This study revealed apparent, independent and “dose-effectiveness” trend in the relationships between LEI and relative risks for reporting CPCs among LBFs. This is noteworthy given that most previous research findings in this regard have been inconclusive [7, 9, 10, 15]. This may due largely to the methods used in combining individual LE items into a single index (LEI) and psycho-social contexts of the subjects we had studied. Both counting the number and summing up the Likert scale ratings of LEs, as being applied in most contemporary studies, treat all individual LEs as equal. This is often inappropriate, since the impact of different LEs varies greatly [16, 38]. Weighing the LE items according to multivariate logistic regression coefficients seemed to be an effective approach in assessing collective effects of multiple items of LEs. Our analysis showed that the majority of the RRs between LBFs grouped according to regression coefficients-based LEI were greater than that grouped according to Likert scale sum. Besides, the factors causing the farmers to be left behind may also have important psychological significances. Being less capable or confident in finding jobs in cities may also mean poorer resources, ability and efficacy etc. for copying with LEs. And, as mentioned earlier, being left behind parallels long-term separation and lack of helps and care from family members, which may all be profound LEs themselves. The number (i.e., 15) of subgroups used for paired-comparisons to disclose RRs/ORs of the CPCs was a balanced consideration of two factors. On one hand, larger number of subgroups means larger potential LEI discrepancies between the baseline and the remaining groups (e.g., the first vs. the last group) and hence larger chances for finding greater mean RRs/ORs. On the other, as the number of subgroups increases, the number of LBFs falling into each subgroup decreases and thus reduces the power for identifying statistically significant differences. In addition, the general trend of greater ORs among the LBFs aged 40–55 years than that among those aged 56–70 years may suggest potential differences in the magnitude and/or mechanisms of LE effects across the stages of life course.
Another point worth noting referrers to the huge discrepancies in the RRs or ORs for different CPCs, e.g., from RR = 1.58 (1.29, 1.94) in our bivariate analysis (or OR = 1.65, in our multi regression analysis) for hypertension to RR = 55.00(7.67, 394.57) (or OR = 78.51) for “other CPCs”. Although numerous studies have already documented similar results (e.g., Quendo MA et al. reported OR = 4.83 for suicidal behavior; while Pietrzak and colleagues, OR = 1.8 for gastritis), this study provided a good opportunity for comparing LE effects on different health problems [39, 40]. Contrary to most previous studies, which generally focused on a singular health problem, this study included a set of CPCs at the same time and thus enabled generating RRs/ORs of different diseases from a same research design, LE instrument, population group etc. The RRs/ORs of some specific CPCs (e.g. prostatitis, cervicitis/vaginitis and chronic gastritis) turned out to be apparently higher than that of others (e.g. diabetes and hypertension). This may be attributed partly to differences in the paths from LEs to different CPCs as mentioned earlier and partly, differences in the prevalence rates of the CPCs that may result in different chances of random errors. One possible explanation for the only null relationship between LEI levels and RRs/ORs of diabetes may be that some of the previously diagnosed diabetics may have been taking glucose lowering medications and/or practicing lifestyle modifications that had resulted in lower FCG. This may also apply to the relatively low RRs/ORs of hypertension.
The third point worth noting concerns a subtle yet important difference between the effects of LEs assessed in this study and that in contemporary ones. Most previous studies asked occurrence of LEs within a limited period (typically 1–2 years) before a given time point (usually when the first wave field data collection was executed) and onset of certain diseases afterwards [7, 11]. Such a research design may be advantageous for probing causal relations; yet it considers only limited LEs and incomplete (mostly immediate but long-term) health effects. This study analyzed relationships between “life-time” LEs and occurrence of the CPCs in the previous year and therefore took into account accumulated effects of all the LEs on the CPCs studied. Given that chronic diseases generally develop over many years, exploring the long-term accumulative effects of LEs may be more important than the immediate effects. And inferring from the various pathways linking LEs to health problems summarized in the introduction section, there are reasons to believe that LEs can have such long-term effects. For example, schooling/ examination failures may not only have immediate health effects (within a few months after the event) but also sustained or repeated effects under certain circumstances. Schooling/examination failures in China determine whether or not an individual can enter most wanted study programs, professions or jobs and are valued high by all Chinese; and these examinations are repeated annually and are widely covered by the media each time. These may make those who had failed the same examinations recall their own failures year after year and thus cause repeated distresses or bad feelings. Schooling/examination failures may lead to higher life-time risk of other potential LEs (e.g., social discriminations, bad job performances, low self-esteem). Schooling/examination failures may also mean less life-time ability coping with potential LEs. In addition, schooling/examination failures may be linked with increased unhealthy behaviors including smoking, sex for money/shelving, low fruit and vegetable intake, under-utilization of health services etc.
The fourth point worth mentioning relates to the LE instrument used. It consisted of 20 items designed as an interviewer-administered questionnaire to suit highly illiterate LBFs. As mentioned earlier in the methods section, each of the instrument items divided into two parts, i.e. a “judging” question followed by a “rating” question (Additional file 1). This arrangement facilitated the interview process since: a) the “judging” question with the simplest responses (“Yes” or “No”) enabled rapid skipping of unnecessary “rating” questions; b) the identical “rating” questions made, after completion of the first few items, the respondent readily prepared for what to response after he/she had given an “Yes” answer. As a result, the instrument administration took only about 5 to 10 min. The standardized CronBach α (0.80) suggests that the instrument is quite reliable; while the correlations coefficients (from −0.037 to 0.291) between the 20 LEs (Additional file 2) indicate that all the items included in the instrument are relatively independent.
In addition, this study documented preliminary information about the prevalence of the CPCs and LEs among all the LBFs and different subgroups. For instances, the study found that: a) the prevalence of hypertension was apparently higher among the LBFs (43.2 %) than the national average (26.6 %) of the same age range [41]; b) about 31 % of the LBFs were tested with pre-diabetes yet had never known their glucose status before; c) “loss of relatives’, “financial hardship”, “over worries about children”, “major injuries/diseases of relatives” and “natural disasters” were most prevalent among the LBFs. Putting together, these findings and others not only call for attention to LE-related issues among LBFs, a newly emerged and thus relatively neglected weak group in vast rural China, but also inform similar studies in the future.
The current study has several strengths. First, it explored the relationships between LEs and CPCs among emerging and relatively neglected weak group. Second, it utilized a tailored instrument for assessing LEs and their effects. Third, it produced and compared two indices for evaluating the cumulative effects of LEs. Fourth, it focused on LEs happened during lifetime rather than within a limited period before a given time point.
This study also suffers from limitations. First, except for hypertension, diabetes and pre-diabetes, the remaining CPCs were all reported chronic conditions that had been diagnosed by doctors before the interview. This raises a number of concerns about biases: a) the criteria used for diagnosing the CPCs may be different across service providers; b) the recall ability and service seeking behavior may differ across LBFs. Second, the relationships between LEs and CPCs are bidirectional in nature and readers are cautioned about the difficulties in inferring cause-and-effect relations using data derived from the cross-sectional design [34, 35]. Third, the current study solicited information about life-time LEs and CPCs diagnosed within the past year. Such a research design makes it difficult to tell whether some of the LEs happened before or after the CPCs, though this difficulty applies to only a very small proportion 1.4–2.5 % (i.e., 1/40 to 1/70) of all the LEs experienced by the LBFs. Fourth, after decades of the internal migration, a highly selective process, the LBFs studied characterized lower education, poorer health and over representation of females etc. These all have implications for interpreting and generalizing the findings. Fifth, the over-representation of female LBFs may bias our findings from a comparative stand point. For example, it may be inappropriate to compare the prevalence rates of LEs and CPCs among our study population as a whole and populations with approximately equal gender compositions. Sixth, although the regression model-based weighing of individual LEs has resulted in seeming better findings than that of traditional methods, it needs to be further validated since there is little previous literature endorsing the method. Last, the study site, Lu’an, locates in the middle of China. It represents typical inland rural areas in the country. Yet the findings should be generalized with caution to costal or boarder areas of the country.
Conclusions and implications
LEs among LBFs in rural Anhui, China were independently related to most common CPCs in a dose-effectiveness way. This relationship varied greatly across CPCs. And RRs between subgroups of LBFs divided by given percentile cutoff points of LEI compiled using logistic regression models turned out to be substantially higher than that between subgroups divided by same cutoff points of LEI produced via summing up the Likert ratings of all the events studied.
These findings have important implications for clinicians and policymakers. Clinicians, especially those in rural areas, may need to bear in mind the significance of LEs to the health of their patients and take LE history into account in preventing, diagnosing and treating CPCs. Similarly, policymakers may need to be fully aware of the radical changes in the composition of farmers, the high prevalence of CPCs among them and the roles of LEs in the epidemics, and take concrete measures in reforming rural health services and addressing LE-related health problems.