Do hospitalizations push households into poverty in India: evidence from national data

Do hospitalizations push households into poverty in... | F1000Research "use strict";function _typeof(t){return(_typeof="function"==typeof Symbol&&"symbol"==typeof Symbol.iterator?function(t){return typeof t}:function(t){return t&&"function"==typeof Symbol&&t.constructor===Symbol&&t!==Symbol.prototype?"symbol":typeof t})(t)}!function(){var t=function(){var t,e,o=[],n=window,r=n;for(;r;){try{if(r.frames.__tcfapiLocator){t=r;break}}catch(t){}if(r===n.top)break;r=r.parent}t||(!function t(){var e=n.document,o=!!n.frames.__tcfapiLocator;if(!o)if(e.body){var r=e.createElement("iframe");r.style.cssText="display:none",r.name="__tcfapiLocator",e.body.appendChild(r)}else setTimeout(t,5);return!o}(),n.__tcfapi=function(){for(var t=arguments.length,n=new Array(t),r=0;r 3&&2===parseInt(n[1],10)&&"boolean"==typeof n[3]&&(e=n[3],"function"==typeof n[2]&&n[2]("set",!0)):"ping"===n[0]?"function"==typeof n[2]&&n[2]({gdprApplies:e,cmpLoaded:!1,cmpStatus:"stub"}):o.push(n)},n.addEventListener("message",(function(t){var e="string"==typeof t.data,o={};if(e)try{o=JSON.parse(t.data)}catch(t){}else o=t.data;var n="object"===_typeof(o)&&null!==o?o.__tcfapiCall:null;n&&window.__tcfapi(n.command,n.version,(function(o,r){var a={__tcfapiReturn:{returnValue:o,success:r,callId:n.callId}};t&&t.source&&t.source.postMessage&&t.source.postMessage(e?JSON.stringify(a):a,"*")}),n.parameter)}),!1))};"undefined"!=typeof module?module.exports=t:t()}(); dataLayer = dataLayer || []; // Standard GTM initialization - Google Consent Mode handles consent automatically (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start': new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0], j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src= 'https://www.googletagmanager.com/gtm.js?id='+i+dl+ '>m_auth=hzk0Vc3qFsQYhCrIoHz68A>m_preview=env-1>m_cookies_win=x';f.parentNode.insertBefore(j,f); })(window,document,'script','dataLayer','GTM-MWFK8L5J'); ;window.NREUM||(NREUM={});NREUM.init={distributed_tracing:{enabled:true},privacy:{cookies_enabled:true},ajax:{deny_list:["bam.nr-data.net"]}}; ;NREUM.loader_config={accountID:"438030",trustKey:"438030",agentID:"772317073",licenseKey:"97f8f67f26",applicationID:"772317073"} ;NREUM.info={beacon:"bam.nr-data.net",errorBeacon:"bam.nr-data.net",licenseKey:"97f8f67f26",applicationID:"772317073",sa:1} ;/*! For license information please see nr-loader-spa-1.236.0.min.js.LICENSE.txt */ (()=>{"use strict";var e,t,r={5763:(e,t,r)=>{r.d(t,{P_:()=>l,Mt:()=>g,C5:()=>s,DL:()=>v,OP:()=>T,lF:()=>D,Yu:()=>y,Dg:()=>h,CX:()=>c,GE:()=>b,sU:()=>_});var n=r(8632),i=r(9567);const o={beacon:n.ce.beacon,errorBeacon:n.ce.errorBeacon,licenseKey:void 0,applicationID:void 0,sa:void 0,queueTime:void 0,applicationTime:void 0,ttGuid:void 0,user:void 0,account:void 0,product:void 0,extra:void 0,jsAttributes:{},userAttributes:void 0,atts:void 0,transactionName:void 0,tNamePlain:void 0},a={};function s(e){if(!e)throw new Error("All info objects require an agent identifier!");if(!a[e])throw new Error("Info for ".concat(e," was never set"));return a[e]}function c(e,t){if(!e)throw new Error("All info objects require an agent identifier!");a[e]=(0,i.D)(t,o),(0,n.Qy)(e,a[e],"info")}var u=r(7056);const d=()=>{const e={blockSelector:"[data-nr-block]",maskInputOptions:{password:!0}};return{allow_bfcache:!0,privacy:{cookies_enabled:!0},ajax:{deny_list:void 0,enabled:!0,harvestTimeSeconds:10},distributed_tracing:{enabled:void 0,exclude_newrelic_header:void 0,cors_use_newrelic_header:void 0,cors_use_tracecontext_headers:void 0,allowed_origins:void 0},session:{domain:void 0,expiresMs:u.oD,inactiveMs:u.Hb},ssl:void 0,obfuscate:void 0,jserrors:{enabled:!0,harvestTimeSeconds:10},metrics:{enabled:!0},page_action:{enabled:!0,harvestTimeSeconds:30},page_view_event:{enabled:!0},page_view_timing:{enabled:!0,harvestTimeSeconds:30,long_task:!1},session_trace:{enabled:!0,harvestTimeSeconds:10},harvest:{tooManyRequestsDelay:60},session_replay:{enabled:!1,harvestTimeSeconds:60,sampleRate:.1,errorSampleRate:.1,maskTextSelector:"*",maskAllInputs:!0,get blockClass(){return"nr-block"},get ignoreClass(){return"nr-ignore"},get maskTextClass(){return"nr-mask"},get blockSelector(){return e.blockSelector},set blockSelector(t){e.blockSelector+=",".concat(t)},get maskInputOptions(){return e.maskInputOptions},set maskInputOptions(t){e.maskInputOptions={...t,password:!0}}},spa:{enabled:!0,harvestTimeSeconds:10}}},f={};function l(e){if(!e)throw new Error("All configuration objects require an agent identifier!");if(!f[e])throw new Error("Configuration for ".concat(e," was never set"));return f[e]}function h(e,t){if(!e)throw new Error("All configuration objects require an agent identifier!");f[e]=(0,i.D)(t,d()),(0,n.Qy)(e,f[e],"config")}function g(e,t){if(!e)throw new Error("All configuration objects require an agent identifier!");var r=l(e);if(r){for(var n=t.split("."),i=0;i {r.d(t,{D:()=>i});var n=r(50);function i(e,t){try{if(!e||"object"!=typeof e)return(0,n.Z)("Setting a Configurable requires an object as input");if(!t||"object"!=typeof t)return(0,n.Z)("Setting a Configurable requires a model to set its initial properties");const r=Object.create(Object.getPrototypeOf(t),Object.getOwnPropertyDescriptors(t)),o=0===Object.keys(r).length?e:r;for(let a in o)if(void 0!==e[a])try{"object"==typeof e[a]&&"object"==typeof t[a]?r[a]=i(e[a],t[a]):r[a]=e[a]}catch(e){(0,n.Z)("An error occurred while setting a property of a Configurable",e)}return r}catch(e){(0,n.Z)("An error occured while setting a Configurable",e)}}},6818:(e,t,r)=>{r.d(t,{Re:()=>i,gF:()=>o,q4:()=>n});const n="1.236.0",i="PROD",o="CDN"},385:(e,t,r)=>{r.d(t,{FN:()=>a,IF:()=>u,Nk:()=>f,Tt:()=>s,_A:()=>o,il:()=>n,pL:()=>c,v6:()=>i,w1:()=>d});const n="undefined"!=typeof window&&!!window.document,i="undefined"!=typeof WorkerGlobalScope&&("undefined"!=typeof self&&self instanceof WorkerGlobalScope&&self.navigator instanceof WorkerNavigator||"undefined"!=typeof globalThis&&globalThis instanceof WorkerGlobalScope&&globalThis.navigator instanceof WorkerNavigator),o=n?window:"undefined"!=typeof WorkerGlobalScope&&("undefined"!=typeof self&&self instanceof WorkerGlobalScope&&self||"undefined"!=typeof globalThis&&globalThis instanceof WorkerGlobalScope&&globalThis),a=""+o?.location,s=/iPad|iPhone|iPod/.test(navigator.userAgent),c=s&&"undefined"==typeof SharedWorker,u=(()=>{const e=navigator.userAgent.match(/Firefox[/\s](\d+\.\d+)/);return Array.isArray(e)&&e.length>=2?+e[1]:0})(),d=Boolean(n&&window.document.documentMode),f=!!navigator.sendBeacon},1117:(e,t,r)=>{r.d(t,{w:()=>o});var n=r(50);const i={agentIdentifier:"",ee:void 0};class o{constructor(e){try{if("object"!=typeof e)return(0,n.Z)("shared context requires an object as input");this.sharedContext={},Object.assign(this.sharedContext,i),Object.entries(e).forEach((e=>{let[t,r]=e;Object.keys(i).includes(t)&&(this.sharedContext[t]=r)}))}catch(e){(0,n.Z)("An error occured while setting SharedContext",e)}}}},8e3:(e,t,r)=>{r.d(t,{L:()=>d,R:()=>c});var n=r(2177),i=r(1284),o=r(4322),a=r(3325);const s={};function c(e,t){const r={staged:!1,priority:a.p[t]||0};u(e),s[e].get(t)||s[e].set(t,r)}function u(e){e&&(s[e]||(s[e]=new Map))}function d(){let e=arguments.length>0&&void 0!==arguments[0]?arguments[0]:"",t=arguments.length>1&&void 0!==arguments[1]?arguments[1]:"feature";if(u(e),!e||!s[e].get(t))return a(t);s[e].get(t).staged=!0;const r=[...s[e]];function a(t){const r=e?n.ee.get(e):n.ee,a=o.X.handlers;if(r.backlog&&a){var s=r.backlog[t],c=a[t];if(c){for(var u=0;s&&u {let[t,r]=e;return r.staged}))&&(r.sort(((e,t)=>e[1].priority-t[1].priority)),r.forEach((e=>{let[t]=e;a(t)})))}function f(e,t){var r=e[1];(0,i.D)(t[r],(function(t,r){var n=e[0];if(r[0]===n){var i=r[1],o=e[3],a=e[2];i.apply(o,a)}}))}},2177:(e,t,r)=>{r.d(t,{c:()=>f,ee:()=>u});var n=r(8632),i=r(2210),o=r(1284),a=r(5763),s="nr@context";let c=(0,n.fP)();var u;function d(){}function f(e){return(0,i.X)(e,s,l)}function l(){return new d}function h(){u.aborted=!0,u.backlog={}}c.ee?u=c.ee:(u=function e(t,r){var n={},c={},f={},g=!1;try{g=16===r.length&&(0,a.OP)(r).isolatedBacklog}catch(e){}var p={on:b,addEventListener:b,removeEventListener:y,emit:v,get:x,listeners:w,context:m,buffer:A,abort:h,aborted:!1,isBuffering:E,debugId:r,backlog:g?{}:t&&"object"==typeof t.backlog?t.backlog:{}};return p;function m(e){return e&&e instanceof d?e:e?(0,i.X)(e,s,l):l()}function v(e,r,n,i,o){if(!1!==o&&(o=!0),!u.aborted||i){t&&o&&t.emit(e,r,n);for(var a=m(n),s=w(e),d=s.length,f=0;fn,p:()=>i});var n=r(2177).ee.get("handle");function i(e,t,r,i,o){o?(o.buffer([e],i),o.emit(e,t,r)):(n.buffer([e],i),n.emit(e,t,r))}},4322:(e,t,r)=>{r.d(t,{X:()=>o});var n=r(5546);o.on=a;var i=o.handlers={};function o(e,t,r,o){a(o||n.E,i,e,t,r)}function a(e,t,r,i,o){o||(o="feature"),e||(e=n.E);var a=t[o]=t[o]||{};(a[r]=a[r]||[]).push([e,i])}},3239:(e,t,r)=>{r.d(t,{bP:()=>s,iz:()=>c,m$:()=>a});var n=r(385);let i=!1,o=!1;try{const e={get passive(){return i=!0,!1},get signal(){return o=!0,!1}};n._A.addEventListener("test",null,e),n._A.removeEventListener("test",null,e)}catch(e){}function a(e,t){return i||o?{capture:!!e,passive:i,signal:t}:!!e}function s(e,t){let r=arguments.length>2&&void 0!==arguments[2]&&arguments[2],n=arguments.length>3?arguments[3]:void 0;window.addEventListener(e,t,a(r,n))}function c(e,t){let r=arguments.length>2&&void 0!==arguments[2]&&arguments[2],n=arguments.length>3?arguments[3]:void 0;document.addEventListener(e,t,a(r,n))}},4402:(e,t,r)=>{r.d(t,{Ht:()=>u,M:()=>c,Rl:()=>a,ky:()=>s});var n=r(385);const i="xxxxxxxx-xxxx-4xxx-yxxx-xxxxxxxxxxxx";function o(e,t){return e?15&e[t]:16*Math.random()|0}function a(){const e=n._A?.crypto||n._A?.msCrypto;let t,r=0;return e&&e.getRandomValues&&(t=e.getRandomValues(new Uint8Array(31))),i.split("").map((e=>"x"===e?o(t,++r).toString(16):"y"===e?(3&o()|8).toString(16):e)).join("")}function s(e){const t=n._A?.crypto||n._A?.msCrypto;let r,i=0;t&&t.getRandomValues&&(r=t.getRandomValues(new Uint8Array(31)));const a=[];for(var s=0;s {r.d(t,{Bq:()=>n,Hb:()=>o,oD:()=>i});const n="NRBA",i=144e5,o=18e5},7894:(e,t,r)=>{function n(){return Math.round(performance.now())}r.d(t,{z:()=>n})},7243:(e,t,r)=>{r.d(t,{e:()=>o});var n=r(385),i={};function o(e){if(e in i)return i[e];if(0===(e||"").indexOf("data:"))return{protocol:"data"};let t;var r=n._A?.location,o={};if(n.il)t=document.createElement("a"),t.href=e;else try{t=new URL(e,r.href)}catch(e){return o}o.port=t.port;var a=t.href.split("://");!o.port&&a[1]&&(o.port=a[1].split("/")[0].split("@").pop().split(":")[1]),o.port&&"0"!==o.port||(o.port="https"===a[0]?"443":"80"),o.hostname=t.hostname||r.hostname,o.pathname=t.pathname,o.protocol=a[0],"/"!==o.pathname.charAt(0)&&(o.pathname="/"+o.pathname);var s=!t.protocol||":"===t.protocol||t.protocol===r.protocol,c=t.hostname===r.hostname&&t.port===r.port;return o.sameOrigin=s&&(!t.hostname||c),"/"===o.pathname&&(i[e]=o),o}},50:(e,t,r)=>{function n(e,t){"function"==typeof console.warn&&(console.warn("New Relic: ".concat(e)),t&&console.warn(t))}r.d(t,{Z:()=>n})},2587:(e,t,r)=>{r.d(t,{N:()=>c,T:()=>u});var n=r(2177),i=r(5546),o=r(8e3),a=r(3325);const s={stn:[a.D.sessionTrace],err:[a.D.jserrors,a.D.metrics],ins:[a.D.pageAction],spa:[a.D.spa],sr:[a.D.sessionReplay,a.D.sessionTrace]};function c(e,t){const r=n.ee.get(t);e&&"object"==typeof e&&(Object.entries(e).forEach((e=>{let[t,n]=e;void 0===u[t]&&(s[t]?s[t].forEach((e=>{n?(0,i.p)("feat-"+t,[],void 0,e,r):(0,i.p)("block-"+t,[],void 0,e,r),(0,i.p)("rumresp-"+t,[Boolean(n)],void 0,e,r)})):n&&(0,i.p)("feat-"+t,[],void 0,void 0,r),u[t]=Boolean(n))})),Object.keys(s).forEach((e=>{void 0===u[e]&&(s[e]?.forEach((t=>(0,i.p)("rumresp-"+e,[!1],void 0,t,r))),u[e]=!1)})),(0,o.L)(t,a.D.pageViewEvent))}const u={}},2210:(e,t,r)=>{r.d(t,{X:()=>i});var n=Object.prototype.hasOwnProperty;function i(e,t,r){if(n.call(e,t))return e[t];var i=r();if(Object.defineProperty&&Object.keys)try{return Object.defineProperty(e,t,{value:i,writable:!0,enumerable:!1}),i}catch(e){}return e[t]=i,i}},1284:(e,t,r)=>{r.d(t,{D:()=>n});const n=(e,t)=>Object.entries(e||{}).map((e=>{let[r,n]=e;return t(r,n)}))},4351:(e,t,r)=>{r.d(t,{P:()=>o});var n=r(2177);const i=()=>{const e=new WeakSet;return(t,r)=>{if("object"==typeof r&&null!==r){if(e.has(r))return;e.add(r)}return r}};function o(e){try{return JSON.stringify(e,i())}catch(e){try{n.ee.emit("internal-error",[e])}catch(e){}}}},3960:(e,t,r)=>{r.d(t,{K:()=>a,b:()=>o});var n=r(3239);function i(){return"undefined"==typeof document||"complete"===document.readyState}function o(e,t){if(i())return e();(0,n.bP)("load",e,t)}function a(e){if(i())return e();(0,n.iz)("DOMContentLoaded",e)}},8632:(e,t,r)=>{r.d(t,{EZ:()=>u,Qy:()=>c,ce:()=>o,fP:()=>a,gG:()=>d,mF:()=>s});var n=r(7894),i=r(385);const o={beacon:"bam.nr-data.net",errorBeacon:"bam.nr-data.net"};function a(){return i._A.NREUM||(i._A.NREUM={}),void 0===i._A.newrelic&&(i._A.newrelic=i._A.NREUM),i._A.NREUM}function s(){let e=a();return e.o||(e.o={ST:i._A.setTimeout,SI:i._A.setImmediate,CT:i._A.clearTimeout,XHR:i._A.XMLHttpRequest,REQ:i._A.Request,EV:i._A.Event,PR:i._A.Promise,MO:i._A.MutationObserver,FETCH:i._A.fetch}),e}function c(e,t,r){let i=a();const o=i.initializedAgents||{},s=o[e]||{};return Object.keys(s).length||(s.initializedAt={ms:(0,n.z)(),date:new Date}),i.initializedAgents={...o,[e]:{...s,[r]:t}},i}function u(e,t){a()[e]=t}function d(){return function(){let e=a();const t=e.info||{};e.info={beacon:o.beacon,errorBeacon:o.errorBeacon,...t}}(),function(){let e=a();const t=e.init||{};e.init={...t}}(),s(),function(){let e=a();const t=e.loader_config||{};e.loader_config={...t}}(),a()}},7956:(e,t,r)=>{r.d(t,{N:()=>i});var n=r(3239);function i(e){let t=arguments.length>1&&void 0!==arguments[1]&&arguments[1],r=arguments.length>2?arguments[2]:void 0,i=arguments.length>3?arguments[3]:void 0;return void(0,n.iz)("visibilitychange",(function(){if(t)return void("hidden"==document.visibilityState&&e());e(document.visibilityState)}),r,i)}},1214:(e,t,r)=>{r.d(t,{em:()=>v,u5:()=>N,QU:()=>S,_L:()=>I,Gm:()=>L,Lg:()=>M,gy:()=>U,BV:()=>Q,Kf:()=>ee});var n=r(2177);const i="nr@original";var o=Object.prototype.hasOwnProperty,a=!1;function s(e,t){return e||(e=n.ee),r.inPlace=function(e,t,n,i,o){n||(n="");var a,s,c,u="-"===n.charAt(0);for(c=0;c 2?n-2:0),o=2;o {r(A[T],e,w),r(E[T],e,w)})),r(l._A,"fetch",y),t.on(y+"end",(function(e,r){var n=this;if(r){var i=r.headers.get("content-length");null!==i&&(n.rxSize=i),t.emit(y+"done",[null,r],n)}else t.emit(y+"done",[e],n)})),t}const O={},j=["pushState","replaceState"];function S(e){const t=function(e){return(e||n.ee).get("history")}(e);return!l.il||O[t.debugId]++||(O[t.debugId]=1,s(t).inPlace(window.history,j,"-")),t}var P=r(3239);const C={},R=["appendChild","insertBefore","replaceChild"];function I(e){const t=function(e){return(e||n.ee).get("jsonp")}(e);if(!l.il||C[t.debugId])return t;C[t.debugId]=!0;var r=s(t),i=/[?&](?:callback|cb)=([^&#]+)/,o=/(.*)\.([^.]+)/,a=/^(\w+)(\.|$)(.*)$/;function c(e,t){var r=e.match(a),n=r[1],i=r[3];return i?c(i,t[n]):t[n]}return r.inPlace(Node.prototype,R,"dom-"),t.on("dom-start",(function(e){!function(e){if(!e||"string"!=typeof e.nodeName||"script"!==e.nodeName.toLowerCase())return;if("function"!=typeof e.addEventListener)return;var n=(a=e.src,s=a.match(i),s?s[1]:null);var a,s;if(!n)return;var u=function(e){var t=e.match(o);if(t&&t.length>=3)return{key:t[2],parent:c(t[1],window)};return{key:e,parent:window}}(n);if("function"!=typeof u.parent[u.key])return;var d={};function f(){t.emit("jsonp-end",[],d),e.removeEventListener("load",f,(0,P.m$)(!1)),e.removeEventListener("error",l,(0,P.m$)(!1))}function l(){t.emit("jsonp-error",[],d),t.emit("jsonp-end",[],d),e.removeEventListener("load",f,(0,P.m$)(!1)),e.removeEventListener("error",l,(0,P.m$)(!1))}r.inPlace(u.parent,[u.key],"cb-",d),e.addEventListener("load",f,(0,P.m$)(!1)),e.addEventListener("error",l,(0,P.m$)(!1)),t.emit("new-jsonp",[e.src],d)}(e[0])})),t}var k=r(5763);const H={};function L(e){const t=function(e){return(e||n.ee).get("mutation")}(e);if(!l.il||H[t.debugId])return t;H[t.debugId]=!0;var r=s(t),i=k.Yu.MO;return i&&(window.MutationObserver=function(e){return this instanceof i?new i(r(e,"fn-")):i.apply(this,arguments)},MutationObserver.prototype=i.prototype),t}const z={};function M(e){const t=function(e){return(e||n.ee).get("promise")}(e);if(z[t.debugId])return t;z[t.debugId]=!0;var r=n.c,o=s(t),a=k.Yu.PR;return a&&function(){function e(r){var n=t.context(),i=o(r,"executor-",n,null,!1);const s=Reflect.construct(a,[i],e);return t.context(s).getCtx=function(){return n},s}l._A.Promise=e,Object.defineProperty(e,"name",{value:"Promise"}),e.toString=function(){return a.toString()},Object.setPrototypeOf(e,a),["all","race"].forEach((function(r){const n=a[r];e[r]=function(e){let i=!1;[...e||[]].forEach((e=>{this.resolve(e).then(a("all"===r),a(!1))}));const o=n.apply(this,arguments);return o;function a(e){return function(){t.emit("propagate",[null,!i],o,!1,!1),i=i||!e}}}})),["resolve","reject"].forEach((function(r){const n=a[r];e[r]=function(e){const r=n.apply(this,arguments);return e!==r&&t.emit("propagate",[e,!0],r,!1,!1),r}})),e.prototype=a.prototype;const n=a.prototype.then;a.prototype.then=function(){var e=this,i=r(e);i.promise=e;for(var a=arguments.length,s=new Array(a),c=0;c e())),t};function m(e,t){i.inPlace(t,["onreadystatechange"],"fn-",E)}function b(){var e=this,t=r.context(e);e.readyState>3&&!t.resolved&&(t.resolved=!0,r.emit("xhr-resolved",[],e)),i.inPlace(e,f,"fn-",E)}if(function(e,t){for(var r in e)t[r]=e[r]}(o,p),p.prototype=o.prototype,i.inPlace(p.prototype,J,"-xhr-",E),r.on("send-xhr-start",(function(e,t){m(e,t),function(e){h.push(e),a&&(y?y.then(A):u?u(A):(w=-w,x.data=w))}(t)})),r.on("open-xhr-start",m),a){var y=c&&c.resolve();if(!u&&!c){var w=1,x=document.createTextNode(w);new a(A).observe(x,{characterData:!0})}}else t.on("fn-end",(function(e){e[0]&&e[0].type===d||A()}));function A(){for(var e=0;e {r.d(t,{t:()=>n});const n=r(3325).D.ajax},6660:(e,t,r)=>{r.d(t,{A:()=>i,t:()=>n});const n=r(3325).D.jserrors,i="nr@seenError"},3081:(e,t,r)=>{r.d(t,{gF:()=>o,mY:()=>i,t9:()=>n,vz:()=>s,xS:()=>a});const n=r(3325).D.metrics,i="sm",o="cm",a="storeSupportabilityMetrics",s="storeEventMetrics"},4649:(e,t,r)=>{r.d(t,{t:()=>n});const n=r(3325).D.pageAction},7633:(e,t,r)=>{r.d(t,{Dz:()=>i,OJ:()=>a,qw:()=>o,t9:()=>n});const n=r(3325).D.pageViewEvent,i="firstbyte",o="domcontent",a="windowload"},9251:(e,t,r)=>{r.d(t,{t:()=>n});const n=r(3325).D.pageViewTiming},3614:(e,t,r)=>{r.d(t,{BST_RESOURCE:()=>i,END:()=>s,FEATURE_NAME:()=>n,FN_END:()=>u,FN_START:()=>c,PUSH_STATE:()=>d,RESOURCE:()=>o,START:()=>a});const n=r(3325).D.sessionTrace,i="bstResource",o="resource",a="-start",s="-end",c="fn"+a,u="fn"+s,d="pushState"},7836:(e,t,r)=>{r.d(t,{BODY:()=>A,CB_END:()=>E,CB_START:()=>u,END:()=>x,FEATURE_NAME:()=>i,FETCH:()=>_,FETCH_BODY:()=>v,FETCH_DONE:()=>m,FETCH_START:()=>p,FN_END:()=>c,FN_START:()=>s,INTERACTION:()=>l,INTERACTION_API:()=>d,INTERACTION_EVENTS:()=>o,JSONP_END:()=>b,JSONP_NODE:()=>g,JS_TIME:()=>T,MAX_TIMER_BUDGET:()=>a,REMAINING:()=>f,SPA_NODE:()=>h,START:()=>w,originalSetTimeout:()=>y});var n=r(5763);const i=r(3325).D.spa,o=["click","submit","keypress","keydown","keyup","change"],a=999,s="fn-start",c="fn-end",u="cb-start",d="api-ixn-",f="remaining",l="interaction",h="spaNode",g="jsonpNode",p="fetch-start",m="fetch-done",v="fetch-body-",b="jsonp-end",y=n.Yu.ST,w="-start",x="-end",A="-body",E="cb"+x,T="jsTime",_="fetch"},5938:(e,t,r)=>{r.d(t,{W:()=>o});var n=r(5763),i=r(2177);class o{constructor(e,t,r){this.agentIdentifier=e,this.aggregator=t,this.ee=i.ee.get(e,(0,n.OP)(this.agentIdentifier).isolatedBacklog),this.featureName=r,this.blocked=!1}}},9144:(e,t,r)=>{r.d(t,{j:()=>m});var n=r(3325),i=r(5763),o=r(5546),a=r(2177),s=r(7894),c=r(8e3),u=r(3960),d=r(385),f=r(50),l=r(3081),h=r(8632);function g(){const e=(0,h.gG)();["setErrorHandler","finished","addToTrace","inlineHit","addRelease","addPageAction","setCurrentRouteName","setPageViewName","setCustomAttribute","interaction","noticeError","setUserId"].forEach((t=>{e[t]=function(){for(var r=arguments.length,n=new Array(r),i=0;i 1?r-1:0),i=1;i {e.exposed&&e.api[t]&&o.push(e.api[t](...n))})),o.length>1?o:o[0]}(t,...n)}}))}var p=r(2587);function m(e){let t=arguments.length>1&&void 0!==arguments[1]?arguments[1]:{},m=arguments.length>2?arguments[2]:void 0,v=arguments.length>3?arguments[3]:void 0,{init:b,info:y,loader_config:w,runtime:x={loaderType:m},exposed:A=!0}=t;const E=(0,h.gG)();y||(b=E.init,y=E.info,w=E.loader_config),(0,i.Dg)(e,b||{}),(0,i.GE)(e,w||{}),(0,i.sU)(e,x),y.jsAttributes??={},d.v6&&(y.jsAttributes.isWorker=!0),(0,i.CX)(e,y),g();const T=function(e,t){t||(0,c.R)(e,"api");const h={};var g=a.ee.get(e),p=g.get("tracer"),m="api-",v=m+"ixn-";function b(t,r,n,o){const a=(0,i.C5)(e);return null===r?delete a.jsAttributes[t]:(0,i.CX)(e,{...a,jsAttributes:{...a.jsAttributes,[t]:r}}),x(m,n,!0,o||null===r?"session":void 0)(t,r)}function y(){}["setErrorHandler","finished","addToTrace","inlineHit","addRelease"].forEach((e=>h[e]=x(m,e,!0,"api"))),h.addPageAction=x(m,"addPageAction",!0,n.D.pageAction),h.setCurrentRouteName=x(m,"routeName",!0,n.D.spa),h.setPageViewName=function(t,r){if("string"==typeof t)return"/"!==t.charAt(0)&&(t="/"+t),(0,i.OP)(e).customTransaction=(r||"http://custom.transaction")+t,x(m,"setPageViewName",!0)()},h.setCustomAttribute=function(e,t){let r=arguments.length>2&&void 0!==arguments[2]&&arguments[2];if("string"==typeof e){if(["string","number"].includes(typeof t)||null===t)return b(e,t,"setCustomAttribute",r);(0,f.Z)("Failed to execute setCustomAttribute.\nNon-null value must be a string or number type, but a type of was provided."))}else(0,f.Z)("Failed to execute setCustomAttribute.\nName must be a string type, but a type of was provided."))},h.setUserId=function(e){if("string"==typeof e||null===e)return b("enduser.id",e,"setUserId",!0);(0,f.Z)("Failed to execute setUserId.\nNon-null value must be a string type, but a type of was provided."))},h.interaction=function(){return(new y).get()};var w=y.prototype={createTracer:function(e,t){var r={},i=this,a="function"==typeof t;return(0,o.p)(v+"tracer",[(0,s.z)(),e,r],i,n.D.spa,g),function(){if(p.emit((a?"":"no-")+"fn-start",[(0,s.z)(),i,a],r),a)try{return t.apply(this,arguments)}catch(e){throw p.emit("fn-err",[arguments,this,"string"==typeof e?new Error(e):e],r),e}finally{p.emit("fn-end",[(0,s.z)()],r)}}}};function x(e,t,r,i){return function(){return(0,o.p)(l.xS,["API/"+t+"/called"],void 0,n.D.metrics,g),i&&(0,o.p)(e+t,[(0,s.z)(),...arguments],r?null:this,i,g),r?void 0:this}}function A(){r.e(439).then(r.bind(r,7438)).then((t=>{let{setAPI:r}=t;r(e),(0,c.L)(e,"api")})).catch((()=>(0,f.Z)("Downloading runtime APIs failed...")))}return["actionText","setName","setAttribute","save","ignore","onEnd","getContext","end","get"].forEach((e=>{w[e]=x(v,e,void 0,n.D.spa)})),h.noticeError=function(e,t){"string"==typeof e&&(e=new Error(e)),(0,o.p)(l.xS,["API/noticeError/called"],void 0,n.D.metrics,g),(0,o.p)("err",[e,(0,s.z)(),!1,t],void 0,n.D.jserrors,g)},d.il?(0,u.b)((()=>A()),!0):A(),h}(e,v);return(0,h.Qy)(e,T,"api"),(0,h.Qy)(e,A,"exposed"),(0,h.EZ)("activatedFeatures",p.T),T}},3325:(e,t,r)=>{r.d(t,{D:()=>n,p:()=>i});const n={ajax:"ajax",jserrors:"jserrors",metrics:"metrics",pageAction:"page_action",pageViewEvent:"page_view_event",pageViewTiming:"page_view_timing",sessionReplay:"session_replay",sessionTrace:"session_trace",spa:"spa"},i={[n.pageViewEvent]:1,[n.pageViewTiming]:2,[n.metrics]:3,[n.jserrors]:4,[n.ajax]:5,[n.sessionTrace]:6,[n.pageAction]:7,[n.spa]:8,[n.sessionReplay]:9}}},n={};function i(e){var t=n[e];if(void 0!==t)return t.exports;var o=n[e]={exports:{}};return r[e](o,o.exports,i),o.exports}i.m=r,i.d=(e,t)=>{for(var r in t)i.o(t,r)&&!i.o(e,r)&&Object.defineProperty(e,r,{enumerable:!0,get:t[r]})},i.f={},i.e=e=>Promise.all(Object.keys(i.f).reduce(((t,r)=>(i.f[r](e,t),t)),[])),i.u=e=>(({78:"page_action-aggregate",147:"metrics-aggregate",242:"session-manager",317:"jserrors-aggregate",348:"page_view_timing-aggregate",412:"lazy-feature-loader",439:"async-api",538:"recorder",590:"session_replay-aggregate",675:"compressor",733:"session_trace-aggregate",786:"page_view_event-aggregate",873:"spa-aggregate",898:"ajax-aggregate"}[e]||e)+"."+{78:"ac76d497",147:"3dc53903",148:"1a20d5fe",242:"2a64278a",317:"49e41428",348:"bd6de33a",412:"2f55ce66",439:"30bd804e",538:"1b18459f",590:"cf0efb30",675:"ae9f91a8",733:"83105561",786:"06482edd",860:"03a8b7a5",873:"e6b09d52",898:"998ef92b"}[e]+"-1.236.0.min.js"),i.o=(e,t)=>Object.prototype.hasOwnProperty.call(e,t),e={},t="NRBA:",i.l=(r,n,o,a)=>{if(e[r])e[r].push(n);else{var s,c;if(void 0!==o)for(var u=document.getElementsByTagName("script"),d=0;d {s.onerror=s.onload=null,clearTimeout(h);var i=e[r];if(delete e[r],s.parentNode&&s.parentNode.removeChild(s),i&&i.forEach((e=>e(n))),t)return t(n)},h=setTimeout(l.bind(null,void 0,{type:"timeout",target:s}),12e4);s.onerror=l.bind(null,s.onerror),s.onload=l.bind(null,s.onload),c&&document.head.appendChild(s)}},i.r=e=>{"undefined"!=typeof Symbol&&Symbol.toStringTag&&Object.defineProperty(e,Symbol.toStringTag,{value:"Module"}),Object.defineProperty(e,"__esModule",{value:!0})},i.j=364,i.p="https://js-agent.newrelic.com/",(()=>{var e={364:0,953:0};i.f.j=(t,r)=>{var n=i.o(e,t)?e[t]:void 0;if(0!==n)if(n)r.push(n[2]);else{var o=new Promise(((r,i)=>n=e[t]=[r,i]));r.push(n[2]=o);var a=i.p+i.u(t),s=new Error;i.l(a,(r=>{if(i.o(e,t)&&(0!==(n=e[t])&&(e[t]=void 0),n)){var o=r&&("load"===r.type?"missing":r.type),a=r&&r.target&&r.target.src;s.message="Loading chunk "+t+" failed.\n("+o+": "+a+")",s.name="ChunkLoadError",s.type=o,s.request=a,n[1](s)}}),"chunk-"+t,t)}};var t=(t,r)=>{var n,o,[a,s,c]=r,u=0;if(a.some((t=>0!==e[t]))){for(n in s)i.o(s,n)&&(i.m[n]=s[n]);if(c)c(i)}for(t&&t(r);u {i.r(o);var e=i(3325),t=i(5763);const r=Object.values(e.D);function n(e){const n={};return r.forEach((r=>{n[r]=function(e,r){return!1!==(0,t.Mt)(r,"".concat(e,".enabled"))}(r,e)})),n}var a=i(9144);var s=i(5546),c=i(385),u=i(8e3),d=i(5938),f=i(3960),l=i(50);class h extends d.W{constructor(e,t,r){let n=!(arguments.length>3&&void 0!==arguments[3])||arguments[3];super(e,t,r),this.auto=n,this.abortHandler,this.featAggregate,this.onAggregateImported,n&&(0,u.R)(e,r)}importAggregator(){let e=arguments.length>0&&void 0!==arguments[0]?arguments[0]:{};if(this.featAggregate||!this.auto)return;const r=c.il&&!0===(0,t.Mt)(this.agentIdentifier,"privacy.cookies_enabled");let n;this.onAggregateImported=new Promise((e=>{n=e}));const o=async()=>{let t;try{if(r){const{setupAgentSession:e}=await Promise.all([i.e(860),i.e(242)]).then(i.bind(i,3228));t=e(this.agentIdentifier)}}catch(e){(0,l.Z)("A problem occurred when starting up session manager. This page will not start or extend any session.",e)}try{if(!this.shouldImportAgg(this.featureName,t))return void(0,u.L)(this.agentIdentifier,this.featureName);const{lazyFeatureLoader:r}=await i.e(412).then(i.bind(i,8582)),{Aggregate:o}=await r(this.featureName,"aggregate");this.featAggregate=new o(this.agentIdentifier,this.aggregator,e),n(!0)}catch(e){(0,l.Z)("Downloading and initializing ".concat(this.featureName," failed..."),e),this.abortHandler?.(),n(!1)}};c.il?(0,f.b)((()=>o()),!0):o()}shouldImportAgg(r,n){return r!==e.D.sessionReplay||!1!==(0,t.Mt)(this.agentIdentifier,"session_trace.enabled")&&(!!n?.isNew||!!n?.state.sessionReplay)}}var g=i(7633),p=i(7894);class m extends h{static featureName=g.t9;constructor(r,n){let i=!(arguments.length>2&&void 0!==arguments[2])||arguments[2];if(super(r,n,g.t9,i),("undefined"==typeof PerformanceNavigationTiming||c.Tt)&&"undefined"!=typeof PerformanceTiming){const n=(0,t.OP)(r);n[g.Dz]=Math.max(Date.now()-n.offset,0),(0,f.K)((()=>n[g.qw]=Math.max((0,p.z)()-n[g.Dz],0))),(0,f.b)((()=>{const t=(0,p.z)();n[g.OJ]=Math.max(t-n[g.Dz],0),(0,s.p)("timing",["load",t],void 0,e.D.pageViewTiming,this.ee)}))}this.importAggregator()}}var v=i(1117),b=i(1284);class y extends v.w{constructor(e){super(e),this.aggregatedData={}}store(e,t,r,n,i){var o=this.getBucket(e,t,r,i);return o.metrics=function(e,t){t||(t={count:0});return t.count+=1,(0,b.D)(e,(function(e,r){t[e]=w(r,t[e])})),t}(n,o.metrics),o}merge(e,t,r,n,i){var o=this.getBucket(e,t,n,i);if(o.metrics){var a=o.metrics;a.count+=r.count,(0,b.D)(r,(function(e,t){if("count"!==e){var n=a[e],i=r[e];i&&!i.c?a[e]=w(i.t,n):a[e]=function(e,t){if(!t)return e;t.c||(t=x(t.t));return t.min=Math.min(e.min,t.min),t.max=Math.max(e.max,t.max),t.t+=e.t,t.sos+=e.sos,t.c+=e.c,t}(i,a[e])}}))}else o.metrics=r}storeMetric(e,t,r,n){var i=this.getBucket(e,t,r);return i.stats=w(n,i.stats),i}getBucket(e,t,r,n){this.aggregatedData[e]||(this.aggregatedData[e]={});var i=this.aggregatedData[e][t];return i||(i=this.aggregatedData[e][t]={params:r||{}},n&&(i.custom=n)),i}get(e,t){return t?this.aggregatedData[e]&&this.aggregatedData[e][t]:this.aggregatedData[e]}take(e){for(var t={},r="",n=!1,i=0;i t.max&&(t.max=e),e 2&&void 0!==arguments[2])||arguments[2];super(e,r,j.t,n),c.il&&((0,t.OP)(e).initHidden=Boolean("hidden"===document.visibilityState),(0,N.N)((()=>(0,s.p)("docHidden",[(0,p.z)()],void 0,j.t,this.ee)),!0),(0,O.bP)("pagehide",(()=>(0,s.p)("winPagehide",[(0,p.z)()],void 0,j.t,this.ee))),this.importAggregator())}}var P=i(3081);class C extends h{static featureName=P.t9;constructor(e,t){let r=!(arguments.length>2&&void 0!==arguments[2])||arguments[2];super(e,t,P.t9,r),this.importAggregator()}}var R,I=i(2210),k=i(1214),H=i(2177),L={};try{R=localStorage.getItem("__nr_flags").split(","),console&&"function"==typeof console.log&&(L.console=!0,-1!==R.indexOf("dev")&&(L.dev=!0),-1!==R.indexOf("nr_dev")&&(L.nrDev=!0))}catch(e){}function z(e){try{L.console&&z(e)}catch(e){}}L.nrDev&&H.ee.on("internal-error",(function(e){z(e.stack)})),L.dev&&H.ee.on("fn-err",(function(e,t,r){z(r.stack)})),L.dev&&(z("NR AGENT IN DEVELOPMENT MODE"),z("flags: "+(0,b.D)(L,(function(e,t){return e})).join(", ")));var M=i(6660);class B extends h{static featureName=M.t;constructor(r,n){let i=!(arguments.length>2&&void 0!==arguments[2])||arguments[2];super(r,n,M.t,i),this.skipNext=0;try{this.removeOnAbort=new AbortController}catch(e){}const o=this;o.ee.on("fn-start",(function(e,t,r){o.abortHandler&&(o.skipNext+=1)})),o.ee.on("fn-err",(function(t,r,n){o.abortHandler&&!n[M.A]&&((0,I.X)(n,M.A,(function(){return!0})),this.thrown=!0,(0,s.p)("err",[n,(0,p.z)()],void 0,e.D.jserrors,o.ee))})),o.ee.on("fn-end",(function(){o.abortHandler&&!this.thrown&&o.skipNext>0&&(o.skipNext-=1)})),o.ee.on("internal-error",(function(t){(0,s.p)("ierr",[t,(0,p.z)(),!0],void 0,e.D.jserrors,o.ee)})),this.origOnerror=c._A.onerror,c._A.onerror=this.onerrorHandler.bind(this),c._A.addEventListener("unhandledrejection",(t=>{const r=function(e){let t="Unhandled Promise Rejection: ";if(e instanceof Error)try{return e.message=t+e.message,e}catch(t){return e}if(void 0===e)return new Error(t);try{return new Error(t+(0,D.P)(e))}catch(e){return new Error(t)}}(t.reason);(0,s.p)("err",[r,(0,p.z)(),!1,{unhandledPromiseRejection:1}],void 0,e.D.jserrors,this.ee)}),(0,O.m$)(!1,this.removeOnAbort?.signal)),(0,k.gy)(this.ee),(0,k.BV)(this.ee),(0,k.em)(this.ee),(0,t.OP)(r).xhrWrappable&&(0,k.Kf)(this.ee),this.abortHandler=this.#e,this.importAggregator()}#e(){this.removeOnAbort?.abort(),this.abortHandler=void 0}onerrorHandler(t,r,n,i,o){"function"==typeof this.origOnerror&&this.origOnerror(...arguments);try{this.skipNext?this.skipNext-=1:(0,s.p)("err",[o||new F(t,r,n),(0,p.z)()],void 0,e.D.jserrors,this.ee)}catch(t){try{(0,s.p)("ierr",[t,(0,p.z)(),!0],void 0,e.D.jserrors,this.ee)}catch(e){}}return!1}}function F(e,t,r){this.message=e||"Uncaught error with no additional information",this.sourceURL=t,this.line=r}let U=1;const q="nr@id";function G(e){const t=typeof e;return!e||"object"!==t&&"function"!==t?-1:e===c._A?0:(0,I.X)(e,q,(function(){return U++}))}function V(e){if("string"==typeof e&&e.length)return e.length;if("object"==typeof e){if("undefined"!=typeof ArrayBuffer&&e instanceof ArrayBuffer&&e.byteLength)return e.byteLength;if("undefined"!=typeof Blob&&e instanceof Blob&&e.size)return e.size;if(!("undefined"!=typeof FormData&&e instanceof FormData))try{return(0,D.P)(e).length}catch(e){return}}}var X=i(7243);class W{constructor(e){this.agentIdentifier=e,this.generateTracePayload=this.generateTracePayload.bind(this),this.shouldGenerateTrace=this.shouldGenerateTrace.bind(this)}generateTracePayload(e){if(!this.shouldGenerateTrace(e))return null;var r=(0,t.DL)(this.agentIdentifier);if(!r)return null;var n=(r.accountID||"").toString()||null,i=(r.agentID||"").toString()||null,o=(r.trustKey||"").toString()||null;if(!n||!i)return null;var a=(0,_.M)(),s=(0,_.Ht)(),c=Date.now(),u={spanId:a,traceId:s,timestamp:c};return(e.sameOrigin||this.isAllowedOrigin(e)&&this.useTraceContextHeadersForCors())&&(u.traceContextParentHeader=this.generateTraceContextParentHeader(a,s),u.traceContextStateHeader=this.generateTraceContextStateHeader(a,c,n,i,o)),(e.sameOrigin&&!this.excludeNewrelicHeader()||!e.sameOrigin&&this.isAllowedOrigin(e)&&this.useNewrelicHeaderForCors())&&(u.newrelicHeader=this.generateTraceHeader(a,s,c,n,i,o)),u}generateTraceContextParentHeader(e,t){return"00-"+t+"-"+e+"-01"}generateTraceContextStateHeader(e,t,r,n,i){return i+"@nr=0-1-"+r+"-"+n+"-"+e+"----"+t}generateTraceHeader(e,t,r,n,i,o){if(!("function"==typeof c._A?.btoa))return null;var a={v:[0,1],d:{ty:"Browser",ac:n,ap:i,id:e,tr:t,ti:r}};return o&&n!==o&&(a.d.tk=o),btoa((0,D.P)(a))}shouldGenerateTrace(e){return this.isDtEnabled()&&this.isAllowedOrigin(e)}isAllowedOrigin(e){var r=!1,n={};if((0,t.Mt)(this.agentIdentifier,"distributed_tracing")&&(n=(0,t.P_)(this.agentIdentifier).distributed_tracing),e.sameOrigin)r=!0;else if(n.allowed_origins instanceof Array)for(var i=0;i 2&&void 0!==arguments[2])||arguments[2];super(r,n,Z.t,i),(0,t.OP)(r).xhrWrappable&&(this.dt=new W(r),this.handler=(e,t,r,n)=>(0,s.p)(e,t,r,n,this.ee),(0,k.u5)(this.ee),(0,k.Kf)(this.ee),function(r,n,i,o){function a(e){var t=this;t.totalCbs=0,t.called=0,t.cbTime=0,t.end=E,t.ended=!1,t.xhrGuids={},t.lastSize=null,t.loadCaptureCalled=!1,t.params=this.params||{},t.metrics=this.metrics||{},e.addEventListener("load",(function(r){_(t,e)}),(0,O.m$)(!1)),c.IF||e.addEventListener("progress",(function(e){t.lastSize=e.loaded}),(0,O.m$)(!1))}function s(e){this.params={method:e[0]},T(this,e[1]),this.metrics={}}function u(e,n){var i=(0,t.DL)(r);i.xpid&&this.sameOrigin&&n.setRequestHeader("X-NewRelic-ID",i.xpid);var a=o.generateTracePayload(this.parsedOrigin);if(a){var s=!1;a.newrelicHeader&&(n.setRequestHeader("newrelic",a.newrelicHeader),s=!0),a.traceContextParentHeader&&(n.setRequestHeader("traceparent",a.traceContextParentHeader),a.traceContextStateHeader&&n.setRequestHeader("tracestate",a.traceContextStateHeader),s=!0),s&&(this.dt=a)}}function d(e,t){var r=this.metrics,i=e[0],o=this;if(r&&i){var a=V(i);a&&(r.txSize=a)}this.startTime=(0,p.z)(),this.listener=function(e){try{"abort"!==e.type||o.loadCaptureCalled||(o.params.aborted=!0),("load"!==e.type||o.called===o.totalCbs&&(o.onloadCalled||"function"!=typeof t.onload)&&"function"==typeof o.end)&&o.end(t)}catch(e){try{n.emit("internal-error",[e])}catch(e){}}};for(var s=0;s 1?e[1]=i:e.push(i)}else e[0]&&e[0].headers&&s(e[0].headers,n)&&(this.dt=n);function s(e,t){var r=!1;return t.newrelicHeader&&(e.set("newrelic",t.newrelicHeader),r=!0),t.traceContextParentHeader&&(e.set("traceparent",t.traceContextParentHeader),t.traceContextStateHeader&&e.set("tracestate",t.traceContextStateHeader),r=!0),r}}function x(e,t){this.params={},this.metrics={},this.startTime=(0,p.z)(),this.dt=t,e.length>=1&&(this.target=e[0]),e.length>=2&&(this.opts=e[1]);var r,n=this.opts||{},i=this.target;"string"==typeof i?r=i:"object"==typeof i&&i instanceof Y?r=i.url:c._A?.URL&&"object"==typeof i&&i instanceof URL&&(r=i.href),T(this,r);var o=(""+(i&&i instanceof Y&&i.method||n.method||"GET")).toUpperCase();this.params.method=o,this.txSize=V(n.body)||0}function A(t,r){var n;this.endTime=(0,p.z)(),this.params||(this.params={}),this.params.status=r?r.status:0,"string"==typeof this.rxSize&&this.rxSize.length>0&&(n=+this.rxSize);var o={txSize:this.txSize,rxSize:n,duration:(0,p.z)()-this.startTime};i("xhr",[this.params,o,this.startTime,this.endTime,"fetch"],this,e.D.ajax)}function E(t){var r=this.params,n=this.metrics;if(!this.ended){this.ended=!0;for(var o=0;o 2&&void 0!==arguments[2])||arguments[2];super(e,t,we.t,r),this.importAggregator()}}new class{constructor(e){let t=arguments.length>1&&void 0!==arguments[1]?arguments[1]:(0,_.ky)(16);c._A?(this.agentIdentifier=t,this.sharedAggregator=new y({agentIdentifier:this.agentIdentifier}),this.features={},this.desiredFeatures=new Set(e.features||[]),this.desiredFeatures.add(m),Object.assign(this,(0,a.j)(this.agentIdentifier,e,e.loaderType||"agent")),this.start()):(0,l.Z)("Failed to initial the agent. Could not determine the runtime environment.")}get config(){return{info:(0,t.C5)(this.agentIdentifier),init:(0,t.P_)(this.agentIdentifier),loader_config:(0,t.DL)(this.agentIdentifier),runtime:(0,t.OP)(this.agentIdentifier)}}start(){const t="features";try{const r=n(this.agentIdentifier),i=[...this.desiredFeatures];i.sort(((t,r)=>e.p[t.featureName]-e.p[r.featureName])),i.forEach((t=>{if(r[t.featureName]||t.featureName===e.D.pageViewEvent){const n=function(t){switch(t){case e.D.ajax:return[e.D.jserrors];case e.D.sessionTrace:return[e.D.ajax,e.D.pageViewEvent];case e.D.sessionReplay:return[e.D.sessionTrace];case e.D.pageViewTiming:return[e.D.pageViewEvent];default:return[]}}(t.featureName);n.every((e=>r[e]))||(0,l.Z)("".concat(t.featureName," is enabled but one or more dependent features has been disabled (").concat((0,D.P)(n),"). This may cause unintended consequences or missing data...")),this.features[t.featureName]=new t(this.agentIdentifier,this.sharedAggregator)}})),(0,T.Qy)(this.agentIdentifier,this.features,t)}catch(e){(0,l.Z)("Failed to initialize all enabled instrument classes (agent aborted) -",e);for(const e in this.features)this.features[e].abortHandler?.();const r=(0,T.fP)();return delete r.initializedAgents[this.agentIdentifier]?.api,delete r.initializedAgents[this.agentIdentifier]?.[t],delete this.sharedAggregator,r.ee?.abort(),delete r.ee?.get(this.agentIdentifier),!1}}}({features:[J,m,S,class extends h{static featureName=oe;constructor(t,r){if(super(t,r,oe,!(arguments.length>2&&void 0!==arguments[2])||arguments[2]),!c.il)return;const n=this.ee;let i;(0,k.QU)(n),this.eventsEE=(0,k.em)(n),this.eventsEE.on(se,(function(e,t){this.bstStart=(0,p.z)()})),this.eventsEE.on(ae,(function(t,r){(0,s.p)("bst",[t[0],r,this.bstStart,(0,p.z)()],void 0,e.D.sessionTrace,n)})),n.on(ce+ne,(function(e){this.time=(0,p.z)(),this.startPath=location.pathname+location.hash})),n.on(ce+ie,(function(t){(0,s.p)("bstHist",[location.pathname+location.hash,this.startPath,this.time],void 0,e.D.sessionTrace,n)}));try{i=new PerformanceObserver((t=>{const r=t.getEntries();(0,s.p)(te,[r],void 0,e.D.sessionTrace,n)})),i.observe({type:re,buffered:!0})}catch(e){}this.importAggregator({resourceObserver:i})}},C,xe,B,class extends h{static featureName=de;constructor(e,r){if(super(e,r,de,!(arguments.length>2&&void 0!==arguments[2])||arguments[2]),!c.il)return;if(!(0,t.OP)(e).xhrWrappable)return;try{this.removeOnAbort=new AbortController}catch(e){}let n,i=0;const o=this.ee.get("tracer"),a=(0,k._L)(this.ee),s=(0,k.Lg)(this.ee),u=(0,k.BV)(this.ee),d=(0,k.Kf)(this.ee),f=this.ee.get("events"),l=(0,k.u5)(this.ee),h=(0,k.QU)(this.ee),g=(0,k.Gm)(this.ee);function m(e,t){h.emit("newURL",[""+window.location,t])}function v(){i++,n=window.location.hash,this[ve]=(0,p.z)()}function b(){i--,window.location.hash!==n&&m(0,!0);var e=(0,p.z)();this[pe]=~~this[pe]+e-this[ve],this[ye]=e}function y(e,t){e.on(t,(function(){this[t]=(0,p.z)()}))}this.ee.on(ve,v),s.on(be,v),a.on(be,v),this.ee.on(ye,b),s.on(ge,b),a.on(ge,b),this.ee.buffer([ve,ye,"xhr-resolved"],this.featureName),f.buffer([ve],this.featureName),u.buffer(["setTimeout"+le,"clearTimeout"+fe,ve],this.featureName),d.buffer([ve,"new-xhr","send-xhr"+fe],this.featureName),l.buffer([me+fe,me+"-done",me+he+fe,me+he+le],this.featureName),h.buffer(["newURL"],this.featureName),g.buffer([ve],this.featureName),s.buffer(["propagate",be,ge,"executor-err","resolve"+fe],this.featureName),o.buffer([ve,"no-"+ve],this.featureName),a.buffer(["new-jsonp","cb-start","jsonp-error","jsonp-end"],this.featureName),y(l,me+fe),y(l,me+"-done"),y(a,"new-jsonp"),y(a,"jsonp-end"),y(a,"cb-start"),h.on("pushState-end",m),h.on("replaceState-end",m),window.addEventListener("hashchange",m,(0,O.m$)(!0,this.removeOnAbort?.signal)),window.addEventListener("load",m,(0,O.m$)(!0,this.removeOnAbort?.signal)),window.addEventListener("popstate",(function(){m(0,i>1)}),(0,O.m$)(!0,this.removeOnAbort?.signal)),this.abortHandler=this.#e,this.importAggregator()}#e(){this.removeOnAbort?.abort(),this.abortHandler=void 0}}],loaderType:"spa"})})(),window.NRBA=o})(); window.jQuery || document.write(' ') CKEDITOR_BASEPATH='https://f1000research.com/js/vendor/ckeditor/' window.reactTheme = 'research'; window.MathJax = { CommonHTML: { linebreaks: { automatic: true } }, 'HTML-CSS': { linebreaks: { automatic: true } }, SVG: { linebreaks: { automatic: true } }, AuthorInit: function() { MathJax.Hub.Register.MessageHook('End Process', function () { let timeout = false; // holder for timeout id const delay = 250; // delay after event is "complete" to run callback const reflowMath = function() { const dispFormulas = document.querySelectorAll('.disp-formula.panel'); if (!dispFormulas) { return; } for (const dispFormula of dispFormulas) { const child = dispFormula.querySelector('.MathJax_Preview').nextSibling.firstChild; const isMultiline = MathJax.Hub.getAllJax(dispFormula)[0].root.isMultiline; if (dispFormula.offsetWidth < child.offsetWidth || isMultiline) { MathJax.Hub.Queue(['Rerender', MathJax.Hub, dispFormula]); } } }; window.addEventListener('resize', function() { clearTimeout(timeout); // clear the timeout timeout = setTimeout(reflowMath, delay); // start timing for event "completion" }); }); }, }; if (window.location.hash == '#_=_'){ window.location = window.location.href.split('#')[0] } !function(f,b,e,v,n,t,s){if(f.fbq)return;n=f.fbq=function() {n.callMethod? n.callMethod.apply(n,arguments):n.queue.push(arguments)} ;if(!f._fbq)f._fbq=n; n.push=n;n.loaded=!0;n.version='2.0';n.queue=[];t=b.createElement(e);t.async=!0; t.src=v;s=b.getElementsByTagName(e)[0];s.parentNode.insertBefore(t,s)}(window, document,'script','https://connect.facebook.net/en_US/fbevents.js'); fbq('init', '1641728616063202'); fbq('track', "PixelInitialized", {}); (function(h,o,t,j,a,r){ h.hj=h.hj||function(){(h.hj.q=h.hj.q||[]).push(arguments)}; h._hjSettings={hjid:2318163,hjsv:6}; a=o.getElementsByTagName('head')[0]; r=o.createElement('script');r.async=1; r.src=t+h._hjSettings.hjid+j+h._hjSettings.hjsv; a.appendChild(r); })(window,document,'https://static.hotjar.com/c/hotjar-','.js?sv='); search file_upload Submit your research search menu close search Browse Gateways & Collections How to Publish Submit your Research My Submissions Article Guidelines Article Guidelines (New Versions) Open Data, Software and Code Guidelines Open Data and Accessible Source Materials Guidelines (HSS) Open Data, Software and Code Guidelines (PSE) Prepublication Checks Production Process Posters and Slides Guidelines Document Guidelines Article Processing Charges Peer Review Finding Article Reviewers About How it Works For Reviewers Our Advisors Policies Glossary FAQs For Developers Newsroom Contact My Research Submissions Content and Tracking Alerts My Details Sign In file_upload Submit your research { "@context": "https://schema.org", "@type": "ScholarlyArticle", "mainEntityOfPage": { "@type": "WebPage", "@id": "https://f1000research.com/articles/13-205" }, "headline": "Do hospitalizations push households into poverty in India: evidence from national data", "datePublished": "2024-03-21T14:55:28", "dateModified": "2024-03-21T14:55:28", "author": [ { "@type": "Person", "name": "Shyamkumar Sriram" }, { "@type": "Person", "name": "Muayad Albadrani" } ], "publisher": { "@type": "Organization", "name": "F1000Research", "logo": { "@type": "ImageObject", "url": "https://f1000research.com/img/AMP/F1000Research_image.png", "height": 480, "width": 60 } }, "image": { "@type": "ImageObject", "url": "https://f1000research.com/img/AMP/F1000Research_image.png", "height": 1200, "width": 150 }, "description": " Introduction High percentage of OOP (Out-of-Pocket) costs can lead to poverty and exacerbate existing poverty, with 21.9% of India’s 1.324 billion people living below the poverty line. Factors such as increased patient cost-sharing, high-deductible health plans, and expensive medications contribute to high OOP costs. Understanding the poverty-inducing impact of healthcare payments is essential for formulating effective measures to alleviate it. Methods The study used data from the 75th round of the National Sample Survey Organization (Household Social Consumption in India: Health) from July 2017-June 2018, focusing on demographic-socio-economic characteristics, morbidity status, healthcare utilization, and expenditure. The analysis included 66,237 hospitalized individuals in the last 365 days. Logistic regression model was used to examine the impact of OOP expenditures on impoverishment. Results Logistic regression analysis shows that there is 0.2868 lower odds of experiencing poverty due to OOP expenditures in households where there is the presence of at least one child aged 5 years and less present in the household compared to households who do not have any children. There is 0.601 higher odds of experiencing poverty due to OOP expenditures in urban areas compared to households in rural areas. With an increasing duration of stay in the hospital, there is a higher odds of experiencing poverty due to OOP health expenditures. There is 1.9013 higher odds of experiencing poverty due to OOP expenditures if at least one member in the household used private healthcare facility compared to households who never used private healthcare facilities. Conclusion In order to transfer demand from private to public hospitals and reduce OOPHE, policymakers should restructure the current inefficient public hospitals. More crucially, there needs to be significant investment in rural areas, where more than 70% of the poorest people reside and who are more vulnerable to OOP expenditures because they lack coping skills. " } { "@context": "http://schema.org", "@type": "BreadcrumbList", "itemListElement": [ { "@type": "ListItem", "position": "1", "item": { "@id": "https://f1000research.com/", "name": "Home" } }, { "@type": "ListItem", "position": "2", "item": { "@id": "https://f1000research.com/browse/articles", "name": "Browse" } }, { "@type": "ListItem", "position": "3", "item": { "@id": "https://f1000research.com/articles/13-205/v1", "name": "Do hospitalizations push households into poverty in India: evidence..." } } ] } Home Browse Do hospitalizations push households into poverty in India: evidence... ALL Metrics - Views Downloads Get PDF Get XML Cite How to cite this article Sriram S and Albadrani M. Do hospitalizations push households into poverty in India: evidence from national data [version 1; peer review: 2 approved, 1 approved with reservations] . F1000Research 2024, 13 :205 ( https://doi.org/10.12688/f1000research.145602.1 ) NOTE: If applicable, it is important to ensure the information in square brackets after the title is included in all citations of this article. Close Copy Citation Details Export Export Citation Sciwheel EndNote Ref. Manager Bibtex ProCite Sente EXPORT Select a format first Track Share ▬ ✚ Research Article Do hospitalizations push households into poverty in India: evidence from national data [version 1; peer review: 2 approved, 1 approved with reservations] Shyamkumar Sriram https://orcid.org/0000-0003-4906-1405 1 , Muayad Albadrani 2 Shyamkumar Sriram https://orcid.org/0000-0003-4906-1405 1 , Muayad Albadrani 2 PUBLISHED 21 Mar 2024 Author details Author details 1 Department of Social and Public Health, Ohio University, Athens, Ohio, 45701, USA 2 Department of Family and Community Medicine, Taibah University, Medina, Al Madinah Province, Saudi Arabia Shyamkumar Sriram Roles: Conceptualization, Data Curation, Formal Analysis, Funding Acquisition, Investigation, Methodology, Project Administration, Resources, Software, Supervision, Validation, Visualization, Writing – Original Draft Preparation, Writing – Review & Editing Muayad Albadrani Roles: Data Curation, Formal Analysis, Funding Acquisition, Investigation, Methodology, Project Administration, Software, Supervision, Validation, Visualization, Writing – Original Draft Preparation, Writing – Review & Editing OPEN PEER REVIEW DETAILS REVIEWER STATUS Abstract Introduction High percentage of OOP (Out-of-Pocket) costs can lead to poverty and exacerbate existing poverty, with 21.9% of India’s 1.324 billion people living below the poverty line. Factors such as increased patient cost-sharing, high-deductible health plans, and expensive medications contribute to high OOP costs. Understanding the poverty-inducing impact of healthcare payments is essential for formulating effective measures to alleviate it. Methods The study used data from the 75th round of the National Sample Survey Organization (Household Social Consumption in India: Health) from July 2017-June 2018, focusing on demographic-socio-economic characteristics, morbidity status, healthcare utilization, and expenditure. The analysis included 66,237 hospitalized individuals in the last 365 days. Logistic regression model was used to examine the impact of OOP expenditures on impoverishment. Results Logistic regression analysis shows that there is 0.2868 lower odds of experiencing poverty due to OOP expenditures in households where there is the presence of at least one child aged 5 years and less present in the household compared to households who do not have any children. There is 0.601 higher odds of experiencing poverty due to OOP expenditures in urban areas compared to households in rural areas. With an increasing duration of stay in the hospital, there is a higher odds of experiencing poverty due to OOP health expenditures. There is 1.9013 higher odds of experiencing poverty due to OOP expenditures if at least one member in the household used private healthcare facility compared to households who never used private healthcare facilities. Conclusion In order to transfer demand from private to public hospitals and reduce OOPHE, policymakers should restructure the current inefficient public hospitals. More crucially, there needs to be significant investment in rural areas, where more than 70% of the poorest people reside and who are more vulnerable to OOP expenditures because they lack coping skills. READ ALL READ LESS Keywords Poverty, Out-of-Pocket Health Expenditures, India, Healthcare Corresponding Author(s) Shyamkumar Sriram ( [email protected] ) Close Corresponding author: Shyamkumar Sriram Competing interests: No competing interests were disclosed. Grant information: The author(s) declared that no grants were involved in supporting this work. Copyright: © 2024 Sriram S and Albadrani M. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. How to cite: Sriram S and Albadrani M. Do hospitalizations push households into poverty in India: evidence from national data [version 1; peer review: 2 approved, 1 approved with reservations] . F1000Research 2024, 13 :205 ( https://doi.org/10.12688/f1000research.145602.1 ) First published: 21 Mar 2024, 13 :205 ( https://doi.org/10.12688/f1000research.145602.1 ) Latest published: 21 Mar 2024, 13 :205 ( https://doi.org/10.12688/f1000research.145602.1 ) Introduction The protection of households from financial risks that are associated with medical expenses is one of the key objectives of health systems. 1 India is actively taking steps to offer its population universal health coverage (UHC). As the core of UHC, financial protection is regarded as essential. India is ranked third in the Southeast Asian region in terms of “countries with highest OOP expenditure on health,” according to the World Health Organization. OOP costs are people’s direct payments to healthcare providers at the time-of-service usage, according to the World Health Organization (WHO). 2 OOPs are defined as completely private transactions (payments made by patients to private physicians and pharmacies), official patient cost-sharing (user fees/copayments) within predetermined public or private benefit packages, and informal payments (payments made in excess of the prescriptions covered by benefits, both in cash and in kind). OOPs can therefore occur through market transactions, as an explicit part of a policy, or both. OOP health spending may rise whenever families choose to utilize and receive healthcare services, but they are not shielded from high expenses since healthcare is expensive. 3 OOP costs make up around 62.6% of all health spending in India, which is one of the highest percentages in the world. 4 In India, OOP health costs account for a sizeable amount of total household spending, which inadvertently drives down spending on other essential items and lowers household wellbeing overall. In contrast to the “health for all” idea that was more prevalent in the previous decade, the present policy discussion is about “health for all with financial protection”. 5 The National Health Policy 2017 of India places a high priority on affordability and the reduction of financial risk. 6 In order to improve fair financing, it is not thought that OOP healthcare payments are a good way to pay for medical services. OOP payments are not a cost-effective way to pay for healthcare, and they may have a negative impact on equity and push vulnerable people into poverty. 7 High OOP medical costs can deplete savings and ruin credits, negatively affect medication adherence, quality of life, and other health outcomes. 8 OOP payments that are relatively significant have the potential to put vulnerable households into poverty and exacerbate the poverty of households who are already poor. According to the 2011 World Bank Poverty Line of USD 1.90, around 21.9% of India’s 1.324 billion people live below the poverty line. 9 High OOP health costs have an impact on household finances and cause many to fall into poverty, according to the evidence. 10 According to a research conducted in India, OOP healthcare payments caused 2.2% of the population to live below the poverty level. 11 OOP health costs in India cause the impoverishment of up to 39 million people each year. 12 , 13 The incidence and depth of poverty can indeed be increased by OOP health expenses, according to the data. Furthermore, poverty has a detrimental effect on one’s health. 14 The most significant methods used by households to cover costs include selling assets and borrowing money. OOP healthcare payments worsen both the occurrence and degree of poverty. 15 In India, majority of health insurance plans solely cover only hospitalization costs. 16 An expected situation in a country with a good health financial protection system is that no one should be forced into poverty as a result of incurring medical costs because of healthcare utilization. 17 , 18 While some households may spend a higher percentage of their income on healthcare, others may spend a much smaller percentage of their income on healthcare and still be considered to be pushed below the poverty line. According to a recent World Bank Group analysis, OOP payments made up a sizeable portion of all healthcare costs in Central and Eastern European nations. Additionally, patients in poor nations pay out-of-pocket for healthcare treatments at a rate of half a trillion dollars annually (about $80 per person). 19 Unfortunately, the poor suffered greatly as a result of these costs. It becomes more challenging for the Poor People’s Health Insurance Program to offer coverage to households that enter poverty if more people are made poorer by OOP expenses. Even those households who are not particularly near to the poverty threshold may become impoverished as a result of OOP expenses. It becomes challenging for the insurance programs for the poor to remain adaptable enough to permit frequent entry and exit without involving significant administrative expenditures due to the dynamic character of poverty. Additionally, understanding how OOP health spending affects poverty is essential for formulating effective measures to alleviate it. The impact of OOP health expenditures on poverty and the numerous factors that influence the occurrence of poverty are the primary research questions this study would focus on. These are the specific inquiries: (i) What steps may be taken to prevent poverty from spreading? And (ii) what are the variables influencing the incidence of household poverty brought on by OOP medical expenses in India? Using the most recent Social Consumption and Health Survey from the National Sample Survey Organization (NSSO), this study makes an effort to determine how OOP payments affect poverty in India. 20 Implementing strong policies can shield households from the frequent and high costs of the healthcare system due to a lack of resources. This analysis is valuable for formulating policies and programs to fight poverty in India, specifically to develop methods for reducing financial risk. Methods Data source The study employed national representative unit-level cross-sectional data from the 75th round of the National Sample Survey Organization (Household Social Consumption in India: Health). The survey was conducted under the stewardship of the Ministry of Statistics and Programme Implementation , Government of India during the time period of July 2017-June 2018. The survey schedule collects the information pertaining to the demographic - socio-economic characteristics , morbidity status , utilization of healthcare services and healthcare expenditure across ambulatory, inpatient, delivery and immunization care for households and individuals. A two-stage stratified random sampling design was adopted in the survey with census villages and urban blocks as the First Stage Units for rural and urban areas respectively and households as the Second Stage Units. Overall sample size consisted of the 1,13,823 households and 5,57,887 individuals (including the death cases). The analysis however, circumscribed 66,237 individuals who were hospitalized in the last 365 days of the survey (without childbirth episodes). The detailed information on the survey design can be found in the official report released by the National Sample Survey Organization. Factors affecting incidence of impoverishment due to OOP health expenditures To study the effects of various factors on the occurrence of impoverishment due to OOP health expenditures, the logistic regression model will be used. The logistic regression model is preferred since the dependent variable is dichotomous. “Whether a household falls below poverty line after making OOP healthcare payments?” will be used as the dependent variable. A dichotomous variable for impoverishment will be created with 0 for not falling below poverty line after making OOP healthcare payments and 1 for falling below poverty line after making OOP healthcare payments. Thus, the dichotomous variable created for incidence of impoverishment in the household will serve as the dependent variable for the logistic regression model. The independent variables include the various characteristics of the households. Results Descriptive statistics of the sample are shown in Table 1 which shows that 47.34% of households reported presence of at least one child (aged 5 years and less) in the household. 30.54% of households reported presence of at least one elderly person (aged 60 years and above) in the household. 41.85% of households reported presence of at least one secondary educated member in the households. 55.54% of households were located in the rural areas and 44.46% of households were located in in urban areas. Majority, 20.54% of households reported socioeconomic status of household as lowest income quartile and 19.64% of households reported socioeconomic status of household as highest income quartile. 44.09% of households were small (1-4 members). 47.01% of households were medium (5-8 members) and 8.90% of households were large (9 and more). 37.02% of households reported that at least one member in the household used a private healthcare facility for hospitalization. Table 1. Descriptive statistics of categorical and continuous variables. Variables Definitions and categories Frequency (%) Weighted percentage (%) Age groups (children) Presence of at least one child (aged 5 years and less) in the household 47.34% 33.25% Age groups (elderly) Presence of at least one elderly person (aged 60 years and above) in the household 30.54% 29.87% Marital status Presence of someone in the household 23.62% 21.23% Female education Presence of at least one secondary educated member in the household 41.85% 41.35% Location of household Rural 55.54% 66.90% Urban 44.46% 33.10% Socioeconomic status of household Lowest income quartile 20.54% 30.05% Second income quartile 19.27% 22.01% Third income quartile 20.87% 21.87% Fourth income quartile 19.68% 15.60% Highest income quartile 19.64% 10.47% Drinking water Safe water 97.66% 99.70% Unsafe water 2.34% 1.10% Household cooking fuel Unclean fuels 52.90% 6.05% Clean fuels 47.10% 39.7% Drainage type Open (kutcha and pucca) 41.83% 39.01% Covered (pucca and underground) 28.41% 27.91% No drainage 29.76% 33.08% Latrine type Service and pit latrine 21.84% 17.18% Septic tank/flush system 46.80% 41.05% No latrine and others 31.30% 41.77% Household size Small household (1-4 members) 44.09% 54.91% Medium household (5-8 members) 47.01% 41.07% Large household (9 and more) 8.90% 4.02% Religion of the household Hinduism 77.01% 81.20% Islam 14.01% 13.04% Christianity 5.86% 2.75% Other religions 3.12% 3.01% Social group of the household Scheduled tribes 13.01% 9.01% Scheduled castes 15.09% 18.98% Other backward castes 40.89% 45.54% Others 31.01% 26.47% Level of care of hospitalization If at least one member in the household used a private healthcare facility for hospitalization 37.02% 10.03% Variables Definition Mean Standard Error Sex Proportion of female members in the household 0.4901 0.0017 Health Insurance coverage Proportion of members enrolled in health insurance in each household 0.1703 0.0035 Chronic Illness Proportion of members suffering from chronic illness in each household 0.0653 0.0013 Hospitalization Proportion members hospitalized in each household 0.0501 0.0006 Duration of hospitalization Total duration of hospitalization of all members in the household 1.3001 0.02500 Duration of ailment Total duration of ailment of all members in each household 412.095 11.901 Monthly consumption expenditure Total consumption expenditure of all members in each household 37,878.30 304.9445 Monthly inpatient OOP health expenditure Total inpatient OOP health expenditure of all members in each household 245.5302 10.4567 Monthly outpatient OOP health expenditure Total outpatient OOP health expenditure of all members in each household 121.098 8.238854 Total monthly OOP health expenditure Total OOP health expenditures of all members in each household 398.089 14.0199 Table 2 shows the incidence of poverty. 15.95% of total households reported poverty which increased to 18.89% after making OOP payments. In rural areas, the incidence of poverty was 18.90% which increased to 21.90 after making OOP payments. In urban areas, the incidence of poverty was 9.30% which increased to 11.30 after making OOP payments. The incidence of poverty in lowest income quartile was 66.98% which increased to 71.03% after making OOP payments. The incidence of poverty was 17.34% for less than 5 days duration of stay in hospital which increased to 18.89% after making OOP payments, while the incidence of poverty was 13.23% for more than 20 days duration of stay in hospital which increased to 32.73% after making OOP payments. The incidence of poverty was 11.23% for at least one member in the household used private healthcare facility which increased to 26.23% after making OOP payments while the incidence of poverty was 18.02% when no member in the household used private healthcare facility which increased to 19.02% after making OOP payments. The incidence of poverty was 24.23% when at least one child aged 5 years and less in the household which increased to 28.01% after making OOP payments. The incidence of poverty was 17.65% where at least one elderly person aged 60 years and above in the household which increased to 20.93% after making OOP payments. Table 2. Incidence of poverty by demographic and household characteristics. Variables Categories Incidence of poverty in population (%) Incidence of poverty among poor people (%) Incidence of poverty after making OOP payments in population (%) Incidence of poverty after making OOP payments among poor people (%) Percentage of total households reporting poverty 15.95 100 18.89 100 Sector Rural 18.90 81.62 21.90 81.32 Urban 9.30 18.38 11.30 18.68 Socioeconomic status of the household Lowest income quartile 66.98 92.52 71.03 82.01 Second lowest income quartile 4.98 7.45 12.01 11.78 Third income quartile 0.00006 0.000083 3.02 0.0324 Fourth income quartile 0 0 0 0.00143 Highest fifth income quartile 0 0 0 0.0112 Household size Small household 9.45 31.02 10.95 31.99 Medium household 24.01 60.55 25.02 59.00 Large household 34.00 8.43 28.09 9.01 Religion of the household Hinduism 15.83 82.01 19.14 81.54 Islam 19.01 14.23 22.01 15.23 Christianity 14.95 3.10 17.23 2.05 Other religions 14.67 0.66 15.36 1.18 Social group of the household Scheduled tribes 32.13 18.23 34.23 16.23 Scheduled castes 23.23 26.02 26.12 27.23 Other backward classes 16.23 39.62 19.01 41.23 Others 9.03 16.13 12.44 15.31 Duration of stay in hospital Less than 5 days 17.34 94.89 18.89 88.61 5-10 days 14.23 2.21 29.89 7.01 11-20 days 14.34 1.87 32.78 3.26 More than 20 days 13.23 1.03 32.73 1.12 Private healthcare facility for hospitalization If atleast one member in the household used private healthcare facility 11.23 7.23 26.23 14.23 No member in the household used private healthcare facility 18.02 92.77 19.02 85.77 Child aged 5 years and less in the household At least one child aged 5 years and less in the household 24.23 47.01 28.01 46.91 No child aged 5 years and less in the household 13.97 52.99 15.21 53.09 Elderly people aged 60 years and above At least one elderly person aged 60 years and above in the household 17.65 29.21 20.93 31.12 No elderly people aged 60 years and above in the household 16.23 70.79 19.23 68.88 Secondary educated female in household At least one secondary educated female in household 9.56 21.12 23.14 31.23 No secondary educated female in household 21.43 78.88 19.12 68.77 Divorced person in household At least one divorced person in household 19.02 26.01 21.12 26.23 No divorced person in household 18.09 73.99 20.23 73.77 Table 3 shows the intensity of poverty due to OOP health expenditures. The poverty gap increased from 19.45% to 23.01% after making OOP payments. In rural areas, the intensity of poverty before making OOP payments was 19.01% which increased to 21.01% after making OOP payments while in the urban areas, the intensity of poverty before making OOP payments was 20.01% which increased to 21.01% after making OOP payments. The intensity of poverty before making OOP payments in lowest income quartile was 21.01% which increased to 23.01% after making OOP payments while in the highest fifth income quartile it increased from 0% to 41.01% after making OOP payments. The intensity of poverty before making OOP payments was 19.34% for less than 5 days duration of stay in hospital which increased to 22.34% after making OOP payments and the intensity of poverty before making OOP payments was 22.13% for more than 20 days duration of stay in hospital which increased to 42.01% after making OOP payments. The intensity of poverty before making OOP payments was 19.43% if at least one member in the household used private healthcare facility which increased to 33.67% after making OOP payments. Table 3. Intensity of poverty by demographic and household characteristics. Variables Categories Pre-OOP payment poverty gap (%) Post-OOP payment poverty gap (%) Normalized poverty gap 19.45 23.01 Sector Rural 19.01 21.01 Urban 20.01 Socioeconomic status of the household Lowest expenditure quartile 21.01 23.01 Second lowest expenditure quartile 6.23 19.03 Third expenditure quartile 1.56 31.02 Fourth expenditure quartile 0 34.14 Highest fifth expenditure quartile 0 41.01 Household size Small household 17.01 22.03 Medium household 20.01 23.01 Large household 23.01 27.45 Religion of the household Hinduism 19.75 23.45 Islam 18.04 27.03 Christianity 17.06 23.45 Other religions 22.03 26.01 Social group of the household Scheduled tribes 24.23 25.23 Scheduled castes 20.23 24.34 Other backward classes 18.15 22.02 Others 17.25 22.13 Duration of stay in hospital Less than 5 days 19.34 22.34 5-10 days 18.98 31.23 11-20 days 21.23 37.23 More than 20 days 22.13 42.01 Private healthcare facility for hospitalization If atleast one member in the household used private healthcare facility 19.43 33.67 No member in the household used private healthcare facility 19.23 22.41 Child aged 5 years and less in the household At least one child aged 5 years and less in the household 19.83 23.45 No child aged 5 years and less in the household 19.23 22.67 Elderly people aged 60 years and above At least one elderly person aged 60 years and above in the household 18.78 23.43 No elderly people aged 60 years and above in the household 19.78 22.52 Secondary educated female in household At least one secondary educated female in household 17.56 22.63 No secondary educated female in household 19.67 23.23 Divorced person in household At least one divorced person in household 18.01 23.76 No divorced person in household 18.98 22.98 Table 4 shows the logistic regression analysis results for the incidence of poverty due to OOP health expenditures. Logistic regression analysis shows that there is 0.2868 lower odds of experiencing poverty due to OOP expenditures in households where there is the presence of at least one child aged 5 years and less present in the household compared to households who do not have any children. There is 0.601 higher odds of experiencing poverty due to OOP expenditures in households in urban areas compared to households in rural areas. There is a decrease in the odds of experiencing poverty due to OOP expenditures in households with an increase in household income. Both medium and larger households have lower odds of incurring poverty due to OOP health expenditures compared to smaller households. With an increasing duration of stay in the hospital, there is a higher odds of experiencing poverty due to OOP health expenditures with an odds of 1.4013 of experiencing poverty due to OOP expenditures for a 5-10 duration of stay in hospital compared to other stay durations compared to 13.9702 higher odds of experiencing poverty due to OOP expenditures for more than 20 days duration of stay in hospital. There is 1.9013 higher odds of experiencing poverty due to OOP expenditures if at least one member in the household used private healthcare facility compared to households who never used private healthcare facilities for treatment. There is 4.6781 higher odds of experiencing poverty due to OOP expenditures if the household has members who suffer from chronic illnesses. Table 4. Logistic regression results for the incidence of impoverishment due to OOP health expenditures. Incidence of poverty after making OOP payments Odds ratio 95% Confidence Interval P Presence of at least one child aged 5 years and less present in the household 0.7132 0.6740 – 0.9027 0.001 Presence of at least one elderly aged 60 years and above present in the household 1.0831 0.8601 – 1.3189 0.890 Presence of someone divorced in the household 1.1234 0.7638 – 1.3456 0.197 Sector Rural (reference) Urban 1.6010 1.4234 – 1.7234 0.000 Socioeconomic status Poorest income quartile (reference) Second lowest income quartile 0.8207 0.1324 – 0.2345 0.0000 Third income quartile 0.0512 0.0301 – 0.0645 0.0000 Fourth income quartile 0.0231 0.0112 – 0.3932 0.0000 Highest fifth income quartile 0.0093 0.0065 – 0.0234 0.0000 Household size Small household (reference) Medium household (5-8) 0.6907 0.5656 – 0.8378 0.000 Large household (9 or more) 0.4967 0.3891 – 0.6331 0.000 Duration of stay in hospital Less than 5 days 5-10 days 2.4013 2.1016 – 2.9785 0.000 11-20 days 4.9014 4.1234 – 6.0980 0.000 More than 20 days 14.9702 10.987 – 19.876 0.000 At least one member in the household used private healthcare facility 2.9013 1.9896 – 3.4352 0.000 Proportion of female members in the household 1.0623 0.6457 – 1.1101 0.987 Proportion of members with chronic illness in each household 5.6781 0.3452 – 9.8901 0.000 At least one member is covered by insurance 0.7235 0.5734 – 0.8345 0.000 Constant 1.6545 0.8890 – 3.0987 0.301 Also, most importantly, there is a 0.2765 lower odds of experiencing poverty due to OOP expenditures if at least one member is covered by health insurance, highlighting the importance of health insurance coverage in protecting households from impoverishment due to OOP health expenditures. Discussion Our studies indicate that the population’s overall poverty rate was 18.89% after OOP payments, and that the normalized poverty difference among households that were already poor due to OOP medical expenses widened by 3.06%. Our findings fall short of World Bank estimates, according to which 21.9% of the population lived below the poverty line, calculated using the updated World Bank Poverty Line. 21 Another research that used NSS data for the years 1995–1996 indicated that 2.2% of the population was living in poverty as a result of OOP health expenses. 22 The results we have obtained indicate that after making OOP payments, the prevalence of poverty has increased among households belonging to various SES levels. According to the results of the logistic model, all households in all other quintiles of expenditure have lower probability of being poor than the poorest families. The likelihood of being financially poor as a result of OOP health expenses decreased steadily as the socioeconomic status of the households rose, with the richest households having the lowest probabilities. This result is in line with other research that has been published in the literature. 23 , 24 Our study showed that the presence of at least one child aged 5 years and less present in the household increases the incidence of poverty after making OOP payments. Studies carried out in Ethiopia also demonstrated that presence of at least one child aged 5 years and less present in the household increases the incidence of poverty after making OOP payments. 25 Our study showed that households in urban areas experienced increased incidence of poverty after making OOP payments compared to rural areas. Research carried out in low-income countries like Uganda, Malawi and Nigeria showed that households in urban areas experienced increased the incidence of poverty after making OOP payments compared to rural areas. 26 Similar studies in Ethiopia found that households in urban areas experienced increased the incidence of poverty after making OOP payments compared to rural areas. 27 Our studies show that households in lowest income quartiles experienced increased incidence of poverty after making OOP payments compared to higher income quartiles. Research on this issue demonstrated that households in lowest income quartiles experienced increased incidence of poverty after making OOP payments compared to higher income quartiles. 28 Another study in Kenya found that households in lowest income quartiles experienced increased incidence of poverty after making OOP payments compared to higher income quartiles. 29 Similar study carried out in Uganda showed that low-income households experienced increased incidence of poverty after making OOP payments compared to their higher income counterparts. 30 Our study showed that medium and large sized households experienced increased the incidence of poverty after making OOP payments compared to small sized households. Findings from a study done in Turkey found that household size played an important role in increased incidence of poverty after making OOP payments. 31 A study in India found that medium and large sized households experienced increased the incidence of poverty after making OOP payments compared to small sized households. 32 Similar study in India found that medium and large sized households experienced increased the incidence of poverty after making OOP payments. 33 Our study shows that with increased duration of stay in hospital increases the incidence of poverty after making OOP payments. Other research carried out in India showed that with increased duration of stay in hospital increases the incidence of poverty after making OOP payments. 34 Another study in India found that with increased duration of stay in hospital increases the incidence of poverty after making OOP payments. 35 Similar study in Bangladesh found that duration of hospital stay has profound impact on increasing the incidence of poverty after making OOP payments. 36 Our study showed that the presence of at least one member in the household who used private healthcare facilities increases the incidence of poverty after making OOP payments. A study carried out in Kenya showed that using private healthcare facility increases the incidence of poverty after making OOP payments. 29 Another study carried out in Tajikistan found that using private healthcare facility increases the incidence of poverty after making OOP payments. 37 Similar study in Turkey found that using private healthcare facility increases the incidence of poverty after making OOP payments. 38 Our studies show that the proportion of members with chronic illness in each household increases the incidence of poverty after making OOP payments. A study carried out in India demonstrated that number of members with chronic illness in each household increases the incidence of poverty after making OOP payments. 39 Another study in Nepal found that a greater number of members with chronic illness in each household increases the incidence of poverty after making OOP payments. 40 Further research on this issue in low middle income countries found that family members with chronic illness increases the incidence of poverty after making OOP payments. 41 Our study showed that presence of at least one member is covered by insurance increases the incidence of poverty after making OOP payments compared to members not covered by insurance. It comes to light that long-term illness plays a significant role in predicting poverty brought on by OOP payments. According to studies, hospitalizations are also significantly influenced by chronic conditions. 42 In our analysis, the odds of poverty were more than twice as high for households with at least one member suffering from a chronic illness than they were for homes without such a member. Further studies conducted on this issue came to the same conclusion that chronic diseases are key factors driving households into poverty; the location of hospitalization, whether in a public or private institution, has an impact on health expenses. 43 , 44 Around 49% of all available beds are in the private sector, which is home to a sizable network of unregulated private hospitals in India. 45 Our research demonstrated that a person’s hospitalization location also affects whether or not OOP payments will cause them to become impoverished. A study in Turkey found that presence of at least one member is covered by insurance increases the incidence of poverty after making OOP payments compared to members not covered by insurance. 38 Another study in Ghana found that members with insurance experienced increased the incidence of poverty after making OOP payments compared to members not covered by insurance. 46 Similar study in Nigeria found that hat members with insurance experienced increased the incidence of poverty after making OOP payments compared to members not covered by insurance. 47 Our research demonstrates that, both in urban and rural areas, the prevalence of poverty has increased as a result of OOP payments. The proportion of persons who become poor after completing OOP payments has grown in urban regions relative to rural ones, although only slightly. This is because only poor people are taken into account. This demonstrates how OOP health expenses are higher for urban residents, which forces them into poverty. The results of the logistic regression also indicate that households in urban regions are more likely than those in rural areas to become impoverished as a result of OOP health expenses. According to evidence from the literature, the number of urban poor people is constantly growing as a result of poor people moving from rural areas to cities in pursuit of economic possibilities. The majority of these migrants settle in crowded city slums with subpar living circumstances. 48 According to the most recent census, 33% of Indians reside in urban settings, and 250 million more will do so by the year 2030. In this group, 27% of urban residents are below the poverty line. 49 Our estimations may have been skewed by the increased migration from rural to urban regions in quest of employment. Although there is a benefit to living in an urban area in terms of access to health care, most urban poor people do not have access to this benefit. 50 The National Rural Health Mission was established by the GOI in 2005 to address the health needs of the rural population. The National Urban Health Mission was not established by the government until 2014 to assist the urban poor, strengthen the health infrastructure in urban areas, and lower OOP health expenditures. 51 The absence of political will to address the health needs of the urban poor is demonstrated by the delay in developing the urban health program for the underprivileged. The National Urban Health Mission and other programs meant to mitigate the OOP burden of the urban population are not performing successfully, as seen by the higher likelihood of poverty among the urban population. Additionally, the majority of urban poor people who depend on daily income are unable to be admitted to hospitals, which may hinder their ability to go to work. However, none of the current health insurance plans available give coverage for outpatient care; the present health insurance programs for the poor only cover hospitalization. Due to the present health insurance programs for the poor’s lack of coverage for outpatient care and their desire to avoid losing their jobs, they may be forced to pay OOP, which will raise their costs. Additionally, compared to households with fewer individuals, larger households are less likely to become impoverished as a result of OOP health expenses. Larger families may be able to arrange for a member of the family to serve as a caretaker in the event of illness or incapacity, which is one of the most likely causes. Furthermore, many common ailments may not require hospitalization because of this family caregiving. Evidence from the United States demonstrates that home health care services have cut down on hospital visits and length of stays. 52 In India, 400 million people live on less than $1.25 per person per day, and according to our data, these poor people spend 11–15% of their total income on OOPHE on average. 53 OOPHE accounts for a substantial percentage of total spending, hence governments should offer health insurance to the poor to lessen their susceptibility to both health and economic shocks. The use of private clinics for medical treatment is the second factor contributing to the high OOPHE. 54 In India, private facilities account for more than 75 percent of health expenditures. Because of their superior health infrastructure and higher level of service, private institutions are preferred over public ones . In order to transfer demand from private to public hospitals and reduce OOPHE, policymakers should restructure the current inefficient public hospitals. More crucially, there needs to be significant investment in rural areas, where more than 70% of the poorest people reside and who are more vulnerable to CHE because they lack coping skills. Data availability The data from the National Sample Survey Organization (NSSO) of the Government of India was used for the study. Social Consumption (Health), NSS 75 th Round for 2017-2018 was used for this analysis. The survey covered whole of the Indian Union. Data can be obtained from the Government of India or from the corresponding author by reasonable request. References 1. Rahman T, Gasbarro D, Alam K: Financial risk protection from out-of-pocket health spending in low- and middle-income countries: a scoping review of the literature. Health Res. Policy Syst. 2022; 20 (1): 83. PubMed Abstract | Publisher Full Text | Free Full Text 2. Glossary|DataBank: 2024. Reference Source 3. Jalali FS, Bikineh P, Delavari S: Strategies for reducing out of pocket payments in the health system: a scoping review. Cost. Eff. Resour. Alloc. 2021; 19 (1): 47. PubMed Abstract | Publisher Full Text | Free Full Text 4. Sriram S, Albadrani M: A STUDY OF CATASTROPHIC HEALTH EXPENDITURES IN INDIA - EVIDENCE FROM NATIONALLY REPRESENTATIVE SURVEY DATA: 2014-2018. F1000Res 2022; 11 : 141. PubMed Abstract | Publisher Full Text | Free Full Text 5. EPHP: Third national conference on bringing Evidence into Public Health Policy Equitable India: All for Health and Wellbeing. PubMed 2016; 1 (Suppl 1): A1–A44. PubMed Abstract | Publisher Full Text | Free Full Text 6. National Health Policy 2017: 2017. Reference Source 7. Mchenga M, Chirwa GC, Chiwaula L: Impoverishing effects of catastrophic health expenditures in Malawi. Int. J. Equity Health 2017; 16 (1): 25. PubMed Abstract | Publisher Full Text | Free Full Text 8. Iuga AO, McGuire M: Adherence and health care costs. Risk Manag. Healthc. Policy. 2014; 7 : 35–44. PubMed Abstract | Publisher Full Text | Free Full Text 9. Power & Equity Brief: World Bank.2020. Reference Source 10. Alam K, Mahal A: Economic impacts of health shocks on households in low and middle income countries: a review of the literature. Glob. Health 2014; 10 (1): 21. PubMed Abstract | Publisher Full Text | Free Full Text 11. Garg C, Karan A: Reducing out-of-pocket expenditures to reduce poverty: a disaggregated analysis at rural-urban and state level in India. Health Policy Plan. 2008; 24 (2): 116–128. PubMed Abstract | Publisher Full Text 12. Nanda M, Sharma R: A comprehensive examination of the economic impact of out-of-pocket health expenditures in India. Health Policy Plan. 2023; 38 (8): 926–938. PubMed Abstract | Publisher Full Text 13. Vuong Q: Be rich or don’t be sick: estimating Vietnamese patients’ risk of falling into destitution. Springerplus. 2015; 4 (1). Publisher Full Text 14. Mchenga M, Chirwa GC, Chiwaula L: Impoverishing effects of catastrophic health expenditures in Malawi. Int. J. Equity Health 2017b; 16 (1): 25. PubMed Abstract | Publisher Full Text | Free Full Text 15. Begum A, Hamid SA: Impoverishment impact of out-of-pocket payments for healthcare in rural Bangladesh: Do the regions facing different climate change risks matter? PLoS One. 2021; 16 (6): e0252706. Publisher Full Text 16. Ghia CJ, Rambhad G: Implementation of equity and access in Indian healthcare: current scenario and way forward. J. Mark. Access Health Policy. 2023; 11 (1). PubMed Abstract | Publisher Full Text | Free Full Text 17. Sanoussi Y, Zounmenou AY, Ametoglo MES: Catastrophic health expenditure and household impoverishment in Togo. J. Public Health Res. 2023; 12 (3). PubMed Abstract | Publisher Full Text | Free Full Text 18. Sirag A, Nor NM: Out-of-Pocket Health Expenditure and Poverty: Evidence from a Dynamic Panel Threshold Analysis. Healthcare 2021; 9 (5): 536. PubMed Abstract | Publisher Full Text | Free Full Text 19. Jalali FS, Bikineh P, Delavari S: Strategies for reducing out of pocket payments in the health system: a scoping review. Cost Eff. Resour. Alloc. 2021; 19 (1): 47. PubMed Abstract | Publisher Full Text | Free Full Text 20. Sriram S, Albadrani M: Impoverishing effects of out-of-pocket healthcare expenditures in India. J. Family Med. Prim. Care 2022; 11 (11): 7120–7128. PubMed Abstract | Publisher Full Text | Free Full Text 21. World Bank Group: FAQs: Global Poverty Line Update. World Bank; 2019. Reference Source 22. Keane MP, Thakur R: Health care spending and hidden poverty in India. Res. Econ. 2018; 72 (4): 435–451. Publisher Full Text 23. Kumar AS, Chen LC, Choudhury M, et al. : Financing health care for all: challenges and opportunities. Lancet. 2011; 377 (9766): 668–679. Publisher Full Text 24. Sriram S, Khan MM: Effect of health insurance program for the poor on out-of-pocket inpatient care cost in India: evidence from a nationally representative cross-sectional survey. BMC Health Serv. Res. 2020; 20 (1): 839. PubMed Abstract | Publisher Full Text | Free Full Text 25. Hailemichael Y, Hanlon C, Tirfessa K, et al. : Catastrophic health expenditure and impoverishment in households of persons with depression: a cross-sectional, comparative study in rural Ethiopia. BMC Public Health. 2019; 19 (1). Publisher Full Text 26. Pinilla-Roncancio M, Amaya-Lara JL, Cedeño-Ocampo G, et al. : Catastrophic health-care payments and multidimensional poverty: Are they related? Health Econ. 2023; 32 (8): 1689–1709. PubMed Abstract | Publisher Full Text 27. Mekuria GA, Ali EE: The financial burden of out of pocket payments on medicines among households in Ethiopia: analysis of trends and contributing factors. BMC Public Health. 2023; 23 (1): 808. PubMed Abstract | Publisher Full Text | Free Full Text 28. Galbraith AA, Wong ST, Kim SE, et al. : Out-of-Pocket Financial Burden for Low-Income Families with Children: Socioeconomic Disparities and Effects of Insurance. Health Serv. Res. 2005; 40 (6p1): 1722–1736. PubMed Abstract | Publisher Full Text | Free Full Text 29. Barasa E, Maina T, Ravishankar N: Assessing the impoverishing effects, and factors associated with the incidence of catastrophic health care payments in Kenya. Int. J. Equity Health 2017; 16 (1): 31. PubMed Abstract | Publisher Full Text | Free Full Text 30. Opara C, Du Y, Kawakatsu Y, et al. : Household economic consequences of rheumatic heart disease in Uganda. Front. Cardiovasc. Med. 2021; 8 . PubMed Abstract | Publisher Full Text | Free Full Text 31. A Fresh Look at Out-of-Pocket Health Expenditures after More than a Decade Health Reform Experience in Turkey: A Data Mining Application - ProQuest: n.d. Reference Source 32. Garg C, Karan A: Reducing out-of-pocket expenditures to reduce poverty: a disaggregated analysis at rural-urban and state level in India. Health Policy Plan. 2008; 24 (2): 116–128. PubMed Abstract | Publisher Full Text 33. Shahrawat R, Rao KD: Insured yet vulnerable: out-of-pocket payments and India’s poor. Health Policy Plan. 2011; 27 (3): 213–221. PubMed Abstract | Publisher Full Text 34. Prinja S, Jagnoor J, Sharma D, et al. : Out-of-pocket expenditure and catastrophic health expenditure for hospitalization due to injuries in public sector hospitals in North India. PLoS One. 2019; 14 (11): e0224721. PubMed Abstract | Publisher Full Text | Free Full Text 35. Sriram S, Khan MM: Effect of health insurance program for the poor on out-of-pocket inpatient care cost in India: evidence from a nationally representative cross-sectional survey. BMC Health Serv. Res. 2020; 20 (1). Publisher Full Text 36. Hamid SA, Ahsan SM, Begum A: Disease-Specific Impoverishment Impact of Out-of-Pocket Payments for Health Care: Evidence from Rural Bangladesh. Appl. Health Econ. Health Policy. 2014; 12 (4): 421–433. PubMed Abstract | Publisher Full Text 37. Falkingham J: Poverty, out-of-pocket payments and access to health care: evidence from Tajikistan. Soc. Sci. Med. 2004; 58 (2): 247–258. PubMed Abstract | Publisher Full Text 38. Narcı HÖ, Şahin İ, Yıldırım HH: Financial catastrophe and poverty impacts of out-of-pocket health payments in Turkey. Eur. J. Health Econ. 2014; 16 (3): 255–270. PubMed Abstract | Publisher Full Text 39. Bhojani U, Thriveni B, Devadasan R, et al. : Out-of-pocket healthcare payments on chronic conditions impoverish urban poor in Bangalore, India. BMC Public Health. 2012; 12 (1). PubMed Abstract | Publisher Full Text | Free Full Text 40. Sapkota T, Houkes I, Bosma H: Vicious cycle of chronic disease and poverty: a qualitative study in present day Nepal. Int. Health 2020; 13 (1): 30–38. PubMed Abstract | Publisher Full Text | Free Full Text 41. Murphy A, McGowan CR, McKee M, et al. : Coping with healthcare costs for chronic illness in low-income and middle-income countries: a systematic literature review. BMJ Glob. Health 2019; 4 (4): e001475. PubMed Abstract | Publisher Full Text | Free Full Text 42. Skinner HG, Coffey RM, Jones J, et al. : The effects of multiple chronic conditions on hospitalization costs and utilization for ambulatory care sensitive conditions in the United States: a nationally representative cross-sectional study. BMC Health Serv. Res. 2016; 16 (1): 77. PubMed Abstract | Publisher Full Text | Free Full Text 43. Kumar K, Singh A, Kumar S, et al. : Socio-Economic Differentials in Impoverishment Effects of Out-of-Pocket Health Expenditure in China and India: Evidence from WHO SAGE. PLoS One. 2015; 10 (8): e0135051. PubMed Abstract | Publisher Full Text | Free Full Text 44. Jayathilaka R, Joachim S, Mallikarachchi V, et al. : Do chronic illnesses and poverty go hand in hand? PLoS One. 2020; 15 (10): e0241232. PubMed Abstract | Publisher Full Text | Free Full Text 45. India: International Health Care System Profiles|Commonwealth Fund.2024. Reference Source 46. Akazili J, Ataguba JE, Kanmiki EW, et al. : Assessing the impoverishment effects of out-of-pocket healthcare payments prior to the uptake of the national health insurance scheme in Ghana. BMC Int. Health Hum. Rights 2017; 17 (1): 13. PubMed Abstract | Publisher Full Text | Free Full Text 47. Aregbeshola BS, Khan SM: Out-of-Pocket payments, catastrophic health expenditure and poverty among households in Nigeria 2010. Int. J. Health Policy Manag. 2018; 7 (9): 798–806. PubMed Abstract | Publisher Full Text | Free Full Text 48. Kuddus A, Tynan E, McBryde ES: Urbanization: a problem for the rich and the poor? Public Health Rev. 2020; 41 (1): 1. PubMed Abstract | Publisher Full Text | Free Full Text 49. Pathak D, Vasishtha G, Mohanty SK: Association of multidimensional poverty and tuberculosis in India. BMC Public Health. 2021; 21 (1): 2065. PubMed Abstract | Publisher Full Text | Free Full Text 50. Sclar ED, Volavka-Close N: Urban Health: An Overview. Elsevier eBooks; 2011; 556–564. Publisher Full Text 51. Raichowdhury S, Khetrapal S, Chin B: Core interventions contributing to the effectiveness of the National Urban Health Mission in India. J. Glob. Health 2023; 13 . Publisher Full Text 52. Arsenault-Lapierre G, Henein M, Gaid D, et al. : Hospital-at-Home Interventions vs In-Hospital Stay for Patients With Chronic Disease Who Present to the Emergency Department. JAMA Netw. Open. 2021; 4 (6): e2111568. PubMed Abstract | Publisher Full Text | Free Full Text 53. World Bank Group: Report finds 400 million children living in extreme poverty. World Bank; 2013. Reference Source 54. Factors that affect Health-Care utilization: National Library of Medicine.2018. Reference Source Comments on this article Comments (0) Version 1 VERSION 1 PUBLISHED 21 Mar 2024 ADD YOUR COMMENT Comment Author details Author details 1 Department of Social and Public Health, Ohio University, Athens, Ohio, 45701, USA 2 Department of Family and Community Medicine, Taibah University, Medina, Al Madinah Province, Saudi Arabia Shyamkumar Sriram Roles: Conceptualization, Data Curation, Formal Analysis, Funding Acquisition, Investigation, Methodology, Project Administration, Resources, Software, Supervision, Validation, Visualization, Writing – Original Draft Preparation, Writing – Review & Editing Muayad Albadrani Roles: Data Curation, Formal Analysis, Funding Acquisition, Investigation, Methodology, Project Administration, Software, Supervision, Validation, Visualization, Writing – Original Draft Preparation, Writing – Review & Editing Competing interests No competing interests were disclosed. Grant information The author(s) declared that no grants were involved in supporting this work. Article Versions (1) version 1 Published: 21 Mar 2024, 13:205 https://doi.org/10.12688/f1000research.145602.1 Copyright © 2024 Sriram S and Albadrani M. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Download Export To Sciwheel Bibtex EndNote ProCite Ref. Manager (RIS) Sente metrics Views Downloads F1000Research - - PubMed Central info_outline Data from PMC are received and updated monthly. - - Citations open_in_new 0 open_in_new 0 open_in_new SEE MORE DETAILS CITE how to cite this article Sriram S and Albadrani M. Do hospitalizations push households into poverty in India: evidence from national data [version 1; peer review: 2 approved, 1 approved with reservations] . F1000Research 2024, 13 :205 ( https://doi.org/10.12688/f1000research.145602.1 ) NOTE: If applicable, it is important to ensure the information in square brackets after the title is included in all citations of this article. COPY CITATION DETAILS track receive updates on this article Track an article to receive email alerts on any updates to this article. TRACK THIS ARTICLE Share Open Peer Review Current Reviewer Status: ? Key to Reviewer Statuses VIEW HIDE Approved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested Approved with reservations A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit. Not approved Fundamental flaws in the paper seriously undermine the findings and conclusions Version 1 VERSION 1 PUBLISHED 21 Mar 2024 Views 0 Cite How to cite this report: Sekinat Opeloyeru O. Reviewer Report For: Do hospitalizations push households into poverty in India: evidence from national data [version 1; peer review: 2 approved, 1 approved with reservations] . F1000Research 2024, 13 :205 ( https://doi.org/10.5256/f1000research.159573.r261034 ) The direct URL for this report is: https://f1000research.com/articles/13-205/v1#referee-response-261034 NOTE: it is important to ensure the information in square brackets after the title is included in this citation. Close Copy Citation Details Reviewer Report 15 May 2024 Olaide Sekinat Opeloyeru , Tai Solarin University of Education, Ijebu Ode, Ogun State, Nigeria Approved with Reservations VIEWS 0 https://doi.org/10.5256/f1000research.159573.r261034 The introduction is attractive to read but the authors need to pass the message of the write up through existing literature. There is no trace of past research related to this work in India. I am aware ... Continue reading READ ALL The introduction is attractive to read but the authors need to pass the message of the write up through existing literature. There is no trace of past research related to this work in India. I am aware that a lot of work has been done in India which people have referenced. The authors need to insert a section separately on the literature review as well to show the gap filled in the existing literature. As it is, it is difficult to see the new contribution to existing literature. The sub-heading under the methodology “Factors affecting incidence of impoverishment due to OOP health expenditures” should be removed and the authors should avoid the use of future words like “will” since the work has been done and is not a proposal (an example of this is under methodology second paragraph, line 2.) The authors should explain how each variable was partitioned or designed for their study. Appropriate statistics were used but the interpretation and how data were reported should be fine-tuned. For example some statistics were reported in 3 decimal places and others in 4 decimal places, there should be consistency. Also, the interpretation of logistic regression should be improved on for readers to appreciate your work (for example, health services received through OOP in the urban area increases the chance or odds of living below the poverty by 60% compared to rural area which is in contrast to what you put in your paper as “There is 0.601 higher odds of experiencing poverty due to OOP expenditures in households in urban areas compared to households in rural areas”). The authors joined discussion of results with the conclusion. A separate heading should be created for conclusions and appropriate language should be used. For example, where the author used “coping skills”, I want to suggest the author use “coping strategies” On a general note, appropriate language and good editorial work is needed for this study e.g. “Similar study in Nigeria found that hat members with insurance experienced increased the incidence of poverty after making OOP payments compared to members not covered by insurance”. Is the work clearly and accurately presented and does it cite the current literature? Partly Is the study design appropriate and is the work technically sound? Partly Are sufficient details of methods and analysis provided to allow replication by others? Yes If applicable, is the statistical analysis and its interpretation appropriate? Partly Are all the source data underlying the results available to ensure full reproducibility? Yes Are the conclusions drawn adequately supported by the results? Partly Competing Interests: No competing interests were disclosed. I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above. Close READ LESS CITE CITE HOW TO CITE THIS REPORT Sekinat Opeloyeru O. Reviewer Report For: Do hospitalizations push households into poverty in India: evidence from national data [version 1; peer review: 2 approved, 1 approved with reservations] . F1000Research 2024, 13 :205 ( https://doi.org/10.5256/f1000research.159573.r261034 ) The direct URL for this report is: https://f1000research.com/articles/13-205/v1#referee-response-261034 NOTE: it is important to ensure the information in square brackets after the title is included in all citations of this article. COPY CITATION DETAILS Report a concern Respond or Comment COMMENT ON THIS REPORT Views 0 Cite How to cite this report: Bele S. Reviewer Report For: Do hospitalizations push households into poverty in India: evidence from national data [version 1; peer review: 2 approved, 1 approved with reservations] . F1000Research 2024, 13 :205 ( https://doi.org/10.5256/f1000research.159573.r261053 ) The direct URL for this report is: https://f1000research.com/articles/13-205/v1#referee-response-261053 NOTE: it is important to ensure the information in square brackets after the title is included in this citation. Close Copy Citation Details Reviewer Report 10 Apr 2024 Sumedh Bele , University of Oxford, Oxford, England, UK Approved VIEWS 0 https://doi.org/10.5256/f1000research.159573.r261053 Thank you for the opportunity to review this research article – Do hospitalizations push households into poverty in India: evidence from national data. This study makes valuable addition to the literature around the impact of out of pocket ... Continue reading READ ALL Thank you for the opportunity to review this research article – Do hospitalizations push households into poverty in India: evidence from national data. This study makes valuable addition to the literature around the impact of out of pocket (OOP) medical expenditures on poverty. Authors have appropriately analysed large dataset to demonstrate the impact of OOP on poverty. I just have few minor comments to further strengthen this article: - I would recommend authors to add citations for few key statements in the introduction section such as, :India is actively taking steps to offer its population universal health coverage (UHC)", "India is ranked third in the Southeast Asian region in terms of “countries with highest OOP expenditure on health,” according to the World Health Organization". - In its current format it is a little hard to understand key take home message from this study. So, I would suggest authors to carve out a "conclusion" section which provides succinct conclusion of this study. Is the work clearly and accurately presented and does it cite the current literature? Yes Is the study design appropriate and is the work technically sound? Yes Are sufficient details of methods and analysis provided to allow replication by others? Yes If applicable, is the statistical analysis and its interpretation appropriate? I cannot comment. A qualified statistician is required. Are all the source data underlying the results available to ensure full reproducibility? Yes Are the conclusions drawn adequately supported by the results? Yes Competing Interests: No competing interests were disclosed. Reviewer Expertise: public health and health services research I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard. Close READ LESS CITE CITE HOW TO CITE THIS REPORT Bele S. Reviewer Report For: Do hospitalizations push households into poverty in India: evidence from national data [version 1; peer review: 2 approved, 1 approved with reservations] . F1000Research 2024, 13 :205 ( https://doi.org/10.5256/f1000research.159573.r261053 ) The direct URL for this report is: https://f1000research.com/articles/13-205/v1#referee-response-261053 NOTE: it is important to ensure the information in square brackets after the title is included in all citations of this article. COPY CITATION DETAILS Report a concern Respond or Comment COMMENT ON THIS REPORT Views 0 Cite How to cite this report: Narayanan S. Reviewer Report For: Do hospitalizations push households into poverty in India: evidence from national data [version 1; peer review: 2 approved, 1 approved with reservations] . F1000Research 2024, 13 :205 ( https://doi.org/10.5256/f1000research.159573.r261054 ) The direct URL for this report is: https://f1000research.com/articles/13-205/v1#referee-response-261054 NOTE: it is important to ensure the information in square brackets after the title is included in this citation. Close Copy Citation Details Reviewer Report 05 Apr 2024 Seetharaman Narayanan , Professor and Head of Community Medicine, KMCH Institute of Health Sciences and Research, Coimbatore, Tamilnadu, India Approved VIEWS 0 https://doi.org/10.5256/f1000research.159573.r261054 Assessment: 1. Presentation and Literature Review: The article is well-structured and clearly presented. It provides a comprehensive review of relevant literature, highlighting the importance of the research problem and situating the study within the existing body of knowledge. ... Continue reading READ ALL Assessment: 1. Presentation and Literature Review: The article is well-structured and clearly presented. It provides a comprehensive review of relevant literature, highlighting the importance of the research problem and situating the study within the existing body of knowledge. 2. Study Design and Academic Merit: The study design is appropriate for addressing the research questions. The use of nationally representative survey data from the NSSO enhances the generalizability and academic merit of the findings. 3. Methods and Repeatability: The methods section provides sufficient details on the data source, variables, and analytical techniques (logistic regression) to allow for replication by others. A short discussion on the suitability of the World bank definition of poverty line (over any other definition of poverty line) would be helpful. 4. Statistical Analysis: The statistical analysis appears appropriate, with logistic regression models employed to examine the factors influencing the incidence of poverty due to OOPHE. The interpretation of the results is generally sound. 5. Data Availability: The authors mention that the data can be obtained from the Government of India or by reasonable request. It would be preferable to provide more specific information on data accessibility to enhance transparency and reproducibility. 6. Conclusions and Support: The conclusions drawn are generally supported by the results presented. The authors highlight the crucial role of health insurance coverage in protecting households from impoverishment due to OOPHE and the need for policy interventions to improve access to public healthcare facilities, particularly in rural areas. Strengths: - Nationally representative data enhances generalizability. - Comprehensive literature review and sound methodology. - Highlights the role of health insurance and public healthcare access in alleviating poverty due to OOPHE. Suggestions: - Clarify the applicability of the World Bank defined poverty line (vis-a-vis any other methodology to define the poverty line currently in use, in India) in the analysis. - Provide more specific information on accessing the source data data from NNSO, to enhance reproducibility. - Discuss potential limitations and directions for future research. - Expand on the policy implications and recommendations for addressing the identified issues. Overall, the article makes a valuable contribution to understanding the impoverishing effects of OOPHE in India and identifying factors that influence household poverty. Is the work clearly and accurately presented and does it cite the current literature? Yes Is the study design appropriate and is the work technically sound? Yes Are sufficient details of methods and analysis provided to allow replication by others? Yes If applicable, is the statistical analysis and its interpretation appropriate? Yes Are all the source data underlying the results available to ensure full reproducibility? Yes Are the conclusions drawn adequately supported by the results? Yes Competing Interests: No competing interests were disclosed. Reviewer Expertise: Public Health, Health Economics I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard. Close READ LESS CITE CITE HOW TO CITE THIS REPORT Narayanan S. Reviewer Report For: Do hospitalizations push households into poverty in India: evidence from national data [version 1; peer review: 2 approved, 1 approved with reservations] . F1000Research 2024, 13 :205 ( https://doi.org/10.5256/f1000research.159573.r261054 ) The direct URL for this report is: https://f1000research.com/articles/13-205/v1#referee-response-261054 NOTE: it is important to ensure the information in square brackets after the title is included in all citations of this article. COPY CITATION DETAILS Report a concern Respond or Comment COMMENT ON THIS REPORT Comments on this article Comments (0) Version 1 VERSION 1 PUBLISHED 21 Mar 2024 ADD YOUR COMMENT Comment keyboard_arrow_left keyboard_arrow_right Open Peer Review Reviewer Status info_outline Alongside their report, reviewers assign a status to the article: Approved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested Approved with reservations A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit. Not approved Fundamental flaws in the paper seriously undermine the findings and conclusions Reviewer Reports Invited Reviewers 1 2 3 Version 1 21 Mar 24 read read read Seetharaman Narayanan , KMCH Institute of Health Sciences and Research, Coimbatore, India Sumedh Bele , University of Oxford, Oxford, UK Olaide Sekinat Opeloyeru , Tai Solarin University of Education, Ijebu Ode, Nigeria Comments on this article All Comments (0) Add a comment Sign up for content alerts Sign Up You are now signed up to receive this alert Browse by related subjects keyboard_arrow_left Back to all reports Reviewer Report 0 Views copyright © 2024 Sekinat Opeloyeru O. This is an open access peer review report distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 15 May 2024 | for Version 1 Olaide Sekinat Opeloyeru , Tai Solarin University of Education, Ijebu Ode, Ogun State, Nigeria 0 Views copyright © 2024 Sekinat Opeloyeru O. This is an open access peer review report distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. format_quote Cite this report speaker_notes Responses (0) Approved With Reservations info_outline Alongside their report, reviewers assign a status to the article: Approved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested Approved with reservations A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit. Not approved Fundamental flaws in the paper seriously undermine the findings and conclusions The introduction is attractive to read but the authors need to pass the message of the write up through existing literature. There is no trace of past research related to this work in India. I am aware that a lot of work has been done in India which people have referenced. The authors need to insert a section separately on the literature review as well to show the gap filled in the existing literature. As it is, it is difficult to see the new contribution to existing literature. The sub-heading under the methodology “Factors affecting incidence of impoverishment due to OOP health expenditures” should be removed and the authors should avoid the use of future words like “will” since the work has been done and is not a proposal (an example of this is under methodology second paragraph, line 2.) The authors should explain how each variable was partitioned or designed for their study. Appropriate statistics were used but the interpretation and how data were reported should be fine-tuned. For example some statistics were reported in 3 decimal places and others in 4 decimal places, there should be consistency. Also, the interpretation of logistic regression should be improved on for readers to appreciate your work (for example, health services received through OOP in the urban area increases the chance or odds of living below the poverty by 60% compared to rural area which is in contrast to what you put in your paper as “There is 0.601 higher odds of experiencing poverty due to OOP expenditures in households in urban areas compared to households in rural areas”). The authors joined discussion of results with the conclusion. A separate heading should be created for conclusions and appropriate language should be used. For example, where the author used “coping skills”, I want to suggest the author use “coping strategies” On a general note, appropriate language and good editorial work is needed for this study e.g. “Similar study in Nigeria found that hat members with insurance experienced increased the incidence of poverty after making OOP payments compared to members not covered by insurance”. Is the work clearly and accurately presented and does it cite the current literature? Partly Is the study design appropriate and is the work technically sound? Partly Are sufficient details of methods and analysis provided to allow replication by others? Yes If applicable, is the statistical analysis and its interpretation appropriate? Partly Are all the source data underlying the results available to ensure full reproducibility? Yes Are the conclusions drawn adequately supported by the results? Partly Competing Interests No competing interests were disclosed. I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above. reply Respond to this report Responses (0) Sekinat Opeloyeru O. Peer Review Report For: Do hospitalizations push households into poverty in India: evidence from national data [version 1; peer review: 2 approved, 1 approved with reservations] . F1000Research 2024, 13 :205 ( https://doi.org/10.5256/f1000research.159573.r261034) NOTE: it is important to ensure the information in square brackets after the title is included in this citation. The direct URL for this report is: https://f1000research.com/articles/13-205/v1#referee-response-261034 keyboard_arrow_left Back to all reports Reviewer Report 0 Views copyright © 2024 Bele S. This is an open access peer review report distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 10 Apr 2024 | for Version 1 Sumedh Bele , University of Oxford, Oxford, England, UK 0 Views copyright © 2024 Bele S. This is an open access peer review report distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. format_quote Cite this report speaker_notes Responses (0) Approved info_outline Alongside their report, reviewers assign a status to the article: Approved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested Approved with reservations A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit. Not approved Fundamental flaws in the paper seriously undermine the findings and conclusions Thank you for the opportunity to review this research article – Do hospitalizations push households into poverty in India: evidence from national data. This study makes valuable addition to the literature around the impact of out of pocket (OOP) medical expenditures on poverty. Authors have appropriately analysed large dataset to demonstrate the impact of OOP on poverty. I just have few minor comments to further strengthen this article: - I would recommend authors to add citations for few key statements in the introduction section such as, :India is actively taking steps to offer its population universal health coverage (UHC)", "India is ranked third in the Southeast Asian region in terms of “countries with highest OOP expenditure on health,” according to the World Health Organization". - In its current format it is a little hard to understand key take home message from this study. So, I would suggest authors to carve out a "conclusion" section which provides succinct conclusion of this study. Is the work clearly and accurately presented and does it cite the current literature? Yes Is the study design appropriate and is the work technically sound? Yes Are sufficient details of methods and analysis provided to allow replication by others? Yes If applicable, is the statistical analysis and its interpretation appropriate? I cannot comment. A qualified statistician is required. Are all the source data underlying the results available to ensure full reproducibility? Yes Are the conclusions drawn adequately supported by the results? Yes Competing Interests No competing interests were disclosed. Reviewer Expertise public health and health services research I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard. reply Respond to this report Responses (0) Bele S. Peer Review Report For: Do hospitalizations push households into poverty in India: evidence from national data [version 1; peer review: 2 approved, 1 approved with reservations] . F1000Research 2024, 13 :205 ( https://doi.org/10.5256/f1000research.159573.r261053) NOTE: it is important to ensure the information in square brackets after the title is included in this citation. The direct URL for this report is: https://f1000research.com/articles/13-205/v1#referee-response-261053 keyboard_arrow_left Back to all reports Reviewer Report 0 Views copyright © 2024 Narayanan S. This is an open access peer review report distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 05 Apr 2024 | for Version 1 Seetharaman Narayanan , Professor and Head of Community Medicine, KMCH Institute of Health Sciences and Research, Coimbatore, Tamilnadu, India 0 Views copyright © 2024 Narayanan S. This is an open access peer review report distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. format_quote Cite this report speaker_notes Responses (0) Approved info_outline Alongside their report, reviewers assign a status to the article: Approved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested Approved with reservations A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit. Not approved Fundamental flaws in the paper seriously undermine the findings and conclusions Assessment: 1. Presentation and Literature Review: The article is well-structured and clearly presented. It provides a comprehensive review of relevant literature, highlighting the importance of the research problem and situating the study within the existing body of knowledge. 2. Study Design and Academic Merit: The study design is appropriate for addressing the research questions. The use of nationally representative survey data from the NSSO enhances the generalizability and academic merit of the findings. 3. Methods and Repeatability: The methods section provides sufficient details on the data source, variables, and analytical techniques (logistic regression) to allow for replication by others. A short discussion on the suitability of the World bank definition of poverty line (over any other definition of poverty line) would be helpful. 4. Statistical Analysis: The statistical analysis appears appropriate, with logistic regression models employed to examine the factors influencing the incidence of poverty due to OOPHE. The interpretation of the results is generally sound. 5. Data Availability: The authors mention that the data can be obtained from the Government of India or by reasonable request. It would be preferable to provide more specific information on data accessibility to enhance transparency and reproducibility. 6. Conclusions and Support: The conclusions drawn are generally supported by the results presented. The authors highlight the crucial role of health insurance coverage in protecting households from impoverishment due to OOPHE and the need for policy interventions to improve access to public healthcare facilities, particularly in rural areas. Strengths: - Nationally representative data enhances generalizability. - Comprehensive literature review and sound methodology. - Highlights the role of health insurance and public healthcare access in alleviating poverty due to OOPHE. Suggestions: - Clarify the applicability of the World Bank defined poverty line (vis-a-vis any other methodology to define the poverty line currently in use, in India) in the analysis. - Provide more specific information on accessing the source data data from NNSO, to enhance reproducibility. - Discuss potential limitations and directions for future research. - Expand on the policy implications and recommendations for addressing the identified issues. Overall, the article makes a valuable contribution to understanding the impoverishing effects of OOPHE in India and identifying factors that influence household poverty. Is the work clearly and accurately presented and does it cite the current literature? Yes Is the study design appropriate and is the work technically sound? Yes Are sufficient details of methods and analysis provided to allow replication by others? Yes If applicable, is the statistical analysis and its interpretation appropriate? Yes Are all the source data underlying the results available to ensure full reproducibility? Yes Are the conclusions drawn adequately supported by the results? Yes Competing Interests No competing interests were disclosed. Reviewer Expertise Public Health, Health Economics I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard. reply Respond to this report Responses (0) Narayanan S. Peer Review Report For: Do hospitalizations push households into poverty in India: evidence from national data [version 1; peer review: 2 approved, 1 approved with reservations] . F1000Research 2024, 13 :205 ( https://doi.org/10.5256/f1000research.159573.r261054) NOTE: it is important to ensure the information in square brackets after the title is included in this citation. The direct URL for this report is: https://f1000research.com/articles/13-205/v1#referee-response-261054 Alongside their report, reviewers assign a status to the article: Approved - the paper is scientifically sound in its current form and only minor, if any, improvements are suggested Approved with reservations - A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit. Not approved - fundamental flaws in the paper seriously undermine the findings and conclusions Adjust parameters to alter display View on desktop for interactive features Includes Interactive Elements View on desktop for interactive features Competing Interests Policy Provide sufficient details of any financial or non-financial competing interests to enable users to assess whether your comments might lead a reasonable person to question your impartiality. Consider the following examples, but note that this is not an exhaustive list: Examples of 'Non-Financial Competing Interests' Within the past 4 years, you have held joint grants, published or collaborated with any of the authors of the selected paper. You have a close personal relationship (e.g. parent, spouse, sibling, or domestic partner) with any of the authors. You are a close professional associate of any of the authors (e.g. scientific mentor, recent student). You work at the same institute as any of the authors. You hope/expect to benefit (e.g. favour or employment) as a result of your submission. You are an Editor for the journal in which the article is published. Examples of 'Financial Competing Interests' You expect to receive, or in the past 4 years have received, any of the following from any commercial organisation that may gain financially from your submission: a salary, fees, funding, reimbursements. You expect to receive, or in the past 4 years have received, shared grant support or other funding with any of the authors. You hold, or are currently applying for, any patents or significant stocks/shares relating to the subject matter of the paper you are commenting on. Stay Updated Sign up for content alerts and receive a weekly or monthly email with all newly published articles Register with F1000Research Already registered? Sign in Not now, thanks close PLEASE NOTE If you are an AUTHOR of this article, please check that you signed in with the account associated with this article otherwise we cannot automatically identify your role as an author and your comment will be labelled as a “User Comment”. If you are a REVIEWER of this article, please check that you have signed in with the account associated with this article and then go to your account to submit your report, please do not post your review here. If you do not have access to your original account, please contact us . All commenters must hold a formal affiliation as per our Policies . The information that you give us will be displayed next to your comment. User comments must be in English, comprehensible and relevant to the article under discussion. We reserve the right to remove any comments that we consider to be inappropriate, offensive or otherwise in breach of the User Comment Terms and Conditions . Commenters must not use a comment for personal attacks. When criticisms of the article are based on unpublished data, the data should be made available. I accept the User Comment Terms and Conditions Please confirm that you accept the User Comment Terms and Conditions. Affiliation ✕ refresh Please enter your institution. Note: To add your institution or organisation, start typing the name and then select the correct name from the list. Where applicable, the name will appear in both the original language and in English. Do not paste in the name. If the name does not appear in the drop-down list, we will display the information you have entered. ✕ refresh Country/Region * USA UK Canada China France Germany Afghanistan Aland Islands Albania Algeria American Samoa Andorra Angola Anguilla Antarctica Antigua and Barbuda Argentina Armenia Aruba Australia Austria Azerbaijan Bahamas Bahrain Bangladesh Barbados Belarus Belgium Belize Benin Bermuda Bhutan Bolivia Bosnia and Herzegovina Botswana Bouvet Island Brazil British Indian Ocean Territory British Virgin Islands Brunei Bulgaria Burkina Faso Burundi Cambodia Cameroon Canada Cape Verde Cayman Islands Central African Republic Chad Chile China Christmas Island Cocos (Keeling) Islands Colombia Comoros Congo Cook Islands Costa Rica Cote d'Ivoire Croatia Cuba Cyprus Czech Republic Democratic Republic of the Congo Denmark Djibouti Dominica Dominican Republic Ecuador Egypt El Salvador Equatorial Guinea Eritrea Estonia Ethiopia Falkland Islands Faroe Islands Federated States of Micronesia Fiji Finland France French Guiana French Polynesia French Southern Territories Gabon Georgia Germany Ghana Gibraltar Greece Greenland Grenada Guadeloupe Guam Guatemala Guernsey Guinea Guinea-Bissau Guyana Haiti Heard Island and Mcdonald Islands Holy See (Vatican City State) Honduras Hong Kong Hungary Iceland India Indonesia Iran Iraq Ireland Israel Italy Jamaica Japan Jersey Jordan Kazakhstan Kenya Kiribati Kosovo (Serbia and Montenegro) Kuwait Kyrgyzstan Lao People's Democratic Republic Latvia Lebanon Lesotho Liberia Libya Liechtenstein Lithuania Luxembourg Macao Madagascar Malawi Malaysia Maldives Mali Malta Marshall Islands Martinique Mauritania Mauritius Mayotte Mexico Minor Outlying Islands of the United States Moldova Monaco Mongolia Montenegro Montserrat Morocco Mozambique Myanmar Namibia Nauru Nepal Netherlands Antilles New Caledonia New Zealand Nicaragua Niger Nigeria Niue Norfolk Island North Korea North Macedonia Northern Mariana Islands Norway Oman Pakistan Palau Palestinian Territory Panama Papua New Guinea Paraguay Peru Philippines Pitcairn Poland Portugal Puerto Rico Qatar Reunion Romania Russian Federation Rwanda Saint Helena Saint Kitts and Nevis Saint Lucia Saint Pierre and Miquelon Saint Vincent and the Grenadines Samoa San Marino Sao Tome and Principe Saudi Arabia Senegal Serbia Seychelles Sierra Leone Singapore Slovakia Slovenia Solomon Islands Somalia South Africa South Georgia and the South Sandwich Is South Korea South Sudan Spain Sri Lanka Sudan Suriname Svalbard and Jan Mayen Swaziland Sweden Switzerland Syria Taiwan Tajikistan Tanzania Thailand The Gambia The Netherlands Timor-Leste Togo Tokelau Tonga Trinidad and Tobago Tunisia Turkey Turkmenistan Turks and Caicos Islands Tuvalu UK USA Uganda Ukraine United Arab Emirates United States Virgin Islands Uruguay Uzbekistan Vanuatu Venezuela Vietnam Wallis and Futuna West Bank and Gaza Strip Western Sahara Yemen Zambia Zimbabwe Please select your country/region. You must enter a comment. Competing Interests Please disclose any competing interests that might be construed to influence your judgment of the article's or peer review report's validity or importance. Competing Interests Policy Provide sufficient details of any financial or non-financial competing interests to enable users to assess whether your comments might lead a reasonable person to question your impartiality. Consider the following examples, but note that this is not an exhaustive list: Examples of 'Non-Financial Competing Interests' Within the past 4 years, you have held joint grants, published or collaborated with any of the authors of the selected paper. You have a close personal relationship (e.g. parent, spouse, sibling, or domestic partner) with any of the authors. You are a close professional associate of any of the authors (e.g. scientific mentor, recent student). You work at the same institute as any of the authors. You hope/expect to benefit (e.g. favour or employment) as a result of your submission. You are an Editor for the journal in which the article is published. Examples of 'Financial Competing Interests' You expect to receive, or in the past 4 years have received, any of the following from any commercial organisation that may gain financially from your submission: a salary, fees, funding, reimbursements. You expect to receive, or in the past 4 years have received, shared grant support or other funding with any of the authors. You hold, or are currently applying for, any patents or significant stocks/shares relating to the subject matter of the paper you are commenting on. Please state your competing interests The comment has been saved. An error has occurred. Please try again. Cancel Post var lTitle = "Do hospitalizations push households into...".replace("'", ''); var linkedInUrl = "http://www.linkedin.com/shareArticle?url=https://f1000research.com/articles/13-205/v1" + "&title=" + encodeURIComponent(lTitle) + "&summary=" + encodeURIComponent('Read the article by '); var deliciousUrl = "https://del.icio.us/post?url=https://f1000research.com/articles/13-205/v1&title=" + encodeURIComponent(lTitle); var redditUrl = "http://reddit.com/submit?url=https://f1000research.com/articles/13-205/v1" + "&title=" + encodeURIComponent(lTitle); linkedInUrl += encodeURIComponent('Sriram S and Albadrani M'); var offsetTop = /chrome/i.test( navigator.userAgent ) ? 4 : -10; var addthis_config = { ui_offset_top: offsetTop, services_compact : "facebook,twitter,www.linkedin.com,www.mendeley.com,reddit.com", services_expanded : "facebook,twitter,www.linkedin.com,www.mendeley.com,reddit.com", services_custom : [ { name: "LinkedIn", url: linkedInUrl, icon:"/img/icon/at_linkedin.svg" }, { name: "Mendeley", url: "http://www.mendeley.com/import/?url=https://f1000research.com/articles/13-205/v1/mendeley", icon:"/img/icon/at_mendeley.svg" }, { name: "Reddit", url: redditUrl, icon:"/img/icon/at_reddit.svg" }, ] }; var addthis_share = { url: "https://f1000research.com/articles/13-205", templates : { twitter : "Do hospitalizations push households into poverty in India: evidence.... Sriram S and Albadrani M, published by " + "@F1000Research" + ", https://f1000research.com/articles/13-205/v1" } }; if (typeof(addthis) != "undefined"){ addthis.addEventListener('addthis.ready', checkCount); addthis.addEventListener('addthis.menu.share', checkCount); } $(".f1r-shares-twitter").attr("href", "https://twitter.com/intent/tweet?text=" + addthis_share.templates.twitter); $(".f1r-shares-facebook").attr("href", "https://www.facebook.com/sharer/sharer.php?u=" + addthis_share.url); $(".f1r-shares-linkedin").attr("href", addthis_config.services_custom[0].url); $(".f1r-shares-reddit").attr("href", addthis_config.services_custom[2].url); $(".f1r-shares-mendelay").attr("href", addthis_config.services_custom[1].url); function checkCount(){ setTimeout(function(){ $(".addthis_button_expanded").each(function(){ var count = $(this).text(); if (count !== "" && count != "0") $(this).removeClass("is-hidden"); else $(this).addClass("is-hidden"); }); }, 1000); } close How to cite this report {{reportCitation}} Cancel Copy Citation Details $(function(){R.ui.buttonDropdowns('.dropdown-for-downloads');}); $(function(){R.ui.toolbarDropdowns('.toolbar-dropdown-for-downloads');}); $.get("/articles/acj/145602/159573") new F1000.Clipboard(); new F1000.ThesaurusTermsDisplay("articles", "article", "159573"); $(document).ready(function() { $( "#frame1" ).on('load', function() { var mydiv = $(this).contents().find("div"); var h = mydiv.height(); console.log(h) }); var tooltipLivingFigure = jQuery(".interactive-living-figure-label .icon-more-info"), titleLivingFigure = tooltipLivingFigure.attr("title"); tooltipLivingFigure.simpletip({ fixed: true, position: ["-115", "30"], baseClass: 'small-tooltip', content:titleLivingFigure + " " }); tooltipLivingFigure.removeAttr("title"); $("body").on("click", ".cite-living-figure", function(e) { e.preventDefault(); var ref = $(this).attr("data-ref"); $(this).closest(".living-figure-list-container").find("#" + ref).fadeIn(200); }); $("body").on("click", ".close-cite-living-figure", function(e) { e.preventDefault(); $(this).closest(".popup-window-wrapper").fadeOut(200); }); $(document).on("mouseup", function(e) { var metricsContainer = $(".article-metrics-popover-wrapper"); if (!metricsContainer.is(e.target) && metricsContainer.has(e.target).length === 0) { $(".article-metrics-close-button").click(); } }); var articleId = $('#articleId').val(); if($("#main-article-count-box").attachArticleMetrics) { $("#main-article-count-box").attachArticleMetrics(articleId, { articleMetricsView: true }); } }); var figshareWidget = $(".new_figshare_widget"); if (figshareWidget.length > 0) { window.figshare.load("f1000", function(Widget) { // Select a tag/tags defined in your page. In this tag we will place the widget. _.map(figshareWidget, function(el){ var widget = new Widget({ articleId: $(el).attr("figshare_articleId") //height:300 // this is the height of the viewer part. [Default: 550] }); widget.initialize(); // initialize the widget widget.mount(el); // mount it in a tag that's on your page // this will save the widget on the global scope for later use from // your JS scripts. This line is optional. //window.widget = widget; }); }); } close Error Close Add Reset F1000.MICROSERVICES.AFFILIATION = ''; $(document).ready(function () { $('.js-affiliations-form').each((index, form) => { new AffiliationForm({ formId: form.id, institutionErrorSelector: '.comment-enter-institution', departmentErrorSelector: '.comment-enter-department', placeSelector: '.js-add-comment-place', stateSelector: '.js-add-comment-state', zipCodeSelector: '.js-add-comment-zipcode', countrySelector: '.js-add-comment-country', countryErrorSelector: '.comment-enter-country', }); }); }); $(document).ready(function () { var reportIds = { "261027": 0, "261043": 0, "261031": 0, "261046": 0, "261034": 9, "261049": 0, "261054": 11, "261037": 0, "261053": 7, "261052": 0, }; $(".referee-response-container,.js-referee-report").each(function(index, el) { var reportId = $(el).attr("data-reportid"), reportCount = reportIds[reportId] || 0; $(el).find(".comments-count-container,.js-referee-report-views").html(reportCount); }); var uuidInput = $("#article_uuid"), oldUUId = uuidInput.val(), newUUId = "838d327d-af55-4877-899a-da90a92cea70"; uuidInput.val(newUUId); $("a[href*='article_uuid=']").each(function(index, el) { var newHref = $(el).attr("href").replace(oldUUId, newUUId); $(el).attr("href", newHref); }); }); An innovative open access publishing platform offering rapid publication and open peer review, whilst supporting data deposition and sharing. Browse Gateways Collections How it Works Contact For Developers Cookie Notice Privacy Notice RSS Submit Your Research Follow us © 2012-2026 F1000 Research Ltd. ISSN 2046-1402 | Legal | Partner of Research4Life • CrossRef • ORCID • FAIRSharing R.templateTests.simpleTemplate = R.template(' $text $text $text $text $text '); R.templateTests.runTests(); var F1000platform = new F1000.Platform({ name: "f1000research", displayName: "F1000Research", hostName: "f1000research.com", id: "1", editorialEmail: "[email protected]", infoEmail: "[email protected]", usePmcStats: true }); $(function(){R.ui.dropdowns('.dropdown-for-authors, .dropdown-for-about, .dropdown-for-myresearch');}); // $(function(){R.ui.dropdowns('.dropdown-for-referees');}); $(document).ready(function () { if ($(".cookie-warning").is(":visible")) { $(".sticky").css("margin-bottom", "35px"); $(".devices").addClass("devices-and-cookie-warning"); } $(".cookie-warning .close-button").click(function (e) { $(".devices").removeClass("devices-and-cookie-warning"); $(".sticky").css("margin-bottom", "0"); }); $("#tweeter-feed .tweet-message").each(function (i, message) { var self = $(message); self.html(linkify(self.html())); }); $(".partner").on("mouseenter mouseleave", function() { $(this).find(".gray-scale, .colour").toggleClass("is-hidden"); }); }); Sign In Remember me Forgotten your password? Sign In Cancel Email or password not correct. Please try again Please wait... $(function(){ // Note: All the setup needs to run against a name attribute and *not* the id due the clonish // nature of facebox... $("a[id=googleSignInButton]").click(function(event){ event.preventDefault(); $("input[id=oAuthSystem]").val("GOOGLE"); $("form[id=oAuthForm]").submit(); }); $("a[id=facebookSignInButton]").click(function(event){ event.preventDefault(); $("input[id=oAuthSystem]").val("FACEBOOK"); $("form[id=oAuthForm]").submit(); }); $("a[id=orcidSignInButton]").click(function(event){ event.preventDefault(); $("input[id=oAuthSystem]").val("ORCID"); $("form[id=oAuthForm]").submit(); }); }); If you've forgotten your password, please enter your email address below and we'll send you instructions on how to reset your password. The email address should be the one you originally registered with F1000. Email address not valid, please try again You registered with F1000 via Google, so we cannot reset your password. To sign in, please click here . If you still need help with your Google account password, please click here . You registered with F1000 via Facebook, so we cannot reset your password. To sign in, please click here . If you still need help with your Facebook account password, please click here . Code not correct, please try again Reset password Cancel Email us for further assistance. Server error, please try again. If your email address is registered with us, we will email you instructions to reset your password. If you think you should have received this email but it has not arrived, please check your spam filters and/or contact for further assistance. Please wait... Register $(document).ready(function () { signIn.createSignInAsRow($("#sign-in-form-gfb-popup")); $(".target-field").each(function () { var uris = $(this).val().split("/"); if (uris.pop() === "login") { $(this).val(uris.toString().replace(",","/")); } }); });