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Do trends in population levels of blood pressure and other cardiovascular risk factors explain trends in stroke event rates? - methodological appendix to a paper published in Stroke

August 2002

Hanna Tolonen¹, Kari Kuulasmaa¹, Kjell Asplund², Markku Mähönen¹ for the WHO MONICA Project³

¹ Department of Epidemiology and Health Promotion, National Public Health Institute (KTL), Helsinki, Finland
² Department of Medicine, University Hospital, Umeå, Sweden
³ Annex: Sites and key personnel of the WHO MONICA Project

Correspondence to Hanna Tolonen (hanna.tolonen@ktl.fi)

© Copyright World Health Organization (WHO) and the WHO MONICA Project investigators 2002. All rights reserved. 

• Copyright notice 
• Document identification:
  • URL:http://www.ktl.fi/publications/monica/stroke_h1/appendix.htm
  • URN:NBN:fi-fe20021258

Contents

• 1. Introduction 
• 2. Quality scores
  • 2.1 Overall quality score 
  • 2.2 Quality score for individual risk factors
• 3. Stroke risk score
• 4. Sensitivity analyses
• References 
• Acknowledgements 
• Specific tables 
  • Table A1. Overall quality score and its components 
  • Table A2. Quality scores for individual risk factors
  • Table A3a. Sensitivity analysis for simple regression model between trends in systolic blood pressure and trends in stroke event rate
  • Table A3b. Simple regression model between trends in individual risk factors and trends in stroke event rate
  • Table A3c. Sensitivity analysis for multiple regression model between trends in systolic blood pressure and daily cigarette smoking and trends in stroke event rates
  • Table A3d. Sensitivity analysis for simple regression model between trends in risk score and trends in stroke event rates
• Annex: Sites and key personnel of contributing MONICA Centres 

1. Introduction 

This document is the methodological appendix to the paper titled "Do trends in population levels of blood pressure and other cardiovascular risk factors explain trends in stroke rates? Comparisons of 15 populations in 9 countries within the WHO MONICA Stroke Project." published in Stroke in 2002 [1]. It covers:

• the derivation of the quality score which was used to weight the populations in the regression analysis;
• a description of the stroke risk score used to summarize the combined impact of blood pressure, smoking, cholesterol and BMI on the risk of stroke;
• results of the sensitivity analyses referred to in the parent publication.

2. Quality scores

2.1 Overall quality score

The overall quality score, which was used for weighting the data in the regression analyses in reference [1], has values between zero and two. If the score is two, no problems were identified in the quality of the data for a population, whereas a score of zero indicates major concern about the data quality. The overall quality score was derived from the quality scores of the individual data components. The values of the overall quality score and its components are shown in Table A1. The definition of the overall quality score is included in the following description of the columns of Table A1: 

• Population: The abbreviation of the population name, as described in Table 1 of reference [1]. The lower case letter at the end of the abbreviation (a, b etc.) identifies the exact definition of the population, and has been described in the MONICA quality assessment reports [2-8]. 
• Event trends: Quality items related to the trends in the coronary event rates.
  • Dem: Square root of two times the Summary score of quality of the population demographic data [Table 6 of reference 2]. In the cases where the population is a combination of several reporting units, the mean of the scores of the contributing reporting units was taken. 
  • Event: The Summary score for stroke event trends quality [3] 
  • Event trends score: Geometric mean of (Dem+0.2)/1.1 and Event. (Note: 0.2 is added to Dem so that it cannot make the geometric mean zero regardless of the value of Event).  
• Risk factor trends: Quality items related to the trends in the risk factors. Even though three surveys were considered for most of the populations, the quality score is based on the initial and final survey only. The middle survey has a relatively small influence in the estimates of the linear trends. Furthermore, for the two populations where the quality of the middle survey was much lower than the quality of the initial and final survey, the middle survey was not used for estimating the trends in the risk factors. 
  • Response rate: Response rates in the MONICA surveys have been reported using two definitions, A and B, which differ in the way of counting those people whose eligibility for the survey could not be assessed because they could not be contacted [4]. For the quality score, the mean of item response rates A and B for Body Mass Index (BMI) was used. BMI was chosen because it reflects best the response rate for the clinical examination. The overall response rate concerns the questionnaire data, and in some populations only a portion of those people who were interviewed at home came to the clinical examination. 
    • Ini: Response rate in the initial survey. 
    • Fin: Response rate in the final survey. 
    • Response rate score: 2×Square root of [1 - (1 - Ini)×(1 - Fin) - (|Ini - Fin|)] 
  • Risk factors
    • Smok: This is based on Section 6 (Recommendations for using MONICA data on smoking behaviour), Subsection 6.3 (Trend analyses) of the Quality Assessment of Data on Smoking Behaviour [5]. Score 0 was given where the quality assessment report recommends that the data should not be used for analysis of trends of daily smoking. Score 1.41 (i.e. the square root of two) was given where there was a change in the relevant question on smoking but there was evidence that the change did not affect the trend estimates much. All other populations were given a score of 2. 
    • Bp: Quality score for blood pressure trends (QST) between the initial and the final surveys from Table 19 of the Quality Assessment of Data on Blood Pressure [6]. 
    • Chol: Total cholesterol overall summary score (TCOSS) for the initial and final surveys from Table 16 of the Quality Assessment of Total Cholesterol Measurements [7]. 
    • BMI: This is derived from the summary score for weight and height measurements for the initial and the final surveys from Table 10 of the Quality Assessment of Weight and Height Measurements [8]. The score is 0 if the summary score for the initial or final survey was 0. Otherwise the score is the mean of the scores for the initial and final surveys. 
  • Risk factors mean: The arithmetic mean of smok, bp, chol and BMI.
  • Risk factor trends score: Half of the product of Response rate score and Risk factors mean. 
• Overall quality score: Geometric mean of Event trends score and Risk factor trends score. 

2.2 Quality score for individual risk factors

The quality scores for individual risk factors (systolic blood pressure, daily cigarette smoking, total cholesterol and BMI) also have values between zero and two, with value two indicating a good quality and value zero indicating major concern about the data quality. The values of the quality score for each risk factor and its components are shown in Table A2. The definition of the quality scores for each risk factor are otherwise the same as for the overall quality score, except that the "Risk factors mean" is replaced with the quality score of the individual risk factor in question.

3. Stroke risk score

Stroke risk score was derived from the follow-up of the Finnish MONICA risk factor surveys conducted in 1982 and 1987. Subjects were 25-64 years old during the baseline examination. The total number of subjects was 14902 (7195 men and 7707 women). They were followed-up until the end of 1995. By that time there were a total of 553 fatal and non-fatal stroke cases (ICD = 430-439). The follow-up procedure has been described elsewhere [9].

Risk factors used for the stroke risk score were systolic blood pressure measurement (mmHg), daily smoking (0/1), total cholesterol (mmol/L) and BMI (kg/m²).

The risk score was defined as a linear combination of the levels of the risk factors, where the coefficients were obtained using the Cox-proportional hazards model [10]. The  coefficients are given in Table 1.

In the analysis, the coefficients for systolic blood pressure and total cholesterol of Table 1 were multiplied by 1.5 to compensate the regression dilution [11-13].

The coefficients of Table 1 are similar to coefficients obtained from other studies. For example, in the Kaunas-Rotterdam Intervention Study [14] the risk ratios for men were: 1.02 for systolic blood pressure, 2.01 for smoking, 0.97 for total cholesterol and 1.03 for BMI. 

4. Sensitivity analyses

The parent publication [1] refers to sensitivity analyses which were performed to assess the robustness of the results. The results of the sensitivity analyses are shown in Table A3a for the simple regression analysis using systolic blood pressure as the explanatory variable. Table A3b shows the results by other individual risk factors (daily smoking, total cholesterol and BMI) as explanatory variables. Table A3c shows the results when systolic blood pressure and smoking are used as the explanatory variables in a multiple regression analysis. The results for the simple regression analysis using the risk score are given in Table A3d. In each table, the analysis was repeated:

• for the full and the lagged event registration period;
• with and without quality weighting;
• with and without excluding populations with low quality;
• with and without subarachnoid haeorrhage included in the stroke events;
• using the full age range (35-64 years) and restricting the analysis to the age group 55-64 years.

References

1. Tolonen H, Mähönen M, Asplund K, Rastenyte D, Kuulasmaa K, Vanuzzo D, Tuomilehto J, for the WHO MONICA Project. Do trends in population levels of blood pressure and other cardiovascular risk factors explain trends in stroke event rates? Comparisons of 15 populations in 9 countries within the WHO MONICA Stroke Project. Stroke 2002;33:2367-2375.
2. Moltchanov V, Kuulasmaa K, Torppa J, for the WHO MONICA Project. Quality assessment of demographic data in the WHO MONICA Project. (April 1999). Available from: URL:http://www.ktl.fi/publications/monica/demoqa/demoqa.htm, URN:NBN:fi-fe19991073.
3. Mähönen M, Asplund K, Tolonen H and Kuulasmaa K, for the WHO MONICA Project. Stroke event trend quality score for the WHO MONICA Project. (2001). Available from: URL:http://www.ktl.fi/publications/monica/strokescore/score.htm, URN:NBN:fi-fe20011554.
4. Wolf H, Kuulasmaa K, Tolonen H, Ruokokoski E, for the WHO MONICA Project. Participation rates, quality of sampling frames and sampling fractions in the MONICA surveys. (September 1998). Available from: URL:http://www.ktl.fi/publications/monica/nonres/nonres.htm, URN:NBN:fi-fe19991076.
5. Molarius A, Kuulasmaa K, Evans A, McCrum E, Tolonen H, for the WHO MONICA Project. Quality assessment of data on smoking behaviour in the WHO MONICA Project. (February 1999). Available from: URL:http://www.ktl.fi/publications/monica/smoking/qa30.htm, URN:NBN:fi-fe19991077.
6. Kuulasmaa K, Hense HW, Tolonen H, for theWHO MONICA Project. Quality assessment of data on blood pressure in the WHO MONICA Project. (May 1998). Available from: URL:http://www.ktl.fi/publications/monica/bp/bpqa.htm, URN:NBN:fi-fe19991082.
7. Ferrario M, Kuulasmaa K, Grafnetter D, Moltchanov V, for the WHO MONICA Project. Quality assessment of total cholesterol measurements in the WHO MONICA Project. (April 1999). Available from: URL:http://www.ktl.fi/publications/monica/tchol/tcholqa.htm, URN:NBN:fi-fe19991083.
8. Molarius A, Kuulasmaa K, Sans S, for the WHO MONICA Project. Quality assessment of weight and height measurements in the WHO MONICA Project. (May 1998). Available from: URL:http://www.ktl.fi/publications/monica/bmi/bmiqa20.htm, URN:NBN:fi-fe19991079.
9. Jousilahti P, Vartiainen E, Tuomilehto J, Puska P. Sex, age, cardiovascular risk factors, and coronary heart disease. A prospective follow-up study of 14 786 middle-aged men and women in Finland. Circulation 1999;99:1165-1172.
10. Clayton D & Hill M. Statistical Models in Epidemiology. New York: Oxford University Press; 1993.
11. Clarke R, Shipley M, Lewington S, et al. Underestimation of risk associations due to regression dilution in long-term follow-up of prospective studies. Am J Epidemiol 1999;150:341-353.
12. MacMahon S, Peto R, Cutler J, et al. Blood pressure, stroke and coronary heart disease, part 1: prolonged differences in blood pressure - prospective observational studies corrected for the regression dilution bias. Lancet 1990;355:765-774.
13. Law MR, Wald NJ, Wu T, Hackshaw B, Bailey A. Systematic underestimation of association between serum cholesterol concentration and ischaemic heart disease in observational studies: data from the BAPU study. BMJ 1994;308:363-366.
14. Rastenyte D, Tuomilehto J, Domarkiene S, Cepaitis Z & Reklaitiene R. Risk factors for death from stroke in middle-aged Lithuanian men. Stroke 1996;27:627-676.

Acknowledgements

We thank Pekka Jousilahti for his help in deriving score risk score from Finnish data. 

The MONICA Centres are funded predominantly by regional and national governments, research councils, and research charities. Coordination is the responsibility of the World Health Organization (WHO), assisted by local fund raising for congresses and workshops. WHO also supports the MONICA Data Centre (MDC) in Helsinki. Not covered by this general description is the ongoing generous support of the MDC by the National Public Health Institute of Finland, and a contribution to WHO from the National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland, USA for support of the MDC. The completion of the MONICA Project is generously assisted through a Concerted Action Grant from the European Community. Likewise appreciated are grants from ASTRA Hässle AB, Sweden, Hoechst AG, Germany, Hoffmann-La Roche AG, Switzerland, the Institut de Recherches Internationales Servier (IRIS), France, and Merck & Co. Inc., New Jersey, USA, to support data analysis and preparation of publications.