Measuring contextual characteristics for community health

Potential Risks for Healthcare Disparities Among Individuals With Voice and Upper Airway Disorders: A Systematic Review

PURPOSE

To assess the potential epidemiological association between various possible risk factors and healthcare disparities specifically related to the access, use and/or quality of speech language pathology services for individuals with voice and upper airway disorders.

METHOD

A systematic review was conducted using the Preferred Reporting Items for Systematic Review and Meta-Analysis. Full text journal articles were identified through PubMed, PsycINFO and Web of Science. The reference sections of included articles were also manually screened and identified four additional studies for consideration of inclusion. Included articles specifically addressed healthcare disparities in voice and upper airway disorders related to speech pathology care. International literature was excluded. Eligible studies were reviewed and data extracted. Risk of bias of each eligible study was performed using the quality assessment tool from National Institute of Health for observational cohort and cross-sectional studies. Data from eligible studies were synthesized thematically.

RESULTS

A total of 1,101 resources were retrieved from the search; of these, 133 were duplicates. Titles and abstracts of 968 articles were screened, with 14 selected for full-text review. Eleven articles were considered eligible for inclusion. Voice disorders were the condition most frequently examined followed by only one article addressing upper airways disorders. There was considerable heterogeneity in the methodology and statistical analyses among the eligible papers. There was a lack of standard methodology for collecting and accurately determining patient characteristics as well as variability in measuring confounding variables and providing statistical analyses for such adjustments that may have impacted the findings. The information extracted from these articles revealed healthcare disparities related to sex/gender, age, insurance status/coverage, race/ethnicity, among others including etiology and preferred language.

CONCLUSIONS

This systematic review highlights the limited research on speech language pathology-specific healthcare disparities for individuals with voice and upper airway disorders. There was significant clinical and methodological heterogeneity between studies which may have contributed to varied results between studies. There is a need for greater methodological rigor and prospectively designed studies to better characterize the impact of disparities in the access to, use of, and quality of speech pathology care for this patient population.

Frameworks for measuring population health: A scoping review

INTRODUCTION

Many regions in the world are using the population health approach and require a means to measure the health of their population of interest. Population health frameworks provide a theoretical grounding for conceptualization of population health and therefore a logical basis for selection of indicators. The aim of this scoping review was to provide an overview and summary of the characteristics of existing population health frameworks that have been used to conceptualize the measurement of population health.

METHODS

We used the Population, Concept and Context (PCC) framework to define eligibility criteria of frameworks. We were interested in frameworks applicable for general populations, that contained components of measurement of health with or without its antecedents and applied at the population level or used a population health approach. Eligible reports of eligible frameworks should include at least domains and subdomains, purpose, or indicators. We searched 5 databases (Pubmed, EMBASE, Web of Science, NYAM Grey Literature Report, and OpenGrey), governmental and organizational sites on Google and websites of selected organizations using keywords from the PCC framework. Characteristics of the frameworks were summarized descriptively and narratively.

RESULTS

Fifty-seven frameworks were included. The majority originated from the US (46%), Europe (23%) and Canada (19%). Apart from 1 framework developed for rural populations and 2 for indigenous populations, the rest were for general urban populations. The numbers of domains, subdomains and indicators were highly variable. Health status and social determinants of health were the most common domains across all frameworks. Different frameworks had different priorities and therefore focus on different domains.

CONCLUSION

Key domains common across frameworks other than health status were social determinants of health, health behaviours and healthcare system performance. The results in this review serve as a useful resource for governments and healthcare organizations for informing their population health measurement efforts.

Data resource profile: the Korean Community Health Status Indicators (K-CHSI) database

Korean Community Health Status Indicators (K-CHSI) is a model-based database containing annual data on health outcomes and determinants at the municipal level (si/gun/gu-level regions, including mid-sized cities, counties, and districts). K-CHSI's health outcomes include overall mortality, disease incidence, prevalence rates, and self-reported health. Health determinants were measured in 5 domains: socio-demographic factors, health behaviors, social environment, physical environment, and the healthcare system. The data sources are 71 public databases, including Causes of Death Statistics, Cancer Registration Statistics, Community Health Survey, Population Census, and Census on Establishments and Statistics of Urban Plans. This dataset covers Korea's 17 metropolitan cities and provinces, with data from approximately 250 municipal regions (si/gun/gu). The current version of the database (DB version 1.3) was built using 12 years of data from 2008 to 2019. All data included in K-CHSI may be downloaded via the Korea Community Health Survey site, with no login requirement (https://chs.kdca.go.kr/chs/recsRoom/dataBaseMain.do). K-CHSI covers extensive health outcomes and health determinants at the municipal level over a period of more than 10 years, which enables ecological and time-series analyses of the relationships among various health outcomes and related factors.

A Methodology for Integrating Population Health Surveys Using Spatial Statistics and Visualizations for Cross-Sectional Analysis

Large-scale population surveys are beneficial in gathering information on the performance indicators of public well-being, including health and socio-economic standing. However, conducting national population surveys for low and middle-income countries (LMIC) with high population density comes at a high economic cost. To conduct surveys at low-cost and efficiently, multiple surveys with different, but focused, goals are implemented through various organizations in a decentralized manner. Some of the surveys tend to overlap in outcomes with spatial, temporal or both scopes. Mining data jointly from surveys with significant overlap gives new insights while preserving their autonomy. We propose a three-step workflow for integrating surveys using spatial analytic workflow supported by visualizations. We implement the workflow on a case study using two recent population health surveys in India to study malnutrition in children under-five. Our case study focuses on finding hotspots and coldspots for malnutrition, specifically undernutrition, by integrating the outcomes of both surveys. Malnutrition in children under-five is a pertinent global public health problem that is widely prevalent in India. Our work shows that such an integrated analysis is beneficial alongside independent analyses of such existing national surveys to find new insights into national health indicators.

Patient characteristics and neighborhood attributes associated with hepatitis C screening and positivity in Philadelphia

Among patients of an urban primary care network in Philadelphia with a universal hepatitis C virus (HCV) screening policy for patients born during 1945-1965, we examined whether being unscreened and HCV positivity were associated with attributes of the census tracts where patients resided, which we considered as proxies for social health determinants. For patients with at least one clinic visit between 2014 and mid-2017, we linked demographic and HCV screening information from electronic health records with metrics that described the census tracts where patients resided. We used generalized estimating equations to estimate adjusted relative risk ratios (aRRs) for being unscreened and HCV positive. Overall, 28% of 6,906 patients were unscreened. Black race, male gender, and residence in census tracts with relatively high levels of violent crime, low levels of educational attainment and household incomes, and evidence of residential segregation by Hispanic ethnicity were associated with lower aRRs for being unscreened. Among screened patients, 9% were HCV positive. Factors associated with lower risks of being unscreened were, in general, associated with higher HCV positivity. Attributes of census tracts where patients reside are probably less apparent to clinicians than patients' gender or race but might reflect unmeasured patient characteristics that affected screening practices, along with preconceptions regarding the likelihood of HCV infection based on prior screening observations or implicit biases. Approaching complete detection of HCV-infected people would be hastened by focusing on residents of census tracts with attributes associated with higher infection levels or, if known, higher infection levels directly.

Neighborhood disadvantage, health status, and health care utilization after blood or marrow transplant: BMTSS report

Living in a disadvantaged neighborhood is associated with poor health outcomes. Blood or Marrow Transplant (BMT) survivors remain at risk of chronic health conditions requiring anticipatory management. We hypothesized that among BMT survivors, neighborhood disadvantage was associated with poor self-reported routine health care utilization and health. We leveraged data from BMTSS - a retrospective cohort study examining long-term outcomes among individuals surviving ≥2 y following BMT at three institutions between 1974 and 2014. Participants in this analysis completed the BMTSS survey (sociodemographics; chronic health conditions; time since routine check-up; self-reported health). The Area Deprivation Index (ADI) represented neighborhood disadvantage; this composite indicator of 17 census measures is a percentile rank (0 = least deprived to 100 = most deprived). Multivariable ordered logit regression adjusted for clinical factors and individual-level sociodemographics, modeling associations between ADI, time since routine check-up, and self-reported health. Among 2,857 survivors, median ADI was 24 (interquartile range: 10-46). Adjusting for self-reported individual-level socioeconomic indicators and chronic health conditions, patients in more disadvantaged neighborhoods had higher odds of reporting longer intervals since routine check-up (ORADI_continuous = 1.007, P < .001) and poorer health status (controlling for time since check-up; ORADI_continuous = 1.005, P = .003). Compared with patients living in the least disadvantaged neighborhood (ADI = 1), patients in the most disadvantaged neighborhood (ADI = 100), had twice the odds (ORADI = 1.007^99 = 2.06) of reporting no routine visits and 1.65-times the odds of reporting poor health (ORADI = 1.005^99 = 1.65). In BMT survivors, access to health care and health status are associated with area disadvantage. These findings may inform strategies to address long-term care coordination and retention for vulnerable survivors.

Selected Research Issues of Urban Public Health

Health is created within the urban settings of people’s everyday lives. In this paper we define Urban Public Health and compile existing evidence regarding the spatial component of health and disease in urban environments. Although there is already a substantial body of single evidence on the links between urban environments and human health, focus is mostly on individual health behaviors. We look at Urban Public Health through a structural lens that addresses health conditions beyond individual health behaviors and identify not only health risks but also health resources associated with urban structures. Based on existing conceptual frameworks, we structured evidence in the following categories: (i) build and natural environment, (ii) social environment, (iii) governance and urban development. We focused our search to review articles and reviews of reviews for each of the keywords via database PubMed, Cochrane, and Google Scholar in order to cover the range of issues in urban environments. Our results show that linking findings from different disciplines and developing spatial thinking can overcome existing single evidence and make other correlations visible. Further research should use interdisciplinary approaches and focus on health resources and the transformation of urban structures rather than merely on health risks and behavior.

Examining the Drivers of Racial/Ethnic Disparities in Non-Adherence to Antihypertensive Medications and Mortality Due to Heart Disease and Stroke: A County-Level Analysis

Background: Prior research has identified disparities in anti-hypertensive medication (AHM) non-adherence between Black/African Americans (BAAs) and non-Hispanic Whites (nHWs) but the role of determinants of health in these gaps is unclear. Non-adherence to AHM may be associated with increased mortality (due to heart disease and stroke) and the extent to which such associations are modified by contextual determinants of health may inform future interventions. Methods: We linked the Centers for Disease Control and Prevention (CDC) Atlas of Heart Disease and Stroke (2014-2016) and the 2016 County Health Ranking (CHR) dataset to investigate the associations between AHM non-adherence, mortality, and determinants of health. A proportion of days covered (PDC) with AHM < 80%, was considered as non-adherence. We computed the prevalence rate ratio (PRR)-the ratio of the prevalence among BAAs to that among nHWs-as an index of BAA-nHW disparity. Hierarchical linear models (HLM) were used to assess the role of four pre-defined determinants of health domains-health behaviors, clinical care, social and economic and physical environment-as contributors to BAA-nHW disparities in AHM non-adherence. A Bayesian paradigm framework was used to quantify the associations between AHM non-adherence and mortality (heart disease and stroke) and to assess whether the determinants of health factors moderated these associations. Results: Overall, BAAs were significantly more likely to be non-adherent: PRR = 1.37, 95% Confidence Interval (CI):1.36, 1.37. The four county-level constructs of determinants of health accounted for 24% of the BAA-nHW variation in AHM non-adherence. The clinical care (β = -0.21, p < 0.001) and social and economic (β = -0.11, p < 0.01) domains were significantly inversely associated with the observed BAA-nHW disparity. AHM non-adherence was associated with both heart disease and stroke mortality among both BAAs and nHWs. We observed that the determinants of health, specifically clinical care and physical environment domains, moderated the effects of AHM non-adherence on heart disease mortality among BAAs but not among nHWs. For the AHM non-adherence-stroke mortality association, the determinants of health did not moderate this association among BAAs; the social and economic domain did moderate this association among nHWs. Conclusions: The socioeconomic, clinical care and physical environmental attributes of the places that patients live are significant contributors to BAA-nHW disparities in AHM non-adherence and mortality due to heart diseases and stroke.

Poverty, Deprivation, and Mortality Risk Among Women With HIV in the United States

BACKGROUND

Prior studies suggest neighborhood poverty and deprivation are associated with adverse health outcomes including death, but evidence is limited among persons with HIV, particularly women. We estimated changes in mortality risk from improvement in three measures of area-level socioeconomic context among participants of the Women's Interagency HIV Study.

METHODS

Starting in October 2013, we linked geocoded residential census block groups to the 2015 Area Deprivation Index (ADI) and two 2012-2016 American Community Survey poverty variables, categorized into national tertiles. We used parametric g-computation to estimate, through March 2018, impacts on mortality of improving each income or poverty measure by one and two tertiles maximum versus no improvement.

RESULTS

Of 1596 women with HIV (median age 49), 91 (5.7%) were lost to follow-up and 83 (5.2%) died. Most women (62%) lived in a block group in the tertile with the highest proportions of individuals with income:poverty <1; 13% lived in areas in the tertile with the lowest proportions. Mortality risk differences comparing a one-tertile improvement (for those in the two highest poverty tertiles) in income:poverty <1 versus no improvement increased over time; the risk difference was -2.2% (95% confidence interval [CI] = -3.7, -0.64) at 4 years. Estimates from family income below poverty level (-1.0%; 95% CI = -2.7, 0.62) and ADI (-1.5%; 95% CI = -2.8, -0.21) exposures were similar.

CONCLUSIONS

Consistent results from three distinct measures of area-level socioeconomic environment support the hypothesis that interventions to ameliorate neighborhood poverty or deprivation reduce mortality risk for US women with HIV. See video abstract at, http://links.lww.com/EDE/B863.

A cross-sectional study of COVID-19-related bullying in a sample of Lebanese adults: scale validation, correlates, and mediating effect of fear and anxiety

Background

The COVID-19 pandemic has led to prolonged exposure to stress and anxiety, raising concerns about a large spectrum of psychological side effects. The primary objective of the study was to validate the COVID-19 Bullying Scale (CBS-11). The second objective was to explore factors associated with COVID-19-related bullying and evaluate the mediating effect of fear and anxiety between knowledge and COVID-19-related bullying.

Methods

A cross-sectional online survey conducted between December 20, 2020, and January 5, 2021, recruited 405 Lebanese adults using a snowball sampling technique. The CBS-11, an 11-item tool specifically created for this study, was used to measure bullying behaviors towards COVID-19 patients.

Results

All items of the CBS-11 converged over a 1-factor solution with an eigenvalue over 1, accounting for a variance of 75.16%. The scale has a high Cronbach’s alpha (.974), indicating excellent reliability. A positive correlation was found between the COVID-19 bullying scale and fear, anxiety, and stigma discrimination. The logistic regression showed that higher fear of COVID-19 (ORa = 1.04), a positive attitude toward COVID-19 preventive measures and hygiene recommendations (ORa = 1.18), higher stigma discrimination scores (ORa = 1.09), and having a health professional family member (ORa = 2.42) were significantly associated with bullying.

Conclusion

Our main findings showed that the CBS-11 could be an efficient tool to measure bullying behaviors toward COVID-19 patients. Stigma discrimination and fear from COVID-19 were associated with higher bullying attitudes. Future prospective studies are needed to understand better the factors related to bullying among adults during a pandemic, such as COVID-19.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40359-021-00643-1.

Regional variation in Black infant mortality: The contribution of contextual factors

BACKGROUND

Compared to other racial/ethnic groups, infant mortality rates (IMR) are persistently highestamong Black infants in the United States, yet there is considerable regional variation. We examined state and county-level contextual factors that may explain regional differences in Black IMR and identified potential strategies for improvement.

METHODS AND FINDINGS

Black infant mortality data are from the Linked Birth/Infant Death files for 2009-2011. State and county contextual factors within social, economic, environmental, and health domains were compiled from various Census databases, the Food Environment Atlas, and the Area Health Resource File. Region was defined by the nine Census Divisions. We examined contextual associations with Black IMR using aggregated county-level Poisson regression with standard errors adjusted for clustering by state. Overall, Black IMR varied 1.5-fold across regions, ranging from 8.78 per 1,000 in New England to 13.77 per 1,000 in the Midwest. In adjusted models, the following factors were protective for Black IMR: higher state-level Black-White marriage rate (rate ratio (RR) per standard deviation (SD) increase = 0.81, 95% confidence interval (CI):0.70-0.95), higher state maternal and child health budget per capita (RR per SD = 0.96, 95% CI:0.92-0.99), and higher county-level Black index of concentration at the extremes (RR per SD = 0.85, 95% CI:0.81-0.90). Modeled variables accounted for 35% of the regional variation in Black IMR.

CONCLUSIONS

These findings are broadly supportive of ongoing public policy efforts to enhance social integration across races, support health and social welfare program spending, and improve economic prosperity. Although contextual factors accounted for about a third of regional variation, further research is needed to more fully understand regional variation in Black IMR disparities.

Designing a toolkit for the assessment of Health in All Policies at a national scale in Iran

Background: Equitable promotion of health indicators requires cooperation among different sectors more than ever. The "Health in All Policies" (HiAP) approach contributes to this process through strengthening intersectoral collaboration. To implement this approach at a national scale, indicators of health-oriented performance from various organizations, and their measurement methods, need to be precisely defined. The aim of present study was to design a toolkit for implementing HiAP in Iran. Methods: A review of literature and documents, as well as conducting semi-structured interviews and focus group discussions were undertaken to collect data for this qualitative study. Content analysis was applied to the collected data and the results were placed in three categories: criteria, sub-criteria and indicators; implementation processes; and implementation requirements. Results: The toolkit aims to achieve various objectives, including intersectoral excellence and the systematic development of intersectoral collaboration. In the process section, reports on measures taken by organizations are assessed by a three-member audit committee. The top three organizations, in terms of intersectoral cooperation in achieving public health goals, are introduced in a Health Week. Requirements for success in achieving the HiAP approach include financial resources to implement the HiAP, a database, an electronic method for submitting reports, training courses, monitoring and annual reporting of relevant indicators, and formulating regulations in order to assess organizations. Conclusion: Justification and training in various organizations to support the implementation of health-oriented measures, providing an annual ranking of organizations, and encouraging the organizations can contribute to the institutionalization of the toolkit through the SupremeCouncil for Health and Food Security. It is recommended that a Secretariat of sustainable development to be established under the Plan and Budget Organization (PBO) of the Islamic republic of Iran to monitor portfolio indicators.

Multilevel analysis of factors associated with unmet need for family planning among Malawian women

Background

Malawi has a high fertility rate which is also characterized by a relatively high prevalence of unmet need for contraception. However, little is known about the influence of individual- and community- level characteristics on unmet need in Malawi. This study examined the individual- and community- level factors associated with unmet need for family planning (FP) among Malawian women.

Methods

Data from the 2015–16 Malawi demographic and health survey were used to analyze 15, 931 women. The association between individual- and community- level factors and unmet need was assessed using multilevel binary logistic regression models.

Results

The prevalence of total unmet need was 21.0%. Women aged ≥35 years were more likely to have total unmet need [adjusted odds ratio (aOR) = 1.19, 95% confidence interval (CI) = 1.04–1.35] compared with those aged 15–24 years. Women who were married [aOR = 0.41, 95% CI = 0.35–0.48], and those employed [aOR = 0.78, 95% CI = 0.71–0.85] were associated with less likelihood of having total unmet need compared with unmarried, and unemployed women, respectively. At community-level, women from communities with a high percentage of women from rich households [aOR = 0.81, 95% CI = 0.67–0.96], and those from communities with a middle and high percentage of educated women [aOR = 0.86, 95% CI = 0.76–0.96 and aOR = 0.81, 95% CI = 0.70–0.93, respectively] were less likely to have total unmet need for FP compared with those from communities with low percentages of rich and educated women, respectively. The proportional change in variance showed that about 36.0% of total variations in the odds of unmet need across the communities were explained by both individual- and community-level factors. Moreover, the intraclass correlation showed that about 3.0% of the total variation remained unexplained even after controlling for both individual- and community-level factors.

Conclusion

Both individual- and community- level factors influenced unmet need for FP in Malawi. Public health practitioners should conduct community profiling and consider individual and community factors when designing FP programs.

Socioeconomic Status and Temporal Urban Environmental Change in Accra: a Comparative Analysis of Area-based Socioeconomic and Urban Environmental Quality Conditions Between Two Time Points

The influence of area-based socioeconomic (SE) conditions on environmental quality conditions has recently been reported showing the precise spatial relationship between area-based SE conditions and neighborhood environmental quality in an urban area in a low-income setting. Nonetheless, there is still a lack of understanding of the nature of the relationship on a temporal scale. This study aimed to investigate the dynamic temporal relationship between area-based SE conditions and urban environmental quality conditions over a decadal period in Accra, Ghana. The results showed that there were differences in environmental quality across the SE quintiles in space (with regard to per capita waste generation (p < 0.012), waste collection/clearing (p < 0.01), and waste deposition (p < 0.001) and that the urban environmental quality conditions had changed dramatically over the decade for most of the environmental variables (p < 0.001). Despite the enormous urban development initiatives, some of the environmental quality indicators (e.g., proportion of households without flush toilet/Water Closet, connection to central sewer p < 0.001) appeared to have worsened in the high class quintile, suggesting that a high proportion of households were without acceptable sanitation facilities. The study concludes that urban development in low-income countries will need to follow strictly international best practice by observing standardized building codes and guidelines, if progress should be made in meeting the Millennium Development Goals targets.

The Stock Performance of American Companies Investing in a Culture of Health

Purpose:

We investigated the relationship between companies’ efforts to build internal (COH-INT) and external cultures of health (COH-EXT) and their stock performance.

Design:

We administered 2 surveys, which measure companies’ programs, policies, and supports for improving the health of their employees and communities. We then compared the companies’ stock performance to the Standard and Poor’s (S&P) 500 Index from January 2013 through August 2017.

Setting:

United States.

Participants:

Representatives from 17 publicly traded companies who completed the COH-INT survey, of whom 14 also completed the COH-EXT.

Measures:

Culture of health scores were dichotomized into high versus low for both surveys. Stock price data for all companies were gathered from public sources.

Analysis:

We constructed 5 stock portfolios: all 17 companies, high COH-INT, low COH-INT, high COH-EXT, and low COH-EXT companies. We examined total returns for each portfolio compared to the S&P 500.

Results:

High COH-INT companies’ stock price appreciated by 115% compared to the S&P benchmark (+69%), while low COH-INT companies appreciated only 43%. In contrast, high COH-EXT companies underperformed (+44%) when compared to the S&P 500 (+69%) and low COH-EXT companies (+89%).

Conclusion:

This study supports the view that employers’ efforts to build an internal culture of health is a sound business strategy. More research is needed, however, to establish whether a link exists between supporting healthy community initiatives and company stock performance.

Immigrants, Place, and Health: Destination Area Health Contexts and Routine Physician and Dental Care for Children of Mexican Immigrants

Notable healthcare disparities are shown among the children of Mexican immigrants across different Hispanic immigrant destinations. A hostile local immigrant-receptivity climate and alternative institutional community context indicators are integrated with individual-level data on physician and dental care from the 1996 and 2001 Survey of Income and Program Participation to explain this variation. Mexican immigrants’ children in new Hispanic immigrant destinations are 20 percent less likely to see a doctor, and a negative receptivity climate explains about half of this effect. Community health clinic availability and greater state leniency toward immigrant child public health insurance eligibility facilitate healthcare access.

Socioeconomic Status and Vulnerability to HIV Infection in Uganda: Evidence from Multilevel Modelling of AIDS Indicator Survey Data

BACKGROUND

There is controversy on the association between socioeconomic status (SES) and HIV infection. Some evidence claims higher SES is negatively associated with HIV infection while others report the reverse.

OBJECTIVES

To examine the association between SES and HIV infection in Uganda and to examine whether the SES-HIV relationship varies by gender, rural-urban place of residence, and time (2004-2005 and 2011) in Uganda.

METHODS

Multilevel analysis was applied to 39,766 individual cases obtained in 887 clusters of Uganda HIV/AIDS Indicators Survey conducted in 2004-2005 and 2011.

RESULTS

Household wealth is associated with increased vulnerability in the general population and in rural areas. Compared with no educational attainment, secondary or higher education is associated with reduced vulnerability to the risk of HIV infection by 37% in the general population. However, this effect was stronger in urban than rural areas. Besides individual-level factors, unobserved community factors too play an important role and account for 9% of unexplained variance after individual-level factors are considered.

CONCLUSION

Household wealth increases vulnerability but education reduces it. The social environment influences vulnerability to HIV infection independent of individual-level factors. HIV/AIDS awareness targeting sexual practices of wealthy individuals and those with primary-level educational attainment together with improving educational attainment and addressing contextual factors influencing vulnerability to HIV infection are necessary strategies to reduce HIV infections in Uganda.

Variations in Obesity Rates between US Counties: Impacts of Activity Access, Food Environments, and Settlement Patterns

There is much ongoing research about the effect of the urban environment as compared with individual behaviour on growing obesity levels, including food environment, settlement patterns (e.g., sprawl, walkability, commuting patterns), and activity access. This paper considers obesity variations between US counties, and delineates the main dimensions of geographic variation in obesity between counties: by urban-rural status, by region, by area poverty status, and by majority ethnic group. Available measures of activity access, food environment, and settlement patterns are then assessed in terms of how far they can account for geographic variation. A county level regression analysis uses a Bayesian methodology that controls for spatial correlation in unmeasured area risk factors. It is found that environmental measures do play a significant role in explaining geographic contrasts in obesity.

Discretionary decisions and disparities in receiving drug-eluting stents under a universal healthcare system: A population-based study

Objectives

One of the main objectives behind the expansion of insurance coverage is to eliminate disparities in health and healthcare. However, researchers have not yet fully elucidated the reasons for disparities in the use of high-cost treatments among patients of different occupations. Furthermore, it remains unknown whether discretionary decisions made at the hospital level have an impact on the administration of high-cost interventions in a universal healthcare system. This study investigated the adoption of drug-eluting stents (DES) versus bare metal-stents (BMS) among patients in different occupations and income levels, with the aim of gauging the degree to which the inclination of health providers toward treatment options could affect treatment choices at the patient-level within a universal healthcare system.

Design and participants

We adopted a cross-sectional observational study design using hierarchical modeling in conjunction with the population-based National Health Insurance database of Taiwan. Patients who received either a BMS or a DES between 2007 and 2010 were included in the study.

Results

During the period of study, 42,124 patients received a BMS (65.3%) and 22,376 received DES (34.7%). Patients who were physicians or the family members of physicians were far more likely to receive DES (OR: 3.18, CI: 2.38–4.23) than were patients who were neither physicians nor in other high-status jobs (employers, other medical professions, or public service). Similarly, patients in the top 5% income bracket had a higher probability of receiving a DES (OR: 2.23, CI: 2.06–2.47, p < .001), than were patients in the lowest income bracket. After controlling for patient-level factors, the inclination of hospitals (proportion of DES>50% or between 25% and 50%) was shown to be strongly associated with the selection of DESs (OR: 3.64 CI: 3.24–4.09 and OR: 2.16, CI: 2.01–2.33, respectively).

Conclusions

Even under the universal healthcare system in Taiwan, socioeconomic disparities in the use of high-cost services remain widespread. Differences in the care received by patients of lower socioeconomic status may be due to the discretionary decisions of healthcare providers.

Epidemiological placism in public health emergencies: Ebola in two Dallas neighborhoods

Super-diverse cities face distinctive challenges during infectious disease outbreaks. For refugee and immigrant groups from epidemic source locations, identities of place blend with epidemiological logics in convoluted ways during these crises. This research investigated the relationships of place and stigma during the Dallas Ebola crisis. Ethnographic results illustrate how Africanness, more than neighborhood stigma, informed Dallas residents' experience of stigma. The problems of place-based stigma, the imprecision of epidemiological placism, and the cohesion of stigma to semiotically powerful levels of place - rather than to realistic risk categories - are discussed. Taking its authority from epidemiology, placism is an important source of potential stigma with critical implications for the success of public health messaging.

Diabetes prevalence is associated with different community factors in the diabetes belt versus the rest of the United States

OBJECTIVE

To investigate differences in community characteristics associated with diabetes prevalence between the Diabetes Belt and the rest of the contiguous United States (U.S.) METHODS: County-level adult diabetes prevalence estimates (i.e., percent of people [≥20 years] with diagnosed diabetes 2009) were used from the Centers for Disease Control and Prevention, in addition to data from the U.S. Census Bureau, U.S. Department of Agriculture, and U.S. Department of Health and Human Services, to carry out a spatial regime analysis to identify county-level factors correlated with diabetes prevalence in the Diabetes Belt versus the remainder of the U.S.

RESULTS

Counties outside of the Diabetes Belt demonstrated stronger positive associations between diabetes prevalence and persistent poverty and greater percentages of unemployed labor forces. For counties in the Diabetes Belt, diabetes prevalence showed a stronger positive association with natural amenities (e.g., temperate climate and topographic features) and a stronger negative association with fitness/recreation facility density.

CONCLUSIONS

Community-level correlates of diabetes prevalence differed between the Diabetes Belt and elsewhere in the U.S. Economic hardship was shown to be more relevant outside the Diabetes Belt, while recreational context effects were more pronounced among counties within the region. Prevention and treatment targets are geographically unique, and public health efforts should acknowledge these differences in crafting policy.

The Association Among Individual and Contextual Factors and Unmet Healthcare Needs in South Korea: A Multilevel Study Using National Data

Objectives

The objective of this study is to investigate associations between contextual characteristics and unmet healthcare needs in South Korea after accounting for individual factors.

Methods

The present study used data from the 2012 Korean Community Health Survey (KCHS) of 228 902 adults residing within 253 municipal districts in South Korea. A multilevel analysis was conducted to investigate how contextual characteristics, defined by variables that describe the regional deprivation, degree of urbanity, and healthcare supply, are associated with unmet needs after controlling for individual-level variables.

Results

Of the surveyed Korean adults, 12.1% reported experiencing unmet healthcare needs in the past. This figure varied with the 253 districts surveyed, ranging from 2.6% to 26.2%. A multilevel analysis found that the association between contextual characteristics and unmet needs varied according to the factors that caused the unmet needs. The degree of urbanity was associated with unmet need due to “financial burden” (odds ratio [OR], 0.53; 95% confidence interval [CI], 0.42 to 0.66 for rural vs. metropolitan), but not unmet need due to “service not available when needed.” There were no significant associations between these unmet need measures and regional deprivation. Among individual-level variables, income level showed the highest association with unmet need due to “financial burden” (OR, 5.63; 95% CI, 4.76 to 6.66), while employment status showed a strong association with unmet need due to “service not available when needed.”

Conclusions

Our finding suggests that different policy interventions should be considered for each at-risk population group to address the root cause of unmet healthcare needs.

Research on neighborhood effects on health in the United States: A systematic review of study characteristics

Neighborhood effects on health research has grown over the past 20 years. While the substantive findings of this literature have been published in systematic reviews, meta-analyses, and commentaries, operational details of the research have been understudied. We identified 7140 multi-level neighborhoods and health papers published on US populations between 1995 and 2014, and present data on the study characteristics of the 256 papers that met our inclusion criteria. Our results reveal rapid growth in neighborhoods and health research in the mid-2000s, illustrate the dominance of observational cross-sectional study designs, and show a heavy reliance on single-level, census-based neighborhood definitions. Socioeconomic indicators were the most commonly analyzed neighborhood variables and body mass was the most commonly studied health outcome. Well-known challenges associated with neighborhood effects research were infrequently acknowledged. We discuss how these results move the agenda forward for neighborhoods and health research.

Effects of Primary Care Case Management (PCCM) on Medicaid Children in Alabama and Georgia: Provider Availability and Race/Ethnicity

This study analyzes the 4-year phase-in of Medicaid Primary Care Case Management (PCCM) in Georgia and Alabama. The effect of PCCM implementation on children's primary and preventive care, independent of changes in Medicaid participating providers, was measured by race. Accounting for provider supply, PCCMwas associated with lower use of primary care for all children except white non-Hispanics in urban Georgia. In urban Alabama, PCCM reduced preventive care for white and black non-Hispanic children. This held only for blacks in urban Georgia, while PCCM was associated with increased preventive care among all children in rural Georgia. The negative effect of PCCM was further compounded by negative effects of reduced provider availability. Reductions in office-based Medicaid providers affected Alabama children more often, while reductions in hospital-based physicians had a negative effect for Georgia children. Implementation of PCCM without fee increases may have had unexpected negative effects that differentially affected minority children.

County-level correlation between adult obesity rates and prevalence of dentists

BACKGROUND

Investigators of previous studies regarding the correlation between area-level health care resources and obesity have not examined the association between the prevalence of dentists and rates of adult obesity. The authors conducted a study to address that knowledge gap.

METHODS

Using data compiled in the Robert Wood Johnson County Health Rankings and Roadmaps database, the authors conducted multivariable analyses of the relationship between the prevalence of dentists (from the 2011 Health Resources and Services Administration Area Resource File) and rates of obesity within counties. The authors controlled for prevalence of primary care providers, measures of the built environment (for example, number of recreational facilities per 10,000 population, the percentage of restaurants serving fast food) and county-level sociodemographic and economic factors.

RESULTS

When the authors conducted a multivariable analysis adjusted for state-level fixed effects, they found that having one additional dentist per 10,000 population was associated significantly with a 1-percentage point reduction in the rate of obesity (P < .001). This effect was significantly larger in counties in which 25 percent of children or more (versus less than 25 percent of children) lived in poverty and in counties that had more primary care physicians per 10,000 population (P ≤ .009).

CONCLUSIONS

The association between the prevalence of dentists and obesity, even after adjusting for primary care resources and sociodemographic factors, was evident. Although these data could not be used to assess causality, given the strength of the ecological, cross-sectional association, additional research involving person-level, longitudinal data is warranted.

PRACTICAL IMPLICATIONS

The correlation between the prevalence of dentists and obesity rates highlights the potential for dental professionals, as well as other primary care providers, to provide meaningful health education and support for improved nutritional behaviors, although the increased obesity rates in counties with fewer dentists per capita present challenges.

Change in Obesity Prevalence across the United States Is Influenced by Recreational and Healthcare Contexts, Food Environments, and Hispanic Populations

OBJECTIVE

To examine change in county-level adult obesity prevalence between 2004 and 2009 and identify associated community characteristics.

METHODS

Change in county-level adult (≥20 years) obesity prevalence was calculated for a 5-year period (2004-2009). Community measures of economic, healthcare, recreational, food environment, population structure, and education contexts were also calculated. Regression analysis was used to assess community characteristics associated (p<0.01) with change in adult obesity prevalence.

RESULTS

Mean±SD change in obesity prevalence was 5.1±2.4%. Obesity prevalence decreased in 1.4% (n = 44) and increased in 98% (n = 3,060) of counties from 2004-2009. Results showed that both baseline levels and increases in physically inactive adults were associated with greater increases in obesity prevalence, while baseline levels of and increases in physician density and grocery store/supercenter density were related to smaller increases in obesity rates. Baseline levels of the Hispanic population share were negatively linked to changing obesity levels, while places with greater Hispanic population growth saw greater increases in obesity.

CONCLUSIONS

Most counties in the U.S. experienced increases in adult obesity prevalence from 2004 to 2009. Findings suggest that community-based interventions targeting adult obesity need to incorporate a range of community factors, such as levels of physical inactivity, access to physicians, availability of food outlets, and ethnic/racial population composition.

Regional disparities in obesity prevalence in the United States: A spatial regime analysis

OBJECTIVE

Significant clusters of high- and low-obesity counties have been demonstrated across the United States (US). This study examined regional disparities in obesity prevalence and differences in the related structural characteristics across regions of the US.

METHODS

Drawing on model-based estimates from the Centers for Disease Control and Prevention, regional differences in county-level adult obesity prevalence (percent of the adult population [≥ 20 years] that was obese [BMI ≥ 30 kg/m(2) ] within a county, 2009) were assessed with a LISA (Local Indicators of Spatial Association) analysis to identify geographic concentrations of high and low obesity levels. Regional regime analysis was utilized to identify factors that were differentially associated with obesity prevalence between regions of the US.

RESULTS

High- and low-obesity county clusters and the effect of a number of county-level characteristics on obesity prevalence differed significantly by region. These included the positive effect of African American populations in the South, the negative effect of Hispanic populations in the Northeast, and the positive effect of unemployed workers in the Midwest and West.

CONCLUSIONS

Our findings suggest the need for public health policies and interventions that account for different regional characteristics underlying obesity prevalence variation across the US.

The geographic concentration of US adult obesity prevalence and associated social, economic, and environmental factors

OBJECTIVE

This study used spatial statistical methods to test the hypotheses that county-level adult obesity prevalence in the United States is (1) regionally concentrated at significant levels, and (2) linked to local-level factors, after controlling for state-level effects.

METHODS

Data were obtained from the Centers for Disease Control and Prevention and other secondary sources. The units of analysis were counties. The dependent variable was the age-adjusted percentage of adults who were obese in 2009 (body mass index >30 kg/m2).

RESULTS

The prevalence of county-level obesity varied from 13.5% to 47.9% with a mean of 30.3%. Obesity prevalence across counties was not spatially random: 15.8% belonged to high-obesity regions and 13.5% belonged to low-obesity regions. Obesity was positively associated with unemployment, outpatient healthcare visits, physical inactivity, female-headed families, black populations, and less education. Obesity was negatively correlated with physician numbers, natural amenities, percent ≥65 years, Hispanic populations, and larger population size. A number of variables were notable for not reaching significance after controlling for other factors, including poverty and food environment measures.

CONCLUSIONS

The findings demonstrate the importance of local-level factors in explaining geographic variation in obesity prevalence, and thus hold implications for geographically targeted interventions to combat the obesity epidemic.

Intention to quit smoking and concerns about household environmental risks: findings from the Health in Common Study in low-income housing

PURPOSE

To assess the association between intention to quit smoking and perceptions of household environmental risks among racially/ethnically diverse residents of low-income housing.

METHODS

Baseline data were collected from 2007 to 2009 for the Health in Common Study, which assessed social and physical determinants of cancer risk-related behaviors among residents of 20 low-income housing developments in the Greater Boston metropolitan area. Participants were surveyed about their tobacco use and concerns about household exposures. Household environmental inspections were also conducted to identify conditions associated with increased risk of exposure to indoor environmental agents, including pesticides, mold, and cleaning products.

RESULTS

Intention to quit smoking was associated with a greater degree of concern about exposures in the home, yet not with the actual presence of household hazards, as identified by home inspections and survey findings.

CONCLUSIONS

An ecological approach targeting multiple levels of influence may help to highlight the importance of both quitting tobacco and reducing potential household environmental exposures as part of comprehensive efforts to promote individual and household health.

Elucidating the role of place in health care disparities: the example of racial/ethnic residential segregation

OBJECTIVE

To develop a conceptual framework for investigating the role of racial/ethnic residential segregation on health care disparities.

DATA SOURCES AND SETTINGS

Review of the MEDLINE and the Web of Science databases for articles published from 1998 to 2011.

STUDY DESIGN

The extant research was evaluated to describe mechanisms that shape health care access, utilization, and quality of preventive, diagnostic, therapeutic, and end-of-life services across the life course.

PRINCIPAL FINDINGS

The framework describes the influence of racial/ethnic segregation operating through neighborhood-, health care system-, provider-, and individual-level factors. Conceptual and methodological issues arising from limitations of the research and complex relationships between various levels were identified.

CONCLUSIONS

Increasing evidence indicates that racial/ethnic residential segregation is a key factor driving place-based health care inequalities. Closer attention to address research gaps has implications for advancing and strengthening the literature to better inform effective interventions and policy-based solutions.

Regional inequalities in the use of contraception in Spain: a multilevel approach

The aim of the present study was to describe the influence of individual and regional socioeconomic factors on the use of contraception among women in Spain in 2006. A cross-sectional study was carried out among women aged 15-49 years (n=5141). The prevalence of contraception use was analyzed as a function of individual and regional characteristics using weighted multilevel logistic regression models. The use of contraception in more deprived regions was lower during first sexual intercourse but higher during the four weeks prior to the interview. Inequalities in the use of contraception were observed among women in Spain after accounting for both individual and regional characteristics.

Vulnerability, risk perception, and health profile of marginalized people exposed to multiple built-environment stressors in Worcester, Massachusetts: a pilot project

Millions of low-income people of diverse ethnicities inhabit stressful old urban industrial neighborhoods. Yet we know little about the health impacts of built-environment stressors and risk perceptions in such settings; we lack even basic health profiles. Difficult access is one reason (it took us 30 months to survey 80 households); the lack of multifaceted survey tools is another. We designed and implemented a pilot vulnerability assessment tool in Worcester, Massachusetts. We answer: (1) How can we assess vulnerability to multiple stressors? (2) What is the nature of complex vulnerability-including risk perceptions and health profiles? (3) How can findings be used by our wider community, and what lessons did we learn? (4) What implications arise for science and policy? We sought a holistic picture of neighborhood life. A reasonably representative sample of 80 respondents captured data for 254 people about: demographics, community concerns and resources, time-activity patterns, health information, risk/stress perceptions, and resources/capacities for coping. Our key findings derive partly from the survey data and partly from our experience in obtaining those data. Data strongly suggest complex vulnerability dominated by psychosocial stress. Unexpected significant gender and ethnic disease disparities emerged: notably, females have twice the disease burden of males, and white females twice the burden of females of color (p < 0.01). Self-reported depression differentiated by gender and age is illustrative. Community based participatory research (CBPR) approaches require active engagement with marginalized populations, including representatives as funded partners. Complex vulnerability necessitates holistic, participatory approaches to improve scientific understanding and societal responses.

Maternal self-report of oral health in six-year-old Pacific children from South Auckland, New Zealand

OBJECTIVE

To examine maternal and socio-demographic factors associated with oral health practices and experiences in six-year-old Pacific children.

METHODS

The longitudinal Pacific Islands Families (PIF) study is following a cohort of Pacific children born in Auckland, New Zealand in 2000. At approximately six years postpartum maternal reports (n = 1001) on child oral health practices and experiences of fillings and extractions were gathered.

RESULTS

Forty-five per cent of mothers reported that their child had experienced fillings or extractions. After adjusting for confounding factors, we found that Tongan children were almost twice as likely to have their teeth filled or extracted than Samoan children (OR, 1.93; 95%, 1.34-2.77). Differences between Samoan children and children of other ethnic groups were not significant. Children of mothers who had secondary qualifications were significantly less likely to have their teeth filled or extracted compared to children of mothers who had postsecondary qualifications (OR, 0.634; 95%, 0.44-0.90). Prolonged duration of breastfeeding was associated with an increased likelihood of filling or extraction experience. In terms of maternal oral hygiene, maternal tooth brushing frequency of less that once a day was significantly associated with increased odds of fillings and/or extractions in their children (OR, 1.35; 95% CI, 1.02-1.79). Children who were sometimes supervised for tooth brushing were significantly more likely to have fillings or extractions than children who were not provided supervision.

CONCLUSIONS

These findings highlight the role of cultural factors and maternal hygiene in child oral health outcomes and suggest that health promotion efforts should encompass the whole family and embrace a culturally appropriate approach.

Assessing the relationship between socioeconomic conditions and urban environmental quality in Accra, Ghana

The influence of socioeconomic status (SES) on health inequalities is widely known, but there is still poor understanding of the precise relationship between area-based socioeconomic conditions and neighborhood environmental quality. This study aimed to investigate the socioeconomic conditions which predict urban neighbourhood environmental quality. The results showed wide variation in levels of association between the socioeconomic variables and environmental conditions, with strong evidence of a real difference in environmental quality across the five socioeconomic classes with respect to total waste generation (p < 0.001), waste collection rate (p < 0.001), sewer disposal rate (p < 0.001), non-sewer disposal (p < 0.003), the proportion of households using public toilets (p = 0.005). Socioeconomic conditions are therefore important drivers of change in environmental quality and urban environmental interventions aimed at infectious disease prevention and control if they should be effective could benefit from simultaneous implementation with other social interventions.

Conceptualizing the healthscape: contributions of time geography, location technologies and spatial ecology to place and health research

Geomatics and related technologies allow for the application of integrated approaches to the analysis of individual spatial and temporal activities in the context of place and health research. The ability to track individuals as they make decisions and negotiate space may provide a fundamental advance. This paper introduces the need to move beyond conventional place-based perspectives in health research, and invokes the theoretical contributions of time geography and spatial ecology as opportunities to integrate human agency into contextual models of health. Issues around the geographical representation of place are reviewed, and the concept of the healthscape is introduced as an approach to operationalizing context as expressed by the spatial and temporal activities of individuals. We also discuss how these concepts have the potential to influence and contribute to empirical place and health research.

Obesity and dental caries in children aged 2-6 years in the United States: National Health and Nutrition Examination Survey 1999-2002

OBJECTIVE

This study assessed the associations between obesity and dental caries in young children participating in a national survey.

METHODS

Participants included 1507 children aged 2-6 years who received dental examinations and had at least 10 primary teeth in the National Health and Nutrition Examination Survey 1999-2002. Decayed/filled teeth (dft) counts of primary dentition were obtained, and weight and height were measured. Body mass index (BMI; kg/m2) was calculated, and participants were categorized using age- and gender-specific criteria as underweight (<5th percent), normal (5th-85th percent), at risk for overweight (>85th and <95th percent), and overweight (> or =95th percent). With appropriate sample weighting, relationships between dft and BMI were assessed using the Kruskal-Wallis test and multivariable logistic regression.

RESULTS

Seventy-four percent of children were classified as normal weight, 11 percent as at risk for overweight, and 11 percent as overweight; 58 percent did not have caries; 30 percent had 1-5 dft and 12 percent had >5 dft. When caries experience was compared across BMI categories stratified by age and race characteristics, statistically significant association between caries and obesity was found only for 60- <72-month age group. In the comparison between children with normal and at-risk BMI only, significant associations were also found in the Hispanic and non-Hispanic Black strata. In multivariable logistic regression models to predict caries experience, family income and age were statistically significant predictors for severe early childhood caries only.

CONCLUSIONS

There appears to be no significant association between childhood obesity and caries experience after controlling forage, race, and poverty/income ratio. However, further studies are needed to better understand this relationship.

Small-area racial disparity in stroke mortality: an application of bayesian spatial hierarchical modeling

BACKGROUND

In the United States, excess burden of stroke mortality has persisted among African Americans compared with whites despite declines in stroke mortality for both groups. New insights may be gleaned by examining local, small-area patterns in racial disparities in stroke.

METHODS

The study population includes all non-Hispanic African Americans and non-Hispanic whites aged 35 to 64 in the southeastern United States during 1999 to 2002. We assessed county-level numbers of stroke deaths and population estimates in a Bayesian spatial hierarchical modeling framework allowing for inclusion of potential covariates (poverty and rurality), and generating county-specific model-based estimates of both absolute and relative racial disparity. The resulting estimates of race-specific stroke death rates, relative racial disparity, and absolute racial disparity were expressed in maps.

RESULTS

After adjustment for age, poverty, and rurality, county-level estimates of relative racial disparity ranged from 2.3 to 3.3 and estimates of absolute racial disparity ranged from 19 to 45 excess deaths per 100,000. For both racial groups, stroke death rates were higher in rural areas and with increasing poverty. High relative racial disparity was concentrated primarily in the eastern portion of the region and large absolute racial disparity was concentrated primarily in the western portion.

CONCLUSIONS

The results highlight the pervasiveness and magnitude of substantial local racial disparities in stroke mortality in the southeast.

Just in the wrong place...?: geographic tools for occupational injury/illness surveillance

BACKGROUND

Geographic analysis is now integral to public health surveillance, but has been underused for occupational injury/illness.

METHODS

Mapping and spatial statistics are used to examine national county-level mean establishment Lost Workday Injury/Illness (LWDII) rates in the Occupational Safety and Health Administration (OSHA) Data Initiative (ODI), 1997-2001. The following questions are explored: Does occupational injury/illness vary geographically at the county level?; Does variation remain after accounting for industry hazard?; Where are rates higher or lower than expected?

RESULTS

The methods provide evidence of geographic variation in nonfatal occupational injury/illness rates, including after adjusting for industry hazard.

CONCLUSIONS

Geographic analyses can improve intervention targeting, suggest risk factors for investigation, and make the case for targeting resources to prevention in hard-hit areas, as well as improving ongoing surveillance.

Heterogeneity in mammography use across the nation: separating evidence of disparities from the disproportionate effects of geography

Background

Mammography is essential for early detection of breast cancer and both reduced morbidity and increased survival among breast cancer victims. Utilization is lower than national guidelines, and evidence of a recent decline in mammography use has sparked concern. We demonstrate that regression models estimated over pooled samples of heterogeneous states may provide misleading information regarding predictors of health care utilization and that comprehensive cancer control efforts should focus on understanding these differences and underlying causal factors. Our study population includes all women over age 64 with breast cancer in the Surveillance Epidemiology and End Results (SEER) cancer registries, linked to a nationally representative 5% reference sample of Medicare-eligible women located in 11 states that span all census regions and are heterogeneous in racial and ethnic mix. Combining women with and without cancer in the sample allows assessment of previous cancer diagnosis on propensity to use mammography. Our conceptual model recognizes the interplay between individual, social, cultural, and physical environments along the pathways to health care utilization, while delineating local and more distant levels of influence among contextual variables. In regression modeling, we assess individual-level effects, direct effects of contextual factors, and interaction effects between individual and contextual factors.

Results

Pooling all women across states leads to quite different conclusions than state-specific models. Commuter intensity, community acculturation, and community elderly impoverishment have significant direct impacts on mammography use which vary across states. Minorities living in isolated enclaves with others of the same race/ethnicity may be either advantaged or disadvantaged, depending upon the place studied.

Conclusion

Careful analysis of place-specific context is essential for understanding differences across communities stemming from different causal factors. Optimal policy interventions to change behavior (improve screening rates) will be as heterogeneous as local community characteristics, so no "one size fits all" policy can improve population health. Probability modeling with correction for clustering of individuals within multilevel contexts can reveal important differences from place to place and identify key factors to inform targeting of specific communities for further study.

Community health status indicators project: the development of a national approach to community health

The Community Health Status Indicators Project (CHSI) 2008 provides 16-page reports for the 3141 counties in the United States, each of which includes more than 300 county-specific data items related to chronic and infectious diseases, birth characteristics or outcomes, causes of death, environmental health, availability of health services, behavioral risk factors, health-related quality of life, vulnerable populations, summary measures of health, and health disparities. The CHSI, originally initiated in 2000, provides county-level health profiles for all U.S. counties so that programs addressing community health can readily access community health indicators. Each county report also permits comparisons of a county's health status with similar "peer counties," with all counties, and with national Healthy People 2010 objectives. Under the leadership of a public-private partnership, the CHSI Steering Committee updated each county report and added new information and features to create CHSI 2008. This new CHSI version includes data for 1994 through 2006 from multiple surveillance systems. New features include an enhanced Web site, an Internet mapping application, and a downloadable database of the indicators for all counties.

Use of peer groupings to assess county public health status

INTRODUCTION

The Community Health Status Indicators Project was undertaken to produce county-specific reports assessing the status of community health for local jurisdictions throughout the United States. To accomplish this assessment, the Community Health Status Indicators Project team selected peer groupings of counties to monitor and analyze the health of local communities relative to peer communities.

METHODS

To identify peer counties, the project team used 5 categorical county demographic variables, a specified order for applying criteria, and a predetermined target for peer grouping size to subdivide counties into homogeneous subgroups called peer groupings.

RESULTS

Eighty-eight peer groupings were developed with 14-58 counties in each. The average size of each peer grouping was 35 counties. All peer groupings included counties representing at least 6 states.

DISCUSSION

Peer groupings are very useful for community health assessment. They convey the range of health status indicator values for similar counties, serve as a basis for expected numbers of reportable diseases, and provide a method for comparing communities with peer and U.S. medians. To maintain their usefulness, peer groupings must be updated periodically.

The importance of social context: neighborhood stressors, stress-buffering mechanisms, and alcohol, drug, and mental health disorders

This study examines the relationship among neighborhood stressors, stress-buffering mechanisms, and likelihood of alcohol, drug, and mental health (ADM) disorders in adults from 60 US communities (n=12,716). Research shows that larger support structures may interact with individual support factors to affect mental health, but few studies have explored buffering effects of these neighborhood characteristics. We test a conceptual model that explores effects of neighborhood stressors and stress-buffering mechanisms on ADM disorders. Using Health Care for Communities with census and other data, we found a lower likelihood of disorders in neighborhoods with a greater presence of stress-buffering mechanisms. Higher neighborhood average household occupancy and churches per capita were associated with a lower likelihood of disorders. Cross-level interactions revealed that violence-exposed individuals in high crime neighborhoods are vulnerable to depressive/anxiety disorders. Likewise, individuals with low social support in neighborhoods with high social isolation (i.e., low-average household occupancy) had a higher likelihood of disorders. If replicated by future studies using longitudinal data, our results have implications for policies and programs targeting neighborhoods to reduce ADM disorders.

Defining neighborhood boundaries for urban health research

The body of literature exploring neighborhood effects on health has increased rapidly in recent years, yet a number of methodologic concerns remain, including preferred methods for identification and delineation of study neighborhoods. In research combining census or other publicly available data with surveys of residents and/or street-level observations, questions regarding neighborhood definition take on added significance. Neighborhoods must be identified and delineated in such a way as to optimize quality and availability of data from each of these sources. IMPACT (Inner-City Mental Health Study Predicting HIV/AIDS, Club and Other Drug Transitions), a multilevel study examining associations among features of the urban environment and mental health, drug use, and sexual behavior, utilized a multistep neighborhood definition process including development of census block group maps, review of land use and census tract data, and field visits and observation in each of the targeted communities. Field observations were guided by a preidentified list of environmental features focused on the potential for recruitment (e.g., pedestrian volume), characteristics commonly used to define neighborhood boundaries (e.g., obstructions to pedestrian traffic, changes in land use), and characteristics that have been associated in the literature with health behaviors and health outcomes (such as housing type and maintenance and use of open spaces). This process, implemented in February through July 2005, proved feasible and offered the opportunity to identify neighborhoods appropriate to study objectives and to collect descriptive information that can be used as a context for understanding study results.