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We investigated whether offspring protect or jeopardize in parents.
Methods
We used data from the Korean Longitudinal Study of Aging and performed a longitudinal analysis of 10,236 individuals at baseline (2006) to estimate the association between offspring-related factors and self-rated health among individuals ≥45 years of age.
Results
The estimate for self-rated health was 0.612 times lower (95% confidence interval [CI], 0.503–0.746; P<0.0001) for those with zero offspring. The estimate for self-rated health was 0.736 (95% CI, 0.635–0.853; P<0.0001) for those with five offspring or more. The estimate for self-rated health was 0.707 (95% CI, 0.528–0.947; P=0.020) for males with zero offspring. The estimate for self-rated health was 0.563 (95% CI, 0.422–0.751; P<0.001) for females with no offspring and for females with five or more offspring. The estimate for self-rated health was 0.686 times lower (95% CI, 0.573–0.822; P<0.0001) for those with five or more offspring compared to females with two offspring.
Conclusion
Those with more offspring (≥5) and those with no offspring tended to have an increased probability of low self-rated health. Overall, our results suggest that offspring have a significant positive effect on self-rated health, which was evident graphically as an inverted U-shape.
Self-rated health (SRH) is a health measure used to rate participants’ general health by asking them a simple question. This question has frequently been employed as a health indicator in sociological health research since the 1950s [1] and has been proposed as a general health assessment screening tool [2].
According to several previous studies, SRH is considered a good indicator of future health and health care utilization [3,4]. Moreover, poor SRH has been shown to predict health outcomes such as mortality or objective health status [2]. SRH does not focus on a specific dimension of health, but rather provides a succinct means of summarizing the diverse components of an individual’s health [5].
SRH is an inclusive measure of health that yields information inaccessible by targeted health measurements and has increased its popularity in population-based and clinical studies [2]. Negative health ratings seem to represent pathogenetic biological processes that compromise health status and may herald future health adversity [2].
Socioeconomic status may be an important determinant of health perception; higher perceived socioeconomic status is protective against a poor health perception and psychosomatic symptoms. This is in comparison to “objective” socioeconomic indicators, such as parental education or employment status [6-8]. Among health behaviors, dietary habits, exercise, smoking, and alcohol use are related to SRH [9,10].
Arguments have been proposed both for and against a positive effect of offspring on health outcome [11]. Offspring provide social support and care within the family and social network. In addition, a greater number of offspring may prevent loneliness and provide parents with feelings of a meaningful life, which might positively affect mental health [12]. In contrast, because the role of parents is physically and mentally demanding, offspring can also be a source of strain when they are young. Therefore, parents can be particularly vulnerable to health problems such as mental disease [13]. As such, we determined whether offspring protect or jeopardize their parents’ SRH.
METHODS
1. Sample
We used data from the 2006 Korean Longitudinal Study of Aging (KLoSA), which was performed by the Korean Labor Institute and funded by the Korean Ministry of Labor. The population of KLoSA participants included adults ≥45 years of age and resident in 15 large administrative areas. Although surveys of the elderly in other countries have studied adults ≥50 years of age, KLoSA extended its population group to include those aged 45–49 years to account for career changes during middle age. This has been an important social issue since the financial crisis in the late 1990s, which caused many people in the 45–49-year age group to become unemployed.
The present study used a sample from the first through fourth waves of data from the KLoSA, which was conducted by the Korean Labor Institute to collect basic data needed to devise and implement effective social and economic policies that address emerging trends related to population aging. KLoSA results are available on a national public database (website: http://survey.keis.or.kr) and the study was repeated every even-numbered year until 2012.
This study did not require an ethical review since the KLoSA dataset was publicly opened and information that could be used for individual identification was removed.
In the first baseline survey conducted in 2006, 10,254 individuals in 6,171 households (1.7 per household) were interviewed using a computer-assisted personal interviewing method. The second survey in 2008 followed up with 8,688 subjects, representing 86.6% of the original population. The third survey in 2010 followed up with 7,920 subjects who represented 80.3% of the original panel. The fourth survey in 2012 followed up with 7,486 subjects who represented 76.2% of the original panel.
Of these participants, we excluded 18, 9, 6, and 7 subjects in 2006, 2008, 2010, and 2012, respectively, due to a lack of information. Thus, a total of 10,236 subjects was selected for this analysis from the baseline survey conducted in 2006 (Figure 1).
2. Study Variables
1) Dependent variable
Self-reported data regarding SRH were extracted from the response to the question “how have you usually perceived your health status in the last year?” Responses to the question were categorized as either “good” or “bad” responses of “very good,” “good,” and “normal” indicated “good,” and responses of “poor” and “very poor” indicated “bad.”
We used the number of offspring and the composition of the offspring (gender, number of grandchildren, proportion of cohabitation) as independent variables. Proportion of cohabitation was the number of offspring living with their parents divided by the total number of offspring in five categories: no cohabiting offspring, ≤24.9, 25.0–49.9, 50.0–74.9, and ≥75.0. Average offspring age was divided into four categories: Q1 (≤27.5 years old), Q2 (27.6–36.0 years old), Q3 (36.1–44.0 years old), and Q4 (≥44.0 years old). In addition, the number of grandchildren was included as a covariate.
3) Control variables
The age groups of participants were as follows: ≤49, 50–54, 55–59, 60–64, 65–69, 70–74, and ≥75 years of age. Education status was divided into four categories: less than or completed elementary school, middle school, high school, and college or more. Individuals were classified as married or single, and the latter group included those married previously, widowed, or divorced. Income status was divided into two categories: yes, the participant received income or no, they did not. The number of interactions with friends was divided into five categories: every day, 1–2 times/wk, 1–2 times/mo, 3–6 times/y, and never. Economic activity status was divided into two categories, namely employed or unemployed. In addition, health status and behavioral variables (smoking status, alcohol use, and depressive symptoms) were included as covariates. Finally, number of chronic diseases (including hypertension, diabetes, arthritis or rheumatoid arthritis, cancer, chronic obstructive pulmonary disease, liver disease, heart disease, cerebrovascular diseases, and mental illness) was categorized into three groups: 0, 1, and ≥2.
3. Analytical Approach and Statistics
A chi-squared test and a longitudinal data analysis were conducted. We ran a generalized linear mixed model (GLIMMIX) with the binary distribution, which controls for the characteristics of individuals that change over time, such as confounding variables, with the exception of sex. To determine whether the probability of all covariates including SRH changed over time, we included time (year) in the model as a categorical covariate; the regression coefficient was used to estimate both the change in probability of SRH and independent variables annually. The criterion for significance was a two-tailed P≤0.05. All analyses were conducted using the SAS statistical software ver. 9.2 (SAS Institute Inc., Cary, NC, USA).
RESULTS
Table 1 lists the general characteristics of the covariates included in this study according to SRH at baseline (2006). There were 10,236 research samples.
The weighted prevalence of bad SRH at baseline for those with: zero offspring was 3.6%, one offspring was 8.8%, two offspring was 40.6%, and five or more offspring was 12.1% (Table 1).
Table 2 shows the adjusted effect of the number of offspring on SRH according to sex of the participants. The estimate for SRH for those with zero offspring was 0.612 (95% confidence interval [CI], 0.503–0.746; P<0.0001) compared to those with two offspring. The estimate for SRH for those with five or more offspring was 0.736 (95% CI, 0.635–0.853; P<0.0001), compared to those with two offspring. The estimate for SRH for males with zero offspring was 0.707 (95% CI, 0.528–0.947; P=0.020) compared to those with two offspring. The estimate for SRH for females with zero offspring was 0.563 (95% CI, 0.422–0.751; P<0.001) compared to females with two offspring. The estimate for SRH for females with five or more offspring was 0.686 (95% CI, 0.573–0.822; P<0.0001) compared to females with two offspring.
Table 3 shows the adjusted effect of offspring composition on SRH according to sex. The estimate for SRH for males with no offspring was 0.808 (male 95% CI, 0.691–0.946; P<0.0001) and 0.768 (female 95% CI, 0.670–0.880; P<0.000) compared to those with two offspring. The estimate for SRH for females with four or more female offspring was 0.834 (95% CI, 0.697–0.997; P=0.047).
DISCUSSION
Our primary purpose was to investigate the impact of offspring on SRH in a longitudinal model using a nationally representative sample of adults ≥45 years of age in South Korea. Our results show that those with more offspring (≥5) and those with no offspring tended to have an increased probability of low SRH. Overall, our results suggest that the number of offspring has a relatively large and significant positive effect on SRH, which was evident graphically as an inverse U-shape.
These associations between SRH and offspring were independent of offspring-related variables (number of grandchildren, proportion of cohabitation, and average age of offspring), sociodemographic variables (age, sex, education, marital status, number of interactions with friends, income, and economic activity status), health risk behavior variables (smoking status and alcohol consumption), health status (depressive symptoms and number of chronic diseases), and year.
Previous studies of the association between offspring and health outcomes have shown that a variety of offspring-related factors affect health outcomes. For example, one previous study showed a high possibility of risk for those with five or more offspring and those who had an adolescent birth [14].
Although substantial evidence is available regarding the effect of offspring on specific physical health outcomes such as chronic diseases that occur frequently [15,16], our research has used general health measures, such as an individual’s SRH [17], to predict future health status.
In general, the simple question, “How would you rate your health? Poor, fair, good, very good, or excellent?” is typically labeled as SRH, and is also known as self-assessed health, self-evaluated health, subjective health, or perceived health. The exact wording and response options for SRH questions vary. The question most widely used in the US has responses on a scale including “excellent,” “very good,” “good,” “fair,” and “poor,” whereas the options recommended by World Health Organization [18] and the EURO-REVES 2 group [19] are “very good,” “good,” “fair,” “bad,” and “very bad.” Another version uses the options “very good,” “fairly good,” “average,” “fairly bad,” and “bad.” [20] Although the levels and distributions are not directly comparable between these different measures, they represent parallel assessments of the same phenomenon, and show basically concordant answers [21].
Idler and Benyamini [22] proposed four explanations for the validity of SRH as a predictor of future health outcomes: (1) SRH is more inclusive than covariates used in many studies, (2) SRH is a dynamic evaluation that judges the trajectory of health and not only current health at a defined point in time, (3) SRH influences behavior that subsequently affects health status, and (4) SRH is influenced by the use of resources that reflect or even affect the ability to cope with health threats.
One possible explanation for our results, based on a previous study, is that raising offspring is associated with direct costs, such as nutrition and education, and opportunity costs. Opportunity costs may possibly be generated by reducing parents’ time on the job and thus the higher probability of profit. Less time on the job results in reduced earnings and a high possibility of experiencing poverty, which is associated with negative health outcomes [23-25].
Offspring from a multiple birth increase the probability of suffering financially and increase a female’s probability of experiencing periods of particularly bad overall health [26]. Females with no offspring often express feelings of emptiness and loneliness, and can feel demoralized. Although the strict sanctions against not having children have abated somewhat, the norms of desirability of having offspring remain strong. Nevertheless, a number of theorists and researchers have challenged the view that offspring increase well-being.
A few strengths and limitations of this study should be mentioned. One of the strengths is that the participants may be representative of relatively older adults (≥45 years). Second, our results were estimated through longitudinal data, which are surveyed annually. We obtained a large sample size, so the results can be generalized to older South Korean adults. Nevertheless, we do acknowledge possible limitations. The first problem is that respondents’ reports are subjective, imperfect, and potentially affected by false consciousness and adaptation of resources. Second, because personality characteristics are likely associated with SRH, failure to include them in the statistical models could lead to an exaggeration of the association of interest. Third, in addition to the potential biases discussed above that are likely to inflate the associations between the number of offspring and some of the health variables, we recognize that the estimates may understate the potential associations for all outcomes because of the short follow-up period. Fourth, although there may have been twins, twin males and females, or triplets, we did not measure offspring composition. Fifth, previous findings suggest that high parity (six or more offspring), early first birth, and the experience of infant death or pregnancy loss are associated with worse self-reported health at an older age. Early childbearing also has a clear positive correlation with limitations in activities of daily living [17,27]. However, we did not include these factors because of a lack of information. Finally, although we used longitudinal data, the results possibly reflect reverse causality and bidirectional relationships when assessing the association between the number of offspring and SRH.
We conducted a longitudinal data analysis using a nationally representative sample among adults ≥45 years of age. Our results provide additional evidence for relatively large and significant positive effects of additional offspring on SRH, which will predict future health status.
Notes
No potential conflict of interest relevant to this article was reported.
Figure. 1.
Adjusted effect of number of offspring on self-rated health according to gender. KLoSA, Korean Longitudinal Study of Aging.
Table 1.
General characteristics of the study variables at baseline (2006)
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