Anthony J. Kondracki

Bio: Anthony J. Kondracki is an academic researcher from Florida International University. The author has contributed to research in topics: Longitudinal study & Odds ratio. The author has an hindex of 2, co-authored 7 publications receiving 7 citations. Previous affiliations of Anthony J. Kondracki include Mercer University.

The association between sleep duration, napping, and stroke stratified by self-health status among Chinese people over 65 years old from the China health and retirement longitudinal study.

Abstract: Stroke is a major cause of death in China. This study aimed to investigate the association between sleep duration (nighttime sleep and daytime napping) and stroke in elderly Chinese individuals with self-reported health status. A total of 4785 Chinese adults over 65 years from the 2011 China Health and Retirement Longitudinal Study (CHARLS) were included. Binary logistic regression was used to estimate odds ratios and 95% confidence intervals of the association between sleep duration and stroke stratified by self-reported health status. A significant association between short sleep duration (< 7 h per day) and the risk of stroke (aOR = 2.05; 95% CI 1.31–3.19), after controlling for sociodemographic characteristics, lifestyle factors, health status, and comorbidities. There was no significant association between short and long sleep duration and stroke in the individuals who reported good general health status. However, in individuals who reported poor health status, short sleep duration (aOR = 2.11; 95% CI 1.30–3.44) and long sleep duration (aOR = 1.86; 95% CI 1.08–3.21) were significantly associated with increased risk of stroke, compared with normal sleep duration (7–8 h per day). Disability was significantly associated with stroke in both self-reported good and poor health groups. Rural residence was significantly associated with a lower risk of stroke among individuals who reported poor health status. Both short and long sleep duration were significantly associated with stroke among individuals who reported poor health. Stroke prevention should be focused on elderly individuals who believe that they have health problems.

Risk of large for gestational age births at early, full and late term in relation to pre-pregnancy body mass index: Mediation by gestational diabetes status.

Abstract: BACKGROUND Maternal pre-pregnancy body mass index (BMI) is strongly associated with infant birthweight and the risk differs in pregnancies complicated by gestational diabetes (GDM). OBJECTIVES To examine the risk of large for gestational age (LGA) (≥97th percentile) singleton births at early term, full term and late term in relation to maternal pre-pregnancy BMI status mediated through GDM. METHODS We analysed data from the 2018 U.S. National Vital Statistics Natality File restricted to singleton term births (N = 3,229,783). In counterfactual models for causal inference, we estimated the total effect (TE), natural direct effect (NDE) and natural indirect effect (NIE) for the association of pre-pregnancy BMI with subcategories of LGA births at early, full and late term mediated through GDM, using log-binomial regression and adjusting for race/ethnicity, age, education, parity and infant sex. Proportion mediated was calculated on the risk difference scale and potential unmeasured confounders were assessed using the E-value. RESULTS Overall, 6.4% of women had GDM, and there were 3.6% LGA singleton term births. The highest prevalence of GDM was among pre-gestational overweight/obesity that also had the highest rates of LGA births at term. The TE estimates for the risk of LGA births were the strongest across women with higher pre-pregnancy BMI compared to women with normal pre-pregnancy BMI. The NDE estimates were higher than the NIE estimates for overweight/obese BMI status. The proportion mediated, which answers the causal question to what extent the total effect of the association between pre-pregnancy BMI and LGA births is accounted for through GDM, was the highest (up to 16%) for early term births. CONCLUSIONS Term singleton births make up the largest proportion in a cohort of newborns. While the percentage mediated through GDM was relatively small, health risks arising from pre-pregnancy overweight, and obesity can be substantial to both mothers and their offspring.

Job-related stress and tobacco smoking: A systematic review

Abstract: Job-related stress may affect smoking initiation, progression, and intensity, therefore, it is important to have a better understanding of these associations to design targeted and effective workpl...

Nighttime sleep duration, daytime napping, and metabolic syndrome: findings from the China Health and Retirement Longitudinal Study.

Abstract: PURPOSE This study aimed to assess the association between nighttime sleep, daytime napping, and metabolic syndrome (MetS) in an elderly Chinese population. METHODS A cross-sectional study was conducted using data from the 2011 China Health and Retirement Longitudinal Study (CHARLS) to examine the association between nighttime sleep, daytime napping, and MetS (defined according to the Chinese Diabetes Society criteria). Sleep duration was assessed by a self-reported questionnaire. Binary logistic regression models were used to estimate odds ratios and 95% confidence intervals of the associations adjusting for covariates. RESULTS Among 4785 elderly Chinese aged over 65 years old, there was no association between short-time sleep duration ( 8 h/day) decreased the odds of MetS by 53% (aOR= 0.47; 95% CI 0.23-0.96) compared to normal sleep duration (7-8 h/day). Compared to no daytime napping, short-time napping (≤ 30 min/day) was associated with increased odds of MetS (aOR = 1.55, 95% CI 1.02-2.36) and long-time napping (> 30 min/day) was associated with even higher odds of MetS (aOR = 1.77, 95%CI 1.24-2.53). Individuals who were over 75 years old, with elementary school education, and good health status had lower odds of MetS, while women, individuals living in rural areas, and those who reported poor health status had higher odds of MetS. CONCLUSION Long-time sleep duration decreased and daytime napping increased the risk of MetS among the elderly Chinese population. We speculate that increasing nighttime sleep duration and decreasing daytime napping may help reduce the risk of MetS.

Sex, Sleep Duration, and the Association of Cognition: Findings from the China Health and Retirement Longitudinal Study.

Abstract: Background: We aimed to examine the association between sleep duration and cognitive impairment among elderly Chinese people. Methods: generalized linear modeling was used to analyze the baseline data for adults aged 65 years and over (n = 4785) selected from the 2011 China Health and Retirement Longitudinal Study (CHARLS). The two aspects of cognitive impairment assessed in the study were mental status and memory. Sex-stratified logistic regression models were conducted to identify the effect of sleep duration in the different gender groups. Results: of all the participants, 49.8% were females and 32.5% aged 75 years and over. Of the participants, 59.7% had short sleep duration ( 8 h/day). Compared to normal sleep duration, long sleep duration was associated with lower mental status scores (β = −0.43, p = 0.001) and lower memory scores (β = −0.26, p = 0.006). Long sleep duration was associated with lower mental status in both men (β = −0.37, p = 0.033) and women (β = −0.46, p = 0.025), however, only in men was long sleep duration found to be associated with low memory scores (β = −0.26, p = 0.047). Conclusions: Our study showed that long sleep duration was significantly associated with poorer mental status and memory scores in elderly Chinese people. Paying greater attention to the effects of sleep patterns on the risk of cognitive decline may yield practical implications for dementia prevention and health promotion, especially among older women with lower educational attainment, living in rural areas, and those who have long sleep duration.

Heart Disease and Stroke Statistics—2023 Update: A Report From the American Heart Association

Abstract: Background: The American Heart Association, in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, diet, and weight) and health factors (cholesterol, blood pressure, and glucose control) that contribute to cardiovascular health. The Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, congenital heart disease, rhythm disorders, subclinical atherosclerosis, coronary heart disease, heart failure, valvular disease, venous disease, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs). Methods: The American Heart Association, through its Epidemiology and Prevention Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States to provide the most current information available in the annual Statistical Update with review of published literature through the year before writing. The 2023 Statistical Update is the product of a full year’s worth of effort in 2022 by dedicated volunteer clinicians and scientists, committed government professionals, and American Heart Association staff members. The American Heart Association strives to further understand and help heal health problems inflicted by structural racism, a public health crisis that can significantly damage physical and mental health and perpetuate disparities in access to health care, education, income, housing, and several other factors vital to healthy lives. This year’s edition includes additional COVID-19 (coronavirus disease 2019) publications, as well as data on the monitoring and benefits of cardiovascular health in the population, with an enhanced focus on health equity across several key domains. Results: Each of the chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics. Conclusions: The Statistical Update represents a critical resource for the lay public, policymakers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.

Heart Disease and Stroke Statistics—2023 Update: A Report From the American Heart Association

Abstract: Background: The American Heart Association, in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, diet, and weight) and health factors (cholesterol, blood pressure, and glucose control) that contribute to cardiovascular health. The Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, congenital heart disease, rhythm disorders, subclinical atherosclerosis, coronary heart disease, heart failure, valvular disease, venous disease, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs). Methods: The American Heart Association, through its Epidemiology and Prevention Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States to provide the most current information available in the annual Statistical Update with review of published literature through the year before writing. The 2023 Statistical Update is the product of a full year’s worth of effort in 2022 by dedicated volunteer clinicians and scientists, committed government professionals, and American Heart Association staff members. The American Heart Association strives to further understand and help heal health problems inflicted by structural racism, a public health crisis that can significantly damage physical and mental health and perpetuate disparities in access to health care, education, income, housing, and several other factors vital to healthy lives. This year’s edition includes additional COVID-19 (coronavirus disease 2019) publications, as well as data on the monitoring and benefits of cardiovascular health in the population, with an enhanced focus on health equity across several key domains. Results: Each of the chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics. Conclusions: The Statistical Update represents a critical resource for the lay public, policymakers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.

Pre-Pregnancy Body Mass Index and Risk of Macrosomia and Large for Gestational Age Births with Gestational Diabetes Mellitus as a Mediator: A Prospective Cohort Study in Central China

Abstract: This study aimed to examine the risk of macrosomia and large for gestational age (LGA) births in relation to maternal pre-pregnancy body mass index (BMI) status mediated through gestational diabetes mellitus (GDM). This prospective study included 34,104 singleton pregnancies at 8–14 weeks of gestation. The interesting outcomes were macrosomia (≥4000 g) and LGA (≥90th percentile). Mediation analyses were conducted using log-binomial regression adjusted for age, education, parity, fetal sex, and gestational weight gain. The proportion mediated was estimated based on the risk difference scale, and the E-value was utilized to assess potential confounders. Overall, 15.9% of women had GDM, and there were 4.0% macrosomia and 9.9% LGA births. The proportion mediated by GDM on macrosomia was up to 40% among obese women, and the estimate of the total effect was 6.18 (95% CI: 5.26–7.26), of the natural direct effect was 4.10 (95% CI: 3.35–4.99), and of the natural indirect effect was 1.51 (95% CI: 1.31–1.76). Likewise, among overweight women, the proportion mediated by GDM on macrosomia was up to 40%. Furthermore, consistent findings were evident for the outcome of LGA births. Pre-pregnancy overweight/obesity increased the risk of macrosomia and LGA births independently and partly mediated by GDM.

Waist-to-height ratio, waist circumference, body mass index, waist divided by height0.5 and the risk of cardiometabolic multimorbidity: A national longitudinal cohort study.

Abstract: Background and aims Cardiometabolic multimorbidity (CM) is an increasing public health burden. This study aimed to evaluate the association of waist-to-height ratio (WHtR), waist circumference (WC), waist divided by height0.5 (WHT.5R) and body mass index (BMI) with the risk of CM. Methods and results We used data from the China Health and Retirement Longitudinal Study (CHARLS). A total of 10,521 participants aged 45 years and over were recruited, including 8807 individuals with 0 cardiometabolic diseases at baseline (stage I) and 1714 individuals with 1 cardiometabolic disease at baseline (stage II). CM was defined as self-reporting of two or more of the following conditions: stroke, diabetes and heart disease. Logistic regression was conducted to estimate the odds ratios (ORs) and 95% confidence intervals (CIs). The net reclassification index (NRI) and integrated discrimination improvement (IDI) were used to evaluate the incremental predictive value beyond conventional factors. In stage I, an increased risk of CM was observed among participants with WHtR ≥0.5 (OR: 1.76, 95% CI: 1.05–2.97), WC ≥ 90 cm (men) + WC ≥ 80 cm (women) (OR: 2.06, 95% CI: 1.29–3.27), WHT.5R ≥ 6.54 cm0.5 (OR: 1.81, 95% CI: 1.16–2.83) or BMI ≥24 kg/m2 (OR: 1.48, 95% CI: 0.98–2.24). Furthermore, the NRI and IDI of WHtR, WC and WHT.5R were all higher than those of BMI. In stage II, the adjusted ORs (95% CIs) of WHtR, WC, WHT.5R and BMI were 2.04 (1.24–3.35), 1.89 (1.29–2.77), 1.86 (1.24–2.78) and 1.47 (1.06–2.04), respectively. In addition, WC exhibited the highest NRI and IDI. Conclusion WHtR, WC, WHT.5R and BMI are independent predictors of CM in the middle-aged and older Chinese population. WHtR, WC and WHT.5R show better abilities in predicting CM than BMI.