Prevalence and Correlates of Smoking among Low-Income Adults Residing in New York City Public Housing Developments—2015

To guide targeted cessation and prevention programming, this study assessed smoking prevalence and described sociodemographic, health, and healthcare use characteristics of adult smokers in public housing. Self-reported data were analyzed from a random sample of 1664 residents aged 35 and older in ten New York City public housing developments in East/Central Harlem. Smoking prevalence was 20.8%. Weighted log-binomial models identified to be having Medicaid, not having a personal doctor, and using health clinics for routine care were positively associated with smoking. Smokers without a personal doctor were less likely to receive provider quit advice. While most smokers in these public housing developments had health insurance, a personal doctor, and received provider cessation advice in the last year (72.4%), persistently high smoking rates suggest that such cessation advice may be insufficient. Efforts to eliminate differences in tobacco use should consider place-based smoking cessation interventions that extend cessation support beyond clinical settings.     

Public Health Consequences of Terrorism on Maternal–Child Health in New York City and Madrid

Past research provides evidence for trajectories of health and wellness among individuals following disasters that follow specific pathways of resilience, resistance, recovery, or continued dysfunction. These individual responses are influenced by event type and pre-event capacities. This study was designed to utilize the trajectories of health model to determine if it translates to population health. We identified terrorist attacks that could potentially impact population health rather than only selected individuals within the areas of the attacks. We chose to examine a time series of population birth outcomes before and after the terrorist events of the New York City (NYC) World Trade Center (WTC) attacks of 2001 and the Madrid, Spain train bombings of 2004 to determine if the events affected maternal–child health of those cities and, if so, for how long. For percentages of low birth weight (LBW) and preterm births, we found no significant effects from the WTC attacks in NYC and transient but significant effects on rates of LBW and preterm births following the bombings in Madrid. We did find a significant positive and sustained effect on infant mortality rate in NYC following the WTC attacks but no similar effect in Madrid. There were no effects on any of the indicator variables in the comparison regions of New York state and the remainder of Spain. Thus, population maternal–health in New York and Madrid showed unique adverse effects after the terrorist attacks in those cities. Short-term effects on LBW and preterm birth rates in Madrid and long-term effects on infant mortality rates in NYC were found when quarterly data were analyzed from 1990 through 2008/2009. These findings raise questions about chronic changes in the population’s quality of life following catastrophic terrorist attacks. Public health should be monitored and interventions designed to address chronic stress, environmental, and socioeconomic threats beyond the acute aftermath of events.     

The Burden of Depression in New York City Adults: Results from the 2013–14 NYC Health and Nutrition Examination Survey

Depression is responsible for a large burden of disability in the USA. We estimated the prevalence of depression in the New York City (NYC) adult population in 2013–14 and examined associations with demographics, health behaviors, and employment status. Data from the 2013–14 New York City Health and Nutrition Examination Survey, a population-based examination study, were analyzed, and 1459 participants met the inclusion criteria for this analysis. We defined current symptomatic depression by a Patient Health Questionnaire (PHQ-9) score ≥?10. Overall, 8.3% of NYC adults had current symptomatic depression. New Yorkers with current symptomatic depression were significantly more likely to be female, Latino, and unemployed yet not looking for work; they were also significantly more likely to have less than a high school education and to live in a high-poverty neighborhood. Socioeconomic inequalities in mental health persist in NYC and highlight the need for better diagnosis and treatment.     

The Dose–Response of Time Served in Prison on Mortality: New York State, 1989–2003

Objectives. I investigated the differential impact of the dose–response of length of stay on postprison mortality among parolees.Methods. Using 1989–2003 New York State parole administrative data from the Bureau of Justice Statistics on state correctional facilities, I employed multinomial logistic regression analyses and formal demographic techniques that used the life table of the populations to deduce changes in life expectancy.Results. Each additional year in prison produced a 15.6% increase in the odds of death for parolees, which translated to a 2-year decline in life expectancy for each year served in prison. The risk was highest upon release from prison and declined over time. The time to recovery, or the lowest risk level, was approximately two thirds of the time served in prison.Conclusions. Incarceration reduces life span. Future research should investigate the pathways to this higher mortality and the possibilities of recovery.Although several studies have documented the findings and detailed the analyses by cause of death1,2 of postprison mortality, limited scholarship has investigated the prison environment’s contribution. Several studies have shown that former prisoners are at considerable risk for drug overdose,3–7 contributing to high mortality immediately after prison. Compared with their nonprisoner counterparts, those who have served time in prison have elevated levels of unnatural deaths. One study of persons released from prisons in Victoria, Australia, in the 1990s revealed that mortality levels owing to unnatural causes for former prisoners was twice that of prisoners and 10 times that of nonprisoners.8 Scholarship has also found that persons who interacted with the criminal justice system were more likely to die from unnatural causes than were those who had no interaction with the criminal justice system.9However, the postprison mortality literature suggests that prisoners possess characteristics coming to prison that set them apart from the rest of the population.8–12 The selectivity of the population is an important issue but is not resolved by comparing the prison population to that of the general population or the mortality of past prisoners to people who have not been incarcerated. It is imperative to take into account that prisoners represent a small portion of those who commit delinquent acts. Prisoners are the people who were caught, indicted, and punished via incarceration. The judicial system does not capture all who commit crimes, nor are the sentencing patterns invariant across age, race, gender, and socioeconomic status.13–18Some scholars have argued that the experience of incarceration can alter health trajectories because it is an axis of stratification relevant to mortality that has strong associations, as do other covariates of mortality such as race, gender, and socioeconomic status. One study showed that the experience of being incarcerated has a negative impact on life chances regardless of prior incarceration history.19 Other work suggests a relationship between mortality and the length of time served in prison: some findings show longer stays are protective and others show the opposite.20,21 Such studies have contributed to our understanding of the link between the criminal justice system and mortality immediately following release, focusing on mortality owing to overdose and suicide. I sought to extend this research by studying the mortality of New York State parolees over a 10-year period. By combining formal demography and survival analysis, I investigated the dose–response of time served in prison to changes in life expectancy.     

Disparities in Sleep Problems by Sexual Orientation among New York City Adults: an Analysis of the New York City Health and Nutrition Examination Survey, 2013–2014

We examined disparities in sleep problems by sexual orientation among a population-based sample of adults, using data from the New York City (NYC) Health and Nutrition Examination Survey (NYC HANES), a population-based, cross-sectional survey conducted in 2013–2014 (n?=?1220). Two log binomial regression models were created to assess the relative prevalence of sleep problems by sexual orientation. In model 1, heterosexual adults served as the reference category, controlling for gender, age, race/ethnicity, education, marital status, and family income. And in model 2, heterosexual men served as the reference category, controlling for age, race/ethnicity, education, marital status, and family income. We found that almost 42% of NYC adults reported sleep problems in the past 2 weeks. Bisexual adults had 1.4 times the relative risk of sleep problems compared to heterosexual adults (p?=?0.037). Compared to heterosexual men, heterosexual and bisexual women had 1.3 and 1.6 times the risk of sleep problems, respectively (p?<?0.05). Overall, adults who self-identified as bisexual had a significantly greater risk of sleep problems than adults who self-identified as heterosexual.     

Gender and Race Disparities in Cardiovascular Disease Risk Factors among New York City Adults: New York City Health and Nutrition Examination Survey (NYC HANES) 2013–2014

While gender and racial/ethnic disparities in cardiovascular disease (CVD) risk factors have each been well characterized, few studies have comprehensively examined how patterns of major CVD risk factors vary and intersect across gender and major racial/ethnic groups, considered together. Using data from New York City Health and Nutrition Examination Survey 2013–2014—a population-based, cross-sectional survey of NYC residents ages 20 years and older—we measured prevalence of obesity, hypertension, hypercholesterolemia, smoking, and diabetes across gender and race/ethnicity groups for 1527 individuals. We used logistic regression with predicted marginal to estimate age-adjusted prevalence ratio by gender and race/ethnicity groups and assess for potential additive and multiplicative interaction. Overall, women had lower prevalence of CVD risk factors than men, with less hypertension (p?=?0.040), lower triglycerides (p?<?0.001), higher HDL (p?<?0.001), and a greater likelihood of a heart healthy lifestyle, more likely not to smoke and to follow a healthy diet (p?<?0.05). When further stratified by race/ethnicity, however, the female advantage was largely restricted to non-Latino white women. Non-Latino black women had significantly higher risk of being overweight or obese, having hypertension, and having diabetes than non-Latino white men or women, or than non-Latino black men (p?<?0.05). Non-Latino black women also had higher total cholesterol compared to non-Latino black men (184.4 vs 170.5 mg/dL, p?=?0.010). Despite efforts to improve cardiovascular health and narrow disparities, non-Latino black women continue to have a higher burden of CVD risk factors than other gender and racial/ethnic groups. This study highlights the importance of assessing for intersectionality between gender and race/ethnicity groups when examining CVD risk factors.     

Change in Diabetes Prevalence and Control among New York City Adults: NYC Health and Nutrition Examination Surveys 2004–2014

National examination surveys provide trend information on diabetes prevalence, diagnoses, and control. Few localities have access to such information. Using a similar design as the National Health and Nutrition Examination Survey (NHANES), two NYC Health and Nutrition Examination Surveys (NYC HANES) were conducted over a decade, recruiting adults ≥?20 years using household probability samples (n =?1808 in 2004; n =?1246 in 2013–2014) and physical exam survey methods benchmarked against NHANES. Participants had diagnosed diabetes if told by a health provider they had diabetes, and undiagnosed diabetes if they had no diagnosis but a fasting plasma glucose ≥?126 mg/dl or A1C?≥?6.5%. We found that between 2004 and 2014, total diabetes prevalence (diagnosed and undiagnosed) in NYC increased from 13.4 to 16.0% (P =?0.089). In 2013–2014, racial/ethnic disparities in diabetes burden had widened; diabetes was highest among Asians (24.6%), and prevalence was significantly lower among non-Hispanic white adults (7.7%) compared to that among other racial/ethnic groups (P <?0.001). Among adults with diabetes, the proportion of cases diagnosed increased from 68.3 to 77.3% (P =?0.234), and diagnosed cases with very poor control (A1C >?9%), decreased from 26.9 to 18.0% (P =?0.269), though both were non-significant. While local racial/ethnic disparities in diabetes prevalence persist, findings suggest modest improvements in diabetes diagnosis and management.     

Social Network Members’ Roles and Use of Mental Health Services Among Drug Users in New York City

Depression is more common among drug users (15–63 %) than the general population (5–16 %). Lack of social support network members may be associated with low mental health service (MHS) use rates observed among drug users. We investigated the relationship between social network members’ roles and MHS use among frequent drug users using Social Ties Associated with Risk of Transition into Injection Drug Use data (NYC 2006–2009). Surveys assessed depression, MHS use, demographics, drug use and treatment, and social network members’ roles. Participants reporting lifetime depressive episode with start/end dates and information on social/risk network members were included (n = 152). Adjusting for emotional support and HIV status, having one or more informational support network members remained associated with MHS use at last depressive episode (adjusted odds ratio (AOR) 3.37, 95 % confidence interval (CI) 1.38–8.19), as did history of drug treatment (AOR 2.75, 95 % CI 1.02–7.41) and no legal income (AOR 0.23, 95 % CI 0.08–0.64). These data suggest that informational support is associated with MHS utilization among depressed drug users.     

A Case-Only Study of Vulnerability to Heat Wave–Related Mortality in New York City (2000–2011)

Background

As a result of climate change, the frequency of extreme temperature events is expected to increase, and such events are associated with increased morbidity and mortality. Vulnerability patterns, and corresponding adaptation strategies, are most usefully conceptualized at a local level.

Methods

We used a case-only analysis to examine subject and neighborhood characteristics that modified the association between heat waves and mortality. All deaths of New York City residents from 2000 through 2011 were included in this analysis. Meteorological data were obtained from the National Climatic Data Center. Modifying characteristics were obtained from the death record and geographic data sets.

Results

A total of 234,042 adult deaths occurred during the warm season of our study period. Compared with other warm-season days, deaths during heat waves were more likely to occur in black (non-Hispanic) individuals than other race/ethnicities [odds ratio (OR) = 1.08; 95% CI: 1.03, 1.12], more likely to occur at home than in institutions and hospital settings (OR = 1.11; 95% CI: 1.06, 1.16), and more likely among those living in census tracts that received greater public assistance (OR = 1.05; 95% CI: 1.01, 1.09). Finally, deaths during heat waves were more likely among residents in areas of the city with higher relative daytime summer surface temperature and less likely among residents living in areas with more green space.

Conclusion

Mortality during heat waves varies widely within a city. Understanding which individuals and neighborhoods are most vulnerable can help guide local preparedness efforts.

Citation

Madrigano J, Ito K, Johnson S, Kinney PL, Matte T. 2015. A case-only study of vulnerability to heat wave–related mortality in New York City (2000–2011). Environ Health Perspect 123:672–678; http://dx.doi.org/10.1289/ehp.1408178     

Relation Between Annual Trends in Food Pantry Use and Long-Term Unemployment in New York State, 2002–2012

We examined the correlation between trends in meals provided through food pantries and long-term unemployment from 2002 through 2012. The New York State Hunger Prevention and Nutrition Assistance Program provided about 192 million meals through food pantries in 2012—double the number before the Great Recession. Annual food pantry use was strongly correlated with long-term unemployment and remained on an upward trend from 2006 through 2012, even after the Great Recession had ended. These findings suggest that efforts to reduce hunger and food insecurity should continue to be priorities.Food pantries are a critical source of relief, used by about one quarter of food-insecure households.1 By providing safe and nutritious foods,2 food pantries may also help prevent health problems because food insecurity is often associated with higher risks of poorer physical, cognitive, behavioral, and mental health outcomes along with inadequate nutrient intake.3–5 However, continuing cuts to national nutrition programs will lead to an increased demand for pantry services,6,7 straining an already overburdened system.There is a paucity of studies on the use of emergency food relief services that is largely the result of a lack of readily accessible data collected on an ongoing and systematic basis regarding the use of emergency food relief services at the local, state, and national levels. Even when data are available, there is often a lag of 6 months or longer. This lag has meant that local and state program planners are not always able to anticipate periods of increased demand for emergency food relief services. However, data on indicators of economic conditions that could be related to use of emergency food relief services are readily available and could be used to inform planning and targeting of food pantry services. In this article, we examine the correlation between trends in meals provided through food pantries and long-term unemployment from 2002 through 2012.     

The Impact of Lifelong Family Care on Family Caregivers’ Perceptions of the Sexuality of Young Adults with Intellectual Disabilities in the Western Cape of South Africa

Sexuality and Disability - This paper presents findings of a constructivist grounded theory study conducted within the Western Cape Province of South Africa. The study explored how family...     

The Association Between Neighborhood Poverty and HIV Diagnoses Among Males and Females in New York City, 2010–2011

Objective

We assessed the association of neighborhood poverty with HIV diagnosis rates for males and females in New York City.

Methods

We calculated annual HIV diagnosis rates by ZIP Code, sex, and neighborhood poverty level using 2010–2011 New York City (NYC) HIV surveillance data and data from the U.S. Census 2010 and American Community Survey 2007–2011. Neighborhood poverty levels were percentage of residents in a ZIP Code with incomes below the federal poverty threshold, categorized as 0%–<10% (low poverty), 10%–<20% (medium poverty), 20%–<30% (high poverty), and 30%–100% (very high poverty). We used sex-stratified negative binomial regression models to measure the association between neighborhood-level poverty and HIV diagnosis rates, controlling for neighborhood-level education, race/ethnicity, age, and percentage of men who have sex with men.

Results

In 2010–2011, 6,184 people were newly diagnosed with HIV. Median diagnosis rates per 100,000 population increased by neighborhood poverty level overall (13.7, 34.3, 50.6, and 75.6 for low-, medium-, high-, and very high-poverty ZIP Codes, respectively), for males, and for females. In regression models, higher neighborhood poverty remained associated with higher diagnosis rates among males (adjusted rate ratio [ARR] = 1.63, 95% confidence interval [CI] 1.34, 1.97) and females (ARR=2.14, 95% CI 1.46, 3.14) for very high- vs. low-poverty ZIP Codes.

Conclusion

Living in very high- vs. low-poverty urban neighborhoods was associated with increased HIV diagnosis rates. After controlling for other factors, the association between poverty and diagnosis rates was stronger among females than among males. Alleviating poverty may help decrease HIV-related disparities.More than 40,000 people in the United States are newly diagnosed with human immunodeficiency virus (HIV) every year.¹ The National HIV/AIDS Strategy called for a 20% drop in this figure by 2015, and emphasis at the federal level on high-impact prevention is attempting to shift the focus of HIV prevention activities from individuals to entire communities or populations.^2,3 Yet, most investigations of the determinants of HIV infection have focused on individual traits, typically identifying people as high risk based on factors such as race/ethnicity or sexual or drug use behaviors. For example, black and Hispanic people have HIV diagnosis rates more than twice that of white people and account for more than two-thirds of HIV diagnoses in the United States. Men who have sex with men (MSM) also account for more than two-thirds of HIV diagnoses.^1,4Area-based social conditions such as neighborhood poverty are increasingly being recognized as important determinants of health inequities, including HIV infection.^4–9 In the United States, areas with relatively high poverty (where ≥20% of the population live in households with incomes below the federal poverty threshold) have the highest HIV diagnosis rates and account for about half of all new HIV diagnoses.⁴ County-level poverty has been shown to be significantly associated with HIV diagnosis rates in the United States, overall, by sex, and by race/ethnicity.⁸ However, this association has not been explored by ZIP Code within a U.S. city. Cities concentrate health risks, and disaggregating their health information (e.g., by neighborhood poverty level) uncovers disparities.¹⁰ Furthermore, it is not known if differences in HIV diagnosis rates by ZIP Code-level poverty can be explained by area-based differences in age and racial/ethnic distribution (e.g., people living in poorer neighborhoods are younger and more likely to be black or Hispanic, which are populations with higher HIV incidence) or area-based poverty is independently associated with HIV diagnosis rates, and whether or not this relationship differs between males and females.The distribution of people with HIV in New York City (NYC) has been described by neighborhood and area-based poverty level.¹¹ Because local governance is a key force in improving social conditions and reducing health inequalities,¹⁰ local demand for expanded analyses that more thoroughly assess the connection between poverty and health exists. The NYC Department of Health and Mental Hygiene (DOHMH) formed the Center for Health Equity in 2014. Its goals are to examine and develop policy that addresses health disparities and their causes, a chief one of which is poverty. To advance these goals, we investigated health disparities related to HIV and poverty among males and females, controlling for other factors.We conducted an ecological analysis¹² using NYC HIV surveillance data to examine if area-based poverty at the ZIP Code level is independently associated with HIV diagnosis rates among males and females.     

Change in Obesity Prevalence among New York City Adults: the NYC Health and Nutrition Examination Survey, 2004 and 2013–2014

The objective of this study was to measure change in obesity prevalence among New York City (NYC) adults from 2004 to 2013–2014 and assess variation across sociodemographic subgroups. We used objectively measured height and weight data from the NYC Health and Nutrition Examination Survey to calculate relative percent change in obesity (≥?30 kg/m²) between 2004 (n =?1987) and 2013–2014 (n =?1489) among all NYC adults and sociodemographic subgroups. We also examined changes in self-reported proxies for energy imbalance. Estimates were age-standardized and statistical significance was evaluated using two-tailed T tests and multivariable regression (p <?0.05). Between 2004 and 2013–2014, obesity increased from 27.5 to 32.4% (p =?0.01). Prevalence remained stable and high among women (31.2 to 32.8%, p =?0.53), but increased among men (23.4 to 32.0%, p =?0.002), especially among non-Latino White men and men age ≥?65 years. Black adults had the highest prevalence in 2013–2014 (37.1%) and Asian adults experienced the largest increase (20.1 to 29.2%, p =?0.06), especially Asian women. Foreign-born participants and participants lacking health insurance also had large increases in obesity. We observed increases in eating out and screen time over time and no improvements in physical activity. Our findings show increases in obesity in NYC in the past decade, with important sociodemographic differences.     

Home Exposure to Secondhand Smoke among People Living in Multiunit Housing and Single Family Housing: a Study of California Adults, 2003–2012

Public health education efforts continue to encourage people to adopt voluntary smoking bans at home; nonetheless, the home remains a place where many people are exposed to secondhand smoke (SHS). Little is known about how SHS exposure in the home differs between adults residing in multiunit housing (MUH) and those residing in single family housing (SFH). This study (1) compared the socio-demographic characteristics, chronic disease conditions, and smoking status of adults living in MUH with those living in SFH, (2) assessed the correlates of living in MUH for adults, and (3) evaluated the association of residency in MUH and SFH with the odds of being exposed to SHS at home using population-based survey data of California adults. Smoking prevalence was significantly higher among MUH residents than SFH residents. The adjusted odds of exposure to SHS at home were 32 % higher for MUH smokers than SFH smokers but were not significantly different for non-smokers. This study presents evidence that there are significant socio-demographic differences between MUH residents and SFH residents and that MUH smokers have higher rates of exposure to SHS at home than SFH smokers after adjusting for other covariates. To reduce home exposure to SHS among MUH residents, it is important to adopt tobacco control policies that are aimed at reducing SHS exposure in and around MUH and at reducing cigarette smoking among current smokers in MUH.     

Influence of Cooking and Heating Fuel Use on 1–59 Month Old Mortality in South Africa

Objectives: To determine the association between the combustion of wood, animal dung, coal and paraffin (polluting fuels) for cooking and heating and 1–59 month old mortality in South Africa, whilst adjusting for a number of confounders. Methods: Data from 3,556 children (142 deaths) living in 2,828 households were extracted from the 1998 South African Demographic and Health Survey (SADHS) database. The SADHS was the first national health survey conducted across the entire country and provided the opportunity to examine the prevalence and determinants of various morbidity and mortality outcomes in a representative national population. Results: The results suggest that exposure to cooking and heating smoke from polluting fuels is significantly associated with 1–59 month mortality, after controlling for mother's age at birth, water source, asset index and household crowdedness (RR=1.95; 95% CI=1.04, 3.68). Conclusions: Although there is potential for residual confounding despite adjustment, the better documented evidence on outdoor air pollution and mortality suggest this association may be real. As nearly half of households in South Africa still rely on polluting fuels and women of childbearing age perform most cooking tasks, the attributable risk arising from this association, if confirmed, could be substantial. It is trusted that more detailed analytical intervention studies will scrutinise these results in order to develop integrated intervention programmes to reduce children's exposure to air pollution emanating from cooking and heating fuels.     

Seeing and hearing: The impacts of New York City’s universal pre-kindergarten program on the health of low-income children

We examine the effect of New York City’s universal pre-kindergarten program (UPK) on the health and utilization of children enrolled in Medicaid using a difference-in-regression-discontinuities design. We find that UPK increases the probability that a child is diagnosed with asthma or with vision problems, receives treatment for hearing or vision problems, or receives an immunization or screening during the pre-kindergarten year. These effects are not offset by lower rates in the kindergarten year, suggesting that UPK accelerates the rate at which children are identified with and treated for conditions that could potentially delay learning and cause behavioral problems.     

Determinants of Severe Maternal Morbidity and Its Racial/Ethnic Disparities in New York City, 2008–2012

Maternal and Child Health Journal - Objectives Severe maternal morbidity (SMM) is an important indicator for identifying and monitoring efforts to improve maternal health. Studies have identified...     

The Impact of Increasing Health Insurance Coverage on Disparities in Mortality: Health Care Reform in Colombia, 1998–2007

Objectives. We examined the impact of expanding health insurance coverage on socioeconomic disparities in total and cardiovascular disease mortality from 1998 to 2007 in Colombia.Methods. We used Poisson regression to analyze data from mortality registries (633 905 deaths) linked to population census data. We used the relative index of inequality to compare disparities in mortality by education between periods of moderate increase (1998–2002) and accelerated increase (2003–2007) in health insurance coverage.Results. Disparities in mortality by education widened over time. Among men, the relative index of inequality increased from 2.59 (95% confidence interval [CI] = 2.52, 2.67) in 1998–2002 to 3.07 (95% CI = 2.99, 3.15) in 2003–2007, and among women, from 2.86 (95% CI = 2.77, 2.95) to 3.12 (95% CI = 3.03, 3.21), respectively. Disparities increased yearly by 11% in men and 4% in women in 1998–2002, whereas they increased by 1% in men per year and remained stable among women in 2003–2007.Conclusions. Mortality disparities widened significantly less during the period of increased health insurance coverage than the period of no coverage change. Although expanding coverage did not eliminate disparities, it may contribute to curbing future widening of disparities.Recent health care reform in the United States has sparked debate on the potential impact of expanding health insurance coverage on access to care and disparities in health care.1 People with lower socioeconomic status are at increased risk of many conditions and are therefore more likely to benefit from an expansion in health insurance coverage.1 Previous observational studies in the United States have suggested that a lack of health insurance was associated with an increased risk of subsequent mortality in all socioeconomic groups.2 However, little is known about the impact of health insurance coverage on socioeconomic disparities in mortality following a major expansion in insurance coverage. In 1993, the Colombian government implemented a major health care reform that introduced mandatory health insurance.3 As a result, coverage increased from 47% in 19944 to 98% in 2010.5 Although the social and economic context of Colombia differs substantially from that in the United States, lessons from the Colombian reform can shed light on the potential impact of increased health insurance coverage on health disparities in the United States and middle-income countries currently expanding insurance coverage.A desirable outcome of coverage expansion is that it will have a larger impact on the health of the poor and will contribute to a reduction in health disparities.3,6 The reform in Colombia established a scheme of subsidies targeted to the poor, assigning citizens to 2 schemes on the basis of income: (1) the contributory scheme, which covers workers and their families with an income above the cut-off and is financed through payroll and employer’s contributions, and (2) the subsidized scheme, which covers the poor as identified through a proxy means test.6In the poorest income quartile, health insurance coverage increased from 6% in 1993 to more than 70% in 2007,6 an increase attributable to the subsidized scheme.5 Increased coverage among the poor is expected to improve health outcomes by ensuring timely care and bringing them into closer contact with the health care system.7 However, the reform also increased the complexity of the system potentially leading to delays in some types of care8 and reducing spending in prevention and public health.9 Previous dynamic simulations for the United States have suggested that expanding health insurance coverage is cost-effective, but failing to also expand the primary care capacity for the disadvantaged could lead to increasing health disparities.10 There have been no empirical studies examining these issues in the context of a major health care reform.Most previous studies have focused on the impact of health care reform on utilization and access to health care services, with only some studies examining the impact on population health.7,11–13 A recent review of available evidence concluded that expanding health insurance coverage generally improves access to care and population health particularly for lower income groups, but health gains may be dependent on the institutional framework and governance arrangements.14 On the other hand, the World Health Organization Commission on Social Determinants of Health concluded that, although inequity in health care is critical, the largest burden of illness arises in large part because of the conditions in which people are born, grow, live, work, and age.15We examined whether expanding health insurance coverage is associated with trends in socioeconomic disparities in mortality in the aftermath of the health care reform in Colombia. Findings from this study are of potential interest to the United States and middle-income countries that have recently implemented reforms to achieve universal access. We hypothesized that expanding health insurance coverage will contribute to curbing unfavorable trends in mortality disparities. To assess the impact of this expansion, we examined trends in mortality disparities by educational level separately for 2 divergent periods. In 2002, a process of decentralization led to a sharp increase in resource allocation to the subsided scheme in regional areas.16 As a result, whereas in the period 1998–2002 there was a moderate increase in total health insurance coverage (coverage went from 59.8% in 1998 to 64.1% in 2002), thereafter total coverage increased rapidly from 65.9% (2003) to 92.5% (2007; Figure 1). This corresponds to a statistically significant increase of 5.1% per year (P < .001) in the period 2003–2007. As illustrated in Figure 1, this increase was driven by a particularly steep increase in affiliates to the subsidized scheme in 2003–2007 (15.1% per year; P < .001), as opposed to a much smaller increase in the period 1998–2002 (6.4% per year; P < .001), suggesting that it may have particularly reached the lower socioeconomic groups. The discrepancy in health insurance coverage trends between these 2 periods thus provides a natural experiment to examine the impact of health insurance coverage on socioeconomic disparities in mortality.Open in a separate windowFIGURE 1—Percentage of population with health insurance coverage: Colombia, 1998–2007.Note. Other schemes include primarily members of the military and teacher and oil workers syndicate members.Source. Annual reports of the Ministry of Health and Social Protection.5,17–19Our specific aim was to evaluate to what extent increased health insurance coverage has contributed to diminishing socioeconomic inequalities in mortality in Colombia. If socioeconomic differences in mortality were responsive to increased health insurance coverage, we would expect a more favorable trend in socioeconomic differences in mortality during the second than the first period. If increased insurance coverage had no impact on socioeconomic disparities in mortality, we would expect similar trends in socioeconomic disparities in mortality between the 2 periods.