scholarly journals Serum Uric Acid Might Be Positively Associated With Hypertension in Chinese Adults: An Analysis of the China Health and Nutrition Survey

2022 ◽  
Vol 8 ◽  
Author(s):  
Yingdong Han ◽  
Kaidi Han ◽  
Xinxin Han ◽  
Yue Yin ◽  
Hong Di ◽  
...  
Keyword(s):  
Uric Acid ◽  
Dose Response ◽  
Response Relationship ◽  
Chinese Adults ◽  
Dose Response Relationship ◽  
Nutrition Survey ◽  
Health And Nutrition ◽  
Increased Risk ◽  
Stratified Analysis

Background: Previous studies have clarified the relationship between serum uric acid (SUA) and hypertension; most of previous studies suggest that elevated uric acid levels are associated with an increased risk of hypertension, while in China, there are relatively few studies to explore above association. The objective of this longitudinal study is to investigate the correlation of SUA and hypertension in Chinese adults with a nationwide large-scale sample.Methods: Data from the China Health and Nutrition Survey 2009, 2011, and 2016 were used; a total of 8,469 participants (3,973 men and 4,496 women) were involved. This study was conducted separately by gender. Clinical characteristics of the participants among different uric acid groups are compared. The binary logistic regression analysis was conducted to examine the association between SUA and hypertension. Restricted cubic spline analysis with three knots of the SUA concentration were used to characterize the dose-response relationship. Additionally, we compared the incidence of hypertension in the different baseline uric acid groups during follow-up in 2011 and 2015.Results: After the covariates were fully adjusted, we found that elevated uric acid levels were correlated with increased risk of hypertension in both males (p < 0.01) and females (p < 0.01). With 2-year or 6-year of follow-up, we found participants with higher baseline uric acid levels had a higher incidence of hypertension (p < 0.01). In stratified analysis by obesity, above relationship remained significant in nonobesity population (males: p < 0.05, females: p < 0.01) and became nonsignificant in obesity people. In stratified analysis by age, above positively correlation remained significant in middle-aged men (p < 0.05) and elderly women (p < 0.01). Restricted cubic spline revealed the dose-response relationship between SUA and hypertension; we also found that above relationship was much stronger in females.Conclusion: This study suggests that elevated SUA levels might be positively associated with an increased risk of hypertension in general Chinese adults.

scholarly journals Long-term BMI change trajectories in Chinese adults and its association with the hazard of type 2 diabetes: evidence from a 20-year China Health and Nutrition Survey

2020 ◽  
Vol 8 (1) ◽  
pp. e000879
Author(s):  
Baibing Mi ◽  
Chenlu Wu ◽  
Xiangyu Gao ◽  
Wentao Wu ◽  
Jiaoyang Du ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Latent Class ◽  
Chinese Adults ◽  
Change Trajectories ◽  
Nutrition Survey ◽  
Health And Nutrition ◽  
Increased Risk

IntroductionTo investigate the relationship between long-term change trajectory in body mass index (BMI) and the hazard of type 2 diabetes among Chinese adults.Research design and methodsData were obtained from the China Health and Nutrition Survey (CHNS). Type 2 diabetes was reported by participants themselves in each survey wave. The duration of follow-up was defined as the period from the first visit to the first time self-reported type 2 diabetes, death, or other loss to follow-up from CHNS. The patterns of change trajectories in BMI were derived by latent class trajectory analysis method. The Fine and Gray regression model was used to estimate HRs with corresponding 95% CIs for type 2 diabetes.ResultsFour patterns of the trajectories of change in BMI were identified among Chinese adults, 42.7% of participants had stable BMI change, 40.8% for moderate BMI gain, 8.9% for substantial BMI gain and 7.7% for weight loss. During the follow-up with mean 11.2 years (158 637 person-years contributed by 14 185 participants), 498 people with type 2 diabetes (3.7%) occurred. Risk of type 2 diabetes was increased by 47% among people who gained BMI more substantially and rapidly (HR: 1.47, 95% CI 1.08 to 2.02, p=0.016) and increased by 20% among those in people with the moderate BMI gain (HR: 1.20, 95% CI 0.98 to 1.48, p=0.078), compared with those with stable BMI change.ConclusionsLong-term substantial gain of BMI was significantly associated with an increased risk of type 2 diabetes in the Chinese adults.

U-shaped Association Between Dietary Zinc Intake and New-onset Diabetes: A Nationwide Cohort Study in China

2021 ◽  
Author(s):  
Panpan He ◽  
Huan Li ◽  
Mengyi Liu ◽  
Zhuxian Zhang ◽  
Yuanyuan Zhang ◽  
...  
Keyword(s):  
Chinese Adults ◽  
Dietary Zinc ◽  
Nutrition Survey ◽  
Zinc Intake ◽  
Health And Nutrition ◽  
Onset Diabetes ◽  
Household Food Inventory ◽  
Diagnosed Diabetes ◽  
New Onset

Abstract Aims We aimed to investigate the relationship of dietary zinc intake with new-onset diabetes among Chinese adults. Materials and Methods A total of 16 257 participants who were free of diabetes at baseline from the China Health and Nutrition Survey were included. Dietary intake was measured by 3 consecutive 24-hour dietary recalls combined with a household food inventory. Participants with self-reported physician-diagnosed diabetes, or fasting glucose ≥ 7.0 mmol/L, or glycated hemoglobin ≥ 6.5% during the follow-up were defined as having new-onset diabetes. Results A total of 1097 participants developed new-onset diabetes during a median follow-up duration of 9.0 years. Overall, the association between dietary zinc intake and new-onset diabetes followed a U-shape (P for nonlinearity < 0.001). The risk of new-onset diabetes was significantly lower in participants with zinc intake < 9.1 mg/day (per mg/day: hazard ratio [HR], 0.73; 95% CI, 0.60-0.88), and higher in those with zinc intake ≥ 9.1 mg/day (per mg/day: HR, 1.10; 95% CI, 1.07-1.13). Consistently, when dietary zinc intake was assessed as deciles, compared with those in deciles 2-8 (8.9 -<12.2 mg/day), the risk of new-onset diabetes was higher for decile 1 (<8.9 mg/day: HR, 1.29; 95% CI, 1.04-1.62), and deciles 9 to 10 (≥12.2 mg/day: HR, 1.62; 95% CI, 1.38-1.90). Similar U-shaped relations were found for plant-derived or animal-derived zinc intake with new-onset diabetes (all P for nonlinearity < 0.001). Conclusions There was a U-shaped association between dietary zinc intake and new-onset diabetes in general Chinese adults, with an inflection point at about 9.1 mg/day.

Abstract P190: Antihypertensive Monotherapy And Risk Of Depression Incidence

Hypertension ◽  
2020 ◽  
Vol 76 (Suppl_1) ◽  
Author(s):  
Anwar Alnakhli ◽  
Richard Shaw ◽  
Daniel Smith ◽  
Sandosh Padmanabhan
Keyword(s):  
Dose Response ◽  
Enzyme Inhibitor ◽  
Previous History ◽  
Cox Proportional Hazards ◽  
Recent Theory ◽  
Defined Daily Dose ◽  
Response Relationship ◽  
Dose Response Relationship ◽  
Antihypertensive Medications ◽  
Increased Risk

Background: Recent theory suggests that antihypertensive medications may be useful as repurposed treatments for mood disorders, however, empirical evidence is inconsistent Objective: We aimed to assess the risk of depression incidence as indicated by first-ever prescription of antidepressant in patients newly exposed to antihypertensive monotherapy and whether there is a dose-response relationship. Method: This study enrolled 2406 new users of antihypertensive monotherapy aged between 18 and 80 years with no previous history of antidepressant prescriptions. The exposure period (EP) to antihypertensive medication was fixed at one year starting from the first date of antihypertensive prescription between Jan 2005 and Mar 2012 and extended up to 12 months. Follow-up commence after the EP until March 2013. To test for dose-response relationship the cumulative defined daily dose (cDDD) of antihypertensive during the EP were stratified into tertiles. Cox proportional hazards models were used to estimate hazard ratios (HR) for depression incidence. Results: Among the five major classes of antihypertensive medications, calcium channel blocker (CCB) had the highest risk of developing depression after adjusting for covariates (HR = 1.40 95%CI 1.11,1.78) compared to angiotensin-converting enzyme inhibitor (ACEI). Angiotensin-receptor blocker (ARB) treatment showed higher risk of depression incidence with tertile 2(HR= 1.46, 95%CI 0.88,2.44) and tertile 3 (HR= 1.75, 95%CI 1.03,2.97) compared to tertile 1 of cDDD. Conclusion: Our findings confirmed previous evidence suggesting that CCB is associated with increased risk of depression incidence compared to ACEI. Risk of developing depression is also linked to ARB, though it might be dose dependent.

scholarly journals Cyproterone Acetate and risk of Meningioma

2021 ◽  
Author(s):  
Anders P. Mikkelsen ◽  
Iben K. Greiber ◽  
Nikolai M. Scheller ◽  
Malene Hilden ◽  
Øjvind Lidegaard
Keyword(s):  
Cumulative Dose ◽  
Cyproterone Acetate ◽  
Hazard Ratio ◽  
Adjusted Hazard Ratio ◽  
Response Relationship ◽  
Dose Response Relationship ◽  
National Healthcare ◽  
Background Population ◽  
Increased Risk

AbstractCyproterone acetate (CPA) is a synthetic steroid hormone. We assessed the association between the use of CPA and the risk of developing meningioma.In a historical prospective cohort study, using Danish national healthcare registers we included a cohort of 5,730,654 individuals, among whom 1,982 were exposed to CPA. During follow-up, we identified 8,957 cases of meningioma, of which 16 were exposed to CPA. From 2013 to 2019 the number of new users increased from 18.1 to 62.3 new users per million, while the proportion of new users who were transgender increased from 18.4 to 68.3%. Analyses showed a significantly increased risk of meningioma according to cumulative dose of CPA; 0.1-10 grams of CPA, incidence rate 78.8 (95% CI 15.7-141.9) per 100.000 person years and adjusted hazard ratio 7.0 (3.1-15.6); >10 grams of CPA, incidence 187.5 (71.3-303.7) and adjusted hazard ratio 19.2 (10.3-35.8), as compared to the background population.In conclusion, the cumulative dose of CPA was associated with an increased incidence and hazard ratio of meningioma, showing a dose-response relationship. The number of new CPA users increased more than 3-fold from 2013 to 2019, primarily driven by new transgender users.

scholarly journals Comparisons Between Hypothesis- and Data-Driven Approaches for Multimorbidity Frailty Index: A Machine Learning Approach (Preprint)

2019 ◽  
Author(s):  
Li-Ning Peng ◽  
Fei-Yuan Hsiao ◽  
Wei-Ju Lee ◽  
Shih-Tsung Huang ◽  
Liang-Kung Chen
Keyword(s):  
Machine Learning ◽  
Dose Response ◽  
Frailty Index ◽  
Risk Groups ◽  
Adverse Outcomes ◽  
Response Relationship ◽  
Dose Response Relationship ◽  
Machine Learning Approach ◽  
Unplanned Hospitalizations

BACKGROUND Using big data and the theory of cumulative deficits to develop the multimorbidity frailty index (mFI) has become a widely accepted approach in public health and health care services. However, constructing the mFI using the most critical determinants and stratifying different risk groups with dose-response relationships remain major challenges in clinical practice. OBJECTIVE This study aimed to develop the mFI by using machine learning methods that select variables based on the optimal fitness of the model. In addition, we aimed to further establish 4 entities of risk using a machine learning approach that would achieve the best distinction between groups and demonstrate the dose-response relationship. METHODS In this study, we used Taiwan’s National Health Insurance Research Database to develop a machine learning multimorbidity frailty index (ML-mFI) using the theory of cumulative diseases/deficits of an individual older person. Compared to the conventional mFI, in which the selection of diseases/deficits is based on expert opinion, we adopted the random forest method to select the most influential diseases/deficits that predict adverse outcomes for older people. To ensure that the survival curves showed a dose-response relationship with overlap during the follow-up, we developed the distance index and coverage index, which can be used at any time point to classify the ML-mFI of all subjects into the categories of fit, mild frailty, moderate frailty, and severe frailty. Survival analysis was conducted to evaluate the ability of the ML-mFI to predict adverse outcomes, such as unplanned hospitalizations, intensive care unit (ICU) admissions, and mortality. RESULTS The final ML-mFI model contained 38 diseases/deficits. Compared with conventional mFI, both indices had similar distribution patterns by age and sex; however, among people aged 65 to 69 years, the mean mFI and ML-mFI were 0.037 (SD 0.048) and 0.0070 (SD 0.0254), respectively. The difference may result from discrepancies in the diseases/deficits selected in the mFI and the ML-mFI. A total of 86,133 subjects aged 65 to 100 years were included in this study and were categorized into 4 groups according to the ML-mFI. Both the Kaplan-Meier survival curves and Cox models showed that the ML-mFI significantly predicted all outcomes of interest, including all-cause mortality, unplanned hospitalizations, and all-cause ICU admissions at 1, 5, and 8 years of follow-up (<i>P</i>&lt;.01). In particular, a dose-response relationship was revealed between the 4 ML-mFI groups and adverse outcomes. CONCLUSIONS The ML-mFI consists of 38 diseases/deficits that can successfully stratify risk groups associated with all-cause mortality, unplanned hospitalizations, and all-cause ICU admissions in older people, which indicates that precise, patient-centered medical care can be a reality in an aging society.

Opioids and the Risk of Motor Vehicle Collision: A Systematic Review

2021 ◽  
pp. 875512252110599
Author(s):  
Silvia J. Leon ◽  
Aaron Trachtenberg ◽  
Derek Briscoe ◽  
Maira Ahmed ◽  
Ingrid Hougen ◽  
...  
Keyword(s):  
Systematic Review ◽  
Dose Response ◽  
Motor Vehicle ◽  
Motor Vehicle Collision ◽  
Prescription Opioid ◽  
Response Relationship ◽  
Dose Response Relationship ◽  
Opioid Prescription ◽  
Vehicle Collision ◽  
Increased Risk

Background: Opioid analgesics are among the most commonly prescribed medications, but questions remain regarding their impact on the day-to-day functioning of patients including driving. We set out to perform a systematic review on the risk of motor vehicle collision (MVC) associated with prescription opioid exposure. Method: We searched Medline, PubMed, EMBASE, Scopus, and TRID from January 1990 to August 31, 2021 for primary studies assessing prescribed opioid use and MVCs. Results: We identified 14 observational studies that met inclusion criteria. Among those, 8 studies found an increased risk of MVC among those participants who had a concomitant opioid prescription at the time of the MVC and 3 found no significant increase of culpability of fatal MVC. The 3 studies that evaluated the presence of a dose-response relationship between the dose of opioids taken and the effects on MVC risk reported the existence of a dose-response relationship. Due to the heterogeneity of the different studies, a quantitative meta-analysis to sum evidence was deemed unfeasible. Our review supports increasing evidence on the association between motor vehicle collisions and prescribed opioids. This research would guide policies regarding driving legislation worldwide. Conclusion: Our review indicates that opioid prescriptions are likely associated with an increased risk of MVCs. Further studies are warranted to strengthen this finding, and investigate additional factors such as individual opioid medications, opioid doses and dose adjustments, and opioid tolerance for their effect on MVC risk.

Treated Versus Untreated Mental Health Problems in Adolescents: A Six-year Comparison of Emotional and Behavioral Problem Trajectories

2017 ◽  
Vol 41 (S1) ◽  
pp. s130-s131
Author(s):  
F. Jörg ◽  
D. Raven ◽  
E. Visser ◽  
R. Schoevers ◽  
T. Oldehinkel
Keyword(s):  
Mental Health ◽  
Dose Response ◽  
Real World ◽  
Response Relationship ◽  
Dose Response Relationship ◽  
Problem Behaviour ◽  
The Real ◽  
Clinical Level ◽  
Pre Treatment

IntroductionMultidisciplinary guidelines in adolescent mental health care are based on RCTs, while treatment efficacy can be different from effectiveness seen in ‘the real world’. Studies in the real world conducted so far suggest that treatment has a negligible effect on follow-up symptomatology. However, these studies did not incorporate the pre-treatment trajectory of symptoms nor investigated a dose-response relationship.ObjectivesTo test whether future treatment users and non-users differed in emotional and behavioural problem scores, whether specialist mental health treatment (SMHT) was effective in reducing problem levels while controlling for pre-treatment trajectory, and to seek evidence of a dose-response relationship.MethodsSix-year follow up data were used from the Tracking Adolescents’ Individual Lives Survey (TRAILS). We identified adolescents with a clinical level of problem behaviour on the Child Behaviour Checklist or Youth Self Report and first SMHT between the ages 13 and 16. Adolescents with a clinical level of problem behaviour but without SMHT use served as control group. A psychiatric case register provided data on number of treatment contacts. Using regression analysis, we predicted the effect of treatment on post-treatment problem scores.ResultsTreated adolescents more often had a (severe) diagnosis than untreated adolescents. Pre-treatment trajectories barely differed between treated and untreated adolescents. Treatment predicted an increase in follow-up problem scores, regardless of the number of sessions.ConclusionThe quasi-experimental design calls for modest conclusions. We might however need to take a closer look at real-world service delivery, and invest in developing treatments that can achieve sustainable benefits.Disclosure of interestThe authors have not supplied their declaration of competing interest.

scholarly journals Occupational Physical Activity and New-Onset Hypertension: A Nationwide Cohort Study in China

Hypertension ◽  
2021 ◽  
Author(s):  
Qinqin Li ◽  
Rui Li ◽  
Shaojie Zhang ◽  
Yuanyuan Zhang ◽  
Panpan He ◽  
...  
Keyword(s):  
Physical Activity ◽  
Blood Pressure ◽  
Occupational Physical Activity ◽  
Nutrition Survey ◽  
Metabolic Equivalent ◽  
Health And Nutrition ◽  
Increased Risk ◽  
Males And Females ◽  
New Onset

The association between occupational physical activity (OPA) and the risk of hypertension remains uncertain. We aimed to examine the prospective relations of OPA and new-onset hypertension among Chinese males and females. A total of 9350 adults who were free of hypertension at baseline were enrolled from the CHNS study (China Health and Nutrition Survey). Data on OPA were obtained by using self-reported questionnaires and calculated as metabolic equivalent task (MET)–hours per week. MET–hours per week may account for both intensity and time spent on activities. The study outcome was new-onset hypertension, defined as systolic blood pressure ≥140 mm Hg or diastolic blood pressure ≥90 mm Hg or diagnosed by physician or under antihypertensive treatment during the follow-up. During a median of 6.1 years (82 410 person-years) of follow-up, a total of 2949 participants developed hypertension. Overall, there was a L-shaped association between the OPA and new-onset hypertension in males and a U-shaped association in females (all P values for nonlinearity <0.001). Accordingly, when OPA was categorized as four groups (<80, 80–<160, 160–<240, and ≥240 metabolic MET–hours per week), in males, the risk of new-onset hypertension was significantly increased only among participants with OPA <80 MET–hours per week; however, in females, the lowest risk of new-onset hypertension was found among those with OPA 80 to 240 MET–hours per week. In summary, moderate OPA, in terms of both duration and intensity, is associated with a lower risk of new-onset hypertension among both males and females, whereas heavy OPA was related to increased risk of new-onset hypertension in females.

scholarly journals Comparisons Between Hypothesis- and Data-Driven Approaches for Multimorbidity Frailty Index: A Machine Learning Approach

10.2196/16213 ◽  
2020 ◽  
Vol 22 (6) ◽  
pp. e16213
Author(s):  
Li-Ning Peng ◽  
Fei-Yuan Hsiao ◽  
Wei-Ju Lee ◽  
Shih-Tsung Huang ◽  
Liang-Kung Chen
Keyword(s):  
Machine Learning ◽  
Dose Response ◽  
Frailty Index ◽  
Risk Groups ◽  
Adverse Outcomes ◽  
Response Relationship ◽  
Dose Response Relationship ◽  
Machine Learning Approach ◽  
Unplanned Hospitalizations

Background Using big data and the theory of cumulative deficits to develop the multimorbidity frailty index (mFI) has become a widely accepted approach in public health and health care services. However, constructing the mFI using the most critical determinants and stratifying different risk groups with dose-response relationships remain major challenges in clinical practice. Objective This study aimed to develop the mFI by using machine learning methods that select variables based on the optimal fitness of the model. In addition, we aimed to further establish 4 entities of risk using a machine learning approach that would achieve the best distinction between groups and demonstrate the dose-response relationship. Methods In this study, we used Taiwan’s National Health Insurance Research Database to develop a machine learning multimorbidity frailty index (ML-mFI) using the theory of cumulative diseases/deficits of an individual older person. Compared to the conventional mFI, in which the selection of diseases/deficits is based on expert opinion, we adopted the random forest method to select the most influential diseases/deficits that predict adverse outcomes for older people. To ensure that the survival curves showed a dose-response relationship with overlap during the follow-up, we developed the distance index and coverage index, which can be used at any time point to classify the ML-mFI of all subjects into the categories of fit, mild frailty, moderate frailty, and severe frailty. Survival analysis was conducted to evaluate the ability of the ML-mFI to predict adverse outcomes, such as unplanned hospitalizations, intensive care unit (ICU) admissions, and mortality. Results The final ML-mFI model contained 38 diseases/deficits. Compared with conventional mFI, both indices had similar distribution patterns by age and sex; however, among people aged 65 to 69 years, the mean mFI and ML-mFI were 0.037 (SD 0.048) and 0.0070 (SD 0.0254), respectively. The difference may result from discrepancies in the diseases/deficits selected in the mFI and the ML-mFI. A total of 86,133 subjects aged 65 to 100 years were included in this study and were categorized into 4 groups according to the ML-mFI. Both the Kaplan-Meier survival curves and Cox models showed that the ML-mFI significantly predicted all outcomes of interest, including all-cause mortality, unplanned hospitalizations, and all-cause ICU admissions at 1, 5, and 8 years of follow-up (P<.01). In particular, a dose-response relationship was revealed between the 4 ML-mFI groups and adverse outcomes. Conclusions The ML-mFI consists of 38 diseases/deficits that can successfully stratify risk groups associated with all-cause mortality, unplanned hospitalizations, and all-cause ICU admissions in older people, which indicates that precise, patient-centered medical care can be a reality in an aging society.

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