Clinical stakeholders' perceptions of patient engagement in outpatient medication treatment for opioid use disorder: A qualitative study

INTRODUCTION

Medications for opioid use disorder (MOUD) reduce risk of opioid overdose and promote recovery from opioid use disorder, but poor retention in MOUD limits these positive effects. This study explored patient engagement in MOUD from the perspective of clinical stakeholders within an outpatient addiction medicine program to identify program factors influencing patient engagement with treatment.

METHODS

We conducted a qualitative case study of a multi-clinic outpatient addiction medicine program embedded within an integrated health system that serves a geographically diverse area of Pennsylvania. Collectively, the program's clinics provide MOUD (primarily buprenorphine) to ~2000 patients annually. From January to March 2021, we conducted semi-structured telephone/video interviews with three stakeholder groups involved in delivering MOUD: administrators (n = 4), providers (n = 7), and addiction care coordinators (n = 5). Data analysis utilized the framework method.

RESULTS

We identified five themes related to patient engagement. First, participants described health system integration as enhancing quality and offering opportunities for addressing patients' comprehensive health care needs. However, lack of knowledge about addiction and stigma among health system providers was felt to limit patient benefits from this integration, including access to MOUD. Second, participants viewed patient engagement as central to the program's policies, practices, and clinical environment. Adoption of a harm reduction approach and maintenance of a non-stigmatizing clinic environment were described as essential facilitators of engagement. Third, while clinics followed uniform operations, physician leads expressed differing philosophical approaches to treatment, which participants associated with variations in clinical practice and patient engagement. Fourth, participants identified key services that bolstered engagement in MOUD, including psychosocial services, psychiatric care, and telemedicine. Finally, staff well-being emerged as a key consideration for patient engagement.

CONCLUSIONS

Understanding perceptions of those who administer and deliver care is critical for identifying barriers and facilitators to patient engagement in MOUD. Findings suggest potential opportunities for addiction treatment programs to improve patient engagement and ultimately MOUD retention, including integration with other healthcare services to meet comprehensive healthcare needs; adoption of a harm reduction approach; creation of non-stigmatizing clinical environments; investment in psychosocial services, psychiatric care, and telemedicine; and prioritization of staff wellness.

Association of initial opioid prescription duration and an opioid refill by pain diagnosis: Evidence from outpatient settings in ten US health systems

OBJECTIVE

The Centers for Disease Control and Prevention's 2022 Clinical Practice Guideline for Prescribing Opioids for Pain cautioned that inflexible opioid prescription duration limits may harm patients. Information about the relationship between initial opioid prescription duration and a subsequent refill could inform prescribing policies and practices to optimize patient outcomes. We assessed the association between initial opioid duration and an opioid refill prescription.

METHODS

We conducted a retrospective cohort study of adults ≥19 years of age in 10 US health systems between 2013 and 2018 from outpatient care with a diagnosis for back pain without radiculopathy, back pain with radiculopathy, neck pain, joint pain, tendonitis/bursitis, mild musculoskeletal pain, severe musculoskeletal pain, urinary calculus, or headache. Generalized additive models were used to estimate the association between opioid days' supply and a refill prescription.

RESULTS

Overall, 220,797 patients were prescribed opioid analgesics upon an outpatient visit for pain. Nearly a quarter (23.5%) of the cohort received an opioid refill prescription during follow-up. The likelihood of a refill generally increased with initial duration for most pain diagnoses. About 1 to 3 fewer patients would receive a refill within 3 months for every 100 patients initially prescribed 3 vs. 7 days of opioids for most pain diagnoses. The lowest likelihood of refill was for a 1-day supply for all pain diagnoses, except for severe musculoskeletal pain (9 days' supply) and headache (3-4 days' supply).

CONCLUSIONS

Long-term prescription opioid use increased modestly with initial opioid prescription duration for most but not all pain diagnoses examined.

Developing a Framework to Infer Opioid Use Disorder Severity From Clinical Notes to Inform Natural Language Processing Methods: Characterization Study

BACKGROUND

Information regarding opioid use disorder (OUD) status and severity is important for patient care. Clinical notes provide valuable information for detecting and characterizing problematic opioid use, necessitating development of natural language processing (NLP) tools, which in turn requires reliably labeled OUD-relevant text and understanding of documentation patterns.

OBJECTIVE

To inform automated NLP methods, we aimed to develop and evaluate an annotation schema for characterizing OUD and its severity, and to document patterns of OUD-relevant information within clinical notes of heterogeneous patient cohorts.

METHODS

We developed an annotation schema to characterize OUD severity based on criteria from the Diagnostic and Statistical Manual of Mental Disorders, 5th edition. In total, 2 annotators reviewed clinical notes from key encounters of 100 adult patients with varied evidence of OUD, including patients with and those without chronic pain, with and without medication treatment for OUD, and a control group. We completed annotations at the sentence level. We calculated severity scores based on annotation of note text with 18 classes aligned with criteria for OUD severity and determined positive predictive values for OUD severity.

RESULTS

The annotation schema contained 27 classes. We annotated 1436 sentences from 82 patients; notes of 18 patients (11 of whom were controls) contained no relevant information. Interannotator agreement was above 70% for 11 of 15 batches of reviewed notes. Severity scores for control group patients were all 0. Among noncontrol patients, the mean severity score was 5.1 (SD 3.2), indicating moderate OUD, and the positive predictive value for detecting moderate or severe OUD was 0.71. Progress notes and notes from emergency department and outpatient settings contained the most and greatest diversity of information. Substance misuse and psychiatric classes were most prevalent and highly correlated across note types with high co-occurrence across patients.

CONCLUSIONS

Implementation of the annotation schema demonstrated strong potential for inferring OUD severity based on key information in a small set of clinical notes and highlighting where such information is documented. These advancements will facilitate NLP tool development to improve OUD prevention, diagnosis, and treatment.

Identification of opioid use disorder using electronic health records: Beyond diagnostic codes

BACKGROUND

We used structured and unstructured electronic health record (EHR) data to develop and validate an approach to identify moderate/severe opioid use disorder (OUD) that includes individuals without prescription opioid use or chronic pain, an underrepresented population.

METHODS

Using electronic diagnosis grouper text from EHRs of ~1 million patients (2012-2020), we created indicators of OUD-with "tiers" indicating OUD likelihood-combined with OUD medication (MOUD) orders. We developed six sub-algorithms with varying criteria (multiple vs single MOUD orders, multiple vs single tier 1 indicators, tier 2 indicators, tier 3 and 4 indicators). Positive predictive values (PPVs) were calculated based on chart review to determine OUD status and severity. We compared demographic and clinical characteristics of cases identified by the sub-algorithms.

RESULTS

In total, 14,852 patients met criteria for one of the sub-algorithms. Five sub-algorithms had PPVs ≥0.90 for any severity OUD; four had PPVs ≥0.90 for moderate/severe OUD. Demographic and clinical characteristics differed substantially between groups. Of identified OUD cases, 31.3% had no past opioid analgesic orders, 79.7% lacked evidence of chronic prescription opioid use, and 43.5% lacked a chronic pain diagnosis.

DISCUSSION

Incorporating unstructured data with MOUD orders yielded an approach that adequately identified moderate/severe OUD, identified unique demographic and clinical sub-groups, and included individuals without prescription opioid use or chronic pain, whose OUD may stem from illicit opioids. Findings show that incorporating unstructured data strengthens EHR algorithms for identifying OUD and suggests approaches limited to populations with prescription opioid use or chronic pain exclude many individuals with OUD.

Mediation of an association between neighborhood socioeconomic environment and type 2 diabetes through the leisure-time physical activity environment in an analysis of three independent samples

INTRODUCTION

Inequitable access to leisure-time physical activity (LTPA) resources may explain geographic disparities in type 2 diabetes (T2D). We evaluated whether the neighborhood socioeconomic environment (NSEE) affects T2D through the LTPA environment.

RESEARCH DESIGN AND METHODS

We conducted analyses in three study samples: the national Veterans Administration Diabetes Risk (VADR) cohort comprising electronic health records (EHR) of 4.1 million T2D-free veterans, the national prospective cohort REasons for Geographic and Racial Differences in Stroke (REGARDS) (11 208 T2D free), and a case-control study of Geisinger EHR in Pennsylvania (15 888 T2D cases). New-onset T2D was defined using diagnoses, laboratory and medication data. We harmonized neighborhood-level variables, including exposure, confounders, and effect modifiers. We measured NSEE with a summary index of six census tract indicators. The LTPA environment was measured by physical activity (PA) facility (gyms and other commercial facilities) density within street network buffers and population-weighted distance to parks. We estimated natural direct and indirect effects for each mediator stratified by community type.

RESULTS

The magnitudes of the indirect effects were generally small, and the direction of the indirect effects differed by community type and study sample. The most consistent findings were for mediation via PA facility density in rural communities, where we observed positive indirect effects (differences in T2D incidence rates (95% CI) comparing the highest versus lowest quartiles of NSEE, multiplied by 100) of 1.53 (0.25, 3.05) in REGARDS and 0.0066 (0.0038, 0.0099) in VADR. No mediation was evident in Geisinger.

CONCLUSIONS

PA facility density and distance to parks did not substantially mediate the relation between NSEE and T2D. Our heterogeneous results suggest that approaches to reduce T2D through changes to the LTPA environment require local tailoring.

Comparing enhancements to well-child visits in the prevention of obesity: ENCIRCLE cluster-randomized controlled trial

BACKGROUND

Obesity disproportionally impacts rural, lower-income children in the United States. Primary care providers are well-positioned to engage parents in early obesity prevention, yet there is a lack of evidence regarding the most effective care delivery models. The ENCIRCLE study, a pragmatic cluster-randomized controlled trial, will respond to this gap by testing the comparative effectiveness of standard care well-child visits (WCV) versus two enhancements: adding a patient-reported outcome (PRO) measure (PRO WCV) and PRO WCV plus Food Care (telehealth coaching and a grocery store tour).

METHODS

A total of 2,025 parents and their preschool-aged children (20-60 months of age) will be recruited from 24 Geisinger primary care clinics, where providers are randomized to the standard WCV, PRO WCV, or PRO WCV plus Food Care intervention arms. The PRO WCV includes the standard WCV plus collection of the PRO-the Family Nutrition and Physical Activity (FNPA) risk assessment-from parents. Parents complete the PRO in the patient-portal or in the clinic (own device, tablet, or kiosk), receive real-time feedback, and select priority topics to discuss with the provider. These results are integrated into the child's electronic health record to inform personalized preventive counseling by providers. PRO WCV plus Food Care includes referrals to community health professionals who deliver evidence-based obesity prevention and food resource management interventions via telehealth following the WCV. The primary study outcome is change in child body mass index z-score (BMIz), based on the World Health Organization growth standards, 12 months post-baseline WCV. Additional outcomes include percent of children with overweight and obesity, raw BMI, BMI50, BMIz extended, parent involvement in counseling, health behaviors, food resource management, and implementation process measures.

DISCUSSION

Study findings will inform health care systems' choices about effective care delivery models to prevent childhood obesity among a high-risk population. Additionally, dissemination will be informed by an evaluation of mediating, moderating, and implementation factors.

TRIAL REGISTRATION

ClinicalTrials.gov identifier (NCT04406441); Registered May 28, 2020.

Application of the COM-B model to patient barriers and facilitators of retention in medication treatment for opioid use disorder in rural Northeastern United States: A qualitative study

Introduction

Medications for opioid use disorder (MOUD) reduce illicit opioid use and overdose mortality, but effectiveness remains limited by poor treatment retention. Understanding multilevel barriers and facilitators to retention from the patient perspective can guide intervention strategies to improve retention.

Methods

We conducted semi-structured telephone interviews to elicit perspectives of individuals with opioid use disorder (OUD) currently (n = 19) and formerly (n = 16) receiving treatment from a multi-clinic outpatient MOUD program in Pennsylvania in July 2020 to January 2021. The Capability, Opportunity, Motivation, Behavior model provided a theoretical framework for analysis.

Results

Based on interview themes, physical, rather than psychological, capability was more salient to MOUD engagement, and pertained to individual-level factors such as side effects, withdrawal, and the degree to which MOUD addressed participants' need for pain management. Co-existing mental health conditions also challenged participants' physical ability to attend appointments. The opportunity domain contained both physical and social aspects. Physical opportunity for MOUD engagement centered on community-level factors related to MOUD access (e.g., distance, transportation) and clinical-level factors including program policies. Themes related to social opportunity included interpersonal influences-such as therapeutic and social support-and stigma associated with OUD and MOUD. Motivation emerged as the dominant domain for patients. Reflective motivation factors included individual-level factors such as participants' recognition of their addiction and "readiness" to quit illicit opioid use, attitudes toward MOUD, future treatment expectations, motivation to engage in MOUD, and perceived consequences of disengagement. Automatic motivation factors included the degree to which MOUD created a sense of normalcy for participants and the use of illicit drugs to numb emotions.

Conclusions

Factors at the individual, interpersonal, clinical, community, and societal levels influenced patients' capability, opportunity, and motivation to engage in MOUD. Understanding such factors can inform implementation strategies to improve retention.

Identifying High-Risk Comorbidities Associated with Opioid Use Patterns Using Electronic Health Record Prescription Data

Introduction

Opioid use disorders (OUDs) constitute a major public health issue, and we urgently need alternative methods for characterizing risk for OUD. Electronic health records (EHRs) are useful tools for understanding complex medical phenotypes but have been underutilized for OUD because of challenges related to underdiagnosis, binary diagnostic frameworks, and minimally characterized reference groups. As a first step in addressing these challenges, a new paradigm is warranted that characterizes risk for opioid prescription misuse on a continuous scale of severity, i.e., as a continuum.

Methods

Across sites within the PsycheMERGE network, we extracted prescription opioid data and diagnoses that co-occur with OUD (including psychiatric and substance use disorders, pain-related diagnoses, HIV, and hepatitis C) for over 2.6 million patients across three health registries (Vanderbilt University Medical Center, Mass General Brigham, Geisinger) between 2005 and 2018. We defined three groups based on levels of opioid exposure: no prescriptions, minimal exposure, and chronic exposure and then compared the comorbidity profiles of these groups to the full registries and to those with OUD diagnostic codes.

Results

Our results confirm that EHR data reflects known higher prevalence of substance use disorders, psychiatric disorders, medical, and pain diagnoses in patients with OUD diagnoses and chronic opioid use. Comorbidity profiles that distinguish opioid exposure are strikingly consistent across large health systems, indicating the phenotypes described in this new quantitative framework are robust to health systems differences.

Conclusion

This work indicates that EHR prescription opioid data can serve as a platform to characterize complex risk markers for OUD using existing data.

Urban-Rural Differences in Health Care Utilization and COVID-19 Outcomes in Patients With Type 2 Diabetes

Introduction

Two studies in Pennsylvania aimed to determine whether community type and community socioeconomic deprivation (CSD) 1) modified associations between type 2 diabetes (hereinafter, diabetes) and COVID-19 hospitalization outcomes, and 2) influenced health care utilization among individuals with diabetes during the COVID-19 pandemic.

Methods

The hospitalization study evaluated a retrospective cohort of patients hospitalized with COVID-19 through 2020 for COVID-19 outcomes: death, intensive care unit (ICU) admission, mechanical ventilation, elevated D-dimer, and elevated troponin level. We used adjusted logistic regression models, adding interaction terms to evaluate effect modification by community type (township, borough, or city census tract) and CSD. The utilization study included patients with diabetes and a clinical encounter between 2017 and 2020. Autoregressive integrated moving average time-series models evaluated changes in weekly rates of emergency department and outpatient visits, hemoglobin A_1c (HbA_1c) laboratory tests, and antihyperglycemic medication orders from 2018 to 2020.

Results

In the hospitalization study, of 2,751 patients hospitalized for COVID-19, 1,020 had diabetes, which was associated with ICU admission and elevated troponin. Associations did not differ by community type or CSD. In the utilization study, among 93,401 patients with diabetes, utilization measures decreased in March 2020. Utilization increased in July, and then began to stabilize or decline through the end of 2020. Changes in HbA_1c tests and medication order trends during the pandemic differed by community type and CSD.

Conclusion

Diabetes was associated with selected outcomes among individuals hospitalized for COVID-19, but these did not differ by community features. Utilization trajectories among individuals with diabetes during the pandemic were influenced by community type and CSD and could be used to identify individuals at risk of gaps in diabetes care.

Family-Based Telehealth Initiative to Improve Nutrition and Physical Activity for Children With Obesity and Its Utility During COVID-19: A Mixed Methods Evaluation

Guidelines recommend primary care providers refer children with obesity to behavioral interventions, but given limited program availability, access, and parental engagement, referrals remain rare. We developed telehealth coaching interventions for families whose children received care at a health system in Pennsylvania, United States in 2019-2020. Intervention referrals were facilitated by the pediatrician and/or project team for 6–12-year-old children with obesity following well-child visits. Participants chose one of three 26-week interventions focused on healthy eating, physical activity, or a hybrid clinical/nutrition intervention. Interventions engaged parents as change agents, enhancing self-efficacy to model and reinforce behavior and providing resources to help create a healthy home environment. We enrolled 77 of 183 eligible parent/child dyads. We used mixed methods to evaluate the interventions. Repeated measures models among participants showed significant reductions in obesogenic nutrition behaviors post-intervention and at 1-year follow-up, including a reduction in sugar-sweetened beverage intake of 2.14 servings/week (95% confidence interval: −3.45, −0.82). There were also improvements in obesoprotective nutrition behaviors (e.g., frequency of family meals, parental self-efficacy related to meal management). One year post-baseline, we observed no significant differences in changes in body mass index (BMI) z-scores comparing child participants with matched controls. Given potential impacts of COVID-19 community restrictions on study outcomes, we conducted qualitative interviews with 13 participants during restrictions, which exemplified how disrupted routines constrained children’s healthy behaviors but that intervention participation prepared parents by providing cooking and physical activities at home. Findings support the potential of a telehealth-delivered nutrition intervention to support adoption of healthy weight behaviors.

Classifying Characteristics of Opioid Use Disorder From Hospital Discharge Summaries Using Natural Language Processing

Background

Opioid use disorder (OUD) is underdiagnosed in health system settings, limiting research on OUD using electronic health records (EHRs). Medical encounter notes can enrich structured EHR data with documented signs and symptoms of OUD and social risks and behaviors. To capture this information at scale, natural language processing (NLP) tools must be developed and evaluated. We developed and applied an annotation schema to deeply characterize OUD and related clinical, behavioral, and environmental factors, and automated the annotation schema using machine learning and deep learning-based approaches.

Methods

Using the MIMIC-III Critical Care Database, we queried hospital discharge summaries of patients with International Classification of Diseases (ICD-9) OUD diagnostic codes. We developed an annotation schema to characterize problematic opioid use, identify individuals with potential OUD, and provide psychosocial context. Two annotators reviewed discharge summaries from 100 patients. We randomly sampled patients with their associated annotated sentences and divided them into training (66 patients; 2,127 annotated sentences) and testing (29 patients; 1,149 annotated sentences) sets. We used the training set to generate features, employing three NLP algorithms/knowledge sources. We trained and tested prediction models for classification with a traditional machine learner (logistic regression) and deep learning approach (Autogluon based on ELECTRA's replaced token detection model). We applied a five-fold cross-validation approach to reduce bias in performance estimates.

Results

The resulting annotation schema contained 32 classes. We achieved moderate inter-annotator agreement, with F1-scores across all classes increasing from 48 to 66%. Five classes had a sufficient number of annotations for automation; of these, we observed consistently high performance (F1-scores) across training and testing sets for drug screening (training: 91-96; testing: 91-94) and opioid type (training: 86-96; testing: 86-99). Performance dropped from training and to testing sets for other drug use (training: 52-65; testing: 40-48), pain management (training: 72-78; testing: 61-78) and psychiatric (training: 73-80; testing: 72). Autogluon achieved the highest performance.

Conclusion

This pilot study demonstrated that rich information regarding problematic opioid use can be manually identified by annotators. However, more training samples and features would improve our ability to reliably identify less common classes from clinical text, including text from outpatient settings.

Neighborhood Socioeconomic Environment and Risk of Type 2 Diabetes: Associations and Mediation Through Food Environment Pathways in Three Independent Study Samples

OBJECTIVE

We examined whether relative availability of fast-food restaurants and supermarkets mediates the association between worse neighborhood socioeconomic conditions and risk of developing type 2 diabetes (T2D).

RESEARCH DESIGN AND METHODS

As part of the Diabetes Location, Environmental Attributes, and Disparities Network, three academic institutions used harmonized environmental data sources and analytic methods in three distinct study samples: 1) the Veterans Administration Diabetes Risk (VADR) cohort, a national administrative cohort of 4.1 million diabetes-free veterans developed using electronic health records (EHRs); 2) Reasons for Geographic and Racial Differences in Stroke (REGARDS), a longitudinal, epidemiologic cohort with Stroke Belt region oversampling (N = 11,208); and 3) Geisinger/Johns Hopkins University (G/JHU), an EHR-based, nested case-control study of 15,888 patients with new-onset T2D and of matched control participants in Pennsylvania. A census tract-level measure of neighborhood socioeconomic environment (NSEE) was developed as a community type-specific z-score sum. Baseline food-environment mediators included percentages of 1) fast-food restaurants and 2) food retail establishments that are supermarkets. Natural direct and indirect mediating effects were modeled; results were stratified across four community types: higher-density urban, lower-density urban, suburban/small town, and rural.

RESULTS

Across studies, worse NSEE was associated with higher T2D risk. In VADR, relative availability of fast-food restaurants and supermarkets was positively and negatively associated with T2D, respectively, whereas associations in REGARDS and G/JHU geographies were mixed. Mediation results suggested that little to none of the NSEE-diabetes associations were mediated through food-environment pathways.

CONCLUSIONS

Worse neighborhood socioeconomic conditions were associated with higher T2D risk, yet associations are likely not mediated through food-environment pathways.

Relations of peri-residential temperature and humidity in tick-life-cycle-relevant time periods with human Lyme disease risk in Pennsylvania, USA

How weather affects tick development and behavior and human Lyme disease remains poorly understood. We evaluated relations of temperature and humidity during critical periods for the tick lifecycle with human Lyme disease. We used electronic health records from 479,344 primary care patients in 38 Pennsylvania counties in 2006-2014. Lyme disease cases (n = 9657) were frequency-matched (5:1) by year, age, and sex. Using daily weather data at ~4 km² resolution, we created cumulative metrics hypothesized to promote (warm and humid) or inhibit (hot and dry) tick development or host-seeking during nymph development (March 1-May 31), nymph activity (May 1-July 30), and prior year larva activity (Aug 1-Sept 30). We estimated odds ratios (ORs) of Lyme disease by quartiles of each weather variable, adjusting for demographic, clinical, and other weather variables. Exposure-response patterns were observed for higher cumulative same-year temperature, humidity, and hot and dry days (nymph-relevant), and prior year hot and dry days (larva-relevant), with same-year hot and dry days showing the strongest association (4th vs. 1st quartile OR = 0.40; 95% confidence interval [CI] = 0.36, 0.43). Changing temperature and humidity could increase or decrease human Lyme disease risk.

Association of community socioeconomic deprivation with evidence of reduced kidney function at time of type 2 diabetes diagnosis

BACKGROUND

While there are known individual-level risk factors for kidney disease at time of type 2 diabetes diagnosis, little is known regarding the role of community context. We evaluated the association of community socioeconomic deprivation (CSD) and community type with estimated glomerular filtration rate (eGFR) when type 2 diabetes is diagnosed.

METHODS

This was a retrospective cohort study of 13,144 adults with newly diagnosed type 2 diabetes in Pennsylvania. The outcome was the closest eGFR measurement within one year prior to and two weeks after type 2 diabetes diagnosis, calculated using the Chronic Kidney Disease Epidemiology Collaboration (CKD-Epi) equation. We used adjusted multinomial regression models to estimate associations of CSD (quartile 1, least deprivation) and community type (township, borough, city) with eGFR and used adjusted generalized estimating equation models to evaluate whether community features were associated with the absence of diabetes screening in the years prior to type 2 diabetes diagnosis.

RESULTS

Of the participants, 1279 (9.7%) had hyperfiltration and 1377 (10.5%) had reduced eGFR. Women were less likely to have hyperfiltration and more likely to have reduced eGFR. Black (versus White) race was positively associated with hyperfiltration when the eGFR calculation was corrected for race but inversely associated without the correction. Medical Assistance (ever versus never) was positively associated with reduced eGFR. Higher CSD and living in a city were each positively associated (odds ratio [95% confidence interval]) with reduced eGFR (CSD quartiles 3 and 4 versus quartile 1, 1.23 [1.04, 1.46], 1.32 [1.11, 1.58], respectively; city versus township, 1.38 [1.15, 1.65]). These features were also positively associated with the absence of a type 2 diabetes screening measure.

CONCLUSIONS

In a population-based sample, more than twenty percent had hyperfiltration or reduced eGFR at time of type 2 diabetes diagnosis. Individual- and community-level factors were associated with these outcomes.

Proximity to freshwater blue space and type 2 diabetes onset: the importance of historical and economic context

Salutogenic effects of living near aquatic areas (blue space) remain underexplored, particularly in non-coastal and non-urban areas. We evaluated associations of residential proximity to inland freshwater blue space with new onset type 2 diabetes (T2D) in central and northeast Pennsylvania, USA, using medical records to conduct a nested case-control study. T2D cases (n=15,888) were identified from diabetes diagnoses, medication orders, and laboratory test results and frequency-matched on age, sex, and encounter year to diabetes-free controls (n=79,435). We calculated distance from individual residences to the nearest lake, river, tributary, or large stream, and residence within the 100-year floodplain. Logistic regression models adjusted for community socioeconomic deprivation and other confounding variables and stratified by community type (townships [rural/suburban], boroughs [small towns], city census tracts). Compared to individuals living ≥1.25 miles from blue space, those within 0.25 miles had 8% and 17% higher odds of T2D onset in townships and boroughs, respectively. Among city residents, T2D odds were 38-39% higher for those living 0.25 to <0.75 miles from blue space. Residing within the floodplain was associated with 16% and 14% higher T2D odds in townships and boroughs. A post-hoc analysis demonstrated patterns of lower residential property values with nearer distance to the region's predominant waterbody, suggesting unmeasured confounding by socioeconomic disadvantage. This may explain our unexpected findings of higher T2D odds with closer proximity to blue space. Our findings highlight the importance of historic and economic context and interrelated factors such as flood risk and lack of waterfront development in blue space research.

Association of community types and features in a case-control analysis of new onset type 2 diabetes across a diverse geography in Pennsylvania

OBJECTIVES

To evaluate associations of community types and features with new onset type 2 diabetes in diverse communities. Understanding the location and scale of geographic disparities can lead to community-level interventions.

DESIGN

Nested case-control study within the open dynamic cohort of health system patients.

SETTING

Large, integrated health system in 37 counties in central and northeastern Pennsylvania, USA.

PARTICIPANTS AND ANALYSIS

We used electronic health records to identify persons with new-onset type 2 diabetes from 2008 to 2016 (n=15 888). Persons with diabetes were age, sex and year matched (1:5) to persons without diabetes (n=79 435). We used generalised estimating equations to control for individual-level confounding variables, accounting for clustering of persons within communities. Communities were defined as (1) townships, boroughs and city census tracts; (2) urbanised area (large metro), urban cluster (small cities and towns) and rural; (3) combination of the first two; and (4) county. Community socioeconomic deprivation and greenness were evaluated alone and in models stratified by community types.

RESULTS

Borough and city census tract residence (vs townships) were associated (OR (95% CI)) with higher odds of type 2 diabetes (1.10 (1.04 to 1.16) and 1.34 (1.25 to 1.44), respectively). Urbanised areas (vs rural) also had increased odds of type 2 diabetes (1.14 (1.08 to 1.21)). In the combined definition, the strongest associations (vs townships in rural areas) were city census tracts in urban clusters (1.41 (1.22 to 1.62)) and city census tracts in urbanised areas (1.33 (1.22 to 1.45)). Higher community socioeconomic deprivation and lower greenness were each associated with increased odds.

CONCLUSIONS

Urban residence was associated with higher odds of type 2 diabetes than for other areas. Higher community socioeconomic deprivation in city census tracts and lower greenness in all community types were also associated with type 2 diabetes.

Association of Greenness with Blood Pressure among Individuals with Type 2 Diabetes across Rural to Urban Community Types in Pennsylvania, USA

Greenness may impact blood pressure (BP), though evidence is limited among individuals with type 2 diabetes (T2D), for whom BP management is critical. We evaluated associations of residential greenness with BP among individuals with T2D in geographically diverse communities in Pennsylvania. To address variation in greenness type, we evaluated modification of associations by percent forest. We obtained systolic (SBP) and diastolic (DBP) BP measurements from medical records of 9593 individuals following diabetes diagnosis. Proximate greenness was estimated within 1250-m buffers surrounding individuals’ residences using the normalized difference vegetation index (NDVI) prior to blood pressure measurement. Percent forest was calculated using the U.S. National Land Cover Database. Linear mixed models with robust standard errors accounted for spatial clustering; models were stratified by community type (townships/boroughs/cities). In townships, the greenest communities, an interquartile range increase in NDVI was associated with reductions in SBP of 0.87 mmHg (95% CI: −1.43, −0.30) and in DBP of 0.41 mmHg (95% CI: −0.78, −0.05). No significant associations were observed in boroughs or cities. Evidence for modification by percent forest was weak. Findings suggest a threshold effect whereby high greenness may be necessary to influence BP in this population and support a slight beneficial impact of greenness on cardiovascular disease risk.

Risk Factors and Outcomes of Treatment Delays in Lyme Disease: A Population-Based Retrospective Cohort Study

Background: Longer time between symptom onset and treatment of Lyme disease has been associated with poor outcomes. Reducing time-to-treatment requires knowledge of risks for treatment delays. We conducted a population-based study to evaluate factors associated with delayed treatment of Lyme disease and the relation between delayed treatment and post-treatment Lyme disease syndrome (PTLDS). Methods: We mailed questionnaires to 5,314 individuals with a Lyme disease diagnosis or blood test followed by an antibiotic order in the medical record of a Pennsylvania health system from 2015 to 2017. Analyses were confined to 778 respondents who reported that they were treated for Lyme disease within the past 5 years and reported a rash and/or a positive blood test for Lyme disease. Time-to-treatment was calculated as the sum of two windows before and after seeking care for Lyme disease symptoms: time to first medical contact and time under care. We used logistic regression to evaluate factors associated with delayed time-to-treatment in each time window (>14 days vs. ≤14 days) and the association between total time-to-treatment (>30 days vs. ≤30 days) and PTLDS. We used inverse probability weighting to calculate estimates for the study's source population (5,314 individuals sent questionnaires). Results: In the source population, 25% had time to first contact >14 days, 21% had time under care >14 days, and 31% had a total time-to-treatment >30 days. Being uninsured and attributing initial symptoms to something other than Lyme disease were positively associated with delayed time to first medical contact, while seeking care at an urgent care or emergency setting (vs. primary care) was negatively associated. Diagnoses between November and April, and the absence of rash were positively associated with delays. Individuals whose treatment was delayed, defined as time-to treatment >30 days had 2.26 (95% confidence interval: 1.25, 4.05) times the odds of PTLDS as those who were treated within 30 days of symptom onset. Conclusions: In a population-based study in Pennsylvania, one-third of Lyme disease patients reported delayed treatment, which was associated with PTLDS. To improve Lyme disease outcomes, prevention efforts should aim to reduce the time before and after seeking care.

The Diabetes Location, Environmental Attributes, and Disparities Network: Protocol for Nested Case Control and Cohort Studies, Rationale, and Baseline Characteristics

BACKGROUND

Diabetes prevalence and incidence vary by neighborhood socioeconomic environment (NSEE) and geographic region in the United States. Identifying modifiable community factors driving type 2 diabetes disparities is essential to inform policy interventions that reduce the risk of type 2 diabetes.

OBJECTIVE

This paper aims to describe the Diabetes Location, Environmental Attributes, and Disparities (LEAD) Network, a group funded by the Centers for Disease Control and Prevention to apply harmonized epidemiologic approaches across unique and geographically expansive data to identify community factors that contribute to type 2 diabetes risk.

METHODS

The Diabetes LEAD Network is a collaboration of 3 study sites and a data coordinating center (Drexel University). The Geisinger and Johns Hopkins University study population includes 578,485 individuals receiving primary care at Geisinger, a health system serving a population representative of 37 counties in Pennsylvania. The New York University School of Medicine study population is a baseline cohort of 6,082,146 veterans who do not have diabetes and are receiving primary care through Veterans Affairs from every US county. The University of Alabama at Birmingham study population includes 11,199 participants who did not have diabetes at baseline from the Reasons for Geographic and Racial Differences in Stroke (REGARDS) study, a cohort study with oversampling of participants from the Stroke Belt region.

RESULTS

The Network has established a shared set of aims: evaluate mediation of the association of the NSEE with type 2 diabetes onset, evaluate effect modification of the association of NSEE with type 2 diabetes onset, assess the differential item functioning of community measures by geographic region and community type, and evaluate the impact of the spatial scale used to measure community factors. The Network has developed standardized approaches for measurement.

CONCLUSIONS

The Network will provide insight into the community factors driving geographical disparities in type 2 diabetes risk and disseminate findings to stakeholders, providing guidance on policies to ameliorate geographic disparities in type 2 diabetes in the United States.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/21377.

Peridomestic and community-wide landscape risk factors for Lyme disease across a range of community contexts in Pennsylvania

Land use and forest fragmentation are thought to be major drivers of Lyme disease incidence and its geographic distribution. We examined the association between landscape composition and configuration and Lyme disease in a population-based case control study in the Geisinger health system in Pennsylvania. Lyme disease cases (n = 9657) were identified using a combination of diagnosis codes, laboratory codes, and antibiotic orders from electronic health records (EHRs). Controls (5:1) were randomly selected and frequency matched on year, age, and sex. We measured six landscape variables based on prior literature, derived from the National Land Cover Database and MODIS satellite imagery: greenness (normalized difference vegetation index), percent forest, percent herbaceous, forest edge density, percent forest-herbaceous edge, and mean forest patch size. We assigned landscape variables within two spatial contexts (community and ½-mile [805 m] Euclidian residential buffer). In models stratified by community type, landscape variables were modeled as tertiles and flexible splines and associations were adjusted for demographic and clinical covariates. In general, we observed positive associations between landscape metrics and Lyme disease, except for percent herbaceous, where associations differed by community type. For example, compared to the lowest tertile, individuals with highest tertile of greenness in residential buffers had higher odds of Lyme disease (odds ratio: 95% confidence interval [CI]) in townships (1.73: 1.55, 1.93), boroughs (1.70: 1.40, 2.07), and cities (3.71: 1.74, 7.92). Similarly, corresponding odds ratios (95% CI) for forest edge density were 1.34 (1.22, 1.47), 1.56 (1.33, 1.82), and 1.90 (1.13, 3.18). Associations were generally higher in residential buffers, compared to community, and in cities, compared to boroughs or townships. Our results reinforce the importance of peridomestic landscape in Lyme disease risk, particularly measures that reflect human interaction with tick habitat. Linkage of EHR data to public data on residential and community context may lead to new health system-based approaches for improving Lyme disease diagnosis, treatment, and prevention.

Associations of multidimensional socioeconomic and built environment factors with body mass index trajectories among youth in geographically heterogeneous communities

Understanding contextual influences on obesity requires comparison of heterogeneous communities and concurrent assessment of multiple contextual domains. We used a theoretically-based measurement model to assess multidimensional socioeconomic and built environment factors theorized to influence childhood obesity across a diverse geography ranging from rural to urban. Confirmatory factor analysis specified four factors—community socioeconomic deprivation (CSED), food outlet abundance (FOOD), fitness and recreational assets (FIT), and utilitarian physical activity favorability (UTIL)—which were assigned to communities (townships, boroughs, city census tracts) in 37 Pennsylvania counties. Using electronic health records from 2001 to 2012 from 163,820 youth aged 3–18 years from 1288 communities, we conducted multilevel linear regression analyses with factor quartiles and their cross products with age, age², and age³ to test whether community factors impacted body mass index (BMI) growth trajectories. Models controlled for sex, age, race/ethnicity, and Medical Assistance. Factor scores were lowest in townships, indicating less deprivation, fewer food and physical activity outlets, and lower utilitarian physical activity favorability. BMI at average age was lower in townships versus boroughs (beta [SE]) (0.217 [0.027], P < 0.001) and cities (0.378 [0.036], P < 0.001), as was BMI growth over time. Factor distributions across community types lacked overlap, requiring stratified analyses to avoid extrapolation. In townships, FOOD, UTIL, and FIT were inversely associated with BMI trajectories. Across community types, youth in the lowest (versus higher) CSED quartiles had lower BMI at average age and slower BMI growth, signifying the importance of community deprivation to the obesogenicity of environments.

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Diverse geographies must be compared to understand contextual influences on obesity.

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Youth body mass index trajectories differed by community type in Pennsylvania.

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Food and physical activity environments were related to trajectories in townships.

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Socioeconomic deprivation was associated with trajectories in all community types.

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Community socioeconomic deprivation appears central to obesogenic environments.

Household Food Insecurity and Home Food Availability in Relation to Youth Diet, Body Mass Index, and Adiposity

BACKGROUND

Food security status is related to food types available in the home, which may shape youth dietary patterns, with implications for obesity.

OBJECTIVE

Investigate whether household food insecurity and home food availability (HFA) are associated with youth fruit and vegetable (F/V) consumption and anthropometric outcomes.

DESIGN

Cross-sectional study. Youth and parents completed questionnaires during in-home visits (2013-2014). Research staff obtained anthropometric measures.

PARTICIPANTS/SETTING

Medical record data for 10- to 15-year-old Pennsylvania youths were used to identify 434 parent-youth dyads, with 408 evaluated after excluding missing data.

MAIN OUTCOME MEASURES

Parent-reported household food security was assessed with the six-item US Department of Agriculture Food Security Scale (dichotomized as high vs low). Healthy and obesogenic HFA scales assessed parent report of how frequently particular foods were present in the home. Youth self-reported daily average F/V consumption. Anthropometric outcomes included age- and sex-standardized z scores for body mass index (BMIz), waist circumference (WCz), and percent body fat (PBFz).

STATISTICAL ANALYSES

Associations were evaluated with multivariable linear regression adjusted for youth age, sex, and race or ethnicity, and parent age and income.

RESULTS

Compared with food secure counterparts, youth from food insecure households had higher mean (beta [standard error]) BMIz (.30 [.15]), WCz (.27 [.12]), and PBFz (.43 [.16]). Food insecure households had lower mean healthy HFA scores (-1.23 [.54]); there was no evidence obesogenic HFA differed between food secure and insecure households. Youth from lower healthy HFA or higher obesogenic HFA households reported fewer mean daily F/V servings (healthy HFA: .08 [.02]; obesogenic HFA: -.06 [.02]). Food security status was not associated with F/V consumption, nor was there evidence HFA modified associations between food insecurity and anthropometric outcomes.

CONCLUSIONS

Despite an observed association between healthy HFA and youth F/V consumption, this study did not provide evidence that HFA explained associations between food insecurity and youth anthropometric outcomes.

Residential proximity to high-density poultry operations associated with campylobacteriosis and infectious diarrhea

Poultry carry zoonotic bacteria that can cause gastroenteritis in humans. Environmental transmission of pathogens from poultry operations may increase gastrointestinal infection risk in surrounding communities. To evaluate associations between residential proximity to high-density poultry operations and individual-level diarrheal illnesses, we conducted a nested case-control study among 514,488 patients in Pennsylvania (2006-2015). Using electronic health records, we identified cases of five gastrointestinal outcomes: three pathogen-specific infections, including Escherichia coli (n = 1425), Campylobacter (n = 567), and Salmonella (n = 781); infectious diarrhea (n = 781); and non-specific diarrhea (2012-2015; n = 28,201). We estimated an inverse-distance squared activity metric for poultry operations based on farm and patient addresses. Patients in the second and fourth (versus first) quartiles of the poultry operation activity metric had increased odds of Campylobacter (AOR [CI], Q2: 1.36 [1.01, 1.82]; Q3: 1.38 [0.98, 1.96]; Q4: 1.75 [1.31, 2.33]). Patients in the second, third, and fourth quartiles had increased odds of infectious diarrhea (Q2: 1.76 [1.29, 2.39]; Q3: 1.76 [1.09, 2.85]; Q4: 1.60 [1.12, 2.30]). Stratification revealed stronger relations of fourth quartile and both Campylobacter and infectious diarrhea in townships, the most rural community type in the study geography. Increasing extreme rainfall in the week prior to diagnosis strengthened fourth quartile Campylobacter associations. The poultry operation activity metric was largely unassociated with E. coli, Salmonella, and non-specific diarrhea. Findings suggest high-density poultry operations may be associated with campylobacteriosis and infectious diarrhea in nearby communities, highlighting additional public health concerns of industrial agriculture.

Comparing objective measures of the built environment in their associations with youth physical activity and sedentary behavior across heterogeneous geographies

We compared two strategies for measuring built environment features in their associations with youth physical activity and sedentary behavior across heterogeneous geographies of Pennsylvania. Physical activity environments of communities representing a rural-to-urban gradient were characterized through direct observation and spatially referenced archival data subjected to confirmatory factor analysis. Stratified regression analyses assessed associations between environmental measures and behavioral outcomes by community type. Neither strategy was consistently associated with behavior across communities. Findings highlight the importance of differentiating community type in evaluating associations of the built environment, and the challenge of measuring meaningful differences that influence youth behavior across heterogeneous geographies.

Home Food Rules in Relation to Youth Eating Behaviors, Body Mass Index, Waist Circumference, and Percent Body Fat

PURPOSE

To investigate agreement and associations between parent and youth acknowledgment of home food rules, youth eating behaviors, and measures of body composition and excess weight.

METHODS

Parent-youth dyads (N = 413) completed the "rules for eating at home" scale (Active Where Survey) and reported dietary intake. Trained research staff obtained anthropometric data. Linear regression analyses separately evaluated relationships between youth and parent acknowledgment of rules and youth-reported eating behaviors and anthropometric outcomes. Food rules were evaluated as a 12-item scale and individually.

RESULTS

Score on the food rule scale was positively associated with fruit and vegetable servings by youth acknowledgment only (β = .09, p = .006), and not with anthropometric outcomes. The rule "no desserts except fruit" was positively associated with fruit and vegetable servings by youth (β = .72, p = .002) and parent (β = .53, p = .03) acknowledgment. The rules "no second helpings at meals" and "limited fast food" were positively associated with body mass index z-score by youth (β = .38, p = .002; β = .32, p = .02, respectively) and parent (β = .74, p < .001; β = .41, p = .006, respectively) acknowledgment, with similar results for waist circumference z-score and percent body fat.

CONCLUSIONS

Inverse associations between specific food rules and healthful eating behaviors but positive associations with anthropometric outcomes suggest potentially bidirectional relationships between food rule implementation and youth weight. Future studies should disentangle how food rules guide youth behavior in the context of youth weight status.

Associations of prenatal and childhood antibiotic use with child body mass index at age 3 years

OBJECTIVE

Early-life antibiotic exposure, whether through prenatal or childhood antibiotic use, may contribute to increased child body mass. Associations of prenatal and childhood antibiotic use with body mass index z-score (BMIz) were evaluated at age 3 years.

METHODS

Electronic health records were utilized from 8,793 mothers and singleton children delivered at Geisinger Clinic in Pennsylvania between 2006 and 2012. Antibiotic orders were ascertained for mothers during pregnancy and for children through their age-3 BMI measurement. Linear mixed-effects regression models evaluated associations of prenatal and childhood antibiotic use with child BMIz.

RESULTS

Prenatal antibiotic orders were not associated with child BMIz. Children in the three largest categories of lifetime antibiotic orders had higher BMIz compared with children with no orders; associations persisted when controlling for prenatal antibiotics (β [95% confidence interval]) (4-5 child orders: 0.090 [0.011 to 0.170]; 6 to 8: 0.113 [0.029 to 0.197]; ≥9: 0.175 [0.088 to 0.263]; trend P value <0.001). Two or more first-year orders were also associated with BMIz (1: 0.021 [-0.038 to 0.081]; 2: 0.088 [0.017 to 0.160]; ≥3: 0.104 [0.038 to 0.170]; trend P value < 0.001).

CONCLUSIONS

Associations of early-life and lifetime childhood antibiotic use with increased child BMI highlight antibiotic exposure as a modifiable factor for reducing population-level excess weight.

Early-life antibiotic use and subsequent diagnosis of food allergy and allergic diseases

BACKGROUND

Antibiotic use in early life has been linked to disruptions in the microbiome. Such changes can disturb immune system development. Differences have been observed in the microbiota of children with and without allergies, but there have been few studies on antibiotic use and allergic disease.

OBJECTIVE

We evaluated associations of early-life antibiotic use with subsequent occurrence of food allergy and other allergies in childhood using electronic health record data.

METHODS

We used longitudinal data on 30 060 children up to age 7 years from Geisinger Clinic's electronic health record to conduct a sex- and age-matched case-control study to evaluate the association between antibiotic use and milk allergy, non-milk food allergies, and other allergies. For each outcome, we estimated conditional logistic regression models adjusting for race/ethnicity, history of Medical Assistance, and mode of birth delivery. Models were repeated separately for penicillins, cephalosporins and macrolides.

RESULTS

There were 484 milk allergy cases, 598 non-milk food allergy cases and 3652 other allergy cases. Children with three or more antibiotic orders had a greater odds of milk allergy (Odds Ratio; 95% Confidence interval) (1.78; 1.28-2.48), non-milk food allergy (1.65; 1.27-2.14), and other allergies (3.07; 2.72-3.46) compared with children with no antibiotic orders. Associations were strongest at younger ages and differed by antibiotic class.

CONCLUSIONS AND CLINICAL RELEVANCE

We observed associations between antibiotic orders and allergic diseases, providing evidence of a potentially modifiable clinical practice associated with paediatric allergic disease. Differences by antibiotic class should be further explored, as this knowledge could inform paediatric treatment decisions.

Urban community gardeners' knowledge and perceptions of soil contaminant risks

Although urban community gardening can offer health, social, environmental, and economic benefits, these benefits must be weighed against the potential health risks stemming from exposure to contaminants such as heavy metals and organic chemicals that may be present in urban soils. Individuals who garden at or eat food grown in contaminated urban garden sites may be at risk of exposure to such contaminants. Gardeners may be unaware of these risks and how to manage them. We used a mixed quantitative/qualitative research approach to characterize urban community gardeners' knowledge and perceptions of risks related to soil contaminant exposure. We conducted surveys with 70 gardeners from 15 community gardens in Baltimore, Maryland, and semi-structured interviews with 18 key informants knowledgeable about community gardening and soil contamination in Baltimore. We identified a range of factors, challenges, and needs related to Baltimore community gardeners' perceptions of risk related to soil contamination, including low levels of concern and inconsistent levels of knowledge about heavy metal and organic chemical contaminants, barriers to investigating a garden site's history and conducting soil tests, limited knowledge of best practices for reducing exposure, and a need for clear and concise information on how best to prevent and manage soil contamination. Key informants discussed various strategies for developing and disseminating educational materials to gardeners. For some challenges, such as barriers to conducting site history and soil tests, some informants recommended city-wide interventions that bypass the need for gardener knowledge altogether.

Localization of health systems in low- and middle-income countries in response to long-term increases in energy prices

External challenges to health systems, such as those caused by global economic, social and environmental changes, have received little attention in recent debates on health systems’ performance in low-and middle-income countries (LMICs). One such challenge in coming years will be increasing prices for petroleum-based products as production from conventional petroleum reserves peaks and demand steadily increases in rapidly-growing LMICs. Health systems are significant consumers of fossil fuels in the form of petroleum-based medical supplies; transportation of goods, personnel and patients; and fuel for lighting, heating, cooling and medical equipment. Long-term increases in petroleum prices in the global market will have potentially devastating effects on health sectors in LMICs who already struggle to deliver services to remote parts of their catchment areas. We propose the concept of “localization,” originating in the environmental sustainability literature, as one element of response to these challenges. Localization assigns people at the local level a greater role in the production of goods and services, thereby decreasing reliance on fossil fuels and other external inputs. Effective localization will require changes to governance structures within the health sector in LMICs, empowering local communities to participate in their own health in ways that have remained elusive since this goal was first put forth in the Alma-Ata Declaration on Primary Health Care in 1978. Experiences with decentralization policies in the decades following Alma-Ata offer lessons on defining roles and responsibilities, building capacity at the local level, and designing appropriate policies to target inequities, all of which can guide health systems to adapt to a changing environmental and energy landscape.

Families matter! Presexual risk prevention intervention

Parent-based HIV prevention programming may play an important role in reaching youths early to help establish lifelong patterns of safe and healthy sexual behaviors. Families Matter! is a 5-session, evidence-based behavioral intervention designed for primary caregivers of children aged 9 to 12 years to promote positive parenting and effective parent-child communication about sexuality and sexual risk reduction. The program's 5-step capacity-building model was implemented with local government, community, and faith-based partners in 8 sub-Saharan African countries with good intervention fidelity and high levels of participant retention. Families Matter! may be useful in other resource-constrained settings.

Enhancing HIV communication between parents and children: efficacy of the Parents Matter! Program

We examine efficacy of the Parents Matter! Program (PMP), a program to teach African-American parents of preadolescents sexual communication and HIV-prevention skills, through a multicenter, randomized control trial. A total of 1115 parent-child participants were randomized to one of three intervention arms (enhanced, brief, control). Percentages and 95% confidence intervals compare parents' perception of child readiness to learn about sexual issues, communication effectiveness, and dyad concordance from baseline to 12 months postintervention. Wilcoxon rank sum tests compare the changes in scores measuring communication content in HIV/AIDS, abstinence, and condom use. Compared to control, parents in the enhanced arm increased perception of child readiness to learn about sex (16% vs. 29%; p < .001), and a greater proportion of parent-child dyads reported concordant responses on communication topics: HIV/AIDS (15%, 95% CI = 8-21%; p < .001), abstinence (13%, 95% CI = 7-20%; p < .001), condoms (15%, 95% CI = 9-22%; p < .001). Increases in communication scores in HIV/AIDS, abstinence, and condom use were greater in the enhanced arm than control (p < 0.01). We conclude that the enhanced PMP can help parents educate children about HIV and prepare children to avoid sexual risk.

Factors associated with parent-child communication about HIV/AIDS in the United States and Kenya: a cross-cultural comparison

This study explored parent-child communication about HIV/AIDS among two populations disproportionately affected by HIV. Similar computer-assisted surveys were completed by parents of pre-teens, including 1,115 African American parents of 9-12-year-old children in southeastern US and 403 parents of 10-12-year-old children in Nyanza Province, Kenya. Multivariate analyses identified factors associated with parental report of ever talking to their child about HIV/AIDS. Twenty-nine percent of US parents and 40% in Kenya had never talked to their pre-teen about HIV/AIDS. In both countries, communication was more likely if parents perceived their child to be ready to learn about sex topics, had gotten information to educate their child about sex, and had greater sexual communication responsiveness (skill, comfort, and confidence communicating about sexuality). Programs are needed that help parents assess children's readiness to learn about sexual issues; access accurate information about adolescent sexual risks; and acquire the responsiveness needed to discuss sexual issues, including HIV/AIDS.

Evaluation of a U.S. evidence-based parenting intervention in rural Western Kenya: from parents matter! To families matter!

We evaluated Families Matter! Program (FMP), an intervention designed to improve parent-child communication about sexual risk reduction and parenting skills. Parents of 10- to 12-year-olds were recruited in western Kenya. We aimed to assess community acceptability and FMP's effect on parenting practices and effective parent-child communication. Data were collected from parents and their children at baseline and 1 year postintervention. The intervention's effect was measured on six parenting and parent-child communication composite scores reported separately for parents and children. Of 375 parents, 351 (94%) attended all five intervention sessions. Parents' attitudes regarding sexuality education changed positively. Five of the six composite parenting scores reported by parents, and six of six reported by children, increased significantly at 1 year postintervention. Through careful adaptation of this U.S. intervention, FMP was well accepted in rural Kenya and enhanced parenting skills and parent-child sexuality communication. Parents are in a unique position to deliver primary prevention to youth before their sexual debut as shown in this Kenyan program.

Cultural adaptation of a U.S. evidence-based parenting intervention for rural Western Kenya: from parents matter! To families matter!

Evidence-based interventions (EBIs) are critical for effective HIV prevention, but time and resources required to develop and evaluate new interventions are limited. Alternatively, existing EBIs can be adapted for new settings if core elements remain intact. We describe the process of adapting the Parents Matter! Program, an EBI originally developed for African American parents to promote effective parent-child communication about sexual risk reduction and parenting skills, for use in rural Kenya. A systematic process was used to assess the community's needs, identify potential EBIs, identify and make adaptations, pilot-test the adapted intervention, and implement and monitor the adapted EBI. Evaluation results showed the adapted EBI retained its effectiveness, successfully increasing parent-child sexual communication and parenting skills. Our experience suggests an EBI can be successfully adapted for a new context if it is relevant to local needs, the process is led by a multidisciplinary team with community representation, and pilot-testing and early implementation are well monitored.

Haploinsufficiency at the protein kinase A RI alpha gene locus leads to fertility defects in male mice and men

Carney complex (CNC) is a familial multiple neoplasia syndrome characterized by spotty skin pigmentation, cardiac and cutaneous myxomas, and endocrine tumors. CNC is inherited as an autosomal dominant trait and is transmitted with greater frequency by women vs. men. Nearly two thirds of CNC patients are heterozygous for inactivating mutations in the gene encoding the protein kinase A (PKA) type I alpha regulatory subunit (RI alpha), PRKAR1. We report here that male mice heterozygous for the Prkar1a gene have severely reduced fertility. Sperm from Prkar1a heterozygous mice are morphologically abnormal and reduced in number. Genetic rescue experiments reveal that this phenotype results from elevated PKA catalytic activity in germ cells as early as the pachytene stage of spermatogenesis. Consistent with this defect in the male mutant mice, sperm from CNC patients heterozygous for PRKAR1A mutations were also found to be morphologically aberrant and decreased in number. We conclude that unregulated PKA activity in male meiotic or postmeiotic germ cells leads to structural defects in mature sperm and results in reduced fertility in mice and humans, contributing to the strikingly reduced transmission of PRKAR1A inactivating mutations by male patients with CNC.

The effect of cimetidine or omeprazole on the pharmacokinetics of escitalopram in healthy subjects

AIMS

To investigate the effects of co-administration of cimetidine or omeprazole on the pharmacokinetics of escitalopram.

METHODS

Two randomized placebo-controlled crossover studies were carried out. Sixteen healthy subjects were administered placebo, or cimetidine (400 mg twice daily) for 5 days (study 1) or omeprazole (30 mg once daily) for 6 days (study 2). On day 4 (study 1) or day 5 (study 2), a single dose of escitalopram (20 mg) was administered. Blood samples were taken at predetermined times for the measurement of serum concentrations of escitalopram and its demethylated metabolite (S-DCT). Treatment-emergent adverse events were also monitored.

RESULTS

Co-administration with cimetidine caused a moderate increase in the systemic exposure [AUC0, infinity] to escitalopram (geometric mean ratio = 1.72, [95% CI 1.34, 2.21]) and a small increase in t(1/2) from 23.7 to 29.0 h (5.24 h [3.75, 6.70]). Co-administration with omeprazole also resulted in a moderate increase in the escitalopram AUC(0, infinity) (1.51 [1.39, 1.64]) and a small increase in t(1/2) from 26.5 to 34.8 h (8.3 h [6.44, 10.2]). There was no significant change in S-DCT AUC0, infinity after co-administration of either cimetidine or omeprazole. Co-administration of cimetidine or omeprazole had no effect on the incidence of treatment-emergent adverse events.

CONCLUSIONS

In view of the good tolerability of escitalopram, the pharmacokinetic changes observed on co-administration with cimetidine or omeprazole are unlikely to be of clinical concern.