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Salud Pública de México

versión impresa ISSN 0036-3634

Salud pública Méx vol.64 no.1 Cuernavaca ene./feb. 2022  Epub 06-Mar-2023

https://doi.org/10.21149/12518 

Artículos originales

Liver cancer mortality in Mexico: trend analysis from 1998 to 2018

Mortalidad por cáncer hepático en México: análisis de tendencias de 1998 a 2018

Christian S Álvarez, PhD, MPH1 

Priscilla Espinosa-Tamez, MD2  3 

Ruy López-Ridaura, MD, ScD2 

Héctor Lamadrid-Figueroa, MD, PhD2 

Javier Melchor-Ruan, MD4 

Katherine A McGlynn, PhD, MPH1 

Martín Lajous, MD, ScD2  5 

(1) Division of Cancer Epidemiology and Genetics, National Cancer Institute. Rockville, Maryland, USA.

(2) Centro de Investigación en Salud Poblacional, Instituto Nacional de Salud Pública. Mexico City, Mexico.

(3) University of California. San Francisco, California, USA.

(4) Departamento de Cirugía Oncológica, Instituto Nacional de Cancerología. Mexico City, Mexico.

(5) Department of Global Health and Population, Harvard T.H. Chan School of Public Health. Boston, Massachusetts, USA.


Abstract:

Objective:

To examine overall, sex, and state-specific liver cancer mortality trends in Mexico.

Materials and methods:

Joinpoint regression was used to examine the trends in age-standardized mortality rates of liver cancer between 1998-2018. Estimated annual percent change with 95% confidence intervals (95%CI) were computed. Age-period-cohort models were used to assess the effects of age, calendar year, and birth cohort.

Results:

The state-specific mortality rates ranged from 3.34 (Aguascalientes) to 7.96 (Chiapas) per 100 000 person-years. Sex-specific rates were roughly equal, nationwide. Overall, we observed a statistically significant decrease in liver cancer mortality rates between 1998-2018 (annual percent change, -0.8%; 95%CI -1.0, -0.6). The overall age-period-cohort models suggest that birth cohort may be the most important factor driving the trends.

Conclusions:

While there was overall decline in liver cancer mortality, differences in rates by region were observed. The regional differences may inform future studies of liver cancer etiology across the country.

Keywords: liver cancer; mortality; trends; Mexico; joinpoint; age-period-cohort

Resumen:

Objetivo:

Examinar la tendencia general, por sexo y estado, de mortalidad por cáncer hepático en México.

Material y métodos:

Se utilizó regresión joinpoint para examinar las tendencias en las tasas de mortalidad estandarizadas por edad de cáncer hepático (1998-2018). Se estimó el cambio porcentual anual con intervalos de confianza al 95% (IC95%). Se usaron modelos de edad-periodo-cohorte para evaluar el efecto de edad, año calendario y cohorte de nacimiento.

Resultados:

La mortalidad osciló entre 3.34 (Aguascalientes) y 7.96 (Chiapas) por 100 000 años-persona. La mortalidad por sexo fue relativamente similar a nivel nacional. La mortalidad general disminuyó entre 1998-2018 (cambio porcentual anual, -0.8%; IC95% -1.0, -0.6). La cohorte de nacimiento parece ser el factor más importante que afecta las tendencias.

Conclusiones:

A pesar de la disminución de mortalidad por cáncer hepático, se observó variación regional en las tasas. Estas diferencias podrían informar estudios futuros sobre la etiología de cáncer hepático en México.

Palabras clave: cáncer hepático; mortalidad; tendencias; México; joinpoint; edad-periodo-cohorte

Introduction

Primary liver cancer, the majority of which are hepatocellular carcinomas (HCC),1 is the sixth mostly occurring common cancer and the third leading cause of cancer mortality worldwide.2 The International Agency for Research on Cancer (IARC) estimates there were over 900 000 new cases and more than 800 000 liver cancer deaths globally in 2020.2 Most of the liver cancer burden falls on countries in Africa and Eastern Asia with China alone bearing over 45% of the total burden.2 Recent reports have noted that liver cancer rates are declining in Eastern Asia, but increasing in other parts of the world including North America.3,4

It has been suggested that the changing trends in liver cancer rates reflects the epidemiological transition of this disease.5 Major risk factors for liver cancer include hepatitis B virus (HBV), hepatitis C virus (HCV), excessive alcohol consumption, and aflatoxin B1 (AFB1) exposure.6 In addition, the metabolic cascade of metabolic syndrome, obesity, diabetes, and non-alcoholic fatty liver diseases (NAFLD) are now recognized as important risk factors for HCC in both high- and low-rate areas.1

Mexico is a country with heterogeneous urban-rural economic development, where geographic differences in liver cancer risk factors have been observed. While the overall prevalence of HBV and HCV infection is reported to be low in the country (<1.5%),7,8 aflatoxin exposure appears to be prevalent, particularly in rural regions. For example, our previous work found detectable levels of AFB1 in ~85% (n=100) of individuals aged 40-59 years old from Chiapas in southern Mexico, recruited from the National Health and Nutritional Survey 2018-19 (Encuesta Nacional de Salud y Nutrición, Ensanut).* In addition, obesity and related metabolic conditions have increased dramatically in Mexico.9 Moreover, the leading causes of deaths in the country are associated with obesity, including cardiovascular disease, cancer, diabetes, and chronic liver diseases.10

Previous reports have found that liver-related mortality increased in Mexico in the 2000s.11,12 In particular, a study that examined liver cancer mortality rates in the early 2000s reported that deaths increased from 2000 to 2006, with regional differences.13 To our knowledge, a new assessment of liver cancer mortality has not been conducted. Therefore, the purpose of the current study was to examine overall, as well as sex- and state-specific, liver cancer mortality trends in Mexico.

Materials and methods

Data sources

Numbers of liver cancer deaths (1998-2018) by age, gender, state of residence, and year of death were retrieved from the mortality databases of the Instituto Nacional de Estadística y Geografía (Inegi). Topography codes C22.0-C22.9 of the International Classification of Disease, tenth revision (ICD-10) were used to identify all liver cancer deaths. Population denominators were obtained from the respective census reported by the Inegi. For the remaining years, estimations were obtained from Consejo Nacional de Población (Conapo) census and estimates.14

Statistical analysis

Liver cancer age-specific mortality rates (ASMR), adjusted to the World standard Segi population,15 were estimated for 21 calendar years between 1998-2018 (1-year intervals) and 19 different age groups (e.g. 0, 1-4, 5-9, 10-14,…,85+). In addition to overall rates, mortality was examined by sex and states of Mexico (31 states and Mexico City). Furthermore, the male:female (M:F) ratio of rates was calculated by state.

Trend analysis: Joinpoint

Overall and sex-specific trends in liver cancer by states of Mexico were plotted for the entire period (1998-2018). Joinpoint regression analysis was used to obtain the estimated annual percent change (EAPC), the average annual percent change (AAPC), and 95% confidence intervals (95%CI) using the National Cancer Institute’s Joinpoint Regression Program (version 4.8.0.1; Information Management Services; Silver Spring, Maryland). Joinpoint regression identifies statistically significant trend change points (joinpoints) and the rate of change in each trend segment using a Monte Carlo permutation method.16 A maximum number of three joinpoints was allowed. A segment was considered significant if the slope of the regression line was statistically different from zero (p<0.05).

Age-Period-Cohort analysis

Age-period-cohort (APC) models were used to evaluate the effects of age, period (calendar year), and birth cohort. The APC method fits a log-linear model with a Poisson distribution to the observed data to estimate age, period, and cohort effects in a multiplicative APC model.17 This method is known as the “classical” approach and it is represented by the formula below:

Logλa,p=f(a)+g(p)+h(c)

This formula assumes that the expected log-mortality rates λa,p is equal to a linear combination of time-related variables or effects that adjust for age (a), calendar year (p) and birth cohort (c), where c=p-a.17 In order to address non-identifiability due to the linear dependency of each time-related variable of the two, two-effect models age-period (AP-C), and age-cohort (AC-P) were first selected and the remaining effect (cohort or period) was then fit to the respective model’s residual using natural splines to reduce random variation.17 Three degrees of freedom/knots for age, six for cohort, and two for period were used for the models. The best-fitted models were determined on the basis of the Akaike information criterion (AIC). The analysis of APC was performed using the Epi package in the R statistical software version 4.0.3.

Results

Over 100 000 liver cancer deaths were registered between 1998-2018, and nearly 32 000 deaths occurred in the last 5-year period. Figure 1 shows state-specific liver cancer mortality rates for the most recent time period 2014-2018. The ASMR ranged from 3.34 (in Aguascalientes) to 7.96 per 100 000 person-years (py) (in Chiapas). The highest rates were seen in the south eastern states and the Yucatan peninsula, including Chiapas (7.96 per 100 000 py), Veracruz (7.94 per 100 000 py), Yucatan (7.24 per 100 000 py), and Tabasco (7.05 per 100 000 py). In contrast, the rates in northern and several central states were lower than five per 100 000 py.

Figure 1 Age-adjusted liver cancer mortality rates per 100 000 by state in Mexico, all ages, 2014-2018 

Figure 2 presents the age-adjusted male and female mortality rates by state during the most recent time period 2014-2018. Overall, sex-specific rates were nearly equal. The nationwide mortality rates were 5.39 per 100 000 py among men and 4.75 per 100 000 py among women (male:female [M:F] ratio=1.1). The highest M:F ratios were seen in northern states (e.g. Baja California Sur [M:F ratio=2.0], Nuevo Leon [M:F ratio=1.6], Sonora and Tamaulipas [M:F ratio=1.5]).

Figure 2 Age-adjusted male and female liver cancer mortality rates by state in Mexico, all ages, 2014-2018 

Over the entire 21-year period, liver cancer mortality rates statistically significantly decreased at an EAPC of -0.8% (95%CI: -1.0, -0.6; p<0.05) (table I). The ASMR decreased from 5.77 per 100 000 py in 1998 to 4.76 per 100 000 py in 2018. The decline occurred in both sexes but was statistically significant only among women (AAPC -1.2, 95%CI: -1.5, -1.0; p<0.05) (table I and figure 3). State-specific trends varied across the country. A decline in liver cancer deaths was statistically significant in several states, including Sinaloa (-2.3%, 95%CI: -2.9, -1.6; p<0.05), Baja California Sur (-2.2%, 95%CI: -4.2, -0.1; p<0.05), and Aguascalientes (-2.1%, 95%CI: -3.4, -0.9, p<0.05) (table I and figure 3). In contrast, there were statistically significant increases in mortality rates in Oaxaca but only among men (AAPC: 1.4%, 95%CI: 0.7, 2.1; p<0.05), where the ASMR increased from 5.22 per 100 000 py in 1998 to 6.14 per 100 000 py in 2018. In other states, mortality rates remained stable for the entire period.

Table I Age-standardized mortality rates (ASMR), estimated annual and average annual percent changes in liver cancer rates by sex and state in Mexico, all ages, 1998-2018 

Population

Segment 1

Segment 2

Segment 3

Segment 4

AAPC, 1998-2018

ASMR

ASMR

Years

EAPC, %

95%CI

Years

EAPC, %

95%CI

Years

EAPC, %

95%CI

Years

EAPC, %

95%CI

%

95%CI

1998

2018

Mexico (nationwide)

All

1998-2018

-0.8

(-1.0, -0.6)

-0.8

(-1.0, -0.6)

5.77

4.76

Men

1998-2004

0.5

(-0.9, 1.9)

2004-2008

-2.5

(-6.3, 1.4)

2008-2016

0.7

(-0.3, 1.6)

2016-2018

-3.6

(-9.8, 3.2)

-0.5

(-1.5, 0.6)

5.84

5.14

Women

1998-2018

-1.2

(-1.5, -1.0)

-1.2

(-1.5, -1.0)

5.74

4.43

Aguascalientes

All

1998-2018

-2.1

(-3.4, -0.9)

-2.1

(-3.4, -0.9)

4.00

2.40

Men

1998-2018

-2.0

(-3.2, -0.8)

-2.0

(-3.2, -0.8)

5.08

2.56

Women

1998-2018

-2.4

(-4.3, -0.4)

-2.4

(-4.3, -0.4)

3.18

2.27

Baja California

All

1998-2018

-0.1

(-1.1, 0.9)

-0.1

(-1.1, 0.9)

3.65

4.58

Men

1998-2018

0.4

(-0.9, 1.7)

0.4

(-0.9, 1.7)

4.18

5.74

Women

1998-2018

-0.6

(-1.9, 0.8)

-0.6

(-1.9, 0.8)

3.20

3.56

Baja California Sur

All

1998-2018

-2.2

(-4.2, -0.1)

-2.2

(-4.2, -0.1)

5.04

3.31

Men

1998-2018

-0.6

(-2.4, 1.3)

-0.6

(-2.4, 1.3)

10.72

8.52

Women

1998-2018

-3.7

(-6.5, -0.8)

-3.7

(-6.5, -0.8)

4.35

2.68

Campeche

All

1998-2018

0.0

(-1.6, 1.6)

0.0

(-1.6, 1.6)

8.87

7.34

Men

1998-2018

-0.6

(-2.4, 1.3)

-0.6

(-2.4, 1.3)

10.72

8.52

Women

1998-2018

0.6

(-1.4, 2.5)

0.6

(-1.4, 2.5)

6.96

6.22

Colima

All

1998-2018

-0.5

(-1.9, 0.9)

-0.5

(-1.9, 0.9)

4.41

4.87

Men

1998-2018

-0.6

(-2.1, 1.0)

-0.6

(-2.1, 1.0)

5.71

5.67

Women

1998-2018

-0.5

(-2.3, 1.4)

-0.5

(-2.3, 1.4)

3.26

4.24

Chiapas

All

1998-2014

0.4

(-0.5, 1.2)

2014-2018

-3.9

(-9.5, 1.9)

-0.5

(-1.8, 0.8)

9.32

7.30

Men

1998-2018

0.1

(-0.7, 1.0)

0.1

(-0.7, 1.0)

8.32

7.13

Women

1998-2018

-0.5

(-1.2, 0.2)

-0.5

(-1.2, 0.2)

10.34

7.47

Chihuahua

All

1998-2011

-3.4

(-4.9, -1.8)

2011-2018

3.0

(-0.6, 6.7)

-1.2

(-2.6, 0.3)

5.07

3.98

Men

1998-2018

-1.3

(-2.4, -0.2)

-1.3

(-2.4, -0.2)

4.69

3.96

Women

1998-2018

-1.7

(-2.9, -0.4)

-1.7

(-2.9, -0.4)

5.41

4.01

Durango

All

1998-2018

-1.8

(-2.6, -1.0)

-1.8

(-2.6, -1.0)

4.25

3.32

Men

1998-2018

-0.9

(-1.9, 0.1)

-0.9

(-1.9, 0.1)

4.72

3.52

Women

1998-2018

-2.7

(-3.9, -1.4)

-2.7

(-3.9, -1.4)

3.85

3.14

Guanajuato

All

1998-2018

-0.7

(-1.4, -0.0)

-0.7

(-1.4, -0.0)

4.68

4.48

Men

1998-2008

-3.7

(-6.2, -1.1)

2008-2018

3.1

(0.8, 5.5)

-0.3

(-1.9, 1.3)

4.76

5.08

Women

1998-2018

-1.2

(-2.1, -0.4)

-1.2

(-2.1, -0.4)

4.64

3.97

Guerrero

All

1998-2018

-0.4

(-1.3, 0.6)

-0.4

(-1.3, 0.6)

4.03

3.82

Men

1998-2018

0.1

(-1.0, 1.2)

0.1

(-1.0, 1.2)

3.91

4.53

Women

1998-2018

-0.8

(-2.1, 0.6)

-0.8

(-2.1, 0.6)

4.12

3.2

Hidalgo

All

1998-2018

0.0

(-0.8, 0.8)

0.0

(-0.8, 0.8)

5.81

5.86

Men

1998-2018

0.7

(-0.4, 1.9)

0.7

(-0.4, 1.9)

5.76

5.49

Women

1998-2018

-0.7

(-1.5, 0.2)

-0.7

(-1.5, 0.2)

5.90

6.21

Jalisco

All

1998-2018

-1.6

(-2.1, -1.1)

-1.6

(-2.1, -1.1)

5.07

3.69

Men

1998-2018

-1.3

(-2.0, -0.6)

-1.3

(-2.0, -0.6)

5.00

3.87

Women

1998-2018

-1.8

(-2.3, -1.3)

-1.8

(-2.3, -1.3)

5.17

3.52

Mexico City

All

1998-2018

-1.6

(-1.9, -1.2)

-1.6

(-1.9, -1.2)

5.95

4.42

Men

1998-2018

-1.3

(-1.8, -0.8)

-1.3

(-1.8, -0.8)

6.19

4.90

Women

1998-2018

-1.9

(-2.2, -1.5)

-1.9

(-2.2, -1.5)

5.91

4.04

Mexico (state)

All

1998-2018

-1.1

(-1.4, -0.7)

-1.1

(-1.4, -0.7)

4.88

3.98

Men

1998-2018

-0.3

(-0.7, 0.2)

-0.3

(-0.7, 0.2)

4.26

3.97

Women

1998-2018

-1.7

(-2.2, -1.2)

-1.7

(-2.2, -1.2)

5.38

3.98

Michoacan

All

1998-2012

-1.7

(-3.0, -0.5)

2012-2015

5.6

(-17.2, 34.7)

2015-2018

-11.4

(-21.9, 0.5)

-2.2

(-5.9, 1.6)

4.94

3.33

Men

1998-2012

-1.9

(-3.8, 0.1)

2012-2015

11.4

(-23.2, 61.7)

2015-2018

-17.1

(-32.0, 1.1)

-2.5

(-8.1, 3.4)

4.57

3.01

Women

1998-2018

-1.6

(-2.4, -0.9)

-1.6

(-2.4, -0.9)

5.27

3.61

Morelos

All

1998-2018

-0.7

(-1.5, 0.1)

-0.7

(-1.5, 0.1)

5.91

3.93

Men

1998-2018

-0.4

(-1.3, 0.6)

-0.4

(-1.3, 0.6)

5.76

3.90

Women

1998-2018

(-2.0, -0.1)

(-2.0, -0.1)

6.01

3.90

Nayarit

All

1998-2018

-1.6

(-2.5, -0.6)

-1.6

(-2.5, -0.6)

6.67

4.58

Men

1998-2018

-1.9

(-3.5, -0.2)

-1.9

(-3.5, -0.2)

5.54

3.21

Women

1998-2018

-1.3

(-2.4, -0.2)

-1.3

(-2.4, -0.2)

7.76

5.91

Nuevo Leon

All

1998-2018

(-1.7, -0.3)

(-1.7, -0.3)

6.22

3.96

Men

1998-2018

-0.5

(-1.2, 0.1)

-0.5

(-1.2, 0.1)

7.28

5.00

Women

1998-2018

-1.7

(-2.6, -0.7)

-1.7

(-2.6, -0.7)

5.39

3.09

Oaxaca

All

1998-2018

0.5

(0.0, 0.9)

0.5

(0.0, 0.9)

5.68

5.79

Men

1998-2018

1.4

(0.7, 2.1)

1.4

(0.7, 2.1)

5.22

6.14

Women

1998-2018

-0.4

(-1.2, 0.4)

-0.4

(-1.2, 0.4)

6.06

5.5

Puebla

All

1998-2018

0.5

(-0.1, 1.1)

0.5

(-0.1, 1.1)

5.05

5.71

Men

1998-2018

0.7

(-0.1, 1.6)

0.7

(-0.1, 1.6)

4.59

5.89

Women

1998-2018

0.3

(-0.3, 0.9)

0.3

(-0.3, 0.9)

5.48

5.56

Queretaro

All

1998-2018

0.3

(-1.0, 1.5)

0.3

(-1.0, 1.5)

3.38

4.37

Men

1998-2018

0.5

(-0.9, 1.9)

0.5

(-0.9, 1.9)

3.90

4.26

Women

1998-2018

0.0

(-1.7, 1.7)

0.0

(-1.7, 1.7)

3.24

4.47

Quintana Roo

All

1998-2016

-0.7

(-2.1, 0.6)

2016-2018

24.3

(-5.6, 63.6)

1.5

(-1.2, 4.4)

5.93

7.67

Men

1998-2009

-3.1

(-6.8, 0.9)

2009-2013

12.9

(-9.7, 41.1)

2013-2016

-13.4

(-41.7, 28.5)

2016-2018

31.3

(-5.9, 83.1)

1.3

(-5.9, 9.1)

5.72

7.69

Women

1998-2016

-1.7

(-3.7, 0.3)

2016-2018

29.7

(-13.9, 95.2)

1.0

(-3.1, 5.3)

6.16

7.7

San Luis Potosi

All

1998-2018

-0.5

(-1.2, 0.2)

-0.5

(-1.2, 0.2)

6.56

5.21

Men

1998-2018

-0.4

(-1.3, 0.5)

-0.4

(-1.3, 0.5)

7.88

5.69

Women

1998-2018

-0.6

(-1.6, 0.4)

-0.6

(-1.6, 0.4)

5.33

4.78

Sinaloa

All

1998-2018

-2.3

(-2.9, -1.6)

-2.3

(-2.9, -1.6)

5.41

3.78

Men

1998-2018

-2.1

(-3.3, -0.9)

-2.1

(-3.3, -0.9)

6.52

4.42

Women

1998-2018

-2.4

(-3.5, -1.3)

-2.4

(-3.5, -1.3)

4.31

3.18

Sonora

All

1998-2018

-0.9

(-1.8, 0.0)

-0.9

(-1.8, 0.0)

5.03

3.93

Men

1998-2018

-0.5

(-1.4, 0.5)

-0.5

(-1.4, 0.5)

5.47

4.67

Women

1998-2018

-1.5

(-3.0, 0.0)

-1.5

(-3.0, 0.0)

4.56

3.25

Tabasco

All

1998-2018

-0.7

(-1.3, -0.1)

-0.7

(-1.3, -0.1)

8.71

6.8

Men

1998-2018

0.3

(-0.5, 1.1)

0.3

(-0.5, 1.1)

7.63

8.11

Women

1998-2018

-1.8

(-2.8, -0.8)

-1.8

(-2.8, -0.8)

9.77

5.52

Tamaulipas

All

1998-2018

-1.5

(-2.4, -0.7)

-1.5

(-2.4, -0.7)

7.65

4.63

Men

1998-2018

-1.6

(-2.5, -0.6)

-1.6

(-2.5, -0.6)

9.91

6.2

Women

1998-2018

-1.5

(-2.5, -0.5)

-1.5

(-2.5, -0.5)

5.62

3.28

Tlaxcala

All

1998-2018

-0.4

(-1.8, 1.0)

-0.4

(-1.8, 1.0)

5.55

3.74

Men

1998-2018

0.0

(-1.8, 1.9)

0.0

(-1.8, 1.9)

3.05

2.62

Women

1998-2018

-0.8

(-2.8, 1.2)

-0.8

(-2.8, 1.2)

7.78

4.74

Veracruz

All

1998-2004

2.7

(1.0, 4.3)

2004-2007

-5.6

(-13.4, 2.9)

2007-2016

0.3

(-0.6, 1.2)

2016-2018

-7.1

(-14.1, 0.5)

-0.7

(-2.1, 0.8)

8.36

7.19

Men

1998-2018

-0.3

(-0.8, 0.2)

-0.3

(-0.8, 0.2)

8.65

7.68

Women

1998-2018

-1.2

(-1.7, -0.6)

-1.2

(-1.7, -0.6)

8.13

6.61

Yucatan

All

1998-2018

-0.6

(-1.3, 0.1)

-0.6

(-1.3, 0.1)

8.92

6.28

Men

1998-2009

-2.6

(-4.4, -0.7)

2009-2012

13.9

(-12.3, 47.8)

2012-2018

-3.9

(-7.6, -0.2)

-0.7

(-4.4, 3.2)

8.8

7.45

Women

1998-2018

-1.5

(-2.5, -0.4)

-1.5

(-2.5, -0.4)

9.05

5.26

Zacatecas

All

1998-2018

-1.1

(-2.3, 0.1)

-1.1

(-2.3, 0.1)

5.13

4.2

Men

1998-2018

-0.3

(-1.8, 1.2)

-0.3

(-1.8, 1.2)

3.44

4.48

Women

1998-2018

-2.0

(-3.5, -0.5)

-2.0

(-3.5, -0.5)

6.71

3.95

In bold denotes that the trend was statistically significant different from 0 at the alpha= 0.05 level

Figure 3 Trends in liver cancer mortality rates in Mexico by sex and state, all ages, 1998-2018 

Figure 4 shows the results of the overall and sex-specific APC analysis for each of the models (APC, AC-P [age-cohort model] in blue, and AP-C [age-period model] in red). The liver cancer mortality rates increased exponentially (linear in log-scale) with age (figure 4 (a) (b) and (c) left lines). The cohort analysis found that younger birth cohorts had a lower risk of liver cancer mortality than did the older birth cohorts (figure 4 (a) (b) and (c) middle lines in blue), which was more pronounced among women (figure 4 (c) middle line in blue). For example, the risk of liver cancer mortality was 52% lower (95%CI: 48.9, 55.8) among women born in 1970 as compared to those born in 1930 (data not shown). In addition, the risk of liver cancer mortality slightly decreased with calendar year, particularly among women (figure 4 (c) right line in red). The AC-P model provided the best fit, and with the greatest difference of deviance residual is observed after the cohort is removed from the full APC models for the overall and sex-specific analysis suggesting that birth cohort was the most important factor driving the decrease in liver cancer mortality.

Note: Relative values that weight the goodness of fit of the model to empirical data. A better model fit is indicated by lower AIC values

AIC: Akaike information criteria

* -2 x log (likelihood) + 2 x number of estimated parameters

In each graph: Age effect (left), cohort effect (middle) and period effect (right). In order to see the cohort effect (AC-P Model [blue lines]), the AC-P model constrains the period effect to be 0 (right). In contrast, to examine the period effect (AP-C Model [red lines]), the AP-C model constrains the cohort effect to be 0 (middle)

The thin lines above and below the three effects represent their 95%CI

Cohort effect- refence birth-cohort: 1940. Period effect- reference calendar-year: 2005

Figure 4: Age-period-cohort trend analysis and AIC values for mortality of liver cancer in Mexico (nationwide) by sex, all ages, 1998-2018 

Finally, the APC analysis of mortality by state shown that results for most states were similar to those observed for the entire country (data not shown). An exception, however, was noted in Oaxaca among men, where calendar period was the most important factor driving the increase in mortality (AP-C model, AIC: 211.73). The liver cancer mortality risk was approximately 23% (95%CI: 4, 45) higher in 2018 compared to 2005.

Discussion

Over the 21-year interval examined, a decline of nearly 1% in liver cancer mortality rates was observed nationwide, likely driven by a birth cohort effect. An analysis by state found that mortality rates statistically significantly decreased or remained stable in the majority of the states, but rates statistically significantly increased in Oaxaca among men. In the most recent five-year period (2014-2018), sex-specific rates were roughly equal nationwide. In addition, wide disparities in liver cancer mortality by state were evident, with the highest mortality rates observed in southern Mexico.

Similar to our findings, a recent study of global liver cancer mortality trends from 1990 to 2017, estimated between 0% and 25% reduction of liver cancer mortality in Mexico.18 Similarly, reductions in mortality have been reported recently in other Latin American countries, such as Colombia (EAPC: -2.8%, 95%CI: -4.0, -1.7 in men; EAPC: -3.6, 95%CI: -4.6, -2.5 in women) and Ecuador (EAPC= -2.7, 95%CI: -4.6, -0.8).4 Previous reports from Mexico, however, indicated that liver cancer mortality statistically significantly increased from 2000-2007.11,13 In addition, these studies described state variations in the liver cancer trends across the country, with non-statistically significant decreasing rates in a number of states.11 In concert with the liver cancer mortality findings, a recent study reported a statistically significant decrease in alcohol-related liver cirrhosis mortality in Mexico from 2000-2017.19 The manuscript suggested that the reduction could be explained by a decrease in alcohol consumption from 1996 to 2004.19 Despite this decline, cirrhosis remains of Mexico’s leading causes of death.10

Our findings indicate that birth cohort may partially explain the overall reduction of liver cancer mortality. These findings are consistent with those of a U.S. study that reported that liver cancer incidence in younger male cohorts was lower than cohorts born before 1960.20 The manuscript hypothesized that their finding could be related to a higher prevalence of hepatitis C virus (HCV) infection in cohorts born between 1945-1964.20 It is unknown if similar changes in HCV infection prevalence occurred in Mexico, though the overall prevalence of HCV is low. It is possible that competing risks may have also contributed to the overall decline in liver cancer mortality, given the heavy burden of other chronic conditions, including ischemic heart disease, diabetes, chronic kidney disease and cirrhosis.10 In addition, the decline may be related to the improvement in the quality of death registration. The liver is a common site of cancer metastasis, as a result, some secondary liver cancers may have been erroneously counted as primary liver cancers in the past.

Our study found that the burden of liver cancer was not equally distributed across the Mexican population, perhaps reflecting the heterogeneous prevalence of risk factors. The major risk factors for liver cancer in Mexico are not well characterized. The prevalence of HBV and HCV appears to be low (<1.5%),7,8 as well as the prevalence of heavy alcohol consumption (3%).21 On the other hand, several studies have reported aflatoxin contamination in foodstuffs, including maize.22,23,24 However, the evidence of AFB1 exposure in human biomarkers is scarce. Our previous work found detectable serum levels of AFB1 in nearly 85% of individuals from Chiapas, where liver cancer mortality was the highest in the entire country. In addition, the study found that the AFB1-signature mutation in TP53 gene (R249S), was found in liver cancers of persons who resided in rural regions (e.g., Oaxaca and Veracruz). Similarly, a study in Guatemala (the country with the highest liver cancer rates in the Western Hemisphere) found detectable serum levels of AFB1 in 100% of the participants, and those AFB1 levels were higher in individuals from rural versus urban areas of Guatemala.25 It is noteworthy to mention that in cancer risk assessment there is the assumption of a no threshold level that constitutes “safe” level of exposure. AFB1-lys adducts is a biomarker of internal dose that reflect the formation of mutagenic AFB1-DNA adducts and the risk of liver carcinogenesis increases with the level of aflatoxin exposure determined by AFB1-lys adducts.25 In the hepatocytes, AFB1 is transformed into an epoxide via activation of p450 enzymes. The AFB1 7,8 epoxide binds to N7-guanine, where it exerts its carcinogenic effect.26 NAFLD and related metabolic conditions such as obesity, diabetes, and metabolic syndrome are becoming recognized as important risk factors for liver cancer in both high- and low- rate regions.27 The prevalence of these conditions has dramatically increased in Mexico, and they are expected to continue increasing particularly in rural areas.9,28,29 Whether these conditions are related to liver cancer in Mexico deserves further investigation.

The strengths of the current study include the use of a robust approach to assess the effect of age, calendar year and birth cohort on liver cancer mortality. In addition, the study included a long period of analysis (21 calendar years). In comparison, the study also had some limitations. The mortality data were based on information obtained from death certificates, which may be inaccurate. For example, death certificates may erroneously code secondary liver cancer as primary liver cancer. However, it has been reported that the completeness and coding characteristics of the official death registration in Mexico has a good quality.30 In addition, a recent study reported an 85% agreement between death certificates and medical records, particularly for neoplasia.31 Finally, another limitation is that the study was unable to examine trends by liver cancer histology, thus was unable to determine if different trends in histologic types occurred.

In conclusion, there was an overall decline in liver cancer mortality in Mexico between 1998 and 2018, but there is notable geographic variability in rates. The regional variability should be used to inform future studies of liver cancer etiology across the country.

Acknowledgments

This research was partially funded by the National Cancer Institute (NCI) (Grant ID 1P20CA210286-01), and the Intramural Research Program. Dr. Espinosa-Tamez is supported by the Consejo Nacional de Ciencia y Tecnología (Conacyt) scholarship 774013, and a Global Cancer Fellowship at the UCSF Helen Diller Family Comprehensive Cancer Center. The content is solely the responsibility of the author(s) and does not necessarily represent the official views of UCSF or NCI.

References

McGlynn KA, Petrick JL, El-Serag HB. Epidemiology of Hepatocellular Carcinoma. Hepatology. 2021;73(supl 1):4-13. https://doi.org/10.1002/hep.31288 [ Links ]

Ferlay J, Ervik M, Colombet M, Piñeros M, Znaor A, Soerjomataram I,et al. Global Cancer Observatory: Cancer Today [internet]. Lyon: International Agency for Research on Cancer, 2020. Available from:https://gco.iarc.fr/todayLinks ]

Petrick JL, Florio AA, Znaor A, Ruggieri D, Laversanne M, Alvarez CS,et al. International trends in hepatocellular carcinoma incidence, 1978-2012. Int J Cancer. 2020;147(2):317-30. https://doi.org/10.1002/ijc.32723 [ Links ]

Wong MC, Jiang JY, Goggins WB, Liang M, Fang Y, Fung FD,et al. International incidence and mortality trends of liver cancer: a global profile. Sci Rep. 2017;7:45846. https://doi.org/10.1038/srep45846 [ Links ]

Wallace MC, Preen D, Jeffrey GP, Adams LA. The evolving epidemiology of hepatocellular carcinoma: a global perspective. Expert Rev Gastroenterol Hepatol. 2015;9(6):765-79. https://doi.org/10.1586/17474124.2015.1028363 [ Links ]

El-Serag HB. Hepatocellular carcinoma. N Engl J Med. 2011;365(12):1118-27. https://doi.org/10.1056/NEJMra1001683 [ Links ]

Polaris Observatory C. Global prevalence, treatment, and prevention of hepatitis B virus infection in 2016: a modelling study. Lancet Gastroenterol Hepatol. 2018;3(6):383-403. https://doi.org/10.1016/S2468-1253(18)30056-6 [ Links ]

Petruzziello A, Marigliano S, Loquercio G, Cozzolino A, Cacciapuoti C. Global epidemiology of hepatitis C virus infection: An up-date of the distribution and circulation of hepatitis C virus genotypes. World J Gastroenterol. 2016;22(34):7824-40. https://doi.org/10.3748/wjg.v22.i34.7824 [ Links ]

Barquera S, Rivera JA. Obesity in Mexico: rapid epidemiological transition and food industry interference in health policies. Lancet Diabetes Endocrinol. 2020;8(9):746-7. https://doi.org/10.1016/S2213-8587(20)30269-2 [ Links ]

Institute for Health Metrics and Evaluation. GBD Compare Data Visualization [internet]. Seattle: IHME, University of Washington, 2020. Available from:http://vizhub.healthdata.org/gbd-compareLinks ]

Mendez-Sanchez N, Garcia-Villegas E, Merino-Zeferino B, Ochoa-Cruz S, Villa AR, Madrigal H,et al. Liver diseases in Mexico and their associated mortality trends from 2000 to 2007: A retrospective study of the nation and the federal states. Ann Hepatol. 2010;9(4):428-38. [ Links ]

Torres-Poveda K, Burguete-Garcia AI, Madrid-Marina V. Liver cirrhosis and hepatocellular carcinoma in Mexico: impact of chronic infection by hepatitis viruses B and C. Ann Hepatol . 2011;10(4):556-8. [ Links ]

Mendez-Sanchez N, Villa AR, Vazquez-Elizondo G, Ponciano-Rodriguez G, Uribe M. Mortality trends for liver cancer in Mexico from 2000 to 2006. Ann Hepatol. 2008;7(3):226-9. [ Links ]

Consejo Nacional de Población. Datos Abiertos de México - Proyecciones de la Población de México y de las Entidades Federativas, 2016-2050 [internet]. Ciudad de México: Conapo, 2020. Available from:https://datos.gob.mx/busca/dataset/proyecciones-de-la-poblacion-de-mexico-y-de-las-entidades-federativas-2016-2050Links ]

Ahmad OB, Boschi-Pinto C, Lopez AD, Murray CJ, Lozano R, Inoue M. Age standardization of rates: A new WHO standard. Geneva: World Health Organization, 2001. [ Links ]

Kim HJ, Fay MP, Feuer EJ, Midthune DN. Permutation tests for joinpoint regression with applications to cancer rates. Stat Med. 2000;19(3):335-51. https://doi.org/10.1002/(sici)1097-0258(20000215)19:3<335::aid-sim336>3.0.co;2-z [ Links ]

Holford TR, Zhang Z, McKay LA. Estimating age, period and cohort effects using the multistage model for cancer. Stat Med . 1994;13(1):23-41. https://doi.org/10.1002/sim.4780130105 [ Links ]

Lin L, Yan L, Liu Y, Qu C, Ni J, Li H. The Burden and Trends of Primary Liver Cancer Caused by Specific Etiologies from 1990 to 2017 at the Global, Regional, National, Age, and Sex Level Results from the Global Burden of Disease Study 2017. Liver Cancer. 2020;9(5):563-82. https://doi.org/10.1159/000508568 [ Links ]

Yeverino-Gutierrez ML, Gonzalez-Gonzalez MDR, Gonzalez-Santiago O. Mortality From Alcohol-Related Liver Cirrhosis in Mexico (2000-2017). Front Public Health. 2020;8:524356. https://doi.org/10.3389/fpubh.2020.524356 [ Links ]

Salvatore M, Jeon J, Meza R. Changing trends in liver cancer incidence by race/ethnicity and sex in the US: 1992-2016. Cancer Causes Control. 2019;30(12):1377-88. https://doi.org/10.1007/s10552-019-01237-4 [ Links ]

Escobar ER, Gamino MNB, Salazar RM, Hernandez ISS, Martinez VC, Bautista CF,et al. National trends in alcohol consumption in Mexico: results of the National Survey on Drug, Alcohol and Tobacco Consumption 2016-2017. Salud Ment. 2018;41(1):7-15. https://doi.org/10.17711/Sm.0185-3325.2018.003 [ Links ]

Camarillo EH, Ramirez-Martinez A, Carvajal-Moreno M, Vargas-Ortiz M, Wesolek N, Rodriguez Jimenes GDC,et al. Assessment of Aflatoxin M1 and M2 exposure risk through Oaxaca cheese consumption in southeastern Mexico. Int J Environ Health Res. 2018;28(2):202-13. https://doi.org/10.1080/09603123.2018.1453054 [ Links ]

Castillo-Urueta P, Carvajal M, Mendez I, Meza F, Galvez A. Survey of aflatoxins in maize tortillas from Mexico City. Food Addit Contam Part B Surveill. 2011;4(1):42-51. https://doi.org/10.1080/19393210.2010.533390 [ Links ]

Suarez-Bonnet E, Carvajal M, Mendez-Ramirez I, Castillo-Urueta P, Cortes-Eslava J, Gomez-Arroyo S,et al. Aflatoxin (B1, B2, G1 and G2) contamination in rice of Mexico and Spain, from local sources or imported. J Food Sci. 2013;78(11):T1822-9. https://doi.org/10.1111/1750-3841.12291 [ Links ]

Smith JW, Kroker-Lobos MF, Lazo M, Rivera-Andrade A, Egner PA, Wedemeyer H,et al. Aflatoxin and viral hepatitis exposures in Guatemala: Molecular biomarkers reveal a unique profile of risk factors in a region of high liver cancer incidence. PLoS One. 2017;12(12):e0189255. https://doi.org/10.1371/journal.pone.0189255 [ Links ]

Kensler TW, Roebuck BD, Wogan GN, Groopman JD. Aflatoxin: a 50-year odyssey of mechanistic and translational toxicology. Toxicol Sci. 2011;120(supl 1):S28-48. https://doi.org/10.1093/toxsci/kfq283 [ Links ]

Agosti P, Sabba C, Mazzocca A. Emerging metabolic risk factors in hepatocellular carcinoma and their influence on the liver microenvironment. Biochim Biophys Acta Mol Basis Dis. 2018;1864(2):607-17. https://doi.org/10.1016/j.bbadis.2017.11.026 [ Links ]

Pinto Marques Souza de Oliveira C, Pinchemel Cotrim H, Arrese M. Nonalcoholic Fatty Liver Disease Risk Factors in Latin American Populations: Current Scenario and Perspectives. Clin Liver Dis (Hoboken). 2019;13(2):39-42. https://doi.org/10.1002/cld.759 [ Links ]

Meza R, Barrientos-Gutierrez T, Rojas-Martinez R, Reynoso-Noveron N, Palacio-Mejia LS, Lazcano-Ponce E,et al. Burden of type 2 diabetes in Mexico: past, current and future prevalence and incidence rates. Prev Med. 2015;81:445-50. https://doi.org/10.1016/j.ypmed.2015.10.015 [ Links ]

Mathers CD, Fat DM, Inoue M, Rao C, Lopez AD. Counting the dead and what they died from: an assessment of the global status of cause of death data. Bull World Health Organ. 2005;83(3):171-7. [ Links ]

Lozano-Esparza S, Stern D, Hernandez-Avila JE, Morales-Carmona E, Mohar A, Lajous M. Evaluation of Mexico’s low cancer mortality using two national death registries. Salud Publica Mex. 2020;62(2):181-5. https://doi.org/10.21149/10635 [ Links ]

* Lino-Silva LS, Lajous M, Brochier M, Santiago-Ruiz L, Melchor-Ruan J, Xie Y,et al. Aflatoxin levels and prevalence of TP53 aflatoxin-mutations in hepatocellular carcinomas in Mexico. Salud Publica Mex. Forthcoming 2022.

Lino-Silva LS, Lajous M, Brochier M, Santiago-Ruiz L, Melchor-Ruan J, Xie Y,et al. Aflatoxin levels and prevalence of TP53 aflatoxin-mutations in hepatocellular carcinomas in Mexico. Salud Publica Mex. Forthcoming 2022.

Received: February 05, 2021; Accepted: August 27, 2021; Published: February 25, 2022

Corresponding author: Martín Lajous. Instituto Nacional de Salud Pública. 7ª Cerrada de Fray Pedro de Gante 50, col. Belisario Domínguez Sección XVI. 14000 Ciudad de México, México. email: mlajous@insp.mx

Declaration of conflict of interests. The authors declare that they have no conflict of interests.

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