Marital status, widowhood duration, gender and health outcomes: a cross-sectional study among older adults in India
Perkins et al. BMC Public Health
Marital status, widowhood duration, gender and health outcomes: a cross-sectional study among older adults in India
Jessica M. Perkins 1 3 4
Hwa-young Lee 0 1
K. S. James 7
Juhwan Oh 0
Aditi Krishna 6
Jongho Heo 0 5
Jong-koo Lee 0 2
S. V. Subramanian 4 6
0 JW LEE Center for Global Medicine, Seoul National University College of Medicine , 71 Ihwajang-gil, Jongno-gu, Seoul 110-810 , Korea
1 Equal contributors
2 Department of Family Medicine, Seoul National University College of Medicine , Seoul , Republic of Korea
3 Massachusetts Center for Global Health, Massachusetts General Hospital , Boston, MA , USA
4 Harvard Center for Population and Development Studies, Harvard T.H. Chan School of Public Health , Boston, MA , USA
5 Public Health Joint Doctoral Program, San Diego State University & University of California , San Diego, CA , USA
6 Department of Social and Behavioral Sciences, Harvard T.H. Chan School of Public Health , Boston, MA , USA
7 Jawaharlal Nehru University , New Delhi , India
Background: Previous research has demonstrated health benefits of marriage and the potential for worse outcomes during widowhood in some populations. However, few studies have assessed the relevance of widowhood and widowhood duration to a variety of health-related outcomes and chronic diseases among older adults in India, and even fewer have examined these relationships stratified by gender. Methods: Using a cross-sectional representative sample of 9,615 adults aged 60 years or older from 7 states in diverse regions of India, we examine the relationship between widowhood and self-rated health, psychological distress, cognitive ability, and four chronic diseases before and after adjusting for demographic characteristics, socioeconomic status, living with children, and rural-urban location for men and women, separately. We then assess these associations when widowhood accounts for duration. Results: Being widowed as opposed to married was associated with worse health outcomes for women after adjusting for other explanatory factors. Widowhood in general was not associated with any outcomes for men except for cognitive ability, though men who were widowed within 0-4 years were at greater risk for diabetes compared to married men. Moreover, recently widowed women and women who were widowed long-term were more likely to experience psychological distress, worse self-rated health, and hypertension, even after adjusting for other explanatory variables, whereas women widowed 5-9 years were not, compared to married women. Conclusions: Gender, the duration of widowhood, and type of outcome are each relevant pieces of information when assessing the potential for widowhood to negatively impact health. Future research should explore how the mechanisms linking widowhood to health vary over the course of widowhood. Incorporating information about marital relationships into the design of intervention programs may help better target potential beneficiaries among older adults in India.
Widowhood; Aging; India; Gender; Self-rated health; Chronic disease; Cognition; Psychological distress
Empirical research spanning several decades has
demonstrated that married people experience a range of
physical and mental health benefits and greater functionality,
self-rated health, and longevity as compared to
nonmarried individuals [
]. Previous research exploring
mechanisms linking marital status and health outcomes
has posited several ways that marriage and health are
causally associated [
1, 7, 8
]. First, marriage may offer
economic, social, and psychological benefits, which may
promote good health. These mechanisms may include
access to sufficient economic resources, social control of
behaviors by one’s spouse, or a sense of social support
within the marital relationship. Second, transitioning to
widowhood may induce significant strain upon a sudden
change in resources, a change which leads to negative
effects . Alternatively, assortative mating based on
health may occur [
]. Also, research has found that
healthier people tend to get married and stay married
while unhealthy people tend to become widowed or
]. Regardless of mechanism, longitudinal
studies have provided evidence of links between earlier
marital status states and marital transitions to later
wellbeing, health-related outcomes, chronic disease and
2, 7, 17–24
] though the direction and
strength of associations vary across studies and
outcomes. Moreover, associations between marital status
and health-related outcomes have remained even after
adjusting for various sets of demographic and
Widowhood is inherently a gendered and cultured
experience as the salience of different mechanisms
linking widowhood to health may depend on gender and on
local norms [
]. Much of the formative research on
marital status and health associations has been
conducted in high-income countries where a substantial
number of studies examining gender differences in the
widowhood-health relationship have found evidence of
worse outcomes for men, [
] findings which are
posited to be due to the loss of social and psychological
support from the wife. However, results are mixed across
the literature [
]. Moreover, research has provided
evidence of variation in the relationships between marital
status and health outcomes across cultures [
Indeed, widowhood may differently affect men and
women across contexts due to differences in gender
norms and marriage traditions. For example, in some
contexts widowhood may lead to increased financial
strain for women while it may lead to increased
household strain for men . That relationship may differ
in other contexts where roles and responsibilities differ
by gender. Moreover, in patriarchal cultures, remarriage
may not be a realistic option for women (particularly
older women), thus forcing older women to remain
widowed and without resources indefinitely [
contrast, men may easily seek remarriage [
]. If a
woman is widowed from a young age without much
ability to remarry due to cultural barriers (particularly
if she already has children), then she may be
economically disadvantaged for life. Alternatively, older men in
some cultures where wives traditionally take care of
men may be less able to cope with a loss of a spouse
for longer periods whereas the existence of strong
family ties (particularly other female familial relationships)
may prevent negative effects in the short-term. In
places where paternalistic norms are pervasive in
everyday life (particularly in patterns of behavior related to
economic opportunities, social activities, marriage
traditions, and reputations), becoming widowed may
severely restrict an individual’s ability to access financial,
affective, informational, or physical resources, which in
turn might affect health outcomes.
In India, a country with strict gender norms and
traditional kinship systems, [
] widowhood is
considered to be a dreaded phase of life among some groups,
particularly for women [
]. Traditionally, the woman’s
main role in India was to care for her husband. Upon
losing her husband, the main purpose to life was lost. As
she belonged to her husband’s family, in-laws frequent
viewed widowed women as a burden. In the past, a
traditional Hindu custom (which is the dominant religion in
India) called for widows to commit suicide upon the
death of their husband, [
] and although the practice is
illegal now, it is still occurs (though obviously with lower
frequency). More recently, the ‘city of widows’ in India
has been highlighted, which is a holy site that is home to
thousands of widowed women who live in dire
circumstances and beg for money [
]. In general,
widowhood for women in India is a very tenuous period of life,
highlighted by significant poverty, lack of social support,
a lack of ability to remarry, and a greater risk of
]. Widowhood for elderly women in
India may be a highly stigmatizing and potentially
public experience as, according to traditional customs,
they may shave their heads, wear only plain or white
clothing, eat only two or fewer meals per day, and
not be permitted to attend social gatherings or to
]. Thus, given historical precedent and
India’s patriarchal society embodying strict norms,
attitudes, and practices that typically affect the social
status of the elderly, and women in particular, [
widowed older women in India may face significant
discrimination (experienced or perceived) as well as a
lack of economic resources [
]. These issues
may in turn affect health outcomes. In this context,
widowhood may present substantial disadvantages for
women if the transition signifies a loss of resources,
particularly in the long-term, though there may be
differences by socioeconomic status and other
demographic factors, as well as by region [
contrast, widowhood may not be associated with health
outcomes for men if other women in the family
immediately take over the daily household chores and
any care the widowed men may need.
Most studies examining health-related outcomes as a
function of marital status among older adults in India
have found worse health to be associated with widowed
status as compared to married status [
studies, however, adjusted for varying sets of covariates and
many of the studies only focused on self-rated health as
the outcome. Moreover, few studies have focused on the
potential health effects of widowhood for men in India.
Yet, as the aging population of India increases in a context
where access to and affordability of social services is
limited for older individuals, [
] it is important to
identify individuals who are more at risk for worse health
outcomes among the general older adult population.
Being widowed represents a relatively easy marker.
Thus, assessing whether there is evidence of a direct
relationship between widowhood and multiple subjective
and objective health-related outcomes and chronic
diseases among older adults in India after adjusting for a
large set of demographic and socioeconomic factors
(such as caste, education, wealth, religion, living with
children, rural/urban location, etc.) is warranted.
Moreover, examining these associations separately for men
and women is critical due to unequal gender norms in
India and also because a higher proportion of men in
India remarry while an increasing fraction of women
remain widows [
]. Finally, no studies of which we are
aware have examined how duration of widowhood is
associated with outcomes among older adults in India.
Yet, men and women recently widowed may experience
worse outcomes than people widowed for much longer.
For example, men who are more recently widowed may
experience stressful transitions and immediate loss of a
known daily support. In the long run, however, they
are likely well-cared for by other female relatives.
Alternatively, women who have been widowed for a long
time may be the worst off due to long-term reduced
access to resources and, perhaps, poor treatment by
their husband’s family. Previous studies from other
countries have revealed a relationship between
duration widowhood and self-reported health,
psychological wellbeing, or other health outcomes, [
] though findings have differed across
populations and outcomes.
The current study attempts to address these gaps in the
literature by providing empirically descriptive answers to
two questions: First, to what extent is widowhood
associated with a variety of health-related outcomes
and chronic diseases among older men and women,
separately, in India, after adjusting for several
demographic and socioeconomic indicators? Second, is there
evidence that widowhood duration matters in these
relationships? We hypothesized that being widowed (without
regards to duration) would be associated with worse
health outcomes for both men and women, even after
adjusting for several indicators of socioeconomic status,
living arrangement, and place, though we thought that
the strength of the relationship would be greater among
women. Moreover, we hypothesized that being widowed
for longer would be associated with an even greater risk
of poor health outcomes for women given a potential
longer period of resource restriction.
We utilized a dataset called “Building Knowledge Base
on Population Ageing in India”, [
] based on older
adults aged 60 years or older from seven states in India
(Himachal Pradesh, Kerala, Maharashtra, Odisha,
Punjab, Tamil Nadu and West Bengal). These states were
purposely chosen during the design of this study as they
represented all regions of India and had a higher
prevalence of elderly individuals as compared to the national
average. In each state, participants were drawn from 40
rural and 40 urban Primary Sampling Units (PSUs),
which were systematically sampled according to a
probability proportional to population size. 16 households
including at least one 60 + year old individual were
sampled per PSU, creating a sample frame of 1,280
households. More detailed information on how
households were selected can be found in the BKPAI report
]. All household residents 60+ years old were
eligible for the study.
From May to September 2011, 8,329 household
interviews were conducted in 560 PSUs (representing a 95 %
household response rate) and 4,672 men and 5,180
women were individually interviewed (leading to a
93 % individual response rate). We only included
adults who were either currently married or who were
widowed (n = 9,615) as the sample sizes for women who
were divorced, separated, cohabiting or never married
were 1 % or less each. The final analytical samples for each
outcome included respondents with no missing values
across explanatory variables or the outcome. Figure 1
provides a flowchart of the final analytical sample sizes and
the number of participants excluded. We chose to exclude
individuals with missing data rather than impute values
for missing responses as there were relatively little missing
data. As the data used for this work were completely
de-identified and publically available for secondary
analysis, the first author’s institutional review board
approved this study and deemed it to be exempt from
full institutional review.
To capture self-rated health, respondents were asked to
rate their current health status on a 5-point scale where
1 = excellent, 2 = very good, 3 = good, 4 = fair, and 5 =
poor. The order was reversed for ease of interpretation
with a value of 1 for poor health and a value of 5 for
excellent health. A binary variable representing ‘poor
health’ was also created where the responses fair and
poor = 1 and excellent, very good, and good = 0.
Psychological distress was measured using the General Health
Questionnaire composed of 12 items [
]. This tool
has been widely used in mental health research and
previous studies have demonstrated its validity and
usefulness in several contexts, including India [
items ask whether the respondent has recently
experienced a particular stressful symptom or behavior. Each
item was rated on a 4-point scale (0 = “less than usual”,
1 = “no more than usual”, 2 = “rather more than usual”,
or 3 = “much more than usual”). Items were rescored
using 0-0-1-1 responses as other studies have previously
done. The items were then summed together with a total
possible score ranging from 0 to 12, which was treated
as continuous variable. A higher score indicated a
greater degree of psychological distress. Probable
‘common mental disorder’ was derived from the
psychological distress score by creating a dichotomous variable
using a cutoff of 5 or less vs. 6 or higher with the latter
indicating a probable common mental disorder’ .
Immediate recall of words was used to measure
cognitive ability [
]. A list of 10 commonly used words was
read out to the respondents, who were then asked to
recall the words within two minutes. The number of
words recalled (0 to 10) was recorded. Therefore, a
higher score represented better cognitive ability.
Four chronic morbidity outcomes were measured by
asking, separately, whether the respondents had ever
been told by a doctor or a nurse that he or she had high
blood pressure (hypertension), diabetes, arthritis, or
asthma (yes/no responses). A binary variable indicating
whether a respondent had been told that he or she had
one or more of those four diseases was created.
For this study, marital status was indicated as either
being currently married (reference group) or widowed.
We also created a second marital status variable where
the widowed category was split into three groups
according to duration of widowhood: 0–4 years, 5–9 years,
or 10+ years. The split between 4 and 5 years was based
on previous rsearch showing differences between the
more recently widowed and the longer-term widows,
] and the split between 9 and 10 years was chosen
because about half of people were widowed beyond that
point. Age was divided into five-year intervals as 60–64
years (reference), 65–69 years, 70–74 years, 75–79 years,
and 80+ years. Respondents indicated a caste (Scheduled
Caste (reference), Scheduled Tribe, Other Backward
Caste, and other caste), and whether they stayed with
children in the same household (reference) or not.
Completed education was categorized as none
(reference), 1–5 years, 6–10 years, and 11 or more years.
Work status was a binary variable categorized as having
worked during the past one year versus not having
worked. Household wealth quintiles were calculated
using information on 30 assets and housing
]. Location of the household in a rural or
urban location and the state was also recorded.
Gender-stratified, multivariable, multilevel linear and
logistic regression analyses were used to estimate the
association between an outcome and widowhood (as
compared to being married) while accounting for the
clustering of observations at the PSU and district levels.
Model 1 used the binary marital status variable and
adjusted for age, caste, living with children, urban/rural
location, and state. Model 2 adjusted for
socioeconomicbased variables including education, work status, and
household wealth in addition to the variables included in
Model 1. Finally, Model 3 was equivalent to Model 2
except it utilized the marital status variable that was
further categorized according to widowhood duration
of less than 5 years, from 5 to 9 years, and 10 or
Table 1 provides descriptive statistics about the sample
and also the average scores of self-reported health,
psychological distress, and cognitive ability across
subcategories of socio-demographic characteristics. For
context, almost two-thirds of the sample population were
within the ages of 60 to 69 years while about 10 % were
80 years or older. In addition, 4 % of men had been
widowed for 0–4 years, 4 % for 5–9 years, and 6 % for
10 years or more. Among women, 14 % had been
widowed for 0–4 years, 13 % for 5–9 years, and 34 % for
10 years or more. Table 2 provides the prevalence
among the sample population of being diagnosed with
each of four chronic diseases (hypertension, diabetes,
arthritis, and asthma), being diagnosed with at least 1
chronic disease, being in poor health, and having a
probable common mental disorder. Among men, 30 % who
were currently married vs. 36 % who were widowed for
10 years or more had at least one chronic disease, 49 to
57 % of men in those same groups reported being in
poor health, and 24 to 35 % had a probable mental
disorder. Among women, the prevalence of being
diagnosed with at least 1 chronic disease, being in poor
health, and having a probable common mental disorder,
separately, was higher among married women than the
associated prevalence among women who had been
widowed for 5 to 9 years.
Table 3 displays the estimated relationships between
widowhood and linear health-related outcomes (scores
of self-rated health, psychological distress, and cognitive
ability, separately), as well as between widowhood and
binary health-related outcomes (being in poor health
and having a probable mental disorder, separately) and
binary indicators of chronic disease (diagnosed with
hypertension, diabetes, arthritis, asthma, and 1 or more
chronic diseases, separately) for men and women
separately. The relationships between widowhood and all
outcomes except for diabetes, arthritis, asthma, and having
1 or more chronic diseases were statistically significant
in Model 1 for women with widowhood being associated
with worse outcomes. The same pattern was found for
men, but only for cognitive ability and having a probable
common mental disorder. Adjusting for socioeconomic
factors in Model 2 attenuated the relationships between
widowhood and outcomes though most of the estimates
remained statistically significant and in the predicted
direction. There was no evidence of widowhood acting
as a protective factor for either gender.
When the widowhood category of marital status was
re-categorized by taking into account widowhood
duration, estimates from Model 3 indicated that only some
categories of widowhood were significantly different in
terms of outcomes as compared to married individuals
(Table 4). Among men, diabetes, cognitive ability, and
having a probable common mental disorder, were
associated with widowhood, but only for widowers of certain
duration. For example, men who were widowed within
0–4 years were more likely to have been diagnosed with
diabetes (AOR = 1.64, 95 % CI = 1.06 to 2.54); men who
were widowed for 5–9 years were more likely to recall
fewer words (b = −0.24, 95 % CI = −0.47 to −0.01) and,
men who had been widowed for 10+ years were more
likely to have a probable common mental disorder
(AOR = 1.38, 95 % CI = 1.01 to 1.88).
Among women, there was evidence of a role for
duration for most outcomes (except for diabetes, and again
arthritis and asthma). For example, women widowed for
4 years or less or for more than 10 years were more likely
to report worse self-rated health (b = 0.14, 95 % CI = 0.06
to 0.22, and b = 0.09, 95 % CI = 0.02 to 0.15, respectively),
and worse psychological distress (b = 0.51, 95 % CI = 0.21
to 0.80, and b = 0.37, 95 % CI = 0.12 to 0.62, respectively),
as well as recall fewer words (b = −0.13, 95 % CI = −0.26
to −0.01, and b = −0.15, 95 % CI = −0.25 to −0.04,
respectively) than married women, separately. In addition,
hypertension was more likely among women who were
recently widowed or who were widowed for a long
time (AOR = 1.52, 95 % CI = 1.22 to 1.90, and AOR =
1.39, 95 % CI - 1.16 to 1.67, respectively). Overall,
results indicated that mostly recently widowed women
and long-term widowed women were at risk for worse
health outcomes compared to married women
whereas women who were widowed for 5–9 years
were no different than women who were married.
Additional file 1: Tables S1–S4 provide the estimates for
the relationships between the other explanatory variables
and outcomes. Age was a strong predictor for all outcomes
for both genders except for diabetes. Men and women
with higher education and higher wealth status were more
likely to have better health-related outcomes and lower
odds of experiencing chronic disease. Wealth status
showed no association with arthritis, asthma, or having
one or more chronic diseases. Living with children was
not associated with any of the outcomes for either men or
women (Additional file 1: Tables S1-S4).
This analysis of marital status and health-related
outcomes and chronic diseases among older adults across
India suggests that, for women, widowhood (as opposed
to being married) may be a risk factor for poor self-rated
health, psychological distress and reduced cognitive
ability, as well as having a probable common mental
disorder and being diagnosed with hypertension, separately.
There is no evidence of these associations among men
except for with cognitive ability and having a probable
common mental disorder. Results did not substantively
change for men or women even after adjusting for
several demographic and socioeconomic factors.
Moreover, examining these associations through a widowhood
duration lens provides evidence that the relationship
between widowhood and health outcomes may be more
nuanced than a simple binary effect (widowed vs. not
widowed). For women, being widowed for a short
amount of time or for the long-term seemed to be worse
for many health outcomes as compared to married
women. In contrast, the relevance of widowhood
duration varied across health outcomes for men though the
health of married men was, for the most part, no
different than the health of widowed men regardless of
More recently widowed older women in India may
struggle to cope with new substantial losses in access to
financial resources and a new (often diminished) social
role within their in-laws or son’s household, which may
negatively affect their health. Not only may women lose
regular economic support when transitioning to
widowhood, they may also be deprived of any inheritance
rights and lose overall purpose within the household. In
contrast, the health of women widowed for an
intermediate amount of time (e.g. 5 to 9 years) may not differ
from the health of married women because these
widowed women have been able to cope (at least
temporarily) with the passing of their spouse, have settled
into a new household context, and are not yet facing the
psychological prospect of having to live for many years
without a new spouse nor having to yet address the
long-term issues of not having access to resources that a
spouse would provide. Perhaps they have found a way to
survive by building new social ties or have taken on new
responsibilities within their husband’s or son’s family. In
addition, survival selection could be playing a role;
women who survived to be widowed 5 to 9 years may,
on average, be healthier than the same cohort of women
when they had only been widowed 4 years or less as the
unhealthiest women in that cohort may have died by the
time this cohort of women became widowed for 5 to
9 years. Finally, the health of women who have been
widowed for 10 or more years may have once again
simply deteriorated in contrast to married women
perhaps because they have both psychologically and
physically remained without resources and spousal support for
a decade, a situation which would likely continue until
they pass away (as they are not likely to remarry).
Critically, regardless of duration, older widowed Indian
women may face an interwoven set of losses and
challenges that affect their health outcomes [
Among men, the situation appears much more varied.
For the most part in India, men’s access to resources
does not change when they become widowed. Instead of
marital status or duration of widowhood, marital quality
might be a better predictor of health outcomes for men.
Interestingly, however, more recently widowed men may
be susceptible to diabetes-related risk factors, such as a
change in diet as wives in India are typically responsible
for household chores, including cooking. The death of a
wife might lead to a worse diet and onset of diabetes at
the beginning before another woman takes over regular
preparation of food for the newly widowed man. In
contrast, men who would have remained widowed for a long
time might have already died or remarried (due to
finding it too difficult) whereas the men who remain single
long after being widowed are perhaps the most resilient.
Importantly, the pathways through which health
outcomes are affected at different points during widowhood
for both men and women warrant further exploration.
Our findings about self-rated health are similar to
previous studies in China and India [
37, 70, 73
]. In addition,
our findings suggesting reduced cognitive ability among
widowed men are similar to a study conducted in three
countries in Europe [
]. However, the present results
indicating a negative relationship between widowhood
and a number of health outcomes for women and a lack
of a relationship between widowhood and most health
outcomes for widowed men are inconsistent with many
studies from high-income countries, which have typically
found a marriage benefit for men and none for women
or for both men and women [
1, 2, 4, 9
]. The results may
be dissimilar in some cases if different mechanisms are
operating to link widowhood and health outcomes across
contexts. When comparing India and high-income
countries like the United States, the United Kingdom, and the
Netherlands, there are significant differences in gender
norms, economic mobility, marriage traditions,
inheritance traditions, and the extent to which government
takes care of certain groups within its citizenry (e.g.
the widowed, the aged, the poor, etc.). Our result
indicating no relationship between psychological distress
and marital status for men was the opposite of the
results from a study of older adults from Korea .
The findings may between these two countries due to
potential differences in gender norms, treatment of
wives, and response to the loss of social support.
An important limitation of this study was our inability
to examine objective markers of health and disease.
Therefore, there are likely undiagnosed cases of mental
distress and chronic disease in our sample. Moreover,
we were unable to adjust for pre-widowhood disease
status, which is likely very important for assessing
determinants of health outcomes after widowhood [
addition, this study does not capture the effect of
widowhood and widowhood duration on overall health
as indicated by mortality. Critical to acknowledge in the
interpretation of these results is that the widowed may
be more likely to die than non-widowed. It could be that
the men in this study are overall a much healthier
population than they would be if the widowed men who had
already died were still alive. Although the same could be
said of the women, men are more likely to die earlier.
Thus, this issue might more strongly bias the findings
about men than the findings about women. Finally, given
the cross-sectional nature of the data, we cannot infer
causality from our associational estimates. Future studies
may clarify the relevance of marital status to health
* p < .05; ** p < .01; ***p < .001. Notes: Model 1 was adjusted for age, caste, living with children, urban/rural, and state. Model 2 was adjusted for all explanatory
variables in Model 1 + education, work status, and household wealth quintile. For all models, estimates also accounted for survey design as a three-level (individual,
primary sampling unit and district) random intercepts model was used
outcomes among older widowed men and women in
India by collecting longitudinal data and biomarkers as
well as information on the quality of marital
relationships and information about gender norms and sex roles
within the household.
This is the first study to our knowledge that reports on the
association between widowhood and several mental and
physical-related health outcomes, as well as self-rated
health, among a large sample of older adults across India,
while adjusting for many demographic and socioeconomic
characteristics. Our study suggests important gender
differences in how widowhood is associated with self-rated
health, psychological distress, hypertension, and diabetes
among older adults in India with recent and long-term
widowhood predicting worse health for women, but not for
men. Incorporating information about marital relationships
into the design of intervention programs may help better
target potential beneficiaries among older adults in India.
Additional file 1: Multilevel linear and logistic regression that estimates
the relationships between explanatory variables and outcomes.
(XLSX 56 kb)
AOR: Adjusted odds-ratio; CI: Confidence interval; PSU: Primary sampling unit
The authors have no support or funding to report.
Availability of data and materials
Data for this study were sourced from the “Building Knowledge Base on
Ageing in India (BKBAI)” survey. These data will be made available upon
request to Population Research Center at Institute for Social and Economic
Change in India ().
JMP, SVS conceived the study. JMP wrote the first draft and led the writing.
HL led the data analysis, and contributed to the literature review,
interpretation and writing. KSJ, JO, AK, JH, JL and SVS contributed to
interpretation and critical revisions. SVS provided overall supervision. All
authors read approved the final manuscript.
The authors declare that they have no competing interests.
Consent for publication
Not applicable. No details, images or videos related to individual participants
were obtained. In addition, data are available in the public domain.
Ethics approval and consent to participate
This study was determined to be ‘Not Human Subjects Research’ by the IRB
council of the Harvard Human Research Protection Program (IRB15-2220).
This study only conducts secondary data analysis with de-identified data.
The data are available in the public domain.
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