Introduction to results on Seasonal Changes in Cholesterol

Transcription

1 Introduction to results on Seasonal Changes in Cholesterol Ed Stanek - May 2001 Introduction This report summarizes results relative to seasonal changes in cholesterol, and provides alternative results to a report based on winter-summer differences in cholesterol (sea01d01.doc). We report descriptive data on the subjects in the seasonal cholesterol study by gender, and within gender, by age (< 50 or 50+). We also include results for variables corresponding to BMI, waist, hip and waist:hip ratio measures. Hip and waist measures were made at the start and end of the study (quarters 1 and 5). BMI measures were made each quarter. The results presented here are based on a different subset of study subjects than the results presented in sea01d01.doc. In the document sea01d01.doc, only n=478 subjects were included, representing all subjects with at least one summer and one winter cholesterol measure and at least 4 or more cholesterol measures. Summer and winter are defined using the common season definition (winter=dec 21-March 20; summer=june 21-Sept. 20). In this document, we present results on a basic subset of n=517 subjects, all of whom have 4 or more cholesterol measures. In addition, we compare this subset of subjects with the basic seasons subjects (n=641) and the more limited set of subjects (n=478) that include a minimum of one summer and one winter measure. For all analyses considered here, we excluded data for ID=77, quarter=5 due to an apparent error in ID coding. Development of the Basic Analysis Data Set and Review of Related Previous Analyses Over time, various definitions of the study subjects have been used to define the Seasons Study cohort. Merriam et al (1999) present baseline results on a total of n=608 subjects. Using Merriam s definition, eligible subjects were between 20 and 70 years of age, literate in English, give an informed consent, and plan to remain in the area for at least 1 year. Also, subjects could not be on pharmacological therapy to lower lipids, be currently on a lipid-lowering or weight-control diet, or have any of several other exclusion factors. Using these criteria, the baseline data set for the seasons study contains 641 subjects, (310 females and 331 males). The descriptive paper by Merriam was written prior to the completion of the data cleaning, and hence the numbers differ. Several analyses have been conducted whose purpose was to understand seasonal variability in cholesterol. The first analysis was described in a series of reports in December (from 12/13/00-12/15/00), This analysis used a subset of n=478 study subjects who had at least 4 cholesterol measures, and at least one measure in summer and one measure in the winter, using the common season definition (winter=dec 21-March 20; summer=june 21-Sept. 20). These analyses were constructed using a basic analysis quarterly data set named SEAS1.SD2 (containing 2340 records). This data set included quarterly data on the n=478 subjects that met the eligibility criteria. 1

2 The analyses that were conducted resulted in the construction of several basic descriptive tables. These tables were as follows: Results in sea00d6.doc (and summarized in sea01d01.doc) Table 1. Basic Demographic and Physical Characteristics of the Seasonal Study Cohort. Programs: sne00p20.sas Data sets: seas1.sd2 and ydcs3.sd2 Table 2. Average cholesterol levels by age group and gender in the seasonal study cohort (n=.478) Programs: sne00p23.sas Data sets: seas1.sd2 Table 2b. Description of BMI, Waist, hip and waist:hip ratio by age and gender- Seasonal study cohort, Worcester, MA (n=478) Programs: sne01p02.sas Table 3. Intake, activity, and light exposure by age and gender- Seasonal study cohort, Worcester, MA (n=478) Programs: sne00p22.sas, sne01p02.sas Data sets: seas1.sd2 Table in sea01d01table3.xls An extensive write-up and analysis of (Winter-summer) difference in cholesterol is provided for the n=478 subjects with both a summer and winter cholesterol measure in sea01d01.doc. Many additional tables are presented in that document. Finally, some correlations between changes in cholesterol, and other variables were explored in sea01d02.doc. Relationships of the Study Cohorts In this report, we describe the relationship between the n=641 subjects entering the seasons study, and the n=517 subjects that reported 4 or more cholesterol measurements. We also describe the demographic variables for this cohort of n=517 subjects. For reference, we note that approximately 5000 subjects were contacted and asked if they would like to volunteer to participate in the study. These subjects came from the Fallon Clinic, and from additional efforts to supplement the number of non-white subjects. Of these subjects initially approached, a total of 1254 verbally met the study entry criteria, and agreed to attend an initial clinic visit. However, although initially agreeing to participate, a total of 641 subjects actually attended the first visit and completed the baseline interview (ie. Enrolled in the study). Among the subject indicating that they would participate in the study, a larger portion of male subjects (54.3%) enrolled in the study than female subjects (48.1%). The Seasons study protocol was demanding on participants time. The study protocol included five quarterly cholesterol measures and accompanying data collection. We operationally define a subject as completing the protocol if at least four quarterly cholesterol measures were made. Using this definition, a total of n=517 subjects (80.7%) completed the study. A comparison of these subjects with others enrolling in the study is given in Table 1. 2

3 Table 1a. Comparison of 641 Seasons subjects with 517 Seasons subjects with 4 or more more cholesterol values for selected demographic variables Less than 4 chol 4+ Chol p-value n=124 n=517 Mean (std) Mean (std) Age 41.0 (11.0) 48.6 (12.1) < Waist (cm) 89.6 (12.9) 89.7 (90.1) 0.96 Hips (cm) (12.0) (10.4) Waist:hips (0.086) (0.092) BMI 27.4 (5.52) 27.3 (5.39) Percent Freq (% of Total) Freq (% of Total) n with 4+ Chol n=124 n=517 Female 58 (46.8) 252 (48.7) % BMI n=123 n= kg/m2 47 (38.2) 186 (36.0) % kg/m2 46 (37.4) 207 (40.0) % kg/m2 30 (24.4) 124 (24.0) % Ethnicity n=118 n= White 89 (75.4) 444 (87.8) % Hispanic 22 (18.6) 37 (7.3) % Other 7 (5.9) 25 (4.9) % Education n=123 n= High School or less 29 (23.6) 129 (25.1) % Post-high School 55 (44.7) 185 (35.9) % College Degree or more 39 (31.7) 201 (39.0) % Occupational Category n=119 n= Unemployed/retired 15 (12.6) 96 (19.1) % Blue-collar 21 (17.7) 79 (15.7) % Service Worker 39 (32.8) 138 (27.5) % White-Collar 44 (37.0) 189 (37.6) % n=121 n=505 Current Smoker (Yes) 28 (23.1) 83 (16.4) % Source: sne01p23 &25.sas Table: comp641tab1.xls 3

4 The results of this comparison indicate that younger enrollees were more likely to drop out. As a result, the subjects included in the seasonal analyses reflected older subjects (mean age=48.6 years). In addition, non-white enrollees were more likely to drop out (particularly Hispanic subjects). Subjects who completed some college, but did not have a degree reported slightly lower completion rates, but this pattern was not pronounced. Finally, there is evidence of a healthy worker effect, such that higher dropout rates are evident for subjects who smoked, compared to non-smoking subjects. Among the 641 subjects, the largest proportion of subjects, 9.5% (n=61) were lost after a single cholesterol measure, while 6.1% (n=39) subjects completed only two cholesterol measures, and 3.7% (n=24) subjects completed only three cholesterol measures. An additional n=79 (12.3%) subjects had four cholesterol measures with the remainder having five cholesterol measures. Among the 517 subjects with 4 or more cholesterol measures, 39 subjects did not have at least one cholesterol measured during both the summer and the winter (where the summer is defined as the period from June 21-Sept. 20, and winter is defined as the period from Dec. 21 to March 20). 4

5 Description of Cholesterol Next we summarize cholesterol and other basic variables. This summary is by age and gender. We note that for nearly all cholesterol fractions (except HDL), there are large differences by age for women, but not for men (Table 2). Table 2a. Cholesterol and other variables - Seasonal Study Cohort, Worcester, MA Age Age <50 Age 50+ p-value H 0 : Equal Age Group Means Men (n= 265) (n= 135) (n= 130) TC 222 (38.4) 220 (44.2) 224 (31.3) TG 169 (151) 179 (183) 160 (108) HDL 43 (9.8) 43 (9.6) 43 (10.0) LDL 146 (32.7) 144 (35.1) 149 (29.8) Women (n= 252) (n= 142) (n= 110) TC 215 (40.6) 198 (37.9) 237 (32.6) <.0001 TG 119 (72.6) 103 (57.0) 140 (84.3) <.0001 HDL 51 (11.5) 51 (11.5) 52 (11.6) LDL 140 (36.0) 126 (34.2) 157 (30.2) < Source: sne01p27.sas File: comp641tab1.xls 5

6 Table 2b. Description of BMI, Wast, Hip and Waist:Hip Ratios- Seasonal Study Cohort, Worcester, MA Age Age <50 Age 50+ Men (n= 265) (n= 135) (n= 130) p-value H 0 : Equal Age Group Means BMI (kg/m2) 27.9 (4.5) 27.8 (4.5) 28.1 (4.5) Waist(cm) 97.4 (11.5) 95.4 (10.9) 99.5 (11.7) Hips (cm) (8.2) (7.9) (8.4) 0.07 Waist:Hip 0.93 (0.053) 0.92 (0.052) 0.94 (0.051) Women (n= 252) (n= 142) (n= 110) BMI (kg/m2) 26.7 (6.2) 26.4 (6.2) 27.0 (6.1) Waist(cm) 81.5 (13.2) 80.6 (13.5) 82.7 (12.8) Hips (cm) (12.2) (12.6) (11.8) Waist:Hip 0.78 (0.055) 0.78 (0.057) 0.79 (0.052) Source: sne01p28.sas File: comp641tab1.xls Other basic variables are described in Table 3. Dietary variables are based on 24-hour recalls. This summary is by age and gender. 6

7 Table 3. Dietary and other variables - Seasonal Study Cohort, Worcester, MA Age Age <50 Age 50+ p-value Men (n= 265) (n= 135) (n= 130) Food Intake Avg Kcal/d 2254 (472) 2332 (498) 2175 (432) Fat % of Kcal 32 (5.5) 32 (5.4) 32 (5.7) Satfat % of Kcal 11 (2.6) 11 (2.6) 12 (2.6) gfat/d 83 (25) 85 (25) 80 (24) gsatfat/d 30 (11) 31 (11) 29 (10) Exercise Total Waking Mets 13 (6.0) 13.5 (6.5) 12.2 (5.4) 0.09 Sleeping Mets 6.4 (0.56) 6.4 (0.56) 6.5 (0.56) 0.11 Sports Mets 2.1 (1.5) 2.2 (1.5) 2.0 (1.4) Occupational Mets 6.4 (6.0) 7.3 (6.4) 5.6 (5.4) Household Mets 4.3 (2.7) 1.7 (1.1) 4.6 (2.7) Light Exposure Total direct light (hrs/d) 1.9 (1.1) 1.7 (1.1) 2.1 (1.1) Light (% available) 16 (9.1) 14 (8.9) 18 (8.8) Women (n= 252) (n= 142) (n= 110) Food Intake Avg Kcal/d 1618 (315) 1665 (323) 1558 (295) Fat % of Kcal 30 (4.4) 30 (4.6) 30 (4.3) Satfat % of Kcal 11 (2.2) 11 (2.2) 11 (2.3) gfat/d 56 (15) 58 (16) 54 (14) gsatfat/d 20 (6.6) 21 (6.7) 19 (6.4) Exercise Total Waking Mets 10 (3.0) 10 (3.1) 9.4 (2.8) Sleeping Mets 6.5 (0.70) 6.6 (0.73) 6.5 (0.66) Sports Mets 1.6 (1.3) 1.7 (1.5) 1.3 (1.1) Occupational Mets 3.4 (2.8) 4.0 (3.1) 2.8 (2.3) Household Mets 5.0 (2.1) 4.8 (2.3) 5.2 (1.8) Light Exposure Total direct light (hrs/d) 1.0 (0.49) 1.0 (0.47) 0.95 (0.51) 0.28 Light (% available) 8.2 (3.8) 8.4 (3.7) 7.9 (3.9) Source: sne01p29sas and sne01p30.sas in comp641tab1.xls 7

8 8

9 Discussion of Analysis Approaches Of primary interest is an estimate of the seasonal change in cholesterol, and an accounting of the extent to which changes in other factor may explain the cholesterol changes. Two analysis approaches are considered. One approach models cholesterol over a year using a sine function, and estimates the amplitude and phase. Using this approach, additional time dependent variables can be added to the model, and the impact on the amplitude and phase assessed. A second approach is to estimate the change in cholesterol directly between summer and winter. This approach relies on past research that has indicated that the change is largest when comparing cholesterol between these two time periods. We used both approaches to evaluate seasonal changes in cholesterol, and its covariates. First, we fit a sine model to cholesterol over time, and used the model to estimate the amplitude and phase. These models were fit separately by gender. Additional analyses were conducted that included covariates that were significantly related to cholesterol. The results of these analyses indicated that the peak cholesterol values were during the winter for all cholesterol fractions. In addition, modest changes in amplitude occurred after controlling for covariates. The sine modeling approach does not enable the amplitude to be estimated directly in the model, but an estimate can be obtained as a non-linear function of regression coefficients to sine and cosine terms. This approach does not lend itself to easily investigation of factors that may modify the amplitude (interaction effects). Such interactions can be evaluated directly is one assumes the seasonal effect can be estimated by the winter-summer difference in cholesterol. For this reason, we used simple differences in cholesterol to evaluate how the amplitude changes between different subject groupings, and covariates. Over 92% of the subjects (n=478) used in the sine modeling had cholesterol recorded in both the summer and winter. Other considerations about the Analyses Neither analysis approach is without its limitations. The sine models account for the detailed time of cholesterol measurement, and incorporate all measures of cholesterol. However, the models impose a structure on the pattern of response over time (the sine curve). It is possible that this even seasonal pattern may not represent the way cholesterol measures change over time. This is a limitation of this approach. More general patterns over time could be fit by including sine and cosine terms with different periods (such as 182 day cycles, or 91 day cyles, etc.). We did not explore these extensions. In addition, it is possible to estimate amplitude directly for each subject. Such estimates could be based on best linear unbiased predictors of random effects in the mixed models, but are complicated by the non-linear functions needed to construct subject specific amplitudes. We did not pursue this further. There are also limitations of analyses the compare winter-summer cholesterol differences. First, these analyses do not make use of all cholesterol data, and hence seem in some sense inadequate. Second, the timing of the cholesterol measures is not at the middle 9

10 of the seasons for each subject, and this timing is not accounted for in the analysis. As a result, some error is introduced into the amplitude measures. As previously noted, not all subjects have cholesterol measured in the summer and winter, and hence a more limited set of subjects contribute to the analysis. When measuring cholesterol, there is response error. We have not attempted to adjust for this response error when estimating the winter-summer difference. It may be possible to dampen this response error using mixed model methods (discuss with George). We have not pursued this approach further. Summary of Reports Related to Seasonal Variation in Cholesterol Over time, many reports and analyses have been conducted to evaluate seasonal changes in cholesterol. We list these reports, and summarize their content. The content in these reports should serve as the basic results for the seasonal cholesterol paper. Note that the results in these reports are available in the Working Papers on the Seasons Web Site: Year 2000 Reports Season paper1.doc Updated draft of seasonal Cholesterol paper (Ockene) Sept Seasons Meeting.doc Updated draft of seasonal Cholesterol paper (Ockene) sea00d1.doc Example of monthly averages of TC, Ed Stanek HDL related anayses.doc SPSS analysis by Mort Harmatz on Seasonal Changes for HDL sea00d2.doc sea00d3.doc Accompanying report to basic HDL results for seasonal Cholesterol Study, Ed Stanek sea00d6.doc Results on seasonal changes in cholesterol Part 1. Ed Stanek sea00d7.doc Results on seasonal changes in cholesterol- Part 2. Ed Stanek sea00d8.doc Results on seasonal changes in cholesterol- Part 3. Ed Stanek overall table sea00d6.doc Basic demo& phys. characteristics of study subjects, Ed Stanek cholesterol et al table sea00d6.doc Cholesterol and other variables, Ed Stanek sea00d9.doc Results on explaining winter-summer changes in cholesterol- Part IV, EdS tc-contr09a.xls table for cholesterol summary, Ed Stanek table 3_dietary data et al.doc Dietary and other variables, Ed Stanek Table 4-winter summer lipid data.doc Winter-summer change: Cholesterol, Ed Stanek sea00d10.doc Results on season changes in cholesterol, Part 1. Ed Stanek sea00d11.doc Results on seasonal changes in cholesterol, Part 5. Ed Stanek Year 2001 Reports sea01d01table3.xls sea01d01.doc sea01d02.doc Tables 3-7b for the paper sea01d01.doc (Ed Stanek) Results on seasonal changes in cholesterol- part 1. Analyses are included on 478 subjects with winter and summer cholesterol measures with 4 or more cholesterol measures. Variables for BMI, waist and hip are included. A summary table is given, along with more than 8 other tables. (Ed Stanek). Correlation of results on winter-summer changes in cholesterol- part 1. This report investigates whether larger seasonal 10

11 sea01d05.doc changes occur for some groups. The analysis was based on wintersummer differences. There were some relationships.(ed Stanek) Results on seasonal changes in cholesterol- part 1. (Ed Stanek) 11