Ching Yun Wang

Implementation of the women's health initiative study design

The Women’s Health Initiative (WHI) Clinical Trial (CT) includes three overlapping components, each a randomized controlled comparison among women who were postmenopausal and 50 to 79 years of age at randomization. The dietary modification (DM) component randomly assigned 48,836 (target 48,000) eligible women to either a sustained low-fat eating pattern (40%) or self-selected dietary behavior (60%), with breast cancer and colorectal cancer as designated primary outcomes and coronary heart disease as a secondary outcome. The nutrition goals for women assigned to the DM intervention group have been to reduce total dietary fat to 20%, and saturated fat to less than 7% of daily calories and, secondarily, to increase daily servings of vegetables and fruits to at least five and of grain products to at least six and to maintain these changes throughout trial follow-up. The randomization of 40%, rather than 50%, of participating women to the DM intervention group was intended to reduce trial costs, while testing trial hypotheses with specified power. The postmenopausal hormone therapy (PHT) component comprises two randomized, double-blind trials among 27,347 (target 27,500) women, with coronary heart disease

Effects of a caloric restriction weight loss diet and exercise on inflammatory biomarkers in overweight/obese postmenopausal women: a randomized controlled trial.

Obese and sedentary persons have increased risk for cancer; inflammation is a hypothesized mechanism. We examined the effects of a caloric restriction weight loss diet and exercise on inflammatory biomarkers in 439 women. Overweight and obese postmenopausal women were randomized to 1-year: caloric restriction diet (goal of 10% weight loss, N = 118), aerobic exercise (225 min/wk of moderate-to-vigorous activity, N = 117), combined diet + exercise (N = 117), or control (N = 87). Baseline and 1-year high-sensitivity C-reactive protein (hs-CRP), serum amyloid A (SAA), interleukin-6 (IL-6), leukocyte, and neutrophil levels were measured by investigators blind to group. Inflammatory biomarker changes were compared using generalized estimating equations. Models were adjusted for baseline body mass index (BMI), race/ethnicity, and age. Four hundred and thirty-eight (N = 1 in diet + exercise group was excluded) were analyzed. Relative to controls, hs-CRP decreased by geometric mean (95% confidence interval, P value): 0.92 mg/L (0.53-1.31, P < 0.001) in the diet and 0.87 mg/L (0.51-1.23, P < 0.0001) in the diet + exercise groups. IL-6 decreased by 0.34 pg/mL (0.13-0.55, P = 0.001) in the diet and 0.32 pg/mL (0.15-0.49, P < 0.001) in the diet + exercise groups. Neutrophil counts decreased by 0.31 × 10(9)/L (0.09-0.54, P = 0.006) in the diet and 0.30 × 10(9)/L (0.09-0.50, P = 0.005) in the diet + exercise groups. Diet and diet + exercise participants with 5% or more weight loss reduced inflammatory biomarkers (hs-CRP, SAA, and IL-6) compared with controls. The diet and diet + exercise groups reduced hs-CRP in all subgroups of baseline BMI, waist circumference, CRP level, and fasting glucose. Our findings indicate that a caloric restriction weight loss diet with or without exercise reduces biomarkers of inflammation in postmenopausal women, with potential clinical significance for cancer risk reduction.

Fasting C-Peptide Levels and Death Resulting From All Causes and Breast Cancer: The Health, Eating, Activity, and Lifestyle Study

PURPOSE To examine the association between serum C-peptide, a marker of insulin secretion, measured 3 years after a breast cancer diagnosis, and death resulting from all causes and breast cancer. PATIENTS AND METHODS This was a prospective, observational study of 604 women enrolled onto the Health, Eating, Activity, and Lifestyle (HEAL) Study who were diagnosed with local or regional breast cancer between 1995 and 1998 and observed until death or December 31, 2006, whichever came first. The hazard ratio (HR) for all deaths and deaths owing to breast cancer and 95% CIs for the HR were estimated using multivariable stratified Cox regression analyses. RESULTS Among women without type 2 diabetes, fasting C-peptide levels were associated with an increased risk of death resulting from all causes and from breast cancer. A 1-ng/mL increase in C-peptide was associated with a 31% increased risk of any death (HR = 1.31; 95% CI, 1.06 to 1.63; P = .013) and a 35% increased risk of death as a result of breast cancer (HR = 1.35; 95% CI, 1.02 to 1.87, P = .048). Associations between C-peptide levels and death as a result of breast cancer were stronger in certain subgroups, including women with type 2 diabetes, women with a body mass index less than 25 kg/m(2), women diagnosed with a higher stage of disease, and women whose tumors were estrogen receptor positive. CONCLUSION Treatment strategies to reduce C-peptide levels in patients with breast cancer, including dietary-induced weight loss, physical activity, and/or use of insulin-lowering medications, should be explored.

Dietary weight loss and exercise interventions effects on quality of life in overweight/obese postmenopausal women: a randomized controlled trial

BackgroundAlthough lifestyle interventions targeting multiple lifestyle behaviors are more effective in preventing unhealthy weight gain and chronic diseases than intervening on a single behavior, few studies have compared individual and combined effects of diet and/or exercise interventions on health-related quality of life (HRQOL). In addition, the mechanisms of how these lifestyle interventions affect HRQOL are unknown. The primary aim of this study was to examine the individual and combined effects of dietary weight loss and/or exercise interventions on HRQOL and psychosocial factors (depression, anxiety, stress, social support). The secondary aim was to investigate predictors of changes in HRQOL.MethodsThis study was a randomized controlled trial. Overweight/obese postmenopausal women were randomly assigned to 12 months of dietary weight loss (n = 118), moderate-to-vigorous aerobic exercise (225 minutes/week, n = 117), combined diet and exercise (n = 117), or control (n = 87). Demographic, health and anthropometric information, aerobic fitness, HRQOL (SF-36), stress (Perceived Stress Scale), depression [Brief Symptom Inventory (BSI)-18], anxiety (BSI-18) and social support (Medical Outcome Study Social Support Survey) were assessed at baseline and 12 months. The 12-month changes in HRQOL and psychosocial factors were compared using analysis of covariance, adjusting for baseline scores. Multiple regression was used to assess predictors of changes in HRQOL.ResultsTwelve-month changes in HRQOL and psychosocial factors differed by intervention group. The combined diet + exercise group improved 4 aspects of HRQOL (physical functioning, role-physical, vitality, and mental health), and stress (p ≤ 0.01 vs. controls). The diet group increased vitality score (p < 0.01 vs. control), while HRQOL did not change differently in the exercise group compared with controls. However, regardless of intervention group, weight loss predicted increased physical functioning, role-physical, vitality, and mental health, while increased aerobic fitness predicted improved physical functioning. Positive changes in depression, stress, and social support were independently associated with increased HRQOL, after adjusting for changes in weight and aerobic fitness.ConclusionsA combined diet and exercise intervention has positive effects on HRQOL and psychological health, which may be greater than that from exercise or diet alone. Improvements in weight, aerobic fitness and psychosocial factors may mediate intervention effects on HRQOL.Trial RegistrationClinical Trials, ClinicalTrials.gov register, NCT00470119

Dietary Weight Loss and Exercise Effects on Insulin Resistance in Postmenopausal Women

BACKGROUND Comprehensive lifestyle interventions are effective in preventing diabetes and restoring glucose regulation; however, the key stimulus for change has not been identified and effects in older individuals are not established. The aim of the study was to investigate the independent and combined effects of dietary weight loss and exercise on insulin sensitivity and restoration of normal fasting glucose in middle-aged and older women. DESIGN Four-arm RCT, conducted between 2005 and 2009 and data analyzed in 2010. SETTING/PARTICIPANTS 439 inactive, overweight/obese postmenopausal women. INTERVENTIONS Women were assigned to: dietary weight loss (n=118); exercise (n=117); exercise+diet (n=117); or control (n=87). The diet intervention was a group-based reduced-calorie program with a 10% weight-loss goal. The exercise intervention was 45 min/day, 5 days/week of moderate-to-vigorous intensity aerobic activity. MAIN OUTCOME MEASURES 12-month change in serum insulin, C-peptide, fasting glucose, and whole body insulin resistance (HOMA-IR). RESULTS A significant improvement in HOMA-IR was detected in the diet (-24%, p<0.001) and exercise+ diet (-26%, p<0.001) groups but not in the exercise (-9%, p=0.22) group compared with controls (-2%); these effects were similar in middle-aged (50-60 years) and older women (aged 60-75 years). Among those with impaired fasting glucose (5.6-6.9 mmol/L) at baseline (n=143; 33%), the odds (95% CI) of regressing to normal fasting glucose after adjusting for weight loss and baseline levels were 2.5 (0.8, 8.4); 2.76 (0.8, 10.0); and 3.1 (1.0, 9.9) in the diet, exercise+diet, and exercise group, respectively, compared with controls. CONCLUSIONS Dietary weight loss, with or without exercise, significantly improved insulin resistance. Older women derived as much benefit as did the younger postmenopausal women. TRIAL REGISTRATION This study is registered at Clinicaltrials.govNCT00470119.

Weighted Estimators for Proportional Hazards Regression With Missing Covariates

Missing covariate data are common in epidemiologic studies and disease prevention trials. In this article regression parameter estimation in the Cox proportional hazards model is considered when certain covariates are observed for all study subjects and other covariate data are collected only for a subset. The article presents both simple weighted and kernel-assisted fully augmented weighted estimators that use the partially incomplete data nonparametrically. We use nonparametric methods to estimate selection probabilities in the simple weighted estimating functions. We also use nonparametric kernel smoothing techniques to estimate certain conditional expectations in fully augmented weighted estimating functions. The proposed methods are nonparametric in the sense that they require neither a model for the missing-data mechanism nor specification of the conditional distribution of missing covariates given observed covariates. These estimators allow the missing-data mechanism to depend on outcome variables and observed covariates, and they are applicable to various cohort sampling procedures, including case-cohort and nested case-control designs. We show that the simple and the kernel-assisted fully augmented weighted estimators are typically consistent and asymptotically normal. Moreover, the proposed estimators are more efficient than the simple weighted estimator with the inverse of true selection probability as weight. They also correct the bias of estimates from analysis of the complete data alone when the missing-data mechanism depends on outcome variables. In addition, when covariates are time-independent, certain simple weighted estimators are shown to be asymptotically equivalent to the kernel-assisted fully augmented weighted estimators. Moderate sample size performance of the estimators is examined via simulation and by application to two real datasets.

Research strategies and the use of nutrient biomarkers in studies of diet and chronic disease

OBJECTIVE To provide an account of the state of diet and chronic disease research designs and methods; to discuss the role and potential of aggregate and analytical observational studies and randomised controlled intervention trials; and to propose strategies for strengthening each type of study, with particular emphasis on the use of nutrient biomarkers in cohort study settings. DESIGN Observations from diet and disease studies conducted over the past 25 years are used to identify the strengths and weaknesses of various study designs that have been used to associate nutrient consumption with chronic disease risk. It is argued that a varied research programme, employing multiple study designs, is needed in response to the widely different biases and constraints that attend aggregate and analytical epidemiological studies and controlled intervention trials. Study design modifications are considered that may be able to enhance the reliability of aggregate and analytical nutritional epidemiological studies. Specifically, the potential of nutrient biomarker measurements that provide an objective assessment of nutrient consumption to enhance analytical study reliability is emphasised. A statistical model for combining nutrient biomarker data with self-report nutrient consumption estimates is described, and related ongoing work on odds ratio parameter estimation is outlined briefly. Finally, a recently completed nutritional biomarker study among 102 postmenopausal women in Seattle is mentioned. The statistical model will be applied to biomarker data on energy expenditure, urinary nitrogen, selected blood fatty acid measurements and various blood micronutrient concentrations, and food frequency self-report data, to identify study subject characteristics, such as body mass, age or socio-economic status, that may be associated with the measurement properties of food frequency nutrient consumption estimates. This information will be crucial for the design of a potential larger nutrient biomarker study within the cohort study component of the Womens Health Initiative. SETTING AND SUBJECTS The methodology under study is expected to be pertinent to a wide variety of diet and chronic disease association studies in the general population. Ongoing work focuses on statistical methods developed using computer simulations motivated by studies of dietary fat in relation to breast and colon cancer among post-menopausal women, and ongoing pilot studies to be described in detail elsewhere, involving post-menopausal women living in the Seattle area. RESULTS AND CONCLUSION A varied research programme appears to be needed to make progress in the challenging diet and chronic disease research area. Such progress may include aggregate studies of diet and chronic disease that include sample surveys in diverse population groups world-wide, analytical epidemiological studies that use nutrient biomarker data to calibrate self-report nutrient consumption estimates, and randomised controlled intervention trials that arise from an enhanced infrastructure for intervention development. New innovative designs, models and methodologies are needed for each such research setting.

Weighted semiparametric estimation in regression analysis with missing covariate data

Abstract This article investigates estimation of the regression coefficients in an assumed mean function when covariates on some subjects are missing. We examine the performance of a Horvitz and Thompson (1952)-type weighted estimator by using different estimates of the selection probabilities, which may be treated as nuisance parameters (or a nuisance function). In particular, we investigate the properties of the estimate of the regression parameters when the selection probabilities are estimated by kernel smoothers. We present large sample theory for the new estimator and conduct simulation studies comparing the proposed estimator to the maximum likelihood estimator and multiple imputation under various model assumptions and different missingness mechanisms. In addition, we provide two real examples that motivate this investigation.

Failure time regression with continuous covariates measured with error

We consider failure time regression analysis with an auxiliary variable in the presence of a validation sample. We extend the nonparametric inference procedure of Zhou and Pepe to handle a continuous auxiliary or proxy covariate. We estimate the induced relative risk function with a kernel smoother and allow the selection probability of the validation set to depend on the observed covariates. We present some asymptotic properties for the kernel estimator and provide some simulation results. The method proposed is illustrated with a data set from an on‐going epidemiologic study.

Sedentary Behavior and Mortality in Older Women: The Women’s Health Initiative

BACKGROUND Although epidemiologic studies have shown associations between sedentary behavior and mortality, few have focused on older women with adequate minority representation and few have controlled for both physical activity and functional status. PURPOSE The objective of this study was to determine the relationship between sedentary time and total; cardiovascular disease (CVD); coronary heart disease (CHD); and cancer mortality in a prospective, multiethnic cohort of postmenopausal women. METHODS The study population included 92,234 women aged 50-79 years at baseline (1993-1998) who participated in the Womens Health Initiative Observational Study through September 2010. Self-reported sedentary time was assessed by questionnaire and examined in 4 categories (≤4, >4-8, ≥8-11, >11 hours). Mortality risks were examined using Cox proportional hazard models adjusting for confounders. Models were also stratified by age, race/ethnicity, body mass index, physical activity, physical function, and chronic disease to examine possible effect modification. Analyses were conducted in 2012-2013. RESULTS The mean follow-up period was 12 years. Compared with women who reported the least sedentary time, women reporting the highest sedentary time had increased risk of all-cause mortality in the multivariate model (HR=1.12, 95% CI=1.05, 1.21). Results comparing the highest versus lowest categories for CVD, CHD, and cancer mortality were as follows: HR=1.13, 95% CI=0.99, 1.29; HR=1.27, 95% CI=1.04, 1.55; and HR=1.21, 95% CI=1.07, 1.37, respectively. For all mortality outcomes, there were significant linear tests for trend. CONCLUSIONS There was a linear relationship between greater amounts of sedentary time and mortality risk after controlling for multiple potential confounders.