Indian Journal of Health Sciences and Biomedical Research KLEU

: 2023  |  Volume : 16  |  Issue : 1  |  Page : 142--146

Age at marriage and first birth interval: A systematic review and meta-analysis

Anushri Pradip Patil, Naresh K Tyagi, Jang Bahadur Prasad 
 Department of Biostatistics and Epidemiology, KLE Academy of Higher Education and Research, Belagavi, Karnataka, India

Correspondence Address:
Ms. Anushri Pradip Patil
Department of Biostatistics and Epidemiology, KLE Academy of Higher Education and Research, Belagavi - 590 010, Karnataka


BACKGROUND: Age at marriage is one of the proximate determinants of fertility. Women with early age at marriage experiences early motherhood, associated with high fertility, low education, and rural residence accompanied with poverty. In the present study, an attempt has been made to evaluate age at marriage and factors affecting it and its effect on first birth interval (FBI) using systematic review and meta-analysis. METHODOLOGY: Inclusion criteria were availability of full- and free-text articles, published in English language, and current married age of mother being 13 years and above. PubMed and Google search was used for systematic review for the study. Meta-analysis was carried out using Microsoft Excel 2013. RESULTS: Pooled-weighted average age at marriage was 19.96 years (with 4.26 standard error). The age at marriage in China was highest (21.56 years). Literacy and occupation of women had significant effect on age at marriage. Urbanization could not affect significantly on age at marriage. Furthermore, FBI has been modified by age at marriage.

How to cite this article:
Patil AP, Tyagi NK, Prasad JB. Age at marriage and first birth interval: A systematic review and meta-analysis.Indian J Health Sci Biomed Res 2023;16:142-146

How to cite this URL:
Patil AP, Tyagi NK, Prasad JB. Age at marriage and first birth interval: A systematic review and meta-analysis. Indian J Health Sci Biomed Res [serial online] 2023 [cited 2023 Mar 27 ];16:142-146
Available from:

Full Text


Age at first marriage is one of the proximate determinants of fertility. The women with early age at marriage experiences early motherhood, associated with high fertility, low education, and rural residence accompanied with poverty.[1],[2],[3]

In a multicentre study conducted in 40 developing countries, it was observed that lower age at marriage (14.1 years) was associated with higher nuptiality (Longer FBI). Amongst the countries studied, Poverty was an additional influencing factor in case of Bangladesh.[4] The early age at marriage in Uttar Pradesh in 1988 was associated with median first birth interval (FBI) of 36.61 months and Assam of 24.87 months. Furthermore, lower age at marriage was observed having positive association with lower income, subcaste, and rural place of residence.[5]

Age at marriage, level of women's education, and menstrual irregularities had significant effect on birth interval after marriage.[6] Among explanatory variables of age at marriage, mother's education and occupation were significant. Furthermore, age at marriage affected FBI significantly. Out of the total study subjects, 59.9% were with two children, 16% with 3, and 10.7% with 4 or above.[7]

The Prentice-Williams-Peterson gap time (PWP-GT) conditional model revealed that, age at marriage had effect on child birth (with HR=0.69, P = 0.001) at first delivery. Also tells that, as educational level increases from secondary (with HR=0.85, P = 0.359) to academic (with HR=0.74, P = 0.183), the child birth decreased, at first delivery. And for the occupational status of a women, the childbirth ratio of employed mothers was less than the unemployed mothers (with HR=0.685, P = 0.005).[8]

Study from China (1996) estimated a median age at marriage is 18 years in 1950 with corresponding median FBI of 21 months, whereas the median age at marriage in 1985 increased to 21.7 years with FBI of 12 months, indicating inverse relationship of age at marriage and FBI.[9] Similar finding was observed from Taiwan study, indicating increase in age at marriage in the years 1970–1985; from 20 to 22 years with corresponding FBI from 27 to 16 months.[10]

Study from Iran (2015) reported a mean age at marriage of 19.5 years with a FBI of 15.4 ± 0.2 months. Furthermore, FBI was also associated with level of education and occupation of women. Women, who studied just till high schools, had FBI of 13.6 months, in higher educated women group, FBI was 25 months. In employed and working women, FBI was 17.7 compared to 15.2 months in nonworking women. The ratio of unwanted pregnancies was 5:1 in unemployed women compared to a working woman.[11]

In a study from Iran (2017) the high parity progression ratio at 5 years after marriage was 0.918, exhibiting significant effect of nonworking status of women (hazard ratio [HR] = 0.68, standard error [SE] = 0.03). The similar relationship was observed with maternal age at marriage (in 18 years and above maternal age at first pregnancy; HR = 0.93 with SE = 0.10).[8]

Study from Bangladesh (2013) observed a significant association of early age at marriage (15.5 years or less) with place of residence, religion, region, wealth index, education, and occupation using multivariate logistic regression analysis.[2]

Hence, in the present systematic review study, an attempt has been made to study the variations in age at marriage by year of a study, region, along with its determinants as place of residence, education, occupation, and effect of age at marriage on FBI.


Literature search for the present study was made with verb “age at marriage and interval from marriage to first birth (FBI).” The full-free text articles with English language and current postmarried age 13 years and above in PubMed and Google Search Engine were considered for the study.[12],[13],[14],[15],[16],[17],[18],[19],[20],[21],[22],[23],[24],[25],[26],[27],[28],[29],[30],[31],[32],[33],[34],[35],[36],[37],[38],[39],[40],[41],[42],[43],[44],[45],[46],[47],[48],[49],[50] The flowchart of the research material used in the study is:

For meta-analysis, the pooled estimates of mean and standard deviation (SD) were computed as:



between variation, i.e., η2 was calculated as:


Within-study variation was calculated as:


To study publication bias, regional variations, or cultural variations, the funnel plot has been constructed using Microsoft Excel by plotting absolute Z-transformation against estimate values. Forest plot giving place and year of the study has been constructed to understand the variation by geographical regions and time of studies carried out. Appropriate statistical models have been used to study variations by explanatory variates. The effect of explanatory variates has been studied using analysis of variance. In Meta Analysis, all articles were published with Ethical Clearance. Hence, no further Ethical Clearance is necessary.


Funnel plot for age at marriage [Figure 1] reveals the study publication bias, regional variations, and by year of study variations in the estimates; 11 studies could meet the inclusion criteria. Two studies, one from China conducted in 2000, and one from south India carried out in 1986, had the highest and lowest age at marriage, but they were within 1.96 of SE, hence considered for the study. Out of total 11 studies, seven exhibited in the center of the funnel plot can be considered as best. The variations in the mean age at marriage were not statistically significant at P > 0.2.{Figure 1}

Forest plot of average age at marriage [Figure 2] reveals the variation in age at marriage by year of the study, and no trend by time or place of study could be seen. The pooled mean age at marriage was 19.96 years with SD 4.27, the variations in the age at marriage were not statistically significant (P > 0.2, Wilks Lambda = 0.86).{Figure 2}

As shown in [Figure 3], age at marriage and education reveal that literacy of women had significant effect on age at marriage (P < 0.001), following third-degree polynomial, explaining 85% of variation in mean age at marriage. In literacy group, <60% age at marriage was 17.8 years ± 4.7, which increased to 20.9 ± 4.2 in education group ≥70% [Table 1]a.{Figure 3}{Table 1}

As shown in [Figure 4], age at marriage and occupational status of women reveal that nonworking women had significant effect on age at marriage (P < 0.001), following second-degree polynomial, explaining 76% of variation in mean age at marriage. In nonworking group, <70% age at marriage was 19.1 years ± 3.9, which increased to 19.4 ± 4 in nonworking group ≥70% [Table 1]b.{Figure 4}

As shown in [Figure 5], age at marriage and urban place of residence of women reveal that the place of residency (percent urban) had significant effect on age at marriage (P < 0.001). In urban residence group, <35% age at marriage was 19.3 years ± 4.2 age at marriage, which decreased up to 17.9 years ± 4.3 age at marriage in ≥35% urban residence [Table 1]c.{Figure 5}

As shown in [Figure 6], FBI and age at marriage reveal that the age at marriage had impact on FBI. Out of 11 studies, seven studies had the information on FBI. FBI followed second-degree polynomial, explaining 60% of variation (R2 = 0.60). Furthermore, in marriage <20 years age at marriage, FBI fluctuated between 1.8 and 2.5 years; thereafter FBI decreased to 1.67 years in ≥20 years age at marriage [Table 2].{Figure 6}{Table 2}

From [Table 2], FBI by age at marriage revealed that in <20 years age at marriage group, the mean FBI was 1.97 years (range: 1.765, 2.5) whereas, in 20 and >20 years age at marriage, the mean FBI was 1.58 years (range: 1.67, 2).


The weighted mean of age at marriage computed from 11 studies was 19.96 years, whereas the study from China, 2000 had the highest age at marriage (21.56) and lowest in south India, 1986 (15.2 years). The reasons of high age at marriage in China might be their population policy accompanied with low fertility and higher education levels, though the south Indian study is very old (1986). Literacy of women had significant effect on increasing age at marriage, as exhibited by the studies in the increasing order Malay, Chinese, and India, 2016 to China, 2000 with corresponding education levels 50.16%–84.45% accompanied with mean age at marriage of 17.55 and 21.56 years. Occupation level of women had significant effect on age at marriage, as age at marriage decreased from 19.3 years (Northwest Ethiopia, 2014) to 18.09 years (Iran, 2013), with increasing percentage of nonworking women from 65.1% to 95.5%. Furthermore, no relationship was observed between place of residency of women and age at marriage. As a consequence of age at marriage, FBI decreased with increasing age at marriage, as was evident from Northwest Ethiopia, 2014 and Rajasthan and Kerala, 2016 with 17.55 and 19.3 years age at marriage, respectively.


FBI varied significantly with respect to Age at Marriage, Educational Level of women and Occupational status of women. Furthermore, FBI was affected by age at marriage. Hence, area-specific planning for parenthood needs to be emphasized in population policies.


In the present study, women characteristics were studied as determinants of age at marriage, whereas spouse attributes may also affect age at marriage. Paid and abstract-only articles from PubMed and Google Scholar were not considered for meta-analysis. This can potentially alter the results of the study. Further meta-analysis is needed using these paid full-text articles to draw more valid conclusions.

Financial support and sponsorship


Conflicts of interest

There are no conflicts of interest.


1Bongaarts J. The proximate determinants of fertility. Technol Soc 1987;9:243-60.
2Nahar MZ, Zahangir MS, Islam SM. Age at first marriage and its relation to fertility in Bangladesh. Chin J Popul Resour Environ 2013;11:227-35.
3Islam MN, Islam MM. Biological and behavioural determinants of fertility in Bangladesh: 1975-1989. Asia Pac Popul J 1993;8:3-18.
4Singh S, Samara R. Early marriage among women in developing countries. Int Fam Plann Perspect 1996;22:148-57.
5Age of Marriage and Length of the First Birth Interval in a Traditional Indian Society: Life Table and Hazards Model Analysis. Available from: [Last acessed on 2020 Nov 05].
6Shayan Z, Ayatollahi SM, Zare N, Moradi F. Prognostic factors of first birth interval using the parametric survival models. Iran J Reprod Med 2014;12:125-30.
7Fallahzadeh H, Farajpour Z, Emam Z. Duration and determinants of birth interval in Yazd, Iran: A population study. Iran J Reprod Med 2013;11:379-84.
8Najafi-Vosough R, Soltanian AR, Fayyazi N. Influence factors on birth spacing and childbearing rates using survival recurrent events model and parity progression ratios. J Res Health Sci 2017;17:e00384.
9Feng W, Quanhe Y. Age at marriage and the first birth interval: The emerging change in sexual behavior among young couples in China. Popul Dev Rev 1996;22:299.
10Barrett RE. Short-term trends in bastardy in Taiwan. J Fam Hist 1980;5:293-312.
11Ranjbar F, Shirzad M, Kamali K, Akhondi MM, Ghoodjani A, Behjati Ardakani Z, et al. Fertility behaviour of Iranian women: A community-based, cross-sectional study. Arch Iran Med 2015;18:2-5.
12Ford K. Socioeconomic differentials and trends in the timing of births. Vital Health Stat 23 1981;23:1-49.
13Retherford R, Ogawa N, Matsukura R, Eini-Zinab H. Multivariate analysis of parity progression-based measures of the total fertility rate and its components. Demography 2010;47:97-124.
14Mandelson MT, Maden CB, Daling JR. Low birth weight in relation to multiple induced abortions. Am J Public Health 1992;82:391-4.
15Caltabiano M, Castiglioni M. Changing family formation in Nepal: Marriage, cohabitation and first sexual intercourse. Int Fam Plan Perspect 2008;34:30-9.
16Kunnuji MO, Eshiet I, Nnorom CC. A survival analysis of the timing of onset of childbearing among young females in Nigeria: Are predictors the same across regions. Reproductive Health 2018;15:173. [doi: 10.1186/s12978-018-0623-3].
17Nandi A, Behrman JR, Black MM, Kinra S, Laxminarayan R. Relationship between early-life nutrition and ages at menarche and first pregnancy, and childbirth rates of young adults: Evidence from APCAPS in India. Matern Child Nutr 2020;16:e12854.
18Afulani PA, Altman M, Musana J, Sudhinaraset M. Conceptualizing pathways linking women's empowerment and prematurity in developing countries. BMC Pregnancy Childbirth 2017;17:338.
19Zaba B, Pisani E, Slaymaker E, Boerma JT. Age at first sex: Understanding recent trends in African demographic surveys. Sex Transm Infect 2004;80 Suppl 2:i28-35.
20Finer LB, Philbin JM. Trends in ages at key reproductive transitions in the United States, 1951-2010. Womens Health Issues 2014;24:e271-9.
21Pratap M, Kumar A, Yadava RC. Pattern of first birth interval: Evidences from NFHS data. Int J Current Res 2011;3:154-9.
22Saleem S, Isa MA. Facilitating inter-spousal communication for birth spacing – A feasibility study of Pakistani couples for policy implications. J Pak Med Assoc 2004;54:182-6.
23Reproductive Characteristics and the Risk of Breast Cancer – A Case-Control Study in Iran,Request PDF. Available from: [Last accessed on 2021 Oct 03].
24Dhillon PK, Yeole BB, Dikshit R, Kurkure AP, Bray F. Trends in breast, ovarian and cervical cancer incidence in Mumbai, India over a 30-year period, 1976-2005: An age-period-cohort analysis. Br J Cancer 2011;105:723-30.
25Khuder SA, Mutgi AB. Reproductive factors are crucial in the aetiology of breast cancer – A reply. Br J Cancer 2000;83:134. [doi: 10.1054/bjoc. 2000.1312]. Available from: https://sci org/10.1054%2Fbjoc. 2000.1312. [Last accessed on 2021 Oct 03].
26Retherford RD, Eini-Zinab H, Choe MK, Ogawa N, Matsukura R. Multidimensional life table estimation of the total fertility rate and its components. Demography 2013;50:1387-95.
27Leve LD, Neiderhiser JM, Ge X, Scaramella LV, Conger RD, Reid JB, et al. The early growth and development study: A prospective adoption design. Twin Res Hum Genet 2007;10:84-95.
28Adedini SA, Odimegwu C, Imasiku EN, Ononokpono DN. Ethnic differentials in under-five mortality in Nigeria. Ethn Health 2015;20:145-62.
29(PDF) Risk Factors for Cancer Cervix among Rural Women of a Hilly State: A Case-Control Study. Available from: HTTPS://WWW.RESEARCHGATE.NET/PUBLICATION/273470081_RISK_FACTORS_FOR_CANCER_CERVIX_AMONG_RURAL_WOMEN_OF_A_HILLY_STATE_A_CASE-CONTROL_STUDY. [Last accessed on 2021 Oct 03].
30The Association between Pre-Pregnancy Parental Support and Control and Adolescent Girls' Pregnancy Resolution Decisions,Elsevier Enhanced Reader. Available from: https://Reader.Elsevier.Com/Reader/Sd/Pii/S1054139X13002553?Token=A88cbf2ae8ae11d3b9b6adb0f3ead00128c1f4e99ba3fe0a90192f54c135dcbb902bfb75688c9 d6cf59e38caa19ad4e5&Originregion=Eu-West-1&Origincreation=20211001112458. [Last accessed on 2021 Oct 01].
31Mccutcheon VV, Kramer JR, Edenberg HJ, Nurnberger JI, Kuperman S, Schuckit MA, et al. Social contexts of remission from DSM-5 alcohol use disorder in a high-risk sample. Alcohol Clin Exp Res 2014;38:2015-23.
32Störmer C, Lummaa V. Increased mortality exposure within the family rather than individual mortality experiences triggers faster life-history strategies in historic human populations. PLoS One 2014;9:e83633.
33Ayele BG, Gebregzabher TG, Hailu TT, Assefa BA. Determinants of teenage pregnancy in Degua Tembien District, Tigray, Northern Ethiopia: A community-based case-control study. PLoS One 2018;13:e0200898.
34Neogi SB, Singh S, Pallepogula DR, Pant H, Kolli SR, Bharti P, et al. Risk factors for orofacial clefts in India: A case-control study. Birth Defects Res 2017;109:1284-91.
35Corcoran C, Perrin M, Harlap S, Deutsch L, Fennig S, Manor O, et al. Effect of socioeconomic status and parents' education at birth on risk of schizophrenia in offspring. Soc Psychiatry Psychiatr Epidemiol 2009;44:265-71.
36Moore E, Blatt K, Chen A, Van Hook J, DeFranco EA. Factors associated with smoking cessation in pregnancy. Am J Perinatol 2016;33:560-8.
37Pedersen JK, Elo IT, Schupf N, Perls TT, Stallard E, Yashin AI, et al. The survival of spouses marrying into longevity-enriched families. J Gerontol A Biol Sci Med Sci 2017;72:109-14.
38Markos Shifti DI, Chojenta C, Holliday EG, Loxton D. Individual and community level determinants of short birth interval in Ethiopia: A multilevel analysis. PLoS One 2020;15:e0227798.
39Strama A, Heimrath J, Dudek K. A comparative analysis of selected demographic parameters for evaluating parity of women in Poland, Spain, England and Wales for the Period 1996-2011. Adv Clin Exp Med 2016;25:551-60.
40Tai-Hun K. Age at first marriage and birth intervals in Korea. Bulletin of the Population Develop Stud Cent 1982;11:1-14. Available from: [Published on 1982 Dec 01].
41Gurmu E, Etana D. Age at first marriage and first birth interval in Ethiopia: Analysis of the roles of social and demographic factors. Afr Popul Stud 2014;28:3. [doi: 10.11564/28-3-625].
42Bloom DE, Reddy PH. Age patterns of women at marriage, cohabitation, and first birth in India. Demography 1986;23:509-23.
43Association between Manganese Exposure through Drinking Water and Infant Mortality in Bangladesh on JSTOR. Available from: [Last accessed on 2021 Oct 07].
44Jena AB, Goldman DP, Joyce G. Association between the birth of twins and parental divorce. Obstet Gynecol 2011;117:892-7.
45Karkee R, Lee AH. Birth spacing of pregnant women in Nepal: A community-based study. Front Public Health 2016;4:205.
46Löfstedt P, Ghilagaber G, Shusheng L, Johansson A. Changes in marriage age and first birth interval in Huaning County, Yunnan Province, PR China. Southeast Asian J Trop Med Public Health 2005;36:1329-38.
47Basu AM. Cultural influences on the timing of first births in India: Large differences that add up to little difference*. Popul Stud 1993;47:85-95.
48Chernet AG, Shebeshi DS, Banbeta A. Determinant of time-to-first birth interval after marriage among Ethiopian women. BMC Womens Health 2019;19:157.
49Singh R, Tripathi V, Kalaivani M, Singh K, Dwivedi SN. Determinants of birth intervals in Tamil Nadu in India: Developing Cox hazard models with validations and predictions. Revista Colombiana de Estadística Número especial en Bioestadística Junio 2012;35:289 a 307.
50Abeje G, Azage M, Setegn T. Factors associated with Institutional delivery service utilization among mothers in Bahir Dar City administration, Amhara region: A community based cross sectional study. Reprod Health 2014;11:22.