Skip to main content
Sexual and Reproductive Health Matters logoLink to Sexual and Reproductive Health Matters
. 2019 Aug 12;27(1):248–261. doi: 10.1080/26410397.2019.1647398

Men on the move and the wives left behind: the impact of migration on family planning in Nepal

Dominick Shattuck a,, Sharada P Wasti b, Naramaya Limbu c, Nokafu Sandra Chipanta d, Christina Riley e
PMCID: PMC7887959  PMID: 31533579

Abstract

Nepali migration is longstanding, and increased from 2.3% of the total population in 2001 to 7.2% in 2011. The estimated 1.92 million migrants are predominantly men. Consequently, 32% of married women have husbands working abroad. Social structures are complicated as many married women live with their in-laws who typically assume decision-making power, including access to health services. This study compares access to reproductive health services, fertility awareness, and decision-making power among a sample of married women aged 15–24 years (n = 1123) with migrant husbands (n = 485), and with resident husbands (n = 638). Predictably, women with migrant husbands had significantly lower contraceptive use than other married women (9.3% vs 30.3%, respectively), and expressed a higher intention to become pregnant in the next year. Despite their intentions, women with migrant husbands scored lower on a fertility awareness index, were less likely to discuss pregnancy planning with their spouse, and less likely to describe their relationships positively. Decision-making for both groups of married women was dominated by both husbands and in-laws in different ways. Yet, across multiple normative scales, fewer women with migrant husbands felt pressure to conform to existing social norms. Married women with migrant husbands reflect a subset of women, with unique fertility issues and desires. Interventions that increase knowledge of fertility among this subset of women, promote healthy preconception behaviours. Linking women for counselling opportunities throughout the pre and postnatal periods may help improve health outcomes for mothers and children.

Keywords: Left wives, male migrants, sexual and reproductive health, family planning, Nepal, migration, couple decision-making

Introduction

Movement of people from Nepal to other countries over the last 200 years includes pilgrims, devotees, political refugees, and soldiers. Throughout the twentieth century, Nepal has increased its role as a major labour-exporting country, facilitated in part through an easier acquisition of passports and increased opportunities to travel overseas for work.1,2 Between 2001 and 2011, the number of Nepalis living abroad for at least six months increased from 2.3% to 7.2% of the country’s total population, an estimated 1.92 million migrants (more recent figures on migration do not present information on the same parameters).3

Until 1981, India was the dominant destination for most Nepali migrant workers. In 2017, migrants were more likely to land in the Gulf States, such as Bahrain, Kuwait, and Oman, with Qatar as the top destination, receiving approximately 31% of all Nepali migrants.4 A World Bank study found that Nepali migrant workers in the Gulf States come from traditionally excluded castes, including 34.3% of Muslims, 17.4% of Hill Janajati, and 15.8% Terai Dalit households.5 Migration impacts some geographic groups within Nepal more than others. For example, there is little uniformity in migration rates across Mountain, Hill and Terai groups in the Eastern Central, Western, and Far Western areas.6

The decision to migrate for work comes with great challenges that include leaving behind wives and other family members. The decision is a collective one that involves the extended family and is driven by the opportunity of remittances for those left behind.7–10 Migration and health researchers cite the complexity of migration on family members left behind. Globally, studies have identified health disparities among women with migrant husbands11 and negative consequences of migration on other family members’ health,12 children’s education,13 and child well-being.14 Mental health issues have also been identified among wives of migrant husbands, including increased feelings of loneliness and isolation15 and depressive symptoms.16 In India, women with migrant husbands have higher levels of reproductive morbidity17 and sexually transmitted infections than women married to non-migrants.18 This is further complicated by limited access to sexual and reproductive health services for wives left behind.19

Positive impacts of husbands’ migration include increased accrual of money and material items and improvement in women’s decision-making power, particularly for the management of resources and household affairs.20 Unfortunately, these benefits can also complicate familial relationships and may place a greater burden on women’s well-being.10,21 This is particularly relevant for wives living with their in-laws. Decision-making power is more likely to reside with in-laws and can extend beyond general household decisions. For example, some wives reported that their mothers-in-law made decisions regarding when a woman with a migrant husband should visit a doctor, attend antenatal care, and who is to accompany them on clinic visits related to their reproductive health.10

The cultural impact of migration on women’s roles is suggested to have rendered women with migrant husbands “ … invisible, and their role, experience, well-being, and interconnectedness with the practice of migration are not well understood”10,22,23 Migration often challenges traditional roles of women at home, as the increased workload for women and dependence on remittances alters the expectations of autonomy and decision-making power.24 Understanding women’s reproductive health and related household decision-making may provide insights on how they manage changing dynamics with in-laws in their husbands’ absence.

Although Nepal has improved across many reproductive health indicators, challenges remain. Since 2006, the contraceptive prevalence rate (CPR) has stagnated (48% vs 53% in 2016), while traditional method use has more than doubled in the same time period.25 Use of modern family planning is nearly three times higher among married women who live with their husbands (68%) than those who do not (24%).25 The rate of family planning discontinuation has become a major concern for the government of Nepal. NDHS 201626 identified the association between husbands moving away from their homes (for any purpose) as the primary reason for discontinuation of family planning, followed by side effects, and desire to become pregnant. The Nepal Family Health Program survey also showed that women with migrant husbands tend to discontinue family planning methods when separated from their spouses to avoid rumours about infidelity from in-laws and community members.27

The objective of this paper was to identify the proportion of women with migrating husbands and describe the understudied implications of male-partner migration on family planning and related reproductive health factors. We examined various reproductive health-related factors including social norms and spousal communication dynamics, fertility awareness, and family planning use. This paper describes the reproductive health context and spousal communication among a large sample of adolescent and young women (15–24 years) with migrant husbands from five districts of Nepal and assesses selected reproductive health indicators compared with women whose husbands are present in the home.

Methods

A cross-sectional baseline quantitative survey was conducted in Nepal between August and September 2016 as part of the Fertility Awareness Community Transformation (FACT) Project. This USAID-funded project implemented by the Institute of Reproductive Health at Georgetown University (IRH), in collaboration with Save the Children, is a cluster randomised, three-arm prospective study. The intervention aims to increase fertility awareness, educate on fertility awareness-based methods, increase access to family planning services, and increase uptake of all modern family planning methods in Nepal.

Sample

Three clusters of three Village Development Committees (VDCs) within five districts of Nepal were identified and randomly assigned to one of three study arms. The five districts reflected the geographic variation in the country: Mountain – Bajura; Hill – Pyuthan and Nuwakot; Terai – Rupandehi and Siraha. Each district contains a blend of religious and ethnic groups (castes) somewhat unique to that area of the country. The clusters tended to have a higher rate of marginalised individuals, which included, for example, Muslims, Dalit and Janajati. Sites were identified from the locations where Save the Children had existing programmatic infrastructure. For the baseline survey, women and men aged 15–24 years were surveyed using a standardised questionnaire across the total of 45 VDCs. The study described here used baseline data that were collected prior to the implementation of the intervention. This study received ethical approval from the Georgetown University’s Institutional Review Board and the Nepal Health Research Council prior to data collection.

The goal of the larger study was to assess changes in contraceptive use among women in Nepal. The average CPR (42%) across the five project implementing districts was used to calculate the sample size28 of 162 women per cluster to detect a 10% increase in CPR among women 15–24 years with 80% power at a significance level of 5% with a one-sided test, resulting in 2430 women across all 45 clusters. Participant selection included a multi-step process. First, a list of eligible households was generated through local contacts and government officials at the ward level, the smallest unit of government administration. Next, households were systematically selected (i.e. every fourth household) from the list and approached for an interview. Households that were not available at the time of data collection were revisited up to three times, and in the instances where they were not available or interested in participating, the next household was selected and approached.

Data collection

Data were collected using mobile/smart phones running the Android platform and the REMO program.29 Written consent was obtained from all the participants in a private setting whereas consent from illiterate participants was obtained with the help of a witness. Voluntary participation and freedom of refusal at any stage of the session were emphasised prior to data collection. Women and men between 15 and 18 years old were treated as adults and administered consent forms without parental approval per ethical approval listed above. Data were double entered and cross-checked in order to enhance reliability.

Measurement

Primary outcome variables within the survey included family planning use and intention to use. Both questions were adopted from the Nepal Demographic Health Survey25 and other questions from previous FACT studies implemented in African countries by IRH. All questions were adapted for the Nepali context which ensures that they are, to a degree, valid and reliable.30 Final data collection tools were pre-tested prior to final field survey.

Women self-reported as married. Women with migrating husbands were defined as having a husband who travels outside of the country for work for more than six months at a time. Across the variety of migration definitions, we focused on the wives of international migrants, as remittances from abroad provide some families with significant income, and the impact of those monies on factors associated with reproductive health has received limited attention in the literature.

Five questions were used to understand women’s decision-making power across a variety of topics: visiting family or friends, financial matters, seeking health care, spending money on health care, and when to get pregnant. Response options on the decision-maker included: the respondent herself; jointly with their partner; and multiple family members (i.e. partner, father-in-law, mother-in-law) reflecting the decision was made by others. Responses were then categorised as either “full autonomy” (making decisions herself), “partial autonomy” (making decision with partner) or “no autonomy” (the decision was made by others).

This study piloted a fertility awareness scale and refined five social normative scales. Fertility awareness is defined as “actionable information about fertility throughout the life cycle and the ability to apply this knowledge to one’s own circumstances and needs”.31,32 Ten knowledge-based questions about the onset of fertility for boys and girls, including facts about the menstrual cycle and fertile window, were included in the scale. Confirmatory factor analysis (CFA) was used to describe the consistency of measurement for a latent construct (fertility awareness),33 while item response theory allows for detailed investigation of items in relation to the latent construct of interest and is more appropriate for measuring knowledge scales.34,35 When testing the scales, the 10 questions yielded a two-factor model that accounted for 41.4% of the variance in responses. The two distinct scales are as follows: (a) the fertility awareness scale measures knowledge around onset of fertility and duration of fertility for both females and males, and knowledge around the menstrual cycle and menstruation; (b) the fertile window scale measures knowledge specifically on the timing of the fertile window in relation to pregnancy intention. Responses were marked correct and incorrect. Sum scores were calculated for each scale and then dichotomised into either a low or high category. Low fertility awareness knowledge scores were means of less than 3.51 of 8, while low fertile window scores were less than 0.45 of 2.

The social normative scales describe participants’ perceived norms related to family planning use: delaying first birth after marriage, couple communication, migration, and preference for sons over daughters. Each social normative scale is comprised of types of questions that relate to what a participant thinks other people in their social group or community actually do (descriptive norms), approve of (injunctive norms), and expect (subjective norms) of other people’s behaviours.36,37 CFA was used to identify the relationship between the observed items for each social norms scale and its underlying latent constructs.38 Items were removed based on standardised inclusion parameters. As a best practice, we report the internal consistency of the scales using two statistics, Cronbach’s coefficient alpha (α) and the Guttmann split-half reliability (λ2) in the tables below.39–42

Analyses

The clean dataset was transferred to STATA and was analysed using descriptive statistics including crosstabs. To test the statistical significance between group difference (e.g. women with migrant and non-migrant husbands), a chi-square test was used to find any independent factors associated with group membership. Differences were considered significant at a p-value of 0.05 or less. Additionally, logistic regression was used to test differences for the two groups of married women across multiple variables including: pregnancy desire, family planning use, and intention to use family planning (at three and six months). Odds ratios and 95% confidence intervals are presented below.

Results

A total of 2430 women aged 15–24 years from 45 VDCs across the five project districts were surveyed. Less than half (n = 1123) of women in the sample were married. More than two-fifths (43.2%) of all married women met our definition of having a migrant husband. An additional 5.3% of married women had husbands who travelled outside of their community, but within Nepal, for work for three or more months.

Married women’s mean age was consistent across the two sub-groups (21.5 years). Within our sample, the Hill Region had the highest percentage of women with migrant husbands (48.5%) followed by women in the Terai Region (32.0%) and Mountain Region (19.5%). Almost all women with migrant husbands identified as Hindu (91.1%), which was higher than other married women (p < 0.001). The proportion of women with migrant husbands differentiated across ethnic groups (p < 0.05). Ethnicities with the highest percentage of migrant husbands were the Dalit (52.0%), Brahman/Chhetri (42.5%), and Muslim (41.7%) (Table 1).

Table 1. Socio-demographic characteristics of married women.

Variables Lives with husband (n = 638) Migrant husbands (n = 485) Total (n = 1123) X2 Df p-value
  n % n % n %    
Ecology belt wise
 Mountain region 152 23.8 95 19.5 247 22.0 2 <0.01
 Hill region 213 33.4 235 48.5 448 39.9
 Terai region 273 42.8 155 32.0 428 38.1
Age distributions
 Mean age (SD) 21.5 (2.6) 21.6 (2.4) 21.5 (2.5) 1121 0.48
 <21 Years 248 38.9 180 37.1 428 38.1 1 0.55
 ≥21 Years 390 61.1 305 62.9 695 61.9
Religions
 Hindu 548 85.9 442 91.1 990 88.2 1 <0.01
 Non-Hindu religion 90 14.1 43 8.9 133 11.8
Caste/ethnicity
 Brahman/Chhetri 184 28.8 136 28.0 320 28.5 4 0.03
 Janajati 175 27.4 116 23.9 291 25.9
 Other Madhesi 132 20.7 84 17.3 216 19.2
 Muslim 28 4.4 20 4.1 48 4.3
 Dalit 119 18.7 129 26.6 248 22.1
Age at marriage
 ≤19 years 547 85.7 426 87.8 973 86.6 1 0.31
 ≥20 years 91 14.3 59 12.2 150 13.4
Number of children
 No children 222 34.8 129 26.6 351 31.3 2 0.01
 1 child 190 45.7 201 56.5 391 50.7
 ≥2 children 226 54.3 155 43.5 381 49.4
Age at first pregnancy
 Mean age (SD) 18.8 (2.0) 18.6 (1.9) 18.7 (1.9) 770 0.09

Access to health services

Sixty-nine percent of women visited a health clinic recently (n = 769). However, less than a third of those women reported receiving any family planning counselling (n = 236). There were no statistical differences between women with and without migrant husbands. In Nepal, Female Community Health Volunteers (FCHVs) and other staff from health clinics provide information about healthy timing and spacing of pregnancies, supply condoms, (second-cycle) contraceptive pills, and refer clients for other FP services. Women with migrant husbands were less likely to receive counselling or outreach services from FCHVs, while they had a greater likelihood of receiving outreach services in the previous six months (Table 2).

Table 2. Access to health services.

  Married women  
Variables Lives with husband (n = 638) Migrant husbands (n = 485) Total (n = 1123) p-value
  n % n % n %  
Visited health facility for self or children in last 6 months 440 69.0 329 67.8 769 68.5 0.69
Counselled on FP at last visit to health facility (n = 769) 143 32.5 93 28.3 236 30.7 0.21
Visited by FCHV & discussed FP in last 6 monthsa 218 34.2 127 26.2 345 30.7 0.01
Previously received with outreach servicesb 99 15.5 129 26.6 228 20.3 0.01

aFCHVs: linked to the local health center and provide lower level counselling on nutrition and family planning (i.e. provision of second-cycle contraceptive pills and condom distribution).

bOutreach services: comprised of larger health-related campaigns implemented through the ministry of health (i.e.; malaria, cholera, and vaccination campaigns).

Fertility awareness, communication, and strength of relationships

Nepali Ministry of Health and Population (MoHP) guidelines advise women to be 20 years old at first pregnancy, and more than 90% of women in the study reported that as the optimal age.43 However, women’s knowledge about fertility, its onset and some details about the menstrual cycle was low. Women answered fewer than half of the questions correctly, with women with migrant husbands scoring lower than other married women (p = 0.02) (Table 3). Although close to three-quarters of women knew what the menstrual period was, less than one-third had accurate knowledge around male fertility and less than one-fifth had knowledge of the fertile window. Women with migrant husbands also scored lower than other married women on two questions about the fertile window (p < 0.01).

Table 3. Fertility awareness.

  Married women  
Variables Lives with husband (n = 638) Migrant husbands (n = 485) Total (n = 1123) p-value
         
  n % n % n %  
General fertility questions
 Sign girl becomes fertile 428 67.1 268 53.5 696 62.0 p < 0.01
 Sign boy becomes fertile 142 22.3 105 21.6 247 22.0 p = 0.81
 Definition of menstrual period 474 74.3 340 70.1 814 72.5 p = 0.12
 Definition of menstrual cycle 167 26.2 122 25.2 289 25.7 p = 0.70
 Beginning of menstrual cycle 192 30.1 143 29.5 335 29.8 p = 0.83
 Ending of menstrual cycle 165 25.9 123 25.4 288 25.6 p = 0.85
 Duration of menstrual cycle 515 80.7 382 78.8 897 79.9% p = 0.42
 Days of male fertility 239 37.5% 139 28.7% 378 33.7% p < 0.01
               
  Mean SD Mean SD Mean SD  
Fertility Awareness Score 3.64 2.39 3.34 2.46 3.51 2.42 p = 0.02
               
  n % n % n %  
Fertile Window Questions
 Days of female fertility 121 19.0% 64 13.2% 185 16.5% p = 0.01
 Time to avoid unprotected sex 214 33.5% 108 22.3% 322 28.7% p < 0.01
               
  Mean SD Mean SD Mean SD  
Fertile Window Score 0.53 0.71 0.35 0.60 0.45 0.67 p < 0.01

Note: Percentages reflect the percentage correct for each item.

The General Fertility Score (range: 0–8) and the Fertile Window Score (range: 0–2) reflect the aggregate mean of dichotomised correct responses for participants.

Fewer women with migrant husbands reported speaking with their husband about their family size and timing of children (64.5%) vs other married women (74%) (p < 0.01). More than 80% of women from both groups reported the strength of their relationship as “strong” or “good”. However, a higher percentage of women with migrant husbands reported their relationships as “fair” or “poor”, than other married women (11.4%, p < 0.01). (Data not shown).

Decision-making

Women were asked several questions about who makes specific decisions in their lives related to visiting and mobility, finances, seeking health care, and when to get pregnant. Responses were categorised in accordance with a perceived level of autonomy: Full (makes decisions independently), Partial (makes a decision jointly with spouse), and No Autonomy (decisions are made for the women). Across multiple variables, about 60% of married women reported no autonomy (neither partial nor full) and that decisions were made by husbands or other family members. Healthcare seeking behaviour is an exception, as roughly half of women from both groups reported either full or partial autonomy. Though partial autonomy was more common than full autonomy across all decision-making topics, wives with migrant husbands were 3.6–5.5 times more likely (p < 0.01) to have full autonomy over the measured decisions vs their counterparts (Table 4). Within the group of women who reported no autonomy, we explored who assumed this decision-making across the four questions with statistical differences. When compared with women living with their husbands, women with migrant husbands were 2.0–5.9 times more likely (p < 0.01) to report these decisions being made by other family members as opposed to their spouses.

Table 4. Autonomy in decision-making among married women.

  Married women
Variables Lives with husband With migrant husband Total p-value
  n % n % n %  
Decision maker to visit family or relatives
 Full Autonomy: Respondents 17 2.7 51 10.5 68 6.1% <0.01
 Partial Autonomy: Joint 209 32.8 113 23.3 322 28.7%
 NO Autonomy: Spouse or Other 412 64.6 321 66.2 733 65.3%
Decision maker for financial matters
 Full Autonomy: Respondents 9 1.4 58 12.0 67 6.0% <0.01
 Partial Autonomy: Joint 253 39.7 130 26.8 383 34.1%
 NO Autonomy: Spouse or Other 376 58.9 297 61.2 673 59.9%
Decision maker for health care seeking
 Full Autonomy: Respondents 84 13.2 163 33.6 247 22.0% <0.01
 Partial Autonomy: Joint 229 35.9 106 21.9 335 29.8%
 NO Autonomy: Spouse or Other 325 50.9 216 44.5 541 48.2%
Decision maker for spending on health services
 Full Autonomy: Respondents 22 3.4 72 14.8 94 8.5% <0.01
 Partial Autonomy: Joint 240 37.6 111 22.9 351 31.3%
 NO Autonomy: Spouse or Other 376 58.9 302 62.3 678 60.4%
Decision maker to get pregnant
 Full Autonomy: Respondents 13 2.0 18 3.7 31 2.8% 0.12
 Partial Autonomy: Joint 240 37.6 163 33.6 403 35.9%
 NO Autonomy: Spouse or Other 385 60.3 304 62.7 689 61.4%

Note: Degrees of freedom = 2; n = 1123 women.

Social norms scales

Table 5 includes the reliability statistics and number of items for each of the normative scales and t-test comparisons of mean scores for the two groups of married women. Each of the scales exceeded the 0.70 threshold for Cronbach’s alpha and Guttmann’s lambda suggesting that the scales have reasonable levels of internal consistency. Women with migrant husbands scored significantly lower on the family planning norms (2.53 vs 2.64), delaying first birth (2.10 vs 2.21), and son preference scales (2.15 vs 2.34) (Table 5). When controlling for ethnicity, religion, age, and literacy, women with migrant husbands were 0.6 times less likely (CI: 0.5–0.8, p < 0.01) to perceive family planning use as acceptable among their immediate community, compared to women who live with their husbands. Women with migrant husbands were also 1.5 times more likely (CI: 1.4–1.9, p < 0.01) not to feel pressure from their families to get pregnant immediately after marriage and 1.5 times less likely to feel pressure to have a son (CI: 1.2–1.9, p < 0.01) (Data not shown).

Table 5. Social norms comparative mean scores for married women with and without migrant husbands.

  With migrant husband Lives with husband    
Scales Mean (SD) 95% CI Mean (SD) 95% CI p-value α λ2
Family planning norms score 2.53 (0.56) (2.48, 2.58) 2.64 (0.56) (2.60, 2.69) <0.001 0.79 0.80
Delay first birth norms score 2.10 (0.82) (2.03, 2.18) 2.21 (0.82) (2.14, 2.27) 0.019 0.85 0.86
Couples communication score 2.55 (0.68) (2.49, 2.61) 2.59 (1.03) (2.51, 2.67) 0.257 0.70 0.72
Migration norms score 2.73 (0.32) (2.70, 2.76) 2.70 (0.41) (2.67, 2.74) 0.106 0.77 0.78
Son preference 2.15 (0.80) (2.08, 2.22) 2.34 (0.84) (2.28, 2.41) <0.001 0.79 0.81

Note: n = 1123 women.

Acceptable internal consistency statistics for α and λ2 is 0.70.

Family planning status

Approximately three in 10 married women reported their intention to become pregnant in the next year. A higher percentage of women with migrant husbands (36.5%) intend to become pregnant than other married women (26.1%) (Table 6). Data from regression analysis are not shown but summarised as follows. Controlling for their current number of children, women with migrant husbands were 1.7 times more likely (CI: 1.1–2.5, p < 0.01) to desire a pregnancy within the next year than a woman whose husband lives at home. About one-fifth (20.4%) of all married women reported that they are currently using modern family planning methods. When controlling for pregnancy status and intention, women with migrant husbands were 80% less likely (OR: 0.2, CI: 0.1–0.3, p < 0.001) to be using family planning. Intention to use family planning six months after data collection remained low for women with migrant husbands (OR: 0.57, CI: 0.4–0.8, p < 0.001). Almost all women (94%) reported husbands’ support for family planning use, but only 37.7% of women with migrant husbands had discussed ever using family planning methods with their spouse compared to more than half (53.5%) of non-migrant wives (p < 0.01). When controlling for migration status, pregnancy status and desire, and the strength of the marital relationship, women who discussed using a family planning method with their spouse were 4.0 times more likely (CI: 2.9–5.5, p < 0.001) to intend to use a family planning method in the next six months.

Table 6. Family planning status.

  Married women  
Variables Lives with husband (n = 638) Migrant husbands (n = 485) Total (n = 1123) P-value
  n % n % n %  
Currently pregnant 97 15.2% 42 8.7% 139 12.4% <0.01
Wishes to become pregnant within next year 166 26.1% 177 36.5% 343 30.6% <0.01
Currently using modern FP method 193 30.3% 45 9.3% 238 21.2% <0.01
Intends to use FP method within next 6 months 259 40.6% 137 28.3% 396 35.3% <0.01
Discussed using FP method with spouse 341 53.5% 183 37.7% 542 46.7% <0.01
Spouse supportive of using FP method 320 93.8% 173 94.5% 493 94.1% 0.75

Discussion

This study compared reproductive health-related knowledge, decision-making, and family planning use between women with migrant husbands and other married women in Nepal. Although statistical differences were not identified in many socio-demographic variables, significant differences were found in health-related factors such as strength of relationship, fertility awareness, and decision-making power. Across these factors, women with migrant husbands were more likely to have full autonomy of decision-making and desired to become pregnant in the next year more frequently than other married women. This combination of factors suggests that programming for all married women should consider a wide range of familial dynamics and fertility desires resulting from migrating husbands.

Within our sample of married women, rates of migration varied by region. Yet, the experiences of these women are not unique and are becoming more commonplace as the number of couples experiencing spousal separation for one or more years continues to increase in Nepal, from 35% to 49%.26 New regions of the country are beginning to experience this exodus of men. Currently, in Nepal, male migration is increasing in the western region. For example, the Labor Migration for Employment report (2014/2015) found that the far western districts of Nepal, which is designated as a mountain region within the ecological belts, has seen the greatest increase in permits for migrant labour.44 One study site, Bajura, is in a far-west mountain region and experienced a seven-fold increase in migration between 2009 and 2015, which is a relatively low increase in comparison to other neighbouring districts (rage: Doti – eight-fold and Acham – 17-fold increases). Interestingly, some of the lowest rates of migration are also in neighbouring, yet more isolated districts bordering China (Mugu and Humla). These dynamics are having a dramatic impact on women, and the proportion of female-headed households across Nepal nearly doubled from 16% in 2011 to 31% in 2016.27

Our analysis found that fewer women with migrating husbands access reproductive health-related services. They also have a high desire to become pregnant. High interest in becoming pregnant in this sample may be partially explained by the mean number of pregnancies of 1.1, which is below the national desired family size of 2.3.26 Limited engagement with health service providers may prove to be a barrier for women with migrant husbands as they attempt to maximise their opportunities for pregnancy with husbands who typically return to their families every 12–18 months, often around major festivals, like Dashain. The elevated interest in pregnancy among women with migrant husbands may provide an opportunity for integrating additional preconception interventions that have been found to be effective in high resource settings.45 In fact, the World Health Organization guidance on preconception interventions includes a wide range of topics that include nutritional screening and counselling, tobacco use, genetic conditions using oral family history, interpersonal violence screening, and sexually transmitted infections including HIV screening.46 These interventions are supported by rigorous research and could potentially be integrated into services delivered by FCHV or mobile auxiliary nurse midwives (a programme soon to be expanded in Nepal). For instance, FCHVs could increase their nutrition counselling services to include dietary interventions (healthier eating), promotion and or provision of folic acid, discuss the harms associated with alcohol and cigarette use and, if relevant, identify ways to increase healthy physical activity among women seeking pregnancy prior to their husband’s return.

Interventions focused on the basic foundations of fertility would benefit women with migrant husbands. Such interventions may provide the opportunity to promote antenatal care guidelines, facility-based delivery, and access to postnatal services, vaccination, and possibly postpartum family planning use. Timing the preconception counselling to provide proper lead-time prior to the return of migrant husbands may increase their chances for conception and improve maternal and child outcomes.

Fewer women with migrant husbands reported their marriage as “strong” while also reporting lower rates of spousal communication. Consistent with previous research,10,21 about two-thirds of women reported no autonomy over their decisions across several behaviours. When considering preconception interventions for women, program developers should develop activities that find ways to increase healthy communication among couples. Globally, improved couple communication has been linked to stronger relationships47 and joint decision-making.48 Two Nepali studies highlight the importance of linking women’s autonomy with opportunities for improving couple communication and negotiation skills.49,50 Enhancing women’s autonomy is all the more relevant given the increased prevalence of female-headed households in Nepal. As such, understanding how autonomy translates to educational or professional opportunities for wives and development gains for children, as well as cohesion and support within families and the wider community, may provide programmatic platforms that maximise sound financial management of remittances and promote health and well-being for the entire family.

Even when considering multiple factors associated with family planning (including migration status), couple communication, and discussing family planning method-use, was the most significant predictor of intended use. The findings from this study suggest that programming related to family planning and reproductive health should engage both spouses and also include components that promote discussion and equitable decision-making, particularly as it relates to the extended family. Understanding the differential impact of interventions that effectively integrate in-laws and place an emphasis on communication with the entire family may help to fill the gaps left by fathers working abroad for extended periods of time. Additionally, in each district, women with migrant husbands were not alone. Identifying ways to harness the collective experience of women with migrant husbands in communities to form collectives and work together may build community bonding and social cohesion.

Limitations

Data collection occurred in October of 2016, shortly after the extended festival season in Nepal. It is a time of year when many migrant husbands return home. As a result, some of the participants’ responses and our conclusions could be influenced by these recent reunions. Future research should take into consideration the timing of visits on family planning use and relationship status. Our study only sampled 5 of the 75 districts of the country and does not capture data from a wide enough swatch of provinces and geographic zones. As a result, the large sample from which this sub-analysis was conducted may not truly provide a comprehensive picture of the experiences of Nepali women. Finally, this sample is comprised of young married women. In Nepal, the average desired family size among women is 2.2, and the average number of children is 2.3.26 The mean number of children among this sample of married women was 1.1, which may help explain the high desire for pregnancy among participants and influences family planning use.

Conclusion

Married women with migrant husbands reflect a subset of women with unique fertility issues and desires. These women are more likely to desire pregnancy despite their husbands’ absence. Interventions that increase this subset of women’s knowledge of fertility, promote healthy preconception behaviours and link women for counselling opportunities throughout the pre and postnatal periods may help improve health outcomes for mothers and children. For example, improving healthy communication between women and their migrant husbands prior to home visits may improve relationship quality. For some women with migrant husbands, interventions should include in-laws and focus on ensuring women’s autonomy over their health, movement and financial decision-making. Such interventions may prove to be timely as the rate of Nepal’s female-headed households continues to rise.

Acknowledgements

The authors would like to acknowledge Victoria Jennings, Sarah Thompson, and Shwetha Srinivasan for their support, which greatly improved the development and publication of this paper. The financial support of and direction provided by USAID and the Nepali Ministry of Health and Population and the Nepal Family Welfare Division were critical to the success of this project. The authors would also like to thank the larger FACT team in Nepal and collaborating partner Save the Children (US and Nepal) staff including Marcie Rubardt, Gabrielle Nguyen, Sangita Khatri, Eliza KC, and Rajan Bandhari who collaborated on the various project activities in Nepal. Without the willing participation of men and women in this study, the research could not have occurred. We hope that meaningful programmes will be developed to address health and development related issues associated with male migration.

ORCID

Dominick Shattuck http://orcid.org/0000-0002-8524-8149

Christina Riley http://orcid.org/0000-0002-6167-1284

References

  • 1.Seddon D, Adhikari J, Guruṅga G.. The new Lahures: foreign employment and remittance economy of Nepal. Kathmandu: Nepal Institute of Development Studies; 2001. [Google Scholar]
  • 2.Maharjan A, Bauer S, Knerr B.. Do rural women who stay behind benefit from male out-migration? A case study in the hills of Nepal. Gend Technol Dev. 2012;16(1):95–123. doi: 10.1177/097185241101600105 [DOI] [Google Scholar]
  • 3.CBS National population and housing census 2011. In: Statistics NCBo, ed. Kathmandu: National Planning Commission Secretariat; 2012. p. 118–149. [Google Scholar]
  • 4.Mishra S. Qatar top destination for Nepali migrants last fiscal year. The Himalayan Times, October 7, 2017.
  • 5.The World Bank Large-scale migration and remittance in Nepal: issues, challenges, and opportunities; 2011.
  • 6.CBS National population and housing census 2011. Kathmandu: Nepal Central Bureau of Statistics; 2012. [Google Scholar]
  • 7.De Haas H. International migration, remittances and development: myths and facts. Third World Q. 2005;26(8):1269–1284. doi: 10.1080/01436590500336757 [DOI] [Google Scholar]
  • 8.Velayutham S, Wise A.. Moral economies of a translocal village: obligation and shame among South Indian transnational migrants. Global Networks. 2005;5(1):27–47. doi: 10.1111/j.1471-0374.2005.00106.x [DOI] [Google Scholar]
  • 9.Yeoh BS, Huang S, Lam T.. Transnationalizing the ‘Asian’ family: imaginaries, intimacies and strategic intents. Global Networks. 2005;5(4):307–315. doi: 10.1111/j.1471-0374.2005.00121.x [DOI] [Google Scholar]
  • 10.Gartaula HN, Visser L, Niehof A.. Socio-cultural dispositions and wellbeing of the women left behind: a case of migrant households in Nepal. Soc Indic Res. 2012;108(3):401–420. doi: 10.1007/s11205-011-9883-9 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 11.Chen F, Liu H, Vikram K, et al. . For better or WORSE: the health implications of marriage separation due to migration in rural China. Demography. 2015;52(4):1321–1343. doi: 10.1007/s13524-015-0399-9 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 12.Gao Y, Li LP, Kim JH, et al. . The impact of parental migration on health status and health behaviours among left behind adolescent school children in China. BMC Public Health. 2010;10(1):56. doi: 10.1186/1471-2458-10-56 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 13.Morooka H, Liang Z.. International migration and the education of left-behind children in Fujian, China. Asian Pac Migr J. 2009;18(3):345–370. doi: 10.1177/011719680901800302 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 14.Schmeer K. Father absence due to migration and child illness in rural Mexico. Soc Sci Med. 2009;69(8):1281–1286. doi: 10.1016/j.socscimed.2009.07.030 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 15.Skledon R. Of skilled migration, brain drains and policy responses. Int Migr. 2009;47(4):3–29. doi: 10.1111/j.1468-2435.2008.00484.x [DOI] [Google Scholar]
  • 16.Lu Y. Household migration, social support, and psychosocial health: The perspective from migrant-sending areas. Soc Sci Med. 2012;74(2):135–142. doi: 10.1016/j.socscimed.2011.10.020 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 17.Roy A, Nangia P.. Impact of male out-migration on health status of left behind wives-a study of Bihar, India. International Union for the Scientific Study of Population XXV International Population Conference; July 18–23; Tours, France; 2005. [Google Scholar]
  • 18.Sevoyan A, Agadjanian V.. Male migration, women left behind, and sexually transmitted diseases in Armenia. Int Migr Rev. 2010;44(2):354–375. doi: 10.1111/j.1747-7379.2010.00809.x [DOI] [Google Scholar]
  • 19.Webber G, Spitzer D, Somrongthong R, et al. . Facilitators and barriers to accessing reproductive health care for migrant beer promoters in Cambodia, Laos, Thailand and Vietnam: a mixed methods study. Global Health. 2012;8(1):21. doi: 10.1186/1744-8603-8-21 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 20.Kaspar H. Gender and sustainable development: case studies from NCCR North-South; 2006.
  • 21.Agasty MP, Patra RN.. Migration of labour and left-behind women: a case study of rural Odisha. Am Int J Res Humanit, Arts Soc Sci. 2014;7(1):28–33. [Google Scholar]
  • 22.Hadi A. Overseas migration and the well-being of those left behind in rural communities of Bangladesh. Asia-Pac Popul J/U N. 1999;14(1):43. [PubMed] [Google Scholar]
  • 23.Nguyen L, Yeoh BS, Toyota M.. Migration and the well-being of the ‘left behind’ in Asia: key themes and trends. Asian Popul Stud. 2006;2(1):37–44. doi: 10.1080/17441730600700507 [DOI] [Google Scholar]
  • 24.Lokshin M, Glinskaya E.. The effect of male migration on employment patterns of women in Nepal. World Bank Econ Rev. 2009;23(3):481–507. doi: 10.1093/wber/lhp011 [DOI] [Google Scholar]
  • 25.NDHS. Nepal Demographic and Health Survey 2011 Kathmandu, Nepal: Ministry of Health and Population.
  • 26.NDHS. Nepal Demographic and Health Survey 2016 Kathmandu, Nepal: Ministry of Health and Population.
  • 27.NFHP II National Family Health Program Survey 2012. Kathmandu, Nepal; 2012.
  • 28.DoH Annual report: department of health services 2015/16. Kathmandu: Ministry of Health; 2016. [Google Scholar]
  • 29.Remo Software, 2018.
  • 30.Bowling A. Research methods in health: investigating health and health services. Maidenhead: McGraw-Hill Education; 2002.
  • 31.Institute for Reproductive Health. Fertility awareness 2018. [cited 2018 Aug 11]. Available from: http://irh.org/focus-areas/fertility_awareness/.
  • 32.Van Enk L. Fertility awareness & body literacy: integrating information about fertility, menstruation, and our bodies into social and behavior change programs. Washington (DC: ): The Institute for Reproductive Health; 2018. [Google Scholar]
  • 33.Campbell DT, Fisk DW.. Convergent and discriminant validation by the multitrait-multimethod matrix. Psychol Bull. 1959;56:81–105. doi: 10.1037/h0046016 [DOI] [PubMed] [Google Scholar]
  • 34.Embretson SE, Reise SP.. Item response theory for psychologists. New York (NY): Psychology Press; 2000. [Google Scholar]
  • 35.Hambleton RK, Swaminathan H, Rogers HJ.. Fundamentals of item response theory. Vol. 2. Newbury Park (CA: ): Sage Press; 1991. [Google Scholar]
  • 36.Mackie G, Moneti F, Denny E, et al. . What are social norms? How are they measured? San Diego: Center on Global Justice, UNICEF/University of California; 2015. [Google Scholar]
  • 37.Bicchieri C. The grammar of society: the nature and dynamics of social norms. Cambridge: Cambridge University Press; 2005. [Google Scholar]
  • 38.Suhr D. Exploratory or confirmatory factor analysis? Cary (NC: ): SAS Institute; 2006. [Google Scholar]
  • 39.Hu LB, P. Cutoff criteria for fit indices in covariance structure analysis: conventional criteria versus new alternatives. Vol. 6; 1999.
  • 40.Nunnally JC. Psychometric theory. New York (NY): McGraw Hill; 1970. [Google Scholar]
  • 41.Raykov T. Coefficient alpha and composite reliability with interrelated nonhomogeneous items. Appl Psychol Meas. 1998;22(4):375–385. doi: 10.1177/014662169802200407 [DOI] [Google Scholar]
  • 42.Zumbo BD, Gadermann AM, Zeisser C.. Ordinal versions of coefficients alpha and theta for Likert rating scales. J Mod Appl Stat Methods. 2007;6(1):4. doi: 10.22237/jmasm/1177992180 [DOI] [Google Scholar]
  • 43.Nepal National Health Training Center Comprehensive Family Planning (COFP) & Counselling Training Reference Manual. Ministry of Health and Population: pg 187; 2016.
  • 44.Ministry of Labour and Employment Labour migration for employment: a Status Report for Nepal, 2013-2014; 2016.
  • 45.Temel S, Voorst SFV, Jack BW, et al. . Evidence-based preconceptional lifestyle interventions. Epidemiol Rev. 2013;36(1):19–30. doi: 10.1093/epirev/mxt003 [DOI] [PubMed] [Google Scholar]
  • 46.World Health Organization (WHO) Preconception care: maximizing the gains for maternal and child health. In: Department of Maternal, Child and Adolescent Health; 2013.
  • 47.Hartmann M, Gilles K, Shattuck D, et al. . Changes in couples’ communication as a result of a male-involvement family planning intervention. J Health Commun. 2012;17(7):802–819. doi: 10.1080/10810730.2011.650825 [DOI] [PubMed] [Google Scholar]
  • 48.Shattuck D, Yadaz D, Doggett E, et al. . Enhancing couples’ family planning decisions through male engagement. Paper presented at: XXVII International Population Conference; August 26–31st, 2013; Busan, Korea; 2013.
  • 49.Thapa D, Niehof A.. Women’s autonomy and husbands’ involvement in maternal care in Nepal. Soc Sci Med. 2013;93:1–10. doi: 10.1016/j.socscimed.2013.06.003 [DOI] [PubMed] [Google Scholar]
  • 50.Mullany B, Hindin M, Becker S.. Can women’s autonomy impede male involvement in pregnancy health in Kathmandu, Nepal? Soc Sci Med. 2005;61(9): 1993–2006. doi: 10.1016/j.socscimed.2005.04.006 [DOI] [PubMed] [Google Scholar]

Articles from Sexual and Reproductive Health Matters are provided here courtesy of Taylor & Francis

RESOURCES