Research | Volume 40, Article 179, 24 Nov 2021 | 10.11604/pamj.2021.40.179.30328

Paternal characteristics associated with low birth weight among singleton births: a hospital-based birth cohort study in northern Tanzania

Romani Roman Sabas, Noreen Nickson Nyange, Andrea Malimi Mayala, Michael Johnson Mahande, Caroline Amour, Innocent Baltazar Mboya

Corresponding author: Romani Roman Sabas, Department of Community Health, Institute of Public Health, Kilimanjaro Christian Medical University College, Moshi,Tanzania

Received: 13 Jun 2021 - Accepted: 17 Aug 2021 - Published: 24 Nov 2021

Domain: Obstetrics and gynecology

Keywords: Paternal age, paternal education, paternal occupation, maternal characteristics, Tanzania

©Romani Roman Sabas et al. Pan African Medical Journal (ISSN: 1937-8688). This is an Open Access article distributed under the terms of the Creative Commons Attribution International 4.0 License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Cite this article: Romani Roman Sabas et al. Paternal characteristics associated with low birth weight among singleton births: a hospital-based birth cohort study in northern Tanzania. Pan African Medical Journal. 2021;40:179. [doi: 10.11604/pamj.2021.40.179.30328]

Available online at: https://www.panafrican-med-journal.com/content/article/40/179/full

Home | Volume 40 | Article number 179

Research

Paternal characteristics associated with low birth weight among singleton births: a hospital-based birth cohort study in northern Tanzania

Paternal characteristics associated with low birth weight among singleton births: a hospital-based birth cohort study in northern Tanzania

Romani Roman Sabas1,&, Noreen Nickson Nyange1, Andrea Malimi Mayala1, Michael Johnson Mahande2, Caroline Amour2, Innocent Baltazar Mboya1, 2, 3

 

1Community Health Department, Institute of Public Health, Kilimanjaro Christian Medical University College, Moshi,Tanzania, 2Department of Epidemiology and Biostatistics, Institute of Public Health, Kilimanjaro Christian Medical University College, Moshi, Tanzania, 3School of Mathematics, Statistics and Computer Science, University of KwaZulu-Natal, Pietermaritzburg, South Africa

 

 

&Corresponding author
Romani Roman Sabas, Department of Community Health, Institute of Public Health, Kilimanjaro Christian Medical University College, Moshi,Tanzania

 

 

Abstract

Introduction: low birth weight (LBW) remains a devastating adverse pregnancy outcome in low and middle income countries (LMICs). There is evidence showing that maternal demographic and pregnancy-related characteristics are associated with LBW. Little attention is given to paternal characteristics, which may be associated with a higher risk of LBW. This study aimed to assess the effect of paternal characteristics on LBW among singleton deliveries at Kilimanjaro Christian Medical Centre (KCMC) zonal referral hospital in Kilimanjaro region, northern Tanzania.

 

Methods: this was a secondary analysis of a hospital-based cohort study from maternally-linked medical birth registry data at KCMC between 2000 and 2018. A total of 47,035 singleton deliveries were included in this study. Data analysis was performed using statistical package for social sciences (SPSS), version 20 (IBM Corp., Armonk, NY). Relative risk and corresponding 95% confidence intervals (CI) were used to determine association between LBW and paternal characteristics using log-binomial regression models, with robust standard errors to account for clustering of deliveries within mothers.

 

Results: the proportion of LBW during the study period was 9.6%. After adjusting for maternal characteristics, higher risk of LBW was among fathers with low education level (RR=1.72, 95% CI: 1.22, 2.41, p=0.002), aged ≤24 years old (RR=1.37, 95% CI: 1.21, 1.55), and those unemployed (RR= 1.11, 95% CI: 1.01, 1.21). Lower risk of LBW was among fathers aged ≥40 years (RR=0.97, 95% CI: 0.88, 1.08), but this association was not statistically significant.

 

Conclusion: the study confirmed paternal young age (≤24 years old), paternal low education level and unemployment as predictors for LBW . Current evidence on the effect of paternal characteristics on LBW might suggest that programs and policies should target their engagement as a key strategy for improving birth outcomes during the perinatal period. Future studies should assess how paternal factors are associated with the risk of adverse birth outcomes.

 

 

Introduction    Down

Low birth weight (LBW) remains to be devastating adverse pregnancy outcomes in low- and middle-income countries (LMICs) [1]. According to the World Health Organization (WHO) study of 2019 on the global burden of diseases, LBW and other perinatal causes are a leading cause of death and disability among children below five years of age [2]. More than 20 million infants worldwide, representing 15.5% of all births are born with LBW [3]. Of the 20 million LBW babies more than half were born in Asia while Africa was home to about one-quarter of all LBW newborns, with the majority born in Eastern and Western Africa [3]. The prevalence of LBW in Tanzania has dramatically reduced from 14% in 1991-1992 to 7.1% in 2010 and 7.0% in 2015-16 [4]. Low birth weight is associated with a higher risk of morbidity, mortality and long-term life health consequences including a higher risk of stunted growth, lower IQ, and adult-onset chronic conditions such as obesity and diabetes [2]. Low birth weight is attributed to multiple economic, maternal, psychosocial, and health behavior factors and represents a large burden for women, families, communities, and health-care providers [5]. Maternal characteristics such as advanced maternal age [6,7] preeclampsia, obesity, smoking during pregnancy, anemia [7,8] and previous history of LBW [7]. HIV positive status of the mother [9] maternal deprived socio-economic conditions [10] and maternal infections such as malaria and syphilis are known factors that increase the risk of LBW. Studies in the developed countries have shown that paternal characteristics such as advanced paternal age [11,12] low education level [12] unemployment [10,13] preconception smoking [8] genetic characteristics [12,14,15] depression, low social support to women [16] and exposure to environmental substances such as pesticides/ herbicides/ professional paints [17] are associated with LBW. The role of paternal characteristics in determining the risk of LBW in LMICs has received less attention than maternal factors.

 

Paternal and maternal unemployment has been associated with LBW in Nigeria [10] while higher paternal age (>45) andlow paternal education level has been associated with the risk of LBW in Tanzania and Pakistan [13,18,19]. Most of these studies, however, are limited to a single risk factor, and have inadequate control for the effects of maternal characteristics [10,19]. Until now, preconception health counseling which has been shown to improve maternal health status and in some cases, have been demonstrated to be effective in limiting the incidence of adverse pregnancy outcomes such as LBW has mainly targeted women [17]. Prospective fathers should also be a target in preconception interventions [20]. Despite efforts to promote male involvement in maternal and child health services in Tanzania, the proportion of male participation at antenatal care (ANC) services is still low (30%) [21,22]. Partner support during antenatal care visits is an important and potentially modifiable intervention to improve pregnancy outcomes. Using data from a maternally linked birth cohort data, we aimed to assess the effect of paternal characteristics on LBW among singleton births at KCMC zonal referral hospital in Kilimanjaro region, northern Tanzania. Findings from this study may provide essential information on the influence of paternal characteristics on LBW. The study will provide evidence for the need of programs and policies to target male engagement in pregnancy. The objective of this study is to determine the association between paternal characteristics and LBW among singleton births at KCMC zonal referral hospital, northern Tanzania. Our specific aims were to; 1) determine the proportion of LBW by paternal characteristics among singleton deliveries at KCMC referral hospital, northern Tanzania, year 2000-2018; and 2) determine paternal characteristics associated with low birth weight among singleton deliveries within the same study period. We hypothesized that paternal characteristics are not associated with LBW among singleton deliveries at KCMC referral hospital, Kilimanjaro region, northern Tanzania (Null hypothesis, H0). We also hypothesized that paternal characteristics are associated with LBW among singleton deliveries at KCMC referral hospital, Kilimanjaro region, northern Tanzania and childcare as a key strategy for improving birth outcomes during the perinatal period. (Alternative hypothesis, H1).

 

 

Methods Up    Down

Study design, setting, and population: we conducted a retrospective cohort study utilizing data from the birth registry at KCMC referral hospital, situated in the Moshi Municipality of Kilimanjaro region, Northern Tanzania. KCMC is one of the four zonal referral hospitals in Tanzania, and serves over 15 million people, including women from the local communities (who may come to deliver on their own accord) and referred cases from neighboring regions. An average of 4000 births occur at KCMC each year [23].The study population was 65,482 deliveries recorded at KCMC medical birth registry from 2000 to 2018. We included 47,035 deliveries with complete records between 2000 and 2018. We excluded women with multiple deliveries (N=3461), those with missing data on both the outcomes and explanatory variables (1578), as well as births from women referred for delivery (13408). We also excluded women with medical conditions during pregnancy such as diabetes (107), hypertension (124), anemia (676), as well as those who experienced obstetric complications such as preeclampsia/eclampsia (1709), abruption placenta and placenta previa to avoid over-representation of high-risk pregnancies [7,24]. We therefore, analyzed data for 47,035 deliveries (Figure 1).

 

Data source and collection methods: the data collection methods for the KCMC medical birth registry are well described elsewhere [23,25]. In brief, data are collected about the mother and father: education, occupation and living conditions, mother's health before and during present pregnancy, expected date of delivery, smoking and drinking (alcohol) habits, use of drugs, plus HIV and syphilis status (if known). This is followed by particulars on the delivery whereby a trained midwives collect data using a standardized questionnaire (within 24 hours after delivery or later if a mother had recovered from complications). Additional data are also abstracted from the antenatal care (ANC) cards and the mother's hospital medical records. Unique identification numbers are used to identify and link women with their subsequent deliveries in the obstetrics and gynecology department at KCMC hospital. The collected data are later entered into a computerized database system at the medical birth registry located in the hospital premise´s reproductive health unit [7,18,26].

 

Study variables: the dependent variable in this study was LBW. LBW was defined as a birth weight of less than 2500g regardless of gestational age, [2,7] and was categorized into a binary variable as normal (weight at birth of ≥2500 grams) and LBW (weight at birth of <2500 grams). The primary independent/exposure variables in this study were paternal characteristics, including age in complete years at the time of childbirth (15-19, 20-24, 25-34, 35-39 and 40+ years). We used the 25-34 years group as the reference category because this is the most common age range for having children among fathers in this setting and the one showing the lowest prevalence of LBW [4,11]. Other paternal background characteristics include the area of residence (rural and urban), level of education (none, primary and secondary/higher), and occupation (unemployed and employed). We considered maternal characteristics as potential confounders; hence they were adjusted in the analysis. These included maternal age, education, occupation and the area of residence categorized in similar manner as paternal characteristics, number of antenatal care visits (<4, ≥4), marital status (married, not married).

 

Statistical Analysis: we performed data cleaning and analysis using the Statistical Package for Social Sciences (SPSS version 20) [27]. Numeric variables were summarized using mean/median and corresponding measures of dispersion, i.e standard deviation/ interquartile range. Categorical variables were summarized using frequency or proportions from the total. Relative risk (RR) and the corresponding 95% confidence intervals (CI) was used to determine the association between LBW and paternal characteristicusing log-binomial regression model, with robust standard errors adjusted for clustering of observations within mothers. The multivariable regression model was adjusted for maternal characteristics. Variables with a p-value of <0.05 were consids ered significantly associated with LBW.

 

 

Results Up    Down

Social Demographics of the participants: the mean paternal age among 47,035 deliveries in this study was 33 (SD=7.0) years. Majority (54%) were aged between 25-34 years. More than half (60%) had secondary or higher education level, two-third (71%) were unemployed. The majority (55%) of the mothers were aged between 25-34 years, with their mean age of 28 (SD=6.0) years. In all, 86.3% were married and 50.1% had secondary/higher education, 76% were unemployed, and 34% were residing in rural areas with only 55% attended more than 4 ANC visits (Table 1).

 

The Proportion of LBW by paternal characteristics among singleton deliveries: the overall proportion of LBW among singleton deliveries in this cohort was 9.6%. There was a significant association between LBW and paternal age, education level and occupation. The proportion of LBW was high (13%) among fathers aged less than 24 years, compared to fathers aged 25-34 (9.1%). LBW was also higher among fathers with no or primary education (16.3%), and those unemployed (10.4%) (Table 1).

 

Paternal characteristics associated with: there was a significant association between LBW and paternal age, education level, and occupation in the unadjusted/crude analysis. The risk of LBW was high among fathers aged ≤24 years old (RR=1.44, 95%CI 1.29, 1.60), and ≥40 years (RR=1.15, 95%CI 1.06-1.25) compared to those aged 25-34, with low education (RR=2.15, 95%CI 1.54-2.90), the unemployed (RR=1.40, 95%CI 1.30, 1.50) (Table 2). However, in the adjusted analysis (adjusted for maternal characteristics), the risk of LBW continued to be relatively higher among fathers with low education level (RR=1.72, 95%CI 1.22, 2.41, p=0.002), aged ≤24 years old (RR=1.37, 95%CI 1.21, 1.55), and those unemployed (RR=1.10, 95%CI 1.01, 1.19). There was lower risk of LBW among fathers aged ≥40 years (RR=0.97, 95%CI 0.88, 1.08), but this association was not statistically significant (Table 2).

 

 

Discussion Up    Down

The study aimed to determine the association between paternal background characteristics and LBW among singleton deliveries at KCMC referral hospital, northern Tanzania. The proportion of LBW in all recorded deliveries from 2000-2018 was 9.6%. Independent of maternal characteristics, low paternal education, unemployed, and low paternal age (≤24 years) increased the risk of LBW. The proportion of LBW in this study is higher than the national estimate (7%) [4]. The fact that the national estimate comes from the Tanzania Demographic and Health Survey, which is population-based, compared to this study that uses data from a tertiary care hospital, might explain these differences. Our findings are somehow consistent to most of the hospital-based studies in sub-Saharan Africa (9.47%) [28] with prevalence ranging from 8.9% in eastern Africa to 10.3% in southern Africa, and the lowest prevalence reported 6.3% in Guinea, 7.3% Nigeria among the western African countries [10,28]. The estimate in this study is lower than 16%, globally [2] which might be due to the differences in the study population, sample size and the social-economic status across the study populations. It is worth noting that LBW proportions might be higher than the reported because the data on LBW remains limited to the most developing countries, including Tanzania, whereas half of deliveries occur at home [3,29]. There was an association between low paternal education level and unemployment with a high risk of LBW, similar to other studies [12]. The association between low paternal education level may be explained by the low level of awareness on the available health services and decrease accessibility and utilization of available health information and technology as a consequence of low education [13,15]. Higher paternal education level could improve their social-economic status, increase their level of awareness on maternal health-related issues and subsequently lower the risks of LBW [10]. Hence, obtaining information on paternal education levels may improve our ability to identify groups at highest risk for LBW. This may allow the development and implementation of the targeted interventions to reduce the risk of LBW among other adverse pregnancy outcomes [10]. Strategies to improve the availability, accessibility, and affordability of maternal health services should be focused on fathers with low education levels.

 

Unemployment significantly increased the risk of LBW, which could be associated with poor socio-economic status.[10,13] Poor socio-economic status has been linked to inadequate access to quality reproductive health care services, poor household nutrition, and hence increased risks of adverse pregnancy outcomes, including LBW [13]. Low paternal age was associated with a higher risk of LBW, as also reported in Finland and Canada [11]. On the contrary, a study done in the USA revealed that paternal age of more than 35 years increased the risk of LBW [30]. However, this study included only maternal age as a confounder, excluding other important maternal background characteristics and complications which were included in our study. Paternal genetic changes due to age might play a role in the risk of LBW associated with abnormal placenta formation [15]. The influence of younger paternal age on LBW is, however, not clear [12]. Therefore, more studies should further investigate how paternal characteristics influence LBW, among other adverse pregnancy outcomes. The observed association between paternal characteristics and LBW emphasizes the need for male involvement in maternal and child health services. This allows for early identification and management of high-risk pregnancies, accounting for the contribution of paternal-related factors. Research in low and middle-income countries have reported low male participation in maternal and child health services [22]. Also, male involvement in maternal and child health services in Tanzania is still a challenge. For instance, only 30% of men in Tanzania participate at ANC [21]. Health care providers and program implementers should take appropriate action to advocate and encourage men´s involvement in ANC. Health education and services provided during ANC have the potential to reduce pregnancy and delivery complications, including LBW, among other birth outcomes [22].

 

 

Strengths and limitations: the large hospital-based birth registry data recorded from 2000-2018 in the KCMC zonal referral hospital enabled us to analyze and establish the association between paternal characteristics and LBW controlling for potential maternal confounders. This study is probably the first, to the best of our knowledge, to report the association between paternal characteristics and LBW in Tanzania and Sub-Saharan Africa. As with other epidemiological studies, some key variables, for instance lifestyle factors of the fathers, such as smoking and alcohol use, were not measured and included in the birth registry, which has been associated with LBW in other studies [8]. The study involved deliveries recorded in a tertiary hospital, which might not reflect the true picture in the general Tanzanian population.

 

Conclusion Up    Down

The study confirmed paternal age, education level and occupation as predictors for LBW. Current evidence on the effect of paternal characteristics on LBW might suggest that programs and policies should target their engagement as a key strategy for improving birth outcomes during the perinatal period. Future studies should assess how paternal factors are associated with the risk of adverse birth outcomes.

What is known about this topic

  • Maternal characteristics are known factors that increase the risk of LBW;
  • Preconception health counseling which has been shown to improve maternal health status and, in some cases, have been demonstrated to be effective in limiting the incidence of adverse pregnancy outcomes such as LBW has mainly targeted women.

What this study adds

  • This study confirmed paternal young age (≤24 years old), paternal low education level and unemployment as predictors for LBW;
  • Programs and policies should target paternal engagement as a key strategy for improving birth outcomes during the perinatal period.

 

 

Competing interests Up    Down

The authors declare no competing interests.

 

 

Authors' contributions Up    Down

All authors made a potential contribution to this study: Romani Roman Sabas, Noreen Nickson Nyange, Andrea Malimi Mayala and Innocent Baltazar Mboya designed the study. Romani Roman Sabas, Noreen Nickson Nyange and Andrea Malimi Mayala analyzed the data: Innocent Baltazar Mboya, Michael Johnson Mahande, and Caroline Amour commented on the manuscript: Romani Roman Sabas, Noreen Nickson Nyange and Andrea Malimi Mayala drafted the manuscript and had primary responsibility for the final content; The manuscript has been read and approved by all authors and each author believes the manuscript represents honest work hence approved the final version for submission and agreed to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. All the authors have read and agreed on the final manuscript.

 

 

Acknowledgments Up    Down

We extend our sincere appreciation to all women who consented and participated in the KCMC birth cohort. We thank the Norwegian Council for Higher education program and Development Research (NUFU) for funding the establishment of the KCMC Medical birth registry.

 

 

Tables and figure Up    Down

Table 1: social demographics and proportion of LBW by paternal and maternal characteristics among singleton deliveries (N=47,035)

Table 2: the association between LBW and paternal characteristics among singleton deliveries (N=47035)

Figure 1: flow-chart showing the number of deliveries analyzed

 

 

References Up    Down

  1. Katz J, Lee ACC, Kozuki N, Lawn JE, Cousens S, Blencowe H et al. Mortality risk in preterm and small-for-gestational-age infants in low-income and middle-income countries: a pooled country analysis. Lancet. 2013 Aug 3;382(9890):417-425. PubMed | Google Scholar

  2. Chawanpaiboon S, Vogel JP, Moller AB, Lumbiganon P, Petzold M, Hogan D et al. Global, regional, and national estimates of levels of preterm birth in 2014: a systematic review and modelling analysis. Lancet Glob Health. 2019 Jan;7(1):e37-e46. PubMed | Google Scholar

  3. World Health Organization. UNICEF-WHO low birthweight estimates: levels and trends 2000-2015. 2019. Google Scholar

  4. Ministry of Health, Community Development, Gender, Elderly and Children (MoHCDGEC), Ministry of Health (MoH), National Bureau of Statistics (NBS), Office of the Chief Government Statistician (OCGS),and ICF. Tanzania demographic and health survey and malaria Indicator Survey (TDHS-MIS) 2015-16. Dar es Salaam, Tanzania. 2016.

  5. Bililign Yimer N, Tenaw Z, Solomon K, Mulatu T, Gedefaw A. Corrigendum to “Inadequate prenatal visit and home delivery as determinants of perinatal outcomes: does parity matter?”J Pregnancy. 2019 Aug 4;2019:9161294 PubMed | Google Scholar

  6. Londero AP, Rossetti E, Pittini C, Cagnacci A, Driul L. Maternal age and the risk of adverse pregnancy outcomes: a retrospective cohort study. BMC Pregnancy Childbirth. 2019 Jul 23;19(1):261. PubMed | Google Scholar

  7. Mitao M, Philemon R, Obure J, Mmbaga BT, Msuya S, Mahande MJ. Risk factors and adverse perinatal outcome associated with low birth weight in Northern Tanzania: a registry-based retrospective cohort study. Asian Pacific J Reprod. 2016;5(1):75-9. Google Scholar

  8. Mutsaerts MAQ, Groen H, Meer AB Der, Sijtsma A, Sauer PJJ, Land JA et al. Effects of paternal and maternal lifestyle factors on pregnancy complications and perinatal outcome. A population-based birth-cohort study?: the GECKO Drenthe cohort. Hum Reprod. 2014 Apr;29(4):824-34. PubMed | Google Scholar

  9. Dadhwal V, Sharma A, Khoiwal K, Deka D, Sarkar P, Vanamail MPS. Pregnancy outcomes in HIV-Infected women: experience from a tertiary care center in India. Int J MCH AIDS. 2017;6(1):75-81. PubMed | Google Scholar

  10. Dahlui M, Azahar N, Oche OM, Aziz NA. Risk factors for low birth weight in Nigeria: evidence from the 2013 Nigeria demographic and health survey. Glob Health Action. 2016 Jan 19;9:28822. PubMed | Google Scholar

  11. Goisis A, Remes H, Barclay K, Martikainen P, Myrskylä M. Paternal age and the risk of low birth weight and preterm delivery: a finish register-based study. J Epidemiol Community Health. 2018 Dec;72(12):1104-1109. PubMed | Google Scholar

  12. Meng Y, Groth S. Fathers count: the impact of paternal risk factors on birth outcomes. Matern Child Health J. 2018 Mar;22(3):401-408. PubMed | Google Scholar

  13. Zakar R, Zakar MZ, Aqil N, Nasrullah M. Paternal factors associated with neonatal deaths and births with low weight: evidence from Pakistan demographic and Health Survey 2006-2007. Matern Child Health J. 2015 Jul;19(7):1634-42. PubMed | Google Scholar

  14. Wiener-Megnazi Z, Auslender R, Dirnfeld M. Advanced paternal age and reproductive outcome. Asian J Androl. 2012 Jan;14(1):69-76. PubMed | Google Scholar

  15. El Rafei R, Ghandour L, Assaf G, Charafeddine L, Al Bizri A, Alameh M et al. Children born to mothers in their 20s and fathers in their 40s: evidence for an increased low birth weight and Cesarean section deliveries in Lebanon. Ann Epidemiol. 2018 Jun;28(6):368-371. PubMed | Google Scholar

  16. Cheng ER, Rifas-Shiman SL, Perkins ME, Rich-Edwards JW, Gillman MW, Wright R et al. The influence of antenatal partner support on pregnancy outcomes. J Womens Health (Larchmt). 2016 Jul;25(7):672-9. PubMed | Google Scholar

  17. Agricola E, Gesualdo F, Carloni E, Ambrosio AD, Russo L, Campagna I et al. Investigating paternal preconception risk factors for adverse pregnancy outcomes in a population of internet users. Reprod Health. 2016 Apr 14;13:37. PubMed | Google Scholar

  18. Mboya IB, Mahande MJ, Mohammed M, Obure J, Mwambi HG. Prediction of perinatal death using machine learning models: a birth registry-based cohort study in northern Tanzania. BMJ Open. 2020;10(10):1-11. PubMed | Google Scholar

  19. Habib NA, Lie RT, Oneko O, Shao J, Brgsjø P, Daltveit AK. Sociodemographic characteristics and perinatal mortality among singletons in North East Tanzania: a registry-based study. J Epidemiol Community Health. 2008 Nov;62(11):960-5. PubMed | Google Scholar

  20. Davis J, Vaughan C, Nankinga J, Davidson L, Kigodi H, Alalo E et al. Expectant fathers´ participation in antenatal care services in Papua New Guinea: a qualitative inquiry. BMC Pregnancy Childbirth. 2018 May 8;18(1):138. PubMed | Google Scholar

  21. Ministry of health community development gender elderly and children (MOHCDGEC). The National road map strategic plan to improve reproductive, maternal, newborn, child and adolescent health in Tanzania. One Plan II. 2016;(June):142.

  22. Peneza AK, Maluka SO. 'Unless you come with your partner you will be sent back home´: strategies used to promote male involvement in antenatal care in Southern Tanzania. Glob Health Action. 2018;11(1):1449724. PubMed | Google Scholar

  23. Maro EW, Mosha NR, Mahande MJ, Obure J, Masenga G. Ten years trend in maternal mortality at Kilimanjaro Christian Medical Center Tanzania, 2003–2012: a descriptive retrospective tertiary hospital based study. Asian Pacific J Reprod. 2016;5(3):214-20. Google Scholar

  24. Taha Z, Hassan AA, Wikkeling-Scott L, Papandreou D. Factors associated with preterm birth and low birth weight in Abu Dhabi, the United Arab Emirates. Int J Environ Res Public Health. 2020 Feb 21;17(4):1382. PubMed | Google Scholar

  25. Bergsjø P, Mlay J, Lie RT, Lie-Nielsen E, Shao JF. A medical birth registry at Kilimanjaro Christian Medical Centre. East Afr J Public Health. 2007 Apr;4(1):1-4. PubMed | Google Scholar

  26. Chuwa FS, Mwanamsangu AH, Brown BG, Msuya SE, Senkoro EE, Mnali OP et al. Maternal and fetal risk factors for stillbirth in Northern Tanzania: a registry-based retrospective cohort study. PLoS One. 2017 Aug 15;12(8):e0182250. PubMed | Google Scholar

  27. IBM Corp. Released. IBM SPSS Statistics for Windows. Armonk, New York, USA. 2012.

  28. Tessema ZT, Tamirat KS, Teshale AB, Tesema GA. Prevalence of low birth weight and its associated factor at birth in sub-Saharan Africa: a generalized linear mixed model. PLoS One. 2021 Mar 11;16(3):e0248417. PubMed | Google Scholar

  29. Kohi TW, Mselle LT, Dol J, Aston M. When, where and who? Accessing health facility delivery care from the perspective of women and men in Tanzania: a qualitative study. BMC Health Serv Res. 2018;18(1):1-9. PubMed | Google Scholar

  30. Khandwala YS, Baker VL, Shaw GM, Stevenson DK, Lu Y, Eisenberg ML. Association of paternal age with perinatal outcomes between 2007 and 2016 in the United States: population based cohort study. BMJ. 2018 Oct 31;363:k4372 PubMed | Google Scholar

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Research

Paternal characteristics associated with low birth weight among singleton births: a hospital-based birth cohort study in northern Tanzania

Research

Paternal characteristics associated with low birth weight among singleton births: a hospital-based birth cohort study in northern Tanzania

Research

Paternal characteristics associated with low birth weight among singleton births: a hospital-based birth cohort study in northern Tanzania