Impact of Healthy Lifestyle Factors on Life Expectancy and Lifetime Health Care Expenditure: Nationwide Cohort Study.

BACKGROUND: The association between lifestyle risk factors and the risk of mortality and chronic diseases has been established, while limited research has explored the impact of healthy lifestyle factors on lifetime health care expenditure using longitudinal individual data. OBJECTIVE: We aimed to determine the individual and combined effects of 5 healthy lifestyle factors on life expectancy and lifetime health care expenditure in Taiwan. METHODS: Using data from the National Health Interview Survey cohort, 5 healthy lifestyle behaviors were defined and analyzed: nonsmoking, avoiding excessive alcohol consumption, engaging in sufficient physical activity, ensuring sufficient fruit and vegetable intake, and maintaining a normal weight. We used a rolling extrapolation algorithm that incorporated inverse probability of treatment weighting to estimate the life expectancy and lifetime health care expenditure of the study populations with and without healthy lifestyle factors. RESULTS: A total of 19,893 participants aged ≥30 (mean age 48.8, SD 13.4) years were included, with 3815 deaths recorded during a median follow-up period of 15.6 years. The life expectancy and per capita estimated lifetime health care expenditures for the overall study population were 35.32 years and US $58,560, respectively. Multivariable-adjusted hazard ratios for all-cause mortality in participants adhering to all 5 healthy lifestyle factors, compared with those adhering to none, were 0.37 (95% CI 0.27-0.49). We found significant increases in life expectancy for nonsmokers (2.31 years; 95% CI 0.04-5.13; P=.03), those with sufficient physical activity (1.85 years; 95% CI 0.25-4.34; P=.02), and those with adequate fruit and vegetable intake (3.25 years; 95% CI 1.29-6.81; P=.01). In addition, nonsmokers experienced a significant reduction in annual health care expenditure (-9.78%; 95% CI -46.53% to -1.45%; P=.03), as did individuals maintaining optimal body weight (-18.36%; 95% CI -29.66% to -8.57%; P=.01). Overall, participants adhering to all 5 healthy lifestyle behaviors exhibited a life gain of 7.13 years (95% CI 1.33-11.11; P=.02) compared with those adhering to one or none, with a life expectancy of 29.19 years (95% CI 25.45-33.62). Furthermore, individuals adopting all 5 healthy lifestyle factors experienced an average annual health care expenditure reduction of 28.12% (95% CI 4.43%-57.61%; P=.02) compared with those adopting one or none. CONCLUSIONS: Adopting a healthy lifestyle is associated with a longer life expectancy and a reduction of health care expenditure in Taiwanese adults. This contributes to a more comprehensive understanding of the impact of healthy lifestyle factors on the overall health and economic burden.

Mortality risk and years of life lost for people with reduced renal function detected from regular health checkup: A matched cohort study.

With the increasing threat of metabolic syndromes, a focus on maintaining kidney health from early- to mid-adulthood is necessary. This study elucidates mortality risk and years of life lost (YLLs) due to abnormal renal function. This was a retrospective, matched cohort study from health checkup data from 2000 to 2015. We identified 12,774 participants with abnormal renal function (eGFR < 60 mL/min/1.73 m2) and used propensity score matching to identify 25,548 participants with normal renal function (eGFR ≥ 60). YLLs were estimated using the life expectancy differences between the abnormal and matched normal cohorts. Cox models were used to estimate the adjusted mortality risk. The estimated life expectancy of participants with proteinuria and eGFR < 60 was 26.24 years, with a 95 % confidence interval of (23.96, 29.36), 17.62 (16.37, 18.78), and 11.70 (11.02, 12.46) for age groups of 30 - 54, 55 - 64, and 65 - 79 years, respectively. The estimated YLLs of participants with proteinuria and eGFR < 60, as compared with the matched normal cohort, were 17.86 (13.41, 20.36), 12.55 (11.41, 13.78), and 8.31 (7.47, 9.13) years for the three age groups, respectively. The Cox model estimates of mortality hazard ratios of participants having proteinuria and eGFR < 60 against matched referents were 5.29 (3.97, 7.05), 3.99 (3.34, 4.75), and 3.05 (2.62, 3.55) for the three age groups, respectively. Abnormal renal function shortens life expectancy, particularly in patients with proteinuria and in younger adults. Active health management of renal function can reduce the disease burden.

Lifetime exposure to PM2.5 air pollution and disability-adjusted life years due to cardiopulmonary disease: A modeling study based on nationwide longitudinal data.

BACKGROUND: As knowledge of the health risks of PM2.5 has grown, the focus of PM2.5-related health impact assessments has evolved from simple risk models to burden-of-disease estimates. We proposed an ecological approach to directly estimate the impacts of lifetime exposure to PM2.5 on expected health losses due to cardiopulmonary diseases for older adult populations in Taiwan. METHODS: We created study cohorts of 3.5 million older people living in 350 townships in Taiwan. We used a weighted regression model, with adjustments of area characteristic variables, to directly estimate the impacts of lifetime mean PM2.5 exposure on health losses among the 350 cohorts. Potential avoidable disability-adjusted life years (DALYs) by assuming that ambient PM2.5 met the air quality standard was estimated. RESULTS: Each 10 µg/m3 increase in lifetime mean exposure to PM2.5 for an individual corresponded to an increment of 0.25 (95 % confidence interval (CI): 0.18-0.32) DALYs due to cardiopulmonary diseases, after adjusting for a wide range of ecological covariates. We estimated that 611.8 (95 % CI: 440.4-783.2) DALYs per 1000 older adult population could potentially be avoided by achieving air quality standards of WHO in Taiwan. CONCLUSIONS: Reducing PM2.5 pollution in Taiwan associated with significant health co-benefits, providing important implications for public health and environmental management.

Later-Life Exposure to Moderate PM2.5 Air Pollution and Life Loss of Older Adults in Taiwan.

BACKGROUND: Few studies have directly estimated expected life loss attributable to lifetime exposure to fine particulate matter (PM2.5). METHODS: We used claims data from Taiwan's National Health Insurance to create 63 study cohorts of 1.91 million residents aged 60-79 years old residing in small areas where air quality monitoring stations are situated. The survival status of each person was followed from 2001 to 2016. We applied an extrapolation algorithm to estimate the lifetime survival function so that we could directly estimate life expectancy (LE) and the lifetime exposure to PM2.5 of each cohort. We estimated the association between LE and lifetime exposure to PM2.5 among the 63 cohorts. We also fit a Cox proportional hazards model to all the data combined to estimate the relative risk of mortality. RESULTS: Older adults who lived in an area with a higher lifetime weighted average PM2.5 of 10 µ g / m 3 had a shortened LE by 0.34 (95% CI: 0.22-0.46) years. The hazard ratio of mortality was 1.0245 (1.0242-1.0248) per one µ g / m 3 increase in lifetime average PM2.5. CONCLUSION: This study provides strong evidence that later-life exposure to moderate PM2.5 air pollution had a substantial impact on the life loss of older adults.

Estimation of Quality-Adjusted Life Expectancy of Patients With Oral Cancer: Integration of Lifetime Survival With Repeated Quality-of-Life Measurements.

BACKGROUND: Quality-adjusted life year is widely applied nowadays, which consider both survival and quality of life (QoL). When most diseases are becoming chronic, it is imperative to quantify the overall health impact of a disease in lifetime perspective. OBJECTIVE: The purpose of this study is to introduce methods for estimating quality-adjusted life expectancy (QALE) and loss of QALE in patients with a disease or specific conditions. METHODS: The QALE of an index cohort can be represented as the integration of the product of lifetime survival function and mean QoL function. We introduce a robust extrapolation approach for estimating lifetime survival function and propose an approach for estimating lifetime mean QoL function for studies with limited follow-up. The best part of the proposed method is that the survival data and QoL data can be collected separately. A cohort of patients with a specific condition can be identified by databases that regularly collect data for the control of diseases, and their survival status is verified by linking to a mortality registry. Although nationwide QoL data are not available, researchers can implement a relative short-term follow-up interview on a random sample of patients to collect QoL data. For demonstration, we applied the proposed methods to estimate QALE and loss of QALE of oral cancer patients. RESULTS: The estimates (95% confidence interval) of QALE for oral cancer patients were 11.0 (10.5-11.6) and 14.2 (12.7-15.5) quality-adjusted life years (QALYs) for men and women, respectively. The estimates of loss of QALE for the male and female patients with oral cancer were 14.4 (13.8-14.9) and 7.5 (6.2-9.0) QALYs, respectively. CONCLUSIONS: The methods for estimating QALE and loss of QALE can be applied to economic evaluation of cancer control, including screening.

Assessing effects of personal behaviors and environmental exposure on asthma episodes: a diary-based approach.

BACKGROUND: Quantifying the effects of personal health behaviors and environmental exposure on asthma flare-ups is a challenge. Most studies have focused on monitoring the symptoms and drug usage for relieving symptoms. In this study, we emphasize the need to understand how personal and environmental conditions are related to the occurrence of asthma symptoms. METHODS: We designed an online health diary platform to collect personal health behaviors from children, their parents and other adults with any allergic diseases including asthma, allergic rhinitis, atopic dermatitis and allergic conjunctivitis. The participants used mobile devices or computers to record their daily health-related activities such as sleep, exercise, diet, perception of air quality and temperature, and asthma symptoms. The participants also recorded secondhand smoke exposure and the time of activities, which were combined with ambient air quality measurements for calculating personal air pollution exposure. A generalized linear mixed model was used to estimate the effects of the factors. RESULTS: During the study period (January 2017-June 2017, and October 2017-September 2018), 132 participants provided 25,016 diary entries, and 84 participants had experienced asthma symptoms in 1458 diary entries. The results showed some different risk factors for the minors and adults. For minors, high-intensity exercise, contact with persons with influenza-like illness (ILI) and the perception of hot temperature and bad indoor air quality were associated with the occurrence of asthma episodes. The identified risk factors for the adult participants included having dehumidifiers at home, exposure to secondhand smoke, having bad sleep quality, contact with persons with ILI, not eating fruit and seafood, perceiving cold temperature, bad quality of indoor and outdoor air, and exposure to high concentration of ozone. CONCLUSIONS: The revealed personal risk factors and perceptions of air quality and temperature may provide guidance on behavioral change for people susceptible to asthma to help control acute onset and severe exacerbation of asthma flare-ups.

Detecting concurrent mood in daily contact networks: an online participatory cohort study with a diary approach.

OBJECTIVES: This paper examines how people express personal mood concurrently with those connected with them by one or two degrees of separation. DESIGN: Participatory cohort study. SETTING: Online contact diary. PARTICIPANTS: 133 participants kept online diaries for 7 months in 2014, which included 127 455 contacts with 12 070 persons. MAIN OUTCOME MEASURES: Diary keepers rated a contacted person's mood during each specific contact, as well as the strength of ties between any pairs of such contacted persons. Such rich information about ties and contacts enable us to construct a complete contact network for each diary keeper, along with the network members' mood and tie strength. We calculate one's overall mood by that person's average mood score during the study period and take the shortest path between any given pair of contacted persons as the degree of separation. We further assume that two connecting persons in a contact network have made contact with each other during the study period, which allows us to examine whether and how personal moods occur concurrently within these contact networks. RESULTS: Using mixed-effects models while controlling for covariates at individual, tie and contact levels, we show that personal mood score positively and significantly correlates with the average mood among those directly tied to the person. The same effect remains positive and significant for those connected to the person by two degrees, although the effect size is reduced by about one-half. The mood of anyone separated by more than two degrees is statistically irrelevant. CONCLUSIONS: Applying network perspectives and rich data at both tie and contact levels to inquiries about subjective well-being, the current study sheds new light on how an improved diary approach can help explain the sophisticated ways in which individuals express their personal moods concurrently during social interactions in everyday life, contact by contact.

Estimating the Risk of Influenza-Like Illness Transmission Through Social Contacts: Web-Based Participatory Cohort Study.

BACKGROUND: Epidemiological studies on influenza have focused mostly on enhancing vaccination coverage or promoting personal hygiene behavior. Few studies have investigated potential effects of personal health behaviors and social contacts on the risk of getting influenza-like illness (ILI). OBJECTIVE: Taking advantage of an online participatory cohort, this study aimed to estimate the increased risk of getting ILI after contact with infected persons and examine how personal health behaviors, weather, and air pollution affect the probability of getting ILI. METHODS: A Web-based platform was designed for participants to record daily health behaviors and social contacts during the influenza season of October 1, 2015 to March 31, 2016, in Taiwan. Data on sleep, diet, physical activity, self-reported ILI, and contact with infected persons were retrieved from the diaries. Measurements of weather and air pollutants were used for calculating environmental exposure levels for the participants. We fitted a mixed-effects logistic regression model to the daily measurements of the diary keepers to estimate the effects of these variables on the risk of getting ILI. RESULTS: During the influenza season, 160 participants provided 14,317 health diaries and recorded 124,222 face-to-face contacts. The model estimated odds ratio of getting ILI was 1.87 (95% CI 1.40-2.50) when a person had contact with others having ILI in the previous 3 days. Longer duration of physical exercise and eating more fruits, beans, and dairy products were associated with lower risk of getting ILI. However, staying up late was linked to an elevated risk of getting ILI. Higher variation of ambient temperature and worse air quality were associated with increased risk of developing ILI. CONCLUSIONS: Developing a healthier lifestyle, avoiding contact with persons having ILI symptoms, and staying alert with respect to temperature changes and air quality can reduce the risk of getting ILI.

Estimating lifetime medical costs from censored claims data.

Claims databases consisting of routinely collected longitudinal records of medical expenditures are increasingly utilized for estimating expected medical costs of patients with a specific condition. Survival data of the patients of interest are usually highly censored, and observed expenditures are incomplete. In this study, we propose a survival-adjusted estimator for estimating mean lifetime costs, which integrates the product of the survival function and the mean cost function over the lifetime horizon. The survival function is estimated by a new algorithm of rolling extrapolation, aided by external information of age- and sex-matched referents simulated from national vital statistics. The mean cost function is estimated by a weighted average of mean expenditures of patients in a number of months prior to their death, of which the number could be determined by observed costs in their final months, and the weights depend on extrapolated hazards. We evaluate the performance of the proposed approach in comparison with that of a popular method using simulated data under various scenarios and 2 cohorts of intracerebral hemorrhage and ischemic stroke patients with a maximum follow-up of 13 years and conclude that our new method estimates the mean lifetime costs more accurately.

Daily forecast of dengue fever incidents for urban villages in a city.

BACKGROUND: Instead of traditional statistical models for large spatial areas and weekly or monthly temporal units, what public health workers urgently need is a timely risk prediction method for small areas. This risk prediction would provide information for early warning, target surveillance and intervention. METHODS: Daily dengue cases in the 457 urban villages of Kaohsiung City, Taiwan from 2009 to 2012 were used for model development and evaluation. There were in total 2,997 confirmed dengue cases during this period. A logistic regression model was fitted to the daily incidents occurring in the villages for the past 30 days. The fitted model was then used to predict the incidence probabilities of dengue outbreak for the villages the next day. A percentile of the 457*30 fitted incidence probabilities was chosen to determine a cut-point for issuing the alerts. The covariates included three different levels of spatial effect, and with four lag time periods. The population density and the meteorological conditions were also included for the prediction. RESULTS: The performance of the prediction models was evaluated on 122 consecutive days from September 1 to December 31, 2012. With the 80th percentile threshold, the median sensitivity was 83% and the median false positive rate was 23%. We found that most of the coefficients of the predictors of having cases at the same village in the previous 14 days were positive and significant for the 122 daily updated models. The estimated coefficients of population density were significant during the peak of the epidemic in 2012. CONCLUSIONS: The proposed method can provide near real-time dengue risk prediction for a small area. This can serve as a useful decision making tool for front-line public health workers to control dengue epidemics. The precision of the spatial and temporal units can be easily adjusted to different settings for different cities.

An index related to the autocorrelation function of RR intervals for the analysis of heart rate variability.

Heart rate variability (HRV) is concerned with analysis of the variations in the intervals between heartbeats, known as RR intervals. Commonly used HRV indices may be insensitive in detecting some dynamic changes related to complex autocorrelation functions of the RR intervals. For example, indices SD1 and SD2 of the Poincaré plot can be expressed by the variance and first auto-covariance of the signal. The acceleration change index is related to the autocorrelation functions of the series only at the first three lags. We extend the idea of characterizing the sign of differences of a time series to propose a new index called VRL, which is the variance of the run length of the sign of the lagged differentiated time series. The theoretical study shows that VRL is directly related to the autocorrelation functions of the RR series at larger lags. Simulated data are used to validate the theoretical results and assess the power of testing group differences measured with VRL and other HRV indices. The performance of VRL is also evaluated for classifying subjects with normal sinus rhythm and congestive heart failure using the RR intervals taken from the PhysioNet database. We apply the index to RR intervals from an animal study of long-term exposure to particulate matter. The VRL values for the young mice susceptible to atherosclerosis in the control and exposure groups decreased gradually with different slopes after several weeks of exposure. The exposure effect changes in this HRV index estimated by fitting a generalized additive model are significant after 7 weeks of exposure.

Effects of concentrated ambient particles on heart rate variability in spontaneously hypertensive rats.

In the present study, the cardiovascular toxicity of PM(2.5) was determined in spontaneously hypertensive (SH) rats using the standard deviation of normal-to-normal intervals (SDNN) and root mean square of successive differences of adjacent normal-to-normal intervals (RMSSD) as outcome measurements. Four SH rats implanted with radiotelemetry transmitters were repeatedly exposed to concentrated PM(2.5) in nose-only exposure chambers. Gravimetric analysis revealed the mean post-concentrating mass concentration of particles during the 5 h of exposure was 202 mug/m(3). Using each animal as its own control and linear mixed-effects model, to adjust for circadian nature and individual differences, we found that SDNN decreased by 15% initially then gradually decreased to 60% of the initial value at the end of exposure. Our results indicate that concentrated PM(2.5) may decrease SDNN on SH rats during PM exposure. The study also showed that SDNN is more sensitive to PM induced effects than RMSSD.

Effects of concentrated ambient particles on heart rate, blood pressure, and cardiac contractility in spontaneously hypertensive rats.

Epidemiological studies have shown that particulate matter (PM) air pollution is associated with cardiovascular mortality and morbidity, especially for particles with aerodynamic diameters under 2.5 microm (PM(2.5)). Recent studies have revealed an association between PM pollution and autonomic functions including heart rate (HR), blood pressure (BP), and heart-rate variability. However, the association and linking mechanisms have not been clearly demonstrated in animal studies. Utilizing a novel approach that employs a mixed-effects model to overcome the problems of variations in diseased animals and circadian cycles, we have previously demonstrated an association between concentrated PM(2.5) and changes of HR and BP in pulmonary hypertensive rats. The objective of this study is to test the plausibility of this methodology and to demonstrate the particle effects under different pathophysiology. The feasibility of cardiac contractility (measured as QA interval, QAI) as an indicator for PM toxicology was also explored. Four spontaneously hypertensive (SH) rats were repeatedly exposed to concentrated PM(2.5) during spring and summer. The mass concentration of particles during the 5 h of exposure was 202.0 +/- 68.8 (mean +/- SE) and 141.0 +/- 54.9 microg/m(3) for spring and summer experiments, respectively. During spring exposures, the maximum increase of HR and mean BP noted at the end of exposure were 51.6 bpm (p <.001) and 8.7 mm Hg (p =.002), respectively. The maximum decrease of QAI noted at the same time was 1.6 ms (p =.001). Though a similar pattern was demonstrated during summer exposures, the responses were less prominent. We conclude that concentrated PM(2.5) may increase HR and mean BP and decrease QAI in SH rats. Our results also show that QAI may be used as an indicator in PM toxicology.