VIETNAM FERTILITY TREND AND DETERMINANTS AFTER A DECADE AT THE REPLACEMENT LEVEL: AN IMPLICATION FOR THE RECENT REBOUND IN DEVELOPED REGIONS

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VIETNAM FERTILITY TREND AND

DETERMINANTS AFTER A DECADE AT THE REPLACEMENT LEVEL: AN IMPLICATION

FOR THE RECENT REBOUND IN DEVELOPED REGIONS

Nguyen Ngoc Anh¹, Dinh Thai Ha², Nguyen Thanh Tung³

ABSTRACT

Vietnam has more than 5 decades of fertility control policy and now authorities are looking for a change after a decade of plateau fertility at the replacement level. They raised questions about fertility determinants which could help predict the total fertility course in coming years.

There were 5 intermediate determinants selected and brought into analysis in a period of 10-15 years. Meaningful visual graphs were employed to identify patterns and changes between determinants and total or age group fertilities overtime. From the data of 63 provinces, in the last decade, there were 2 opposite trends to keep the country wide fertility in balance: declining one in less developed areas, and uprising one

in low land developed regions. While the former was a result of development and its components like poverty reduction, education for girls, gender equity and public health, the later was the consequence of migration process more obviously in industrialized provinces.

Vietnam is still facing possible rising fertility unless the family planning services and jobs are available for young couples. In this point of view, there is a need for immediate and effective family planning and job creation policies for the youth in both less and developed regions. The fi ndings not only supported but also applied Adaptation theory to explain the rebound of fertility in developed regions. At a larger picture, the recent rebound of fertility in

1. Researcher at CPRID – Investigator, statistician 2. Deputy of Planning and Finance Department - GOPFP 3. Officer of Population and family planning Department – GOPFP

* Correspondent author: Nguyen Thanh Tung, Officer of Population and family planning Department – GOPFP, Email: [email protected]

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56 Vietnam Journal of Public Health - www.vjph.vn 2017 Vol. 5 Iss. 1

developed countries which experienced a long, continuous fl ows of migrants could be part of migration process and continue evolving.

INTRODUCTION

Vietnam in the last four decades, like many other developing countries, has experienced a sharp decline in fertility from its peak 6.8 children per woman in the 1960s to 2.1 in 2005¹ and continued stable till 2014². The government recognized the effort to keep the fertility at the replacement level as the success of a long run family planning (FP) program which was widely implemented at community level³. After decades of strong fertility control policy and a decade of fertility at the replacement level, authorities raised questions about the fertility trend and its determinants to refocus their population policy⁴. The fact that the fertility went fl at, slowing down from 2.1 children per woman in 2005 to 1.99 (2010) then bouncing back to 2.1 (2012)⁵, could bring to authorities and researchers three scenarios: (i) decrease gradually, (ii) keep a plateau trend before decline, (iii) increase in short term. The last scenario is least expected as fertility declining trend has been common internationally for decades⁶. However with the recent uptrend of fertility in many countries in Europe and North America nothing is impossible.

When looking at fertility trend and projection, researchers suggested two groups of determinants: intermediate and proximate.

The former determinants are socio-economic and demographic factors, such as economic development, education, urbanization, labor participation, public healthcare, which infl uence the biographic and behavioral patterns. While the later determinants suggested by Bongaarts

and Potter (1983) are postponement of marriage, contraceptive use, induced abortion and post- partum infecundability which mostly contribute to fertility variation of a country^{7, 8}. In many cases, demographers used these determinants to project fertility for two or more decades period of time. For example, well known FAMPLAN software was developed to project fertility of a country as users assign inputs of the four proximate determinants. While, Anthony L.

Redwood (1983) suggested a formula with eight independent variables including: Female labor participation, marriage patterns, female education level, level of income, relative size of youth cohort, contraceptive use. Recently, some scientists are in favor to probability calculation to project fertility for 100 years that is based on historical national fertility courses⁹. However, the fertility projection in relation with socio-demographic determinants appears more practical in short term, 10 to 15 years, as their factors’ projection is more reasonable and realistic.

This study did not set an objective to project Vietnam fertility for a period of time, but aimed at identifying a set of determinants which most infl uenced the fertility course in the last decade nationally and provincially. By undermining potential intermediate determinants in short term, the authorities could have a more realistic scenario of fertility with effective interventions and policy changes. The study was analyzed at provincial level. The results were discussed with current fertility theories and studies to gain an in depth explanation and implication.

METHODS

To look at changes of fertility over time, like the analysis used in United Nations’ report: World fertility report 2013: fertility at extremes, the authors used visual graphs of fertility and its

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determinants to identify patterns of change and association. A number of socio-economic indicators were identified from available literature, then later short-listed based on their availability and validity at provincial level.

There were six variables pre-selected for analysis as presented in below formula:

FERT = F(ED^- + FE^- + FL^- + UR^-/+ + CPR^- + MR^-/+) Where dependent variable is fertility (FERT), other independent variables are: ED = economic development; FE = female/girl education; FL = female labor participation; UR = urbanization;

CPR = modern contraceptive prevalence; MR

= migration. The marks ‘-’ and ‘+’ above each independent variable represent their correlation with fertility. While 4 socio-economic variables have negative association with fertility, there are two variables with unspecifi ed correlation including urbanization and migration. As many scientists suggested that human development has signifi cant infl uence on fertility^{7, 10}, the association was analyzed and discussed separately with other components including life expectancy, gender index, adult literacy, GDP per capita.

For each variable, one representative indicator was chosen for analysis. (Appendix 1). All periodical data were from national surveys or censuses conducted and published by General Offi ce of Statistics (GSO). As the data used for analysis were from surveys and censuses which were executed in the fi rst half of the years, the estimated average fertility data were presented and indicated for the year before. The time frame for analysis was expected for a period of ten years. As some indicators were not available at provincial level in annual surveys, data from Population and housing census 1999 and 2009

was used instead. Among 6 indicators were selected, the female labor participation rate was not included in analysis due to its unavailability at provincial level. It should be noted that the study was conducted in 2015, and at the time the result of Midterm population and housing census 2014 was not published so that the data of this census was used for referencing purpose only. In addition, the most expected data on ASFRs were not available at provincial level in 2014 midterm census so that the use of data in period 2002-2012 was valid and acceptable by the time being.

RESULTS

Vietnam’s total fertility rate (TFR) and adolescent fertility

Since 2005, Vietnam fertility fl uctuated around the replacement level, keeping a downward trend until 2010 (TFR = 1.99) before bounded back recently to the replacement level. This recent rebound of fertility was not expected by some authorities and researchers who projected the fertility to decline further as the economy continued growing. At provincial level, there was a declining trend in most provinces with high fertility, especially in mountainous areas, but a rebound of fertility in many provinces in low land areas was keeping the nationwide fertility virtually unchanged (Appendix 2).

From 2002 to 2012, the fertility declining trend was more popular as 38 over 60 provinces (not counted three provinces recently established) reported to experience a decrease in fertility to some extent. Among that, there were 29 provinces having a decrease over 0.1 unit in absolute term. In contrast, there were 13 provinces, mostly in coastal and lowland areas, with an increase of 0.1 unit or over. Despite of lower variance of the fertility increase, lowland provinces were resided by larger population

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so that the country wide fertility was kept in balance overtime.

At national level, the data showed that the age specifi c fertility rate (ASFR) was almost unchanged in the last decade, except a decrease of group 20-24, from 140 births/1000 women in 2002 to 122 births/1000 women in 2012, or declining 12.9 percent. It appeared reasonable as the mean age at marriage of women increased overtime along with the national socio- economic growth. At a quick look, the increase in ASFR of group 15-19 from 31 births/1000 women to 36, increasing 5 births/1000 women or 16.1 percent, did not affect much the total fertility rate. However, when screening by regions, from the perspective of health, there was an inequity for the youth living in mountainous areas where hosted mostly minority populations. Female adolescents living in the Northern mountainous areas not only contributed mostly to national adolescent birth rates (ABR), but also had increasing birth rates in the last decade (Appendix 3). From the point of view that the FP program has had strong impact on controlling fertility nationwide, it could be argued that the program had little or no effect on the group of female adolescents, especially in the mountainous North.

Actually, two out of four proximate determinants of Bongaarts, postponement of marriage and contraceptive use have been applied to explain the small changes in Vietnam ASFR and TFR over the decade. The other determinants of abortion and post-partum infecundability were not available at both provincial and national level. So far, Das et al. (2013) suggested that induced abortion had lowest effect on fertility while post-partum infecundability had signifi cant effect only in urban areas. In the perspective of development, in the time frame

in Vietnam, it could be expected a higher rate in induced abortion, no signifi cant change in contraceptive use and infecundability, the last one of postponement of marriage could lay the answer for countering effect on the declining trend in fertility to keep it in balance.

Fertility and development

There were many studies investigating and confi rming the negative relationship between fertility and development7, 10. Like the analysis method used by Guengant (2002), our analysis applied a linear regression to estimate the correlation of fertilities of 63 provinces and human development indices (HDIs) and its components. See (Table 1). Considering all 63 provinces, the correlation between HDI and total fertility appeared to have a weak association with R2 was only 0.364. This value increased to 0.467 for 29 provinces above 2.1 threshold.

The correlation totally disappeared for the other 34 provinces. The relationship among provinces with high fertility was stronger when looking at the correlation between fertility and life expectancy as R2 reached 0.613.

Table 1. R2 values in linear regression between fertility and human development index and its components by provinces and fertility groups, 2008

TFR 2008

R2 HDI Life

expectancy Adult literacy rate

GDP per capita

Gender equality index

Net female enrolment rate 63 provinces 0,364 0,605 0,312 0,133 0,355 0,087

(N=63) (N=63) (N=63) (N=63) (N=63) (N=63)

Provinces with TFR > 2.1 children/woman

0,467 0,613 0,383 0,250 0,460 0,003

(N=29) (N=29) (N=29) (N=29) (N=29) (N=29)

Provinces with TFR =< 2.1 children/woman

0,038 0,102 0,001 0,046 0,030 0,203*

(N=34) (N=34) (N=34) (N=34) (N=34) (N=34)

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Note: (*) positive relationship

(Source: Vietnam population and housing census 2009, GSO, and Social services for human development: National report on human development 2011, UNDP, 2011)

Within provinces with high fertility, adult literacy and gender indices had weak correlation with fertility, while GDP and female adolescent education had very weak or no correlation.

Among provinces with low fertility, there was no correlation between fertility and development components. It should be noted that, almost all development components had negative impact on fertility, only female adolescent education had a weak positive association for provinces with low fertility. In short, development promotes lower fertility for those with fertility in transition only but has less effect on those with fertility at and below the replacement level.

Socio-economic indicators and fertility

Overtime, many researchers, demographers tried to investigate in fertility decline process via Bongaart model with four proximate determinants which were recognized as suitable at national level⁸. In this study,

the research objective was set at provincial level so that there were fi ve socio-economic indicators includinged: poverty reduction, education for girls, urbanization, public health/contraceptive use, and migration.

Overtime, many researchers, demographers tried to investigate in fertility decline process via Bongaart model with four proximate determinants which were recognized as suitable at national level⁸. In this study, the

research objective was set at provincial level so that there were fi ve socio-economic indicators includeding: poverty reduction, education for girls, urbanization, public health/contraceptive use, and migration.

Poverty reduction

In developing countries like Vietnam, the use of household poverty rate representing for socio- economic development is practical as poverty reduction is still a primary target of Vietnam government’s strategies¹¹ and this indicator has been monitored for decades. As the poverty rates at provincial level were not available for 2002, the data of 1998 was used instead for the periodical analysis.

In Figure 1, there is a common pattern that household poverty, in both fertility groups decreased overtime in parallel with fertility declining trend. However, there was a rebound in provinces with lowest fertilities despite a lowering trend in poverty. In the period 1998 – 2012, poverty reduction success promoted lower fertility for those with high fertilities, but

Figure 1. Changes in total fertility and household poverty rate by provinces and fertility groups for period 1998-2012

Source: Poverty and inequality in Vietnam: spatial and geogrphical determinants. 2003, Development studies institute; Vietnam living standards survey 2013, GSO

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had different effects on those with low fertility.

Female education

Net female high school enrollment rate was chosen for the analysis as Vietnam has universalized its primary and secondary education. In 2013 national survey, the overall enrolment rate for primary education was 103.1% and 91.6% for secondary education. In the fi rst glance when looking at the relationship between total fertility and female education, in Table 1, the 2008 statistics showed that there was no association. It was more practical when

the relationship was investigated through ASFR of adolescents and net female high school enrolment rate. As we did not have ASFR data at provincial level until 2008, the relationship was presented in period of fi ve years from 2008 to 2012 (Figure 2). The ABRs of 63 provinces were presented in proportion with TFR, instead of absolute number to have better comparison among provinces.

Spatially, when applying linear regression to investigate the ABR differentials and female adolescent education, there was a strong relationship, especially for provinces with high

fertilities with R² (0.73, 2012) close to 1. In contrast, this R² value for provinces with low fertilities was only 0.241 (2012). In Appendix 3, we saw an increase in ABRs overtime critically.

In Figure 2, that the regression line of 2012 was steeper than 2008 line suggested that the inequity of fertility and education among adolescents in mountainous areas in comparison with those in low land areas was more serious overtime.

In short term, in Vietnam, female education alone, without an effective FP program for girls could not help bring adolescent fertility down effectively overtime.

Urbanization

Urbanization, commonly measured by proportion of urban population, is a component of development and affects total fertility in some ways¹⁰. In Vietnam, the proportion of urban population increased from 25.8 percent to 32.2 percent in 2002- 2012 period, a level which was very low in comparison with other South east Asian countries such as around 46 percent in Thailand (2012)¹². By provinces, there were six over 63 provinces reporting negative growth rates of urban population, while 10 provinces with an increase above 10 percentage units. In practice, the change of urban geographical boundary, other than industrial development, played a crucial role in the growth of urban population.

For example, the merge of Hanoi capital with less developed province of Ha Tay in 2007 made the urban population down from 57.6%

in 1999 to 40.8% in 2009¹³.

From Figure 3, urbanization did not drive down fertility rates. Even in the same group with fertility above 2.1, there were six Figure 2. Changes in ABR proportion in TFR and female

net high school enrolment rate by provinces and fertility groups for period 2008-2012

Source: Vietnam housing and population census 2009, GSO;

Vietnam population and family planning survey 2013, GSO

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provinces with high urbanization levels reporting a decline in fertility, ten provinces reporting some degrees of fertility increase. In the group with low fertility, the two² provinces with highest urbanization rates experienced a modest increase in fertility.

Contraceptive use

As many scientists suggested that the contraceptive prevalence rate (CPR) of a country would not surpass 80 percent⁷ since 2002 Vietnam’s CPR has approached this maximum level with 75%

among married couples, and around 78% in recent fi ve years. The modern contraceptive use rates were around 67% in the last decade¹². By provinces, in the last decade the fertility declining trend was popular with increasing modern contraceptive rates. However, there were some provinces experienced increasing fertility regardless lower or higher modern contraceptive use rates. In the group with high fertility, fi ve provinces having a signifi cant increase in fertility reported a decrease above fi ve percentage units in contraceptive use rates (Figure 4). In other words, while modern contraceptive use played a critical role in fertility control in provinces with high

fertility, its effect on fertility was less signifi cant in provinces with fertility below 2.1 threshold.

Migration

Migration is a coherent part of development process and could be seen as a development tool for authorities to attract laborers from less developed regions. As international migration in Vietnam

was not signifi cant so that only internal migration was considered in this analysis.

To investigate in the effects of migration on fertility, the study preferred to using data on migrant population in fi ve years period which are available only in population censuses. In the fi rst glance, see Figure 5, migration did not promote fertility declining trend at all as 34 provinces experiencing declining fertilities had a proportion of migrant population less than 10 percent in 2008. Three provinces with highest migration rates including Ho Chi Minh (14%), Binh Duong (35%), Da Nang (8.9%) were those experiencing a fertility increase.

From 1998 to 2008, there were 13 provinces reporting higher fertility.

Figure 3. Changes in total fertility rate and urban population proportion by provinces and fertility groups, 2002-2012 Source: Vietnam population and family planning survey 2003 and 2013, GSO

Figure 4. Changes in total fertility rate and modern contraceptive use by provinces and fertility groups, 2002-2012

Source: Vietnam population and family planning survey 2003 and 2013, GSO

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As migrant population is young in nature, we have a closer look at fertility of group 20-24 years of age. (Figure 6). All three provinces with highest migration rates, around 30%, experienced sharp decline in ASFR of 20-24 groups. From the point of view that migration had strong impact on fertility of young couple groups, there were still 2 exceptional cases.

Dong Nai with a migration rate of 10.8%

reported unchanged in the ASFR in this period, 24.8 children per 1000 women in 1998 compared with 24.3 in 2008. Hai Phong with a migration rate of 2.8% witnessed a sharp decline from 38.2 children/1000 women in 1998 to 28.3 in 2008.

DISCUSSION

In the last decade, Vietnam has witnessed a fl at fertility trend around the replacement level despite of a growing socio-economic trend. At national level, the ASFR was almost unchanged except a decline in women group 20-24². Looking at provincial level, there were two opposite trends of fertilities to keep the national fertility at balance: (i) Continuing decline in mountainous areas; and (ii) A rise

mostly in developed areas. While socio- economic development, including education, poverty reduction, public health has been well recognized as a major force to drive fertility downward, the determinants of rebounding trend do not have an immediate answer. That improper understanding could raise a question about a possibility of rising fertility, or at least being fl at in coming years before it declines to a balanced level. In addition, the increasing fertility in adolescents in mountainous areas could be a potential hindrance to lower fertility in provinces with high fertility.

For determinants of fertility, in accordance with the results of the research at international level conducted by Guengant (2002), development and its components like life expectancy, literacy, and gender equity are contributed to the fertility transition, especially in less developed regions. At macro level, girl education appeared to have no effect on total fertility. That early conclusion is partially Figure 5. Changes in fertility and migrant

population by provinces, 1998-2008 Source: Vietnam housing and population census 1999 – 2009, GSO

Figure 6. Changes in ASFR of group 20-24 and migrant population proportion by provinces and fertility groups, 1998 – 2008 Source: Vietnam housing and population census 1999 – 2009, GSO

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opposite to the accepted agreement that female education promotes low fertility^{6, 14}. However, girl education has showed its inhibiting effect on fertility of adolescent groups. When looking in a time frame, in short term girl education alone is not enough to keep ABR to decrease.

This could be a bias result of the current FP program focusing much on married couples, especially in mountainous areas. Another important indicator of development, poverty rate has showed a strong negative correlation with fertility, especially in less developed areas.

The two variables have a mutual relationship as couples with less children have more time and resources to work and invest in their children, while better off families are more likely to use contraceptives and have smaller family size¹⁵. The convergence of the relationship between fertility and poverty reduction in provinces with low fertility has raised a question about what factor is behind the rebound of fertility.

Among the other three determinants, urbanization had a different meaning and did not show a correlation with fertility.

Many less developed provinces with high fertility declining pace reported low level of urbanization. This fi nding is not outstanding as in its recent report UN acknowledged that fertility transition started regardless of urbanization levels. In addition, urban population is technically and signifi cantly affected by urban geographical changes overtime. In this case, urbanization is an indicator of development rather than an intermediate fertility determinant.

Contraceptive use has played a critical role in the success of fertility control effort since the beginning of FP program in Vietnam^{3, 8}. It is well agreed that contraceptive use keeps fertility lowered⁸. In the case of Vietnam,

which has a CPR approaching an ideal level, or 58 over 63 provinces having modern contraceptive use rates above 60%, an effort to increase higher contraceptive use would not keep fertility lowered technically. However, the fact that some provinces with decreasing contraceptive use rates in the last decade went parallel with rising fertility rates giving out a message for a possible rise in fertility unless the level of contraceptive use is maintained.

From this point of view, resources should be effi ciently directed to all public, private and non-government FP services to catch up with growing demand of a rising number of couples, regardless their marriage status at reproductive age in the next decade.

The last determinant, migration required additional investigation as it has timing effect on fertility in cities with low fertility. Firstly, by its nature of young population, migration population in a short period of time has kept the total fertility of provinces like Ho Chi Minh and Binh Duong at a critical low level, around 1.5 children per woman in 1998. By 2008 data¹, after fi ve years, Ho Chi Minh received an amount of newly migrant women equal to 18.1% of women population at reproductive age, and this proportion was 41.4% in Binh Duong. It also means that statisticians added 1/5 to 2/5 migrant women, who were without or less children to their denomination of TFR calculation, so that total fertility rates were decreased technically. Secondly, when looking at the group of women 20-24, migration process promotes young migrant couples to have no or only one child as a temporary strategy to save time and resources. In literature, this effect is called fertility postponement and migrant couples would have more children later¹⁶. As a family with two children has been a norm of

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Vietnamese couples for a long time, it could be expected that migrant couples, after one or two decades of integration at destination would have another child or more. In this case, for some cities experiencing high infl ux of migration for decades, late births of migrant couples could be the answer for the recent rebound of fertility.

In line with Boongart model, postponement of fertility could be regarded as part of postponement of marriage determinant. In this point of view, postponement of marriage and migration could be a solution for lingering high fertility in minority populations regardless of their living locations.

At international level, Sobotka (2013) suggested that the recent rising fertility in many European countries was attributed to migration population.

In some studies on migration and fertility at household level, migrants commonly set up for themselves a postponement of childbearing to have more time and opportunities for work^16,

17. This strategy of migrants has promoted later marriage and births which foster leveraged fertility in regions received high infl ux of immigrants¹⁸. On one hand, the fi ndings in Vietnam supports this hypothesis, in other words Adaptation theory explains the mechanism of the fertility rebound in developed provinces in Vietnam. On the other hand, the study suggests that high infl ux of young migrants exacerbates the situation of critically low fertilities in many developed regions or even countries before a fertility rebound happens. In addition, although the effect of migration on the fertility of destination regions is explainable, there is a question about the effect of out-migration on fertility of origin regions.

CONCLUSION

Vietnam is experiencing a decade of plateau

fertility at the replacement level as a balancing result of declining and rebounding fertility trends. While development and its components such as poverty reduction, girl education and public health are strong determinants for driving total fertility downward, the late childbearing phenomenon of migrant couples is a chief determinant of rebounding fertility in developed areas. It should be noted that there are some provinces with lowering modern contraceptive use rates also experiencing higher fertility. In addition, the stubborn high ABRs in mountainous areas, despite of the available lasting family planning interventions is asking for more efforts to lower the fertility. In short term, the uprising effect of late childbearing of migration population would balance with fertility inhibiting effect of development to keep the national total fertility at the current replacement level. This projection of fertility is practical only when the government and other partners maintain the level of contraceptive use. In addition, the declining trend is possible unless Vietnam government has effective interventions to keep fertility of adolescent groups lowered.

For Vietnam government and other domestic, international stakeholders, there is a need to maintain or expand their FP services to young couples, regardless of their marriage status, especially for those in mountainous areas. Development interventions including girl education, poverty reduction are kept to be available in less developed, mountainous regions to create an environment conducive to later marriage and small size families. In addition, as migration is an inherent part of development process, authorities should have strong policies for promoting jobs for young population to balance and regulate the migration

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fl ows among regions as a mean of fertility control. In health aspect, FP service providers could keep in mind and have suitable approach when providing services to migrant couples who have more attention to use contraceptive for spacing purpose.

The fi ndings support the Adaptation theory on migration and it could be argued that the timing effects of migration process explain for the extreme low and later rebound of fertility in developed regions. As migration is a sophisticate process that conveys temporary and permanent, domestic and international migration, there is a need for further research on: (i) fertility and migration in Vietnam; (ii) measuring the magnitude of the effect of migration on fertility of both origin and destination areas.

ACKNOWLEDGEMENT

We would like to express great thanks to General Offi ce for Population and Family Planning – Vietnam for their funding and technical supports for the implementation and evaluation of the research. Special thanks to specialists from GOPFP, UNFPA who gave us valuable comments in the preparation of the fi nal report.

I also give thanks to those who provided time and expertise in project coordination, report review, paper preparation, including:

- MSc. Nguyen Ngoc Anh, Researcher at CPRID – Investigator, statistician

- MSc. Dinh Thai Ha, Deputy of Planning and Finance Department - GOPFP

- Mr. Nguyen Thanh Tung, Offi cer of Population and family planning Department – GOPFP

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Appendix 3. Changes in adolescent birth rate in absolute number and proportion in total fertility by provinces, 1998 - 2012

Source: Vietnam population and housing census 1999 and population and family planning surveys 2013, GSO Source: Vietnam population and family planning surveys 2003, 2013, GSO

Appendix 2. Changes in total fertility by provinces, 2002-2012 APPENDICES

Appendix 1.

No. Variables Indicator Census/survey Interval

1 Economic development Household poverty rate Household living standard survey 2 years

2 Female education Female high school enrolment rate Population and family planning survey Annually 3 Female labor participation Female labor participation rate Labor force survey Annually

4 Urbanization Urban population rate Population and family planning survey Annually

5 Contraceptive use Modern contraceptive prevalence rate Population and family planning survey Annually

6 Migration 5 year migrant population rate Population and housing census 10 years

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