Ambient particulate matter and in-hospital case fatality of acute myocardial infarction: A multi-province cross-sectional study in China.

The acute myocardial infarction (AMI) outcomes have been extensively linked with ambient particulate matter (PM). However, whether a smaller particle has greater impact and the consequent attributable burden associated with PM of different sizes remain unclear. We conducted a multi-province cross-sectional study among AMI patients using the inpatient discharge datasets from four Chinese provinces (Shanxi, Sichuan, Guangxi, and Guangdong) from 2014 to 2019. Ambient PM exposure for each patient was assessed using the ChinaHighAirPollutants dataset. We employed the mixed-effects logistic regression models to evaluate the association of PM of different sizes (PM1, PM2.5, PM10) on in-hospital case fatality. The potential reducible fractions in in-hospital case fatality were estimated through counterfactual analyses. Of 177,749 participants, 125,501 (70.6 %) were male and the in-hospital case fatality rate was 4.9%. For short-term (7-day average) exposure, the odds ratios (ORs) for PM1, PM2.5, and PM10 (per 10 µg/m3) were 1.052 (95 % confidence interval [CI], 1.032-1.071), 1.026 (95 % CI, 1.014-1.037), and 1.016 (95% CI, 1.008-1.024), respectively. The estimated ORs for long-term exposure (annual average) were 1.303 (95 % CI, 1.252-1.356) for PM1, 1.209 (95 % CI, 1.178-1.241) for PM2.5, 1.157 (95 % CI, 1.134-1.181) for PM10. Short-term exposure to PM1 showed the highest potential reducible fraction (8.5 %, 95 % CI, 5.0-11.7 %), followed by PM2.5 and PM10, while the greatest potential reducible fraction of long-term exposure was observed in PM10 (30.9 %, 95 % CI, 27.2-34.4%), followed by PM2.5 and PM1. In summary, PM with smaller size had a more pronounced impact on in-hospital AMI case fatality, with PM1 exhibiting greater effects than PM2.5 and PM10. Substantial health benefits for AMI patients could be achieved by mitigating ambient PM exposure.

Health Insurance Literacy and Medical Care Avoidance Among International Students: A Case Study.

Objectives: This research examines the health insurance literacy and healthcare utilization of international students attending a university in the US Midwest. Methods: One hundred and forty-three undergraduate and graduate students attending a midsize metropolitan university in the Midwest completed an online survey in early 2022. Results: Many students surveyed could not identify the definitions of basic terms, such as copay. Furthermore, about 80% of students surveyed could not determine their financial responsibilities in two medical settings. Regression results show that the continent they are from and the length of their stay in the United States significantly predict their understanding of key health insurance terms. More than half of the international students surveyed indicated they often feel confused about their health insurance (57.34%). Only about 20% have delayed or skipped care due to unfamiliarity with the health insurance system. Conclusion: The health insurance literacy of most international students at the midwestern university we surveyed is not ideal. This and possibly other universities in the United States should take more initiatives to help their international students understand the health insurance system.

The impact of healthcare industry convergence on the performance of the public health system: a geospatial modeling study of provincial panel data from China.

Objective: This paper examines the impact of healthcare industry convergence on the performance of the public health system in the eastern, central, and western regions of China. Methods: Public health performance was measured by a composite index of three standards: average life expectancy at birth, perinatal mortality, and maternal mortality. The healthcare industry convergence was measured using a coupling coordination degree method. The spatial lag, spatial error, and spatial Durbin models were used to estimate the effect of healthcare industry convergence on public health system performance and this effect's spatial dependence and heterogeneity across eastern, central, and western China using panel data from 30 Chinese provinces from 2002 to 2019. Results: The convergence of the healthcare industry significantly promotes regional public health [ß =0.576, 95% CI: (0.331,0.821)]. However, the convergence does not have a spatial spillover effect on the public health system at the national level. Additionally, analysis of regional heterogeneity shows that the direct effects of healthcare industry convergence on public health are positive and statistically significant for Eastern China, statistically insignificant for Central China, and positive and statistically significant for Western China. The indirect effects are negative, statistically significant, positive, statistically significant, and statistically insignificant for these three regions, respectively. Conclusion: Policy efforts should strengthen the convergence between the healthcare industry and relevant industries. It can produce more current healthcare services to improve public health and reduce regional health inequality.

Factors associated with food insecurity among the chronically ill population during the COVID-19 pandemic in the United States.

Introduction: Little is known about food insecurity among Americans with chronic diseases, one of the vulnerable groups in health care. Factors influencing food insecurity among this population group are especially poorly understood. Methods: Using data from the COVID Impact Survey, this cross-sectional study sought to examine food insecurity among adults with chronic diseases in the United States and to identify factors associated with their risks for food insecurity during the COVID-19 pandemic. Results: Nearly 28% of the national and 32% of the regional samples from the COVID Impact Survey were at risk for food insecurity. The logistic regressions show that chronically ill US adults with one of the following characteristics have higher odds of being at risk for food insecurity: younger than 60 years, having financial stress, unemployed, having received food from a food pantry, without health insurance, having a household income lower than $100,000, and without a college degree. Discussion: Targeted policies and programs are warranted to address underlying determinants of food insecurity that adults with chronic illnesses experience.

Short-term air pollution exposure associated with death from kidney diseases: a nationwide time-stratified case-crossover study in China from 2015 to 2019.

BACKGROUND: Long-term exposure to air pollution has been associated with the onset and progression of kidney diseases, but the association between short-term exposure to air pollution and mortality of kidney diseases has not yet been reported. METHODS: A nationally representative sample of 101,919 deaths from kidney diseases was collected from the Chinese Center for Disease Control and Prevention from 2015 to 2019. A time-stratified case-crossover study was applied to determine the associations. Satellite-based estimates of air pollution were assigned to each case and control day using a bilinear interpolation approach and geo-coded residential addresses. Conditional logistic regression models were constructed to estimate the associations adjusting for nonlinear splines of temperature and relative humidity. RESULTS: Each 10 µg/m3 increment in lag 0-1 mean concentrations of air pollutants was associated with a percent increase in death from kidney disease: 1.33% (95% confidence interval [CI]: 0.57% to 2.1%) for PM1, 0.49% (95% CI: 0.10% to 0.88%) for PM2.5, 0.32% (95% CI: 0.08% to 0.57%) for PM10, 1.26% (95% CI: 0.29% to 2.24%) for NO2, and 2.9% (95% CI: 1.68% to 4.15%) for SO2.  CONCLUSIONS: Our study suggests that short-term exposure to ambient PM1, PM2.5, PM10, NO2, and SO2 might be important environmental risk factors for death due to kidney diseases in China.

Self-esteem and weight status of young adults: Findings from a pilot study.

BACKGROUND: Researchers have examined the association between self-esteem and obesity in past studies. However, most studies have focused on pediatric or adolescent populations. In this pilot study, we aim to explore the association of self-esteem with weight status in young adults, a group of individuals in a significant and pivotal period of their lives whose needs and challenges have received little attention in previous studies. MATERIALS AND METHODS: Exactly 127 college juniors and seniors in the Midwest participated in late 2017. For our survey, we collected the following information: body weight, height, self-esteem score from the state self-esteem scale, grade point average, risk of eating disorders, sleep quality, nutritional behavior, lifestyle (smoking, frequency of exercise, alcohol drinking, average daily time watching television, playing video games, and social media use), and demographic and socioeconomic background. We used logistic regression for our analysis. RESULTS: The logistic regression indicates that a one-point increase in the self-esteem score was negatively associated with a young adult's odds of having an unhealthy weight (being overweight or obese) by approximately 3%. Furthermore, soda drinking is a statistically significant factor associated with weight status. CONCLUSIONS: This finding suggests self-esteem is positively associated with a healthy weight in young adults. A larger-scale study should be conducted in the future to validate this relationship and better understand young adults' needs.

Association between maternal family history of hypertension and preterm birth: modification by noise exposure and multivitamin intake.

OBJECTIVE: To measure the effect of maternal family history of hypertension on preterm birth (PTB) and to identify factors that modified this association. METHODS: A case-control study was nested in a prospective cohort of the entire pregnant population in Wuhan, China, from 2011 to 2013. Home-visit interviews were scheduled for all PTBs and their controls, to collect extensive information on maternal exposures to behavioral, environmental, and intergenerational risk factors of PTB. The effects of maternal family history of hypertension on PTB were measured by logistic regression analyses, controlling for potential confounders. Potential effect modifiers were examined using stratified analyses. RESULTS: There were 2393 PTBs and 4263 full-term births out of all eligible births. A positive association was observed between maternal family history of hypertension and PTB, after adjusted for potential confounders (adjusted odds ratio: 1.17 [1.03, 1.33]). A higher effect was observed when mothers were exposed to certain noise during pregnancy (adjusted odds ratio: 1.37 [1.14, 1.65]) and/or when they did not take multivitamins during pregnancy (adjusted odds ratio: 1.46 [1.20, 1.78]), whereas, this association was weaker and no longer significant when mothers took multivitamins during pregnancy (adjusted odds ratio: 1.00 [0.84, 1.19]) and/or when they were not exposed to certain noise during pregnancy (adjusted odds ratio: 1.01 [0.85, 1.12]). The modification effect from maternal multivitamin intake was significant on both spontaneous and medically indicated PTBs, and the modification effect from maternal exposure to certain noise was only significant on spontaneous PTB. CONCLUSIONS: Increased PTB risk was observed for pregnant women with a family history of hypertension in Wuhan, China. This effect was stronger when pregnant women did not take multivitamin and/or exposed to certain noise during pregnancy, than those who took multivitamin and/or unexposed to certain noise.

The Chasm in Percutaneous Coronary Intervention and In-Hospital Mortality Rates Among Acute Myocardial Infarction Patients in Rural and Urban Hospitals in China: A Mediation Analysis.

Objectives: To determine to what extent the inequality in the ability to provide percutaneous coronary intervention (PCI) translates into outcomes for AMI patients in China. Methods: We identified 82,677 patients who had primary diagnoses of AMI and were hospitalized in Shanxi Province, China, between 2013 and 2017. We applied logistic regressions with inverse probability weighting based on propensity scores and mediation analyses to examine the association of hospital rurality with in-hospital mortality and the potential mediating effects of PCI. Results: In multivariate models where PCI was not adjusted for, rural hospitals were associated with a significantly higher risk of in-hospital mortality (odds ratio [OR]: 1.19, 95% confidence interval [CI]: 1.03-1.37). However, this association was nullified (OR: 0.94, 95% CI: 0.81-1.08) when PCI was included as a covariate. Mediation analyses revealed that PCI significantly mediated 132.3% (95% CI: 104.1-256.6%) of the effect of hospital rurality on in-hospital mortality. The direct effect of hospital rurality on in-hospital mortality was insignificant. Conclusion: The results highlight the need to improve rural hospitals' infrastructure and address the inequalities of treatments and outcomes in rural and urban hospitals.

Population attributable fraction of lung cancer due to genetic variants, modifiable risk factors, and their interactions: a nationwide prospective cohort study.

BACKGROUND: Genetic variants and modifiable risk factors (including environmental exposure and lifestyle) greatly contribute to the development of lung cancer. The population attributable fraction (PAF) of these risk factors, especially their interactive effects, has not been well quantified. METHODS: A total of 398,577 participants were included in this analysis. There were 2504 incident lung cancer cases identified over an average 10.4-year follow-up. We applied Cox proportional hazards models to examine the associations between risk factors and incident lung cancer. We further developed a polygenic risk score and evaluated whether environmental factors modified the effect of genetic risk on incident lung cancer. Furthermore, we calculated the PAF for each risk factor, as well as their gene-environment additive interaction, and then combined them to create a weighted PAF that takes into consideration participants with overlapping risk factors. RESULTS: Our analysis showed that smoking was the leading risk factor for lung cancer with a PAF of 63.73%. We observed additive interactions between smoking, PM2.5, NOx, and genetic risk, with PAFs of 17.85% (smoking-high genetic risk interaction), 10.79% (smoking-intermediate genetic risk interaction), 5.30% (NOx-high genetic risk interaction), 6.55% (PM2.5-high genetic risk interaction), and 4.99% (PM2.5-intermediate genetic risk interaction). We estimated that 73.46% of lung cancer cases could be attributable to potentially modifiable risk factors after adjusting for the correlation between them. CONCLUSION: High genetic risk and several modifiable factors may increase the risk of incident lung cancer. Participants with a high genetic risk may be more vulnerable to developing lung cancer if exposed to smoking and/or high air pollution. Our findings provide evidence that the majority of incident lung cancer cases could be prevented by eliminating modifiable risk factors.

Underlying Factors of Health Insurance Use Among Blacks and Hispanics With Ambulatory Care-Sensitive Conditions.

This study examined satisfaction with and confidence in understanding health insurance use among Blacks and Hispanic Americans with ambulatory care-sensitive conditions. Using the 2013-2016 Health Reform Monitoring Survey data sets, descriptive statistics and ordinary least-square regressions estimated the association between satisfaction and confidence scores and racial or ethnic groups with ambulatory care-sensitive conditions. Compared with their White counterparts, Black (ß = -.13; 95% confidence interval [CI], -0.19 to -0.06) and Hispanic (ß = -0.41; 95% CI, -0.48 to -0.33) participants' standardized confidence scores were significantly lower. Research is needed to identify factors that may enhance this population's confidence level.

Health Insurance Literacy and Medical Debt in Middle-Age Americans.

BACKGROUND: Health insurance literacy (HIL) may influence medical financial burden among people who are sick and the most vulnerable. OBJECTIVE: This study examined the relationships between HIL, health insurance factors, and medical debt among middle-age Americans, a population with an increasing prevalence of illnesses. METHODS: Linear and generalized linear regression analyses were conducted on data drawn from the 2015-2016 waves of the Health Reform Monitoring Survey, a national, internet-based sample of Americans age 18 to 64 years. The analytical sample included 8,042 people age 50 to 64 years. KEY RESULTS: Adjusted mean HIL scores did not differ by private versus public insurance or by out-of-pocket costs. Mean HIL scores were lower with higher deductibles; however, differences in mean scores were small. Higher HIL was associated with lower medical debt (odds ratio = 0.97; 95% confidence interval [0.96, 0.98]), but at the highest HIL score, the risk of having medical debt was still 13.8%. Public coverage, higher annual deductibles, and out-of-pocket costs were associated with higher risks of having medical debt. CONCLUSIONS: The findings suggest that HIL plays an important role in medical debt burden. However, with the shift toward high cost-sharing insurance plans, addressing health care affordability issues along with HIL are critical to eliminate medical debt problems. [HLRP: Health Literacy Research and Practice. 2021;5(4):e319-e332.] Plain Language Summary: Understanding and using health insurance (also defined as health insurance literacy) may influence the ability to pay medical bills among people who are sick and vulnerable. This study examined the relationships among health insurance literacy, health insurance factors, and difficulty paying medical bills (i.e., medical debt) in Americans age 50 to 64 years using data from the Health Reform Monitoring Survey. People with higher health insurance literacy reported lower medical debt. Type of insurance coverage did not influence medical debt. Those with annual deductibles and out-of-pocket health care costs were more likely to report having medical debt.

Maternal PM2.5 exposure associated with stillbirth: A large birth cohort study in seven Chinese cities.

BACKGROUND: Maternal exposure to fine particulate matter (PM2.5) has been associated with a few adverse birth outcomes. However, its effect on stillbirth remains unknown in China, especially the susceptible windows and potential modifiers. OBJECTIVE: This study aimed to evaluate the associations between maternal PM2.5 exposure and stillbirth in seven Chinese cities. METHODS: We used birth cohort data of 1,273,924 mother-and-birth pairs in seven cities in southern China between 2014 and 2017 to examine these associations. Pregnant women were recruited in the cohort at their first visit to a doctor for pregnancy, and stillbirths were recorded at the time of birth. Air pollution exposures were assessed through linking daily air pollutant concentrations from nearby monitoring stations to the mother's residential community. Cox regression models were applied to determine the associations between PM2.5 and stillbirth for different gestational periods. RESULTS: Among the participants, 3150 (2.47‰) were identified as stillbirth cases. The hazard ratio (HR) of stillbirths was 1.52 (95% CI: 1.42, 1.62) for each 10 µg/m3 increase in PM2.5 during the entire pregnancy after controlling for some important covariates. Relatively stronger associations were observed during the second trimester [adjusted HR = 1.67 (95% CI: 1.57, 1.77)] than trimesters 1 [HR = 1.44 (95% CI: 1.37, 1.52)] and trimester 3 [HR = 1.23 (95% CI: 1.16, 1.30)]. Stratified analyses also showed a stronger association among pregnant women without previous pregnancy and previous delivery experiences. CONCLUSION: The study indicates that maternal exposure to PM2.5, especially during the midpoint period of pregnancy, might increase the risk of stillbirths. Maternal previous pregnancy and delivery may modify this association.

Association between maternal outdoor physical exercise and the risk of preterm birth: a case-control study in Wuhan, China.

BACKGROUND: China had the second largest proportion of preterm birth (PTB) internationally. However, only 11% of pregnant women in China meet international guidelines for maternal physical activity, a significantly lower proportion than that in Western countries. This study aims to examine the association between outdoor physical exercise during pregnancy and PTB among Chinese women in Wuhan, China. METHODS: A case-control study was conducted among 6656 pregnant women (2393 cases and 4263 controls) in Wuhan, China from June 2011 to June 2013. Self-reported measures of maternal physical exercise (frequency per week and per day in minutes) were collected. Adjusted odds ratios were estimated using Bayesian hierarchical logistic regression and a generalized additive mixed model (GAMM). RESULTS: Compared to women not involved in any physical activity, those who participated in physical exercise 1-2 times, 3-4 times, and over five times per week had 20% (aOR: 0.80, 95% credible interval [95% CI]: 0.68-0.92), 30% (aOR: 0.70, 95% CI: 0.60-0.82), and 32% (aOR: 0.68, 95% CI: 0.59-0.78) lower odds of PTB, respectively. The Bayesian GAMM showed that increasing physical exercise per day was associated with lower risk of PTB when exercise was less than 150 min per day; however, this direction of association is reversed when physical exercise was more than 150 min per day. CONCLUSION: Maternal physical exercise, at a moderate amount and intensity, is associated with lower PTB risk. More data from pregnant women with high participation in physical exercise are needed to confirm the reported U-shape association between the physical exercise and risk of preterm birth.

Association between socioeconomic welfare and depression among older adults: Evidence from the China health and Retirement Longitudinal Study.

This study aims to examine the association between province-level socioeconomic welfare factors and depression symptoms among older adults in China. Province-level socioeconomic characteristics were merged with microdata for respondents over 65 years from the 2018 China Health and Retirement Longitudinal Study (CHARLS) Wave 4 (N = 6657). Principal component analysis (PCA) was used to extract three socioeconomic welfare factors constructed from 14 province-level variables. A Bayesian mixed-effects logistic model was applied to measure the association between the three socioeconomic welfare factors and depression symptoms while controlling for socio-demographic variables. The PCA showed that economic welfare, medical resource welfare, and social service welfare together explained 72.2 percent of the total variance of the 14 province-level variables. It was found that increasing economic welfare was significantly associated with a lower probability of depression symptoms (OR = 0.806, 95%CI: [0.674, 0.967]), while medical facilities were associated with a higher probability of depression symptoms (OR = 1.181, 95%CI: [1.029, 1.354]) among Chinese older adults. Uncertainty existed as to whether having access to social welfare (OR = 0.941, 95%CI: [0.835, 1.060]) was associated with prevalence of depression. Thus, improved socioeconomic welfare systems for older adults (which possibly require an increase in spending) are necessary to contribute further to reduced depression risk in China. Policymakers should also improve the utilization of medical resources to mitigate the incidence of depression among the elderly in China.

Association between ambient air pollution and hyperuricemia in traffic police officers in China: a cohort study.

To evaluate the association between ambient air pollution and hyperuricemia, we prospectively followed 1748 traffic police officers without hyperuricemia at baseline (2009-2014) from 11 districts in Guangzhou, China. We calculated six-year average PM10, SO2 and NO2 concentrations using data collected from air monitoring stations. The hazard ratios for hyperuricemia per 10 µg/m3 increase in air pollutants were 1.46 (95% CI: 1.28-1.68) for PM10, 1.23 (95% CI: 1.00-1.51) for SO2, and 1.43 (95% CI: 1.26-1.61) for NO2. We also identified changes in the ratio of serum uric acid to serum creatinine concentrations (ua/cre) per 10 µg/m3 increase in air pollutants as 11.54% (95% CI: 8.14%-14.93%) higher for PM10, 5.09% (95% CI: 2.76%-7.42%) higher for SO2, and 5.13% (95% CI: 2.35%-7.92%) higher for NO2, respectively. Long-term exposure to ambient air pollution was associated with a higher incidence of hyperuricemia and an increase in ua/cre among traffic police officers.

Investigation of simple, objective, and effective indicators for predicting acute paraquat poisoning outcomes.

Initial symptoms of paraquat (PQ) toxicity are often not obvious, and the lack of advanced testing equipment and medical conditions in the primary hospital make it difficult to provide early diagnosis and timely treatment. To explore simple, objective, and effective indicators of prognosis for primary clinicians, we retrospectively analyzed acute PQ poisoning in 190 patients admitted to our hospital from 2008 to 2017. Based on their condition at the time of discharge, patients were categorized into either the survival group (n = 71) or the mortality group (n = 119). Age, PQ ingested amount, urinary PQ, urinary protein, white blood cell (WBC), and serum creatinine (Cr) were the key factors associated with the prognosis for PQ poisoning. We identified specific diagnostic thresholds for these key indicators of PQ poisoning: PQ ingested amount (36.50 mL), urinary PQ (semiquantitative result "++"), urinary protein (semiquantitative result "±"), WBC (16.50 × 109/L), and serum Cr (102.10 µmol/L). Combining these five indicators to identify poisoning outcomes was considered objective, accurate, and convenient. When the combined score was <1, the predicted probability of patient death was 6%. When the combined score was ≥3, the predicted probability of patient death was 96%. These findings provide metrics to assist primary clinicians in predicting outcomes of acute PQ poisoning at earlier stages, a basis for administering treatment.

Confidence in Understanding Health Insurance and Challenges Paying Medical Bills Among Men in the United States.

Although the number of men with health insurance has increased, men are less likely to utilize health services than females, and experience difficulty in paying medical bills. Understanding the details of health insurance can be challenging and the lack of understanding can have financial consequences. This study, guided by Andersen's model of health-care utilization, assessed the relationship between confidence level in understanding health insurance terms and difficulty in paying medical bills among American men. Data were drawn from the Health Reform Monitoring Survey, 2015-2016. The study included 6,643 men aged between 18 and 64. Descriptive statistics examined participants' difficulty in paying medical bills by predisposing, enabling, and need characteristics, and by confidence in understanding health insurance terms. A modified Poisson regression analysis examined the association between difficulty in paying medical bills, confidence in understanding health insurance terms score, and predisposing, enabling, and need characteristics. An increase in confidence in understanding health insurance terms score was associated with significantly lower reported difficulty in paying medical bills (PR = .98; 95% CI = [.97-.99]; p = .002). Participants with a college degree or higher were less likely to report difficulty in paying their medical bills compared to participants with less than a high school degree (PR = .72; 95% CI = [.56-.92]; p = .009). A better understanding of health insurance might prevent men from experiencing difficulties in paying medical bills. Additional research should be performed to understand the relationship between the level of confidence in understanding health insurance, knowledge level of health insurance terms, use of health insurance, and their impact on difficulty in paying medical bills.

Comparing the Performance of Charlson and Elixhauser Comorbidity Indices to Predict In-Hospital Mortality Among a Chinese Population.

OBJECTIVE: Earlier comorbidity measures have been developed or validated using the North American population. This study aims to compare five Charlson or Elixhauser comorbidity indices to predict in-hospital mortality using a large electronic medical record database from Shanxi, China. METHODS: Using the primary diagnosis code and surgery procedure codes, we identified four hospitalized patient cohorts, hospitalized between 2013 and 2017, in Shanxi, China, as follows: congestive heart failure (CHF, n=41,577), chronic renal failure (CRF, n=40,419), diabetes (n=171,355), and percutaneous coronary intervention (PCI, n=39,097). We used logistic regression models and c-statistics to evaluate the in-hospital mortality predictive performance of two multiple comorbidity indicator variables developed by Charlson in 1987 and Elixhauser in 1998 and three single numeric scores by Quan in 2011, van Walraven in 2009, and Moore 2017. RESULTS: Elixhauser comorbidity indicator variables had consistently higher c-statistics (0.824, 0.843, 0.904, 0.853) than all other four comorbidity measures, across all four disease cohorts. Moore's comorbidity score outperformed the other two score systems in CHF, CRF, and diabetes cohorts (c-statistics: 0.776, 0.832, 0.869), while van Walraven's score outperformed all others among PCI patients (c-statistics: 0.827). CONCLUSION: Elixhauser comorbidity indicator variables are recommended, when applied to large Chinese electronic medical record databases, while Moore's score system is appropriate for relatively small databases.

Association between depressive symptoms and poor sleep quality among Han and Manchu ethnicities in a large, rural, Chinese population.

OBJECTIVES: To estimate the relationship between sleep quality and depression, among Han and Manchu ethnicities, in a rural Chinese population. METHODS: A sample of 8,888 adults was selected using a multistage cluster and random sampling method. Sleep quality was evaluated using the Pittsburgh Sleep Quality Index (PSQI). Depressive symptoms were assessed via the Center for Epidemiological Survey, Depression Scale (CES-D). Logistic regression was conducted to assess associations between sleep quality and depression. RESULTS: The prevalence of poor sleep quality and depression in the Manchus (20.74% and 22.65%) was significantly lower than that in the Hans (29.57% and 26.25%), respectively. Depressive participants had higher odds ratios of global and all sub PSQI elements than non-depressive participants, both among the Hans and the Manchus. Additive interactions were identified between depressive symptoms and ethnicity with global and four sub-PSQI elements, including subjective sleep quality, sleep disturbance, use of sleep medication and daytime dysfunction. CONCLUSIONS: The findings revealed that the prevalence of poor sleep quality and depression among the Hans was greater than among the Manchus. Depression was associated with higher odds of poor sleep quality.