| Literature DB >> 35909885 |
Rebeca Revenga Becedas1,2, Carmen Sant Fruchtman1,2, Irina Dincu3, Donald De Savigny1,2, Daniel Cobos Muñoz1,2.
Abstract
Objectives: Considering the aspiration embedded in the Sustainable Development Goals to Leave No One Behind by 2030, civil registration and vital statistics systems have an essential role in providing reliable, up-to-date information to monitor the progress. Thus, the aim of this systematic review is to compile empirical evidence on the benefits of a functioning civil registration and vital statistics system.Entities:
Keywords: birth registration/certification; civil registration; civil registration and vital statistics system; death registration/certification; divorce registration/certification; marriage registration/certification; vital statistics
Year: 2022 PMID: 35909885 PMCID: PMC9330020 DOI: 10.3389/phrs.2022.1604560
Source DB: PubMed Journal: Public Health Rev ISSN: 0301-0422
FIGURE 1Flow diagram of article selection. Addressing the evidence gap in the economic and social benefits of Civil Registration and Vital Statistics Systems: A Systematic Review, 2021. Adapted from PRISMA (Systematic review, Asia, America, Africa and Europe, 1910–2019).
Characteristics of the 18 studies included in the systematic review. Addressing the evidence gap in the economic and social benefits of Civil Registration and Vital Statistics Systems: A Systematic Review, 2021 (Systematic review, Asia, America, Africa and Europe, 1910–2019).
| References | Location | Year of data collection | Study type | Study population | CRVS output | |
|---|---|---|---|---|---|---|
| Birth Registration and Children’s Rights: A Complex Story | [ | India, Kenya, Sierra Leone, Vietnam | 2005–2012 | Mixed methods | Children in rural and urban areas | Birth certificate and/or registration |
| Birth Registration and Protection for Children of Transnational Labor Migrants in Indonesia | [ | Indonesia | 2014 | Qualitative | 22 families, and 54 adults, children aged 9–14 years in rural areas | Birth certificate and/or registration |
| Identifying the Rich: Civil Registration and State- Building in Tanzania | [ | Tanzania | 2008–2015 | Quantitative | 4,000 households | Birth certificate and/or registration |
| Does birth under-registration reduce childhood immunization? Evidence from the Dominican Republic | [ | Dominican Republic | 2007 | Quantitative | Children under 59 months of age | Birth certificate and/or registration |
| Underlying dynamics of child birth registration in Zimbabwe | [ | Zimbabwe | 2014 | Mixed methods | Children—parents/guardian in 105 households in Bindura district | Birth certificate and/or registration |
| Birth registration and child undernutrition in sub-Saharan Africa | [ | Thirty-seven sub-Saharan African countries | 2014 | Quantitative | Children under 5 years of age | Birth certificate and/or registration |
| Birth Registration and the Impact on Educational Attainment | [ | Dominican Republic | 2007 | Quantitative | Children under 5 years of age | Birth certificate and/or registration |
| Papers, please! The effect of birth registration on child labor and education in early 20th century United States | [ | United States | 1910–1930 | Quantitative | Children from 12 to 15 years old | Birth certificate and/or registration |
| Protection through Proof of Age. Birth Registration and Child Labor in Early 20th Century United States | [ | United States | 1910–1930 | Quantitative | Children from 12 to 15 years old | Birth certificate and/or registration |
| Who Says I Do: The Changing Context of Marriage and Health and Quality of Life for LGBT Older Adults | [ | United States | 2014 | Quantitative | LGBT Older Adults | Marriage certificate and/or registration |
| Associations between birth registration and early child growth and development: evidence from 31 low- and middle-income countries | [ | 31 LMICs | 2010–2014 | Quantitative | Children aged 36–59 months | Birth certificate and/or registration |
| Back to what counts: Birth and death in Indonesia. Jakarta, Indonesia | [ | Indonesia | 2015–2016 | Mixed methods | 5,552 individuals | Birth certificate and/or registration |
| 1,222 adults (95.7% female and 4.3% male) and 2,361 children (50.4% female and 49.6% male) | Death certificate and/or registration | |||||
| Marriage certificate and/or registration | ||||||
| Data for the Sustainable Development Goals: Metrics for Evaluating Civil Registration and Vital Statistics Systems Data Relevance and Production Capacity, Illustrations with Nigeria | [ | Nigeria | 2003, 2008, 2013 | Qualitative | CRVS data | Vital statistics |
| Integrated human rights and poverty eradication strategy: the case of civil registration rights in Zimbabwe | [ | Zimbabwe | 2005–2006 | Mixed methods | Individuals who were 13 years and older without any other restriction in their socio-demographic factors | Birth certificate and/or registration |
| Are well functioning civil registration and vital statistics systems associated with better health outcomes? | [ | 144 countries | 2010 | Quantitative | CRVS performance data from 144 countries | Vital statistics |
| Difference-in-Differences Analysis of the Association Between State Same-Sex Marriage Policies and Adolescent Suicide Attempts | [ | United States | 1999–2015 | Quantitative | Adolescents who participated in the Youth Risk Behavior Surveillance System in 47 states | Marriage certificate and/or registration |
| Impact of Civil Marriage Recognition for Long-Term Same-Sex Couples | [ | United States | 2013 | Quantitative | Adults who identify as members of female, male same-sex couples | Marriage certificate and/or registration |
| The work of inscription: antenatal care, birth documents, and Shan migrant women in Chiang Mai | [ | Thailand | 2010–2012 | Mixed methods | Shan migrant women from Myanmar in Chiang Mai | Birth certificate and/or registration |
Quantitative results extracted from the 18 studies included in the systematic review. Addressing the evidence gap in the economic and social benefits of Civil Registration and Vital Statistics Systems: A Systematic Review, 2021 (Systematic review, Asia, America, Africa and Europe, 1910–2019).
| Effect | Indicator (references) | Exposure | Outcome | Result control group | Measure of effect | Results as reported by authors |
|---|---|---|---|---|---|---|
| Access to civil and social rights and services | ||||||
| Child Labour Elimination | Likelihood that child reports an occupation for individuals aged 12–15 [ | Being born in a state with a child labour law but without a birth registration law | Child report an occupation |
| When born before registration law, children below the minimum age were 3.4% points less likely to work than work eligible children | |
| SE (0.008) | ||||||
|
| ||||||
| Likelihood that child reports an occupation for male individuals aged 12–15 [ | Being born in a state with a child labour law and a birth registration law | Child report an occupation |
| Male individuals below the minimum aged, were 9% points less likely to work than the work-eligible than the work-eligible, when born with a birth registration law in place | ||
| SE (0.003) | ||||||
|
| ||||||
| Likelihood that child reports an occupation for black individuals aged 12–15 [ | Being born in a state with a child labour law and a birth registration law | Child report an occupation |
| Black individuals below the minimum age were 7.8% points less likely to work than the work-eligible than the work-eligible, when born with a birth registration law in place | ||
| SE (0.003) | ||||||
|
| ||||||
| Likelihood that child reports an occupation in an urban area for individuals aged 12–15 [ | Being born in a state without a birth registration law in an urban area | Child report an occupation |
| In urban areas, under-aged children born before the registration laws were 2.8% points less likely to work | ||
| SE (0.008) | ||||||
|
| ||||||
| Likelihood that child reports an occupation in a rural area for individuals aged 12–15 [ | Being born in a state without a birth registration law in a rural area | Child report an occupation |
| In rural areas, under-aged children born before the registration laws were 1.6% points less likely to work | ||
| SE (0.007) | ||||||
|
| ||||||
| Likelihood that child reports an occupation in an agricultural county for individuals aged 12–15 [ | Being born in an agricultural county with a birth registration law | Child report an occupation |
| In agricultural counties, children below the minimum age limit were 3.6 percentage points less likely to work if they were born with birth registration laws | ||
| SE (0.010) | ||||||
| Likelihood that child reports an occupation in a non-agricultural county for individuals aged 12–15 [ | Being born in an agricultural county with a birth registration law | Child report an occupation |
| In non-agricultural counties, children below the minimum age limit were 5.9 percentage points less likely to work if they were born with birth registration laws | ||
| SE (0.007) | ||||||
|
| ||||||
| Access to protection services | Relationship correlating the access to Basic Education Assistance Module (BEAM) to birth certificate in Zimbabwe [ | Having a birth certificate | Access to BEAM |
| The expansion of BEAM and other conditional cash transfers will likely reinforce parents’ and guardians’ perception of direct material benefits of child birth registration. In fact, the study found a significant relationship ( | |
| Positive impact on economic outcomes for individuals and governments | ||||||
| Increased the amount of tax payers | Likelihood that registered citizens paid council tax in Tanzania [ | Having a birth registration | Tax outcomes |
| In one of the reform districts, registered citizens are 22.9 percentage points more likely to pay council taxes | |
| SE (0.099) | ||||||
|
| ||||||
| Increased the access to formal economic sector | Probability of having a bank account in Tanzania [ | Having a birth registration | Finance outcomes |
| Birth registration is associated with a 47.7% point increase in the probability of someone in the respondent’s household possessing a bank account | |
| SE (0.244) | ||||||
|
| ||||||
| Human capital for economic development: Increased access to education and educational attainment | ||||||
| Increased access to education | Probability of being enrolled in formal education in India [ | Having a birth certificate | Attending formal education |
| A sponsored child with birth registration is 37% more likely to be attending formal education in India | |
| SE (0.156) | ||||||
| OR = 1.890 | ||||||
|
| ||||||
| Probability of being enrolled in formal education in Kenya [ | Having a birth certificate | Attending formal education | Data not included | A sponsored child with birth registration is 50% more likely to be attending formal education in Kenya | ||
| Probability of being enrolled in formal education in Sierra Leone [ | Having a birth certificate | Attending formal education | Data not included | A sponsored child with birth registration is 60% more likely to be attending formal education in Sierra Leone | ||
| Likelihood that child attends school for individuals aged 12–15 [ | Being born in a state with a child labour law but without a birth registration law | Child school attendance |
| Under-aged children born before the registration law were 3.6 percentage points more likely to attend school than the work-eligible | ||
| SE (0.008) | ||||||
|
| ||||||
| Likelihood that child attends school for individuals aged 12–15 [ | Being born in a state with a child labour law but with a birth registration law | Child school attendance | Data not included | Those born in a state with a birth registration law were 6.5 percentage points more likely to attend school than the work-eligible | ||
| Likelihood that school-age children were enrolled in Indonesia [ | Having a birth certificate | Enrolled in school | AOR = 2.0, 95% CI = 1.6–2.5 | School-age children that were enrolled at the time of the study were twice as likely to have a birth certificate as those who were not enrolled in school | ||
| Increased educational attainment | Likelihood that children aged 11 to 18 pass the first cycle primary school in Dominic Republic [ | Lack of birth certificate | Passing the first cycle primary school | OLS | An unregistered child would have between 20 and 40-% points lower probability of passing the first cycle of primary school | |
|
| ||||||
| SE = 0.084 | ||||||
|
| ||||||
| PROBIT | ||||||
|
| ||||||
| SE (0.217) | ||||||
|
| ||||||
| Years of education in 1960 (birth cohorts: 1896–1925), OLS [ | Being born in a state with birth registration laws | Education |
| For individuals born in the United States between 1896 and 1925, the average educational attainment increased from 8.7 to 11 years | ||
| SE (0.21) | ||||||
|
| ||||||
|
| The coverage of the registration law increased from 25 to 100% for the same cohorts. Thus, a 0.09 years increase in attainment due to the birth registration laws would account for 3% of the total increase | |||||
| SE (0.31) | ||||||
|
| ||||||
| Probability of English literacy as an education outcome in Tanzania [ | Having a birth certificate | Education |
| This effect on the population of compliers, birth registration is associated with a 41-percentage point increase in the probability of English literacy | ||
| SE = 0.185 | ||||||
|
| ||||||
| Likelihood that adults attended elementary or middle school in Indonesia [ | Having a birth certificate | Attended elementary or middle school in Indonesia | AOR = 2.1, 95% CI = 1.1–3.8 | Adults that had attended elementary or middle school were twice as likely to have a birth certificate as those who had not attended school | ||
| Likelihood that adults attended high school or higher in Indonesia [ | Having a birth certificate | Attended high school or higher | AOR = 3.7, 95% CI = 1.9–7.2 | Adults that had attended high school or higher were almost four times as like to have a birth certificate than those who had not attended school | ||
| General | Likelihood that Healthy Life Expectancy (HALE), in 144 countries [ | Associated to vital statistics performance index (VSPI) | HALE |
| HALE was estimated to increase by 0.044% with each unit increase in VSPI on a 100-point scale | |
| 95% CI [1.020–1.068] | The regression indicates that if worldwide CRVS performance was high (0.9) rather than at its worldwide average based on the 144 countries or territories with available data (0.591), average HALE would increase by nearly 1 year (63.1 years vs. 62.3 years) | |||||
|
| ||||||
| Likelihood that Maternal Mortality Ratio (MMR) in 144 countries [ | Associated to vital statistics performance index (VSPI) | MMR |
| Countries with high VSPI values have low MMR. | ||
| 95% CI | ||||||
| 0.508–1.023 | ||||||
|
| ||||||
| Likelihood that child mortality risk (5q0) values, in 144 countries [ | Associated to vital statistics performance index (VSPI) | 5q0 |
| Countries with high VSPI values have low 5q0 | ||
|
| ||||||
| Improved nutrition | Values of children’s height-for-age Z-score (HAZ) in 40 cases out of 140 comparisons [ | Registered vs. not registered children | HAZ |
| Effects of selection bias due to birth registration on undernutrition prevalence | |
| 28.6% | Registered children generally presented a better nutritional status than unregistered ones, with significantly higher HAZ mean values in 40 cases out of 140 comparisons: 28.6% | |||||
| Values of children’s Weight for age Z-score (WAZ) in 51 cases of 140 comparisons [ | Registered vs. not registered children | WAZ |
| Effects of selection bias due to birth registration on undernutrition prevalence | ||
| 36.4% | Registered children generally presented a better nutritional status than unregistered ones, with significantly higher WAZ mean values in 51 cases out of 140 comparisons: 36.4% | |||||
| Values of children’s Weight-for-height Z-score (WHZ) <–2) in 38 cases of 140 comparisons [ | Registered vs. not registered children | WHZ |
| Effects of selection bias due to birth registration on undernutrition prevalence | ||
| 27.1% | Registered children generally presented a better nutritional status than unregistered ones, with significantly higher WHZ mean values in 38 cases out of 140 comparisons: 27.1% | |||||
| Likelihood that children are stunting in Uttar Pradesh, India [ | Having a birth registration | Nutrition outcomes |
| In Uttar Pradesh a child with birth registration is approximately 0.7 times less likely to be stunted | ||
| SE (0.019) | ||||||
| OR [0.670] | ||||||
|
| ||||||
| Likelihood that children are under-weight in Uttar Pradesh, India [ | Having a birth registration | Nutrition outcomes |
| In Uttar Pradesh a child with birth registration is approximately 0.8 times less likely to be under-weight | ||
| SE (0.018) | ||||||
| OR [0.781] | ||||||
|
| ||||||
| Likelihood that children are stunting in Kenya [ | Having a birth registration | Nutrition outcome |
| In Kenya a child with birth registration is approximately 0.8 times less likely to be stunted | ||
| SE (0.023) | ||||||
| OR [0.767] | ||||||
|
| ||||||
| Likelihood that children are under-weight in Kenya [ | Having a birth registration | Nutrition outcome |
| In Kenya a child with birth registration is approximately 0.7 times less likely to be under-weight | ||
| SE (0.021) | ||||||
| OR [0.658] | ||||||
|
| ||||||
| Likelihood of children’s height-for-age z-scores (HAZ) aged 36–59 months in 31 LMICs [ | Lack of birth certificate | Nutrition outcome |
| Not having a birth certificate was negatively associated with children’s HAZ | ||
| 95% CI: −0.23, −0.14 | ||||||
|
| ||||||
| Likelihood of children’s weight-for-age z-scores (WAZ) aged 36–59 months in 31 LMICs [ | Lack of birth certificate | Nutrition outcome |
| Not having a birth certificate was negatively associated with children’s WAZ | ||
| 95% CI: −0.13, −0.07 | ||||||
|
| ||||||
| Likelihood of children’s ECDI z-score aged 36–59 months in 31 LMICs [ | Lack of birth certificate | Nutrition outcome |
| Not having a birth certificate was negatively associated with children’s ECDI z-scores | ||
| 95% CI: −0.13, −0.07 | ||||||
|
| ||||||
| Better vaccination outcomes | Effect on number of vaccines for children aged 0–59 months in Dominic Republic [ | Lack of birth certificate | Immunisation |
| This estimate suggests that lacking a birth certificate is associated with a reduction of 0.7 vaccines | |
| SE (0.156) | ||||||
|
| ||||||
| Effect on vaccination outcomes in Uttar Pradesh, India [ | Having a birth registration | Immunisation | BCG | Children with birth registration in Maharashtra, India are between 1.2 and 3.8 times more likely to have been vaccinated than children without birth registration, depending on the type of vaccine (e.g., BCG, POL0, DPT1, DPT2, DPT3, Measles, POL1) | ||
| SE (0.031) | ||||||
| OR [2.127] | ||||||
| POL 0 | ||||||
| SE (0.032) | ||||||
| OR [1.898] | ||||||
| DPT1 | ||||||
| SE (0.031) | ||||||
| OR [2.092] | ||||||
| DPT2 | ||||||
| SE (0.033) | ||||||
| OR [2.012] | ||||||
| DPT3 | ||||||
| SE (0.033) | ||||||
| OR [1.815] | ||||||
| Measles | ||||||
| SE (0.033) | ||||||
| OR [2.006] | ||||||
|
| ||||||
| — | ||||||
| POL 1 | ||||||
| SE (0.016) [1.805] | ||||||
|
| ||||||
| Effect on vaccination outcomes in Kenya [ | Having a birth registration | Immunisation | BCG | Children with birth registration in Kenya are between 1.3 and 2.2 times more likely to have been vaccinated than children without birth registration, depending on the type of vaccine (e.g. BCG, POL0, DPT1, DPT2, DPT3, Measles, POL1) | ||
| SE (0.014) | ||||||
| OR [2.235] | ||||||
| POL 0 (0.019) [1.807] | ||||||
| DPT1 (0.015) [1.887] | ||||||
| POL 1 (0.015) [1.901] | ||||||
| DPT2 (0.017) [1.866] | ||||||
| POL 2 (0.017) [1.700] | ||||||
| DPT3 (0.019) [1.469] | ||||||
| POL 3 (0.020) [1.364] | ||||||
| Measles (0.020) [1.484] | ||||||
|
| ||||||
| Effect on vaccination outcomes in Sierra Leone [ | Having a birth registration | Immunisation | BCG | Children with birth registration in Sierra Leone are between 1.6 and 2.1 times more likely to have been vaccinated than children without birth registration, depending on the type of vaccine (e.g. BCG, POL0, DPT1, DPT2, DPT3, Measles, POL1) | ||
| SE (0.016) | ||||||
| OR [2.126] | ||||||
| POL0 (0.020) [1.658] | ||||||
|
| ||||||
| — | ||||||
| DPT1 (0.018) [1.845] | ||||||
| POL 1 (0.018) [1.948] | ||||||
| DPT2 (0.019) [1.767] | ||||||
| POL 2 (0.019) [1.797] | ||||||
| DPT3 (0.019) [1.711] | ||||||
| Measles (0.019) [1.589] | ||||||
|
| ||||||
| Improved mental health and quality of life | Changes in high school student (ages 15–19) suicide attempts in US. Net Change in Suicide Attempts, Percentage Points [ | After implementation of Same-Sex Marriage Policies | Suicide attempts- (Students identifying as sexual minorities) –4.0 | (All students) −0.6 | 95% CI | The reduction in suicide attempts, represents a 7% relative reduction in the proportion of high school students attempting suicide owing to same-sex marriage implementation |
| –6.9 to –1.2 | ||||||
|
| ||||||
| — | ||||||
| 95% CI | These results are equivalent to a 14% relative decline in the proportion of adolescents who were sexual minorities reporting suicide attempts in the past year | |||||
| –1.2 to –0.01 | ||||||
|
| ||||||
| Positive LGBIS identity and social support outcomes by marital status and state recognition [ | Having a marriage registration | LGB Identity centrality | 95% | The positive coefficients for marital status indicate that individuals who are in a civil marriage report significantly higher levels of LGB identity centrality | ||
| γ020 = 0.20 | CI = [0.04, 0.36] | |||||
|
| ||||||
| Positive LGBIS identity and social support outcomes by marital status and state recognition [ | Having a marriage registration | Social support from partner γ020 = 0.17 | 95% | The positive coefficients for marital status indicate that individuals who are in a civil marriage perceive their partner as more supportive | ||
| CI = [0.04, 0.30] | ||||||
|
| ||||||
| Mean/(SE) or %—general health and quality of life (QOL) characteristics by relationship status and gender, between married and unmarried partnered men in 2017, United States [ | Having a marriage registration | General Health married men | unmarried partnered men |
| Married men showed advantages over unmarried partnered men in general health -QOL | |
| 3.62/(0.10) | 3.29/(0.11) | |||||
| Mean/(SE) or %—physical health and quality of life (QOL) characteristics by relationship status and gender, between married and unmarried partnered men in 2017, United States [ | Having a marriage registration | Physical Health married men | unmarried partnered men |
| Married men showed advantages over unmarried partnered men in physical health -QOL | |
| 77.05/(1.39) | 69.58/(2.45) | |||||
| Mean/(SE) or %—environmental health and quality of life (QOL) characteristics by relationship status and gender between married and unmarried partnered men in 2017, United States [ | Having a marriage registration | Environmental Health married men | Unmarried partnered men |
| Married men showed advantages over unmarried partnered men in environmental health -QOL | |
| 82.51/(1.39) | 75.72/(1.45) | |||||
| Mean/(SE) or %—general health characteristics by relationship status and gender—quality of life (QOL) between married and single women in 2017, United States [ | Having a marriage registration | General Health married women | Single women |
| Married women showed advantages over single women in general health -QOL | |
| 3.64/(0.10) | 2.88/(010) | |||||
| Mean/(SE) or %—psychological health -quality of life (QOL) characteristics by relationship status and gender between married and single women in 2017, United States [ | Having a marriage registration | Psychological | Single women |
| Among women, those who were legally married had better general health, lower rates of disability, and better QOL across all domains compared with those who were single | |
| Health married women | 62.22 (2.05) | |||||
| 71.64 (1.42) | ||||||
| Mean/(SE) or %—social health and quality of life (QOL) characteristics by relationship status and gender between married and unmarried women in 2017, United States [ | Having a marriage registration | Social | Unmarried women |
| Married women only had greater social QOL than those unmarried partnered | |
| Health married women | 63.39 (2.49) | |||||
| 72.85 (1.87) | ||||||
FIGURE 2Table Chart of the benefits of CRVS systems per vital event. Addressing the evidence gap in the economic and social benefits of Civil Registration and Vital Statistics Systems: A Systematic Review, 2021 (Systematic review, Asia, America, Africa and Europe, 1910–2019).