Heidi Guyer

A Single Factor Underlies the Metabolic Syndrome: A confirmatory factor analysis

OBJECTIVE Confirmatory factor analysis (CFA) was used to test the hypothesis that the components of the metabolic syndrome are manifestations of a single common factor. RESEARCH DESIGN AND METHODS Three different datasets were used to test and validate the model. The Spanish and Mauritian studies included 207 men and 203 women and 1,411 men and 1,650 women, respectively. A third analytical dataset including 847 men was obtained from a previously published CFA of a U.S. population. The one-factor model included the metabolic syndrome core components (central obesity, insulin resistance, blood pressure, and lipid measurements). We also tested an expanded one-factor model that included uric acid and leptin levels. Finally, we used CFA to compare the goodness of fit of one-factor models with the fit of two previously published four-factor models. RESULTS The simplest one-factor model showed the best goodness-of-fit indexes (comparative fit index 1, root mean-square error of approximation 0.00). Comparisons of one-factor with four-factor models in the three datasets favored the one-factor model structure. The selection of variables to represent the different metabolic syndrome components and model specification explained why previous exploratory and confirmatory factor analysis, respectively, failed to identify a single factor for the metabolic syndrome. CONCLUSIONS These analyses support the current clinical definition of the metabolic syndrome, as well as the existence of a single factor that links all of the core components.

The association between leptin and left ventricular hypertrophy: a population-based cross-sectional study

Background and objectives Plasma leptin levels have been shown to be an independent risk factor for cardiovascular disease. Leptin has been shown to have sympathetic and vascular effects, and may increase cardiovascular risk through increased blood pressure, left ventricular hypertrophy, or atherosclerotic mechanisms. This study examines whether leptin levels, independent of body mass and insulin resistance, are a risk factor for hypertension and left ventricular hypertrophy. Methods and participants A population-based, cross-sectional sample of 410 adults from rural Spain was studied. The correlations between plasma leptin levels and left ventricular mass index, sum of wall thicknesses, and blood pressure were calculated. Multiple linear regression analysis was used to adjust for other cardiovascular risk factors. Results After adjusting for age, body mass index, systolic blood pressure, sex, and insulin resistance, leptin was inversely associated with left ventricular mass index (β = −0.20, P < 0.01). Leptin was also inversely related to the sum of wall thicknesses; however, this association did not reach statistical significance (β = −0.12, P = 0.063). Leptin was not statistically associated with blood pressure after adjusting for body mass index. Conclusions The results do not support the hypothesis that leptin increases cardiovascular risk by increasing left ventricular mass index or blood pressure. Other mechanisms, related to atherosclerosis, could explain the increased risk of cardiovascular diseases observed with high leptin levels.

Neuroprotective Diets Are Associated with Better Cognitive Function: The Health and Retirement Study

To evaluate the association between the Mediterranean diet (MedDiet) and the Mediterranean‐DASH diet Intervention for Neurodegeneration Delay (MIND diet) and cognition in a nationally representative population of older U.S. adults.

Does Sequence Matter in Multi-Mode Surveys: Results from an Experiment.

Interest in a multi-mode approach to surveys has grown substantially in recent years, in part due to increased costs of face-to-face interviewing and the emergence of the internet as a survey mode. Yet, there is little systematic evidence of the impact of a multimode approach on survey costs and errors. This paper reports the results of an experiment designed to evaluate whether a mixed-mode approach to a large screening survey would produce comparable response rates at a lower cost than a face-to-face screening effort. The experiment was carried out in the Health and Retirement Study (HRS), an ongoing panel study of Americans over age 50. In 2010, HRS conducted a household screening survey to recruit new sample members to supplement the existing sample. The experiment varied the sequence of modes with which the screening interview was delivered. One treatment offered mail first, followed by face-to-face interviewing; the other started with face-to-face and then mail. A control group was offered only face-to-face interviewing. Results suggest that the mixed mode options reduced costs without reducing response rates to the screening interview. There is some evidence, however, that the sequence of modes offered may impact the response rate for a follow-up in-depth interview.Interest in a multimode approach to surveys has grown substantially in recent years, in part due to increased costs of face-to-face (FtF) interviewing and the emergence of the Internet as a survey mode. Yet, there is little systematic evidence of the impact of a multimode approach on survey costs and errors. This article reports the results of an experiment designed to evaluate whether a mixed-mode approach to a large screening survey would produce comparable response rates at a lower cost than an FtF screening effort. The experiment was carried out in the Health and Retirement Study (HRS), an ongoing panel study of Americans over age 50. In 2010, HRS conducted a household screening survey to recruit new sample members to supplement the existing sample. The experiment varied the sequence of modes with which the screening interview was delivered. One treatment offered mail first, followed by FtF interviewing; the other started with FtF and then mail. A control group was offered only FtF interviewing. Results suggest that the mixed-mode options reduced costs without reducing response rates to the screening interview. There is some evidence, however, that the sequence of modes offered may impact the response rate for a follow-up in-depth interview.

A Single Factor Underlies the Metabolic Syndrome: A Confirmatory Factor Analysis: Response to McCaffery et al.

We thank McCaffery et al. (1) for their comments on our study (2). In their first report (3), they used confirmatory factor analysis to analyze the metabolic syndrome structure and to expose the limitations of exploratory factor analysis (EFA). We agree that their results support the concept of a common factor underlying the different components of the metabolic syndrome. What, therefore, are the differences between our studies? The one-factor model in our study was based …

New options for national population surveys: The implications of internet and smartphone coverage

Challenges to survey data collection have increased the costs of social research via face-to-face surveys so much that it may become extremely difficult for social scientists to continue using these methods. A key drawback to less expensive Internet-based alternatives is the threat of biased results from coverage errors in survey data. The rise of Internet-enabled smartphones presents an opportunity to re-examine the issue of Internet coverage for surveys and its implications for coverage bias. Two questions (on Internet access and smartphone ownership) were added to the National Survey of Family Growth (NSFG), a U.S. national probability survey of women and men age 15-44, using a continuous sample design. We examine 16 quarters (4 years) of data, from September 2012 to August 2016. Overall, we estimate that 82.9% of the target NSFG population has Internet access, and 81.6% has a smartphone. Combined, this means that about 90.7% of U.S. residents age 15-44 have Internet access, via either traditional devices or a smartphone. We find some evidence of compensatory coverage when looking at key race/ethnicity and age subgroups. For instance, while Black teens (15-18) have the lowest estimated rate of Internet access (81.9%) and the lowest rate of smartphone usage (72.6%), an estimated 88.0% of this subgroup has some form of Internet access. We also examine the socio-demographic correlates of Internet and smartphone coverage, separately and combined, as indicators of technology access in this population. In addition, we look at the effect of differential coverage on key estimates produced by the NSFG, related to fertility, family formation, and sexual activity. While this does not address nonresponse or measurement biases that may differ for alternative modes, our paper has implications for possible coverage biases that may arise when switching to a Web-based mode of data collection, either for follow-up surveys or to replace the main face-to-face data collection.

Sleep, Diet, and Cardiometabolic Health Investigations: a Systematic Review of Analytic Strategies

Purpose of ReviewPoor sleep is a risk factor for cardiometabolic morbidity. The relationship of sleep and cardiometabolic health could be confounded, mediated, or modified by diet, yet the incorporation of diet in sleep-cardiometabolic health studies is inconsistent. This rapid systematic literature review evaluates the conceptualization of diet as a confounder, mediator, or effect modifier within sleep-cardiometabolic health investigations, and the statistical approaches utilized.Recent FindingsOf 4692 studies identified, 60 were retained (28 adult, 32 pediatric). Most studies included diet patterns, quality, or energy intake as confounders, while a few examined these dietary variables as mediators or effect modifiers. There was some evidence, mostly in pediatric studies, that inclusion of diet altered sleep-cardiometabolic health associations.SummaryDiet plays a diverse role within sleep-cardiometabolic health associations. Investigators should carefully consider the conceptualization of diet variables in these relationships and utilize contemporary statistical approaches when applicable.