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Objectives: To assess the risk of mortality from suicide among male veteran participants in a large population-based health survey. Design and setting: A prospective follow-up study in the US. Data were obtained from the US National Health Interview Surveys 1986–94 and linked to the Multiple Cause of Death file (1986–97) through the National Death Index. Participants: The sample comprised 320 890 men, aged ≥18 years at baseline. The participants were followed up with respect to mortality for 12 years. Results: Cox proportional hazards analysis showed that veterans who were white, those with ≥12 years of education and those with activity limitations (after adjusting for medical and psychiatric morbidity) were at a greater risk for completing suicide. Veterans were twice as likely (adjusted hazard ratio 2.04, 95% CI 1.10 to 3.80) to die of suicide compared with non-veterans in the general population. The risk of death from “natural” causes (diseases) and the risk of death from “external” causes did not differ between the veterans and the non-veterans. Interestingly, male veterans who were overweight had a significantly lower risk of completing suicide than those who were of normal weight. Conclusions: Veterans in the general US population, whether or not they are affiliated with the Department of Veterans Affairs (VA), are at an increased risk of suicide. With a projected rise in the incidence of functional impairment and psychiatric morbidity among veterans of the conflicts in Afghanistan and Iraq, clinical and community interventions that are directed towards patients in both VA and non-VA healthcare facilities are needed.

Background Self-rated health is widely considered a good indicator of morbidity and mortality but its validity for health equity analysis and public health policies in Italy is often disregarded by policy-makers. This study had three objectives. O1: To explore response distribution across dimensions of age, chronic health conditions, functional limitations and SRH in Italy. O2: To explore associations between SRH and healthcare demand in Italy. O3: To explore the association between SRH and household income. Methods Cross-sectional data were obtained from the 2015 Health Interview Survey (HIS) conducted in Italy. Italian respondents ( n  = 20,814) were included in logistic regression analyses. O1: associations of chronic health conditions (CHC), functional limitations (FL), and age with self-rated health (SRH) were tested. O2: associations of CHC, FL, and SRH with hospitalisation (H), medical specialist consultations (MSC), and medicine use (MU) were tested. O3: associations of SRH and CHC with household income (PEI) were tested. Results O1: CHC, FL, and age had an independent summative effect on respondents’ SRH. O2: SRH predicted H and MSC more than CHC; age and MU were more strongly correlated than SRH and MU. O3: SRH and PEI were significantly correlated, while we found no correlation between CHC and PEI. Conclusions Drawing from our results and the relevant literature, we suggest that policy-makers in Italy could use SRH measures to: 1) predict healthcare demand for effective allocation of resources; 2) assess subjective effectiveness of treatments; and 3) understand geosocial pockets of health inequity that require special attention.

Objective: To describe the characteristics of betel quid chewers and to investigate the behavioural and mortality relations between betel quid chewing and cigarette smoking. Method: Prevalence and mortality risks of betel quid chewers by smoking status were calculated, based on the National Health Interview Survey in 2001 and a community based cohort, respectively. Cox’s proportional hazards model was used to adjust mortality risks for age, alcohol use, and education. Results: Almost all betel quid chewers were smokers, and most started chewing after smoking. Chewers were predominantly male, mostly in their 30s and 40s, more likely being among the lowest educational or income group, and residing in the eastern regions of Taiwan. On average, betel quid chewers who smoked consumed 18 pieces of betel quid a day, and smoked more cigarettes per day. Far more smokers use betel quid than non-smokers (27.5% v 2.5%), but ex-smokers quit betel quid more than smokers (15.1% v 6.8%). The significantly increased mortality of betel quid users who also smoked, for all causes, all cancer, oral cancer, and cancer of the nasopharynx, lung, and liver, was the result of the combined effects of chewing and smoking. Smokers who chewed betel quid nearly tripled their oral cancer risks from a relative risk of 2.1 to 5.9. Increasing the number of cigarettes smoked among betel quid chewers was associated with a synergistic effect, reflective of the significant interaction between the two. Conclusion: To a large extent, the serious health consequences suffered by betel quid chewers were the result of the combined effects of smoking and chewing. Betel quid chewing should not be considered as an isolated issue, but should be viewed conjointly with cigarette smoking. Reducing cigarette smoking serves as an important first step in reducing betel quid chewing, and incorporating betel quid control into tobacco control may provide a new paradigm to attenuate the explosive increase in betel quid use in Taiwan.

Purpose Health-related quality of life outcomes are increasingly used to monitor population health and health inequalities and to assess the (cost-) effectiveness of health interventions. The EQ-5D-5L has been included in the Belgian Health Interview Survey, providing a new source of population-based self-perceived health status information. This study aims to estimate Belgian population norms for the EQ-5D-5L by sex, age, and region and to analyze its association with educational attainment. Methods The BHIS 2018 provided EQ-5D-5L data for a nationally representative sample of the Belgian population. The dimension scores and index values were analyzed using logistic and linear regressions, respectively, accounting for the survey design. Results More than half of respondents reported problems of pain/discomfort, while over a quarter reported problems of anxiety/depression. The average index value was 0.84. Women reported more problems on all dimensions, but particularly on anxiety/depression and pain/discomfort, resulting in significantly lower index values. Problems with mobility, self-care, and usual activities showed a sharp increase after the age of 80 years. Consequently, index values decreased significantly by age. Lower education was associated with a higher prevalence of problems for all dimensions except anxiety/depression and with a significantly lower index value. Conclusion This paper presents the first nationally representative Belgian population norms using the EQ-5D-5L. Inclusion of the EQ-5D in future surveys will allow monitoring over time of self-reported health, disease burden, and health inequalities.

BackgroundHigh patient out-of-pocket (OOP) spending for medical care is associated with medical debt, distress about household finances, and forgoing medical care because of cost in the USA.ObjectiveTo examine the national prevalence of medical financial hardship domains: (1) material conditions from increased OOP expenses (e.g., medical debt), (2) psychological responses (e.g., distress), and (3) coping behaviors (e.g., forgoing care); and factors associated with financial hardship.Design and ParticipantsWe identified adults aged 18–64 years (N = 68,828) and ≥ 65 years (N = 24,614) from the 2015–2017 National Health Interview Survey. Multivariable analyses of nationally representative cross-sectional survey data were stratified by age group, 18–64 years and ≥ 65 years.Main MeasuresPrevalence of material, psychological, and behavioral hardship and hardship intensity.Key ResultsApproximately 137.1 million (95% CI 132.7–141.5) adults reported any medical financial hardship in the past year. Hardship is more common for material, psychological and behavioral domains in adults aged 18–64 years (28.9%, 46.9%, and 21.2%, respectively) than in adults aged ≥ 65 years (15.3%, 28.4%, and 12.7%, respectively; all p < .001). Lower educational attainment and more health conditions were strongly associated with hardship intensity in multivariable analyses in both age groups (p < .001). In the younger group, the uninsured were more likely to report multiple domains of hardship (52.8%), compared to those with some public (26.5%) or private insurance (23.2%) (p < .001). In the older group, individuals with Medicare only were more likely to report hardship in multiple domains (17.1%) compared to those with Medicare and public (12.1%) or Medicare and private coverage (10.1%) (p < .001).ConclusionsMedical financial hardship is common in the USA, especially in adults aged 18–64 years and those without health insurance coverage. With trends towards higher patient cost-sharing and increasing health care costs, risks of hardship may increase in the future.

Potential is seen in web data collection for population health surveys due to its combined cost-effectiveness, implementation ease, and increased internet penetration. Nonetheless, web modes may lead to lower and more selective unit response than traditional modes, and this may increase bias in the measured indicators. This research assesses the unit response and costs of a web study versus face-to-face (F2F) study. Alongside the Belgian Health Interview Survey by F2F edition 2018 (BHISF2F; net sample used: 3316), a web survey (Belgian Health Interview Survey by Web [BHISWEB]; net sample used: 1010) was organized. Sociodemographic data on invited individuals was obtained from the national register and census linkages. Unit response rates considering the different sampling probabilities of both surveys were calculated. Logistic regression analyses examined the association between mode system and sociodemographic characteristics for unit nonresponse. The costs per completed web questionnaire were compared with the costs for a completed F2F questionnaire. The unit response rate is lower in BHISWEB (18.0%) versus BHISF2F (43.1%). A lower response rate was observed for the web survey among all sociodemographic groups, but the difference was higher among people aged 65 years and older (15.4% vs 45.1%), lower educated people (10.9% vs 38.0%), people with a non-Belgian European nationality (11.4% vs 40.7%), people with a non-European nationality (7.2% vs 38.0%), people living alone (12.6% vs 40.5%), and people living in the Brussels-Capital (12.2% vs 41.8%) region. The sociodemographic characteristics associated with nonresponse are not the same in the 2 studies. Having another European (OR 1.60, 95% CI 1.20-2.13) or non-European nationality (OR 2.57, 95% CI 1.79-3.70) compared to a Belgian nationality and living in the Brussels-Capital (OR 1.72, 95% CI 1.41-2.10) or Walloon (OR 1.47, 95% CI 1.15-1.87) regions compared to the Flemish region are associated with a higher nonresponse only in the BHISWEB study. In BHISF2F, younger people (OR 1.31, 95% CI 1.11-1.54) are more likely to be nonrespondents than older people, and this was not the case in BHISWEB. In both studies, lower educated people have a higher probability of being nonrespondent, but this effect is more pronounced in BHISWEB (low vs high education level: Web, OR 2.71, 95% CI 2.21-3.39 and F2F OR 1.70, 95% CI 1.48-1.95). The BHISWEB study had a considerable advantage; the cost per completed questionnaire was almost 3 times lower (€41 [US $48]) compared with F2F data collection (€111 [US $131]). The F2F unit response rate was generally higher, yet for certain groups the difference between web and F2F was more limited. Web data collection has a considerable cost advantage. It is therefore worth experimenting with adaptive mixed-mode designs to optimize financial resources without increasing selection bias (eg, only inviting sociodemographic groups who are keener to participate online for web surveys while continuing to focus on increasing F2F response rates for other groups).

In this study, we aimed to investigate healthcare access and utilization among patients with limited English proficiency (LEP). We analyzed aggregated data from the 2018 California Health Interview Survey, a large population-based survey. Survey weighted univariate and multivariable logistic regression analyses were conducted. A total of 21,177 participants were included with 8.2% having LEP. Compared to participants with proficient English, LEP participants were less likely to have a usual place to go to when sick other than the ER or have a preventive care visit in the past year after adjusting for sociodemographic characteristics. However, LEP participants were also less likely to need to see a medical specialist and less likely to delay necessary medical care compared to English proficient participants. While patients with LEP were less likely to have access to preventative care, they were also less likely to delay necessary care.

This study illuminates the association between cigarette smoking and adult mortality in the contemporary United States. Recent studies have estimated smoking attributable mortality using indirect approaches or with sample data that are not nationally representative and that lack key confounders. We use the 1990-2011 National Health Interview Survey Linked Mortality Files to estimate relative risks of all-cause and cause-specific mortality for current and former smokers compared with never smokers. We examine causes of death established as attributable to smoking as well as additional causes that appear to be linked to smoking but have not yet been declared by the U.S. Surgeon General to be caused by smoking. Mortality risk is substantially elevated among smokers for established causes and moderately elevated for additional causes. We also decompose the mortality disadvantage among smokers by cause of death and estimate the number of smoking-attributable deaths for the U.S. adult population ages 35+, net of sociodemographic and behavioral confounders. The elevated risks translate to 481,887 excess deaths per year among current and former smokers compared with never smokers, 14 % to 15 % of which are due to the additional causes. The additional causes of death contribute to the health burden of smoking and should be considered in future studies of smoking-attributable mortality. This study demonstrates that smoking-attributable mortality must remain a top population health priority in the United States and makes several contributions to further underscore the human costs of this tragedy that has ravaged American society for more than a century.

PurposeThe risk psychological distress (PD) confers on mortality due to specific chronic diseases compared to suicide is unclear. Using the National Health Interview Survey (NHIS), we investigated the association between PD levels and risk of all-cause and chronic disease-specific mortality and compared the contribution of chronic disease-related mortality to that of suicide.MethodsData from 195, 531 adults, who participated in the NHIS between 1997 and 2004, were linked to the National Death Index records through to 2006. Multivariable Cox regression models were used to estimate hazard ratios (HRs) and their 95% confidence intervals (CIs) across four levels of PD, measured using the Kessler-6 scale. Outcomes included all-cause mortality, and mortality due to all CVDs and subtypes, all cancers and subtypes, diabetes mellitus, alcoholic liver disease and suicide.ResultsDuring a mean follow-up time of 5.9 years, 7665 deaths occurred. We found a dose–response association between levels of PD and all-cause mortality, with the adjusted HRs (95% CI) elevated for all levels of PD, when compared to asymptomatic levels: subclinical 1.10 (1.03–1.16), symptomatic 1.36 (1.26–1.46) and highly symptomatic 1.57 (1.37–1.81). A similar association was found for all CVDs and certain CVD subtypes, but not for cancers, cerebrovascular diseases diabetes mellitus. Excess mortality attributable to suicide and alcoholic liver disease was evident among those with levels of PD only.ConclusionPD symptoms, of all levels, were associated with an increased risk of all-cause and CVD-specific mortality while higher PD only was associated with suicide. These findings emphasise the need for lifestyle interventions targeted towards improving physical health disparities among those with PD.

Background Multimorbidity is a rising public health concern. Indicators that address these complex health conditions are often exclusively devoted to physical diseases. Because of their high disease burden, mental health disorders ought to be considered as well. This paper aims to measure the added value of including a mental health dimension in a population-based multimorbidity indicator and identify which mental health measures are most appropriate. Methods Secondary analyses were conducted on data from the Belgian Health Interview Survey 2018. We compared the prevalence of different multimorbidity indicators (MIs) in relation to health impact measures, such as quality of life (EQ-5D score) and activity limitation (GALI). The MIs differed as to the health conditions involved: one was based on physical conditions only; the other three included mental health dimensions that were either self-reported or assessed by a scale (GAD-7, PHQ-9, and GHQ-12). We performed linear and logistic regressions to assess the association between the MIs and the health correlates and compared the goodness of fit of the different models. Results MI prevalence was higher when including a mental health dimension assessed with the GHQ-12 (42.0%) and with the GAD-7 or the PHQ-9 (39.4%) as compared to physical conditions only (35.0%). Associations between the MI and health correlates were consistently stronger if the MI included a mental health dimension. The regression models with MI including the GAD-7 and PHQ-9 showed the strongest association between MI and the health correlates and also had the best goodness-of-fit measures. Conclusions MIs that only take physical conditions into account underestimate their impact on individuals’ lives. Including mental ill-health in an MI is key to linking it to health correlates.