Association between plasma and dietary trace elements and obesity in a rural Chinese population.

Trace elements may play an important role in obesity. This study aimed to assess the plasma and dietary intake levels of four trace elements, Mn, Cu, Zn and Se in a rural Chinese population, and analyse the relationship between trace elements and obesity. A cross-sectional study involving 2587 participants was conducted. Logistic regression models were used to analyse the association between trace elements and obesity; restricted cubic spline (RCS) models were used to assess the dose-response relationship between trace elements and obesity; the weighted quantile sum (WQS) model was used to examine the potential interaction of four plasma trace elements on obesity. Logistic regression analysis showed that plasma Se concentrations in the fourth quartile (Q4) exhibited a lower risk of developing obesity than the first quartile (Q1) (central obesity: OR = 0·634, P = 0·002; general obesity: OR = 0·525, P = 0·005). Plasma Zn concentration in the third quartile (Q3) showed a lower risk of developing obesity in general obesity compared with the first quartile (Q1) (OR = 0·625, P = 0·036). In general obesity, the risk of morbidity was 1·727 and 1·923 times higher for the second and third (Q2, Q3) quartiles of dietary Mn intake than for Q1, respectively. RCS indicated an inverse U-shaped correlation between plasma Se and obesity. WQS revealed the combined effects of four trace elements were negatively associated with central obesity. Plasma Zn and Se were negatively associated with obesity, and dietary Mn was positively associated with obesity. The combined action of the four plasma trace elements had a negative effect on obesity.

Association between the dietary antioxidant index and relative telomere length of leucocytes in the Chinese population.

Dietary antioxidant indices (DAI) may be potentially associated with relative telomere length (RTL) of leucocytes. This study aimed to investigate the relationship between DAI and RTL. A cross-sectional study involving 1656 participants was conducted. A generalised linear regression model and a restricted cubic spline model were used to assess the correlation of DAI and its components with RTL. Generalised linear regression analysis revealed that DAI (ß = 0·005, P = 0·002) and the intake of its constituents vitamin C (ß = 0·043, P = 0·027), vitamin E (ß = 0·088, P < 0·001), Se (ß = 0·075, P = 0·003), and Zn (ß = 0·075, P = 0·023) were significantly and positively correlated with RTL. Sex-stratified analysis showed that DAI (ß = 0·006, P = 0·005) and its constituents vitamin E (ß = 0·083, P = 0·012), Se (ß = 0·093, P = 0·006), and Zn (ß = 0·092, P = 0·034) were significantly and positively correlated with RTL among females. Meanwhile, among males, only vitamin E intake (ß = 0·089, P = 0·013) was significantly and positively associated with RTL. Restricted cubic spline analysis revealed linear positive associations between DAI and its constituents' (vitamin E, Se and Zn) intake and RTL in the total population. Sex-stratified analysis revealed a linear positive correlation between DAI and its constituents' (vitamin E, Se and Zn) intake and RTL in females. Our study found a significant positive correlation between DAI and RTL, with sex differences.

Association between multiple-heavy-metal exposures and systemic immune inflammation in a middle-aged and elderly Chinese general population.

BACKGROUND: Exposure to heavy metals alone or in combination can promote systemic inflammation. The aim of this study was to investigate potential associations between multiple plasma heavy metals and markers of systemic immune inflammation. METHODS: Using a cross-sectional study, routine blood tests were performed on 3355 participants in Guangxi, China. Eight heavy metal elements in plasma were determined by inductively coupled plasma mass spectrometry. Immunoinflammatory markers were calculated based on peripheral blood WBC and its subtype counts. A generalised linear regression model was used to analyse the association of each metal with the immunoinflammatory markers, and the association of the metal mixtures with the immunoinflammatory markers was further assessed using weighted quantile sum (WQS) regression. RESULTS: In the single-metal model, plasma metal Fe (log10) was significantly negatively correlated with the levels of immune-inflammatory markers SII, NLR and PLR, and plasma metal Cu (log10) was significantly positively correlated with the levels of immune-inflammatory markers SII and PLR. In addition, plasma metal Mn (log10 conversion) was positively correlated with the levels of immune inflammatory markers NLR and PLR. The above associations remained after multiple corrections. In the mixed-metal model, after WQS regression analysis, plasma metal Cu was found to have the greatest weight in the positive effects of metal mixtures on SII and PLR, while plasma metals Mn and Fe had the greatest weight in the positive effects of metal mixtures on NLR and LMR, respectively. In addition, blood Fe had the greatest weight in the negative effects of the metal mixtures for SII, PLR and NLR. CONCLUSION: Plasma metals Cu and Mn were positively correlated with immunoinflammatory markers SII, NLR and PLR. While plasma metal Fe was negatively correlated with immunoinflammatory markers SII, NLR, and PLR.

Analysis of the association between dietary patterns and nonalcoholic fatty liver disease in a county in Guangxi.

BACKGROUND: This study aims to investigate the relationship between different dietary patterns and non-alcoholic fatty liver disease (NAFLD). METHODS: Residents over 30 years old in the ecological longevity cohort in Gongcheng Yao Autonomous County, Guangxi Province were the research objects selected from 2018 to 2019. Physical examination, baseline population survey, and food frequency questionnaire (FFQ) survey were conducted. Dietary patterns were analyzed by factor analysis. Influencing factors of NAFLD were analyzed by multiple logistic regression. RESULTS: NAFLD was diagnosed in 241 of 2664 participants based on ultrasonography, and the detection rate was 9.0%. Factor analysis yielded a total of three dietary patterns, namely, traditional Chinese, Western, and cereal-potato dietary patterns. Results of multivariate logistic regression analysis showed that after adjusting for confounding factors, participants in the highest quartile of the Western dietary pattern exhibited a higher prevalence of NAFLD (OR = 2.799; 95% CI: 1.620-4.837; p < 0.05) than participants in the lowest quartile. Participants in the highest quartile of the cereal-potato pattern exhibited a decreased risk of NAFLD compared with those in the lowest quartile (OR = 0.581; 95% CI: 0.371-0.910, p < 0.05). The traditional Chinese patterns did not show any association with the risk of NAFLD. CONCLUSIONS: The Western dietary pattern increases the risk of NAFLD, whereas the cereal-potato dietary pattern reduces the risk of NAFLD. It is important for the prevention and control of NAFLD to adhere to the cereal-potato dietary.

The relationship between dietary complexity and cognitive function in Guangxi, China: A cross-sectional study.

BACKGROUND AND OBJECTIVES: The composition of the human diet is complex and diverse, and the relation-ship between dietary composition and cognitive decline has not been adequately studied. Therefore, this study explored the possible association between food items and the risk of cognitive impairment. METHODS AND STUDY DESIGN: This cross-sectional study was based on an ecological longevity cohort and included 2881 participants (1086 men and 1795 women) aged ≥30 years between December 2018 and November 2019. The association between food items and the risk of cognitive impairment was explored using the Bayesian kernel machine regression (BKMR) learning model. RESULTS: Finally, 2881 participants (1086 men and 1795 women) were included. In all participants, the multivariable logistic analysis showed that fresh fruit consumption was associated with cognitive function (OR=0.999, 95% CI: 0.998-0.999, p=0.021). Using the BKMR model, none of the 18 food items were significantly correlated with cognitive function among women. In men, when the other food items were fixed at the 25th, 50th, and 75th percentile values (P25, estimate=-0.239; P50, estimate=-0.210; P75, estimate=-0.158), there was a negative correlation between fresh fruit consumption and the predicted risk of cognitive function disorders. CONCLUSIONS: Men displayed a negative association be-tween fresh fruit consumption and the risk of cognitive function disorders, but this was not apparent among women.

DriverRWH: discovering cancer driver genes by random walk on a gene mutation hypergraph.

BACKGROUND: Recent advances in next-generation sequencing technologies have helped investigators generate massive amounts of cancer genomic data. A critical challenge in cancer genomics is identification of a few cancer driver genes whose mutations cause tumor growth. However, the majority of existing computational approaches underuse the co-occurrence mutation information of the individuals, which are deemed to be important in tumorigenesis and tumor progression, resulting in high rate of false positive. RESULTS: To make full use of co-mutation information, we present a random walk algorithm referred to as DriverRWH on a weighted gene mutation hypergraph model, using somatic mutation data and molecular interaction network data to prioritize candidate driver genes. Applied to tumor samples of different cancer types from The Cancer Genome Atlas, DriverRWH shows significantly better performance than state-of-art prioritization methods in terms of the area under the curve scores and the cumulative number of known driver genes recovered in top-ranked candidate genes. Besides, DriverRWH discovers several potential drivers, which are enriched in cancer-related pathways. DriverRWH recovers approximately 50% known driver genes in the top 30 ranked candidate genes for more than half of the cancer types. In addition, DriverRWH is also highly robust to perturbations in the mutation data and gene functional network data. CONCLUSION: DriverRWH is effective among various cancer types in prioritizes cancer driver genes and provides considerable improvement over other tools with a better balance of precision and sensitivity. It can be a useful tool for detecting potential driver genes and facilitate targeted cancer therapies.

Association between combined exposure to plasma heavy metals and dyslipidemia in a chinese population.

BACKGROUND: Exposure to heavy metals in the environment is widespread, while the relationship between combined exposure to heavy metals and dyslipidemia is unclear. METHODS: A cross-sectional study was performed, and 3544 participants aged 30 years or older were included in the analyses. Heavy metal concentrations in plasma were based on inductively coupled plasma‒mass spectrometry. The relationship between heavy metals and dyslipidemia was estimated by logistic regression. BKMR was used to evaluate metal mixtures and their potential interactions. RESULTS: In logistic regression analysis, participants in the fourth quartile of Fe and Zn (Fe > 1352.38 µg/L; Zn > 4401.42 µg/L) had a relatively higher risk of dyslipidemia (Fe, OR = 1.13, 95% CI: 0.92,1.38; Zn, OR = 1.30, 95% CI: 1.03,1.64). After sex stratification, females in the third quartile of plasma Zn (1062.05-4401.42 µg/L) had a higher relative risk of dyslipidemia (OR = 1.75, 95% CI: 1.28, 2.38). In BKMR analysis, metal mixtures were negatively associated with dyslipidemia in females when all metal concentrations were above the 50th percentile. In the total population (estimated from 0.030 to 0.031), As was positively associated with dyslipidemia when other metals were controlled at the 25th, 50th, or 75th percentile, respectively, and As was below the 75th percentile. In females (estimated from - 0.037 to -0.031), Zn was negatively associated with dyslipidemia when it was above the 50th percentile. CONCLUSION: This study indicated that As was positively associated with dyslipidemia and that Zn may be negatively associated with dyslipidemia in females. Combined metal exposure was negatively associated with dyslipidemia in females. Females with low plasma Zn levels are more likely to develop dyslipidemia and should receive more clinical attention in this population.

Association between plasma cadmium and renal stone prevalence in adults in rural areas of Guangxi, China: a case-control study.

BACKGROUND: Kidney stones have become a worldwide public health problem. The purpose of this research is to study the relationship between plasma cadmium level and the prevalence of kidney stones in an adult population. METHODS: The data of this study were based on a current survey conducted from December 2018 to November 2019 in Gongcheng Yao Autonomous County, Guangxi, China. A total of 940 study subjects of the same sex and age (within 2 years of each other) according to 1:1 matching were selected for a case-control study. The diagnosis of kidney stones was based on the presence of strong light spots, patches, clusters, or bands within the renal sinus region, followed by an echo-free bundle of acoustic images. Plasma metal elements were determined by the metal plasma method. The relationship between plasma cadmium concentration and the prevalence of kidney stones was assessed using logistic regression and restricted cubic spline regression. RESULTS: The crude ratio for kidney stones in the highest quartile of plasma cadmium was 1.164 (95% CI, 1.121 to 2.324) compared with the lowest quartile. A positive correlation was found between the two (P for trend = 0.039). After adjusting for potential confounders, the ratio of plasma cadmium to kidney stones in the highest quartile was 1.606 (95% CI, 1.100 to 2.344) compared with the lowest quartile, and the findings remained unchanged. CONCLUSION: The odds of kidney stones in adults increased with increasing plasma cadmium exposure, and high plasma cadmium may be a risk factor for kidney stones.

Adherence to dietary guide for elderly adults and health risks of older adults in ethnic minority areas in China: a cross-sectional study.

BACKGROUND: The impact of dietary guidelines on health in ethnic minority regions needs to be further explored because of multiple sociocultural factors. Therefore, this study was conducted to analyze the association between adherence to dietary guidelines and health risks in an elderly population in an ethnic minority region. METHODS: A cross-sectional survey was conducted among 836 older adults in ethnic minority areas. They were asked to describe their daily dietary intake levels through a semi-quantitative food frequency questionnaire. The closeness coefficient for each study subject was calculated by using the technique for order preference by similarity to an ideal solution (TOPSIS), which measures the adherence to Dietary Guide for Elderly Adults (DGEA). Regression models were used to analyze the association between adherence and health risks. RESULTS: The daily food of the elderly in this area comprised cereals and vegetables. They had low intake of milk, dairy products, and water and high intake of salt. The closeness coefficient for the total population was 0.51, and the adherence of this population to dietary guidelines for the elderly was low. In both the crude model and the models adjusted for covariates, the closeness coefficient was not significantly associated with clinical indicators and health outcomes (p > 0.05). CONCLUSIONS: No association was found between adherence to large sample-based dietary guidelines and clinical indicators or health outcomes in ethnic minority populations. The applicability of dietary guidelines to ethnic minority areas and whether they yield the expected health benefits require further study.

Geographical distinctions of longevity indicators and their correlation with climatic factors in the area where most Chinese Yao are distributed.

Longevity research is a hot topic in the health field. Considerable research focuses on longevity phenomenon in Bama Yao Autonomous County, which has a typical karst landform and is located in Southwest China. This study aims to illustrate the spatial feature of longevity indicators in other Yao areas, to analyze the correlation between climatic factors and longevity indicators, and to provide new clues and targets for further longevity studies. We collect and integrate population, climate, and terrain data into a spatial database. The main analysis methods include spatial autocorrelation, high/low clustering, and multiscale geographically weighted regression (MGWR). Two longevity clusters are identified in Guijiang River Basin (longevity index (LI%): 2.49 ± 0.63) and Liujiang River Basin (LI%: 2.13 ± 0.60). The spatial distribution of longevity indicators is autocorrelative (Moran's I = 0.652, p < 0.001) and clustered significantly (Z score = 4.268, p < 0.001). MGWR shows that the atmospheric pressure significantly affects the spatial distribution of LI% (estimate value (EV) = - 0.566, p = 0.012), centenarity index (CI%) (EV = - 0.425, p = 0.007), UC (EV = - 0.502, p = 0.006), and CH (EV = - 0.497, p = 0.007). Rainfall significantly affects the spatial distribution of LI% (EV = 0.300, p = 0.003) and CI% (EV = - 0.191, p = 0.016). The spatial distribution of the main longevity indicators shows significant heterogeneity and autocorrelation, and they cluster in the Guijiang River and Liujiang River basins. Atmospheric pressure and rainfall may contribute to the longevity phenomenon through complex mechanisms. The longevity phenomenon in the Yao nationality in Guijiang River Basin requires further study to improve our understanding of the health effect of meteorological, environmental, and social conditions on longevity.

Correlation between urinary contents of some metals and fasting plasma glucose levels: A cross-sectional study in China.

Many metals are involved in the pathogenesis of diabetes, but most of existing studies focused on single metals. The study of mixtures represents real-life exposure scenarios and deserves attention. This study aimed to explore the potential relationship of urinary copper (Cu), zinc (Zn), arsenic (As), selenium (Se), and strontium (Sr) contents with fasting plasma glucose (FPG) levels in 2766 participants. The levels of metals in urine were determined by inductively coupled plasma-mass spectrometry. We used linear regression models and the Bayesian kernel machine regression (BKMR) to evaluate the association between metals and FPG levels. In the multiple metals linear regression, Zn (ß = 0.434), Se (ß = 0.172), and Sr (ß = -0.143) showed significant association with FPG levels (all P < 0.05). The BKMR model analysis showed that the results of single metal association were consistent with the multiple metals linear regression. The mixture of five metals had a positive over-all effect on FPG levels, and Zn (PIP = 1.000) contributed the most to the FPG levels. Cu and As were negatively correlated with FPG levels in women. The potential interaction effect between Cu and Sr was observed in participants aged ≥ 60 years old (Pinteraction = 0.035). In summary, our results suggested that multiple metals in urine are associated with FPG levels. Further studies are needed to confirm these findings and clarify the underlying mechanisms.

Association between oil tea intake and the risk of type 2 diabetes in adults: A cross-sectional study in Gongcheng, Guangxi, China.

BACKGROUND AND OBJECTIVES: The associations between oil tea and type 2 diabetes (T2D) have been little studied in the population. This study aimed to evaluate whether oil tea intake is related to the reduced risk of T2D in adults. METHODS AND STUDY DESIGN: A rural-based cross-sectional study was conducted in Gongcheng Yao Autonomous County, Guangxi, southern China (2018-2019), with a total of 3178 population included in the final analysis. A multivariable logistic regression model was used to analyze the associations between the intake frequency, daily intake of oil tea and the risk of T2D. We further compared the association differences between the daily intake of oil tea and the risk of diabetes under different dietary patterns, which were generated from food frequency intake data using principal factor analysis. RESULTS: The differences in the frequency and daily intake of oil tea in both groups (diabetes group and the non-diabetes group) were statistically significant (p<0.05). After adjusting for age, sex, smoking status, physical activity, body mass index (BMI), compared with non-oil tea drinkers, intake ≥3 times /d had an inverse association with T2D (OR=0.417; 95% CI: 0.205-0.848, p<0.05); while daily intake of more than 600 mL/d but less than 900 mL/d was significantly associated with reduced T2D risk (OR=0.492; 95% CI: 0.284-0.852, p=0.011). In the Chinese traditional dietary and the plant-based dietary model, compared with the non-oil tea drinkers, the fourth intake group had a lower risk of diabetes, with an OR (95%CI) value of 0.500 (0.291-0.854) and 0.505 (0.298-0.855), respectively, but no statistical significance (All p>0.05). CONCLUSIONS: Our study suggests that oil tea was associated with a reduced risk of T2D aged 30 years or older.

Comparations of major and trace elements in soil, water and residents' hair between longevity and non-longevity areas in Bama, China.

Natural environment is an important factor affecting longevity. Soil, water and hair samples from Bama were assayed to investigate the effects of elements on the regional longevity. The concentrations of Cd, Co and Mg in soil and Co in drinking water were significantly higher in longevity area than those in non-longevity area (p < 0.05). The concentrations of K, Mo, Na, Pb and V in soil, Mg, Na, Fe, Li and Mn in drinking water and I, K, Mg, Mn, Na and Sr in hair were significantly lower in longevity area than those in non-longevity area (p < 0.05). Mg, Mn, Na and Sr in hair were affected by soil and drinking water. Our results indicate that adequate concentration of Mg in soil might benefit longevity, excessive concentrations of Na in soil, Mg, Mn and Na in drinking water and Mg, Mn, Na and Sr in hair might reduce lifespan of local residents.

Spatial, temporal, and spatiotemporal analysis of mumps in Guangxi Province, China, 2005-2016.

BACKGROUND: The resurgence of mumps around the world occurs frequently in recent years. As the country with the largest number of cases in the world, the status of mumps epidemics in China is not yet clear. This study, taking the relatively serious epidemic province of Guangxi as the example, aimed to examine the spatiotemporal pattern and epidemiological characteristics of mumps, and provide a scientific basis for the effective control of this disease and formulation of related health policies. METHODS: Geographic information system (GIS)-based spatiotemporal analyses, including spatial autocorrelation analysis, Kulldorff's purely spatial and space-time scan statistics, were applied to detect the location and extent of mumps high-risk areas. Spatial empirical Bayesian (SEB) was performed to smoothen the rate for eliminating the instability of small-area data. RESULTS: A total of 208,470 cases were reported during 2005 and 2016 in Guangxi. Despite the fluctuations in 2006 and 2011, the overall mumps epidemic continued to decline. Bimodal seasonal distribution (mainly from April to July) were found and students aged 5-9 years were high-incidence groups. Though results of the global spatial autocorrelation based on the annual incidence largely varied, the spatial distribution of the average annual incidence of mumps was nonrandom with the significant Moran's I. Spatial cluster analysis detected high-value clusters, mainly located in the western, northern and central parts of Guangxi. Spatiotemporal scan statistics identified almost the same high-risk areas, and the aggregation time was mainly concentrated in 2009-2012. CONCLUSION: The incidence of mumps in Guangxi exhibited spatial heterogeneity in 2005-2016. Several spatial and spatiotemporal clusters were identified in this study, which might assist the local government to develop targeted health strategies, allocate health resources reasonably and increase the efficiency of disease prevention.

Impact of meteorological factors on mumps and potential effect modifiers: An analysis of 10 cities in Guangxi, Southern China.

BACKGROUND: In the current context of global climate change, understanding the impact of climate on respiratory infectious diseases such as mumps and the potential modified factors is crucial, especially in developing countries. However, research on the climate-related incidence of mumps is rare, inconsistent and mainly limited to a single city or region. METHODS: Daily mumps cases and meteorological variables of 10 cities in Guangxi, Southern China were collected for 2005-2017. Two-stage analyses were performed to assess the relationship between meteorological factors and mumps incidence during two time-periods: 2005-2012 and 2013-2017, separately. First, a Poisson regression model that allows over-dispersion was used to estimate the city-specific climate-related morbidity after controlling for temporal trends, day of week, and national statutory holidays. Then, we used a multivariate meta-analytical model to pool the city-specific effect estimates and conducted subgroup analyses. Multivariate meta-regression was applied to detect potential effect modifiers. RESULTS: Non-linear relationships were observed among mean temperature, wind speed, and mumps incidence in 2005-2012. The impact of high temperature on mumps incidence was short and rapid, whereas the impact of low temperature was long and slow. The total cumulative relative risk (RR) associated with hot temperature was 1.18 [95% Confidence Interval (CI): 0.93, 1.48], which was calculated by comparing the incidence of mumps above the 90th percentile of temperature with its incidence at the median temperature at lag of 0-30 days. Meanwhile, the RR associated with cold temperature was calculated to be 1.50 (95% CI: 1.08, 2.10) by comparing the incidence of mumps below the 10th percentile of temperature with its incidence at the median temperature. Similarly, the RRs associated with windless and windy conditions for the total population were 1.23 (95% CI: 1.04, 1.46) and 0.83 (95% CI: 0.67, 1.02), respectively. Effects based on extreme temperature and wind speed conditions were more prominent in males than in females. Compared with children and adults, adolescents (5-14 years old) were more sensitive to extreme weather conditions. Geographical latitude, Population density, GDP per capita, Number of health institutions, Highly educated population and Inoculation rate were considered the most likely associated modifiers. In addition, the correlation between meteorological factors and the incidence of mumps and modification of socioeconomic factors after 2013 showed similar curves compared with results in 2005-2012, but the cumulative effect was not statistically significant. CONCLUSIONS: Meteorological factors, such as temperature and wind speed, exert a significant impact on the incidence of mumps. The relationship varies depending on gender and age. Socioeconomic factors such as vaccination, GDP, geographical latitude, etc. may substantially affect the weather-related mumps incidence.

Association between Copper Exposure and Cognitive Function: A Cross-Sectional Study in a County, Guangxi, China.

There has been growing attention to the impact of copper exposure on cognitive function; however, current research on the specific information regarding urinary copper and cognitive function is limited, particularly detailed analyses in the Chinese adult population. This study aimed to explore the association between copper exposure and cognitive function in a cross-sectional design. A total of 2617 participants in a county, Guangxi Zhuang Autonomous Region (Guangxi), China, were included. The mini-mental state examination (MMSE) was used to assess cognitive function, and inductively coupled plasma mass spectrometry was used to measure urinary metal levels. Spearman's rank correlation was used to analyze the correlation between urinary copper levels and various cognitive function assessment indices. After adjusting for potential confounders, binary logistic regression was used to explore the association between urinary copper levels and the risk of cognitive impairment (CI) as revealed by MMSE, and restricted cubic spline regression was further used to explore the dose-response relationship. The results showed a negative correlation between urinary copper levels and orientation, attention and calculation, memory, language ability, and MMSE total scores (P < 0.05). Compared with the low copper exposure group, the high exposure group showed a 58.5% increased risk of CI (OR = 1.585, 95%CI: 1.125 to 2.235, P = 0.008). A significant linear dose-response relationship was observed between urinary copper levels and the risk of CI (P overall = 0.045, P nonlinearity = 0.081). Our findings suggest that higher copper exposure may be associated with CI in the population of a county, Guangxi, China.

Association Between Combined Polymetallic Exposure and Osteoporosis.

Combined polymetallic exposure may be an influential factor in osteoporosis. This study aimed to explore the association between polymetallic combined exposure and osteoporosis. A total of 2115 participants were included. Plasma concentrations of 22 metals were determined by inductively coupled plasma mass spectrometry. Osteoporosis was defined as a T ≤ - 2.5. The least absolute shrinkage and selection operator (LASSO) regression, binary logistics regression, and Bayesian kernel machine regression (BKMR) model were used to explore the association between plasma metals and osteoporosis. LASSO regression showed that 10 metals were associated with osteoporosis in the total population (magnesium, calcium, manganese, nickel, cobalt, arsenic, selenium, rubidium, cadmium, aluminum) and women (magnesium, calcium, molybdenum, nickel, cobalt, arsenic, selenium, rubidium, cadmium, aluminum), and four metals associated with men (magnesium, cobalt, aluminum, iron). Logistics regression showed that in total population, magnesium (ORQ3 = 0.653, 95% CI = 0.446-0.954) was negatively correlated with osteoporosis, while aluminum (ORQ2 = 1.569, 95% CI = 1.095-2.248, ORQ4 = 1.616, 95% CI = 1.109-2.354) and cadmium (ORQ4 = 1.989, 95% CI = 1.379-2.870) were positively correlated; in women, magnesium (ORQ3 = 0.579, 95% CI = 0.379-0.883) was negatively correlated with osteoporosis, while aluminum (ORQ2 = 1.563, 95% CI = 1.051-2.326, ORQ4 = 1.543, 95% CI = 1.024-2.326) and cadmium (ORQ3 = 1.482, 95% CI = 1.003-2.191, ORQ4 = 1.740, 95% CI = 1.167-2.596) were positively correlated. BKMR model showed that combined polymetallic exposure had an overall positive effect on osteoporosis, magnesium was negatively associated with osteoporosis, and cadmium, selenium, and aluminum were positively associated with osteoporosis. Metal mixtures in plasma were associated with osteoporosis risk. Magnesium may reduce the risk of osteoporosis, while cadmium, selenium, and aluminum may increase the risk of osteoporosis. Future studies needed to explore correlations and mechanisms.

Correlations between growth differentiation factor 15 (GDF-15) serum levels and gene polymorphism with type 2 diabetes mellitus.

Purpose: To date, the relationship between Growth Differentiation Factor 15 (GDF-15) gene polymorphism and the risk of type 2 diabetes mellitus (T2DM) has not been clarified. Our study aims to explore the association between serum GDF-15 levels and related gene polymorphism with the risk of T2DM in a Chinese rural Yao population. Methods: This was a 1:1 case-control study with 179 T2DM patients and 179 age- and sex-matched control participants. Serum GDF-15 levels were measured by enzyme-linked immunosorbent assay, and polymorphisms (rs1059519, rs1059369, rs1804826 and rs1054564) were genotyped by MassArray mass spectrometry. Results: Serum GDF-15 (sGDF-15) levels were higher in patients with T2DM and glycosylated hemoglobin (HbA1c) ≥ 6.5 % compared to that in controls (p < 0.001). The area under the curve (AUC) corresponding to sGDF-15 levels was 0.626. Serum GDF-15 was positively correlated with fasting plasma glucose (FPG) (rs = 0.150, p < 0.001) and HbA1c (rs = 0.160, p < 0.001). The frequency of GDF-15 gene rs1054564 GC + CC genotype was significantly associated with increased risk of T2DM compared to GG genotype (OR = 1.724, 95CI: 1.046-2.841, p = 0.033). Frequencies of rs1804826 T allele (ß additive = 113.318, p = 0.026) and rs1054564 C allele (ß additive = 247.282, p = 0.001, ß dominant = 286.109, p = 0.001) was significantly correlated with higher sGDF-15. The rs1059519 C allele was negatively correlated with FPG (ß recessive = -0.607, p = 0.047) and HbA1c (ß recessive = -0.456, p = 0.020). Conclusion: Serum GDF-15 levels were positively correlated with FPG and HbA1c. The GDF-15 rs1054564 GC + CC genotype was associated with a significantly higher T2DM risk. The rs1059519 C allele was negatively correlated with FPG and HbA1c.

Associations of Dietary and Plasma Copper Levels with Liver Function in a Chinese Population.

The potential mechanisms underlying the association between copper (Cu) exposure and impaired liver function are unclear. This study aimed to investigate the potential associations of dietary Cu intake and plasma Cu levels with liver function biomarkers. A cross-sectional study was performed to assess liver function biomarkers-namely, levels of total bilirubin (TBIL), direct bilirubin (DBIL), indirect bilirubin (IBIL), alanine transaminase (ALT), and aspartate transaminase (AST)-in 2376 subjects in Guangxi, China. Dietary Cu intake was determined from a food frequency questionnaire containing 109 common foods. Plasma Cu concentrations were determined by inductively coupled plasma‒mass spectrometry. Multiple linear regression and multivariate restricted cubic splines (RCS) were used to evaluate the correlations of plasma Cu levels and dietary Cu levels with liver function biomarkers. The covariate-adjusted results of the linear regression analysis showed that plasma Cu levels were significantly negatively correlated with serum IBIL (ß = - 0.37), DBIL (ß = - 0.22), and TBIL levels (ß = - 0.32) (all p < 0.05), and dietary Cu was negatively correlated with serum AST levels (ß = - 0.12, p < 0.05). The RCS analysis further indicated a negative linear relationship between dietary Cu levels and AST levels. In summary, our results suggested that the plasma Cu level is associated with serum bilirubin levels and that dietary Cu intake is associated with serum AST levels. Further studies are needed to validate these associations and elucidate the underlying mechanisms.