Face-to-face interviews were conducted on patients with hypertension and/or stroke and CHD in the Hong Kong Kadoorie Project. Self-administrated questionnaires were used to collect data on medical payments, including out-of-pocket (OOP) and NRCMS-reimbursed expenses. The pre- and post-reimbursement (via the NRCMS) prevalence of household poverty, catastrophic medical payment (CMP) incidence (H
), mean CMP gap (G
), mean positive CMP gap (MPG
) and other determinants of CMP incidence were calculated.
The research protocol was approved by the Ethics Committee of Tongji Medical College, Huazhong University of Science and Technology (IRB No: FWA000007304). Informed consents were obtained from all participants prior to collection of the data.
Study area and subjects
The research was conducted based on data collected from an investigation carried out between October 15 and October 30 in 2009. The investigation took place in areas where hypertension patients were all involved in the Hong Kong Kadoorie Project of ‘Community Health Promotion in Poor Rural Areas of China’, which funds the systematic management of prevalent hypertension and its complications in rural districts of central and western China. Under the Kadoorie Project, local general practitioners are trained to diagnose hypertension and its complications, perform regular interviews, provide guidelines for drug use and offer health education programs to patients. This project differs from health insurance (e.g., NRCMS) and does not provide the patients with any economic help. A total of 10 towns—three in the Ledu county of Qinghai Province, three in the Hezheng county of Gansu Province, one in the Jiaocheng county and three in the Pinglu county of Shanxi Province—were involved in this investigation. All of them were classified as fourth-class rural areas where the average annual income was less than RMB1500/$240.2 per capita in 2003. In other words, these rural areas have the worst economic level among all Chinese rural districts . At the time of the investigation, the four counties (i.e. Ledu, Hezheng, Jiaocheng and Pinglu) had total populations of 209,046, 166,586, 158,331 and 213,912, respectively, and an average annual income of RMB3130/$501.1, RMB1727/$276.5, RMB2920/$467.5 and RMB1440/$230.5 per capita, respectively. Cluster sampling strategy was used to randomly select two villages in each of the 10 towns.
All of the 1528 hypertension patients in the 20 selected villages were involved in the Kadoorie Project. According to the reported 12.6% prevalence of hypertension among adults aged 18 years or above in fourth-class rural regions, about 2500 prevalent hypertension cases existed in all of the 20 villages (with a total of 20,000 adults aged 18 years or above) . However, some of the patients had left their hometown for residence or work in other cities. Only 1528 hypertension patients were left in the study area, and only 1262 of them from 1176 households participated in our investigation. The other 266 patients were not interviewed because of various reasons, such as leaving home for work and inconvenient communication. More than 95% of the rural residents in the selected areas were NRCMS participants.
In this study, hypertension was defined as systolic blood pressure of ≥ 140 mmHg, diastolic blood pressure of ≥ 90 mmHg and/or a self-reported current treatment for hypertension. All subjects were aged 21 to 90 years (with a mean of 61.2 years) and were diagnosed with hypertension by a physician in township health centres or reputed hospitals. The respondents consisted of 1000 patients with hypertension from 947 families, 112 patients with stroke from 110 families, and 150 patients with CHD from 149 families. Patients who were suffering from secondary hypertension were excluded from the count.
Self-administered questionnaires were used for collecting data on sociodemographic characteristics including gender, age, nationality (i.e. Han or others such as Hui, Uygur, Dongxiang, Tujia or Kazak), marital status (i.e. married, divorced, widowed or unmarried), educational background (i.e. elementary, middle or senior middle school), occupation (i.e. farming or non-farming), and family status (i.e. general or enjoying five guarantees (i.e. childless and infirm; old persons who are guaranteed food, clothing, medical care, housing and burial expenses by communes; low-income families)), household income and household medical expenditures for treatment of hypertension, stroke, CHD and other diseases (including costs of outpatient and inpatient services) that were disbursed through either OOP or the NRCMS (reimbursement) in the preceding year (i.e. 2008). The economic status of households was evaluated by comparing the annual per capita income with the poverty line of RMB1300/$208.1 per capita set by the Chinese State Council Poverty Alleviation Leading Group Office; a poor economic status indicates an annual per capita income below the threshold, and a non-poor economic status indicates an annual per capita income equal to or above the threshold.
Most of the participants were recruited to the village health care centres by local general practitioners. Face-to-face interviews were conducted by trained investigators. All completed questionnaires were returned on the spot. Some of the participants who experienced difficulties in walking received the interview and completed the questionnaire at their own homes with the help of our investigators.
Prevalence of household poverty
The Chinese State Council Poverty Alleviation Leading Group Office set the poverty line at an annual income of RMB1300/$208.1 per capita. Families with income less than this amount are considered poverty-stricken families in the present study. The prevalence of household poverty (H
) was calculated using the formula below, where N represents the sample size of families and P is designated a value of 0 or 1, which indicates whether a household is poverty-stricken or not.
A household’s poverty status can be evaluated by H
. Impoverishment (expressed as H
) as a result of health costs related to hypertension, stroke or CHD was estimated by subtracting the medical costs prior to NRCMS reimbursements from the household income. Thus, the difference between H
indicates the extent to which the health costs of the studied diseases impoverish the households. H
was also calculated after the NRCMS reimbursements. The role of the NRCMS in alleviating impoverishment induced by the studied diseases can thus be evaluated quantitatively using the difference between pre- and post-reimbursement (via the NRCMS) H
Incidence and severity of catastrophic medical payments
The incidence and intensity of CMP were measured as described previously by Wagstaff and van Doorslaer MP .
An OOP medical payment is considered financially catastrophic when it is large relative to the household’s ability to pay (e.g., exceeding 15% of the family income) . Thresholds of 10%, 20%, 30%, 40%, 50% and 60% of household capacity to pay (CTP) were used to define CMP. In this study, a threshold of 40% was adopted . The World Bank and the WHO define CTP as the household’s disposable income calculated as the total income minus subsistence expenditure . CTP can be evaluated based on household consumption, expenditure, income or wealth index. Household income was used to evaluate CTP in this study. In the following description, X represents CTP, T represents payments for healthcare and z
represents the threshold of CMP, which amounts to 40%. Oi is the catastrophic overshoot, which is equal to Ti/xi-z
if Ti/xi > z
and to 0 if otherwise; Ei is equal to 1 if Oi > 0 and to zero if otherwise.
CMP incidence describes the frequency of CMP in all the studied households. It is calculated from the formula below, where H
is the CMP incidence, and N is the sample size of families.
CMP incidence reflects the number of families with catastrophic medical spending (i.e. the number of families with health payments that go beyond the predetermined threshold). However, it cannot represent how much a given household pays beyond its CTP. Another parameter of mean CMP gap was thus used to measure catastrophic severity. The CMP gap describes how much of a household’s medical payment is in excess of the threshold of 40% of its CTP. The mean CMP gap can be calculated from the equation below, where G
is the mean CMP gap, and N is the sample size of all selected families.
is estimated to reveal the average level of CMP severity for all studied households, but it cannot indicate to what extent excessive payments affect the said households. This value can be illustrated by the parameter mean positive CMP gap (MPG
), which refers to the average excess payment made by households in the sample, and is calculated as follows:
EpiData version 3.1 was used to manage all data. Chi-squared test was used to analyse the demographics of the subjects among the three groups (i.e. hypertension, stroke, and CHD groups). Multiple logistic regression analysis was performed with a multilevel model because both individual- and family-level variables are potential determinants of CMP incidence caused by hypertension, stroke and CHD. Statistical analysis was conducted using SAS version 8.12.