Composite Risk Factor Score Research Articles

Effect of Personalized Risk-Reduction Strategies on Cognition and Dementia Risk Profile Among Older Adults

Modifiable risk factors are hypothesized to account for 30% to 40% of dementia; yet, few trials have demonstrated that risk-reduction interventions, especially multidomain, are efficacious. To determine if a personalized, multidomain risk reduction intervention improves cognition and dementia risk profile among older adults. The Systematic Multi-Domain Alzheimer Risk Reduction Trial was a randomized clinical trial with a 2-year personalized, risk-reduction intervention. A total of 172 adults at elevated risk for dementia (age 70-89 years and with ≥2 of 8 targeted risk factors) were recruited from primary care clinics associated with Kaiser Permanente Washington. Data were collected from August 2018 to August 2022 and analyzed from October 2022 to September 2023. Participants were randomly assigned to the intervention (personalized risk-reduction goals with health coaching and nurse visits) or to a health education control. The primary outcome was change in a composite modified Neuropsychological Test Battery; preplanned secondary outcomes were change in risk factors and quality of life (QOL). Outcomes were assessed at baseline and 6, 12, 18, and 24 months. Linear mixed models were used to compare, by intention to treat, average treatment effects (ATEs) from baseline over follow-up. The intervention and outcomes were initially in person but then, due to onset of the COVID-19 pandemic, were remote. The 172 total participants had a mean (SD) age of 75.7 (4.8) years, and 108 (62.8%) were women. After 2 years, compared with the 90 participants in the control group, the 82 participants assigned to intervention demonstrated larger improvements in the composite cognitive score (ATE of SD, 0.14; 95% CI, 0.03-0.25; P = .02; a 74% improvement compared with the change in the control group), better composite risk factor score (ATE of SD, 0.11; 95% CI, 0.01-0.20; P = .03), and improved QOL (ATE, 0.81 points; 95% CI, -0.21 to 1.84; P = .12). There were no between-group differences in serious adverse events (24 in the intervention group and 23 in the control group; P = .59), but the intervention group had greater treatment-related adverse events such as musculoskeletal pain (14 in the intervention group vs 0 in the control group; P < .001). In this randomized clinical trial, a 2-year, personalized, multidomain intervention led to modest improvements in cognition, dementia risk factors, and QOL. Modifiable risk-reduction strategies should be considered for older adults at risk for dementia. ClinicalTrials.gov Identifier: NCT03683394.

One size does not fit all - translating absolute accelerometry to relative individual physical activity intensity for health

Abstract Funding Acknowledgements Type of funding sources: Foundation. Main funding source(s): The main funding body of The Swedish CArdioPulmonary bioImage Study (SCAPIS) is theSwedish Heart-Lung Foundation. The study is also funded by the Knut and Alice Wallenberg Foundation, the Swedish Research Council and VINNOVA (Sweden’s Innovation agency) the University of Gothenburg and Sahlgrenska University Hospital, Karolinska Institutet and Stockholm county council, Linköping University and University Hospital, Lund University and Skåne University Hospital, Umeå University and University Hospital, Uppsala University and University Hospital. Introduction Physical activity intensity can be expressed in either absolute (e.g. brisk walking or metabolic equivalents) or relative terms (e.g. proportion of maximal oxygen consumption or perceived exertion) (1). Although intervention studies typically use relative intensity for exercise prescription, large scale observational studies measuring physical activity with accelerometers always use absolute intensity. The association between relative physical activity intensity and cardiometabolic risk factors has not been studied using accelerometry previously. Purpose To compare absolute and relative measures of physical activity intensity in terms of physical activity level and associations with cardiovascular risk factors among individuals with different fitness level. Methods A subsample of the Swedish CArdioPulmonary bioImage Study (SCAPIS), in total 4234 men and women aged 50-64, was analysed (2). Physical activity was measured by accelerometers and the raw data processed with the 10 Hz frequency extended method (FEM) to get a more accurate measure of physical activity intensity compared to previous methods (3). Maximal oxygen consumption (fitness) was estimated by a submaximal ergometer test. Waist to hip ratio, systolic blood pressure, glycated haemoglobin (HBA1c) and high-density lipoprotein to total cholesterol ratio were combined into a composite cardiometabolic risk factor score. Partial least squares regression was used to investigate the associations of absolute and relative physical activity intensity with fitness as well as the composite score. The sample was divided into tertiles of fitness for stratified analyses. Results Overall, there was an association between physical activity at absolute moderate intensity and above, and the health outcomes. Yet, the main associations were found in the absolute moderate intensity range for the low fitness group and in the absolute vigorous intensity range for the high fitness group. When considering relative intensity however, all the main associations started in the upper part of the moderate intensity range and peaked in the vigorous intensity range (Figure 1). In addition, when comparing absolute and relative cut-offs for moderate intensity, absolute moderate intensity was too low for 95% of individuals in the sample (Figure 2). When using absolute intensity, 99% of individuals reached the general guidelines of 150 minutes of moderate-to-vigorous physical activity per week, while only 21% reached the guidelines based on relative intensity. Conclusions Health benefits of absolute intensity are misleading for most individuals in this sample and absolute measures of physical activity overestimate time spent at moderate intensity and above. Relative intensity should be used when interpreting accelerometer measured physical activity and when communicating health promoting physical activity.

Dynamic Regional Brain Atrophy Rates in the First Year After Ischemic Stroke.

Brain atrophy can be regarded as an end-organ effect of cumulative cardiovascular risk factors. Accelerated brain atrophy is described following ischemic stroke, but it is not known whether atrophy rates vary over the poststroke period. Examining rates of brain atrophy allows the identification of potential therapeutic windows for interventions to prevent poststroke brain atrophy. We charted total and regional brain volume and cortical thickness trajectories, comparing atrophy rates over 2 time periods in the first year after ischemic stroke: within 3 months (early period) and between 3 and 12 months (later period). Patients with first-ever or recurrent ischemic stroke were recruited from 3 Melbourne hospitals at 1 of 2 poststroke time points: within 6 weeks (baseline) or 3 months. Whole-brain 3T magnetic resonance imaging was performed at 3 time points: baseline, 3 months, and 12 months. Eighty-six stroke participants completed testing at baseline; 125 at 3 months (76 baseline follow-up plus 49 delayed recruitment); and 113 participants at 12 months. Their data were compared with 40 healthy control participants with identical testing. We examined 5 brain measures: hippocampal volume, thalamic volume, total brain and hemispheric brain volume, and cortical thickness. We tested whether brain atrophy rates differed between time points and groups. A linear mixed-effect model was used to compare brain structural changes, including age, sex, years of education, a composite cerebrovascular risk factor score, and total intracranial volume as covariates. Atrophy rates were greater in stroke than control participants. Ipsilesional hemispheric, hippocampal, and thalamic atrophy rates were 2 to 4 times greater in the early versus later period. Regional atrophy rates vary over the first year after stroke. Rapid brain volume loss in the first 3 months after stroke may represent a potential window for intervention. Registration: URL: https://www.clinicaltrials.gov. Unique identifier: NCT02205424.

Muscle strength in youth and cardiovascular risk in young adulthood (the European Youth Heart Study)

BackgroundWhether muscle strength in youth is related to cardiovascular risk later in life independent of cardiorespiratory fitness is unclear.MethodsWe examined the independent association of isometric muscle strength in youth with...

Spatial Modelling of Cardiovascular Mortality Patterns: A GIS based Study of Rural Bist Doab Region (Punjab, India)

Population health is a major area of concern for researchers in developing nations with large demographic base. Most of the geographical studies done in India have focused on modelling communicable diseases only. The importance of constructing spatial models for non-communicable diseases has risen tremendously in recent times due to their ever-increasing burden. The present paper attempts to create a regression model of cardiovascular mortality in Bist Doab region of Punjab (India) . A composite risk factor score was calculated block-wise and was used as an explanatory variable for the observed spatial patterns of cardiovascular mortality. The regression modelling was done using Ordinary Least Squares method of Spatial Analyst tool in ArcGIS 9.3. The resultant regression coefficient was 0.44 and the model was capable of explaining nearly 35% of variation in the observed spatial patterns of cardiovascular deaths. The model was statistically significant at 0.05 level. Given the complex aetiology of cardiovascular diseases and the lack of block-wise data on several key risk factors, it was concluded that this model displayed considerably good performance. Finally, Moran’s I test was used to check spatial autocorrelation to ensure that the residuals are not spatially autocorrelated.

Body fat, abdominal fat and body fat distribution related to cardiovascular risk factors in prepubertal children

We analysed whether total body fat (TBF), abdominal fat and body fat distribution are associated with higher composite risk factor scores for cardiovascular disease (CVD) in young children. Cross-sectional study of 238 children aged 8-11 years. TBF and abdominal fat mass (AFM) were measured by Dual-Energy X-Ray Absorptiometry. TBF was expressed as a percentage of body weight (BF%). Body fat distribution was calculated as AFM/TBF. Maximal oxygen uptake (VO(2PEAK) ), systolic and diastolic blood pressure (SBP, DBP), and resting heart rate (RHR) were measured. Mean arterial pressure (MAP) and pulse pressure (PP) were calculated. Left atrial diameter (LA) was measured, and left ventricular mass (LVM) and relative wall thickness (RWT) were calculated. Z-scores were calculated. Sum of z-scores for SBP, DBP, MAP, PP, RHR, LVM, LA, RWT and -VO(2PEAK) was calculated in boys and girls, separately, and used as composite risk factor score. Pearson correlations between ln BF%, ln AFM and AFM/TBF versus composite risk factor score for boys were r = 0.56, r = 0.59 and r = 0.48, all p < 0.001, and for girls r = 0.45, r = 0.50 and r = 0.48, all p < 0.001. Total body fat, abdominal fat and body fat distribution were all associated with higher composite risk factor scores for CVD in young children.

Aerobic fitness related to cardiovascular risk factors in young children

Low aerobic fitness (maximum oxygen uptake (VO(2 PEAK))) is predictive for poor health in adults. In a cross-sectional study, we assessed if VO(2 PEAK) is related to a composite risk factor score for cardiovascular disease (CVD) in 243 children (136 boys and 107 girls) aged 8 to 11 years. VO(2 PEAK) was assessed by indirect calorimetry during a maximal exercise test and scaled by body mass (milliliters per minute per kilogram). Total body fat mass (TBF) and abdominal fat mass (AFM) were measured by Dual-energy X-ray absorptiometry. Total body fat was expressed as a percentage of total body mass (BF%) and body fat distribution as AFM/TBF. Systolic and diastolic blood pressure (SDP and DBP) and resting heart rate (RHR) were measured. The mean artery pressure (MAP) and pulse pressure (PP) were calculated. Echocardiography, 2D-guided M-mode, was performed. Left atrial diameter (LA) was measured and left ventricular mass (LVM) and relative wall thickness (RWT) were calculated. Z scores (value for the individual - mean value for group)/SD were calculated by sex. The sum of z scores for DBP, SDP, PP, MAP, RHR, LVM, LA, RWT, BF%, AFM and AFM/TBF were calculated in boys and girls, separately, and used as composite risk factor score for CVD. Pearson correlation revealed significant associations between VO(2 PEAK) and composite risk factor score in both boys (r = -0.48 P < 0.05) and in girls (r = -0.42, P < 0.05). One-way ANOVA analysis indicated significant differences in composite risk factor score between the different quartiles of VO(2 PEAK) (P < 0.001); thus, higher VO(2 PEAK) was associated with lower composite risk factor score for CVD. In conclusion, low VO(2 PEAK) is associated with an elevated composite risk factor score for CVD in both young boys and girls.

Cycling to School and Cardiovascular Risk Factors: A Longitudinal Study

Cycling to school may potentially increase physical activity level in sedentary children. Transport to school occur twice a day and could improve cardiovascular health in children. Commuter cycling is associated with lower mortality and cardiovascular disease rate in adults, but limited evidence exists in children. Participants were 334 children (age 9.7 ± 0.5 years) who were followed up 6 years later. Mode of travel to school was investigated by questionnaire. Cardiovascular (CVD) risk factors were compared by mode of travel to school both at baseline and at follow up and for subjects who changed mode of transportation. No difference was found between walkers and passive travelers, and these groups were merged in the analysis. A consistent pattern of better CVD risk factor profile in commuter cyclists compared with children using other means of transport was found. Participants, who did not cycle to school at baseline, and who had changed to cycling at follow up, were fitter, had better cholesterol/HDL ratio, better glucose metabolism, and a lower composite CVD risk factor score than those who did not cycle at either time point. Cycling to school may contribute to a better cardiovascular risk factor profile in young people.

The association between physical activity, physical fitness and development of metabolic disorders

Cardiovascular (CVD) risk factors have been shown to cluster in some children. This has been shown in children from the age of nine years, but recently we found no clustering in six-year old children. It is uncertain when clustering develops and which parameters are related to the development of clustered CVD risk. A longitudinal study including 484 children aged six years. Three years later, 434 children participated in a follow-up. The main outcome was clustering of five CVD risk factors: homeostasis assessment insulin resistance (HOMA), total cholesterol:HDL ratio, triglyceride (TG), systolic blood pressure and sum of four skinfolds. Independent variables were physical activity and cardiorespiratory fitness. CVD risk factors were independently distributed in the six-year-olds, and there was no association between composite risk factor score and physical fitness or activity even if there were obese and unfit children in the population. Clustering of CVD risk factors was found at the age of nine years, and the observed number with three or more CVD risk factors was 3.33 (95% CI: 1.41-7.87) times higher than expected if risk factors had been independently distributed. At the age of nine years, the lowest quartile of fitness had 34.9 (95% CI: 8.0-152.5) times higher risk of having clustered risk than the most fit quartile. Clustering of CVD risk factors developed between the age of six and nine years. At nine years of age clustered CVD risk was highly associated with low fitness level.

Lack of physical activity in young children is related to higher composite risk factor score for cardiovascular disease

This study evaluates whether accelerometer-measured physical activity is related to higher composite risk factor scores for cardiovascular disease (CVD) in children. Cross-sectional study that included 223 children aged 7.9-11.1 years (boys n = 123, girls n = 100). Daily physical activity was assessed by accelerometers for 4 days. Body fat was quantified by dual X-ray absorptiometry. Maximal oxygen uptake was measured during a maximal exercise test. Resting heart rate and blood pressure were measured. Z-scores [(value for the individual - mean value for group)/SD] were calculated for each variable, and the sum of different risk factor z-scores used as an index of composite risk factors score for CVD. Partial correlations, from General Linear Model, between moderate to vigorous physical activity (MVPA), vigorous physical activity (VPA) and general physical activity versus index of composite risk factor score were in boys 0.29, 0.33 and 0.30 (all p < 0.05), respectively. The corresponding correlations in girls were -0.28, -0.32 (both p < 0.05) and -0.18 (NS), respectively. Low amounts of MVPA and VPA were related to higher composite risk factor scores for CVD in children aged 8-11 years.

Low Muscle Fitness Is Associated with Metabolic Risk in Youth

To examine the independent associations of muscle fitness and cardiorespiratory fitness with clustered metabolic risk in youth. In 2005-2006, a cohort of 9- and 15-yr-olds (N = 2818) was randomly selected from all regions of Norway. The participation rate was 89% and 74% among the 9-and 15-yr-olds, respectively. We assessed muscular strength by measuring explosive, isometric, and endurance strength. Cardiorespiratory fitness was measured directly as peak oxygen uptake during a cycle ergometry test. Risk factors included in the composite risk factor score (sum of z-scores) were systolic blood pressure, triglyceride, high-density lipoprotein cholesterol, insulin resistance, and waist circumference. Muscle fitness was negatively associated with clustered metabolic risk, independent of cardiorespiratory fitness, and after adjustment for age, sex, and pubertal stage (beta = -0.112, P < 0.001). Independent of muscle fitness, an inverse association was found between cardiorespiratory fitness and clustered metabolic risk (beta = -0.337, P < 0.001). Moreover, the odds ratios for having clustered risk in the least fit quartile compared with the most fit quartile were 7.2 (95% confidence interval (CI)=4.3-12.0) and 17.3 (95% CI = 9.2-32.7) for muscle fitness and cardiorespiratory fitness, respectively. Our results show that muscle fitness and cardiorespiratory fitness are independently associated with metabolic risk in youth.

Physical activity and clustered cardiovascular risk in children: a cross-sectional study (The European Youth Heart Study)

Atherosclerosis develops from early childhood; physical activity could positively affect this process. This study's aim was to assess the associations of objectively measured physical activity with clustering of cardiovascular disease risk factors in children and derive guidelines on the basis of this analysis. We did a cross-sectional study of 1732 randomly selected 9-year-old and 15-year-old school children from Denmark, Estonia, and Portugal. Risk factors included in the composite risk factor score (mean of Z scores) were systolic blood pressure, triglyceride, total cholesterol/HDL ratio, insulin resistance, sum of four skinfolds, and aerobic fitness. Individuals with a risk score above 1 SD of the composite variable were defined as being at risk. Physical activity was assessed by accelerometry. Odds ratios for having clustered risk for ascending quintiles of physical activity (counts per min; cpm) were 3.29 (95% CI 1.96-5.52), 3.13 (1.87-5.25), 2.51 (1.47-4.26), and 2.03 (1.18-3.50), respectively, compared with the most active quintile. The first to the third quintile of physical activity had a raised risk in all analyses. The mean time spent above 2000 cpm in the fourth quintile was 116 min per day in 9-year-old and 88 min per day in 15-year-old children. Physical activity levels should be higher than the current international guidelines of at least 1 h per day of physical activity of at least moderate intensity to prevent clustering of cardiovascular disease risk factors.

Aerobic fitness, body mass index, and CVD risk factors among adolescents: the Québec family study

The purpose of this study was to examine the association of body mass index (BMI) and aerobic fitness on cardiovascular disease (CVD) risk factors in adolescents. The sample included 416 boys and 345 girls 9-18 y of age from the Québec Family Study. Participants were cross-tabulated into four groups using a median split of age-adjusted physical working capacity (PWC) and body mass index (BMI). Group differences in age-adjusted CVD risk factors (blood pressures, fasting total cholesterol (CHOL), LDL -C, HDL-C, HDL/CHOL, triglycerides, glucose, and a composite risk factor score) were examined by two-way ANOVA. Several CVD risk factors showed significant main effects for PWC, BMI and/or the PWC by BMI interaction. In general, low fit males and females had higher blood lipids and glucose compared to their high fit counterparts within BMI categories although none of the differences reached statistical significance. The high fit/low BMI group showed the best CVD risk factor profile while the low fit/high BMI showed a poorer profile as evidenced by several significant differences between these two groups. Other significant differences occurred for various risk factors between groups. Both aerobic fitness and BMI show an independent association with CVD risk factors in adolescents.

Cardiorespiratory Fitness, Body Mass Index And Cardiovascular Disease Risk Factors Among Children And Adolescents

PURPOSE The purpose of this study was to examine differences in cardiovascular disease (CVD) risk factors across four cross-tabulated groups of cardiorespiratory fitness and body mass index in adolescents. METHODS The sample included 296 boys and 188 girls 8–18 years of age participating in the Aerobics Center Longitudinal Study. Participants were cross-tabulated into four groups using a median split of age-adjusted treadmill time to exhaustion (TM) and body mass index (BMI). Group differences in CVD risk factors (systolic blood pressure (SBP), diastolic blood pressure (DBP), mean arterial pressure (MAP), fasting total cholesterol (CHOL), low-density lipoprotein-cholesterol (LDL -C), high-density lipoprotein-cholesterol (HDL-C), TC: HDL-C, triglycerides, glucose, and a composite risk factor score) were examined by ANCOVA, controlling for age. RESULTS In males, significant differences across groups were apparent for SBP, MAP, CHOL, LDL-C, TC:HDL-C and the composite risk factor score (p <0.05). In females, the only significant difference across groups involved TG (p <0.05). A trend for significance was also observed for DBP and TG in males (p = 0.09 to 0.11) and DBP, MAP, HDL-C, and the composite risk factor score in females (p = 0.14 to 0.16). In general, males and females in the low BMI group, either fit or unfit, had lower blood pressure and blood lipid values than those in the high BMI group. In both sexes, the high BMI/low fit group had the highest (most adverse) composite risk factor score. CONCLUSIONS This study utilized a unique approach to examining the interaction of fitness and fatness on CVD risk factors in children and adolescents. The results provide some evidence for the consideration of both variables when interpreting CVD risk factors in young people. Supported by National Institutes of Health Grant AG06945

Relationship between adolescent fitness and fatness and cardiovascular disease risk factors in adulthood: The Aerobics Center Longitudinal Study (ACLS)

To examine the relationship between cardiorespiratory fitness and body fatness during adolescence and cardiovascular disease (CVD) risk factors in adulthood. The sample was 48 participants from the Aerobics Center Longitudinal Study (ACLS) who had one clinical visit during adolescence (mean age = 15.8 years) and a follow-up visit during adulthood (mean age = 26.6 years). Values for treadmill time (TM), body fatness (body mass index [BMI], percent body fat [%BF], and waist circumference [WC]), traditional CVD risk factors (blood pressure [BP], fasting total cholesterol [TC], high-density lipoprotein cholesterol [HDL-C], triglycerides [TG], and glucose), and a composite metabolic syndrome risk factor score were adjusted for age and sex. The relationships between adolescent TM and body fatness variables and adult CVD risk factors were examined by partial correlations, controlling for length of follow-up (mean = 11 years). The correlation between changes in TM and body fatness (DeltaTM and Deltabody fatness, respectively) and changes in CVD risk factors between adolescence and adulthood (DeltaCVD risk factors) were also examined. Adolescent cardiorespiratory fitness and body fatness variables also were separated into 2 categories based on the median split: low (below median) and high (above median). TM and body fatness variables showed moderate stability between adolescence and adulthood ( r = 0.44-0.78). Adolescent TM and DeltaTM showed moderate correlations with adult body fatness indicators (BMI, WC, and %BF, r = -0.34 to -0.47) and Deltabody fatness ( r = -0.24 to -0.46), respectively. Adolescent TM was not significantly related to traditional CVD risk factors in adulthood. Adolescent WC was significantly related to adult BP ( r = 0.33 to 0.45), and body fatness variables during adolescence were significantly related to adult TM ( r = -0.32 to -0.44). The DeltaWC was significantly related to DeltaTM ( r = -0.46) and DeltaHDL-C ( r = -0.51), and DeltaBMI was significantly related to DeltaBP ( r = 0.45) and DeltaHDL-C ( r = -0.34). Subjects with a high TM during adolescence showed lower levels of body fatness as adults, and those with high levels of WC during adolescence showed higher BP during adulthood. The results indicate a significant relationship between adolescent cardiorespiratory fitness and adult body fatness and a lack of an association between adolescent cardiorespiratory fitness and adult cholesterol, BP, and glucose levels. Adolescent body fatness is moderately related to selected adult CVD risk factors.

Stability of variables associated with the metabolic syndrome from adolescence to adulthood: The Aerobics Center Longitudinal Study

The purpose of the study was to examine the stability of variables associated with the metabolic syndrome from adolescence to adulthood. The sample included 48 subjects from the Aerobics Center Longitudinal Study who had one clinical visit during adolescence (mean age = 15.8 years) and a follow-up visit during adulthood (mean age = 26.6 years). The following variables were considered: treadmill time to exhaustion (TM), body mass index (BMI), waist circumference (WC), percent body fat (%BF), total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), TC:HDL-C, triglycerides (TG), glucose (GLU), and systolic (SBP), diastolic (DBP), and mean (MAP) blood pressure. A composite risk factor score using variables consistent with the WHO and ATP III definition of the metabolic syndrome (WC, HDL-C, TG, MAP, and GLU) was calculated. Tracking coefficients were computed as partial correlations, controlling for length of follow-up (mean = 11 years). Tracking coefficients (r values) were moderate for all variables (TM, 0.53; BMI, 0.64; WC; 0.79;%BF, 0.44; TC, 0.62; HDL-C, 0.60; TG, 0.54; TC:HDL-C, 0.78; SBP, 0.45; and MAP, 0.41), except GLU (0.26) and DBP (0.21). The composite risk factor score also tracked moderately well (0.56) from adolescence into adulthood. The results support previous findings that variables associated with the metabolic syndrome track moderately well from adolescence to adulthood. The findings support the prevention and treatment of obesity, atherosclerosis, type 2 diabetes, and the metabolic syndrome during childhood and adolescence.

Algorithms for resource allocation of substance abuse prevention funds based on social indicators: a case study on state of Florida--Part 3.

The purpose of Part 3 is to develop an algorithm for an equitable distribution of state prevention funds to its substate jurisdictions based on the need for prevention services. In this series, the need for prevention services is measured in terms of the existing social indicators observed at the county level. In order to establish a conceptual link as well as the empirical relevance of the selected social indicators as proxy measurements of the estimated need for prevention at the county level, we have employed both concurrent and construct validity tests using the following three constructs as the criterion variables in a multiple regressing setting: 1) county-based composite drug use index score (COMDRUG) measured via the statewide drug survey; 2) county-based proportions of prevention target populations using the conceptual definition advanced by the Institute of Medicine (IOM); and 3) the composite risk factor score (COMRISK) assembled from a list of twenty-two risk and protective factors observed for each county. These constructs were identified previously in Parts 1 and 2. While employing eight social indicators to estimate the overall prevention needs observed at the county level, the social indicators thus selected were able to explain 69 percent of the variations in COMDRUG, 68 percent of the variation in the proportions of students in need of prevention services using IOM definition, and 60 percent of the variation in COMRISK. Following successful validations of the social indicators as viable media with which to estimate county-based prevention needs, the ensuing multiple regression equation is, then, used to build a resource allocation model by determining the proportion of each county's share of the total statewide COMDRUG-predicted from the social indicators and, then, by weighting the latter proportion by the population size of each county under age eighteen. In this way, we have devised county-based Prevention Needs Index (PNI) scores based solely on social indicators. Finally, the county's share of PNI score is computed as a proportion of to the total statewide PNI score. Following this line of algorithm for resource allocation, we were able to develop yet another resource allocation model solely based on social indicators without the benefits of survey data. Comparing the funding results originating from four resource allocation models (i.e., COMDRUG, IOM Definition, COMRISK, and Social Indicators), it has been learned that there is a remarkable similarity from one funding level to another. Since all four schedules of county-based prevention funding levels have shown very high intercorrelations with a range from .9862 to .9993, it has been determined that these schedules are measuring essentially either the same domain or latent domains that are functionally equivalent to one another. Accordingly, no preference is made among the resource allocation models suggested, although it is suggested that the final decision on the level of funding must be based on the selection of the schedule for resource allocation rather than the suggested amount or level of funding computed for each county.

Algorithms for Resource Allocation of Substance Abuse Prevention Funds Based on the Estimated Need: A Case Study on State of Florida—Part 1

The purposes of Parts 1-3 of this article is to develop a framework for county-based prevention resource allocation algorithms based on the aggregated need for substance abuse prevention services estimated at the county level. The development of these algorithms is founded upon two databases: statewide student drug survey and a set of social indicators routinely collected and published by various agencies of the state of Florida. The resource allocation models are devised by developing several indices of prevention needs that are conceptualized in terms of: 1) county-based composite drug use index (COMDRUG), 2) the definitions of prevention target populations as envisioned by the Institute of Medicine (IOM), 3) composite risk-factor index score, and 4) a set of social indicators that are empirically related to COMDRUG observed at the county level. The first three models are based on the prevention needs estimated from the statewide student survey on substance abuse. The social indicator model, however, is presented as an alternative resource allocation model which may be used in lieu of or in the absence of statewide survey. The resource allocation algorithms found on these four conceptualizations are thought to be more equitable and appropriate to the prevention needs of various communities than may be contrived otherwise. Due to a significant amount of information leading to the development of these models, Part 1 of this series is devoted to the following three topics: 1) sampling method used, 2) poststratification weighting methods used to estimate county-based COMDRUG, and 3) the development of resource allocation models based on COMDRUG and the IOM definitions of prevention target populations.

Risk factors for coronary heart disease among firefighters in Cincinnati.

Since 1984, coronary heart disease (CHD) risk factors have been prospectively assessed among Cincinnati firefighters free of CHD at study entry. In total, 806 firemen with a mean age of 37 years at entry have been followed for 6.4 years on average, contributing 5,173 person-years. CHD risk factors were measured every 1-4 years and included weight, blood pressure, cigarette use, fasting glucose, and lipid profile. When, in aggregate, these CHD risk factors were found to be in a high risk range, suggestions were made serially to reduce CHD risk. A composite high CHD risk factor score led to an exercise electrocardiogram (ECG) with thallium scan, which was repeated every 1-4 years. Myocardial infarction (MI) occurred in 7 men, with 1.35 MIs/1,000 man-years; 15 others developed CHD, with 4.25 MI + CHD/1,000 man-years. The firefighters' MI event rate (1.35 MIs/1,000 man-years) was lower (but not significantly, p > 0.1) than that for employed 30- to 39-year-old men free of CHD at entry (2.07/1,000 man years), who had an average follow-up of 5.4 years in the NHANES I study. At study entry, the 22 men who later developed CHD (vs. the 784 who did not develop CHD) were older (p = .0001), smoked more (p = .0001), and were more likely to have first degree relatives with CHD before age 60 (p = .017). After covariance adjusting for age, race, and Quetelet index, men with CHD (vs. those CHD free) had higher systolic and diastolic blood pressures (p = .0001, .0001), higher LDL cholesterol (p = .04), higher total cholesterol (p = .014), and higher triglycerides (p = .03). By Poisson regression, significant independent predictors of CHD events were age (p = .0007), cigarette smoking (p = .001), diastolic blood pressure (p = .056), and family history of CHD at age < or = 60 (p = .048). Men who later developed CHD and those without CHD did not differ by history of smoke inhalation (p > 0.3). The calculated ratio of savings to cost attributable to the program per year was 5.9/1 ($258,500/$43,600). In the current study, firefighting as an occupation was not associated with increased CHD event rates. CHD events that did develop were, for the most part, associated with modifiable CHD risk factors.

Changes in population cholesterol concentrations and other cardiovascular risk factor levels after five years of the non-communicable disease intervention programme in Mauritius

To study changes in the prevalence of risk factors for cardiovascular disease after a five year population-wide intervention programme promoting a healthy lifestyle in a developing country. Cross sectional cluster surveys in 1987 and 1992. Methodology included a two hour 75 g oral glucose tolerance test, measurement of body mass index, waist:hip ratio, basal lipid concentrations, and blood pressure; and a lifestyle questionnaire. Mauritius, in the Indian Ocean. All adults aged 25-74 years residing in geographically defined clusters. Age standardised prevalence of categorical disease and risk factor conditions and mean levels and frequency distributions of continuous variables. Response rates were 86.2% (5080/5892) in 1987 and 89.5% (5162/5770) in 1992. Significant decreases were found in the prevalence of hypertension (15.0% to 12.1% in men and 12.4% to 10.9% in women); cigarette smoking (58.2% to 47.2% and 6.9% to 3.7% respectively); and heavy alcohol consumption (38.2% to 14.4% and 2.6% to 0.6% respectively). Moderate leisure physical activity increased from 16.9% to 22.1% in men and from 1.3% to 2.7% in women. Mean population serum total cholesterol concentration fell appreciably from 5.5 mmol/l to 4.7 mmol/l (P < 0.001). The prevalence of overweight or obesity increased, and the rates of glucose intolerance changed little. The population frequency distributions of blood pressure, serum lipid concentration, and a composite risk factor score shifted advantageously. Lifestyle intervention projects can be implemented and have positive effects in developing countries. A pronounced improvement in the population lipid profile in Mauritius was probably related to a change in the saturated fat content of a widely used cooking oil.