Smoking may compromise physical function long before it kills you.

Introduction: Although prior research has demonstrated an association between smoking and worse physical function, most of those studies are based on older people and do not evaluate whether the age-related increase in physical limitations differs by smoking history. We quantify how the magnitude of the smoking differential varies across age. Methods: This cohort study comprised a national sample of Americans aged 20-75 in 1995-1996, who were re-interviewed in 2004-2005 and 2013-2014. Our analysis was restricted to respondents who completed the self-administered questionnaires at Wave 1 (N = 6,325). Follow-up observations for those respondents were included if they completed the self-administered questionnaires at Wave 2 (N = 3,929) and/or Wave 3 (N = 2,849). The final analysis sample comprised 13,103 observations over a follow-up period of up to 19 years (1995-2014). We used a linear mixed model to regress physical limitations on smoking status at baseline adjusted for sex, age, race, socioeconomic status, alcohol abuse, drug abuse, and obesity with an interaction between age and smoking to test whether the age pattern of physical limitations differed by smoking history. Additional models incorporated measures of smoking duration and intensity. Results: In the fully-adjusted model, smokers exhibited a steeper age-related increase in physical limitations than never smokers. Thus, the disparities in physical limitations by smoking status widened with age but were evident even at young ages. The estimated differential between heavy smokers and never smokers rose from 0.24 SD at age 30 to 0.49 SD at age 80. At younger ages, heavy smokers who quit recently fared worse than current light smokers and not much better than current heavy smokers. Discussion: We know smoking is bad for our health, but these results reveal that differences in physical limitations by smoking history are evident even at ages as young as 30. Physical limitations that emerge early in life are likely to have an especially large impact because they can jeopardize health for decades of remaining life. Smoking probably will not kill you at young age, but it may compromise your physical function long before it kills you. Just do not do it.

Is the Pain killing you? Could Pain interference be a warning signal for midlife mortality?

Although prior studies have documented an association between various measures of pain and mortality, none of those studies has evaluated whether the association between pain and mortality varies significantly by age. We suspect that pain-particularly pain that interferes with the ability to lead a normal life-could be an early warning sign that may portend increased risk of physical impairment and mortality later in life. In this paper, we investigated whether pain was associated with increased mortality risk, particularly in midlife. Data came from the Midlife in the US study, which sampled non-institutionalized, English-speaking adults aged 25-74 in the contiguous United States in 1995-96. Our analysis included 4041 respondents who completed a follow-up self-administered questionnaire in 2004-05, 2703 of whom completed another self-administered questionnaire in 2013-14. We modeled mortality through December 31, 2021. In demographic-adjusted models, pain interference was more strongly associated with mortality than other pain measures, and the association was stronger at younger ages. The hazard ratio for pain interference declined from 1.39 per SD (95% CI 1.26-1.54) at age 60 to 1.14 (95% CI 1.04-1.24) at age 90. Although potential confounders accounted for more than 60% of the association with premature mortality, pain interference remained significantly associated with increased mortality rates (HR = 1.13 at age 60, 95% CI 1.02-1.26). We found no evidence that the association between pain and mortality was driven by cancer. If anything, pain interference was more strongly associated with cardiovascular than cancer mortality. At the oldest ages, physical function is likely to be a better predictor of mortality than pain. Yet, pain interference may be a useful warning sign at younger ages, when there are fewer physical limitations and mortality rates are low. It may be particularly helpful in identifying risk of premature mortality in midlife, before the emergence of severe physical limitations.

Assessment of Mortality Disparities by Wealth Relative to Other Measures of Socioeconomic Status Among US Adults.

Importance: The association between wealth and mortality is likely to be nonlinear and may result from selection and reverse causality. Objective: To compare the magnitude of mortality disparities by wealth relative to other measures of socioeconomic status (SES). Design, Setting, and Participants: This population-based cohort study began in 1995 to 1996, with approximately 18 years of mortality follow-up. These analyses were completed in November 2021. Data were derived from a population-based sample that targeted noninstitutionalized, English-speaking adults aged 25 to 74 years in the contiguous US. The response rate for the telephone interview ranged from 60% (twin subsample) to 70% (main sample). A self-administered questionnaire was completed by 89% of those interviewed by telephone. Exposures: Net assets of the respondent and spouse or partner in 1995 to 1996. Main Outcomes and Measures: All-cause mortality. Results: Among 6320 respondents (mean [SD] age at baseline, 46.9 [12.9] years; 3318 women [52.5%]), 1000 (15.8%) died by May 31, 2013. Adjusted for age, sex, and race, the mortality disparity by wealth was larger than the disparities by education, occupation, income, or childhood SES, especially at the oldest ages. After age 65 years, the hazard ratio [HR] was 2.69 (95% CI, 2.00-3.62) for those with no assets relative to those with at least $300 000 of wealth (in 1995 dollars), which translated into a 31 percentage point differential in estimated probability of surviving from age 65 years to 85 years (40% vs 71%). Additional wealth greater than $500 000 was not associated with lower mortality. In fully adjusted models, there was still a sizeable wealth disparity in mortality after age 65 years (HR, 1.89; 95% CI, 1.33-2.67). After adjustment for confounders, the estimated probability of surviving from age 65 to 85 years was 19 percentage points higher for persons with at least $300 000 in wealth (70%) than for those with no assets (51%), but there was a much larger 37 percentage point differential between never smokers (70%) and current smokers (33%). Conclusions and Relevance: In this cohort study, the fully adjusted disparity in mortality associated with wealth beyond age 65 years remained sizeable but was much smaller than the smoking differential.

Socioeconomic disparities in U.S. mortality: The role of smoking and alcohol/drug abuse.

Prior studies have identified smoking as a key driver of socioeconomic disparities in U.S. mortality, but the growing drug epidemic leads us to question whether drug abuse is exacerbating those disparities, particularly for mortality from external causes. We use data from a national survey of midlife Americans to evaluate socioeconomic disparities in all-cause and cause-specific mortality over an 18-year period (1995-2013). Then, we use marginal structural modeling to quantify the indirect effects of smoking and alcohol/drug abuse in mediating those disparities. Our results demonstrate that alcohol/drug abuse makes little contribution to socioeconomic disparities in all-cause mortality, probably because the prevalence of substance abuse is low and socioeconomic differences in abuse are small, especially at older ages when most Americans die. Smoking prevalence is much higher than drug/alcohol abuse and socioeconomic differentials in smoking are large and have widened among younger cohorts. Not surprisingly, smoking accounts for the majority (62%) of the socioeconomic disparity in mortality from smoking-related diseases, but smoking also makes a substantial contribution to cardiovascular (38%) and all-cause mortality (34%). Based on the observed cohort patterns of smoking, we predict that smoking will further widen SES disparities in all-cause mortality until at least 2045 for men and even later for women. Although we cannot yet determine the mortality consequences of recent widening of the socioeconomic disparities in drug abuse, social inequalities in mortality are likely to grow even wider over the coming decades as the legacy of smoking and the recent drug epidemic take their toll.

Predicting Survival from Telomere Length versus Conventional Predictors: A Multinational Population-Based Cohort Study.

Telomere length has generated substantial interest as a potential predictor of aging-related diseases and mortality. Some studies have reported significant associations, but few have tested its ability to discriminate between decedents and survivors compared with a broad range of well-established predictors that include both biomarkers and commonly collected self-reported data. Our aim here was to quantify the prognostic value of leukocyte telomere length relative to age, sex, and 19 other variables for predicting five-year mortality among older persons in three countries. We used data from nationally representative surveys in Costa Rica (N = 923, aged 61+), Taiwan (N = 976, aged 54+), and the U.S. (N = 2672, aged 60+). Our study used a prospective cohort design with all-cause mortality during five years post-exam as the outcome. We fit Cox hazards models separately by country, and assessed the discriminatory ability of each predictor. Age was, by far, the single best predictor of all-cause mortality, whereas leukocyte telomere length was only somewhat better than random chance in terms of discriminating between decedents and survivors. After adjustment for age and sex, telomere length ranked between 15th and 17th (out of 20), and its incremental contribution was small; nine self-reported variables (e.g., mobility, global self-assessed health status, limitations with activities of daily living, smoking status), a cognitive assessment, and three biological markers (C-reactive protein, serum creatinine, and glycosylated hemoglobin) were more powerful predictors of mortality in all three countries. Results were similar for cause-specific models (i.e., mortality from cardiovascular disease, cancer, and all other causes combined). Leukocyte telomere length had a statistically discernible, but weak, association with mortality, but it did not predict survival as well as age or many other self-reported variables. Although telomere length may eventually help scientists understand aging, more powerful and more easily obtained tools are available for predicting survival.

Quantifying the value of biomarkers for predicting mortality.

PURPOSE: In light of widespread interest in the prognostic value of biomarkers, we apply three discrimination measures to evaluate the incremental value of biomarkers--beyond self-reported measures--for predicting all-cause mortality. We assess whether all three measures--area under the receiver-operating characteristic curve, continuous net reclassification improvement, and integrated discrimination improvement--lead to the same conclusions. METHODS: We use longitudinal data from a nationally representative sample of older Taiwanese (n = 639, aged 54 or older in 2000, examined in 2000 and 2006, with mortality follow-up through 2011). We estimate age-specific mortality using a Gompertz hazard model. RESULTS: The broad conclusions are consistent across the three discrimination measures and support the inclusion of biomarkers, particularly inflammatory markers, in household surveys. Although the rank ordering of individual biomarkers varies across discrimination measures, the following is true for all three: interleukin-6 is the strongest predictor, the other three inflammatory markers make the top 10, and homocysteine ranks second or third. CONCLUSIONS: The consistency of most of our findings across metrics should provide comfort to researchers using discrimination measures to evaluate the prognostic value of biomarkers. However, because the degree of consistency varies with the level of detail inherent in the research question, we recommend that researchers confirm results with multiple discrimination measures.

Perceived stress and mortality in a Taiwanese older adult population.

Perceived stress is associated with poor health outcomes including negative affect, increased susceptibility to the common cold and cardiovascular disease; the consequences of perceived stress for mortality, however, have received less attention. This study characterizes the relationship between perceived stress and 11-year mortality in a population of Taiwanese adults aged 53+ years. Using the Survey of Health and Living Status of the Near Elderly and Elderly of Taiwan, we calculated a composite measure of perceived stress based on six items pertaining to the health, financial situation, and occupation of the respondents and their families. Proportional hazard models were used to determine whether perceived stress predicted mortality. After adjusting for sociodemographic factors only, we found that a one standard deviation increase in perceived stress was associated with a 19% increase in all-cause mortality risk during the 11-year follow-up period (hazard ratio, HR = 1.19, 95% confidence interval, CI 1.13-1.26). The relationship was greatly attenuated when perceptions of stress regarding health were excluded, and was not significant after adjusting for medical conditions, mobility limitations and depressive symptoms. We conclude that the association between perceived stress and mortality is explained by an individual's current health; however, our data do not allow us to distinguish between two possible interpretations of this conclusion: (a) the relationship between perceived stress and mortality is spurious, or (b) poor health acts as the mediator.

Social relationships and inflammatory markers: an analysis of Taiwan and the U.S.

We evaluated the association between two aspects of social relationships and six inflammatory markers in Taiwan and the U.S. These two countries share similar levels of current life expectancy, but exhibit important differences in social structure. The data comprised population based samples from Taiwan (aged 53+; n=962) and the U.S. (aged 35-86; n=990) collected between 2003 and 2009. Circulating levels of interleukin-6 (IL-6), C-reactive protein (CRP), fibrinogen, and soluble forms of intercellular adhesion molecule 1, E-selectin, and IL-6 receptor (sIL-6R) were measured in fasting blood samples. A social integration score was based on marital status, contact with family and friends, church attendance, and other social participation. A perceived social support index was based on questions regarding the availability of care and support from family and friends. Linear regression models tested the association between these two measures and each inflammatory marker controlling for sociodemographic characteristics, obesity, medication use, and baseline health status. After adjusting for potential confounders, social integration had a significant but weak inverse association with CRP in Taiwan. Perceived social support was significant in two of 12 models, and the coefficient was positive (i.e., higher support was associated with higher CRP and sIL-6R in the U.S.). We found no evidence that the coefficients for social relationship measures varied by sex or age. Our results yielded limited evidence of a weak association between two dimensions of social relationships and six inflammatory markers in Taiwan and the U.S. Given that the literature suggests a strong link between social relationships and mortality, and that inflammation plays an important role in the leading causes of death, we had expected to find consistent and moderately strong associations between social relationships and inflammatory markers. The small effect sizes and lack of robustness across markers were surprising.

A new method for estimating smoking-attributable mortality in high-income countries.

BACKGROUND: Cigarette smoking is responsible for a massive loss of life in both developed and developing countries. This article develops an alternative to the Peto-Lopez method for estimating the number or fraction of smoking-attributable deaths in high-income countries. METHODS: We use lung cancer death rates as an indicator of the damage caused by smoking. Using administrative data for the population aged > or =50 years from 20 high-income countries in the period from 1950 to 2006, we estimate a negative binomial regression model that predicts mortality from causes other than lung cancer as a function of lung cancer mortality and other variables. Using this regression model, we estimate smoking-attributable deaths based on the difference between observed death rates from lung cancer and expected rates among non-smokers. RESULTS: Combining the estimated number of excess deaths from lung cancer with those from other causes, we find that among males in 1955 the smoking-attributable fraction was highest in Finland (18%); among women, no country exceeded 1%. By 2003, Hungary had the highest fraction of smoking-attributable deaths among males (32%), whereas the USA held that position among women (24%). Our estimates are remarkably similar to those produced by the Peto-Lopez method, a result that supports the validity of each approach. CONCLUSIONS: We provide a simple and straightforward method for estimating the proportion of deaths attributable to smoking in high-income countries. Our results demonstrate that smoking has played a central role in levels, trends and international differences in mortality over the past half century.

The role of life satisfaction and depressive symptoms in all-cause mortality.

The objective of this study was to investigate whether life satisfaction and depressive symptoms are independent predictors of mortality in a non-Western sample of adults. The sample included 5,131 adults (ages 50-95 at baseline) in Taiwan who participated in the Survey of Health and Living Status of the Near Elderly and Elderly. There were 1,815 deaths recorded over a 10-year period. Higher life satisfaction significantly predicted lower risk of mortality after controlling for age, sex, education, marital status, and health status. Depressive symptoms significantly predicted higher risk of mortality. A significant interaction with age revealed that the protective effect of life satisfaction weakened with age. The results suggest that life satisfaction and depressive symptoms independently predict mortality risk in adults.

Improving mortality prediction using biosocial surveys.

The authors used data from a nationally representative survey of 933 adults aged 54 years or older (mean age = 66.2 years; standard deviation, 8.0) in Taiwan to explore whether mortality prediction at older ages is improved by the use of 3 clusters of biomarkers: 1) standard cardiovascular and metabolic risk factors; 2) markers of disease progression; and 3) nonclinical (neuroendocrine and immune) markers. They also evaluated the extent to which these biomarkers account for the female advantage in survival. Estimates from logistic regression models of the probability of dying between 2000 and 2006 (162 deaths; mean length of follow-up = 5.8 years) showed that inclusion of each of the 3 sets of markers significantly (P = 0.024, P = 0.002, and P = 0.003, respectively) improved discriminatory power in comparison with a base model that adjusted for demographic characteristics, smoking, and baseline health status. The set of disease progression markers and the set of nonclinical markers each provided more discriminatory power than standard risk factors. Most of the excess male mortality resulted from the men being more likely than women to smoke, but each of 3 markers related to disease progression or inflammation (albumin, neutrophils, and interleukin-6) explained more than 10% of excess male mortality.

The narrowing sex differential in life expectancy in high-income populations: effects of differences in the age pattern of mortality.

Using data from the Human Mortality Database for 29 high-income national populations (1751-2004), we review trends in the sex differential in e(0). The widening of this gap during most of the 1900s was due largely to a slower mortality decline for males than females, which previous studies attributed to behavioural factors (e.g., smoking). More recently, the gap began to narrow in most countries, and researchers tried to explain this reversal with the same factors. However, our decomposition analysis reveals that, for the majority of countries, the recent narrowing is due primarily to sex differences in the age pattern of mortality rather than declining sex ratios in mortality: the same rate of mortality decline produces smaller gains in e(0) for women than for men because women's deaths are less dispersed across age (i.e., survivorship is more rectangular).

Dehydroepiandrosterone sulfate (DHEAS) and risk for mortality among older Taiwanese.

PURPOSE: Studies based on Western populations showed a negative relationship between dehydroepiandrosterone sulfate (DHEAS) level and mortality, but no study examined this relationship in a non-Western country. We use data from a large, nationally representative sample (n = 963) of older Taiwanese to investigate whether serum DHEAS, predicts subsequent mortality during a 3-year period (2000 to 2003) and whether an effect remains after controlling for baseline health status. METHODS: Baseline data collection included an individual interview, physical examination, and blood sample. A logit model is used to test the relationship between DHEAS level and risk for mortality, controlling for age, sex, and smoking status. RESULTS: Results show a marginally significant inverse relationship between DHEAS level and 3-year mortality risk. Participants with low DHEAS levels (<54.5 microg/dL) have 64% greater odds of dying than those with higher DHEAS levels (p < 0.06). After adjusting for various indicators of health status in 2000, the odds ratio (OR) for low DHEAS level remains substantial (OR = 1.41), but not statistically significant. CONCLUSIONS: Although the analysis is limited by the short follow-up and small number of deaths, results are consistent with the notion that DHEAS level has a sizeable effect on mortality.

Dehydroepiandrosterone sulfate (DHEAS) and health: does the relationship differ by sex?

This study uses data from a large, nationally representative sample of older Taiwanese (aged 54 and older in 2000) to investigate sex differences in the relationship between DHEAS and various health outcomes. Data collection included an individual interview, a physical examination, and samples of blood and (12-h) urine. Regression models of health outcomes on DHEAS are estimated in two steps: first, including only controls for age and sex as well as an interaction between DHEAS and sex; and second, adding covariates likely to be related to both DHEAS and health outcomes (e.g. smoking). Results reveal that higher levels of DHEAS are associated with fewer mobility limitations (especially for women), better cognitive function (among women but not men), and better self-rated health (significant only for men but of similar magnitude for women). These findings are in contrast to previous studies conducted in the US and Europe that generally find stronger associations for men than women. Also unlike previous studies, which often demonstrate a negative relationship between DHEAS and depressive symptoms at least for women, we find little evidence of such a relationship for either sex.