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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Determinants of internal migrant health and the healthy migrant effect in South India: a mixed methods study
|
|---|---|
| Published in |
BMC Public Health, September 2017
|
| DOI | 10.1186/s12914-017-0132-4 |
| Pubmed ID | |
| Authors |
Warren Dodd, Sally Humphries, Kirit Patel, Shannon Majowicz, Matthew Little, Cate Dewey |
| Abstract |
Internal labour migration is an important and necessary livelihood strategy for millions of individuals and households in India. However, the precarious position of migrant workers within Indian society may have consequences for the health of these individuals. Previous research on the connections between health and labour mobility within India have primarily focused on the negative health outcomes associated with this practice. Thus, there is a need to better identify the determinants of internal migrant health and how these determinants shape migrant health outcomes. An exploratory mixed methods study was conducted in 26 villages in the Krishnagiri district of Tamil Nadu. Sixty-six semi-structured interviews were completed using snowball sampling, followed by 300 household surveys using multi-stage random sampling. For qualitative data, an analysis of themes and content was completed. For quantitative data, information on current participation in internal labour migration, in addition to self-reported morbidity and determinants of internal migrant health, was collected. Morbidity categories were compared between migrant and non-migrant adults (age 14-65 years) using a Fisher's exact test. Of the 300 households surveyed, 137 households (45.7%) had at least one current migrant member, with 205 migrant and 1012 non-migrant adults (age 14-65 years) included in this study. The health profile of migrant and non-migrants was similar in this setting, with 53 migrants (25.9%) currently suffering from a health problem compared to 273 non-migrants (27.0%). Migrant households identified both occupational and livelihood factors that contributed to changes in the health of their migrant members. These determinants of internal migrant health were corroborated and further expanded on through the semi-structured interviews. Internal labour migration in and of itself is not a determinant of health, as participation in labour mobility can contribute to an improvement in health, a decline in health, or no change in health among migrant workers. Targeted public health interventions should focus on addressing the determinants of internal migrant health to enhance the contributions these individuals can make to their households and villages of origin. |
X Demographics
The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Canada | 1 | 33% |
| Unknown | 2 | 67% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 67% |
| Scientists | 1 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 117 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 117 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 24 | 21% |
| Student > Master | 13 | 11% |
| Researcher | 8 | 7% |
| Student > Doctoral Student | 7 | 6% |
| Lecturer | 6 | 5% |
| Other | 13 | 11% |
| Unknown | 46 | 39% |
| Readers by discipline | Count | As % |
|---|---|---|
| Social Sciences | 24 | 21% |
| Nursing and Health Professions | 10 | 9% |
| Medicine and Dentistry | 8 | 7% |
| Agricultural and Biological Sciences | 4 | 3% |
| Economics, Econometrics and Finance | 4 | 3% |
| Other | 17 | 15% |
| Unknown | 50 | 43% |
Attention Score in Context
This research output has an Altmetric Attention Score of 4. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 01 April 2018.
All research outputs
#8,476,767
of 25,382,440 outputs
Outputs from BMC Public Health
#9,372
of 17,517 outputs
Outputs of similar age
#124,298
of 323,484 outputs
Outputs of similar age from BMC Public Health
#103
of 170 outputs
Altmetric has tracked 25,382,440 research outputs across all sources so far. This one has received more attention than most of these and is in the 66th percentile.
So far Altmetric has tracked 17,517 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 14.4. This one is in the 46th percentile – i.e., 46% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 323,484 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 61% of its contemporaries.
We're also able to compare this research output to 170 others from the same source and published within six weeks on either side of this one. This one is in the 38th percentile – i.e., 38% of its contemporaries scored the same or lower than it.