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1 Journal of Preventive Medicine and Public Health March 00, Vol., No., - doi: 0./jpmph Assessment of Applicability of Standardized Rates for Health State Comparison Among Areas: 00 Community Health Survey Geun-Yong Kwon, Do-Sang Lim, Eun-Ja Park, Ji-Sun Jung, Ki-Won Kang, Yun-A Kim, Ho Kim, Sung-Il Cho School of Public Health, Seoul National University; Korea Center for Diease Control and Prevention; Korea Institute for Health and Social Affairs Objectives: This study shows the issues that should be considered when applying standardized rates using Community Health Survey(CHS) data. Methods: We analyzed 00 CHS data. In order to obtain the reliability of standardized rates, we calculated z-score and rank correlation coefficients between direct standardized rate and indirect standardized rate for major indices. Especially, we assessed the change of correlations according to population composition (age and sex), and characteristics of the index. We used Mantel-Haenszel chi-square to quantify the difference of population composition. Results: Among major indices, indices z-score and rank correlation coefficients were over 0.. However, regions with larger differences in population composition showed lower reliability. Low reliability was also observed for the indices specific to subgroups with small denominator such as permanent lesion from stroke, and the index with large regional variations in age-related differences such as obtaining health examinations. Conclusions: Standardized rates may have low reliability, if comparison is made between areas with extremely large differences in population composition, or for indicies with large regional variations in age-related differences. Therefore, the special features of standardized rates should be considered when health state are compared among areas. Key words: Age distribution, Health surveys, Population characteristics, Standardization J Prev Med Public Health 00;():-

4 Table. Correlation coefficient between two standardized rates Index (%) Z-score correlation coefficient (% CI) Rank correlation coefficient (% CI) Permanent lesion from stroke* Obtaining a health examination (In two years) Checkup of an eye complication of diabetes* Lack of medical treatment due to the economical situation Stroke diagnosed by a doctor in a lifetime Asthma diagnosed by a doctor in a lifetime Myocardial infarction diagnosed by a doctor in a lifetime Diabetes diagnosed by a doctor in a lifetime Angina pectoris diagnosed by a doctor in a lifetime Checkup of a kidney complication of diabetes* Influenza vaccination yearly Completion of education for diabetes* Smokers trying to quit smoking* Good subjective recognition of a health state Hypertension diagnosed by a doctor in a lifetime Smokers who plan to quit smoking in a month* Thinking of committing suicide Experiencing depression Osteoporosis diagnosed by a doctor in a lifetime Subjective recognition of obesity Hyperlipidemia diagnosed by a doctor in a lifetime Experiencing a non-smoking campaign Subjective recognition of stress Completion of education for people with arthritis* Lifetime smoking Fastening seat belts in the seat next to the driver* Arthritis diagnosed by a doctor in a lifetime Trying to control weight Lifetime drinking Walking Fastening seat belts during driving CI: Confidece interval. * : Indices have denominator of special group. 0. ( ) 0. (0.-0.0) 0.0 (0.-0.) 0. (0.-0.) 0. (0.-0.) 0. (0.-0.) 0. (0.0-0.) 0.0 (0.-0.) 0. (0.-0.) 0. (0.0-0.) 0. (0.-0.) 0. (0.-0.) 0.0 (0.-0.) 0. (0.-0.) 0.0 (0.-0.) 0. (0.-0.) 0. (0.-0.) 0. (0.0-0.) 0. (0.-0.) 0. (0.-0.0) 0. (0.-0.) 0. (0.-0.) 0. (0.-0.) 0. (0.-0.) 0. (0.-0.) 0.0 (0.-0.) 0. (0.-0.) 0. (0.-0.) 0. (0.-0.) 0. (0.-0.) 0. (0.-0.) 0. (0.-0.) 0. (0.-0.) 0. (0.0-0.) 0. (0.-0.) 0. (0.-0.0) 0. (0.-0.0) 0. (0.-0.) 0. (0.-0.) 0. (0.-0.) 0. (0.-0.) 0. (0.-0.) 0. (0.0-0.) 0. (0.-0.) 0. (0.-0.) 0.0 (0.-0.) 0. (0.-0.) 0. (0.-0.) 0. (0.-0.) 0. (0.-0.) 0. (0.-0.) 0. (0.-0.) 0. (0.-0.0) 0. (0.-0.0) 0. (0.-0.0) 0. (0.-0.) 0. (0.0-0.) 0. (0.0-0.) 0. (0.-0.) 0. (0.-0.) 0. (0.-0.) 0. (0.-0.)

5 Figure. Mantel-Haenszel Chi-square of area populations corresponding with standard population. Table. Mean of the Mantel-Haenszel Chi-square (df=) by wide area Area Seoul Busan Daegu Incheon Kwangju Daejeon Ulsan Gyeonggi Mean of Chi-square Area Gangwon Chungbuk Chungnam Chunbuk Chunnam Gyeongbuk Gyeongnam Cheju Mean of Chi-square

6 Table. Number of areas with quartile rank change Index (%) 0- (n = 0) - (n = 0) Mantel-Haenszel Chi-square - (n = ) - (n = 0) -0 (n = 0) Sum of area Permanent lesion from stroke Obtaining a health examination (In two years) Checkup of an eye complication of diabetes Checkup of a kidney complication of diabetes Myocardial infarction diagnosed by a doctor in a lifetime Angina pectoris diagnosed by a doctor in a lifetime Lack of medical treatment due to the economical situation Smokers trying to quit smoking Smokers who plan to quit smoking in a month Influenza vaccination yearly Diabetes diagnosed by a doctor in a lifetime Stroke diagnosed by a doctor in a lifetime Osteoporosis diagnosed by a doctor in a lifetime Asthma diagnosed by a doctor in a lifetime Subjective recognition of obesity Experiencing depression Good subjective recognition of a health state Completion of education for diabetes Subjective recognition of stress Thinking of committing suicide Experiencing a non-smoking campaign Hypertension diagnosed by a doctor in a lifetime Lifetime drinking Hyperlipidemia diagnosed by a doctor in a lifetime Completion of education for people with arthritis Lifetime smoking Fastening seat belts during driving Fastening seat belts in the seat next to the driver Trying to control weight Arthritis diagnosed by a doctor in a lifetime Walking Sum of area 0

7 Figure. Number of outliers in Bland-Altman plots.

8 Figure. Rank correlation of permanent lesion from stroke. Figure. Rank correlation of obtaining a health examination (in two years).

9 Table. Age-specific rate of obtaining a health examination in A, B region Area A B Rank of direct standardization rate Rank of indirect standardization rate Age specific rate (%)

11 . Lee KS. Health promotion strategies under regional health planning. Korean J Health Policy Adm ; (): -. (Korean). Jeong BG, Jung KY, Kim JY, Moon OR, Lee YH. Hong YS, et al. The Relationship between regional material deprivation and the standardized mortality ratio of the community residents aged - in Korea. J Prev Med Public Health 00; (): -. (Korean). Lee SI, Kim CW, Moon OR. The possibility of regional health insurance data in blueprinting the local community health plan. Korean J Prev Med ; 0(): 0-. (Korean). Carson CA, Taylor HR, McCARTY DJ, Zimmet P. Agestandardization in epidemiological data. Int J Epidemiol ; (): -.. Fleiss JL. Statistical Methods for Rates and Proportions, rd ed. New Jersey: John Wiley & Sons Inc.; 00. pp. -.. Inskip H, Beral V, Fraser P, Haskey J. Methods for ageadjustment of rates. Stat Med ; (): -.. Julious SA, Nicholl J, George S. Why do we continue to use standardized mortality ratios for small area comparisons? J Public Health Med 00; (): 0-.. Kitagawa EM. Standardized comparisons in popoulation research. Demography ; (): -.. Breslow NE, Day NE. Indirect standardization and multiplicative models for rates, with reference to the age adjustment of cancer incidence and relative frequency data. J Chronic Dis ; (-): Gail M. The analysis of heterogeneity for indirect standardized mortality ratios. J R Stat Soc Ser A ; (): -.. John WT, Lyle VJ, David RB. The Collected Works of John W. Tukey: Graphics, th ed. New Jersey: Bell Telephone Laboratories Inc.;. p Cressie NA. Statistics for Spatial Data, New York: John Wiley & Sons Inc.;. p Curtin LR. A short history of standardization for vital events. Vital Health Stat ; (): -.. Anderson R, Rosenberg H. Age standardization of death rates: Implementation of the year 000 standard. Natl Vital Stat Rep ; (): -, 0.. Korea Center for Disease Control and Prevention. Operating System of Community Health Survey: Center for Chronic Disease. Seoul: Korea Center for Disease Control and Prevention; 00. (Korean). Curtin, LR. Klein RJ. Direct standardization (age-adjusted death rates). Healthy People 000 Stat Notes ; (): Pickle LW, White AA. Effects of the choice of ageadjustment method on maps of death rates. Stat Med ; (-): -.. Spiegelman M, Marks HH. I. Empirical testing of standards for the age adjustment of death rates by the direct method. Hum Biol ; (): 0-.. Walter SD, Birnie SE. Mapping mortality and morbidity patterns: An international comparison. Int J Epidemiol ; 0(): Kim JH, Yoon TH. Comparisons of health inequalities in small areas with using the standardized mortality ratios in Korea. J Prev Med Public Health 00; (): (Korean). Yule GU. On some points relating to vital statistics, more especially statistics of occupational mortality. J R Stat Soc ; (): -.. Kilpatrick SJ. Mortality comparisons in socio-economic groups. J R Stat Soc, Ser C (Appl Stat) ; (): -.. Rezaeian M, Dunn G, Leger SS, Appleby L. Do hot spots of deprivation predict the rates of suicide within London boroughs? Health Place 00; (): -.. Kang YH, Hwang IA, Yun SC, Lee MS, Lee SI, Jo MW, et al. Census population vs. registration population: Which population denominator should be used to calculate geographical mortality. J Prev Med Public Health 00; (): -. (Korean)

한국성인에서초기황반변성질환과 연관된위험요인연구

한국성인에서초기황반변성질환과 연관된위험요인연구 한국성인에서초기황반변성질환과 연관된위험요인연구 - - i - - i - - ii - - iii - - iv - χ - v - - vi - - 1 - - 2 - - 3 - - 4 - 그림 1. 연구대상자선정도표 - 5 - - 6 - - 7 - - 8 - 그림 2. 연구의틀 χ - 9 - - 10 - - 11 -