/pidsdps0314

Philippine Institute for Development Studies Surian sa mga Pag-aaral Pangkaunlaran ng Pilipinas

Family Planning and Maternal and Child Health Outcomes, Utilization and Access to Services by Asset Quintile Aniceto Orbeta Jr., Iris Acejo, Janet Cuenca and Fatima del Prado DISCUSSION PAPER SERIES NO. 2003-14

The PIDS Discussion Paper Series constitutes studies that are preliminary and subject to further revisions. They are being circulated in a limited number of copies only for purposes of soliciting comments and suggestions for further refinements. The studies under the Series are unedited and unreviewed.

The views and opinions expressed are those of the author(s) and do not necessarily reflect those of the Institute.

Not for quotation without permission from the author(s) and the Institute.

September 2003 For comments, suggestions or further inquiries please contact: The Research Information Staff, Philippine Institute for Development Studies 3rd Floor, NEDA sa Makati Building, 106 Amorsolo Street, Legaspi Village, Makati City, Philippines Tel Nos: 8924059 and 8935705; Fax No: 8939589; E-mail: publications@pidsnet.pids.gov.ph Or visit our website at http://www.pids.gov.ph

FAMILY PLANNING AND MATERNAL AND CHILD HEALTH OUTCOMES, UTILIZATION AND ACCESS TO SERVICES BY ASSET QUINTILE: New Evidence from the Family Planning Surveys (FPS) and Maternal and Child Health Surveys (MCHS) Aniceto C. Orbeta, Iris Acejo, Janet Cuenca and Fatima del Prado September 2003

Abstract

This paper addresses the lack of information on the disparity of outcomes, utilization and access to Family Planning and Maternal and Child Health services by socioeconomic classes. Household statistics on these services by asset class are presented in this paper. The asset classes were derived from an index generated using principal components analysis on the presence of household amenities and means of transportation. The information generated are useful for better targeting of government Family Planning and Maternal and Child Health Services which are supposedly primarily targeted to the poor.

Key words: Family Planning, Maternal and Child Health, Population

FAMILY PLANNING AND MATERNAL AND CHILD HEALTH OUTCOMES, UTILIZATION AND ACCESS TO SERVICES BY ASSET QUINTILE: New Evidence from the Family Planning Surveys (FPS) and Maternal and Child Health Surveys (MCHS)

Aniceto C. Orbeta, Iris Acejo, Janet Cuenca and Fatima del Prado

1

INTRODUCTION Government social services are supposed to be directed primarily to the poor. The question to ask is this: Do government services reach the poor? This paper attempts to shed light to this question with respect to family planning and maternal and child health services. In particular, the paper compares outcomes, utilization and service access statistics across socioeconomic classes using a wealth indicator. The wealth indicator uses an asset index constructed from the presence or absence of household amenities, such as electricity, appliances and motor vehicles. Published survey results show only the disparity of access between the poor and the non-poor. The extent of disparity in access or utilization of services is often clouded by a lumpy poor – non -poor classification. A finer dis-aggregation will be able to depict better the extent of disparity of access across socioeconomic classes. This is the primary motivation of the paper. The results are expected to shed light on where government services are failing in reaching the poor. This information is important for better targeting government services.

Gwatkin et al. (2000) have shown the health, nutrition and population access and outcomes indicators of different socioeconomic classes for the Philippines using the 1998 NDHS. Using a similar methodology, this paper shows the extent of disparity in access by economic status using the 2000 Family Planning Survey (FPS) and 2000 Maternal Child and Health Survey (MCHS).

The paper is organized as follows. The next section describes the data and the methodology used in computing the asset index. The results of the classification of service access and utilization indicators by asset class are presented in the third section. The final sector provides a summary and policy implications.

METHODOLOGY AND DATA Data The paper used the 2000 Family Planning Survey and the 2000 Maternal and Child Health Survey to show service access and utilization disparities across income classes. Below is a brief description of the surveys.

The Fa mily Planning Survey The family planning survey is a nationwide survey conducted by the National Statistics Office 2 (NSO). It is a rider to the April round of the quarterly Labor Force Survey (LFS). The survey has been conducted annually since 1995 except in 1998 where the more comprehensive National Demographic and Health Survey (NDHS) was conducted. The subjects of the survey are the women aged 15-49 in the sample households of the LFS. The women are asked about recent births, family planning practice and sources of family planning supplies. Since 1999, questions pertaining to the presence of household amenities such as electricity, radio/cassette, television, telephone, refrigerator/freezer, bicycle, motorcycle, and car/jeep/van, have been included in the FPS. These variables were used to identify women belonging to what was considered poor households. NSO (n.d.) provides an explanation to 1

Senior Research Fellow, and research assistants, Philippine Institute for Development Studies. Email: aorbeta@mail.pids.gov.ph. We gratefully acknowledge the invaluable help of the National Statistics Office, in particular, Dr. Socoro Abejo and Elpidio Maramot. All errors remain the responsibility of the authors.

2 Survey in 1995, 1996 and 1997 are riders to the July round of the LFS.

2 this methodology. Even if asset variables are available as early as the 1999 round, the “socioeconomic status index” was only published for the first time in the in the 2000 round of FPS. The Maternal and Child Health Survey Another nationwide survey conducted by the NSO is the Maternal and Child Health Survey (MCHS). Like the FPS, it is also a rider to the April round of the LFS. The survey interviews women between 15-49 years old with surviving children below 5 years old. The survey has been conducted since 1997 except for 1998 when the NDHS was conducted. The survey before 2000 covered only those women with surviving children below 3 years old3. Currently, the survey now includes women with surviving children below 5 years old. It collects information on prenatal and postnatal care, immunization, breastfeeding, and micro -nutrient supplementation.

Methodology To generate an asset index from the presence or absence of household amenities, the primary concern is what weight to use for each of the assets. Two methods of computing the weights are explained in this section. First is the statistical method called principal components analysis and the other is the NSO method, which may be called “relative deprivation” index. Presented in this paper are the results using the asset index generated the principal components method. The results using the NSO method can be obtained from the authors upon request. Suffice it is to mention that the results are very similar. This is because the correlation between the asset index generated using principal components and the NSO method is very high at 0.96.

Principal Components Analysis Principal components analysis (PCA) is a technique of summarizing a set of variables into a smaller set of mutually orthogonal components that best capture the common information present in the variables. The first principal component captures the largest and the most common variation among the variables. The succeeding components progressively capture smaller proportion of the variation in the variables.

The generic problem with principal components analysis is that while the first principal componen t is easy to interpret, the interpretation of the higher order components is more problematic. Filmer and Pritchett (1998) used the first principal component weights to define an asset index. They have shown that the index is comparable with other measures of economic status such as the family size-adjusted per capita consumption. The variables are standardized before weights are computed.

NSO Socioeconomic Index The NSO socioeconomic index uses “relative deprivation” as the weights to the asset variables. The weight is computed as one minus the proportion of households in the survey owning the asset. As such, the assets more commonly owned by households will have smaller weights and, conversely, assets owned by fewer households will have larger weights.

Hence, we dubbed it a “relative deprivation” index. Note that this method will only work when the asset measure is dichotomous and works with the assets information available in the FPS. In contrast, the principal component method can handle continuous values, e.g. number of rooms in the house.

While in the FPS publication NSO chooses to classify only poor and non-poor households using the poverty incidence in recent FIES survey, it may be more informative to use the whole range of quintiles to describe the relative access to services as is done in Gwatkin, et al.

(2000).

3

The main reason identified for the change in the coverage from 3 to 5 years old is to collect information on vitamin A, iron and iodine supplementation of children below 5 years old who are the target population of micro -nutrient supplementation per recommendation of the World Health Organization.

3

The Asset Index from the Principal Components Analysis The details of the results of the PCA using Stata are given in Annex A. From Panel A, the first principal component captures as much as 38% of the variation in the variables. The weights used in computing for the index is given in Panel C which is taken from the first column of Panel B. Table 1 shows the descriptive statistics derived from using the index to classify households.

The second column of Table 1 shows that 77 percent of households have electricity, 82 percent have radios or radio cassettes, 62 percent have TV, and 9 percent have cars, jeep or van. The factor weights generated by PCA given in the fourth column shows that the ownership of TVs and refrigerators are given higher weights (0.4626 and 0.4551, respectively) than ownership of cars or motorcycles (0.2931 and 0.2249, respectively).

Table 1. Means, Standard Errors and Factor Weights of Household Assets, 2000

Assets

PCA

NSO

Mean

Std. Err.

Weights

Weights

Poor

L Middle

Means Middle

U Middle

Highest

Electricity

0.7658

0.0025

0.4119

0.2342

0.0000

0.8334

0.9968

0.9991

1.0000

Radio

0.8220

0.0022

0.3212

0.1780

0.4865

0.6771

0.9634

0.9856

0.9977

TV

0.6193

0.0028

0.4626

0.3807

0.0000

0.1545

0.9511

0.9920

0.9991

Telephone

0.1781

0.0022

0.3703

0.8219

0.0000

0.0022

0.0072

0.0502

0.8307

Refrigerator

0.3980

0.0029

0.4551

0.6020

0.0000

0.0237

0.0703

0.9057

0.9905

Bicycle

0.2274

0.0024

0.1800

0.7726

0.0408

0.2256

0.2302

0.2547

0.3860

Motorcycle

0.1196

0.0019

0.2249

0.8804

0.0044

0.0468

0.0562

0.1849

0.3061

Automobile

0.0893

0.0017

0.2931

0.9107

0.0000

0.0044

0.0036

0.0184

0.4202

Source of basic data: 2000 Family Planning Survey, NSO

The classification results using the asset index agrees with common sense. For instance, while none in the sample households in the poorest quintile have electricity, all households in the richest quintile have electricity. This proportion rises as one goes up the asset quintiles.

Ownership of radio, on the other hand, starts at 47 percent for the poo rest quintile to almost universal for households in the richest quintile. The proportion of ownership of TV, refrigerators, and telephones is very low for the poorest quintile rising to almost universal ownership for households in the richest quintile. The asset index demonstrates internal consistency with expected household conditions by socioeconomic status.

Filmer and Prichett (1998) provides a comprehensive discussion on the performance of the technique in classifying households by socioeconomic class using Indian data. Using the 2000 round of the matched Family Income and Expenditure Survey (FIES) and the October Labor Force Survey (LFS), Orbeta (2003) analyzed the performance of the technique using the limited set of assets available in the FPS and the more expanded set in the FIES against usual socioeconomic indicators such as consumption and income per capita.

OUTCOMES, UTILIZATION AND ACCESS TO SERVICES BY ASSET QUINTILE The index was used to classify outcomes and access to servi ces by asset quintile. For averages and trends please refer to the survey reports - “2000 Family Planning Survey Final Report” NSO (2000) and “2000 Maternal and Child Health Survey Final Report” NSO (2001).

4 Children Ever Born Children ever-born (CEB) or current parity is one of the basic measures of fertility. It measures current fertility of a woman. It is therefore low for younger women and higher for those who are approaching completion of their reproductive cycle. Thus, fertility of women 4049 i s the one often used to represent completed fertility (e.g., NSO and Macro Int’l., 1998).

The differential in fertility across asset class is larger in the younger ages, except for the youngest age group 15 -19. For instance, for age group 20-24, women in the poorest quintile have on the average 4 times as much child born compared to the women from the richest quintile (Table 2). For women aged 45-49, the CEB is 5.8 for the poorest quintile while only 3.4 for the richest quintile or 1.7 times as many. This represents the extent of disparity of completed fertility between women from poor and rich households.

Table 2. Mean children ever born by age group by asset quintile, Philippines, 2000

Age Group

Poorest

L Middle

Middle

U Middle

Richest

Total

Poor/Rich Ratio

15-19

0.06

0.05

0.05

0.04

0.03

0.04

2.0

20-24

1.02

0.67

0.52

0.36

0.25

0.50

4.1

25-29

2.66

2.08

1.78

1.30

0.80

1.66

3.3

30-34

3.90

3.27

2.82

2.27

1.66

2.76

2.3

35-39

4.82

4.18

3.74

2.91

2.31

3.55

2.1

40-44

5.60

4.83

4.38

3.46

2.90

4.14

1.9

45-49

5.83

5.00

4.75

3.84

3.37

4.47

1.7

Total

3.15

2.56

2.14

1.74

1.33

2.12

2.4

Source of raw data: NSO, 2000 Family Planning Survey

Family Planning Practice Contraceptive Prevalence In the case of all women, the contraceptive prevalence rate (CPR) does not show great disparity across asset classes. The prevalence of any method in the poorest quintile is about 25.8 percent while it is 22.6 percent in the richest quintile or the poor have even higher prevalence rate. In contrast, there is considerable disparity when it comes to women who are married and living together or those who are at risk of pregnancy. For instance, any method prevalence is only 37.6 percent in the poorest quintile, i.e., much lower compared to the 47.5 percent for the richest quintile. In addition, there is even higher proportion for the middle quintiles specifically the upper middle quintile, which posted a prevalence rate of 51.8 percent (Table 3). The disparity is not so much on the traditional methods as shown by the poor-rich ratio of 1.0 but rather in the modern methods. The modern method prevalence for the poorest quintile is 24.0 percent while for the riches quintile it is 34.1 percent which gives a poor-rich ratio of 0.7 or only 7 poor women use modern methods for every 10 rich women who use the method.

5 Table 3. Percent distribution of current users of modern method by five-year age group by asset quintile, Philipppines, 2000 Poorest

L Middle

Middle

U Middle

Richest

Total

Poor/Rich Ratio

Contraceptive Prevalence (all women) Any Method 25.8 30.0 Modern 16.6 20.6 Traditional 9.3 9.4 No Method 74.2 70.0

29.7 20.6 9.1 70.3

28.2 19.7 8.5 71.8

22.7 16.4 6.3 77.3

27.1 18.7 8.4 72.9

1.1 1.0 1.5 1.0

Contraceptive Prevalence (married women) Any Method 37.6 47.6 Modern 24.0 32.6 Traditional 13.6 15.0 No Method 62.4 52.4

50.9 35.0 15.9 49.1

51.8 36.0 15.8 48.2

47.5 34.1 13.4 52.4

47.0 32.3 14.7 53.0

0.8 0.7 1.0 1.2

Source of raw data: NSO, 2000 Family Planning Survey and Annex Table 1

Moreover, the disparity across asset class is not very glaring with respect to more universally available services such as pill, IUD, and injection. Notably, the prevalence rate for pill is almost the same for both the poorest and richest quintiles as indicated by the poor-rich ratio, i.e., 1.0 (Table 4). Although the gap between the poorest and richest quintile in terms of IUD and injection is evident, this is not as glaring as the gap between the two quintiles when it comes to ligation. Apparentl y, the prevalence rate across services which are available only in advance facilities such as hospital and more sophisticated clinics and require considerable out-o f-pocket cost vary significantly. Ligation prevalence among married women from the richest quintile almost quadrupled, i.e., 16.1 percent vis -Ă -vis 4.3 percent for the poorest quintile. Further, the poor-rich ratio is 0.3, which is considerably low.

As regards the methods used, it appears that women in the richer households have preference for p ermanent methods unlike women from poorer households as they opt for pills.

Further, there is higher prevalence rate in the use of modern methods compared to the traditional methods. Nevertheless, the combined prevalence rate of these methods is noteworthy. The survey results indicate that almost half of the married women do not use any method at all. In particular, more than 60 percent of the married women from the poorest households did not use any contraceptive method. For the married women from the richest households, more than 50 percent did not resort to contraception.

Table 4. Percent distribution of married women by current users of modern method by asset quintile, Philipppines, 2000 Poorest

Lower Middle

Middle

Upper Middle

Richest

Total

Poor/Rich Ratio

Any Method Modern Pill Ligation

37.6 24.0 11.9 4.3

47.6 32.6 15.5 8.2

50.9 35.0 14.5 11.6

51.8 36.0 14.4 13.4

47.6 34.1 12.0 16.1

47.0 32.3 13.7 10.6

0.8 0.7 1.0 0.3

Traditional Calendar Withdrawal

13.6 9.2 3.6

15.0 9.6 5.1

15.9 9.2 6.4

15.8 10.2 5.4

13.4 9.5 3.7

14.7 9.5 4.8

1.0 1.0 1.0

No Method

62.4

52.4

49.1

48.2

52.4

53.0

1.2

Source of raw data: NSO, 2000 Family Planning Survey and Annex Table 2

The contraceptive prevalence across age groups is also different by socioeconomic class.

While pill is the commonly used contraceptive in the poorer households, the prevalence is

6 highest among women aged 25 -29 except for married women in the lower middle class (Table 5). For married women aged 20-24 of the richest class, pills is more popular. With regard to the permanent methods, ligation in particular, prevalence is much higher (2 8.3 percent) for married women from the richest quintile specifically for those in the 40-44 age bracket.

Interestingly, ligation prevalence in the 40-44 age-group is also highest among women in the richest quintile.

Furthermore, most (84%) of the married women between 15-19 years old belonging to the poorest households do not have any method compared to women from the richest households (69%). Among the middle-age married women, i.e., 30-34 years old, 58 percent and 47 percent do not practice any contrace ption among the poorest households and richest households, respectively.

In terms of modern methods, only 8 percent of married women 15-19 years old use modern methods among the poorest households compared to 25 percent for the richest households.

There is also a drastic increase in adoption of more permanent methods among the women in richer households as they age while women in poorer households continue to use temporary methods such as pills.

Table 5. Percent distribution of married women by current users of modern method by five-year age group by asset quintile, Philipppines, 2000 ANY METHOD

Pill

MODERN Ligation

TOTAL

Calendar

TRADITIONAL Withdrawal TOTAL

Poorest 15-19 20-24 25-29 30-34 35-39 40-44 45-49

37.6 16.2 33.6 39.6 42.3 43.9 38.6 22.8

11.9 4.4 13.5 18.3 16.6 12.3 6.9 2.1

4.3 0.0 1.1 1.8 2.1 5.2 8.8 6.8

24.0 8.3 25.6 29.7 27.8 26.2 21.4 11.7

9.2 2.3 4.8 5.7 11.2 11.9 11.1 8.0

3.6 3.6 1.7 3.6 2.6 5.4 4.9 2.2

13.6 7.8 8.0 9.9 14.5 17.7 17.1 11.1

62.4 83.8 66.4 60.4 57.8 56.1 61.4 77.2

Richest 15-19 20-24 25-29 30-34 35-39 40-44 45-49

47.6 31.1 42.4 44.8 52.9 51.0 52.0 39.2

12.0 16.6 23.8 17.9 19.1 12.3 6.0 1.4

16.1 0.0 1.6 3.0 10.7 15.4 28.3 25.8

34.1 25.3 34.1 29.7 35.8 35.7 38.1 30.6

9.5 2.5 4.2 10.7 12.8 11.0 10.2 6.2

3.7 3.4 3.8 4.4 4.4 4.3 3.5 2.2

13.4 5.8 8.3 15.2 17.2 15.4 14.0 8.6

52.4 68.9 57.6 55.2 47.1 49.0 48.0 60.8

No Method

Source of raw data: NSO, 2000 Family Planning Survey and Annex Table 2

There is not much disparity in prevalence rates between urban and rural areas across asset quintiles. For instance, the prevalence of any method in the poorest quintile is 41 percent and 37 percent for urban and rural, respectively. In contrast, it is 47 percent for urban areas and 50 percent for rural areas with respect to the richest quintile. Nevertheless, Table 6 shows that the prevalence of pills usage is higher for married women from lower middle and richest classes in the rural areas. On the one hand, there is larger proportion of married women in urban areas who had ligation compared to married women in rural areas across asset class.

Moreover, the low poor -rich ratio, i.e., 0.3 for both urban and rural areas, in terms of ligation denotes that indeed married women from poorest households have much lesser access to such family planning service.

7 Table 6. Percent distribution of married women by current contraceptive method used, by urbanity by asset quintile Philippines, 2000 Any Method

MODERN

TRADITIONAL

Ligation 4.3 5.2 4.1

Total 24.0 27.6 23.4

Calendar 9.2 9.4 9.2

Withdrawal 3.6 3.1 3.7

Total 13.6 13.4 13.7

NO METHOD

Poorest Urban Rural

37.6 40.9 37.1

Pill 11.9 12.7 11.8

Richest Urban Rural

47.6 46.8 50.4

12.0 11.8 12.6

16.1 16.1 16.0

34.1 33.8 35.6

9.5 9.2 10.9

3.7 3.7 3.8

13.4 13.0 14.8

52.4 53.2 49.6

Poor-rich ratio Urban Rural

0.9 0.7

1.1 0.9

0.3 0.3

0.8 0.7

1.0 0.8

0.8 1.0

1.0 0.9

1.1 1.3

62.4 59.1 62.9

Source of raw data: NSO, 2000 Family Planning Survey and Annex Table 3

As regards contraceptive prevalence rate across regions, there are interesting twists. While it is expected that the women from poorest household would have lower CPRs than the national average, this is not true for Cagayan Valley and Central Luzon. This is particularly shown in the case of modern methods (Table 7).

Table 7. Percent distribution of married women by current contraceptive method used by asset quintile, by region, Philippines, 2000 MODERN

TRADITIONAL

ANY METHOD

Pill

Ligation

Total

Calendar

Withdrawal

Total

NO METHOD

Poorest Cagayan Valley Central Luzon

37.6 63.1 60.3

11.9 29.4 9.1

4.3 11.6 17.1

24.0 53.8 46.9

9.2 3.5 3.7

3.6 5.9 8.1

13.6 9.4 13.4

62.4 36.9 39.7

Lower Middle Cagayan Valley Central Luzon

47.6 61.2 52.4

15.5 25.1 13.2

8.2 12.6 13.3

32.6 51.1 29.8

9.6 6.4 5.0

5.1 3.7 17.4

15.0 10.2 22.6

52.4 38.8 47.6

Middle Cagayan Valley Central Luzon

50.9 59.8 56.4

14.5 19.1 16.4

11.6 19.3 17.6

35.0 45.9 39.1

9.2 7.2 5.3

6.4 6.7 11.9

15.9 13.9 17.4

49.1 40.2 43.6

Upper Middle Cagayan Valley Central Luzon

51.8 58.0 57.7

14.4 19.5 15.7

13.4 18.5 19.3

36.0 45.9 40.2

10.2 6.3 7.3

5.4 5.9 10.2

15.8 12.2 17.6

48.2 42.0 42.3

Richest Cagayan Valley Central Luzon

47.6 64.2 50.3

12.0 27.4 10.7

16.1 14.2 20.5

34.1 52.9 34.3

9.5 7.9 8.3

3.7 2.9 7.6

13.4 11.3 16.0

52.4 35.8 49.7

Source of raw data: NSO, 2000 Family Planning Survey and Annext Table 4

Sources of Supply Table 8 presents the sources of supply of modern methods by asset class. The table indicates that as much as 91 percent of women from the poorest households obtain their supplies from the government. About one half (51%) does the same for the richest quintile.

These figures show that not only the women from the poorest households but also a substantial proportion (51%) of women from the richest households get their supplies from the government facilities particularly from the government hospital and rural health units.

8 In terms of specific methods, government it is also the main source of supply of poorer households except for vasectomy, which is mainly supplied by the private sector. Richer households likewise depend on the government for contraceptives except for condoms that are largely supplied by the private sector, specifically the pharmacy.

Some 45 percent and 65 percent of women from the richest households still get their pills and IUDs, respectively, from government facilities. The same holds true for those who seek out government hospitals to undergo ligation (54%). The rural health units and barangay health stations are the only sources of diaphragms for women from poorer and richest households, respectively. The private sector and other sources of contraceptives do not supply diaphragms.

Table 8. Source of modern method excluding LAM, Philippines, 2000

Source of Modern Methods

Poorest

L Middle

U Middle

Middle

Richest

Total

Poor/Rich Ratio

Government

90.7

84.8

78.2

69.0

50.9

73.8

1.8

Private

8.8

13.4

19.4

29.3

47.5

24.6

0.2

Others

0.2

1.4

1.6

1.2

0.9

1.1

0.3

DK

0.2

0.4

0.8

0.5

0.8

0.5

0.3

Source of raw data: NSO, 2000 Family Planning Survey and Annex Table 5

Reason for not using contraception Among the reasons given for not using contraceptives, problems with side effects, religion and fatalistic attitude are more prevalent among women from poorer households (14%, 7% and 9%, respectively) than among women from richer households (7%, 1%, and 4%, respectively) (Table 9).

Overall, women coming from both the poorest and richest households consider want of children as the top reason for not using contraceptives. The poor-rich ratio of 0.6 indicates higher prevalence rates for richer women. In addition, preferences of women from poorer households are mostly influenced by method related reasons such as side effects and health concerns. On the contrary, accessibility in terms of cost and availability is uniformly not mentioned as often by women from all asset classes. The 2.8 poor-rich ratio reveals that reasons related to opposition to use is almost 3 times more prevalent among the poorer women as reason for non -use of contraception. Finally, it should be noted that among those who mentioned lack of knowledge as the reason for not using contraceptives, there are more than 4 times as many women from the poorest households as there are from the richest households.

For women in age groups 20–24 and 35– 39 years old, regardless of socio-economic status, the main reason for non-use is the fear of side effects. However, comparing poor and richer women, this reason occurred significantly more among poor women in all age groups. When it comes to younger women between ages 15-19, lack of knowledge hinders the use of contraceptives.

9 Table 9. Percent distribution of married women, reason of not using contraceptives by asset quintile Philippines, 2000

Reason for not using contraception Wants Children Lacks Knowledge Method-related Opposition to Use Relating to Exposure Others

Poorest 14.6 6.3 27.9 9.9 28.7 12.6

L Middle 18.1 2.8 28.9 6.3 32.5 11.5

U Middle 18.4 2.2 29.7 3.9 35.7 10.1

Middle 23.5 1.3 24.7 3.4 37.4 9.7

Richest 25.4 1.4 19.0 3.5 43.6 7.3

Total 19.8 3.0 26.1 5.6 35.3 10.3

Poor/Rich Ratio 0.6 4.4 1.5 2.8 0.7 1.7

Maternal and Child Care The tables in this section were generated from the 2000 Maternal and Child Health Survey.

The asset index computed from the 2000 Family Planning Survey, which gathered data on household assets, was added to the MCHS since both surveys used the same households.

Prenatal Care Provider The disparity in utilization of prenatal care is revealing. The disparity is conspicuous not only in the degree and level of utilization, but also in terms of preferred prenatal care service provider. The disparity in use of doctors as providers of prenatal care is very glaring with only 6 percent of women from the poorest households utilizing doctors as against 66 percent for the richest households (Table 10). There is not much disparity in the utilization of nurses.

Women from poorer households have greater tendency to confer with midwives, as compared to their richer counterpart with only 22 percent (as against 46% from poorer households) admitting to have gone to midwives for their prenatal concerns. Utilization of hilots follows the same pattern as that of midwives except that the women from richer households utilize them less.

The poor-rich ratio reveals the disparity even more clearly. Only 1 woman from the poorest households for every 10 women from the richest households avails of services of a doctor for pre-natal care. On the other hand, 5 women from the poorest households for every 1 woman in the richest households go to hilots for pre-natal care. The same trend can be observed in both urban and rural areas except for the greater reliance on hilots among poor relative to rich women in urban compared to rural areas (6:1 in urban compared to 4:1 in rural areas)

10 Table 10. Percent distribution of women with surviving children 0-35 months of age, by type of pre-natal care service provider, by asset quintile, and by type of residence, Philippines: 2000 Poorest LMiddle

Middle

UMiddle Richest Total Poor/Rich Ratio

Philippines Doctors

6.0

12.4

26.2

38.8

65.7

27.3

0.1

Nurses

2.1

1.3

3.2

3.4

3.1

2.5

0.7

Midwife

45.1

49.3

47.1

37.5

22.3

41.3

2.0

Hilot

46.6

36.8

23.3

19.8

8.8

28.6

5.3

Doctors

8.6

17.1

32.3

45.5

69.1

40.8

0.1

Nurses

2.2

2.4

3.9

4.8

3.9

3.7

0.6

Midwife

43.1

49.2

43.9

31.2

19.5

35.3

2.2

Hilot

46.0

30.8

19.7

17.8

7.4

19.8

6.2

Doctors

5.5

9.5

18.0

28.0

55.4

15.4

0.1

Nurses

2.0

0.6

2.2

1.1

0.7

1.5

2.8

Midwife

45.4

49.4

51.3

47.7

30.8

46.6

1.5

Hilot

46.7

40.4

28.1

23.0

13.0

36.3

3.6

Urban

Rural

Source of raw data: NSO, 2000 Maternal and Child Health Survey and Annex Table 7

Number of visits In terms of the number of visits, the modal number of visits is nine (or once a month for the pregnancy term) for women from the richest quintile and only three (or once a trimester) for women from poorest households (Table 11). The use of prenatal care is positively associated with wealth. The modal number of visits increases as one goes from the poorest households to the richest households.

The pattern is similar for urban and rural areas, except for higher frequency of visits in urban compared to rural areas. A slightly higher proportion (24.6%) of rural women in poorer households do not meet the required number of visits of at least three compared to their urban counterpart (23%). The observed tendency for women in both rural and urban areas to make more frequent pre-natal visits as their socio-economic conditions improve provides evidence to wealth and pre-natal care connection.

The large disparity in the frequency of prenatal visits between the poor and rich households is clearly demonstrated in the poor-rich ratio. For most women in poorer households, the most number of visits is only one hence, the recommended number of prenatal visits is not sufficiently met. The gap between quintiles increases as the number of visits rises. Just like the national estimate, both rural and urban figures illustrate the higher tendency of women belonging to the richest quintile, to make more frequent prenatal visits than those in lower income groups.

11 Table 11. Percent distribution of women with surviving children 0-35 months of age, by number of pre-natal visits, by asset quintile and by type of residence, Philippines, 2000 No. of Pre-Natal Visits Poorest LMiddle

Middle UMiddle Richest Total Poor/Rich Ratio

Philippines 3

22.5

20.7

15.8

11.7

6.3

16.1

3.6

6

8.2

10.2

10.4

11.3

8.8

9.7

0.9

9

5.2

7.9

11.8

17.7

25.0

12.7

0.2

10 or more

2.0

4.5

7.2

11.6

19.9

8.3

0.1

3

21.5

20.7

13.7

10.3

4.7

12.3

4.6

6

11.1

11.9

9.9

10.9

7.7

10.0

1.4

9

4.8

9.0

13.1

19.1

25.6

16.5

0.2

10 or more

1.6

5.2

7.3

13.2

22.6

12.0

0.1

3

22.6

20.6

18.6

14.1

11.2

19.5

2.0

6

7.7

9.2

11.0

11.9

12.1

9.5

0.6

9

5.3

7.3

10.0

15.6

23.1

9.3

0.2

10 or more

2.1

4.0

7.1

9.0

11.8

5.1

0.2

Urban

Rural

Source of raw data: NSO, 2000 Maternal and Child Health Survey and Annex Table 8

Vitamin Supplementation The difference in prevalence of supplementation between poorer and richer households is more evident in the cas e of iron tables and iodine capsules but not for tetanus toxoid vaccination4. About 67 percent of women from the poorest households had iron tablets compared to 92 percent for women in the richest households (Table 12). In the case of iodine capsules, 49 percent of women from poorest households and 73 percent of women from the richest household had the capsules. Thus, ther are only 7 women from the poorest households for every 10 women from the richest households that had iron and iodine supplements.

In terms of urbanity, the pattern is similar except that there is slightly higher supplementation in urban compared to rural areas. In addition, there is a clearer disparity in the tetanus toxoid vaccination prevalence between women from poorer to richer households in rural compared to urban areas. Sixty eight percent of women from poorest households and 76 percent of women from richest households had tetanus toxoid vaccination.

4

It is recommended that pregnant women should receive at least 2 tetanus injections during pregnancy.

12 Table 12. Percent distribution of women with surviving children 0-35 months of age who received supplementation during pregnancy with youngest child, by asset quintile and by type of residence, Philippines, 2000 Poorest LMiddle Middle UMiddle Richest Total Poor/Rich Ratio Philippines Iron Tablet

66.9

73.5

80.9

84.8

91.5

78.3

0.7

Iodine Capsule

48.9

54.7

61.9

68.2

72.8

60.0

0.7

Tetanus Toxoid Vaccine

66.8

69.8

75.9

75.2

67.2

70.9

1.0

Iron Tablet

63.4

76.2

82.0

84.5

92.2

82.8

0.7

Iodine Capsule

41.7

55.7

63.8

69.6

72.7

64.3

0.6

Tetanus Toxoid Vaccine

62.7

70.5

75.2

73.8

64.3

70.3

1.0

Iron Tablet

67.5

71.9

79.4

85.1

89.7

74.4

0.8

Iodine Capsule

50.1

54.0

59.4

66.0

73.0

56.3

0.7

Tetanus Toxoid Vaccine

67.5

69.4

76.9

77.5

75.8

71.4

0.9

Urban

Rural

Source of raw data: NSO, 2000 Maternal and Child Health Survey and Annex Table 9

For the number of shots received for the youngest child, more than half received at least one tetanus toxoid injection and about 29 percent received the recommended two injections while 16 percent had three or more injections (Table 13). The disparity across asset quintiles is not that large even if there is slightly more women from poorer households who tend to have only one injection and there are more women from richer households who had two or more injections.

Table 13. Percent distribution of women, with surviving children 0 -35 months of age, by number of tetanus toxoid injections received during pregnancy of youngest child, by asset quintile and residence, Philippines 2000 No. of TTI received

Poorest LMiddle

Middle

UMiddle

Richest Total Poor/Rich Ratio

Philippines 1

54.3

48.6

50.5

48.9

51.9

50.8

1.0

2

27.1

31.7

27.9

30.8

28.9

29.2

0.9

3 or more

15.5

16.6

17.4

17.3

15.2

16.4

1.0

1

54.9

53.0

51.0

51.6

51.7

51.9

1.1

2

24.4

30.8

28.4

28.2

27.7

28.3

0.9

3 or more

15.5

13.8

15.9

16.6

15.7

15.6

1.0

1

54.2

45.9

49.7

44.6

52.6

49.9

1.0

2

27.6

32.3

27.2

34.9

32.3

30.0

0.9

3 or more

15.5

18.3

19.3

18.4

13.8

17.2

1.1

URBAN

RURAL

Source of raw data: NSO, 2000 Maternal and Child Health Survey and Annex Table 10

13 Post Natal Care Provider Again, the disparity in the type of provider of postnatal care is quite revealing. Women from richer households go to doctors while women from poorer household consult midwives and hilots. These may reflect either the status of supply and/or the affordability of the services.

Only 11 percent of women from poorest households confer with doctors com pared to 75 percent for women in richest households or 1 woman from the poorest households for every 10 women from the richest households consult a doctor for post-natal care a ratio that is identical to pre-natal care (Table 14). On the other hand, 42 percent of women in poorer household and 16 percent in richer households consulted midwives. Finally, 44 percent of women from poorest household and 6 percent of women from richest households utilized hilots for postnatal care or 8 women from the poorest households per 1 woman from the richest households go to hilots for post-natal care which is an even greater than the 5:1 ratio for pre-natal care.

Similar pattern occurs in urban and rural areas except for disparity in type of provider being used. There is higher propensity of consulting doctors in urban areas compared to rural areas – 55 percent as against 24 percent. Moreover, there is higher propensity of conferring with midwives in rural (41%) compared to rural areas (29%). Likewise, there is higher proportion of women availing the services of hilots in rural (31%) compared to urban (13%) areas.

Table 14. Percent distribution of women with surviving children 0-35 months of age, by type of post-natal care service provider, by asset quintile, and by type of residence, Philippines: 2000 Poorest LMiddle Middle UMiddle Richest Total Poor/Rich Ratio Philippines Doctors

10.6

19.0

37.9

52.1

74.7

39.5

0.1

Nurses

2.4

3.6

3.4

4.5

3.8

3.5

0.6

Midwife

42.2

46.8

40.9

30.3

15.8

34.9

2.7

Hilot

44.2

30.0

17.3

12.9

5.5

21.6

8.1

12.1

27.9

45.0

58.9

77.5

54.7

0.2

Urban Doctors Nurses

4.5

2.8

3.2

4.0

4.1

3.7

1.1

Midwife

45.4

43.0

37.5

27.5

13.4

28.5

3.4

Hilot

38.0

25.6

13.5

9.1

4.5

12.6

8.4

Doctors

10.4

14.4

26.8

40.2

66.0

24.2

0.2

Nurses

2.1

4.0

3.8

5.2

2.8

3.4

0.8

Midwife

41.7

48.8

46.2

35.2

22.9

41.4

1.8

Hilot

45.2

32.3

23.2

19.3

8.3

30.8

5.5

Rural

Source of raw data: NSO, 2000 Maternal and Child Health Survey and Annex Table 11

Types of Services In all types of services, there is lower propensity of women receiving the service among poorer compared to richer households (Table 15). The largest disparity is observed in internal examination with only 17 percent of women from poorest households while 49 percent of women from the richest households had the examination. What is disturbing is that even for simple services such as family planning, breastfeeding and baby care advice, there is still

14 disparity between women from poorer as against richer households though these are not as large as those for abdominal and breast examination. Finally, baby check up is the most common service sought for with 63 percent of women from poorest households and 87 percent of women from richest households having this service.

For both urban and rural areas, women belonging to poorer households often receive postnatal care for abdominal exams, baby care advice and check up. In particular, the types of services received by urban women from all asset classes are centered on baby care advice and check up. Services such as family planning advice, breast exam and internal exam are availed by a greater proportion of richer women compared to poorer women. In the same manner, richest households in the rural areas largely benefit from the same services though the inequality is much less (43% for richer women and around 24% - 33% for poorer women).

Table 15. Percent distribution of women with surviving children 0-35 months of age who received post natal care by type of service received, by asset quintile and by type of residence, Philippines 2000 Poorest LMiddle Middle UMiddle Richest Total Philippines Abdominal Exam Breast Exam Internal Exam Family Planning Advice Breastfeeding Advice Baby Care Advice Check Up of Baby URBAN Abdominal Exam Breast Exam Internal Exam Family Planning Advice Breastfeeding Advice Baby Care Advice Check Up of Baby RURAL Abdominal Exam Breast Exam Internal Exam Family Planning Advice Breastfeeding Advice Baby Care Advice Check Up of Baby

Poor-rich ratio

49.7 24.3 15.9 34.4 47.8 55.5 61.8

51.2 31.0 27.6 38.3 53.5 60.6 76.5

53.8 36.1 31.3 38.3 56.6 64.8 78.5

58.8 42.5 45.2 43.9 61.1 69.3 84.2

62.8 46.8 49.1 45.4 61.9 70.8 87.6

55.4 36.3 34.2 40.1 56.3 64.3 77.9

0.8 0.5 0.3 0.8 0.8 0.8 0.7

48.6 29.1 19.8 42.0 51.1 61.9 69.1

57.3 33.0 36.1 37.6 55.1 59.5 78.5

55.2 36.1 34.2 42.1 57.8 64.8 79.1

58.5 43.0 47.7 47.2 62.7 70.1 84.9

64.0 48.2 53.8 50.3 63.4 72.9 88.6

58.8 40.9 43.3 45.4 60.1 67.8 83.0

0.8 0.6 0.4 0.8 0.8 0.8 0.8

49.9 23.5 15.3 33.1 47.2 47.2 60.6

47.9 29.9 23.2 38.6 52.6 52.6 75.4

51.6 36.1 26.9 32.3 54.8 54.8 77.5

59.4 41.7 40.9 38.1 58.3 58.3 82.9

59.0 42.5 34.6 30.3 57.1 57.1 84.2

51.9 31.7 24.9 34.8 52.4 52.4 72.8

0.8 0.6 0.4 1.1 0.8 0.8 0.7

Source of raw data: NSO, 2000 Maternal and Child Health Survey and Annex Table 12

Immunization The proportion of children with immunization is expected to increase as on goes up the asset ladder. Surprisingly, however, Table 16 shows that there are cases when the poorest households have highest rate in terms of specific types of immunization compared to other households. For instance, the immunization rate for children with age 0 to 11 months from the poorest households is highest for Hepatitis B 2 and Hepatitis B 3. However, this holds true for poorest households in the urban areas only. In contrast, children aged 12-23 months and 2435 months from poorest households in rural areas have the highest immunization rate for Hepatitis B 2 and Hepatitis B 3, respectively. Nevertheless, access of poorest households to other immunization services such as BCG, DPT, Polio, Measles and Hepatitis 1 are lagging behind the richer households. The poorest households have the lowest immunization rates in almost all of these services.

15 Table 16. Percent distribution of children 0-35 months of age, by type of immunization received, by asset quintile and by type of residence, Philippines 2000

Poorest

URBAN Richest

Total

Poor/Rich Ratio

Poorest

RURAL Richest

Total

Poor/Rich Ratio

0 to 11 months BCG

74.8

90.1

84.3

0.8

65.9

86.1

72.5

0.8

DPT 1 Polio 1 Measles 1

64.3 68.2 20.2

82.6 80.1 23.6

77.4 75.6 21.1

0.8 0.9 0.9

61.9 59.9 15.5

78.3 75.0 18.6

69.3 66.2 18.2

0.8 0.8 0.8

Hepatitis B 2 Hepatitis B 3

94.6 91.0

88.8 77.9

89.9 83.5

1.1 1.2

91.0 87.3

90.6 87.3

91.4 86.8

1.0 1.0

BCG DPT 1

76.7 72.0

98.6 97.6

95.0 93.0

0.8 0.7

86.6 85.4

91.8 91.8

90.4 89.3

0.9 0.9

Polio 1 Measles 1 Hepatitis B 2

73.1 59.4 84.4

97.4 89.5 82.4

92.2 81.5 83.5

0.8 0.7 1.0

85.0 72.5 86.8

91.8 85.0 84.9

89.1 78.1 81.8

0.9 0.9 1.0

Hepatitis B 3

75.4

68.5

72.0

1.1

74.4

76.5

69.8

1.0

BCG DPT 1 Polio 1

80.9 79.5 82.5

97.9 98.9 98.5

94.2 93.8 93.2

0.8 0.8 0.8

83.4 81.3 81.7

97.3 97.7 97.7

89.4 87.9 88.3

0.9 0.8 0.8

Measles 1 Hepatitis B 2 Hepatitis B 3

74.3 87.7 81.6

94.9 85.7 73.4

86.6 86.0 73.2

0.8 1.0 1.1

71.1 84.1 76.8

92.3 90.4 76.1

79.2 82.4 72.6

0.8 0.9 1.0

12 to 23 months

24 to 35 months

Source of raw data: NSO, 2000 Maternal and Child Health Survey and Annex Table 16

SUMMARY AND POLICY IMPLICATIONS Using an asset index to determine the extent of disparity in access and utilization of family planning and maternal and child health services has shown interesting revelations. For one, it has been shown that the over all contraceptive prevalence is considerably lower for women from poorer households compare to those from richer households. The disparity is particularly more striking for modern methods. In addition, with more universally available services such as the pill, IUD and injection, the disparity is not as pronounced as methods that are available only in more advance clinics and hospitals such as ligation. Furthermore, the rich appears to prefer more permanent methods, such as ligation, while women from poor households prefer the pill. In terms of age groups, the disparity in contraception across asset classes is even more pronounced particularly in younger age groups. Government facilities are still the main source of supply for modern methods. While we already see a larger proportion of women from poorer families get their supplies from government facilities, there is still a considerable proportion of women from the richest household that also get their supply from government facilities. In terms of reason for not using contraception, more women from poorer households compared to richer households mentioned opposition to family planning, religion and fatalistic attitude as well as side effects as reasons.

Turning now to maternal and child care, there is a clear pattern in the disparity of access by type of provider for both pre-natal and post-natal care. The women from richer households use doctors while those from poorer household used either midwives or “hilots� with clear implication on the quality of service. In terms of number of pre-natal care visits, the modal number for the rich is nine (or once a month for the pregnancy term) while only three (or once a trimester) for women from the poorest households. In terms of vitamin supplementation, there is clear disparity in terms of iron tablets and iodine capsules and not so much on having

16 tetanus toxoid injections although there is still a large disparity in terms of the proportion that have the recommended two shots. In terms of types of post-natal services, there is a large disparity in those having internal and, to a lesser extent, breast and abdominal examinations.

While it is more understandable to observe disparities in more involved and expectedly more expensive procedures such as internal examination, it disturbing to find that even for simple services such as family planning, breastfeeding and baby care advice, there is still considerable disparity between women from poor and rich households. Finally, immunization rates reveal interesting and welcomed twists. For Hepatitis B2 and B3 children from poorest household appears to have higher immunization rates. But for BCG, DPT, Polio, Measles and Hepatitis 1, access of the poor households are still considerably lower than those of children from richer households.

The foregoing discussions imply the following considerations for policy. One, the women from poorer households continues to have poorer control over their fertility compared to the rich.

Given that poor households tend to have higher unmet needs and larger family sizes, this highlights the urgent need to address this disparity. Two, government facilities are still the primary the source of modern contraceptive supplies even for the very rich. Knowing that supplies in public facilities are provided by donors, once these supplies are withdrawn there will be acute drying up of supplies even for women from richer households and even more so for poorer households. Three, there is still a lot to do to counteract the fatalistic attitude and fear of side effects as reasons for not using contraception particularly for women from poor hous eholds. This means continued and even heightened IEC campaign for this particular group of the clientele. Four, improving the quality of pre-natal and post-natal service providers for the poor continues to be a challenge. Fifth, while it is more understan dable to find disparities for the more involved and expectedly more expensive post natal services, such as internal examination, this should not be allowed to happen to simple services such as family planning, breastfeeding and baby care advice. Sixth, iron and iodine supplementation for the poor needs attention. Finally, BCG, DPT, Polio, Measles and Hepatitis 1 immunization for the poor also needs continued attention.

The exercise done in this paper has provided information that are important for improving targeting government services. It is recommended that this exercise should be continuously done in the future.

REFERENCES Filmer, D. and L. Pritchett (1998) “Estimating Wealth Effects without Expenditure Data -- or Tears: An Application to Educational Enrollments in States of India” WPS1994 World Bank.

Gwatkin, D., S. Rustein, K. Johnson, R. Pande, and A. Wagstaff (2000) “Socio-economic Differences in Health, Nutrition and Population in the Philippines,” Processed. World Bank.

NSO. “Family Planning Survey,” various years.

NSO. “Maternal and Child Health Survey,” various years.

NSO (n.d.) “Socioeconomic Indicator to Identify the Poorest Households for Family Planning Survey and Maternal and Child Health Survey,” processed.

NSO, DOH and Macro Int’l (1999) National Demographic and Health Survey 1998. Manila, NSO and MI. Orbeta, A. (2003) “Comparing the Performance of the Different Proxies for Socio-Economic Status Using Philippine Data,” Processed.

17 Annex A – Principal Components Results Panel A (principal components; 8 components retained) Component Eigenvalue Difference Proportion Cumulative -----------------------------------------------------------------1 3.04453 1.91074 0.3806 0.3806 2 1.13379 0.12646 0.1417 0.5223 3 1.00733 0.17965 0.1259 0.6482 4 0.82769 0.13493 0.1035 0.7517 5 0.69275 0.12006 0.0866 0.8383 6 0.57270 0.15977 0.0716 0.9098 7 0.41292 0.10464 0.0516 0.9615 8 0.30828 .

0.0385 1.0000

Panel B Eigenvectors Variable | 1 2 3 4 5 6 -------------+----------------------------------------------------------------q16a | 0.41194 -0.40697 -0.07488 0.00559 -0.27494 0.39327 q16b | 0.32115 -0.39081 -0.05128 0.05940 0.84123 -0.16945 q16c | 0.46262 -0.28619 -0.08797 -0.02793 -0.26381 0.13646 q16d | 0.37033 0.45637 -0.24509 0.09019 -0.02522 -0.48348 q16e | 0.45508 0.09643 -0.13519 -0.05115 -0.24067 -0.35878 q17a | 0.17998 0.01381 0.76154 0.60817 -0.07977 -0.10555 q17b | 0.22492 0.15457 0.56492 -0.76911 0.07756 -0.00161 q17c | 0.29314 0.59840 -0.08128 0.15333 0.27606 0.65144 Eigenvectors Variable | 7 8 -------------+--------------------q16a | 0.40041 0.51813 q16b | -0.02923 0.02725 q16c | -0.09755 -0.77319 q16d | 0.58869 -0.07371 q16e | -0.66973 0.35711 q17a | 0.01001 0.00130 q17b | 0.09400 0.00227 q17c | -0.15898 -0.00156

Panel C Scoring Coefficients Variable | 1 -------------+---------q16a | 0.41194 q16b | 0.32115 q16c | 0.46262 q16d | 0.37033 q16e | 0.45508 q17a | 0.17998 q17b | 0.22492 q17c | 0.29314

where: q16a – Electricity; q16b – Radio; q16c – TV; q16d – Telephone; q16e – Refrigerator; q17a – Bicycle; q17b – Motorcycle; q17c - Automobile

Annex Table 1. Percent distribution of all women by current users of modern method by five-year age group by asset quintile, Philipppines, 2000 ANY METHOD

Pill

IUD

Injection

Diaphragm

Condom

MODERN Ligation

Vasectomy

Mucus

Thermometer

LAM

Total

Calendar

Total 15-19 20-24 25-29 30-34 35-39 40-44 45-49

27.1 1.3 12.5 31.8 43.2 47.4 43.4 30.0

7.84 0.6 5.6 14.4 16.3 12.7 6.1 2.0

1.9 0.1 1.1 2.7 4.2 3.3 1.9 0.9

1.45 0.1 1.4 2.8 2.2 2.4 1.4 0.3

0.02 0.0 0.0 0.0 0.1 0.1 0.0 0.0

0.77 0.0 0.4 0.9 1.4 1.4 1.0 0.8

6.29 0.0 0.3 2.0 5.9 11.2 17.2 15.8

0.1 0.0 0.0 0.1 0.1 0.1 0.2 0.4

0.03 0.0 0.0 0.0 0.0 0.2 0.0 0.0

0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

0.31 0.1 0.4 0.6 0.4 0.5 0.2 0.1

18.7 0.9 9.2 23.5 30.5 31.8 28.0 20.4

5.44 0.1 1.8 4.8 8.7 10.3 10.4 6.5

2.75 0.2 1.4 3.3 3.8 5.2 4.5 2.7

0.2 0.0 0.1 0.2 0.3 0.1 0.6 0.4

Poorest 15-19 20-24 25-29 30-34 35-39 40-44 45-49

25.8 1.1 17.2 33.3 39.7 40.2 35.5 20.4

8.2 0.3 6.9 15.5 15.5 11.3 6.3 1.8

2.0 0.0 1.6 3.2 4.4 2.4 1.8 1.0

2.1 0.1 3.4 3.5 2.5 3.3 1.5 0.6

0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

0.6 0.0 0.2 0.6 0.6 1.5 1.4 0.4

3.1 0.0 0.6 1.6 2.1 4.8 8.5 6.5

0.1 0.0 0.0 0.0 0.0 0.0 0.1 0.4

0.0 0.0 0.0 0.0 0.1 0.0 0.0 0.0

0.0 0.0 0.0 0.1 0.0 0.0 0.0 0.0

0.5 0.1 0.5 0.6 1.2 0.8 0.3 0.1

16.6 0.6 13.3 25.0 26.4 24.0 20.0 10.7

6.3 0.2 2.4 4.8 10.3 11.0 10.1 6.9

2.4 0.3 0.8 3.0 2.4 4.9 4.3 2.0

Lower Middle 15-19 20-24 25-29 30-34 35-39 40-44 45-49

30.0 1.7 16.5 36.0 47.8 51.6 42.6 28.7

9.8 0.7 7.0 17.1 20.5 15.2 6.8 3.4

2.4 0.2 1.7 3.0 5.2 4.5 1.9 0.9

1.9 0.1 1.9 3.6 2.8 3.3 2.1 0.3

0.1 0.0 0.0 0.0 0.2 0.3 0.0 0.0

0.6 0.1 0.2 1.0 1.3 1.0 1.0 0.0

5.3 0.0 0.3 1.6 5.3 9.7 13.0 12.7

0.1 0.0 0.0 0.2 0.0 0.1 0.0 0.0

0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1

0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

0.4 0.0 0.7 0.7 0.4 1.1 0.2 0.0

20.6 1.1 11.8 27.2 35.6 35.2 24.9 17.4

6.1 0.2 3.6 4.7 7.4 10.8 11.8 8.1

Middle 15-19 20-24 25-29 30-34 35-39 40-44 45-49

29.7 1.4 13.1 40.4 50.0 52.0 47.9 30.9

8.4 0.8 5.0 17.8 17.7 12.8 6.4 2.1

2.3 0.0 1.2 4.3 4.9 3.1 2.5 1.7

1.6 0.2 1.2 3.5 3.2 2.3 1.0 0.3

0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

0.8 0.0 0.7 0.9 1.3 1.5 1.6 0.6

7.0 0.0 0.4 3.7 8.4 13.4 18.4 16.2

0.1 0.0 0.0 0.0 0.2 0.1 0.2 0.8

0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1

0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

0.4 0.1 0.5 1.0 0.2 0.4 0.1 0.2

20.6 1.1 8.9 31.1 35.8 33.6 30.2 22.1

Upper Middle 15-19 20-24 25-29 30-34 35-39 40-44 45-49

28.2 1.2 11.2 29.7 44.2 52.7 47.5 34.0

7.8 0.5 5.5 14.3 15.4 14.7 6.3 1.8

2.0 0.2 0.7 2.4 5.1 4.1 2.1 0.8

1.2 0.1 1.0 2.3 1.6 1.8 1.9 0.1

0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

0.9 0.0 0.5 0.6 2.5 1.2 0.6 1.3

7.5 0.0 0.0 1.5 6.5 15.0 20.4 18.4

0.1 0.0 0.0 0.0 0.2 0.2 0.5 0.2

0.0 0.0 0.0 0.0 0.0 0.1 0.0 0.0

0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

0.2 0.1 0.5 0.4 0.2 0.2 0.1 0.0

Richest 15-19 20-24 25-29 30-34 35-39 40-44 45-49

22.7 1.1 8.6 21.3 35.6 40.8 42.6 34.2

5.7 0.6 4.7 8.7 12.8 9.7 4.8 1.2

1.0 0.0 0.8 0.8 1.8 2.3 1.4 0.5

0.7 0.1 0.6 1.3 0.9 1.5 0.5 0.5

0.0 0.0 0.0 0.1 0.0 0.0 0.0 0.0

0.9 0.1 0.3 1.4 1.2 1.9 0.8 1.4

7.8 0.0 0.3 1.4 7.3 12.6 23.3 22.8

0.1 0.0 0.0 0.1 0.0 0.1 0.2 0.5

0.1 0.0 0.0 0.0 0.0 0.7 0.0 0.0

0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

0.2 0.1 0.2 0.4 0.2 0.0 0.1 0.1

Source of raw data: NSO, 2000 Family Planning Survey

TRADITIONAL Withdrawal Other

No Method

Total

8.4 0.4 3.3 8.3 12.7 15.7 15.4 9.6

72.88 98.7 87.5 68.2 56.8 52.6 56.6 70.0

100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0

0.6 0.1 0.8 0.5 0.7 0.3 1.1 0.8

9.3 0.6 4.0 8.3 13.3 16.3 15.5 9.7

74.2 98.9 82.8 66.7 60.3 59.8 64.5 79.6

100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0

3.2 0.4 1.2 4.0 4.6 5.6 5.1 2.8

0.2 0.0 0.0 0.1 0.3 0.1 0.9 0.5

9.4 0.6 4.8 8.8 12.2 16.5 17.7 11.3

70.0 98.3 83.5 64.0 52.2 48.4 57.4 71.3

100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0

5.3 0.2 1.7 4.8 8.5 10.8 11.5 5.3

3.7 0.1 2.6 4.3 5.3 7.5 5.5 3.5

0.2 0.0 0.0 0.3 0.4 0.1 0.7 0.0

9.1 0.3 4.2 9.3 14.2 18.4 17.7 8.8

70.3 98.6 86.9 59.6 50.0 48.0 52.1 69.1

100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0

19.7 0.9 8.2 21.4 31.6 37.2 31.8 22.5

5.5 0.1 1.3 4.9 8.6 10.5 10.6 7.2

2.9 0.2 1.7 3.3 4.0 4.8 5.0 3.6

0.1 0.0 0.0 0.0 0.1 0.2 0.1 0.7

8.5 0.3 3.0 8.2 12.7 15.5 15.7 11.5

71.8 98.8 88.8 70.3 55.8 47.3 52.5 66.0

100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0

16.4 0.9 6.8 14.2 24.1 28.7 31.2 26.9

4.5 0.1 0.9 5.0 8.6 8.7 8.3 5.2

1.7 0.1 0.7 2.1 2.9 3.4 2.8 1.9

0.1 0.0 0.1 0.0 0.0 0.1 0.2 0.2

6.3 0.2 1.7 7.1 11.5 12.1 11.4 7.3

77.3 98.9 91.4 78.7 64.4 59.2 57.4 65.8

100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0

Total

Annex Table 2. Percent distribution of married women by current users of modern method by five-year age group by asset quintile, Philipppines, 2000 ANY METHOD

Pill

IUD

Injection

Diaphragm

Condom

Total 15-19 20-24 25-29 30-34 35-39 40-44 45-49

47.0 22.9 38.1 47.2 52.7 54.4 49.9 34.5

13.7 10.6 17.0 21.3 19.9 14.6 7.0 2.4

3.3 1.2 3.4 4.0 5.1 3.8 2.3 1.1

2.5 2.6 4.1 4.1 2.6 2.8 1.6 0.4

0.0 0.2 0.0 0.0 0.1 0.1 0.0 0.0

1.3 0.6 1.2 1.4 1.6 1.6 1.2 0.9

10.6 0.0 0.9 2.9 7.0 12.5 19.4 17.7

Poorest 15-19 20-24 25-29 30-34 35-39 40-44 45-49

37.6 16.2 33.6 39.6 42.3 43.9 38.6 22.8

11.9 4.4 13.5 18.3 16.6 12.3 6.9 2.1

3.0 0.6 3.0 3.9 4.6 2.6 2.0 1.2

3.0 2.1 6.6 4.2 2.7 3.7 1.6 0.7

0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

0.9 0.3 0.4 0.7 0.5 1.6 1.6 0.5

Lower Middle 15-19 20-24 25-29 30-34 35-39 40-44 45-49

47.6 26.8 39.8 46.4 54.0 56.8 47.7 33.8

15.5 9.9 16.9 21.9 23.1 16.8 7.6 4.1

3.9 4.1 4.1 3.9 5.9 4.9 2.1 1.1

3.1 1.1 4.5 4.6 3.1 3.8 2.4 0.4

0.1 0.0 0.0 0.0 0.3 0.3 0.0 0.0

Middle 15-19 20-24 25-29 30-34 35-39 40-44 45-49

50.9 20.6 36.9 55.6 59.5 57.9 54.4 35.4

14.5 12.2 14.0 24.4 21.2 14.4 7.2 2.5

3.9 0.3 3.2 5.8 5.8 3.6 3.0 2.0

2.8 3.4 3.2 4.9 3.7 2.6 1.2 0.4

Upper Middle 15-19 20-24 25-29 30-34 35-39 40-44 45-49

51.8 23.2 38.6 48.8 56.8 62.3 55.8 39.2

14.4 11.3 18.8 23.3 20.1 17.3 7.4 2.1

3.7 0.6 2.6 3.9 6.6 4.9 2.4 1.0

Richest 15-19 20-24 25-29 30-34 35-39 40-44 45-49

47.6 31.1 42.4 44.8 52.9 51.0 52.0 39.2

12.0 16.6 23.8 17.9 19.1 12.3 6.0 1.4

2.0 0.0 4.1 1.7 2.6 2.8 1.7 0.5

Source of raw data: NSO, 2000 Family Planning Survey

MODERN Ligation Vasectomy

TRADITIONAL Withdrawal Other

No Method

Total

14.7 6.8 10.1 12.4 15.7 18.0 18.0 11.3

53.0 77.1 61.9 52.8 47.3 45.6 50.1 65.5

100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0

0.8 2.0 1.5 0.6 0.7 0.4 1.2 1.0

13.6 7.8 8.0 9.9 14.5 17.7 17.1 11.1

62.4 83.8 66.4 60.4 57.8 56.1 61.4 77.2

100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0

5.1 6.8 2.9 5.1 5.2 6.2 5.8 3.2

0.4 0.0 0.0 0.1 0.4 0.1 1.0 0.5

15.0 10.1 11.4 11.2 13.7 18.0 20.3 13.4

52.4 73.2 60.2 53.6 46.0 43.2 52.4 66.2

100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0

9.2 2.5 4.7 6.7 10.3 12.2 13.5 6.2

6.4 1.8 7.3 5.9 6.5 8.3 6.3 4.2

0.3 0.0 0.1 0.4 0.5 0.1 0.8 0.0

15.9 4.3 12.1 12.9 17.2 20.6 20.6 10.4

49.1 79.4 63.1 44.4 40.5 42.1 45.6 64.6

100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0

36.0 16.8 28.2 35.0 40.6 43.8 37.1 25.6

10.2 2.7 4.5 8.2 10.9 12.4 12.8 8.6

5.4 3.6 5.9 5.5 5.2 5.8 5.8 4.1

0.2 0.0 0.0 0.1 0.1 0.2 0.1 0.9

15.8 6.4 10.4 13.8 16.2 18.5 18.7 13.6

48.2 76.8 61.4 51.2 43.2 37.8 44.2 60.8

100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0

34.1 25.3 34.1 29.7 35.8 35.7 38.1 30.6

9.5 2.5 4.2 10.7 12.8 11.0 10.2 6.2

3.7 3.4 3.8 4.4 4.4 4.3 3.5 2.2

0.2 0.0 0.4 0.1 0.0 0.1 0.3 0.2

13.4 5.8 8.3 15.2 17.2 15.4 14.0 8.6

52.4 68.9 57.6 55.2 47.1 49.0 48.0 60.8

100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0

Mucus

Thermometer

LAM

TOTAL

Calendar

0.2 0.0 0.0 0.1 0.1 0.1 0.2 0.5

0.1 0.0 0.0 0.0 0.0 0.2 0.0 0.0

0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

0.5 1.1 1.3 0.9 0.5 0.6 0.2 0.1

32.3 16.1 27.9 34.7 37.0 36.3 31.9 23.2

9.5 2.6 5.4 7.2 10.6 11.8 12.1 7.7

4.8 3.8 4.3 4.9 4.7 6.0 5.2 3.1

0.4 0.4 0.4 0.3 0.4 0.2 0.7 0.5

4.3 0.0 1.1 1.8 2.1 5.2 8.8 6.8

0.1 0.0 0.0 0.0 0.0 0.0 0.1 0.5

0.0 0.0 0.0 0.0 0.1 0.0 0.0 0.0

0.0 0.0 0.1 0.1 0.0 0.0 0.0 0.0

0.7 1.0 0.8 0.7 1.3 0.9 0.4 0.1

24.0 8.3 25.6 29.7 27.8 26.2 21.4 11.7

9.2 2.3 4.8 5.7 11.2 11.9 11.1 8.0

3.6 3.6 1.7 3.6 2.6 5.4 4.9 2.2

1.0 1.2 0.4 1.4 1.5 1.1 1.1 0.1

8.2 0.0 0.8 2.1 5.9 10.5 13.9 14.6

0.1 0.0 0.0 0.3 0.0 0.2 0.0 0.0

0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1

0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

0.7 0.4 1.7 0.9 0.4 1.2 0.2 0.0

32.6 16.7 28.3 35.1 40.3 38.8 27.4 20.4

9.6 3.2 8.5 6.0 8.2 11.7 13.4 9.7

0.0 0.0 0.0 0.0 0.0 0.1 0.0 0.0

1.4 0.0 1.9 1.2 1.5 1.7 1.6 0.7

11.6 0.0 1.1 5.0 9.6 14.5 20.5 18.0

0.2 0.0 0.0 0.0 0.2 0.1 0.2 1.0

0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1

0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

0.6 0.5 1.5 1.4 0.2 0.4 0.1 0.3

35.0 16.3 24.9 42.6 42.2 37.3 33.8 25.0

2.2 2.5 3.5 3.8 2.1 2.2 2.2 0.1

0.0 0.8 0.1 0.0 0.0 0.0 0.0 0.0

1.6 0.0 1.7 1.0 3.3 1.4 0.7 1.5

13.4 0.0 0.0 2.4 8.0 17.4 23.7 20.6

0.3 0.0 0.0 0.0 0.2 0.3 0.6 0.3

0.0 0.0 0.0 0.0 0.0 0.1 0.0 0.0

0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

0.4 1.6 1.5 0.6 0.3 0.3 0.1 0.0

1.5 4.1 2.5 2.8 1.4 1.9 0.7 0.5

0.0 0.0 0.0 0.1 0.0 0.0 0.0 0.0

1.8 2.0 1.4 3.0 1.7 2.3 1.0 1.6

16.1 0.0 1.6 3.0 10.7 15.4 28.3 25.8

0.2 0.0 0.0 0.2 0.0 0.2 0.3 0.6

0.2 0.0 0.0 0.1 0.0 0.8 0.0 0.0

0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

0.3 2.5 0.8 0.9 0.3 0.0 0.1 0.1

TOTAL

Annex Table 3. Percent distribution of married women by current contraceptive method used, by urbanity, by asset quintile Philippines, 2000

MODERN

TRADITIONAL

Any Method Pill

IUD

Injection Diaphragm

Condom

Ligation

Vasectomy

Mucus

Thermometer

LAM

Total

Calendar

Withdrawal

Other

Total

NO METHOD

Total

No. of Women ('000)

Total Urban Rural

47.0 48.6 45.5

13.7 13.7 13.6

3.3 3.2 3.4

2.5 1.9 3.1

0.0 0.0 0.1

1.3 1.6 1.1

10.6 12.9 8.5

0.2 0.2 0.2

0.1 0.0 0.1

0.0 0.0 0.0

0.5 0.6 0.5

32.3 34.1 30.6

9.5 9.4 9.7

4.8 4.9 4.8

0.4 0.3 0.5

14.7 14.6 14.9

53.0 51.4 54.5

100.0 100.0 100.0

11029 5336 5694

Poorest Urban Rural

37.6 40.9 37.1

11.9 12.7 11.8

3.0 5.1 2.6

3.0 2.7 3.1

0.0 0.0 0.0

0.9 1.1 0.9

4.3 5.2 4.1

0.1 0.0 0.1

0.0 0.0 0.0

0.0 0.0 0.0

0.7 0.7 0.7

24.0 27.6 23.4

9.2 9.4 9.2

3.6 3.1 3.7

0.8 0.9 0.8

13.6 13.4 13.7

62.4 59.1 62.9

100.0 100.0 100.0

2276 330 1946

Lower Middle Urban Rural

47.6 48.9 46.9

15.5 14.4 16.1

3.9 3.8 4.0

3.1 3.0 3.2

0.1 0.0 0.2

1.0 1.4 0.8

8.2 8.9 7.8

0.1 0.1 0.1

0.0 0.0 0.0

0.0 0.0 0.0

0.7 0.9 0.6

32.6 32.5 32.7

9.6 10.2 9.2

5.1 5.9 4.6

0.4 0.4 0.4

15.0 16.4 14.2

52.4 51.1 53.1

100.0 100.0 100.0

2217 773 1444

Middle Urban Rural

50.9 50.7 51.2

14.5 15.2 13.6

3.9 4.0 3.8

2.8 2.3 3.3

0.0 0.0 0.0

1.4 1.4 1.4

11.6 11.5 11.8

0.2 0.1 0.4

0.0 0.0 0.0

0.0 0.0 0.0

0.6 0.6 0.6

35.0 35.2 34.9

9.2 8.6 10.0

6.4 6.7 6.0

0.3 0.3 0.4

15.9 15.5 16.3

49.1 49.2 48.8

100.0 100.0 100.0

2236 1192 1044

Upper Middle Urban Rural

51.8 50.8 53.4

14.4 14.5 14.2

3.7 3.2 4.6

2.2 1.7 3.1

0.0 0.0 0.0

1.6 1.4 1.9

13.4 14.3 11.9

0.3 0.2 0.3

0.0 0.0 0.0

0.0 0.0 0.0

0.4 0.5 0.1

36.0 36.0 36.1

10.2 10.0 10.5

5.4 4.7 6.5

0.2 0.2 0.4

15.8 14.8 17.4

48.2 49.2 46.6

100.0 100.0 100.0

2154 1364 790

Richest Urban Rural

47.6 46.8 50.4

12.0 11.8 12.6

2.0 2.0 2.2

1.5 1.2 2.5

0.0 0.0 0.1

1.8 1.9 1.5

16.1 16.1 16.0

0.2 0.3 0.0

0.2 0.1 0.6

0.0 0.0 0.0

0.3 0.4 0.1

34.1 33.8 35.6

9.5 9.2 10.9

3.7 3.7 3.8

0.2 0.2 0.1

13.4 13.0 14.8

52.4 53.2 49.6

100.0 100.0 100.0

2147 1677 470

Source of raw data: NSO, 2000 Family Planning Survey

Annex Table 4. Percent distribution of married women by current contraceptive method used by asset quintile by region, Philippines, 2000 MODERN

TRADITIONAL

ANY METHOD

Pill

IUD

Total Ilocos Region Cagayan Valley Central Luzon Southern Tagalog Bicol Region W.Visayas C.Visayas E.Visayas W.Mindanao N.Mindanao S.Mindanao C.Mindanao Metro Manila CAR ARMM Caraga

47.0 41.0 61.2 54.9 48.7 31.7 47.6 47.0 37.2 49.3 57.3 55.4 50.9 45.7 50.6 12.5 47.3

13.7 12.3 24.2 14.1 13.6 8.8 15.2 12.7 8.4 19.1 15.6 16.2 15.0 13.6 8.7 4.5 11.7

3.3 1.0 3.7 0.9 2.6 1.2 3.0 4.8 1.5 6.6 9.4 7.6 6.4 2.1 1.2 0.2 6.8

2.5 3.9 5.3 1.9 3.2 1.7 2.8 2.3 1.4 2.0 3.2 2.2 4.4 1.2 5.4 0.8 3.3

0.0 0.0 0.3 0.0 0.0 0.0 0.0 0.0 0.0 0.2 0.0 0.0 0.4 0.0 0.1 0.0 0.0

1.3 0.7 0.4 1.5 1.4 1.0 1.2 2.7 0.5 0.6 0.9 1.8 0.9 1.5 4.3 0.5 1.8

10.6 13.3 14.9 18.0 11.9 5.8 8.2 7.9 7.9 3.8 7.9 8.8 6.5 14.5 13.4 1.3 8.2

0.2 0.0 0.4 0.3 0.2 0.0 0.3 0.1 0.2 0.1 0.2 0.3 0.0 0.2 0.1 0.0 0.1

0.1 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.0 0.1 0.0 0.4 0.0 0.1 0.1 0.0 0.0

Poorest Ilocos Region Cagayan Valley Central Luzon Southern Tagalog Bicol Region W.Visayas C.Visayas E.Visayas W.Mindanao N.Mindanao S.Mindanao C.Mindanao Metro Manila CAR ARMM Caraga

37.6 38.5 63.1 60.3 39.4 22.6 41.5 40.8 25.6 43.5 53.6 45.6 46.0 8.0 37.9 11.6 41.5

11.9 15.3 29.4 9.1 12.5 7.4 13.5 11.1 6.4 16.0 16.4 13.9 16.3 8.0 5.0 3.7 10.8

3.0 0.0 4.3 1.8 1.5 1.5 2.7 3.6 1.2 4.7 6.1 5.4 8.1 0.0 0.6 0.0 3.9

3.0 6.1 6.2 11.7 5.9 1.3 1.8 2.7 0.8 1.5 5.6 2.2 4.6 0.0 5.3 0.6 3.9

0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.0 0.0 0.0 0.0 0.0 0.0

0.9 0.6 0.6 7.2 0.4 1.0 0.7 1.2 0.5 0.5 0.4 0.9 1.3 0.0 4.6 0.2 0.6

4.3 5.4 11.6 17.1 4.6 2.5 5.3 4.5 2.7 1.9 4.6 5.0 3.6 0.0 6.7 0.5 4.0

0.1 0.0 0.0 0.0 0.0 0.0 0.2 0.4 0.0 0.0 0.5 0.0 0.0 0.0 0.0 0.0 0.0

0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.2 0.0 0.0 0.0 0.0 0.0

Injection Diaphragm Condom

Ligation

Vasectomy Mucus Thermometer

LAM

Total

Calendar Withdrawal

0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.0 0.0 0.0 0.0 0.0 0.0

0.5 0.3 0.9 0.5 0.8 0.0 0.7 0.2 0.0 0.8 0.3 0.8 0.5 0.6 0.7 0.7 0.5

32.3 31.5 50.0 37.2 33.8 18.5 31.3 30.9 19.9 33.4 37.6 38.1 34.2 33.6 34.0 8.1 32.2

9.5 3.6 6.1 6.4 7.6 9.4 12.6 13.2 12.4 12.7 17.0 15.0 12.4 7.5 9.6 1.0 12.1

0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.4 0.0 0.0 0.0 0.0 0.0 0.0

0.7 0.5 1.8 0.0 2.1 0.0 0.2 0.5 0.0 0.9 0.2 1.5 0.0 0.0 1.8 1.3 1.0

24.0 28.0 53.8 46.9 27.0 13.9 24.4 24.0 11.5 25.5 34.3 29.0 33.9 8.0 24.1 6.3 24.1

9.2 2.2 3.5 3.7 5.4 5.8 13.1 13.8 10.0 13.4 14.8 13.4 9.3 0.0 6.4 1.2 13.1

NO METHOD

Total

14.7 9.5 11.2 17.7 14.9 13.2 16.3 16.2 17.3 15.9 19.7 17.3 16.7 12.1 16.6 4.4 15.1

53.0 59.0 38.8 45.1 51.3 68.3 52.4 53.0 62.8 50.7 42.7 44.6 49.2 54.3 49.4 87.4 52.7

100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0

13.6 10.5 9.4 13.4 12.3 8.7 17.1 16.8 14.1 18.0 19.3 16.6 12.2 0.0 13.9 5.3 17.3

62.4 61.6 36.9 39.7 60.6 77.4 58.5 59.3 74.4 56.5 46.4 54.4 54.0 92.0 62.1 88.4 58.5

100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0

Other

Total

4.8 5.8 5.1 11.2 6.5 3.6 3.6 2.5 4.4 2.1 2.2 2.2 3.7 4.5 6.9 1.7 2.8

0.4 0.0 0.1 0.2 0.8 0.2 0.0 0.5 0.4 1.2 0.5 0.2 0.6 0.1 0.2 1.7 0.3

3.6 8.3 5.9 8.1 4.8 2.8 4.0 2.4 3.1 2.7 3.7 3.2 1.5 0.0 7.5 1.8 3.9

0.8 0.0 0.0 1.5 2.1 0.1 0.0 0.7 1.0 1.8 0.8 0.0 1.4 0.0 0.0 2.4 0.4

Annex Table 4. Percent distribution of married women by current contraceptive method used by asset quintile by region, Philippines, 2000 MODERN

TRADITIONAL

ANY METHOD

Pill

IUD

Lower Middle Ilocos Region Cagayan Valley Central Luzon Southern Tagalog Bicol Region W.Visayas C.Visayas E.Visayas W.Mindanao N.Mindanao S.Mindanao C.Mindanao Metro Manila CAR ARMM Caraga

47.6 41.3 61.2 52.4 49.4 32.6 51.9 49.9 37.2 52.6 64.7 51.7 49.3 44.2 49.2 11.7 46.5

15.5 13.6 25.1 13.2 16.4 11.0 18.9 14.3 11.8 24.2 15.2 17.4 14.6 12.6 14.1 4.5 12.2

3.9 1.4 6.3 0.7 4.3 0.5 2.6 5.4 1.1 7.3 11.5 6.7 4.6 1.8 1.5 0.1 5.1

3.1 5.5 5.4 1.5 4.1 2.2 3.9 2.6 1.0 2.2 4.7 3.3 3.6 1.3 5.5 0.5 2.7

0.1 0.0 0.9 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.6 0.0 0.0 0.0 0.0

1.0 0.0 0.0 0.2 0.7 1.6 1.3 2.5 0.6 0.0 0.6 0.7 1.5 2.4 3.3 0.5 1.7

8.2 10.8 12.6 13.3 9.2 5.9 8.4 7.6 7.2 4.6 5.1 4.8 5.5 12.0 8.3 3.0 10.4

0.1 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.3 0.3 0.0 0.5 0.0 0.0 0.0 0.0 0.0

0.0 0.0 0.0 0.0 0.1 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

Middle Ilocos Region Cagayan Valley Central Luzon Southern Tagalog Bicol Region W.Visayas C.Visayas E.Visayas W.Mindanao N.Mindanao S.Mindanao C.Mindanao Metro Manila CAR ARMM Caraga

50.9 43.2 59.8 56.4 50.5 39.8 52.0 52.8 48.2 52.2 54.7 62.2 49.1 50.1 52.0 9.2 55.1

14.5 10.7 19.1 16.4 13.0 8.2 17.4 13.2 10.0 22.3 16.6 17.7 16.5 15.7 9.0 3.0 14.2

3.9 1.1 1.5 0.7 3.9 1.6 3.2 5.7 1.6 7.0 11.1 13.1 8.1 4.0 0.5 1.6 16.1

2.8 4.6 3.3 2.4 3.2 1.5 3.3 3.0 2.2 3.3 1.9 1.0 4.1 2.0 5.6 1.9 2.4

0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.6 0.0 0.0

1.4 1.0 0.8 1.2 1.6 0.0 0.8 4.0 0.0 0.0 0.6 4.2 0.0 1.0 3.7 1.4 2.6

11.6 14.8 19.3 17.6 11.0 6.4 9.4 9.7 10.5 4.1 9.6 8.8 7.3 11.4 12.9 1.3 7.0

0.2 0.0 1.6 0.4 0.0 0.0 0.1 0.0 0.0 0.0 0.2 1.3 0.0 0.2 0.0 0.0 0.4

0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.3 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

Injection Diaphragm Condom

Ligation

Vasectomy Mucus Thermometer

LAM

Total

Calendar Withdrawal

0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

0.7 0.5 0.9 0.9 1.5 0.0 0.3 0.0 0.0 0.0 0.5 1.3 0.9 2.2 0.0 0.0 0.5

32.6 31.8 51.1 29.8 36.3 21.3 35.4 32.4 21.9 38.6 37.5 34.7 32.3 32.2 32.7 8.6 32.5

9.6 3.3 6.4 5.0 6.0 6.8 12.8 12.6 10.2 11.9 25.7 15.0 11.6 5.0 10.3 0.2 11.0

0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

0.6 0.5 0.4 0.4 1.0 0.0 2.4 0.0 0.0 2.9 0.6 0.2 0.4 0.2 0.0 0.0 0.0

35.0 32.7 45.9 39.1 33.8 17.6 36.5 35.8 24.3 39.5 40.6 46.3 36.4 34.5 32.2 9.2 42.7

9.2 2.7 7.2 5.3 7.6 18.0 12.3 14.5 14.8 8.8 12.1 12.6 9.9 9.7 11.0 0.0 11.4

NO METHOD

Total

15.0 9.5 10.2 22.6 13.1 11.3 16.5 17.5 15.3 14.0 27.2 17.0 17.0 12.0 16.5 3.1 13.9

52.4 58.7 38.8 47.6 50.6 67.4 48.1 50.1 62.8 47.4 35.3 48.3 50.7 55.8 50.8 88.4 53.5

100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0

15.9 10.5 13.9 17.4 16.7 22.2 15.5 17.0 23.9 12.7 14.1 15.9 12.7 15.6 19.8 0.0 12.4

49.1 56.8 40.2 43.6 49.5 60.2 48.0 47.2 51.8 47.8 45.3 37.8 50.9 49.9 48.1 90.8 44.9

100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0

Other

Total

5.1 6.2 3.7 17.4 6.0 4.5 3.6 4.5 5.1 1.2 1.5 2.0 4.6 7.0 5.4 2.0 2.7

0.4 0.0 0.0 0.2 1.1 0.0 0.0 0.5 0.0 0.9 0.0 0.0 0.9 0.0 0.8 0.9 0.2

6.4 7.8 6.7 11.9 8.6 3.6 3.2 1.6 9.2 3.2 1.6 2.1 2.8 5.7 8.8 0.0 0.6

0.3 0.0 0.0 0.1 0.6 0.6 0.0 0.9 0.0 0.7 0.4 1.2 0.0 0.2 0.0 0.0 0.4

Annex Table 4. Percent distribution of married women by current contraceptive method used by asset quintile by region, Philippines, 2000 MODERN

TRADITIONAL

ANY METHOD

Pill

IUD

Upper Middle Ilocos Region Cagayan Valley Central Luzon Southern Tagalog Bicol Region W.Visayas C.Visayas E.Visayas W.Mindanao N.Mindanao S.Mindanao C.Mindanao Metro Manila CAR ARMM Caraga

51.8 44.2 58.0 57.7 53.0 45.6 47.5 45.5 41.1 54.2 59.1 61.8 56.5 47.3 60.8 20.8 52.3

14.4 12.0 19.5 15.7 14.2 9.6 11.3 11.8 7.5 15.9 16.1 19.2 15.2 15.5 9.2 9.1 12.2

3.7 1.8 3.8 1.3 2.0 1.7 5.1 6.2 1.6 11.3 12.7 8.9 2.8 1.4 2.4 0.0 9.2

2.2 3.4 4.1 1.5 3.4 1.6 1.7 0.5 1.5 1.8 1.1 2.3 7.2 0.7 6.8 4.0 3.5

0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.9 0.0 0.0 0.0 0.0 0.0 0.7 0.0

1.6 1.7 0.0 1.4 1.3 1.8 2.1 4.2 0.3 0.8 1.3 2.1 0.7 1.2 6.5 0.0 2.6

13.4 16.3 18.5 19.3 14.5 9.9 9.9 7.4 12.4 6.1 10.7 10.3 7.8 15.0 15.0 2.4 10.7

0.3 0.0 0.0 0.5 0.3 0.0 0.9 0.0 0.6 0.0 0.0 0.0 0.0 0.3 0.6 0.0 0.2

0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.5 0.0 0.0 0.0 0.0 0.0 0.0 0.0

Richest Ilocos Region Cagayan Valley Central Luzon Southern Tagalog Bicol Region W.Visayas C.Visayas E.Visayas W.Mindanao N.Mindanao S.Mindanao C.Mindanao Metro Manila CAR ARMM Caraga

47.6 36.9 64.2 50.3 47.2 37.2 47.2 48.9 60.9 51.8 52.9 63.4 58.7 42.9 59.5 31.4 48.5

12.0 11.6 27.4 10.7 12.1 10.0 13.2 13.9 5.7 17.1 12.1 11.5 11.0 11.6 6.2 13.8 7.7

2.0 0.6 0.6 0.6 1.5 0.3 2.1 3.9 3.4 5.5 4.5 5.3 9.3 1.6 1.1 0.0 4.0

1.5 1.1 8.0 0.2 1.2 3.0 3.2 2.0 3.3 2.2 0.6 1.2 1.9 1.0 4.0 0.0 4.1

0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.8 0.0 0.0 0.0 0.0 0.0 0.0 0.0

1.8 0.3 0.4 1.8 2.1 0.5 1.5 2.4 1.7 3.1 2.6 2.6 0.4 1.8 3.9 3.3 2.8

16.1 15.6 14.2 20.5 15.8 13.3 11.4 13.3 21.2 5.5 13.5 21.0 12.4 16.2 27.9 0.0 10.7

0.2 0.0 0.6 0.1 0.4 0.0 0.4 0.1 0.9 0.0 0.0 0.3 0.0 0.2 0.0 0.0 0.0

0.2 0.0 0.0 0.0 0.0 0.0 0.3 0.0 0.0 0.0 0.0 2.6 0.0 0.1 0.7 0.0 0.0

Injection Diaphragm Condom

Source of raw data: NSO, 2000 Family Planning Survey

Ligation

Vasectomy Mucus Thermometer

LAM

Total

Calendar Withdrawal

0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

0.4 0.0 0.0 0.6 0.1 0.0 0.4 0.4 0.0 1.0 0.0 0.1 0.6 0.7 1.5 0.0 0.3

36.0 35.1 45.9 40.2 35.8 24.6 31.4 30.3 23.8 38.3 41.9 43.0 34.3 34.8 41.8 16.3 38.7

10.2 4.6 6.3 7.3 9.0 13.6 11.4 13.1 16.2 12.2 15.0 16.8 14.7 7.9 11.9 0.9 11.1

0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

0.3 0.0 1.8 0.3 0.3 0.0 0.0 0.3 0.0 0.0 0.0 0.4 0.6 0.4 0.0 1.2 0.0

34.1 29.1 52.9 34.3 33.4 27.0 32.1 35.8 36.2 34.2 33.3 44.8 35.5 32.8 43.9 18.3 29.2

9.5 4.9 7.9 8.3 8.6 10.0 13.1 11.4 19.6 17.6 17.0 17.3 20.6 6.7 9.8 7.7 15.8

NO METHOD

Total

15.8 9.1 12.2 17.6 17.2 21.0 16.1 15.1 17.3 15.9 17.2 18.8 22.2 12.5 19.0 4.5 13.6

48.2 55.8 42.0 42.3 47.0 54.4 52.5 54.5 58.9 45.8 40.9 38.2 43.5 52.7 39.2 79.2 47.7

100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0

13.4 7.8 11.3 16.0 13.8 10.2 15.1 13.0 24.7 17.6 19.6 18.6 23.2 10.1 15.6 13.1 19.3

52.4 63.1 35.8 49.7 52.8 62.8 52.8 51.1 39.1 48.2 47.1 36.6 41.3 57.1 40.5 68.6 51.5

100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0

Other

Total

5.4 4.5 5.9 10.2 7.5 7.4 4.7 2.1 1.1 2.5 1.9 2.0 7.5 4.5 7.1 2.0 2.3

0.2 0.0 0.0 0.0 0.8 0.0 0.0 0.0 0.0 1.2 0.3 0.0 0.0 0.1 0.0 1.6 0.3

3.7 2.7 2.9 7.6 5.0 0.2 2.0 1.7 4.5 0.0 1.2 1.3 2.6 3.4 5.9 3.4 3.4

0.2 0.2 0.5 0.1 0.2 0.0 0.0 0.0 0.6 0.0 1.5 0.0 0.0 0.1 0.0 2.0 0.0

Annex Table 5. Percentage distribution of source of modern method excluding LAM, Philippines, 2000

MODERN Diaphragm Condom

Pill

IUD

Injection

Ligation

Vasectomy

Total

GOVERNMENT Government Hospital RHU/Urban Health Center BHS Barangay Supply/Service Point Office/BHW PRIVATE Private Hospital or Clinic Private Doctor Private Midwife Pharmacy Store NGO Industry-based clinic OTHERS Puericulture Center Church Friend/Relative Other Don't Know

73.0 1.7 31.6 35.2 4.5 25.9 1.6 0.8 0.3 21.4 1.2 0.4 0.1 0.9 0.1 0.0 0.3 0.4 0.3

80.2 19.1 58.3 2.3 0.5 17.4 11.6 3.6 1.5 0.0 0.0 0.7 0.0 2.1 1.9 0.0 0.0 0.2 0.3

93.9 5.3 44.1 43.4 1.1 4.6 1.6 1.6 0.3 0.9 0.0 0.2 0.0 0.6 0.5 0.0 0.0 0.1 1.0

100.0 0.0 57.0 43.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

50.3 2.3 21.7 23.0 3.3 45.9 1.2 0.6 0.8 36.7 6.3 0.0 0.3 1.5 0.0 0.0 0.9 0.6 2.3

71.0 64.1 6.7 0.1 0.0 27.2 24.8 1.8 0.0 0.0 0.0 0.6 0.0 1.3 0.6 0.4 0.0 0.3 0.6

67.8 52.7 7.9 7.2 0.0 31.5 30.7 0.0 0.0 0.0 0.0 0.0 0.8 0.0 0.0 0.0 0.0 0.0 0.7

73.8 25.1 26.5 20.0 2.2 24.6 10.6 1.5 0.4 10.9 0.8 0.5 0.1 1.1 0.5 0.1 0.2 0.3 0.5

Total

127

120

105

100

147

128

131

126

GOVERNMENT Government Hospital RHU/Urban Health Center BHS Barangay Supply/Service Point Office/BHW PRIVATE Private Hospital or Clinic Private Doctor Private Midwife Pharmacy Store NGO Industry-based clinic OTHERS Puericulture Center Church Friend/Relative Other Don't Know

91.6 0.7 35.2 46.9 8.8 8.2 0.1 0.6 0.6 5.9 0.5 0.5

90.8 17.1 66.7 4.1 2.8 8.8 4.9 3.9 0.0 0.0 0.0 0.0

98.1 1.9 47.9 45.7 2.7 1.9 1.6 0.0 0.3 0.0 0.0 0.0

100.0 0.0 100.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

76.5 0.0 31.8 38.6 6.1 21.2 0.0 0.0 4.7 7.6 8.9 0.0

87.2 77.6 9.6 0.0 0.0 11.8 8.2 3.6 0.0 0.0 0.0 0.0

26.0 26.0 0.0 0.0 0.0 74.0 74.0 0.0 0.0 0.0 0.0 0.0

90.7 17.2 35.9 32.1 5.5 8.8 2.7 1.4 0.5 3.3 0.6 0.3

0.0 0.0

0.5 0.5

0.0 0.0

0.0 0.0

0.0 0.0

0.9 0.3

0.0 0.0

0.2 0.1

0.0 0.0 0.3

0.0 0.0 0.0

0.0 0.0 0.0

0.0 0.0 0.0

0.0 0.0 2.3

0.0 0.7 0.1

0.0 0.0 0.0

0.0 0.1 0.2

Total

108.2

109.2

101.8

100.0

121.2

112.7

174.0

109.0

GOVERNMENT Government Hospital RHU/Urban Health Center BHS Barangay Supply/Service Point Office/BHW PRIVATE Private Hospital or Clinic Private Doctor Private Midwife Pharmacy Store NGO Industry-based clinic OTHERS Puericulture Center Church Friend/Relative Other Don't Know

86.6 1.4 38.6 41.4 5.2 12.2 0.9 0.2 0.3 10.4 0.2 0.2

84.1 17.7 65.4 1.0 0.0 11.3 8.0 2.0 0.9 0.0 0.0 0.4

98.0 6.6 42.0 49.4 0.0 1.6 0.6 0.0 1.0 0.0 0.0 0.0

100.0 0.0 70.2 29.8 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

66.6 1.2 26.2 32.2 7.0 32.0 0.0 0.0 0.6 31.4 0.0 0.0

79.5 70.8 8.7 0.0 0.0 18.4 16.2 0.9 0.1 0.0 0.0 1.2

21.0 21.0 0.0 0.0 0.0 79.0 79.0 0.0 0.0 0.0 0.0 0.0

84.8 21.7 34.2 26.2 2.8 13.4 5.8 0.6 0.4 6.0 0.1 0.5

0.9 0.2 0.0 0.5 0.3 0.3

3.5 2.7 0.0 0.0 0.8 1.1

0.4 0.4 0.0 0.0 0.0 0.0

0.0 0.0 0.0 0.0 0.0 0.0

1.4 0.0 0.0 1.4 0.0 0.0

1.8 0.7 0.6 0.0 0.5 0.3

0.0 0.0 0.0 0.0 0.0 0.0

1.4 0.6 0.2 0.3 0.4 0.4

Total

113.1

114.8

102.0

100.0

133.4

120.2

179.0

114.8

POOREST

LOWER MIDDLE

Annex Table 5. Percentage distribution of source of modern method excluding LAM, Philippines, 2000

MODERN Diaphragm Condom

Pill

IUD

Injection

Ligation

Vasectomy

Total

GOVERNMENT Government Hospital RHU/Urban Health Center BHS Barangay Supply/Service Point Office/BHW PRIVATE Private Hospital or Clinic Private Doctor Private Midwife Pharmacy Store NGO Industry-based clinic OTHERS Puericulture Center Church Friend/Relative Other Don't Know

73.8 1.4 33.4 34.4 4.6 23.5 0.7 0.3 0.1 21.0 0.9 0.3 0.2 2.2 0.0 0.0 0.9 1.3 0.5

78.0 23.5 53.9 0.6 0.0 20.2 14.0 2.5 3.5 0.0 0.0 0.2 0.0 1.9 1.9 0.0 0.0 0.0 0.0

97.7 5.7 45.1 45.2 1.8 2.3 1.1 0.2 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

100.0 0.0 100.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

56.9 1.4 21.4 32.1 2.0 32.0 1.6 0.0 0.0 27.1 3.2 0.0 0.0 2.8 0.0 0.0 2.2 0.6 8.3

81.4 73.8 7.6 0.0 0.0 16.9 15.1 0.9 0.0 0.0 0.0 0.9 0.0 1.1 0.6 0.6 0.0 0.0 0.7

94.4 56.2 12.4 25.8 0.0 3.0 3.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 2.6

78.2 29.1 27.3 19.6 2.2 19.4 7.2 0.7 0.5 9.9 0.5 0.5 0.1 1.6 0.4 0.2 0.5 0.6 0.8

Total

125.7

122.0

102.3

100.0

134.8

118.0

103.0

121.0

GOVERNMENT Government Hospital RHU/Urban Health Center BHS Barangay Supply/Service Point Office/BHW PRIVATE Private Hospital or Clinic Private Doctor Private Midwife Pharmacy Store NGO Industry-based clinic OTHERS Puericulture Center Church Friend/Relative Other Don't Know

64.0 1.0 29.0 31.0 3.0 35.1 3.2 0.8 0.2 27.9 1.9 0.8 0.4 0.7 0.2 0.0 0.0 0.5 0.2

78.0 13.8 60.9 3.3 0.0 20.9 14.0 4.4 1.9 0.0 0.0 0.6 0.0 0.9 0.9 0.0 0.0 0.0 0.2

92.6 5.9 46.1 40.4 0.3 5.3 1.5 2.8 0.0 1.0 0.0 0.0 0.0 1.0 1.0 0.0 0.0 0.0 1.1

100.0 0.0 18.2 81.8 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

45.4 4.6 22.8 13.9 4.1 52.8 1.6 2.7 0.0 40.3 8.2 0.0 0.0 0.7 0.0 0.0 0.7 0.0 1.1

70.7 62.9 7.7 0.1 0.0 26.7 24.6 1.9 0.0 0.0 0.0 0.3 0.0 1.9 0.8 0.5 0.0 0.6 0.7

76.1 60.4 15.6 0.0 0.0 24.0 21.1 0.0 0.0 0.0 0.0 0.0 2.9 0.0 0.0 0.0 0.0 0.0 0.0

69.0 26.5 25.0 16.1 1.4 29.3 12.3 1.8 0.3 13.2 1.1 0.5 0.2 1.2 0.5 0.2 0.0 0.4 0.5

Total

135.8

121.8

106.3

100.0

153.5

128.6

124.0

130.5

GOVERNMENT Government Hospital RHU/Urban Health Center BHS Barangay Supply/Service Point Office/BHW PRIVATE Private Hospital or Clinic Private Doctor Private Midwife Pharmacy Store NGO Industry-based clinic OTHERS Puericulture Center Church Friend/Relative Other Don't Know

45.2 4.5 19.5 20.4 0.8 54.5 3.2 2.7 0.4 45.3 2.7 0.2 0.0 0.2 0.2 0.0 0.0 0.0 0.1

64.7 25.6 35.4 3.7 0.0 30.7 19.4 7.1 0.4 0.0 0.0 3.9 0.0 4.6 4.6 0.0 0.0 0.0 0.0

70.7 8.3 35.7 26.7 0.0 20.2 5.1 8.9 0.0 6.1 0.0 0.0 0.0 2.6 1.9 0.0 0.0 0.7 6.6

100.0 0.0 0.0 100.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

25.7 2.9 12.9 9.9 0.0 72.2 2.0 0.0 0.0 60.0 9.2 0.0 1.0 2.1 0.0 0.0 0.3 1.8 0.0

54.2 50.6 3.3 0.3 0.0 44.3 41.3 2.5 0.0 0.0 0.0 0.5 0.0 0.7 0.4 0.2 0.0 0.1 0.8

61.9 61.9 0.0 0.0 0.0 38.2 38.2 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

50.9 28.2 13.0 9.4 0.3 47.5 22.6 3.0 0.2 19.6 1.5 0.5 0.1 0.9 0.6 0.1 0.0 0.2 0.8

Total

154.7

135.3

122.8

100.0

174.3

144.9

138.2

148.4

MIDDLE

UPPER MIDDLE

RICHEST

Source of raw data: NSO, 2000 Family Planning Survey

Annex Table 6. Percent distribution of married women, reason of not using contraceptives by age group by asset quintile, Philippines, 2000 15-19

20-24

25-29

30-34

35-39

40-44

45-49

Total

Wants children Lacks knowledge Method-related reasons Side effects Health concerns Incovenient to use Costs too much Hard to get Opposition to use Opposed to family planning Prohibited by religion Reasons Relating to Exposure Menopausal/had hysterectomy Old/difficult to get pregnant Infrequent sex/husband away Amenorrheic Not married/Not sexually active Others Fatalistic (bahala na) Other

33.0 4.1 11.3 5.2 4.3 0.8 0.4 0.6 2.7 0.2 2.5 40.2 0.0 2.1 4.4 9.2 24.6 8.7 2.8 6.0

34.3 4.8 21.5 10.7 8.9 0.7 0.8 0.4 4.5 2.1 2.4 24.5 0.4 1.5 8.8 10.5 3.3 10.4 4.8 5.6

30.0 3.6 25.0 12.3 10.5 1.7 0.3 0.2 5.8 1.7 4.1 26.1 0.5 2.3 12.0 10.5 0.9 9.5 5.2 4.4

24.0 4.0 29.7 14.6 12.4 1.9 0.3 0.6 6.9 2.3 4.6 23.7 0.6 5.1 8.9 8.4 0.7 11.8 6.6 5.2

22.3 1.8 33.0 16.1 13.2 2.3 0.6 0.8 7.9 3.2 4.7 23.5 1.4 8.4 9.3 3.6 0.8 11.6 7.3 4.4

12.5 2.9 29.1 12.5 13.4 1.6 1.1 0.5 5.6 2.7 2.9 37.4 8.7 15.2 10.2 2.1 1.3 12.5 9.7 2.8

6.5 2.0 19.0 6.9 8.6 2.0 0.7 0.7 3.4 1.4 2.1 62.3 32.1 22.3 5.0 1.5 1.4 6.8 4.3 2.4

19.8 3.0 26.1 12.0 11.1 1.8 0.6 0.6 5.6 2.2 3.4 35.3 8.9 10.5 8.7 5.4 1.8 10.3 6.4 3.9

Total

100.0

100.0

100.0

100.0

100.0

100.0

100.0

100.0

Poorest Wants children Lacks knowledge Method-related reasons Side effects Health concerns Incovenient to use Costs too much Hard to get Opposition to use Opposed to family planning Prohibited by religion Reasons Relating to Exposure Menopausal/had hysterectomy Old/difficult to get pregnant Infrequent sex/husband away Amenorrheic Not married/Not sexually active Others Fatalistic (bahala na) Other

28.0 8.7 9.4 4.3 5.1 0.0 0.0 0.0 3.2 0.0 3.2 46.0 0.0 2.5 6.4 13.8 23.4 4.7 2.9 1.8

26.3 10.2 22.0 13.3 7.5 0.6 0.0 0.7 8.5 2.9 5.6 21.2 0.3 2.5 4.2 12.4 1.8 11.9 6.8 5.1

26.9 8.6 23.5 10.9 10.2 1.9 0.1 0.3 9.3 2.2 7.1 20.1 0.0 3.6 2.4 13.7 0.4 11.7 7.8 3.9

13.9 6.5 32.5 17.9 12.2 0.9 0.7 0.9 12.5 3.1 9.5 20.4 0.4 4.4 3.8 11.4 0.5 14.1 8.7 5.5

12.9 4.0 36.4 21.2 11.6 2.2 0.3 1.2 14.1 4.1 10.0 19.1 1.5 7.9 2.4 6.1 1.2 13.5 9.9 3.6

9.5 5.1 33.9 13.0 16.4 1.6 2.3 0.7 9.5 2.7 6.7 26.6 8.7 10.9 3.0 3.0 0.9 15.5 13.3 2.2

5.3 5.4 17.7 7.9 5.9 2.1 0.8 1.0 5.7 2.0 3.8 56.8 34.3 18.6 1.9 1.5 0.5 9.1 7.6 1.5

14.6 6.3 27.9 14.0 10.8 1.6 0.8 0.8 9.9 2.8 7.2 28.7 8.4 8.6 2.9 7.6 1.3 12.6 9.1 3.5

Total

100.0

100.0

100.0

100.0

100.0

100.0

100.0

100.0

Lower Middle Wants children Lacks knowledge Method-related reasons Side effects Health concerns Incovenient to use Costs too much Hard to get Opposition to use Opposed to family planning Prohibited by religion Reasons Relating to Exposure Menopausal/had hysterectomy Old/difficult to get pregnant Infrequent sex/husband away Amenorrheic Not married/Not sexually active Others Fatalistic (bahala na) Other

40.8 2.7 16.7 10.0 3.3 0.0 0.0 3.4 3.7 0.0 3.7 29.4 0.0 6.5 6.7 1.9 14.5 6.6 2.5 4.2

34.6 3.7 21.2 10.9 6.6 0.0 3.2 0.6 4.1 2.2 2.0 24.2 0.0 1.7 8.2 11.5 2.8 12.3 7.0 5.3

23.8 4.0 28.8 14.7 11.7 1.4 0.7 0.3 6.2 0.9 5.3 25.6 0.5 1.4 8.6 14.7 0.4 11.7 4.3 7.4

22.3 3.1 38.9 22.6 13.4 2.7 0.2 0.0 6.4 2.2 4.3 19.1 0.6 4.1 5.7 8.7 0.0 10.2 6.1 4.1

19.0 2.3 35.3 14.1 17.0 2.7 0.9 0.7 9.1 4.9 4.2 21.5 1.7 8.3 4.8 5.7 1.0 12.8 7.2 5.6

13.6 1.9 29.1 16.7 9.7 1.5 0.7 0.6 6.8 3.8 3.0 31.7 10.7 12.6 4.3 2.6 1.4 17.0 13.0 4.1

3.9 2.4 20.3 7.0 9.1 1.9 1.5 0.8 4.5 1.8 2.8 62.6 33.9 24.7 2.3 0.7 0.9 6.3 4.9 1.4

18.1 2.8 28.9 14.2 11.3 1.8 1.0 0.6 6.3 2.6 3.6 32.5 9.4 10.1 5.3 6.4 1.3 11.5 7.1 4.4

Total

100.0

100.0

100.0

100.0

100.0

100.0

100.0

100.0

Annex Table 6. Percent distribution of married women, reason of not using contraceptives by age group by asset quintile, Philippines, 2000 15-19

20-24

25-29

30-34

35-39

40-44

45-49

Total

Middle Wants children Lacks knowledge Method-related reasons Side effects Health concerns Incovenient to use Costs too much Hard to get Opposition to use Opposed to family planning Prohibited by religion Reasons Relating to Exposure Menopausal/had hysterectomy Old/difficult to get pregnant Infrequent sex/husband away Amenorrheic Not married/Not sexually active Others Fatalistic (bahala na) Other

31.1 3.1 17.0 8.2 7.5 1.3 0.0 0.0 0.6 0.6 0.0 38.6 0.0 0.0 1.9 12.0 24.6 9.6 3.0 6.6

39.5 2.8 24.3 7.9 14.6 1.3 0.6 0.0 2.6 0.9 1.7 23.3 0.0 0.8 7.6 11.7 3.2 7.5 2.4 5.1

27.9 1.1 32.0 16.7 13.4 1.3 0.4 0.2 5.4 1.1 4.2 21.6 0.3 3.7 8.5 7.7 1.4 12.1 7.3 4.8

22.2 5.6 31.9 13.6 15.7 2.1 0.5 0.0 4.9 1.4 3.5 23.0 0.3 4.4 7.7 9.6 1.1 12.5 6.9 5.6

17.7 1.1 35.6 19.7 12.9 2.2 0.5 0.3 5.1 2.9 2.3 26.9 0.7 12.2 11.2 2.3 0.4 13.6 7.5 6.2

10.6 3.2 32.8 17.1 13.1 1.5 0.7 0.5 4.6 2.4 2.2 39.5 14.7 17.0 4.9 1.7 1.2 9.3 6.0 3.3

4.8 0.4 23.9 6.3 11.8 4.6 0.7 0.5 1.7 1.0 0.7 63.2 33.1 23.9 3.2 1.7 1.3 6.1 2.9 3.3

18.4 2.2 29.7 13.4 13.2 2.3 0.5 0.3 3.9 1.6 2.2 35.7 10.0 11.6 6.8 5.2 2.1 10.1 5.4 4.7

Total

100.0

100.0

100.0

100.0

100.0

100.0

100.0

100.0

Upper Middle Wants children Lacks knowledge Method-related reasons Side effects Health concerns Incovenient to use Costs too much Hard to get Opposition to use Opposed to family planning Prohibited by religion Reasons Relating to Exposure Menopausal/had hysterectomy Old/difficult to get pregnant Infrequent sex/husband away Amenorrheic Not married/Not sexually active Others Fatalistic (bahala na) Other

31.6 1.5 5.9 1.3 2.3 0.0 2.3 0.0 0.5 0.0 0.5 46.5 0.0 0.0 4.3 7.9 34.2 14.1 4.7 9.4

40.8 2.8 16.5 9.6 5.5 0.7 0.3 0.3 3.9 3.1 0.8 27.7 1.5 2.3 13.7 7.2 3.1 8.3 3.5 4.8

37.1 0.0 25.2 13.6 8.7 2.9 0.0 0.0 3.6 2.1 1.5 27.4 0.4 2.3 17.6 6.5 0.6 6.8 3.7 3.1

30.1 0.7 26.4 9.4 13.0 3.3 0.0 0.8 3.5 1.6 1.9 27.0 0.3 8.3 9.7 7.6 1.2 12.3 7.1 5.2

26.1 0.2 32.1 12.9 15.8 1.6 0.4 1.4 5.5 1.7 3.8 25.9 1.9 8.3 14.0 1.3 0.5 10.3 6.3 3.9

13.7 2.9 29.9 10.8 15.7 1.6 1.6 0.3 2.3 1.5 0.8 39.6 4.3 18.5 13.8 1.9 1.2 11.6 8.5 3.1

9.7 1.3 18.2 7.7 7.9 0.8 0.5 1.3 2.6 1.6 1.0 60.8 32.0 21.6 3.9 1.5 1.9 7.5 4.3 3.2

23.5 1.3 24.7 10.3 11.4 1.8 0.6 0.7 3.4 1.8 1.6 37.4 8.4 11.7 11.3 3.9 2.1 9.7 5.8 3.9

Total

100.0

100.0

100.0

100.0

100.0

100.0

100.0

100.0

Richest Wants children Lacks knowledge Method-related reasons Side effects Health concerns Incovenient to use Costs too much Hard to get Opposition to use Opposed to family planning Prohibited by religion Reasons Relating to Exposure Menopausal/had hysterectomy Old/difficult to get pregnant Infrequent sex/husband away Amenorrheic Not married/Not sexually active Others Fatalistic (bahala na) Other

36.2 3.6 4.1 0.0 0.9 3.1 0.0 0.0 7.0 0.0 7.0 39.9 0.0 1.9 3.2 7.7 27.1 9.3 0.0 9.3

30.5 3.6 23.2 12.0 9.8 1.0 0.0 0.5 2.5 1.4 1.1 27.8 0.3 0.0 12.4 8.5 6.6 12.4 4.2 8.2

36.8 1.8 15.8 6.3 8.3 0.9 0.2 0.2 3.1 2.4 0.8 38.4 1.3 0.3 27.3 7.3 2.2 4.1 2.0 2.1

36.8 2.9 17.1 7.3 7.9 0.8 0.1 0.9 4.0 2.8 1.1 30.7 1.4 4.6 20.4 3.2 1.2 8.5 3.2 5.4

37.2 0.4 25.2 11.6 9.9 2.4 0.8 0.5 3.8 2.1 1.8 25.4 1.3 5.8 15.9 1.6 0.8 7.9 4.9 3.0

15.3 1.2 20.3 5.9 11.9 1.9 0.2 0.5 4.2 2.9 1.3 50.4 6.0 17.6 24.2 1.0 1.7 8.6 6.9 1.7

8.7 0.5 15.6 5.9 8.4 0.9 0.2 0.2 2.5 0.7 1.9 67.9 27.9 23.2 12.4 2.1 2.3 4.9 2.1 2.8

25.4 1.4 19.0 7.5 9.3 1.4 0.3 0.4 3.5 2.0 1.5 43.6 8.5 11.0 18.5 3.2 2.4 7.3 3.9 3.4

Total

100.0

100.0

100.0

100.0

100.0

100.0

100.0

100.0

124

441

709

827

908

967

1,065

5,040

No. of Women (000)

Source of raw data: NSO, 2000 Family Planning Survey

Annex Table 7. Percent distribution of women with surviving children 0-35 months of age, by type of pre-natal care service provider, by asset quintile, and by type of residence, Philippines: 2000

Poorest

L_Middle

Asset Class Middle U_Middle

Richest

Total

Total Doctors Nurses Midwife Hilot Others

10.6 2.4 42.2 44.2 0.5

19.0 3.6 46.8 30.0 0.6

37.9 3.4 40.9 17.3 0.5

52.1 4.5 30.3 12.9 0.3

74.7 3.8 15.8 5.5 0.3

39.5 3.5 34.9 21.6 0.4

No. of Women ('000)

637

663

658

637

712

3,307

Urban Doctors Nurses Midwife Hilot Others

12.1 4.5 45.4 38.0 0.0

27.9 2.8 43.0 25.6 0.6

45.0 3.2 37.5 13.5 0.7

58.9 4.0 27.5 9.1 0.5

77.5 4.1 13.4 4.5 0.3

54.7 3.7 28.5 12.6 0.5

91

228

401

404

536

1,659

Rural Doctors Nurses Midwife Hilot Others

10.4 2.1 41.7 45.2 0.6

14.4 4.0 48.8 32.3 0.6

26.8 3.8 46.2 23.2 0.0

40.2 5.2 35.2 19.3 0.1

66.0 2.8 22.9 8.3 0.0

24.2 3.4 41.4 30.8 0.4

Total No. of Women ('000)

547

435

257

233

176

1,647

No. of Women ('000)

Source of raw data: NSO, 2000 Maternal and Child Health Survey

Annex Table 8. Percent distribution of women with surviving children 0-35 months of age, by number of pre-natal visits, by asset quintile and by type of residence, Philippines, 2000 Asset Class Middle U_Middle

No. of Pre-Natal Visits Total 0 1 2 3 4 5 6 7 8 9 10 or more Unreported DK

Poorest

L_Middle

Richest

Total

0.0 7.7 16.6 22.5 15.2 9.6 8.2 4.0 3.3 5.2 2.0 0.0 5.7

0.1 6.8 11.5 20.7 11.3 12.3 10.2 6.5 5.2 7.9 4.5 0.0 3.1

0.0 5.0 10.5 15.8 11.6 10.5 10.4 8.4 5.7 11.8 7.2 0.0 3.1

0.1 2.8 5.5 11.7 11.0 10.6 11.3 7.8 6.9 17.7 11.6 0.0 2.8

0.0 1.6 3.3 6.3 7.8 7.6 8.8 7.4 7.8 25.0 19.9 0.1 4.4

0.0 5.1 10.1 16.1 11.6 10.2 9.7 6.7 5.6 12.7 8.3 0.0 3.9

Total No. of Women ('000)

100.0 1,189

100.0 1,149

100.0 1,073

100.0 925

100.0 862

100.0 5,199

0.0 8.1 14.7 21.5 14.6 12.1 11.1 5.1 2.5 4.8 1.6 0.0 4.0

0.0 5.0 10.7 20.7 12.7 10.1 11.9 6.4 6.1 9.0 5.2 0.0 2.2

0.0 5.2 9.2 13.7 12.8 9.7 9.9 9.0 6.8 13.1 7.3 0.0 3.3

0.1 2.9 6.0 10.3 10.2 10.3 10.9 6.9 7.0 19.1 13.2 0.0 3.2

0.0 1.4 3.6 4.7 7.2 6.8 7.7 8.2 8.2 25.6 22.6 0.2 3.7

0.0 3.8 7.6 12.3 10.8 9.3 10.0 7.5 6.8 16.5 12.0 0.0 3.2

100.0 172

100.0 432

100.0 612

100.0 570

100.0 648

100.0 2,434

0.0 7.6 17.0 22.6 15.3 9.2 7.7 3.8 3.4 5.3 2.1 0.0 6.0

0.1 7.9 12.1 20.6 10.4 13.6 9.2 6.6 4.6 7.3 4.0 0.0 3.6

0.0 4.8 12.2 18.6 10.0 11.4 11.0 7.6 4.3 10.0 7.1 0.0 3.0

0.0 2.8 4.8 14.1 12.3 11.1 11.9 9.4 6.8 15.6 9.0 0.0 2.3

0.0 2.1 2.2 11.2 9.5 10.0 12.1 4.9 6.5 23.1 11.8 0.0 6.6

0.0 6.2 12.2 19.5 12.3 11.0 9.5 6.0 4.5 9.3 5.1 0.0 4.4

100.0 1,017

100.0 718

100.0 461

100.0 355

100.0 214

100.0 2,765

Urban 0 1 2 3 4 5 6 7 8 9 10 or more Ureported DK Total No. of Women ('000)

Rural 0 1 2 3 4 5 6 7 8 9 10 or more Unreported DK Total No. of Women ('000)

Source of raw data: NSO, 2000 Maternal and Child Health Survey

Annex Table 9. Percent distribution of women with surviving children 0-35 months of age who received supplementation during pregnancy with youngest child, by asset quintile and by type of residence, Philippines, 2000

Asset Class

Poorest

L Middle

Middle

U Middle

Richest

Total

Total Iron Tablet Iodine Capsule Tetanus Toxoid Vaccine

66.9 48.9 66.8

73.5 54.7 69.8

80.9 61.9 75.9

84.8 68.2 75.2

91.5 72.8 67.2

78.3 60.0 70.9

No. of Women ('000)

1,310

1,232

1,132

957

880

5,511

Urban Iron Tablet Iodine Capsule Tetanus Toxoid Vaccine

63.4 41.7 62.7

76.2 55.7 70.5

82.0 63.8 75.2

84.5 69.6 73.8

92.2 72.7 64.3

82.8 64.3 70.3

No. of Women ('000)

192

463

643

591

658

2,548

Rural Iron Tablet Iodine Capsule Tetanus Toxoid Vaccine

67.5 50.1 67.5

71.9 54.0 69.4

79.4 59.4 76.9

85.1 66.0 77.5

89.7 73.0 75.8

74.4 56.3 71.4

Total No. of Women ('000)

1,118

769

489

366

222

2,963

Source of raw data: NSO, 2000 Maternal and Child Health Survey

Annex Table 10. Percent distribution of women, with surviving children 0 -35 months of age, by number of tetanus toxoid injections received during pregnancy of youngest child, by asset quintile and residence, Philippines 2000

Asset Class

No. of TTI received

Poorest

L Middle

Middle

U Middle

Richest

Total

0 1 2 3 or more DK Unreported

0.0 54.3 27.1 15.5 3.1 0.0

0.0 48.6 31.7 16.6 3.0 0.1

0.1 50.5 27.9 17.4 4.1 0.0

0.0 48.9 30.8 17.3 3.1 0.0

0.0 51.9 28.9 15.2 3.9 0.0

0.0 50.8 29.2 16.4 3.4 0.0

Total

100.0

100.0

100.0

100.0

100.0

100.0

877

861

875

730

620

3,962

1 2 3 or more DK Unreported

54.9 24.4 15.5 5.2 0.0

53.0 30.8 13.8 2.2 0.2

51.0 28.4 15.9 4.7 0.0

51.6 28.2 16.6 3.7 0.0

51.7 27.7 15.7 4.9 0.0

51.9 28.3 15.6 4.1 0.0

Total

100.0

100.0

100.0

100.0

100.0

100.0

122

331

492

446

450

1,841

0 1 2 3 or more DK

0.0 54.2 27.6 15.5 2.8

0.0 45.9 32.3 18.3 3.6

0.3 49.7 27.2 19.3 3.4

0.0 44.6 34.9 18.4 2.1

0.0 52.6 32.3 13.8 1.3

0.1 49.9 30.0 17.2 2.9

Total

100.0

100.0

100.0

100.0

100.0

100.0

755

530

383

284

170

2,122

TOTAL

No. of Women ('000) URBAN

No. of Women ('000) RURAL

No. of Women ('000)

Source of raw data: NSO, 2000 Maternal and Child Health Survey

Annex Table 11. Percent distribution of women with surviving children 0-35 months of age, by type of post-natal care service provider, by asset quintile, and by type of residence, Philippines: 2000 Asset Class

Poorest

L Middle

Middle

U Middle

Richest

Total

Doctors Nurses Midwife Hilot Others

10.6 2.4 42.2 44.2 0.5

19.0 3.6 46.8 30.0 0.6

37.9 3.4 40.9 17.3 0.5

52.1 4.5 30.3 12.9 0.3

74.7 3.8 15.8 5.5 0.3

39.5 3.5 34.9 21.6 0.4

No. of Women ('000)

637

663

658

637

712

3,307

12.1 4.5 45.4 38.0 0.0

27.9 2.8 43.0 25.6 0.6

45.0 3.2 37.5 13.5 0.7

58.9 4.0 27.5 9.1 0.5

77.5 4.1 13.4 4.5 0.3

54.7 3.7 28.5 12.6 0.5

91

228

401

404

536

1,659

10.4 2.1 41.7 45.2 0.6

14.4 4.0 48.8 32.3 0.6

26.8 3.8 46.2 23.2 0.0

40.2 5.2 35.2 19.3 0.1

66.0 2.8 22.9 8.3 0.0

24.2 3.4 41.4 30.8 0.4

547

435

257

233

176

1,647

Total

Urban

Doctors Nurses Midwife Hilot Others No. of Women ('000) Rural

Doctors Nurses Midwife Hilot Others Total No. of Women ('000)

Source of raw data: NSO, 2000 Maternal and Child Health Survey

Annex Table 12. Percent distribution of women with surviving children 0-35 months of age who received post natal care by type of service received, by asset quintile and by type of residence, Philippines 2000 Asset Class Middle U Middle

Poorest

L Middle

Richest

Total

TOTAL Abdominal Exam Breast Exam Internal Exam Family Planning Advice Breastfeeding Advice Baby Care Advice Check Up of Baby Others

49.7 24.3 15.9 34.4 47.8 55.5 61.8 4.2

51.2 31.0 27.6 38.3 53.5 60.6 76.5 4.9

53.8 36.1 31.3 38.3 56.6 64.8 78.5 4.5

58.8 42.5 45.2 43.9 61.1 69.3 84.2 2.7

62.8 46.8 49.1 45.4 61.9 70.8 87.6 1.9

55.4 36.3 34.2 40.1 56.3 64.3 77.9 3.6

No. of Women ('000)

638

665

658

638

718

3,317

URBAN Abdominal Exam Breast Exam Internal Exam Family Planning Advice Breastfeeding Advice Baby Care Advice Check Up of Baby Others

48.6 29.1 19.8 42.0 51.1 61.9 69.1 3.0

57.3 33.0 36.1 37.6 55.1 59.5 78.5 3.2

55.2 36.1 34.2 42.1 57.8 64.8 79.1 4.7

58.5 43.0 47.7 47.2 62.7 70.1 84.9 1.8

64.0 48.2 53.8 50.3 63.4 72.9 88.6 1.9

58.8 40.9 43.3 45.4 60.1 67.8 83.0 2.8

91

229

401

406

542

1,670

RURAL Abdominal Exam Breast Exam Internal Exam Family Planning Advice Breastfeeding Advice Baby Care Advice Check Up of Baby Others

49.9 23.5 15.3 33.1 47.2 47.2 60.6 4.3

47.9 29.9 23.2 38.6 52.6 52.6 75.4 5.8

51.6 36.1 26.9 32.3 54.8 54.8 77.5 4.2

59.4 41.7 40.9 38.1 58.3 58.3 82.9 4.3

59.0 42.5 34.6 30.3 57.1 57.1 84.2 2.0

51.9 31.7 24.9 34.8 52.4 52.4 72.8 4.4

No. of Women ('000)

547

436

257

232

176

1,647

No. of Women ('000)

Source of raw data: NSO, 2000 Maternal and Child Health Survey

Annex Table 13. Percent distribution of children 0-35 months of age, by type of immunization received, by asset quintile and by type of residence, Philippines, 2000

POOREST L MIDDLE

TOTAL MIDDLE U MIDDLE RICHEST

TOTAL

POOREST L MIDDLE

URBAN MIDDLE U MIDDLE RICHEST

TOTAL

POOREST L MIDDLE

RURAL MIDDLE U MIDDLE RICHEST

TOTAL

0 to 35 months No. of Children ('000)

1,315

1,239

1,150

972

918

5,595

193

469

656

606

694

2,617

1,122

770

494

367

225

2,978

(%) BCG

78.0

84.1

88.3

93.2

93.9

86.7

77.0

87.6

89.1

93.8

95.0

90.6

78.2

82.0

87.3

92.2

90.5

83.3

DPT 1

75.0

81.3

86.5

90.3

90.8

84.0

70.8

83.2

86.5

90.3

92.0

87.1

75.8

80.1

86.6

90.3

87.1

81.3

DPT 2

91.2

92.4

90.8

93.9

94.3

92.3

92.4

91.7

90.3

93.4

94.9

92.6

91.0

92.8

91.5

94.7

92.3

92.1

DPT 3

81.2

81.6

81.2

83.6

85.9

82.4

82.3

80.3

81.5

83.8

87.6

83.5

81.0

82.3

80.7

83.1

80.6

81.5

Polio 1

74.8

80.2

85.1

88.4

89.6

82.9

73.4

82.6

84.1

88.9

90.8

85.9

75.0

78.7

86.4

87.7

85.7

80.2

Polio 2

90.4

91.8

91.2

92.9

93.6

91.8

89.8

90.7

91.2

93.4

94.6

92.4

90.4

92.5

91.2

92.1

90.5

91.3

Polio 3

81.2

81.3

81.8

83.8

85.2

82.5

80.1

78.8

82.6

84.0

87.8

83.4

81.4

82.8

80.9

83.3

77.2

81.6

Measles 1

50.9

55.0

58.3

62.1

62.9

57.2

47.4

54.1

56.6

62.8

64.8

59.1

51.5

55.6

60.4

60.8

57.2

55.6

Hepatitis B 1

36.7

42.0

43.6

54.6

58.3

46.0

33.6

40.6

41.9

52.2

60.8

48.5

37.2

42.9

45.9

58.7

50.4

43.8

Hepatitis B 2

87.8

85.4

85.2

85.4

86.5

86.1

89.2

87.3

87.1

85.8

85.8

86.7

87.5

84.2

82.7

84.7

88.6

85.6

Hepatitis B 3

80.2

77.1

77.3

73.2

75.4

76.9

83.0

79.4

79.9

73.4

73.6

76.9

79.7

75.7

73.8

72.9

81.2

77.0

481

471

437

397

375

2,159

76

183

254

240

276

1,028

404

288

183

157

99

1,131

0 to 11 months No. of Children ('000) (%) BCG

67.3

72.7

78.9

86.5

89.1

78.1

74.8

77.8

81.8

88.1

90.1

84.3

65.9

69.4

74.9

84.0

86.1

72.5

DPT 1

62.3

68.8

75.8

80.7

81.5

73.2

64.3

73.0

74.9

81.5

82.6

77.4

61.9

66.2

77.1

79.5

78.3

69.3

DPT 2

83.8

87.3

83.7

88.1

88.2

86.1

85.2

87.7

83.1

87.0

89.3

86.6

83.5

87.1

84.4

89.8

85.1

85.6

DPT 3

69.6

72.6

68.8

73.2

71.2

71.0

72.8

71.8

69.7

71.7

74.2

72.0

69.0

73.1

67.6

75.6

62.9

70.2

Polio 1

61.2

65.8

73.5

77.1

78.8

70.7

68.2

71.7

73.0

78.3

80.1

75.6

59.9

62.1

74.3

75.3

75.0

66.2

Polio 2

85.2

87.5

84.6

88.3

87.4

86.6

83.6

86.5

83.8

86.7

89.7

86.5

85.5

88.2

85.9

90.7

81.2

86.6

Polio 3

71.1

74.3

69.3

73.1

70.8

71.8

69.2

72.0

69.5

72.4

76.3

72.4

71.5

75.8

69.0

74.1

55.6

71.2

Measles 1

16.2

17.7

20.3

22.6

22.2

19.6

20.2

18.6

18.1

23.6

23.6

21.1

15.5

17.2

23.3

20.9

18.6

18.2

Hepatitis B 1

15.5

17.9

16.4

30.6

30.3

21.5

11.2

17.4

16.5

27.1

33.5

23.3

16.3

18.1

16.3

35.8

21.2

19.9

Hepatitis B 2

91.6

91.9

90.7

89.4

89.2

90.7

94.6

91.4

89.3

89.1

88.8

89.9

91.0

92.1

92.6

89.8

90.6

91.4

Hepatitis B 3

87.9

88.2

88.2

79.7

80.4

85.2

91.0

88.6

87.3

79.8

77.9

83.5

87.3

87.9

89.5

79.6

87.3

86.8

468

471

412

312

310

1,974

72

174

234

197

232

909

397

298

178

115

77

1,064

12 to 23 months No. of Children ('000) (%) BCG

85.1

91.0

94.9

98.5

96.9

92.5

76.7

94.2

94.8

98.2

98.6

95.0

86.6

89.1

95.0

98.8

91.8

90.4

DPT 1

83.4

88.5

93.7

97.5

96.1

91.0

72.0

89.8

93.8

97.1

97.6

93.0

85.4

87.7

93.6

98.1

91.8

89.3

DPT 2

95.7

96.0

94.2

98.3

99.1

96.4

96.6

94.0

94.1

98.2

98.9

96.4

95.6

97.2

94.3

98.5

99.7

96.4

DPT 3

87.8

87.5

87.7

90.8

96.8

89.6

87.6

83.5

88.2

92.7

97.7

90.7

87.9

89.8

87.1

87.5

94.0

88.7

Polio 1

83.1

88.9

92.3

96.3

96.0

90.5

73.1

90.0

91.1

96.4

97.4

92.2

85.0

88.2

93.8

96.3

91.8

89.1

Polio 2

93.3

94.4

93.4

96.1

98.1

94.8

93.5

92.0

94.2

98.6

97.7

95.6

93.2

95.7

92.5

91.8

99.4

94.1

Polio 3

86.8

85.1

88.6

91.2

95.3

88.8

86.9

78.7

89.3

93.4

95.9

89.7

86.8

88.8

87.6

87.5

93.4

88.0

Measles 1

70.5

76.1

79.0

91.0

88.4

79.6

59.4

73.4

78.7

90.4

89.5

81.5

72.5

77.6

79.3

91.8

85.0

78.1

Hepatitis B 1

51.6

56.8

61.7

72.5

78.5

62.5

50.2

58.1

57.8

69.2

81.0

65.7

51.9

56.0

66.8

78.2

70.8

59.8

Hepatitis B 2

86.4

82.8

78.2

82.0

83.0

82.6

84.4

87.2

82.5

82.4

82.4

83.5

86.8

80.2

72.6

81.4

84.9

81.8

Hepatitis B 3

74.5

71.1

68.5

68.2

70.5

70.8

75.4

75.3

74.0

69.6

68.5

72.0

74.4

68.7

61.2

65.6

76.5

69.8

366

297

301

263

234

1,462

45

112

168

168

186

680

321

185

133

95

48

782

24 to 35 months No. of Children ('000) (%) BCG

83.1

91.4

92.9

97.0

97.8

91.6

80.9

93.1

92.0

96.7

97.9

94.2

83.4

90.3

94.0

97.5

97.3

89.4

DPT 1

81.1

89.7

92.2

96.3

98.6

90.7

79.5

89.8

93.7

94.9

98.9

93.8

81.3

89.7

90.2

98.7

97.7

87.9

DPT 2

95.0

94.6

96.6

97.3

97.6

96.1

97.7

94.7

95.9

96.7

98.1

96.6

94.6

94.5

97.6

98.3

95.5

95.6

DPT 3

87.8

86.3

90.3

90.5

95.0

89.6

89.8

89.2

90.1

90.6

94.8

91.4

87.5

84.5

90.5

90.4

95.5

88.2

Polio 1

81.8

89.1

92.0

96.1

98.3

90.6

82.5

89.0

91.1

95.3

98.5

93.2

81.7

89.1

93.1

97.7

97.7

88.3

Polio 2

93.4

94.6

97.8

96.1

97.6

95.7

94.6

95.3

98.4

96.9

98.2

97.2

93.2

94.2

97.0

94.7

95.5

94.4

Polio 3

87.4

86.3

90.8

91.1

94.9

89.7

87.7

90.2

92.8

89.8

94.8

91.8

87.4

83.9

88.3

93.5

95.5

88.0

Measles 1

71.5

80.7

85.0

87.4

94.4

82.7

74.3

82.0

84.0

86.5

94.9

86.6

71.1

80.0

86.3

88.9

92.3

79.2

Hepatitis B 1

45.4

56.9

58.5

69.7

76.5

59.8

45.1

51.2

58.3

67.8

76.1

63.5

45.4

60.4

58.7

73.0

78.1

56.6

Hepatitis B 2

84.5

79.4

86.9

83.3

86.6

84.1

87.7

80.9

90.3

85.0

85.7

86.0

84.1

78.4

82.7

80.2

90.4

82.4

Hepatitis B 3

77.4

68.9

73.4

69.5

73.9

72.9

81.6

70.9

76.8

68.8

73.4

73.2

76.8

67.7

69.2

70.6

76.1

72.6

Source of raw data: NSO, 2000 Maternal and Child Health Survey