Martin S. Lipsky

A cross-sectional study on health differences between rural and non-rural U.S. counties using the County Health Rankings

BackgroundBy examining 2013 County Health Rankings and Roadmaps data from the University of Wisconsin and the Robert Wood Johnson Foundation, this paper seeks to add to the available literature on health variances between United States residents living in rural and non-rural areas. We believe this is the first study to use the Rankings data to measure rural and urban health differences across the United States and therefore highlights the national need to address shortfalls in rural healthcare and overall health. The data indicates that U.S. residents living in rural counties are generally in poorer health than their urban counterparts.MethodsWe used 2013 County Health Rankings data to evaluate differences across the six domains of interest (mortality, morbidity, health behaviors, clinical care, social and economic factors, and physical environment) for rural and non-rural U.S. counties. This is a cross-sectional study employing chi-square analysis and logit regression.ResultsWe found that residents living in rural U.S. counties are more likely to have poorer health outcomes along a variety of measurements that comprise the County Health Rankings’ indexed domains of health quality. These populations have statistically significantly (pu2009≤u20090.05) lower scores in such areas as health behavior, morbidity factors, clinical care, and the physical environment. We attribute the differences to a variety of factors including limitations in infrastructure, socioeconomic differences, insurance coverage deficiencies, and higher rates of traffic fatalities and accidents.DiscussionsThe largest differences between rural and non-rural counties were in the indexed domains of mortality and clinical care.ConclusionsOur analysis revealed differences in health outcomes in the County Health Rankings’ indexed domains between rural and non-rural U.S. counties. We also describe limitations and offer commentary on the need for more uniform measurements in the classification of the terms rural and non-rural. These results can influence practitioners and policy makers in guiding future research and when deciding on funding allocation.

Rurality as a Root or Fundamental Social Determinant of Health

lace matters; it contextualizes health. When examining the influence of ommunity, neighborhood, and social space, researchers from multiple isciplines found that geography matters when assessing health status, ealth service use, health service deficits, adequacy of health care, and ealth-related behaviors. Where people live, work, and play protects and romotes their health and/or contributes to the health risks they experince. Koh et al advocate that all individuals should have an equal pportunity to maximize their health. However, some might experience a ealth disparity because of where they live. Such disparities, though, are ot fixed. Once identified, changes to improve health outcomes and educe disparities are possible. A health disparity or health inequity refers to differences in health or ealth outcomes related to factors such as gender, race, ethnicity, ocioeconomic status, or sexual orientation. As government reports such s Healthy People 2020 advocate for the fundamental human justice of ddressing avoidable health-related inequities, it is important to recognize he extensive body of public health-related research associating place or eographic locale as a significant factor in identifying populations ulnerable to health disparities. Although there is long-standing awareess of the health inequities for people living in the inner city, there is an merging body of research acknowledging the importance of rurality in ocial epidemiology, as well as the vulnerability of this specific opulation.

A review of the current epidemiology and treatment options for prostate cancer

Prostate cancer—the 2nd leading cause of cancer death among US men—affects 1 in 7 men at some point in their lifetime. Nearly 1 in 36 men die from prostate cancer in the US annually. The American Cancer Society estimates that in 2013 there will be about 239,000 new cases of diagnosed prostate cancer, and about 30,000 deaths due to prostate cancer. The overall ageadjusted annual incidence rate is 152 per 100,000 men, but the incidence varies widely across different race and ethnicity categories. For example, the annual incidence rate for Caucasian men is 144.9 per 100,000 men, while for African-American men it is 228.5 per 100,000. Native American/Alaska Native men have the lowest annual incidence rate at 77.8 per 100,000 men. Prostate cancer mostly affects older men, with about 60% of cases diagnosed in men 65 years or older and with 67 years being the average age at diagnosis. Relative to stage of diagnosis, local and regional stages have a 100% 5-year survival rate. However, distant-stage prostate cancer (which has spread to distant lymph nodes, bones, or other organs) has a 28% 5-year survival rate. The purpose of this review is to explain the most important issues surrounding prostate cancer and to offer primary care providers up-to-date information on guidelines and recommendations. The ultimate intention of this review is that it will assist primary care providers in the informed decision-making process that we advise should take place between physician and patient.

Clinical implications of aging

Figure summarizes the major changes of aging and some key ways these changes affect pages. Though many changes occur with aging, under normal or resting conditions, there is usually very little functionally that is diminished solely on the basis of aging. The net effects are reductions in reserve capacity and placing geriatric patients at higher risk for adverse consequences related to medications and diseases. Interactions between lifestyle factors, such as exercise, diet, and environmental exposures, have a large impact on aging and lead to great individual variability. The interplay between these environmental factors, aging, and development of chronic diseases multiply the amount of variation seen as individuals age.

Periodontitis: a global disease and the primary care provider’s role

Individuals who regularly visit a primary care provider (PCP) may not see a dentist, creating opportunities for PCPs to improve oral health. However, a lack of expertise among PCPs may limit their impact to improve public oral health. Using a non-systematic literature review, this article summarises the relevant literature about periodontitis. Periodontitis affects 10% to –15% of the world’s population. Caused by bacterial inflammation in gingival pockets, periodontal disease can destroy tissues surrounding the teeth. Factors linked to periodontal disease include diabetes, atherosclerosis and smoking. Good oral hygiene is important for both prevention and treatment. Mechanical removal of gingival irritants by scaling and root planing combined with adjunctive antimicrobial therapy are first-line treatment options. Surgery is indicated when healthy levels of gingival tissue are not attained from first-line treatments. By understanding the fundamentals of periodontitis the primary care provider can educate patients, promote healthy oral health behaviours and appropriately refer patients with signs and symptoms of periodontal disease.

An argument for male gender as a root cause or fundamental social determinant of health

Undeniably health disparities and social determinants of health are connected. While there are many definitions of health disparities, in the United States the legal definition comes from US Public Law 106-525 and is as follows: Health disparities are differences in the incidence, prevalence, mortality, and burden of diseases and other adverse health conditions that exist among specific population groups in the United States. Whitehead in the United Kingdom defined health inequities as the differences in prevalence, incidence, mortality, and morbidity that are unnecessary, avoidable, and unfair. For our purposes, a health disparity occurs whenever a negative, unjust, and preventable health-related prevalence, incidence, or disease burden difference (e.g., cancer incidence rates and mortality rates) is measured between population groups (i.e., men and women, African American and Caucasian men, or low and high socioeconomic status groups). Health disparities grow out of social determinants of health. A social determinant of health is an independent factor that influences and/or shapes health. Such factors may be geographic, socioeconomic, psychosocial, behavioral, or social in nature. Disparities or inequities in health arise because of the circumstances or social determinants that influence how people live, work, and age and the social structures or systems constructed to deal with disease and illness. In the late 1990s, Link and Phelan opened up a provocative debate about which social determinants of health are key contributors to health disparities or inequities. We believe that examining how male gender affects health status, health care, and health behaviors can affirm male gender as a fundamental or root social cause of health inequity. As defined by Link and Phelan, the following four features characterize a fundamental social cause: (1) it influences multiple disease or health outcomes; (2) it affects these outcomes through multiple risk factors; (3) it impacts access to resources that may be used to either avoid risks or minimize the consequence of disease; and (4) the association between the fundamental cause and health is reproduced over time through the replacement of intervening mechanisms. In this article, male gender is explored as a fundamental or root social cause of health inequities by taking these characteristics and posing four questions about male gender.

A scoping review exploring the opioid prescribing practices of US dental professionals

BACKGROUNDnThe prescribing practices of dental professionals may play an important role in the opioid epidemic. The authors performed a scoping review of the current original research literature onxa0dental professionals prescribing practices for opioid analgesics published from 2000 through 2017.nnnTYPES OF STUDIES REVIEWEDnWith the use of a modified Preferred Reporting Items for Systematic Reviews and Meta-Analyses approach, the inclusion criteria entailed published articles written in English that had an opioid focus, had a dental health care professional prescriber, entailed a US setting, were peer reviewed, had an identified data source, were not review articles, and were not opinion articles. Five databases were searched to identify relevant literature.nnnRESULTSnOf 221 articles, 18 met the inclusion criteria. Eight distinct and mutually exclusive themes emerged from these studies: impact of patient demographic characteristics on opioid prescribing, comparison of opioid prescribing by different provider type, quantity of opioids prescribed and consumed, types of opioids prescribed by dental professionals, assessment of self-reported opioid prescribing, opioid prescriptions by procedure, impact of pharmacy integration into dental practice, and implementation of risk mitigation strategies.nnnCONCLUSIONS AND PRACTICAL IMPLICATIONSnThere is a surprising paucity of research that investigated the prescribing patterns of dentists. Available research suggests that dental practice does not always align with proposed guidelines for opioid prescribing. Some studies that explored interventions found changes in prescribing, suggesting the potential benefit of developing practical strategies targeted to dental providers who prescribed opioids.

A scoping review of opioid misuse in the rural United States

INTRODUCTIONnThis study is a scoping review of the original research literature onthe misuse of opioids in the rural United States (US) and maps theliterature of interest to address the question: What does theoriginal research evidence reveal about the misuse of opioids inrural US communities?nnnMETHODSnThis study used a modified preferred reporting items for systematicreviews and meta-analyses (PRISMA) approach which is organized byfive distinct elements or steps: beginning with a clearly formulatedquestion, using the question to develop clear inclusion criteria toidentify relevant studies, using an approach to appraise the studiesor a subset of the studies, summarizing the evidence using anexplicit methodology, and interpreting the findings of the review.nnnRESULTSnThe initial search yielded 119 peer reviewed articles and aftercoding, 41 papers met the inclusion criteria. Researcher generatedsurveys constituted the most frequent source of data. Most studieshad a significant quantitative dimension to them. All the studieswere observational or cross-sectional by design.nnnCONCLUSIONSnThis analysis found an emerging research literature that hasgenerated evidence supporting the claim that rural US residents andcommunities suffer a disproportionate burden from the misuseof opioidscompared to their urban or metropolitan counterparts.

A Population-Based, Cross-Sectional Study Examining Health Services Deficits of US Veterans Using 2014 Behavioral Risk Factor Surveillance System Data: Is Rural Residency an Independent Risk Factor after Controlling for Multiple Covariates?

Introduction: In 2014, it was reported that there was a backlog of an estimated 1.2 million claims nationwide at the United States Veterans Administration (VA). This ecological occurrence opened up a space for asking and answering some important questions about health service deficits (HSD) of US veterans, which is the focus of the research reported on in this paper. The purpose of this study was to ascertain if rural veterans were more likely to experience HSDs than urban military veterans after controlling for a number of covariates. Methods: Bivariate and multivariate data analysis strategies were used to examine 2014 Behavioral Risk Factor Surveillance System (BRFSS) survey data. HSD was the dependent variable. Results: Two multivariate models were tested. The first logistic regression analysis yielded that rural veterans had higher odds of having at least one HSD. The second yielded that rural US veterans in 2014 who had higher odds of having at least one HSD were: 18–64 years of age, unemployed seeking employment, living in households with annual incomes lower than

Biological theories of aging

75,000, without a university degree, not part of a married or unmarried couple, a current smoker, and/or a binge drinker within the last 30 days. Conclusions: The study described here fills identified epidemiological gaps in our knowledge regarding rural US military veterans and HSDs. The findings are not only interesting but important, and should be used to inform interventions to reduce HSDs for rural veterans.