The Association of Body Fat Percentage With Hypertension in a Chinese Rural Population: The Henan Rural Cohort Study

Menopause modified the association of blood pressure with osteoporosis among gender: a large-scale cross-sectional study

Purpose

This study aimed to assess the potential association between blood pressure and osteoporosis in a rural population with limited resources. Existing evidence on this association is limited, particularly in such settings.

Methods

Data from 7,689 participants in the Henan Rural Cohort study were analyzed. Four blood pressure indicators [systolic blood pressure (SBP), diastolic blood pressure (DBP), mean arterial pressure (MAP), and pulse pressure (PP)] were measured. The logistic regression model and restricted cubic spline plots were used to assess the relationship between blood pressure indicators and osteoporosis prevalence.

Results

Positive trends were noted between blood pressure indicators and osteoporosis prevalence in the entire group and women (P trend < 0.05 for SBP, MAP, and PP). Women with higher SBP and PP exhibited elevated odds of osteoporosis compared with those with the lowest SBP and PP (ORs ranging from 1.15 to 1.5 for SBP and 1.06 to 1.83 for PP). No such associations were found in men. These relationships were only evident in postmenopausal women. Dose-response analysis confirmed these findings. Excluding participants taking hypertension medication did not alter the results.

Conclusion

In resource-limited settings, higher SBP and PP are associated with the increased prevalence of osteoporosis in women, potentially influenced by menopause-related factors. This indicates that potential gender-based differences and social inequalities may affect bone health.

Clinical trial registration

The Henan Rural Cohort Study has been registered at the Chinese Clinical Trial Register (Registration number: ChiCTR-OOC-15006699) http://www.chictr.org.cn/showproj.aspx?proj=11375.

Additive interactions between obesity and insulin resistance on hypertension in a Chinese rural population

BACKGROUND

Adiposity and insulin resistance (IR) are closely associated with hypertension; however, the role of interactions between obesity phenotypes and IR in hypertension is unclear. This study aimed to evaluate the interactions of body mass index (BMI), waist circumference (WC), and body fat percentage (BF%) with IR on hypertension risk.

METHODS

We analyzed data from 4888 participants (mean age 57 years, 41.2% men) in the China Northwest Natural Population Cohort, Ningxia Project. BMI, WC, and BF% were determined using bioelectrical impedance analysis devices. IR was estimated using a homeostasis model assessment index (HOMA-IR). Multivariable-adjusted logistic regression was used to evaluate the association between HOMA-IR and hypertension risk. We calculated the relative excess risk and attributable proportion with their 95% confidence intervals (CIs) to assess whether adiposity phenotypes modified the effect of HOMA-IR on hypertension risk.

RESULTS

The crude prevalence of hypertension was 52.2%. The multivariable-adjusted odds ratio of HOMA-IR was 1.80 (95% CI: 1.23-2.65) for the risk of hypertension in the highest versus the lowest quartiles, but this association became marginal in models further adjusting for BMI, WC, and BF% (P for trend = 0.056). Relative excess risk and attributable proportion for interaction between high HOMA-IR and high BF% were 0.32 (0.04-0.59) and 0.33 (0.06-0.60), respectively. Additionally, high truncal and leg BF% and high HOMA-IR accounted for the hypertension risk in women, but not in men. We did not observe any significant interactions between BMI or WC and HOMA-IR on hypertension.

CONCLUSION

BF% modified the association between IR and increased risk of hypertension in women with high truncal and leg BF%, but not in men.

The role of SGLT2i in attenuating residual cardiovascular risk through blood pressure-lowering: mechanistic insights and perspectives

Sodium glucose cotransporter 2 inhibitors (SGLT2) have been increasingly pursued as a promising target for addressing residual cardiovascular risk. Prior trials demonstrated that SGLT2i not only promotes glucose-lowering, but also improves endothelial dysfunction, adiposity, fluid overload, and insulin sensitivity thus contributing to hemodynamic changes implicated in its cardiorenal benefits. The mechanisms in the effect of SGLT2i on blood pressure and their potential role in preventing cardiovascular events are hereby revised.

Body composition predicts hypertension using machine learning methods: a cohort study

We used machine learning methods to investigate if body composition indices predict hypertension. Data from a cohort study was used, and 4663 records were included (2156 were male, 1099 with hypertension, with the age range of 35-70 years old). Body composition analysis was done using bioelectrical impedance analysis (BIA); weight, basal metabolic rate, total and regional fat percentage (FATP), and total and regional fat-free mass (FFM) were measured. We used machine learning methods such as Support Vector Classifier, Decision Tree, Stochastic Gradient Descend Classifier, Logistic Regression, Gaussian Naïve Bayes, K-Nearest Neighbor, Multi-Layer Perceptron, Random Forest, Gradient Boosting, Histogram-based Gradient Boosting, Bagging, Extra Tree, Ada Boost, Voting, and Stacking to classify the investigated cases and find the most relevant features to hypertension. FATP, AFFM, BMR, FFM, TRFFM, AFATP, LFATP, and older age were the top features in hypertension prediction. Arm FFM, basal metabolic rate, total FFM, Trunk FFM, leg FFM, and male gender were inversely associated with hypertension, but total FATP, arm FATP, leg FATP, older age, trunk FATP, and female gender were directly associated with hypertension. AutoMLP, stacking and voting methods had the best performance for hypertension prediction achieving an accuracy rate of 90%, 84% and 83%, respectively. By using machine learning methods, we found that BIA-derived body composition indices predict hypertension with acceptable accuracy.

Sex-specific difference in the relationship between body fat percentage and arterial stiffness: Results from Fuzhou study

Obesity and overweight are closely related to cardiovascular mortality. Arterial stiffness is one of the important risks for cardiovascular diseases and is strongly related with the cardiovascular mortality. However, the relationship between obesity and arterial stiffness is still controversial. A cross-sectional study was performed to examine the relationship of body fat percentage (BFP), an indicator of obesity, with carotid-femoral pulse wave velocity (cfPWV) in 2603 subjects (aged 58.62 ± 11.27 years, male 71.07%, hypertension 64.89%). All participants were divided into four groups according to the gender and the presence of arterial stiffening based on a value ≥10 m/s of cfPWV(group1 : male with cfPWV <10 m/s, group2 : male with cfPWV ≥10 m/s, group3 : female with cfPWV <10 m/s, group4 : female with cfPWV ≥10 m/s). Body weight, height, waist circumference, blood pressure were measured and clinical biochemical tests were recorded. cfPWV was measured using a non-invasive automatic device (Complior Analysis, France). BFP were calculated by CUN-BAE equation. The level of cfPWV was significantly increased with the increasing trend of BFP in both males and females. Stepwise multiple regression analysis revealed that SBP, DBP, HR, Hcy, BFP, FPG were independent associated with cfPWV in females and SBP, eGFR, FPG, BFP, DBP were independent associated with cfPWV in males. In the subgroups stratified by age, BFP was correlated with cfPWV only in females over 60 years old, but not in female those aged under 60 years old and males. In addition to the age and blood pressure, BFP was one of important predictor of arterial stiffening special in females aged over 60 years old.

Independent Associations of Education, Intelligence, and Cognition With Hypertension and the Mediating Effects of Cardiometabolic Risk Factors: A Mendelian Randomization Study

BACKGROUND

Education, intelligence, and cognition are associated with hypertension, but which one plays the most prominent role in the pathogenesis of hypertension and which modifiable risk factors mediate the causal effects remains unknown.

METHODS

Using summary statistics of genome-wide association studies of predominantly European ancestry, we conducted 2-sample multivariable Mendelian randomization to estimate the independent effects of education, intelligence, or cognition on hypertension (FinnGen study, 70 651 cases/223 663 controls; UK Biobank, 77 723 cases/330 366 controls) and blood pressure (International Consortium of Blood Pressure, 757 601 participants), and used 2-step Mendelian randomization to evaluate 25 potential mediators of the association and calculate the mediated proportions.

RESULTS

Meta-analysis of inverse variance weighted Mendelian randomization results from FinnGen and UK Biobank showed that genetically predicted 1-SD (4.2 years) higher education was associated with 44% (95% CI: 0.40-0.79) decreased hypertension risk and 1.682 mm Hg lower systolic and 0.898 mm Hg lower diastolic blood pressure, independently of intelligence and cognition. While the causal effects of intelligence and cognition on hypertension were not independent of education; 6 out of 25 cardiometabolic risk factors were identified as mediators of the association between education and hypertension, ranked by mediated proportions, including body mass index (mediated proportion: 30.1%), waist-to-hip ratio (22.8%), body fat percentage (14.1%), major depression (7.0%), high-density lipoprotein cholesterol (4.7%), and triglycerides (3.4%). These results were robust to sensitivity analyses.

CONCLUSIONS

Our findings illustrated the causal, independent impact of education on hypertension and blood pressure and outlined cardiometabolic mediators as priority targets for prevention of hypertension attributable to low education.

The relation between prenatal stress, overweight and obesity in children diagnosed according to BMI and percentage fat tissue

BACKGROUND

One of the environmental factors contributing to abnormal weight changes in children may be maternal exposure to adverse environmental factors during pregnancy, which in previous studies led to inconclusive results showing both overweight or obesity and underweight in children. The aim of the study was to assess the influence of prenatal stress on the BMI status and cut-off points for the percentage of fat content.

METHODS

The cohort study included 254 girls and 276 boys. Information on prenatal stress was collected retrospectively with a questionnaire on objective adverse events completed by a parent/guardian of a 6-12-year-old child. We examined the body weight of children and performed an electrical bioimpedance analysis of their body composition. We assessed the BMI status according to the International Obesity Task Force (IOTF) criterion and on the basis of body fat according to McCarthy criterion.

RESULTS

The results of our study show that the prenatal stress was related to increased risk of overweight (OR 2.14, 95% CI: 1.25-3.65) diagnosed on the basis of body fat cut-off points, but not when the BMI was a diagnostic criterion (OR 1.03, 95% CI: 0.58-1.83).

CONCLUSION

The method of diagnosis based on the fat content appears to be an indicator of the occurrence of abnormalities in body composition due to prenatal stress more sensitive than that based on the BMI.

LEVEL OF EVIDENCE

Level III evidence obtained from well-designed cohort or case-control analytic studies.

Body mass index, body fat percentage, and visceral fat as mediators in the association between health literacy and hypertension among residents living in rural and suburban areas

Background

Hypertension is a major cause of death and disability worldwide. Enhancing health literacy (HL) may help to alleviate the risk of hypertension and its burden. However, evidence on the association between HL and hypertension and potential mechanisms remain to be explored.

Objectives

This study examined the association between HL and hypertension; and explored whether body mass index (BMI), body fat percentage (PBF), and visceral fat (VF) were mediators of this association in people who resided in rural and suburban areas in Vietnam.

Methods

A cross-sectional survey was conducted from 1st July to 31st December 2019, involving 1655 residents and exploring participants' sociodemographic characteristics, HL, health-related behaviors, comorbidities, body composition, and blood pressure (BP). People with systolic BP ≥ 140 mmHg or diastolic BP ≥ 90 mmHg or using antihypertensive medication were classified as having hypertension. Multiple logistic regression and mediation analyses were used to explore associations.

Results

The hypertension prevalence was 41.9% (694/1,655). In adjusted models, a higher HL score was associated with a lower hypertension likelihood (OR = 0.96; 95%CI = 0.95–0.97; p < 0.001). Factors associated with a higher odd of hypertension were overweight/obese (OR = 1.69; 95%CI = 1.24–2.29; p = 0.001), high PBF (OR = 2.35; 95%CI = 1.85–2.99; p < 0.001), and high VF (OR = 2.27; 95%CI = 1.63–3.16; p < 0.001). Notably, PBF significantly mediated the association between HL and hypertension (indirect effect, OR = 0.99; 95%CI = 0.98–0.99; p = 0.009; percent mediated = 8.56%). The mediating roles of BMI and VF were not found.

Conclusion

The prevalence of hypertension was relatively high. People with better HL were less likely to have hypertension. The association between HL and hypertension was partially explained by PBF. Strategic approaches are required to improve people's HL and body fat which further help to manage hypertension in rural and suburban areas.

The Relationship between Body Composition and ECG Ventricular Activity in Young Adults

This study aimed to determine the correlation between body composition (measured as weight, body mass index, and body fat percentage (BFP)) and electrocardiographic ventricular parameters (the QT and TQ intervals and the ratios between the electrical diastole and electrical systole (TQ/QT) and between the cardiac cycle and electrical diastole (RR/TQ), both for uncorrected and corrected intervals) in a sample of 50 healthy subjects (age interval 19-23 years, mean age 21.27 ± 1.41 years, 33 women and 17 men). Subjects' measurements were performed with a bioimpedancemetry body composition analyzer and a portable ECG monitor with six leads. Starting from the correlations obtained between the investigated continuous variables, we performed a standard linear regression analysis between the body composition parameters and the ECG ones. Our results revealed that some of our regression models are statistically significant (p < 0.001). Thus, a specific part of the variability of the dependent variables (ECG ventricular activity parameters for corrected QT intervals) is explained by the independent variable BFP. Therefore, body composition influences ventricular electrical activity in young adults, which implies a differentiated interpretation of the electrocardiogram in these situations.

The Reliability and Validity of Recalled Body Shape and the Responsiveness of Obesity Classification Based on Recalled Body Shape Among the Chinese Rural Population

Background

The reliability and validity of recalled body shape were unknown in China. This study was conducted to examine the reliability and validity of recalled body shape as well as the responsiveness of obesity classification by recalled body shape among the Chinese rural population.

Methods

A total of 166 people from the Henan rural cohort were enrolled. The Spearman's correlation coefficient (SCC), intraclass correlation coefficient (ICC), and Cronbach's α were calculated to assess the reliability and validity of recalled body shape. Additionally, the receiver operator characteristic curve (ROC) was performed to assess the responsiveness.

Results

The SCC between the twice recalled body shape ranged from 0.383 to 0.578, and the ICC ranged from 0.357 to 0.615. Besides, the Cronbach's α of the recalled body shape questionnaire was 0.845. At the age of 20–70, the SCC between recalled body shape and actual body mass index (BMI) and waist circumference (WC) ranged from 0.563 to 0.699 and 0.409 to 0.661, respectively. Furthermore, above the age of 20, the area under the curve (AUC) of classifying general obesity and abdominal obesity by recalled body shape ranged from 0.833 to 0.960 and 0.686 to 0.870, respectively.

Conclusion

The results indicated that recalled body shape had moderate reliability, validity, and discriminative degree for earlier obesity among the Chinese rural population.

Associations between depressive symptoms, anxiety symptoms, their comorbidity and health-related quality of life: a large-scale cross-sectional study

Background

There were few studies exploring the associations between depressive symptoms, anxiety symptoms and health-related quality of life (HRQoL) in the general population, especially in resource limited area. The aims of this study were to assess the associations between depressive symptoms, anxiety symptoms, their comorbidity and HRQoL in rural area.

Methods

A total of 23,496 eligible participants from Henan rural cohort were included. The Patient Health Questionnaire-2 (PHQ-2) and Generalized Anxiety Disorder-2 (GAD-2) were employed to assess depressive and anxiety symptoms, respectively. HRQoL was measured via European Quality of Life Five Dimension Five Level Scale (EQ-5D-5L). Tobit regression and generalized linear model were utilized to explore the associations between depressive symptoms, anxiety symptoms, their comorbidity and HRQoL.

Results

A total of 1320 individuals were identified as depressive symptoms with a prevalence rate of 5.62%, while 1198 participants were classified as anxiety symptoms with a prevalence rate of 5.10%. After multiple adjustment, the regression coefficients (β) and 95% confidence interval (CI) of utility index for depressive and anxiety symptoms were − 0.166 (− 0.182, − 0.149) and − 0.132 (− 0.149, − 0.114), respectively. The β and 95% CI of VAS score for depressive and anxiety symptoms were − 7.65 (− 8.60, − 6.70) and − 5.79 (− 6.78, − 4.80), respectively. Additionally, the comorbidity was strongly associated with low utility index and VAS score. These findings were observed robustly in men and women.

Conclusion

Depressive symptoms, anxiety symptoms and their comorbidity were associated with low HRQoL in rural population, which needed further efforts on preventive and treatment interventions.

Clinical trial registration

The Henan Rural Cohort Study has been registered at Chinese Clinical Trial Register (Registration number: ChiCTR-OOC-15006699). Date of registration: 06 July, 2015.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-021-11969-1.

Physical activity attenuated the association of air pollutants with telomere length in rural Chinese adults

BACKGROUND

Exposure to air pollutants (nitrogen dioxide (NO₂) and particulate matters (PMs)) or physical inactivity is linked to telomere length (TL) shortening. However, there is a lack of research on combined effects of either NO₂ or PMs and physical activity (PA) on TL. This study aimed to explore the joint associations of air pollutants (NO₂ or PMs) and PA with relative TL in rural Chinese adults.

METHODS

This study was conducted among 2704 participants aged 18-79 years in rural China. Concentrations of NO₂ and PMs (PM with an aerodynamics diameter ≤ 1.0 μm (PM₁), ≤2.5 μm (PM_2.5) or ≤10 μm (PM₁₀)) were estimated using random forest models incorporated with satellites data, meteorological data, and land use information. Relative TL of each participant was measured by a quantitative real-time polymerase chain reaction. Linear regression models were applied to examine the independent associations between PA, NO₂ or PMs and relative TL. Interaction plots were used to depict the altered associations between NO₂, PM₁, PM_2.5, or PM₁₀ and relative TL along with increasing PA levels.

RESULTS

Each 1 μg/m³ increment in NO₂, PM₁, PM_2.5, or PM₁₀ was associated with a 0.038 (95% confidence intervals (CI): -0.044, -0.033), 0.036 (95% CI: -0.041, -0.031), 0.052 (95% CI: -0.059, -0.045), or 0.022 (95% CI: -0.025, -0.019) decrease in relative TL among all participants; similar findings were observed among normal glucose tolerance or impaired fasting glucose (IFG) participants as well as type 2 diabetes mellitus (T2DM) patients. PA at certain levels counteracted the association of air pollutants (NO₂, PM₁, PM_2.5, and PM₁₀) with relative TL among IFG participants or T2DM patients.

CONCLUSIONS

Long-term exposure to NO₂ and PMs was associated with relative TL shortening and these effects may be counteracted by PA at certain levels in IFG participants or T2DM patients.

Genetic Risk Score Increased Discriminant Efficiency of Predictive Models for Type 2 Diabetes Mellitus Using Machine Learning: Cohort Study

Background: Previous studies have constructed prediction models for type 2 diabetes mellitus (T2DM), but machine learning was rarely used and few focused on genetic prediction. This study aimed to establish an effective T2DM prediction tool and to further explore the potential of genetic risk scores (GRS) via various classifiers among rural adults.

Methods: In this prospective study, the GRS for a total of 5,712 participants from the Henan Rural Cohort Study was calculated. Cox proportional hazards (CPH) regression was used to analyze the associations between GRS and T2DM. CPH, artificial neural network (ANN), random forest (RF), and gradient boosting machine (GBM) were used to establish prediction models, respectively. The area under the receiver operating characteristic curve (AUC) and net reclassification index (NRI) were used to assess the discrimination ability of the models. The decision curve was plotted to determine the clinical-utility for prediction models.

Results: Compared with the individuals in the lowest quintile of the GRS, the HR (95% CI) was 2.06 (1.40 to 3.03) for those with the highest quintile of GRS (P_trend < 0.05). Based on conventional predictors, the AUCs of the prediction model were 0.815, 0.816, 0.843, and 0.851 via CPH, ANN, RF, and GBM, respectively. Changes with the integration of GRS for CPH, ANN, RF, and GBM were 0.001, 0.002, 0.018, and 0.033, respectively. The reclassifications were significantly improved for all classifiers when adding GRS (NRI: 41.2% for CPH; 41.0% for ANN; 46.4% for ANN; 45.1% for GBM). Decision curve analysis indicated the clinical benefits of model combined GRS.

Conclusion: The prediction model combined with GRS may provide incremental predictions of performance beyond conventional factors for T2DM, which demonstrated the potential clinical use of genetic markers to screen vulnerable populations.

Clinical Trial Registration: The Henan Rural Cohort Study is registered in the Chinese Clinical Trial Register (Registration number: ChiCTR-OOC-15006699). http://www.chictr.org.cn/showproj.aspx?proj=11375.