Journal of Preventive Medicine and Public Health

Original Articles

Spatio-temporal Distribution of Suicide Risk in Iran: A Bayesian Hierarchical Analysis of Repeated Cross-sectional Data: Seyed Saeed Hashemi Nazari, Kamyar Mansori, Hajar Nazari Kangavari, Ahmad Shojaei, Shahram Arsang-Jang; J Prev Med Public Health. 2022;55(2):164-172. Published online February 10, 2022; DOI: https://doi.org/10.3961/jpmph.21.385

2,463 View
119 Download
2 Web of Science
1 Crossref

Objectives
We aimed to estimate the space-time distribution of the risk of suicide mortality in Iran from 2006 to 2016.
Methods
In this repeated cross-sectional study, the age-standardized risk of suicide mortality from 2006 to 2016 was determined. To estimate the cumulative and temporal risk, the Besag, York, and Mollié and Bernardinelli models were used.
Results
The relative risk of suicide mortality was greater than 1 in 43.0% of Iran’s provinces (posterior probability >0.8; range, 0.46 to 3.93). The spatio-temporal model indicated a high risk of suicide in 36.7% of Iran’s provinces. In addition, significant upward temporal trends in suicide risk were observed in the provinces of Tehran, Fars, Kermanshah, and Gilan. A significantly decreasing pattern of risk was observed for men (β, -0.013; 95% credible interval [CrI], -0.010 to -0.007), and a stable pattern of risk was observed for women (β, -0.001; 95% CrI, -0.010 to 0.007). A decreasing pattern of suicide risk was observed for those aged 15-29 years (β, -0.006; 95% CrI, -0.010 to -0.0001) and 30-49 years (β, -0.001; 95% CrI, -0.018 to -0.002). The risk was stable for those aged >50 years.
Conclusions
The highest risk of suicide mortality was observed in Iran’s northwestern provinces and among Kurdish women. Although a low risk of suicide mortality was observed in the provinces of Tehran, Fars, and Gilan, the risk in these provinces is increasing rapidly compared to other regions.

Summary

Citations

Citations to this article as recorded by

Spatial, geographic, and demographic factors associated with adolescent and youth suicide: a systematic review study
Masoud Ghadipasha, Ramin Talaie, Zohreh Mahmoodi, Salah Eddin Karimi, Mehdi Forouzesh, Masoud Morsalpour, Seyed Amirhosein Mahdavi, Seyed Shahram Mousavi, Shayesteh Ashrafiesfahani, Roya Kordrostami, Nahid Dadashzadehasl
Frontiers in Psychiatry.2024;[Epub] CrossRef

Associations Between Preschool Education Experiences and Adulthood Self-rated Health: Jeehye Lee, Jinwook Bahk, Young-Ho Khang; J Prev Med Public Health. 2017;50(4):228-239. Published online May 10, 2017; DOI: https://doi.org/10.3961/jpmph.16.110

6,992 View
206 Download
1 Crossref

Abstract PDF Supplementary Material

Objectives
This study aimed to examine the association between preschool education experiences and adulthood self-rated health using representative data from a national population-based survey. Methods: Data from the Korean Labor and Income Panel Study in 2006 and 2012 were used. A total of 2391 men and women 21-41 years of age were analyzed. Log-binomial regression analyses were conducted to examine the associations between preschool education experience and self-rated health in adulthood. Parental socioeconomic position (SEP) indicators were considered as confounders of the association between preschool education experience and adulthood subjective health, while current SEP indicators were analyzed as mediators. Age-adjusted prevalence ratios (PRs) and the associated 95% confidence intervals (CIs) were estimated. Results: Compared with men without any experience of preschool education, those with both kindergarten and other preschool education experiences showed a lower prevalence of self-rated poor health (PR, 0.65; 95% CI, 0.47 to 0.89). In women, however, such an association was not evident. The relationship of preschool education experiences with self-rated poor health in adulthood among men was confounded by parental SEP indicators and was also mediated by current SEP indicators. After adjustment for parental and current SEP indicators, the magnitude of the associations between preschool education experiences and adulthood subjective health was attenuated in men. Conclusions: Preschool education experience was associated with adulthood self-rated health in men. However, this association was explained by parental and current SEP indicators. Further investigations employing a larger sample size and objective health outcomes are warranted in the future.

Summary

Citations

Citations to this article as recorded by

Self-rated health and its determinants in patients with hypertension in Isfahan in 2019
Asieh Mansouri, Alireza Khosravi Farsani, Noushin Mohammadifard, Fatemeh Nouri, Mahnaz Jozan, Ghazaal Alavi Tabatabaei, Rezvan Salehidoost, Hamed Rafiee
BMC Public Health.2024;[Epub] CrossRef

A Longitudinal Study on the Causal Association Between Smoking and Depression.: Eunjeong Kang, Jaehee Lee; J Prev Med Public Health. 2010;43(3):193-204.; DOI: https://doi.org/10.3961/jpmph.2010.43.3.193

6,014 View
164 Download
33 Crossref

Abstract PDF

OBJECTIVES
The objective of this study was to analyze the causal relationship between smoking and depression using longitudinal data. METHODS: Two waves of the Korea Welfare Panel collected in 2006 and 2007 were used. The sample consisted of 14 426 in 2006 and 13 052 in 2007 who were aged 20 and older. Smoking was measured by smoking amount (none/ or = two packs). Depression was defined when the summated CESD (center for epidemiological studies depression)-11 score was greater than or equal to 16. The causal relationship between smoking and depression was tested using logistic regression. In order to test the causal effect of smoking on depression, depression at year 2 was regressed on smoking status at year 1 only using the sample without depression at year 1. Likewise, smoking status at year 2 was regressed on depression at year 1 only using those who were not smoking at year 1 in order to test the causal effect of depression on smoking. The statistical package used was Stata 10.0. Sampling weights were applied to obtain the population estimation. RESULTS: The logistic regression testing for the causal relationship between smoking and depression showed that smoking at year 1 was significantly related to depression at year 2. Smoking amounts associated with depression were different among age groups. On the other hand, the results from the logistic regression testing for the opposite direction of the relationship between smoking and depression found no significant association regardless of age group. CONCLUSIONS: The study results showed some evidence that smoking caused depression but not the other way around.

Summary

Citations

Citations to this article as recorded by

Risk and protective factors for severe mental disorders in Asia
Fatima Zahra Rami, Ling Li, Thi Hung Le, Chaeyeong Kang, Mi Ah Han, Young-Chul Chung
Neuroscience & Biobehavioral Reviews.2024; 161: 105652. CrossRef
Prenatal predictors of postpartum depression trajectories from birth to 24 months amongst smoking women
Seth Frndak, Samie Syed, Julian Saleh, Megan Kocher, Xiaozhong Wen
Journal of Clinical Nursing.2022; 31(11-12): 1643. CrossRef
The long‐term health effects of initiating smoking in adolescence: Evidence from a national longitudinal survey
Aliaksandr Amialchuk, Onur Sapci
Health Economics.2022; 31(4): 597. CrossRef
Tobacco smoking and depressive symptoms in Chinese middle-aged and older adults: Handling missing values in panel data with multiple imputation
Xiahua Du, Rina Wu, Lili Kang, Longlong Zhao, Changle Li
Frontiers in Public Health.2022;[Epub] CrossRef
Physical activity mitigates the link between adverse childhood experiences and depression among U.S. adults
Michael F. Royer, Christopher Wharton, Catalina Castaño
PLOS ONE.2022; 17(10): e0275185. CrossRef
Smoking and Neuropsychiatric Disease—Associations and Underlying Mechanisms
Omar Hahad, Andreas Daiber, Matthias Michal, Marin Kuntic, Klaus Lieb, Manfred Beutel, Thomas Münzel
International Journal of Molecular Sciences.2021; 22(14): 7272. CrossRef
Association of Alcohol and Tobacco Consumption with Depression Severity in the Oldest Old. Results from the Age Different Old Age Cohort Platform
Janine Quittschalle, Alexander Pabst, Margrit Löbner, Melanie Luppa, Kathrin Heser, Michael Wagner, Hendrik van den Bussche, André Hajek, Hans-Helmut König, Birgitt Wiese, Matthias C. Angermeyer, Wolfgang Maier, Martin Scherer, Steffi G. Riedel-Heller
International Journal of Environmental Research and Public Health.2021; 18(15): 7959. CrossRef
Waterpipe and cigarette tobacco smoking and depressive symptoms among public school students in central Jordan
Sukaina Alzyoud, Farah Massoud
Journal of Health Research.2020;[Epub] CrossRef
Happiness among second year MBBS students and its correlates using Oxford Happiness Questionnaire
Shivam Kamthan, Saurabh Sharma, Rahul Bansal, Bhawna Pant, Parul Saxena, Shivakshi Chansoria, Arvind Shukla
Journal of Oral Biology and Craniofacial Research.2019; 9(2): 190. CrossRef
Mechanisms Underlying the Anti-Depressive Effects of Regular Tea Consumption
Dylan O’Neill Rothenberg, Lingyun Zhang
Nutrients.2019; 11(6): 1361. CrossRef
Acute Effects of Aerobic Exercise on Affect and Smoking Craving in the Weeks Before and After a Cessation Attempt
Ana M Abrantes, Samantha G Farris, Haruka Minami, David R Strong, Deborah Riebe, Richard A Brown
Nicotine & Tobacco Research.2018; 20(5): 575. CrossRef
The Association of Cigarette Smoking With Depression and Anxiety: A Systematic Review
Meg Fluharty, Amy E. Taylor, Meryem Grabski, Marcus R. Munafò
Nicotine & Tobacco Research.2017; 19(1): 3. CrossRef
Depressive Symptoms Delayed Quit Attempts and Shortened Abstinence in Young Smokers of the Hong Kong Youth Quitline
David C. N. Wong, Sophia S. C. Chan, Tai-hing Lam
Nicotine & Tobacco Research.2016; 18(3): 251. CrossRef
Happiness Among College Students: A Cross-Sectional Web-Based Study Among Iranian Medical Students
Azadeh Lesani, Asghar Mohammadpoorasl, Maryam Javadi, Hossein Ansari, Ali Fakhari
Biotechnology and Health Sciences.2016;[Epub] CrossRef
Increased Risk of Major Depression With Early Age of Exposure to Cigarettes
Bishnu Devkota, Joanne Salas, Lauren Garfield
American Journal of Preventive Medicine.2016; 51(6): 933. CrossRef
Effects of corticotropin-releasing hormone receptor 1 SNPs on major depressive disorder are influenced by sex and smoking status
Bruna S. da Silva, Diego L. Rovaris, Jaqueline B. Schuch, Nina R. Mota, Renata B. Cupertino, Angelita P. Aroche, Guilherme P. Bertuzzi, Rafael G. Karam, Eduardo S. Vitola, Luciana Tovo-Rodrigues, Eugenio H. Grevet, Claiton H.D. Bau
Journal of Affective Disorders.2016; 205: 282. CrossRef
Emotional and Affective Temperaments in Smoking Candidates for Bariatric Surgery
Karin Daniele Mombach, Cesar Luis de Souza Brito, Alexandre Vontobel Padoin, Daniela Schaan Casagrande, Claudio Cora Mottin, Franco Folli
PLOS ONE.2016; 11(3): e0150722. CrossRef
Mood, Mood Regulation, and Frontal Systems Functioning in Current Smokers, Long-Term Abstinent Ex-Smokers, and Never-Smokers
Michael Lyvers, Cassandra Carlopio, Vicole Bothma, Mark S. Edwards
Journal of Psychoactive Drugs.2014; 46(2): 133. CrossRef
How robust is the association between smoking and depression in adults? A meta-analysis using linear mixed-effects models
Tana M. Luger, Jerry Suls, Mark W. Vander Weg
Addictive Behaviors.2014; 39(10): 1418. CrossRef
Changes in prevalence of depression and anxiety following smoking cessation: results from an international cohort study (ATTEMPT)
L. Shahab, S. Andrew, R. West
Psychological Medicine.2014; 44(1): 127. CrossRef
The impact of lifestyle factors on the 2-year course of depressive and/or anxiety disorders
Lynn Boschloo, Kerstin G. Reeuwijk, Robert A. Schoevers, Brenda W.J.H. Penninx
Journal of Affective Disorders.2014; 159: 73. CrossRef
Prenatal maternal depression is associated with low birth weight through shorter gestational age in term infants in Korea
Hyoung Yoon Chang, Katherine M. Keyes, Kyung-Sook Lee, In Ae Choi, Se Joo Kim, Kyung Won Kim, Youn Ho Shin, Kang Mo Ahn, Soo-Jong Hong, Yee-Jin Shin
Early Human Development.2014; 90(1): 15. CrossRef
Heavy overtime work and depressive disorder among male workers
R. Kato, Y. Haruyama, M. Endo, A. Tsutsumi, T. Muto
Occupational Medicine.2014; 64(8): 622. CrossRef
Inverted U shaped effect of nicotine on the severity of depressive symptoms: A population-based survey
Ammar W. Ashor
Journal of Young Pharmacists.2013; 5(2): 60. CrossRef
Mood, mood regulation expectancies and frontal systems functioning in current smokers versus never-smokers in China and Australia
Michael Lyvers, Cassandra Carlopio, Vicole Bothma, Mark S. Edwards
Addictive Behaviors.2013; 38(11): 2741. CrossRef
Smoking is a predictor of depression onset among National Guard soldiers
Renee D. Goodwin, Marta Prescott, Marijo Tamburrino, Joseph R. Calabrese, Israel Liberzon, Sandro Galea
Psychiatry Research.2013; 206(2-3): 321. CrossRef
Compositional and Contextual Factors Related to Area Differentials in Suicide
Eunjeong Kang
Korean Journal of Health Education and Promotion.2013; 30(1): 41. CrossRef
Trends in the Prevalence of Tobacco Use in the United States, 1991–1992 to 2004–2005
Roberto Secades-Villa, Mark Olfson, Mayumi Okuda, Natalie Velasquez, Gabriela Pérez-Fuentes, Shan-Min Liu, Carlos Blanco
Psychiatric Services.2013; 64(5): 458. CrossRef
Association of smoking and nicotine dependence with severity and course of symptoms in patients with depressive or anxiety disorder
Mumtaz Jamal, A.J. Willem Van der Does, Pim Cuijpers, Brenda W.J.H. Penninx
Drug and Alcohol Dependence.2012; 126(1-2): 138. CrossRef
Differences in happiness between smokers, ex-smokers and never smokers: cross-sectional findings from a national household survey
Lion Shahab, Robert West
Drug and Alcohol Dependence.2012; 121(1-2): 38. CrossRef
A twin study of depression and nicotine dependence: Shared liability or causal relationship?
Alexis C. Edwards, Kenneth S. Kendler
Journal of Affective Disorders.2012; 142(1-3): 90. CrossRef
Age at Smoking Onset and the Onset of Depression and Anxiety Disorders
M. Jamal, A. J. W. V. d. Does, B. W. J. H. Penninx, P. Cuijpers
Nicotine & Tobacco Research.2011; 13(9): 809. CrossRef
Tobacco smoking and depression: results of a cross-sectional study
Vanessa Argondizo dos Santos, Ana Maria Migott, Claiton Henrique Dotto Bau, José Miguel Chatkin
British Journal of Psychiatry.2010; 197(5): 413. CrossRef

Self-Rating Perceived Health: The Influence on Health Care Utilization and Death Risk.: Sun Seog Kweon, Sang Yong Kim, Jeong Soo Im, Seok Joon Sohn, Jin Su Choi; Korean J Prev Med. 1999;32(3):355-360.

2,039 View
32 Download

Abstract PDF: OBJECTIVES
This 3-year longitudinal study was conducted to evaluate the influence of self-rating health perception on health care utilization and all cause-death risk. METHODS: The hypothesis was tested using a community-based samples, among which subjects 3,414 were interviewed in 1995. Self-rating health perception was assessed by single-item question. Three components of health care utilization amount(number of visits, number of medications, yearly health care expenses) per year were measured using medical insurance data during 3-year follow-up period among subjects in district health care insurance. There were 123 deaths from all causes among 3,085 subjects interviewed. RESULTS: The results showed that those who had poor health perception revealed more increases in the amount of health care utilization than good health perception group (p<0.05). After adjusting for age and sex, the poor health perception group had higher death risk over 3 years than good health perception group(hazard ratio=1.88). but, after adjusting health care utility, supplementary, was not significant. CONCLUSION: These results suggest that self-rating health percep-tion was associated with difference in health care utilization and all cause-death risk.; Summary

Twelve-year Study on Body Mass Index Changes of Obese Adolescents.: Yun Ju Kang, Il Suh, Chang Ho Hong, Jong Ku Park; Korean J Prev Med. 1994;27(4):665-676.

2,012 View
21 Download

Abstract PDF: The purpose of this study is to observe the longitudinal changes in BMI (Body Mass Index) of obese and non-obese 3rd. grade high school students in Seoul for 12 years and to see the trends of overt weight gain in obese adolescents. The results are as follows; 1. The average annual increasing rates of body mass indices in male students were 1.14kg/m2 in obese group and 0.59 in non-obese group. In female students, the average annual increasing rates of body mass indices were 0.93kg/m2 in obese group and 0.53kg/m2 in non-obese group. 2. The change rate of BMI for 12 years was significantly higher in obese group than non-obese group. 3. Puberty had less influence on the change rate of BMI in obese group compared to non-obese group. 4. In obese group, 71.8% of the variance in BMI at 17 can be predicted by BMI at 16 years in male students. In female students 44.4% can be predicted by BMI at age 16. 5. Among the 17-year-old obese students, 58.8% of the males and 56.2% of females were found not to have been obese at 7 years of age. 6. Among the 17-year-old obese students, those who were obese at 7 years of age were found to have higher BMI at later ages than those who were in the non-obese group. Obese adolescents were more likely to be obese in their childhood than non-obese group. There was no optimal age for the significant weight gain and the increasing rate of BMI was constantly higher in obese group than in non-obese group. Due to the fact that child obesity in early age contributes to obesity in adolescence, close observation is advised on the other hand, a large proportion of obese adolescents can be preventable by early interventions, because about 50% of obese adolescents were not obese in early elementary school age.; Summary

A Longitudinal Study of the Relationship Between Health Behavior Risk Factors and Dependence in Activities of Daily Living.: Sang Hyuk Jung, Truls Oslash stbye, Kyoung Ok Park; J Prev Med Public Health. 2006;39(3):221-228.

2,269 View
102 Download

Abstract PDF: OBJECTIVES
The purpose of this study was to shed further light on the effect of modifiable health behavior risk factors on dependence in activities of daily living, defined in a multidimensional fashion. METHODS: The study participants were 10,278 middle aged Americans in a longitudinal health study, the Health and Retirement Survey (HRS). A multi-stage probability sampling design incorporating the effect of population sizes (Metropolitan and non-metropolitan), ethnicity (the non-Hispanic White, the Hispanic, and the Black), and age (age 51-61) was utilized. Basic Activities of Daily Living (ADL) were measured using five activities necessary for survival (impairment in dressing, eating, bathing, sleeping, and moving across indoor spaces). Explanatory variables were four health behavior risk factors included smoking, exercise, Body Mass Index (BMI), and alcohol consumption. RESULTS: Most participants at baseline were ADL independent (1992). 97.8% of participants were independent in all ADL's at baseline and 78.2% were married. Approximately 27.5% were current smokers at baseline, and the subjects reported moderate or heavy exercise were 74.8%. All demographic characteristics and behavioral risk factors were significantly associated with the ADL status at Wave 4 except alcohol consumption. Risk behaviors such as current smoking, sedentary life style and high BMI at Wave 1 were associated with ADL status deterioration; however, moderate alcohol consumption tended to be more related to better ADL status than abstaining at Wave 4. ADL status at Wave 1 was the strongest factor and the next was exercise and smoking affecting ADL status at Wave 4. People who were in ADL dependent at Wave 1 were 15.17 times more likely to be ADL dependent at Wave 4 than people who were in ADL independent at Wave 1. Concerning smoking cigarettes, people who kept only light exercise or sedentary life style at Wave 1 were 1.70 times more likely to be died at Wave 4 than the people who did not smoke at Wave 1. CONCLUSIONS: All demographics and health behaviors at wave 1 had consistently similar OR trends for ADL status to each other except alcohol consumption. Smoking and exercise in health behaviors, and age and gender in demographics at Wave 1 were significant factors associated with ADL group separation at Wave 4.; Summary

English Abstract

Socioeconomic Mortality Inequality in Korea: Mortality Follow-up of the 1998 National Health and Nutrition Examination Survey(NHANES) Data.: Young Ho Khang, Hye Ryun Kim; J Prev Med Public Health. 2006;39(2):115-122.

2,794 View
73 Download

Abstract PDF: OBJECTIVES
This study was conducted to examine the relationships of the several socioeconomic position indicators with the mortality risk in a representative longitudinal study of South Korea. METHODS: The 1998 National Health and Nutrition Examination Survey was conducted on a cross-sectional probability sample of South Korean households, and it contained unique 13-digit personal identification numbers that were linked to the data on mortality from the National Statistical Office of Korea. Of 5,607 males and females, 264 died between 1999 and 2003. Cox's regression was used to estimate the relative risks (RR) and their 95% confidence intervals (CI) of mortality. RESULTS: Socioeconomic differences in mortality were observed after adjustments were made for gender and age. Compared with those people having college or higher education, those people without any formal education had a greater mortality risk (RR=2.21, 95% CI=1.12-4.40). The mortality risk among manual workers was significantly greater than that for the non-manual workers (RR=2.73, 95% CI=1.47-5.06). A non-standard employment status was also associated with an increase in mortality: temporary or daily workers had a greater mortality risk than did the full-time workers (RR=3.01, 95% CI=1.50-6.03). The mortality risk for the low occupational class was 3.06 times greater than that of the high and middle occupational classes (95% CI=1.75-5.36). In addition, graded mortality differences according to equivalized monthly household income were found. A reduction of monthly household income by 500 thousand Korean Won (about 400 US dollars) was related with a 20% excess risk of mortality. Self-reported poor living standards were also associated with an increased risk of mortality. Those without health insurance had a 3.63 times greater risk of mortality than the insured (95% CI=1.61-8.19). CONCLUSIONS: This study showed the socioeconomic differentials in mortality in a national longitudinal study of South Korea. The existence of socioeconomic mortality inequalities requires increased social discussion on social policies in Korean society. Furthermore, the mechanisms for the socioeconomic inequalities of mortality need to be explored in future studies.; Summary

First
Prev
Page of 1
Next
Last

Search