Age-period-cohort analysis and projection of cancer mortality in Hong Kong, 1998-2030

© Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY. Published by BMJ..

OBJECTIVES: To explore the relationship between immigration groups and cancer mortality, this study aimed to explore age, period, birth cohort effects and effects across genders and immigration groups on mortality rates of lung, pancreatic, colon, liver, prostate and stomach cancers and their projections.

DESIGN, SETTING, AND PARTICIPANTS: Death registry data in Hong Kong between 1998 and 2021, which were stratified by age, sex and immigration status. Immigration status was classified into three groups: locals born in Hong Kong, long-stay immigrants and short-stay immigrants.

METHODS: Age-period-cohort (APC) analysis was used to examine age, period, and birth cohort effects for genders and immigration groups from 1998 to 2021. Bayesian APC models were applied to predict the mortality rates from 2022 to 2030.

RESULTS: Short-stay immigrants revealed pronounced fluctuations of mortality rates by age and of relative risks by cohort and period effects for six types of cancers than those of long-stay immigrants and locals. Immigrants for each type of cancer and gender will be at a higher mortality risk than locals. After 2021, decreasing trends (p<0.05) or plateau (p>0.05) of forecasting mortality rates of cancers occur for all immigration groups, except for increasing trends for short-stay male immigrants with colon cancer (p<0.05, Avg+0.30 deaths/100 000 per annum from 15.47 to 18.50 deaths/100 000) and long-stay male immigrants with pancreatic cancer (p<0.05, Avg+0.72 deaths/100 000 per annum from 16.30 to 23.49 deaths/100 000).

CONCLUSIONS: Findings underscore the effect of gender and immigration status in Hong Kong on mortality risks of cancers that immigrants for each type of cancer and gender will be at a higher mortality risk than locals.

Medienart:

E-Artikel

Erscheinungsjahr:

2023

Erschienen:

2023

Enthalten in:

Zur Gesamtaufnahme - volume:13

Enthalten in:

BMJ open - 13(2023), 10 vom: 11. Okt., Seite e072751

Sprache:

Englisch

Beteiligte Personen:

Zhao, Yanji [VerfasserIn]
Zhuang, Zian [VerfasserIn]
Yang, Lin [VerfasserIn]
He, Daihai [VerfasserIn]

Links:

Volltext

Themen:

Journal Article
ONCOLOGY
Research Support, Non-U.S. Gov't
Risk Factors
STATISTICS & RESEARCH METHODS

Anmerkungen:

Date Completed 23.10.2023

Date Revised 23.10.2023

published: Electronic

Citation Status MEDLINE

doi:

10.1136/bmjopen-2023-072751

funding:

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

NLM363141898