Association of Waist Circumference and Body Mass Index Deciles Ratio with All-Cause Mortality: Findings from the National Health and Nutrition Examination Survey.

Given the importance and continued interest in finding a simple, accessible, and universal measure which reflects both general and abdominal adiposity, this study tested for an association of the ratio of WC decile to BMI decile (WC-d/BMI-d) with all-cause mortality. Individuals aged 18-79 years who had participated in the National Health and Nutrition Examination Survey (NHANES) during the years 2007 to 2018 were included in the analysis. WC and BMI deciles were defined separately for males and females, while WC-d/BMI-d was calculated for each individual. The association of WC-d/BMI-d with mortality was assessed using logistic models for the total study population, and then again after stratification by sex, ethnicity, morbidity level, and BMI categories. Positive associations between WC-d/BMI-d and mortality were demonstrated for the total study population (adjusted OR = 1.545, 95%CI: 1.369-1.722) and within different sub-groups, including the population with a normal BMI level (adjusted OR = 1.32, 95%CI: 1.13-1.50). WC-d/BMI-d increased with age, with ~40 years representing a critical time point when WC-d surpasses BMI-d, with a sharper incline for males as compared to females. WC-d/BMI-d was significantly associated with all-cause mortality amongst NHANES American adults; thus, measurements of WC and its integration with BMI in this metric should be considered in clinical practice.

Body mass index trajectories among people with obesity and association with mortality: Evidence from a large Israeli database.

OBJECTIVE: Previous studies using longitudinal weight data to characterize obesity are based on populations of limited size and mostly include individuals of all body mass index (BMI) levels, without focusing on weight changes among people with obesity. This study aimed to identify BMI trajectories over 5 years in a large population with obesity, and to determine the trajectories' association with mortality. METHODS: For inclusion, individuals aged 30-74 years at index date (1 January 2013) with continuous membership in Clalit Health Services from 2008 to 2012 were required to have ≥1 BMI measurement per year in ≥3 calendar years during this period, of which at least one was ≥30 kg/m2. Latent class analysis was used to generate BMI trajectories over 5 years (2008-2012). Cox proportional hazards models were used to assess the association between BMI trajectories and all-cause mortality during follow-up (2013-2017). RESULTS: In total, 367,141 individuals met all inclusion criteria. Mean age was 57.2 years; 41% were men. The optimal model was a quadratic model with four classes of BMI clusters. Most individuals (90.0%) had stable high BMI over time. Individuals in this cluster had significantly lower mortality than individuals in the other trajectory clusters (p < 0.01), including clusters of people with dynamic weight trajectories. CONCLUSIONS: The results of the current study show that people with stable high weight had the lowest mortality of all four BMI trajectories identified. These findings help to expand the scientific understanding of the impact that weight trajectories have on health outcomes, while demonstrating the challenges of discerning the cumulative effects of obesity and weight change, and suggest that dynamic historical measures of BMI should be considered when assessing patients' future risk of obesity-related morbidity and mortality, and when choosing a treatment strategy.

Translating clinical trial results into personalized recommendations by considering multiple outcomes and subjective views.

Currently, clinicians rely mostly on population-level treatment effects from RCTs, usually considering the treatment's benefits. This study proposes a process, focused on practical usability, for translating RCT data into personalized treatment recommendations that weighs benefits against harms and integrates subjective perceptions of relative severity. Intensive blood pressure treatment (IBPT) was selected as the test case to demonstrate the suggested process, which was divided into three phases: (1) Prediction models were developed using the Systolic Blood-Pressure Intervention Trial (SPRINT) data for benefits and adverse events of IBPT. The models were externally validated using retrospective Clalit Health Services (CHS) data; (2) Predicted risk reductions and increases from these models were used to create a yes/no IBPT recommendation by calculating a severity-weighted benefit-to-harm ratio; (3) Analysis outputs were summarized in a decision support tool. Based on the individual benefit-to-harm ratios, 62 and 84% of the SPRINT and CHS populations, respectively, would theoretically be recommended IBPT. The original SPRINT trial results of significant decrease in cardiovascular outcomes following IBPT persisted only in the group that received a "yes-treatment" recommendation by the suggested process, while the rate of serious adverse events was slightly higher in the "no-treatment" recommendation group. This process can be used to translate RCT data into individualized recommendations by identifying patients for whom the treatment's benefits outweigh the harms, while considering subjective views of perceived severity of the different outcomes. The proposed approach emphasizes clinical practicality by mimicking physicians' clinical decision-making process and integrating all recommendation outputs into a usable decision support tool.

Patient clusters based on HbA1c trajectories: A step toward individualized medicine in type 2 diabetes.

AIMS: To identify clinically meaningful clusters of patients with similar glycated hemoglobin (HbA1c) trajectories among patients with type 2 diabetes. METHODS: A retrospective cohort study using unsupervised machine learning clustering methodologies to determine clusters of patients with similar longitudinal HbA1c trajectories. Stability of these clusters was assessed and supervised random forest analysis verified the clusters' reproducibility. Clinical relevance of the clusters was assessed through multivariable analysis, comparing differences in risk for a composite outcome (macrovascular and microvascular outcomes, hypoglycemic events, and all-cause mortality) at HbA1c thresholds for each cluster. RESULTS: Among 60,423 patients, three clusters of HbA1c trajectories were generated: stable (n = 45,679), descending (n = 6,084), and ascending (n = 8,660) trends, which were reproduced with 99.8% accuracy using a random forest model. In the clinical relevance assessment, HbA1c levels demonstrated a J-shape association with the risk for outcomes. HbA1c level thresholds for minimizing outcomes' risk differed by cluster: 6.0-6.4% for the stable cluster, <8.0% for the descending cluster, and <9.0 for the ascending cluster. CONCLUSIONS: By applying unsupervised machine learning to longitudinal HbA1c trajectories, we have identified clusters of patients who have distinct risk for diabetes-related complications. These clusters can be the basis for developing individualized models to personalize glycemic targets.

Association Between Achieved Low-Density Lipoprotein Levels and Major Adverse Cardiac Events in Patients With Stable Ischemic Heart Disease Taking Statin Treatment.

IMPORTANCE: International guidelines recommend treatment with statins for patients with preexisting ischemic heart disease to prevent additional cardiovascular events but differ regarding target levels of low-density lipoprotein cholesterol (LDL-C). Trial data on this question are inconclusive and observational data are lacking. OBJECTIVE: To assess the relationship between levels of LDL-C achieved with statin treatment and cardiovascular events in adherent patients with preexisting ischemic heart disease. DESIGN, SETTING, AND PARTICIPANTS: Population-based observational cohort study from 2009 to 2013 using data from a health care organization in Israel covering more than 4.3 million members. Included patients had ischemic heart disease, were aged 30 to 84 years, were treated with statins, and were at least 80% adherent to treatment or, in a sensitivity analysis, at least 50% adherent. Patients with active cancer or metabolic abnormalities were excluded. EXPOSURES: Index LDL-C was defined as the first achieved serum LDL-C measure after at least 1 year of statin treatment, grouped as low (≤70.0 mg/dL), moderate (70.1-100.0 mg/dL), or high (100.1-130.0 mg/dL). MAIN OUTCOMES AND MEASURES: Major adverse cardiac events included acute myocardial infarction, unstable angina, stroke, angioplasty, bypass surgery, or all-cause mortality. The hazard ratio of adverse outcomes was estimated using 2 Cox proportional hazards models with low vs moderate and moderate vs high LDL-C, adjusted for confounders and further tested using propensity score matching analysis. RESULTS: The cohort with at least 80% adherence included 31 619 patients, for whom the mean (SD) age was 67.3 (9.8) years. Of this population, 27% were female and 29% had low, 53% moderate, and 18% high LDL-C when taking statin treatment. Overall, there were 9035 patients who had an adverse outcome during a mean 1.6 years of follow-up (6.7 per 1000 persons per year). The adjusted incidence of adverse outcomes was not different between low and moderate LDL-C (hazard ratio [HR], 1.02; 95% CI, 0.97-1.07; P = .54), but it was lower with moderate vs high LDL-C (HR, 0.89; 95% CI, 0.84-0.94; P < .001). Among 54 884 patients with at least 50% statin adherence, the adjusted HR was 1.06 (95% CI, 1.02-1.10; P = .001) in the low vs moderate groups and 0.87 (95% CI, 0.84-0.91; P = .001) in the moderate vs high groups. CONCLUSIONS AND RELEVANCE: Patients with LDL-C levels of 70 to 100 mg/dL taking statins had lower risk of adverse cardiac outcomes compared with those with LDL-C levels between 100 and 130 mg/dL, but no additional benefit was gained by achieving LDL-C of 70 mg/dL or less. These population-based data do not support treatment guidelines recommending very low target LDL-C levels for all patients with preexisting heart disease.

Towards a subsiding diabetes epidemic: trends from a large population-based study in Israel.

BACKGROUND: With increasing diabetes prevalence worldwide, an impending diabetes "pandemic" has been reported. However, definitions of incident cases and the population at risk remain varied and ambiguous. This study analyzed trends in mortality and screening that contribute to diabetes prevalence and incidence, distinguishing between new incident cases and newly detected cases. METHODS: In an integrated provider-and-payer-system covering 53% of Israel's population, a composite diabetes case-finding algorithm was built using diagnoses, lab tests, and antidiabetic medication purchases from the organization's electronic medical record database. Data were extracted on adult members aged 26+ each year from January 1, 2004 through December 31, 2012. Rates of diabetes prevalence, incidence, screening, and mortality were reported, with incidence rates evaluated among the total, "previously-screened," and "previously-unscreened" at-risk populations. RESULTS: There were 343,554 diabetes cases in 2012 (14.4%) out of 2,379,712 members aged 26+. A consistent but decelerating upward trend in diabetes prevalence was observed from 2004-2012. Annual mortality rates among diabetics decreased from 13.8/1000 to 10.7/1000 (p = 0.0002). Total population incidence rates declined from 13.3/1000 in 2006 to 10.8/1000 in 2012 (p < 0.0001), with similar incidence trends (13.2/1000 to 10.2/1000; p = 0.0007) among previously-screened at-risk members, and a rise in testing rates from 53.0% to 66.7% (p = 0.0004). The previously-unscreened group decreased 28.6%, and the incidence rates within this group remained stable. CONCLUSIONS: The increase in diabetes prevalence is decelerating despite declining mortality and increasing testing rates. A decline in previously-screened incident cases and a shrinking pool of previously-unscreened members suggests that diabetes trends in Israel are moving toward equilibrium, rather than a growing epidemic.

The Israel Diabetes and Cognitive Decline (IDCD) study: Design and baseline characteristics.

BACKGROUND: Type 2 diabetes (T2D) is associated with increased risk of dementia. The prospective longitudinal Israel Diabetes and Cognitive Decline study aims at identifying T2D-related characteristics associated with cognitive decline. METHODS: Subjects are population-based T2D 65+, initially cognitively intact. Medical conditions, blood examinations, and medication use data are since 1998; cognitive, functional, demographic, psychiatric, DNA, and inflammatory marker study assessments were conducted every 18 months. Because the duration of T2D reflects its chronicity and implications, we compared short (0-4.99 years), moderate (5-9.99), and long (10+) duration for the first 897 subjects. RESULTS: The long duration group used more T2D medications, had higher glucose, lower glomerular filtration rate, slower walking speed, and poorer cognitive functioning. Duration was not associated with most medical, blood, urine, and vital characteristics. CONCLUSIONS: Tracking cognition, with face-to-face evaluations, exploiting 15 years of historical detailed computerized, easily accessible, and validated T2D-related characteristics may provide novel insights into T2D-related dementia.

Disparities in pneumococcal and influenza immunization among older adults in Israel: a cross-sectional analysis of socio-demographic barriers to vaccination.

OBJECTIVE: Vaccinations against influenza and pneumonia reduce morbidity and mortality among older adults. We examined vaccination rates among Israel's diverse geriatric population to determine socio-demographic barriers to vaccination. METHODS: This study is a quantitative data analysis with a cross-sectional design, comprising 136,944 patients aged 65 and older enrolled during 2008-2009 in the Maccabi Healthcare Services, one of Israel's four sick funds (preferred provider organizations). We conducted multivariable logistic regression analyses to determine the association between vaccination status and socio-demographic characteristics, including age, gender, rural residency, socio-economic status, region of origin, immigrant status, and Holocaust survivorship. We controlled for potential confounders, including comorbidities, primary care visits and hospitalizations, as well as the physician's gender and region of origin. RESULTS: Overall, vaccination rates were 72% for pneumonia and 59% for influenza. The strongest socio-demographic barriers to vaccination included female gender, rural residency, low socio-economic status, recent immigration, and being from or having a physician from the Former Soviet Union. CONCLUSION: Efforts to further explore barriers to influenza and pneumococcal vaccination and interventions to reduce disparities in vaccination rates should focus on the sub-groups identified in this paper, with careful thought being given as to how to overcome these barriers.

The impact of the Yom Kippur fast on emergency room visits among people with diabetes.

This retrospective review of an Israeli computerized medical data base assessed visits to emergency departments in the 48h following the commencement of the Jewish Yom Kippur fast in the years 1999-2009, and showed that fasting does not seem to be associated with an increased rate of visits.

Identifying frail older people using predictive modeling.

OBJECTIVES: To determine whether a designation of frailty using the Adjusted Clinical Groups-diagnoses based computerized predictive model (ACG Dx-PM) can identify an elderly population who (1) have the clinical characteristics of frailty and (2) are frail as determined by the validated Vulnerable Elders Survey (VES), and to determine the ability of these tools to predict adverse outcomes. STUDY DESIGN: Secondary analysis of administrative and survey data. METHODS: Participants over age 65 years (n = 195) in an outpatient comprehensive geriatric assessment study at an Israeli health maintenance organization (HMO) were screened for frailty using the ACG Dx-PM and VES. Administrative and demographic data were also gathered. RESULTS: Compared with ACG nonfrail patients, ACG frail patients were older and less likely to be married; had a higher rate of falls, incontinence, and need for personal care; and had a poorer quality of life consistent with a clinical picture of frailty. The ACG frailty tag identified a frail population using the VES frailty determination as the accepted standard with moderate success (area under the curve 0.62). Adjusting for sex and functional status in backward logistic regression, the ACG frailty tag predicted hospitalizations (P <.032) and the VES frailty tool predicted emergency department visits (P <.016). CONCLUSIONS: The ACG frailty tag identified an elderly population with clinical characteristics of frailty and performed with moderate success compared with the VES. Both tools predicted adverse outcomes in older HMO members. A combined screening approach for frailty using predictive modeling with a function-based survey deserves further study.

Does low socioeconomic status affect use of nutritional services by pre-diabetes patients?

PURPOSE: This paper's aim is to identify whether community-level socioeconomic status (SES) predicts: screening test for pre-diabetes; actual diagnosis of pre-diabetes; or nutritional counseling. DESIGN/METHODOLOGY/APPROACH: This is an analysis of 1,348,124 insured adults receiving medical care from Maccabi Healthcare Services (MHS) in 107 MHS clinics throughout Israel. The research population comprised 79 percent of the MHS members over 18 years of age in 2004-2006. Area level socioeconomic data were drawn from the Israel Central Bureau of Statistics SES index for every geographical area and each MHS clinic in the study was coded from: - 1.03 to 2.73 (- 1.03 indicating low SES and 2.73 + high SES) according to the SES index for the location. The fasting glucose laboratory test was used for analysis. Pre-diabetes diagnosis was based on a fasting glucose above 100 mg/dl. Nutritional counseling was defined by dietitian visits in the claims database. FINDINGS: The percentage of insured individuals who underwent blood glucose testing during the study increased with age from 67 percent at ages 18-45 to92 percent for age 65 and over. The percentage of individuals diagnosed with pre-diabetes also increased with age, rising from 4 percent in the younger group to 14 percent in those aged 46-65 and to 14-16 percent of 65 and older. The percentage of individuals with pre-diabetes who visited a dietitian was 16-27 percent for those under 65 and 14-17 percent for those over 65 (males and females, respectively). Individuals living in lower socioeconomic areas were less likely to have blood tests. Among tested patients, the prevalence of pre-diabetes was higher in areas of lower SES and their dietitian visits were less frequent. PRACTICAL IMPLICATIONS: In lower SES index areas, there is a need for better identification and treatment of patients. ORIGINALITY/VALUE: The paper shows that a proactive approach is needed both to detect pre-diabetes and to encourage patients to receive nutritional treatment.