Association of hemoglobin glycation index and its interaction with obesity/family history of hypertension on hypertension risk: a community-based cross-sectional survey.

BACKGROUND: Hemoglobin glycation index (HGI) is considered to be a convenient measurable indicator to assess the inter-individual variation of HbA1c. In the present study, we tested the relationship between HGI and risk of hypertension, and further explored the possible interacting influences of HGI with other such factors on hypertension risk among Chinese individuals. METHODS: The eligible subjects were chosen from a community-based cross-sectional survey in China. We collected relevant data and clinical indicators for each participant. HGI was calculated as "measured HbA1c-predicted HbA1c" and divided into four categories according to quartile. The following indicators were used to assess interactive effects: (1) relative excess risk due to interaction (RERI); (2) attributable proportion due to interaction (AP); and (3) synergy index (SI). Statistical analysis was performed using R software. RESULTS: Specifically, 1777 eligible participants were selected in this cross-sectional survey. There were 433 subjects who were identified to have hypertension (24.4%). A significant increase in the prevalence of hypertension from Q1 to Q4 of HGI was observed (p < 0.001). Multivariable logistic model demonstrated that subjects at the highest HGI group had a substantially increased risk of being hypertensive than subjects in the first quartile of HGI, as indicated by the OR value of 1.87 (95% CI 1.26-2.78). Moreover, a significant interaction between family history of hypertension and HGI on hypertension risk was detected (RERI: 1.36, 95% CI 0.11-2.63; AP: 0.43, 95% CI 0.17-0.69; and SI:2.68, 95% CI 1.10-6.48). The interactive effect between HGI and abdominal obesity was also found to be significant, as estimated by the value of RERI (1.04, 95% CI 0.24-1.85), AP (0.33, 95% CI 0.11-0.56) and SI (1.96, 95% CI 1.01-3.79). However, in the analysis of the interaction between HGI and general obesity, only the AP value (0.28, 95% CI 0.01-0.54) was observed to be significant. CONCLUSION: High HGI was independently associated with the risk of hypertension. Moreover, HGI significantly shared interactions with obesity and family history of hypertension that influenced the risk of hypertension.

Elevated glycosylated hemoglobin levels and their interactive effects on hypertension risk in nondiabetic Chinese population: a cross-sectional survey.

BACKGROUND: Abnormal glucose metabolism has been suggested to be involved in the development of hypertension. This study investigated the effect of the association and potential interaction of glycosylated hemoglobin (HbA1c) and other factors on the risk of hypertension among Chinese nondiabetic adults. METHODS: As a cross-sectional survey, the current work deployed a questionnaire survey, anthropometric tests, and biochemical measures for each of the eligible participants. The HbA1c levels were quantified and grouped by quartiles. Correlations between HbA1c and hypertension, isolated systolic hypertension (ISH), and isolated diastolic hypertension (IDH) risk were investigated by logistic analyses. For evaluating the interactive effects, the parameters of relative excess risk due to interaction (RERI), attributable proportion due to interaction (AP), and synergy index (SI) were calculated, respectively. RESULTS: In the current study, 1462 nondiabetic subjects were enrolled. In total, the prevalence rates of hypertension, ISH and IDH were 22.4, 9.6 and 4.5%, respectively. When HbA1c levels were grouped by quartile, it was revealed that the prevalence rates of hypertension and ISH were substantially elevated across groups (Pfor trend < 0.001). In the multivariable logistic regression analyses, in comparison with the first quartile of HbA1c, the normalized OR for hypertension risk was 1.90 (95% CI: 1.28-2.80) for the highest quartile. Also, the risk of ISH was significantly increased with HbA1c level in the highest quartile relative to in the bottom quartile (OR: 2.23,95% CI:1.47-3.71). However, no significant relationship between the HbA1c level and IDH risk was observed (OR: 1.78, 95% CI: 0.82-3.84). Eventually, it was demonstrated from the interactive effect analysis that HbA1c significantly interacted with abdominal obesity (RERI: 1.48, 95% CI: 0.38-2.58; AP: 0.37, 95% CI: 0.14-0.60 and SI: 1.96, 95% CI: 1.06-3.62) and family history of hypertension (AP: 0.37, 95% CI: 0.05-0.70) in influencing the risk of hypertension in nondiabetic participants. CONCLUSION: Higher HbA1c levels significantly enhanced the risk of hypertension and ISH, but not IDH among Chinese nondiabetic adults. Moreover, the risk of hypertension was also aggravated by the upregulated HbA1c in a synergistic manner alongside abdominal obesity and family history of hypertension.

Risk factors for prehypertension and their interactive effect: a cross- sectional survey in China.

BACKGROUND: Individuals with prehypertension are at higher risk of developing hypertension and cardiovascular diseases, while the interaction between factors may aggravate prehypertension risk. Therefore, this study aimed to evaluate the risk factors for prehypertension in Chinese middle-aged and elderly adults, and explore the potentially interactive effect of evaluated factors. METHODS: All the participants that came from a community based cross-sectional survey were investigated in Bengbu, China, by being interviewed with a questionnaire. Body mass index (BMI), Waist circumference (WC) and lipid accumulation product (LAP) that reflect participants' obesity were also calculated. In addition, logistic regression model was applied to explore the risk factors of prehypertension, followed by the assessment of the interactive effects between risk factors on prehypertension by the relative excess risk due to interaction (RERI), attributable proportion due to interaction (AP) and synergy index (SI). RESULTS: A total of 1777 participants were enrolled in this study, among which the prevalence of normtension, prehypertension and hypertension were 41.70%, 33.93% and 24.37% respectively. According to the multivariate logistic regression analysis, age (OR: 1.01, 95%CI: 1.00-1.02), smoking (OR: 1.67, 95%CI: 1.22-2.29), family history of cardiovascular diseases (OR: 1.52, 95%CI: 1.14-2.02), general obesity (OR: 1.51, 95%CI: 1.15-1.97) and LAP (OR: 2.58, 95%CI: 1.76-3.80) were all defined as the major factors that significantly related with the risk of prehypertension. When identifying prehypertension risk, the receiver-operating characteristics (ROC) curves (AUC) analysis indicated that LAP performed better than BMI in males (Z = 2.05, P = 0.03) and females (Z = 2.12, P = 0.03), but was superior to WC only in females (Z = 2.43, P = 0.01). What is more, there were significant interactive effects of LAP with family history of cardiovascular diseases (RERI: 1.88, 95%CI: 0.25-3.51; AP: 0.44, 95%CI: 0.20-0.69; SI: 2.37, 95%CI: 1.22-4.60) and smoking (RERI: 1.99, 95%CI: 0.04-3.93; AP: 0.42, 95%CI: 0.17-0.67; SI: 2.16, 95%CI: 1.68-4.00) on prehypertension risk. The value of AP (0.40, 95%CI: 0.03-0.77) also indicated a significant interaction between family history of cardiovascular diseases and smoking on prehypertension. CONCLUSION: Prehypertension is currently prevalent in Chinese adults. This study indicated that age, family history of cardiovascular diseases, smoking, general obesity and LAP were significantly related with prehypertension risk. Furthermore, interactive effects on risk of prehypertension had been demonstrated in this study as well, which would help researchers to build strategy against prehypertension more comprehensively and scientifically.

A powerful score-based test statistic for detecting gene-gene co-association.

BACKGROUND: The genetic variants identified by Genome-wide association study (GWAS) can only account for a small proportion of the total heritability for complex disease. The existence of gene-gene joint effects which contains the main effects and their co-association is one of the possible explanations for the "missing heritability" problems. Gene-gene co-association refers to the extent to which the joint effects of two genes differ from the main effects, not only due to the traditional interaction under nearly independent condition but the correlation between genes. Generally, genes tend to work collaboratively within specific pathway or network contributing to the disease and the specific disease-associated locus will often be highly correlated (e.g. single nucleotide polymorphisms (SNPs) in linkage disequilibrium). Therefore, we proposed a novel score-based statistic (SBS) as a gene-based method for detecting gene-gene co-association. RESULTS: Various simulations illustrate that, under different sample sizes, marginal effects of causal SNPs and co-association levels, the proposed SBS has the better performance than other existed methods including single SNP-based and principle component analysis (PCA)-based logistic regression model, the statistics based on canonical correlations (CCU), kernel canonical correlation analysis (KCCU), partial least squares path modeling (PLSPM) and delta-square (δ (2)) statistic. The real data analysis of rheumatoid arthritis (RA) further confirmed its advantages in practice. CONCLUSIONS: SBS is a powerful and efficient gene-based method for detecting gene-gene co-association.

Differences in depression between unknown diabetes and known diabetes: results from China health and retirement longitudinal study.

BACKGROUND: Both diabetes and depression have become serious public health problems and are major contributors to the global burden of disease. People with diabetes have been shown to have higher risk of depression. The purpose of this study was to observe the differences in depression between older Chinese adults with known or unknown diabetes. METHODS: Data came from the national baseline survey of China Health and Retirement Longitudinal Study (CHARLS). The Center for Epidemiologic Studies Depression Scale was used to assess depression. Participants with a history of diabetes diagnosis were considered to have known diabetes, and those with newly-diagnosed diabetes were considered to have unknown diabetes. Multiple logistic regression analysis was applied to estimate odds ratio (OR) for depression in predictor variables. RESULTS: Overall, 39.1% of the 2,399 participants with diabetes suffered from depression. The prevalence of depression was significantly higher (p < 0.001) in people with known diabetes (43.5%) than those with unknown diabetes (35.1%). The biggest differences between the two groups were found in the middle aged, in women, in the less educated and in married people. In known diabetes, people treated with traditional Chinese medicine (TCM) coupled with oral western medicine (WM) and/or insulin had two-fold odds of depression compared to those without treatment. CONCLUSION: The knowledge of having diabetes, treatments and suffering from other chronic diseases were associated with the higher prevalence of depression in people with known diabetes compared to those with unknown diabetes. Prevention of depression in diabetics should receive more attention in the middle aged, women and the less education.

A novel statistic for genome-wide interaction analysis.

Although great progress in genome-wide association studies (GWAS) has been made, the significant SNP associations identified by GWAS account for only a few percent of the genetic variance, leading many to question where and how we can find the missing heritability. There is increasing interest in genome-wide interaction analysis as a possible source of finding heritability unexplained by current GWAS. However, the existing statistics for testing interaction have low power for genome-wide interaction analysis. To meet challenges raised by genome-wide interactional analysis, we have developed a novel statistic for testing interaction between two loci (either linked or unlinked). The null distribution and the type I error rates of the new statistic for testing interaction are validated using simulations. Extensive power studies show that the developed statistic has much higher power to detect interaction than classical logistic regression. The results identified 44 and 211 pairs of SNPs showing significant evidence of interactions with FDR<0.001 and 0.001

Global trends and hotspots in the digital therapeutics of autism spectrum disorders: a bibliometric analysis from 2002 to 2022.

Introduction: Autism spectrum disorder (ASD) is a severe neurodevelopmental disorder that has become a major cause of disability in children. Digital therapeutics (DTx) delivers evidence-based therapeutic interventions to patients that are driven by software to prevent, manage, or treat a medical disorder or disease. This study objectively analyzed the current research status of global DTx in ASD from 2002 to 2022, aiming to explore the current global research status and trends in the field. Methods: The Web of Science database was searched for articles about DTx in ASD from January 2002 to October 2022. CiteSpace was used to analyze the co-occurrence of keywords in literature, partnerships between authors, institutions, and countries, the sudden occurrence of keywords, clustering of keywords over time, and analysis of references, cited authors, and cited journals. Results: A total of 509 articles were included. The most productive country and institution were the United States and Vanderbilt University. The largest contributing authors were Warren, Zachary, and Sarkar, Nilanjan. The most-cited journal was the Journal of Autism and Developmental Disorders. The most-cited and co-cited articles were Brian Scarselati (Robots for Use in Autism Research, 2012) and Ralph Adolphs (Abnormal processing of social information from faces in autism, 2001). "Artificial Intelligence," "machine learning," "Virtual Reality," and "eye tracking" were common new and cutting-edge trends in research on DTx in ASD. Discussion: The use of DTx in ASD is developing rapidly and gaining the attention of researchers worldwide. The publications in this field have increased year by year, mainly concentrated in the developed countries, especially in the United States. Both Vanderbilt University and Yale University are very important institutions in the field. The researcher from Vanderbilt University, Warren and Zachary, his dynamics or achievements in the field is also more worth our attention. The application of new technologies such as virtual reality, machine learning, and eye-tracking in this field has driven the development of DTx on ASD and is currently a popular research topic. More cross-regional and cross-disciplinary collaborations are recommended to advance the development and availability of DTx.

Peripubertal exposure to low doses of tributyltin chloride affects the homeostasis of serum T, E2, LH, and body weight of male mice.

Previous studies have shown that tributyltin could act as an endocrine disruptor in mammals. However, the data on the low-dose effect of tributyltin in animals are still lacking. The objective of this study was to demonstrate the endocrine disruption induced by low levels of tributyltin chloride (TBTCl) in male KM mice. The animals were treated with 0.05 or 0.5 mg TBTCl/kg body weight/3 days from postnatal days (PNDs) 24 to 45, and killed on PNDs 49 and 84, respectively. Mice treated with 0.5 mg TBTCl/kg exhibited decreased serum and intratesticular testosterone (T) levels on PND 49 and then followed by an obvious recovery on PND 84. Furthermore, mice treated with 0.05 mg TBTCl/kg showed reduced serum 17ß-estradiol (E2) levels on PND 49. However, treatments with TBTCl resulted in a dose-dependent increase in serum E2 concentration of the mice on PND 84. Administration of TBTCl also decreased levels of serum luteinizing hormone and intratesticular E2 on PND 84. In addition, mice exposed to 0.05 mg/kg TBTCl exhibited an increase in body weight in the late stage of the experiment. These results indicate that treatment with low doses of TBTCl could disturb hormone homeostasis and body weight gain in rodents, and exposure to different levels of TBTCl might have different effects on changing some physiologic parameters.

Association of neighborhood greenness exposure with cardiovascular diseases and biomarkers.

AIM: Living in areas with neighborhood greenness may be associated with the incidence of cardiovascular diseases (CVDs). However, little evidence in this regard has emerged from developing countries. In the present study, we examined neighborhood greenness associated with CVDs and the lipid accumulation product (LAP) and pulse pressure (PP) in China. METHODS: We undertook our analysis using a community cross-sectional survey conducted in Longzihu District of Bengbu from July to August 2015. We measured triglyceride levels, waist circumference, and blood pressure. To assess exposure to neighborhood greenness, we used the average normalized difference vegetation index (NDVI) at 1,000-, 1,500-, and 2,000-m buffers in the participant community. We employed generalized mixed models to determine the association among neighborhood greenness, CVDs, LAP, and PP. We conducted stratified analysis by age, gender, income, and education. We assessed the potential mediating effects of road proximity and physical activity on greenness and CVDs, PP, and LAP. RESULTS: The highest tertiles of NDVI1500-m were steadily and significantly associated with lower odds of CVDs prevalence: the adjusted OR of such prevalence was 0.612 (95% CI, 0.462-0.811); higher NDVI was significantly associated with lower PP levels. The NDVI was strongly associated with CVDs prevalence among participants who were male and had high income. Ambient road proximity significantly mediated 9.7% of the estimated association between greenness and PP, there was no evidence of mediation effects for physical activity. CONCLUSIONS: Higher neighborhood greenness could have a beneficial effect on CVDs and biomarkers. There were higher associations between residential greenness and CVDs among male and higher-income individuals; road proximity partially mediated the observed association between greenness and PP.

Comparison of Body-Image Dissatisfaction Among Chinese Children and Adolescents at Different Pubertal Development Stages.

BACKGROUND: Body-image dissatisfaction among children and adolescent has become increasingly serious, and may be the result of staged differences in the puberty-development process. The aim of this study was to compare differences in body-image dissatisfaction among children and adolescents at different pubertal stages. METHODS: A total of 574 students aged 8-15 years were recruited from two nine-year schools via stratified cluster sampling, their secondary sex characteristics and external genital development examined, and body-image cognition surveyed using the teenage body-image annoyance questionnaire. This questionnaire covers body-shape, gender, sexual organ, and appearance dissatisfaction. Lower scores indicate a more negative body image. RESULTS: Total, gender, and appearance-dissatisfaction scores in girls were significantly lower than in boys (P<0.05); however, sexual organ-dissatisfaction scores in girls were significantly higher than in boys (P<0.05). Girls' gender-dissatisfaction scores before breast development Tanner II were higher than those after menarche (P<0.05); however, girls' sexual organ-dissatisfaction scores before breast development Tanner II were significantly higher than those after menarche (P<0.05). CONCLUSION: The girls were more dissatisfied with their gender and appearance than the boys, and the boys were more dissatisfied with their sexual organs than the girls. The girls were more dissatisfied with their sexual organs before breast development Tanner II and more dissatisfied with their gender after menarche.

Systematic Meta-analysis Revealed an Association of PGC-1α rs8192678 Polymorphism in Type 2 Diabetes Mellitus.

BACKGROUND: Genome-wide association study (GWAS) provides an unprecedented opportunity to reveal substantial genetic contribution to type 2 diabetes mellitus (T2DM) and glycemic identification of allelic heterogeneity and population-specific genetic variants, yet it also faces difficulty due to the vast amount of potential confounding factors and limited availability of clinical data. To identify responsible susceptibility loci and genomic polymorphism for T2DM and glycemic traits, we have systematically investigated a genome-wide association study related to T2DM. Although GWAS has captured many common genetic variations, which are related to T2DM, each risk allele (RA) of single-nucleotide polymorphisms (SNPs) at these loci is not conclusive. Therefore, it is common to present a combination of several SNPs to infer T2DM risk, yet it is still insufficient to be deterministic. To streamline the identification of a deterministic genetic variation in T2DM, we developed this meta-analysis as a showcase to comprehensively identify the association between cumulative RAs and T2DM risk by combining different studies in reported literature and databases. After all, we identified that PGC-1α rs8192678 polymorphism can be considered as a potentially deterministic biomarker in T2DM risk. Previous studies have potentially linked PGC-1α rs8192678 polymorphism to type 2 diabetes mellitus (T2DM) risk, but the results remain inconsistent in different populations and are not conclusive. We developed a new meta-analysis approach to systematically identify the association between PGC-1α rs8192678 polymorphism and T2DM, and we have comprehensively assessed different ethnic groups to validate our findings. METHODS: We performed comprehensive information retrieval and knowledge discovery meta-analysis by searching extensively published literature and different electronic databases to acquire eligible studies for the above association study. We developed a method to use pooled odds ratios (ORs) and their corresponding 95% confidence intervals (CIs) in five genetic models (allelic, dominant, recessive, homozygous, and heterozygous genetic models) to identify the relationship among ethnicity subgroup analyses comprehensively. RESULTS: We identified 20 eligible studies consisting of 16,182 subjects (8,038 cases and 8,144 controls) in our meta-analysis. PGC-1α rs8192678 polymorphisms of all subjects showed a significant association with T2DM susceptibility under all genetic models: allelic (OR: 1.24, 95% CI: 1.13-1.35), dominant (OR: 1.27, 95% CI: 1.14-1.42), recessive (OR: 1.24, 95% CI: 1.14-1.36), homozygous (OR: 1.40, 95% CI: 1.20-1.64), and heterozygous (OR: 1.20, 95% CI: 1.06-1.35). In the subgroup analysis, we identified a significant association between PGC-1α rs8192678 polymorphism and T2DM in the Caucasian and Indian populations under all genetic models we investigated. This is the most comprehensive study of the subject to date. CONCLUSION: Our development of meta-analysis revealed that the minor allele (A) carriers, especially AA genotype carriers, can lead to risk of T2DM in the Caucasian and Indian populations. This is the first report that such risk has been confirmed. Our finding shed new light into the genetic alteration in T2DM.

Association and Interaction Analysis of Lipid Accumulation Product with Impaired Fasting Glucose Risk: A Cross-Sectional Survey.

AIMS: Lipid accumulation product (LAP) is put forward as a powerful marker showing the accumulation of visceral fat. The present study is aimed at (i) analyzing the predictive performances of LAP in the identification of impaired fasting glucose (IFG) in Chinese population and (ii) exploring the potentially interactive effect between LAP and other factors on IFG risk. METHODS: Analysis was conducted on the data obtained from a community-based cross-sectional survey in Chinese population, and all the participants enrolled were required to complete a face-to-face questionnaire survey and related health checks. Then, for the purpose of comparing predictive values between LAP and conventional obesity indices for IFG, relevant analysis was carried out on the receiver operating characteristic (ROC) curve. The assessment of interactive effects was conducted by employing the three indicators as follows: (1) RERI (the relative excess risk due to interaction), (2) AP (attributable proportion due to interaction), and (3) SI (synergy index). RESULTS: A total of 1777 participants (748 males and 1029 females) were involved in the final analysis. It was finally obtained that the prevalence rate of IFG was 14.1% in total, 15.5% for males and 13.1% for females, respectively. In logistic regression analysis, individuals with LAP levels in the fourth quartile had a significant higher risk of getting IFG in comparison with that of the lowest quartile (crude OR: 4.58, 95% CI: 3.01-6.98; adjusted OR: 3.81, 95% CI: 2.33-6.23). In addition, it was indicated by the ROC curve analysis that LAP showed a better performance in discriminating IFG risk than BMI in both males (Z = 2.20, P = 0.028) and females (Z = 2.13, P = 0.033). However, LAP displayed a higher predictability in comparison with WC only in females (Z = 2.07, P = 0.038), but not in males (Z = 0.18, P = 0.860). Furthermore, LAP and family history of diabetes were able to impose significant synergistic interaction on the risk of IFG, which was indicated by all the parameters in females (RERI: 2.52, 95% CI: 0.19-4.84; AP: 0.47, 95% CI: 0.20-0.74; SI: 2.39, 95% CI: 1.17-4.87) and males (RERI: 2.18, 95% CI: 0.08-4.73; AP: 0.43, 95% CI: 0.07-0.79; SI: 2.15, 95% CI: 1.03-5.45). However, none of the indicators showed significant interaction between LAP and smoking on the risk of IFG in females (RERI: 0.92, 95% CI: -2.79-4.63; AP: 0.20, 95% CI: -0.50-0.92; SI: 1.37, 95% CI: 0.42-4.52). Meanwhile, there was also no significant interaction between LAP and smoking on the risk of IFG in males as indicated by the value of SI (2.22, 95% CI: 0.80-6.21). CONCLUSION: It was concluded that LAP was significantly related to a higher risk of IFG in Chinese population, and its performance was superior to that of conventional obesity indices, especially in females. Apart from that, LAP with family history of diabetes may have an interactive effect that can impose a great influence on the development of IFG.

Composite measure of linkage disequilibrium for testing interaction between unlinked loci.

Widely used statistical interaction models essentially treated the interaction effect as a residual term and hence are likely to limit the power to detect interaction. Alternatively, interactions between two loci can be understood as irreducible dependencies between loci causing disease or viewed as the linkage disequilibrium (LD) between them. This motivated the development of LD-based statistics for the detection of interaction between two loci. Although LD-based statistics have demonstrated high power to detect interaction between two loci, in general, linkage phase information of marker loci for unrelated individuals is unknown. To overcome this limitation, we classify the interaction between two loci into intragametic interaction that characterizes interaction of two alleles from different loci on the same haplotype and intergametic interaction that characterizes the interaction of two alleles from different loci on different haplotypes. Then we show that intragametic and intergametic interaction will lead to the corresponding intragametic and intergametic LD. This stimulates the use of composite measure of LD for developing statistics to detect interaction between two unlinked loci. To study the validity of the composite LD-based statistic for testing interaction, we estimate its type 1 error rates by simulation. To evaluate the performance of the composite LD-based statistic for detection of interaction between two loci, we compare its power with logistic regression and apply it to two real examples. The preliminary results demonstrate that the composite LD-based statistic is a strong alternative to the logistic regressions and the intragametic LD-based statistic for the detection of interaction between two unlinked loci.

A spatial analysis of genetic structure of human populations in China reveals distinct difference between maternal and paternal lineages.

Analyses of archeological, anatomical, linguistic, and genetic data suggested consistently the presence of a significant boundary between the populations of north and south in China. However, the exact location and the strength of this boundary have remained controversial. In this study, we systematically explored the spatial genetic structure and the boundary of north-south division of human populations using mtDNA data in 91 populations and Y-chromosome data in 143 populations. Our results highlight a distinct difference between spatial genetic structures of maternal and paternal lineages. A substantial genetic differentiation between northern and southern populations is the characteristic of maternal structure, with a significant uninterrupted genetic boundary extending approximately along the Huai River and Qin Mountains north to Yangtze River. On the paternal side, however, no obvious genetic differentiation between northern and southern populations is revealed.

The effect of lipid accumulation product and its interaction with other factors on hypertension risk in Chinese Han population: A cross-sectional study.

OBJECTIVES: Lipid accumulation product (LAP) is a simple and effective indicator that reflects visceral obesity. This study aimed to compare the significance of LAP in predicting hypertension risk with other obesity indices, and to evaluate the interactive effects of LAP and smoking, family history of hypertension on hypertension risk in Chinese Han adults. METHODS: A community based cross-sectional study was performed in Bengbu, China. Participants received face-to-face questionnaire survey, anthropometric tests and laboratory examinations. Relevant indicators that reflect obesity including BMI (body mass index), waist-to-height ratio (WHtR) and LAP were calculated. Multivariate logistic regression analysis was applied to explore the association between LAP and hypertension risk. The area under the receiver-operating characteristics curves (AUC) of LAP, BMI, and WHtR were calculated and then compared. Interactive effect was evaluated by relative excess risk due to interaction (RERI), attributable proportion due to interaction (AP) and synergy index (SI). RESULTS: A total of 1777 participants were enrolled, and the prevalence of hypertension was 24.4% (n = 433). There was a significant increase in hypertension risk with LAP levels in the fourth quartile as compared with the bottom quartile (OR: 3.31, 95%CI: 1.76-6.25). The AUC of LAP was significantly different than that of BMI in males (Z = 2.158, p = 0.0309) and females (Z = 3.570, p = 0.0004), while only performed better in females as compared with that of WHtR (Z = 2.166, p = 0.0303). LAP was significantly interacted with family history of hypertension on hypertension risk both in males (RERI: 1.07, 95%CI: 0.09-2.05; AP: 0.33, 95%CI: 0.23-0.44; SI: 1.92, 95%CI: 1.53-2.41) and females (RERI: 0.80, 95%CI: 0.07-1.53; AP: 0.25, 95%CI: 0.11-0.39; SI: 1.59, 95%CI: 1.16-2.19). However, a significant interaction between LAP and smoking was only observed in males (RERI: 1.32, 95%CI: 0.15-2.75; AP: 0.40, 95% CI: 0.14-0.73). CONCLUSION: Increased LAP was significantly associated with a higher risk of hypertension in Chinese Han adults. Moreover, the effect of LAP on predicting hypertension risk was better than that of other obesity indices. Our results also demonstrated interactive effects of LAP with smoking, family history of hypertension on hypertension risk.

Association between Physical Exercise and Biomarkers of Oxidative Stress among Middle-Aged and Elderly Community Residents with Essential Hypertension in China.

This study aimed to investigate the role of different types and frequencies of physical exercise in biomarkers of oxidative stress among middle-aged and elderly community residents with essential hypertension in China. A community-based cross-sectional survey was undertaken in 7 subdistricts. Individuals, 45-79 years old, with essential hypertension (n = 402) and without cardiovascular disease (n = 1047) were included. Superoxide dismutase (SOD) activities and plasma levels of malondialdehyde (MDA) and 4-hydroxynonenal (4-HNE) were determined. Multilevel linear regression was used to estimate the associations between various types of physical exercise and oxidative stress biomarker levels. Participants engaged in high frequency walking/square dancing or taiji/yoga demonstrated decreased systolic blood pressure in both groups; however, diastolic blood pressure decreased only among individuals with hypertension participating in walking/square dancing. In individuals with hypertension, MDA levels decreased in those participating in walking/square dancing, SOD activity increased in those participating in walking/square dancing, and 4-HNE levels decreased in those involved in taiji/yoga. In individuals without cardiovascular disease, MDA levels decreased in those involved in walking/square dancing or taiji/yoga, SOD activity increased in those performing walking/square dancing, and 4-HNE levels decreased in those involved in taiji/yoga. Oxidative stress marker levels also improved in those involved in walking/square dancing or taiji/yoga groups as the exercise frequency increased. Thus, frequent participation in walking/square dancing or taiji/yoga effectively decreases hypertension-related oxidative stress biomarker levels.

Evaluation of successful aging among older people in China: Results from China health and retirement longitudinal study.

AIM: China faces a "time-bomb" of the aging population. Successful aging has long been a goal in the field of gerontology. The present study aimed to evaluate successful aging among Chinese older adults. METHODS: Data on a total of 7102 people in the China Health and Retirement Study aged ≥60 years were analyzed in the present study. Successful aging is defined by the model of Rowe and Kahn including the following five indicators: "no major diseases," "no disability," "high cognitive functioning," "high physical functioning" and "active engagement with life." Using logistic regression analysis, crude and adjusted odds ratios with 95% confidence intervals were calculated to evaluate the relationship between sociodemographic parameters and successful aging. RESULTS: The prevalence of successful aging was 13.2% among Chinese older people. The percentage of older people with the five indicators, "no major diseases," "no disability," "high cognitive functioning," "high physical functioning," and "active engagement with life" was 41.7%, 92.1%, 54.2%, 70.2% and 46.0%, respectively. Multiple logistic regression showed people who had received education of high/vocational school or above had significantly greater odds of successful aging compared with those with less than primary school education (P < 0.05). The effect of education to college level or above on cognitive functioning was 2.51-fold higher in women than men (P = 0.006). Older people from a non-agricultural Hukou had 1.85-fold higher odds of successful aging than those from an agricultural Hukou. Older people living in the central, northeast or western regions had lower odds of successful aging relative to those living in the east coast region (0.72, 0.72 and 0.56, respectively). CONCLUSIONS: The prevalence of successful aging is low among Chinese older people, and is affected by sociodemographic factors, such as education, Hukou and regions. Geriatr Gerontol Int 2017; 17: 1183-1190.

Association between nighttime sleep and successful aging among older Chinese people.

OBJECTIVE: This study aims to assess the association between sleep and successful aging among Chinese ≥60 years of age. METHODS: Data were collected from the baseline survey of the China Health and Retirement Longitudinal Study. Two self-reported questions about sleep quality and duration were examined. Successful aging was defined following Rowe and Kahn's multidimensional model. To assess the adjusted association between sleep and successful aging, multivariable logistic regression was applied. RESULTS: The average number of self-reported hours of sleep was 6.2 ± 2.0 among older Chinese people. Successful aging was related to sleep duration, with the proportion of those adults considered to be aging successfully falling into the following sleep duration categories (<6 h - 7.8%; 6 h - 16.3%; 7 h - 19.1%; 8 h - 14.7%; and ≥9 h - 12.8%). The plots between sleep duration and successful aging were an inverse U-shape. Participants who slept less than 6 h per day had lower odds ratios of successful aging [odds ratio (OR) = 0.52, 95% confidence interval (CI) 0.40-0.67] relative to those who slept for 7 h per day. Compared with those who reported poor sleep less than once a week, older people who reported poor sleep five to seven days a week showed a lower ratio of successful aging (OR = 0.29, 95% CI 0.21-0.39). CONCLUSION: Older age, shorter or longer sleep, and poor sleep were related to lower odds of, rates of successful aging. Most older Chinese adults experience insufficient sleep and poor sleep quality, which could be an important influential factor in successful aging.

Effectiveness of a public dietitian-led diabetes nutrition intervention on glycemic control in a community setting in China.

OBJECTIVE: Diabetes mellitus requires lifelong treatment, most of which is accomplished in family and community settings. The present study was designed to identify the effectiveness of nutrition intervention provided by public dietitian on glycemic control in a community setting in China. METHODS: Two communities were selected and randomly assigned to a routine care group (59 subjects) and a public dietitian-led intervention group (58 subjects) who received diabetic nutrition management for one year. The main measures included fasting plasma glucose, HbA1c, weight, body mass index (BMI), lipid profile, and blood pressure. RESULTS: In the intervention group, there was significant improvement in fasting plasma glucose, HbA1c, cholesterol, and triglyceride levels relative to the control subjects (p<0.05). Over the 12-month period, there was a decrease in energy intake, including reductions in absolute amounts (grams) of protein and fat in the intervention group. The energy percent values of carbohydrate, protein, and fat were 50.7%, 17.0%, and 32.3%, respectively, at baseline and 53.0%, 17.1%, and 29.9% (within the recommended range) after the intervention. There were significant improvements in total energy, absolute amounts of fat and protein, and the energy percent values of carbohydrates and fat. In the control group, however, these values were similar before and after the intervention, and the energy percent values of fat were still above the recommended range. CONCLUSIONS: In a community setting, a diabetes nutrition intervention led by a public dietitian significantly improved the glycemic control of type 2 diabetic patients.

[Multiple nonlinear statistical method of population genetic structure based on the allelic polymorphism data].

The distribution and structure of the allelic polymorphism data are analyzed and it is pointed out that the distribution of allelic polymorphism data reveals the characteristic of closed data (also named as compositional data or data of constant sum). It is interpreted that the correlation structure of the allelic polymorphism data contains null correlations introduced by "closure" and the statistical distribution of the data is not normal because of its constant row sum, which resulted in great difficulties in analyzing the data with traditional multiple linear statistical methods such as principal component analysis, factor analysis, cluster analysis and canonical correlation analysis. Based on the theory of compositional data analysis proposed by Aitchison in 1982, a multiple nonlinear statistical method originating from the "logratios" approach to the statistical analysis of compositional data is put forward in this paper. As an example, the "logratios" method was used to analyze the genetic structure of TH01 polymorphic loci in Chinese population and the results were compared with those of multiple linear methods such as component principal. It is concluded that the "logratios" multiple nonlinear principle component analysis is a better method with the virtue of sensitivity and specificity for analyzing the genetic structure of population from the data of allelic polymorphism.