INTRODUCTION: This systematic economic review examined the cost-benefit and cost-effectiveness of park, trail, and greenway infrastructure interventions to increase physical activity or infrastructure use. METHODS: The search period covered the date of inception of publications databases through February 2022. Inclusion was limited to studies that reported cost-benefit or cost-effectiveness outcomes and were based in the United States and other high-income countries. Analyses were conducted during March 2022 through December 2022. All monetary values reported are in 2021 U.S. dollars. RESULTS: The search yielded 1 study based in the United States and 7 based on other high-income countries, with 1 reporting cost-effectiveness and 7 reporting cost-benefit outcomes. The cost-effectiveness study based in the United Kingdom reported $23,254 per disability-adjusted life year averted. The median benefit to cost ratio was 3.1 (Interquartile Interval: 2.9 to 3.9) based on 7 studies. DISCUSSION: The evidence shows that economic benefits exceed the intervention cost of park, trail, and greenway infrastructure. Given large differences in the size of infrastructure, intervention cost and economic benefits varied substantially across studies. There was insufficient number of studies to determine cost-effectiveness of these interventions.

Recent investments in built environment infrastructure to create healthy communities have highlighted the need for equity and environmental justice. Although the benefits of healthy community design (e.g., connecting transportation systems and land use changes) are well established, some reports suggest that these changes may increase property values. These increases can raise the risk of displacement for people with low incomes and/or who are from racial and ethnic minority groups, who would then miss out on benefits from changes in community design. This review scanned the literature for displacement mitigation and prevention measures, with the goal of providing a compilation of available strategies for a wide range of audiences including public health practitioners. A CDC librarian searched the Medline, EbscoHost, Scopus, and ProQuest Central databases, and we identified grey literature using Google and Google Scholar searches. The indexed literature search identified 6 articles, and the grey literature scan added 18 articles. From these 24 total articles, we identified 141 mitigation and prevention strategies for displacement and thematically characterized each by domain using an adapted existing typology. This work provides a well-categorized inventory for practitioners and sets the stage for future evaluation research on the implementation of strategies and practices to reduce displacement.

INTRODUCTION: Community fears of gentrification have created concerns about building active living infrastructure in neighborhoods with low-income populations. However, little empirical research exists related to these concerns. This work describes characteristics of residents who reported 1) concerns about increased cost of living caused by neighborhood development and 2) support for infrastructural improvements even if the changes lead to a higher cost of living. METHODS: Data on concerns about or support for transportation-related and land use-related improvements and sociodemographic characteristics were obtained from the 2018 SummerStyles survey, an online panel survey conducted on a nationwide sample of US adults (n = 3,782). Descriptive statistics characterized the sample, and χ(2) tests examined associations among variables. RESULTS: Overall, 19.1% of study respondents agreed that development had caused concerns about higher cost of living. Approximately half (50.7%) supported neighborhood changes for active living opportunities even if they lead to higher costs of living. Prevalences of both concern and support were higher among respondents who were younger and who had higher levels of education than their counterparts. Support did not differ between racial or ethnic groups, but concern was reported more often by Hispanic/Latino (28.9%) and other non-Hispanic (including multiracial) respondents (25.5%) than by non-Hispanic White respondents (15.6%). Respondents who reported concerns were more likely to express support (65.3%) than respondents who did not report concerns (47.3%). CONCLUSION: The study showed that that low-income, racial, or ethnic minority populations support environmental changes to improve active living despite cost of living concerns associated with community revitalization.

This paper arises from a series of workshops held by the National Collaborative on Childhood Obesity Research (NCCOR)1 and summarizes priorities and next steps for enhancing measurement tools and advancing the incorporation of high-quality measurement for surveillance, epidemiology, and intervention research aimed at accelerating progress in addressing the childhood obesity epidemic. It is intended to stimulate and inform new research on diverse aspects of childhood obesity among researchers and those who plan research initiatives.

BACKGROUND: Built environment approaches to promoting physical activity can provide economic value to communities. How best to assess this value is uncertain. This study engaged experts to identify a set of key economic indicators useful for evaluation, research, and public health practice. METHODS: Using a modified Delphi process, a multidisciplinary group of experts participated in (1) one of 5 discussion groups (n = 21 experts), (2) a 2-day facilitated workshop (n = 19 experts), and/or (3) online surveys (n = 16 experts). RESULTS: Experts identified 73 economic indicators, then used a 5-point scale to rate them on 3 properties: measurement quality, feasibility of use by a community, and influence on community decision making. Twenty-four indicators were highly rated (≥3.9 on all properties). The 10 highest-rated "key" indicators were walkability score, residential vacancy rate, housing affordability, property tax revenue, retail sales per square foot, number of small businesses, vehicle miles traveled per capita, employment, air quality, and life expectancy. CONCLUSION: This study identified key economic indicators that could characterize the economic value of built environment approaches to promoting physical activity. Additional work could demonstrate the validity, feasibility, and usefulness of these key indicators, in particular to inform decisions about community design.

Increasing physical activity in communities is a key public health strategy for chronic disease prevention and health promotion. Very few Americans get the minimum amount of physical activity necessary for substantial health benefits.1 Activity-friendly communities make physical activity easier or more accessible by providing opportunities for active transportation, leisure-time physical activity, or both.2 They are easy to navigate by foot, bicycle, or wheelchair, and they connect useful destinations, including public transit.3

Structured lifestyle interventions can reduce diabetes incidence and cardiovascular disease (CVD) risk among persons with impaired glucose tolerance (IGT), but it is unclear whether they should be implemented among persons without IGT. We conducted a systematic review and meta-analyses to assess the effectiveness of lifestyle interventions on CVD risk among adults without IGT or diabetes. We systematically searched MEDLINE, EMBASE, CINAHL, Web of Science, the Cochrane Library, and PsychInfo databases, from inception to May 4, 2016. We selected randomized controlled trials of lifestyle interventions, involving physical activity (PA), dietary (D), or combined strategies (PA+D) with follow-up duration ≥12 months. We excluded all studies that included individuals with IGT, confirmed by 2-hours oral glucose tolerance test (75g), but included all other studies recruiting populations with different glycemic levels. We stratified studies by baseline glycemic levels: (1) low-range group with mean fasting plasma glucose (FPG) <5.5mmol/L or glycated hemoglobin (A1C) <5.5%, and (2) high-range group with FPG ≥5.5mmol/L or A1C ≥5.5%, and synthesized data using random-effects models. Primary outcomes in this review included systolic blood pressure (SBP), diastolic blood pressure (DBP), total cholesterol (TC), low density lipoprotein cholesterol (LDL-C), high density lipoprotein cholesterol (HDL-C), and triglycerides (TG). Totally 79 studies met inclusion criteria. Compared to usual care (UC), lifestyle interventions achieved significant improvements in SBP (-2.16mmHg[95%CI, -2.93, -1.39]), DBP (-1.83mmHg[-2.34, -1.31]), TC (-0.10mmol/L[-0.15, -0.05]), LDL-C (-0.09mmol/L[-0.13, -0.04]), HDL-C (0.03mmol/L[0.01, 0.04]), and TG (-0.08mmol/L[-0.14, -0.03]). Similar effects were observed among both low-and high-range study groups except for TC and TG. Similar effects also appeared in SBP and DBP categories regardless of follow-up duration. PA+D interventions had larger improvement effects on CVD risk factors than PA alone interventions. In adults without IGT or diabetes, lifestyle interventions resulted in significant improvements in SBP, DBP, TC, LDL-C, HDL-C, and TG, and might further reduce CVD risk.

This study systematically assessed the effectiveness of lifestyle interventions on glycemic indicators among adults (18years) without IGT or diabetes. Randomized controlled trials using physical activity (PA), diet (D), or their combined strategies (PA+D) with follow-up 12months were systematically searched from multiple electronic-databases between inception and May 4, 2016. Outcome measures included fasting plasma glucose (FPG), glycated hemoglobin (HbA1c), fasting insulin (FI), homeostasis model assessment-estimated insulin resistance (HOMA-IR), and bodyweight. Included studies were divided into low-range (FPG <5.5mmol/L or HbA1c <5.5%) and high-range (FPG 5.5mmol/L or HbA1c 5.5%) groups according to baseline glycemic levels. Seventy-nine studies met inclusion criteria. Random-effect models demonstrated that compared with usual care, lifestyle interventions achieved significant reductions in FPG (-0.14mmol/L [95%CI, -0.19, -0.10]), HbA1c (-0.06% [-0.09, -0.03]), FI (%change: -15.18% [-20.01, -10.35]), HOMA-IR (%change: -22.82% [-29.14, -16.51]), and bodyweight (%change: -3.99% [-4.69, -3.29]). The same effect sizes in FPG reduction (0.07) appeared among both low-range and high-range groups. Similar effects were observed among all groups regardless of lengths of follow-up. D and PA+D interventions had larger effects on glucose reduction than PA alone. Lifestyle interventions significantly improved FPG, HbA1c, FI, HOMA-IR, and bodyweight among adults without IGT or diabetes, and might reduce progression of hyperglycemia to type 2 diabetes mellitus.

Electronic health (e-health) services have become increasingly important as a method to improve access to health care, including online renewal of prescription medications and making appointments. Healthy People 2020 includes objectives related to e-health to improve population health outcomes and to reduce health disparities, particularly to improve shared decision-making processes between patients and health care professionals (1). E-health services have been encouraged as part of the strategy to improve diabetes care and prevention (2,3). The adoption of these services among health care professionals has improved the quality and efficiency of care (4). However, e-health services may be underutilized among patients with diabetes. While research related to e-health services has been conducted in clinical and managed care settings (5), there are no national population estimates or trends for the utilization of e-health services among U.S. adults with diabetes. | We analyzed the 2009–2013 National Health Interview Survey (NHIS) (12,689 respondents aged ≥18 years with diabetes) self-reported data. NHIS is a cross-sectional household survey, using a multistage area probability design of the U.S. noninstitutionalized civilian population. NHIS is the first nationally representative household survey to include questions on the use of health information technology. Utilization of e-health services was defined as scheduling appointments, communicating with health care providers, and refilling prescription medications online. We calculated the predictive margins for the estimates of e-health utilization from multivariate logistic regression, controlling for age, sex, race/ethnicity, educational attainment, poverty-to-income ratio, health insurance coverage, having at least one visit to a doctor or health care professional in the past year, self-rated health status, history of other chronic diseases, diabetes duration, and diabetes medication. We used SAS-Callable SUDAAN 10.0.1 software to account for the complex sampling design of the NHIS. Differences were considered statistically significant at P values < 0.05.

INTRODUCTION: Diabetes is one of the most common and fastest-growing comorbidities of pregnancy. Temporal trends in gestational diabetes mellitus (GDM) have not been examined at the state level. This study examines GDM prevalence trends overall and by age, state, and region for 19 states, and by race/ethnicity for 12 states. Sub-analysis assesses trends among GDM deliveries by insurance type and comorbid hypertension in pregnancy. METHODS: Using the Agency for Healthcare Research and Quality's National and State Inpatient Databases, deliveries were identified using diagnosis-related group codes for GDM and comorbidities using ICD-9-CM diagnosis codes among all community hospitals. General linear regression with a log-link and binomial distribution was used in 2014 to assess annual change in GDM prevalence from 2000 through 2010. RESULTS: The age-standardized prevalence of GDM increased from 3.71 in 2000 to 5.77 per 100 deliveries in 2010 (relative increase, 56%). From 2000 through 2010, GDM deliveries increased significantly in all states (p<0.01), with relative increases ranging from 36% to 88%. GDM among deliveries in 12 states reporting race and ethnicity increased among all groups (p<0.01), with the highest relative increase in Hispanics (66%). Among GDM deliveries in 19 states, those with pre-pregnancy hypertension increased significantly from 2.5% to 4.1% (relative increase, 64%). The burden of GDM delivery payment shifted from private insurers (absolute decrease of 13.5 percentage points) to Medicaid/Medicare (13.2-percentage point increase). CONCLUSIONS: Results suggest that GDM deliveries are increasing. The highest rates of increase are among Hispanics and among GDM deliveries complicated by pre-pregnancy hypertension.

BACKGROUND: Trends in state-level prevalence of pre-pregnancy diabetes mellitus (PDM; i.e., type 1 or type 2 diabetes diagnosed before pregnancy) among delivery hospitalizations are needed to inform healthcare delivery planning and prevention programs. PURPOSE: To examine PDM trends overall, by age group, race/ethnicity, primary payer, and with comorbidities such as pre-eclampsia and pre-pregnancy hypertension, and to report changes in prevalence over 11 years. METHODS: In 2014, State Inpatient Databases from the Agency for Healthcare Research and Quality were analyzed to identify deliveries with PDM and comorbidities using diagnosis-related group codes and ICD-9-CM codes. General linear regression with a log-link and binomial distribution was used to assess the annual change. RESULTS: Between 2000 and 2010, PDM deliveries increased significantly in all age groups, all race/ethnicity groups, and in all states examined (p<0.01). The age-standardized prevalence of PDM increased from 0.65 per 100 deliveries in 2000 to 0.89 per 100 deliveries in 2010, with a relative change of 37% (p<0.01). Although PDM rates were highest in the South, some of the largest relative increases occurred in five Western states (≥69%). Non-Hispanic blacks had the highest PDM rates and the highest absolute increase (0.26 per 100 deliveries). From 2000 to 2010, the proportion of PDM deliveries with pre-pregnancy hypertension increased significantly (p<0.01) from 7.4% to 14.1%. CONCLUSIONS: PDM deliveries are increasing overall and particularly among those with PDM who have hypertension. Effective diabetes prevention and control strategies for women of childbearing age may help protect their health and that of their newborns.

Diabetes has steadily increased in prevalence, becoming one of the nation’s most challenging public health threats (1). Prevalence among adults is now more than 10%, and diabetes is the leading cause of nontraumatic lower-extremity amputation, end-stage kidney disease, and blindness; it more than doubles the risk of heart disease, stroke, and disability (1,2). Strong clinical trial evidence indicates that much of the illness caused by diabetes is preventable, further positioning diabetes as a public health priority (3,4) and stimulating a national emphasis on the quality of diabetes care and self-management (5–7). Although many such efforts have been successful, leading to better care, risk factor control, and reduced risk of complications, new challenges have arisen. The increases in obesity and in diabetes incidence demand that health systems and communities apply primary prevention strategies at the population level while simultaneously tackling the pervasive geographic and socioeconomic disparities in diabetes prevalence, care, and complications that remain (8,9). | Compared to the long list of clinical best practices to prevent diabetes complications, the evidence base is thin for population- and policy-level approaches to improve health behaviors, access to and delivery of care and preventive services, and the healthful attributes of communities. This imbalance of evidence calls for a new platform of public health research for diabetes. We contend that the imbalance can be corrected by a greater emphasis on natural experiments: rigorously designed quasi-experimental studies to investigate the health effects of naturally occurring population- and policy-level approaches emanating from health systems, communities, business organizations, and governments.

OBJECTIVE: To examine variability in diagnosed gestational diabetes mellitus (GDM) prevalence at delivery by race/ethnicity and state. RESEARCH DESIGN AND METHODS: We used data from the Healthcare Cost and Utilization Project State Inpatient Databases for 23 states of the United States with available race/ethnicity data for 2008 to examine age-adjusted and race-adjusted rates of GDM by state. We used multilevel analysis to examine factors that explain the variability in GDM between states. RESULTS: Age-adjusted and race-adjusted GDM rates (per 100 deliveries) varied widely between states, ranging from 3.47 in Utah to 7.15 in Rhode Island. Eighty-six percent of the variability in GDM between states was explained as follows: 14.7% by age; 11.8% by race/ethnicity; 5.9% by insurance; and 2.9% by interaction between race/ethnicity and insurance at the individual level; 17.6% by hospital level factors; 27.4% by the proportion of obese women in the state; 4.3% by the proportion of Hispanic women aged 15-44 years in the state; and 1.5% by the proportion of white non-Hispanic women aged 15-44 years in the state. CONCLUSIONS: Our results suggest that GDM rates differ by state, with this variation attributable to differences in obesity at the population level (or "at the state level"), age, race/ethnicity, hospital, and insurance.