| Literature DB >> 26228911 |
Giuliano Russo1,2,3, Luzia Gonçalves4,5,6, Isabel Craveiro7,8,9, Gilles Dussault10,11,12.
Abstract
BACKGROUND: Women represent an increasingly growing share of the medical workforce in high-income countries, with abundant research focusing on reasons and implications of the phenomenon. Little evidence is available from low- and middle-income countries, which is odd given the possible repercussion this may have for the local supply of medical services and, ultimately, for attaining universal health coverage.Entities:
Mesh:
Year: 2015 PMID: 26228911 PMCID: PMC4521355 DOI: 10.1186/s12960-015-0064-9
Source DB: PubMed Journal: Hum Resour Health ISSN: 1478-4491
Selected characteristics for the three study locations
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| Country’s GDP per capita (PPP)a | 1186 | 942 | 3984 |
| Total health expenditures per capita (current prices, 2010) | 46.9 | 21.3 | 154.6 |
| Position in the HDI (out of 187)b | 176th | 184th | 133rd |
| Physicians registered in the countryc | 172 | 1105 | 400 |
| Physicians residing in the countries’ capital citiesc | 127 | 487 | 131 |
| Population in capital citiesc | 387 908 | 1 178 116 | 131 453 |
| Physician density in capital cities (per 100 000 population) | 3.27 | 6.64 | 9.96 |
Sources: a The World Bank (2012); b UNDP (2011); c National Medical Councils (2012), National Statistical Institutes.
Physician sample’s characteristics by city and gender
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| Age (median years) | 47 | 37 | 0.001 | 46 | 36 | 0.001 | 45 | 37 | <0.001 | 49 | 48 | 0.11 |
| Dependents (median) | 4 | 2 | <0.001 | 2 | 1 | 0.032 | 3 | 2 | 0.049 | 8 | 4 | <0.001 |
| Married (% yes) | 81.4% | 64.1% | 0.368 | 68.8% | 59.7% | 0.327 | 80.3% | 73.4% | 0.212 | 91.2% | 51.9% | <0.001 |
| Having a physician in the family | 35.0% | 60.3% | <0.001 | 51.1% | 58.7% | 0.158 | 29.5% | 50.8% | 0.016 | 29.0% | 73.1% | <0.001 |
| Working as a physician also outside the capital | 18.6% | 15.0% | 0.657 | 27.7% | 12.9% | 0.053 | 19.7% | 18.8% | 0.896 | 11.6% | 11.1% | 1.000(a) |
| Holding a specialization | 76.3% | 52.3% | 0.004 | 74.5% | 58.1% | 0.075 | 70.5% | 42.2% | 0.001 | 82.6% | 63.0% | 0.039 |
| Public sector only | 41.8% | 42.8% | 0.254 | 31.% | 38.7% | 0.259 | 36.1% | 48.4% | 0.373 | 53.6% | 38.5% | 0.008 |
| Private sector only | 10.2% | 12.5% | 0.657 | 17.0% | 9.7% | 0.373 | 4.9% | 7.8% | 0.260 | 10.1% | 30.8% | 0.165 |
| Dual practice | 48.0% | 44.7% | 0.456 | 51.1% | 51.6% | 0.345 | 50.0% | 43.8% | 0.567 | 36.2% | 30.8% | 0.458 |
| Weekly working hours (public and private) | 53.88 | 50.23 | 0.025 | 52.98 | 51.11 | 0.530 | 51.40 | 49.54 | 0.522 | 56.77 | 49.81 | 0.008 |
| Public sector pay (2012 USD) | – | – | – | 1472.48 | 1362.87 | 0.144 | 1056.15 | 887.36 | 0.030 | 386.96 | 360.12 | 0.577 |
Note: quantitative variables: Mann–Whitney test; qualitative variables: chi-square test or the alternative (a) Fisher exact test.
Figure 1Age distribution of physician population in the three locations, by gender.
GLM on hours worked per week in public and in private sector
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| (Intercept) | 3.998 | 0.070 | 57.057 | <0.001** |
| City (Maputo, Mozambique) | −0.039 | 0.038 | −1.013 | 0.3113 |
| City (Bissau, Guinea-Bissau) | 0.039 | 0.041 | 0.942 | 0.3460 |
| Q2 gender (sex: female) | −0.077 | 0.034 | −2.255 | 0.0242* |
| Q3 civil status (not married) | −0.004 | 0.037 | −0.101 | 0.9292 |
| Q4 dependents (yes) | 0.103 | 0.057 | 1.803 | 0.0715 |
| Q8 specialization (yes) | −0.062 | 0.038 | −1.637 | 0.1016 |
| Q6 years as a medical doctor (by 5-year increases) | −0.023 | 0.001 | −2.358 | 0.0184* |
*: P < 0.05; **: P < 0.001; P = 0.10 AIC = 2557.9.
Deviance residuals: min. −4.29, max. 2.83; median: −0.029.