Fitting multilevel models in complex survey data with design weights: Recommendations

Abstract Background Multilevel models (MLM) offer complex survey data analysts a unique approach to understanding individual and contextual determinants of public health. However, little summarized guidance exists with regard to fitting MLM in complex survey data with design weights. Simulation work suggests that analysts should scale design weights using two methods and fit the MLM using unweighted and scaled-weighted data. This article examines the performance of scaled-weighted and unweighted analyses across a variety of MLM and software programs. Methods Using data from the 2005–2006 National Survey of Children with Special Health Care Needs (NS-CSHCN: n = 40,723) that collected data from children clustered within states, I examine the performance of scaling methods across outcome type (categorical vs. continuous), model type (level-1, level-2, or combined), and software (Mplus, MLwiN, and GLLAMM). Results Scaled weighted estimates and standard errors differed slightly from unweighted analyses, agreeing more with each other than with unweighted analyses. However, observed differences were minimal and did not lead to different inferential conclusions. Likewise, results demonstrated minimal differences across software programs, increasing confidence in results and inferential conclusions independent of software choice. Conclusion If including design weights in MLM, analysts should scale the weights and use software that properly includes the scaled weights in the estimation.</p

Equity in the use of antithrombotic drugs, beta-blockers and statins among Finnish coronary patients

Background Earlier studies have mainly reported the use of antithrombotic drugs, beta-blockers and statins among hospital patient populations or MI patients. This study aimed to describe the use of these drugs among middle-aged Finnish coronary patients and to identify patient groups in risk of being prescribed inadequate medication for secondary prevention of coronary heart disease. Methods One-year follow-up survey data from a random sample of a cohort of coronary patients were used along with register data linked to the survey. The response rate was 54% (n = 2650). The main outcome measures were use of antithrombotic drugs, beta-blockers and statins and the data were analysed using logistic regression analysis. Results Among men and women, respectively, 82% and 81% used beta-blockers, 95% and 89% used antithrombotic drugs, and 62% and 59% used statins. Younger men and men from higher socioeconomic groups were more likely to use statins, even after controlling for disease severity and comorbidity. In women, the age trend was reversed and no socioeconomic differences were found. Drug use increased with increased disease severity, but diabetes had only a slight effect. Conclusion The use of antithrombotic drugs and beta-blockers among Finnish coronary patients seemed to be rather appropriate and, to some extent, prescription practices of preventive medication varied according to patients' risk of coronary events. However, statin use was remarkably low among men with low socio-economic status, and there is need to improve preventive drug treatment among diabetic coronary patients.BioMed Central Open acces

Body Mass Index and Employment-Based Health Insurance

<p>Abstract</p> <p>Background</p> <p>Obese workers incur greater health care costs than normal weight workers. Possibly viewed by employers as an increased financial risk, they may be at a disadvantage in procuring employment that provides health insurance. This study aims to evaluate the association between body mass index [BMI, weight in kilograms divided by the square of height in meters] of employees and their likelihood of holding jobs that include employment-based health insurance [EBHI].</p> <p>Methods</p> <p>We used the 2004 Household Components of the nationally representative Medical Expenditure Panel Survey. We utilized logistic regression models with provision of EBHI as the dependent variable in this descriptive analysis. The key independent variable was BMI, with adjustments for the domains of demographics, social-economic status, workplace/job characteristics, and health behavior/status. BMI was classified as normal weight (18.5–24.9), overweight (25.0–29.9), or obese (≥ 30.0). There were 11,833 eligible respondents in the analysis.</p> <p>Results</p> <p>Among employed adults, obese workers [adjusted probability (AP) = 0.62, (0.60, 0.65)] (<it>P </it>= 0.005) were more likely to be employed in jobs with EBHI than their normal weight counterparts [AP = 0.57, (0.55, 0.60)]. Overweight workers were also more likely to hold jobs with EBHI than normal weight workers, but the difference did not reach statistical significance [AP = 0.61 (0.58, 0.63)] (<it>P </it>= 0.052). There were no interaction effects between BMI and gender or age.</p> <p>Conclusion</p> <p>In this nationally representative sample, we detected an association between workers' increasing BMI and their likelihood of being employed in positions that include EBHI. These findings suggest that obese workers are more likely to have EBHI than other workers.</p

Human Herpesvirus 8 Seropositivity Among Sexually Active Adults in Uganda

Sexual transmission of human herpesvirus 8 (HHV8) has been implicated among homosexual men, but the evidence for sexual transmission among heterosexual individuals is controversial. We investigated the role of sexual transmission of HHV8 in a nationally representative sample in Uganda, where HHV8 infection is endemic and transmitted mostly during childhood.The study population was a subset of participants (n = 2681) from a population-based HIV/AIDS serobehavioral survey of adults aged 15-59 years conducted in 2004/2005. High risk for sexual transmission was assessed by questionnaire and serological testing for HIV and herpes simplex virus 2. Anti-HHV8 antibodies were measured using two enzyme immunoassays targeting synthetic peptides from the K8.1 and orf65 viral genes. The current study was restricted to 2288 sexually active adults. ORs and 95% CIs for HHV8 seropositivity were estimated by fitting logistic regression models with a random intercept using MPLUS and SAS software.The weighted prevalence of HHV8 seropositivity was 56.2%, based on 1302 seropositive individuals, and it increased significantly with age (P(trend)<0.0001). In analyses adjusting for age, sex, geography, education, and HIV status, HHV8 seropositivity was positively associated with reporting two versus one marital union (OR:1.52, 95% CI: 1.17-1.97) and each unit increase in the number of children born (OR: 1.04, 95% CI: 1.00-1.08), and was inversely associated with ever having used a condom (OR: 0.64, 95% CI: 0.45-0.89). HHV8 seropositivity was not associated with HIV (P = 0.660) or with herpes simplex virus 2 (P = 0.732) seropositivity. Other sexual variables, including lifetime number of sexual partners or having had at least one sexually transmitted disease, and socioeconomic variables were unrelated to HHV8 seropositivity.Our findings are compatible with the conclusion that sexual transmission of HHV8 in Uganda, if it occurs, is weak

Comparing methods to estimate treatment effects on a continuous outcome in multicentre randomized controlled trials: A simulation study

<p>Abstract</p> <p>Background</p> <p>Multicentre randomized controlled trials (RCTs) routinely use randomization and analysis stratified by centre to control for differences between centres and to improve precision. No consensus has been reached on how to best analyze correlated continuous outcomes in such settings. Our objective was to investigate the properties of commonly used statistical models at various levels of clustering in the context of multicentre RCTs.</p> <p>Methods</p> <p>Assuming no treatment by centre interaction, we compared six methods (ignoring centre effects, including centres as fixed effects, including centres as random effects, generalized estimating equation (GEE), and fixed- and random-effects centre-level analysis) to analyze continuous outcomes in multicentre RCTs using simulations over a wide spectrum of intraclass correlation (ICC) values, and varying numbers of centres and centre size. The performance of models was evaluated in terms of bias, precision, mean squared error of the point estimator of treatment effect, empirical coverage of the 95% confidence interval, and statistical power of the procedure.</p> <p>Results</p> <p>While all methods yielded unbiased estimates of treatment effect, ignoring centres led to inflation of standard error and loss of statistical power when within centre correlation was present. Mixed-effects model was most efficient and attained nominal coverage of 95% and 90% power in almost all scenarios. Fixed-effects model was less precise when the number of centres was large and treatment allocation was subject to chance imbalance within centre. GEE approach underestimated standard error of the treatment effect when the number of centres was small. The two centre-level models led to more variable point estimates and relatively low interval coverage or statistical power depending on whether or not heterogeneity of treatment contrasts was considered in the analysis.</p> <p>Conclusions</p> <p>All six models produced unbiased estimates of treatment effect in the context of multicentre trials. Adjusting for centre as a random intercept led to the most efficient treatment effect estimation across all simulations under the normality assumption, when there was no treatment by centre interaction.</p

Public Acceptability in the UK and USA of Nudging to Reduce Obesity: The Example of Reducing Sugar-Sweetened Beverages Consumption.

BACKGROUND: "Nudging"-modifying environments to change people's behavior, often without their conscious awareness-can improve health, but public acceptability of nudging is largely unknown. METHODS: We compared acceptability, in the United Kingdom (UK) and the United States of America (USA), of government interventions to reduce consumption of sugar-sweetened beverages. Three nudge interventions were assessed: i. reducing portion Size, ii. changing the Shape of the drink containers, iii. changing their shelf Location; alongside two traditional interventions: iv. Taxation and v. Education. We also tested the hypothesis that describing interventions as working through non-conscious processes decreases their acceptability. Predictors of acceptability, including perceived intervention effectiveness, were also assessed. Participants (n = 1093 UK and n = 1082 USA) received a description of each of the five interventions which varied, by randomisation, in how the interventions were said to affect behaviour: (a) via conscious processes; (b) via non-conscious processes; or (c) no process stated. Acceptability was derived from responses to three items. RESULTS: Levels of acceptability for four of the five interventions did not differ significantly between the UK and US samples; reducing portion size was less accepted by the US sample. Within each country, Education was rated as most acceptable and Taxation the least, with the three nudge-type interventions rated between these. There was no evidence to support the study hypothesis: i.e. stating that interventions worked via non-conscious processes did not decrease their acceptability in either the UK or US samples. Perceived effectiveness was the strongest predictor of acceptability for all interventions across the two samples. CONCLUSION: In conclusion, nudge interventions to reduce consumption of sugar-sweetened beverages seem similarly acceptable in the UK and USA, being more acceptable than taxation, but less acceptable than education. Contrary to prediction, we found no evidence that highlighting the non-conscious processes by which nudge interventions may work decreases their acceptability. However, highlighting the effectiveness of all interventions has the potential to increase their acceptability.The study was funded by the UK Department of Health Policy Research Programme (Policy Research Unit in Behaviour and Health) (Grant ID: PRUN-0409-10109)This is the final version of the article. It first appeared from the Public Library of Science via http://dx.doi.org/10.1371/journal.pone.015599

Prevalence and Correlates of At-Risk Drinking Among Older Adults: The Project SHARE Study

At-risk drinking, excessive or potentially harmful alcohol use in combination with select comorbidities or medication use, affects about 10% of elderly adults and is associated with higher mortality. Yet, our knowledge is incomplete regarding the prevalence of different categories of at-risk drinking and their associations with patient demographics. To examine the prevalence and correlates of different categories of at-risk drinking among older adults. Cross-sectional analysis of survey data. Current drinkers ages 60 and older accessing primary care clinics around Santa Barbara, California (n = 3,308). At-risk drinkers were identified using the Comorbidity Alcohol Risk Evaluation Tool (CARET). At-risk alcohol use was categorized as alcohol use in the setting of 1) high-risk comorbidities or 2) high-risk medication use, and 3) excessive alcohol use alone. Adjusted associations of participant characteristics with at-risk drinking in each of the three at-risk categories and with at-risk drinking of any kind were estimated using logistic regression. Over one-third of our sample (34.7%) was at risk. Among at-risk individuals, 61.9% had alcohol use in the context of high-risk comorbidities, 61.0% had high-risk medication use, and 64.3% had high-risk alcohol behaviors. The adjusted odds of at-risk drinking of any kind were decreased and significant for women (odds ratio, OR = 0.41; 95% confidence interval: 0.35-0.48; p-value &lt; 0.001), adults over age 80 (OR = 0.55; CI: 0.43-0.72; p &lt; 0.001 vs. ages 60-64), Asians (OR = 0.40; CI: 0.20-0.80; p = 0.01 vs. Caucasians) and individuals with higher education levels. Similar associations were observed in all three categories of at-risk drinking. High-risk alcohol use was common among older adults in this large sample of primary care patients, and male Caucasians, those ages 60-64, and those with lower levels of education were most likely to have high-risk alcohol use of any type. Our findings could help physicians identify older patients at increased risk for problems from alcohol consumption

Association of urinary phthalate metabolite concentrations with body mass index and waist circumference: a cross-sectional study of NHANES data, 1999–2002

BACKGROUND: Although diet and activity are key factors in the obesity epidemic, laboratory studies suggest that endocrine disrupting chemicals may also affect obesity. METHODS: We analyzed associations between six phthalate metabolites measured in urine and body mass index (BMI) and waist circumference (WC) in National Health and Nutrition Examination Survey (NHANES) participants aged 6–80. We included 4369 participants from NHANES 1999–2002, with data on mono-ethyl (MEP), mono-2-ethylhexyl (MEHP), mono-n-butyl (MBP), and mono-benzyl (MBzP) phthalate; 2286 also had data on mono-2-ethyl-5-hydroxyhexyl (MEHHP) and mono-2-ethyl-5-oxohexyl (MEOHP) phthalate (2001–2002). Using multiple regression, we computed mean BMI and WC within phthalate quartiles in eight age/gender specific models. RESULTS: The most consistent associations were in males aged 20–59; BMI and WC increased across quartiles of MBzP (adjusted mean BMI = 26.7, 27.2, 28.4, 29.0, p-trend = 0.0002), and positive associations were also found for MEOHP, MEHHP, MEP, and MBP. In females, BMI and WC increased with MEP quartile in adolescent girls (adjusted mean BMI = 22.9, 23.8, 24.1, 24.7, p-trend = 0.03), and a similar but less strong pattern was seen in 20–59 year olds. In contrast, MEHP was inversely related to BMI in adolescent girls (adjusted mean BMI = 25.4, 23.8, 23.4, 22.9, p-trend = 0.02) and females aged 20–59 (adjusted mean BMI = 29.9, 29.9, 27.9, 27.6, p-trend = 0.02). There were no important associations among children, but several inverse associations among 60–80 year olds. CONCLUSION: This exploratory, cross-sectional analysis revealed a number of interesting associations with different phthalate metabolites and obesity outcomes, including notable differences by gender and age subgroups. Effects of endocrine disruptors, such as phthalates, may depend upon endogenous hormone levels, which vary dramatically by age and gender. Individual phthalates also have different biologic and hormonal effects. Although our study has limitations, both of these factors could explain some of the variation in the observed associations. These preliminary data support the need for prospective studies in populations at risk for obesity.National Institutes of Environmental Health Sciences (R21ES013724