Journal of Preventive Medicine and Public Health

Special Article

Application of Standardization for Causal Inference in Observational Studies: A Step-by-step Tutorial for Analysis Using R Software: Sangwon Lee, Woojoo Lee; J Prev Med Public Health. 2022;55(2):116-124. Published online February 11, 2022; DOI: https://doi.org/10.3961/jpmph.21.569

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Epidemiological studies typically examine the causal effect of exposure on a health outcome. Standardization is one of the most straightforward methods for estimating causal estimands. However, compared to inverse probability weighting, there is a lack of user-centric explanations for implementing standardization to estimate causal estimands. This paper explains the standardization method using basic R functions only and how it is linked to the R package stdReg, which can be used to implement the same procedure. We provide a step-by-step tutorial for estimating causal risk differences, causal risk ratios, and causal odds ratios based on standardization. We also discuss how to carry out subgroup analysis in detail.

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Korean summary
본 논문에서는 standardization 방법을 이용하여 risk difference, relative risk, risk ratio와 같은 인과성 효과를 R software을 이용하여 도출하는 튜토리얼을 제공합니다. 간암환자의 치료를 예시로, 합성 데이터를 이용한 치료제의 사망에 대한 인과적 효과를 탐색하는 튜토리얼을 제공합니다. 추가적으로, 인과성 관련 기본 이론을 집약적으로 설명하였고, standardization을 이용한 subgroup analysis 수행 방법이 제공됩니다.

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Original Articles

Reliability of Covariates in Baseline Survey of a Cohort Study: Epidemiological Investigation on Cancer Risk Among Residents Who Reside Near the Nuclear Power Plants in Korea.: Sanghyuk Bae, Bo Young Park, Zhong Min Li, Yoon Ok Ahn; J Prev Med Public Health. 2010;43(2):159-165.; DOI: https://doi.org/10.3961/jpmph.2010.43.2.159

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OBJECTIVES
We evaluated the reliability of the possible covariates of the baseline survey data collected for the Epidemiological Investigation on Cancer Risk Among Residents Who Reside Near the Nuclear Power Plants in Korea. METHODS: Follow-up surveys were conducted for 477 participants of the cohort at less than 1 year after the initial survey. The mean interval between the initial and follow-up surveys was 282.5 days. Possible covariates were identified by analyzing the correlations with the exposure variable and associations with the outcome variables for all the variables. Logistic regression analysis with stepwise selection was further conducted among the possible covariates to select variables that have covariance with other variables. We considered that these variables can be representing other variables. Seven variables for the males and 3 variables for the females, which had covariance with other possible covariates, were selected as representative variables. The Kappa index of each variable was calculated. RESULTS: For the males, the Kappa indexes were as follow; family history of cancer was 0.64, family history of liver diseases in parents and siblings was 0.56, family history of hypertension in parents and siblings was 0.51, family history of liver diseases was 0.50, family history of hypertension was 0.44, a history of chronic liver diseases was 0.53 and history of pulmonary tuberculosis was 0.36. For females, the Kappa indexes were as follow; family history of cancer was 0.58, family history of hypertension in parents and siblings was 0.56 and family history of hypertension was 0.47. CONCLUSIONS: Most of the possible covariates showed good to moderate agreement.

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Cancer Risk in Adult Residents near Nuclear Power Plants in Korea - A Cohort Study of 1992-2010
Yoon-Ok Ahn, Zhong Min Li
Journal of Korean Medical Science.2012; 27(9): 999. CrossRef

Leukocyte count and hypertension in the health screening data in some rural and urban residents.: Choong Won Lee, Nung Ki Yoon, Sung Kwan Lee; Korean J Prev Med. 1991;24(3):363-372.

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Abstract PDF: We used the health screening data of some rural and urban residents to examine the cross-sectional association between leukocyte count and hypertension. The 206 male and 203 female rural residents were selected by multi-stage cluster sampling method in Kyungsan-Kun area of Kyungbuk province in 1985 and 600 urban residents were selected by the same sampling method as the rural residents in Daegu city of the same province in 1986 compatible with age-sex distribution of Daegu city of 1985 census, but of whom 384 actually responded. The rest of 600 were replaced by age and sex with those who were members of the medical insurance plan visiting the health management department of the university hospital to get the biannual preventive medical checkups. Excluded in the analysis were those having hypertensive history, diseases and extreme outlying values of the screening tests, leaving 373 rural and 571 urban residents. Leukocyte count was measured with ELT-8 Laser shadow method and the unit cells/mm3. Blood pressures were determined with an aneroid sphygmomanometer with pre-standardized method and hypertensives were defined as those showing systolic blood pressure more than 140 mmHg and / or diastolic blood pressure more than 90 mmHg. Total residents pooled (N=944) showed a significant difference between hypertensives and normotensives (6965.93+/-1997.01 vs 6490.61+/-1941.32, P=0.00) and in rural residents was noted the similar significant difference (P=0.03). None of significant differences were noted in any stratum stratified by residency and sex. Compared to the lowest quintile of WBC, 2/5 quintile showed odds ratio 0.99 (95% CI 0.90-2.21), 4/5 quintile 1.76 (95% CI 1.14-2.72), and highest quintile 1.80 (1.15-2.82) in the total residents. Likelihood ratio test for linear trend for in indicated a significant trend (x2 trend=5.53, df=1, P<0.05). There were no other significant odds ratios compared to the lowest quintile of WBC in strata stratified by residency and sex. The odds ratios in total residents which had showed significant odds ratios became nonsignificant and of reduced magnitude after controlling age, frequency of smoking and drinking with multiple logistic regression. In each stratum, it changed magnitudes of odds ratios slightly and unstably. None of the trend tests showed any significant trend. These results suggest that the Friedman et al's finding of association between leukocyte count and hypertension may be due to an statistical type I error result in from the data dredging in an exploratory study, in which more than 800 variables were screened as possible predictors of hypertension.; Summary

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