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.     

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.     

Ethnic Density Effects on Birth Outcomes and Maternal Smoking During Pregnancy in the US Linked Birth and Infant Death Data Set

Objectives. We investigated whether mothers from ethnic minority groups have better pregnancy outcomes when they live in counties with higher densities of people from the same ethnic group—despite such areas tending to be more socioeconomically deprived.Methods. In a population-based US study, we used multilevel logistic regression analysis to test whether same-ethnic density was associated with maternal smoking in pregnancy, low birthweight, preterm delivery, and infant mortality among 581 151 Black and 763 201 Hispanic mothers and their infants, with adjustment for maternal and area-level characteristics.Results. Higher levels of same-ethnic density were associated with reduced odds of infant mortality among Hispanic mothers, and reduced odds of smoking during pregnancy for US-born Hispanic and Black mothers. For Black mothers, moderate levels of same-ethnic density were associated with increased risk of low birthweight and preterm delivery; high levels of same ethnic density had no additional effect.Conclusions. Our results suggest that for Hispanic mothers, in contrast to Black mothers, the advantages of shared culture, social networks, and social capital protect maternal and infant health.Numerous studies have shown that living in a socioeconomically deprived neighborhood exerts a contextual effect on the health of individual residents beyond their own socioeconomic status.^1,2 This is likely to have a differential impact on some ethnic minority groups, such as African Americans and Hispanics. (Throughout this paper we have defined “ethnicity” as a global indicator of a person''s heritage including both racial and ethnic origins.) Whereas the majority of poor White people live in nondeprived areas, poor African Americans are concentrated in areas of high poverty.³ Thus, it might be paradoxical to suggest that members of ethnic minority groups might be healthier when they live in areas with a high concentration of people of the same ethnicity.^4,5 However, there is some evidence that living in communities that contain proportionally more people from the same ethnic group is protective for some health outcomes, once material deprivation is accounted for. The evidence for the protective effects of same-ethnic density is strongest for mental health,^4,5 with the evidence for maternal and infant health outcomes more mixed.The majority of studies that have investigated the impact of same-ethnic density on maternal and infant health have focused on African Americans or Black families (in this article, we use whichever term was used in the studies we describe). Two older ecological studies^6,7 found that increasing levels of same-ethnic density for New York City African Americans were associated with increased fetal and neonatal mortality but not postneonatal mortality. Another study found no association between ethnic density measured in US cities and postneonatal mortality.⁸ More recent studies have tended to use multilevel analyses that controlled for individual-level measures of socioeconomic status, and focused on measures of morbidity, such as low birthweight (LBW), with less consistent results.^9–14One study of Chicago neighborhoods found that an increasing proportion of African American residents was associated with a reduced risk of LBW.¹³ Two other studies found that an increasing proportion of Black residents was associated with increased risk of LBW.^11,14 However, other studies have found no significant associations between same-ethnic density and LBW.^9,10,12Five studies have investigated the impact of ethnic density on preterm delivery rates among African Americans.^{9,10,12,15,16} Studies of neighborhoods in Minnesota⁹ and North Carolina¹⁵ found same-ethnic density to be associated with increased risk of preterm delivery after adjustment for individual but not area measures of socioeconomic circumstances. Three other studies found no association between same-ethnic density and preterm delivery in models that included individual-level maternal education and area-level measures of socioeconomic circumstances.^10,12,16We are aware of only 1 study that has investigated the impact of same-ethnic density on maternal smoking during pregnancy, which found that it was associated with reduced risk of maternal smoking after adjustment for both individual and area measures of socioeconomic conditions.¹⁷We found only 2 studies that have investigated the impact of ethnic density on Hispanic maternal and infant health. The first, conducted in the states of Arizona, California, New Mexico, and Texas, found lower rates of infant mortality for US-born Mexican-origin mothers living in counties with high concentrations of mothers of the same ethnicity.¹⁸ However, this effect was not found for mothers born outside the United States. The second study found no associations between same-ethnic density, as measured in Chicago census tracts, and LBW, preterm delivery, and maternal smoking after adjustment for economic disadvantage, maternal education, and violent crime.¹²Further support for the protective effects of Hispanic density comes from the “Hispanic paradox.”¹⁹ Compared with the White majority population, Hispanic mothers tend to have better or equal pregnancy outcomes and better health-related behaviors despite generally having more disadvantaged socioeconomic circumstances.^20–24 It has been proposed that this “paradox” can be explained by dietary factors, social support and cohesion, and cultural differences in relation to the importance of motherhood.^23,24 However, long-term US residents who move away from ethnic enclaves²⁵ are more likely to adopt Western health behaviors and values²⁶ and may lose any protective effects of Hispanic culture. Thus, the protective effects of Hispanic culture are more likely to be maintained in communities of higher Hispanic density.We hypothesized that maternal smoking during pregnancy, infant mortality, LBW, and preterm birth would be lower for non-Hispanic Black and Hispanic White (hereafter referred to as “Hispanic mothers”) mothers living in counties with a higher percentage of people of the same ethnicity, relative to their counterparts living in counties with a low percentage of people of the same ethnicity.     

The Long-Term Health Consequences of Relationship Violence in Adulthood: An Examination of Low-Income Women From Boston, Chicago, and San Antonio

Objectives. We examined the long-term health consequences of relationship violence in adulthood.Methods. Using data from the Welfare, Children, and Families project (1999 and 2001), a probability sample of 2402 low-income women with children living in disadvantaged neighborhoods in Boston, Massachusetts; Chicago, Illinois; and San Antonio, Texas, we predicted changes in the frequency of intoxication, psychological distress, and self-rated health over 2 years with baseline measures of relationship violence and a host of relevant background variables.Results. Our analyses showed that psychological aggression predicted increases in psychological distress, whereas minor physical assault and sexual coercion predicted increases in the frequency of intoxication. There was no evidence to suggest that relationship violence in adulthood predicted changes in self-rated health.Conclusions. Experiences with relationship violence beyond the formative and developmental years of childhood and adolescence can have far-reaching effects on the health status of disadvantaged urban women.Over the past 2 decades, numerous studies have examined the long-term health consequences of relationship violence during childhood. This body of research suggests that physical and sexual abuse in early life can be devastating to health in adulthood, contributing to poor mental^1–6 and physical health^3–5,7 and to higher rates of substance abuse.^5,6,8,9 These patterns are remarkably consistent across studies and notably persistent through the life course. In a recent study of more than 21 000 older adults, Draper et al.³ reported that physical and sexual abuse before 15 years of age is associated with poor mental and physical health well into late life.Although previous research has made significant contributions to our understanding of the lasting effects of abuse in early life, few studies have considered the long-term health consequences of relationship violence in adulthood. Our review of the literature revealed 5 longitudinal studies of relationship violence and health in adulthood. Not surprisingly, research suggests that women who experience relationship violence in adulthood are vulnerable to poor health trajectories, including increases in depressive symptoms,^10–12 functional impairment,^10,12 and alcohol consumption.^13,14Relationship violence is an important issue in all segments of society; however, studies consistently show that women of low socioeconomic status exhibit higher rates of intimate partner victimization than do their more affluent counterparts.^15–17 For example, Tolman and Raphael¹⁷ reported that between 34% and 65% of women receiving welfare report having experienced some form of relationship violence in their lifetime, and between 8% and 33% experience some form of relationship violence each year, levels that surpass those for women overall.¹⁸ Research also shows that residence in disadvantaged neighborhoods^19,20 and the presence of children in the household^21,22 may elevate the odds of relationship violence. Given their high violence-risk profile, attention must be directed to the patterns and health consequences of intimate partner victimization in the lives of disadvantaged urban women with children.^23–25Building on previous research, we used data collected from a large probability sample of low-income women with children living in low-income neighborhoods in Boston, Massachusetts, Chicago, Illinois, and San Antonio, Texas, to predict changes in the frequency of intoxication, psychological distress, and self-rated health over 2 years with measures of relationship violence in early life and adulthood and a host of relevant background variables. In accordance with previous research, we expected that intimate partner victimization in adulthood would predict increases in psychological distress and the frequency of intoxication and decreases in self-rated health over the study period.     

Social gradients in oral health in older adults: findings from the English longitudinal survey of aging

Objectives. We examined prospective associations between socioeconomic position (SEP) markers and oral health outcomes in a national sample of older adults in England.Methods. Data were from the English Longitudinal Survey of Aging, a national cohort study of community-dwelling people aged 50 years and older. SEP markers (education, occupation, household income, household wealth, subjective social status, and childhood SEP) and sociodemographic confounders (age, gender, and marital status) were from wave 1. We collected 3 self-reported oral health outcomes at wave 3: having natural teeth (dentate vs edentate), self-rated oral health, and oral impacts on daily life. Using multivariate logistic regression models, we estimated associations between each SEP indicator and each oral health outcome, adjusted for confounders.Results. Irrespective of SEP marker, there were inverse graded associations between SEP and edentulousness, with proportionately more edentate participants at each lower SEP level. Lower SEP was also associated with worse self-rated oral health and oral impacts among dentate, but not among edentate, participants.Conclusions. There are consistent and clear social gradients in the oral health of older adults in England, with disparities evident throughout the SEP hierarchy.The inverse linear relationship between socioeconomic position (SEP) and health is well established.^1–4 The uneven distribution of health across socioeconomic strata has been observed in both industrialized and less developed countries and for most common diseases and causes of death.^1,5–8 In most cases, the association between SEP and health is characterized by a linear graded pattern, with people in each lower SEP category having successively worse levels of health and dying earlier than those that are better off, a characteristic known as the social gradient in health.⁹Although there is clear and consistent evidence about the existence of the social gradient in working-age adults,^10,11 studies in older adults are less consistent, with some showing attenuation of the gradient^12,13 and others reporting that it persisted^14,15 or even increased¹⁶ in magnitude.Oral health is particularly important at older ages with tooth loss shown to be independently associated with disability and mortality.^17–20 Oral health status in older people is also an important determinant of nutritional status.²¹Socioeconomic disparities in oral health have been consistently demonstrated for various indicators, mostly clinical and disease related^22–31 but also subjective measures of oral health and quality of life.^30,32–38 Some of these studies have explicitly assessed the existence of an oral health gradient,^{23,25–31,34–37} but almost all were carried out on adolescents and adults, with very few focusing on older people.^33,36 These few relevant studies are cross-sectional and inconclusive and have used a limited number of SEP indicators (typically, education and occupational class), thereby hindering any comprehensive analysis on the relationship between SEP and oral health.We addressed the gap in the literature about the existence of an oral health gradient at older ages by examining the prospective associations between a wide range of SEP indicators (education, occupation, household income, household wealth, subjective social status [SSS], and childhood SEP) and various oral health outcomes (presence of natural teeth, self-rated oral health, and oral impacts) in a national sample of older adults from the English Longitudinal Survey of Aging (ELSA). We explored whether there are any significant socioeconomic inequalities in oral health among older people in England and, if so, whether these take the form of a gradient.     

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).     

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.     

Differential Trends in Weight-Related Health Behaviors Among American Young Adults by Gender, Race/Ethnicity, and Socioeconomic Status: 1984�C2006

Objectives. We investigated temporal patterns from 1984 to 2006 in 6 weight-related health behaviors by using longitudinal data for multiple cohorts of young adults (aged 19–26 years) from the nationally representative Monitoring the Future Study.Methods. We used growth curve models to examine historical trends in 6 health behaviors: frequency of eating breakfast, eating green vegetables, eating fruit, exercising, watching television, and sleeping 7 hours each night. Variations across gender, race/ethnicity, and socioeconomic status were investigated.Results. Frequency of exercising was consistently lower among young adult women than young adult men over this 23-year period. Compared with White women, Hispanic women, and women from other race/ethnic groups, Black women showed declines in the frequency of exercise since 1984. In general, young adult women showed a marked increase in the frequency of eating breakfast over this period, although Black women did not show any net gains.Conclusions. Social disparities in body weight may increase because Black women, Hispanic women, and men with lower socioeconomic status show declining trends in positive weight-related health behaviors compared with White young adults with higher socioeconomic status.As the prevalence of obesity and overweight rises in the United States,^1–5 researchers continue to investigate a range of mechanisms by which people attain excessive body weight.^6–10 Agreement is growing that the source of the obesity epidemic lies in an environment that produces an energy gap,^11–15 where energy intake exceeds energy expenditure even by as little as 100 excess calories per day.^12,13 Yet, it is unclear whether this 100-calorie excess is a function of increased intake or decreased output (or some combination of both) in American activity and consumption behaviors over time.Limited data exist on trends in energy intake and energy expenditure among Americans over the past 3 decades, but the data that are available are nonetheless consistent with the rise in obesity observed over the same period. Between 1977 and 1996, Americans increased their total energy consumption by about 200 kcal/day.¹⁶ This was largely a result of increased consumption of snacks and soft drinks, particularly among young adults,^16,17 while vegetable and fruit consumption remained low.^18–21 These consumption behaviors have all been linked to excess weight gain.^22–25 The increased availability of inexpensive, energy-dense food and beverages^26–30 coupled with a lack of access to fresh fruits and vegetables^31,32 are some of the environmental factors that may contribute to these trends. The US population has also adopted an increasingly sedentary lifestyle^33–36 in an environment that is associated with a reduction in energy expenditure, including car-dependent neighborhoods that discourage walking and biking^37–41 and limited physical activity in schools.^28,42 On average, American youth spend over 30 hours per week watching television,⁴³ which is positively associated with being overweight, either through sedentary activity or through exposure to the marketing of poor-quality foods.^43–46 Modern lifestyles are increasingly characterized by skipping breakfast and sleeping less,^36,47–49 which have also been linked to energy imbalance.^50–56These reported trends in health behaviors, however, are based on data from repeated cross-sectional surveys^18,21,57 that were often conducted up to 5 years or more apart,^16,21,57 the results of which are typically reported in aggregate across a time span of 4 to 7 years.^20,57 Moreover, published articles frequently focus on trends in only 1 health behavior (e.g., fruit and vegetable consumption^18,20) and not the relative practice of energy consumption and expenditure behaviors among individuals over time. As a result, more detailed trends in health behaviors, particularly as they illustrate subtle changes in the balance of energy intake and output occurring annually among American young adults over the last quarter century, are poorly understood.Also, differences in these behaviors and their trends by gender, socioeconomic status (SES), and racial/ethnic background are not well described at a population level, even though well-documented health disparities in obesity by social position exist.^4,58–61 Using data from the National Health and Nutrition Examination Survey (1988–2002), one study found that non-Hispanic Blacks, persons in poverty, and those with less than a high school education were less likely to meet US Department of Agriculture fruit and vegetable guidelines than were non-Hispanic Whites and socioeconomically advantaged individuals.⁵⁷ However, these results were based on 2 cross-sectional data sets collected 5 years apart. Delva et al.¹⁰ used repeat cross-sectional data collected annually from secondary school students between 1986 and 2003 to report declining trends in the proportion of adolescents who ate breakfast or exercised regularly, with a lower prevalence among women, racial/ethnic minorities, and those with low SES. Trends in the frequency of these behaviors beyond the secondary school setting, however, remain largely undocumented.The purpose of our study was, first, to investigate long-term patterns in weight-related health behaviors among young adults (aged 19–26 years) over the past 23 years (1984–2006) and, second, to assess how these patterns varied by social position (race/ethnicity, gender, and SES). Analyses were based on longitudinal data for multiple cohorts of individuals with frequent repeat measures to better track historical changes in weight-related health behaviors over time. By focusing on young adults, we aimed to better understand how weight-related health behaviors have changed in this early period of the adult life course, when many adult health behavior patterns show their formative roots. The transition to adulthood (sometimes referred to as emerging or early adulthood) is a period when individuals are on their own typically for the first time, when life plans are put into action, and when distinctive life paths become more manifest.⁶² We hypothesized that the frequency of healthy behaviors would generally decline among young adults over this period, and that the rate of decline would be greater among those in disadvantaged social positions (women, Blacks, Hispanics, and those of lower SES).     

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.     

Effect of health care system distrust on breast and cervical cancer screening in Philadelphia, Pennsylvania

Objectives. We investigated whether health care system distrust is a barrier to breast and cervical cancer screening and whether different dimensions of distrust—values and competence—have different impacts on cancer screening.Methods. We utilized data on 5268 women aged 18 years and older living in Philadelphia, Pennsylvania, and analyzed their use of screening services via logistic and multinomial logistic regression.Results. High levels of health care system distrust were associated with lower utilization of breast and cervical cancer screening services. The associations differed by dimensions of distrust. Specifically, a high level of competence distrust was associated with a reduced likelihood of having Papanicolaou tests, and women with high levels of values distrust were less likely to have breast examinations within the recommended time period. Independent of other covariates, individual health care resources and health status were associated with utilization of cancer screening.Conclusions. Health care system distrust is a barrier to breast and cervical cancer screening even after control for demographic and socioeconomic determinants. Rebuilding confidence in the health care system may improve personal and public health by increasing the utilization of preventive health services.Cancer is a leading cause of death in the United States. Approximately 1.5 million Americans are diagnosed with cancer per year and 1 in 4 deaths are attributed to cancer.¹ Among women, an estimated 192 000 breast and 11 000 cervical cancer cases are detected each year, and in 2009 more than 40 000 women died of breast cancer and approximately 4000 of cervical cancer.¹ To effectively reduce the morbidity and mortality resulting from breast and cervical cancer, efforts need to be made to increase the proportion of women who comply with screening recommendations²; according to a recent report, a third of women are not in compliance with screening guidelines for breast cancer, and more than a fifth are not in compliance for cervical cancer.³ Our goal was to investigate whether health care system distrust (hereafter referred to as distrust) is a barrier to breast and cervical cancer screening.The late 20th century saw many changes in the theoretical underpinnings of research on health in general and women''s health in particular. The prevailing biomedical model was criticized for ignoring social determinants of health, such as social class, gender roles, and poverty,⁴ and health determinants models that incorporated multiple social, economic, and demographic dimensions were embraced.^5–7 The multiple determinants of health perspective emphasizes the relationships between socioeconomic factors and health outcomes,⁴ but the role of psychological factors (i.e., depression and distrust) in cancer screening has only recently been recognized.^8–11 Relatively little is known about whether distrust affects health outcomes, and specifically whether it influences cancer screening behaviors among women.¹¹Americans’ overall confidence in their health care system has declined markedly in recent decades. In 2010, only 34% of adults reported “a great deal” of confidence in the health system, down from over 70% in 1966.¹² More than 80% of Americans, however, held high levels of trust in their personal physicians or providers,¹³ a paradox that has been widely documented in the literature.^14–17 Previous studies suggest that trust in physicians is associated with seeking timely medical care, maintaining appropriate health care, and adhering to medical advice,^18–20 but it is unclear whether trust or its converse, distrust, affects the adoption of preventive health services among women.¹¹The emerging distrust research in health care shows that distrust is a multidimensional concept.^21–23 For example, Shea et al. used focus groups, pilot testing, and a telephone survey to develop a highly reliable 9-item distrust scale that includes 2 subscales: competence distrust and values distrust.²² Competence distrust is expected to be high when the quality of service fails to meet patient expectations and does not improve health. Values distrust is expected to be high when the integrity of the health care system is questioned (e.g., ethical issues, financial priorities, transparency of care). Although dimensions of distrust may influence the use of preventive health services in different ways, little research has addressed this issue explicitly.A range of individual characteristics has been found to be associated with the use of breast and cervical cancer screening, including age,^5,24 race/ethnicity,^11,25 socioeconomic factors,^5,24 marital status,^5,11,24 and availability and utilization of health care resources.^11,24 Access to insurance and health care providers is associated with higher likelihood of interaction with the health care system and has been hypothesized to be related to levels of distrust and to individuals’ health-related behaviors.²⁶ Personal health status has been found to be related to levels of distrust,²⁷ although the underlying causal mechanisms have not been well documented. Evidence concerning the association of health status with use of preventive health services is inconclusive.¹¹ An important contribution of our study is the investigation of the association of distinct aspects of distrust—values distrust and competence distrust—with receipt of 2 preventive health services for adult women: the Papanicolaou (Pap) test for cervical cancer and clinical breast examination to screen for breast cancer. We tested the following 2 hypotheses: after we controlled for individual socioeconomic and demographic characteristics, (1) high levels of distrust are associated with low utilization of cancer screening services and (2) the negative relationship between distrust and cancer screening utilization holds for the values and competence dimensions of distrust.     

Health inequalities in Rio de Janeiro, Brazil: lower healthy life expectancy in socioeconomically disadvantaged areas

Objectives. We investigated deprivation and inequalities in life expectancy and healthy life expectancy by location in Rio de Janeiro, Brazil.Methods. We conducted a health survey of 576 adults in 2006. Census tracts were stratified by income level and categorization as a slum. We determined health status by degree of functional limitation, according to the approach proposed by the World Health Organization. We calculated healthy life expectancies by Sullivan''s method with abridged life table.Results. We found the worst indicators in the slum stratum. The life expectancy at birth of men living in the richest parts of the city was 12.8 years longer than that of men living in deprived areas. For both men and women older than age 65 years, healthy life expectancy was more than twice as high in the richest sector as in the slum sector.Conclusions. Our analysis detailed the excess burden of poor health experienced by disadvantaged populations of Rio de Janeiro. Policy efforts are needed to reduce social inequalities in health in this city, especially among the elderly.Recent studies on health inequality have focused on individual characteristics such as education, income, or ethnicity, as well as group characteristics, to explain social and spatial variations in health.^1–7 Highlighting inequalities at the local level is especially important, because social and environmental conditions have been shown to be significant determinants of health status.⁸The majority of geographical health studies have analyzed mortality data, largely because they are readily accessible. However, increased longevity in developed countries has resulted in a greater emphasis on the quality of the later years.^9,10 A long life does not necessarily mean a healthy life, as an increase in years lived is often accompanied by an increase in chronic morbidity and disability.¹¹ As such, it is generally agreed upon that mortality indicators alone are insufficient to appropriately characterize the state of a population''s health.¹² Newer, more relevant indicators such as quality-adjusted life years and disability-adjusted life years, which combine mortality data with morbidity and disability data, provide methods to investigate and compare the burden of diseases.¹³Over the past 4 decades, different health indicators that consider morbidity, functional limitations, and disabilities along with mortality have been proposed.^14–16 A single measure of morbidity and mortality obtained by the Sullivan method (healthy life expectancy)¹⁷ has been the most frequently used.¹⁴ It estimates the number of years a person of a given population may expect to enjoy full health. Variations of this measure are established by different definitions of healthy, which are usually based on self-perceived health, long-term illness or disability, and functional or cognitive limitations.The summarized measures of morbidity and mortality obtained by the Sullivan method have been adopted for monitoring health inequalities in many developed countries.¹⁸ In the United Kingdom, the regional variation in healthy life expectancy (as measured by limiting long-standing illness) has been found to be much greater than are the regional variations in life expectancy.¹⁹ Studies in other countries have produced similar findings.^20,21 Substantial inequalities in healthy life years among persons aged 50 years were also found in European Union countries, with greater variation in healthy life expectancy than in life expectancy.²²In Brazil, differences in mortality across regions have been well documented, often with a steep north–south gradient.^23,24 These inequalities persist; the more prosperous southern states have lower infant mortality and higher life expectancies. Small-area variations in health indicators in large Brazilian cities are also evident, reflecting socioeconomic and environmental inequalities.^25–28In Rio de Janeiro, Brazil, mortality studies have established an association between adverse health outcomes and residential concentration of poverty. The worst health indicators were found in the sector of the city with the highest concentration of slum residents, which also had an extremely high homicide rate.²⁹ A geographic study in Goiânia, a newly urbanized city of Brazil, also detected a spatial cluster of violent deaths on its outskirts.³⁰ This cluster had a significantly higher proportion of people with the lowest educational level and income and the worst housing conditions in the city.Whether these conditions are associated with differences in quality of life for older adults has been less well studied. In Brazil, healthy life expectancy was estimated for the total adult population^31,32 and for the elderly in the city of São Paulo,³³ but this measure has not been used to monitor inequalities in quality of life among older persons.We examined deprivation and inequalities in total life expectancy and healthy life expectancy by location in the municipality of Rio de Janeiro. We calculated healthy life expectancy with the approach developed by the World Health Organization (WHO),³⁴ in which healthy status is established by degree of functional limitation, with data from a survey carried out in the city during 2006.     

Mortality risk associated with disability: a population-based record linkage study

Objectives. We assessed the association between mortality and disability and quantified the effect of disability-associated risk factors.Methods. We linked data from cross-sectional health surveys in the Netherlands to the population registry to create a large data set comprising baseline covariates and an indicator of death. We used Cox regression models to estimate the hazard ratio of disability on mortality.Results. Among men, the unadjusted hazard ratio for activities of daily living, mobility, or mild disability defined by the Organization for Economic Co-operation and Development at age 55 years was 7.85 (95% confidence interval [CI] = 4.36, 14.13), 5.21 (95% CI = 3.19, 8.51), and 1.87 (95% CI = 1.58, 2.22), respectively. People with disability in activities of daily living and mobility had a 10-year shorter life expectancy than nondisabled people had, of which 6 years could be explained by differences in lifestyle, sociodemographics, and major chronic diseases.Conclusions. Disabled people face a higher mortality risk than nondisabled people do. Although the difference can be explained by diseases and other risk factors for those with mild disability, we cannot rule out that more severe disabilities have an independent effect on mortality.Population aging is associated with an increase in the number of people who are disabled. This increase presents a challenge for society because elderly persons disabled in 1 or more domains of life are hospitalized more often,¹ need more medical and long-term care,^2–5 and face a higher risk of death than nondisabled persons do.^6–13Disablement refers to the impact that chronic and acute conditions have on people''s ability to perform tasks necessary for daily living and normal social functioning.¹⁴ In a broader context, the disablement process is described as a causal chain in which the progression of disease leads to functional limitations, loss of mobility, and eventually to inability to perform activities of daily living (ADLs).^14–17 Empirical studies have found numerous risk factors associated with disablement. These factors are usually seen as risks that increase the chance of developing a disability. The major underlying causes are (acute and progressive) chronic diseases,¹⁸ but other risk factors including sociodemographic factors (e.g., age, gender,¹⁹ socioeconomic status²⁰), behavioral factors (e.g., smoking),²¹ nutrition,²² physical activity,²³ comorbidity,¹⁸ self-rated health,²⁴ and cognitive impairment²⁵ are also associated with incident disability.Disability is most often assessed in cross-sectional studies without information on mortality. The few longitudinal studies that have been conducted tend to emphasize incident disability rather than the trajectory of disability following onset because of lack of statistical power.²⁶ Thus, although the onset of disability has been extensively researched, there has been far less investigation into the mortality risk associated with disability. In previous studies, the study populations were often limited to specific disease groups^9,12 or based on small sample sizes with few control variables.^{6–8,10,11,13} Moreover, the focus was often on other determinants of mortality rather than on disability. Nonetheless, disability has been found to be an independent predictor of death after adjustment for heart disease,⁹ depressive symptoms,¹⁰ physical activity,¹¹ socioeconomic status,¹³ or health status.¹⁰ However, no study has assessed the extent to which the relationship between disability and mortality can be explained by risk factors known to be associated with disablement. Assessment of this relationship may enhance understanding of the public health aspects of aging. If disability is found to be independently associated with mortality, developing strategies to prevent disability would not only increase disability-free life expectancy but also total life expectancy.We assessed the association between mortality and 3 disability measures reflecting different levels of disability severity. The linking of cross-sectional health surveys to municipal health registries in the Netherlands permitted the compilation of a large time-to-event data set with covariates measured at baseline.²⁷ We quantified the magnitude of the association between disability and mortality, unadjusted and adjusted for groups of risk factors. These risk factors included distal and proximal risk factors that may influence the speed of disablement.^28–31 We used hazard ratios (HRs) and life expectancy to summarize the association between disability and mortality.     

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.     

Neighborhoods and obesity in later life

Objectives. We examined the influence of neighborhood environment on the weight status of adults 55 years and older.Methods. We conducted a 2-level logistic regression analysis of data from the 2002 wave of the Health and Retirement Study. We included 8 neighborhood scales: economic advantage, economic disadvantage, air pollution, crime and segregation, street connectivity, density, immigrant concentration, and residential stability.Results. When we controlled for individual- and family-level confounders, living in a neighborhood with a high level of economic advantage was associated with a lower likelihood of being obese for both men (odds ratio [OR] = 0.86; 95% confidence interval [CI] = 0.80, 0.94) and women (OR = 0.83; 95% CI = 0.77, 0.89). Men living in areas with a high concentration of immigrants and women living in areas of high residential stability were more likely to be obese. Women living in areas of high street connectivity were less likely to be overweight or obese.Conclusions. The mechanisms by which neighborhood environment and weight status are linked in later life differ by gender, with economic and social environment aspects being important for men and built environment aspects being salient for women.Over the past few decades the prevalence of obesity has been rising for men and women across all age groups, including the elderly.¹ For example, in 2001 to 2002 in the United States, about 1 in 3 adults 60 years or older was obese.² This trend raises concerns because excess weight is associated with a number of chronic health conditions, including diabetes, high blood pressure, asthma, and arthritis.³ Moreover, obesity can have very important implications for publicly financed health care.⁴ Recent research suggests that a number of demographic, socioeconomic, and family factors⁵ influence obesity, but the role of the neighborhood context has not been fully explored.Excess weight results from an energy imbalance in which caloric intake exceeds energy expenditures, the latter closely related to physical activity. The neighborhood environment may influence energy intake (through its influence on food availability⁶) and energy expenditure (by facilitating or impeding physical activity). For example, the presence of supermarkets in the neighborhood is associated with higher fruit and vegetable intake,⁷ whereas eating at fast-food restaurants is associated with a high-fat diet and higher body mass index (BMI; weight in kilograms divided by height in meters squared).⁸ In terms of physical activity, individuals living in neighborhoods with less crime,^9–13 higher land-use mix,¹⁴ higher street connectivity,^11,14,15 higher residential density,^11,14 a greater number of destinations,^9,16 better aesthetics,^9,10,17 and sidewalks^10,12,17,18 tend to walk more often.^19,20Only a handful of studies linking neighborhood features to late-life obesity have focused on older adults.^{11,13,16,21–23} National studies are particularly lacking for the elderly. Yet evidence from national studies of adults of all ages suggests plausible connections between obesity and neighborhood factors. Using the 1990 to 1994 waves of the National Health Interview Survey, for example, Boardman et al.²⁴ found that adults residing in neighborhoods with a high concentration of poverty and in neighborhoods with a high percentage of Blacks were more likely to be obese. In another study, Robert and Reither²⁵ found that higher community socioeconomic disadvantage was related to higher BMI among women but not among men. Because these studies had very limited characterizations of the neighborhoods, the mechanism through which poor neighborhoods result in obesity remains unclear. It could be, for instance, that poor neighborhoods tend to have fewer supermarkets^26–28 and more-limited access to places for physical activity.^29,30Using a large, nationally representative survey, we examined the relationship between the economic, built, and social environments and weight status among men and women 55 years and older. We included 8 previously validated neighborhood scales reflecting neighborhood safety and segregation, concentration of immigrants, air pollution, residential stability, connectivity, density or access, and high and low neighborhood socioeconomic status.³¹ We modeled both obesity and overweight status by using multilevel modeling techniques in which we controlled for detailed individual- and family-level confounders.     

Effects of Different Types of Antismoking Ads on Reducing Disparities in Smoking Cessation Among Socioeconomic Subgroups

Objectives. We assessed which types of mass media messages might reduce disparities in smoking prevalence among disadvantaged population subgroups.Methods. We followed 1491 adult smokers over 24 months and related quitting status at follow-up to exposure to antismoking ads in the 2 years prior to the baseline assessment.Results. On average, smokers were exposed to more than 200 antismoking ads during the 2-year period, as estimated by televised gross ratings points (GRPs). The odds of having quit at follow-up increased by 11% with each 10 additional potential ad exposures (per 1000 points, odds ratio [OR] = 1.11; 95% confidence interval [CI] = 1.00, 1.23; P < .05). Greater exposure to ads that contained highly emotional elements or personal stories drove this effect (OR = 1.14; 95% CI 1.02, 1.29; P < .05), which was greater among respondents with low and mid-socioeconomic status than among high–socioeconomic status groups.Conclusions. Emotionally evocative ads and ads that contain personalized stories about the effects of smoking and quitting hold promise for efforts to promote smoking cessation and reduce socioeconomic disparities in smoking.Tobacco use inflicts the greatest burden of illness on those least able to afford it.^1,2 An enormous challenge for tobacco control is how to tackle the consistently higher levels of smoking prevalence found among disadvantaged groups,^3–5 especially because these gaps may be widening.^6,7 Televised antismoking campaigns provide an effective population-wide method of preventing smoking uptake,^8,9 promoting adult smoking cessation,¹⁰ and reducing adult smoking prevalence,¹¹ and research indicates that some types of ads may be more effective than others. Antismoking messages that produce strong emotional arousal, particularly personal stories or graphic portrayals of the health effects of smoking, tend to perform well¹²; they are perceived to be more effective than others, are more memorable, and generate more thought and discussion.^13–16 However, it is unclear whether different types of messages might maintain, increase, or mitigate the disparities in smoking prevalence across population subgroups.Research on subgroup differences in responses to a range of anti-tobacco ads has not found systematic differences by gender, race/ethnicity, or nationality.^13,17–19 A review of the literature on the use of mass media concluded that in comparison with their effects on other populations, campaigns have often been less effective, sometimes equally effective, but rarely more effective in promoting cessation among socioeconomically disadvantaged populations.²⁰ However, many of the less effective general-audience campaigns were hampered by minimal reach to smokers of low socioeconomic status (SES) because they were low-cost campaigns unable to afford extensive media exposure.²⁰Most research examining longer-term quit rates in the context of large-scale, well-funded antismoking campaigns found comparable quit rates or reductions in smoking prevalence in low- and high-SES groups.^21–28 However, to our knowledge, no population-based research has examined the relationship between the degree of exposure to different types of antismoking messages and quit rates between low- and high-SES groups.A variety of theories^29–38 provide guidance about which styles of ads may best encourage quitting, especially among members of lower socioeconomic groups. Consistent with these theories, reviews of the effects of antismoking advertising have concluded that advertisements that evoke strong emotional responses through negative visceral imagery or personal stories about the health effects of smoking can increase attention, generate greater recall and appeal, and influence smoking beliefs and intentions.^12,39,40 Recent research indicates that self-relevant emotional reactions (i.e., emotional reflections about one''s life, body, or behavior that are triggered by the ad⁴¹) may be especially persuasive, because they affect perceptions of future risk of becoming ill,⁴² which in turn have been linked with reduced cigarette consumption, increased intentions to quit, and quit attempts.⁴³Antismoking ads that use strong graphic imagery of the health effects of smoking are likely to be predominately associated with high negative emotional arousal, but personal stories of the consequences of smoking may evoke high or low levels of emotion depending on the particular story and the degree to which smokers relate to the characters.³⁸ However, less emotional personal testimonials may still be more effective than other types of less emotional ads because there is no explicit persuasive intent against which smokers may react^38,44 and because health information is presented in a story-based format, which people learn to process naturally from an early age.⁴⁵Because lower-SES groups tend to have a greater degree of resistance to messages from the health care sector,⁴⁶ lower health literacy levels,^47,48 greater likelihood of belief in myths about cancer risks and prevention,⁴⁹ and less perception that smoking increases a person''s chance of getting cancer,⁴⁸ we proposed that emotional messages and personal stories might be especially influential. Presenting antismoking messages in an emotional or personal testimonial format may convey health information to these smokers in a way that is difficult to discount, natural and easy to process, and likely to arouse emotions that lead to increased perceptions of susceptibility to smoking-related diseases and motivation to quit.^38,42,44Drawing on the only previous study to examine the effect on adult quitting of the degree of exposure to antismoking ads,¹⁰ we first hypothesized that when all types of advertisements were considered together, greater exposure to these antismoking ads would be associated with greater likelihood of quitting by follow-up. Our second hypothesis was that particular types of antismoking ads (those containing highly emotional elements or personal testimonials about the effects of smoking) would be associated with a greater chance of successful quitting by follow-up than would exposure to ads without these elements. Finally, we hypothesized that highly emotional or personal testimonial ads would be especially effective among lower-SES groups.     

Alcohol advertising at Boston subway stations: an assessment of exposure by race and socioeconomic status

Objectives. We investigated the frequency of alcohol ads at all 113 subway and streetcar stations in Boston and the patterns of community exposure stratified by race, socioeconomic status, and age.Methods. We assessed the extent of alcohol advertising at each station in May 2009. We measured gross impressions and gross rating points (GRPs) for the entire Greater Boston population and for Boston public school student commuters. We compared the frequency of alcohol advertising between neighborhoods with differing demographics.Results. For the Greater Boston population, alcohol advertising at subway stations generated 109 GRPs on a typical day. For Boston public school students in grades 5 to 12, alcohol advertising at stations generated 134 GRPs. Advertising at stations in low-poverty neighborhoods generated 14.1 GRPs and at stations in high-poverty areas, 63.6 GRPs.Conclusions. Alcohol ads reach the equivalent of every adult in the Greater Boston region and the equivalent of every 5th- to 12th-grade public school student each day. More alcohol ads were displayed in stations in neighborhoods with high poverty rates than in stations in neighborhoods with low poverty rates.Excessive alcohol use is the third-leading lifestyle-related cause of death in the United States.¹ Immediate health risks include unintentional injuries,² violence,^2,3 risky sexual behaviors,^4,5 miscarriage and stillbirth among pregnant women,^6,7 fetal alcohol syndrome,⁷ and alcohol poisoning.⁸ Long-term health risks include neurological,^9,10 cardiovascular,^11,12 and psychiatric problems,¹³ as well as an increased risk of cancer,^12,14 liver disease,^12,15,16 and pancreatitis.^12,17,18 Excessive alcohol use is also linked to a variety of social problems, including increased unemployment¹⁹ and frequency of violent crime and incarceration.^20,21 Drinking among underage youths is increasing.^22–25 Excessive alcohol use also has economic consequences. Alcohol-related health care utilization (e.g., motor vehicle crashes, fires), productivity losses, social welfare (e.g., food stamps), and criminal justice cost the United States an estimated $184.6 billion in 1998 alone.^12,26Alcohol advertising has historically been linked to increased consumption of alcohol in youths,^25,27–31 and a more recent study also shows an increase in consumption by adults.³² These data come from studies of advertising in a variety of media, including television, music video, public transit, and outdoor advertising.^25–31 Alcohol is disproportionately advertised in low-income neighborhoods^33,34 and in neighborhoods with a high proportion of racial and ethnic minorities.^32,34–36Studies have shown that people of color experience poorer health outcomes and shorter life expectancies than do Whites.³⁷ Individuals of lower socioeconomic status also have been found to have higher morbidity and mortality and more risk factors for heart disease and stroke than do people of higher socioeconomic status.³⁸ Minorities are more likely to live in poverty, which exacerbates the negative consequences of alcohol use.³⁹ Because racial and ethnic minorities and individuals of lower socioeconomic status are at a higher risk for poor health and have been identified as targets of alcohol advertising, it is critical that advertising policies change to protect these disadvantaged groups. Hackbarth et al. suggest that reducing alcohol consumption among disadvantaged groups through community intervention, such as banning alcohol advertising, would be one way to eliminate such health disparities.³⁶In 2007 Kwate et al. determined that Black neighborhoods in New York City had more advertising space than White neighborhoods and that these spaces were disproportionately used to market alcohol and tobacco products.³⁵ However, they did not find a significant relationship between median income and ad density, which suggests that relative affluence did not protect Black neighborhoods from targeted outdoor advertising.Advertising on public transportation has received little attention in the literature. In 2007, a report issued by the Marin Institute documented the advertising practices of 20 public transit agencies nationwide. The report found that 2 major cities, Boston, Massachusetts and New York City, lagged far behind other cities that had policies in place to protect children from alcohol advertising.²⁵ Chicago, Illinois; Los Angeles, California; San Francisco, California; Washington, DC; and other places explicitly prohibit alcohol advertising on public transit systems. For example, San Francisco imposes a $5000 per day fine for violating advertising policies.²⁵ By contrast, the Massachusetts Bay Transit Authority (MBTA), which serves the Boston area, has no such restrictions against alcohol advertising, although it claims to prohibit all “adult-oriented goods and services.” The MBTA bans advertising that features tobacco, violence, or nudity because they are considered inappropriate for viewing by minors.²⁵ It is disturbing that one of the largest cities in the United States has not yet adopted stricter policies to protect its riders from potentially harmful alcohol ads.In 2009, Nyborn et al. studied the frequency of alcohol advertising on MBTA train cars and found that alcohol advertisers were able to reach the equivalent of nearly half of all transit passengers each day.⁴⁰ These data showed that roughly 315 000 people, or 11% of the entire adult population in the greater Boston area (Suffolk, Middlesex, and Norfolk counties; total 2008 population = 2 841 374⁴¹) may be exposed to alcohol ads on the MBTA train lines alone. However, that study focused on ads on moving trains and did not consider the frequency of alcohol ads at train stations and how this frequency might differ between neighborhoods. We expanded the focus to include train stations to investigate whether alcohol advertising targeted particular socioeconomic or racial/ethnic groups.We aimed to (1) quantify exposure to alcohol advertising at MBTA train stations among adults in the greater Boston area and among Boston public school students in grades 5 to 12 and (2) compare the frequency of alcohol ads in different MBTA train stations to determine whether minority or poor populations were disproportionately exposed.     

Socioeconomic and ethnic differences in disease burden and disparities in physical function in older adults

Objectives. We investigated whether a greater burden of disease among poorer individuals and ethnic minorities accounted for socioeconomic and racial disparities in self-reported physical functioning among older adults.Methods. We used data from adults aged 60 years or older (n = 5556) in the Third National Health and Nutrition Examination Survey, 1988–1994 to test associations between education level, poverty index, and race/ethnicity and limitations in 11 functions. We adjusted for demographic features and measures of disease burden (comorbid conditions, smoking, hemoglobin level, serum albumin level, knee pain, body mass index, and skeletal muscle index).Results. Associations between education and functional limitations were attenuated after adjustment, but those with 0–8 years of education were more likely than those with 13 or more years of education to have limitations in 3 functions. Poverty was associated with a higher likelihood of limitations despite adjustment. The likelihood of limitations among non-Hispanic Blacks and Mexican Americans was similar to that of non-Hispanic Whites after adjustment.Conclusions. Socioeconomic disparities in functional limitations among older Americans exist independent of disease burden, whereas socioeconomic differences and disease burden account for racial disparities.Although the prevalence of disability among older adults in the United States has generally declined over the past decade, this trend has not extended to all segments of the population.^1–4 Disability among ethnic minorities and economically disadvantaged groups has not declined, resulting in widening ethnic and socioeconomic disparities.^5–11 Racial minorities and those who are economically disadvantaged are up to 3 times more likely to experience disability than are Whites and those who are not economically disadvantaged, respectively.^8,10,12,13 Achieving health equity has been a public policy priority, and collective interventions have been proposed.^12,14,15 Functional limitations in older adults are particularly important because of their prognostic and economic implications.¹⁶ Functional limitations predict further future decline in physical function,¹⁷ an increased risk of dementia,¹⁸ loss of independence, institutionalization, and mortality.^19–21According to the Institute of Medicine model of the enabling–disabling process, disability is a product of the complex interactions between a person and his or her psychological, social, and physical environments.²² In this context, functional limitations are partly a consequence of an individual''s burden of disease. Musculoskeletal conditions, chronic neurological and cardiopulmonary disorders, sensory and cognitive deficits, anemia, sarcopenia, and chronic pain may lead to functional limitations and disability. Many of the chronic health conditions that can affect physical functioning are more common among ethnic minorities and economically disadvantaged groups,^5,6,9–12 raising the question of whether a greater burden of disease can primarily explain the higher prevalence of functional limitations and disability in these groups.Previous studies of socioeconomic and ethnic disparities in functional limitations reported unadjusted data or data adjusted only for differences in demographic characteristics.^{10,11,23–27} Few studies have examined the role of differences in comorbid conditions, obesity, or smoking or simultaneously examined a range of indicators of disease burden.^6,9,28 We sought to determine whether socioeconomic and ethnic differences in functional limitations among noninstitutionalized older adults in the United States remain after adjusting for measures of disease burden.     

Suicidal Behavior Among Female Sex Workers in Goa, India: The Silent Epidemic

Objectives. We sought to study suicidal behavior prevalence and its association with social and gender disadvantage, sex work, and health factors among female sex workers in Goa, India.Methods. Using respondent-driven sampling, we recruited 326 sex workers in Goa for an interviewer-administered questionnaire regarding self-harming behaviors, sociodemographics, sex work, gender disadvantage, and health. Participants were tested for sexually transmitted infections. We used multivariate analysis to define suicide attempt determinants.Results. Nineteen percent of sex workers in the sample reported attempted suicide in the past 3 months. Attempts were independently associated with intimate partner violence (adjusted odds ratio [AOR] = 2.70; 95% confidence interval [CI] = 1.38, 5.28), violence from others (AOR = 2.26; 95% CI = 1.15, 4.45), entrapment (AOR = 2.76; 95% CI = 1.11, 6.83), regular customers (AOR = 3.20; 95% CI = 1.61, 6.35), and worsening mental health (AOR = 1.05; 95% CI = 1.01, 1.11). Lower suicide attempt likelihood was associated with Kannad ethnicity, HIV prevention services, and having a child.Conclusions. Suicidal behaviors among sex workers were common and associated with gender disadvantage and poor mental health. India''s widespread HIV-prevention programs for sex workers provide an opportunity for community-based interventions against gender-based violence and for mental health services delivery.Suicide is a public health priority in India. Rates of suicide in India are 5 times higher than in the developed world,^1,2 with particularly high rates of suicide among young women.^3–5 Verbal autopsy surveillance from southern India suggests that suicide accounts for 50% to 75% of all deaths among young women, with average suicide rates of 158 per 100 000.²Common mental disorders such as depressive and anxiety disorders, and social disadvantage such as gender-based violence and poverty, are major risk factors for suicide among women.^1,3,6–8 Although research from high-income countries shows that common mental disorders are a major contributor to the risk of suicidal behavior, their role is less clear in low- and middle-income countries in which social disadvantage has been found to be at least as important.^1,3,6–8 Gender disadvantage is increasingly seen as an important contributing factor to the high rates of suicide seen among women in Asia.^1,3,6,7 Gender-based violence is a common manifestation of gender disadvantage and has been linked with common mental disorders and suicide in population-based studies of women and young adults in Goa, India.^4,5,9 Lack of autonomy, early sexual debut, limited sexual choices, poor reproductive health, and social isolation are other manifestations of gender disadvantage.Sex work in India is common. An estimated 0.6% to 0.7% of the female adult urban population are engaged in commercial sexual transactions.¹⁰ Studies from developed nations have found a high prevalence of self-harming behaviors in people engaged in transactional sexual activity.¹¹ There is also growing evidence suggesting that HIV-positive individuals from traditionally stigmatized groups report higher rates of violence exposure and suicidal ideation.^12,13 Female sex workers in India are a traditionally stigmatized group, with high prevalence of HIV¹⁰ and levels of stigma and violence that relate to the context of their work.¹⁴ Yet, despite substantial investigation of their reproductive and sexual health needs, there is virtually no information on suicide and its determinants among female sex workers from low- and middle-income countries.¹⁵As demonstrated in the hierarchical conceptual framework outlined in Figure 1,^4,5,9 we hypothesized that gender disadvantage, sex work, and health factors together with factors indicative of social disadvantage are distal determinants of female sex workers'' vulnerability to suicidal behaviors,^4,5,9,15 the effects of which would be mediated though poor mental health.³ We studied the burden of suicidal behaviors in a cross-sectional sample of female sex workers in Goa, India. We explored the association of sociodemographic factors, type of sex work, sexual health, and gender disadvantage, with and without measures of poor mental health, on suicide attempts in the past 3 months.Open in a separate windowFIGURE 1A conceptual framework for social risk factors for suicide among female sex workers in India.Note. STI = sexually transmitted infection.     

Joint Effects of Structural Racism and Income Inequality on Small-for-Gestational-Age Birth

Objectives. We examined potential synergistic effects of racial and socioeconomic inequality associated with small-for-gestational-age (SGA) birth.Methods. Electronic medical records from singleton births to White and Black women in 10 US states and the District of Columbia (n = 121 758) were linked to state-level indicators of structural racism, including the ratios of Blacks to Whites who were employed, were incarcerated, and had a bachelor’s or higher degree. We used state-level Gini coefficients to assess income inequality. Generalized estimating equations models were used to quantify the adjusted odds of SGA birth associated with each indicator and the joint effects of structural racism and income inequality.Results. Structural racism indicators were associated with higher odds of SGA birth, and similar effects were observed for both races. The joint effects of racial and income inequality were significantly associated with SGA birth only when levels of both were high; in areas with high inequality levels, adjusted odds ratios ranged from 1.81 to 2.11 for the 3 structural racism indicators.Conclusions. High levels of racial inequality and socioeconomic inequality appear to increase the risk of SGA birth, particularly when they co-occur.In the United States, Black women are more than 1.5 times as likely as White women to give birth to a small-for-gestational-age (SGA) infant, typically defined as an infant with a birth weight below the 10th percentile for a given gestational age; such births increase the risk of neonatal morbidity and long-term deficits in growth and development.1 This disparity has persisted for decades and is not fully explained by differences in health behaviors or access to prenatal care.2–4 Although individual socioeconomic status attenuates some of the increase in risk experienced by Black women, residual disparities remain.5Racial discrimination may be a distinct and critical source of chronic stress among women of color, both during pregnancy and across the life course.6 Disparities in perinatal outcomes, including SGA birth, are of particular interest to researchers concerned with the potential health effects of discrimination. A growing body of research has identified the harmful effects of racial discrimination on the health of Blacks in the United States.7 Evidence suggests that discrimination may be at least partially responsible for the large and persistent disparities in morbidity and mortality that exist between Whites and Americans of color.8 Much of this research has focused on individual experiences of discrimination, but a relatively recent paradigm shift has begun to identify such experiences as part of a larger system of policies and practices that reinforce racial inequity.9This system refers to the concept of structural racism, defined as the exclusion of racial minorities from resources and opportunities (e.g., wealth, housing, education), effectively creating a health disadvantage.10 The historical legacy of racial oppression experienced by Black Americans9,11 and persistent differences in access to resources have resulted in a system of strong links between race and social class at the population level. Inequalities in health therefore are not driven by race or class alone,12 and disentangling the health effects of both racial and socioeconomic disadvantage continues to present conceptual and methodological difficulties.13Previous work highlighting the detrimental effects of structural racism on pregnancy outcomes, including infant size and gestational age at delivery, has been largely limited to analyses of neighborhood or metropolitan area contexts such as segregation patterns,14–19 deprivation,20–23 and crime,24 which may stem from, for example, discriminatory mortgage lending, population differences in buying power, and federal housing policies.25 Furthermore, studies that have considered contextual socioeconomic characteristics have produced inconsistent results in terms of the degree to which these factors explain racial disparities in adverse birth outcomes between neighborhoods.15,19,21It remains unknown whether structural racism measured at the state level is associated with SGA birth. In a recent investigation of structural racism and myocardial infarction, Lukachko et al. developed a series of state-level indicators intended to represent the systematic exclusion of people of color from access to resources, opportunities, and social mobility.26 Using similar indicators, we investigated the potential synergistic effects of state-level structural racism and socioeconomic inequality on the risk of SGA birth among White and Black women in a large US obstetrical cohort study. We aimed to describe the degree of structural racism across the study states, determine whether the effects of structural racism differed according to maternal race and across levels of income inequality, and quantify the risk of SGA birth associated with high levels of both racial and socioeconomic inequality.