Health-Related Practices of Urban Migrant Workers in Metro Manila: Determinants and Outcomes Kenneth Jim Joseph Jimeno, MHSS, RN Behavioral Sciences Department, College of Liberal Arts De La Salle University–Manila kenneth_jimeno@dlsu.edu.ph INTRODUCTION Table 4. Association of civil status and HRP Fisher’s exact Cramer’s V Interpretation HRP Physical Activity Nutrition Sleeping Pattern .191 .040 .891 .568 .2560 .2585 .1076 .1252 Not significant Significant There are an estimated 1 billion migrants in the world today of whom 214 million international migrants and 740 million internal migrants (IOM, 2013). In the Philippines, external migrants constitute only 4.5% of all migrants (Philippine Statistics Authority, 2012). Two-thirds of the world population will be residing in cities by 2050 (UNDESA, 2014). There is an immediate concern on the impact of urban migration in the healthcare system (Mou et al., 2015). No study in the Philippines to date that has explored this topic in the advent of growing mobility across cities and adjacent areas. This study aims to describe the health-related practices of urban migrant workers in Metro Manila. It also ascertains the relationships of health-related practices with personal characteristics and health condition. In addition, the study determines the correlation between health condition and work performance Table 5. Correlation of educational attainment and HRP Spearman’s rho (rs) p-value Interpretation HRP Physical Activity Nutrition Sleeping Pattern .1959 .0503 .0133 .1836 .0327 .5869 .8857 .0456 Significant Not significant Table 6. Association of occupation type and HRP Table 7. Correlation of income level and HRP Fisher’s exact Cramer’s V Interpretation HRP Physical Activity Nutrition Sleeping Pattern .033 .006 .063 .042 .2943 .3346 .2685 .2731 Significant Not significant Spearman’s rho (rs) p-value Interpretation HRP Physical Activity Nutrition Sleeping Pattern +.0123 −.1154 −.2175 +.2082 .8946 .2112 .0175 .0231 Not significant Significant Table 8. Association of residential arrangement and HRP Fisher’s exact Cramer’s V Interpretation HRP Physical Activity Nutrition Sleeping Pattern 0.944 0.870 0.155 0.845 0.1345 0.1429 0.2435 0.1239 Not significant METHODOLOGY Table 9. Correlation matrix of HRP and health condition   HRP Physical Activity Nutrition Sleeping Pattern Health Condition 0.1481 (0.1079) −0.0516 (0.5771) −0.0504 (0.5863) 0.3711 (0.0000) Not significant Significant Physical Health 0.0024 (0.9791) 0.0216 (0.8160) 0.0293 (0.7521) 0.1178 (0.2019) Psychological Health 0.1393 (0.1309) −0.1194 (0.1960) −0.1902 (0.0383) 0.3771 Emotional Health 0.1463 (0.1124) 0.0035 (0.9696) −0.0275 (0.7665) 0.2236 (0.0145) Social Health 0.1379 (0.1347) −0.0172 (0.8527) 0.0070 (0.9394) 0.0909 (0.3254) Research Design Cross-sectional, correlational study Population & Sampling Purposive sampling Inclusion criteria: Filipinos working regularly in Metro Manila; Living outside Metro Manila or returning back to place of origin every week; Age of at least 18 years; No functional limitation. Instrumentation 53-item self-administered survey questionnaire Primary outcome: 5-point Likert scale indicating frequency of engagement Data Analysis Spearman’s rank correlation coefficient or Spearman’s rho (rs) Fisher’s exact and Cramer’s V (for nominal-ordinal variables) Stata/MP version 14.0 Association/correlation is significant when P <.05 Table 9. Correlation matrix of health condition and work performance   Health Condition Physical Health Psychological Health Emotional Health Social Health Work Performance 0.1940 (0.0345) 0.0399 (0.6668) 0.1023 (0.2681) 0.0974 (0.2918) 0.3901 (0.0000) Significant Not significant Productivity 0.1859 (0.0429) 0.0945 (0.3068) 0.0203 (0.8269) 0.0642 (0.4880) 0.3612 (0.0001) Adherence to Rules 0.2392 (0.0088) −0.0093 (0.9199) 0.1239 (0.1794) 0.1376 (0.1355) 0.3038 (0.0008) RESULTS CONCLUSION Sociodemographic Profile 119 respondents mostly from Bulacan (n=80), Rizal (n=16) and Cavite (n=11) Majority of them were working in Quezon City (n=56) and Manila (n=21) Education and occupation are major determinants of health-related practices among urban migrant workers in Metro Manila. Sleep tends to have the most impact on health while interpersonal relationships affect work performance. Healthy migrant hypothesis appears true for this population and the results can be attributed to resiliency, family-oriented values, and importance of harmonious relationships in Filipino culture. The findings of this study can be used in developing migrant-sensitive health system in cities and further inquiry in this emerging research field. RECOMMENDATIONS Table 1. Personal characteristics of urban migrant workers Future Research A cohort study tracking the exposure of urban migrant workers will be more appropriate to establish the causality. Exploration of other practices that are perceived to contribute to their health condition and work performance through qualitative study is important. Tracing proximate determinants would help in identifying the links among variables and understanding the collective behavior of migrant workers in cities. Program Intervention Establish a government agency to offer specialized services to urban migrant workers. Conduct training on the nexus of urbanization, migration, and health for practitioners. Develop partnerships and networks in resource-poor settings. Frequency (n=119) Percentage (%) Age 18 to 25 y/o 26 y/o & above   68 51 57.14 42.86 Sex Male Female 71 48 59.66 40.34 Civil Status Single Married 111 8 93.28 6.72 Education Non-college College Postgraduate 13 94 12 10.92 78.99 10.08 Frequency (n=119) Percentage (%) Occupation Blue-collar White-collar   50 69 42.02 57.98 Income (Monthly in PHP) 15 000 & below 15 001 to 30 000 Above 30 000 (1 USD = 50 PHP) 56 52 11 47.06 43.70 9.24 Residential Arrangement Alone With family With relatives With friends or colleagues 13 90 8 10.92 75.63 6.72 Table 2. Correlation of age group and HRP Spearman’s rho (rs) p-value Interpretation HRP Physical Activity Nutrition Sleeping Pattern −.0427 −.1891 −.1955 −.0022 .6447 .0394 .0331 .9814 Not significant Significant