual-level data to generate personalized, local community resource referrals for basic, health and caregiving needs. In early 2020, two in-person RCT protocols were pre-tested. In March 2020, when pandemic conditions prohibited face-to-face clinical enrollment, both protocols were iterated to efficient, caregiver-centered remote operations. Iterations were enabled in part by the Automated Randomized Controlled Trial Information-Communication System (ARCTICS), a trial management system innovation engineered to integrate the data collection database (REDCap) with community resource referral (NowPow) and SMS texting (Mosio) platforms. Enabled by engaged Community Advisory Boards and ARCTICS, both RCTs quickly adapted to remote operations. To accommodate these adaptations, launch was delayed until November (CommunityRx-Hunger) and December (CommunityRx-Dementia) 2020. Despite the delay, 65% of all planned participants (CommunityRx-Hunger n = 417/640; CommunityRx-Dementia n = 222/344) were enrolled by December 2021, halfway through our projected enrollment timeline. Both trials enrolled 13% more participants in the first 12 months than originally projected for in-person enrollment. Discussion: Our asset-based, community-engaged approach combined with widely accessible institutional and commercial information technologies facilitated rapid migration of in-person trials to remote operations. Remote or hybrid RCT designs for social care interventions may be a viable, scalable alternative to in-person recruitment and intervention delivery protocols, particularly for caregivers and other groups that are under-represented in traditional health services research. Trial registration: ClinicalTrials.gov: CommunityRx-Hunger (NCT04171999, 11/21/2019); CommunityRx for Caregivers (NCT04146545, 10/31/2019).</p

Identifying Reduced-Form Relations with Panel Data

The literature that tests for U-shaped relationships using panel data, such as those between pollution and income or inequality and growth, reports widely divergent (parametric and non-parametric) empirical findings. We explain why lack of identification lies at the root of these differences. To deal with this lack of identification, we propose an identification strategy that explicitly distinguishes between what can be identified on the basis of the data and what is a consequence of subjective choices due to a lack of identification. We apply our methodology to the pollution-income relationship of both CO2- and SO2-emissions. Interestingly, our approach yields estimates of both income (scale) and time (composition and/or technology) effects for these reduced-form relationships that are insensitive to the required subjective choices and consistent with theoretical predictions