comparing fertility in brazil and mexico: does policy matter? · 2012-12-09 · brazilian women...

Comparing Fertility in Brazil

and Mexico:

Does Policy Matter?

What motivated this exercise?

• A recent controversy in the Brazilian press

• Previous work with Brazilian census data

• We realized that the 2000 census samples

had a lot in common:

– 10% samples

– date of last live birth

– many other household and individual variables

FOLHA DE SÃO PAULO—Newspaper 23 August 2003

“Back to Fertility” by Drauzio Varella

• One of Brazil’s most pressing problems is the high fertility rate among the

poor. I know this statement is considered politically incorrect among

intellectuals, and it may even get me in trouble, but I’ll spend some words

on it…

• Even in such a modern age as ours in which effective contraception

methods are available, there are still a huge number of undesired

pregnancies among the poor. This difference is so striking that it’s quite

reasonable to ask: Why do policy-makers keep avoiding this issue?

• According to IBGE (Brazilian Institute of Geography and Statistics),

Brazilian women holding a bachelor’s degree have a fertility rate of 1.4

(similar to developed countries). On the other hand, among the “illiterate”

women who studied for only one year, the fertility rate is 5.6 (same rate of

Namibia, Africa).

MARIA JOSÉ de OLIVEIRA ARAÚJO—

Coordinator of Woman’s Health, Brazilian Ministry of Health

• Q: What do you think about the return of this debate, linking the control of poverty and criminality with family planning?

• A: I believe it’s an extremely important issue. Many years ago, the women’s movement, along with other social sectors in Brazil—demographers and parliamentarians concerned with women’s health—were able to demystify this link between poverty and the number of children. This relation doesn’t exist because Brazil, in the last 20 years, was one of the countries whose fertility rates fell most rapidly. We are talking about IBGE data, public data. On the other hand, poverty is still a reality; social exclusion is still out there; misery is still out there. So, I believe it is a grave contradiction that social sectors—governmentally-owned or not—re-start the debate over poverty, social exclusion and violence as an issue that requires fertility control!

MARIA JOSÉ de OLIVEIRA ARAÚJO

cont’d

• Q: What would be the role of social movements—specifically the

role of the feminist movement—concerning this topic?

• A: The Women’s Movement and the social movements in general

play a fundamental role. Thanks to the union with forward thinking

sectors of Brazilian society during the 1980’s and 90’s, the women’s

movement has been able to undo this neomalthusian (controlista)

discourse. It is imperative that women return to this struggle once

again, considering the existence of legal tools to do so. Brazil has

signed the Plans of Action of Cairo and Beijing; we have the

constitution and the Federal Law of Family Planning.

• As incredible as it may seem, the women’s movement must

now…look for allies in Brazilian society with which to return to this

debate…

On the Thoughts of President Lula—from his speech,

March 2003

I went to Irma Dulce village in Piaui state, along with Secretaries Emilia Fernandes, Benedita, and Dilma. We visited a poor neighborhood where approximately 70 thousand people live, and in this village, we visited 17 or 18 homes—we entered the house, talked with the people. In all the homes, the women were no more than 21 years old, had two, three or more children, and were without a husband.

I wonder how we can solve such a serious problem—which is no longer a legal problem. It’s a cultural problem, and ultimately, a matter of individual responsibility, for this young lady most likely has not had any sexual education during her childhood, teenage years, and even adult years.

Contrast with respect to FP/RH

services and policies

Mexico: Programs of

SSA, IMSS and

IMSS-Solidaridad for

both insured and

uninsured with

promotion of IUD and

Female Sterilization.

Postpartum, but also

via clinics.

Brazil: Much less

emphasis on the

supply of methods,

restrictions on female

sterilization, especially

postpartum, frustrated

demand, abortion, and

exchange of

sterilization for votes.

What we know already

• Brazil: The TFR in a

municipality is well

predicted by the

degree of

electrification and the

average level of

women’s education.

• Mexico: The use of

female sterilization

and the IUD in a

community is strongly

associated with the

proportion of births

taking place in public

hospitals.

Question we address here

• Within a municipality, will fertility

differentials by economic and social status

be smaller in Mexico than in Brazil?

– So long as the demand for children is

approximately equal between the very poor and

the not so poor in both countries

Data

• 2000 Censuses, 10% (15%) of four states: Piauí, Pernambuco, Guerrero y Veracruz, using individual data on date of last live birth

• Four categories of educational attainment: 0-2, 3-6,7-9, and 10+ years

• Municipal development factor based on the percentage of households with electricity, refrigerators, and TV

• Data on fertility desires from 1996 DHS and 1997 ENADID

PERCENT OF WOMEN WITH CHILD BORN ALIVE LAST YEAR

IN THE POPULATION OF BRAZILIAN AND MEXICAN STATES, 2000

8.67.4 7.5 7.8

19.5

15.0

12.213.5

7.6

4.93.6 3.3

0

5

10

15

20

25

Guerrero Veracruz Pernambuco Piaui

%

15 to 19 years 20 to 29 years 30 to 49 years

PERCENT OF YEARS OF SCHOOLING GROUPS


33.2 33.832.7

35.6

21.7 22.4

18.8 18.1

25.9 26.628.3

19.217.3

20.3

25.7

20.6

0

5

10

15

20

25

30

35

40


%

0 to 2 years/school 3 to 6 years/school 7 to 9 years/school 7 to 9 years/school

PERCENT OF HOUSEHOLDS WITH SPECIFIC INFRASTRUCTURE


82.6 84.7

92.3

59.7

44.6

75.7

65.4

55.9

38.8

53.7

35.439.1

0

10

20

30

40

50

60

70

80

90

100


%

Electrification Television Refrigerator

Municipalities variables Guerrero Veracruz Pernambuco Piaui

(n) 76 210 185 221

Electrification

Mean 0.8256 0.8472 0.9227 0.5965

Standard deviation 0.1823 0.1479 0.0813 0.2129

5th percentile 0.4325 0.5611 0.7424 0.1987

25th percentile 0.7554 0.7990 0.9099 0.4620

Median 0.9147 0.8933 0.9455 0.6239

75th percentile 0.9532 0.9391 0.9703 0.7532

95th percentile 0.9775 0.9878 0.9936 0.9232

IQR 0.1978 0.1401 0.0604 0.2911

Women with Recoded Parity "4" by Years of Schooling

and Fertility Preference, Brazilian Northeast - DHS1996

39.332.0

23.8 25.1

71.865.6

60.751.5

0

10

20

30

40

50

60

70

80

90

100

0-2 3-6 7-9 10+

Years of Schooling

%

No more children Sterilized



40.427.3 25.0

17.1

78.470.866.5

49.3

0

10

20

30

40

50

60

70

80

90

100

0-2 3-6 7-9 10+

Years of Schooling

%




36.3 40.326.1

33.9

50.357.7

37.034.9

0

10

20

30

40

50

60

70

80

90

100

0-2 3-6 7-9 10+

Years of Schooling

%




41.9 36.8 41.5 39.4

4.61.9

3.4 2.5

0

10

20

30

40

50

60

70

80

90

100

0-2 3-6 7-9 10+

Years of Schooling

%


Women with Recoded Parity "1" by Years of Schooling and

Fertility Preference, Guerrero/Veracruz (MX) - ENADID1997

13.222.3 18.0

31.3

9.6 1.10.5

2.3

0

10

20

30

40

50

60

70

80

90

100

0-2 3-6 7-9 10+

Years of Schooling

%




44.433.5 32.8 38.4

36.6

29.532.918.2

0

10

20

30

40

50

60

70

80

90

100

0-2 3-6 7-9 10+

Years of Schooling

%




53.3

35.4 40.430.5

64.853.8

45.9

30.9

0

10

20

30

40

50

60

70

80

90

100

0-2 3-6 7-9 10+

Years of Schooling

%




47.639.5

24.9 22.1

74.071.052.041.3

0

10

20

30

40

50

60

70

80

90

100

0-2 3-6 7-9 10+

Years of Schooling

%


Women with 15-19 Years of Age by Years of Schooling and

Ideal Number of Children, Brazilian Northeast - DHS1996

12.23.9 2.7

48.158.9

61.4 58.7

6.5 10.7

1.5

14.39.7

15.4

15.3

13.815.4

15.6 21.2

4.410.7

0

10

20

30

40

50

60

70

80

90

100

0-2 3-6 7-9 10+

Years of Schooling

%

No child 1 child 2 children 3 children 4 children or more



13.47.4 8.5

41.2 48.554.0 57.7

8.9 4.9

5.1

14.416.0 15.1 14.7

15.517.619.3

14.8

16.27.0

0

10

20

30

40

50

60

70

80

90

100

0-2 3-6 7-9 10+

Years of Schooling

%




18.6 13.3 11.9

34.336.1 33.2 41.4

23.1 18.0

9.1

9.110.1 12.6

9.7

22.624.417.415.8

22.2 17.2

0

10

20

30

40

50

60

70

80

90

100

0-2 3-6 7-9 10+

Years of Schooling

%


Women 15-19 Years of Age by Years of Schooling and Ideal

Number of Children, Guerrero/Veracruz (MX) - ENADID1997

12.8

43.3

46.7 59.263.8

20.210.7

1.33.3 1.1

12.77.710.3

13.2

18.3

19.6

21.213.2

9.112.3

0

10

20

30

40

50

60

70

80

90

100

0-2 3-6 7-9 10+

Years of Schooling

%




22.5

7.0

1.72.8 2.2 3.21.9 4.7 9.3

12.6

60.1

57.2

41.638.1

18.324.8

29.1

25.7

31.5

5.8

0

10

20

30

40

50

60

70

80

90

100

0-2 3-6 7-9 10+

Years of Schooling

%




30.5

13.9

3.8 2.23.2 3.17.9 4.0

11.2 7.4

22.7

43.644.5

31.2

31.128.2

31.1

18.8

46.9

14.9

0

10

20

30

40

50

60

70

80

90

100

0-2 3-6 7-9 10+

Years of Schooling

%


Women with 0-2 Years of Schooling by Age Group

and Desire for Last Child, Brazil - DHS1996

43.2 42.227.5

10.7

32.5

56.7

15.9

25.3

46.2

0

10

20

30

40

50

60

70

80

90

100

15-19 20-29 30-49

Age Group

%

Wanted then Wanted later Wanted no more



51.9 49.042.3

11.017.8

37.637.1

33.2

20.2

0

10

20

30

40

50

60

70

80

90

100

15-19 20-29 30-49

Age Group

%




50.7 50.2 47.3

8.616.4

22.3

40.733.5

30.4

0

10

20

30

40

50

60

70

80

90

100

15-19 20-29 30-49

Age Group

%


Women with 10 Years of Schooling or More by Age Group


39.5 41.953.4

12.419.2 20.1

26.539.048.1

0

10

20

30

40

50

60

70

80

90

100

15-19 20-29 30-49

Age Group

%


Women by Years of Schooling and Place of Delivery of Last

Child, Brazilian Northeast - DHS1996

74.487.5 84.4

63.1

1.2

3.5 11.3

34.0

23.4

9.0 3.5 2.5

0

10

20

30

40

50

60

70

80

90

100

0-2 3-6 7-9 10+

Years of Schooling

%

Public hospital Private hospital At home Another place

Women by Years of Schooling and Place of Delivery of Last

Child, Guerrero and Veracruz, Mexico - ENADID1997

46.9 52.5

71.9 68.2

42.934.2

27.818.8

12.5

9.6

4.19.3

0

10

20

30

40

50

60

70

80

90

100

0-2 3-6 7-9 10+

Years of Schooling

%

Public hospital Private hospital At home Another place Total

Summary of the model specified

FOR EACH OF THREE LARGE AGE GROUPS : 15-19, 20-29, 30-49

Level-1 Model

Prob(Y=1|B) = P

log[P/(1-P)] = B0 + B1*(AGE) + B2*(INDIG) + B3*(CATHOLIC) + B4*(ED0_2) +

B5*(ED3_6) + B6*(ED10_17)

Level-2 Model

B0 = G00 + G01*(GUE) + G02*(VC) + G03*(PE) + G04*(LIGHT) + U0


B2 = G20

B3 = G30




PREDICTED FERTILITY BY AGE AND YEARS OF SCHOOLING

GUERRERO-MEXICO, 2000

0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

15 16 17 18 19

AGE

PR

ED

ICT

ED

FE

RT

ILIT

Y

7-9 years/sch



0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

15 16 17 18 19

AGE

PR

ED

ICT

ED

FE

RT

ILIT

Y

0-2 years/sch 7-9 years/sch



0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

15 16 17 18 19

AGE

PR

ED

ICT

ED

FE

RT

ILIT

Y



VERACRUZ-MEXICO, 2000

0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

15 16 17 18 19

AGE

PR

ED

ICT

ED

FE

RT

ILIT

Y




0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

15 16 17 18 19

AGE

PR

ED

ICT

ED

FE

RT

ILIT

Y




0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

15 16 17 18 19

AGE

PR

ED

ICT

ED

FE

RT

ILIT

Y



PIAUI-BRAZIL, 2000

0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

15 16 17 18 19

AGE

PR

ED

ICT

ED

FE

RT

ILIT

Y




0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

15 16 17 18 19

AGE

PR

ED

ICT

ED

FE

RT

ILIT

Y




0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

15 16 17 18 19

AGE

PR

ED

ICT

ED

FE

RT

ILIT

Y



PERNAMBUCO-BRAZIL, 2000

0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

15 16 17 18 19

AGE

PR

ED

ICT

ED

FE

RT

ILIT

Y



PIAUI-BRAZIL, 2000

0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

15 16 17 18 19

AGE

PR

ED

ICT

ED

FE

RT

ILIT

Y




0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

15 16 17 18 19

AGE

PR

ED

ICT

ED

FE

RT

ILIT

Y

0-2 years/sch 3-6 years/sch 7-9 years/sch



0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

15 16 17 18 19

AGE

PR

ED

ICT

ED

FE

RT

ILIT

Y




0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

15 16 17 18 19

AGE

PR

ED

ICT

ED

FE

RT

ILIT

Y



PIAUI-BRAZIL, 2000

0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

15 16 17 18 19

AGE

PR

ED

ICT

ED

FE

RT

ILIT

Y




0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

15 16 17 18 19

AGE

PR

ED

ICT

ED

FE

RT

ILIT

Y

0-2 years/sch 3-6 years/sch 7-9 years/sch 10+ years/sch



0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

15 16 17 18 19

AGE

PR

ED

ICT

ED

FE

RT

ILIT

Y




0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

15 16 17 18 19

AGE

PR

ED

ICT

ED

FE

RT

ILIT

Y



PIAUI-BRAZIL, 2000

0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

15 16 17 18 19

AGE

PR

ED

ICT

ED

FE

RT

ILIT

Y




0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

20 21 22 23 24 25 26 27 28 29

AGE

PR

ED

ICT

ED

FE

RT

ILIT

Y

7-9 years/sch



0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

20 21 22 23 24 25 26 27 28 29

AGE

PR

ED

ICT

ED

FE

RT

ILIT

Y




0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

20 21 22 23 24 25 26 27 28 29

AGE

PR

ED

ICT

ED

FE

RT

ILIT

Y




0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

20 21 22 23 24 25 26 27 28 29

AGE

PR

ED

ICT

ED

FE

RT

ILIT

Y




0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

20 21 22 23 24 25 26 27 28 29

AGE

PR

ED

ICT

ED

FE

RT

ILIT

Y




0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

20 21 22 23 24 25 26 27 28 29

AGE

PR

ED

ICT

ED

FE

RT

ILIT

Y




0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

20 21 22 23 24 25 26 27 28 29

AGE

PR

ED

ICT

ED

FE

RT

ILIT

Y




0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

20 21 22 23 24 25 26 27 28 29

AGE

PR

ED

ICT

ED

FE

RT

ILIT

Y




0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

20 21 22 23 24 25 26 27 28 29

AGE

PR

ED

ICT

ED

FE

RT

ILIT

Y




0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

20 21 22 23 24 25 26 27 28 29

AGE

PR

ED

ICT

ED

FE

RT

ILIT

Y



PIAUI-BRAZIL, 2000

0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

20 21 22 23 24 25 26 27 28 29

AGE

PR

ED

ICT

ED

FE

RT

ILIT

Y




0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49

AGE

PR

ED

ICT

ED

FE

RT

ILIT

Y

7-9 years/sch



0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49

AGE

PR

ED

ICT

ED

FE

RT

ILIT

Y




0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49

AGE

PR

ED

ICT

ED

FE

RT

ILIT

Y




0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49

AGE

PR

ED

ICT

ED

FE

RT

ILIT

Y




0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49

AGE

PR

ED

ICT

ED

FE

RT

ILIT

Y




0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49

AGE

PR

ED

ICT

ED

FE

RT

ILIT

Y




0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49

AGE

PR

ED

ICT

ED

FE

RT

ILIT

Y




0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49

AGE

PR

ED

ICT

ED

FE

RT

ILIT

Y




0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49

AGE

PR

ED

ICT

ED

FE

RT

ILIT

Y




0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49

AGE

PR

ED

ICT

ED

FE

RT

ILIT

Y



PIAUI-BRAZIL, 2000

0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49

AGE

PR

ED

ICT

ED

FE

RT

ILIT

Y



LIGHT FACTOR EQUALS -1.0, VERACRUZ-MEXICO, 2000

0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

15 16 17 18 19

AGE

PR

ED

ICT

ED

FE

RT

ILIT

Y




0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

15 16 17 18 19

AGE

PR

ED

ICT

ED

FE

RT

ILIT

Y



LIGHT FACTOR EQUALS +0.3, VERACRUZ-MEXICO, 2000

0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

15 16 17 18 19

AGE

PR

ED

ICT

ED

FE

RT

ILIT

Y




0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

15 16 17 18 19

AGE

PR

ED

ICT

ED

FE

RT

ILIT

Y




0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

15 16 17 18 19

AGE

PR

ED

ICT

ED

FE

RT

ILIT

Y




0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

15 16 17 18 19

AGE

PR

ED

ICT

ED

FE

RT

ILIT

Y




0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

15 16 17 18 19

AGE

PR

ED

ICT

ED

FE

RT

ILIT

Y




0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

15 16 17 18 19

AGE

PR

ED

ICT

ED

FE

RT

ILIT

Y




0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

20 21 22 23 24 25 26 27 28 29

AGE

PR

ED

ICT

ED

FE

RT

ILIT

Y




0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

20 21 22 23 24 25 26 27 28 29

AGE

PR

ED

ICT

ED

FE

RT

ILIT

Y




0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

20 21 22 23 24 25 26 27 28 29

AGE

PR

ED

ICT

ED

FE

RT

ILIT

Y




0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

20 21 22 23 24 25 26 27 28 29

AGE

PR

ED

ICT

ED

FE

RT

ILIT

Y




0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49

AGE

PR

ED

ICT

ED

FE

RT

ILIT

Y




0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49

AGE

PR

ED

ICT

ED

FE

RT

ILIT

Y




0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49

AGE

PR

ED

ICT

ED

FE

RT

ILIT

Y




0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49

AGE

PR

ED

ICT

ED

FE

RT

ILIT

Y


Conclusiones

• Drauzio Varela no tiene razón cuando dice

que la fecundidad de mujeres pobres se

asemeja a Namibia

• Estos hallazgos son consistente con la

hipótesis de que programas de SRH

dirigidas a la “población abierta” llevan a

reducir diferenciales

comparing fertility in brazil and mexico: does policy matter? · 2012-12-09 · brazilian women...

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