Effect of alcohol consumption on breast cancer: probabilistic bias analysis for adjustment of exposure misclassification bias and confounders.

PURPOSE: This study was conducted to evaluate the effect of alcohol consumption on breast cancer, adjusting for alcohol consumption misclassification bias and confounders. METHODS: This was a case-control study of 932 women with breast cancer and 1000 healthy control. Using probabilistic bias analysis method, the association between alcohol consumption and breast cancer was adjusted for the misclassification bias of alcohol consumption as well as a minimally sufficient set of adjustment of confounders derived from a causal directed acyclic graph. Population attributable fraction was estimated using the Miettinen's Formula. RESULTS: Based on the conventional logistic regression model, the odds ratio estimate between alcohol consumption and breast cancer was 1.05 (95% CI: 0.57, 1.91). However, the adjusted estimates of odds ratio based on the probabilistic bias analysis ranged from 1.82 to 2.29 for non-differential and from 1.93 to 5.67 for differential misclassification. Population attributable fraction ranged from 1.51 to 2.57% using non-differential bias analysis and 1.54-3.56% based on differential bias analysis. CONCLUSION: A marked measurement error was in self-reported alcohol consumption so after correcting misclassification bias, no evidence against independence between alcohol consumption and breast cancer changed to a substantial positive association.

The effect of smoking on latent hazard classes of metabolic syndrome using latent class causal analysis method in the Iranian population.

BACKGROUND: The prevalence of metabolic syndrome is increasing worldwide. Clinical guidelines consider metabolic syndrome as an all or none medical condition. One proposed method for classifying metabolic syndrome is latent class analysis (LCA). One approach to causal inference in LCA is using propensity score (PS) methods. The aim of this study was to investigate the causal effect of smoking on latent hazard classes of metabolic syndrome using the method of latent class causal analysis. METHODS: In this study, we used data from the Tehran Lipid and Glucose Cohort Study (TLGS). 4857 participants aged over 20 years with complete information on exposure (smoking) and confounders in the third phase (2005-2008) were included. Metabolic syndrome was evaluated as outcome and latent variable in LCA in the data of the fifth phase (2014-2015). The step-by-step procedure for conducting causal inference in LCA included: (1) PS estimation and evaluation of overlap, (2) calculation of inverse probability-of-treatment weighting (IPTW), (3) PS matching, (4) evaluating balance of confounding variables between exposure groups, and (5) conducting LCA using the weighted or matched data set. RESULTS: Based on the results of IPTW which compared the low, medium and high risk classes of metabolic syndrome (compared to a class without metabolic syndrome), no association was found between smoking and the metabolic syndrome latent classes. PS matching which compared low and moderate risk classes compared to class without metabolic syndrome, showed that smoking increases the probability of being in the low-risk class of metabolic syndrome (OR: 2.19; 95% CI: 1.32, 3.63). In the unadjusted analysis, smoking increased the chances of being in the low-risk (OR: 1.45; 95% CI: 1.01, 2.08) and moderate-risk (OR: 1.68; 95% CI: 1.18, 2.40) classes of metabolic syndrome compared to the class without metabolic syndrome. CONCLUSIONS: Based on the results, the causal effect of smoking on latent hazard classes of metabolic syndrome can be different based on the type of PS method. In adjusted analysis, no relationship was observed between smoking and moderate-risk and high-risk classes of metabolic syndrome.

The causal effect and impact of reproductive factors on breast cancer using super learner and targeted maximum likelihood estimation: a case-control study in Fars Province, Iran.

OBJECTIVES: The relationship between reproductive factors and breast cancer (BC) risk has been investigated in previous studies. Considering the discrepancies in the results, the aim of this study was to estimate the causal effect of reproductive factors on BC risk in a case-control study using the double robust approach of targeted maximum likelihood estimation. METHODS: This is a causal reanalysis of a case-control study done between 2005 and 2008 in Shiraz, Iran, in which 787 confirmed BC cases and 928 controls were enrolled. Targeted maximum likelihood estimation along with super Learner were used to analyze the data, and risk ratio (RR), risk difference (RD), andpopulation attributable fraction (PAF) were reported. RESULTS: Our findings did not support parity and age at the first pregnancy as risk factors for BC. The risk of BC was higher among postmenopausal women (RR = 3.3, 95% confidence interval (CI) = (2.3, 4.6)), women with the age at first marriage ≥20 years (RR = 1.6, 95% CI = (1.3, 2.1)), and the history of oral contraceptive (OC) use (RR = 1.6, 95% CI = (1.3, 2.1)) or breastfeeding duration ≤60 months (RR = 1.8, 95% CI = (1.3, 2.5)). The PAF for menopause status, breastfeeding duration, and OC use were 40.3% (95% CI = 39.5, 40.6), 27.3% (95% CI = 23.1, 30.8) and 24.4% (95% CI = 10.5, 35.5), respectively. CONCLUSIONS: Postmenopausal women, and women with a higher age at first marriage, shorter duration of breastfeeding, and history of OC use are at the higher risk of BC.

Effects of Hypothetical Interventions on Ischemic Stroke Using Parametric G-Formula.

Background and Purpose- Standard analytic approaches (eg, logistic regression) fail to adequately control for time-dependent confounding and, therefore, may yield biased estimates of the total effect of the exposure on the outcome. In the present study, we estimate the effect of body mass index, intentional physical activity, HDL (high-density lipoprotein) cholesterol, LDL (low-density lipoprotein) cholesterol, hypertension, and cigarette smoking on the 11-year risk of ischemic stroke by sex using the parametric g-formula to control time-dependent confounders. Methods- Using data from the MESA (Multi-Ethnic Study of Atherosclerosis), we followed 6809 men and women aged 45 to 84 years. We estimated the risk of stroke under 6 hypothetical interventions: maintaining body mass index <25 kg/m2, maintaining normotension (systolic blood pressure <140 and diastolic <90 mm Hg), quitting smoking, maintaining HDL >1.55 mmol/L, maintaining LDL <3.11 mmol/L, and exercising at least 210 minutes per week. The effects of joint hypothetical interventions were also simulated. Results- In men, the 11-year risk of ischemic stroke would be reduced by 85% (95% CI, 66-96) for all 6 hypothetical interventions. In women, this same effect was estimated as 55% (95% CI, 6-82). Conclusions- The hypothetical interventions explored in our study resulted in risk reduction in both men and women.

Accounting for Time-Varying Confounding in the Relationship Between Obesity and Coronary Heart Disease: Analysis With G-Estimation: The ARIC Study.

In longitudinal studies, standard analysis may yield biased estimates of exposure effect in the presence of time-varying confounders that are also intermediate variables. We aimed to quantify the relationship between obesity and coronary heart disease (CHD) by appropriately adjusting for time-varying confounders. This study was performed in a subset of participants from the Atherosclerosis Risk in Communities (ARIC) Study (1987-2010), a US study designed to investigate risk factors for atherosclerosis. General obesity was defined as body mass index (weight (kg)/height (m)2) ≥30, and abdominal obesity (AOB) was defined according to either waist circumference (≥102 cm in men and ≥88 cm in women) or waist:hip ratio (≥0.9 in men and ≥0.85 in women). The association of obesity with CHD was estimated by G-estimation and compared with results from accelerated failure-time models using 3 specifications. The first model, which adjusted for baseline covariates, excluding metabolic mediators of obesity, showed increased risk of CHD for all obesity measures. Further adjustment for metabolic mediators in the second model and time-varying variables in the third model produced negligible changes in the hazard ratios. The hazard ratios estimated by G-estimation were 1.15 (95% confidence interval (CI): 0.83, 1.47) for general obesity, 1.65 (95% CI: 1.35, 1.92) for AOB based on waist circumference, and 1.38 (95% CI: 1.13, 1.99) for AOB based on waist:hip ratio, suggesting that AOB increased the risk of CHD. The G-estimated hazard ratios for both measures were further from the null than those derived from standard models.

The association between serum 25OHD levels and hypothyroid Hashimoto's thyroiditis.

BACKGROUND: Vitamin D is shown to be a potent immunomodulator. Considering the potential role of low serum vitamin D levels in autoimmune disorder, we evaluated the association between Hashimoto's thyroiditis (HT) (with subclinical or overt hypothyroidism) and serum 25-hydroxyvitamin D (25OHD) levels in an Iranian population. METHODS: A total number of 86 individuals were enrolled. The case group included 41 patients with hypothyroid HT (overt or subclinical). The control group comprised 45 healthy euthyroid persons. Serum 25OHD levels were measured in all subjects. THE CASE: control ratio of geometric means of 25OHD levels was 0.66 (95 % CI: 0.49-0.90; P = 0.008). There was a significant inverse association between serum 25OHD levels and HT (OR: 0.81 for 5 ng/ml increase in 25OHD level, 95 % CI: 0.68-0.96; P = 0.018). This association remained significant after adjustment for potential confounding factors including age, sex and BMI. CONCLUSIONS: Our study suggested that higher serum 25OHD levels was associated with decreased risk of HT so that each 5 ng/ml increase in the serum 25OHD levels results in 19 % decrease in odds of HT.

Protective effect of intensive glucose lowering therapy on all-cause mortality, adjusted for treatment switching using G-estimation method, the ACCORD trial.

Previous analysis of the action to control cardiovascular risk in diabetes showed an increased risk of mortality among patients receiving intensive glucose lowering therapy using conventional regression method with intention to treat approach. This method is biased when time-varying confounder is affected by the previous treatment. We used 15 follow-up visits of ACCORD trial to compare the effect of time-varying intensive vs. standard treatment of glucose lowering drugs on cardiovascular and mortality outcomes in diabetic patients. The treatment effect was estimated using G-estimation and compared with accelerated failure time model using two modeling strategies. The first model adjusted for baseline confounders and the second adjusted for both baseline and time-varying confounders. While the hazard ratio of all-cause mortality for intensive compared to standard therapy in AFT model adjusted for baseline confounders was 1.17 (95% CI 1.01-1.36), the result of time-dependent AFT model  was compatible with both protective and risk effects. However, the hazard ratio estimated by G-estimation was 0.64 (95% CI 0.39-0.92). The results of this study revealed a protective effect of intensive therapy on all-cause mortality compared with standard therapy in ACCORD trial.

Effect of physical activity on functional performance and knee pain in patients with osteoarthritis : analysis with marginal structural models.

BACKGROUND: A previous analysis of the Osteoarthritis Initiative study reported a dose-response relationship between physical activity and improved physical function in adults with knee osteoarthritis, using conventional statistical methods. These methods are subject to bias when confounders are affected by prior exposure. METHODS: We used baseline and 1-, 2-, and 3-year follow-up data from the Osteoarthritis Initiative study of 2545 US adults with knee osteoarthritis recruited between 2004 and 2006 from 4 clinical sites. Physical activity was measured using the Physical Activity Scale for the Elderly, and outcomes were functional performance measured by the timed 20-meter walk test and self-reported knee pain measured by the Western Ontario and McMaster Universities Osteoarthritis Index. We estimated the effect of physical activity on each outcome using inverse probability-weighted (IPW) estimators of marginal structural models. For each outcome, we fitted 2 separate IPW models adjusting for concurrent or lagged confounders. RESULTS: The mean differences in walking speed for the second, third, and fourth quartiles of physical activity relative to the first were 0.48 (95% confidence interval = -0.12 to 1.08), 0.45 (-0.23 to 1.13), and 0.46 (-0.29 to 1.22) meters/min based on the IPW model adjusting for concurrent confounders. When adjusting for lagged confounders, the results were 1.35 (0.64 to 2.07), 1.33 (0.54 to 2.14), and 1.26 (0.40 to 2.12). Both IPW models indicated that physical activity did not affect knee pain. CONCLUSIONS: Physical activity has no effect on knee pain and may have either a very small effect or no effect on functional performance in adults with knee osteoarthritis.

Association of +45(T/G) and +276(G/T) polymorphisms in the adiponectin gene with coronary artery disease in a population of Iranian patients with type 2 diabetes.

The relation of Two single nucleotide polymorphisms (SNPs) at the adiponectin locus (+45T/G and +276G/T) with coronary artery disease (CAD) is controversial. The aim of the present study was to evaluate the genetic influence of the adiponectin gene polymorphisms in the development of CAD among patients with Type 2 diabetes (T2D). The adiponectin genotypes were detected by polymerase chain reaction and restriction analysis (PCR-RFLP) in our patients. Two adiponectin gene (ADIPOQ) SNPs (i.e. SNPs +45T>G and +276G>T) were genotyped in 114 Type 2 diabetic subjects with CAD, and 127 Type 2 diabetic patients without CAD. Demographic and anthropometric data along with plasma biochemistry including lipids, glycemic indices, and adiponectin were collected. There was a significant difference in the distribution of genotypes of +45T/G and +276G/T between CAD and non-CAD individuals (P < 0.05). Based on our results SNP+276G>T is associated with decreased risk of CAD after adjustment for potential confounding factors [adjusted OR = 0.39 (95%CI: 0.22-0.68); P = 0.001]. Similar findings were not observed for the +45T>G SNP. Two haplotypes 45T-276T and 45G-276T were associated with a decreased risk of CAD [adjusted OR = 0.47 (95% CI: 0.32-0.94); P = 0.03 and adjusted OR = 0.33 (95% CI: 0.13-0.83); P = 0.02 respectively]. No significant difference was observed between HOMA-IR, BMI, waist circumference, history of hypertension, HbA1C, and lipid concentrations regarding the two SNPs. In conclusion, these findings suggest that T allele of +276G>T SNP is significantly associated with decreased risk of CAD in T2D Patients. Also Haplotype analysis showed that two haplotypes 45T-276T and 45G-276T were associated with a decreased risk of CAD.

The Effects of Smoking on Metabolic Syndrome and Its Components Using Causal Methods in the Iranian Population.

BACKGROUND: The aim of this study was to estimate the effect of smoking on metabolic syndrome (MS) and its components applying inverse probability-of-treatment weighting (IPTW) and propensity score (PS) matching. METHODS: Using data from Tehran Lipid and Glucose Study, 4857 participants aged over 20 years with information on smoking and confounders in the third phase (2005-2008) were included, and the MS was assessed in the fifth phase (2011-2014). IPTW and PS matching were used to adjust for confounders. RESULTS: Based on average treatment effect (ATE) estimates, smoking decreased the risk of hypertension (RR: 0.62; 95% CI: 0.43, 0.88), but increased the risk of low HDL cholesterol (1.20; 0.98, 1.48). Similarly, the average treatment effect in the treated (ATT) estimates using IPTW and PS matching suggested that smoking decreased the risk of hypertension (0.63; 0.52, 0.76, and 0.68; 0.54, 0.85), and increased the risk of low HDL cholesterol (1.24; 1.07, 1.43, and 1.28; 1.06, 1.54), respectively. CONCLUSIONS: Smoking seems to increase the risk of low HDL cholesterol but decreases the risk of hypertension.

Risk factors of developing critical conditions in Iranian patients with COVID-19.

COVID-19 due to novel Coronavirus was first reported in Wuhan, China. Nowadays, the Islamic Republic of Iran stands among countries with high COVID-19 prevalence and high burden of disease. Since the medical resources are limited, we aimed to identify the risk factors for patients developing critical conditions. This can help to improve resource management and treatment outcomes. In this retrospective study, we included 12,677 patients who were from 26 hospitals, supervised by Tehran University of Medical Sciences with signs and symptoms of COVID-19, until April 12. University integrated IT system was adopted to collect the data. We performed Logistic regression to evaluate the association between death in COVID-19 positive patients and other variables. Cough, respiratory distress and fever were the most common symptoms in our patients, respectively. Cancer, chronic lung diseases and chronic neurologic diseases were the strongest risk factors for death in COVID-19 patients.

Evaluation of biochemical markers of kidney function in patients with subclinical hypothyroidism in comparison with euthyroid people.

BACKGROUND: Subclinical hypothyroidism (SCH) as a compensated or preclinical type of primary and overt hypothyroidism (OHT) can affect approximately 4-10% of the general population. Treating SCH can slowdown the progression to OHT, the formation of cardiovascular diseases, neuropsychiatric symptoms, and other miscellaneous problems. MATERIALS AND METHODS: The present study is a case-control study that was conducted on 239 adults who were referred to 501 Imam Reza Hospital from March 2019 up to September 2019. Of the 239 patients and their families admitted to the hospital, 121 (50.6%) were euthyroid (as control group) and the remaining participants (118, 49.4%) were SCH (as case group). The serum levels of thyroid stimulating hormone (TSH), urea, uric acid, creatinine, T3, and T4 were asked to be determined at a single laboratory. Biochemical markers of kidney function and the level of thyroid hormones were compared between the two groups of euthyroid and SCH. RESULTS: TSH was significantly higher in SCH (7.25 (4.4-18.15)) compared to euthyroid (1.4 (0.2-3.7)) patients (P < 0.001). Among biochemical markers, creatinine (P < 0.001) and uric acid (P = 0.006) had higher serum levels in the case group. There was no remarkable difference in the thyroxine hormone levels and urea between the euthyroid and SCH patients (P > 0.05). Within the SCH group, there was a significant positive correlation between TSH and the level of creatinine (P = 0.001, r = 0.302). CONCLUSION: Regular monitoring of the major function of the kidneys in patients with hypothyroidism and SCH can help early diagnosis of kidney dysfunction, thus increasing the chance of restoring normal kidney function.

Effect of Smoking on Breast Cancer by Adjusting for Smoking Misclassification Bias and Confounders Using a Probabilistic Bias Analysis Method.

PURPOSE: The aim of this study was to determine the association between smoking and breast cancer after adjusting for smoking misclassification bias and confounders. METHODS: In this case-control study, 1000 women with breast cancer and 1000 healthy controls were selected. Using a probabilistic bias analysis method, the association between smoking and breast cancer was adjusted for the bias resulting from misclassification of smoking secondary to self-reporting as well as a minimally sufficient adjustment set of confounders derived from a causal directed acyclic graph (cDAG). Population attributable fraction (PAF) for smoking was calculated using Miettinen's formula. RESULTS: While the odds ratio (OR) from the conventional logistic regression model between smoking and breast cancer was 0.64 (95% CI: 0.36-1.13), the adjusted ORs from the probabilistic bias analysis were in the ranges of 2.63-2.69 and 1.73-2.83 for non-differential and differential misclassification, respectively. PAF ranges obtained were 1.36-1.72% and 0.62-2.01% using the non-differential bias analysis and differential bias analysis, respectively. CONCLUSION: After misclassification correction for smoking, the non-significant negative-adjusted association between smoking and breast cancer changed to a significant positive-adjusted association.

The effect of alcohol on osteoporosis: A systematic review and meta-analysis.

BACKGROUND: Osteoporosis is a multifactorial disease hallmarked by the interaction of genetic, nutritional and environmental factors. We aimed to assess the effect of alcohol consumption on the osteoporosis by undertaking a systematic review and meta-analysis. METHODS: We searched electronic databases including MEDLINE, Scopus, and Web of Science until June 2018. We identified all pertinent observational studies that examined the risk of OSTEOPOROSIS with alcohol use including cohort, case-control and cross-sectional studies. Relative risks (RR) for cohort studies and odds ratios (ORs) for case-control studies were pooled using the random effects model. Risk of bias was assessed using the Newcastle-Ottawa scale. RESULTS: From a pool of 3479 studies identified six met the study inclusion criteria (three case control, two cohorts and one cross-sectional study). Compared with abstainers of alcohol, persons consuming 0.5-1 drinks per day had 1.38 times the risk of developing osteoporosis (adjusted RR = 1.38, 95% CI: 0.90-2.12), persons consuming 1-2 drinks per day had 1.34 times the risk of developing OSTEOPOROSIS (adjusted RR = 1.34, 95% CI: 1.11-1.62), and persons consuming two drinks or more per day had 1.63 times the risk of developing osteoporosis (adjusted RR = 1.63, 95% CI: 1.01-2.65). We found a positive association between alcohol consumption and osteoporosis in the case-control studies (adjusted OR = 2.95, 95% CI: 1.78-4.90). CONCLUSION: Our study demonstrates a positive relationship between alcohol consumption and osteoporosis.

Effects of Azelnidipine-Carboxymethylcellulose Gel on Healing of Full-Thickness Skin Wounds in Streptozotocin Induced Diabetic Rats.

OBJECTIVE: To evaluate the effects of azelnidipine-carboxyl methyl cellulose (AZL-CMC) gel and carboxyl methyl cellulose 2% gel (CMC) on the healing of full-thickness skin wounds of diabetic rats. METHODS: Fifteen Sprague Dawley male rats were studied. The rats were divided into three groups: AZL-CMC gel-treated, CMC 2% gel-treated, and control group. Wounds were assessed by wound area measurement every 3 days and histopathology samples were collected at 4, 7 and 12 days post wounding to evaluate the healing process using stereological study. Mann-Whitney U-test repeated measurement and non-parametric one-way analysis of variance (ANOVA) were used to analyze the data using SPSS, version 18. RESULTS: Numerical density of the fibroblasts of the AZL-CMC gel treated group was 59.17±2.69 (×104/mm3) and higher than the control 22.64±1.34 (×104/mm3) and CMC 2%-treated groups 40.80±5.27 (×104/mm3), respectively, P<0.001. The volume density of the collagen bundles and LV of the vessels were 83.1±4.46 and 42.16±5.78, respectively, in the AZL-CMC treated group, and higher compared to the control (53.96±5.07, 9.9±2.49) and the CMC 2%-treated (65.88±2.13, 18.1±2.20) groups (P <0.001). CONCLUSION: The healing of AZL-CMC gel-treated wound was better than the control wounds, grossly. Wound healing processes and wound closure in the intervention group began sooner and was completed more quickly. The quantitative and qualitative parameters showed the significant wound healing effect of the AZL-CMC gel-treated group.

Geographical Patterning of Physical Activity Prevalence in Iran: Spatial Analysis of 4 Pooled National Health Surveys Among 119,560 Adults.

BACKGROUND: To investigate the geographical distribution of physical activity (PA) prevalence among adults aged 15-64 years old across Iran provinces using geographic maps. METHODS: Data from 4 consecutive national surveys conducted between 2007 and 2010 were pooled to determine the geographical distribution. Prevalence of low PA with 95% confidence interval was estimated by sociodemographic subpopulations over provinces using complex survey design. RESULTS: In total, 119,560 participants (49.9% females) were included in the analyses. The mean (SD) age of participants was 39.5 (14.3) years. The prevalence of the low PA in the pooled 2007-2010 was 35.8% (95% confidence interval, 34.1-37.6). The 3 provinces with the highest prevalence of low PA were Sistan and Baluchestan, Yazd, and Hormozgan. The results of hot spot analysis showed that the Kerman province was a hot spot, and Ilam, Kermanshah, Hamedan, and Markazi were cold spots for low PA. Ilam, Kohgiluyeh and Boyer-Ahmad, and Mazandaran had the highest total PA volume (metabolic equivalent minutes per week). Hot spot analysis showed that Ilam and Khuzestan provinces were hot spots for the total PA volume. CONCLUSIONS: The regions with low and high PA are predominately situated in the near center/southeast and west, respectively.

Effects of food items and related nutrients on metabolic syndrome using Bayesian multilevel modelling using the Tehran Lipid and Glucose Study (TLGS): a cohort study.

OBJECTIVES: Diet and nutrition might play an important role in the aetiology of metabolic syndrome (MetS). Most studies that examine the effects of food intake on MetS have used conventional statistical analyses which usually investigate only a limited number of food items and are subject to sparse data bias. This study was undertaken with the goal of investigating the concurrent effect of numerous food items and related nutrients on the incidence of MetS using Bayesian multilevel modelling which can control for sparse data bias. DESIGN: Prospective cohort study. SETTING: This prospective study was a subcohort of the Tehran Lipid and Glucose Study. We analysed dietary intake as well as pertinent covariates for cohort members in the fourth (2008-2011) and fifth (2011-2014) follow-up examinations. We fitted Bayesian multilevel model and compared the results with two logistic regression models: (1) full model which included all variables and (2) reduced model through backward selection of dietary variables. PARTICIPANTS: 3616 healthy Iranian adults, aged ≥20 years. PRIMARY AND SECONDARY OUTCOME MEASURES: Incident cases of MetS. RESULTS: Bayesian multilevel approach produced results that were more precise and biologically plausible compared with conventional logistic regression models. The OR and 95% confidence limits for the effects of the four foods comparing the Bayesian multilevel with the full conventional model were as follows: (1) noodle soup (1.20 (0.67 to 2.14) vs 1.91 (0.65 to 5.64)), (2) beans (0.96 (0.5 to 1.85) vs 0.55 (0.03 to 11.41)), (3) turnip (1.23 (0.68 to 2.23) vs 2.48 (0.82 to 7.52)) and (4) eggplant (1.01 (0.51 to 2.00) vs 1 09 396 (0.152×10-6 to 768×1012)). For most food items, the Bayesian multilevel analysis gave narrower confidence limits than both logistic regression models, and hence provided the highest precision. CONCLUSIONS: This study demonstrates that conventional regression methods do not perform well and might even be biased when assessing highly correlated exposures such as food items in dietary epidemiological studies. Despite the complexity of the Bayesian multilevel models and their inherent assumptions, this approach performs superior to conventional statistical models in studies that examine multiple nutritional exposures that are highly correlated.

Direct and indirect effects of central and general adiposity on cardiovascular diseases: The Tehran Lipid and Glucose Study.

Aim The mechanisms linking body mass index to cardiovascular disease are still not clearly defined. The purpose of this study was to find out how much of the effect of central and general adiposity on cardiovascular disease is mediated through blood pressure, cholesterol, and glucose, and how much is independent of these factors. Methods and results The study population included participants, aged ≥30 years, free of cardiovascular disease at baseline with median follow-up of 13.9 years. The total effects were broken down into natural direct and indirect effects using the inverse odds weighting method in the context of survival models. Systolic blood pressure, total serum cholesterol, and fasting plasma glucose as the primary measure of blood glucose were used as mediators. Blood pressure and cholesterol with indirect hazard ratios of 1.09 (95% confidence interval: 1.006-1.18) and 1.35 (95% confidence interval: 1.12-1.62) were the most important mediators for overweight-cardiovascular disease and obesity-cardiovascular disease relationships, respectively. The proportion mediated of overweight was 22% (6-47%) for blood pressure, 18% (5-37%) for blood glucose, and 20% (7-43%) for cholesterol. The same measure for obesity was 65% (35-91%) for cholesterol. For central adiposity, blood pressure, glucose, and cholesterol were the most important mediators with proportion mediated of 36% (17-72%), 23% (9-48%), and 21% (8-45%), respectively. Conclusions The findings of this study show that proper control of cardiometabolic risk factors of blood pressure, blood glucose, and dyslipidemia in an adult population can be effective to significantly reduce the effects of general and abdominal adiposity on cardiovascular diseases.

Causal Effects of Intensive Lifestyle and Metformin Interventions on Cardiovascular Disease Risk Factors in Pre-Diabetic People: An Application of G-Estimation.

BACKGROUND: In the presence of non-adherence, intention-to-treat analysis preserves randomization, but does not lead to a valid comparison of outcome between the assigned groups. Using a reanalysis of Diabetes Prevention Program, this study aimed to estimate the causal effect of treatment with intensive lifestyle intervention or metformin vs. placebo on blood pressure and lipid profile using G-estimation after accounting for non-adherence. METHODS: The Diabetes Prevention Program randomized 3,052 pre-diabetic individuals to metformin (N = 1015), placebo (N = 1014), or an intensive lifestyle intervention (N = 1023). G-estimation was used to estimate the causal effect of intensive lifestyle intervention or metformin vs. placebo on blood pressure and lipid profile in 2,973 patients who had adherence data. For comparison, we also performed the standard intention-to-treat analysis. RESULTS: The G-estimation results showed that intensive lifestyle substantially improves systolic and diastolic blood pressure and lipid profile. The G-estimates of the effects of metformin vs. placebo as well as intensive lifestyle intervention vs. metformin on blood pressure and lipid profile were also stronger than the intention-to-treat effect estimates. CONCLUSION: G-estimation suggests that intensive lifestyle modification improves known risk factors for cardiovascular disease, including systolic blood pressure, diastolic blood pressure, triglyceride, and HDL levels more than what standard ITT analysis suggests. Adherence to the assigned treatment should be measured in all randomized trials, and G-estimation should be the standard analysis of randomized trials with substantial non-adherence.

Development and Validation of a Skinfold Model for Estimation of Body Density for a Safe Weight Reduction in Young Iranian Wrestlers.

BACKGROUND: Adverse effects of excessive body mass reduction among wrestlers dictate minimum weight determination through body composition. Although skinfold equations are essential to estimate body composition in the field setting, they are mostly derived from Western societies and may lack generalizability to other populations. PURPOSE: Previously published skinfold equations lacked external validity in predicting body density of Iranian wrestlers. We aimed to derive a new anthropometric model specific to young Iranian male wrestlers. STUDY DESIGN: Cross-sectional cohort study. LEVEL OF EVIDENCE: Level 3. METHODS: One hundred twenty-six Iranian male wrestlers with at least 1 year of experience and a mean age of 19 ± 4.0 years underwent underwater weight analysis for body density estimation and anthropometric measurements. The previously published equations were validated, followed by new regression modeling, using multivariable fractional polynomials, with body density as the criterion predicted by common anthropometric variables. The final model was validated throughout the modeling procedure using 1000 bootstrap replications. RESULTS: The mean body fat percentage (%BF) was 12.6% (95% CI, 11.9%-13.4%), lower than that of previous studies. Six previously published equations each had significant deviations from the line of identity (all P < 0.001). The new prediction equation combined subscapular, tricipital, and midaxillary skinfolds and body mass index cubed to predict body density. CONCLUSION: The development of ethnicity-specific equations, using statistically unbiased and comprehensive validation methods, is imperative for body composition estimation to determine the minimum weight for regulation of health in athletes. CLINICAL RELEVANCE: Using equations without external validation can bias the prediction of minimum weight, leading to unsafe weight reduction by athletes. Compared with a previous study, much lower mean %BF was found using an ethnicity-specific equation (12.6% vs 15.9%). This difference observed in %BF prediction could affect safe fat reduction in athletes.