NCD-Related Lifestyle Patterns from Childhood to Adolescence: A 13 Years Longitudinal Study Yi-Han Chang a, Lee-Lan Yen a,b, Hsing-Yi Chang b, Chi-Chen Wu b a Institute of Health Policy and Management, College of Public Health, National Taiwan University, Taipei City, Taiwan b Division of Preventive Medicine and Health Service Research, Institute of Population Health Science, National Health Research Institutes, Zhunan Town, Miaoli County, Taiwan, ROC APHA 143rd Annual Meeting and Exposition

Outline Background Method Result Conclusion 2

Non-communicable diseases (NCDs) known as chronic diseases 4 main types of NCDs: cardiovascular diseases,cancers, chronic respiratory diseases and diabetes (WHO, 2015) Burdens of NCDs 2012: 38 million people have died of NCDs (68% of all deaths globally) Sixteen million NCD deaths occur before the age of 70 (WHO, 2015) : NCD deaths have increased the most in the WHO South-East Asia Region and Western Pacific Region (WHO, 2014) In Taiwan, eight of the ten leading causes of death were NCDs responsible for 66% of deaths in 2013 (MOHW, 2014) 3

Modifiable behavioural risk factors most common modifiable behaviors (WHO, 2013) typically establish during adolescence and persist throughout life (Kipping, Campbell, MacArthur, Gunnell, & Hickman, 2012) unhealthy diet tobacco use harmful use of alcohol physical inactivity 4

Healthy lifestyle (Dever, 1976 、 1991) 5 27% 19% Human Biology Environment 43% 11% Lifestyle Health Care Organization (Lalonde, 1974) A healthy lifestyle is… aggregation of decisions by individuals which affect their health and over which they more or less have control (Lalonde, 1974) Patterns of behavior that maximize one's quality of life and decrease one's susceptibility to negative health outcomes (Report of the 2000 Joint Committee on Health Education and Promotion Terminology, 2002) “collective patterns of health-related behavior based on choices from options available to people according to their life chances” (Cockerham, 2000, 2007)

Lifestyle or single behavior? 6  Lifestyle is a collective pattern of health-related behaviors Risk health behaviors tend to cluster together coexistence of risk behaviors increases the likelihood of NCDs Interventions targeting the underlying lifestyle and associated identities may be effective than focusing on a single behavior

Knowledge gap in healthy lifestyle research focus on single behavior most researches in a healthy lifestyle perspective targeted adults population cross-sectional data various behavior indicators In this study… using a longitudinal data during childhood and adolescence finding underlying lifestyle patterns placing emphasis on the four main behaviors related to NCDs 7

Aim To investigates distinct lifestyle development patterns and the predictors from childhood to adolescence. 8

Outline Background Method Result Conclusion 9

Data Child and Adolescent Behavior in Long-term Evolution (CABLE) project 2001-now SAMPLE ： all students in grade one and four 6 small, 2 medium, 1 large schools from each location were selected Schools size: categorized as small, medium or large (based on the nunber of 1 st grade students) POPULATION ： 152 primary schools in Taipei City and Hsinchu Country in Taiwan 10

Methods of repeat measurement Latent Growth Curve Model(LGCM) Multilevel Modeling Growth Mixture Models(GMMs) Group-based Trajectory Model Repeated-measures Latent Class Analysis Intercept behavior time1 behavior time2 behavior time3 Class Latent class Categorical variable Slope 11

Variable - NCD-related Lifestyle Patterns four behavior indicators measured when sample was grade 5 th, 7 th, 9 th, 10 th, 12 th, 14 th repeated-measures latent class analysis (RMLCA) 【 Categorical variable 】 12 【 Categorical variable 】

Variables - Focus variables Gender Boy, Girl Mother’s Education Junior high or below, Senior high, College and above Husband's education Junior high or below, Senior high, College and above Parents marital status Married, Divorced or single Family monthly income 100,000 (NTD) Emotional Variability 0~10 13

Data Analysis Statistics Method repeated-measures latent class analysis (RMLCA) multinomial logistic regression model Statistics Software SAS 9.2

Outline Background Method Result Conclusion 15

Characteristics of Participants Total : 2,415 students 51.41% boys father’s education : 48.73% college and above, 34.94% high school and 16.33% junior high and under mother’s education: 46.53% high school, 36.41% college and above and 17.77% junior high and under Income: 52.89% middle income family, 27.07% high and 20.04% low 8% students came from single parent family mean score of emotional variability is 3.98 (range 0-10) 16

Bayesian information criterion values 17

item probability 18 V: eating vegetables and fruits everyday PA: physical activity three times a week T: no tobacco use A: no alcohol use

Class 1- persistently inactive lifestyle (18.64%) 19 V: eating vegetables and fruits everyday PA: physical activity three times a week T: no tobacco use A: no alcohol use

Class 2-high risk lifestyle (12.02%) 20 V: eating vegetables and fruits everyday PA: physical activity three times a week T: no tobacco use A: no alcohol use

Class 3- early alcohol use (12.64%) 21 V: eating vegetables and fruits everyday PA: physical activity three times a week T: no tobacco use A: no alcohol use

Class 4- lack of health promotion lifestyle (19.29%) 22 V: eating vegetables and fruits everyday PA: physical activity three times a week T: no tobacco use A: no alcohol use

Class 5-persistent healthy lifestyle (22.97%) 23 V: eating vegetables and fruits everyday PA: physical activity three times a week T: no tobacco use A: no alcohol use

Class 6- non-smoking lifestyle(14.44%) 24 V: eating vegetables and fruits everyday PA: physical activity three times a week T: no tobacco use A: no alcohol use

25 1: persistently inactive lifestyle (18.64%), 2: high risk lifestyle (12.02%), 3: early alcohol use (12.64%), 4: lack of health promotion lifestyle(19.29%), 5: persistently healthy lifestyle (22.97%), 6: non-smoking (14.44%) Class 1Class 2Class 3 Class 4Class 5Class 6

Adjusted multinomial logistic regression models of the association of factors with NCD-related trajectory patterns among students in the CABLE cohort 1: persistently inactive lifestyle (18.64%), 2: high risk lifestyle (12.02%), 3: early alcohol use (12.64%), 4: lack of health promotion lifestyle(19.29%), 5: persistently healthy lifestyle (22.97%), 6: non-smoking (14.44%)

Outline Background Method Result Conclusion 27

NCD-related lifestyle development patterns were found The existence of heterogeneity of NCD-related lifestyle development patterns during childhood and adolescence was found. Unhealthy diet and inactivity behaviors existed even among those who presented non-smoking or non-drinking subgroups It is interesting to note latent classes that did not emerge in this analysis. For example, the model does not include a latent class characterized by improving healthy lifestyle. Adolescents got decreasing probability to live with healthy behaviors In all lifestyle patterns 28

Important factors associated with lifestyle We also found preliminary evidence of differential clustering by gender, parents’ education level, family income, parents’ marriage status and personal personality. 29 Critical time point good eating vegetables and fruits behaviors relatively stable from elementary school period alcohol use: junior high school period tobacco use: grade 7 (entry to junior high school)

Future research… To identify the mechanism of subgroups lifestyle patterns and the shared affecting factors, thus policies or interventions aim to multiple behaviors can be designed accordingly. 30

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