Introduction
Increased mortality risk among surviving spouses is a documented health consequence of widowhood (Boyle et al., Reference Boyle, Feng and Raab2011; Moon et al., Reference Moon, Kondo, Glymour and Subramanian2011; Schone and Weinick, Reference Schone and Weinick1998; Shor et al., Reference Shor, Roelfs, Curreli, Clemow, Burg and Schwartz2012). Although the direction and strength of relationships differ among studies and across countries, both the cross-sectional and longitudinal research have shown linkages between widowhood and death, regardless of the cause (Blanner et al., Reference Blanner, Mejldal, Prina, Munk-Jørgensen, Ersbøll and Andersen2020; Mendes de Leon et al., Reference Mendes de Leon, Kasl and Jacobs1993; Moon et al., Reference Moon, Glymour, Vable, Liu and Subramanian2014). Even after correcting for various demographic and socio-economic factors, connections between widowhood and mortality have persisted. Some research has also referred to the higher mortality risk associated with the widowhood phenomenon as the widowhood effect (Caputo et al., Reference Caputo, Li, Kühn, Brønnum-Hansen and Oksuzyan2021; Dabergott, Reference Dabergott2021a; Kristiansen et al., Reference Kristiansen, Bojesen, Munk-Jørgensen, Andersen, Manusheva, Bajraktarov, Arsova and Vujovic2017; Sullivan and Fenelon, Reference Sullivan and Fenelon2014).
A considerable discussion exists about the cause of the increased mortality risk among widowed individuals. Previous research examining the mechanisms linking widowhood and mortality has suggested a number of ways in which widowhood and mortality are thought to be related. For instance, some evidence demonstrates that a change in the economic and social role following the death of a spouse may increase the risk of death among the widowed population (Bowling, Reference Bowling1987; Liu, Jiang, et al., Reference Liu, Jiang and Feldman2020; Liu, Umberson, et al., Reference Liu, Umberson and Xu2020; Zick and Smith, Reference Zick and Smith1991). Other pioneering research speculated that the stress of caring for a terminally ill spouse might induce the caregiver spouse to neglect his or her own health, which may also increase their early mortality (Sanders, Reference Sanders1982, Reference Sanders1988). At the same time, some of the seminal studies have also suggested that the loss of a spouse, in addition to causing a transition in the socio-economic roles that existed throughout their marriage, may trigger the onset of various diseases and premature death among the widowed population (Smith and Zick, Reference Smith and Zick1994, Reference Smith and Zick1996). While most of the formative research on links between widowhood and mortality has been conducted in high-income countries, the majority of these studies have looked at the different socio-economic dimensions in the link between widowhood and mortality by gender (Hu and Goldman, Reference Hu and Goldman1990; Manor and Eisenbach, Reference Manor and Eisenbach2017; Manzoli et al., Reference Manzoli, Villari, Pirone and Boccia2007; Martikainen and Valkonen, Reference Martikainen and Valkonen1996; Rendall et al., Reference Rendall, Weden, Favreault and Waldron2011; Smith and Zick, Reference Smith and Zick1996; Vable et al., Reference Vable, Subramanian, Rist and Glymour2015). However, with the other component, the epidemiology aspect among widowed people and its relationship to health is one of the most recent developments in the literature of widowhood and health (Elwert and Christakis, Reference Elwert and Christakis2008; Grundy and Tomassini, Reference Grundy and Tomassini2010; Manor and Eisenbach, Reference Manor and Eisenbach2017; Murphy et al., Reference Murphy, Grundy and Kalogirou2007). As already mentioned, most research has been conducted in high-income countries, and there is an urgent need to examine widowhood and mortality from an epidemiological viewpoint, particularly in low- and middle-income countries.
In general, it has been found that the widowed population reported poorer health and more symptoms than the married population (Aoun et al., Reference Aoun, Breen, Howting, Rumbold, McNamara and Hegney2015; Einiö et al., Reference Einiö, Moustgaard, Martikainen and Leinonen2017). Numerous studies have quantified the extent of the increased risk of cardiovascular disease (CVD), elevated systolic blood pressure, major cardiovascular events, cholesterol levels, and chronic pain symptoms following the death of a spouse among widowed ones (Erlangsen et al., Reference Erlangsen, Runeson, Bolton, Wilcox, Forman, Krogh, Katherine Shear, Nordentoft and Conwell2017; Fagundes et al., Reference Fagundes, Murdock, LeRoy, Baameur, Thayer and Heijnen2018; Fagundes and Wu, Reference Fagundes and Wu2020). However, study findings on widowhood and physical health outcomes were inconsistent and mixed across the study population and countries by gender. In contrast, study findings are significantly gender- and age-specific, focusing on widowhood and mortality (Espinosa and Evans, Reference Espinosa and Evans2008; Manzoli et al., Reference Manzoli, Villari, Pirone and Boccia2007; Prior et al., Reference Prior, Fenger-Grøn, Davydow, Olsen, Li, Guldin and Vestergaard2018; Zivin and Christakis, Reference Zivin and Christakis2007). It has been observed that men experienced a higher risk of mortality after widowhood than women (Dabergott, Reference Dabergott2021a; Liu, Jiang, et al., Reference Liu, Jiang and Feldman2020; Liu, Umberson, et al., Reference Liu, Umberson and Xu2020; Shor et al., Reference Shor, Roelfs, Curreli, Clemow, Burg and Schwartz2012; Smith and Zick, Reference Smith and Zick1996). Existing research indicates that the unexpected loss of a spouse affects men more severely than women, with a 54% increase in mortality risk for men and no increase in risk for women (Sullivan and Fenelon, Reference Sullivan and Fenelon2014). Moon et al. (Reference Moon, Glymour, Vable, Liu and Subramanian2014) found that within 12 months after experiencing the loss of a spouse, men were at higher risk of mortality than women (Moon et al., Reference Moon, Glymour, Vable, Liu and Subramanian2014). While by the cause of the death, men were more likely to experience cardiac problems and increased mortality risk (Vable et al., Reference Vable, Subramanian, Rist and Glymour2015). However, such a pattern was not observed for women (Dereuddre et al., Reference Dereuddre, Van de Velde and Bracke2016). Mortality risk had elevated by more than 20% for widowers with chronic obstructive pulmonary disease, diabetes, accidents or significant fractures, and lung cancer and by 10% with colon cancer, heart disease, heart failure, renal disease, stroke, vascular disorders, and other malignancies (Elwert and Christakis, Reference Elwert and Christakis2008). In this context, Jin and Chrisatakis (Reference Jin and Chrisatakis2009) concluded that a reduction in service quality, a lack of coordination across the different levels of healthcare, and an inability to advocate and communicate effectively during official medical consultations might also contribute to the rising mortality risk among men due to widowhood (Jin and Chrisatakis, Reference Jin and Chrisatakis2009). While, in the post-widowhood phase, many widowers engage in unhealthy risk behaviours such as smoking, alcohol use, and lack of good nutrition, a sleeping disorder accelerates the onset of many lifestyle-related symptoms and chronic morbidities and may raise their pre-mature death compared to married men (Eng et al., Reference Eng, Kawachi, Fitzmaurice and Rimm2005; Manor and Eisenbach, Reference Manor and Eisenbach2017).
In India, strong gender norms and traditional kinship structures are observed in contrast to many high-income, egalitarian societies (Singh et al., Reference Singh, Chokhandre, Singh, Barker, Kumar, McDougal, James and Raj2022). The patriarchal social structure is also the cause of the dreaded stage of life among widowed individuals, notably among women (Chakravarti, Reference Chakravarti1998; Chen and Dreze, Reference Chen and Dreze1992, Reference Chen and Dreze1995). Traditionally, a woman’s primary responsibility was to take care of her husband in India. She lost the fundamental reason for living when she lost her husband. In India, widowhood among women is often a highly fragile stage of life marked by extreme poverty, a lack of social support, and the inability to remarry (Dasgupta, Reference Dasgupta2017; Drbze and Srinivasan, Reference Drbze and Srinivasan1997). Existing evidence also indicated that women’s widowhood status is substantially connected with worse physical and mental health conditions and poor healthcare utilisation compared to men (Lloyd-Sherlock et al., Reference Lloyd-Sherlock, Corso and Minicuci2015a; Pandey and Jha, Reference Pandey and Jha2012; Perkins et al., Reference Perkins, Lee, James, Oh, Krishna, Heo, Lee and Subramanian2016, Reference Perkins, Lee, Lee, Heo, Krishna, Choi, Nam, Oh and Subramanian2018; Sreerupa and Rajan, Reference Sreerupa and Rajan2010). For instance, Perkins et al. (Reference Perkins, Lee, James, Oh, Krishna, Heo, Lee and Subramanian2016) found that recently widowed women and women who had been widowed for an extended period had higher levels of psychiatric distress, lower self-rated health, and hypertension compared to married women, whereas long-term widowed men had a higher risk of developing diabetes when compared to married men (Perkins et al., Reference Perkins, Lee, James, Oh, Krishna, Heo, Lee and Subramanian2016). Agrawal and Keshri (Reference Agrawal and Keshri2014) older widows had a higher prevalence of non-communicable diseases (G. Agrawal and Keshri, Reference Agrawal and Keshri2014). While there are a number of studies reporting that widows had poorer self-reported health and a higher depression level than married women, such a pattern is missing for men (Lloyd-Sherlock et al., Reference Lloyd-Sherlock, Corso and Minicuci2015; Perkins et al., Reference Perkins, Lee, James, Oh, Krishna, Heo, Lee and Subramanian2016). Given this background, women experiencing adverse social and economic repercussions of widowhood and also being more susceptible to worse health conditions might also have greater morbidity-related deaths than men in India. The present study aims to assess the widowhood and health in the Indian setting concurrently, bringing substantial empirical evidence to explore the link between widowhood, morbidity, and mortality. Thus, the main objective of this paper is to examine the mortality difference between widowed and married individuals by the morbidity condition across the age group and gender.
To the best of our knowledge, no research has attempted to predict mortality among the widowed over the married population with the presence of morbidity in India. While, except for a few studies, the majority of previous research has also given less consideration to Indian men and more emphasis to the possible health implications of widowhood on women. Thus, the present study contributes to the epidemiological aspect of mortality among widowhood population and also contributes to the widowhood literature highlighting mortality–morbidity dimension from a gender perspective in Indian settings.
Materials and methods
Data source
The study used prospective data from India Human Development Survey (IHDS) wave 1 (2004–2005) and wave 2 (2011–2012). The IHDS is a panel survey that provides adequate samples for vital events like birth, marriage, migration, and death, as well as various socio-demographic variables, including education, employment, social-cultural capital, household assets, and family structure (Desai et al., Reference Desai, Dubey, Joshi, Sen, Shariff, Vanneman and Codebook2005, Reference Desai, Dubey, Joshi, Sen, Shariff, Vanneman and Codebook2012). IHDS 1 collected information on 41,554 households and 215,754 individuals in 1,503 villages and 971 urban areas across 33 states. In the second wave, 2011–2012, 83 % were re-interviewed. In the second wave, a tracking sheet was also filled out for individuals surveyed in IHDS wave 1 (including migration and death-related information). In addition, the tracking sheet provides specific information on the deaths of people, including the number of years since the individual’s death at the time of the second wave, as well as their educational, marital, and job status. This information from the IHDS was used to estimate deaths among adults aged 25 years and above by marital status in the present study.
Sample
The main interest of this research was in studying the mortality of widowed individuals compared to married ones with chronic morbidity conditions. For this, the main study population was married and widowed adults aged 25 years and above in IHDS-1. The sample size selection started with information on 104,774 individuals aged 25 years and above (out of a total of 215,754 measured) in IHDS-1. Out of these, 98,044 were married or widowed during IHDS 1 (2005–2006). The IHDS tried to contact these individuals in 2011–2012, for its second wave. Thus, this study ignored individuals (5,947 individuals) whose marital status changed from IHDS 1 to IHDS 2. Another 5,650 individuals were lost to follow-up. Besides, individuals with missing information on their morbidity status and health risk behaviour were further excluded from the final analysis, and 82,607 individuals were part of the final sample in the study.
Dependent variable
The dependent variable in this study was the individuals surveyed in IHDS 1 (2005–2006) and their survival status (alive or dead) by IHDS 2 (2011–2012). As mentioned earlier, the survival status of individuals between the two IHDS rounds was observed in the tracking sheet (Barik et al., Reference Barik, Desai and Vanneman2018).
Independent variable
The main independent variable was marital status (married or widowed) with or without morbidity reported in IHDS-1. This study obtained information from the IHDS on major morbidity to predict the processes by which widowhood status might affect mortality. The IHDS provided information on various major morbidities, while we focused on five particular morbidities: tuberculosis (TB), hypertension, CVDs, diabetes, and asthma. Afterwards, this study constructed a variable with the presence of any of the mentioned morbidity or the absence of any morbidity (Ennis and Majid, Reference Ennis and Majid2021; Prior et al., Reference Prior, Fenger-Grøn, Davydow, Olsen, Li, Guldin and Vestergaard2018).
Covariates
The present study considered a number of socio-economic characteristics to control by which mortality among currently widowed and married individuals could vary. The age group was divided into two broad age groups, that is, 25–59 years and 60 years and above (Hossain and Sk, Reference Hossain and Sk2022). The social group was considered which included higher caste (HC), other backward classes (OBC), scheduled caste (SC) and scheduled tribe (ST) (Gupta and Sudharsanan, Reference Gupta and Sudharsanan2022). The economic condition was measured using the wealth index. The wealth index was constructed using principal component analysis (PCA) using 23 equally weighted dichotomous items that measured household consumer goods possessions. The wealth index in this study categorised households into three groups: poor, middle, and rich. Education of the individual was categorised as uneducated, up to 5th standard, up to metrics, up to secondary level, and above secondary level. Currently, smoking and alcohol consumption were divided into yes and no.
Statistical analysis
The main empirical strategy relies on a descriptive analysis of deaths reported in IHDS 2 for widowed and married individuals with morbidity reported in IHDS 1. The chi-square test was applied to analyse death differences between married and widowed adults with morbidity conditions. Then morbidity-specific mortality percentage was calculated for married and widowed adults by age group and gender. Further, to determine to what extent the morbidity could explain differences in mortality between widowed and married individuals, a logistic regression framework was applied. The regression coefficients were then used to estimate predictive margins to compare predicted probabilities of mortality by marital status and morbidity conditions. Separate morbidity-adjusted odds of mortality were estimated for widowed individuals over married ones. To understand the influence of morbidity condition (whether individuals suffered any morbidity and specific morbidity), the interaction effect of marital status with the presence of any morbidity condition and specific morbidity condition on the probability of death was estimated. All results were stratified by age group and gender (Smith and Zick, Reference Smith and Zick1996). For better understanding, the specific morbidity was clubbed to two categories. The first broad category was respiratory ailments including asthma and TB, while the second broad category was non-communicable diseases (NCDs) including hypertension, CVDs, and diabetes. In all the regression analyses, standard errors were clustered at the level of the primary sampling unit. The regressions were also adjusted for social group, wealth index, education level, current smoking, and alcohol consumption. For all of the analyses, IHDS 1 individual weights were applied. All the statistical analysis was done using Stata (version 15) and MS Excel.
Result
Sample characteristics
Table 1 demonstrates the survival status of the individual samples across selected characteristics followed in the IHDS, 2011–2012, from 2004 to 2005. About 28% of older adults died between waves of the IHDS. Between the two waves, a higher proportion of men (10%) died than women (7%). By marital status, widowed adults had a higher proportion of deaths during the survey period. While socially backward groups like ST and SC had a higher proportion of deaths. Similarly, those with low socio-economic status (SES), that is, those with a low wealth index (8.6%) or who were uneducated (9%), had more deaths. While individuals who smoke (10%) or drink alcohol (9.2%) had a higher share of death than their counterparts. While individuals reporting having any morbidity (TB, hypertension, CVDs, diabetes, and asthma) in IHDS 1 had died more (19%) compared to those who reported no morbidity (7.6%).
Table 1. Survival status of individual samples across selected characteristics followed in the India Human Development Survey, 2011–2012, from 2004 to 2005 (N = 82,607)
Note: Five major morbidity conditions include tuberculosis (TB), hypertension, cardiovascular diseases (CVDs), diabetes, and asthma. HC denotes higher caste, OBC denotes other backward classes, SC denotes scheduled caste, and ST denotes scheduled tribe.
IHDS-1 individual weights were applied.
Deceased individuals with morbidity among married and widowed individuals
Table 2 depicts the percentage of deceased individuals with any morbidity by their marital status followed in the IHDS, 2011–2012, from 2004 to 2005. Older widowed reported morbidity had a higher percentage of mortality than older married reported morbidity. Compared to married men (around 24%) and women (10%) who had morbidity, widowers (49%) and widows (28%) who reported having morbidity had a higher proportion of deaths. Widowed people with morbidity from other or Muslim groups had a higher percentage share of death. Additionally, compared to other economic categories, the widowed people from the poor wealth index with morbidity (43%) had a greater proportion of death. Although married individuals with morbidity had an advantage in mortality with improved educational levels, there was no consistency in mortality and educational level among widowed individuals with morbidity conditions. In addition, widowed persons reported having morbidity those who smoke (45%) had a higher proportion of deaths.
Table 2. Percentage of individuals who died between two waves of IHDS reporting the presence of any of the five major morbidity conditions by their marital status at the base wave (2004–2005) in the India Human Development Survey, 2011–2012, from 2004 to 2005 (N = 82,607)
Note: Five major morbidity conditions include tuberculosis (TB), hypertension, cardiovascular diseases (CVDs), diabetes, and asthma.
P values were obtained using the chi-square test.
IHDS-1 individual weights were applied.
Predicted probabilities of death among widowed over married with the presence of any morbidity by age group and gender
Figure 1 examines the interaction effect between widowhood and morbidity on the probability of death. The top left panel, for men aged 25–59 years, shows that morbidity status was a greater modifier for young men’s mortality after widowhood. Due to the presence of any morbidity, more than 40% increased percentage point (PP) of the probability of death had been found among young widowers than those without reported morbidity. While due to the presence of any morbidity, 8% increased PP of the probability of death had been found among young married men. Among the older men, the presence of any morbidity had 60% increased PP of the probability of death among widowers than 40% increased PP among the married ones. Among women, we did not find evidence of an interaction effect of widowhood and morbidity status on the probability of death. In addition to this, the evidence of the interaction effect of health risk behaviours and widowhood status predicting the probability of mortality was given in Appendix Fig. 1.
Figure 1. Predicted probabilities of death by marital status, from logistic regression interacting marital status with the presence of any morbidity by gender and age group, IHDS, India.
Predicted probabilities of death among widowed over married with specific morbidity by age group and gender
The probability of mortality among widowed and married by the specific morbidity condition was predicted in Figs. 2 and 3. Fig. 2 shows the predicted probabilities of death by the interaction effect of marital status and respiratory ailments (asthma and TB). Among the respiratory ailments, young widowers reporting asthma had almost 80% increased PP of the probability of mortality and 20% increased PP of the probability of mortality for married men (Fig. 2). And, no evidence of excess mortality for women with asthma was found. In addition to this, there was no significant evidence of the interaction effect of widowhood and TB predicting mortality across age and gender. Even, no observation was found for young widows with TB in the dataset.
Figure 2. Predicted probabilities of death from 2004–2005 to 2011–2012 by marital status, from logistic regression interacting marital status with the respiratory ailments in 2004–2005 by gender and age group, IHDS, India.
Figure 3. Predicted probabilities of death from 2004–2005 to 2011–2012 by marital status, from logistic regression interacting marital status with the NCDs in 2004–2005 by gender and age group, IHDS, India.
Figure 3, on the other hand, shows the predicted probabilities of death by the interaction effect of marital status and NCD-related ailments (hypertension, CVDs, and diabetes). Among the older men, CVDs had 84% increased PP of the probability of mortality for widowers and 45% increased PP of the probability of mortality for married men. No observation was found for young widowers with CVDs and diabetes in the dataset. Interestingly, older widowed women with diabetes reported a lower probability of mortality than older married women with diabetes. For more information on the specific morbidity-wise mortality among married and widowed adults across socio-economic status, see the supplementary material (Appendix Table A1).
Discussion
The present research explores the relationship between chronic morbidity and mortality among individuals in the post-widowhood phase compared to married people by age and gender. Across all socio-economic groups, widowed individuals reporting any morbidity had a higher mortality proportion than married people. We found that young men with any morbidity are more susceptible to increased mortality risk because of their widowhood status. While, by the specific morbidity conditions, asthma among young widowers and CVDs among old widowers increased the probability of death significantly. On the contrary, among women, older widowed women with diabetes had a lower probability of mortality than older married women with diabetes.
The study results indicate that for men, particularly younger ones, the widowhood status with any morbidity significantly predicts increased mortality even after controlling SES and behavioural factors. There is no such pattern of widowhood and morbidity interaction effect on mortality for young women. A potential implication of the higher mortality among young widowers than among young widows with morbidity possibly is that morbidity conditions worsen the health status of young widowers more than young women, despite the fact that men own the resource access and may have more protective qualities of higher SES (Brenn and Ytterstad, Reference Brenn and Ytterstad2016; Dabergott, Reference Dabergott2021b). On the other hand, widows have worse social and economic consequences after widowhood than widowers, yet widows may be able to cope with the loss of a husband (McCrae and Costa, Reference McCrae and Costa1988; Peña-Longobardo et al., Reference Peña-Longobardo, Rodríguez-Sánchez and Oliva-Moreno2021). In contrast, the consequences of widowhood among men, such as emotional shock or coping with the lifestyle, have a more significant impact on men’s capacity to cope with loss (Drbze and Srinivasan, Reference Drbze and Srinivasan1997; Stroebe et al., Reference Stroebe, Stroebe and Schut2001), which may onset and develop the morbidity condition (Stroebe et al., Reference Stroebe, Stroebe and Schut2001, Reference Stroebe, Schut and Stroebe2007). Further lack of care widowers previously received from the deceased wife worsened their health, increasing the mortality risk among the younger widowers (Chami and Pooley, Reference Chami and Pooley2021).
This research also revealed that the predicted mortality for young widowers with asthma is much higher. As marriage represents a crucial institution, it may prevent men from engaging in risky behaviours such as smoking, drinking excessively, and other harmful healthy behaviours, consequently reducing their mortality risk (Schone and Weinick, Reference Schone and Weinick1998). With the loss of a spouse, to cope with distress and loneliness, widowers are more likely to engage in unhealthy behaviours such as smoking, alcohol, and other drug use, which may contribute to the development of lifestyle-based diseases (Umberson, Reference Umberson1992; Williams, Reference Williams2004). In the Indian set-up, the study by Perkins et al. (Reference Perkins, Lee, Lee, Heo, Krishna, Choi, Nam, Oh and Subramanian2018) also found that recently widowed men are 62% and 76% more likely to smoke and have consumed alcohol (Perkins et al., Reference Perkins, Lee, Lee, Heo, Krishna, Choi, Nam, Oh and Subramanian2018). Thus, this study’s findings may imply that the increased risk of death among widowers with asthma is the result of an unhealthy lifestyle. In this study, the findings on the probability of young widower mortality with asthma are also consistent with existing studies (Brenn and Ytterstad, Reference Brenn and Ytterstad2016; Ikeda et al., Reference Ikeda, Iso, Toyoshima, Fujino, Mizoue, Yoshimura, Inaba and Tamakoshi2007). In addition, results shown in Appendix Fig. 1 also confirm that smoking among young widowers was associated with the increased probability of mortality than young married men.
It is well established that mortality due to CVDs is increasing and that men in India are much more likely than women to die from CVDs (Prabhakaran et al., Reference Prabhakaran, Jeemon, Sharma, Roth, Johnson, Harikrishnan, Gupta and Pandian2018). However, our survey also suggests that older men with CVDs who are widowers have a greater risk of mortality. This pattern of elevated likelihood of death among older widowers implies that the effect of widowhood may lead to less healthier living style, resulting in increased mortality among the widowers. Johnson et al. (Reference Johnson, Backlund, Sorlie and Loveless2000) also established in their study that a change in the behaviour would lead to higher mortality among the widowers occurring out of anger, frustration, or feeling which may lead to deteriorated health status (Johnson et al., Reference Johnson, Backlund, Sorlie and Loveless2000).
However, our finding that widowers with CVDs have a higher death rate than married men with CVDs suggests that older widowers may not seek treatment for their deteriorating health and also fail to get care in the post-widowhood period. In this context, it is theorised that elderly widowers are particularly vulnerable due to their long-standing inability or lack of experience in obtaining emotional assistance outside of the marriage during times of crisis. Previous research on the higher probability of deaths among older widowers suggests that older widowers suffer from greater loneliness and social isolation, and these elements might be the risk factors for CVD events increasing their mortality risk (Valtorta et al., Reference Valtorta, Kanaan, Gilbody, Ronzi and Hanratty2016).
Notably, the older widows with diabetes reported a lower probability of mortality than the older married with diabetes. Our study finding is also in line with the existing studies where a significant lower risk of diabetes for widowed women was found compared to married women (Erlangsen et al., Reference Erlangsen, Runeson, Bolton, Wilcox, Forman, Krogh, Katherine Shear, Nordentoft and Conwell2017; Ramezankhani et al., Reference Ramezankhani, Azizi and Hadaegh2019). Possible explanations include a shift in diet and a lower BMI among widows in India (Agrawal et al., Reference Agrawal, Lalji and Pakrashi2021). In India, widowed women, particularly Hindu widows, had to give up their regular dietary choices in order to adhere to the traditions of the Hindu culture, and this meant renouncing the ‘heating foods’ which include onion, garlic, eggs, and so forth (Agrawal et al., Reference Agrawal, Lalji and Pakrashi2021). In addition, after the death of the husband, surviving spouses have less influence over home affairs and decisions, which may reduce their consumption leading to undernutrition (Chen and Dreze, Reference Chen and Dreze1992). Thus, it may be possible that the differential diet and nutritional level among widows and married women in later ages may explain the probability of mortality among widows.
According to our knowledge, this is the largest nationally representative study of mortality among widowed men and women in India, focusing on the morbidity condition. It is also the first study of its kind to examine widowhood status and morbidity effect on mortality by age and gender. However, there are some limitations in the present study. First, the morbidity considered in the study is self-reported, which may impact the results. Second, the study considers a small number of morbidities to assess the morbidity–widowhood impact on mortality. However, existing studies show that, to examine the morbidity and mortality aspect of marital status, a larger number of morbidities need to be considered (Prior et al., Reference Prior, Fenger-Grøn, Davydow, Olsen, Li, Guldin and Vestergaard2018). Third, the duration of the widowhood can be a proximate factor to explain the widowhood–morbidity impact on mortality (Johnson et al., Reference Johnson, Backlund, Sorlie and Loveless2000). However, due to data restraints, we failed to adjust the duration of the widowhood in this study.
Conclusion
Morbidity conditions among widowed adults strongly predicted death. At the same time, the impact of widowhood–morbidity conditions differed by gender and age. Men with morbidity in India are more vulnerable to experiencing the elevated probability of mortality than women due to widowhood status. The increased mortality risk among young or older widowers is a consequence of behavioural risk. In order to lower the mortality risk, additional health-related education and counselling in the post-bereavement period may help protect widowers from various lifestyle-based diseases and reduce excess mortality. While, evidence of the diabetes and marital status predicting mortality for women raises number of questions which need further explanation and detailed research, given the vulnerable stand of women in post-widowhood stages in India.
Data availability statement
The dataset utilised in the study is readily accessible in the public domain through the Inter-university Consortium for Political and Social Research (ICPSR). To download the data, please follow the link: https://ihds.umd.edu/data/data-download
Acknowledgements
None.
Author contributions
The concept was drafted by B.H and K.S.J.; B.H. contributed to the analysis design, K.S.J. advised on the paper and assisted in paper conceptualisation. B.H and K.S.J contributed to the comprehensive writing of the article. All authors read and approved the final manuscript.
Funding statement
The authors did not receive any funding to carry out this research.
Competing interests
The authors declare no competing interests.
Ethics approval and consent to participate
The dataset utilised in the study is readily accessible in the public domain through Inter-university Consortium for Political and Social Research (ICPSR), and the survey organisations that performed the field survey for data collecting obtained the respondents’ informed consent beforehand. National Council of Applied Economic Research (NCAER) provided the required direction and ethical permission for the IHDS. All methods were carried out in accordance with relevant guidelines and regulations.
Appendix A
Table A1. Percentage of deceased individuals’ cross-marital status between two waves of the India Human Development Survey, 2011–2012, by specific morbidity condition reported at base wave (2004–2005)
Note: IHDS-1 individual weights were applied. P value obtained from the chi-square test.
Those who reported no morbidity were excluded from this table and only those samples reporting any of the selected morbidities in the study were considered.
NA: Not available.
Figure A1. Predicted probabilities of death during 2004–2005 to 2011–2012 by marital status, from logistic regression interacting marital status with the health risk behaviours in 2004–2005 by gender and age group, IHDS, India.
