Health status, neighborhood socioeconomic context, and premature mortality in the United States: The National Institutes of Health-AARP Diet and Health Study

Objectives. We examined whether the risk of premature mortality associated with living in socioeconomically deprived neighborhoods varies according to the health status of individuals.Methods. Community-dwelling adults (n = 566 402; age = 50–71 years) in 6 US states and 2 metropolitan areas participated in the ongoing prospective National Institutes of Health–AARP Diet and Health Study, which began in 1995. We used baseline data for 565 679 participants on health behaviors, self-rated health status, and medical history, collected by mailed questionnaires. Participants were linked to 2000 census data for an index of census tract socioeconomic deprivation. The main outcome was all-cause mortality ascertained through 2006.Results. In adjusted survival analyses of persons in good-to-excellent health at baseline, risk of mortality increased with increasing levels of census tract socioeconomic deprivation. Neighborhood socioeconomic mortality disparities among persons in fair-to-poor health were not statistically significant after adjustment for demographic characteristics, educational achievement, lifestyle, and medical conditions.Conclusions. Neighborhood socioeconomic inequalities lead to large disparities in risk of premature mortality among healthy US adults but not among those in poor health.Research dating back to at least the 1920s has shown that the United States has experienced persistent and widening socioeconomic disparities in premature mortality over time.^1–5 However, it has been unclear whether socioeconomic inequalities affect the longevity of persons in good and poor health equally. Socioeconomic status (SES) and health status are interrelated,^6–8 and both are strong independent predictors of mortality.⁹ Low SES is associated with greater risk of ill health and premature death,^{1–5,8,10–13} partly attributable to disproportionately high prevalence of unhealthful lifestyle practices^10,14,15 and physical and mental health conditions.^13,16 Correspondingly, risk of premature mortality is higher in poor than in more affluent areas.^16,17 Although the association between neighborhood poverty and mortality is independent of individual-level SES,^17,18 aggregation of low-SES populations in poor areas may contribute to variations in health outcomes across neighborhoods. Conversely, economic hardships resulting from ill health may lead persons in poor physical or mental health to move to poor neighborhoods.¹⁹ This interrelatedness may create spurious associations between neighborhood poverty and mortality.Although previous studies have found that the risk of premature death associated with poor health status varies according to individuals'' SES,^20,21 no published studies have examined whether the relative risks for premature mortality associated with living in neighborhoods with higher levels of socioeconomic deprivation vary by health status of individuals. Clarifying these relationships will inform social and public health policies and programs that aim to mitigate the health consequences of neighborhood poverty.^22,23We used data from a large prospective study to examine whether the risk of premature mortality associated with neighborhood socioeconomic context differs according to health status at baseline and remains after adjustment for person-level risk factors for mortality, such as SES, lifestyle practices, and chronic medical illnesses.     

Medication Prescribing Practices for Older Prisoners in the Texas Prison System

Objectives. We sought to assess appropriateness of medication prescribing for older Texas prisoners.Methods. In this 12-month cross-sectional study of 13 117 prisoners (aged ≥ 55 years), we assessed medication use with Zhan criteria and compared our results to prior studies of community prescribing. We assessed use of indicated medications with 6 Assessing Care of Vulnerable Elders indicators.Results. Inappropriate medications were prescribed to a third of older prisoners; half of inappropriate use was attributable to over-the-counter antihistamines. When these antihistamines were excluded, inappropriate use dropped to 14% (≥ 55 years) and 17% (≥ 65 years), equivalent to rates in a Department of Veterans Affairs study (17%) and lower than rates in a health maintenance organization study (26%). Median rate of indicated medication use for the 6 indicators was 80% (range = 12%–95%); gastrointestinal prophylaxis for patients on nonsteroidal anti-inflammatories at high risk for gastrointestinal bleed constituted the lowest rate.Conclusions. Medication prescribing for older prisoners in Texas was similar to that for older community adults. However, overuse of antihistamines and underuse of gastrointestinal prophylaxis suggests a need for education of prison health care providers in appropriate prescribing practices for older adults.More than 1 in 100 Americans are incarcerated in a US prison or jail¹ and older prisoners are among the most rapidly growing correctional populations.^1–4 With high rates of chronic disease,^5–7 older prisoners cost on average 2 to 3 times more than younger prisoners to incarcerate.^1,8 Yet prisons are often ill-equipped to care for older prisoners with complex medical problems, such as functional or cognitive impairments.^9–12 This is largely because older adults have substantively different health care needs than younger adults who have traditionally been the focus of prison health care.¹² Despite the increasing numbers and cost of older prisoners, research about the quality of geriatric care in prisons is sparse.One important difference in the care of younger and older adults is medication prescribing.^13,14 Older adults often require medications for multiple chronic diseases, whereas younger adults typically require short-term medications for acute injuries or infection. Although older patients are at increased risk for medication-related adverse events leading to morbidity, mortality, and high costs,^15,16 underuse of indicated medications can deny older adults improved quality and length of life.¹⁵ Despite the safety concerns and high cost associated with inappropriate medication use in older adults, little is known about medication prescribing practices for older prisoners.We assessed medication prescribing practices among older prisoners in the Texas Department of Criminal Justice (TDCJ)—one of the nation''s largest state prison systems. Since 1994, when the TDCJ implemented an academic-based managed care system run by the University of Texas Medical Branch, it has reported substantial improvements in health care and has been proposed as a nationwide model.^17,18 It is unknown if this improved quality has extended to elements of care of the older prisoners, such as medication prescribing quality.     

Determining What We Stand for Will Guide What We Do: Community Priorities,Ethical Research Paradigms,and Research With Vulnerable Populations

Prisoners, ex-offenders, and the communities they belong to constitute a distinct and highly vulnerable population, and research must be sensitive to their priorities. In light of recent suggestions that scientific experimentation involving prisoners be reconsidered, community-based participatory research can be a valuable tool for determining the immediate concerns of prisoners, such as the receipt of high-quality and dignified health care inside and outside prisons. In building research agendas, more must be done to ensure the participation of communities affected by the resulting policies.GIVEN RECENT PROPOSALS to reexamine federal regulations pertaining to human experimentation in prisons,^1–4 it is important that more be done to ensure that the viewpoints and life experiences of prisoners, ex-offenders, and their communities be considered. There has been recent debate about what constitutes ethical research in prisons and about the possible expansion of the scope of what is allowable. These questions arise because biomedical researchers are having difficulty in recruiting volunteers for clinical trials⁵ in the United States and because a number of private companies are increasingly seeking volunteers in other countries in which the costs of these experiments are less expensive, protocols are less complex, and compliance standards are less onerous.^6–9Some US researchers suggest that current regulations guiding prison research may be too strict and outdated,^1,4 and arguments have been made in favor of reassessing the current norms.^3,4 It has been noted, for example, that with the existence of institutional research boards, prisoners may actually benefit from this research if protocols are strengthened.^1,3,4 At least one researcher has argued that prisoners have a constitutional right to choose to participate in a study, clinical or otherwise.² Other work has suggested that prisoners ought to have the same access to experimental drugs as people who are not in prison and that there are ways to erect safeguards to ensure that the abuses committed in the past are not repeated.^2–4We argue that until the question of adequate health care for prisoners is resolved, human experimentation should not be allowed. Why are so many people from low-income, minority communities incarcerated? Why do these populations appear to be a convenient and natural source for social research? And, given that prisons do exist, why is it that that a stronger focus is not placed on appropriate and dignified care for confined populations, such as those inside prisons as well as for ex-offenders and their communities? Why is not greater precedence being given to finding the best methods for ensuring one single standard for all?We know, for example, that prisoners tend to be sicker than the rest of the population, bearing significantly higher rates of infectious diseases such as hepatitis C, tuberculosis, and HIV as well as chronic conditions including asthma, hypertension, diabetes, and oral illnesses. High rates of mental illness are also prevalent,^10–12 as well as the co-occurrence of substance abuse and mental illness. How these illnesses are treated in prison, and how much care is provided to ex-offenders after they leave prison, have direct implications for whether an ex-offender will reintegrate into society successfully.¹³For research in prisons to be ethical, it must be interested in upholding prisoners’ constitutional right to appropriate quality care while in prison and ensuring a stronger and more effective safety net for them when they return home. It must focus first on ensuring that the health of all is protected. It must ask what safeguards are in place for those who have engaged in clinical trials while in prison should they later become ill or infected.     

All-cause and cause-specific mortality among men released from state prison, 1980-2005

Objectives. We compared mortality of ex-prisoners and other state residents to identify unmet health care needs among former prisoners.Methods. We linked North Carolina prison records with state death records for 1980 to 2005 to estimate the number of overall and cause-specific deaths among male ex-prisoners aged 20 to 69 years and used standardized mortality ratios (SMRs) to compare these observed deaths with the number of expected deaths had they experienced the same age-, race-, and cause-specific death rates as other state residents.Results. All-cause mortality among White (SMR = 2.08; 95% confidence interval [CI] = 2.04, 2.13) and Black (SMR = 1.03; 95% CI = 1.01, 1.05) ex-prisoners was greater than for other male NC residents. Ex-prisoners'' deaths from homicide, accidents, substance use, HIV, liver disease, and liver cancer were greater than the expected number of deaths estimated using death rates among other NC residents. Deaths from cardiovascular disease, lung cancer, respiratory diseases, and diabetes were at least 30% greater than expected for White ex-prisoners, but less than expected for Black ex-prisoners.Conclusions. Ex-prisoners experienced more deaths than would have been expected among other NC residents. Excess deaths from injuries and medical conditions common to prison populations highlight ex-prisoners'' medical vulnerability and the need to improve correctional and community preventive health services.The United States has the highest incarceration rate in the world,¹ but 95% of prisoners are eventually released,² with most reentering society after less than 2 years of imprisonment.³ The result is a large and ever-increasing population of former inmates.⁴This growing population shoulders a heavy burden of disease, particularly infectious diseases such as hepatitis C virus, HIV, and other sexually transmitted infections.⁵ This burden is a reflection of high disease rates in the impoverished communities from which prisoners come and prisoners'' engagement in behaviors that are both illegal and harmful to health.⁶ Mental health conditions, including substance use disorders, are also common among prisoners.^7,8 These conditions are not only directly harmful, they also may exacerbate other comorbidities (e.g., cardiovascular disease and diabetes)^9,10 and are associated with diminished access to routine medical care.^11,12The transition from prison back into the community is typically difficult. Ex-prisoners often need to seek out housing and employment, reestablish personal relationships, navigate access to supportive services, and abide by the restrictions of parole and other legal sanctions.¹³ These needs frequently supersede routine health care.¹⁴For some, the transition is also dangerous. For ex-prisoners, risk of death in the first year—and especially in the first few weeks—after release is high compared with the risk of death among the general population.^15–18 The vast majority of these deaths are the result of nonnatural causes, particularly homicide, suicide, and drug overdose.^15–18 In one of the few US studies of its kind, risk of death among former Washington state prisoners during the first 2 weeks after release was 12.7 times the risk of death among other state residents, and risk of death from drug overdose during the first 2 weeks after release was 129 times that of other state residents.¹⁸Even less well-studied in the United States are the long-term health outcomes of former prisoners. A large retrospective study conducted in Australia reported that mortality among prisoners exceeded that of the general population across all major causes of death.¹⁹ The public health implication of these findings for the United States is troubling given the large size of the US ex-prisoner population, the heavy burden of disease among prisoners, and the legal sanctions and social stigma that diminish access to resources after release from prison.The purpose of our study was to examine the mortality of prisoners after their release. Specifically, we used age-standardized mortality ratios stratified by race to examine overall and cause-specific mortality among male former inmates. In addition, we examined the relative risk of mortality among former prisoners after we controlled for a measure of socioeconomic status (SES) and assessed time between prison release and death from injuries common to former prisoners. Enumeration of mortality disparities among former inmates could help detect lapses in the continuity between correctional and community health care resources.     

The Case for Improving the Health of Ex-Prisoners

The global prison population exceeds 10 million and continues to grow; more than 30 million people are released from custody annually. These individuals are disproportionately poor, disenfranchised, and chronically ill.There are compelling, evidence-based arguments for improving health outcomes for ex-prisoners on human rights, public health, criminal justice, and economic grounds. These arguments stand in stark contrast to current policy and practice in most settings.There is also a dearth of evidence to guide clinicians and policymakers on how best to care for this large and growing population during and after their transition from custody to community. Well-designed longitudinal studies, clinical trials, and burden of disease studies are pivotal to closing this evidence gap.The world prison population is more than 10.75 million and is growing at a rate in excess of population growth.1 Although in the United States there is a distinction between prisoners (felony offenders incarcerated in state and federal prisons) and jail detainees (mostly misdemeanor offenders), this distinction is not made in most countries. Here we use the term prisoner to refer to both prisoners and jail detainees. Because of the rapid turnover of custodial populations, it has been estimated that globally, more than 30 million people move through prisons each year.2 Incarceration rates vary markedly within and between countries, and are heavily influenced by public policy decisions, such as the criminalization of drug users3 and the de-institutionalization of the mentally ill.4 The United States has the highest incarceration rate in the world (743 per 100 000 population) and accounts for more than one fifth of the world’s prisoners, with approximately 2.2 million people in custody on any one day.1 Of these, 1.5 million are held in state and federal prisons, and spend on average three years in custody before returning to the community; more than 700 000 are held in local jails, where the average stay is less than seven days. Given the large incarcerated population and rapid turnover of jail detainees, in excess of 11 million persons pass through US correctional facilities each year—more than in any other country.5–7Prisoners globally are characterized by complex and multifaceted health problems.8 Although imprisonment confers its own unique health risks,9,10 health usually improves in custody, where stable accommodation and regular meals are provided at little or no cost, illicit drugs are less readily available, and high-intensity health services are routinely provided.11,12 Unfortunately, these health gains are often rapidly lost after return to the community, where many ex-prisoners experience poor health-related outcomes, including poorly controlled disease,13 elevated rates of life-threatening drug overdose,14,15 preventable hospitalization,16,17 and mortality.18,19 Key to improving these outcomes is increased access to health care for ex-prisoners,20 but this has proven difficult to achieve. Despite recent encouraging research findings,21 the greater challenge has been translating promising pilot programs into policy, at scale and in a sustainable way. Here we make the case for improving the health of ex-prisoners, in the hope that this will provide a platform for evidence-based advocacy to improve the health of this profoundly marginalized, challenging, and underserved population.     

The Impact of Quitting Smoking on Weight Among Women Prisoners Participating in a Smoking Cessation Intervention

Objectives. We examined the impact of smoking cessation on weight change in a population of women prisoners.Methods. Women prisoners (n = 360) enrolled in a smoking cessation intervention; 250 received a 10-week group intervention plus transdermal nicotine replacement.Results. Women who quit smoking had significant weight gain at 3- and 6-month follow-ups, with a net difference of 10 pounds between smokers and abstainers at 6 months. By the 12-month follow-up, weight gain decreased among abstainers.Conclusions. We are the first, to our knowledge, to demonstrate weight gain associated with smoking cessation among women prisoners. Smoking cessation interventions that address postcessation weight gain as a preventative measure may be beneficial in improving health and reducing the high prevalence of smoking in prisoner populations.Smoking and obesity are the 2 major causes of mortality and morbidity in the United States.^1,2 Although smoking is the leading preventable cause of death, resulting in approximately 440 000 deaths each year,³ obesity is a growing epidemic and is the second leading cause of preventable death, resulting in more than 300 000 deaths annually.^4,5 Whereas smoking rates have declined from their peak in the 1960s, obesity rates have been steadily climbing each year, and obesity is expected to soon eclipse smoking as the most preventable cause of mortality in the United States.¹The relationship between smoking and weight is complex, and the mechanisms by which smoking influences weight are not fully understood. Smoking affects weight by increasing metabolic rate and decreasing caloric absorption, which is thought to help suppress appetite.⁶ Sympathoadrenal activation by nicotine is thought to be primarily responsible for the metabolic effect of smoking.⁷ Smoking is also associated with increased energy expenditure.⁸ Smoking a single cigarette also decreases caloric consumption by 3% within 20 minutes.⁹Compared with light smokers and nonsmokers, heavy smokers tend to have greater body weight, which likely reflects a clustering of risk behaviors (i.e., little physical activity and poor diet) and increased insulin resistance and accumulation of abdominal fat.^6,10,11 Overall, smokers tend to be less physically active than nonsmokers, which may confound explanations of weight differences between smokers and nonsmokers.¹²Most studies on weight and smoking have reported postcessation weight gain. Smoking cessation has been associated with approximately 10 pounds of weight gain after 1 year of abstinence,¹³ suggesting that health benefits from smoking cessation may be mitigated to some degree by increased health risks associated with weight gain.¹⁴ To prevent or reduce weight gain, those administering cessation programs are recommended to integrate follow-up support for weight control, provide regular body weight measurement, provide recommendations for dietary change, and encourage increased physical activity.¹⁴ Despite concerns about weight, few studies have systematically investigated weight gain following smoking cessation, particularly with underserved populations such as prisoners.Correctional populations especially are vulnerable to the negative health consequences of smoking. Smoking rates are 3 to 4 times higher among correctional populations than among the general population, and smoking is normative within the correctional environment.^15–17 Smoking prevalence is 70% to 80% among male and female prisoners,^15–20 while almost half (46%) of adolescents in juvenile justice are daily smokers.²¹ This compared to about 21% of adults in the general population who are current smokers.²² However, in the research literature, the emphasis on smoking prevalence, prevention, cessation, and policies is much greater among other populations than it is among criminal justice populations—despite the human, health, and economic costs that occur in prison and in the community.^20,23In addition to the larger prevalence of smoking in prisons, there is less access to interventions for smoking cessation in correctional facilities. Lack of resources amplifies the negative health risks associated with smoking, such as heart, circulatory, and respiratory problems. Over the past 2 decades, correctional facilities in the United States have implemented tobacco-control policies ranging from restrictions on indoor smoking to complete tobacco bans.²⁴ Tobacco restrictions and bans have not succeeded in suppressing smoking, and reduced access to programs and materials that might increase long-term smoking cessation have paralleled them.^16,17,24,25We recently conducted a randomized controlled trial of smoking cessation with women prisoners and found 7-day point prevalence cessation rates comparable to those seen in community smoking cessation interventions.¹⁵ The intervention combined nicotine replacement with a 10-week group therapy intervention.²⁶ The community-tested intervention was modified for the prison environment and included a discussion of weight gain and weekly monitoring of weight during the intervention and follow-up assessments.¹⁵ Point prevalence quit rates for intervention participants were 18% at end of treatment, 17% at 3-month follow-up, 14% at 6-month follow-up, and 12% at 12-month follow-up, compared with less than 1% at these same time points for control participants.¹⁵ We examined differences in weight change over time for (1) women in the intervention condition compared with women in the control condition and (2) women in the intervention condition who quit smoking compared with those who continued to smoke. To our knowledge, ours is the first study to conduct such a trial among women prisoners.     

Effect of intensity and type of physical activity on mortality: results from the Whitehall II cohort study

Objectives. We examined the association of intensity and type of physical activity with mortality.Methods. We assessed the duration of physical activity by intensity level and type in 7456 men and women from the Whitehall II Study by questionnaire in 1997–1999 (mean ±SD age = 55.9 ±6.0 years) and 5 years later. All-cause mortality was assessed until April 2009.Results. A total of 317 participants died during the mean follow-up of 9.6 years (SD = 2.7). Reporting at least 1 hour per week of moderate activity was associated with a 33% (95% confidence interval [CI] = 14%, 45%) lower risk of mortality compared with less than 1 hour. For all physical activity types examined, except housework, a duration of physical activity greater than 0 (≥ 3.5 hours for walking) was associated with lower mortality in age-adjusted analyses, but only the associations with sports (hazard ratio [HR] = 0.71; 95% CI = 0.56, 0.91) and do-it-yourself activity (HR = 0.68; 95% CI = 0.53, 0.98) remained in fully adjusted analyses.Conclusions. It is important to consider both intensity and type of physical activity when examining associations with mortality.The dose-response association between physical activity and all-cause mortality is well established,^1,2 but few studies have investigated whether the different types of leisure-time physical activity are equally beneficial.^3–5 There are a variety of ways to expend energy, such as sports, walking, and domestic physical activity, and different types of activities require different levels of energy expenditure.⁶ Sports activities have been clearly shown to be associated with a lower risk of mortality.^3,5,7,8 However, less is known about less intensive physical activities, particularly those that are a part of daily living and leisure. Two recent reports showed “global domestic activity” to protect against all-cause mortality,^3,5 and a previous article on Finnish data suggested that specific types of domestic physical activity may have a protective effect.⁴ Our objective in the present study was to examine the associations of mortality with intensity, in terms of mild, moderate, and vigorous activity, and type of physical activity, specifically, walking, sports, housework, gardening, and do-it-yourself activities.     

Posttraumatic Stress Disorder and Incident Heart Failure Among a Community-Based Sample of US Veterans

Objectives. We investigated the association between posttraumatic stress disorder (PTSD) and incident heart failure in a community-based sample of veterans.Methods. We examined Veterans Affairs Pacific Islands Health Care System outpatient medical records for 8248 veterans between 2005 and 2012. We used multivariable Cox regression to estimate hazard ratios and 95% confidence intervals for the development of heart failure by PTSD status.Results. Over a mean follow-up of 7.2 years, veterans with PTSD were at increased risk for developing heart failure (hazard ratio [HR] = 1.47; 95% confidence interval [CI] = 1.13, 1.92) compared with veterans without PTSD after adjustment for age, gender, diabetes, hyperlipidemia, hypertension, body mass index, combat service, and military service period. Additional predictors for heart failure included age (HR = 1.05; 95% CI = 1.03, 1.07), diabetes (HR = 2.54; 95% CI = 2.02, 3.20), hypertension (HR = 1.87; 95% CI = 1.42, 2.46), overweight (HR = 1.72; 95% CI = 1.25, 2.36), obesity (HR = 3.43; 95% CI = 2.50, 4.70), and combat service (HR = 4.99; 95% CI = 1.29, 19.38).Conclusions. Ours is the first large-scale longitudinal study to report an association between PTSD and incident heart failure in an outpatient sample of US veterans. Prevention and treatment efforts for heart failure and its associated risk factors should be expanded among US veterans with PTSD.Posttraumatic stress disorder (PTSD) is a psychiatric illness that affects approximately 7.7 million Americans aged older than 18 years.1 PTSD typically results after the experience of severe trauma, and veterans are at elevated risk for the disorder. The National Vietnam Veterans Readjustment Study reported the prevalence of PTSD among veterans who served in Vietnam as 15.2% among men and 8.1% among women.2 In fiscal year 2009, nearly 446 045 Veterans Administration (VA) patients had a primary diagnosis of PTSD, a threefold increase since 1999.3 PTSD is of growing clinical concern as evidence continues to link psychiatric illnesses to conditions such as arthritis,4 liver disease,5 digestive disease,6 and cancer.6 When the postwar health status of Vietnam veterans was examined, those with PTSD had higher rates of diseases of the circulatory, nervous, digestive, musculoskeletal, and respiratory systems.7The evidence linking PTSD to coronary heart disease (CHD) is substantial.8–10 Veterans with PTSD are significantly more likely to have abnormal electrocardiograph results, myocardial infarctions, and atrioventricular conduction deficits than are veterans without PTSD.11 In a study of 605 male veterans of World War II and the Korean War, CHD was more common among veterans with PTSD than among those without PTSD.12 Worldwide, adults exposed to the disaster at Chernobyl experienced increased rates of CHD up to 10 years after the event,13 and studies of stressors resulting from the civil war in Lebanon found elevated CHD mortality.14,15Although the exact biological mechanism by which PTSD contributes to CHD remains unclear, several hypotheses have been suggested, including autonomic nervous system dysfunction,16 inflammation,17 hypercoagulability,18 cardiac hyperreactivity,19 altered neurochemistry,20 and co-occurring metabolic syndrome.16 One of the hallmark symptoms of PTSD is hyperarousal,21 and the neurobiological changes brought on from sustained sympathetic nervous system activation affect the release of neurotransmitters and endocrine function.22 These changes have negative effects on the cardiovascular system, including increased blood pressure, heart rate, and cardiac output.22,23Most extant literature to date examining cardiovascular sequelae has shown a positive association between PTSD and coronary artery disease.8–10 Coronary artery disease is well documented as one of the most significant risk factors for future development of heart failure.24 Despite burgeoning evidence for the role of PTSD in the development of coronary artery disease, there are few studies specifically exploring the relationship between PTSD and heart failure. Limited data suggest that PTSD imparts roughly a threefold increase in the odds of developing heart failure in both the general population5 and in a sample of the elderly.25 These investigations, however, have been limited by cross-sectional study design, a small proportion of participants with PTSD, and reliance on self-reported measures for both PTSD and heart failure.5,25 Heart failure is a uniquely large public health issue, as nearly 5 million patients in the United States are affected and there are approximately 500 000 new cases each year.26 Identifying predictors of heart failure can aid in early detection efforts while simultaneously increasing understanding of the mechanism behind development of heart failure.To mitigate the limitations of previous investigations, we undertook a large-scale prospective study to further elucidate the role of prevalent PTSD and development of incident heart failure among veterans, while controlling for service-related and clinical covariates. Many studies investigating heart failure have relied on inpatient records; we leveraged outpatient records to more accurately reflect the community burden of disease.     

Intergenerational relationships between the smoking patterns of a population-representative sample of US mothers and the smoking trajectories of their children

Objectives. We assessed intergenerational transmission of smoking in mother-child dyads.Methods. We identified classes of youth smoking trajectories using mixture latent trajectory analyses with data from the Children and Young Adults of the National Longitudinal Survey of Youth (n = 6349). We regressed class membership on prenatal and postnatal exposure to maternal smoking, including social and behavioral variables, to control for selection.Results. Youth smoking trajectories entailed early-onset persistent smoking, early-onset experimental discontinued smoking, late-onset persistent smoking, and nonsmoking. The likelihood of early onset versus late onset and early onset versus nonsmoking were significantly higher among youths exposed prenatally and postnatally versus either postnatally alone or unexposed. Controlling for selection, the increased likelihood of early onset versus nonsmoking remained significant for each exposure group versus unexposed, as did early onset versus late onset and late onset versus nonsmoking for youths exposed prenatally and postnatally versus unexposed. Experimental smoking was notable among youths whose mothers smoked but quit before the child''s birth.Conclusions. Both physiological and social role-modeling mechanisms of intergenerational transmission are evident. Prioritization of tobacco control for pregnant women, mothers, and youths remains a critical, interrelated objective.Women who smoke during pregnancy are more likely to have offspring who become adolescent smokers.^1–7 Studies link mother''s smoking during pregnancy with youths'' earlier smoking initiation,^3,7–9 greater persistence in regular smoking,^3,7 and stronger nicotine dependency.^6,8,10,11Hypothesized physiological pathways for mother-to-child transmission of smoking are reviewed elsewhere^12–14 and may include inherited susceptibility to addiction alone or in combination with in utero neurodevelopmental exposure and scarring that activates nicotine susceptibility. Furthermore, because few women who smoke during pregnancy quit after delivery^15,16 higher rates of smoking among offspring may reflect role modeling of maternal smoking behavior. Notably, parental smoking is hypothesized to demonstrate pro-smoking norms and solidify pro-smoking attitudes.^17,18Studies considering both smoking during pregnancy and subsequent maternal smoking outcomes have sought to distinguish between these proposed social and physiological transmission pathways.^{1–4,6,7,9,19} Similarly, studies controlling for family sociodemographic factors^{1,2,4,5,7,8,10,11,19,20} or maternal propensity for health or risk taking^1,2,9,10 have sought to further distinguish direct physiological or social transmission from selection. Studies considering children''s cognitive and behavioral outcomes have shown that selection by maternal social and behavioral precursors to smoking during pregnancy strongly biases findings on smoking during pregnancy^21,22; however, it remains unclear whether this is also the case for youth smoking. Some studies^2,3,5,6,19 have observed that smoking during pregnancy operates independently of subsequent maternal smoking. A few have found that smoking during pregnancy is only independently associated in select analyses (e.g., for initiation but not frequency or number of cigarettes^6,9 or only among females^7,20). Several have found that smoking during pregnancy does not operate independently of subsequent maternal smoking behavior,^1,4 and the remaining studies do not address postnatal maternal smoking.^8,9,11We explored whether these inconsistencies in findings supporting social or physiological mechanisms for intergenerational transmission can be accounted for by more comprehensively examining maternal and child smoking behavior. Previous work has established the advantages of statistical models for youth smoking trajectories that capture initiation, experimentation, cessation, or continued use.^23–28 Studies focusing on parental smoking concurrent with youth smoking suggest that postnatal exposures may differentially predispose youths for specific smoking trajectories.^24,26–28 Only 3 known studies have considered whether smoking during pregnancy influences youth smoking progression, and these have shown greater likelihood of early regular use^3,11 and telescoping to dependence.⁸ However, limitations of sample selectivity and measurement and modeling of maternal and youth smoking outcomes restrict the generalizability and scope of these findings.²⁹ To specifically address these limitations and more comprehensively assess hypothesized intergenerational transmission pathways, we used US population–representative data, latent variable techniques, and a rich set of data on maternal and youth smoking and social and behavioral selection factors. We characterized trajectories of youth smoking from adolescence through young adulthood and considered exposure to various maternal smoking patterns from prebirth to the child''s early adolescence.     

Clustering of Midlife Lifestyle Behaviors and Subsequent Cognitive Function: A Longitudinal Study

Objectives. We examined the association between individual and clustered lifestyle behaviors in middle age and later in cognitive functioning.Methods. Middle-aged participants (n = 2430) in the Supplémentation en Vitamines et Minéraux Antioxydant study self-reported their low physical activity, sedentary behavior, alcohol use, smoking, low fruit and vegetable consumption, and low fish consumption. We assessed cognition 13 years later via 6 neuropsychological tests. After standardization, we summed the scores for a composite cognitive measure. We estimated executive functioning and verbal memory scores using principal component analysis. We estimated the mean differences (95% confidence intervals [CIs]) in cognitive performance by the number of unhealthy behaviors using analysis of covariance. We identified latent unhealthy behavior factor via structural equation modeling.Results. Global cognitive function and verbal memory were linearly, negatively associated with the number of unhealthy behaviors: adjusted mean differences = −0.36 (95% CI = −0.69, −0.03) and −0.46 (95% CI = −0.80, −0.11), respectively, per unit increase in the number of unhealthy behaviors. The latent unhealthy behavior factor with low fruit and vegetable consumption and low physical activity as main contributors was associated with reduced verbal memory (RMSEA = 0.02; CFI = 0.96; P = .004). No association was found with executive functioning.Conclusions. Comprehensive public health strategies promoting healthy lifestyles might help deter cognitive aging.Noncommunicable diseases with notable lifestyle components are the leading causes of death worldwide.1,2 There is also growing evidence of the critical role of different midlife health and risk behaviors in cognitive aging.3–7 Because lifestyles are inherently modifiable and no treatment of cognitive decline is available, such findings argue for the paramount importance of prevention.8,9Current data support a deleterious effect of alcohol abstinence or abuse (compared with moderate alcohol consumption),10 smoking,7 low fruit and vegetable intake,11 low fish intake,12 and low physical activity (PA) levels13 on cognitive aging. However, it has been widely documented that lifestyle factors are strongly correlated with each other, forming a cluster of healthy or unhealthy behaviors.14 Traditionally, such interrelations have been accounted for by statistical adjustment; however, it is of major public health interest to consider the cumulative and combined effect of the various lifestyle behaviors on health by using multidimensional strategies.14Research that examines the combined effect of lifestyle factors on mortality is plentiful, and data have been colligated in a recent meta-analysis.15 These authors reported a 66% reduction in mortality risk by comparing adherence to 4 or more healthy lifestyle behaviors versus engagement in any number of unhealthy behaviors.The combined effect of lifestyle factors has also been explored in relation to cardiovascular diseases,16–18 cancer,18–22 diabetes,18,23 memory complaints,24 and dementia25–27; however, very few studies have reported findings regarding cognition.28,29 Despite heterogeneity in the definition of a healthy lifestyle, study design, and residual confounding, available, but scarce, data support a critical, protective role of healthy lifestyles in cognitive health through their beneficial properties via oxidative, inflammatory, vascular, and other neuroprotective pathways.30–33Our objectives in this study were to examine the association between individual and clustered lifestyle behaviors and later cognitive functioning. We employed traditional and innovative techniques (structural equation modeling) in our epidemiological pursuit.     

Meta-analysis of All-Cause Mortality According to Serum 25-Hydroxyvitamin D

We examined the relationship between serum 25-hydroxyvitamin D (25[OH]D) and all-cause mortality. We searched biomedical databases for articles that assessed 2 or more categories of 25(OH)D from January 1, 1966, to January 15, 2013. We identified 32 studies and pooled the data.The hazard ratio for all-cause mortality comparing the lowest (0–9 nanograms per milliliter [ng/mL]) to the highest (> 30 ng/mL) category of 25(OH)D was 1.9 (95% confidence interval = 1.6, 2.2; P < .001). Serum 25(OH)D concentrations less than or equal to 30 ng/mL were associated with higher all-cause mortality than concentrations greater than 30 ng/mL (P < .01).Our findings agree with a National Academy of Sciences report, except the cutoff point for all-cause mortality reduction in this analysis was greater than 30 ng/mL rather than greater than 20 ng/mL.An inverse association was proposed between solar irradiance and incidence of colon and breast cancer, based on a mechanism involving insufficient vitamin D. Individuals with lower serum 25-hydroxyvitamin D (25[OH]D) have higher risk of breast1–3 and colon cancer,4–6 other specific cancers,7 all invasive cancers combined,8 and coronary heart disease.9,10 Physiological mechanisms for the inverse association of 25(OH)D with cancer have been reported.11Despite research on the association between low vitamin D status and many diseases,12 no consensus has emerged on the optimal serum 25(OH)D concentration. The concern is whether it is safe to maintain serum 25(OH)D concentrations in the range high enough to prevent some types of cancers13–15 and coronary heart disease.9,10We decided to analyze the strength and consistency of the inverse association between levels of serum 25(OH)D and age-adjusted mortality hazard ratios in a rapidly expanding field of public health. A previous meta-analysis summarized 12 studies,16 another summarized 14,17 and another summarized a broader range.18We hypothesized that lower serum 25(OH)D was associated with higher all-cause mortality hazard ratios, and defined the age-adjusted hazard ratio for death from any cause as the outcome addressed by the meta-analysis. This analysis includes all studies of all-cause mortality hazard ratios by categories of serum 25(OH)D in healthy or general medical clinic cohorts that met the eligibility criteria. Twenty new studies of serum 25(OH)D and all-cause mortality entered the literature since the Zittermann et al. review,17 for a total of 32 in this review.19–50 Two studies in the review by Zittermann et al. did not meet the stringent inclusion criterion of the present study, and were not included.     

Reinforcement of smoking and drinking: tobacco marketing strategies linked with alcohol in the United States

Objectives. We investigated tobacco companies’ knowledge about concurrent use of tobacco and alcohol, their marketing strategies linking cigarettes with alcohol, and the benefits tobacco companies sought from these marketing activities.Methods. We performed systematic searches on previously secret tobacco industry documents, and we summarized the themes and contexts of relevant search results.Results. Tobacco company research confirmed the association between tobacco use and alcohol use. Tobacco companies explored promotional strategies linking cigarettes and alcohol, such as jointly sponsoring special events with alcohol companies to lower the cost of sponsorships, increase consumer appeal, reinforce brand identity, and generate increased cigarette sales. They also pursued promotions that tied cigarette sales to alcohol purchases, and cigarette promotional events frequently featured alcohol discounts or encouraged alcohol use.Conclusions. Tobacco companies’ numerous marketing strategies linking cigarettes with alcohol may have reinforced the use of both substances. Because using tobacco and alcohol together makes it harder to quit smoking, policies prohibiting tobacco sales and promotion in establishments where alcohol is served and sold might mitigate this effect. Smoking cessation programs should address the effect that alcohol consumption has on tobacco use.Smoking remains the leading preventable cause of premature mortality in the United States, accounting for more than 440 000 deaths annually.¹ Alcohol consumption is the third-leading cause of mortality in the nation.² Each year, approximately 79 000 deaths are attributable to excessive alcohol use.³ The concurrent use of cigarettes and alcohol further increases risks for certain cancers, such as cancer of the mouth, throat, and esophagus.^4,5 In addition, the use of both tobacco and alcohol makes it more difficult to quit either substance.⁶Smoking and drinking are strongly associated behaviors.^7–13 Smokers are more likely to drink alcohol,¹¹ drink more frequently,^8,11 consume a higher quantity of alcohol,^8,11,14 and demonstrate binge drinking (5 or more drinks per episode) than are nonsmokers.^9,11,12 Alcohol drinkers, especially binge drinkers, are also more likely to smoke^7,8,10 and are more likely to smoke half a pack of cigarettes or more per day.¹⁰The association between tobacco use and alcohol use becomes stronger with the heavier use of either substance.^8,15,16 Alcohol consumption increases the desire to smoke,^17,18 and nicotine consumption increases alcohol consumption.¹⁹ Experimental studies have demonstrated that nicotine and alcohol enhance each other''s rewarding effects.^16,18 Alcohol increases the positive subjective effects of smoking,^8,15,16,20 and smoking while using alcohol is more reinforcing than is smoking without concurrent alcohol use.⁸ Smokers smoke more cigarettes while drinking alcohol,^8,15,18 especially during binge-drinking episodes.^8,15 This behavior has also been observed among nondaily smokers^8,15 and light smokers.¹⁷The concurrent use of alcohol and tobacco is common among young adults,^8,10,12,21 including nondaily smokers,^19,22–24 nondependent smokers,⁸ and novice smokers.¹³ Young adult smokers have reported that alcohol increases their enjoyment of and desire for cigarettes^8,25 and that tobacco enhances the effect of alcohol: it “brings on the buzz” or “gave you a double buzz.”^13,23,26 Young adult nondaily smokers described the pairing of alcohol and cigarettes as resembling “milk and cookies” or “peanut butter with jelly.”²⁴ Young adults have also been the focus of aggressive tobacco promotional efforts in places where alcohol is consumed, such as bars and nightclubs.^27,28Consumer products often fall into cohesive groups (sometimes referred to as “Diderot unities”) that may reinforce certain patterns of consumption,²⁹ and these groupings may be influenced by marketing activities. In the case of tobacco and alcohol, these product links may have been further enhanced by cooperation between tobacco and alcohol companies (e.g., cosponsorship) or corporate ownership of both tobacco and alcohol companies (e.g., Philip Morris''s past ownership of Miller Brewing Company).We used tobacco industry documents to explore tobacco companies’ knowledge regarding linked tobacco and alcohol use and the companies’ marketing strategies that linked cigarettes with alcohol. We were interested in 3 basic issues: (1) what tobacco companies knew about the association between drinking and smoking, especially about smokers’ drinking behaviors, (2) how tobacco and alcohol companies developed cross promotions featuring cigarettes and alcohol, and (3) how tobacco companies linked cigarettes with alcohol in their marketing activities and the benefits they expected to gain from those activities.     

Impact of individual-, environmental-, and policy-level factors on health care utilization among US farmworkers

Objectives. We examined individual-, environmental-, and policy-level correlates of US farmworker health care utilization, guided by the behavioral model for vulnerable populations and the ecological model.Methods. The 2006 and 2007 administrations of the National Agricultural Workers Survey (n = 2884) provided the primary data. Geographic information systems, the 2005 Uniform Data System, and rurality and border proximity indices provided environmental variables. To identify factors associated with health care use, we performed logistic regression using weighted hierarchical linear modeling.Results. Approximately half (55.3%) of farmworkers utilized US health care in the previous 2 years. Several factors were independently associated with use at the individual level (gender, immigration and migrant status, English proficiency, transportation access, health status, and non-US health care utilization), the environmental level (proximity to US–Mexico border), and the policy level (insurance status and workplace payment structure). County Federally Qualified Health Center resources were not independently associated.Conclusions. We identified farmworkers at greatest risk for poor access. We made recommendations for change to farmworker health care access at all 3 levels of influence, emphasizing Federally Qualified Health Center service delivery.US farmworkers face significant disease burden¹ and excessive mortality rates for some diseases (e.g., certain cancers and tuberculosis) and injuries.² Disparities in health outcomes likely stem from occupational exposures and socioeconomic and political vulnerabilities. US farmworkers are typically Hispanic with limited education, income, and English proficiency.³ Approximately half are unauthorized to work in the United States.³ Despite marked disease burden, health care utilization appears to be low.^1,4–9 For example, only approximately half of California farmworkers received medical care in the previous year.⁶ This rate parallels that of health care utilization for US Hispanics, of whom approximately half made an ambulatory care visit in the previous year, compared with 75.7% of non-Hispanic Whites.¹⁰ Disparities in dental care have a comparable pattern.^6,8,11,12 However, utilization of preventive health services is lower for farmworkers^5,7,13,14 than it is for both US Hispanics and non-Hispanic Whites.^15,16Farmworkers face numerous barriers to health care^1,4,17: lack of insurance and knowledge of how to use or obtain it,^6,18 cost,^{5,6,12,13,18–20} lack of transportation,^{6,12,13,19–21} not knowing how to access care,^6,18,20,21 few services in the area or limited hours,^12,20,21 difficulty leaving work,¹⁹ lack of time,^5,13,19 language differences,^6,8,18–20 and fear of the medical system,¹³ losing employment,⁶ and immigration officials.²¹ Few studies have examined correlates of health care use among farmworkers. Those that have are outdated or limited in representativeness.^5,7,14,22,23 Thus, we systematically examined correlates of US health care use in a nationally representative sample of farmworkers, using recently collected data. The sampling strategy and application of postsampling weights enhance generalizability. We selected correlates on the basis of previous literature and the behavioral model for vulnerable populations.²⁴ The behavioral model posits that predisposing, enabling, and need characteristics influence health care use.²⁵ The ecological model, which specifies several levels of influence on behavior (e.g., policy, environmental, intrapersonal),²⁶ provided the overall theoretical framework. To our knowledge, we are the first to extensively examine multilevel correlates of farmworker health care use. We sought to identify farmworkers at greatest risk for low health care use and to suggest areas for intervention at all 3 levels of influence so that farmworker service provision can be improved.     

The association between perceived discrimination and obesity in a population-based multiracial and multiethnic adult sample

Objectives. We examined whether perceived chronic discrimination was related to excess body fat accumulation in a random, multiethnic, population-based sample of US adults.Methods. We used multivariate multinomial logistic regression and logistic regression analyses to examine the relationship between interpersonal experiences of perceived chronic discrimination and body mass index and high-risk waist circumference.Results. Consistent with other studies, our analyses showed that perceived unfair treatment was associated with increased abdominal obesity. Compared with Irish, Jewish, Polish, and Italian Whites who did not experience perceived chronic discrimination, Irish, Jewish, Polish, and Italian Whites who perceived chronic discrimination were 2 to 6 times more likely to have a high-risk waist circumference. No significant relationship between perceived discrimination and the obesity measures was found among the other Whites, Blacks, or Hispanics.Conclusions. These findings are not completely unsupported. White ethnic groups including Polish, Italians, Jews, and Irish have historically been discriminated against in the United States, and other recent research suggests that they experience higher levels of perceived discrimination than do other Whites and that these experiences adversely affect their health.It is estimated that 2 of every 3 adults in the United States are overweight or obese.^1,2 Obesity is a major risk factor for chronic health conditions, such as type 2 diabetes, coronary heart disease, hypertension, stroke, some forms of cancer, and osteoarthritis.³ Although it is widely accepted that high-fat diets and physical inactivity are preventable risk factors,⁴ obesity continues to increase.^1,2,5There is a growing interest in the relationship between psychosocial risk factors and excess body fat accumulation.^6–16 In particular, some evidence suggests that psychosocial stressors may play a role in disease progression in general and in excess body fat in particular.^7,8,17 The key factors underlying physiological reactions to psychosocial stress have not been completely elucidated, but McEwen and Seeman¹⁷ and others^7,18,19 posit that the continued adaptation of the physiological system to external challenges alters the normal physiological stress reaction pathways and that these changes are related to adverse health outcomes.^8,17,18,20 For example, in examining the association between psychosocial stress and excess body fat accumulation, Björntorp and others have suggested that psychosocial stress is linked to obesity, especially in the abdominal area.^7,8Perceived discrimination, as a psychosocial stressor, is now receiving increased attention in the empirical health literature.^21–24 Such studies suggest perceived discrimination is inversely related to poor mental and physical health outcomes and risk factors, including hypertension,^24,25 depressive symptoms,^26–28 smoking,^29–31 alcohol drinking,^32,33 low birthweight,^34,35 and cardiovascular outcomes.^36–38Internalized racism, the acceptance of negative stereotypes by the stigmatized group,³⁹ has also been recognized as a race-related psychosocial risk factor.⁴⁰ Recent studies have also suggested that race-related beliefs and experiences including perceived discrimination might be potentially related to excess body fat accumulation. Three of these studies^9,13,41 showed that internalized racism was associated with an increased likelihood of overweight or abdominal obesity among Black Caribbean women in Dominica⁴¹ and Barbados¹³ and adolescent girls in Barbados.⁹ These researchers posit that individuals with relatively high levels of internalized racism have adopted a defeatist mindset, which is believed to be related to the physiological pathway associated with excess body fat accumulation. However, Vines et al.¹⁶ found that perceived racism was associated with lower waist-to-hip ratios among Black women in the United States. Although the assessment of race-related risk factors varied across these studies, the findings suggest that the salience of race-related beliefs and experiences may be related to excess body fat accumulation.Collectively, the results of these studies are limited. First, because they examined the relationship between race-related beliefs and experiences and excess body fat only among women, we do not know if this relationship is generalizable to men.^13,16,41 Second, these studies only examined this relationship among Blacks, even though perceived unfair treatment because of race/ethnicity has been shown to be adversely related to the health of multiple racial/ethnic population groups in the United States^42–49 and internationally.^27,50–55 Third, none of the studies have examined the relationship between excess body fat accumulation and perceived nonracial/nonethnic experiences of interpersonal discrimination. Some evidence suggests that the generic perception of unfair treatment or bias is adversely related to health, regardless of whether it is attributed to race, ethnicity, or some other reason.^45,55,56 Fourth, none of these studies included other measures of stress. We do not know if the association between race-related risk factors and obesity is independent of other traditional indicators of stress.Using a multiethnic, population-based sample of adults, we examined the association of perceived discrimination and obesity independent of other known risk factors for obesity, including stressful major life events. Additionally, because reports of perceived racial/ethnic discrimination and non-racial/ethnic discrimination vary by racial/ethnic groups^24,45,46,57 and because Whites tend to have less excess body fat than do Blacks and Hispanics,^1,3 we examined the relationships between perceived discrimination and excess body fat accumulation among Hispanics, non-Hispanic Whites, and non-Hispanic Blacks.     

Smoking cessation intervention for female prisoners: addressing an urgent public health need

Objectives. We tested the efficacy of a combined pharmacologic and behavioral smoking cessation intervention among women in a state prison in the southern United States.Methods. The study design was a randomized controlled trial with a 6-month waitlist control group. The intervention was a 10-week group intervention combined with nicotine replacement therapy. Two hundred and fifty participants received the intervention, and 289 were in the control group. Assessments occurred at baseline; end of treatment; 3, 6, and 12 months after treatment; and at weekly sessions for participants in the intervention group.Results. The intervention was efficacious compared with the waitlist control group. Point prevalence quit rates for the intervention group were 18% at end of treatment, 17% at 3-month follow-up, 14% at 6-month follow-up, and 12% at 12-month follow-up, quit rates that are consistent with outcomes from community smoking-cessation interventions.Conclusions. Female prisoners are interested in smoking cessation interventions and achieved point-prevalence quit rates similar to community samples. Augmenting tobacco control policies in prison with smoking cessation interventions has the potential to address a significant public health need.Smoking is the leading preventable cause of death in the United States.¹ Smoking prevalence and associated morbidity and mortality have decreased in the general US population; however, smoking prevalence remains 3 to 4 times higher among prisoners than in the nonincarcerated adult population.² The most common medical problems of prisoners are smoking related, including heart, circulatory, respiratory, kidney, and liver problems and diabetes.³ Medical care for prisoners consumes 11% of correctional budgets and is expected to double in 10 years, in part because of high rates of smoking and associated medical conditions.⁴ The continued high prevalence of smoking among prisoners has important public health implications because of the increasing incarceration rate in the United States,⁵ high prevalence of comorbid psychiatric and substance abuse disorders associated with nicotine dependence, and low natural rates of smoking cessation among prisoners.Among incarcerated men, 70%–80% are current smokers.^2,6–11 Smoking prevalence among incarcerated women ranges from 42% to 91%, 2 to 4 times higher than among women in the general population.^2,12,13 Prisoners are also more likely to have comorbid conditions—psychiatric disorders and substance dependence—associated with greater nicotine dependence and less likelihood of smoking cessation in the absence of intensive interventions.¹⁴Over the past 10 years, because of concerns about secondhand smoke, threats of litigation, and desires to protect employee and prisoner health, reduce prison health care expenditures, and limit prisoner amenities, correctional facilities have implemented smoking bans and restrictions. Smoking bans in prisons differ from smoking bans in other settings. Prisoners are confined and have no legitimate opportunities to smoke for the duration of their sentence. Hence, they have no recourse except to quit smoking—usually “cold turkey” and without smoking cessation treatment or nicotine replacement—or to obtain cigarettes or tobacco from the underground prison economy. Prison smoking bans often have unintended consequences: prisoners continue to smoke, and a thriving contraband economy grows to meet the demand for cigarettes.^8,9,15,16From a public health perspective, temporary cessation of smoking because of punitive smoking restrictions is different from “quitting” smoking.¹⁷ Indeed, 97% of people in a smoke-free jail returned to smoking within 6 months of release, suggesting that smoking bans or restrictions during incarceration are unlikely to have a marked effect on the lifetime prevalence of smoking.¹⁸ The National Commission on Correctional Health Care, in its 2002 report on the health status of soon-to-be-released inmates, recommended that all inmates be provided with a smoke-free environment and that smoking cessation programs be offered to staff members and inmates. Offering smoking cessation programs along with smoking restrictions might increase the likelihood of tobacco control in the prison environment and sustained smoking cessation after release.¹⁹ However, the need for smoking cessation interventions shown to be effective in correctional settings remains virtually ignored, despite the enormous human, health, and economic costs of smoking among prisoners.^13,19,20Among the burgeoning literature on smoking cessation with other populations, we could locate only 2 published papers of smoking cessation interventions with prisoners. Edinger et al. conducted 2 small studies of self-control procedures for smoking cessation among male prisoners.²¹ Their studies had methodological limitations, including small sample sizes (N = 14 and N = 28), significant treatment attrition, and lack of biological verification of treatment outcomes. Richmond et al. reported a pilot study with 30 male prisoners who received 2 sessions of cognitive–behavioral counseling, nicotine replacement therapy, buproprion, and self-help materials.²² Self-reported smoking verified through levels of expired carbon monoxide (CO) was assessed 6-months after intervention. At 6 months, 26% had verified point-prevalence abstinence, and 22% had continuous abstinence. Overall, these studies are notable for their small sample sizes and focus on male prisoners.To our knowledge, our study is the first-ever randomized clinical trial of smoking cessation with female prisoners. We examined the efficacy of a combined behavioral and pharmacologic intervention compared with a waitlist control group. The study was designed to overcome the limitations of previous studies and to focus on female prisoners. We anticipated that the group exposed to the intervention would have superior quit rates at all time points compared with the waitlist control group.     

First-Trimester Working Conditions and Birthweight: A Prospective Cohort Study

Objectives. We investigated the relationship between women''s first-trimester working conditions and infant birthweight.Methods. Pregnant women (N = 8266) participating in the Amsterdam Born Children and Their Development study completed a questionnaire gathering information on employment and working conditions. After exclusions, 7135 women remained in our analyses. Low birthweight and delivery of a small-for-gestational-age (SGA) infant were the main outcome measures.Results. After adjustment, a workweek of 32 hours or more (mean birthweight decrease of 43 g) and high job strain (mean birthweight decrease of 72 g) were significantly associated with birthweight. Only high job strain increased the risk of delivering an SGA infant (odds ratio [OR] = 1.5; 95% confidence interval [CI] = 1.1, 2.2). After adjustment, the combination of high job strain and a long workweek resulted in the largest birthweight reduction (150 g) and the highest risk of delivering an SGA infant (OR = 2.0; 95% CI = 1.2, 3.2).Conclusions. High levels of job strain during early pregnancy are associated with reduced birthweight and an increased risk of delivering an SGA infant, particularly if mothers work 32 or more hours per week.Delivery of a low-birthweight or small-for-gestational-age (SGA) infant as a result of fetal growth restriction is one of the principal adverse pregnancy outcomes. In the short term, low birthweight and small size for gestational age are major determinants of infant mortality and morbidity¹ and impaired neonatal development.² In the long term, they increase metabolic and cardiovascular disease risk.^3–5 Prevention of fetal growth restriction is therefore of undisputed clinical and economic importance.Maternal factors, obstetric factors (e.g., placental dynamics), and social factors,⁵ including employment-related factors, can all play a role in fetal growth impairment.^6–24 Although employment in general is associated with enhanced outcomes,^6,20,21 certain working conditions represent potential risk factors for the mother and child. Increased levels of risk resulting from long working hours,^{12,13,17,18,24} high physical workloads,^13–16 prolonged standing,^13,18 and psychosocial job strain^7,9,10,24 have been suggested, but the findings in this area are not unequivocal.^8,11,22,23 So far, 2 reviews have been conducted that focused on physical workload and delivery of an SGA infant. Mozurkewich et al.¹⁶ concluded from their review of 29 studies that physically demanding work is associated with SGA births (pooled odds ratio [OR] = 1.37; 95% confidence interval [CI] = 1.30, 1.44). Bonzini et al.¹⁹ reached the same conclusion in their study. To our knowledge, job strain has not been considered in any published review.Limitations in research designs,^6,8,19–21 variability in definitions and measurement of work-related factors,^6,18–20 and true variability across countries and cultures may account for the inconsistent results observed to date. Another important limitation of occupational hazard research is the focus on third-trimester exposures.^11,13 Experimental data and emerging theory point to the first rather than the second or third trimester as a crucial period for regulating the relevant fetal hormonal set points, in particular the hypothalamic pituitary axis (HPA).^25–27 Stress-dependent dysregulation of the HPA affects birthweight and a child''s subsequent growth and development.^25–31 From this perspective, employment during pregnancy is perhaps the most prevalent potential stress factor, given that few working women quit their jobs early in pregnancy.In an effort to overcome the limitations of previous studies, we explored the association between infant birthweight and employment-related conditions (e.g., hours worked per week, hours standing or walking, physical demands of work, and job strain) in an unselected urban cohort of pregnant women. We hypothesized that after adjustment for all known major cofactors, first-trimester work-related effects on birthweight would exceed the third-trimester effects reported in previous research.     

Life-Course Socioeconomic Position and Incidence of Diabetes Mellitus Among Blacks and Whites: The Alameda County Study, 1965�C1999

Objectives. We examined associations between several life-course socioeconomic position (SEP) measures (childhood SEP, education, income, occupation) and diabetes incidence from 1965 to 1999 in a sample of 5422 diabetes-free Black and White participants in the Alameda County Study.Methods. Race-specific Cox proportional hazard models estimated diabetes risk associated with each SEP measure. Demographic confounders (age, gender, marital status) and potential pathway components (physical inactivity, body composition, smoking, alcohol consumption, hypertension, depression, access to health care) were included as covariates.Results. Diabetes incidence was twice as high for Blacks as for Whites. Diabetes risk factors independently increased risk, but effect sizes were greater among Whites. Low childhood SEP elevated risk for both racial groups. Protective effects were suggested for low education and blue-collar occupation among Blacks, but these factors increased risk for Whites. Income was protective for Whites but not Blacks. Covariate adjustment had negligible effects on associations between each SEP measure and diabetes incidence for both racial groups.Conclusions. These findings suggest an important role for life-course SEP measures in determining risk of diabetes, regardless of race and after adjustment for factors that may confound or mediate these associations.Diabetes mellitus is a major cause of morbidity and mortality in the United States.^1,2 Type 2 diabetes disproportionately affects Hispanics, as well as non-Hispanic Black Americans, American Indians/Alaska Natives, and some Asian/Pacific Islander groups. In the United States, members of racial and ethnic minority groups are almost twice as likely to develop or have type 2 diabetes than are non-Hispanic Whites.^2–5 Significant racial and ethnic differences also exist in the rates of diabetes-related preventive services, quality of care, and disease outcomes.^6–10Researchers have attempted to determine why, relative to Whites, members of racial and ethnic minority groups are disproportionately affected by diabetes. For example, compared with White Americans, Black Americans are presumed to have stronger genetic^5,11 or physiological^11–13 susceptibility to diabetes, or greater frequency or intensity of known diabetes risk factors, such as obesity, physical inactivity, and hypertension.^14–17Black Americans also are more likely than are White Americans to occupy lower socioeconomic positions.¹⁸ Low socioeconomic position (SEP) across the life course is known to influence the prevalence^19–24 and incidence^3,19,25–30 of type 2 diabetes. The risk of diabetes also is greater for people who are obese,^3,17,31 physically inactive,^3,32 or have hypertension,^33,34 all of which are conditions more common among people with lower SEP.^16,35–37Several studies have focused on the extent to which socioeconomic factors, body composition (i.e., weight, height, body mass index, and waist circumference), and behaviors explain the excess risk of diabetes attributed to race.^4,12,19,30 For example, 2 separate studies, one with data from the Health and Retirement Study¹⁹ and the other with data from the Atherosclerosis Risk in Communities Study,³⁰ used race to predict diabetes incidence. Attempting to separate the direct and indirect effects of race on diabetes,³⁸ these studies assessed, via statistical adjustment, which socioeconomic measures and diabetes-related risk factors, when adjusted, could account for the excess risk among Black participants relative to White participants.^19,30 Adjustment for education lessened the effect of Black race on diabetes incidence in the Atherosclerosis Risk in Communities Study.³⁰ In the Health and Retirement Study, excess risk attributed to Black race was not explained by early-life socioeconomic disadvantage, but it was reduced after adjustment for education and later-life economic resources.¹⁹ The validity of this analytic approach has been challenged, however, because the socioeconomic measures used were assumed to have the same meaning across all racial/ethnic groups, a questionable assumption³⁸ in the United States, especially in 1965.We sought to explore the predictive effects of several life-course socioeconomic factors on the incidence of diabetes among both Black and White Americans. We examined demographic confounders (age, gender, marital status) and diabetes risk factors (obesity, large waist circumference, physical inactivity, high blood pressure, depression, access to health care) as possible mediators of the observed associations between SEP and incident diabetes (i.e., the development of new cases of diabetes over time).     

Epidemiology of Hepatitis C Virus in Pennsylvania State Prisons, 2004–2012: Limitations of 1945–1965 Birth Cohort Screening in Correctional Settings

Objectives. We described hepatitis C virus antibody (anti-HCV) prevalence in a state prison system and retrospectively evaluated the case-finding performance of targeted testing of the 1945 to 1965 birth cohort in this population.Methods. We used observational data from universal testing of Pennsylvania state prison entrants (June 2004–December 2012) to determine anti-HCV prevalence by birth cohort. We compared anti-HCV prevalence and the burden of anti-HCV in the 1945 to 1965 birth cohort with that in all other birth years.Results. Anti-HCV prevalence among 101 727 adults entering prison was 18.1%. Prevalence was highest among those born from 1945 to 1965, but most anti-HCV cases were in people born after 1965. Targeted testing of the 1945 to 1965 birth cohort would have identified a decreasing proportion of cases with time.Conclusions. HCV is endemic in correctional populations. Targeted testing of the 1945 to 1965 birth cohort would produce a high yield of positive test results but would identify only a minority of cases. We recommend universal anti-HCV screening in correctional settings to allow for maximum case identification, secondary prevention, and treatment of affected prisoners.HCV is the most common blood-borne viral infection in the United States, with an estimated 4.1 million persons having been exposed to the virus, and 3.2 million people, or about 1.3% of the population, having chronic HCV infection.1 Although overall HCV prevalence in the United States is declining,2 recently there have been multiple reports of outbreaks among young people, predominantly in suburban and rural areas.3–5 The primary mode of HCV transmission is injection drug use,6 and as a result, HCV disproportionately affects people in contact with the criminal justice system.7 An estimated 17.4% of US state prisoners were HCV antibody positive (anti-HCV positive) in 2006, and perhaps 28.5% to 32.8% of the US case burden was in contact with the criminal justice system in that year.8People may be infected with HCV for several decades without symptoms. At least half of the affected individuals in the United States are unaware of their infection9 and thus are unable to receive treatment. Without treatment, HCV infection can lead to cirrhosis, chronic liver disease, and hepatocellular carcinoma.10–12 At current treatment rates, HCV will kill nearly 380 000 people in the United States by 2030 and more than 1 million by 2060.13Until recently, the Centers for Disease Control and Prevention (CDC) recommended HCV testing only for people with known or at high risk for past or current HCV exposure, including people who had ever injected drugs, who had certain medical conditions, or who had received blood transfusions or blood products before HCV screening of such products became routine.14 In recognition of the urgent need to diagnose and treat extant infections and reduce HCV-related mortality, in 2012 the CDC also recommended 1-time HCV testing of all people born between 1945 and 1965.14 This birth cohort was selected on the basis of findings from the National Health and Nutrition Examination Survey (NHANES). NHANES is an ongoing nationally representative survey of the civilian, noninstitutionalized population. NHANES data from 1999 to 2008 indicated that 81.6% of anti-HCV–positive people in the United States were born between 1945 and 1965.15 However, an acknowledged limitation of the NHANES data in assessing the epidemiology of HCV is the exclusion of incarcerated people from the sample.1 As such, it is unclear how applicable the 1945 to 1965 birth cohort screening recommendation may be for prisoner populations.The Federal Bureau of Prisons now recommends HCV antibody testing for all inmates who request a test or report risk factors for infection.16 This approach assumes that inmates will reliably report a history of injection drug use, but concerns about self-incrimination and confidentiality may prevent this disclosure. Although 1 study has reported success in using risk-based testing to identify acute HCV in an incarcerated population,17 that study did not assess the proportion of all chronic HCV cases identified by risk-based testing. Analysis of data from a large representative sample of prison entrants found that testing only those inmates who reported injection drug use would have identified 56% of anti-HCV–positive women and just 35% of anti-HCV–positive men.18Given the high anti-HCV prevalence and limited case-finding performance of risk-based HCV screening in correctional settings, universal screening has been suggested as an alternative approach.19 If, however, HCV infection in the correctional population is concentrated in the 1945 to 1965 birth cohort, targeting testing toward this group may be an efficient and cost-effective approach to HCV case finding.20 Limited recent epidemiological data on HCV prevalence in correctional settings hamper evaluation of these different approaches to HCV testing. We present data from universal HCV screening on entry to state prisons in Pennsylvania and consider the case-finding performance of the CDC 1945 to 1965 birth cohort recommendation in this setting.     

Health Among Caregivers of Children With Health Problems: Findings From a Canadian Population-Based Study

Objectives. We used population-based data to evaluate whether caring for a child with health problems had implications for caregiver health after we controlled for relevant covariates.Methods. We used data on 9401 children and their caregivers from a population-based Canadian study. We performed analyses to compare 3633 healthy children with 2485 children with health problems. Caregiver health outcomes included chronic conditions, activity limitations, self-reported general health, depressive symptoms, social support, family functioning, and marital satisfaction. Covariates included family (single-parent status, number of children, income adequacy), caregiver (gender, age, education, smoking status, biological relationship to child), and child (age, gender) characteristics.Results. Logistic regression showed that caregivers of children with health problems had more than twice the odds of reporting chronic conditions, activity limitations, and elevated depressive symptoms, and had greater odds of reporting poorer general health than did caregivers of healthy children.Conclusions. Caregivers of children with health problems had substantially greater odds of health problems than did caregivers of healthy children. The findings are consistent with the movement toward family-centered services recognizing the link between caregivers'' health and health of the children for whom they care.Caring for a child with health problems can entail greater than average time demands,^1,2 medical costs,^3,4 employment constraints,^5,6 and childcare challenges.^6–8 These demands may affect the health of caregivers, a notion supported by a variety of small-scale observational studies that have shown increased levels of stress, distress, emotional problems, and depression among caregivers of children with health problems.^1,2,5,9–12Whether these problems are caused by the additional demands of caring for children with health problems or by confounding variables is difficult to answer definitively. The literature reports the identification of a variety of factors purported to be associated with caregiver health, including contextual factors such as socioeconomic status^13–17; child factors such as level of disability,^{1,11,13,18–21} presence of behavior problems,^22–25 and overall child adjustment²⁶; and caregiver-related characteristics such as coping strategies^11,22,27 and support from friends and family.^15,17,28,29 In general, this work has been based on small clinic-based samples^9,30 or specific child populations (e.g., cerebral palsy,^5,25 attention-deficit/hyperactivity disorder^31,32), and typically has been hampered by limited generalizability and a lack of careful, multivariate analysis. Furthermore, most studies have focused on caregivers'' psychological health,^1,2,5,9–12 although physical health effects may also exist among caregivers.^5,19,25,33One of the few studies to involve large-scale, population-based data compared the health of 468 caregivers of children with cerebral palsy to the health of a population-based sample of Canadian parents.⁵ The study showed that caregivers of children with cerebral palsy had poorer health on a variety of physical and psychological health measures. Furthermore, the data were consistent with a stress process model,^5,25 which proposes that additional stresses associated with caring for a child with cerebral palsy directly contribute to poorer caregiver health. However, these findings were based on a specific subpopulation of caregivers and univariate comparisons that could not control for potentially important confounders such as variation in caregiver education, income, and other demographic factors.We used population-based data to test the hypothesis that the health of caregivers of children with health problems would be significantly poorer than that of caregivers of healthy children, even after we controlled for relevant covariates. Our approach of using large-scale, population-based data representing a broad spectrum of childhood health problems³⁴ makes 4 key contributions to the current literature. First, our use of population-based data rather than small-scale, clinic-based studies yielded results that are potentially generalizable to a wide group of caregivers caring for children with health problems. Second, our examination of children with and without health problems allowed us to examine caregiver health effects across a wide variety of caregiving situations. Third, consideration of physical health outcomes (in addition to more regularly studied psychological outcomes) increased our knowledge of the breadth of caregiver health issues. Finally, controlling for relevant covariates allowed us to rule out a number of alternative explanations for caregiver health effects.     

Walking and Cycling to Health: A Comparative Analysis of City, State, and International Data

Objectives. We sought to determine the magnitude, direction, and statistical significance of the relationship between active travel and rates of physical activity, obesity, and diabetes.Methods. We examined aggregate cross-sectional health and travel data for 14 countries, all 50 US states, and 47 of the 50 largest US cities through graphical, correlation, and bivariate regression analysis on the country, state, and city levels.Results. At all 3 geographic levels, we found statistically significant negative relationships between active travel and self-reported obesity. At the state and city levels, we found statistically significant positive relationships between active travel and physical activity and statistically significant negative relationships between active travel and diabetes.Conclusions. Together with many other studies, our analysis provides evidence of the population-level health benefits of active travel. Policies on transport, land-use, and urban development should be designed to encourage walking and cycling for daily travel.Many nations throughout the world have experienced large increases in obesity rates over the past 30 years.^1,2 The World Health Organization estimates that more than 300 million adults are obese,³ putting them at increased risk for diseases such as diabetes, hypertension, cardiovascular disease, gout, gallstones, fatty liver, and some cancers.^4,5 Several studies have linked the increase in obesity rates to physical inactivity^6–8 and to widespread availability of inexpensive, calorie-dense foods and beverages.^1,9The importance of physical activity for public health is well established. A US Surgeon General''s report in 1996, Physical Activity and Health,¹⁰ summarized evidence from cross-sectional studies; prospective, longitudinal studies; and clinical investigations. The report concluded that physical inactivity contributes to increased risk of many chronic diseases and health conditions. Furthermore, the research suggested that even 30 minutes per day of moderate-intensity physical activity, if performed regularly, provides significant health benefits. Subsequent reports have supported these conclusions.^11–13The role of physical activity in prevention of weight gain is well documented.¹⁴ Strong evidence from cross-sectional studies has established an inverse relationship between physical activity and body mass index.^15,16 In addition, longitudinal studies have shown that exercisers gain less weight than do their sedentary counterparts.^6,8 Thus, the obesity epidemic may be explained partly by declining levels of physical activity.^1,17,18A growing body of evidence suggests that differences in the built environment for physical activity (e.g., infrastructure for walking and cycling, availability of public transit, street connectivity, housing density, and mixed land use) influence the likelihood that people will use active transport for their daily travel.^19,20 People who live in areas that are more conducive to walking and cycling are more likely to engage in these forms of active transport.^21–25 Walking and cycling can provide valuable daily physical activity.^26–30 Such activities increase rates of caloric expenditure,³¹ and they generally fall into the moderate-intensity range that provides health benefits.^32–35 Thus, travel behavior could have a major influence on health and longevity.^29,30,36,37Over the past decade, researchers have begun to identify linkages between active travel and public health.^38–40 Cross-sectional studies indicate that walking and cycling for transport are linked to better health. The degree of reliance on walking and cycling for daily travel differs greatly among countries.^39,41 European countries with high rates of walking and cycling have less obesity than do Australia and countries in North America that are highly car dependent.²⁶ In addition, walking and cycling for transport are directly related to improved health in older adults.⁴² The Coronary Artery Risk Development in Young Adults Study found that active commuting was positively associated with aerobic fitness among men and women and inversely associated with body mass index, obesity, triglyceride levels, resting blood pressure, and fasting insulin among men.^26,39,41,43Further evidence of the link between active commuting and health comes from prospective, longitudinal studies.⁴⁴ Matthews et al. examined more than 67 000 Chinese women in the Shanghai women''s health study and followed them for an average of 5.7 years.³⁷ Women who walked (P < .07) and cycled (P < .05) for transport had lower rates of all-cause mortality than did those who did not engage in such behaviors. Similarly, Andersen et al. observed that cycling to work decreased mortality rates by 40% among Danish men and women.³⁶ A recent analysis of a multifaceted cycling demonstration project in Odense, Denmark, reported a 20% increase in cycling levels from 1996 to 2002 and a 5-month increase in life expectancy for males.⁴⁵We analyzed recent evidence from a variety of data sources that supports the crucial relationship between active travel, physical activity, obesity, and diabetes. We used city- and state-level data from the United States and national aggregate data for 14 countries to determine the magnitude, direction, and statistical significance of each relationship.